Developing database criteria for the assessment of biomass supply chains for biorefinery

development.

M. J. Black1, J. Sadhukhan1*, Kenneth Day2, Geoffrey Drage2 and R. J. Murphy1.

1Centre for Environmental Strategy, University of Surrey, Guildford, GU2 7XH, UK.

2Bio-Sep Ltd. Clapton Revel, Wooburn Moor, Buckinghamshire, HP10 0NP, UK.

Abstract

The sustainable biorefinery will only be realised with a focus on optimal combinations of feedstock-

process technologies-products. For many years, industry has been looking to add value to the by-

products of commercial agriculture, forestry and processing. More recently, as concerns about

climate change have increased around the globe, the use of biomass as a carbon saving feedstock

(compared to fossil feedstock) has led to the implementation of policies to encourage its use for

bioenergy, biofuels and bio-based products. As biomass conversion technologies become reality at

the commercial scale for a range of diverse end products, the need to establish bespoke biomass

supply chains also becomes a reality and industrial developers will face many business-critical

decisions on the sourcing of biomass and location of conversion plants (biorefineries). The research

presented here, aims to address these issues through the development of a comprehensive

database to aid biomass sourcing and conversion decision-making. The database covers origin,

logistics, technical suitability (in this case for a proprietary organosolv pre-treatment process) and

policy and other risk attributes of the system. The development of key criteria required by the

business community to develop biomass supply chains for specific requirements is discussed.

Keywords: biorefinery, biomass characterisation, biomass supply chain, bioenergy, biomass

database

*Corresponding author: Email: j.sadhukhan@surrey.ac.uk; phone: +44 1483 686642

1. Introduction

Demand for food and biomass1 is likely to increase dramatically in the coming years, as the result of

increased requirement for food, energy and material from a global population of 9.1 billion by 2050.

It is expected that 70% more food and feed will be will be required, with further demands for

biomass for bioenergy and biomaterials, to reduce dependency on fossil feedstock for fuel and

materials, and to reduce greenhouse gas (GHG) emissions to counter climate change effects

(European Commission, 2012). Each of these demands will increase pressure on land and water

resources, with the potential for hugely detrimental effects on land productivity, de-forestation and

biodiversity. In planning policies to address these issues, clearly there is a need to address each of

these within a particular policy sector, whilst developing a strategy for the integration of

interconnected policies, which relate to the management of biological resources. In the European

Union, a strategy and action plan has been developed under the ‘Strategy for “Innovating for

Sustainable Growth: A Bioeconomy2 for Europe” (European Commission, 2012). The bioeconomy, as

defined by the European Commission covers food, energy, forestry, agriculture, marine and chemical

industries and the development of the biorefinery is a key component of this strategy. The

biorefinery concept also addresses components of European Commission policies on climate change

(European Commission, 2008); resource efficiency and waste (European Commission, 2008); and

innovation and competitiveness (European Commission, 2007).

The biorefinery can be defined in several ways taking into account multiple types of biomass-based

inputs e.g. oils, starches, lignocelluloses; potentially multiple conversion technologies e.g.

biochemical, thermochemical, sonochemical; producing multiple product streams (NNFCC, 2007).

For the purposes of this paper, the definition given by the US National Renewable Energy Laboratory

is used to describe the concept i.e. ‘a biorefinery is a facility that integrates biomass conversion

processes and equipment to produce fuels, power, and chemicals from biomass. The biorefinery

concept is analogous to today’s petroleum refineries, which produce multiple fuels and products

from petroleum’ according to the NREL (2009). "In the most advanced sense, a biorefinery is a

facility with integrated, efficient and flexible conversion of biomass feedstocks, through a

combination of physical, chemical, biochemical and thermochemical processes, into multiple

products. The concept was developed by analogy to the complex crude oil refineries adopting the

1 Biomass is written in this paper as a generic term for agricultural and forest derived biological material used as feedstock for bioenergy, biofuels and biomaterials.2 The bioeconomy as defined by the European Commission encompasses the sustainable production of renewable resources from land, fisheries and aquaculture environments and their conversion to food, feed, fibre, biobased products and bioenergy as well as the related public goods. The bioeconomy includes primary production, such as agriculture, forestry, fisheries and aquaculture and industries using/processing biological resources, such as the food and pulp and paper industries and parts of the chemical, biotechnical and energy industries.

process engineering principles applied in their designs, such as feedstock fractionation, multiple

value-added productions, process flexibility and integration." (Sadhukhan et al., 2014) The term

biorefinery can be used to describe the conversion of biomass via one pathway or many and may

also take into account several pre- and post- processing treatments before end products are

achieved. Consideration of the many processes which could be applied to the conversion of biomass

and the importance of the techno-economic evaluation of conversion processes, has led to the

development of a whole new discipline of chemical engineering and modelling (Sadhukhan et al.,

2014).

