Air Qualt ontrn in Central Asia 'and- the Cauca-sus...variability and transient nature of pollution episodes, none of which could be captured from the sampling strategy currently in

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Air Qualt ontrnin Central Asia'and- the Cauca-sus

FILECOPRepo rt for'the Regional Study on:

Cleaner Transportation- Fuels for7Urban Air. Quality Inirveentin Ce ntral Asia and the Ca'ucasus

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Air Quality Monitoringin Central Asia and the Caucasus

Report for the Regional Study on:

Cleaner Transportation Fuels forUrban Air Quality Improvement in

Central Asia and the Caucasus

Joint UNDP/World Bank Energy Sector Management Assistance Programme (ESMAP)

Contents1 Introduction.1

1.2 Health Concerns of Air Pollution .................................... 1

1.3 Air Quality Monitoring .................................... 2

2 Data Collection and Analysis ................................... 5

2.1 Monitoring Locations .................................... 5

2.2 Automatic Air Pollution Monitoring .................................... 5

2.3 Passive Sampler Monitoring ................................... 10

2.4 Lead Monitoring ................................... 13

3 Comparison of Data ................................... 15

3.1 Azerbaijan ................................... 15

3.1 Uzbekistan ................................... 18

4 Review of Methodologies ................................... 23

4.1 Sampling Strategy ................................... 23

4.2 Nitrogen Dioxide ................................... 25

4.3 Sulphur Dioxide ................................... 25

4.4 Ozone ................................... 26

4.5 Carbon Monoxide ................................... 26

4.6 TSP (Dust) ................................... 27

4.7 Lead ................................... 28

4.8 Filter Efficiency Tests ................................... 28

4.9 Quality Assurance/Quality Control Measures ................................... 29

5 Review of Historical Data ................................... 31

6 Summary and Conclusions ................................... 33

iii

6.1 Monitoring Locations .............................................. 33

6.2 Monitoring Procedures and Strategy ...... 33

6.3 Sample Collection Systems .............................................. 33

6.4 Recommendations .............................................. 33

Appendix 1 Monitoring Locations .............................................. 35

Appendix 2 International Air Quality Guidelines and Standards .............................................. 41

Appendix 3 Nitrogen Dioxide Diffusion Tube Samplers ............................................... 47

iv

Acknowledgments

The present report was prepared as part of a broader regional study, Cleaner TransportationFuels for Urban Air Quality Improvement in Central Asia and the Caucasus, undertakenjointly by the Energy and Environment Units of the Europe and Central Asia Region. TheEnvironment Department, and the Oil, Gas and Petrochemicals Department of the World BankGroup with support from the joint UNDP/World Bank Sector Management AssistanceProgramme (ESMAP) and the Canadian International Development Agency (CIDA). Thefinancial assistance of the Government of the United Kingdom for this part of the study isgratefully acknowledged.

This report is based on the work carried out in 1999 by Steve Telling and Brian Stacey of AEATechnology in the United Kingdom with contributions from the following staff ofHydrometeorology in Azerbaijan and Uzbekistan: Rzakhan Mansimov. Abdul Hajiev, ZakiGasan-Zade and Gazanfar Abbasov in Azerbaijan, and Dr. Victor Chub, Tatyana Ososkova,Valentina Nazarova, and Olga Sventsiskaya in Uzbekistan.

The World Bank team includes Masami Kojima (task manager) and Robert Bacon of the Oil, Gasand Chemicals Department, and Martin Fodor and Magda Lovei of the Environment Department.

v

Abbreviations and Acronyms

C degrees Celsius

cm centimetre, 10-2 metre

CO carbon monoxide

CO2 carbon dioxide

GF/A glass fibre, grade A

ICP-AES inductively coupled plasma - atomic emission spectrometry

ICP-MS inductively coupled plasma - mass spectrometry

KI potassium iodide

1/min litres per minute

m metre

m3 cubic metre

mg milligram, 10-3 gram

mg/m3 milligrams per cubic metre

ml millilitre. 10-3 litre

NH3 ammonia

NIOSH National Institute for Occupational Safety and Health

nm nanometre, 10-9 metre

NO nitrogen monoxide

NO2 nitrogen dioxide

NO3- nitrate ion

NO, oxides of nitrogen

03 ozone

PM2.5 particulate matter with an aerodynamic diameter smaller than 2.5 microns

PM1 O particulate matter with an aerodynamic diameter smaller than 10 microns

ppm parts per million

ppb parts per billion

PTFE polytetrafluoroethylene, trademarked Teflon

SO2 sulphur dioxide

S042 sulphate ion

TEA triethanolamine

TSP total suspended particulates

UK United Kingdom

vi

Cleaner Transportation Fuels for Urban Air Quality Management

UJN-ECE United Nations Economic Commission for Europe

VOC volatile organic compounds

WHO World Health Organisation

Rtg microgram, 10-6 gram

.Ig/m3 micrograms per cubic metre

gm micrometre or micron, 10-6 metre

vii

Executive Summary

As part of the regional study. Cleaner Transportation Fuels for Urban Air Quality Improvementin Central Asia and the Caucasus, the air quality monitoring component summarised in thisreport was undertaken to (i) carry out ambient air quality monitoring for key air pollutants in twocities using continuous analysers: (ii) assess the current air quality monitoring system; and (iii)provide recommendations for improving air quality monitoring.

Baku. Azerbaijan and Tashkent, Uzbekistan were selected for carrying out air quality monitoringcampaigns on account of the fairly extensive air quality monitoring efforts by the localHydrometeorology Department so that the data obtained using different instruments could becompared. The air quality monitoring campaigns lasting about 10 days in each city were carriedout in July and August 1999. Nitrogen dioxide, carbon monoxide, ozone and total suspendedparticulates were measured using portable, high resolution, continuos analysers. Additionallypassive diffusion tube samplers were used to collect nitrogen dioxide, sulphur dioxide and ozonedata over a wide area of each city. Finally a personal monitor was used to collect particulates forlead analysis.

The weather conditions were such that ambient pollutant concentrations would be expected to below in Baku and high in Tashkent during the period of air quality monitoring. The data collectedindicated that the guidelines of the World Health Organisation (WHO) were exceeded fornitrogen dioxide in both Baku and Tashkent, and for ozone in Tashkent. Additionally, localmonitoring data for 1997, 1998 and up to July 1999 in Tashkent, Uzbekistan appear to suggest anunderlying trend of increasing levels of nitrogen dioxide and decreasing levels of sulphur dioxideand carbon monoxide.

The methods for sample collection and analysis employed in Central Asia and the Caucasus arecommon to all former Soviet Union republics. The sampling strategy of monitoring for twentyminutes at a time, three times a day is not considered to be effective in establishing mean ortransient air quality data indicators, and it is especially unsuitable for areas where concentrationsof pollutants change rapidly. The continuous data from automatic analysers showed thevariability and transient nature of pollution episodes, none of which could be captured from thesampling strategy currently in use in these countries.

Of special importance in urban air quality management are fine suspended particulates, becauseof their serious impact on human health. In Central Asia and the Caucasus, however, only totalsuspended particulates, which include coarse particulates having no impact on human health.have been measured, and no data are available for fine particulates. Further, there are manyshortcomings in the measurement of even total suspended particulates. including filters that havea large pore size, extremely high sampling flow rate, inadequate filter conditioningmethodologies. and poor resolution of the balance used to weigh the filters.

ix

Comparison of the data from automatic, continuous analysers shows that agreement ranged fromvery good to a difference of a factor of three for nitrogen dioxide. Comparisons of carbonmonoxide and total suspended particulate concentrations are complicated by the fact that theresults reported by Hydrometeorology are at the detection limits for the techniques used, whereasthe automatic analysers are much more sensitive to lower concentrations. In this study, carbonmonoxide concentrations were found to be under-estimated on most occasions and totalsuspended particulates over-estimated using the instruments run by Hydrometeorology.Comparison of daily averages showed that expressing daily mean values from three discretetwenty minute values-as opposed to averaging 24 hours' worth of continuous data-over-estimated ambient concentrations for the most part. on account of large variations during the 24hour period.

Comparison of lead monitoring data obtained using equipment brought in from the UnitedKingdom and those obtained by the local Hydrometeorology Department indicated that leadconcentrations were being under-estimated by an order of magnitude or more by the latter. As thefilters used to collect particulates are then subsequently used for the determination of leadconcentrations, this phenomenon is linked to the deficiencies in particulate measurements.Ambient lead concentrations measured during the course of this study varied from 0.03 to 0.1micrograms per cubic metre (jig/M3) in Baku and were 0.15 gig/m3 in Tashkent.

The following specific recommendations have been made to improve the current system of airquality monitoring:

* Sampling Integrity: Great care should be taken to ensure that the system which drawsambient air to the absorbing solutions is chemically inert and free from contamination. Thiswill greatly enhance the validity of the data collected.

* Site Maintenance: The immediate vicinity around the site should be representative of a largearea. Overgrowing vegetation will act as a sink for acidic pollutants and severely compromisethe representative nature of the data. It is essential, therefore, to ensure vegetation is kept to aminimum in the immediate vicinity of the sample collection inlet.

* Site Locations: As most of the monitoring stations are currently located in residential areas,very little information can be obtained about other environments within each of the cities. Itwould be useful to deploy a number of sites in kerbside, industrial and rural/suburbanlocations, to build up a fuller picture of air quality.

* Sample collection methodology: Consideration should be given to measuring air quality forlonger sampling periods by modification of the existing methodologies and equipmentupgrade, supplemented by use of passive sampling techniques.

* Filter collection systems: Lead and particulate sampling should be undertaken for longerperiods to accurately reflect true ambient concentrations. At present, all the filters collectedthrough the course of the month are analyzed together in one test, yielding a pseudo-"monthlyaverage" for ambient concentrations of lead. Sampling longer each time (for example. several

x


hours instead of 20 minutes) would allow detection of daily flucturations for lead, and wouldalso allow sampling to be undertaken at greatly reduced flow rates. which would improve thecollection efficiency of the filters.

