Research Report No. UVACTS-5-14-63 July, 2004 DEVELOPMENT OF COUNTER MEASURES TO SECURITY

RISKS FROM AIR CARGO TRANSPORT

By:

Carla D. Rountree Dr. Michael J. Demetsky

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A Research Project Report For the Mid-Atlantic Universities Transportation Center (MAUTC) A U.S. DOT University Transportation Center

Dr. Michael J. Demetsky Department of Civil Engineering Email: mjd@virginia.edu Center for Transportation Studies at the University of Virginia produces outstanding transportation professionals, innovative research results and provides important public service. The Center for Transportation Studies is committed to academic excellence, multi-disciplinary research and to developing state-of-the-art facilities. Through a partnership with the Virginia Department of Transportation’s (VDOT) Research Council (VTRC), CTS faculty hold joint appointments, VTRC research scientists teach specialized courses, and graduate student work is supported through a Graduate Research Assistantship Program. CTS receives substantial financial support from two federal University Transportation Center Grants: the Mid-Atlantic Universities Transportation Center (MAUTC), and through the National ITS Implementation Research Center (ITS Center). Other related research activities of the faculty include funding through FHWA, NSF, US Department of Transportation, VDOT, other governmental agencies and private companies.

Disclaimer: The contents of this report reflect the views of the authors, who are responsible for the facts and the accuracy of the information presented herein. This document is disseminated under the sponsorship of the Department of Transportation, University Transportation Centers Program, in the interest of information exchange. The U.S. Government assumes no liability for the contents or use thereof.

ABSTRACT

CTS Website Center for Transportation Studieshttp://cts.virginia.edu University of Virginia

351 McCormick Road, P.O. Box 400742Charlottesville, VA 22904-4742

434.924.6362

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ABSTRACT

The terrorist attacks of September 11, 2001 displayed the shortcomings of aviation

security in the United States. Most of the attention on aviation security since that time

has focused on airline passengers, their luggage, and their carry-on items, leaving air

cargo security on the back burner. The lack of security screening and screening

guidelines of cargo traveling by both passenger and all-cargo aircraft is the driving

purpose behind this research project: the development of a framework that may be used

by individual airports or airlines to analyze various security setups for screening

outbound air cargo within an on-airport cargo facility. This was accomplished through

airport surveys, a case study at an air cargo facility, and computer simulations testing

various setups of security technologies to screen cargo within a facility.

Data collected from surveys sent to over 100 of the nation’s major airports

revealed the lack of security in the air cargo environment and validated the need for this

research. Information was obtained on security measures utilized for cargo and

personnel, as well as the frequency of cargo screenings and information on the size and

setups of cargo facilities. Also, a results comparison between large and small airports

was conducted. A case study was performed at a cargo facility within a major U.S.

airport in order to gather data pertinent to the simulations used to test the security setups.

Information gathered on truck arrivals, the number of flight destinations, security

measures in place, as well as the general facility setup was used to form the basis of the

simulations. The simulations, conducted in Arena 7.01, tested the effectiveness and

cargo throughput of four security cases. Each case employed a different combination of

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security measures proven suitable for an air cargo environment. The security setups were

evaluated based on the security systems’ costs, the overall effectiveness of catching high-

risk cargo, and the average amount of time taken to process cargo through the facility.

The Arena simulations present airlines, freight forwarders, and airport authorities

with the necessary tool to evaluate various cargo security screening measures that will

provide the best security solution for their particular facility or facilities. However,

further research is needed on the effectiveness of many security technologies. With this

information, government and aviation officials will be able to use this framework as a

step toward achieving a well-rounded plan for ensuring the safety and security of our

nation’s air cargo.

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TABLE OF CONTENTS

CHAPTER 1: INTRODUCTION 12 1.1: Introduction to the Air Cargo Industry 12 1.2: Emphasis on Transportation Security 13 1.3: Current State of Air Cargo and Future Forecasts 14 1.4: Problem Statement and Purpose 15 1.5: Scope 16 1.6: Report Organization 17 CHAPTER 2: LITERATURE REVIEW 18 2.1: Efforts to Secure Air Cargo 18 2.2: Screening Methods 21 2.3: Efforts to Secure Ports and Ocean-bound Cargo 30 2.4: Electronic Supply Chain Manifest (ESCM) 33 2.5: Hazardous Materials (Hazmat) Regulations and Security Efforts 35 2.6: Simulation Models 37 2.7: Summary 40 CHAPTER 3: METHODOLOGY 41 3.1: Methodology Introduction 41 3.2: Airport Surveys 41 3.3: Evaluations of Screening Methods 44

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3.4: Case Study 45 3.5: Arena Simulation of Cargo Flow Through an On-airport Cargo Facility 51 CHAPTER 4: RESULTS 59 4.1: Airport Surveys 59 4.2: Screening Methods 77 4.3: Arena Models 78 CHAPTER 5: CONCLUSIONS AND RECOMMENDATIONS 97 5.1: Conclusions 97 5.2: Recommendations 99 REFERENCES 101 APPENDIX A: SURVEY MATERIALS 105

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LIST OF TABLES

Table 2.1: Breakdown of Screening Method Characteristics 26 Table 3.1: Detection Capabilities of Screening Methods Researched 53 Table 4.1: Results of the First Phase of Evaluation of Screening Methods 77 Table 4.2: Cases with Screening Technologies Capable of Screening for Explosives 79 Table 4.3: Cases with Screening Technologies Capable of Screening for

Stolen/Mislabeled Goods 79 Table 4.4: Cases with Screening Technologies Capable of Screening for Illegal

Drugs 79 Table 4.5: Cases with Screening Technologies Capable of Screening for Radioactive

Materials 79

Table 4.6: Cases with Screening Technologies Capable of Screening for

Dangerous/Illegal Gases 79 Table 4.7: Number of Screening Technologies In Each Case Capable of Detecting

Each Threat Type 80 Table 4.8: Case Costs and Processing Results 80 Table 4.9: Results for Explosives/Explosive Materials Detection 82 Table 4.10: Results for Stolen/Mislabeled Goods Detection 83 Table 4.11: Results for Illegal Drug Detection 84 Table 4.12: Results for Dangerous Gases Detection 85 Table 4.13: Results for Radioactive Materials Detection 86 Table 4.14: Results for Overall High-Risk Cargo Detection 87

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Table 4.15: Means and 95% Confidence Intervals for Explosives Detection 88 Table 4.16: Means and 95% Confidence Intervals for Stolen Goods Detection 88 Table 4.17: Means and 95% Confidence Intervals for Illegal Drugs Detection 89 Table 4.18: Means and 95% Confidence Intervals for Radioactive Materials

Detection 89 Table 4.19: Means and 95% Confidence Intervals for Dangerous Gases Detection 90

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LIST OF FIGURES

Figure 1.1: Breakdown of U.S. Domestic Air Cargo Market for 2001 15 Figure 3.1: Case Study Facility Layout, Outbound Side 46 Figure 3.2: Flow Chart Illustrating Cargo Flow Through An On-airport Cargo

Facility 48 Figure 3.3: Histogram of Time Between Truck Arrivals to Case Study Facility 50 Figure 3.4: Best Fit Distribution from Arena’s Input Analyzer,

-0.001 + 15.4(0.382)-15.4x15.4-1e-(x/0.382)^15.4 50 Figure 4.1: 95% Confidence Interval Spreads for 10% Screening in All Four Cases

and for All Five High-Risk Types for Percent Found from Security 91 Figure 4.2: 95% Confidence Interval Spreads for 25% Screening in All Four Cases

and for All Five High-Risk Types for Percent Found from Security 91 Figure 4.3: 95% Confidence Interval Spreads for 50% Screening in All Four Cases

and for All Five High-Risk Types for Percent Found from Security 92 Figure 4.4: 95% Confidence Interval Spreads for 10% Screening in All Four Cases

and for All Five High-Risk Types for Total Percent Found 93 Figure 4.5: 95% Confidence Interval Spreads for 25% Screening in All Four Cases

and for All Five High-Risk Types for Total Percent Found 94 Figure 4.6: 95% Confidence Interval Spreads for 50% Screening in All Four Cases

and for All Five High-Risk Types for Total Percent Found 94

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GLOSSARY

Belly cargo/freight: cargo or freight that is carried underneath the main cabin of

passenger aircraft.

Cargo unit: a single cargo parcel of any size

Cutoff time: the time past which an airline or freight forwarder will no longer accept

cargo shipments for same-day flights. Cutoff times differ between domestic and

international cargo, and also between airlines or freight forwarders.

Freight forwarder: a person or company that picks up, transports, and delivers

shipments on behalf of another party. Freight forwarders may also be referred to

as indirect air carriers.

Known shipper program: federal mandate that airlines (both direct and indirect)

shipping cargo aboard passenger aircraft know the origin of that cargo. Airlines

often accomplish this by verifying the customer’s location and type of business

before accepting any shipments. Cargo flying on all-cargo aircraft is not required

to originate from known shippers.

Outbound air cargo: air cargo that is awaiting transport by aircraft to a destination.

Tug/cart system: a popular method of transporting air cargo and passenger luggage

between facilities and aircraft. A small truck (tug) carries a train of about 3 or 4

platforms (carts) on wheels that hold ULDs or luggage.

Unit loading device (ULD): a container designed to fit precisely inside the hull of an

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aircraft that can hold one or more cargo shipments. ULDs have differing designs

for differing types of aircraft and therefore will only fit in one specific make of

aircraft.

ACKNOWLEDGEMENTS

I would like to thank my advisor, Professor Michael J. Demetsky, for his

encouragement and support of a project that fit my interests and career goals, and for his

assistance and advice throughout the pursuit of this research. I would also like the thank

Saeed Eslambolchi for his gracious help in developing the surveys, along with Professor

K. Preston White for his assistance in troubleshooting my efforts in the simulations.

Your guidance throughout this project is sincerely appreciated.

I would also like to express my gratitude to the officials from the case study

airport and case study facility. This project would not have been possible without your

kind assistance.

Finally, I would like to thank my family and friends for their continued interest

and support of this work and my career goals.

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CHAPTER 1: INTRODUCTION

1.1: Introduction to the Air Cargo Industry

Since its beginnings in the 1920s, the air cargo industry has been known for its

speedy yet expensive service. This sector of the freight transportation market thrives on

the narrow time frame in which it can deliver goods, and customers in need of quick

deliveries are willing to pay the price. Air transport is especially advantageous when

long distances must be overcome. Cargo may traverse an ocean and be delivered within

24 hours by aircraft, whereas the same journey may take five to ten times as long by sea.

As should be expected, the cargo will cost five to ten times as much to transport by air

rather than by sea.1

The air cargo industry began with a single scheduled cargo shipment that flew just

after the end of World War I, and the first regular all-cargo flight service began in 1926.

After World War II ended many war veterans began their own non-scheduled air cargo

services that lead to high competition, increased flight frequencies, and the eventual

failure of most of the non-scheduled services. The scheduled services that survived grew

steadily through the 1940’s and 1950’s. The air transport deregulation of 1977 and 1978

resulted in an influx of new domestic airline companies seeking to take advantage of the

new ability to negotiate shipment rates. The latest change in the industry occurred in the

1 William Armbruster , “Breaking News,” Air Cargo World Online, October 8, 2002.

http://www.aircargoworld.com/break_news/3.htm.

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1980s with the introduction of the “just-in-time” concept, in which deliveries are planned

in advance with the intent of keeping customer’s inventories low.2

Today air cargo can be transported one of two ways: as belly freight on a

commercial passenger flight, or on a dedicated all-cargo aircraft. Commercial airlines

make between five and ten percent of their revenue through the air cargo business.3

Around 50 to 60 percent of domestic air cargo by tons is transported by commercial

passenger aircraft.4

1.2: Emphasis on Transportation Security

The terrorist attacks of September 11, 2001 spurred the recent focus on

transportation security and its apparent shortcomings, including the creation of the

Department of Homeland Security and the Transportation Security Administration

(TSA). The vast majority of the TSA’s new federal security regulations and programs

have targeted airline passengers and their luggage, as well as ocean-bound cargo. New

federal security screeners, screening machines such as x-rays and trace detection devices,

luggage and carry-on rules, and stricter screening of passengers themselves have been

introduced in airports around the country. Fear of a “dirty” bomb or a weapon of mass

destruction in a cargo container instigated the focus on ocean-bound cargo security,

which has ranged from new federal security programs that involve international

cooperation to the installation of security devices such as radiation detectors, radio

frequency identification, and electronic cargo unit sensors. Air cargo is one

2 Richard Malkin, “An Air Cargo Century,” Air Cargo World Online, January 2000.

http://www.aircargoworld.com/archives/feat1jan00.htm. 3 Karim Nice, “How Air Freight Works,” How Stuff Works, October 2002.

http://www.howstuffworks.com/air-freight/htm. 4 “Airport Security Report,” PBI Media LCC, Volume 9, No. 5, February 27, 2002, p. 3.

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transportation sector that has been mostly overlooked from a security standpoint. Very

few regulations pertaining to air cargo security have been passed by the federal

government, and most of those that have are vague and non-specific. Major legislation

that would outline specific and strict air cargo security regulations has been introduced

into Congress, but so far nothing has been passed.

1.3: Current State of Air Cargo and Future Forecasts

U.S. domestic air cargo tonnage (revenue-ton kilometers) grew by 41% in the

1990s. In 2000 alone domestic tonnage went up 3.7%, however it dropped by 9.2% in

2001 because of the September 11 attacks and a slowing economy. Air cargo carriers’

use of trucks has increased in recent years, even faster than air transport itself. Trucks

have developed into a major part of the air cargo market as a major linkage point to the

cargo facilities, making the air cargo industry increasingly intermodal. From 1995 to

2000 truck-transported freight (tons) increased by 4.5%, while air-transported freight

grew by only 1.9%. In 2001 express deliveries made up the vast majority of the domestic

air freight market, at 60.5%, while another 20.1% was taken by scheduled freight. The

domestic air freight market is illustrated in Figure 1.1.

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Figure 1.1: Breakdown of U.S. Domestic Air Cargo Market for 2001

Breakdown of U.S. Domestic Air Cargo in 2001

19.4%

20.1% 60.5%

Express Deliveries Scheduled Freight Deliveries Other

Boeing predicts that U.S. domestic air cargo will grow steadily at about 4.5%

through 2011 and will grow at a rate of about 4.3% through 2021. North American cargo

traffic with Europe, Asia, and Latin America decreased by 10% to 16% in 2001, but is

expected to steadily increase by 6% to 8% through 2021.5

1.4: Problem Statement and Purpose

According to the FBI, cargo terminals, cargo transfer facilities, and consolidation

facilities are hotbeds for cargo theft.6 And while 50% to 60% of all U.S. air cargo travels

as belly cargo, only about 4% is screened for explosives.7 The precise effectiveness of

most screening methods used, along with the effectiveness of screeners themselves, is not

known.8 This, along with the lacking legislation pertaining to air cargo security, has left

a large gap in a major sector of transportation security. A standardized system or set

5 “Boeing World Air Cargo Forecast 2002-2003: North America,” The Boeing Company, 2002.

http://www.boeing.com/commercial/cargo/n_america.html. 6 “Aviation Security: Vulnerabilities and Potential Improvements for the Air Cargo System,” U.S.

General Accounting Office, December 2002, pp. 8-9. 7 Gordon Dickson and Byron Okada, “Gaps Cited in Air Cargo Security,” Knight-Ridder/Tribune

News Service, February 27, 2002, p. 1. 8 “Aviation Security: Efforts to Measure Effectiveness and Address Challenges,” U.S. General

Accounting Office, November 2003, p. 1.

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procedure for screening cargo within airport facilities is needed. Various combinations

of security measures need to be evaluated in order to develop a system that effectively

screens as much cargo as the limited time element allows and at a reasonable cost to the

industry.

The purpose of this study is to analyze outbound cargo flow through an on-airport

cargo facility and develop a systematic framework for evaluating air cargo screening

alternatives within an air cargo facility without jeopardizing the crucial time element

involved in air cargo transport and with minimal cost. Hazards such as explosives,

explosive materials, cargo theft and smuggling, and chemical attacks will be considered

in the analysis. A computer simulation of an on-airport cargo facility will be used to

evaluate various combinations of security technologies used to counteract such risks.

1.5: Scope

For this project, five major tasks will be undertaken in order to develop a best-

case security framework for on-airport cargo facilities. The first task is a comprehensive

literature review of security regulations, screening methods, and security programs across

various transportation modes. For the second task, the results of surveys sent to major

U.S. airports will be analyzed in order to determine the current state of national air cargo

security and cargo operations for both large and small cargo facilities. Third, various

screening methods will be analyzed in order to determine what can feasibly be used in an

air cargo environment. For the forth task, information obtained from a case study

conducted at a large on-airport air cargo facility at a major U.S. airport will be analyzed

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and used to form the basis for the fifth task, which is a computer simulation of outbound

cargo flow through an on-airport facility. The simulation will analyze varying

combinations of security methods from the third task that directly screen cargo. Inbound

cargo and U.S. mail are not included in the analysis. The results of this project will be

useful for gaining insight into the implications of stricter air cargo screening regulations

and provide a general outline that airlines, freight forwarders, airport authorities, and

government organizations can use to analyze operations and security techniques.

1.6: Report Organization

Chapter 2 describes the literature review, including regulatory efforts to secure air

cargo, screening methods available, efforts to secure cargo intermodally and in seaports,

hazardous materials regulations, and a review of various computer simulation models. In

Chapter 3, the methodology behind the surveys, the case study, and the evaluation of the

screening technologies and the simulation models will be discussed. Chapter 4 will show

the results, and conclusions and recommendations will be given in Chapter 5.

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CHAPTER 2: LITERATURE REVIEW

2.1: Efforts to Secure Air Cargo

Efforts to ensure nationwide security of air cargo since September 11, 2001 have

come from the newly formed Transportation Security Administration (TSA). Only a few

regulations have been put into law, but many more are currently being debated by TSA

and Congress.

2.1.1: TSA Enacted Regulations Pertaining to Air Cargo Security

On November 11, 2001, President George W. Bush signed into law the Aviation

and Transportation Security Act (ATSA), which established the creation of the TSA

within the U.S. Department of Transportation. This act outlined numerous new

regulations and guidelines for security of the transportation sector as a whole, however

only one sentence in the act directly pertains to air cargo: “Cargo deadline – A system

must be in operation to screen, inspect, or otherwise ensure the security of all cargo that

is to be transported as soon as practicable after the date of enactment of the Aviation and

Transportation Security Act,” 9. Other rules and guidelines directly and indirectly

pertaining to air cargo security have been enacted since the signing of the ATSA:

1. All cargo aboard passenger flights must be screened10

2. All freight forwarders must have a TSA-approved security program in order to

be allowed to ship on passenger flights

9 Aviation and Transportation Security Act, Section 110(f), Public Law 107-071. Passed by 107th

Congress November 19, 2001. 10 James R. Carroll, “Legislation Would Tighten Security Rules for Air Freight,” The Courier-

Journal (Louisville, Kentucky), April 7, 2003.

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3. Airlines must have a TSA-approved security program for cargo

4. TSA requires ID checks of anyone entering restricted cargo areas within

airports

5. TSA requires random screening of people, vehicles, and property at airport

perimeter access points.

6. Criminal history checks are mandatory for cargo employees working in

restricted or secure areas11

7. Physical inspection of air cargo is required, however the exact percentage

required by TSA is classified.12

It should be noted that airlines and freight forwarders are not required to check

and record IDs of known shipper employees delivering cargo to a facility.

2.1.2: Proposed Rules and Regulations Pertaining to Air Cargo Security

In January of 2003, a bill entitled Air Cargo Security Act was proposed by

Senators Kay Bailey Hutchison (R-TX) and Diane Feinstein (D-CA), and the measure

was approved by the Committee on Commerce, Science, and Transportation in March of

2003. The measure, which has not been passed by Congress as of June 2004, outlines the

following regulations:

1. Air cargo facilities and aircraft must be inspected on a regular basis

2. Cargo handlers must undergo security training

3. Creation of a national known shipper database, listing all companies and cargo

11 “Airport Security,” Title 49 of the Code of Federal Regulations, Subchapter B, Part 1542.

http://www.tsa.gov/public/display?theme=79&content=0900051980096ff5. 12 Asa Hutchinson, Under Secretary for Border and Transportation Security, Eno Transportation

Foundation 2004 Leadership Development Conference, Session on Security: Transforming How We Manage Transportation. May 26, 2004.

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transporting/transported on U.S. and international passenger carriers13

4. Random security checks must be conducted at air cargo facilities and in

aircraft

5. Screening/inspection systems for air cargo must be established

6. Mandatory background checks for all airline employees handling cargo

7. Government ability to stop shippers who have violated regulations from

shipping air cargo.14

Another bill that is currently being debated in Congress would require mandatory

screening and inspection of all air cargo. This bill was introduced by Senator Ed Markey

(D-MA) and has passed in the House of Representatives, but has yet to pass in the

Senate.15

The Transportation Security Administration has outlined an Air Cargo Strategic

Plan, which officials call a “blueprint” for a comprehensive approach to air cargo

security. The plan includes the following proposed rules:

1. Prescreen all cargo to determine its threat level

2. Examine all cargo deemed to be of “elevated risk”16

3. Inspect all aircraft prior to the day’s first flight17

4. Randomly inspect low-risk cargo and cargo bound for passenger aircraft

13 “Committee Approves Air Cargo Security Bill,” U.S. Senate Press Release, March 13, 2003.

http://www.senate.gov/~commerce/press/03/2003313730.html. 14 James R. Carroll, “Legislation Would Tighten Security Rules for Air Freight,” The Courier-

Journal (Louisville, Kentucky), April 7, 2003. 15 “McGreevey Calls on Fed to Establish Stricter Air Cargo Guidelines,” Press Release, New

Jersey Office of the Governor, August 8, 2003. http://www.state.nj.us/cgi-bin/governor/njnewsline/view_article.pl?id=1329.