As this industry has been developing, modelling of biomass supply chains has been concerned with

addressing inputs associated with the growing, transport and conversion of biomass to allow GHG

Life Cycle Assessment (LCA) and sustainability assessment, to address specific policy mechanisms

(see section 1.1) however, as large scale biomass conversion has become a reality, biomass Value

Chain Assessment (VCA) for economic sustainability is more often being carried out for specific

circumstances, requiring specific data inputs (IEA Bioenergy, 2013).

This paper describes the development of a knowledge and data system to structure and output

information about biomass sourcing, composition and availability, and the key factors which may

impact on biomass suitability, cost and availability. The database is intended to supply VCA models

with data for diverse supply chains globally, as well as be a stand-alone biomass informational

database for other uses. A case study is also reported for the availability of bagasse in key sugarcane

growing countries and the availability and accessibility of data is summarised.

2. Methodology: Database development

Recent years have seen the development of many innovative technologies with potential for the

conversion of biomass in a biorefinery. Whilst many of these have not yet moved beyond the bench-

scale, it is necessary for organisations aiming to commercialise technology to gain a full

understanding of their biomass of choice, geographic source, local logistical consideration, storage

requirements, process plant location and distribution of end product (to final market or to secondary

processing). This has led to many new and increasingly complex value chain models which aim to

inform the commercialisation process however, many data points are based on assumptions and

require ‘real’ data to populate them. In the development of this database, a clean fractionation

process for biomass, which provides cellulose, hemicellulose, sugars and lignin for further biorefining

to high value chemicals and biofuels, has been used as a test value chain to inform the structure of

the database (Bio-Sep Ltd, 2009; 2014).

Figure 1. VCM for a lignocellulosic supply chain (Bussemaker, 2015).

Bussemaker (2015) has developed a techno-economic model for this technology, which is structured

to consider multiple scenarios based on source/locational of biomass, pre-processing, processing

and end product market location, considering transport options for supply chains based on forestry

feedstock and processing facilities based in Scotland (Figure 1). Value chain models have also been

developed by other authors, to address bioenergy value chains in the UK from similar forestry and

agricultural biomass feedstock base e.g. the Bioenergy Value Chain Model (Energy Technologies

Institute, 2014).

A business interface questionnaire was developed, following an approach taken by Slade and Bauen

(2009) to address the opinions and priorities of industry and academic personnel, who might be

considered to be database users in the future, to establish what information is of value and to

prioritise other information which might influence supply chain development for a given technology,

in a given region, for sale in a given market. Figure 2 illustrates the database navigation tool

customised for users. Semi-formal interviews were carried out using the questionnaire, to develop

the structure of the database to complement the numeric data required for the VCM.

Knowledge Structure Mapping of biomass feedstock was set up to consider potential biomass supply

chains from raw material to end product via the conversion process as a standalone facility, or via

the process attached to an existing primary processing facility (e.g. pulping mill). The database has

also been structured so that biomass compositional analysis can also be directed to techno-

economic evaluation of a range of fractionation technologies, such as mechanical and physical or

combinations of the two (e.g. extrusion), chemical (acid hydrolysis, alkali treatment, organosolv,

steam explosion, hydrothermal, microwave, ultrasonication) and biochemical (enzymatic hydrolysis)

processes to recover products (Sadhukhan et al, 2014).

