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Human exposure to indoor pollutant concentrations is receiving increasing interest in Life Cycle Assessment (LCA). We address this issue by incorporating an indoor compartment into the USEtox model, as well as by providing recommended parameter values for households in four different regions of the world differing geographically, economically, and socially. With these parameter values, intake fractions and comparative toxicity potentials for indoor emissions of dwellings for different air tightness levels were calculated. The resulting intake fractions for indoor exposure vary by 2 orders of magnitude, due to the variability of ventilation rate, building occupation, and volume. To compare health impacts as a result of indoor exposure with those from outdoor exposure, the indoor exposure characterization factors determined with the modified USEtox model were applied in a case study on cooking in non-OECD countries. This study demonstrates the appropriateness and significance of integrating indoor environments into LCA, which ensures a more holistic account of all exposure environments and allows for a better accountability of health impacts. The model, intake fractions, and characterization factors are made available for use in standard LCA studies via www.usetox.org and in standard LCA software.

Habitat degradation and subsequent biodiversity damage often take place far from the place of consumption because of globalization and the increasing level of international trade. Informing consumers and policy makers about the biodiversity impacts "hidden" in the life cycle of imported products is an important step toward achieving sustainable consumption patterns. Spatially explicit methods are needed in life cycle assessment to accurately quantify biodiversity impacts of products and processes. We use the Countryside species-area relationship (SAR) to quantify regional species loss due to land occupation and transformation for five taxa and six land use types in 804 terrestrial ecoregions. Further, we calculate vulnerability scores for each ecoregion based on the fraction of each species' geographic range (endemic richness) hosted by the ecoregion and the IUCN assigned threat level of each species. Vulnerability scores are multiplied with SAR-predicted regional species loss to estimate potential global extinctions per unit of land use. As a case study, we assess the land use biodiversity impacts of 1 kg of bioethanol produced using six different feed stocks in different parts of the world. Results show that the regions with highest biodiversity impacts differed markedly when the vulnerability of species was included.

Agricultural land use is a main driver of global biodiversity loss. The assessment of land use impacts in decision-support tools such as life cycle assessment (LCA) requires spatially explicit models, but existing approaches are either not spatially differentiated or modeled at very coarse scales (e.g., biomes or ecoregions). In this paper, we develop a high-resolution (900 m) assessment method for land use impacts on biodiversity based on habitat suitability models (HSM) of mammal species. This method considers potential land use effects on individual species, and impacts are weighted by the species' conservation status and global rarity. We illustrate the method using a case study of crop production in East Africa, but the underlying HSMs developed by the Global Mammals Assessment are available globally. We calculate impacts of three major export crops and compare the results to two previously developed methods (focusing on local and regional impacts, respectively) to assess the relevance of the methodological innovations proposed in this paper. The results highlight hotspots of product-related biodiversity impacts that help characterize the links among agricultural production, consumption, and biodiversity loss.

Resources have received significant attention in recent years resulting in development of a wide range of resource depletion indicators within life cycle assessment (LCA). Understanding the differences in assessment principles used to derive these indicators and the effects on the impact assessment results is critical for indicator selection and interpretation of the results. Eleven resource depletion methods were evaluated quantitatively with respect to resource coverage, characterization factors (CF), impact contributions from individual resources, and total impact scores. We included 2247 individual market inventory data sets covering a wide range of societal activities (ecoinvent database v3.0). Log-linear regression analysis was carried out for all pairwise combinations of the 11 methods for identification of correlations in CFs (resources) and total impacts (inventory data sets) between methods. Significant differences in resource coverage were observed (9-73 resources) revealing a trade-off between resource coverage and model complexity. High correlation in CFs between methods did not necessarily manifest in high correlation in total impacts. This indicates that also resource coverage may be critical for impact assessment results. Although no consistent correlations between methods applying similar assessment models could be observed, all methods showed relatively high correlation regarding the assessment of energy resources. Finally, we classify the existing methods into three groups, according to method focus and modeling approach, to aid method selection within LCA.

