Description: Purpose   The aim of this paper is to provide science-based consensus and guidance for health effects modelling in comparative assessments based on human exposure and toxicity. This aim is achieved by (a) describing the USEtox™ exposure and toxicity models representing consensus and recommended modelling practice, (b) identifying key mechanisms influencing human exposure and toxicity effects of chemical emissions, (c) extending substance coverage. Methods   The methods section of this paper contains a detailed documentation of both the human exposure and toxic effects models of USEtox™, to determine impacts on human health per kilogram substance emitted in different compartments. These are considered as scientific consensus and therefore recommended practice for comparative toxic impact assessment. The framework of the exposure model is described in details including the modelling of each exposure pathway considered (i.e. inhalation through air, ingestion through (a) drinking water, (b) agricultural produce, (c) meat and milk, and (d) fish). The calculation of human health effect factors for cancer and non-cancer effects via ingestion and inhalation exposure respectively is described. This section also includes discussions regarding parameterisation and estimation of input data needed, including route-to-route and acute-to-chronic extrapolations. Results and discussion   For most chemicals in USEtox™, inhalation, above-ground agricultural produce, and fish are the important exposure pathways with key driving factors being the compartment and place of emission, partitioning, degradation, bioaccumulation and bioconcentration, and dietary habits of the population. For inhalation, the population density is the key factor driving the intake, thus the importance to differentiate emissions in urban areas, except for very persistent and mobile chemicals that are taken in by the global population independently from their place of emission. The analysis of carcinogenic potency (TD 50 ) when volatile chemicals are administrated to rats and mice by both inhalation and an oral route suggests that results by one route can reasonably be used to represent another route. However, we first identify and mark as interim chemicals for which observed tumours are directly related to a given exposure route (e.g. for nasal or lung, or gastrointestinal cancers) or for which absorbed fraction by inhalation and by oral route differ greatly. Conclusions   A documentation of the human exposure and toxicity models of USEtox™ is provided, and key factors driving the human health characterisation factor are identified. Approaches are proposed to derive human toxic effect factors and expand the number of chemicals in USEtox™, primarily by extrapolating from an oral route to exposure in air (and optionally acute-to-chronic). Some exposure pathways (e.g. indoor inhalation, pesticide residues, dermal exposure) will be included in a later stage. USEtox™ is applicable in various comparative toxicity impact assessments and not limited to LCA. Content Type Journal Article Pages 1-18 DOI 10.1007/s11367-011-0316-4 Authors Ralph K. Rosenbaum, Section for Quantitative Sustainability Assessment, Department of Management Engineering, Technical University of Denmark (DTU), Produktionstorvet, Building 426, 2800 Lyngby, Denmark Mark A. J. Huijbregts, Department of Environmental Science, Radboud University Nijmegen, P.O. Box 9010, 6500 GL, Nijmegen, The Netherlands Andrew D. Henderson, Department of Environmental Health Sciences, School of Public Health, University of Michigan, Ann Arbor, MI, USA Manuele Margni, Department of Chemical Engineering, CIRAIG, École Polytechnique de Montréal, 2900 Édouard-Montpetit, P.O. Box 6079, Stn. Centre-ville, Montréal, Québec H3C 3A7, Canada Thomas E. McKone, University of California Berkeley, Lawrence Berkeley National Laboratory, Berkeley, CA 94720, USA Dik van de Meent, Department of Environmental Science, Radboud University Nijmegen, P.O. Box 9010, 6500 GL, Nijmegen, The Netherlands Michael Z. Hauschild, Section for Quantitative Sustainability Assessment, Department of Management Engineering, Technical University of Denmark (DTU), Produktionstorvet, Building 426, 2800 Lyngby, Denmark Shanna Shaked, Department of Environmental Health Sciences, School of Public Health, University of Michigan, Ann Arbor, MI, USA Ding Sheng Li, Department of Environmental Health Sciences, School of Public Health, University of Michigan, Ann Arbor, MI, USA Lois S. Gold, University of California Berkeley, and Children’s Hospital Oakland Research Institute (CHORI), Oakland, CA, USA Olivier Jolliet, Department of Environmental Health Sciences, School of Public Health, University of Michigan, Ann Arbor, MI, USA Journal The International Journal of Life Cycle Assessment Online ISSN 1614-7502 Print ISSN 0948-3349