The database was set up to consider a ‘processing facility’ located in regions of biomass availability

or allowing for feedstock transport, to a facility out-with a biomass growing region. The database

was then divided into sections, to correspond to the data requirements of the VCM, and responses

from the business interface questionnaire, addressing:-

Feedstock

- characteristics: chemical composition and density; local agro-processing industries

yielding agri/forestry industry residue by-products e.g. sawmill residues, sugarcane

bagasse, oil palm field and processing residues

- quantity: based on existing industries and potential for competition with competing

industries e.g. bioelectricity; next generation biofuels

- seasonal availability: based on harvest times in ‘local’ regions

Logistics (transport, storage and handling): based on existing industries and infrastructures

available; types of transport available and practicality of transport distances for low density

biomass material

Conversion: primary focus on clean fractionation technology application; the database

structure also allows for development of a wider range of biorefinery processes

Policy Mechanisms: policies have been developed in many countries to address climate

change; greenhouse gas emission reduction; agricultural productivity; environmental

protection and sustainability. Some of these actively support the development of renewable

energies based on biomass feedstock e.g. bioelectricity; biofuels. These may be positive in

establishing new technologies/industry around biomass use but may also lead to

competitive industries and limitations to biomass use or a requirement for reporting

greenhouse gas (GHG) emissions and sustainability. The database has been developed to

highlight this information to inform commercial decision making.

Cost: basic feedstock cost, handling and pre-processing

It is understood that these criteria are likely to vary in time however the value to the user is to be

able to link the criteria to a VCM to assess variations and fluctuations in e.g. cost of biomass or cost

of transport.

Figure 2. Database navigation tool for stakeholders across supply chains.

Supply chains were considered addressing feedstock; logistics; conversion options (with a focus on

the specific clean fractionation technology for the following countries/regions: United Kingdom and

European Union; United States of America; Canada; Brazil; Australia; New Zealand; India; Indonesia;

China; Russia and the Eurasian States.

Case studies were carried out for different biomass types and sources, to assess data sources

available and to populate the database. The case study for sugarcane bagasse from Brazil is reported

here. Data searching and the availability of data was a key component of the work carried out and

limitations were placed on data collection where information was not available without monetary

charge. Data was used where available from peer reviewed academic literature, policy documents

and recognised industry reports.

The database was structured using Microsoft Access to allow better accessibility with the VCM and

better usability for database users.

2.1 Database structure

Following the requirements of the VCM and the results of the business interface questionnaire, the

following criteria were established as key searchable terms:

Biomass Type: describes the simplest differentiation of biomass recognised in many data sources i.e.

softwood, hardwood, agri-residue, energy crop

Market Name: the next level of differentiation of biomass based on the ‘common names’ of plants in

the biomass market place e.g. pine, oak, straw, miscanthus

Species Name: describes specific differentiation of biomass material by species or Latin name e.g.

Pinus sylvestris L.

Biomass Form: describes the form in which the biomass might be bought in the market place e.g saw

log, tops and branches, chips, bales.

Country Source: Describes the country from which the biomass might be bought, or the location

where processing facilities might be established.

These criteria were considered the most important in terms of identification of feedstock, sourcing

and location of feedstock (or process facility), to allow key data points such as composition, form,

cost etc to be extracted form the database for techno-economic analysis, and allow qualitative data

to be included as a reference source for business decisions making.

The database structure was established and the user interface is shown in Figure 2.

The database can then be searched to find information on biomass cost; biomass composition in

term of cellulose, hemicellulose and lignin composition; storage options; milling and pre-processing

options; transport options; processing technology options and end product options. Seasonality is

also described for biomass as part of composition (see section 3.2). The database also provides links

to country specific policies for renewable energy, climate change, and forestry and agriculture.

2.2 Feedstock characteristics and conversion technology

Physical and chemical characteristics of feedstock play a key role in the efficiency and outcomes of

biomass processing and conversion, as well as having an impact on logistical costs and pre-

processing requirements such as drying. The chemical composition of biomass is very

heterogeneous, affected not only by distinction between softwood, hardwood, agri-residue and

energy crop but also by species, geographic location, aspect, climate, plantation/field management,

time of harvest, and pest and disease impacts. In reviewing academic and trade literature for

information on biomass composition it became apparent that:

1. A large body of work exists for forestry and wood products industries. Historic and current

literature considers the physical and chemical aspects of woody biomass with a view to use

for the pulp and paper industry (or physical properties for the use of timber in the building

industry). The key factor for paper production is cellulose content and cellulose accessibility

based on the requirement to remove hemicellulose and lignin (without necessarily

considering the finer details of the hemicellulose and lignin components).

2. More recently, technical specifications have been developed for biomass for the pellet

industry (e.g. En-Plus certification includes some specific chemical requirements for

moisture content, ash content, nitrogen content, sulphur and chlorine content (European

Pellet Council, 2013).

