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Quantifying effects of physical, chemical and biological stressors in life cycle assessment

Quantifying effects of physical, chemical and biological stressors in life cycle assessment
MARLIA MOHD HANAFIAH

2013

Faculty of Mathematics and Computer Science, Radboud University, 6525 HP Nijmegen, NETHERLANDS.

ABSTRACT

Life Cycle Assessment (LCA) is a tool to evaluate and model the environmental impacts and resources associated with a product, process or service throughout its life cycle (i.e., from raw material acquisition, via production and use phases and to disposal). This PhD thesis focuses on the life cycle impact assessment (LCIA), the phase where potential environmental impacts associated with identified inputs and releases are modelled and expressed in terms of characterization factors (CFs).

Although the characterization factors to assess impacts associated with terrestrial ecosystems in the LCIA methodology are available for a wide range of stressors, evaluation on how the results for terrestrial ecosystems would be when a simple method such as ecological footprint (EF) is applied still remains unknown. For the assessment of effects on freshwater ecosystem quality, this part is still lacking in the LCA framework. While few freshwater-related impacts are currently included in LCA at the level of effects on biodiversity, other relevant impacts due to thermal emissions, global warming, water use and exotic species have so far not been included in the LCIA.

The overall aim of this PhD thesis is two-fold:
  • 1. To include impacts of other stressors (nutrients and non-CO2 greenhouse gases) on terrestrial ecosystems in the ecological footprint methods and to compare the common bioproductivity-based with a newly developed biodiversity-based ecological footprint.
  • 2. To develop life cycle impact assessment methods to assess damages towards freshwater ecosystems related to thermal emissions, climate change, water use and introduction of exotic species.

Chapter 2 investigates the influence of nutrients and non-CO2 greenhouse gases in the ecological footprint (EF) calculations. It was found that for most of the products included in the study, the influence of the addition of emissions of nutrients and non-CO2 greenhouse gases was typically smaller than 20%. The EF was generally dominated by CO2 emissions or direct land use. However, for goods and services within specific product categories, i.e., waste treatment processes, bio-based energy, agricultural products and chemicals, adding non-CO2 greenhouse gas emissions to air and nutrient emissions to water can have a dominant influence on the EF. Our findings suggest that in specific cases, the inclusion of non-CO2 greenhouse gases and nutrient emissions can indeed change the interpretation of the EF results.

Chapter 3 analyzed the ecological footprint (EFs) of products comparing biodiversity-based impacts with bioproductivity-based impacts. Impact on biodiversity was quantified with the mean species abundance indicator, while impact on bioproductivity was based on the common ecological footprint calculations. In the analysis we used a data set of 1340 product systems, subdivided into 13 product groups. The product groups include various types of energy generation and material production. We found that the ranking of production processes can change by the selection of biodiversity-based EF instead of the common bioproductivity-based EF. This is particularly the case if the EFs of bio-based products, dominated by direct land use, are compared with the EFs of fossil-based products, dominated by CO2 emissions. The results also show that the relative importance of different drivers can change over time within the biodiversity perspective. The relative importance of climate change is expected to increase significantly, particularly when projected for a longer time horizon. As the interpretation of the biodiversity-based EFs can differ from the bioproductivity-based EFs, the inclusion of impacts on biodiversity should be considered in the EF calculation.

Chapter 4 develops and implements a model framework to assess the impact of thermal pollution on freshwater ecosystem. A method to derive characterization factors for the impact of cooling water discharges on aquatic ecosystems was developed which uses space and time explicit integration of fate and effects of water temperature changes. The fate factor is calculated with a 1-dimensional steady-state model and reflects the residence time of heat emissions in the river. The effect factor specifies the loss of species diversity per unit of temperature increase and is based on a species sensitivity distribution of temperature tolerance intervals for various aquatic species. As an example, time explicit characterization factors were calculated for the cooling water discharge of a nuclear power plant in Switzerland, quantifying the impact on aquatic ecosystems of the rivers Aare and Rhine. The relevance of thermal emissions constitutes 0.01% of the total environmental impact. For freshwater ecosystem quality, thermal emissions contribute 49% of the whole freshwater impact in the case of a once-through cooling system.

In chapter 5, an operational method is developed to derive characterization factors for direct water consumption and global warming based on freshwater ecosystem damages. We derived characterization factors for water consumption and global warming based on freshwater fish species loss. Calculation of characterization factors for potential freshwater fish losses from water consumption were estimated using a generic species-river discharge curve for 214 global river basins. We also derived characterization factors for potential freshwater fish species losses per unit of greenhouse gas emission. Based on five global climate scenarios, characterization factors for 63 greenhouse gas emissions were calculated. The study shows that depending on the river considered, characterization factors for water consumption can differ up to 3 orders of magnitude. Characterization factors for greenhouse gas emissions can vary up to 5 orders of magnitude, depending on the atmospheric residence time and radiative forcing efficiency of greenhouse gas emissions. An emission of 1 ton of CO2 is expected to cause the same impact on potential fish species disappearance as the water consumption of 10-1000 m3, depending on the river basin considered.

Chapter 6 demonstrates the possibility of calculating the introduction of exotic species characterization factors for freshwater ecosystem. The ecological impact of anthropogenically introduced exotic species is generally not accounted for in the environmental life cycle assessment (LCA) of products, while it is considered one of the major treats for anthropogenic stressors nowadays. Here, we propose a framework to include exotic species introduction in an LCA context. As an example, we derived characterization factors for exotic fish species introduction, expressed as the potentially disappeared fraction of native freshwater species in the rivers Rhine and Danube integrated over space and time, related to transport of goods across the Rhine-Main-Danube canal. We also quantified the relative importance of exotic fish species introduction compared to other anthropogenic stressors in the freshwater environment. We found that the relative importance of introduction of exotic fish species is 20 - 34% of the total freshwater ecosystem impact, depending on the transport distance of goods (3000 km vs. 1500 km, respectively). Our analysis showed that it is relevant and feasible to include the introduction of exotic species in an LCA framework. The framework proposed can be further extended by including impacts of other exotic species groups, types of water bodies and pathways for introduction.

Chapter 7 provides an overview of the new approaches to the modelling of the terrestrial and freshwater ecosystems damage caused by several relevant impact categories. Limitations and uncertainties of the methods developed in this PhD thesis are also touched upon in the Chapter 7. Practical implications and recommendations for future research are given in the end of this chapter.