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Developing sustainable supply chains in the UK construction industry: A case study

P. Dadhich a, A. Genovese b,n, N. Kumar b, A. Acquaye c

a Centre for Sustainable Road Freight School of Management and Languages, Heriot-Watt University, Edinburgh EH14 4AS, United Kingdom b Logistics and Supply Chain Management Research Centre, Sheffield University Management School, Conduit Road, Sheffield S10 1FL, United Kingdom c Kent Business School, University of Kent Canterbury, Kent CT2 7P, United Kingdom

a r t i c l e i n f o

Article history: Received 31 March 2014 Accepted 6 December 2014 Available online 16 December 2014

Keywords: Sustainable supply chain Life cycle assessment Greenhouse gases Construction industry Case study

a b s t r a c t

In recent years, increased concerns over pollution and greenhouse gas emissions have initiated a wave of policy change in both governmental, industry and non-governmental organisations in order to reduce the overall environmental impact and ensure a sustainable future. The UK Green Building Council for instance has identified construction as one of the most emission-intensive industries, accounting for around 50% of greenhouse gas production in the UK. In this study, a hybrid life cycle assessment (LCA) technique is used to analyse the plasterboard supply chain; the most commonly used product in the UK construction industry of one of the Europe's leading distributor and contractor of building materials. This study demonstrates how emission ‘hotspots’ across the lifecycle of products can be identified and analysed using different intervention options in the supply chain in an attempt to reduce greenhouse gas emissions. For the plasterboard supply chain, the implementation of cross-docking principles and use of renewable sources of energy in warehousing were determined to be major decarbonzation interven- tions.

1. Introduction

Business communities across the globe are facing increased concerns over rising carbon emissions, climate change, scarcity of resources and waste generation. In current business environment, companies are facing major challenges arising from resource constraints; furthermore, rising energy and fuel prices causing irreparable damage. In the UK, central government has set an ambitious target to reduce the overall carbon emissions by 50% till 2025. The role of the UK construction sector within this target cannot be overemphasised given that it has been estimated that construction can potentially influence 47% of total UK carbon emissions (HM Government, 2010). However, a number of eco- nomic and political challenges exist to decarbonise the economy whilst alleviating the ongoing impacts from current financial crises. Although these challenges seem divergent, improving one aspect can inherently lead to improvements in other. For most organisations, as the budget tightens, their priorities will change to cut costs, improve sales and increase the market base. Devel- oping greener supply chains can add to revenue generation by cutting carbon emissions, making processes more efficient and decreasing surplus consumption bills. To strengthen its stand on

low carbon economy, the UK government has recently announced that all companies listed in the London Stock Exchange have to report their carbon footprint in their annual reports (Scott, 2012).

Green Supply Chain Management (GSCM) is a growing practice among industries that seek improvements in their environmental performance. In general, the introduction of GSCM could be either ethical (values driven by managers) and/or commercial (to gain competitive advantage in the market). In the last decade, an increased number of studies have been published in academic literature about GSCM and its benefits focusing on several aspects of environmental practices. For example, Zhang et al. (1997) reviewed green design; Bras and McIntosh (1999) described production planning and control for remanufacturing; Gungor and Gupta (1999) reviewed the issues related to green manufac- turing and product recovery; Carter and Ellram (1998) researched about reverse logistics; and Jayaraman et al. (2003) reviewed the importance of logistics network design for greener supply chains.

According to the Carbon Trust (2006), carbon reporting and auditing is the first step towards reducing carbon emissions which may positively influence unnecessary resources consumption. Companies can benefit from carbon measurement and reporting to set their carbon management initiative in place for a carbon neutral future. A report by the Department of Environment, Food and Rural Affairs (DEFRA, 2009) estimates that a saving of 4 million tonnes of carbon emission by 2021 will be achieved using emis- sion reporting. These regulations on reporting will directly or

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indirectly require companies to develop strategies to work towards a carbon neutral future. In a green supply chain, compa- nies need to review their strategies to connect and collaborate with each member in the chain. In recent years companies are becoming more proactive and are addressing the emissions out of their direct control, referred as Sustainability 2.0 (Ranconteur, 2012). Therefore, collaborating at the supply chain (SC) level will help to manage risks and integrate sustainable practices in busi- ness processes.

Measuring and controlling carbon emissions is challenging for any company's supply chain. This study seeks to measure the direct and indirect lifecycle greenhouse gas emissions of the plasterboard supply chain of a leading European distributor of building materials with the help of a hybrid life cycle assessment (LCA) technique. The supply chain of plasterboard is mapped to identify total lifecycle emissions from manufacturing, storing and transportation. This helps to improve the visibility, transparency and understanding of carbon emissions in the supply chain network. Later, carbon emissions hotspots are identified and a series of scenario analyses presented to understand the possible interventions that could cut down the lifecycle carbon emissions. This study further offer recommendations to the company for consideration in future strategies.