* Pollutants measured: Consideration should be given to the pollutants measured on a regularbasis. Particulates that have a direct health impact, such as PM,o or PM,.5 (particles smallerthan 10 and 2.5 microns, respectively), rather than total suspended particulates, should bemeasured. Ozone was found to be measured at only a single observation post in Tashkent,Uzbekistan. Given the results from the continuous monitoring and passive sampling studies,especially in Tashkent where there were exceedances of the WHO guidelines, it isrecommended that ozone be measured at additional observation posts.

xi

1 IntroductionPhasing out lead from gasoline, as a cost-effective way of addressing a priority urbanenvironmental problem, has received much attention world-wide. including the transitioneconomies of Central and Eastern Europe and the Newly Independent States. Many countries inthe region participated in a two-year effort between 1996 and 1998 by the United NationsEconomic Commission for Europe (UN-ECE) and the Government of Denmark to prepare aregional strategy for gasoline lead elimination, setting deadlines and intermediate targets.

The World Bank has recently undertaken, with support of the Danish Environmental ProtectionAgency, a National Commitment Building Program to Phase out Leadfrom Gasoline inAzerbaijan, Kazakhstan and Uzbekistan. In the framework of this program. preliminary studieswere carried out to assess the level of lead pollution, and to explore different options for theelimination of lead in gasoline in the three participating countries. The findings were discussed ata regional workshop in Almaty, Kazakhstan, in May 1998. The workshop adopted a resolutionrecommending that lead in gasoline be eliminated by the year 2005 in Azerbaijan andKazakhstan, and by 2008 in Uzbekistan.

The regional study. Cleaner Transportation Fuels for Urban Air Quality Improvement in CentralAsia and the Caucasus, has built upon the momentum created by the above and other regionalinitiatives. The chief objective of this regional study is to recommend improvements inautomotive fuel quality, vehicle emission abatement, and air quality monitoring that will ensurereasonable air quality in the future. The programme will assess (i) the current status of air quality;(ii) current and future vehicle fleet characteristics and their fuel requirements; (iii) the impact ofdifferent fuel specifications on vehicular emissions and air quality; (iv) the impact of changingdemand and fuel quality on the refining sector; (v) economic analysis of different options; and(vi) the appropriateness of changes in petroleum sector policy-including pricing, fiscalmeasures and liberalisation of product trade-to facilitate the introduction of cleaner fuels. Theultimate objective of this program is to improve the public health of urban dwellers in Armenia,Azerbaijan, Georgia, Kazakhstan, Kyrgyzstan, Tajikistan. Turkmenistan and Uzbekistan byreducing vehicular emissions and improving urban air quality management. This reportsummarises the results of the air quality monitoring component of the study.

1.2 HEALTH CONCERNS OF AIR POLLUTION

Urban air pollution is an emerging environmental problem in many Newly Independent States.Among the key sources of pollution are increasing urban traffic and the prevalence of poor fuelquality. As a result, there is a growing awareness among policymakers of the need to mitigate airpollution from vehicles in the framework of urban air quality management.

International experience has indicated that typically, lead and fine particulates pose the greatesthealth concern in the urban environment. Lead is one of the highest-risk pollutants still widely inuse in gasoline in Central Asia and the Caucasus as an octane enhancer. Exposure to lead causesdiminished intelligence, behavioural and learning problems, lower productivity, and increased

I


health care costs. Lead is especially harmful to the developing brain and nervous system of smallchildren who retain significantly more lead to which they are exposed than do adults. Leadpoisoning affects the poor disproportionately-available data suggest that more lead is absorbedwhen there is iron or calcium deficiency, and the amount of lead absorbed by the body increasessignificantly when the stomach is empty. Unlike other pollutants, lead does not degrade, andcontinues to accumulate in the environment unless its use is stopped.

Suspended particulates. especially fine fractions with an aerodynamic diameter smaller than 2.5microns (~tm) (PM2 .5), are responsible for high incidence of respiratory infections, resulting inlost work days. hospitalisation and premature death. Particulate emissions from vehicles fallpredominantly in the PM2.5 range, diesel emissions being a significant source. This is of specialconcern, because demand for diesel is increasing rapidly throughout Central Asia and theCaucasus as heavy-duty vehicles switch from gasoline to diesel to take advantage of higher fueleconomy and greater engine durability. Furthermore, there is mounting epidemiological evidencewhich has emerged in recent years that diesel exhaust poses a serious cancer risk.

Ozone (03), which is formed by photochemical reactions of hydrocarbons and oxides of nitrogen(NO,), may become a problem in some cities in the region once the volume of traffic isincreased, on account of the prevalence of thermal inversion and sunny weather. Other concernsinclude increased emissions of carcinogens such as benzene.

1.3 AIR QUALITY MONITORING

Establishing an urban air quality management strategy and mitigating transport emissions requireco-operation of a large number of stakeholders in the environment, energy and transport sectors.Owing to the cross-sectoral nature of this issue, different government ministries and agenciesneed to come together and formulate a common strategy.

The effectiveness of such a strategy depends on proper fuel quality and vehicle emissionregulations and their enforcement. Inadequate monitoring of fuel quality and vehicle emissions,or standards set so stringent that significant non-compliance is inevitable, may result in thebreakdown of the air quality management system. In order to assess the impact of variousmeasures taken as part of the air quality management strategy, it is essential to obtain reliableambient air quality data on a regular basis.

This study of air quality monitoring in Central Asia and the Caucasus was conducted by Britishconsultants from AEA Technology plc. in collaboration with Hydrometeorology staff in Baku,Azerbaijan and Tashkent. Uzbekistan. The AEA Technology staff visited Baku from 8 July 1999until 21 July 1999. and Tashkent from 29 July 1999 until 9 August 1999. During this periodambient air quality data were collected using equipment brought from the United Kingdom aswell as the equipment used by the local Hydrometeorology Department. Ambient concentrationsof nitrogen dioxide (NO2 ), carbon monoxide (CO), 03 and total suspended particulates (TSP,commonly called "dust" in the region) were measured using portable high resolution ambient airpollution monitors. In addition, passive diffusion tube samplers were used to collect NO2 ,sulphur dioxide (SO2 ) and 03 data over a wide area of each city. The final component of the air

2

Introduction

monitoring conducted was the collection of particulate samples and subsequent analysis of leadconcentrations. The collected data were analysed and compared to those obtained by theHydrometeorology Department. An assessment of the current air quality monitoring programs inAzerbaijan and Uzbekistan has been made, and recommendations are given at the end of thisreport.

3

2 Data Collection and AnalysisAir quality data were collected in each city using a combination of methods:

1. automatic analysers providing time resolved measurements of NO2 , CO, 03 and TSP;2. a diffusion tube survey to collect average pollutant concentrations over a large area of the city

for NO2, SO2 and 03; and3. a personal sample pump was used to collect dust onto a filter which was subsequently

analysed for lead concentrations.

The data from these surveys, together with a description of the methodologies, are described inthe following sections.

2.1 MONITORING LOCATIONS

Descriptions of the monitoring locations for both the automatic monitoring and the diffusion tubesurveys are given in Appendix 1.

2.2 AUTOMATIC AIR POLLUTION MONITORING

Portable analysers were used to measure concentrations of NO2, CO, 03 and TSP. A personalsampler was used to collect particulate matter for analysis of lead content. The analysers usedare listed in Table 1.

Table 1. Portable Analysers

Paramete7- Analyser model Principle of detection Limit of Resolutiondetection

NO, TRI Odyssey 2001 Electrochemical cell 5 ppb I ppb

CO Draeger miniPac CO Electrochemical cell 1 ppm 1 ppm

03 Cosmos 030P Ozone Hunter Semiconductor sensor 10 ppb 10 ppb

Dust (TSP) R&P Dustlite 3000 Infrared light scattering 2 ptg/m3 I ,g/m3

Lead SKC Sidekick PersonalISampler

The gaseous pollutant analysers were calibrated using traceable gas standards both before leavingthe United Kingdom and on return. As it was not possible to calibrate the analysers whilst in thecountries visited. the sensitivity of measurements, i.e.. the calibration factors, are based on theresponses to calibration gas in the United Kingdom. There was a small change in the sensitivityof the analysers on their return to the United Kingdom, and this has been accounted for incalculating the data submitted in this report.

5


The Dustlite 3000 particulate analyser is manufacturer calibrated using Arizona Road Dust'against NIOSH (National Institute for Occupational Safety and Health) Method 0600 forrespirable dust to an accuracy of ±10%. The instrument can be field calibrated for zero and spanusing a sub-micron particulate filter and calibration artefact for the respective points.

The gaseous analysers (NO2, CO and 03) directly report in units of parts per million (ppm).These have been converted in the following text to gg/m3 at a reference temperature of 25°C andpressure of 1013 millibars (1 atmosphere).

These instruments have been used extensively in the United Kingdom for both ambient andworkplace monitoring studies. The main application of these types of mobile/portable analysersis for screening studies and for "hot spot" locating, where there is a need to provide monitoringdata quickly. Experience in the United Kingdom has shown that under typical temperate climateconditions (temperature range 20°C i 5°C during operation), the accuracy of these analysers canbe demonstrated to be within ±20%.

There are, however, drawbacks with these types of monitors. Typically they are often subject tointerference from other pollutant species, temperature and humidity. Stability of response canalso be a problem and frequent calibration is necessary.

