Broadly speaking, there are three main methodological approaches taken to the computation of embodied emissions, namely: Process-based, Input/Output-based and Hybrid. Each of these is briefly discussed in the next sub sections.
2.10.1. Process-based
The process-based approach for embodied emissions analysis is one of the most commonly used methods. It utilises process flows to systematically gather data and calculate known environmental inputs and outputs. At an industrial level, process-based analysis is undertaken by measuring the input and output of energy and materials during all the processes and activities involved in the manufacturing of a product (Acquaye, 2010). The estimation process works backward in the upstream of main process by starting with the material as a final product (Figure 2-7), taking into consideration all the potential forms of inputs related to direct energy or the contribution of sequestered energy by each material (ibid).
Production of B
Production of target product Production of A
Production of C
Production of D
STAGE 1 STAGE 2
STAGE 3
•
• • Input to C
Inputs to A
Inputs to target product Input to B
•
•
•
Input to D
•
•
•
Figure 2-7: Diagrammatic illustration of the process-based approach
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The total energy consumed during the manufacture of the product, directly and indirectly, per unit output of the product, is described as the process energy intensity, normally expressed as energy per unit mass (e.g. GJ/kg) for that particular product. The embodied energy of a product is therefore evaluated by multiplying the energy intensity by the quantity of materials used in tonnes. Process-based analysis is more suitable for adoption in instances where the flows of a range of goods and services for specific processes, products, or chains of manufacturing are easy to trace and track at a physical level. Essentially, the process-based approach is employed to gain an understanding of the “cradle to grave” environmental impacts associated with specific products.
With the use of specific and basic primary and secondary process data, the process-based approach can be adopted to achieve high-precision results for defined products (Wiedmann, 2010). The approach is limited to the flows of product under consideration, where the energy consumed along the supply chain up to and including the manufacturing of a product is estimated and energy intensity established (Acquaye and Duffy, 2011). In practice, all the many energy inputs involved in the manufacturing processes of a product cannot be estimated in this manner.
Process analysis is generally time consuming to carry out because all the energy inputs that go into the production of a product are numerous and therefore almost impossible to determine with accuracy due to circular relationship and boundary problems (Acquaye, 2010). A system boundary (i.e. “the interface or the border between a product system and the environment or other product system”, as explained in ISO 14040) is therefore set, leading to the truncation of some of the energy inputs and resulting in errors of unknown size in embodied emissions estimates (Dixit et al., 2013). The degree of the incompleteness and inaccuracy posed by setting a system boundary varies subject to the type of product or process under consideration and how thorough the study is, but it can be as high as 50% or more (Lenzen et al., 2002). Process analysis also relies on the availability of data from manufacturers, who may not be willing to supply the information unless required by law. An alternative has been suggested in the form of the input-output approach.
2.10.2. The input-output based
The input-output (I-O) approach to lifecycle assessment operates through the tracking of all economic transactions between different sectors within an economy and the consumers. It is an economic modelling method which facilitates the understanding of the interactions between economic sectors of a country, the producers and the final consumers (Wiedmann, 2010). A
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general I-O 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).
As an example, the construction industry utilises fabricated metal products, machinery and equipment, electricity and gas etc. to construct houses. This implies that when a house is built, the demands for metal products, electricity and gas, machineries etc. are affected. This shows that outputs from one industry become inputs to another industry. The I–O concept is illustrated in Figure 2-8.
Figure 2-8: Diagrammatic illustration of the framework for I–O based analysis
An I-O model is therefore a matrix representation of all economic (production and consumption) activities taking place within a country, region or multi-region. With process-based approach, the flows of material and energy are expressed in physical quantities, but with input-output analysis, flows are expressed in monetary terms. The I-O process utilises cash flow within different sectors of a given industry. The data are organised into an input-output table which is usually compiled by the national government. The table gives a full description of the trading activities happening in a national economy. It shows how products from producers are being sold to final consumers for their use or to contribute to further production in other sectors of an industry (Nielsen and Wiedmann, 2001). Essentially, the I-O table is an economic map which shows how the economy is broken down into various sectors and the inter-relationships between
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all the economic sectors (Acquaye, 2010). The number of sectors within an industry and their respective definitions vary from region to region.
The I-O table takes the form of a square matrix which illustrates the financial input of products in £ (as in the case for UK) from every sector of the economy (row) required to produce total output of each industry sector (column) also expressed in £. The main data used in I-O analysis in this research are the UK input-output table. The general I-O methodology has been well documented in literature (Lenzen et al., 2003; Ten Raa, 2007; Miller and Blair, 2009).
