R. van Zelm

ReCiPe2016: A harmonised life cycle impact assessment method at midpoint and endpoint level

PurposeLife cycle impact assessment (LCIA) translates emissions and resource extractions into a limited number of environmental impact scores by means of so-called characterisation factors. There are two mainstream ways to derive characterisation factors, i.e. at midpoint level and at endpoint level. To further progress LCIA method development, we updated the ReCiPe2008 method to its version of 2016. This paper provides an overview of the key elements of the ReCiPe2016 method.MethodsWe implemented human health, ecosystem quality and resource scarcity as three areas of protection. Endpoint characterisation factors, directly related to the areas of protection, were derived from midpoint characterisation factors with a constant mid-to-endpoint factor per impact category. We included 17 midpoint impact categories.Results and discussionThe update of ReCiPe provides characterisation factors that are representative for the global scale instead of the European scale, while maintaining the possibility for a number of impact categories to implement characterisation factors at a country and continental scale. We also expanded the number of environmental interventions and added impacts of water use on human health, impacts of water use and climate change on freshwater ecosystems and impacts of water use and tropospheric ozone formation on terrestrial ecosystems as novel damage pathways. Although significant effort has been put into the update of ReCiPe, there is still major improvement potential in the way impact pathways are modelled. Further improvements relate to a regionalisation of more impact categories, moving from local to global species extinction and adding more impact pathways.ConclusionsLife cycle impact assessment is a fast evolving field of research. ReCiPe2016 provides a state-of-the-art method to convert life cycle inventories to a limited number of life cycle impact scores on midpoint and endpoint level.

Implementing Groundwater Extraction in Life Cycle Impact Assessment: Characterization Factors Based on Plant Species Richness for the Netherlands

An operational method to evaluate the environmental impacts associated with groundwater use is currently lacking in life cycle assessment (LCA). This paper outlines a method to calculate characterization factors that address the effects of groundwater extraction on the species richness of terrestrial vegetation. Characterization factors (CF) were derived for The Netherlands and consist of a fate and an effect part. The fate factor equals the change in drawdown due to a change in groundwater extraction and expresses the amount of time required for groundwater replenishment. It was obtained with a grid-specific steady-state groundwater flow model. Effect factors were obtained from groundwater level response curves of potential plant species richness, which was constructed based on the soil moisture requirements of 625 plant species. Depending on the initial groundwater level, effect factors range up to 9.2% loss of species per 10 cm of groundwater level decrease. The total Dutch CF for groundwater extraction depended on the value choices taken and ranged from 0.09 to 0.61 m(2)·yr/m(3). For tap water production, we showed that groundwater extraction can be responsible for up to 32% of the total terrestrial ecosystem damage. With the proposed approach, effects of groundwater extraction on terrestrial ecosystems can be systematically included in LCA.

Valuing the human health damage caused by the fraud of Volkswagen.

Recently it became known that Volkswagen Group has been cheating with emission tests for diesel engines over the last six years, resulting in on-road emissions vastly exceeding legal standards for nitrogen oxides in Europe and the United States. Here, we provide an estimate of the public health consequences caused by this fraud. From 2009 to 2015, approximately nine million fraudulent Volkswagen cars, as sold in Europe and the US, emitted a cumulative amount of 526 ktonnes of nitrogen oxides more than was legally allowed. These fraudulent emissions are associated with 45 thousand disability-adjusted life years (DALYs) and a value of life lost of at least 39 billion US dollars, which is approximately 5.3 times larger than the 7.3 billion US dollars that Volkswagen Group has set aside to cover worldwide costs related to the diesel emissions scandal.

Combined ecological risks of nitrogen and phosphorus in European freshwaters.