A process model of municipal solid waste incinerators (MSWIs) and new technologies for metal recovery from combustion residues was developed. The environmental impact is modeled as a function of waste composition as well as waste treatment and material recovery technologies. The model includes combustion with a grate incinerator, several flue gas treatment technologies, electricity and steam production from waste heat recovery, metal recovery from slag and fly ash, and landfilling of residues and can be tailored to specific plants and sites (software tools can be downloaded free of charge). Application of the model to Switzerland shows that the treatment of one tonne of municipal solid waste results on average in 425 kg CO2-eq. generated in the incineration process, and 54 kg CO2-eq. accrue in upstream processes such as waste transport and the production of operating materials. Downstream processes, i.e. residue disposal, generates 5 kg CO2-eq. Savings from energy recovery are in the range of 67 to 752 kg CO2-eq. depending on the assumptions regarding the substituted energy production, while the recovery of metals from slag and fly ash currently results in a net saving of approximately 35 kg CO2-eq. A similar impact pattern is observed when assessing the MSWI model for aggregated environmental impacts (ReCiPe) and for non-renewable resource consumption (cumulative exergy demand), except that direct emissions have less and no relevance, respectively, on the total score. The study illustrates that MSWI plants can be an important element of industrial ecology as they provide waste disposal services and can help to close material and energetic cycles., (Copyright © 2013 Elsevier Ltd. All rights reserved.)

Land use is one of the main drivers of biodiversity loss. However, many life cycle assessment studies do not yet assess this effect because of the lack of reliable and operational methods. Here, we present an approach to modeling the impacts of regional land use on plants, mammals, birds, amphibians, and reptiles. Our global analysis calculates the total potential damage caused by all land uses within each WWF ecoregion and allocates this total damage to different types of land use per ecoregion. We use an adapted (matrix-calibrated) species-area relationship to model the potential regional extinction of nonendemic species caused by reversible land use and land use change impacts. The potential global extinction of endemic species is used to assess irreversible, permanent impacts. Model uncertainty is assessed using Monte Carlo simulations. The impacts of land use on biodiversity varied strongly across ecoregions, showing the highest values in regions where most natural habitat had been converted in the past. The approach is thus retrospective and was able to highlight the impacts in highly disturbed regions. However, we also illustrate how it can be applied to prospective assessments using scenarios of future land use. Uncertainties, modeling choices, and validity are discussed.

Household consumption, apart from governmental consumption, is the main driver of worldwide economy. Attached to each household purchase are economic activities along the preceding supply chain, with the associated resource use and emissions. A method to capture and assess all these resource uses and emissions is life cycle assessment. We developed a model for the life cycle assessment of housing and land-based mobility (excluding air travel) consumption of individual households a small village in Switzerland. Statistical census and dwelling register data are the foundations of the model. In a case study performed on a midsized community, we found a median value of greenhouse gas emissions of 3.12 t CO2 equiv and a mean value of 4.30 t CO2 equiv per capita and year for housing and mobility. Twenty-one percent of the households in the investigated region were responsible for 50% of the total greenhouse gas emissions, meaning that if their emissions could be halved the total emissions of the community would be reduced by 25%. Furthermore, a cluster analysis revealed that driving factors for large environmental footprints are demands of large living area heated by fossil energy carriers, as well as large demands of motorized private transportation.

Comprehensive sensitivity analysis is a significant tool to interpret and improve life cycle assessment (LCA) models, but is rarely performed. Sensitivity analysis will increase in importance as inventory databases become regionalized, increasing the number of system parameters, and parametrized, adding complexity through variables and nonlinear formulas. We propose and implement a new two-step approach to sensitivity analysis. First, we identify parameters with high global sensitivities for further examination and analysis with a screening step, the method of elementary effects. Second, the more computationally intensive contribution to variance test is used to quantify the relative importance of these parameters. The two-step sensitivity test is illustrated on a regionalized, nonlinear case study of the biodiversity impacts from land use of cocoa production, including a worldwide cocoa products trade model. Our simplified trade model can be used for transformable commodities where one is assessing market shares that vary over time. In the case study, the highly uncertain characterization factors for the Ivory Coast and Ghana contributed more than 50% of variance for almost all countries and years examined. The two-step sensitivity test allows for the interpretation, understanding, and improvement of large, complex, and nonlinear LCA systems.