16 “Air Cargo Strategic Plan,” Transportation Security Administration Press Release, November 17, 2003. http://www.tsa.gov/public/interapp/press_release/press_release_0371.xml.

17 David Harris, “The Air Cargo Security Plan,” The International Air Cargo Association, December 17, 2003. http://www.tiaca.org/articles/2003/12/17/388C7D7AAA454B9D86BB24EF50333B66.asp.

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5. Airport operators and operators of all-cargo aircraft with a gross take-off

weight of 12,500 lbs or more will have to conduct criminal record checks on

all employees and use other additional means to screen and identify anyone

with aircraft access

6. Use facility security measures to ensure security of all-cargo aircraft

7. Have a centralized, more comprehensive known shipper program (done

through TSA, not individual airlines or freight forwarders).18

TSA also plans to require all non-U.S. all-cargo carriers with operations within

the U.S. to have TSA-approved security plans outlining screening procedures and

identifying all personnel with access to aircraft.19

2.2: Screening Methods 2.2.1: Direct Cargo Screening

Numerous non-intrusive technologies and methods exist that may be used to

screen cargo units directly and specifically for various types of threats. Eight

technologies and methods will be analyzed for this project: pulsed fast neutron analysis,

vapor detection, trace detection, canines, x-ray machines, gamma ray, thermal neutron

activation, and radiation detection. All the methods discussed do not require cargo

containers to be opened, and they all have difficulty detecting biological threats.

a. Pulsed Fast Neutron Analysis

18 “Air Cargo Strategic Plan,” Transportation Security Administration Press Release, November

17, 2003. http://www.tsa.gov/public/interapp/press_release/press_release_0371.xml. 19 David Harris, “The Air Cargo Security Plan,” The International Air Cargo Association,

December 17, 2003. http://www.tiaca.org/articles/2003/12/17/388C7D7AAA454B9D86BB24EF50333B66.asp.

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A pulsed fast neutron analysis machine works by measuring cargo density to

identify the chemical composition of the container’s contents. Pulsed neutrons

are directed at the cargo unit, interact with the cargo’s material, and “create

gamma rays with energies characteristic of its elemental composition” that are

used to display an image of the contents on a screen. This can reveal the presence

of any material with specific elemental concentrations similar to known threat

objects and materials. This machine is classified as an active detection system,

meaning that it stimulates the material so that detectors may analyze the effects of

stimulation. It can require building modifications due to its size. The cost per

machine ranges from $10 million to $25 million, and inspection time takes a

minimum of one hour per cargo unit.

b. Vapor Detection

Vapor detection machines are equipped with a sensor that collects air samples

from around the cargo unit. Spectrographic analysis is performed to determine

the molecular makeup of the material within the unit. Vapor detection machines

are relatively small and light, and they can be battery-operated, computer-

operated, or electrically operated. Vapor detection is a passive detection system,

meaning it does not require the stimulation of materials to determine a threat

presence. The cost per machine ranges from $30,000 to $50,000, and they can

process a cargo unit in about 30 to 60 seconds.

c. Trace detection

Trace detection machines use a swipe to wipe the cargo unit and pick up

particulate matter. Spectrographic analysis is performed on the swipe to

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determine the molecular makeup of the material picked up on the unit. Like

vapor detection machines, trace detection machines are relatively small and can

be operated by battery, computer, or electronically. According to TSA, these

machines have “shown few problems” when screening cargo. The cost per unit is

$30,000 to $50,000, and they can process a cargo shipment in about 30 to 60

seconds.20

d. Canines

Drug- and explosives-detecting canines are widely considered by security experts

to be the most effective way to screen cargo since they have the fewest drawbacks

of any method currently available. Dogs have a very sensitive sense of smell, and

they can be trained to passively alert handlers of the presence of explosive

materials or drugs. Properly trained canines very rarely give false positive alerts.

Canines can be trained to detect either explosives or drugs, but should never be

trained to detect both. All canines used at U.S. airports must receive TSA

certification. Canines used for drug detection may work 2 or 4 hour shifts each

day with periodic rest. Canines trained to detect explosives may only work 30 to

60 minutes before taking a 20-minute rest. Canines can clear 400 to 500 cargo

parcels for both drugs and explosives in about 30 minutes. It is very important for

a canine to receive extensive training, care, and rest for it to perform properly.

Yearly maintenance costs can range from $7,000 to $50,000 per canine unit (a

canine unit consists of 2 to 4 teams with 1 handler and 1 to 2 dogs per team).

20 “Volume 6 – Report on Non-intrusive Detection Technologies,” U.S. Treasury Advisory

Committee on Commercial Operations of The United States Customs Service Subcommittee on U.S. Border Security Technical Advisory Group and Customs Trade Partnership Against Terrorism, June 14, 2002. http://www.cargosecurity.com/ncsc/coac/Non-intrusive.pdf.

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However, the start-up costs for a canine unit can be quite high. The first year of

maintenance and training can cost well over $100,000.21

e. X-ray Machines

X-ray machines scan cargo units by directing x-ray beams at the unit so that the

beams interact with the material inside and form an image of the material on a

screen. X-ray energy may be low or high, but higher energies are needed for

denser materials. X-ray machines are classified as active detection systems, and

they generally take 2 to 5 minutes to scan a cargo unit. A drawback of x-ray

machines is that they cannot specifically identify a threat (i.e., differentiate

between materials), except for certain systems used with a high-energy

transmission. Costs range from $2 million to $10 million.

f. Gamma Ray

Gamma ray systems are active detection systems that use a radioactive element to

produce gamma rays, which are directed at the cargo unit. An image is displayed

on a screen as the gamma rays interact with the material in the container. These

machines may be fixed in place, or they may be placed on a vehicle for mobility.

The downsides to gamma ray systems are that they cannot identify specific

threats, and they have difficulty differentiating between materials when scanning

high-density cargo. Costs range from $500,000 to about $3 million per machine,

and they can scan a cargo unit in 2 to 5 minutes.

g. Thermal Neutron Activation

21 TCRP Report 86: Public Transportation Security Volume 2, K9 Units in Public Transportation:

A Guide for Decision Makers, National Academy Press, Washington D.C., 2002.

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Thermal neutrons are directed at the cargo unit and absorbed by the material

within. As a result, a gamma ray photon is emitted and its energy signature is

detected by sensors, which can then determine specific element concentrations

that might be a sign of an explosive. Thermal neutron activation systems are

active detection systems that can either be fixed in place or mounted on a vehicle

for mobility. Costs range from $500,000 to $3 million per machine. The system

takes a minimum of one hour to scan a cargo unit.

h. Radiation Detection

All radioactive substances emit radiation (i.e., x-rays, alpha rays, neutrons), which

is detected and measured by a detector in the radiation detection system. High

levels of specific types of radiation may indicate a threat object. These machines

are classified as passive detection systems. The systems are small and are easily

portable, and they can be operated either by a battery, a computer, or

electronically. Machines typically cost between $10,000 and $50,000 and can

scan a cargo unit in 30 to 60 seconds.

Table 2.1 compares the costs, inspection times, installation requirements, and

identification abilities of the screening methods discussed in this section.

26

SCREEN TIME TO MAT’L MAT’L COST FOR INSPECT DISCR. ID INSTALLATION ACTIVE SYSTEMS X-ray $1 - 10 million Explosives, 2 - 5 min No No Mobile or fixed. Standard $1 - 5 million stolen 2 - 5 min No No Fixed sites need Dual View $10 million mat’ls, 2 - 5 min No No power, road Backscatter $2 - 5 million drugs 2 - 5 min No No access, Gamma Ray $500,000 - 2 - 5 min No No personnel $3 million facilities, and Pulsed Fast $10 - Explosives, 1 hr + Yes Yes attention to Neutron 25 million drugs radiation safety. Analysis Vehicles Thermal $500,000 - Explosives 1 hr + Yes Yes needed Neutron $3 million for mobility. Activation PASSIVE SYSTEMS Vapor $30,000 - Prohibited 30 - 60 sec Yes Yes Portable or Detection $50,000 gases desktop equip. Trace $30,000 - Explosives, 30 - 60 sec Yes Yes operated by Detection $50,000 drugs battery or Radiation $10,000 - Radiation 30 - 60 sec No Yes, for wallplug. Detection $50,000 radioactive material Canines $7,000 - Explosives, 10 - 60 sec Limited Yes Require care, $120,000 per drugs by amt. of feeding, shelter. unit per year training

Table 2.1: Breakdown of Screening Method Characteristics. Source: U.S. Treasury Advisory Committee on Commercial Operations of the United States Customs Service22

2 2.2: Screening Methods for Personnel, Visitors, and Truck Drivers

Some of the most popular methods for screening individuals at airports involve

manual and paper-based processes. At most airports around the country, airport

employees carry official airport IDs or badges as identification. Some airports issue IDs

to frequently-visiting truck drivers, as well. These IDs or badges usually clearly identify

22 “Volume 6 – Report on Non-intrusive Detection Technologies,” U.S. Treasury Advisory

Committee on Commercial Operations of The United States Customs Service Subcommittee on U.S. Border Security Technical Advisory Group and Customs Trade Partnership Against Terrorism, June 14, 2002. http://www.cargosecurity.com/ncsc/coac/Non-intrusive.pdf.

27

the airport, list the individual’s name, and include a picture. Such identification must be

clearly displayed at all times. IDs are often equipped with a magnetic strip that is

programmed to allow an individual entry to certain areas, depending on their job and

rank. Truck drivers delivering or picking up cargo who are issued airport IDs usually

have to check with security personnel upon arriving at the airport, and their arrival is

documented by established FAA procedures, which are paper-based.

Visitors who have official business at airports and need access to secured areas do

not have many options for gaining such access. One of the more popular screening

methods for airport visitors is to simply assign them an authorized escort who has proper

clearance. At some airports visitors can be issued temporary IDs valid only for the day or

days they are scheduled to be there.

Biometrics is a newly emerging security technology that many industry and

government officials see as the future of access security for airport personnel, truck

drivers, and even airline passengers. Biometrics uses biological identification by

matching signatures in fingerprints, thumbprints, hands, voices, faces, or irises. A

person’s signature may be stored either in a central database or on a “smart card,” a

plastic driver’s license-sized card with an embedded computer chip that stores the

individual’s biological signature. A biometric reader scans the part of the body that it is

programmed to read and matches the person’s signature to the signature stored in the

smart card or the central database.23

As promising and secure as the technology sounds, there are problems and issues

that have arisen. Privacy issues have been raised about the fact that some biometric

23 Liza Porteus, “Homeland Security Technologies in the Pipeline,” Fox News, January 14, 2004.

http://foxnews.com/story/0,2933,108289,00.html.

28

systems store detailed personal information in a centralized database that numerous

people, including some government organizations, could have access to. Smart cards

could be lost or stolen.24 Tests performed on iris scanning systems have found that

individuals with very light or very dark eyes or people whose iris is not connected to the

eye socket can cause identification errors.25 Also, people without fingerprints cannot be

identified by fingerprint-based biometric systems.

2.2.3: Perimeter Security and Surveillance

Three of the most popular methods for perimeter security and surveillance are

canine patrols, guard patrols, and closed circuit television (CCTV). Canines, as

explained under Section 2.2.1, require a large initial investment for equipment, care and

training. However, after the first year, maintenance costs are quite low, and a properly

trained canine is considered to be one of the most effective screening and patrol methods

available today. Canines used for patrol only do not require as much training as those

used for drug and explosives detection. Patrol canines enforce general good behavior in

public areas and can quickly and effectively apprehend a suspect person without causing

harm. Guard patrols can be used virtually anywhere to deter unlawful activity. Guard

patrols have a variety of responsibilities including keeping watch over secured areas to

ensure only proper personnel are present, monitoring airport perimeters to check for any

24 Jennifer Jones, “A Moving Target – Border Control and Transportation Safety Apps Put

Biometrics to the Test,” Federal Computer Week, June 23, 2003. http://www.fcw.com/fcw/articles/2003/0623/cov-report2-06-23-03.asp.

25 Celeste Perry, “Iridian Helps Cut Airport Waits as Security Tightens (Update 1),” Bloomberg L.P., January 8, 2003. http://www.biometricgroup.com/in_the_news/bloomberg.html.

29

forced entry onto airport property, and watching for suspicious activity of any sort.

Guard and canine patrols can and often are used together.

CCTV has the capability to monitor and store video of any area in which a video

camera is installed. Within an air cargo facility, properly placed cameras can record

container loading, unloading, and handling so that any improper activity can be seen by

personnel monitoring the videos. CCTV is limited in the fact that it does not provide any

actual protection from cargo tampering. CCTV can provide constant monitoring of any

place that has a camera installed. For such areas, CCTV can be an advantage over guard

and canine patrols because they are under constant surveillance. However, patrols have

the ability to stop any unlawful activity while it is in action and apprehend the person or

persons involved.26

Canine patrol teams can cost anywhere from $7,000 to over $100,000, depending

on when the canines are first obtained, how many canines make up the team, and many

other factors. Guard patrols can cost anywhere from $30,000 to $60,000 per year per

guard depending on location and experience.27 CCTV cameras cost anywhere from $50

to $1,000 apiece. Additional components such as switching and recording devices vary

greatly in cost.28

26 “Aviation Security: Vulnerabilities and Potential Improvements for the Air Cargo System,” U.S. General Accounting Office, December 2002.

27 TCRP Report 86: Public Transportation Security Volume 2, K9 Units in Public Transportation: A Guide for Decision Makers, National Academy Press, Washington D.C., 2002.

28 “Aviation Security: Vulnerabilities and Potential Improvements for the Air Cargo System,” U.S. General Accounting Office, December 2002.

30

2.3: Efforts to Secure Ports and Ocean-Bound Cargo

2.3.1: Introduction

The vast majority of cargo security efforts by the U.S. government thus far have

been geared toward ocean-bound cargo container security. The Department of Homeland

Security has initiated a number of new security programs along with private companies

and foreign countries in order to reduce the supply chain’s vulnerability to terrorist

actions. These programs include the Container Security Initiative (CSI), the Customs-

Trade Partnership Against Terrorism (C-TPAT), and the Rapid Information Security

Knowledge (RISK) Alert.

2.3.2: Container Security Initiative (CSI) and the 24-Hour Rule

The Container Security Initiative (CSI) was implemented in January of 2002. It

requires the cooperation of foreign countries to allow U.S. Customs officials into their

major ports shipping cargo to the U.S. in order to screen “high risk” containers that are

U.S.-bound. Customs officials work closely with the port officials using non-intrusive

surveillance equipment to screen any cargo believed to present a significant threat. The

goal of CSI is to discover and clear high-risk cargo before it reaches the U.S. By

inspecting high-risk cargo during “down time” as it waits to board a vessel, the need to

inspect it once it arrives in the U.S. is eliminated, thereby reducing the overall processing

time.

All containers arriving at the port that are bound for the U.S. have their manifest

data electronically evaluated and are assigned a risk level. Data from the host country’s

31

customs department is also analyzed in the risk assignment process. During the first year

of operation, U.S. Customs enacted the 24-Hour Rule to ensure that manifest data would

be received in time to conduct inspections if needed. The 24-Hour Rule states that U.S.

Customs must receive a cargo container’s electronic manifest data at least 24 hours

before the cargo is to be loaded onto a ship. This rule applies to all U.S.-bound cargo, not

just cargo originating at foreign ports with CSI presence. This regulation allows U.S.

Customs to directly receive manifest data without having to obtain it from foreign

customs agents.

During CSI’s first year, 15 foreign governments agreed to allow U.S. Customs

officials into their major ports (24 ports total), and five of these ports became home to

CSI teams. CSI is now operable in 19 of the 20 largest foreign ports transporting cargo to

the U.S.29

2.3.3: Customs-Trade Partnership Against Terrorism (C-TPAT)

C-TPAT is a program through which participating private companies commit to

increasing their efforts to ensure supply chain security and in return, U.S. Customs

promises a decreased likelihood of inspecting those companies’ shipments for weapons

of mass destruction. Companies currently participating in the program include domestic

manufacturers, truckers, and shipping companies. Program officials plan to allow foreign

manufacturers into the program in the near future. The program requires participants to

document the security procedures that they conduct and report them to U.S. Customs.

29 “Container Security: Expansion of Key Programs Will Require Greater Attention to Critical

Success Factors,” U.S. General Accounting Office, July 2003.

32

To become a C-TPAT member, a company must enter into an agreement with

Customs to support the C-TPAT security recommendations and work with its supply

chain partners to increase security. Companies are given risk scores that are reduced

when they officially become C-TPAT members. The lower the risk score, the lower the

likelihood that Customs will inspect shipments for WMDs.

C-TPAT officials periodically conduct validations of member’s security measures

that are based on information such as security-related incidents, cargo volumes, and

geographic location. The validations, along with information from Customs on past

relations between a company and U.S. Customs (including trade compliance and any

criminal investigations) determine updated risk score computations. Depending on any

vulnerabilities found, a company can have its benefits suspended until action is taken to

address the problems. If overall security has been enhanced to the satisfaction of C-TPAT

officials, a company’s risk score will be further reduced.30

2.3.4: Rapid Information Security Knowledge (RISK) Alert

RISK Alert is a data software and tracking system for ocean cargo, ships, and ship

crews from origin to destination that can also collect data from electronic seals and

bioterrorism sensors on cargo containers. The system was developed by Transentric, part

of the Union Pacific Corporation, and the Delaware River Maritime Enterprise Council.

If a ship or its cargo veers off the intended course, appropriate law enforcement agencies

will be notified immediately. Participating agencies can choose what types of security

30 “Container Security: Expansion of Key Programs Will Require Greater Attention to Critical

Success Factors,” U.S. General Accounting Office, July 2003.

33

situations they would like to be notified about and by what method they would like to

receive notification.31

The system benefits commercial shippers and other participants by allowing them

to prove their security and safety management practices work and benefit supply chain

security. Participants also benefit by having to submit updated security information just

one time, since the information will automatically be sent to the proper agencies once

submitted.32

2.3.5: Summary

In terms of inter-governmental collaboration, efforts and research toward ocean

cargo security is more advanced than that for air cargo security. Programs such as CSI,

C-TPAT, and the RISK Alert could be implemented in the air cargo industry and serve as

another protective measure against cargo security threats. Programs of this nature would

complement the known shipper program and provide a means to secure cargo without

adding time to the processing that goes on within the air cargo facility.

2.4: Electronic Supply Chain Manifest (ESCM) The Electronic Supply Chain Manifest is a test project using new screening

technologies to identify people responsible for cargo along its journey and to track cargo

itself along and between different transportation modes. The purpose of the project was

to find an alternative to the manual security tracking processes currently used for air

31 Henry J. Holcomb, “Security Tightens by Monitoring Ships and Cargo,” Philadelphia Inquirer,

March 19, 2003. http://www.centredaily.com/mld/centredaily/news/5428395.htm. 32 “R.I.S.K. Alert – Supply Chain Technology Aids Homeland Security,” Transentric Press

Release, March 28, 2003. www.transentric.com/WhatsNew/pressReleases1.asp?intWhatsNewID=65.

34

cargo that facilitates efficient and secure cargo movements. The testing mainly involved

motor carriers and air carriers. Around 200 people and 40 companies signed up to be

involved in the test project that took place around Chicago’s O’Hare Airport and New

York City’s JFK Airport. Authorized system users can monitor information on a

shipment as it moves along the supply chain from manufacturing and shipping to motor

carrier and aircraft.

The system works by matching cargo with its proper handler, known shipper

information, and its origin and destination. The system makes use of technologies

including encrypted internet transactions, smart cards, and biometric fingerprint readers.

All access points along the chain are equipped with biometric fingerprint readers to

validate the person handling the cargo (usually the truck driver). Smart cards are used to

verify the identity of the cargo handlers and the transfer of cargo from one person to

another, as well as to transfer information on the cargo itself. The smart cards are given

to the handlers for use at pick-up and delivery, and they contain the handler’s thumbprint

(for biometric identification), information on the cargo’s manifest, and a copy of the

handler’s driver’s license. A Triple DES 192 bit encryption is used for internet

transactions, which is the current encryption standard for the federal government because

of its low cost and high security.

The program began in 1999 and was tested for 2.5 years. An analysis of the test

results found that the computer network was very reliable and that the use of electronic

manifests, smart cards, and biometrics proved to be an effective and time-efficient

combination. Nearly 75% of all manifests were processed in less than 1 minute, 15

35

seconds. 86% of the manifests were processed in less than 2 minutes, and 92% of the

manifests took less than 3 minutes to process.

Participants who consistently used the system were very pleased and remained

interested in keeping the system. Many even used the system longer than the testing plan

called for. Very few technical problems were reported. Participants felt that security was

increased because of the limited access to information, limited documentation needing to

be accessed.33

2.5: Hazardous Materials (Hazmat) Regulations and Security Efforts

Among air carriers, more types of dangerous goods (and larger quantities) are

allowed on all-cargo aircraft than on passenger aircraft. About 50% of all regulated

dangerous goods may travel on both all-cargo aircraft and passenger aircraft. Around

30% of regulated hazardous materials are allowed on all-cargo aircraft, but not passenger

aircraft, and the final 20% may not travel by air at all. Materials included in the final

20% include highly toxic, explosive, oxidizing, self-reactive, and flammable chemicals.