3. Glucose content of biomass and that which can then be made available through release by

pre-processing of feedstock using a particular technology is considered an important criteria

for the production of lignocellulosic ethanol, however the physical interaction or gross

structure of cellulose, hemicellulose and lignin is also a factor influencing ethanol

productivity.

4. Several methods of analysis for the chemical composition of biomass exist but currently

there is no globally used methodology. NREL (2011) have developed a standardised

approach which has been used by different laboratories but not universally. Establishing

biomass compositional analysis to this degree of accuracy is costly and running times for

analysis is lengthy. For the purposes of modelling work, using a range of cellulose,

hemicellulose and lignin may be the simplest option to assess outcomes but may not reflect

the best way to ‘source’ biomass.

5. Species nomenclature has evolved over time so that some historical references to tree

species may not reflect species nomenclature today.

Current analytical methodologies used for biomass assessment for cellulose, hemicellulose and

component sugar analysis can lead to very different compositional analysis results between

feedstock types from the same source. Often biomass is simply described by a range given for the

component polymers i.e. cellulose, hemicellulose and lignin, with the general description of variation

between hemicellulose polysaccharides as being predominantly glucuronoxylan for hardwood, with

some glucomannan depending on wood species and predominantly galactoglucomannan for

softwood, with varying proportions of arabinoglucuronoxylan and arabinogalactan, depending on

species. In grasses and cereals, hemicelluloses with a xylan backbone predominate, making up to

50% of the biomass composition in some tissues. In the database where specific analytical

compositions have not been found in recent literature, the generic description is given. It is the

intention that the database would be updated as more specific compositional analysis is sourced in

literature or becomes available as biomass compositional assessment progresses. Table 1 gives

cellulose, hemicellulose and lignin content of a range of biomass feedstocks relevant for the

proprietary organosolv pre-treatment process.

Table 1 Generic cellulose, hemicellulose and lignin content of biomass (% dry weight) (Sun and

Cheng, 2002; Prasad et al., 2007; Sanchez and Cardona, 2009).

Raw Material Cellulose Hemicelluloses Lignin

Woody biomass

hardwood 40-55 24-40 18-25

softwood 45-50 25-35 25-35

Agri residues

corn cobs 45 35 15

wheat straw 29-35 26-32 16-21

barley straw 31-34 24-29 14-15

oat straw 31-37 24-29 14-15

rye straw 33-35 27-30 16-19

rice straw 32.1 24 18

sugarcane bagasse 32-34 27-32 19.24

nut shells 25-30 25-30 30-40

Energy crops

grasses 25-40 25-50 10-30

bamboo 26-43 15-26 21-31

switch grass 45 31.4 12

elephant grass 22 24 23.9

‘Waste’

banana waste 13.2 14.8 14

paper 0-15

waste papers from

chemical pulp

60-70 10-20 5-10

newspaper 40-55 25-40 18-30

primary wastewater

solids

8-15 n.a. 24-29

swine waste 6 28 n.a.

solid cattle manure 1.6-4.7 1.4-3.3 2.7-5.7

For the purposes of this work, the database was set up to allow description of biomass composition

by range of cellulose, hemicellulose, lignin compositions or by species specific analysis where a

recognised analytical methodology has been used e.g. the NREL methodology.

2.3 Biomass sourcing

Data on the availability of biomass for Austria, Brazil, Canada, Denmark, Finland, Germany, Italy,

Norway, Sweden, United Kingdom, United States, Australia and New Zealand and South-East Asia

have been taken from IEA Bioenergy Task 40 reports. National Forest Inventories have also been

used as data sources for woody biomass availability and Food and Agriculture Association data has

been used to estimate agri-residue availability (FAO, 2010). Many countries have already made maps

publically available which describe biomass availability (NREL Biomass Maps, 2012) and allow

interactive calculations to be made for delivered cost for specific biomass to specific sites according

to the Biomass Market Watch. Complete assessments of agri-residue availability are less easy to

access as historically statistical data has not been kept for by-products of the primary industry i.e.

food production. Assumptions have been made using the FAOSTAT data for agricultural crops based

on assumptions made of the % component of agricultural crops that would be considered field or

process residue and which could be removed without adverse effects on soil fertility. There is also a

handful of literature on biomass potentials in advanced biofuel production (Hamelinck and Faaij,

2006).