During the studies reported here, temperatures reached levels for which the performance of theanalysers cannot be guaranteed. This, together with the inability to calibrate the analysers on-site, would normally mean that the data reported have associated uncertainties that aresignificantly higher than ±20%. Every effort was made to minimise the uncertainty ofmeasurement using the results of extensive analyser testing both before leaving the UnitedKingdom and on their return. Based on these analyser tests, estimates of temperatures theinstruments were exposed to and manufacturers' specifications. it is believed that theuncertainties associated with the data presented in this report are no greater than ±30%.

2.2.1 Automatic monitoring data - Baku, Azerbaijan

Data were collected in Baku at one of the Observation Posts operated by the HydrometeorologyDepartment. Monitoring at a position co-located with the local monitoring equipment enables acomparison of the data obtained using the two techniques. The Observation Post was located inan "uptown" region of Baku. approximately 5 meters from the kerbside and 15 meters from thecentre of the road. The area surrounding the immediate vicinity of the monitoring station was amixture of residential and commercial properties. Data for NO2 , CO and TSP were collected inthe period 9 July to 17 July 1999 and data for 03 were collected in the period 12 to 17 July 1999.

' Arizona Road Dust is a standard source of particles used for calibration of particulate analysers under the NIOSHmethod 0600. These particles have a diameter of approximately 3.5 urm and are of uniform colour, and hence anytechnique used to measure particulates can be referenced to a common source.

6

Data Collection and Analysis

Weather conditions during the monitoring period will have had a significant bearing on the datacollected. The automatic analysers were installed at the observation post on Friday, 9 July whichwas a hot and relatively calm day. The following two days were similar before a very wet andovercast day on Monday, 12 July leading to several days of windy conditions, the wind blowingfrom an easterly direction-straight off of the Caspian Sea. The wind calmed towards the end ofthe week. Saturday. 17 July. before increasing again on Monday, 20 July, however by this timethe direction had changed about completely and the wind was now from a westerly direction.

The data collected are presented graphically in Figure 1 below.

Figure 1. Air Pollution Monitoring - Baku

250 ......... .... .6

5200A

i 4

150

0 ~ ~ ~ ~ ~ ~ ~ ~ ~~~~~~~~~~~~ DustZ -~~~~~~~~~~~~~~~~~~~~~~~~~~N02

03i i

0.i. 1,1 -7 E *COE 100 EAV, . it i kiC

1 I ~~~~~~~~~~2

50i .!: i.,,,

0 0

00:00 00 00 00:00 00o00 00o00 00:00 00o00 00:00 00 00 00:00 00:0009/07/99 10/07/99 11/07/99 12/07/99 13/07/99 14/07/99 15/07/99 16107/99 17/07/99 18/07/99 19/07199

DateTinme

From the plot of the data it can be seen that the levels of all pollutants vary considerably duringthe study. Levels of NO, show the greatest variations with concentrations dropping to below 10gg/M3 on occasions. Although these data points seem anomalous, it is not considered to be avalid course of action to delete them from the dataset, as there appears to be no good justificationfor doing so. The diurnal variations in pollutant concentrations are unusual and not what wouldhave been expected from a roadside monitoring location. As the analysers appear to havefunctioned correctly, there is no reason to believe an instrumental error has caused the unusualdistribution of the data. Moreover, the changeable weather conditions, especially the strongwinds, are most likely to be the cause of the unexpected way in which maximum concentrationsoccur at times normally associated with low pollutant concentrations.

7


Table 2 lists summary statistics from the automatic data collected in Baku.

Table 2 Summary statistics - Baku

NO, CO | , TSP (dust)

____________ mg/m3

!lg/mr' g/m

Average 88 2 73 38

Hourly maximum 212 5.2 95 124

8 hour maximum 176 4.2 88 94

Daily maximum 121 2.9 83 64

Analysis of the data indicates that WHO health guidelines (as listed in Appendix 2) would havebeen exceeded on two occasions. Theses exceedances would have been for NO2 when themaximum hourly average reached 212 ,ug/m3. the guidance value being 200 [tg/m 3. WHOguidance values were not exceeded for any of the other pollutants during the period of the survey.

2.2.2 Automatic data - Tashkent, Uzbekistan

As with the monitoring in Baku, the automatic analysers were co-located with aHydrometeorology Observation Post. The Observation Post was chosen as the one likely to givethe highest values for the pollutants concerned during the monitoring period. The post wassituated on a major crossroads in the centre of Tashkent. The analyser used to collect data forTSP (dust) analysis was damaged in transit to Uzbekistan and therefore data are not available forthis pollutant. Additionally, frequent cuts in the power supply to the monitoring station resultedin the data capture (the number of valid data points) for the other pollutants being appreciablylower than was the case for the survey in Baku. Where the analyser was not functioning, due topower outages., the corresponding data points are ignored for the purposes of calculation ofaverages and statistics.

In contrast to the weather conditions in Baku. the weather in Tashkent remained almost constantthroughout the period of the survey. With the exception of Saturday, 31 July, when it rained inthe morning, temperatures were high during the days, over 30°C, with little wind and/or cloudcover.

The data collected are presented graphically in Figure 2.

8


Figure 2. Air Pollution Monitoring - Tashkent

300 - 16

14250

12

20010

0~~~~~~~~~~~~~~~~~~~~~~~~~o0

150 i80 E 0 03

SO - k - . . > . . ::~~~~~~~~~~~, -C

0)~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~L

-6

100

4

50 -

0 000:00 00:00 00:00 00:00 00:00 00:00 00:00 00:00 00:00

30/07/99 31/07/99 01/08/99 02/08/99 03/08/99 04/08/99 05/08/99 06/08/99 07/08/99Date/Time

As with the data from Baku, the plot of the data from Tashkent shows that the levels of allpollutants vary considerably during the study. Once again some data points appear to drop tovery low levels without a reasonable explanation and as with the Baku dataset, it is notconsidered to be a valid course of action to delete them from the dataset, as there appears to beno good justification for doing so.

Table 3 lists summary statistics from the automatic data collected in Tashkent.

Table 3 Summary statistics - Tashkent

NO, CO 03

FLglm3 mg/m3 Ig/lm3

Average 90 4.2 72

Hourly maximum 250 13.9 218

8 hour maximum 171 8.7 162

Daily maximum 109 5.7 75

Analysis of the data indicates that WHO health guidelines (as listed in Appendix 2) would havebeen exceeded on seven occasions for NO2 and on fifteen occasions for 03. The NO,exceedances would have been against the hourly average standard of 200 j.g/in3 . The maximumrecorded hourly average was 250 ,ug/mi3. The 03 exceedances would have been against the

9


running eight hour mean standard of 120 ag/m3 . The maximum recorded eight hour average was162 gg/m'.

Guidelines were not exceeded for CO during the period of the survey, although the running eighthour mean limit value of 10 milligrams per cubic metre (mg/mi3) was approached on severaloccasions with the maximum value being 8.7 mg/m3.

2.3 PASSIVE SAMPLER MONITORING

In addition to the automatic analyser monitoring, a passive sampling survey using diffusion tubesfor the measurement of NO2, SO2 and 03 was conducted in the two cities. These diffusion tubesoffer a cost effective means of assessing longer term average pollutant levels over a wide area. Ineach city the diffusion tubes were left to sample for at least seven days and were spread overtwenty different locations throughout the cities.

Diffusion tubes are typically clear plastic tubes open. or with a membrane screen, at one end anda pollutant-absorbing chemical matrix or gel at the closed end. The tubes are prepared and sealedbefore being transported to the monitoring site. At the site, the tube is exposed by removing a capand leaving it for a period of between one week and one month. The diffusion tube "collects" thepollutant during the exposure period, at the end of which the tube is re-sealed and returned to ananalytical laboratory. By the laboratory analysis of the quantity of pollutant absorbed, it ispossible to estimate the average ambient pollutant concentration over the exposure period.

However, the time resolution of this technique is limited, as it can only provide information onintegrated average pollutant concentrations over the exposure period (typically 1-4 weeks). Manyair quality standards and guidelines are based on short term measurements (hourly or dailyaverages) and compliance with these can, therefore, be determined directly only using automaticmonitors. For some applications, however, statistical techniques allow the likelihood of non-compliance with short-term standards to be estimated from long-term passive samplermeasurements. Such estimation techniques need to be used with caution.

Passive samplers have been widely used for many years in personal exposure monitoring andoccupational health assessments. For monitoring ambient air, passive samplers are particularlyuseful for baseline surveys, area screening or indicative monitoring. They can also be usefulwhen used in combination with automatic analysers. In such hybrid surveys, passive samplerscan provide geographically-resolved air quality data, whilst the more sophisticated devices offertime-resolved information on concentration peaks and diurnal variations. Hybrid surveys of thistype can be particularly cost-effective.

2.3.1 Passive sampler data - Baku, Azerbaijan

Twenty sets of passive samplers were deployed throughout Baku. Exact details of the locationsalong with site description codes as used in UK (United Kingdom) monitoring studies are given

10


in Appendix 1. The results from the subsequent analysis of the diffusive samplers are given inTable 4.

