Fundamentals of life cycle assessment

A life cycle assessment (LCA) analyses the environmental impacts linked with all stages of a product’s life usually from cradle-to-grave and sometimes for limited production steps. A formal approach is defined by the International Organization of Standardization (ISO, 2006a, ISO, 2006b). The approach covers four steps, as also shown in Figure 6 (blue boxes). They are explained in more detail in this sub-chapter and if not provided with another reference, they are in accordance with the ISO standards.

3.2.1 Goal and scope

The goal and scope definition talks about aims and intention of a study, as well as its functional unit and system boundaries. The functional unit is a measure for the product’s quantified functions, i.e. the inputs and outputs related to it. It makes a system comparable to a reference system, e.g. if there are two different systems that produce biogas in different ways. Hence, the functional unit for each system could then be the kilowatt-hours of produced heat or electricity or the cubic meters of obtained biogas. The system boundary defines the boundaries within which the product’s manufacturing, usage and disposal are analysed. It makes assumptions

Figure 3.3: Steps of a formal life cycle assessment.

Caption: own creation in accordance with the ISO standards (ISO, 2006a, MCMANUS, 2012, p.15).

about constraints due to data and cut-off criteria. The latter describes the level of precision and completeness within an LCA. As it is impossible to know and account for all impacts of a product, it is inevitable to cut-off, i.e., leave out, certain processes. LCA systems are often represented in a flow diagram which considers all unit processes within the boundaries. Normally, boundaries are defined for either the production of a product (cradle-to-gate), the utilisation and end-of-life phase (gate-to-grave or sometimes gate-to-gate) or both (cradle-to-grave) (ISO, 2006a, ISO, 2006b). The terminology for LCAs of transportation fuels often differentiates between well-to-pump (WTP) and well-to-wheels (WTW) analyses.

The first describes the exploitation and transportation of feedstock and the production, the transport and the distribution of a fuel. The second also includes the operation of the vehicle (LEE et al., 2016).

Goal and scope

Definition of the aim and the system boundary

Life cycle inventory (LCI)

Data collection

Life cycle impact assessment (LCIA)

Calculation of the environmental impact

Interpretation

Selection of impact categories, category indicators and characterisation models

Classification

Data sorting into different impacts such as GHG gases, ozone depleting gases etc.

Characterisation

Calculation of the contribution each flow makes to each category (e.g. CO2

equivalents)

Normalisation, grouping and weighting

MandatoryOptional

In general, it can be differentiated between attributional and consequential LCAs, which pursue different objectives. An attributional LCA quantifies the material and energy flows, as well as the environmental impacts, that are ideally directly linked with a product’s life cycle. The consequential approach stretches the boundaries and also includes indirectly linked environmental burdens as a consequence of the production decision. Hence, the systems contain only processes that are affected by the decision and thus change or modify their output (SONNEMANN et al., 2011, p. 47f). In principle, the attributional approach is also suitable for analyses that expand their system boundaries. However, the consequential approach is generally more elaborate than the attributional one, as it contains assumptions about processes and market mechanisms that occur far away from the actual product (BECK et al., 2019).

3.2.2 Life cycle inventory

The LCI comprises all inputs and outputs within the product system that occur for the production of the functional unit. For each unit process, data must be collected, as well as input and output flows defined; i.e., energy and raw materials used, other products produced and emissions emitted to air, soil and water (ISO, 2006a, ISO, 2006b). There are often constraints during data collection, which is why background data of elementary flows within the system are often taken from life cycle inventory databases. Foreground data of the main unit processes that are evaluated can also be gathered from literature or own measurements. LCA software can help to process inventory data (MCMANUS, 2012).

If the system produces valuable products aside from the main one, there are different opportunities to account for so-called co-products. This problem is called multi-functionality problem and often applies to integrated fuel production systems with cogeneration (ESCOBAR et al., 2015). It needs to be considered whether to allocate impacts to all products produced or use system expansion. According to the ISO (ISO, 2006a, ISO, 2006b), this can be solved by either partitioning (often referred to as ‘allocation’) or system expansion. The ISO 14044 (ISO, 2006b) recommends system expansion over allocation for attributional LCAs when the system delivers more than one product or function. This entails assuming that co-products replace other co-products in the market, generating co-product credits under system expansion approaches. The need for assumptions produces uncertainty due to modelling choices, in addition to parameter and model uncertainty (HUIJBREGTS et al., 2001). The products to be replaced normally depend on the relative prices, amongst other market factors, which in turn depend on the geographical and temporal scope of the LCA. In attributional LCA, co-product

credits are normally estimated by considering those co-products to be most likely replaced in the market, i.e. from average suppliers (FINNVEDEN et al., 2009). On the contrary, consequential LCA considers suppliers of marginal technologies by incorporating economic reasoning (EKVALL et al., 2004). Thus, the influence of such assumptions on results from both attributional and consequential LCA can be critical, especially when comparing systems against each other, and must be conveniently assessed through scenario analysis (ESCOBAR et al., 2014).

3.2.3 Life cycle impact assessment

The life cycle impact assessment (LCIA) evaluates the LCI results to determine significant environmental impacts. For this, the inventory data is associated with environmental categories and impact category indicators (also category indicator) in an attempt to better understand the impacts. This means that LCI results are assigned to impact categories, which in turn each have a quantifiable category indicator. However, the choice of impact categories introduces subjectivity.