The remainder of the paper is structured as follows: Section 2 presents the background information related to green supply chain and sustainability in construction sector. Section 3 proposes the hybrid LCA framework to evaluate the carbon emission in the supply chain. Section 4 discusses the implementation process of the hybrid LCA framework and presents the case study of the plasterboard supply chain in context of the UK construction sector. Section 5 evaluates multiple scenarios in an attempt to lower the carbon emission of the supply chain. Section 6 provides a discus- sion over the findings and recommendations to the industry, while Section 7 concludes the paper.

2. Background

2.1. Green supply chain management

Previous work (see, for instance: Mefford, 2011; Winkler, 2011; Sarkis et al., 2011) have identified GSCM as a key business value driver. Porter (2008) also emphasises that such sustainable frame- works provides a strategic process which can enable organisations to create competitive advantages. Lake et al. (2014) provides insight into how decision support systems based on the concept can be developed to aid businesses in developing supply chain strategies. Srivastava (2007) also states that the lack of integration of sustainable practices in upstream and downstream supply chain partners may lead to reduction in profits. This means that specific criteria such as environment responsibility and social behaviour need to be applied by all supply chain members for greater and more long-term benefits. Studies show that GSCM not only reduces the environmental and social impact but also improves the operational effectiveness in following ways:

� Green design: Designing products to reduce the environmental impact over the full life cycle from the starting stage of developing new product and production processes (Fiksel, 1996).

� Green operations: Covering all aspects of greening the product by remanufacturing, handling, re-usage, logistics and waste manage- ment after the design phase (Lund, 1984; Srivastava, 2007).

� Green manufacturing: Reducing environmental impact by select- ing recycled or reused products or products which have been refurbished/remanufactured (Srivastava, 2007; Lund, 1984).

� Green packaging: Utilising less materials resulting in small, thin and light packages. This packaging can be recycled and also

occupies less space during storage and transportation (Kassaye and Verma, 1992).

� Waste minimisation: From production and operations (Lund, 1984).

� Reverse logistics: Defined as “the process of planning, develop- ment and efficient control of the flow of materials, products and information from place of origin to that of consume as to meet customer needs, recovering the residue obtained and managing it so that possible reintroduction in the supply chain, giving added value and/or proper disposal of it” (Tibben- Lembke and Rogers, 1998).

Different stages of GSCM involve activities including product safety, environmental risk management, occupational health and safety, pollution prevention, conservation of resources, cradle to grave product lifecycle analysis and waste management (Srivastava, 2007; Zhu et al., 2008). Managing these activities systematically in the supply chain helps companies to integrate their discrete activities resulting in increased efficiencies, reduc- tion of costs, promotion of economies of scale, better management of risks and improvement in operational effectiveness.

In the current global competitive environment, businesses are facing ever-increased challenges to satisfy the ever-rising expecta- tions of their customers and seek ways to reduce costs, improve quality and meet their sustainability goals. To meet these goals, many of them have identified GSCM as an area to gain the competitive advantage in the long term (Zhu and Sarkis, 2004; Genovese et al., 2013b). Every stage of the supply chain contains energy consumption, waste elimination and carbon emissions, and therefore, the SC needs to be restructured to reduce the waste and carbon emissions by re-engineering, re-manufacturing, re- furbishing and re-usage (Koh and Aoshima, 2001). Bernon and Cullen (2007) also explain the necessity to measure SC perfor- mance of reverse logistics and closed loop supply chains in both environmental and financial profitability. Many companies face problems in implementing environmental management systems due to internal and external barriers.

2.2. Sustainability in construction industry

The UK government is committed to rebuilding the economy as it recovers from recession, and believes that mainstream sustainable development policies will result in long-term improvement in well- being and economic prosperity. According to Kolk and van Tulder (2005), Scherer et al. (2006) and Moon (2007), industries may play a significant role in shaping the policies for a sustainable future. According to a report by UK Green Building Council (2008), the construction of buildings accounts for the 50% of the greenhouse gas emissions in the UK.

Plasterboard is one of the notable products utilised in the construction industry. The construction industry consumes approximately 3 million tonnes of plasterboard for construction in the UK each year. Detailed statistics from the Department for Environment, Food & Rural Affair (DEFRA, 2009) show that around 300,000 t of plasterboard waste are generated from new construc- tion activities each year. Moreover, it is difficult to quantify the amount of plasterboard waste arising from demolition and refurb- ishment projects; estimates however show this lies in the range of around 500,000 t to more than 1 million tonnes per year. From an environmental perspective, climate change is the main impact associated during manufacturing due to the energy consumption at several stages of production (namely ‘calcinations’ and drying of the plasterboard) (DEFRA, 2009). As discussed in the DEFRA report, other impacts include the cost of disposal of plasterboard at the end of the life cycle (economic impact) and the potential

P. Dadhich et al. / Int. J. Production Economics 164 (2015) 271–284272

health risks emanating from the manual handling of plasterboard sheets in construction sites (social impact).