For those hazmat goods allowed on aircraft (cargo, passenger, or both), the

government has 4 types of quantity restrictions:

1. Restrictions by name: names of certain materials are prohibited if they

present a dire hazard or have cause aircraft incidents (i.e., fires or explosions).

2. Restrictions by hazard class or subdivision: hazardous materials are divided

into classes, and certain subdivisions of these classes are highly toxic or

reactive and are either allowed only on all-cargo aircraft or not at all.

33 “Electronic Supply Chain Manifest Freight ITS Operational Test Evaluation: Final Report,”

U.S. Department of Transportation, December 2002. http://www.itsdocs.fhwa.dot.gov//JPODOCS/REPTS_TE//13769.html.

36

3. Restrictions by quantity listed on packages: if the quantity of a certain

dangerous good exceeds government regulations, it will not be allowed onto

the aircraft.

4. Restrictions by package integrity: the material must be packaged so as to

protect the shipment and prevent leaks or spills.

In the past few years, concern has arisen over undeclared hazmat shipments and

the risks they pose to air transport. In 2000, U.S. Customs and the Federal Aviation

Administration performed inspections of international cargo, both arriving and departing,

at 19 U.S. airports and found that around 8% of hazmat shipments contained undeclared

dangerous material. Major air carriers usually only discover undeclared dangerous goods

when they are prompted to search a shipment for some reason, and such promptings and

discoveries are rare. For those that are discovered, neither the government nor the air

transport industry keeps a record of such discoveries, so trends cannot be identified. Air

carriers’ only options for screening for undeclared goods consist of physical inspection

and limited x-ray use. Air carriers have found that casual shippers are much more likely

to try to ship undeclared hazmat shipments than known shippers, and most major carriers

restrict their customers to known shippers only. However, most carriers and other

industry experts believe that undeclared shipments are not usually intentionally

undeclared, but result from ignorance of regulations governing dangerous goods.34

34 “Aviation Safety: Undeclared Air Shipments of Dangerous Goods and DOT’s Enforcement Approach,” U.S. General Accounting Office, January 2003.

37

2.6: Simulation Models Three simulation software packages capable of simulating air cargo flow through

an air cargo facility were researched for potential use in this project. The packages

examined were CargoVIZ, AutoMod, and Arena 7.01.

2.6.1: CargoVIZ

CargoViz is a three-dimensional simulation software package that allows the user

to design and visualize the flow of airline passenger baggage through security

checkpoints. CargoViz allows the user to virtually construct the interior of an airport

security inspection area and specify what security equipment is to be used, the quantity of

each type of equipment, and rate of passenger traffic passing through the inspection area.

The user may choose from airport models within the software, or he may construct his

own. By running scenarios, the user can evaluate the effectiveness of the type and

quantity of security equipment used for various passenger flow rates. The three-

dimensional environment lets the user view the scene from any angle, and he may

navigate right, left, up, down, forward, backward, or zoom in and out. The toolbar allows

the user to add objects to the workspace; change, create, or delete baggage flow paths;

change the viewpoint and the lighting; and activate or deactivate the floorspace grid.

CargoVIZ was created by the Applied Visualization Center at the University of

Tennessee, Knoxville in conjunction with the Transportation Security Administration and

the Safe Skies Program of the National Safe Skies Alliance. The National Safe Skies

38

Alliance statistically determined measurements for quantifying the impacts of various

airport and equipment layouts on the flow of baggage through the security checkpoint.35

2.6.2: AutoModTM

AutoModTM, a product of Brooks PRI Automation, is discrete event simulation

software that can be used to model most any system. The user can create 3-D animation

for any simulation. The system requires programming knowledge, although the software

does come with ready-built model logic for system portions such as conveyors, path-

based vehicle movements, bridge cranes, tanks, and pipes. Modules use a combination of

a graphical user interface and a CAD system to make simulation of material handling

systems simpler and allow for virtually unlimited simulation size and detail. The

software has also incorporated automatic connections and routings for certain systems.

Statistical reports and graphs are automatically generated when a simulation is performed

that give information on equipment utilization, processing time, and other aspects of the

process. The 3-D animation allows the user to view the model from any angle at any

point in time. Various airport authorities, air carriers, and government organizations have

used AutoModTM to simulate airport operations such as baggage systems and passenger

security checkpoints. Brooks PRI Automation offers consulting services to organizations

using their products, including on-site training, video production, and technical support.36

35 “Cargo VIZ User Manual,” Applied Visualization Center, University of Tennessee, Knoxville, July 30, 2003. http://viz.utk.edu/projects/tsa/cargoviz/cargo_viz.pdf.

36 AutoModTM Information Packet, Brooks-PRI Automation, 2003.

39

2.6.3: Arena 7.01

Arena, like AutoModTM, is discrete event simulation software than can be used to

model almost any system including manufacturing, logistics, warehousing, and

distribution systems. Arena is a product of Rockwell software and usually uses 2-D

animation. The software does not require computer programming knowledge and has a

user-friendly interface. The software has various templates with modules used to

simulate basic and advances processes as well as transfer elements. The software has an

optional component called OptQuest that serves as an optimization tool, as well as a

Factory Analyzer that can be used to improve performance and capacity for

manufacturing systems. A Flow Process template may also be used, which models

discrete-continuous systems. 3-D animation is possible with Arena’s extra 3-D player.

After a simulation has run to completion, the simulation history can be used to create the

3-D animation.37

2.6.4: Simulation Models Summary

From these three simulation packages, Arena 7.01 was chosen for use in this

project. Arena was readily available at a reasonable cost, it does not require

programming knowledge, and it comes with various useful statistical analysis programs.

CargoVIZ is intended for use with passenger luggage, not cargo, and AutoMod requires

moderate computer programming knowledge in order to use. Prior experience with the

Arena was also a factor. This allowed for time to be spent calibrating the models rather

than learning new simulation software.

37 W. David Kelton, Simulation with Arena 3rd Edition,” McGraw-Hill: Boston, 2004.

40

2.7: Summary

Looking at the current regulations in place pertaining to air cargo, it can be seen

that few regulations have been put into effect, and many of them are quite vague. A large

number of the proposed regulations are also vague and could be open to interpretation.

Stating that cargo must be screened could simply mean that it must originate from a

known shipper, or it could be intended to mean that cargo must be screened by a specific

screening method such as the methods discussed in this chapter. Ensuring air cargo

security must involve more than just direct cargo screening – methods to validate

personnel and truck drivers, perimeter security, and programs such as those implemented

at ports for ocean-bound cargo will help ensure a layered security program. Determining

the most efficient and effective way to directly screen cargo as an integral part of a

layered security approach will be discussed in subsequently.

41

CHAPTER 3: METHODOLOGY

3.1: Introduction

The methodology discussed in this chapter includes the airport surveys, the

evaluations of the cargo screening methods, the case study, and the simulation of cargo

flow through an on-airport cargo facility. The literature review, which is also part of the

methodology, was discussed in the last chapter.

3.2: Airport Surveys

3.2.1: Introduction and Purpose

In August of 2003, a survey containing questions about air cargo facilities,

operations, and security measures (titled “Air Cargo Operations and Security Survey”)

was sent out to 118 medium- to large-sized airports around the U.S. A list of 181 major

U.S. airports and their corresponding airport codes was obtained from

www.infoguides.com/airports/code_stn.htm. Airport data and contact information for all

of these airports was obtained from the Federal Aviation Administration’s webpage. The

airport managers, airport addresses, and airport information telephone numbers were

included in the list. A phone call was made to each airport on the list in order to get the

name, mailing address, and email address of an appropriate person to whom the survey

should be sent. The appropriate person was usually not the person spoken with on the

phone. The list was narrowed to 118 airports since some airports did not have on-airport

42

cargo operations, and contact with some airports could not be established within a

reasonable time frame. Appropriate contacts and mailing addresses were obtained for all

118 airports. However, only 59 of the contacts’ email addresses were obtained. Many of

the airport employees giving out the appropriate contact information either did not know

the contact’s email, could not locate it, or did not wish to disclose it. Surveys were sent

to all 118 airports at the beginning of August of 2003 with a return deadline of September

5, 2003. Hard copies were sent to all airports on the list. Electronic copies were emailed

to contacts for which email addresses had been obtained. A cover letter accompanied

each survey, referring the contacts to a website where the survey could also be taken

online. This provided the person completing the survey multiple options for filling out

and returning the survey: regular mail, email, fax, or online completion.

The survey’s purpose was to gather information on the cargo operations, security

measures used, and the physical layout of the facilities themselves in order to gain an

understanding of the layout of a typical on-airport cargo facility and the process of

operations within it. As an incentive to return the surveys, a copy of the aggregate

results was offered to participants.

The survey questions were divided into two general sections: operations and

security. The survey and an accompanying cover letter stated that no individual

responses would be released, keeping individual airports’ responses confidential. The

cover letter and the survey may be seen in Appendix A.

As of September 5, 2003, only 16 surveys had been returned. It was decided to

extend the deadline to October 8, 2003, and a second email (also included in Appendix

A) was sent to those airport contacts with email addresses that had not returned the

43

survey asking them to reconsider completing it and returning it before the new deadline.

An additional 3 surveys were returned by the second deadline. Since aviation security

has been a sensitive subject since September 11, 2001, this may have discouraged many

airports from returning the survey.

3.2.2: Operations, Facilities, and Cargo Volumes

The first section of the survey asked questions pertaining to airports’ cargo

operations, the size of their facilities, and the types and volumes of cargo carried. The

first five questions asked for information on the number of companies sorting cargo and

leasing space at the airport, the size of the cargo facilities themselves, and the number of

aircraft parking positions at each facility. The next five questions dealt with the method

of cargo sorting, the number of facility employees, the percentage of cargo handled as

belly freight, the percentage of cargo as international freight, and the method of transport

between the facility and the plane. The final two questions in this section asked for a

listing of common cargo types handled and quarterly cargo volumes.

The intent of this section was to gain an understanding of the scale of the

operations within air cargo facilities, along with information on the nature of the cargo

itself.

3.2.3: Security

The second section of the survey was targeted toward security measures in place

at airports that would have bearing on air cargo. The first four questions asked for the

amount of cargo screened and the methods available to do so, how employees working in

44

secure cargo areas are screened, and if visitors are allowed in the cargo facilities. The

next four questions ask for the percentage of cargo coming from known shippers,

information on screening trucks and truck drivers, and whether or not international cargo

is handled at the airport. The final four questions asked about the clearance times and

screening methods of international cargo, surveillance of dumpsters, plans to expand on

current security technologies, and the final question asked whether or not the airport

would be interested in allowing a case study for this project to be conducted on site.

The intent of this section was to gather specific information on how employees,

trucks, truck drivers, and cargo itself is screened for security purposed and to what extent.

The objective of the final question was to find an airport willing to host the case study

needed for this project.

3.3: Evaluations of Screening Methods

The direct cargo screening technologies discussed in Section 2.2.1 will be

evaluated in two phases. The first phase consists of evaluation based on the

technologies’ cost, screening time, and applicability in an air cargo environment. The

technologies that meet the requirements for this criteria will move on to the second phase,

which consists of testing via computer simulation in an operational environment.

For the first phase, any technology that carries a high cost (millions of dollars or

more per unit) or requires more than a few minutes to scan a single unit will be

eliminated. Also, any method that would be difficult to apply in an air cargo facility due

to factors such as size and mobility will also be eliminated from consideration. In the

45

second phase, each screening method will be evaluated in combination with other

methods to determine which combination or combinations result in the lowest cost and

time required, as well as the greatest detection coverage of various threat materials. A

range of effectiveness will be incorporated into the simulation for each screening method,

however very little data is available on the effectiveness of security screening

technologies, therefore it will not play a pivotal role in the overall evaluations.

3.4: Case Study

3.4.1: Introduction

A case study was conducted at an on-airport air cargo facility owned by a major

U.S. airline at a major U.S. airport. A total of three visits were made to the facility in

order to gain an understanding of how a cargo facility is laid out and the process of

outbound cargo operations within it, determine what security measures are used, and

gather data on truck arrivals for use in the Arena simulations. Information on the

airline’s known shipper program and truck schedules was also obtained.

3.4.2: Facility Layout and Operations

The air cargo facility is divided into two sections: the right side of the facility is

used to process outbound cargo, and the left side is used to process inbound cargo and

U.S. mail. The outbound cargo side will be considered for this project. Figure 3.1 shows

the layout of the outbound cargo side (the right side) of facility.

46

Figure 3.1: Case Study Facility Layout, Outbound Side

The facility consists of 7 landside cargo doors and 10 flight destinations that are labeled

along the walls of the facility. The yellow line traversing the width of the facility is the

dividing point between the delivery area and the processing area. Cargo is not officially

accepted by the airline until it has crossed the yellow line. On the date that data was

collected from the facility, an average of 6 employees were working in the facility (not

including the forklift operators) and 3 forklifts were in use. An employee stated that one

of the forklifts was not in operation on that day.

The basic procedure for processing cargo through the facility is outlined below.

Figure 3.2 illustrates the flow process.

1. Trucks arrive and dock at one of the 7 landside cargo doors.

2. Truck drivers have their paperwork verified and the cargo’s flight status is

checked.

3. Cargo is unloaded. Once it crosses the yellow line, it has been officially accepted

by the airline.

Office

Cold Storage

TemporaryStorage

Area

Destination

Wall Labels

Yellow Cross-line for Acceptance of Cargo

Airside Cargo

Doors (for

Landside

Cargo Doors

Side Cargo Door

47

4. Cargo is taken to the temporary storage area for measurements, labeling, and

possible physical inspection.

5. Cargo is sorted by destination and is placed on the floor under the appropriate

destination wall label. The cargo is held in this area until its intended flight

departure time nears.

6. Cargo units bound for the same flight are placed in unit loading devices (ULDs)

and loaded onto tugs.

7. Tugs leave through the airside cargo doors to take ULDs to the aircraft.

The airline delivers cargo to both domestic and international destinations. The cutoff

time for domestic cargo is 2 hours, and the cutoff for international cargo is 4 hours.

Trucks delivering cargo may be owned by the airline and operate on a schedule, or they

may be local trucks that do not operate on a schedule with the airline. Cargo units are

usually unloaded and sorted by forklifts, which are equipped with scales for weighing

each unit. Cargo is taken by tugs to the aircraft 20 to 30 minutes before the scheduled

takeoff. All but around 10% of arriving outbound cargo is shipped the same day it

arrives at the facility.

48

Figure 3.2: Flow Chart Illustrating Cargo Flow Through An On-airport Cargo Facility

3.4.3: Security

The airline relies mainly on the known shipper program, x-ray, and physical

inspection to keep their facility and cargo secure. The airline will only do business with

known shippers, but they make exceptions for shippers needing to transport live animals

and human remains. In order to verify a new potential customer as a known shipper, the

airline will send a cargo manager to the customer’s location to ensure that they have a

physical address, will be shipping legitimate goods, and can pay the shipping fees. Any

company that has been a known shipper in the past but has sent less than 12 shipments in

the past two years must be re-verified. The airline has never encountered any terrorist

groups wanting to obtain known shipper status, but they have turned down potential

Cargo Sorted by

Destination

N

Contents Verified?

Y

Remove for More

Inspection

Cargo Loaded onto ULDs, then

tugs

Tugs Take Cargo to Aircraft

Y

N

Cargo Accepted,Truck Leaves

Cargo Moved to Temporary Area Truck

Arrives

Physical Inspection?

(25%)

Paperwork Verified, Flight

Status Checked Ok?

N Cargo Denied,Truck Leaves

Y

1. 2. 3. 4. 4.

5. 6. 7.

49

customers for various reasons. They have also never encountered an unknown shipper

attempting to give them a shipment.

The airline uses x-ray and physical inspection to ensure cargo security once cargo

is in their possession. The x-ray machines they have are not in plain sight, and

information on the number of machines, their exact location, and frequency of use could

not be obtained. The airline mandates physical inspection of 25% of their outbound

cargo, which is an unusually high percentage of physical inspection for any airline or

freight forwarder. However, they cannot open any shipments from the U.S. government,

and they will only inspect shipments that can easily be opened and re-sealed.

3.4.4: Truck Arrivals

Data on the time between truck arrivals was obtained from the airline’s truck

schedule and observations of local truck arrivals to the facility. Data on local truck

arrivals was taken on February 19, 2004. The time between truck arrivals was used in the

Arena simulations to generate truck arrivals and their cargo deliveries. Figure 3.3 shows

that the time between arrivals was usually 20 minutes or less.

50

Figure 3.3: Histogram of Time Between Truck Arrivals to Case Study Facility

In order to properly represent this pattern of time between arrivals in Arena, the

data was put into a statistical analysis program within Arena called the Input Analyzer in

order to determine the statistical distribution that best fit the data set. The Input Analyzer

found that a Weibull distribution of the equation

-0.001 + 15.4(0.382)-15.4x15.4-1e-(x/0.382)^15.4 gave the best representation. Figure 3.4 shows

the distribution output from the Input Analyzer.

Figure 3.4: Best Fit Distribution from Arena’s Input Analyzer, -0.001 + 15.4(0.382)-15.4x15.4-1e-(x/0.382)^15.4

Time Between Truck Arrivals

02468

1012141618

20 40 60 80 100 120 140 160 180 200 200+

Minutes

Freq

uenc

y of

Tru

cks

51

The Weibull distribution equation takes the form

f(x) = a + αβ -αxα-1e-(x/β)^α if x > 0

where

a = offset from y-axis α = shape parameter of the distribution, and β = scale parameter of the distribution.38

This equation will be used to generate both trucks and their cargo arriving to the facility

in all the Arena simulations.

3.4.5: Summary

The layout of the case study facility and its operations will serve as the basis for

the Arena simulations. The processes described in this section will be duplicated in

Arena, and the data gathered from the truck arrivals will be used to generate truck and

cargo arrivals. Section 3.5 discusses the Arena simulations in detail.

3.5: Arena Simulation of Cargo Flow Through an On-airport Cargo Facility

3.5.1: Introduction

Arena will be used first to create a base case simulation without incorporation of

any security technologies, however it will include a small percentage of physical

inspection. The simulations will be based on the layout of the case study facility and will

use the data gathered during the case study. Each simulation will run for a period of 5

38 Averill M. Law and W. David Kelton, Simulation Modeling and Analysis Third Edition, McGraw-Hill, Boston, 2000, p. 303.

52

years and will undergo 3 replications. Some of the major factors from the case study that

will be incorporated into the Arena models will be the following:

1. Truck arrival times

2. Distribution of cargo units per truck arrival

3. Number of facility employees and forklifts

4. Number of flight destinations

5. Allowable time in which processing must be completed

6. Inclusion of physical inspection

It should be noted that although the case study facility routinely conducts physical

inspections on 25% of their outbound cargo, this is known to be greater than the

classified amount of physical inspection required by TSA. It will be assumed that TSA

requires 10% physical inspection, and this will be the value used in the simulations.

At the beginning of the simulation when the cargo units are created, 0.1% of the

units coming through will be assigned a high-risk status. The physical inspection in the

simulation will be conducted randomly, and statistics will be collected on the number of

high risk units inspected and found, along with the number of units that are not inspected

and work their way through the entire process. It will be assumed that physical

inspection is 100% effective at finding high-risk cargo.

Once the base case simulation is completed and evaluated, the combinations of

security methods will be incorporated for evaluation as discussed in Section 3.3. The rate

of 10% physical inspection will be included in these cases, as well. For these cases, the

cargo units will be assigned a specific high-risk status, meaning they contain a dangerous

or prohibited material. The five specific risks used in this project will include illegal or

53

dangerous gases, illegal drug shipments, stolen or mislabeled goods, radioactive

materials, and explosives (or explosive materials) not including gases and radioactive

materials. Table 3.1 shows which screening methods listed in Section 2.2 can detect

these five risks.

Screening Method Risks Detected X-Ray Explosives, stolen/mislabeled goods, illegal drugs Gamma Ray Explosives, stolen/mislabeled goods, illegal drugs Pulsed Fast Neutron Analysis Explosives, illegal drugs Thermal Neutron Activation Explosives Vapor Detection Dangerous gases Trace Detection Explosives, illegal drugs Radiation Detection Radioactive materials Canines Explosives, illegal drugs

Table 3.1: Detection Capabilities of Screening Methods Researched

Once a cargo unit is chosen for security screening, it will be inspected by all the

security methods included in the case unless one of the methods detects risk. If this

occurs, the cargo unit will be taken out of the security queue to undergo physical

inspection in order to verify the risk. If the risk is verified, the unit will be immediately

removed from the facility. If the risk is not verified (thus resulting in a false positive on

the part of the method that detected the “risk”), the unit will be routed to the cargo sorting

area. Screening for all five high-risk cargo types occurs simultaneously within the Arena

models.

Each combination case will be simulated three times. The first simulation will

screen a total of 10% of the outbound cargo, the second simulation will screen 25% of the

outbound cargo, and the third will screen 50% of the outbound cargo. Each of these

simulations will go through three replications. These percentages do not include the 10%

54

physical inspection. The screening time for each percentage for each case will be

evaluated, and comparisons of cost and screening time will be made among the different

combination cases. Statistics will be collected on the number and types of high-risk

cargo units caught, the number and types of high-risk cargo units not caught, the number

of true and false positives, and the total process time. The assumptions made in the

simulations are presented in the next section.

3.5.2: Simulation Setup and Assumptions

Each simulation except for the base case simulation will consist of four parts: a

truck model, a cargo flow model that includes the 10% physical inspection, a security

case model, and animation. The base case simulation will not have a security case model.