Description: Purpose   In general, pentachloroaniline (PCA) biodechlorination is specific to the conditions of a system; such conditions include the type and concentration of electron donors and oxidizing agents as well as nutrient availability, pH, and temperature. In the bioremediation of contaminated sediments and soil, most researchers have focused on the ability of various electron donors to remove target compounds. However, the amended electron donors and the byproduct of the anoxic/anaerobic systems may cause more environmental impact. Therefore, methods for consistently evaluating the environmental effects of such electron donors and byproducts are highly needed. Accordingly, life cycle assessment (LCA) was carried out to estimate the environmental effect of PCA biodechlorination under acidogenic/methanogenic conditions through laboratory-scale experiments. Four scenarios, intended to assess the influence of electron donors on the environment and develop laboratory experimental research, were compared. In these scenarios, four compounds were used: acetate, lactate, methanol, and glucose + methanol. Materials and methods   The LCA was carried out using IMPACT2002+ to estimate the environmental impact of PCA biodechlorination under acidogenic/methanogenic conditions. To add credibility to the study, sensitivity analysis was also conducted. Results and discussion   In all scenarios, the technologies significantly contributed to respiratory inorganics, global warming, as well as increased the adverse impact of nonrenewable energy on the environment. Specifically, the emissions from the electron donor production processes played an important role in the scenarios. PCA dechlorination and methanogenic processes substantially contributed to the aquatic/terrestrial ecotoxicity and global warming, respectively. Optimizing the concentration of amended electron donors and increasing the population size of dechlorinating microorganisms are highly important in reducing the environmental burden by PCA bioremediation. Conclusions   Results showed that the methanol scenario was the most suitable option determined in this research. In addition, results indicate amended electron donors can cause fewer environmental impacts in carcinogens and noncarcinogens categories. By contrast, the amended electron donors can significantly increase environmental impacts in respiratory inorganics, global warming, and nonrenewable energy categories. Increasing the population size of dechlorinating microorganisms and optimizing the concentration of amended electron donors are highly recommended to reduce adverse environmental impacts. Content Type Journal Article Category LIFE CYCLE MANAGEMENT Pages 1-10 DOI 10.1007/s11367-011-0338-y Authors Jinglan Hong, Shandong Provincial Key Laboratory of Water Pollution Control and Resource Reuse, School of Environmental Science and Engineering, Shandong University, Jinan, 250100 Shandong, People’s Republic of China Xiangzhi Li, Shandong University School of Medicine, Jinan, 250012 Shandong, People’s Republic of China Journal The International Journal of Life Cycle Assessment Online ISSN 1614-7502 Print ISSN 0948-3349

Description:    Although policymaking in response to the climate change threat is essentially a challenge of risk management, most studies of the relation of emissions targets to desired climate outcomes are either deterministic or subject to a limited representation of the underlying uncertainties. Monte Carlo simulation, applied to the MIT Integrated Global System Model (an integrated economic and earth system model of intermediate complexity), is used to analyze the uncertain outcomes that flow from a set of century-scale emissions paths developed originally for a study by the U.S. Climate Change Science Program. The resulting uncertainty in temperature change and other impacts under these targets is used to illustrate