In July 2008, the government collaborated with industries to launch strategy for sustainable construction. This project was coordinated by DEFRA and plasterboard was identified as one of the 10 priority products in its programme on Sustainable Con- sumption and Production (DEFRA, 2010). Due to its high usage and environmental impact, Gypsum Products Development Associa- tion and DEFRA developed the Sustainability Action Plan to curb the impacts caused by Plasterboard throughout the product life cycle. The objectives incorporated into the plan include efficient manufacturing, safer handling, zero waste to landfill, utilising materials and sustainable partnerships. This initiative by construc- tion industry sets a good example to produce carbon neutral plasterboards and contribute to the control of climate change (DEFRA, 2010). Srivastava (2007) believes that creating awareness and collaborating with supply chain partners can influence directly or indirectly the sustainability plans such as for plaster- board supply chains. An exhaustive study by Carter and Easton (2011) identifies many areas of sustainable practices can be applied to the GSCM strategy for a greener future. It could be the materials used in manufacturing; location of vendors; trans- portation; or final consumption of the product. The environmental effect of a product can also be reduced by sustainable logistics (Varma and Clayton, 2010) and warehousing (Tan et al., 1998). Both are independent activities and, without consideration, can have harmful effects on the environment when magnified at multiple levels across the Supply Chain. Optimising the transport routes and reducing the inventory level can also lead to better savings and improved efficiency (Gavirneni, 2005).

To this end, the paper aims to explore the development of sustainable supply chains in the UK construction sector using the supply chain for plasterboard products as a case study. Within this process, the greenhouse gas emissions are assessed throughout the product lifecycle using a Hybrid LCA methodology. The impact of logistics activities and multiple scenarios of the operations function of the supply chain such as cross-docking as an alter- native storage solution are analysed in this paper.

3. Hybrid LCA methodology

In this paper, the top-down environmental input–output metho- dology and the bottom-up process analysis methodology are inte- grated together to develop the hybrid LCA framework. The environmental input–output methodology is formulated on the con- cept of Multi-Regional Input–Output (MRIO) analysis based on the Supply and Use format. Because supply chains are generally complex with extended system boundary as a result of the globalised nature of all the interconnecting and theoretically infinite tier-level product, process and service inputs, the use of the MRIO framework enables the complexity issue to be resolved. Fundamentals of this methodology are described in the following.

3.1. General input–output model

An input–output (IO) model records the flows of resources (products and services) from each industrial sector considered as a producer to each of the other sectors considered as consumers (Miller and Blair, 2009). An IO model is therefore a matrix representation of all economic (production and consumption) activities taking place within a country, region or multi-region.

The general input–output approach has been well documented in literature (Albino et al., 2002; ten Raa, 2007; Ferng, 2009; Minx

et al., 2009). It can be shown that:

x ¼ ðI�AÞ�1 Uy

where A¼[aij] describes all the product requirements (i) needed by industry (j) to produce a unit monetary output. It is called the technical coefficient or technology matrix because it describes the technology of a given industry which is characterised by the mix of supply chain inputs (including raw materials, machinery, energy, goods, transport, services, etc.) required to produce a unit output (Barrett and Scott, 2012). Vector x represents the total output in a given sector and is equal to the sum of those products consumed by other industries and those consumed by the final demand y (households, governments, exports, etc.).

(I�A)�1 is referred to as the Leontief Inverse matrix and ðI �AÞ�1 Uy describes the total (direct and indirect) requirements needed to produce the total output, x for a given final demand y (Miller and Blair, 2009). Hence, in terms of supply chain visibility, the supply chain of a given product can be set up in such a way that not only direct inputs are captured, but also, irrespective of the origin of these inputs (domestic or imported), indirect supply chain input can also be captured in the analysis. This is as a result of the extended system boundary of the IO framework (Acquaye and Duffy, 2010; Mattila et al., 2010; Wiedmann et al., 2011). As a result, the whole lifecycle perspective, which is a key principle of green supply chain management (Sundarakani et al., 2010; Carter and Easton, 2011), can be adopted based on the generalised ideas surrounding Multi-Regional Input–Output (MRIO) analysis (Wiedmann, 2009).

3.2. Multi-Regional Input–Output (MRIO) hybridised framework

The MRIO model used in environmental input–output analysis is usually presented as a 2-region model; see for instance McGregor et al. (2008) who used a two-region MRIO model to enumerate CO2 emissions embodied in interregional trade flows between Scotland and the rest of the UK. In this paper, the Supply and Use format within a two-region (UK and the Rest of the World) IO framework is adopted. As reported by EUROSTAT (2008), the advantages of Supply and Use tables as an integral part of the national accounts lie in the fact that they have a stronger level of detail which ensures that there is a higher degree of homogeneity of the individual product and therefore better possibilities for determining categories of uses and consequently the environmental impacts. Additionally, it enables us to split emissions as a result of using supply chain inputs either sourced from the UK or from the rest of the world (ROW). The methodology encompassing this MRIO approach and developed within the integrated hybrid LCA methodology (Suh and Huppes, 2005) is presented below. The general equation is given by Eq. (1) (see also Acquaye et al., 2011).