Table 4 Results of passive sampler survey - Baku

Sampler Classificution Sanmplinig period NO, SO, 02Location ppb (4g/m3) ppb (tg/mr) ppb (4g/m3)

Intermediate 12 to 20 July 31.6 (60.8) 5.7 (15.2) 9.0 (18.1)

2 Intermediate/ 12 to 19 July 21.9 (42.2) 4.9 (13.1) 19.0 (38.1)Background

3 Background 12 to 19 July 7.7 (14.8) 4.9 (13.1) 43.3 (86.6)


5 Intermediate/ 12 to 19 July 13.7 (26.4) 3.2 (8.6) 35.7 (71.4)Background

6 Intermnediate 12 to 19 July 17.2 (33.1) 3.2 (8.6) 22.2 (44.5)

7 Background I 2to 19 July 10.2 (19.5) < LOD 24.1 (48.2)


9 Background 12to l9July 17.6 (33.9) <LOD 24.2 (48.5)

10 Intermediate 12 to 19 July 16.4 (31.5) 4.1 (11.0) 31.3 (62.7)


12 Background 12 to 19 July 10.6 (20.5) < LOD 26.3 (52.6)


14 Backg,round 12 to 19 July 7.4 (14.2) 5.0 (13.3) 22.9 (45.8)

15 Intermnediate 12 to 19 July 16.7 (32.1) < LOD 19.4 (38.8)


17 Intermediate 12 to 19 July 44.1 (84.9) 3.3 (8.8) 8.7 (17.4)

18 Roadside 13 to 20 July 15.3 (29.3) 3.3 (8.8) 29.3 (58.5)

19 Background 13 to 20 Julv 6.3 (12.2) 6.5 (17.4) 37.9 (75.7)

20 Roadside 14 to 20 July 38.6 (74.2) 4.8 (12.8) 26.3 (52.6)

LOD: less than limit of detection

For some of the samplers, a result cannot be quoted and therefore "< LOD" (less than limit ofdetection) is entered into the relevant space. This is because the amount of pollutant found onthe diffusive absorbent is either less than or equal to the amount found on the quality controlblanks associated with the batch of samplers.

2.3.2 Passive sampler data - Tashkent, Uzbekistan

11


Twenty sets of passive samplers were deployed throughout Tashkent. Exact details of thelocations along with site description codes as used in UK monitoring studies are given inAppendix 1. The results from the subsequent analysis of the diffusive samplers are given inTable 5.

Table 5 Results of passive sampler survey - Tashkent

Samlpler Classification Sampling period NO, SO2 (3Location ppb (gLg/m') ppb ([tg/m3) ppb (~tg/m')

I Background 30 July to 7 August 20.2 (38.8) 3.6 (9.5) 61.7 (123.5)

2 Background Tube Lost Tube Lost Tube Lost

3 Background 30 July to 7 August 31.8 (61.1) 16.7 (44.4) 26.0 (52.0)


5 Intermediate 30 July to 7 August 38.9 (74.8) 5.8 (15.4) 32.1 (64.2)

6 Background 30 Julyto 7 August 31.2 (60.0) 5.9 (15.8) 64.1 (128.1)


8 Background Tube Lost Tube Lost Tube Lost



11 Roadside 31 July to 7 August 43.1 (83.0) 9.8 (26.2) 26.0 (51.9)

12 Roadside/ 31 July to 7 August 40.9 (78.6) 11.5 (30.6) 24.2 (48.5)Intermediate









Unfortunately during the course of the study the tubes at locations two and eight were lost. Thisis not an unusual occurrence in studies of this kind in the United Kingdom, where tubes are oftenstolen or destroyed by vandals. Although every effort to minimise the chances of this happeningwere taken, i.e., tubes placed at a height where they cannot be reached by the casual observer, thesecurity of the tubes cannot be guaranteed.

12


2.4 LEAD MONITORING

A personal sampler pump was used to collect particulate onto filters at the continuous monitoringsite locations in each city. The pump was set to sample at a rate of 1.8 litres per minute (1/min).These filters were subsequently analysed in the United Kingdom using Inductively CoupledPlasma - Atomic Emission Spectrometry (ICP-AES) and Inductively Coupled Plasma - MassSpectrometry (ICP-MS).

Table 6 Lead concentrations as determined by AEA

City and sampling period Samiipling time Sanmple volume Lead Concentration(hours) (m3) (gg/rn)

Baku - 9 July to 12 Ju]y 1999 68.5 7.4 0.10

Baku - 12 July to 14 July 1999 45.5 4.9 0.04

Baku - 14 July to 16 July 1999 48 5.2 0.06

Baku - 16 July to 19 July 1999 75 8.1 0.03

Tashkent- 30Juiy to I August 1999 46.5 5.0 0.14

Tashkent - 2 August to 4 August 1999 46 5.0 0.15

Tashkent - 4 August to 7 August 1999 74 8.0 0.14

Observations of the dust collected on the filters, with reference to the colour of the dust, can giveindications of the source of the dust. The filters exposed in Baku contained dust which wasbrown in colour; this tends to suggest that the dust originates from soil rather than combustionproducts.

The filters exposed in Tashkent revealed dust that was grey in colour. This is more in line withthe dust collected in the United Kingdom, which is primarily considered to be the product of thecombustion of fossil fuels.

13

3 Comparison of DataIn the following section the data collected by the British consultants is compared with the datasupplied by the local Hydrometeorology Department. For the study in Azerbaijan, the datacollected by Hydromet are compared with the data collected by AEA Technology usingautomatic analysers, while for the Uzbekistan study the Hydromet data are compared against theresults of the diffusion tube survey.

3.1 AZERBAIJAN

For the data collected in Baku it is possible to make comparisons between both the individualmeasurement points, and the resulting daily average concentrations.

The table below gives the average concentration as measured for each pollutant on a daily basis.Data are provided from both the results obtained by Hydromet using their standard monitoringtechniques, and by AEA using automatic analysers.

Table 7 Comparison of daily average data - Baku

Date Hvdromet Data AEA Data

NO, ig/m3 CO mg/m' TSP pig/m' NO, jig/mr3 CO mg/m TSP jg/r 3

9 July 70 2 100

10 July 80 1 100 84 2.8 45

12 JuIv 90 1 200 76 0.9 41

13 July 80 1 200 53 1.1 28

14 July 60 1 200 100 0.9 53

15 July 60 1 200 121 1.0 64

16 July 90 1 100 114 1.6 61

17 July 80 1 100 105 2.0 56

The data that are reported from Hydromet are daily average concentrations based on the threespot samples taken throughout the respective day. The AEA daily averages reported in the tableare calculated as the mean of 1440. one-minute measurements collected throughout the twenty-four hour period.

Comparison of the NO- values reported by Hydromet and AEA show that agreement ranges fromvery good (10 July) to a difference of a factor of two (15 July). Comparisons of CO and TSPconcentrations are complicated by the fact that the results reported by Hydromet are at the

15


detection limits for the techniques used, whereas the instruments used by AEA are very muchmore sensitive to lower concentrations.

These comparisons are shown graphically in Figures 3. 4 and 5.

Examination of the individual measurements made by Hydromet. and the corresponding 20minute average concentrations as measured by AEA using automatic analysers, is presented inTable 8.

Table 8 Comparison of individual measurement points - Baku

Date Tinie Hydromet Data AEA Data

NO2 CO TSP NO2 CO TSPtg/m3 mg/rn3 ,gglm3 ,g/m3 mglm/ g/m3

9 July 07:00 90 2 10013:00 60 1 10019:00 60 2 200 131 4 20

10 July 07:00 90 1 100 2* 1.7 5013:00 70 1 0 134 2.9 3419:00 70 1 0 145 5.3 28

12 July 07:00 80 2 200 60 1.1 5013:00 90 1 200 103 0.8 5719:00 110 1 200 85 0.6 34

13 July 07:00 70 1 300 45 0.9 3513:00 80 1 200 56 0.9 3319:00 80 1 200 51 1.9 16

14 July 07:00 70 1 200 58 0.3 3313:00 60 1 100 88 1.2 2219:00 60 1 200 194 0.9 45

15 July 07:00 70 1 200 62 1.1 5013:00 50 1 200 120 0.9 2919:00 70 1 100 177 0.9 18

16 July 07:00 100 2 0 88 1.5 4313:00 80 1 100 94 1.2 3419:00 100 1 0 197 2.6 59

17 July 07:00 90 1 0 94 1.8 6613:00 80 1 100 137 1.6 2819:00 80 1 100 88 3.2 33

* This anomalous result cannot be explained from examination of the dataset, although the time seriesplot indicates no good reason for removing it from the dataset.

As with the daily means the comparison of CO and TSP data is limited by the fact that Hydrometare working at or near to their detection limits. The concentrations of NO2 reported, however,show even greater discrepancies than from the daily mean figures. The differences in reported

16

Comparison of Data

concentrations range from an overestimation by Hydromet of a factor 1.6 to an under estimationof a factor 3.2. both with respect to the AEA data.

Compaison of daily NO2 data - Baku

o 150

h 100 . , t- 1 -

~bi%= i>, 50 D_74 H50

o 0 ~~~~~~~~~~Hydromet

M UAEAC's Z N c' ~

Date

Figure 3 Comparison of Daily NO2 data in Baku

Comparison of daily CO data - Baku

= ~4

- 9) , __ __. _ ___

2

1~~~~~~~~~~z 0 E l z. IEHydromet

S , N - - b |AE,A5 ) o C 9~ s [o ..

Date

Figure 4 Comparison of Daily CO Data in Baku

17

Cleaner Transportation Fuels for Urban Air Qualitv Management

Comparison of daily Dust data - Baku250200150 -

50. ... ........... 0 @Hydromet

I." _ - . t- _- N r -

O z

Date

Figure 5 Comparison of Daily TSP Data in Baku

3.1 UZBEKISTAN

Table 9 gives the average concentrations for the period 30 July to 6 August 1999 for thepollutants specified at each of the Hydromet Observation Posts. These data should be comparedwith that obtained by AEA using diffusion tubes for NO2 , SO2 and O3. These comparisons aremade graphically for NO2 and SO2 in Figures 6 and 7.

18

Comparison of Data

Table 9 Concentrations of pollutants as measured by Hydromet - Tashkent

Station No. AEA Samnplei ConcentrationLocationi pg/iri3

NO, sC) CO C

1 0 6 1000 60

2 3 40 3 3000

4 6 150 10 2000

6 2 30 4 1000

8 7 10 2 2000

12 8 60 3 1000

14 4 120 3 2000

15 5 50 5 4000

19 9 90 7 3000

20 1 0 1 30 2 1 1000

Due to the frequent power failures of the monitoring station used to house the continuousanalysers, it is not possible to calculate a valid average concentration for the complete monitoringperiod. A valid average requires a minimum of 75% data capture. which was not achieved forNO2 (58% data capture), or 03 (58% data capture). For this reason it is not possible to comparethe data from the continuous analysers with the data provided by Hydromet.