three insights not obtainable from deterministic analyses: that the reduction of extreme temperature changes under emissions constraints is greater than the reduction in the median reduction; that the incremental gain from tighter constraints is not linear and depends on the target to be avoided; and that comparing median results across models can greatly understate the uncertainty in any single model. Content Type Journal Article Pages 1-15 DOI 10.1007/s10584-011-0260-0 Authors Mort Webster, Joint Program on the Science and Policy of Global Change, Massachusetts Institute of Technology, Cambridge, MA, USA Andrei P. Sokolov, Joint Program on the Science and Policy of Global Change, Massachusetts Institute of Technology, Cambridge, MA, USA John M. Reilly, Joint Program on the Science and Policy of Global Change, Massachusetts Institute of Technology, Cambridge, MA, USA Chris E. Forest, Department of Meteorology, Pennsylvania State University, University Park, PA, USA Sergey Paltsev, Joint Program on the Science and Policy of Global Change, Massachusetts Institute of Technology, Cambridge, MA, USA Adam Schlosser, Joint Program on the Science and Policy of Global Change, Massachusetts Institute of Technology, Cambridge, MA, USA Chien Wang, Joint Program on the Science and Policy of Global Change, Massachusetts Institute of Technology, Cambridge, MA, USA David Kicklighter, The Ecosystems Center, Marine Biological Laboratory, Woods Hole, MA, USA Marcus Sarofim, AAAS Science and Technology Policy Fellow, U.S. Environmental Protection Agency, Washington DC, USA Jerry Melillo, The Ecosystems Center, Marine Biological Laboratory, Woods Hole, MA, USA Ronald G. Prinn, Joint Program on the Science and Policy of Global Change, Massachusetts Institute of Technology, Cambridge, MA, USA Henry D. Jacoby, Joint Program on the Science and Policy of Global Change, Massachusetts Institute of Technology, Cambridge, MA, USA Journal Climatic Change Online ISSN 1573-1480 Print ISSN 0165-0009

Description: Purpose   Sustainable manufacturing is practiced globally as a comprehensive strategy for improving the sustainability performance of the manufacturing industry. While sustainability is characterized into such three dimensions as economic, environmental, and social, currently, there is no quantitative method yet to measure the so-called “sustainability” in the manufacturing industry. The objective of this research is to develop a comprehensive and effective quantitative method to measure the overall sustainability performance of manufacturing companies. Methods   In this paper, an integrated methodology is presented for the development of composite sustainability indicators based on principal component analysis (PCA). In developing this integrated approach, both industry and academia surveys are conducted to identify what sustainability indicators are favored by the sustainable manufacturing community. A unique index is then generated to measure the overall sustainability performance of industrial practices. The methodology can be used for benchmarking the overall sustainability performance of various manufacturing companies. Results   A case study is conducted on a total of 11 global electronic manufacturing companies. The overall sustainability performance of these companies are measured, benchmarked, and ranked. The results showed that PCA is an effective approach for constructing composite sustainability indicators across environmental, economic, and social dimensions. Conclusions   From this research, it is found that industry and academia have different views on the sustainability measurement, evidenced by different weights put on the same indicator in industry and academia. The case study demonstrated that the methodology presented in this paper is an effective tool for comprehensive measurement of sustainability performance of manufacturing companies. Strengths and weaknesses of each company can be identified. Then, the recommended improvements can be suggested based on the study of each of the individual indicators. Content Type Journal Article Category SUSTAINABLE DEVELOPMENT Pages 1-11 DOI 10.1007/s11367-012-0394-y Authors Tao Li, School of Mechanical Engineering, Dalian University of Technology, No. 2 Linggong Road, Ganjingzi District, Dalian, Liaoning 116023, People’s Republic of China Hongchao Zhang, School of Mechanical Engineering, Dalian University of Technology, No. 2 Linggong Road, Ganjingzi District, Dalian, Liaoning 116023, People’s Republic of China Chris Yuan, Department of Mechanical Engineering, University of Wisconsin, Milwaukee, WI, USA Zhichao Liu, School of Mechanical Engineering, Dalian University of Technology, No. 2 Linggong Road, Ganjingzi District, Dalian, Liaoning 116023, People’s Republic of China Chengcheng Fan, Department of Management Science and Engineering, Stanford University, Stanford, CA, USA Journal The International Journal of Life Cycle Assessment Online ISSN 1614-7502 Print ISSN 0948-3349