Total emissions impact ¼ Êp 0

0 Êio

" # Ap �D �U I�Aioð Þ

" #�1 y 0

� � ð1Þ

where Ap represents the square matrix representation of process inventory (dimension: s� s), Aio represents the MRIO technology coefficient matrix (dimension: m� m), I represents an identity matrix (dimension: m� m), U provides the matrix representation of upstream cut-offs to the process system (dimension: m� s), D reproduces the matrix of downstream cut-offs to the process system (dimension: s� m), Ep represents the process inventory environmental extension matrix. CO2-eq emissions are diagonalised (dimension: s� s), Eio represents the MRIO environmental extension matrix. CO2-eq emis-

sions are diagonalised (dimension: m� m), y

� � represents the

functional unit column matrix with dimension (sþm,1) where all entries are 0 except y

The following sub-sections details how each part of the MRIO model is set-up.

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3.2.1. Process LCA Referring back to Eq. (1), Ap describes the matrix representation

of the Process LCA system following developments made by Suh and Huppes (2005). For n different types of supply chain inputs accounted for in the Process LCA system, Ap would be of dimen- sion (nþ1) by (nþ1); where there are n supply chain product inputs and 1 main product output. Let qn represent the quantity of supply chain inputs used for any given input, n and Ap¼[krc]; r (rows) represents inputs and c (columns) processes in the process LCA system. The mathematical formulation of the Process LCA system becomes:

Ap ¼ krc � �

krc ¼ 0 if rac k rcð Þn ¼ qn if r ¼ c krc ¼ kr;nþ1 ¼ �krr 8 r and if c ¼ nþ1 krc ¼ knþ1;nþ1 ¼ 1

8>>>>< >>>>:

3.2.2. Input–output LCA system, Aio Following on from Eq. (1), the input–output LCA system in this

paper is setup as a multi-regional input–output LCA system (Aio) presented in the Supply and Use format. In matrix representation, this becomes

Aio ¼

0 A UKð ÞU 0 0 A UKð Þs 0 A UKð ÞEXP 0 0 0 0 A ROWð ÞU A UKð ÞIMP 0 A ROWð ÞS 0

2 66664

3 77775

where Aio becomes the 2-region MRIO technical coefficient matrix. This includes the following technical coefficient matrices:

� A(UK)U, representing the UK Domestic Use. � A(UK)s, representing the UK Domestic Supply. � A(UK)EXP, representing the UK Export to ROW. � A(ROW)U, representing ROW Use. � A(UK)IMP, representing UK Imports from ROW. � A(ROW)s, representing ROW supply to ROW.

All of the individual A matrices are of dimensions 224 � 224; hence, Aio and I (the Identity Matrix) are therefore of dimension 896 � 896.

The Technical Coefficient Matrix for UK Imports from ROW, A(UK)IMP, for example is defined as:

A UKð ÞIMP ¼ qðROW;UKÞij

" #

where qðROW;UKÞij represents elements of UK imports input–output table from the ROW region indicating the input of product (i) from ROW into the industry (j) of the UK while xj represents the total output of UK industry, (j).

3.2.3. Upstream (U) and downstream (D) inputs From Eq. (1), the upstream inputs or Matrix U is assigned a

negative sign because it represents inputs from the upstream supply chain (IO system) into the process system. Matrix D, is also assigned a negative sign, because it represents inputs from the process system into the background economy (IO system). Both Strømman et al. (2009) and Acquaye et al. (2011) explains that the downstream inputs from process LCA system into the wider economy or (IO system) can be considered negligible; hence matrix D set to zero. Using the basic principles of input–output analysis, Acquaye et al. (2011) provides details in estimating the upstream inputs U.

3.2.4. Final demand y As shown in Eq. (1), y represents the final demand; in this

instance, the output of the hybrid LCA system. In matrix notation, y is a column matrix of dimension: ((nþ1þ896) by 1); where n is the number of supply chain product inputs of the process LCA system, 1 represents the main product output and 896 the dimension of the MRIO matrix used in this paper. It is given as

y ¼ f d;1 � �

; where f d;1 ¼ 1 if d ¼ nþ1 and 0; 8 other d

3.2.5. Environmentally extended MRIO hybridised model The MRIO component of the hybridised model can be extended

to an Environmental MRIO lifecycle assessment (LCA) to generate results which can be used in the assessment of product supply chain emissions.

Given that x ¼ ðI�AioÞ�1 Uy defines the total (direct and indir- ect) requirements needed to produce an output x for a given final demand, y; the MRIO based hybrid LCA can therefore be defined in a generalised form as

E ¼ Eio Ux ¼ Eio UðI�AioÞ�1 Uy

where Eio is the direct emissions intensity (kg CO2-eq/d) of the IO industries and Eio UðI �AioÞ�1 the total (direct and indirect) emis- sions intensities (kg CO2-eq/d) of the IO industries.