Wind energy is a fast-growing and promising renewable energy source. The investment costs of wind turbines have decreased over the years, making wind energy economically competitive to conventionally produced electricity. Size scaling in the form of a power law, experience curves and progress rates are used to estimate the cost development of ever-larger turbines. In life cycle assessment, scaling and progress rates are seldom applied to estimate the environmental impacts of wind energy. This study quantifies whether the trend toward larger turbines affects the environmental profile of the generated electricity. Previously published life cycle inventories were combined with an engineering-based scaling approach as well as European wind power statistics. The results showed that the larger the turbine is, the greener the electricity becomes. This effect was caused by pure size effects of the turbine (micro level) as well as learning and experience with the technology over time (macro level). The environmental progress rate was 86%, indicating that for every cumulative production doubling, the global warming potential per kWh was reduced by 14%. The parameters, hub height and rotor diameter were identified as Environmental Key Performance Indicators that can be used to estimate the environmental impacts for a generic turbine., (© 2012 American Chemical Society)

Global water use is dominated by agriculture and has considerable influence on people's livelihood and ecosystems, especially in semiarid and arid regions. Methods to address the impacts of water withdrawal and consumption on terrestrial and aquatic ecosystems within life cycle assessment are still sparse and very generic. Regionalized characterization factors (CFs) for a groundwater-fed wetland at the arid coast of Peru are developed for groundwater and surface water withdrawal and consumption in order to address the spatial dependency of water use related impacts. Several agricultural scenarios for 2020 were developed in a workshop with local stakeholders and used for calculating total biodiversity impacts. In contrast to assumptions used in top-down approaches (e.g., Pfister et al. Environ. Sci Technol. 2009, 43, 4098 ), irrigation with surface water leads in this specific region to benefits for the groundwater-fed wetland, due to additional groundwater recharge from surplus irrigation water. However, irrigation with groundwater leads to ecological damage to the wetland. The CFs derived from the different scenarios are similar and can thus be used as general CFs for this region, helping local decision-makers to plan future agricultural development, including irrigation technologies, crop choices, and protection of the wetland., (© 2012 American Chemical Society)

In the life cycle of engineered nanoparticles (ENP), their manufacturing requires particular attention because of unwanted potential ENP emissions to workplaces. We simulated three scenarios of equipment failure during gas phase production of nanoparticles in a laboratory. The emission plume of nanoparticles was tracked with high spatial and temporal resolution by 10 measurement devices. While under normal production conditions, no elevated ENP concentrations were observed, worst case scenarios led to homogeneous indoor ENP concentrations of up to 10(6)cm(-3) in a 300m(3) production room after only 60s. The fast dispersal in the room was followed by an exponential decrease in number concentration after the emission event. Under conditions like those observed - rapid dispersal and good mixing - a single measurement device alone can provide valuable information for an ENP exposure assessment. A one-box model adequately reflected measured number concentrations (r(2)>0.99). The ENP emission rates to the workplace were estimated between 2.5·10(11) and 6·10(12)s(-1) for the three emission scenarios. The worst case emission rate at the production zone was also estimated at 2·10(13)s(-1) with a stoichiometric calculation based on the precursor input, density and particle size. ENP intake fractions were 3.8-5.1·10(-4) inhaled ENP per produced ENP in the investigated setting. These could only be substantially lowered by leaving the production room within a few minutes after the emission event., (Copyright © 2012 Elsevier B.V. All rights reserved.)