Eutrophication is a key water quality issue triggered by increasing nitrogen (N) and phosphorus (P) levels and potentially posing risks to freshwater biota. We predicted the probability that an invertebrate species within a community assemblage becomes absent due to nutrient stress as the ecological risk (ER) for European lakes and streams subjected to N and P pollution from 1985 to 2011. The ER was calculated as a function of species-specific tolerances to NO3(-) and total P concentrations and water quality monitoring data. Lake and stream ER averaged 50% in the last monitored year (i.e. 2011) and we observed a decrease by 22% and 38% in lake and stream ER (respectively) of river basins since 1985. Additionally, the ER from N stress surpassed that of P in both freshwater systems. The ER can be applied to identify river basins most subjected to eutrophication risks and the main drivers of impacts.

Characterization factors for terrestrial acidification at the global scale: a systematic analysis of spatial variability and uncertainty.

Characterization factors (CFs) are used in life cycle assessment (LCA) to quantify the potential impact per unit of emission. CFs are obtained from a characterization model which assess the environmental mechanisms along the cause-effect chain linking an emission to its potential damage on a given area of protection, such as loss in ecosystem quality. Up to now, CFs for acidifying emissions did not cover the global scale and were only representative of their characterization model geographical scope. Consequently, current LCA practices implicitly assume that all emissions from a global supply chain occur within the continent referring to the characterization method geographical scope. This paper provides worldwide 2°×2.5° spatially-explicit CFs, representing the change in relative loss of terrestrial vascular plant species due to an emission change of nitrogen oxides (NOx), ammonia (NH3) and sulfur dioxide (SO2). We found that spatial variability in the CFs is much larger compared to statistical uncertainty (six orders of magnitude vs. two orders of magnitude). Spatial variability is mainly caused by the atmospheric fate factor and soil sensitivity factor, while the ecological effect factor is the dominant contributor to the statistical uncertainty. The CFs provided in our study allow the worldwide spatially explicit evaluation of life cycle impacts related to acidifying emissions. This opens the door to evaluate regional life cycle emissions of different products in a global economy.

Plant Species Sensitivity Distributions for ozone exposure

This study derived Species Sensitivity Distributions (SSD), representing a cumulative stressor-response distribution based on single-species sensitivity data, for ozone exposure on natural vegetation. SSDs were constructed for three species groups, i.e. trees, annual grassland and perennial grassland species, using species-specific exposure-response data. The SSDs were applied in two ways. First, critical levels were calculated for each species group and compared to current critical levels for ozone exposure. Second, spatially explicit estimates of the potentially affected fraction of plant species in Northwestern Europe were calculated, based on ambient ozone concentrations. We found that the SSD-based critical levels were lower than for the current critical levels for ozone exposure, with conventional critical levels for ozone relating to 8-20% affected plant species. Our study shows that the SSD concept can be successfully applied to both derive critical ozone levels and estimate the potentially affected species fraction of plant communities along specific ozone gradients.

Global spatially explicit CO2 emission metrics for forest bioenergy.

Emission metrics aggregate climate impacts of greenhouse gases to common units such as CO2-equivalents (CO2-eq.). Examples include the global warming potential (GWP), the global temperature change potential (GTP) and the absolute sustained emission temperature (aSET). Despite the importance of biomass as a primary energy supplier in existing and future scenarios, emission metrics for CO2 from forest bioenergy are only available on a case-specific basis. Here, we produce global spatially explicit emission metrics for CO2 emissions from forest bioenergy and illustrate their applications to global emissions in 2015 and until 2100 under the RCP8.5 scenario. We obtain global average values of 0.49 ± 0.03 kgCO2-eq. kgCO2−1 (mean ± standard deviation) for GWP, 0.05 ± 0.05 kgCO2-eq. kgCO2−1 for GTP, and 2.14·10−14 ± 0.11·10−14 °C (kg yr−1)−1 for aSET. We explore metric dependencies on temperature, precipitation, biomass turnover times and extraction rates of forest residues. We find relatively high emission metrics with low precipitation, long rotation times and low residue extraction rates. Our results provide a basis for assessing CO2 emissions from forest bioenergy under different indicators and across various spatial and temporal scales.