By extension, the matrix Eio expressed in terms of the MRIO Supply and Use structure becomes:

Eio ¼

ÊUK 0 0 0 0 0 0 0 0 0 ÊROW 0 0 0 0 0

2 66664

3 77775

where ÊUK and ÊROW are respectively the diagonalised direct emissions intensity (sector emissions in kg CO2-eq per total output in d) of each industrial sector in the UK and the ROW.

Similarly, the environmental extended component for the process LCA system Ep (refer to Eq. (1)) is defined by a diagonalised matrix of the respective environmental values en of each input n into of the process LCA system. en is obtained by multiplying the quantity of each product inputs q and the respective emissions intensity eint.

Ep ¼ ên � �

where 8n into the process LCA system

en ¼ qn UeðintÞn This environmentally extended MRIO model (with each com-

ponent described in Section 3.2) forms the basis for undertaking a robust comparative environmental impacts assessment (in terms of carbon emissions) and carbon hot-spotting analysis between the reverse supply chain management system and a linear pro- duction paradigm of the forward supply chain. Indeed, by inter- connecting the domestic and ROW Supply and Use input–output tables into a 2-region MRIO table as shown, the model can overcome the complexity of product supply chains as a result of the globalised nature of all the interconnecting and theoretically infinite tier-level product, process and service inputs. This is so because in addition to direct inputs, the model captures all indirect upstream requirement that are needed to produce all the indivi- dual supply chain inputs either from resources from the UK or from outside the UK (that is ROW).

In this study, the Hybrid LCA has been employed to evaluate carbon emissions across the supply chain.

P. Dadhich et al. / Int. J. Production Economics 164 (2015) 271–284274

3.2.6. Supply chain mapping The output of the Hybrid LCA methodology will be organised

and presented in tables (reporting supply chain inputs and related amounts, reference units, unit cost, emission intensities per reference unit, total emissions, emissions percentages over total and input category) and supply chain maps. Supply chain maps visually represent the interaction between different entities within a supply chain and can be presented at different levels of the value chain such as product, process, firm and industry levels. In this paper, a product-level perspective is used highlighting the direct and indirect supply chain interactions. Koh et al. (2013) and Acquaye et al. (2014) explain that the concept of a supply chain map can be used to provide clear understanding of the exact flow of materials and impacts along the supply chain and hence form the basis for managing and benchmarking the environmental performance of the supply chain. Specifically, supply chain inputs will be classified according to the following categories:

� Transport to plant, involving the transport of raw materials and semi-finished goods to intermediate production stages and to the main manufacturing plant.

� Materials from supplier, involving manufacturing activities related to the production of raw materials and semi-finished goods then utilised at the main manufacturing plant.

� Utilities at plant, including the use of electricity, gas, fuels, water and other types of energy/utilities at the main manufacturing plant within the supply chain.

� Transport to warehouse, representing logistical activities related to the transport of finished products from the main manufac- turing plant to the distribution warehouse.

� Transport inside warehouse, being related to loading, unloading and handling operations happening at the distribution ware- house (involving, for instance, the use of forklifts).

� Utilities at warehouse, including the use of electricity, gas, fuels, water and other types of energy/utilities at the distribution warehouse.

� Transport from warehouse, representing logistical activities related to the transport of finished products from the distribu- tion warehouse to the final customer.

Inputs (and related aggregated categories) will be classified (in both tables and maps) according to their related emissions amount according to the colour-code and thresholds shown in Table 1.

4. Implementation

4.1. The case study

In this study, the implementation of the hybrid life cycle assessment (LCA) technique is demonstrated on the plasterboard supply chain of one of Europe's leading distributors and contrac- tors of building materials. The company offers an integrated supply chain solution to the construction industry and related markets. It maintains a fleet of over 1300 vehicles for supply chain operations in the UK and the core products distributed by the company are interiors, exteriors, insulation and energy manage- ment. It has achieved ISO 14001 certification in 2006 and intro- duced the Low Carbon Business Policy which has resulted in gaining Carbon Trust Standard.

Plasterboards are a commonly used construction product due to its inherent qualities such as low flammability, acoustic benefits and ease of build. Approximately 270 million m2 of plasterboard is produced, distributed and used in the UK every year (DEFRA, 2010). This high consumption also generates waste by the refurb- ishment and demolition of plasterboard at the end of the life cycle.

Every year, over 2400 t of plasterboard is produced and supplied to the case company warehouses. This study identifies the emission ‘hotspots’ across the lifecycle of the plasterboard and analyse different interventions in the supply chain in an attempt to reduce greenhouse gas emissions.

4.2. Data collection

In this study, data has been collected using primary and secondary sources. The primary data is collected using a data collection protocol completed by the company, and through a number of interviews conducted during meetings with company managers. The data proto- col is provided to the company listing the data requirements and the units of the primary dataset. The following specific information was provided by the company:

� The total energy usage (electricity, gas, petrol and diesel) by 1 t of plasterboard annually with their quantities and units.

� The total output of insulation plasterboard distribution annually. � The percentage of total energy usage that can be allocated to insulation

plasterboard (through production, storage or transportation). � All the inputs and related quantities and unit cost that goes into

the production of 1 t of insulation plasterboard. � The average distance (in km) travelled by 1 t of plasterboard for

delivery of final product to customer. � Details of the waste management service implemented during

the production of plasterboard.