2.4 Policy and policy impacts on biomass availability and price in the future

Biomass is a common component within the EU Bioeconomy, with cross-over into renewable energy

and climate change policies. The Renewable Energy Directive (RED) (European Commission, 2009)

sets out targets for the replacement of fossil fuels by 2020 and each member state has developed a

National Renewable Energy Action Plan (NREAP) which defines how renewables targets will be met.

Liquid biofuels for transport are expected to report on life cycle GHG emissions for specific biofuel

supply chains under the Fuels Quality Directive (FQD) (European Commission, 2009) and under the

RED, biomass must report specific sustainability characteristics relating to land use. A

comprehensive account of biomass and bioenergy policies, industry specific policies supporting the

sustainable production of food and biomass (agriculture, forestry, marine), as well as funding

mechanisms to support the development of the bioeconomy in Europe has been published by

Scarlat et al. (2015). The impact of the 27 EU member states NREAPS on biomass demand has been

reviewed by Van Stralen et al. (2012), for specific targets to 2020 and extending targets to 2030,

under different scenarios for electricity, heat and transport, and taking into consideration the

application of stricter sustainability criteria in time.

Commodities which support the bioeconomy are globally traded, from primary feedstock such as

grain and oilseed to secondary products such as biodiesel and bioethanol or wood pellets and wood

chips for bioenergy. Reducing dependency on fossil fuels is a global ambition, as fossil fuel prices

fluctuate and concerns about climate change remain high on the global political agenda (at the time

of writing, the 21st Session of the Conference of the Parties of the United Nations Framework

Convention on Climate Change (COP21/CMP11) is anticipated (http://www.cop21.gouv.fr/en/cop21-

cmp11/what-cop)). According to the International Renewable Energy Agency (IRENA, 2015), 154

countries have set renewable energy targets as of mid-2015, however, these are not easily

quantifiable in terms of impact on biomass demand and availability as renewable targets may be

non-binding, not necessarily technology specific (i.e. targets aimed at solar, wind hydropower,

geothermal, bioenergy) and not necessarily sector specific (e.g. target aimed at the electricity,

heating/cooling or transport sectors). A further report from IRENA (2015) gives details of renewable

energy capacities for member countries up to 2014. Renewable energy policy mechanisms, country

specific biomass resource, existing access to energy infrastructure and transport infrastructure may

have a great impact on locally available biomass and price. Furthermore, sourcing and

demonstration of the sustainability of biomass/biofuels for European markets is a pre-requisite to

their use under the RED, and for forest products (including those which may be used for the

production of bioenergy i.e. wood pellets) under the EU Timber Regulation (European Commission,

2010), adding to the costs and potential risks associated with establishing biomass supply chains. In

future, as the EU Bioeconomy strategy develops, biobased products may also be subject to the same

rigour. Addressing these policies requires country specific knowledge of agricultural and forest

management policies, and their interpretation and implementation, to ensure that biomass resource

use is not exacerbating other environmental conditions which its use was intended to address. The

case study for bagasse from Brazil (section 3.4) highlights how external factors including policy

development can contribute to increased biomass costs.

3 Case study – sugarcane bagasse Brazil

3.1 Sugarcane background

Sugarcane is one of the top 5 global commodity crops (by tonnage), followed by maize, rice, wheat

and potatoes (FAOSTAT, 2012). Grown for the production of sugar (sucrose) for the food industry, it

also has a long history in the production of potable alcohol, as well as increasing importance as a

feedstock for the production of bioenergy (fuel ethanol, heating/cooling and electricity). There are

30-40 sugarcane species which originated from 2 centres of diversity: the Old World (Asia and Africa)

and the New World (North, Central and South America) (Cheavegatti-Gianotto et al., 2011).

Sugarcane is now widely grown commercially in over 90 countries from temperate to tropical

regions, between 35oN and 35oS, with the majority of world production occurring in regions between

22oN and 22oS. Commercial crops have been developed historically from Saccharum offinarum; S.

barberi, S. edule, S. sinense, S. spontaneum and S. robustum and varieties grown today are complex

inter and intra-specifically bred hybrids of S. officinarum (Verheye, 2009). A detailed history of

sugarcane botanical classification and breeding history can be found in Cheavegatti-Gianotto et al.

(2011).

Sugarcane is a semi-perennial crop which can be harvested 10 or more times in succession in 10-24

month cycles, depending on growing conditions and husbandry. Traditionally, sugarcane fields are

burned prior to harvest to remove dry leaves and cane tops, leaving the cane ready for hand harvest.