The CO analyser achieved the required data capture level and a valid comparison can be madefor this pollutant. The continuous analyser was located at station 15 where the CO mean value asreported by Hydromet was 4 mg/mi3 . The continuous analyser gave a mean value (calculatedfrom the one-minute readings) of 4.3 mg/m3.

19


Comparison of NO2 data - Tashkent

o 200O20

150 U u * Hydromet

~~~~50 EI~~AEA0~5

1 2 4 6 8 12 14 15 19 20

Station Number

Figure 6 Comparison of NO2 data in Tashkent

Figure 6 indicates that there is no significant bias between the two monitoring techniques for themeasurement of NO2. Generally the concentrations obtained by Hydromet are higher than thosethat AEA obtained from diffusion tubes. This is most likely an indication that the samplingstrategy employed by Hydromet (three, twenty minute samples per day, averaged over thesampling period) is biased towards periods of higher pollutant concentration, i.e., daytime onlymeasurements, as opposed to continuous sampling.

Comparison of SO2 data - Tashkent

0 600

g ffi 40 1 m Hydromet

Vo L2 E]AEA

0 ~0

1 2 4 6 8 12 14 15 19 20

Station Number

Figure 7 Comparison of SO2 data in Tashkent

20

Comparison of Data

Figure 7 indicates a clear bias whereby AEA's diffusion tubes show higher concentrations ateach monitoring station. It should be noted, however, that the accuracy of results from SO2

diffusion tubes is least reliable for concentrations of less than 30 ,ug/m3 . As SO, concentrations,using the results from either technique (with the exception of monitoring station 2). do notapproach the WHO health guideline value of 50 [tg/m3 as an annual mean (Appendix 2), thenSO, is not considered to be a pollutant of concern in Tashkent.

21

4 Review of MethodologiesWithin the former Soviet Union, many atmospheric pollutants are monitored on a regular basis,examples of which are the six pollutants around which this survey is based, as well as phenol,formaldehyde, hydrogen fluoride, ammonia and sulphate. This review of monitoringmethodologies and strategies concentrates on the six pollutants for which comparative data setshave been accumulated, i.e.. NO2 , SO2, CO, 03, TSP and lead.

4.1 SAMPLING STRATEGY

The standard Soviet system of air sampling is employed. This involves taking pumped samplesthree times a day on all days except holidays. These samples are then transferred to a centrallaboratory for analysis. The methods employed for the analysis are described in the followingsections.

To investigate the method of sampling and averaging employed in both the countries visited, acomparison of data collected using automatic analysers in Baku (12 to 17 July 1999) andTashkent (31 July to 6 August 1999) is made in Table 10. In this table the daily averageconcentration from the continuous analyser (1440, one-minute measurements) is compared withthe average of the three sampling periods corresponding to the Hydromet sampling strategy, i.e.,the average of the concentrations measured at 07:00. 13:00 and 19:00 (representing a total of 60minutes' worth of measurements).

23


Table 10 Comparison of sample means

Dale City NvO~ co

daily mean mean of 3 daily mean mean of 3samples samples

12 July 1999 76 83 0.9 0.8

13 July 53 51 1.1 1.2

14 July 100 113 0.9 0.8

15 July Baku 121 120 1.0 1.0

16 JuIy 114 126 1.6 1.8

17 July 105 106 2.0 2.2

31 July 1999 76 95 3.7 4.6

1 August 4.3 5.7

2 August 4.1 5.7

3 August Tashkent 4.9 7.5

4 August 5.6 7.2

5 August 74 95 4.5 6.7

6 August 78 74 3.5 4.5

Of the twenty-two comparisons made in Table 10, use of the Hydromet method for calculatingdaily means would have resulted in an overestimation of the concentration in sixteen cases. Thecomparison of sampling techniques for the data collected in Baku gives very good agreement foralmost all data pairs. It should be noted, however, that this comparison is conducted over a verysmall sample of data points.

This method of analysis shows from the Tashkent CO data, where the monitoring was conductedat a large open crossroads, the effect of transient exposure on the data set. The samples collectedby Hydromet are taken at times when the traffic density is likely to be high; therefore, the COconcentrations will also be high. Using these three results to produce a daily average will give anartificially high indication of concentrations, as is illustrated by the analysis in Table 10.

This method-of expressing daily mean values from three discrete twenty minute values-isperfectly valid if concentrations do not change significantly on a diurnal basis. However, wherelarge variations are experienced throughout the twenty-four hour period, this method has beenshown to over-estimate and could equally under-estimate concentrations of pollutants.

24

Summary and Conclusions

4.2 NITROGEN DIOXIDE

Concentrations of NO, are measured using a modified version of the Russian solid film sorbentmethod.

NO? is absorbed from the air by a layer of glass beads coated with a potassium iodide (KI)solution. The beads are washed with glycerine, and naphthamine and sulphanilic acid is added tothe resulting solution. A pink dye is formed, and the concentration of nitrite ion is thendetermined photometrically at 540 nanometres (nm).

The laboratories calibrate their spectrophotometers using a series of freshly prepared referencesolutions. The intensity of the dye from the station sample is then referenced against thesestandard solutions, to determine the actual concentration.

This method, as demonstrated during visits to the Hydromet laboratory in Tashkent, differs fromthe standard procedure, which uses a toxic, non drying KI/Na3AsO3 absorbent, and normal-(l-naphthyl)-ethylenediamine and sulphanilic acid are used to react with nitrite ion. However, themodified procedure appears to be specific for NO2, and has demonstrated excellent agreementwith methods used by European reference laboratories at a WHO intercomparison workshop. Itis likely, therefore, that any NO2 that is absorbed in the bubbler solution will be successfullyanalysed in the laboratory.

4.3 SULPHUR DIOXIDE

Concentrations of SO?- are measured using a modified version of the pararosaniline method.

SO2 is absorbed in a buffered acetate solution containing sodium hydroxide and formaldehyde.This solution is reacted with pararosaniline, disodium ethylenediamine tetraacetic acid and aminosulphonic acid. The concentration of the resulting pararosaniline methyl sulphonic acid dye isthen measured photometrically at 540 nm. As with the method for NO2, the spectrophotometer isregularly calibrated with standard reference solutions, to determine the response of theinstrument for calculating station concentrations.

This method, as demonstrated during visits to the Hydromet laboratory in Tashkent, differs fromthe standard pararosaniline method, which uses toxic sodium tetrachloromercurate as theabsorbent solution, and pararosaniline hydrochloride and formaldehyde as the analytical reagents.However, the modified procedure appears to be specific for SO2, and has demonstrated excellentagreement with methods used by European reference laboratories at a WHO intercomparisonworkshop. It is likely, therefore, that any SO2 that is absorbed in the bubbler solution will besuccessfully analysed in the laboratory.

25


4.4 OZONE

Ozone concentrations are determined using the standard test method for oxidant content of theatmosphere (Neutral KI method). Samples are collected by absorption in a solution of KIbuffered to pH 6.8. The released iodine equivalent of the concentration of oxidant present in theair sample is determined in a photometer by measuring the absorption of the tri-iodide ion at awavelength of 352 nm. As with the methods for NO2 and SO2 , the spectrophotometer isregularly calibrated with standard reference solutions. to determine the response of theinstrument for calculating station concentrations.

It should be noted that the neutral KI method covers the determination of low concentration ofnet oxidants in the atmosphere, including 03. Therefore this method is not specific for 03, sinceother oxidising and reducing agents will affect the results.

The method has demonstrated good agreement with methods used by European referencelaboratories at a WHO intercomparison workshop, although it should be noted that the testatmospheres generated contained only 03. It is likely, therefore. that the oxidants absorbed in thebubbler solution will be successfully analysed in the laboratory, but because the method is notspecific for 03, it may over-estimate 03 concentrations.

4.5 CARBON MONOXIDE

Air samples are hand pumped into a small rubber balloon at the monitoring station. The sampleis analysed at the laboratory using a self contained automatic analyser. This analyser uses anelectrochemical cell to determine the concentration of CO present in the sample from thecontrolled potential oxidation of CO to carbon dioxide (CO2 ). Sample gas is passed across acatalytically-active electrode where any CO present is oxidised to CO2. The rate of this oxidationis related to the concentration of CO and is read directly from the front panel display of theinstrument.

The technique is specific for CO. but it should be noted that the analyser performance is affectedby changes in temperature and pressure. It is therefore important that the analyser is regularlycalibrated with zero gas and CO to evaluate its performance, preferably during the process ofdetermining station concentrations.

Although CO is a relatively unreactive gas, the effect of the rubber balloon on sample losses doesnot appear to have been quantified. As the sample may remain in the balloon for over 12 hours,it is important to assess how stable the gas is in this type of environment. It is recommended thata series of tests be undertaken to quantify any losses to the sampling system.

26

Summarv and Conclusions

4.6 TSP (DUST)

Air is drawn through a filter for twenty minutes whereupon 1.8 cubic metres (mi3 ) will have beensampled. This operation is conducted three times daily in conjunction with the sampling ofgaseous phase pollutants. However where the gaseous pollutants collect separate measurementsat each observation, the TSP sampling uses the same filter for the three measurements per day.Therefore each filter will have collected TSP from a 5.4 m3 sample of air.