In the actual case study facility, cargo does not leave the facility immediately after

processing – it is held in the facility until close to its flight departure time. However, for

accurate evaluation of processing times in the simulation, it is assumed that cargo leaves

the facility as soon as the processing is completed. All cargo is assumed to be domestic

cargo and therefore will have a cutoff time of 2 hours. The base case simulation is set up

so that all cargo may be processed within 1 hour and 40 minutes or less to allow at least

20 minutes to transport cargo from the facility to the plane.

The cargo must “seize,” or take hold of, resources at various instances throughout

the simulation. The resources available for cargo to seize are 7 cargo bay doors, 6 facility

employees, and 4 forklifts. Both trucks and their associated cargo will simultaneously

seize an available cargo bay door upon arrival at the facility. Cargo must seize an

employee when going through paperwork and flight status verification, labeling and

55

measurements, physical inspection, and each technology in the security model. Cargo

must seize a forklift when being transported to the temporary storage area, being

transported to its city destination station, undergoing placement in ULDs and tugs, and

when being screened by certain technologies. If all resources are busy, the cargo must

wait in a queue to be serviced by the next available resource.

As stated in Section 3.3, very little data is available on the effectiveness of

screening technologies. Billie Vincent, president and CEO of Aerospace Services

International, estimates that explosive-detecting technologies are around 70% effective in

a cargo environment for units up to 79”x 60”x 64”.39 A triangular distribution with a

minimum of 60% effectiveness, a mean of 70% effectiveness, and a maximum of 80%

effectiveness will be assumed for all screening technologies. A uniform false positive

rate of 1% to 3% will be assumed for each technology.

Other assumptions have also been made in the simulations for truck arrivals,

cargo, and security processes. These assumptions are based on observations, not actual

recorded data, from the case study facility. Assumptions of a stochastic nature have been

assigned either triangular or uniform distributions because of their simplicity. Triangular

distributions take the form

f(x) = [2(x-a)]/[(b-a)(c-a)] if a ≤ x ≤ c

f(x) = [2(b-x)]/[(b-a)(b-c))] if c < x ≤ b

where

a < c < b

a = a location parameter; the minimum possible value c = the shape parameter; the value that maximizes the density function, and

39 Stephen Parezo, “Containing Security,” Air Cargo World Online,

http://www.aircargoworld.com/archives/features/2_apr02.htm. April 2, 2002.

56

b – a = a scale parameter; b is the maximum possible value.

Uniform distributions take the form

f(x) = 1/(b-a) if a ≤ x ≤ b

where

a < b

a = a location parameter; the minimum possible value, and b - a = a scale parameter; b is the maximum possible value.40

The assumptions that have been made about truck arrivals are the following:

1. Trucks (and the cargo contained within) will randomly choose an available cargo

bay door.

2. The number of cargo units unloaded from a truck will follow a triangular

distribution of the form TRIA(1, 8, 18) cargo units per truck.

The assumptions that have been made about the cargo process are the following:

1. The amounts of high-risk cargo: it is assumed that only 0.1% of all cargo entering

the facility will be high-risk. All designated high-risk cargo will be divided

evenly among the 5 high-risk types considered in this study, so that all incoming

cargo has a 0.02% chance of being one of the 5 high-risk types.

2. Cargo will be evenly distributed among the ten destinations served, so that all

incoming cargo has a 10% chance of being bound for any one destination.

3. The cargo delay time for paperwork and flight status verification will follow a

triangular distribution of the form TRIA(0.2, 0.75, 2) minutes per cargo unit.

40 Averill M. Law and W. David Kelton, Simulation Modeling and Analysis Third Edition,

McGraw-Hill, Boston, 2000, pp. 299 and 317.

57

4. Physical inspection of cargo will follow a triangular distribution of the form TRIA

(1,7,20) minutes per cargo unit.

5. Physical inspection is 100% effective at discovering all 5 types of high-risk cargo.

6. Any high-risk cargo that is discovered will be immediately removed from the

facility for further inspection.

7. Cargo sorting will follow a triangular distribution of the form TRIA(0.4, 0.6, 0.8)

minutes per cargo unit.

8. Cargo will be delayed at the city destination stations for a length of time

following a triangular distribution of the form TRIA(0.2, 0.4, 0.75) minutes per

cargo unit for the purpose of batching cargo into ULDs.

9. Cargo units will be batched together in ULDs and follow a triangular distribution

of the form TRIA(1, 2, 3) units per ULD.

10. The time required to place ULDs onto tugs will follow a triangular distribution of

the form TRIA(0.2, 0.3, 0.5) minutes per ULD.

11. ULDs are batched together on tugs following a uniform distribution of the form

UNIF(3, 4) ULDs per tug.

The assumptions that have been made about the security technologies and processes are

the following:

1. The time needed to process a cargo unit through x-ray, gamma ray, trace

detection, vapor detection, radiation detection, and canine scanning will follow

uniform distributions using the minimum and maximum time values listed in

Table 2.1 if they are chosen for analysis in the simulations.

58

2. The time needed to process a cargo unit through pulsed fast neutron analysis and

thermal neutron activation will maintain a constant value of 1 hour if chosen for

analysis in the simulations.

3. For each security case, cargo selected for security screening will proceed through

each security method unless a unit is found to be high risk, in which case it will be

removed from the security queue and physically inspected to determine whether

or not the cargo poses an actual risk.

3.5.3: Simulation Evaluations

The final evaluations of each security case will be based on the average amount of

time it takes a cargo unit to be processed, the percentage of high-risk cargo found based

on the amount of high-risk cargo selected for security screening, and the percentage of

high-risk cargo found based on the total amount of high-risk cargo being processed

through the facility regardless of whether or not it was selected for screening (henceforth

referred to as Percent Found from Security and Percent Found Total, respectively).

Significance testing will be performed on the Percent Found from Security and Percent

Found Total for each case in order to evaluate the results of the simulations.

59

CHAPTER 4: RESULTS

4.1: Airport Surveys

4.1.1: Introduction and Classification

The surveys yielded a 16% return rate. Most airports returning the survey did not

fully complete it, especially Part 2 that pertained to security. One initial observation was

that of a large gap in reported quarterly cargo volumes. Responding airports either had

volumes of 6,000 tons or less, or 12,000 tons or more. For the purposes of this project,

the responding airports were divided into two groups based on cargo volumes. Airports

that reported having 6,000 tons per quarter or less were classified as small cargo-handling

airports, and airports that reported processing more than 12,000 tons per quarter were

classified as large cargo-handling airports.

Six airports did not report any cargo volumes, so an alternative classification

method was needed in order to determine their group placement. The answers to

questions 1 through 5 were analyzed and compared with the answers given by airports

reporting quarterly cargo volumes. Airports reporting larger cargo volumes tended to

have more companies leasing and sorting cargo on site, along with larger facilities and

more aircraft parking positions. Airports not reporting cargo volumes with answers

similar to either large or small airports for the first five questions were placed in the

respective groups.

60

4.1.1: Responses and Reactions

Only 19 of the 118 surveys sent out were returned. One airport called to get

clarification on Questions 1 and 2, making sure the questions pertained to on-airport

cargo facilities only. A TSA official from another airport called to obtain verbal

reassurance that individual responses would not be published. The TSA official felt that

the survey questions were in compliance with TSA regulations, meaning that airports

should not be prohibited by law from answering any of the questions. However, some of

the airports that returned the surveys answered few or none of the questions pertaining to

security, stating that it was either against airport policy, TSA policy, or that the

information was simply unavailable. Two airports sent emails stating that they would not

return the survey because they thought it conflicted with TSA regulations. Out of 19

responses, 5 airports were interested in having a case study on cargo operations

performed at their cargo facilities.

4.1.2: Detailed Findings

The results from each individual question are given. The full set of graphical

results is given in Appendix A and shows the differences between small and large

airports, as well as the overall trends for all responding airports.

Question 1: How many companies/airlines SORT cargo at your airport (either at a

central sorting facility or at individual locations on airport property?

Total: The majority of respondents (61.1%) have 5 or fewer airlines/companies

(freight forwarders, etc) sorting cargo at their airports. Only 11.2% of respondents

61

have more than 15 airlines/companies sorting at their airports. 90% of airports

reporting 5 companies sorting or fewer were small airports.

Small Airports: 90% of small airports have 5 or fewer airlines/companies sorting

cargo at their airports. 40% of responding small airports have no airlines or

companies sorting cargo at their airports.

Large Airports: 75% of large airports have anywhere from 5 to 15

airlines/companies sorting cargo at their airports, and the spread between these

numbers is very even.

Question 2: How many companies/airlines LEASE cargo space (for storage, sorting,

etc.) at your airport?

Total: The majority of respondents (50%) have 5 or fewer airlines/companies

(freight forwarders, etc) leasing cargo space at their airports. Only 11.2% of

respondents have more than 15 airlines/companies leasing cargo space at their

airports.

Small Airports: 80% of small airports have 5 or fewer airlines/companies leasing

space at their airports.

Large Airports: Large airports tend to have more airlines/companies leasing from

them than smaller airports. Almost 40% of large airports have between 6 and 10

airlines/companies leasing from them. Another 25% have between 11 and 15

airlines/companies leasing space from them.

62

Question 3: What is the total size (e.g., in square feet, acres, etc) of your cargo

facilities?

Total: 47.1% of respondents have a total facility size of 100,000 square feet or

less. Only 11.8% of respondents have more than 250,000 square feet of total

cargo facility space. All airports with more than 200,000 square feet of total

facility space belong to large airports.

Small Airports: 60% of all small airports have 50,000 square feet or less of total

cargo facility space.

Large Airports: 75% of large airports have more than 200,000 square feet of total

cargo facility space.

Question 4: What is the total size (e.g., in square feet, acres, etc.) of each individual

facility?

Note: The results presented here represent size ranges for individual airport cargo

facilities. The results do not reflect whether a respondent had one facility or

multiple facilities.

Total: The majority of the facilities (35.6%) are 20,000 square feet or less. 27.1%

of the facilities are between 20,000 square feet and 40,000 square feet.

Small Airports: Over 60% of small airports have individual facilities that are

20,000 square feet or less. Nearly 24% have between 20,000 and 40,000 square

feet per facility.

Large Airports: 50% of large airports have 40,000 square feet per facility or less.

The large airports tend to have more space per facility than smaller airports.

63

Question 5: How many aircraft parking positions are there at each cargo facility?

Please list the number of positions for each facility.

Total: The majority of respondents (48.5%) reported that their facilities had 2 or

fewer aircraft parking positions. 93.9% of respondents have 10 or fewer aircraft

parking positions.

Small Airports: 78.6% of small airports have 2 or fewer aircraft parking positions

at their cargo facilities.

Large Airports: 31.3% of large airports have 2 or fewer aircraft parking positions,

and another 50% have between 3 and 6 aircraft parking positions per facility.

Question 6: Is sorting conducted centrally for all carriers, or individually by each

carrier?

All respondents reported that sorting is conducted individually by each carrier.

Question 7: How many airport/airline employees work in secure air cargo areas?

Total: 41.7% of respondents reported that 50 or fewer employees work in secure

air cargo areas. 83.3% have 150 or fewer employees working in secure air cargo

areas. Only 16.7% have over 200 employees working in secure air cargo areas.

Small Airports: 55.6% of small airports have 50 or fewer employees working in

secure cargo areas.

Large Airports: 50% of large airports have between 101 and 150 employees

working in secure cargo areas. No large airports reported having fewer than 51

employees in secure cargo areas.

64

Question 8: What percentage of the air cargo flowing through your airport is

international cargo?

Total: The majority of respondents (60%) reported that only 10% or less of their

cargo is international cargo. 93.3% of respondents reported 40% or less of their

cargo is international cargo.

Small Airports: 66.7% of small airports reported that 0-10% of their cargo is

international. No small airports reported having more than 40% international

cargo.

Large Airports: About 57% of large airports have between 0% and 10%

international cargo. 14.3% of large airports reported having over 90%

international cargo. Large airports have a tendency to have a higher percentage of

international cargo compared to small airports.

Question 9: What percentage of cargo flowing through your airport comes through as

belly freight on passenger planes?

Total: 40% of respondents reported that 10% or less of their cargo is transported

as belly freight. 60% of respondents reported that 20% or less of their cargo is

transported as belly freight. The corresponding histogram shows a significant gap

between responses: respondents tend to have 40% or less belly freight, or more

than 80% of cargo as belly freight.

Small Airports: Nearly 45% of small airports have less than 10% belly freight.

Another 22.2% have more than 90% belly freight.

65

Large Airports: 33.3% of large airports reported having less than 10% belly

freight, and another 33.3% reported having between 31% and 40% belly freight.

Nearly 17% of large airports have 81-90% belly freight.

Question 10: How is belly cargo from passenger planes transported from the plane to

the cargo facility and vice versa?

Total: Of the answers given, 68.8% of respondents report that tugs and/or carts

are used to transport belly cargo between the facility and the aircraft. Another

12.5% use trucks. Other responses, at 6.3% each, were pod loaders, belt loaders,

and ramps.

Small Airports: Small airports reported using only tugs and/or carts or trucks.

80% of small airports use tugs and/or carts to transport cargo.

Large Airports: Large airports use more methods than small airports. 60% of

large airports reported using tugs and/or carts to transport cargo.

Question 11a: What are the most common types of cargo passenger carriers?

Total: The two most common types are mail and perishable items (50% and

41.7%, respectively. Other reported items were fish, human remains, express

packages, electronics, medicine, live animals, gaming equipment, and caskets.

Small Airports: The most common types of cargo for passenger carriers reported

by small airports are mail and perishable items (reported by 50% and 33.3% of

small airports, respectively). Human remains and caskets were also reported.

66

Large Airports: The most common types of cargo for passenger carriers reported

by large airports are mail and perishable items (each reported by 50% of large

airports).

Question 11b: What are the most common types of cargo for all-cargo carriers?

Total: Express packages make up the majority at 36.6%. Electronics are second

at 36.4%. Also reported were manufactured items, retail merchandise, machine

parts, mail, perishable items, international goods, automobile parts,

pharmaceuticals, furniture, and chemicals.

Small Airports: 80% of small airports reported express packages as a common

cargo type for all-cargo carriers. Also reported were manufactured items, retail

merchandise, international freight, perishable items, and electronics at 20% each.

Large Airports: 50% of large airports report both express packages and

electronics as common cargo types for all-cargo carriers. Mail, perishable items,

and automobile parts were all reported by 33.3% of large airports.

Question 12: What are the latest quarterly volumes of cargo flow by weight for your

airport?

Note: Results reflect quarterly volumes from the past year and are split up by

quarter.

Total: For all 4 quarters, the majority of respondents reported a cargo flow of

3,000 tons or less per quarter (38.5% for Quarters 1 and 2, and 41.7% for Quarters

3 and 4). A significant percentage of respondents reported cargo flow in excess

67

of 27,000 tons per quarter (15.4% for Quarters 1 and 2, and 16.7% for Quarters 3

and 4).

Small Airports: For the first two quarters, about 80% of small airports reported

volumes less than 3,000 tons per quarter. No small airports reported volumes in

excess of 6,000 tons per quarter. For the third and fourth quarters, all small

airports reported volumes less than 3,000 tons per quarter.

Large Airports: For the first and second quarters, all large airports had more than

12,000 tons per quarter. Cargo volumes were fairly spread out from 12,000 tons

to more than 27,000 tons. For the last two quarters, all large airports had more

than 15,000 tons per quarter. For the third quarter, volumes were fairly spread out

again from 15,000 tons to more than 27,000 tons. In the fourth quarter, nearly

43% of large airports reported cargo volumes between 21,001 tons and 24,000

tons.

Question 13: Of all cargo flowing through your airport, what percentage of it is

subject to any sort of security screening, scanning, or inspection process?

Total: 70% of all respondents reported screening up to 10% of their cargo. Only

30% of respondents reported screening 91-100% of their cargo.

Small Airports: 71% of small airports reported screening 10% or less of their

cargo, and 29% reported screening more than 90% of their cargo.

Large Airports: 75% of large airports screen less than 10% of their cargo, and

25% reported screening over 90% of their cargo.

68

Question 14: What screening technologies are currently available and/or used for

cargo?

Total: Technologies reported were closed circuit television, x-ray technology,

canines, trace detection, and physical inspection. X-ray is the most popular

method, used by 54.5% of responding airports. Canines are the second most

popular method, used by 45.5% of responding airports. Physical inspection was

the least popular method, only used by 9.1% of respondents. Many respondents

reported using multiple screening methods at their airports.

Small Airports: X-ray is the most popular cargo screening method for small

airports, used by 83.3%. Closed circuit television (CCTV) is the second most

popular method at 66.7%. Both trace detection and canines are used at 50% of

responding small airports. Physical inspection is rarely used, at 9.1%.

Large Airports: Large airports do not use as many cargo-screening methods as

small airports do. Only CCTV, x-ray, and canines were reported as being used.

X-ray machines and canines were reported most frequently, each used be 80% of

responding large airports. CCTV is used by 60% of responding large airports.

Question 15: What type(s) of screening for airport/airline workers is currently used to

allow them to enter secure airport areas?

Total: Screening methods reported were background checks, ID badges,

biometrics, pin numbers, fingerprinting, badges, and smart or swipe cards.

Background checks and ID badges were the most popular methods, each used by

66.7% of responding airports. Badges and smart cards/swipe cards are also used

69

frequently, at 55.6% and 50.0%, respectively. Only 5.6% of respondents reported

using biometrics, pin numbers, or fingerprinting. Most respondents reported

using multiple screening methods at their airports.

Small Airports: 100% of responding small airports use background checks and ID

badges for employees accessing secure cargo areas. 80% use badges (i.e., an

airport patch on a uniform) and smart or swipe cards to control access. A small

percentage use biometrics and fingerprinting.

Large Airports: 87.5% of large airports use both background checks and ID

badges. 75% use both badges and smart or swipe cards. As can be seen from the

graph above, the use of various employee control access methods is similar

among both large and small airports.

Question 16: Are visitors allowed in the cargo facilities?

Total: 62.5% of responding airports allow visitors in the cargo facilities.

Small Airports: Just over 50% of small airports allow visitors in cargo facilities.

Large Airports: More than 70% of responding large airports allow visitors into the

cargo facilities.

Question 16a: If YES, are they subject to any type of screening?

Total: Of those airports that allow visitors, 80% screen them. All responding

airports that screen visitors do so by providing them with an authorized escort.

Small Airports: 80% of small airports provide visitors with an authorized escort.

70

Large Airports: 80% of large airports provide visitors with an authorized escort.

Question 17: What percentage of cargo coming through the airport is from known

shippers?

Total: The majority of responding airports, at 72.7%, have 91% to 100% of their

cargo coming from known shippers.

Small Airports: 57% of small airports have 91%-100% of their cargo coming

from known shippers. No small airports reported transporting less than 71%

known shipper cargo.

Large Airports: All responding large airports reported shipping 91%-100% known

shipper cargo.

Question 18: Are trucks carrying cargo to or from airport property allowed to enter

secured areas of the airport?

Total: 55.6% of all responding airports allow trucks to enter secure airport areas.

Small Airports: 60% of small airports allow trucks to enter secure airport areas.

Large Airports: 50% of large airports allow trucks to enter secure airport areas.

Question 19a: Truck clearance and security: Must the truck driver obtain clearance

for himself as the correct driver? Please explain.

Total: Of responding airports that allow trucks to enter secure airport areas, 100%

require truck driver verification. Verification methods reported were ID

verification, airport ID check, pin number, smart card or badge, biometrics,

71

prearranged clearance, and assignment of an authorized escort. ID verification

and assignment of an authorized escort were the most common responses, at

23.1% each. Airport ID checks and smart cards or badges were the second most

popular responses at 15.4% each.

Small Airports: Truck driver clearance methods for small airports are varied.

Identity verification is the most popular method, used by 28.6% of small airports.

Also reported used were airport IDs, biometric readers, authorized escorts, pin

numbers, and smart cards.

Large Airports: Large airports do not use as many methods as small airports do –

airport IDs, authorized escorts, and prearranged clearance were the only clearance

methods reported. Authorized escort was the most common measure used,

reported by 50% of large airports.

Question 19b: Truck clearance and security: How are the trucks themselves cleared?

Total: Of responding airports that allow trucks to enter secure airport areas, 80%

clear trucks manually. 10% clear them electronically, while another 10% clear

trucks by other methods.

Small Airports: 66.7% of small airports use manual clearance to allow trucks to

enter secure airport areas. Computer/electronic clearance and other methods are

each used by 16.7% of small airports.

Large Airports: 100% of responding large airports clear trucks manually.

72

Question 19c: Truck clearance and security: Are trucks inspected for firearms/stolen

goods, etc.?

Total: 25% of respondents reported inspecting trucks always, 25% sometimes,

and 25% never. 12.5% of responding airports reported frequently inspecting

trucks, and another 12.5% reported rarely inspecting trucks.

Small Airports: There is a significant gap in truck inspections at small airports.

Trucks are inspected frequently/always, or not at all. 40% of small airports

reported always inspecting trucks, while another 40% reported never inspecting

trucks.

Large Airports: Truck inspections at large airports are more synonymous,

occurring either sometimes or rarely. 66.7% of large airports report sometimes

inspecting trucks.

Question 20: Does international cargo flow through your airport?

Total: 61.1% of responding airports report that international cargo does flow

through them.

Small Airports: Only 40% of small airports handle international cargo. 75% of

small airports handling international cargo also have customs on site.

Large Airports: Almost 88% of large airports handle international cargo.

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Question 21a: For international cargo: On average, how long does it take for cargo to

clear customs?

