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5 Life Cycle Assessment of Chemical Products and Processes
method at early stages. Even with limited data, an LCA based on key indicators such
as energy and material use, water consumption, solvent consumption, production
of coproducts and waste, critical individual substances, etc. can provide important
screening information on the environmental compatibility of product and process
alternatives.
The functional unit is an important aspect within an LCA. It can be understood
as the reference utility or service to which input and output flows and the associated
impacts of a product or process are all related. It should express the benefits of the
technical system (normally a product or process) under review as comprehensively
and quantitatively as possible, which means it should be clearly definable and
measurable. A few examples of functional units include:
• For an herbicide: The quantity of the herbicide required for the control of
infestation by weeds of a given cultivated area with a specific selectivity and
over a certain period
• For a textile dye: The quantity of dyestuff required to color a given amount and
quality of cotton in a specific way (considering desired color, lightfastness, etc.)
• For the production of a chemical: Production of a specific quantity (e.g., 1 kg)
of a given chemical of a certain quality that has to be produced under specific
technical and socioeconomic conditions
The system boundaries that need to be defined within an LCA include the spatial
and temporal limits of the system, processes and emissions to be neglected, as well
as the definition of allocation criteria (introduced later in Sect. 5.4.2). The desired
impact categories to be calculated are also chosen and documented in this first step,
along with the methods and models that will be used to calculate them. These are
introduced and discussed in more detail in Sect. 5.5.
Naturally, the results of a life cycle assessment are associated with uncertainties.
When defining the goal and scope, it is important to also determine the width and
depth needed for the analysis. This includes the completeness, consistency, and level
of data quality required, as well as how data gaps will be treated. The uncertainty
can be characterized using confidence intervals and sensitivity analyses or by error
calculations. Recent literature has provided a better understanding of how system
assumptions and value choices can impact overall uncertainty (De Schryver et al.,
2013; Gregory et al., 2013), and quantitative uncertainty assessment methods are
also available (Lloyd and Ries, 2008).
The set goal and scope of the LCA also have an impact on the choice of
background technologies (such as energy supply and waste disposal methods) that
will be used in the second LCA step of inventory analysis, which is introduced
in the next section. For example, while the evaluation of existing products and
processes may be based on averaged data from existing technologies, development
projects should use background data from the latest or even future (prospective)
technologies, such as advanced renewable energy sources or recycling processes.
5 Life Cycle Assessment of Chemical Products and Processes
method at early stages. Even with limited data, an LCA based on key indicators such
as energy and material use, water consumption, solvent consumption, production
of coproducts and waste, critical individual substances, etc. can provide important
screening information on the environmental compatibility of product and process
alternatives.
The functional unit is an important aspect within an LCA. It can be understood
as the reference utility or service to which input and output flows and the associated
impacts of a product or process are all related. It should express the benefits of the
technical system (normally a product or process) under review as comprehensively
and quantitatively as possible, which means it should be clearly definable and
measurable. A few examples of functional units include:
• For an herbicide: The quantity of the herbicide required for the control of
infestation by weeds of a given cultivated area with a specific selectivity and
over a certain period
• For a textile dye: The quantity of dyestuff required to color a given amount and
quality of cotton in a specific way (considering desired color, lightfastness, etc.)
• For the production of a chemical: Production of a specific quantity (e.g., 1 kg)
of a given chemical of a certain quality that has to be produced under specific
technical and socioeconomic conditions
The system boundaries that need to be defined within an LCA include the spatial
and temporal limits of the system, processes and emissions to be neglected, as well
as the definition of allocation criteria (introduced later in Sect. 5.4.2). The desired
impact categories to be calculated are also chosen and documented in this first step,
along with the methods and models that will be used to calculate them. These are
introduced and discussed in more detail in Sect. 5.5.
Naturally, the results of a life cycle assessment are associated with uncertainties.
When defining the goal and scope, it is important to also determine the width and
depth needed for the analysis. This includes the completeness, consistency, and level
of data quality required, as well as how data gaps will be treated. The uncertainty
can be characterized using confidence intervals and sensitivity analyses or by error
calculations. Recent literature has provided a better understanding of how system
assumptions and value choices can impact overall uncertainty (De Schryver et al.,
2013; Gregory et al., 2013), and quantitative uncertainty assessment methods are
also available (Lloyd and Ries, 2008).
The set goal and scope of the LCA also have an impact on the choice of
background technologies (such as energy supply and waste disposal methods) that
will be used in the second LCA step of inventory analysis, which is introduced
in the next section. For example, while the evaluation of existing products and
processes may be based on averaged data from existing technologies, development
projects should use background data from the latest or even future (prospective)
technologies, such as advanced renewable energy sources or recycling processes.