However, recently there has been a move away from this practice to reduce emissions from burning

and improve efficiency by mechanising harvest.

Growing sugarcane and the process of extracting sugar yields by-products in the form of sugarcane

trash (leaves and cane tops left behind in the field by mechanized harvest), and bagasse, molasses

and filtercake (as process residues).

3. 2 Sugarcane bagasse and trash availability

Commercial sugarcane has been bred for high productivity, high sucrose and low fibre content.

Sugarcane yields per ha vary according to variety, location, husbandry and climate and can vary from

28 tonnes/ha to estimates of over 100 tonnes/ha (FAOSTAT, 2013). 1 tonne of harvested cane is

quoted to yield 240 kg bagasse (Dias et al., 2009) to 300 kg bagasse at 50% wet basis (w.b.) moisture

content (Hofsetz and Silva, 2012), after processing for sugar.

Table 2 gives production estimates from the top 10 sugarcane producing countries and regional

assessments for groups of countries. Bagasse values are estimated based on 270 kg bagasse/tonne

sugarcane but do not consider any other current uses.

Table 2. Sugarcane production by country (FAOSTAT, 2013)3.

Country Area Harvested (ha) Average Yield

(tonne/ha)

Production quantity

(tonnes)

Estimated

bagasse (tonnes)4

Brazil 9 835 169

(9.83 million)

75.16 739 267 042

(739 million)

199 602 101

(199 million)

India 5 060 000

(5 millon)

67.43 341 200 000

(341 million)

92 124 000

(92 million)

China 1 827 300

(1.82 million)

69.02 126 136 000

(126 million)

34 056 720

(34 million)

Thailand 1 321 600

(1.32 million)

75.73 100 096 000

(100 million)

27 025 920

(27 million)

Pakistan 1 128 800

(1.12 million)

56.47 63 749 900

(63 million)

17 212 473

(17 million)

Mexico 782 801 78.15 61 182 077 16 519 160

3 FAOSTAT data is based on aggregated data from official, semi-official, estimated or calculated data4 Estimate based on 270 kg bagasse/tonne sugarcane

(0.78 million) (61 million) (16 million)

Philippines 435 405

(0.43 million)

73.20 31 874 000

(31 million)

8 605 980

(8 million)

United

States

368 588

(0.36 million)

75.71 27 905 943

(27 million)

7 534 604

(7 million)

Australia 329 303

(0.32 million)

82.40 27 136 082

(27 million)

7 326 742

(7 million)

Region

World totals 26 522 734

(26.52 million)

70.77 1 877 105 112

(1.877 billion)

506 818 380

(0.5 billion)

South East

Asia

2 736 305

(2.73 million)

72.43 198 198 400

(198 million)

53 513 568

(53 million)

Africa 1 533 641

(1.53 million)

63.35 99 168 645

(99 million)

26 775 534

(26 million)

Caribbean 540 929

(0.54 million)

42.72 23 111 733

(23 million)

6 240 167

(6 million)

For many years, due to the large volume produced, bagasse has been considered a low value by-

product of the sugar milling process. Traditionally in regions of the world where energy costs are

high, bagasse has been used to fuel the internal power and steam requirements of sugar processing

mills. The efficiency of these systems has been fairly low, as the burners are also seen as a means of

disposal of the bagasse. In recent years, with growing interest in renewable feedstock for bioenergy,

biofuel and biomaterials, bagasse is no longer seen in this light. In countries like Brazil, technical

improvements in the efficiency of power and steam cogeneration, have improved the energy

extraction efficiency for bagasse and, where surplus electricity can be sold on to the grid, it is now

viewed as the second main business after sugar and ethanol production. Other uses of bagasse

include the production of pulp used in paper and packaging, where bagasse is one of the most

important non-wood sources of cellulose. It is estimated that the pulp and paper industry accounts

for 10% of world bagasse production (Guillaume, 2006).

In the case of Brazil, which has the most developed sugar-ethanol processing regime in the world, it

is anticipated that bagasse will no longer be in surplus (Hofsetz and Silva, 2012) as the result of its

potential for the production of bioelectricity. Since the promotion of the use of bagasse for

bioelectricity, under the Brazilian Program of Incentives for Alternative Sources of Electrical Power

2005 according to the World Resources Institute, the use of bagasse has moved from 50% use from

the 1999/2000 sugarcane harvest to a potential 100% use, as it is anticipated that the energy

efficiency of sugar mill turbines will improve to allow surplus bioelectricity to be sold to the grid.