Total: Of airports responding to Question 20, 42.9% report that international

cargo takes 1 to 2 hours to clear customs. 14.3% reported that it takes 4 or more

hours to clear international cargo through customs, while an equal percentage

reported 1 hour or less.

Small Airports: All responding small airports take a minimum of 3 hours to clear

international cargo through customs.

Large Airports: 60% of large airports take between 1 and 2 hours to clear

international cargo through customs. No large airports reported a clearance time

greater than 3 hours.

Question 21b: For international cargo: In general, for cargo that is selected for

screening, is it subject to more stringent screening than domestic cargo?

Total: For this question, 60% of airports reported that they do not screen

international cargo more stringently than domestic cargo.

Small Airports: 100% of small airports reported that international cargo is not

subject to additional screening.

Large Airports: 66.7% of large airports do screen international cargo more

stringently than domestic cargo.

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Question 22: Are the dumpsters in secure airport areas subject to any type of

surveillance?

Total: 73.3% of responding airports report that dumpsters are subject to

surveillance.

Small Airports: 66.7% of small airports subject dumpsters to surveillance.

Large Airports: 83.3% of large airports subject dumpsters to surveillance.

Question 22a: If YES, what type (CCTV, guard patrol, etc.)?

Total: Of those responding yes to the previous question, 53.3% use closed circuit

television for surveillance and 46.7% use a guard patrol.

Small Airports: Most small airports (62.5%) use CCTV to keep surveillance on

dumpsters. The rest use guard patrols.

Large Airports: 57.1% of large airports use guard patrols to keep an eye on

dumpsters. The rest reported using CCTV.

The results of the first section of the survey were used to gain an understanding of

how air cargo facilities are laid out, the size and scope of the operations within them, and

the characteristics of the cargo handled within them. The answers from the first section

were also used to classify airports as small cargo-handling airports and large cargo-

handling airports. The second section of the survey, which dealt with security issues, was

used to determine the state of security in and around air cargo facilities, what specific

measures are in use for ensuring security of cargo and personnel, and the frequency of

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use. In terms of direct cargo screening, which is the focus of this research, the results

show that only a small amount of cargo is screened.

4.1.3: Summary

As should be expected, larger airports have more companies sorting and leasing

space, larger cargo facilities, more aircraft parking positions, more employees, and more

varied types of cargo flowing through their airports than smaller airports.

Small airports are more inclined to use newer types of screening technologies for

cargo, truck drivers, trucks, and airport personnel. All responding small airports require

employee background checks, which is now also required by TSA. However, a small

percentage of large airports do not conduct background checks. This is a significant

vulnerability in that these airports are unaware of potential criminal behavior that could

easily go unnoticed amidst large, busy cargo operations.

Most airports require visitors to cargo facilities to remain under the supervision of

an authorized escort. However, the minority that does not leaves their cargo operations

vulnerable to theft and tampering.

None of the responding large airports will ship cargo from unknown shippers.

Many small airports ship a small percentage of cargo from unknown shippers. As long as

some type of verification process is in place to determine the legitimacy of the unknown

shipper and its shipments, this small percentage of unknown shipper cargo should not

pose a significant security threat.

76

Small airports are more likely to allow trucks into secured airport areas than

larger airports are. Those airports allowing trucks into secure areas should ensure that a

security checkpoint is in place to catch any suspicious people, vehicles, or cargo before

they gain access to secured areas. This can reduce susceptibility to theft and tampering.

All airports report requiring truck drivers to properly identify themselves. Identification

procedures vary.

Small airports either consistently inspect trucks or do not inspect them at all.

Large airports were more consistent with their responses – inspections are not frequent,

but they are conducted on some level at all responding large airports. Small airports

devoid of truck inspections leave themselves open to criminal activity, especially if the

lack of inspections is known.

Large airports handle much more international cargo than small airports, and they

can clear it through customs twice as fast. Most large airports reported subjecting

international cargo to more stringent screening than domestic cargo, yet none of the

responding small airports reported doing so.

Three quarters of airports keep their dumpsters under surveillance. Dumpsters

can be an outlet for cargo theft, so this is an important area of security coverage. Small

airports tend to use CCTV to watch dumpsters, while large airports lean more toward the

use of guard patrols.

Almost three quarters of all responding airports screen less than 10% of their air

cargo. This presents a serious security issue, leaving criminals and terrorists with ample

opportunities to transport explosive materials, stolen goods, and other contraband.

77

4.2: Screening Methods

As discussed in Section 3.3, the first phase of evaluation of the screening methods

consisted of analysis of the screening time, cost, and applicability in an air cargo

environment in order to determine what technologies would be chosen for the second

phase of evaluation (the simulations). Table 4.1 shows the results of the first evaluation

phase.

Screening Method Simulate? Reason for Not Simulating X-Ray Yes -- Gamma Ray Yes -- Pulsed Fast Neutron Analysis No Price ($25 million), time (1 hr +) Thermal Neutron Activation No Time (1 hr +) Vapor Detection Yes -- Trace Detection Yes -- Radiation Detection Yes -- Canines No More information needed

Table 4.1: Results of the First Phase of Evaluation of Screening Methods All of these methods were found to be applicable in an air cargo environment. Pulsed

fast neutron analysis was cut from consideration due to its high cost and unusually long

required screening time of one hour or more. Thermal neutron activation was

disqualified due to its lengthy screening time, as well. More research must be conducted

before canines can be accurately simulated. Although there is information available on

their screening time and their general effectiveness could be assumed, other information

such as the average frequency and duration of air cargo facility visits would be required

in order to effectively simulate canine screening. X-ray, gamma ray, vapor detection,

trace detection, and radiation detection will move to the second phase of evaluation, the

Arena simulations. The results of these will be discussed in the next section.

78

4.3: Arena Models

4.3.1: Simulation Results

The five screening technologies deemed suitable for simulation were arranged

into four different combinations that made up the four security cases simulated in Arena.

The average processing time of these combinations will be compared to the processing

time in the base case, which has no inspection technologies.

Case 1: X-ray

Case 2: X-ray, trace detection, and vapor detection

Case 3: X-ray, trace detection, vapor detection, and radiation detection

Case 4: X-ray, gamma ray, trace detection, vapor detection, and radiation

detection.

For each case, cargo units that were selected to go through the security process passed

through each technology in the order listed above unless one of the technologies detected

a risk. When a risk was detected in a cargo unit, the unit was removed from the security

queue and inspected physically to determine whether or not a risk actually existed.

Tables 4.2 through 4.6 show which cases are capable of scanning for a particular threat

along with how many of the technologies in each case can scan for one particular threat.

Table 4.7 is a combination of Tables 4.2 through 4.6, showing how many technologies in

each case can scan for each threat. An “x” denotes one screening method.

79

Case 1 Case 2 Case 3 Case 4 X-Ray x x x x Gamma Ray x Vapor Detection Trace Detection x x x Radiation Detection

Table 4.2: Cases with Screening Technologies Capable of Screening for Explosives

Case 1 Case 2 Case 3 Case 4 X-Ray x x x x Gamma Ray x Vapor Detection Trace Detection Radiation Detection

Table 4.3: Cases with Screening Technologies Capable of Screening for Stolen/Mislabeled Goods

Case 1 Case 2 Case 3 Case 4 X-Ray x x x x Gamma Ray x Vapor Detection Trace Detection x x x Radiation Detection

Table 4.4: Cases with Screening Technologies Capable of Screening for Illegal Drugs

Case 1 Case 2 Case 3 Case 4 X-Ray Gamma Ray Vapor Detection Trace Detection Radiation Detection x x

Table 4.5: Cases with Screening Technologies Capable of Screening for Radioactive Materials

Case 1 Case 2 Case 3 Case 4 X-Ray Gamma Ray Vapor Detection Trace Detection x x x Radiation Detection

Table 4.6: Cases with Screening Technologies Capable of Screening for Dangerous/Illegal Gases

80

Case 1 Case 2 Case 3 Case 4 Explosives x xx xx xxx Stolen/Mislabeled Goods x x x xx Illegal Drugs x xx xx xxx Illegal/Dangerous Gases x x x Radioactive Materials x x Table 4.7: Number of Screening Technologies In Each Case Capable of Detecting Each Threat Type

All the simulations incorporate 10% physical inspection, the assumed required

percentage by TSA, however the analysis of the physical inspection will be separate from

the analysis of the security cases. Table 4.8 shows the results for the average number of

cargo units processed during the 5-year simulation period and the average length of time

required to process the cargo. The percentages listed underneath each case represent the

total percentage of cargo screened.

Cases Avg.

System Cost

Avg. No. Units

Processed

Avg. Units Processed Per Case

Avg. Process

Time (min)

Avg. Process Time Per

Case Base - 579,354 579,354 99 99

Case 1: 10% 572,883 102 25% 572,474 106 50%

$5,000,000

578,348

574,568

114

108

Case 2: 10% 565,080 104 25% 569,562 107 50%

$5,580,000

575,300

569,981

113

108

Case 3: 10% 569,433 103 25% 579,036 106 50%

$5,610,000

565,041

571,170

118

109

Case 4: 10% 568,377 105 25% 554,789 117 50%

$7,360,000

581,675

568,280

136

119

Table 4.8: Case Costs and Processing Results

81

The cost of each case increases as more screening methods are added to the cases. The

amount of time needed to process cargo increases as screening methods are added, as

well. This was expected since additional screening required additional time. Within each

case it can be seen that increasing the percentage of cargo screened results in a significant

increase in the average cargo processing time. The average number of units processed

did not uniformly decrease as expected. This is most likely due to a problem inherent in

Arena, in which units that are “batched” together to form a single unit all take on the

properties and attributes of the first unit in the batch.

Tables 4.9 through 4.13 show the results from the screenings for each high-risk

material including the number of each high-risk type caught by each applicable screening

method, the number of each high-risk type missed by each applicable screening method,

the number of false positives given by each screening method, the percentage of high-risk

cargo units caught that went through each security case, and the percentage of the total

number of high-risk goods entering the facility that were caught. The values given are

the averages of the three simulations performed for each percentage screened (10%, 25%,

and 50% for each case). The base case is not included in these results since there are no

technologies incorporated in the base case simulation. These results also do not include

any high-risk units caught by the initial physical inspection.

82

Case 1 Case 2 Case 3 Case 4 10% 25% 50% 10% 25% 50% 10% 25% 50% 10% 25% 50% Expl. Found

by X-Ray 3 9 22 2 9 21 3 8 15 5 6 18

Expl. Not Found by X-

Ray 1 4 11 2 2 7 2 4 9 1 4 9

Expl. Found by GR - - - - - - - - - 1 3 6

Expl. Not Found by

GR - - - - - - - - - 0 2 3

Expl. Found by TD - - - 1 2 6 2 2 7 0 1 2

Expl. Not Found by

TD - - - 1 1 1 0 2 2 0 1 1

False Positives 0 1 1 0 0 0 0 0 1 0 0 1

Total Found 3 9 22 3 11 27 5 10 22 6 10 26

Total Not Found 1 4 11 3 3 8 2 6 11 1 7 13

% Found from

Screening 69% 69% 66% 75% 92% 97% 93% 87% 90% 100

% 93% 97%

% Found from

Screening (Case Avg.)

68% 88% 90% 97%

Total % Found 5% 14% 35% 5% 19% 43% 8% 15% 37% 9% 16% 43%

Total % Found (Case

Avg.) 18% 22% 20% 23%

Table 4.9: Results for Explosives/Explosive Materials Detection

Looking at Table 4.9, the likelihood of discovering explosives increases when more than

one screening method is used to scan for them. In Case 1, where x-ray was the only

method used to scan for explosives, only 68% of the explosives passing through the x-ray

machine were found. In Cases 2 and 3 where a trace detector was introduced, this

statistic increased to around 90%. Case 4 used x-ray, trace detection, and gamma ray to

screen for explosives, and nearly 100% of all explosives going through the security

83

machines were discovered. The overall percentage of explosives found increased, also,

but the increase was small.

Case 1 Case 2 Case 3 Case 4 10% 25% 50% 10% 25% 50% 10% 25% 50% 10% 25% 50%

SG Found by X-Ray 4 7 19 4 8 17 3 8 19 4 7 15

SG Not Found by X-

Ray 0 5 9 1 3 7 1 3 7 2 2 8

SG Found by GR - - - - - - - - - 1 1 5

SG Not Found by

GR - - - - - - - - - 0 1 3

False Positives 0 0 0 0 0 0 0 0 0 0 0 0

Total Found 4 7 19 4 8 17 3 8 19 5 8 20

Total Not Found 0 5 9 1 3 7 1 3 7 2 3 11

% Found from

Screening

100% 58% 68% 86% 66% 70% 69% 74% 76% 83% 85% 87%

% Found from

Screening (Case Avg.)

75% 74% 73% 85%

Total % Found 8% 11% 32% 7% 14% 32% 5% 14% 37% 11% 16% 37%

Total % Found (Case

Avg.) 17% 17% 19% 21%

Table 4.10: Results for Stolen/Mislabeled Goods Detection

Like Table 4.9, Table 4.10 shows the increased likelihood of discovering more units

containing stolen/mislabeled goods when more than one technology is used to scan for

them. Cases 1 through 3 used only x-ray to scan for stolen/mislabeled goods, and the

overall percentage discovered was fairly consistent at 17% to 19%. The percentage

found from the security queue varied only slightly within Cases 1 through 3. When the

gamma ray detector was introduced in Case 4, both percentages increased, but the

increase in the total percentage found was slight – about 3%.

84

Case 1 Case 2 Case 3 Case 4 10% 25% 50% 10% 25% 50% 10% 25% 50% 10% 25% 50%

Drugs Found by

X-Ray 4 10 18 3 5 16 4 9 18 6 8 13

Drugs Not Found by

X-Ray 1 5 7 2 4 6 1 3 7 0 4 7

Drugs Found by

GR - - - - - - - - - 0 3 5

Drugs Not Found by

GR - - - - - - - - - 0 1 2

Drugs Found by

TD - - - 2 3 3 1 2 6 0 1 1

Drugs Not Found by

TD - - - 0 1 3 1 1 1 0 0 0

False Positives 0 0 0 0 0 1 0 0 0 0 0 0

Total Found 4 10 18 5 8 19 5 11 24 6 12 19

Total Not Found 1 5 7 2 5 9 2 5 13 0 5 9

% Found from

Screening 86% 69% 73% 89% 86% 85% 86% 95% 95% 100

% 100% 98%

% Found from

Screening (Case Avg.)

76% 87% 92% 99%

Total % Found 7% 18% 34% 9% 14% 32% 6% 19% 45% 11% 22% 38%

Total % Found

(Case Avg.) 19% 18% 23% 24%

Table 4.11: Results for Illegal Drug Detection

Looking at Table 4.11, increasing the number of technologies to scan for illegal drugs

increased the percentage caught, as was the case for explosives and stolen/mislabeled

goods. Case 1, which only used an x-ray machine, only caught 76% of all illegal drugs

passing through security, while Cases 3 and 4 caught over 90% of the illegal drugs

passing through security. Using a trace detector or a trace detector coupled with a

85

gamma ray detector as backup methods for the x-ray machine increased the percentage of

illegal drugs caught that passed through the security case. The overall percentage

increase was very slight moving from Case 1 through Case 4, with an overall increase of

5%.

Case 1 Case 2 Case 3 Case 4 10% 25% 50% 10% 25% 50% 10% 25% 50% 10% 25% 50%

Gases Found by VD - - - 5 8 21 3 9 17 5 10 18

Gases Not Found by

VD - - - 3 2 9 1 5 6 3 5 8

False Positives - - - 0 1 0 0 0 0 0 0 0

Total Found - - - 5 8 21 3 9 17 5 10 18

Total Not Found - - - 3 2 9 1 5 6 3 5 8

% Found from

Screening 0% 0% 0% 62% 75% 69% 56% 67% 75% 61% 69% 69%

% Found from

Screening (Case Avg.)

0% 68% 66% 67%

Total % Found 0% 0% 0% 8% 15% 35% 6% 14% 31% 8% 19% 34%

Total % Found (Case

Avg.) 0% 19% 17% 20%

Table 4.12: Results for Dangerous Gases Detection

Since only one of the technologies was suited for detecting dangerous gases, no real

increase in the percentage of dangerous gases found can be seen. Incorporation of the

vapor detector resulted in about an 18% detection rate of all dangerous gases entering the

facility and a 67% detection rate of dangerous gases passing through the security case.

86

Case 1 Case 2 Case 3 Case 4 10% 25% 50% 10% 25% 50% 10% 25% 50% 10% 25% 50%

Rad. Found by RD - - - - - - 2 9 18 3 7 17

Rad. Not Found by

RD - - - - - - 0 3 10 1 3 8

False Positives - - - - - - 0 0 1 0 0 0

Total Found - - - - - - 2 9 18 3 7 17

Total Not Found - - - - - - 0 3 10 1 3 8

% Found from

Screening 0% 0% 0% 0% 0% 0% 92% 74% 63% 50% 69% 64%

% Found from

Screening (Case Avg.)

0% 0% 76% 61%

Total % Found 0% 0% 0% 0% 0% 0% 5% 16% 30% 4% 13% 29%

Total % Found (Case

Avg.) 0% 0% 17% 15%

Table 4.13: Results for Radioactive Materials Detection

The radiation detector was only incorporated in Cases 3 and 4, and both cases show

around a 16% overall radiation detection rate. For radioactive substances passing

through security, 76% of them were detected in Case 3, and 61% were detected in Case 4.

Table 4.14 shows the percentage of all high-risk cargo found for each case – for

high-risk cargo just going through security and for all high-risk cargo entering the

facility. Again, the base case is not included in the table since there are no technologies

incorporated in the base case simulation, and these results also do not include high-risk

cargo caught by the initial physical inspection.

87

Case 1 Case 2 Case 3 Case 4 % of All High-Risk Cargo Found

from Screening 44% 63% 79% 82%

Total % of All High-Risk Cargo Found 11% 15% 19% 21%

Table 4.14: Results for Overall High-Risk Cargo Detection

The percentage of high-risk cargo found increased with each case. As more technologies

are added to the security lineup, more high-risk cargo is discovered. The percentages of

high-risk cargo found in Case 4 nearly doubles the percentages found in Case 1, and Case

3 has percentages only marginally smaller than those in Case 4.

4.3.2: Simulation Significance Testing

Three replications were performed for each screening percentage (i.e., 10%, 25%,

and 50% of cargo screened) within each case, and significance testing based on the 95%

confidence intervals of each set of replications was conducted to discover any significant

differences in the results. Tables 4.15 through 4.19 show the means and the 95%

confidence intervals for all four cases and for all five high-risk types.

88

% Found from Security % Found Total Mean 95% Conf. Interval Mean 95% Conf. Interval

Case 1 10% 69% 67 5% 7 25% 69% 41 14% 3 50% 66% 23 35% 16

Case 2 10% 75% 62 5% 3 25% 92% 21 19% 22 50% 97% 14 43% 10

Case 3 10% 93% 29 8% 8 25% 87% 28 15% 4 50% 90% 5 37% 11

Case 4 10% 100% 0 9% 17 25% 94% 15 16% 13 50% 97% 9 42% 14

Table 4.15: Means and 95% Confidence Intervals for Explosives Detection

% Found from Security % Found Total Mean 95% Conf. Interval Mean 95% Conf. Interval

Case 1 10% 100% 0 8% 18 25% 58% 39 11% 8 50% 68% 31 32% 9

Case 2 10% 86% 32 7% 5 25% 66% 51 14% 13 50% 70% 24 32% 18

Case 3 10% 69% 75 6% 5 25% 74% 37 14% 7 50% 76% 39 36% 8

Case 4 10% 84% 41 10% 19 25% 85% 9 16% 13 50% 87% 11 37% 15

Table 4.16: Means and 95% Confidence Intervals for Stolen Goods Detection

89

% Found from Security % Found Total Mean 95% Conf. Interval Mean 95% Conf. Interval

Case 1 10% 86% 62 7% 10 25% 70% 8 18% 4 50% 73% 22 34% 14

Case 2 10% 89% 47 9% 6 25% 86% 38 14% 2 50% 85% 10 32% 9

Case 3 10% 86% 42 6% 14 25% 95% 11 19% 12 50% 95% 14 45% 7

Case 4 10% 100% 0 11% 3 25% 100% 0 22% 13 50% 98% 7 38% 14

Table 4.17: Means and 95% Confidence Intervals for Illegal Drugs Detection

% Found from Security % Found Total Mean 95% Conf. Interval Mean 95% Conf. Interval

Case 1 10% - - - - 25% - - - - 50% - - - -

Case 2 10% - - - - 25% - - - - 50% - - - -

Case 3 10% 92% 36 5% 4 25% 74% 14 16% 6 50% 63% 25 30% 5

Case 4 10% 50% 100 4% 9 25% 70% 52 13% 17 50% 64% 8 29% 6

Table 4.18: Means and 95% Confidence Intervals for Radioactive Materials Detection

90

% Found from Security % Found Total Mean 95% Conf. Interval Mean 95% Conf. Interval

Case 1 10% - - - - 25% - - - - 50% - - - -

Case 2 10% 62% 27 7% 9 25% 75% 53 15% 21 50% 69% 21 35% 18

Case 3 10% 55% 96 6% 16 25% 67% 15 14% 15 50% 75% 4 31% 5

Case 4 10% 61% 13 8% 9 25% 69% 20 19% 8 50% 69% 50 34% 30

Table 4.19: Means and 95% Confidence Intervals for Dangerous Gases Detection

Figures 4.1 through 4.6 show the spreads of the 95% confidence intervals for the

Percent Found from Security and the Percent Found Total. Figures 4.1 through 4.3 show

the confidence interval spreads for the percentages screened (10%, 25%, and 50%)

among the four cases for the Percent Found from Security, and Figures 4.4 through 4.6

show the same spreads for the Percent Found Total. Spreads that overlap suggest that

there is not a significant difference in the results. Each figure has a dashed line indicating

the average of the means for the intervals presented (the assumed true mean) through

which most of the intervals should intersect. Fewer intersections indicate more of a

significant difference in the results.