Global crop production is causing pressure on water and land resources in many places. In addition to local resource management, the related environmental impacts of commodities traded along international supply chains need to be considered and managed accordingly. For this purpose, we calculate the specific water consumption and land use for the production of 160 crops and crop groups, covering most harvested mass on global cropland. We quantify indicators for land and water scarcity with high geospatial resolution. This facilitates spatially explicit crop-specific resource management and regionalized life cycle assessment of processed products. The vast cultivation of irrigated wheat, rice, cotton, maize, and sugar cane, which are major sources of food, bioenergy, and fiber, drives worldwide water scarcity. According to globally averaged production, substituting biofuel for crude oil would have a lower impact on water resources than substituting cotton for polyester. For some crops, water scarcity impacts are inversely related to land resource stress, illustrating that water consumption is often at odds with land use. On global average, maize performs better than rice and wheat in the combined land/water assessment. High spatial variability of water and land use related impacts underlines the importance of appropriate site selection for agricultural activities.

Chemical synthesis is a complex and diverse procedure, and production data are often scarce or incomplete. A detailed inventory analysis of all mass and energy flows necessary for the production of chemicals is often costly and time-intensive. Therefore only few chemical inventories exist, even though they are essential for process optimization and the environmental assessment of many products. This paper introduces a newtype of model to provide estimates for inventory data and environmental impacts of chemical production based on the molecular structure of a chemical and without a priori knowledge of the production process. These molecular-structure-based models offer inventory data for users in process design and optimization, screening life cycle assessment (LCA), and supply chain management. They can be applied even if the producer is unknown or the production process is not documented. We assessed the capabilities of linear regression and neural network models for this purpose. All models were generated with a data set of inventory data on 103 chemicals. Different input sets were chosen as ways to transform the chemical structure into a numerical vector of descriptors and the effectiveness of the different input sets was analyzed. The results show that a correctly developed neural network model can perform on an acceptable level for many purposes. The models can assist process developers to improve energy efficiency in all design stages and aid in LCA and supply chain management by filling data gaps.

Industrial wastewater-treatment systems need to ensure a high level of protection for the environment as a whole. Life-cycle assessment (LCA) comprehensively evaluates the environmental impacts of complex treatment systems, taking into account impacts from auxiliaries and energy consumption as well as emissions. However, the application of LCA is limited by a scarcity of wastewater-specific life-cycle inventory (LCI) data. This study presents a modular gate-to-gate inventory model for industrial wastewater purification in the chemical and related sectors. It enables the calculation of inventory parameters as a function of the wastewater composition and the technologies applied. Forthis purpose, data on energy and auxiliaries' consumption, wastewater composition, and process parameters was collected from chemical industry. On this basis, causal relationships between wastewater input, emissions, and technical inputs were identified. These causal relationships were translated into a generic inventory model. Generic and site-specific data ranges for LCI parameters are provided for the following processes: mechanical-biological treatment, high-pressure wet-air oxidation, nanofiltration, and extraction. The input- and technology-dependent process inventories help to bridge data gaps where primary data are not available. Thus, they substantially help to perform an environmental assessment of industrial wastewater purification in the chemical and associated industries, which may be used, for instance, for technology choices.

Pesticide leaching from agricultural fields to groundwater is an environmentally relevant and highly variable process. In the present paper, leaching scenarios typical in European agriculture are defined. These scenarios consider important sources of pesticide leaching variability, namely site factors, farming practice, and substance properties. The logic-tree method was used to structure these scenarios. For each scenario, leached fractions of pesticide applied in agriculture were calculated with data and models used in the registration process of the European Union (EU). Contributions of all parameters to variability were calculated for 11 pesticides. Substance properties (Koc and DT50,soil) contributed the mostto variability, followed by site, weather, season of application, crop, and macropore flow. The results of the variability assessment may be directly applied in policy making or they may be used in the environmental assessment of pesticides, e.g. with the life-cycle assessment (LCA) method. Several approaches are suggested for howthe variability assessment presented in this paper may be incorporated in LCA. The application of these approaches is illustrated by a case study on atrazine.