The method offers comprehensiveness and completeness because it captures nearly the entire system boundary (Dixit et al., 2010), by taking into account the entire activities along the chain of supply of a product including those accrued by indirect suppliers, allowing the tracking of the complete range of inputs to a process, thus avoids systems boundary issues that characterises the process-based approach (Sousa e Silva, 2001; Acquaye and Duffy, 2010).
The I-O approach has been used in many applications. For instance, the concept has been applied to environmental impact assessment (Lenzen et al., 2003; Mattila, 2010; Yang and Suh, 2011), ecological and industrial systems (Bailey et al., 2008), waste management (Nakamura and Kondo, 2006), energy and embodied energy analysis (Park and Heo, 2007; Acquaye and Duffy, 2010), carbon footprint analysis (Wiedmann et al., 2010), material flow analysis (Hawkins et al., 2006), and energy systems (Crawford and Treloar, 2004; Crawford, 2009). The use of the I-O approach in energy and environmental research studies has several advantages, such as being inexpensive to carry out and the fact that the analysis can be completed within a short period of time as well as minimising cut-off error and system boundary incompleteness, some of the major drawbacks of a process-based approach (Acquaye and Duffy, 2010).
By linking environmental information (e.g. GHG emissions) with economic data (e.g.
financial transactions) to each sector, an environmental burden (i.e. carbon footprint) can be determined. This characterises the environmental impact of an additional £1 of output from each industry. Similar to tracking cash flow from the time of production to the period of final consumption, an environmentally extended input-output model allows tracking of the flow of environmental impacts along both the supply and production chains. Given that each step in the production process yields an environmental burden, a lifecycle inventory of impacts of production and consumption carbon footprints is produced (Wiedmann, 2010).
Despite the fact that the I-O method has the ability to cover an infinite number of production steps in an elegant manner as described above, the method suffer from a number of
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well-recognised limitations that are well-documented in literatures, including proportionality assumption, homogeneity assumption, conversion of economic quantities into physical quantities (Dixit et al., 2012; Acquaye and Duffy, 2010; Pullen, 2007; Nielsen and Wiedmann, 2001; Treloar et al. 2001; Pullen, 2000).
I-O tables are generated at the national level, and domestic productions of imports are usually assumed during modelling. In open economies, this can lead to considerable errors (Weber and Mathews, 2007). Additionally, in the I-O method, the supply network can be artificially bounded based on the dataset employed for the analysis and does not take other factors such as important business processes and geographic location into consideration. In Chapter four (Sections 4.4.3 and 4.9), the approaches used to overcome some of the identified limitations are discussed. A comparison between process-based and I–O based methods is presented in Table 2-3.
Table 2-3: A comparison between process and I–O based approaches to lifecycle assessment
Method Advantages Disadvantages
Process
Provides detailed analysis of related to specific products, processes, or manufacturing chains of goods and services whose flows are easy to track at the physical level
Lack of quality data in most cases
Offers more reliable comparison of products Truncation error due to subjective system boundary
Allows easier identification of process
improvements Uncertainties in data collected
Time and cost intensive
Requires a great deal of data and specific information about the manufacturing of the target product
Input-Output
Comprehensive system boundary defined as
whole economy Errors in converting economic data to physical
quantities
Publicly available data Data is usually aggregated
Results can be reproduced Uncertainties in data collected
Suitable for aggregated nationwide problems. Identification of process improvements is difficult
Changes in price levels over time affects results Homogeneity and proportionality assumptions (i.e. Physical flows are assumed proportional to monetary values)
Change in the structure of the economy or change in technology adopted for producing goods and services can affect results
2.10.3. Hybrid analysis
Combining the accuracy and specificity of process-based approach together with the extended system boundary completeness of the I-O method in what has become collectively
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known as ‘hybrid analysis’ can produce results that has the benefits of both approaches in terms detail and comprehensiveness (Suh et al., 2004; Suh and Huppes, 2005; Mattila et al., 2010;
Acquaye, 2010; Wiedmann et al., 2011). By integrating the benefits of both process and I-O analysis, fundamental errors and limitations associated with each method can be eliminated, improving accuracy and precisions (ibid). Guinée et al. (2001) and all the researchers listed here also recommended the use of the hybrid approach as a procedure for filling data gaps. In the section that follows, a review of embodied emissions of international trade flows is presented