Furthermore, the LCIA phase can also include iterative processes, which require the re-evaluation of the goal and scope if they are impossible to achieve. The steps in an LCIA are summarised in the dashed blue box in Figure 6. Three of four presented steps are mandatory, beginning with the selection of impact categories, category indicators and a characterisation model. During the classification step, input and output flows are sorted into different impact types such as GHG gases, ozone depleting gases and others. In the characterisation step, their relative contribution to each impact category is quantified using characterisation factors (e.g. kg CO2-eq. as presented in Table 3.7). Last but not least, it is optional if normalisation, grouping or weighting are applied. The first describes the calculation of the indicator results relative to a reference factor in order to better understand the magnitude of each indicator. Grouping combines impact categories into sets and sometimes sorts and ranks them based on value-choices. The categories either are sorted on a nominal basis or ranked according to a given hierarchy (ISO, 2006a, ISO, 2006b). Weighting converts indicator results using selected weighting factors or aggregates results across impact categories. Weighting helps with the identification of the most important impact categories and provides an aggregated score for the results (SALA et al., 2018).

For the characterisation step, there is a number of characterisation models available in LCA software to simplify the process. Although there are several models that can be used for this stage, such as CML 2001, TRACI 2.1, Environmental Footprint

2.0 and 3.0, we decided to introduce the ReCiPe 2016 in this study. The model is commonly used and also relevant for this LCA. It differentiates between the individualist, hierarchist and egalitarian perspective. This choice category determines the time horizon, which in turn affects both midpoint and endpoint modelling of climate change. Midpoint analyses consider impact categories such as global warming, i.e., climate change, marine and freshwater eutrophication and particulate matter among others. Endpoint analyses, on the other hand, use characterisation factors to summarise the impact categories in three main areas of protection, namely human health, (terrestrial and aquatic) ecosystems and resource availability (HUIJBREGTS et al., 2016). Weighting factors of environmental indicators are also included in the model, providing relative global warming impacts for a 100-year period for CO2, CH4 and N2O as presented in Table 3.7.

Commonly, the hierarchist view is taken, where the global warming potential of CH4 and N2O is 34 and 298 times higher compared to CO2, respectively.

Table 3.7: ReCiPe 2016 value choices of the modelling of the effect of GHGs and global warming potential for the three perspectives according to HUIJBREGTS et al. (2016, p. 24f).

Choice category Individualist Hierarchist Egalitarian

Time horizon 20 years 100 years 1000 years

Name Formula

Carbon dioxide CO2 1 1 1

Methane CH4 84 34 4.8

Nitrous oxide N2O 264 298 78.8

In the following, several environmental indicators are described that are calculated under the ReCiPe 2016 model and relevant to this analysis:

• Climate change or global warming potential (CC or GWP); excluding or including biogenic carbon, accounts for all GHG emissions in kg CO2-equivalents (kg CO2-eq. = category indicator) (CREMIATO et al., 2017).

• Freshwater and marine eutrophication potential (EP) have kg P-eq. and kg N-eq. as category indicators. It refers to an accumulation of nutrients in water or soil, i.e. the nutrient concentration rises above the specific water or soil volume. An augmentation in nutrients can lead to an overproduction of aquatic plants and algae, which then cover the water surface and reduce oxygen and sunlight penetration through the water’s top layer. In soil,

nitrogen can leach into water streams and cause eutrophication (MEZZULLO et al., 2013).

• The acidification potential (AP) accounts for NOx, SOx and ammonia emissions and summarises them under the category indicator of kg SO2-eq.

According to MEZZULLO et al. (2013), acidification is the effect of increasing pH acidity in waters and soils. Acid rain, as a form of acidification, can also be caused by air emission. It has a harmful effect especially on vegetation and is then summarised under the term terrestrial acidification.

• Human toxicity refers to several toxic substances that can be cancerous and non-cancerous and pose a risk to human health (kg 1,4-DB-eq.).

• The photochemical ozone formation (POF) cover the substances that are responsible for the production of photochemical ozone in the troposphere (kg NOx-eq.) (CREMIATO et al., 2017).

• Fossil depletion (FD) refers to abiotic resource consumption (kg oil-eq.).

• Stratospheric ozone depletion (ODP) refers to ozone-depleting gases that damage the ozone layer (kg CFC-11-eq.) (KUCKSHINRICHS et al., 2012).

There are certain levels of uncertainty and variability that occur due to the subjective choices, e.g., in impact categories and allocation or system expansion approaches. The level of completeness and precision (cut-off criteria) that is achieved is judged based on the LCIA results. Therefore, a sensitivity analysis should be carried out that shows how LCIA results are affected by methodological choices and data changes. It identifies the main elementary flows that contribute to the environmental impacts and those that are negligible. This makes it possible to check and validate the LCIA with reference to the goal and scope setup (EC et al., 2010).

3.2.4 Interpretation

The last phase in an LCA is the interpretation phase, which presents the results and compares them with the defined goal and scope. The phase should explain limitations, draw conclusions and ideally provide recommendations enabling future improvement of the system. It should also contain a sufficient evaluation of completeness, consistency and sensitivity. Further, it is important to point out that

LCIA results only represent the environmental potential and do not include risks or safety margins (ISO, 2006a, ISO, 2006b).