The filters are then transferred to the central laboratory for weighing. As the filters were weighedbefore the sampling the mass of TSP collected is calculated by subtracting the pre-measurementfilter weight from the post sampling filter weight. The balance which is used for thesemeasurements is capable of measuring to 0.0001 g (0.1 Img).

The methods used for collecting TSP and analysing the weights deposited give some cause forconcern, and are discussed below.

The filters are weighed before and after exposure on a 4 decimal place balance. At an average(UK) TSP concentration of 30 yg/m3, the mass deposited on an exposed filter would be (5.4 x30) A160 ,ug (0.16 mg). It is therefore vitally important that suitable filter handling andconditioning procedures are employed to minimise losses and errors which could arise. Thereare two main areas which require particular attention:

1. There was no evidence of filter conditioning either before or after exposure. Most filter typesand dusts sampled are, to some extent, sensitive to moisture collection.

Any moisture collected on or removed from the filter before, during or after exposure willseverely compromise the validity of the results obtained. This is especially true if thedifferences in mass are small. and the resolution of the balance is poor. Worst case resultswould be if the mass of the filter after exposure was lower than at the start, resulting in anapparent negative mass concentration, or equally serious, if water is deposited duringexposure, adding significantly to the overall result.

For the above reasons, conditioning of filters should usually be undertaken for a period of notless than 24 hours in a temperature and humidity controlled environment (in Europe this isnominally 20'C, 50% relative humidity), to allow the filter mass to stabilise in a known,constant atmosphere. This should minimise errors associated with water interference.

It is recommended that a dedicated area be assigned to filter conditioning, whoseenvironment can be accurately and reproducibly controlled. This could be as simple as aglass dessiccator located inside an air-conditioned room or fume cupboard. Considerationshould also be given to the purchase of a 5 decimal place balance (0.01 mg). which wouldgreatly enhance the resolution of the data collected.

2. It is very important that the filters are handled with utmost care. As the changes in mass arevery small. any contact with the filter between weighings may have a significant effect on the

27


final result. Contact with fingers, storage and transportation media, or laboratory benchesand equipment (grease, dirt, risk of dislodging collected sample) must all be eliminated topreserve the integrity of the filter.

The filter papers do not appear to be very well suited to the task of collecting dust in a high flowgas stream. It is possible that significant quantities of dust are passing through the filters withoutdetection. This is discussed further in Section 4.8

4.7 LEAD

For each monitoring station, all the filters used to collect TSP samples are brought together at theend of each month and used for the analysis of lead concentrations. The set of filters are burnttogether at a temperature of 460 to 500°C. The residue is then dissolved in nitric acid and thissolution is allowed to evaporate until a wet salt remains. This salt is then dissolved in a 5%solution of nitric acid. 10 millilitres (ml) of this solution is taken and analysed using atomicabsorption spectroscopy. The method should be specific for lead, and calibration of the analyseris verified with a series of standard solutions on a regular basis, to ensure the reliability of theresults obtained.

4.8 FILTER EFFICIENCY TESTS

The pore size of the filters used for the collection and analysis of TSP and lead was not known bythe operators of the monitoring stations, but was thought to be in the region of 10 gm. A sampleof the filters used was returned to the United Kingdom for testing.

The majority of lead particulate matter exiting motor vehicle exhausts is of the size fractions 0.8to 3 gm in diameter. Filter penetration tests were performed for a range of size fractions toestablish the filter efficiency of both the paper filters used by Hydromet and the glass fibre filtersused by AEA Technology in their respective sampling modes. These tests were carried out usinga flow rate of 1 1/min. where in practice the Hydromet filters are sample at some 90 I/min andAEA Technology's personal sample pump operated at 1.8 I/min. The results are shown in Table11.

28

Summarv and Conclusions

Table 1 I Results of filter efficiency tests

Size ftaction Particle capture efficiencv

Pim Hydromet paper filter AEA GF/A* filter

0.65 -0.80 91 100

0.80- 1.00 90 99

1.00- 1.25 85 96

1.25- 1.50 89 100

1.50 - 2.00 89 92

2.00 - 2.50 75 1002.50 - 3.00 25 1 00

*GF/A: glass fibre, grade A

Hydromet filters show good capture efficiency towards small particle size fractions and are lessefficiency towards larger particles. It is believed this is due to diffusive capture of the smallerparticles. where the fibres of the paper capture the particles as they pass through the filtermembrane. Larger particles, having greater momentum, pass through the filter. This appears tobe a good result as the smallest fractions are captured with a high efficiency, but this is only thecase at the low (test conditions) flow rate. When the filter is used at the Observation Post tocollect TSP samples the flow rate used is in the region of 90 1/min, and at this flow rate even thesmallest particle sizes will have great momentum and as a consequence pass through the filter.

4.9 QUALITY ASSURANCE/QUALITY CONTROL MEASURES

For the pollutants measured by photometric absorption, the absorptiometer is calibrated usingstandard solutions obtained from the Chief Geophysical Laboratory of Russia. The CO analyseris returned to the manufacturer for calibration and certification with traceable gas standards.

The Hydrometeorology Department of Uzbekistan attended the WHO European IntercomparisonWorkshop on Air Quality Monitoring in 1998. This workshop focused on the measurement ofCO, nitrogen monoxide (NO). NO2 and benzene/toluene/xylenes. The results of thisintercomparison showed that the measurement techniques employed by Hydromet for thesepollutants gave very good agreement with the target value at most concentrations, and goodagreement at all other concentrations.

Participation at intercomparison workshops is an invaluable method of demonstrating theeffectiveness of monitoring capabilities, both in terms of accuracy of measurements andsuitability of monitoring techniques.

29

5 Review of Historical DataHistorical data were presented graphically to the consultants while visiting each country.Meaningful long term trend analysis would normally be considered only when at least five yearsof uninterrupted data had been collected. The data presented to the British consultants inUzbekistan was for the years 1997, 1998 and up to July 1999. It is difficult to establish anytrends in the data from the limited amount available. However, taking into consideration the datafrom all the monitoring stations in Tashkent, it would appear that the underlying trend is of anincrease in NO2 levels and decreases in the levels of SO2 and CO. There is insufficient data tocomment on the trend for 03.

Reproduced below as Figure 8 is the graphical plot for historical data relating to observation post15 in Tashkent.

nocT Ne 15 TaUlerT

£IwKNCMJ CW6I

0,2

i ii ii: v vi VII IJ l x xi ;ii

N4A

0,00~~~~~~~~~~x

7

3 -

~~Figr Hitorica daafr ObevainPot1 - Tah.n

-* o - ~~~~~~~~~3


Listed below in Table 12 are the monthly lead concentrations as collected and analysed byHydromet in Tashkent. The figures quoted relate to the average concentration from observationpost number 15 (where AEA's monitoring was conducted).

Table 12 Lead concentrations in ,ug/m3 measured at observation post 15

Year Month

1 2 3 4 5 6 7 8 9 10 I 1 12

1997 0.00 0.01 0.00 0.01 0.00 0.00 0.03 0.00 0.05 0.04 0.00 0.03

1998 0.00 0.01 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00

1999 0.00 0.00 0.02 0.03 0.00 0.03 0.01

These data indicate that the concentrations of lead measured are very low. However, based onthe data collected by AEA Technology and the subsequent filter efficiency tests, it is believedthat lead concentrations are being severely underestimated.

32

6 Summary and Conclusions6.1 MONITORING LOCATIONS

The majority of the Observation Posts, in both countries, are located in residential areas. Thesegive good indicators for air pollution exposure to the general public but do not always capture thefull impact of pollution episodes.

At many of the Observation Posts in Tashkent, foliage was seen to be obstructing and evengrowing into the inlet sample ports. As vegetation is a significant absorber of acid pollutantsconcentrations measured by Hydromet. may be severely compromised at these monitoring points.

6.2 MONITORING PROCEDURES AND STRATEGY

The sampling strategy of monitoring for twenty minutes at a time, three times a day, is notconsidered to be effective in establishing mean or transient air quality data indicators. Thecontinuous data from the automatic analysers show the variability and transient nature ofpollution episodes, none of which could be interpreted from the sampling strategy currently inuse in these countries.

6.3 SAMPLE COLLECTION SYSTEMS

It is vitally important that the sample inlet system, which introduces ambient air to the absorbingsolutions, is chemically inert and clean. It was observed that tubing used to connect to theglassware in both countries was seen to be soiled and did not appear to be of inert material, e.g..polytetrafluoroethylene (PTFE. trademarked Teflon). It is likely, therefore, that large scale lossesto the sampling system will occur which will have significant effects on the validity of the datasets.

6.4 RECOMMENDATIONS

* Sampling IntegrityGreat care should be taken to ensure that the system which draws ambient air to the absorbingsolutions is chemically inert and free from contamination. This will greatly enhance thevalidity of the data collected.

* Site MaintenanceThe immediate vicinity around the site should be representative of a large area. Overgrowingvegetation will act as a sink for acidic pollutants and severely compromise the representativenature of the data. It is essential, therefore, to ensure vegetation is kept to a minimum in the