Relevant secondary data are collected from eco-invent; a widely used emission inventory database. In this study, Ecoinvent (2012) data provides the information about the emissions related to the activities involved in the manufacturing. The cumulative effects of emissions are represented using CO2 kilogram equivalents (kgCO2- eq) of the unit of input over a 100-year period. The secondary data for plasterboard supply chain inputs was retrieved from the Ecoinvent (2012) database version v2.2. It consists of more than 4000 up-to- date lifecycle inventory (LCI) datasets for a wide range of areas including: energy supply and production, agriculture, transportation, construction materials, packaging materials, metals, biofuels and bio materials, electronics and ICT and also waste treatment.

The data from both primary and secondary sources are used as inputs to the hybrid LCA methodology to calculate total lifecycle carbon emissions and develop the supply chain maps.

Table 1 Colour-code for emissions.

Impact Interval Colour-code

Low enr1.00%

Moderate 1.00%oenr5.00%

High 5.00%oenr10.00%

Very high enZ10.00%

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4.3. Data analysis

4.3.1. Preliminary findings The primary data supplied by the company are mainly related

to their logistical (storage and transportation) activities, consider- ing a distribution centre located in the North-West of England. Approximately 200 t of plasterboards per month are produced by the suppliers, sourced and stored in the warehouse until distrib- uted to the customers. The company transports plasterboard all around the UK by road using its own fleet of 1300 vehicles. The data sheet provided by the company includes the distance from a national distribution centre to the warehouse and from the ware- house to the customers. Based on primary data provided by the company, the average distance for customer deliveries was calcu- lated to be 54 km to and from the warehouse (or 27 km one way). On average, 255,477 kWh of electricity is consumed per year by one of the warehouses in the UK. The total cost of water consumption in a month by the warehouse is d2169. In the warehouse, 9 diesel forklifts operate for 42.5 h per week and are used to load, unload and store the plasterboard in the warehouse.

Relevant secondary dataset used in the study is obtained from the Ecoinvent (2012) lifecycle inventory database, which is shown in Table 2. Data given in Table 2 show inputs as part of the production system supply chain of a typical plasterboard. The information on plasterboard's upstream supply chain is obtained from the GHG Scope 3 emission report by World Resources Institute and WBCSD (Greenhouse Gas Protocol, 2011). According to the report, Scope 1 emissions are the direct emissions that are controlled and owned by the companies while Scope 2 emissions are related to indirect use of energy (electricity, heat, steam). Scope 3 emissions are the indirect emissions that are not reported in the company's value chain. These potential Scope 3 emission activities are also analysed in this paper using the following upstream indirect inputs in the supply chain:

(a) Travelling of employees by Air, Road and Rail (b) Construction of commercial buildings (c) Manufacturing of plasterboard (d) Machinery used in production (e) Extraction of gypsum (f) Collection and treatment of waste in the whole supply chain (g) Landfill of waste (h) Computer services

The primary data of the warehouse are converted according to the standard unit of 1 kg of plasterboard and the emissions are calculated in kg CO2-eq. The carbon emission per unit weight of plasterboard due to inbound logistics, forklift trucks used in the warehouse, outbound logistics, and electricity and water con- sumption are summarised in Table 3.

4.3.2. Supply chain mapping In this step, the data calculated from the primary and second-

ary resources are mapped and emissions are calculated to evaluate the environmental impact of the plasterboard supply chain based on the hybrid LCA methodology. Fig. 1 presents the upstream and downstream carbon emission of the plasterboard supply chain.

Direct emissions identified in the plasterboard distribution are related to the production, transportation and warehouse activities. The indirect emissions include gas and electricity consumption where the company does not control the production process. In addition, Scope 3 indirect emissions produced as a consequence of ‘other’ activities. Table 4 reports the complete break-out of carbon emissions across the supply chain, including both direct and indirect emissions.

The total lifecycle carbon emission of the supply chain is estimated to be 0.7187 kg CO2-eq for per kilogram of plasterboard production. This analysis estimates that 90.47% of the total lifecycle emission is contributed by direct inputs, and 9.53% originates from the indirect emissions associated with the plasterboard supply chain. The indirect emissions in the supply chain are based on the inputs from different sectors such as, construction, trade, minerals, fuels, wood and papers, food, textiles, chemicals, fishing forestry, personal and business services, transport and communication, utilities and mining. In the case of plasterboard, the indirect emissions are linked to the opera- tions related to Extraction of minerals (1.60%), Utilities (2.30%), Transport and Communication (1.10%), Mining (1.17%) and Construc- tion (1.06%).