91

All High-Risk, 10% Screening: 95% Confidence Intervals for % Found from Security

0 20 40 60 80 100 120

95% Confidence Interval Spreads

Case 1, ExplCase 2, ExplCase 3, ExplCase 4, ExplCase 1, SGCase 2, SGCase 3, SGCase 4, SGCase 1, DrugsCase 2, DrugsCase 3, DrugsCase 4, DrugsCase 3, RMCase 4, RMCase 2, GasesCase 3, GasesCase 4, Gases

Figure 4.1: 95% Confidence Interval Spreads for 10% Screening in All Four Cases and for All Five

High-Risk Types for Percent Found from Security

All High-Risk, 25% Screening: 95% Confidence Intervals for % Found from Security

0 20 40 60 80 100 120

95% Confidence Interval Spreads

Case 1, ExplCase 2, ExplCase 3, ExplCase 4, ExplCase 1, SGCase 2, SGCase 3, SGCase 4, SGCase 1, DrugsCase 2, DrugsCase 3, DrugsCase 4, DrugsCase 3, RMCase 4, RMCase 2, GasesCase 3, GasesCase 4, Gases

Figure 4.2: 95% Confidence Interval Spreads for 25% Screening in All Four Cases and for All Five

High-Risk Types for Percent Found from Security

µ = 78.3

µ = 79.8

92

All High-Risk, 50% Screening: 95% Confidence Intervals for % Found from Security

0 20 40 60 80 100 120

95% Confidence Interval Spreads

Case 1, ExplCase 2, ExplCase 3, ExplCase 4, ExplCase 1, SGCase 2, SGCase 3, SGCase 4, SGCase 1, DrugsCase 2, DrugsCase 3, DrugsCase 4, DrugsCase 3, RMCase 4, RMCase 2, GasesCase 3, GasesCase 4, Gases

Figure 4.3: 95% Confidence Interval Spreads for 50% Screening in All Four Cases and for All Five

High-Risk Types for Percent Found from Security

Looking at Figures 4.1 through 4.3, the interval overlap for 10% screening is very good,

meaning that there are no real significant differences in the results of 10% screening of

all high-risk cargo among the four cases. The interval overlap for 25% screening is fair,

and there is not as much total overlap as in the 10% screening. It should be noted that the

confidence interval spreads are smaller in the 25% screening compared to the 10%

screening. The interval overlap for the 50% screening is poor. Just over half of the

intervals intersect with the assumed true mean, µ. The confidence intervals are much

smaller for the 50% screening than in the 10% or 25% screenings. This suggests that

there are some significant differences in the results for the 50% screening. These

possible significant differences and large confidence interval spreads likely result from

µ = 78.9

93

the randomness of stochastic simulations along with the batching problem inherent in

Arena.

All High-Risks, 10% Screening: 95% Confidence Intervals for % Total Found

0 5 10 15 20 25

95% Confidence Interval Spreads

Case 1, ExplCase 2, ExplCase 3, ExplCase 4, ExplCase 1, SGCase 2, SGCase 3, SGCase 4, SGCase 1, DrugsCase 2, DrugsCase 3, DrugsCase 4, DrugsCase 3. RMCase 4, RMCase 2, GasesCase 3, GasesCase 4, Gases

Figure 4.4: 95% Confidence Interval Spreads for 10% Screening in All Four Cases and for All Five

High-Risk Types for Total Percent Found

µ = 7.1

94

All High-Risk, 25% Screening: 95% Confidence Intervals for % Total Found

0 5 10 15 20 25 30 35

95% Confidence Interval Spreads

Case 1, ExplCase 2, ExplCase 3, ExplCase 4, ExplCase 1, SGCase 2, SGCase 3, SGCase 4, SGCase 1, DrugsCase 2, DrugsCase 3, DrugsCase 4, DrugsCase 3, RMCase 4, RMCase 2, GasesCase 3, GasesCase 4, Gases

Figure 4.5: 95% Confidence Interval Spreads for 25% Screening in All Four Cases and for All Five

High-Risk Types for Total Percent Found

All High-Risk, 50% Screening: 95% Confidence Intervals for % Total Found

0 10 20 30 40 50 60

95% Confidence Interval Spreads

Case 1, ExplCase 2, ExplCase 3, ExplCase 4, ExplCase 1, SGCase 2, SGCase 3, SGCase 4, SGCase 1, DrugsCase 2, DrugsCase 3, DrugsCase 4, DrugsCase 3, RMCase 4, RMCase 2, GasesCase 3, GasesCase 4, Gases

Figure 4.6: 95% Confidence Interval Spreads for 50% Screening in All Four Cases and for All Five

High-Risk Types for Total Percent Found

µ = 15.8

µ = 35.4

95

Looking at Figures 4.4 through 4.6, the interval overlap for all three screening

percentages is good, although a slight decrease in the number of overlapping spreads can

be seen the results for 50% screening. The confidence intervals do not narrow moving

from 10% screening up to 50% screening as they did in the results from Percent Found

from Security. The results presented in Figures 4.4 through 4.6 do not suggest significant

differences within the screening percentages. Although these results do not suggest any

real significant differences in the screening percentages, the confidence interval overlaps

could be improved and the intervals themselves shortened if the batching problem in

Arena had not been a factor.

4.3.3: Summary

The simulation results show that the average cargo processing time increases as

the percentage of all cargo screened moves from 10% up to 25% and 50%. The average

cargo processing time also increases as more screening technologies are added into the

simulations (especially when looking at the results of Case 4), but this increase is not as

dramatic. Looking at the results from the Percent Total Found, a steady but slight

increase can be seen moving from Case 1 to Case 4 for the detection of explosives,

stolen/mislabeled goods, and illegal drugs. This increase is not seen for radioactive

materials or dangerous gases among the cases since only one technology was used to scan

for these threats. In terms of all the high-risk cargo types found, there is a sizeable

increase in the percentage found for both Percent Found Total and Percent Found from

Security – Case 4 nearly doubles the percents found in Case 1. Significance testing

shows that for the Percent Found Total, there is not evidence to suggest that the results

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are significantly different. However, this is not the case for the Percent Found from

Security, where the confidence intervals in the 25% and 50% screening suggest that there

could be some significant differences. This is noteworthy since the Percent Found Total

is of greater consequence than the Percent Found from Security. The Percent Found

Total indicates how much of all high-risk cargo entering the facility was discovered and

therefore how effective each case truly is. The Percent Found from Security indicates

how effective the screening technologies are only in terms of the high-risk cargo they

catch based on the high-risk cargo chosen for inspection. The implications of these

results and the impacts of the batching errors in Arena will be discussed in the next

chapter.

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CHAPTER 5: CONCLUSIONS AND RECOMMENDATIONS

5.1: Conclusions

5.1.1: Surveys

The airport surveys gave an insightful look into the security practices at the

nation’s airports and the differences in security practices between larger and smaller

airports. Small airports are more likely to invest in newer screening technologies for both

people and cargo, including biometrics and trace detection. For cargo screening, larger

airports rely heavily on x-ray machines and canine inspections. Truck driver verification

is a standard practice at U.S. airports, however occurrence of inspections of the trucks

themselves is quite varied. The most alarming statistic gathered from the surveys is that

three quarters of the nation’s airports screen less than 10% of their air cargo, thus

validating the need for this project.

5.1.2: Arena Models

One conclusion that can be made from the results is that simply an increase in the

amount of cargo screened provides a higher number of high-risk cargo caught than

adding more screening technologies to the security lineup. However, increasing the

variety of screening technologies results in a better chance of catching a variety of

threats. In terms of a recommendation for the case study facility, Case 3 would best serve

the purpose. Although Case 4 found more high-risk cargo both for Percent Found from

Security and Percent Found Total, the significantly higher cost and average processing

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time cannot be justified. Case 4 found only a slightly higher percentage of high-risk

cargo than Case 3, and the cost and processing time of Case 3 are comparable to Cases 1

and 2.

The significance testing of the confidence intervals revealed that there may be

some significant differences in the Percent Found from Security, which could be

explained by the error caused when Arena batches two or more entities together to form a

single entity that takes on the properties of the first entity in the batch. Evidence of this

error can be seen in Table 4.8, where the average number of units processed per case does

not uniformly decrease as expected. As more screening methods are added in each case,

the time to process cargo should increase, which should in turn result in fewer cargo units

being processed. Another simulation package may be able to give the expected results.

The results show that this framework (albeit with a different simulation package)

can be used to determine how well a particular security case will perform in an individual

facility. With a few minor changes to the simulations and the proper sets of data, the

results of this research can be applied to any individual air cargo facility. Government

organizations, airport authorities and organizations, airlines, and freight forwarders could

benefit from the implementation of this framework for their own security testing purposes

because of its adaptability. The government could also use the results of such security

testing to develop better and more specific legislation to regulate air cargo security. The

setup requires only minor changes to the models in order to properly reflect the facility of

concern, and with the appropriate data, any security screening method may be tested

within the models.

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5.2: Recommendations

From the results of the Arena models, Case 3 is recommended as the best case for

the case study facility. Ultimately, the recommended case would depend on the

individual needs and specific security concerns of an airport, airline, freight forwarder, or

government organization. Case recommendations aside, a framework such as the one

presented in this project can be of help to government organizations attempting to create

better air cargo security legislation. Evaluations of screening methods with this

framework can give the government detailed information on what methods or

combinations thereof are feasible for application in an air cargo facility and how effective

they will be at discovering threats. Using this information, the federal government can

enact specific security standards that will ensure the security of air cargo parcels, the

aircraft they travel in, and the facilities that process them.

In order to make the framework outlined in this project more feasible, more

detailed data must be gathered on the processes within a cargo facility, thereby

eliminating the need for assumptions in the simulations. The simulations may be

specifically tailored to a facility to determine the best case for that facility. More

research is also needed on the frequency and duration of canine teams to cargo facilities.

Again, this information can be used to specifically tailor the simulations to a certain

facility. Also, more research is needed on the efficiency of the screening technologies.

This information is essential to properly determine what type or types of security setups

will work in an air cargo setting. Finally, a different simulation package would serve to

eliminate Arena’s batching errors and give results that are not significantly different.

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In the end, the best security setup for an air cargo facility will be a layered

approach consisting of direct cargo screening, perimeter access control, personnel

screening, and security programs such as the known shipper program or C-TPAT adapted

for an air cargo environment. A layered setup ensures multiple back-ups in case of a

failure in one area. Direct cargo screening, the portion of air cargo security explored in

this project, alone will not ensure the security of air cargo, but it is an integral part of the

larger, layered picture, and it can be an important first step in the development of this

layered approach.

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REFERENCES

1. ACI-NA Air Cargo Facilities and Security Survey. Michael Webber, Airports

Council International-North America. September 2002.

2. Air Cargo Development Manager at case study airport. Personal interview.

December 4, 2003.

3. “Air Cargo Security,” Transportation Security Administration Q & A from Airports

Council International North America. May 8, 2002. www.aci-na.org.

4. “Air Cargo Strategic Plan,” Transportation Security Administration Press Release.

November 17, 2003.

http://www.tsa.gov/public/interapp/press_release/press_release_0371.xml

5. “Airport Data (5010) and Contact Information,” The Federal Aviation

Administration. April 9, 2004.

http://www.faa.gov/arp/safety/5010/index.cfm?nav=safedata.

6. “Airport Security Report,” PBI Media LCC, Volume 6, Number 5. February 27,

2002.

7. “Airport Security,” Title 49 of the Code of Federal Regulations, Subchapter B, Part

1542. http://www.tsa.gov/public/display?theme=79&content=0900051980096ff5.

8. Armbruster, William. “Breaking News,” Air Cargo World Online. October 2002.

www.aircargoworld.com/break_news/3.htm.

9. AutoModTM Information Packet, Brooks-PRI Automation. 2003

10. Aviation and Transportation Security Act, Section 110(f), Public Law 107-071.

Passed by 107th Congress, November 19, 2001.

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11. “Aviation Safety: Undeclared Air Shipments of Dangerous Goods and DOT’s

Enforcement Approach,” U.S. General Accounting Office, Presented to U.S. House

of Representatives. January 2003.

12. “Aviation Security: Efforts to Measure Effectiveness and Address Challenges,” U.S.

General Accounting Office. November 2003.

13. “Aviation Security: Vulnerabilities and Potential Improvements for the Air Cargo

System,” U.S. General Accounting Office, Presented for the U.S. Senate. December

2002.

14. “Boeing World Air Cargo Forecast 2002-2003: North America,” Boeing.com. April

2002. www.boeing.com/commercial/cargo/n_america.html.

15. Cargo Sales Manager at case study facility. Personal interview. December 4, 2003.

16. “Cargo VIZ User Manual,” Applied Visualization Center, University of Tennessee,

Knoxville. July 30, 2003. http://viz.utk.edu/projects/tsa/cargoviz/cargo_viz.pdf.

17. Carroll, James R. “Legislation Would Tighten Security Rules for Air Freight,” The

Courier Journal. April 7, 2003.

www.courier-journal.com/localnews/2003/04/07/ke040703s393116.htm

18. “Committee Approves Air Cargo Security Bill,” U.S. Senate Press Release. March

13, 2003. www.senate.gov/~commerce/press/03/2003313730.html.

19. “Container Security: Expansion of Key Programs Will Require Greater Attention to

Critical Success Factors,” U.S. General Accounting Office. July 2003.

20. Dickson, Gordon and Byron Okada. “Gaps cited in air cargo security,” Knight-

Ridder/Tribune News Service. February 27, 2002. InfoTrac

Web, Electronic Collection CJ83335612.

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21. “Electronic Supply Chain Manifest Freight ITS Operational Test Evaluation: Final

Report,” U.S. Department of Transportation. December 2002.

http://www.itsdocs.fhwa.dot.gov//JPODOCS/REPTS_TE//13769.html.

22. Harris, David. “The Air Cargo Security Plan,” The International Air Cargo.

Association. December 17, 2003.

http://www.tiaca.org/articles/2003/12/17/388C7D7AAA454B9D86BB24EF5033

3B66.asp.

23. Holcomb, Henry J. “Security Tightens by Monitoring Ships and Cargo,”

Philadelphia Inquirer. March 19, 2003.

www.centredaily.com/mld/centredaily/news/5428395.htm.

24. Hutchinson, Asa. Under Secretary for Border and Transportation Security, Eno

Transportation Foundation 2004 Leadership Development Conference, Session on

Security: Transforming How We Manage Transportation. May 26, 2004.

25. Jones, Jennifer. “A Moving Target – Border Control and Transportation Safety Apps

Put Biometrics to the Test,” Federal Computer Week. June 23, 2003.

www.fcw.com/fcw/articles/2003/0623/cov-report2-06-23-03.asp.

26. Law, Averill M. and W. David Kelton. Simulation with Arena 3rd Edition,”

McGraw-Hill: Boston. 2004.

27. Malkin, Richard. “An Air Cargo Century,” Air Cargo World Online. January 2000.

http://www.aircargoworld.com/archives/feat1jan00.htm.

28. “McGreevey Calls on Fed to Establish Stricter Air Cargo Guidelines,” Press Release,

New Jersey Office of the Governor. August 8, 2003. http://www.state.nj.us/cgi-

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bin/governor/njnewsline/view_article.pl?id-1329.

29. Nice, Karim. “How Air Freight Works,” Howstuffworks.com. September 2002.

www.howstuffworks.com/air-freight.htm.

30. Parezo, Stephen. “Containing Security,” Air Cargo World Online. April 2002.

http://www.aircargoworld.com/archives/features/2_apr02.htm.

31. Partnership Against Terrorism. June 14, 2002.

http://www.cargosecurity.com/ncsc/coac/Non-intrusive.pdf.

32. Perry, Celeste. “Iridian Helps Cut Airport Waits as Security Tightens (Update 1),”

Bloomberg L.P. January 8, 2003.

http://www.biometricgroup.com/in_the_news/bloomberg.html.

33. Porteus, Liza. “Homeland Security Technologies in the Pipeline,” Fox News.

January 14, 2004. http://foxnews.com/story/0,2933,108289,00.html.

34. “R.I.S.K. Alert—Supply Chain Technology Aids Homeland Security,” Transentric

Press Release. March 28, 2003.

www.transentric.com/WhatsNew/pressReleases1.asp?intWhatsNewID=65.

35. TCRP Report 86: Public Transportation Security Volume 2, K9 Units in Public

Transportation: A Guide for Decision Makers, National Academy Press, Washington

D.C. 2002.

36. “Volume 6 – Report on Non-intrusive Detection Technologies,” U.S. Treasury

Advisory Committee on Commercial Operations of The United States Customs

Service Subcommittee on U.S. Border Security Technical Advisory Group and

Customs Trade Partnership Against Terrorism. June 14, 2002. http://www.cargosecurity.com/ncsc/coac/Non-intrusive.pdf.

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APPENDIX A: SURVEY MATERIALS

A.1: Air Cargo Operations and Security Survey

University of Virginia Center for Transportation Studies

Air Cargo Operations and Security Survey

Airport Name and Location: ________________________________________________ Airport Code: ____________________________________________________________ Respondent’s Name and Title: _______________________________________________ Address: ________________________________________________________________ ________________________________________________________________________ Telephone: _______________________ Email: ________________________________ Note: Answers to all questions will be kept confidential. No identifying information about any individual airport will be included in the results summaries. Would you like to receive a results summary from this survey? Yes No If yes, please make sure that the address information above is completed.

PART 1: GENERAL AIR CARGO AND AIRPORT INFORMATION

1. How many companies/airlines sort cargo at your airport (either at a central sorting facility or at individual locations on airport property)? ______________

2. How many companies/airlines lease cargo space (for storage, sorting, etc.) at your airport? __________________________________________________________

3. What is the total size (e.g., in square feet, acres, etc.) of your cargo facilities? _________________________________________________________________

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4. What is the total size (e.g., in square feet, acres, etc.) of each individual facility?

Facility Number Size 1 2 3 4 5 6

5. How many aircraft parking positions are there at each cargo facility? Please list the number of positions for each facility.

Facility Number Number of Aircraft Parking Positions 1 2 3 4 5 6

6. Is sorting conducted: Centrally (for all carriers)? Individually by each carrier?

a. If sorting is central, what time of day does sorting usually occur? Check all that apply.

Morning Evening Midday Late Night

7. How many airport/airline employees work in secure air cargo areas?

____________________________________________________________

8. What percentage of the air cargo flowing through your airport is international

cargo? 0-10% 31-40% 61-70% 91-100% 11-20% 41-50% 71-80% 21-30% 51-60% 81-90%

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9. What percentage of cargo flowing through your airport comes through as belly freight on passenger planes?

0-10% 31-40% 61-70% 91-100% 11-20% 41-50% 71-80% 21-30% 51-60% 81-90%

10. How is belly cargo from passenger planes transported from the plane to the cargo

facility and vice versa? ____________________________________________ _______________________________________________________________

11. What are the most common types of cargo for: a. Passenger carriers? _________________________________________

_________________________________________________________ b. All-cargo carriers? _________________________________________

_________________________________________________________

12. What are the latest quarterly volumes of cargo flow by weight for your airport (for the past year, or the last year on record)?

Year Quarter 1

Total Weight Quarter 2

Total Weight Quarter 3

Total Weight Quarter 4

Total Weight

PART 2: CARGO SCREENING, SCANNING, AND SECURITY

13. Of all cargo flowing through your airport, what percentage of it is subject to any sort of security screening, scanning, or inspection process? ________________

14. What screening technologies are currently available and/or used for cargo?

Check all that apply. Pulsed fast neutron analysis Canines Thermal neutron activation Trace detection Bulk explosives protection systems Vapor detection Radiation detection Gamma ray Closed circuit TV X-ray Decompression chambers Other (please list) ________________________________________

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15. What type(s) of screening for airport/airline workers is currently used to allow them to enter secure airport areas? Check all that apply.

Badges Background checks (no. of years checked?) _____________________ Smart cards/swipe cards Biometrics (fingerprint/face recognition/iris scan) ID badges with employee picture Other (please list) _________________________________________ _________________________________________ _________________________________________ 16. Are visitors allowed in the cargo facilities? Yes No

a. IF YES, are they subject to any type of screening? Please explain. ___________________________________________________________ ___________________________________________________________ ___________________________________________________________

17. What percentage of cargo coming through the airport is from known shippers? 0-10% 31-40% 61-70% 91-100% 11-20% 41-50% 71-80% 21-30% 51-60% 81-90%

18. Are trucks carrying cargo to or from airport property allowed to enter secured areas of the airport? Yes No

IF YES, go to Question 19. IF NO, skip Question 19 and go to Question 20.

19. Truck clearance and security: a. Must the truck driver obtain clearance for himself as the correct driver?

Yes No Please explain: ____________________________________________ _________________________________________________________ _________________________________________________________

b. How are the trucks themselves cleared? Manually Computer/electronic clearance Other (please list/explain) ________________________________ ________________________________ ________________________________

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c. Are trucks inspected for firearms/stolen goods, etc.? Always Rarely Frequently Never Sometimes

20. Does international cargo flow through your airport? Yes No IF YES, go to Question 21. IF NO, skip Question 21 and go to Question 22.