33


immediate vicinity of the sample collection inlet.

* Site LocationsAs most of the monitoring stations are currently located in residential areas, very littleinformation can be obtained about other environments within each of the cities. It would beuseful to deploy a number of sites in kerbside, industrial and rural/suburban locations, tobuild up a fuller picture of air quality.

* Sample collection methodologyThe current method of collecting data is three 20-minute samples per day. From the dataobtained from the continuous analysers during this study, it is clear that this is not sufficientto derive a full picture of air quality in the cities. Consideration should be given to measuringair quality for longer sampling periods by modification of the existing methodologies andequipment upgrade, supplemented by use of passive sampling techniques (details of whichare given in Appendix 3).

* Filter collection systemsThe filters currently used for the collection of airborne lead and TSP do not appear to beappropriate to the task. This is due to a number of shortcomings, i.e., the pore size andcomposition of the filters and the high flow rate used for collection. As with the samplecollection methodology currently used for gaseous pollutants, lead and TSP sampling shouldbe undertaken for longer periods to accurately reflect true ambient concentrations. Thiswould also allow sampling to be undertaken at greatly reduced flow rates, which wouldimprove the collection efficiency of the filters.

* Pollutants measuredConsideration should be given to the pollutants measured on a regular basis. PM10 or PM2 sshould be measured rather than TSP on account of the public health impact of respirableparticulates. Ozone was found to be measured at only a single observation post in Tashkent,Uzbekistan. Given the results from the continuous monitoring and passive sampling studies,especially in Tashkent where there were exceedances of the WHO guideline, it isrecommended that ozone is measured at additional observation posts.

34

Appendix 1 Monitoring Locations

Monitoring Locations in Baku, Azerbaijan

Site Number Description Classification

Hydromet Offices - 2 nd floor balcony, overlooking road in central IntermediateBaku

2 Old Inner Citv - on wall of carpet shop, next to quiet road IntermediateBackground

3 Observation Post. in residential area in SW Baku (near new Backgroundmosque)

4 Observation post, Hydromet boatyard Background

5 Apartment, 2 nd floor, Nizami district IntermediateBackground

6 Observation post, N Baku. 15 metres from centre of road (location Intermediatefor portable analysers)

7 Observation post, Credolan suburb Background

8 Apartment 5th floor. black city Background

_ 9 Apartment, 4th floor, 8th micro district Background10 Observation post, Montin district Intermediate

11 Apartment, I 1 th floor. Montin district Background12 Observation post, Babek Avenue Background

13 Observation post, 8th kilometre Background

14 Apartment 2nd floor, Guneshli district Background15 Hydromet Laboratory Intermediate16 Apartment, Airport Road, city limits Background17 Apartment on busy road junction (near Mill Bank) Intermediate18 Crescent Beach Hotel Roadside Roadside19 Crescent Beach Hotel Tennis Courts Background20 Boulevard. in the middle of the Christmas Tree roundabout Roadside

35


Monitoring Locations in Tashkent, Uzbekistan

Site Nunmber Description Classification

Station 1, Hydromet Offices Background2 Station 6, near to Tractor factory Background

3 Station 2, 50 metres from road, next to cafe Background

4 Station 14. residential area Background5 Station 15, 30 metres from busy crossroad. Location of portable Intermediate

analysers

6 Station 4, Residential Area, 75 metres from road Background7 Station 8, residential area. Site overgrown with trees Background8 Station 12, residential area. Site overgrown with trees and vines Background9 Station 19, TV station aerial Background10 Station 20, Residential area approximately 100 metres from road. Background

Site overgrown with trees11 Traffic lights, Metro Terminal Roadside12 Hippodrome - Car park entrance Roadside /

Intermediate13 Automobile Market - Car park entrance Roadside /

Intermediate14 Sergeli - residential area Background15 Sergeli - near cement works Intermediate16 Kuyluk - Next to entrance to market car park Roadside /

Intermediate

17 Kubyshev highway, on window of automobile shop. Intermediateapproximately 20 metres from road

18 Cafe, Severo-Vostok district, approximately 1 0 metres from road Intermediate19 Ground floor apartment, Unosabad crossroad, approximately 20 Intermediate

metres from roadside20 Shilonzor - Next to small kiosk shop, under dense trees Background

36

Appendices

Site Classification in the UK Automatic Monitoring Networks

In the UK monitoring takes place tit a variety of locations, these incluide: irban "hot-spotsareas affected by vehicle and indutstrial emissions: citv centre pedestrian precincts andresidential areas representative of population exposure: parks and suburban areas.

Below is the site classification scheme which is used in the national automatic networks, in orderto broadly categorise sites according to their location. In addition, more detailed definitions ofeach site classification are also provided.

Site Type Code

-Kerbside Ul-Roadside U2

URBAN Centre U3-Background U4

Industrial U5

SUBURBAN SU

RURAL RI

REMOTE R2

"SPECIAL" SP

Site Classification System Used in the UK National Automatic Networks

Definitions of each site type, as well as major source influences and pollutants likely to be ofmost importance, are given below for each category. Most sites in the AUN are classed U4(Urban Background) or U3 (Urban Centre) whilst sites in the Rural Network are classed RI(Rural) or R2 (Remote).

Although not currently forming part of national monitoring programmes, a "special" source-oriented site category has been included which covers monitoring undertaken in relation tospecific emission sources such as power stations, garages, car parks or airports.

Definition Of Site Classes

Kerbside (U1)

A site sampling within Im of the edge of a busy road.

Sources Influences Local traffic

37


Pollutants NO2,. VOCs (volatile organic compounds), PM 0,. CO. SO2

Examples of Objectives Identifying vehicle pollution "hotpots"Assessing worst case scenariosEvaluating impacts of vehicle emission control technologiesDetermining impacts of traffic planning/calming schemes

Roadside (U2)

A site sampling between 1 m of the kerbside of a busy road and the back of the pavement.Typically this will be within 5 m of the road, with a sampling height of 2-3 m.

Sources Influences Local traffic

Pollutants NO,, VOCs, PM,o, CO, S02

Examples of Objectives Assessing worst case population exposureEvaluating impacts of vehicle emission controlsDetermining impacts of traffic planning/calming schemes

Urban Centre (U3)

A non-kerbside site, located in an area representative of typical population exposure in town orcity centres (e.g., pedestrian precincts and shopping areas). This is likely to be stronglyinfluenced by vehicle emissions, as well as other general urban sources of pollution. Sampling ator near breathing-zone heights will be applicable.

Sources Influences Vehicles, commercial, space heating

Pollutants NO2, VOCs, PM10, CO, S02, 03

Examples of Objectives Identification of long-term urban trendsExposure assessment of large numbers of people

Urban-Background (U4)

An urban location distanced from sources and therefore broadly representative of city-widebackground conditions, e.g., elevated locations, parks and urban residential areas.

Sources Influences Vehicles, commercial, space heating

Pollutants NO2, VOCs, PM10, CO. S0 2, 03

Examples of Objectives Assessing exposure of large numbers of peopleTrend analysisUrban planningTraffic and land-use planning

Urban Industrial (U5)

An area where industrial sources make an important contribution to the total pollution burden.

38

Appendices

Sources Influences Industrial, motor vehicles

Pollutants NO2, VOCs, PM10, CO, SO2 . process emissions

Examples of Objectives Assessing local impacts on health and amenityProcess optimisationSource attribution/identificationProviding model input dataModel development/validationLocal planning and plant authorisation

Suburban (SU)

A location type situated in a residential area on the outskirts of a town or city.

Sources Influences Traffic, commercial, space heating, regional transport, urban plumedownwind of city

Pollutants NO2 , VOCs, PM10, CO, SO2, 03

Examples of Objectives Assessing exposure of large numbers of people to elevated 03

levelsTraffic and land-use planningInvestigating urban plumes

Rural (R1)

An open country location, in an area of low population density, distanced as far as possible fromroads, populated and industrial areas.

Sources Influences Regional long-range transport, urban plume

Pollutants NO2, S02, 03, ammonia (NH3 ). acid deposition, sulphate (SO42)and nitrate (NO3-) aerosol

Examples of Objectives Ecosystem impact studiesAssessing compliance with Critical Loads and Levels for crops andvegetationInvestigating regional and long-range transportIdentification of ozone "hotspots"

Remote (R2)

A site in open country. located in an isolated rural area experiencing regional backgroundpollutant levels for much of the time.

Sources Influences Regional/hemispheric background, long-range transport

Pollutants O, peroxyacetylnitrate, chlorofluorocarbons; also backgroundlevels of urban pollutants such as NO2, VOCs, PMlo

39


Examples of Objectives Assessing "unpolluted" global or hemispheric backgroundconditionsLong-range transport studiesLong-term baseline trend analysis

"Special" (SP)

A special source-oriented category covering monitoring studies undertaken in relation to specificemission sources such as power stations, garages, car parks or airports.

40

Appendices

Appendix 2 International Air Quality Guidelines and Standards

National and International Ambient Air Quality Guidelines and Standards for NO2, SO2, 03, CO,Benzene, 1,3-Butadiene, PM1o and Lead

Nitrogen Dioxide

Guideline Set By Descriptio ] Crteria Based On | Value / ppb (pgm- )

LIK Government LOW Ai Pollitioni - 150 (287)DETR' MODERATE Air Pollitioni 1-hoatr meani 150 - 299 1287 - 572)

-Air Pollution Bandings HIGH Air PolLitioni 300 - 399 573 - 763 iV HIGH Air Pollution -400 (764)