The Hybrid LCA model helps to identify the carbon ‘hotspots’ and quantify their impacts in the plasterboard supply chain. This is translated in a supply chain carbon map (as seen in Fig. 1) aggregating the different direct emission inputs into identified categories identified in Tables 4 and 5. In particular, the utilities consumption at the manufacturing plant account for 24.99% of the total emissions. Transport of finished products to the warehouse accounted for 18.68% of emissions, while materials received from suppliers and utilised at the manufacturing plant account for 16.02%. Utilities consumption at the warehouse estimated to account for 14.67% share of total emissions (Fig. 2).

Table 2 Relevant secondary data retrieved from ECOINVENT.

Supply Chain Input Name Quantity Unit Emissions in kg CO2-eq Cost (d)

Washing agents Alkylbenzene sulphonate, linear, petrochemical, at plant 0.00001 kg 1.63090 0.47 Electricity/supply mix Electricity, medium voltage, at grid 0.09370 kWh 0.65700 0.08 Glass/construction Glass fibre, at plant 0.00016 kg 2.63510 0.50 Oil/heating systems Light fuel oil, burned in industrial furnace 1 MW, non-modulating 1.36000 MJ 0.08670 0.01 Agricultural production/plant production Potato starch, at plant 0.00290 kg 0.71735 0.92 Chemicals/inorganics Silicone product, at plant 0.00013 kg 2.71060 0.47 Construction materials/binder Stucco, at plant 0.81100 kg 0.07383 0.58 water supply/production Tap water, at user 0.36400 kg 0.00032 0.01 transport systems/road Transport, lorry 20–28 t, fleet average 0.30000 tkm 0.19460 0.50 Paper & cardboard/cardboard & corrugated board

Whitelined chipboard, WLC, at plant 0.04840 kg 1.08300 0.14

Table 3 Carbon emission data related to different operations in the warehouse.

Activity Quantity Unit Emissions in kg CO2-eq

Cost (in d)

Road transport (from plant to warehouse)

0.69000 tkm 0.19460 0.50

Forklifts 0.00727 kg 0.67000 0.50 Outbound logistics (at warehouse)

0.27000 tkm 0.19460 0.50

Electricity 0.16044 kwh 0.65700 0.08 Water 0.00001 m3 0.65661 0.01

P. Dadhich et al. / Int. J. Production Economics 164 (2015) 271–284276

5. Scenario analysis

In this section, different scenarios are modelled to identify the potential strategies to reduce the environmental impacts of the plasterboard supply chain. Scenario analysis is an important tool for strategic decision-making, particularly in environmental impact assessments, due to its ability to define future develop- ments for cumulative impact assessment and to determine the effects of contextual change (for example climate change) on possible interventions (Duinker and Greig, 2007).

During the production of plasterboard many of the raw materials used need to be utilised efficiently to cut down on environmental impacts. The impacts related to oil consumption, electricity and utilities are very high in production and manufac- turing operations such as:

� Gypsum production: Environmental impact due to the extrac- tion of natural gypsum and production of Flue Gas Desulphur- isation (FGD) is significant. Mining and extraction of minerals causes 2.77% of the total emissions (see Table 3).

Fig. 1. Plasterboard supply chain mapping with upstream and downstream emissions.

Table 4 Life-cycle analysis calculation (base case).

Input name Amount Reference Unit

Avg. Unit Cost Emission intensity

Emissions in kg CO2-eq

Emissions (%)

Category

Road (from plant to warehouse) 0.69000 tkm d0.50 0.19460 0.13427 24.00 Transport to warehouse Oil (at plant) 1.36000 MJ d0.01 0.08670 0.11791 21.07 Utilities at plant Stucco (at plant) 0.81100 kg d0.59 0.07380 0.05985 10.70 Materials from supplier Road transport (to plant) 0.30000 tkm d0.50 0.19460 0.05838 10.43 Transport to plant Outbound logistics (at warehouse) 0.27000 tkm d0.00 0.19460 0.05254 9.39 Transport from warehouse Paper and cardboard/chipboard (at plant)

0.04840 kg d0.14 1.08300 0.05242 9.37 Materials from supplier

Utilities (indirect) N/A N/A N/A N/A 0.01640 2.93 Indirect Minerals (indirect) N/A N/A N/A N/A 0.01150 2.06 Indirect Mining (indirect) N/A N/A N/A N/A 0.00840 1.50 Indirect Transport and communication (indirect) N/A N/A N/A N/A 0.00790 1.41 Indirect Construction (indirect) N/A N/A N/A N/A 0.00760 1.36 Indirect Metals (indirect) N/A N/A N/A N/A 0.00510 0.91 Indirect Wind energy (at warehouse) 0.16044 kWh d0.03 0.03120 0.00501 0.89 Utilities at warehouse Forklift fuel consumption (at warehouse) 0.00727 kg d0.50 0.67000 0.00487 0.87 Transport inside