However, the same paper reports that the uptake of new technologies to improve efficiency of

bioelectricity generation is not (yet) wide spread, as many mill owners don’t see the bioelectricity

market as ‘good business’. Future expectations for 1st and 2nd generation bioethanol from sugarcane

are also high, with estimates that second generation ethanol will increase from 7 million tonnes per

year in 2015 to 25.9 million tonnes by 2030 and it is expected that bagasse will be utilized entirely

between these two markets. In Brazil, the sugarcane industry is moving away from in-field burning of

cane prior to harvest, as a means of reducing emissions. It is anticipated that 428 million tonnes of

sugarcane trash will be available by 2020, as the result of improved mechanisation of harvest and

the desire to reduce emissions caused by in-field burning (Bryant and Yassumoto, 2009). This vast

potential source of sugarcane biomass is also expected to feed the sugar mill boilers, freeing up

bagasse for 2nd generation bioethanol production. Figures 3-4 show the maps of sugarcane growing

regions and sugar to ethanol mills, respectively, in Brazil.

Figure 3. Map of sugarcane growing regions in Brazil

(http://www.brazilintl.com/agsectors/sugarcane/map-sugarcane/map-sugarcane.htm)

Figure 4. Sugar/ethanol mills in Brazil (2010); Estudos – under study; Implantacao – under

construction; Operando – operating. (http://www.brazilintl.com/agsectors/sugarcane/map-

sugarcane/map-sugarcane.htm).

3. 3. Bagasse cost

In Brazil, bagasse has long been seen as a problem for the sugar industry as a ‘waste’ which is not

easily disposed of. In recent years however, the value of bagasse has increased as cost and potential

use of bagasse is now influenced by electricity costs. Whilst Brazil has been promoting the use of

biomass for bioenergy, and bioelectricity now accounts for 3-4% of the countries electrical capacity,

in the last 2 years, drought conditions have reduced generation of hydroelectricity. This has led to

increased value of bioelectricity, reflected in the price for bagasse. Bagasse has seen a sharp increase

in costs from R$ 70 —R$ 80 in 2012, to R$120-R$140 in 2014 (UNICA, 2015). As Brazil is also looking

to increase production of lignocellulosic ethanol from bagasse, it is expected in the future that

market fluctuations would influence bioethanol production vs. bioelectricity from bagasse, in the

same way that sugar mills are currently able to flex between the production of sugar or ethanol as

the markets require.

3.4 Logistics costs in the supply chain

Sugarcane is a bulky, low density crop and the cost of transport of sugarcane to mill is a key factor in

locating sugar mills in sugarcane growing areas. Transportation of bagasse will face this same issue,

and in LCA studies of ethanol, it is assumed that a biofuel refinery would be situated beside or

integrated with the sugar mill (Macedo et al., 2004). LCA papers indicate that an average distance for

transport of sugarcane is 20km (Gonzales et al., 2010). It might be assumed that a bagasse

biorefinery would also be situated as close to the sugar mill as possible, as modeled by Seabra et al

(2010).

3.5 Bagasse chemical composition and variation

Sugarcane, like all biomass materials, has composition characteristics which vary by species,

geographic location, growing conditions (i.e. soil), climatic conditions over the growing season and

husbandry. Several compositional analyses paper have been reviewed however, as with woody

biomass, there does not appear to be sufficient correlation to allow specific compositional (sugar)

characteristics to be selected by source. Table 3 gives the results of studies which reviewed variation

between different Brazilian sources of bagasse and slight differences seen by using different

analytical methodologies. The results from specific studies do not always fall within the generic

cellulose, hemicellulose and lignin content of biomass as reported (Sun and Cheng, 2002; Prased et

al., 2007; Sanchez, 2009).

Studies which have analysed the composition of sugarcane trash show that bagasse and the trash

(leaves and tops of sugarcane) left behind in the field show similar variation, some reporting similar

composition (Pippo and Luengo., 2013), whilst others report slight some variation

Table 3 Sugarcane bagasse compositional analyses.

Raw material

source

Cellulose Hemicellulose Lignin source

Literature review 32-34 27-32 19.24 Sun and Cheng, 2002; Prased et

al., 2007; Sanchez, 2009.