21. For international cargo: a. On average, how long does it take for cargo to clear customs? _______

_________________________________________________________

b. In general, for cargo that is selected for screening, is it subject to more stringent screening than domestic cargo? Yes No

22. Are the dumpsters in secure airport areas subject to any type of surveillance? Yes No a. IF YES, what type? (CCTV, guard patrol, etc.) ____________________

___________________________________________________________

23. Do you plan to expand your screening technologies/procedures or make any

changes to your facilities in the near future that pertain to air cargo security and safety? If yes, please describe. _____________________________________ ________________________________________________________________ ________________________________________________________________ ________________________________________________________________ ________________________________________________________________ ________________________________________________________________ ________________________________________________________________ ________________________________________________________________ ________________________________________________________________ ________________________________________________________________ ________________________________________________________________ ________________________________________________________________ ________________________________________________________________ ________________________________________________________________ ________________________________________________________________ ________________________________________________________________ ________________________________________________________________ ________________________________________________________________

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24. Would you be interested in allowing a case study to be conducted (for university research purposes) on unit operations of cargo flow through your airport?

Yes No If yes, the researchers will contact you for further information.

For any questions, please contact Carla Rountree by phone (334) 663-5885 or by email (cdr8z@virginia.edu)

Thank you for your time. Please return:

By Mail: fold and seal survey and send postage-paid

By Fax: (434) 982-2951

By Email: attach the survey to your email and send to cdr8z@virginia.edu

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A.2: Survey Cover Letter Center for Transportation Studies University of Virginia 351 McCormick Rd. P.O. Box 400742 Charlottesville, VA 22904-4742 July 27, 2003 Dear Sir or Madam: The University of Virginia Center for Transportation Studies is conducting a study concerning air cargo security risks and countermeasures as a part of an ongoing research project. An important part of this study is the enclosed survey, “Air Cargo Operations and Security Survey,” in which we are asking selected airports to participate and provide information pertinent to the study. All information provided will be strictly confidential. Information about individual airports will not be included in any of the results of the survey or the study itself. The Center for Transportation Studies will also provide a summary of responses to any interested parties. The survey may be completed in 10 to 15 minutes. The survey may be completed using the enclosed hard copy and returned either by fax at 434-982-2951, or by mail (the enclosed copy may be folded and sealed for ease of return, and postage is paid). An electronic copy of the survey will be emailed to you as well. This version may be returned as a hard copy via the fax number or mailing address above, or by email to Carla Rountree at cdr8z@virginia.edu. Please return the survey by your preferred method by September 5, 2003. Your participation in this study is greatly appreciated. Sincerely, Carla Rountree Center for Transportation Studies Department of Civil Engineering University of Virginia

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A.3: Survey Follow-up Email Dear Survey Recipient, In August the Center for Transportation Studies at the University of Virginia sent you a survey entitled “Air Cargo Operations and Security Survey.” This survey is a very important part of an ongoing study being conducted by the Center for Transportation Studies, and your response is needed. We are extending our return deadline to October 8, 2003 in hopes that you will reconsider completing and returning the survey.

An electronic copy of the survey has been attached and may be returned either by fax (434-982-2951) or by email (send to Carla Rountree at cdr8z@virginia.edu). There is also a web-based version of the survey that may be found at www.zoomerang.com/survey.zgi?AQYN9D93L3J855DA7VCWQL5Q for completion online. You may also return the hard copy that was sent to you in August either by fax or by mail (postage is paid, the survey may be folded and dropped in the mail). If you do not wish to participate in this study, please send an email to cdr8z@virginia.edu, and you will not be contacted any further concerning this survey.

Your participation in this survey is greatly appreciated. Sincerely, Carla Rountree Center for Transportation Studies Department of Civil Engineering University of Virginia

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A.4: Graphical Results

Question 1: How many companies/airlines SORT cargo at your airport (either at a central sorting facility or at individual locations on airport property)?

(Total) Response % Cumulative

% 0 22.2 22.2 1 11.1 33.3 2 11.1 44.4 4 5.6 50.0 5 11.1 61.1 8 5.6 66.7 9 11.1 77.8

11 5.6 83.3 15 5.6 88.9 20 5.6 94.4 25 5.6 100.0

n = 8 mean = 6.88 median = 5 (Sm. Airports)

Response % Cumulative %

0 40.0 40.0 1 20.0 60.0 2 20.0 80.0 4 10.0 90.0 9 10.0 100.0

n = 10 mean = 1.9 median = 1

(Lg. Airports) Response % Cumulative

% 5 25.0 25.0 8 12.5 37.5 9 12.5 50.0

11 12.5 62.5 15 12.5 75.0 20 12.5 87.5 25 12.5 100.0

n = 8 mean = 12.25 median = 10

Question 1: All Airports

0

10

20

30

40

50

60

70

0-5 6-10 11-15 16-20 21-25

Number Companies/Airlines Sorting Cargo at Airport

Perc

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es

Question 1: Small Airports vs. Large Airports

0

20

40

60

80

100

0-5 6-10 11-15 16-20 21-25

Number Companies/Airlines Sorting Cargo at Airport

Perc

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Small Airports Large Airports

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Question 2:How many companies/airlines LEASE cargo space (for storage, sorting, etc.) at your airport?

(Total) Responses % Cumulative

% 0 5.6 5.6 1 11.1 16.7 2 16.7 33.3 4 11.1 44.4 5 5.6 50.0 6 5.6 55.6 8 5.6 61.1 9 11.1 72.2

10 5.6 77.8 13 5.6 83.3 15 5.6 88.9 20 5.6 94.4 25 5.6 100.0

n = 18 mean = 7.56 median = 5.5 (Sm. Airports)

Responses % Cumulative %

0 10.0 10.0 1 20.0 30.0 2 30.0 60.0 4 20.0 80.0 6 10.0 90.0 9 10.0 100.0

n = 10 mean = 3.1 median = 2

(Lg. Airports) Response % Cumulative

% 5 12.5 12.5 8 12.5 25.0 9 12.5 37.5

10 12.5 50.0 13 12.5 62.5 15 12.5 75.0 20 12.5 87.5 25 12.5 100.0

n = 8 mean = 13.1 median = 11.5

Question 2: All Airports

0

10

20

30

40

50

60

0-5 6-10 11-15 16-20 21-25

Number Companies/Airlines Leasing Cargo Space at Airport

Perc

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es

Question 2: Small Airports vs. Large Airports

0102030405060708090

0-5 6-10 11-15 16-20 21-25

Number Companies/Airlines Leasing Cargo Space at Airport

Perc

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Small Airports Large Airports

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Question 3:What is the total size (e.g., in square feet, acres, etc.) of your cargo facilities?

(Total) Response, sq. ft. % Cumulative

% 0-50,000 33.3 33.3

50,001-100,000 11.1 44.4 100,001-150,000 11.1 55.6 150,001-200,000 11.1 66.7 200,001-250,000 16.7 83.3

250,000 + 16.7 100.0 n = 18 mean = 547,676 median = 142,000

(Sm. Airports) Response, sq. ft. % Cumulative

% 0-50,000 60.0 60.0

50,001-100,000 20.0 80.0 100,001-150,000 10.0 90.0 150,001-200,000 10.0 100.0 200,001-250,000 0.0 100.0

250,000 + 0.0 1000 n = 10 mean = 59,542 median = 37,056

(Lg. Airports) Response, sq. ft. % Cumulative

% 0-50,000 0.0 0.0

50,001-100,000 0.0 0.0 100,001-150,000 12.5 12.5 150,001-200,000 12.5 25.0 200,001-250,000 37.5 62.5

250,000 + 37.5 100.0 n = 8 mean = 1,048,135 median = 223,750

Question 3: All Airports

0

5

10

15

20

25

30

35

0-50,000 50,001-100,000

100,001-150,000

150,001-200,000

200,001-250,000

250,001 +

Total Size (sq. ft.) of Cargo Facilities

Perc

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esQuestion 3: Small Airports vs. Large

Airports

0

10

20

30

40

50

60

70

0 -50,000

50,000 -100,000

100,001 -150,000

150,001 -200,000

200,001 -250,000

250,001 +

Total Size (sq. ft.) of Cargo Facilities

Perc

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Small Airports Large Airports

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Question 4: What is the total size (e.g., in square feet, acres, etc.) of each individual facility?

(Total) Responses, sq. ft. % Cumulative

% 0-20,000 35.6 35.6

20,001-40,000 27.1 62.7 40,001-60,000 10.2 72.9 60,001-80,000 10.2 83.1

80,001-100,000 8.5 91.5 100,001-120,000 5.1 96.6 120,001-140,000 0.0 96.6 140,001-160,000 1.7 98.3 160,001-180,000 0.0 98.3 180,001-200,000 0.0 98.3

200,000 + 1.7 100.0 n = 16 mean = 115,398 median = 27,274

(Sm. Airports) Response, sq. ft % Cumulative

% 0-20,000 61.9 61.9

20,001-40,000 23.8 85.7 40,001-60,000 4.8 90.5 60,001-80,000 0.0 90.5

80,001-100,000 4.8 95.2 100,001-120,000 0.0 95.2 120,001-140,000 0.0 95.2 140,001-160,000 4.8 100.0 160,001-180,000 0.0 100.0 180,001-200,000 0.0 100.0

200,000 + 0.0 100.0 n = 8 mean = 28,639 median = 17,990

(Lg. Airports) Response, sq. ft. % Cumulative

% 0-20,000 21.1 21.1

20,001-40,000 28.9 50.0 40,001-60,000 13.2 63.2 60,001-80,000 15.8 78.9

80,001-100,000 10.5 89.5 100,001-120,000 7.9 97.4 120,001-140,000 0.0 97.4 140,001-160,000 0.0 97.4 160,001-180,000 0.0 97.4 180,001-200,000 0.0 97.4

200,000 + 2.6 100.0 n = 38 mean = 163,344 median = 45,000

Question 4: All Airports

05

10152025303540

0-20

20-40

40-60

60-80

80-10

0

100-1

20

120-1

40

140-1

60

160-1

80

180-2

0020

0 +

Size (1000's of sq. ft.) of Individual Cargo Facilities

Perc

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Question 4: Small Airports vs. Large Airports

010203040506070

0-20

20-40

40-60

60-80

80-10

0

100-1

20

120-1

40

140-1

60

160-1

80

180-2

0020

0 +

Size (1000's of sq ft) of Individual Cargo Facilities

Perc

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Small Airports Large Airports

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Question 5:How many aircraft parking positions are there at each cargo facility?

(Total) Response % Cumulative

% 0-2 48.5 48.5 3-4 27.3 75.8 5-6 12.1 87.9 7-8 3.0 90.9

9-10 3.0 93.9 11 + 6.1 100.0

n = 15 mean = 9 median = 3

(Sm. Airports) Response % Cumulative

% 0-2 78.6 78.6 3-4 14.3 92.9 5-6 7.1 100.0 7-8 0.0 100.0

9-10 0.0 100.0 11 + 0.0 100.0

n = 9 mean = 1.4 median = 1

(Lg. Airports) Response % Cumulative

% 0-2 31.3 31.3 3-4 25.0 56.3 5-6 25.0 81.2 7-8 6.3 87.5

9-10 6.3 93.8 11 + 6.3 100.0

n = 6 mean = 6.2 median = 3

Question 5: All Airports

0

10

20

30

40

50

60

0-2 3-4 5-6 7-8 9-10 11 +

No. Aircraft Parking Positions at Individual Cargo Facilities

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Large Airports

0102030405060708090

0-2 3-4 5-6 7-8 9-10 11 +

No. Aircraft Parking Positions at Individual Cargo Facilities

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Small Airports Large Airports

118

Question 6:Is sorting conducted centrally (for all carriers) or individually by each carrier?

(Total) Response % Cumulative

% Individually 100.0 100.0 Centrally 0.0 100.0

n = 15 *Note: Airports are not separated by size for this question because all airports reported individual sorting.

Question 7: How many airport/airline employees work in secure cargo areas?

(Total) Response % Cumulative

% 0-50 41.7 41.7

51-100 25.0 66.7 101-150 16.7 83.3 151-200 0.0 83.3

200 + 16.7 100.0 n = 13 mean = 284 median = 59

(Sm. Airports) Response % Cumulative

% 0-50 55.6 55.6

51-100 22.2 77.8 101-150 11.1 88.9 151-200 11.1 100.0

200 + 0.0 100.0 n = 9 mean = 133.4 median = 50

(Lg. Airports) Response % Cumulative

% 0-50 0.0 0.0

51-100 25.0 25.0 101-150 50.0 75.0 151-200 0.0 75..

200 + 25.0 100.0 n = 4 mean = 582.5 median = 137.5

Question 6: All Airports

0

20

40

60

80

100

Individually Centrally

Method of Cargo Sorting

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Question 7: All Airports

0

10

20

30

40

50

0-50 51-100 101-150 151-200 200 +

No. Airport/Airline Employees Working in Secure Cargo Areas

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Question 7: Small Airports vs. Large Airports

0102030405060

0-50 51-100 101-150 151-200 200 +

No. Airport/Airline Employees Working in Securre Cargo Areas

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Small Airports Large Airports

119

Question 8: What percentage of the air cargo flowing through your airport is international cargo?

(Total) Response, % % Cumulative

% 0-10 60.0 60.0 11-20 0.0 60.0 21-30 20.0 80.0 31-40 13.3 93.3 41-50 0.0 93.3 51-60 0.0 93.3 61-70 0.0 93.3 71-80 0.0 93.3 81-90 0.0 93.3 91-100 6.7 100.0

n = 16 mean = 19 median = 5

(Sm. Airports) Response, % % Cumulative

% 0-10 66.7 66.7 11-20 0.0 66.7 21-30 22.2 88.9 31-40 11.1 100.0 41-50 0.0 100.0 51-60 0.0 100.0 61-70 0.0 100.0 71-80 0.0 100.0 81-90 0.0 100.0 91-100 0.0 100.0

n = 9 mean = 10.6 median = 5

(Lg. Airports) Response, % % Cumulative

% 0-10 57.1 57.1 11-20 0.0 57.1 21-30 14.3 71.4 31-40 14.3 85.7 41-50 0.0 85.7 51-60 0.0 85.7 61-70 0.0 85.7 71-80 0.0 85.7 81-90 0.0 85.7 91-100 14.3 100.0

n = 7 mean = 24.3 median = 5

Question 8: All Airports

0

10

20

30

40

50

60

70

0-10

11-20

21-30

31-40

41-50

51-60

61-70

71-80

81-90

91-10

0

% of Cargo as International Cargo

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Large Airports

010203040506070

0-10

11-20

21-30

31-40

41-50

51-60

61-70

71-80

81-90

91-10

0

% of Cargo at International Cargo

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Small Airports Large Airports

120

Question 9: What percentage of cargo flowing through your airport comes through as belly freight on passenger planes?

(Total) Response, % % Cumulative

% 0-10 40.0 40.0 11-20 20.0 60.0 21-30 6.7 66.7 31-40 13.3 80.0 41-50 0.0 80.0 51-60 0.0 80.0 61-70 0.0 80.0 71-80 0.0 80.0 81-90 6.7 86.7 91-100 13.3 100.0

n = 15 mean = 30 median = 15

(Sm. Airports) Response, % % Cumulative

% 0-10 44.4 44.4 11-20 22.2 66.6 21-30 11.1 77.7 31-40 0.0 77.7 41-50 0.0 77.7 51-60 0.0 77.7 61-70 0.0 77.7 71-80 0.0 77.7 81-90 0.0 77.7 91-100 22.2 100.0

n = 9 mean = 29.4 median = 15

(Lg. Airports) Response, % % Cumulative

% 0-10 33.3 33.3 11-20 16.7 50.0 21-30 0.0 50.0 31-40 33.3 83.3 41-50 0.0 83.3 51-60 0.0 83.3 61-70 0.0 83.3 71-80 0.0 83.3 81-90 6.7 100.0 91-100 0.0 100.0

n = 6 mean = 30 median = 25

Question 9: All Airports

05

1015202530354045

0-10

11-20

21-30

31-40

41-50

51-60

61-70

71-80

81-90

91-10

0

% Cargo as Belly Freight

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Question 9: Small Airports vs. Large Airports

0

10

20

30

40

50

0-10

11-20

21-30

31-40

41-50

51-60

61-70

71-80

81-90

91-10

0

% Cargo as Belly Freight

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Small Airports Large Airports

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Question 10: How is belly cargo from passenger planes transported from the plane to the cargo facility and vice versa?

(Total) Response % Cumulative

% on trucks 12.5 12.5

tug &/or cart 68.8 81.3 belt loaders 6.3 87.5 pod loaders 6.3 93.8

ramp 6.3 100.0 n = 15

(Sm. Airports) Response % Cumulative

% on trucks 20.0 20.0

tug &/or cart 80.0 100.0 belt loaders 0.0 100.0 pod loaders 0.0 100.0

ramp 0.0 100.0 n = 5

(Lg. Airports) Response % Cumulative

% on trucks 10.0 10.0

tug &/or cart 60.0 70.0 belt loaders 10.0 80.0 pod loaders 10.0 90.0

ramp 10.0 100.0 n = 10

Question 10: All Airports

01020304050607080

on trucks tug &/orcart

beltloaders

podloaders

ramp

Belly Cargo Transport Method from Plane to Facility

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Question 10: Small Airports vs. Large Airports

0

20

40

60

80

100

ontrucks

tug &/orcart

beltloaders

podloaders

ramp

Belly Cargo Transport Method from Plane to Facility

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Question 11a: What are the most common types of cargo for passenger carriers?

(Total) Response % Cumulative

% mail 50.0 N/A

perishable items 41.7 N/A human remains 8.3 N/A exp. packages 8.3 N/A

electronics 8.3 N/A live animals 8.3 N/A

medicine 8.3 N/A gaming equip. 8.3 N/A

caskets 8.3 N/A n = 12

(Sm. Airports) Response % Cumulative

% mail 50.0 N/A

perishable items 33.3 N/A human remains 16.7 N/A exp. packages 0.0 N/A

electronics 0.0 N/A live animals 0.0 N/A

medicine 0.0 N/A gaming equip. 0.0 N/A

caskets 16.7 N/A n = 6

(Lg. Airports) Response % Cumulative

% mail 50.0 N/A

perishable items 50.0 N/A human remains 0.0 N/A exp. packages 16.7 N/A

electronics 16.7 N/A live animals 16.7 N/A

medicine 16.7 N/A gaming equip. 16.7 N/A

caskets 0.0 N/A n = 6

Question 11a: All Airports

0102030405060

mail

peris

hable

items

human r

emains

expre

ss pa

ckag

es

electr

onics

live an

imals

medici

ne

gaming

equipm

ent

cask

ets

Types of Cargo Transported by Passenger Carriers

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Question 11a: Small Airports vs. Large Airports

0102030405060

mail

peris

hable

items

human r

emains

expre

ss pa

ckag

es

electr

onics

live an

imals

medici

ne

gaming

equipm

ent

cask

ets

Types of Cargo Transported by Passenger Carriers

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Small Airports Large Airports

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Question 11b: What are the most common types of cargo for all-cargo carriers?

(Total) Responses % Cumulative

% manufact. items 9.1 N/A

retail merch. 18.2 N/A mail 18.2 N/A

exp. packages 63.6 N/A machine parts 9.1 N/A

int’l freight 9.1 N/A perishable items 27.3 N/A automobile parts 18.2 N/A

electronics 36.4 N/A pharmaceuticals 9.1 N/A

furniture 9.1 N/A chemicals 9.1 N/A

n = 11

(Sm. Airports) Responses % Cumulative

% manufact. items 20.0 N/A

retail merch. 20.0 N/A mail 0.0 N/A

exp. packages 80.0 N/A machine parts 0.0 N/A

int’l freight 20.0 N/A perishable items 20.0 N/A automobile parts 0.0 N/A

electronics 20.0 N/A pharmaceuticals 0.0 N/A

furniture 0.0 N/A chemicals 0.0 N/A

n = 5

(Lg. Airports) Responses % Cumulative

% manufact. items 0.0 N/A

retail merch. 16.7 N/A mail 33.3 N/A

exp. packages 50.0 N/A machine parts 16.7 N/A

int’l freight 0.0 N/A perishable items 33.3 N/A automobile parts 33.3 N/A

electronics 50.0 N/A pharmaceuticals 16.7 N/A

furniture 16.7 N/A chemicals 16.7 N/A

n = 6

Question 11b: All Airports

010203040506070

manufac

t. item

s

retail

merc

h.mail

exp.

pack

ages

machin

e part

s

int'l frei

ght

peris

hable

items

autom

obile

parts

electr

onics

pharm

aceu

ticals

furnit

ure

chem

icals

Types of Cargo Transported by All-Cargo Carriers

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Question 11b: Small Airports vs. Large Airports

0102030405060708090

manufac

t. item

s

retail

merc

h.mail

exp.

pack

ages

machin

e part

s

internati

onal fr

eight

peris

hable

items

autom

obile

parts

electr

onics

pharm

aceu

ticals

furnit

ure

chem

icals

Types of Cargo Transported by All-Cargo Carriers

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Question 12: What are the latest quarterly volumes of cargo flow by weight for your airport (for the past year, or the last year on record)?