- UK Air Quality Strategy'2- Objective for 2005 1 -hour nean 150 (287)Objective for 2005 Aiusiial meani 21 (40)

Staindard I-horu mean 150 1287)Staindard Annual meals 1 (401

Calendar year of data.European Communitv) Limit Value 98%ile of hoUrly meaiis. 104.6 (200)

Guilde Valiue 98%oile of hourly meanis 70 6 (135)Guide Valie 50e Ale of hourly meanis 26 2 (50)

Daughter Directive Limit Valie I bour mean 105 (200)not to be exceeded more than

18 times per calendar yearLimit Value Calendar year annual meai 21 (40)Limit Value Calendar year amusial mean 16 (30)

World Health Organisation Health Gudeline I-houir mean 110 (200)(Revised Guidelines in press) Health Gutidehine Aniual mean 21 (40)

LUnited Nations Economic Vegetation Guideline Alinual meani 15 (29)Commission for Europe

41


Sulphur Dioxide

GLuideline Set By Description Criteria Based On Value / ppb (pgtl

tL[ Government LOW Air Pollution < 100 (266)DETR ' Air Pollution MODERATE Air Polltition 15-miLute meani 100 - 199 (266 - 531)

Bandings HIGH Air Polltition 200 - 399 (532 - 1063)V HIGH Air Pollution >= 400 (1064)

- [K Air Quality Strategy,2' Objective for 2005 99.9 %ile of 100 (266)1 5-m1i1tite mleanlS

Standard I -minilute meani 100 (266)

European Community") Limit Value Pollution Year 30 (80) if smoke'5' > 34(mediani of daily values) 45 (120)if sm. <= 34

Limit Valie Whiter 49 (130)if sin. - 51(median of daily valuies Oct- 68 (180if sm. <- 51

Limit Value'61 Mar) 94 (250)ifsin > 128Pollution Year 131 (350)ifsm. < 128

Gtuide Valtue (98%ile of daily valtues) 15 - 23 (40 - 60)Pollutionl Year

Guide Valie (meani of daily values) 38 - 56 (100 - 150)24 HoLurs

Daughter Directive Limit Value (daily mean value) 132 (350)not to be exceeded more thani

I hotir mealt 24 tines per calendar yearLimit Valuie 47 (125)

24 houirs (daily mean) not to be exceeded more than 3times per calenldar year

Limit Value 8 (20)Calendar year aniaiial mean

Limit Value 8 (20)Winter mean

World Health Organisation Health Guideline 1 0-minute meani 175 (500)(Revised Guidelines in press) Health Guideline 24-hour mean 44 (125)

Health Guideline AnIlial Mean 17 (50)

United Nations Economic Vegetation Guideline Daily meani 26 (70)Commission for Europe Vegetation Guideliime Anmual mean 7.5 (20)

"DETR = Departnenit of the Eaiviromtnent. Transport and the Regions'2'The United Kingdom National Air Qtualitx Strategy. Cm 3587. March 1997. ISBN 0 10 135872 5(3) Couniicil Directive 85/203/EEC(4) Counzcil Directive 80/779/EEC(5)Lonits for black smoke are giveni in IgmT' for the BSI method as Lised in the United Kingdom.The limits stated it the EC Directive relate to the OECD method, where OECD = BSI / 0 85.

''Member states maist take all appropriate steps to enisure that thiree consectitive days do not exceed this limit value.

42

Appendices

Ozone

Guildeline Set By Description Criteria Based On Value , ppb (pgmi)

UlK Government LOW Air Polilitioni Ruiiiuiig 8-houir aid I -hour - 50 m100)- DETR ' Air Pollution MODERATE Air Pollutioni ineani 50 - 89 1100 - 179 i

Bandings HIGH Air Polilition Runmtite 8-lhour or -hoir neast 90- 179 i180- 359)V HIGH Air Polltimois I-hotir mean -=180 1360)

I -houir meats

- UK Air Quality Strategymi Objective for 2005 50 (100)97th °oile of dailh miaxinnuI

Staidard ruilllllg 8-hour means 50 (100)Ruinimllg 8-houir nean

European Community' POpiilatioit liifonnationl 1-hoir meani 90 (180iThreshold

I -hotir mean 180 (360)Population Warming ValLue

Fixed 8-hoLr meanis 55 (110)Health Protectioni Tlueshold (houirs 1-8. 9-16. 17-0, 13-20)

I-hour meani 100 (200)Vegetatiois Protectioms

Thresliold 24 hoLurs (daily mIean) 32 1651

Vegetationi ProtectioisThreshold

World Health Organisation Health Guideline Running 8-houir mean 60 (120)(Revised Guidelines in press)

United Nations Economic Vegetatioii Guidelmine Growving Season'9 imeaD 25 (50)Commission for Europe Vegetation Giadelihe I -hour meats 75 (150)

Vegetatiois Giiideline Running 8-hour meats 30 (60)

51 7 1 C 10 I -Y21 IC

Growinig season is defiued as April to September for WHO guidelines, bLit is daytime 10900-1500) April to September for UNECE guidelines

43


Carbon Monoxide

Guideliie Set By Description Critera Based On Value / ppm (mgin)

UK Government LOW Air Pollution < 10 (11,6)- DETR"I Air Pollution MODERATE Air Pollition Ruinining 8-lhouir meani 10 - 14.9 (11.6 - 17.4)

Bandings HIGH Air Pollitioni 15 - 19.9 (17.5 - 231)V HIGH Air Polilition - 20 (23.2)

- LiK Air QualitY Strategy2' Objective for 2005 Runniiing 8-liotir ineati 1 0 (11,6)Stanidard Ruitniig 8-hour meati 10 (11 6)

European Community .

World Health Organisation Health Guiideline 15-miuIte mean 90 (100)(Revised Guidelines in press) Health Gutideline 30-minite meani 50 (60)

Healthi GuLideline I-houir meani 25 (30)Healthi Gulideline 8-hour meani 10 (10)

United Nations EconomicCommission for Europe

Benzene

Guidesine Set Bv Des-nption Criteria Based On Value ppb

tIh; Government4-DETRW " Air Pollution

Bindings

- UliAir QualityStrategy"'1 Objective for 2005 Rulnming anmoal meanl 5. ~~~~~~~~~Standard Rtijining anm1ual meain 5

Target Rliilming animial mTean I

European C ommunityv

World Health Organisation

United Nations EconomicComnmission for Europe

44

Appendices

I .3-Butadiene

Guiideliine Set By Descriptioii Cln ena Based Oii Valuei ppb

LIK Government- DETR Air Pollution

Bandings

- tik Air Quality Strategys2' Objective for 2005 Running anllLnal meanStanidard Rninii,iig annuiltal mean

European Communit)

WVorld Health Organisation

Linited Nations EconomicCommission for Europe

PMio

Guideline Set By Description { Cnteria Based On 1 Value (qggt )

IIK Government LOW Air Pollution < 50- DETR' Air Pollution MODERATE Air Pollution Rtiaiting 24-houir ineani 50 - 74

Bandings HIGH Air Pollutioni 75 - 99V HIGH Air Pollution - 100

- IiK Air Quality Str4tegy12) Objective for 2005 99th e oile of daily inaxmiuni 50

niniiiig 24-holr ineaiisStandard Ruining 24-houir meani 50

European Community Limit Value 24 houirs (daily meani) 50Daughter Directive not to be exceeded more than

35 times per calendam vearLimnit Valie Calendar year aniniuial meaii 40

VA orld Health Organisation -

United Nations EconomicCommission for Europe

45


Lead

Gtuideliine Set Bv | Description Criteia Based Oni Value / (igpm-)

[1K Government- DETR 'r Air Pollution

Bandings

- [L Air Qualitv Strategy2 ' Objective for 2005 Annulal meani 0.5|Standard Ailnial mean_

European Community"' Limit Value Anmual mean) 2

Daughter Directive Limit Valuie Annial mean 05

World Health Organisation Healtih Gulideline Aniual mean 0.5(Revised Guidelines in press)

[;nited Nations EconomicCommission for Europe -

(9) CoLiuicil Directive 82/884/EEC

46

Appendices

Appendix 3 Nitrogen Dioxide Diffusion Tube Samplers

The development and use of passive samplers originated in the field of occupational exposuremonitoring. However, in recent years, diffusion sampling techniques have been further developedand tested for ambient air quality monitoring, where concentrations are generally much lower.NO2 diffusion samplers are designed either as a badge, or tube configuration. In this study,diffusion tube samplers are used. These consist of a small plastic tube, approximately 7centimetres (cm) long. During sampling, one end is open and the other closed. The closed endcontains an absorbent for the gaseous species to be monitored, in this case NO2.

Diffusion tube samplers operate on the principle of molecular diffusion, with molecules of a gasdiffusing from a region of high concentration (open end of the sampler) to a region of lowconcentration (absorbent end of the sampler). The movement of molecules of gas (1) through gas(2) is described by Fick's law, which states that the flux is proportional to the concentrationgradient:

J jD2 dCdC

where J = the flux of gas (1) through gas (2) across unit area in the z-directionC = the concentration of gas (1) in gas (2)z = the length of the diffusion pathD1 2 = the constant of proportionality-the molecular diffusion constant of gas

(1) in gas (2)-with dimensions of length2 time-'.

For a tube of area a (m2 ) and length I (m), Q (moles), the quantity of gas transferred along thetube in t (seconds), is given by:

0=D,, (C -C,) a t

where Co and C 1 are the gas concentrations at either end of the tube.

In a diffusion tube, the concentration of gas (1) is maintained at zero (by an efficient absorbent)at one end of the tube (i.e., Co = zero) and the concentration C 1 is the average concentration ofthe gas (1) at the open end of the tube over the period of exposure. Hence:

0l1C= QlDI, at

where Q = the quantity of the gas absorbed over the period of exposurea = the cross sectional area of the tubet = the time of exposureI = the length of the tube

47

Cleaner Transportation Fuels for Urban Air Qualitv Management

For the gas monitored. the diffusion coefficient must be determined, or obtained from theliterature. The area and length of the tube are determined by measurement.

Triethanolamine (TEA) has been shown to be a suitable NO2 absorber for use in diffusion tubes.Stainless steel mesh discs are coated with the absorber by either dipping into a solution of TEAand acetone or pipetting a small quantity of the aqueous solution onto the disc in the assembledtube. This must be done in a clean atmosphere to ensure minimal contamination due toatmospheric NO2 . The impregnated mesh discs are held at the closed end of the tube. The openend of the tube is sealed and the tube stored prior to exposure.

For monitoring, the end cap not containing the mesh discs is removed and the tube mountedvertically with the open end at the bottom. NO2 is absorbed as nitrite and after exposure, thelower end cap is replaced and the tubes sent for chemical analysis.

For the purpose of the network, the tubes must be analysed by standard colorimetric orspectrophotometric techniques. This generally involves the addition of a solution ofsulphanilamide in orthophosphoric acid and naphthyl ethylene diamine dihydrochloride solution,to form an azo dye, the intensity of which is determined on a spectrometer at 540 nm. Thespectrometer is calibrated against standard nitrite solutions, to allow the total NO2 as nitrite,collected by the tube, to be determined. If required, the method can be automated for a largethroughput of samples.

48

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