warehouse Business services (indirect) N/A N/A N/A 0.00300 0.54 Indirect Wind energy (at plant) 0.09370 kWh d0.03 0.03120 0.00292 0.52 Utilities at plant Potato starch (at plant) 0.00290 kg d0.92 0.71740 0.00208 0.37 Materials from supplier Fuels (indirect) N/A N/A N/A N/A 0.00200 0.36 Indirect Agriculture (indirect) N/A N/A N/A N/A 0.00200 0.36 Indirect Chemicals (indirect) N/A N/A N/A N/A 0.00170 0.30 Indirect Wood and paper (indirect) N/A N/A N/A N/A 0.00120 0.21 Indirect Equipment (indirect) N/A N/A N/A N/A 0.00080 0.14 Indirect Trade (indirect) N/A N/A N/A N/A 0.00050 0.09 Indirect Glass (at plant) 0.00016 kg d0.50 2.63510 0.00042 0.08 Materials from supplier Silicone product (at plant) 0.00013 kg d0.47 2.70160 0.00035 0.06 Materials from supplier Food (indirect) N/A N/A N/A N/A 0.00010 0.02 Indirect Water supply (at ilant) 0.36400 kg d0.00 0.00030 0.00011 0.02 Utilities at plant Textiles (indirect) N/A N/A N/A N/A 0.00010 0.02 Indirect Forestry (indirect) N/A N/A N/A N/A 0.00010 0.02 Indirect Washing agents (at plant) 0.00001 kg d0.47 1.63090 0.00002 0.00 Materials from supplier Fishing (pndirect) N/A N/A N/A N/A 0.00000 0.00 Indirect Water (at warehouse) 0.00001 kg d0.01 0.65510 0.00001 0.00 Utilities at warehouse Personal services (indirect) N/A N/A N/A N/A 0.00000 0.00 Indirect TOTAL 0.55956 100.00

Table 9 Life-cycle analysis calculation (wind energy adoption) - emissions by category.

Category Emissions in kg CO2-eq Emissions (%)

Transport to plant 0.05838 10.43 Materials from supplier 0.11514 20.58 Utilities at plant 0.12094 21.61 Transport to warehouse 0.13427 24.00 Utilities at warehouse 0.00501 0.90 Transport inside warehouse 0.00487 0.87 Transport from warehouse 0.05254 9.39 Total direct emissions 0.49116 87.78 Total indirect emissions 0.06840 12.22 Total emissions 0.55956 100.00

P. Dadhich et al. / Int. J. Production Economics 164 (2015) 271–284282

be considered in collaboration with SC members. Mixed mode of transportation including the low emission options should also be considered along with network optimisation.

6.7. Aligning sustainable practices in SC

The strategic plan for reducing the environmental impact could be short-term, mid-term or long-term. However, the strategic planning should be properly aligned with the operational mea- sures to ensure the implementation of the sustainable practices in the SC.

� Strategic llanning: Current sustainability goals of the SC can be examined to see how much they align with the future sustain- ability planning and goal setting. If the current goals are not promising enough then there is a need to work on the design of new goals and policies.

� Sustainability review: As soon as the goals are defined, suppli- ers’ evaluation should be performed to check the alignment with the sustainability goals of the SC. The evaluation process should identify and rank the suppliers on their alignment to the SC green goals. It could be the reduction of waste, implementa- tion of reverse logistics, logistics route optimisation, green packaging, JIT, energy efficient products or sustainable ware- housing. A review of the progress made by the suppliers would be undertaken over a fixed period to check if the company is improving at the required pace.

� Sustainability standards: Sustainability standards of the product and processes in the SC should be decided in collaboration with partners so that everyone understands the sustainability goal of the SC. This will increase awareness among the supply chain members and help in developing innovative ideas for sustain- able practices.

� Execution: Execution of strategic goal needs efficient coordina- tion and information sharing with suppliers. Due to the limited sharing of data with suppliers, sustainability goals will not be achieved. If required, training to suppliers to understand the execution process should be provided.

7. Concluding remarks

In the context of problems related to sustainability issues, this study discussed the need for improving environmental performances of a supply chain. Hybrid LCA based methodology is proposed in the paper to measure the carbon emission in the supply chain and evaluate potential strategies to reduce the carbon emission. Plaster- board, one of the most commonly used product in the UK construction industry and responsible for a significant impact on the environment was used to exemplify developments made in the paper. The presented case study assesses the carbon emissions at the SC level and analyses multiple interventions in an attempt to develop sustain- able SC. Calculating and monitoring the emission level in the SC is a complex process. Therefore, collaboration along the SC is required to collect relevant data to identify the emission hotspots and implement strategies to reduce the emission level. The holistic view of SC considering the product life cycle would be appropriate for imple- menting the green practices in the SC.

Companies in the SC should focus on data sharing and collaboration with suppliers and customers to gain long-term sustainability benefits. Better collaboration and green sourcing are considered useful to achieve the target of zero waste to landfill. Introducing logistics principles like reverse logistics and cross docking can further support to achieve the sustainability targets. Supply chain members need to develop collaborative strategy and

continuously monitor it against the sustainability goals in an attempt to develop a sustainable supply chain.

Acknowledgements

The research related to this paper has been partially supported by the project entitled Promoting Environmentally Sustainable SMEs – PrESS, funded by the Erasmus Lifelong Programme from the European Commission.

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