(Total) Response, tons

Quarter 1 % Cumulative

%

0-3,000 38.5 38.5 3,001-6,000 7.7 46.2 6,001-9,000 0.0 46.2 9,001-12,000 0.0 46.2

12,001-15,000 7.7 53.8 15,001-18,000 7.7 61.5 18,001-21,000 15.4 76.9 21,001-24,000 7.7 76.9 24,001-27,000 0.0 84.6

27,000 + 15.4 100.0 n = 13 mean = 44,056 median = 12,882

(Sm. Airports) Response, tons

Quarter 1 % Cumulative

%

0-3,000 83.3 83.3 3,001-6,000 16.7 100.0 6,001-9,000 0.0 100.0 9,001-12,000 0.0 100.0

12,001-15,000 0.0 100.0 15,001-18,000 0.0 100.0 18,001-21,000 0.0 100.0 21,001-24,000 0.0 100.0 24,001-27,000 0.0 100.0

27,000 + 0.0 100.0 n = 6 mean = 1,271 median = 886

(Lg. Airports) Response, tons

Quarter 1 % Cumulative

%

0-3,000 0.0 0.0 3,001-6,000 0.0 0.0 6,001-9,000 0.0 0.0 9,001-12,000 0.0 0.0

12,001-15,000 14.3 14.3 15,001-18,000 14.3 28.6 18,001-21,000 28.6 57.1 21,001-24,000 0.0 57.1 24,001-27,000 14.3 71.4

27,000 + 28.6 100.0 n = 7 mean = 80,730 median = 20,939

Question 12: All Airports (Quarter 1)

05

1015202530354045

0-3 3-6 6-9 9-12

12-15

15-18

18-21

21-24

24-27

27+

Quarter 1 Volumes of Cargo (1000's of tons)

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Question 12: Small Airports vs. Large Airports (Quarter 1)

0102030405060708090

0-3 3-6 6-9 9-12

12-15

15-18

18-21

21-24

24-27

27+

Quarter 1 Volumes of Cargo (1000's of tons)

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(Total) Response, tons

Quarter 2 %

Cumulative %

0-3,000 38.5 38.5 3,001-6,000 7.7 46.2 6,001-9,000 0.0 46.2 9,001-12,000 0.0 46.2

12,001-15,000 7.7 53.8 15,001-18,000 7.7 61.5 18,001-21,000 0.0 61.5 21,001-24,000 15.4 76.9 24,001-27,000 7.7 84.6

27,000 + 15.4 100.0 n = 13 mean = 44,531 median = 12,845

(Sm. Airports) Response, tons

Quarter 2 %

Cumulative %

0-3,000 83.3 83.3 3,001-6,000 16.7 100.0 6,001-9,000 0.0 100.0 9,001-12,000 0.0 100.0

12,001-15,000 0.0 100.0 15,001-18,000 0.0 100.0 18,001-21,000 0.0 100.0 21,001-24,000 0.0 100.0 24,001-27,000 0.0 100.0

27,000 + 0.0 100.0 n = 6 mean = 1,096 median = 374

(Lg. Airports) Response, tons

Quarter 2 % Cumulative

%

0-3,000 0.0 0.0 3,001-6,000 0.0 0.0 6,001-9,000 0.0 0.0 9,001-12,000 0.0 0.0

12,001-15,000 14.3 14.3 15,001-18,000 14.3 28.6 18,001-21,000 0.0 28.6 21,001-24,000 28.6 57.1 24,001-27,000 14.3 71.4

27,000 + 28.6 100.0 n = 7 mean = 81,616 median = 23,295

Question 12: All Airports (Quarter 2)

05

1015202530354045

0-3 3-6 6-9 9-12

12-15

15-18

18-21

21-24

24-27

27 +

Quarter 2 Volumes of Cargo (1000's of tons)

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Large Airports (Quarter 2)

0102030405060708090

0-3 3-6 6-9 9-12

12-15

15-18

18-21

21-24

24-27

27+

Quarter 2 Volumes of Cargo (tons)

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(Total) Response, tons

Quarter 3 %

Cumulative %

0-3,000 41.7 41.7 3,001-6,000 0.0 41.7 6,001-9,000 0.0 41.7 9,001-12,000 0.0 41.7

12,001-15,000 0.0 41.7 15,001-18,000 8.3 50.0 18,001-21,000 16.7 66.7 21,001-24,000 8.3 75.0 24,001-27,000 8.3 83.3

27,000 + 16.7 100.0 n = 12 mean = 48,336 median = 17,886

(Sm. Airports) Response, tons

Quarter 3 %

Cumulative %

0-3,000 100.0 100.0 3,001-6,000 0.0 100.0 6,001-9,000 0.0 100.0 9,001-12,000 0.0 100.0

12,001-15,000 0.0 100.0 15,001-18,000 0.0 100.0 18,001-21,000 0.0 100.0 21,001-24,000 0.0 100.0 24,001-27,000 0.0 100.0

27,000 + 0.0 100.0 n = 5 mean = 421 median = 174

(Lg. Airports) Response, tons

Quarter 3 % Cumulative

%

0-3,000 0.0 0.0 3,001-6,000 0.0 0.0 6,001-9,000 0.0 0.0 9,001-12,000 0.0 0.0

12,001-15,000 0.0 0.0 15,001-18,000 14.3 14.3 18,001-21,000 28.6 42.9 21,001-24,000 14.3 57.1 24,001-27,000 14.3 71.4

27,000 + 28.6 100.0 n = 7 mean = 82,417 median = 23,638

Question 12: All Airports (Quarter 3)

05

1015202530354045

0-3 3-6 6-9 9-12 12-15

15-18

18-21

21-24

24-27

27 +

Quarter 3 Volumes of Cargo (1000's of tons)

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Large Airports (Quarter 3)

0

20

40

60

80

100

0-3 3-6 6-9 9-12

12-15

15-18

18-21

21-24

24-27

27+

Quarter 3 Volumes of Cargo (1000's of tons)

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(Total) Response, tons

Quarter 4 %

Cumulative %

0-3,000 41.7 41.7 3,001-6,000 0.0 41.7 6,001-9,000 0.0 41.7 9,001-12,000 0.0 41.7

12,001-15,000 0.0 41.7 15,001-18,000 8.3 50.0 18,001-21,000 0.0 50.0 21,001-24,000 25.0 75.0 24,001-27,000 8.3 83.3

27,000 + 16.7 100.0 n = 12 mean = 48,279 median = 18,388

(Sm. Airports) Response, tons

Quarter 4 %

Cumulative %

0-3,000 100.0 100.0 3,001-6,000 0.0 100.0 6,001-9,000 0.0 100.0 9,001-12,000 0.0 100.0

12,001-15,000 0.0 100.0 15,001-18,000 0.0 100.0 18,001-21,000 0.0 100.0 21,001-24,000 0.0 100.0 24,001-27,000 0.0 100.0

27,000 + 0.0 100.0 n = 5 mean = 421 median = 179

(Lg. Airports) Response, tons

Quarter 4 % Cumulative

%

0-3,000 0.0 0.0 3,001-6,000 0.0 0.0 6,001-9,000 0.0 0.0 9,001-12,000 0.0 0.0

12,001-15,000 0.0 0.0 15,001-18,000 14.3 14.3 18,001-21,000 0.0 14.3 21,001-24,000 42.9 57.1 24,001-27,000 14.3 71.4

27,000 + 28.6 100.0 n = 7 mean = 82,302 median = 21,634

Question 12: All Airports (Quarter 4)

05

1015202530354045

0-3 3-6 6-9 9-12

12-15

15-18

18-21

21-24

24-27

27 +

Quarter 4 Volumes of Cargo (1000's of tons)

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esQuestion 12: Small Airports vs.

Large Airports (Quarter 4)

0

20

40

60

80

100

0-3 3-6 6-9 9-12

12-15

15-18

18-21

21-24

24-27

27+

Quarter 4 Volumes of Cargo (1000's of tons)

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Question 13: Of all cargo flowing through your airport, what percentage of it is subject to any sort of security screening, scanning, or inspection process?

(Total) Response, % % Cumulative

% 0-10 70.0 70.0 11-20 0.0 70.0 21-30 0.0 70.0 31-40 0.0 70.0 41-50 0.0 70.0 51-60 0.0 70.0 61-70 0.0 70.0 71-80 0.0 70.0 81-90 0.0 70.0 91-100 30.0 100.0

n = 10 mean = 35 median = 10

(Sm. Airports) Response, % % Cumulative

% 0-10 70.0 70.0 11-20 0.0 70.0 21-30 0.0 70.0 31-40 0.0 70.0 41-50 0.0 70.0 51-60 0.0 70.0 61-70 0.0 70.0 71-80 0.0 70.0 81-90 0.0 70.0 91-100 30.0 100.0

n = 7 mean = 32 median = 10

Question 13: All Airports

01020304050607080

0-10

11-20

21-30

31-40

41-50

51-60

61-70

71-80

81-90

91-10

0

% Cargo Subject to Screening

Perc

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Question 13: Small Airports vs. Large Airports

01020304050607080

0 - 10

11 - 2

0

21 - 3

0

31 - 4

0

41 - 5

0

51 - 6

0

61 - 7

0

71 - 8

0

81 - 9

0

91 - 1

00

% Cargo Subject to Screening

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Small Airports Large Airports

129

Question 14: What screening technologies are currently available and/or used for cargo?

(Total) Response % Cumulative

% CCTV 36.4 N/A

Trace Detection 27.3 N/A X-Ray 54.5 N/A

Canines 45.5 N/A Phys. Inspection 9.1 N/A n = 11

(Sm. Airports) Response % Cumulative

% CCTV 66.7 N/A

Trace Detection 50.0 N/A X-Ray 83.3 N/A

Canines 50.0 N/A Phys. Inspection 16.7 N/A n = 6

(Lg. Airports) Response % Cumulative

% CCTV 60.0 N/A

Trace Detection 0.0 N/A X-Ray 80.0 N/A

Canines 80.0 N/A Phys. Inspection 0.0 N/A n = 5

Question 14: All Airports

0

10

20

30

40

50

60

CCTV TraceDetection

X-Ray Canines Physicalinspection

Screening Methods used for Cargo

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esQuestion 14: Small Airports vs.

Large Airports

0102030405060708090

CCTV TraceDetection

X-Ray Canines Physicalinspection

Screening Methods used for Cargo

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130

Question 15: What type(s) of screening for airport/airline workers is currently used to allow them to enter secure airport areas?

(Total) Response % Cumulative

% Badges 55.6 N/A

Background Checks 66.7 N/A

Smart/Swipe Cards 50.0 N/A

Biometrics 5.6 N/A ID Badges 66.7 N/A

Fingerprinting 5.6 N/A Pin Number 5.6 N/A

n = 18

(Sm. Airports) Response % Cumulative

% Badges 80.0 N/A

Background Checks 100.0 N/A

Smart/Swipe Cards 80.0 N/A

Biometrics 20.0 N/A ID Badges 100.0 N/A

Fingerprinting 10.0 N/A Pin Number 0.0 N/A

n = 10

(Lg. Airports) Response % Cumulative

% Badges 75.0 N/A

Background Checks 87.5 N/A

Smart/Swipe Cards 75.0 N/A

Biometrics 12.5 N/A ID Badges 87.5 N/A

Fingerprinting 12.5 N/A Pin Number 12.5 N/A

n = 8

Question 15: Small Airports vs. Large Airports

0102030405060708090

100

Badge

s

Backg

round

Che

cks

Smart/S

wipe C

ards

Biometr

ics

ID Badg

es

Fingerpr

inting

Pin Num

ber

Screening Methods Used for Cargo Employees

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Small Airports Large Airports

Question 15: All Airports

01020304050607080

Badge

s

Backg

round

Che

cks

Smart/S

wipe C

ards

Biometr

ics

ID Badg

es

Fingerpr

inting

Pin Num

ber

Screening Methods Used for Cargo Employees

Perc

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Question 16: Are visitors allowed in the cargo facilities?

(Total) Response % Cumulative

% Yes 62.5 62.5 No 37.5 100.0

n = 16

(Sm. Airports) Response % Cumulative

% Yes 55.6 55.6 No 44.4 100.0

n = 9

(Lg. Airports) Response % Cumulative

% Yes 71.4 71.4 No 28.6 100.0

n = 7

Question 16: All Airports

0

10

20

30

40

50

60

70

Yes No

Are Visitors Allowed in Cargo Facilities?

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Large Airports

01020304050607080

Yes No

Are Visitors Allowed in Cargo Facilities?

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Question 16a: If YES, are they subject to any type of screening?

(Total) Response % Cumulative

% Yes 80.0 80.0 No 20.0 100.0

n = 10 *Type of screening: Authorized Escort (100%)

(Sm. Airports) Response % Cumulative

% Yes 80.0 80.0 No 20.0 100.0

n = 5

(Lg. Airports) Response % Cumulative

% Yes 80.0 80.0 No 20.0 100.0

n = 5

Question 16a: Small Airports vs. Large Airports

0102030405060708090

Yes No

Are Visitors Subject to Screening?

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Question 16a: All Airports

01020

30405060

708090

Yes No

Are Visitors Subject to Screening?

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Question 17: What percentage of cargo coming through the airport is from known shippers?

(Total) Response, % % Cumulative

% 0-10 0.0 0.0 11-20 0.0 0.0 21-30 0.0 0.0 31-40 0.0 0.0 41-50 0.0 0.0 51-60 0.0 0.0 61-70 0.0 0.0 71-80 9.1 9.1 81-90 18.2 27.3 91-100 72.7 100.0

n = 11 mean = 91 median = 95

(Sm. Airports) Response, % % Cumulative

% 0-10 0.0 0.0 11-20 0.0 0.0 21-30 0.0 0.0 31-40 0.0 0.0 41-50 0.0 0.0 51-60 0.0 0.0 61-70 0.0 0.0 71-80 14.3 14.3 81-90 28.6 42.9 91-100 57.1 100.0

n = 8 mean = 89.3 median = 95

(Lg. Airports) Response, % % Cumulative

% 0-10 0.0 0.0 11-20 0.0 0.0 21-30 0.0 0.0 31-40 0.0 0.0 41-50 0.0 0.0 51-60 0.0 0.0 61-70 0.0 0.0 71-80 0.0 0.0 81-90 0.0 0.0 91-100 100.0 100.0

n = 3 mean = 95 median = 95

Question 17: Small Airports vs. Large Airports

0

20

40

60

80

100

0-10

11-20

21-30

31-40

41-50

51-60

61-70

71-80

81-90

91-10

0

% Cargo from Known Shippers

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Question 17: All Airports

0

10

20

30

40

50

60

70

80

0-10

11-20

21-30

31-40

41-50

51-60

61-70

71-80

81-90

91-10

0

% Cargo from Known Shippers

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Question 18: Are trucks carrying cargo to or from airport property allowed to enter secured areas of the airport?

(Total) Response % Cumulative

% Yes 55.6 55.6 No 44.4 100.0

n = 18

(Sm. Airports) Response % Cumulative

% Yes 60.0 60.0 No 40.0 100.0

n = 10

(Lg. Airports) Response % Cumulative

% Yes 50.0 50.0 No 50.0 100.0

n = 8

Question 18: All Airports

0

10

20

30

40

50

60

Yes No

Are Trucks Allowed to Enter Secure Airport Areas?

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Question 18: Small Airports vs. Large Airports

010203040506070

Yes No

Are Trucks Allowed to Enter Secure Airport Area?

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Question 19a: Must the truck driver obtain clearance for himself as the correct driver?

(Total) Response % Cumulative

% Yes 100.0 100.0 No 0.0 100.0

n = 9 Clearance Method

(Total) Response % Cumulative

% Airport ID 15.4 15.4

Biometric reader 7.7 23.1 Authorized

escort 23.1 46.2

Prearranged 7.7 53.8 Identity

verification 23.1 76.9

Pin number 7.7 84.6 Smart

card/badge 15.4 100.0

n = 10

(Sm. Airports) Response % Cumulative

% Airport ID 14.3 14.3

Biometric reader 14.3 28.6 Authorized

escort 14.3 42.9

Prearranged 0.0 42.9 Identity

verification 28.6 71.4

Pin number 14.3 85.7 Smart

card/badge 14.3 100.0

n = 6

Question 19a: All Airports (Clearance Methods)

0

5

10

15

20

25

airp

ort I

D

biom

etric

read

er

Auth

oriz

edes

cort

prea

rran

ged

clea

ranc

e

iden

tity

verif

icat

ion

pin

#

smar

tca

rd/b

adge

Clearance Methods for Truck Drivers

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Question 19a: All Airports

0102030405060708090

100

Yes No

Must Truck Driver Obtain Clearance?

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Question 19b: How are the trucks themselves cleared?

(Total) Response % Cumulative

% Manually 80.0 80.0

Comupter/Elec. 10.0 90.0 Other 10.0 100.0

n = 10

(Sm. Airports) Response % Cumulative

% Manually 66.7 66.7

Comupter/Elec. 16.7 83.3 Other 16.7 100.0

n = 6

(Lg. Airports) Response % Cumulative

% Manually 100.0 100.0

Comupter/Elec. 0.0 100.0 Other 0.0 100.0

n = 4

Question 19b: Small Airports vs. Large Airports

0102030405060708090

100

Manually Computer/Elec. Other

Clearance Methods forTrucks

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Question 19b: All Airports

0

10

20

30

40

50

60

70

80

90

Manually Computer/Elec. Other

Clearance Methods forTrucks

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Question 19c: Are trucks inspected for firearms/stolen goods, etc.?

(Total) Responses % Cumulative

% Always 25.0 25.0

Frequently 12.5 37.5 Sometimes 25.0 62.5

Rarely 12.5 75.0 Never 25.0 100.0

n = 8

(Sm. Airports) Responses % Cumulative

% Always 40.0 40.0

Frequently 20.0 60.0 Sometimes 0.0 60.0

Rarely 0.0 60.0 Never 40.0 100.0

n = 5

(Lg. Airports) Responses % Cumulative

% Always 0.0 0.0

Frequently 0.0 0.0 Sometimes 66.7 66.7

Rarely 33.3 100.0 Never 0.0 100.0

n = 3

Question 19c: Small Airports vs. Large Airports

010203040506070

Alway

s

Frequen

tly

Someti

mes

Rarely

Never

Frequency of Truck Inspections

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Question 19c: All Airports

0

5

10

15

20

25

30

Alway

s

Frequen

tly

Someti

mes

Rarely

Never

Frequency of Truck Inspections

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Question 20:Does international cargo flow through your airport?

(Total) Response % Cumulative

% Yes 61.1 61.1 No 38.9 100.0

n = 18

(Sm. Airports) Response % Cumulative

% Yes 40.0 40.0 No 60.0 100.0

n = 10

(Lg. Airports) Response % Cumulative

% Yes 87.5 87.5 No 12.5 100.0

n = 8

Question 20: All Airports

0

10

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30

40

50

60

70

Yes No

Does International Cargo Flow Through Your Airport?

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Large Airports

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20

40

60

80

100

Yes No

Does International Cargo Flow Through Your Airport?

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Question 21a: For international cargo: On average, how long does it take for cargo to clear customs?

(Total) Response % Cumulative

% 0-1 14.3 14.3 1-2 42.9 57.1 2-3 14.3 71.4 3-4 14.3 85.7 4 + 14.3 100.0

n = 7 mean = 9 median = 2

(Sm. Airports) Response % Cumulative

% 0-1 0.0 0.0 1-2 0.0 0.0 2-3 0.0 0.0 3-4 50.0 50.0 4 + 50.0 100.0

n = 2 mean = 26 median = 26

(Lg. Airports) Response % Cumulative

% 0-1 20.0 20.0 1-2 60.0 80.0 2-3 20.0 100.0 3-4 0.0 100.0 4 + 0.0 100.0

n = 5 mean = 2 median = 2

Question 21a: All Airports

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10

20

30

40

50

0-1 1-2 2-3 3-4 4 +

Time (hrs) for International Cargo to Clear Customs

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Question 21a: Small Airports vs. Large Airports

010203040506070

0-1 1-2 2-3 3-4 4 ormore

Time (hrs) for International Cargo to Clear Customs

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Question 21b: In general, for international cargo that is selected for screening, is it subject to more stringent screening than domestic cargo?

(Total) Response % Cumulative

% Yes 40.0 40.0 No 60.0 100.0

n = 5

(Sm. Airports) Response % Cumulative

% Yes 0.0 0.0 No 100.0 100.0

n = 2

(Lg. Airports) Response % Cumulative

% Yes 66.7 66.7 No 33.3 100.0

n = 3

Histogram Question 21b

0

10

20

30

40

50

60

70

Yes No

Is International Cargo Subject to More Screening than Domestic?

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Question 21b: Small Airports vs. Large Airports

0

20

40

60

80

100

Yes No

Is International Cargo Subject to More Screening than Domestic?

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Question 22: Are the dumpsters in secure airport areas subject to any type of surveillance?

(Total) Response % Cumulative

% Yes 73.3 73.3 No 26.7 100.0

n = 15

(Sm. Airports) Response % Cumulative

% Yes 66.7 66.7 No 33.3 100.0

n = 9

(Lg. Airports) Response % Cumulative

% Yes 83.3 83.3 No 16.7 100.0

n = 6

Question 22: All Airports

0

10

20

30

40

50

60

70

80

Yes No

Are Dumpsters Subject to Surveillance?

Perc

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Large Airports

0102030405060708090

Yes No

Are Dumpsters Subject to Surveillance?

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Question 22a: If YES, what type?

(Total) Response % Cumulative

% CCTV 53.3 53.3

Guard Patrol 46.7 100.0 n = 15

(Sm. Airports)

Response % Cumulative %

CCTV 62.5 62.5 Guard Patrol 37.5 100.0

n = 8

(Lg. Airports) Response % Cumulative

% CCTV 42.9 42.9

Guard Patrol 57.1 100.0 n = 7

Question 22: All Airports

0

10

20

30

40

50

60

CCTV Guard patrol

Type of Surveillance Used for Dumpsters

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Large Airports

0

10

20

30

40

50

60

70

CCTV Guard patrol

Type of Surveillance Used for Dumpsters

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