Biodiversity impacts from water consumption on a global scale for use in life cycle assessment

PurposeAgriculture is a major water user worldwide, potentially depriving many ecosystems of water. Comprehensive global impact assessment methodologies are therefore required to assess impacts from water consumption on biodiversity. Since scarcity of water, as well as species richness, varies greatly between different world regions, a spatially differentiated approach is needed. Therefore, our aim is to enhance a previously published methodology in terms of spatial and species coverage.MethodsWe developed characterization factors for lifecycle impact assessment (LCIA) targeting biodiversity loss of various animal taxa (i.e., birds, reptiles, mammals, and amphibians) in wetlands. Data was collected for more than 22,000 wetlands worldwide, distinguishing between surface water- and groundwater-fed wetlands. Additionally, we account for a loss of vascular plant species in terrestrial ecosystems, based on precipitation. The characterization factors are expressed as global fractions of potential species extinctions (PDF) per cubic meter of water consumed annually and are developed with a spatial resolution of 0.05 arc degrees. Based on the geographic range of species, as well as their current threat level, as indicated by the International Union for Conservation of Nature (IUCN), we developed a vulnerability indicator that is included in the characterization factor.Results and discussionCharacterization factors have maximal values in the order of magnitude of 10−11 PDF·year/m3 for animal taxa combined and 10−12 PDF·year/m3 for vascular plants. The application of the developed factors for global cultivation of wheat, maize, cotton, and rice highlights that the amount of water consumption alone is not sufficient to indicate the places of largest impacts but that species richness and vulnerability of species are indeed important factors to consider. Largest impacts are calculated for vascular plants in Madagascar, for maize, and for animal taxa; in Australia and the USA for surface water consumption (cotton); and in Algeria and Tunisia for groundwater consumption (cotton).ConclusionsWe developed a spatially differentiated approach to account for impacts from water consumption on a global level. We demonstrated its functionality with an application to a global case study of four different crops.

Evaluation of SimpleTreat 4.0: Simulations of pharmaceutical removal in wastewater treatment plant facilities

In this study, the removal of pharmaceuticals from wastewater as predicted by SimpleTreat 4.0 was evaluated. Field data obtained from literature of 43 pharmaceuticals, measured in 51 different activated sludge WWTPs were used. Based on reported influent concentrations, the effluent concentrations were calculated with SimpleTreat 4.0 and compared to measured effluent concentrations. The model predicts effluent concentrations mostly within a factor of 10, using the specific WWTP parameters as well as SimpleTreat default parameters, while it systematically underestimates concentrations in secondary sludge. This may be caused by unexpected sorption, resulting from variability in WWTP operating conditions, and/or QSAR applicability domain mismatch and background concentrations prior to measurements. Moreover, variability in detection techniques and sampling methods can cause uncertainty in measured concentration levels. To find possible structural improvements, we also evaluated SimpleTreat 4.0 using several specific datasets with different degrees of uncertainty and variability. This evaluation verified that the most influencing parameters for water effluent predictions were biodegradation and the hydraulic retention time. Results showed that model performance is highly dependent on the nature and quality, i.e. degree of uncertainty, of the data. The default values for reactor settings in SimpleTreat result in realistic predictions.

Addressing land use and ecotoxicological impacts in Life cycle Assessments of food production technologies

Abstract: Effects of land use and ecotoxicity are not commonly addressed in Life Cycle Assessment on agricultural food production, due to the expected high level of uncertainties in the impact assessment and a lack of available inventory data. This chapter provides an overview of the cause–effect pathways related to the release of toxic chemicals and physical land use practices caused by food production practices. It also discusses the background and application of several Life Cycle Impact Assessment methods that produce so-called Characterization Factors to quantify the environmental effects of the agricultural activity occurring along the cause–effect pathways. Particular attention is paid to advances in the data and modelling of ecotoxicological and land use impacts that resulted in the development of a consensus model to calculate characterization factors for aquatic ecotoxicity and several models to calculate characterization factors for land use. Finally, for both ecotoxicity and land use modelling, a number of uncertainties are discussed and several requirements for improvement are proposed.