Brazil 36-42 22.8-27.3 15.6-22.2 DIBANET database

Brazil 45 25.8 19.1 Canilha et al., 2011 (using

validated Brazillian methodology

for sugarcane)

Brazil 44.9 25.9 19.3 Canilha et al., 2011 (using NREL

methodology)

3.6 Discussion on the availability of ‘surplus’ bagasse

The level of technological development in sugar processing mills is very variable between countries

and within cane producing regions, even in Brazil. As a means of assessing the potential availability

of bagasse for other uses, Pippo and Lungo (2013) have suggested classifying the efficiency of

sugarmill processing into four categories:

1. Very low technological development (VLTD)

2. Low technological development (LTD)

3. State-of-the-art technology

4. Future step of technology development (FSOTD)

These classifications are based on mill parameters such as milling capacity (tonne of cane processed

per day); electrical and mechanical consumption of energy per tonne of cane, efficiency of process

equipment used and energy self-sufficiency based on use of sugarcane bagasse. Mapping sugarmill

parameters to regional sugar cane productivity would go some way to providing more detailed

assessment of ‘surplus’ bagasse for other uses.

Several databases are available which map out the sugarcane industry and technological

advancement in mills. The above classification system could be used in conjunction with these data

sources, to assess the likelihood of surplus bagasse being available. It is suggested that this

classification would also be useful for evaluating the likely availability of bagasse from particular mills

in different countries, the likelihood of competition between uses and cost of bagasse. Further

considerations would be whether or not mills have access to grid for selling on of surplus electricity.

3.7 Discussion of bagasse case study

The use of bagasse has become a more valuable option where policy support is available to develop

co-generation markets however, it is also noted that many of these policies are relatively recent and

there remains a range of uptake of efficient boiler technologies to maximise the production of

bioelectricity. For each scenario, access to grid infrastructure is key to whether bagasse might be

used for bioelectricity, bioethanol or other biorefining options however, competitive pricing is likely

to occur in the future as advanced technologies for the use of bagasse mature and reach

commercialisation. Where the development of the bioelectricity market is an option, the price of

electricity will be the benchmark for the value of bagasse, and in the next few years, potentially

competing with ethanol prices (if commercialisation of advanced technology biofuels becomes a

reality or is adopted by countries with supporting policy mechanisms). Further value chain modeling

should be linked to costs for the production of bioelectricity, bioethanol and/or other biorefining

options, also taking end product price into account.

4. Conclusions

This paper discusses the development of a data system to provide structured quantitative data for

techno-economic and value chain analysis, as well as the provision of qualitative data to inform

business decision making, based on current county specific policy mechanisms which may impact on

biomass feedstock cost, sourcing and requirements for selling biomass based products in the

European market.

Developing a knowledge and data system for information on biomass use and sourcing requires

consideration of many factors, some of which are changing constantly in time e.g. feedstock costs

and the influence of policy on biomass availability. Qualitative data which impacts on quantitative

data is more difficult to define and model, however providing a database which brings the datatypes

together will be useful for business decision makers (provided that data is kept updated).

Targeting the use of biomass by better understanding the chemistry and technology required for a

specific conversion pathway may be one way of improving feedstock choice but requires significantly

more analytical capability regarding chemistry and conversion technology, than is likely to be

available to business developers at the time at which they are looking to locate a biorefinery. Using

academic literature with standardised methodologies for biomass compositional analysis would

allow more direct comparisons to be made however, depending on the stage of project

development, this level of detail may not necessarily impact on business decisions unless a specific

chemical outcome is defined.

Practical aspects of supply chains development are assisted by value chain modelling if data on costs

is up to date and accurate, and assumptions made in models for given circumstances are reasonable.

Providing numeric values which allow modelling to be carried out provide great benefit to business

developers however, knowledge of end product market (and potential sustainability reporting

requirements) as well as local market knowledge of the biomass source are equally important. This

database has been developed to provide a sources of information which address both of these

points, including links to other policy regimes which feature in the approach of the EU Bioeconomy

Stategy.

5. Acknowledgements

The authors would like to acknowledge the EPSRC Impact Acceleration Account, University of Surrey

and Bio-Sep Ltd, as funders of this project and Chemical Engineering Department, University of

Surrey for access to their Value Chain Model. Thanks also to Bio-Sep Ltd, e4tech, Imperial College

London, NNFCC, Pera Technology and Resource Efficiency Services LCG Ltd for their input into the

Business Interface Questionnaire.

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