Description:    Representative Concentration Pathway 6.0 (RCP6) is a pathway that describes trends in long-term, global emissions of greenhouse gases (GHGs), short-lived species, and land-use/land-cover change leading to a stabilisation of radiative forcing at 6.0 Watts per square meter (Wm −2 ) in the year 2100 without exceeding that value in prior years. Simulated with the Asia-Pacific Integrated Model (AIM), GHG emissions of RCP6 peak around 2060 and then decline through the rest of the century. The energy intensity improvement rates changes from 0.9% per year to 1.5% per year around 2060. Emissions are assumed to be reduced cost-effectively in any period through a global market for emissions permits. The exchange of CO 2 between the atmosphere and terrestrial ecosystem through photosynthesis and respiration are estimated with the ecosystem model. The regional emissions, except CO 2 and N 2 O, are downscaled to facilitate transfer to climate models. Content Type Journal Article Pages 1-18 DOI 10.1007/s10584-011-0150-5 Authors Toshihiko Masui, National Institute for Environmental Studies, 16-2 Onogawa, Tsukuba, Ibaraki 305-8506, Japan Kenichi Matsumoto, National Institute for Environmental Studies, 16-2 Onogawa, Tsukuba, Ibaraki 305-8506, Japan Yasuaki Hijioka, National Institute for Environmental Studies, 16-2 Onogawa, Tsukuba, Ibaraki 305-8506, Japan Tsuguki Kinoshita, Ibaraki University, 3-21-1 Chuo, Ami, Ibaraki 300-0393, Japan Toru Nozawa, National Institute for Environmental Studies, 16-2 Onogawa, Tsukuba, Ibaraki 305-8506, Japan Sawako Ishiwatari, National Institute for Environmental Studies, 16-2 Onogawa, Tsukuba, Ibaraki 305-8506, Japan Etsushi Kato, Japan Agency for Marine-Earth Science and Technology, 3173-25 Showa-machi, Kanazawa, Yokohama, Kanagawa 236-0001, Japan P. R. Shukla, Indian Institute of Management, Ahmedabad, Vastrapur, Ahmedabad, 380015 India Yoshiki Yamagata, National Institute for Environmental Studies, 16-2 Onogawa, Tsukuba, Ibaraki 305-8506, Japan Mikiko Kainuma, National Institute for Environmental Studies, 16-2 Onogawa, Tsukuba, Ibaraki 305-8506, Japan Journal Climatic Change Online ISSN 1573-1480 Print ISSN 0165-0009

Description: Wigand, L. A., Klinger, T., and Logsdon, M. G. 2013. Patterns in groundfish abundance along the Eastern Bering Sea outer continental margin. – ICES Journal of Marine Science, 70: 1181–1197. Place-based management approaches require understanding the spatial arrangement and interaction of elements. To address this need, we explored the utility of spatial-pattern analysis to understand the distribution of groundfish in the Eastern Bering Sea outer continental margin. We divided this region into discrete geomorphological units to explore spatial pattern on a range of scales. We used groundfish catch per unit effort (cpue) trawl survey data collected in four years to quantify spatial autocorrelation. Global statistics indicated that groundfish cpue was dominated by clusters of low values in all years. Local statistics showed that clusters of low values in groundfish cpue were confined to the southern portion of the study area, while clusters of high values varied across the study area. Outliers were most commonly found in close proximity to the shelf–slope break. Our results reveal the existence of spatial dependency in groundfish abundance and demonstrate that spatial analysis can be used to better understand spatial arrangements of these and other living marine resources, and to quantify and validate the local ecological knowledge of resource users. Our results indicate the feasibility of using spatially explicit tools to improve integration and visualization of marine environmental data for purposes of management and conservation.

Description:    This paper investigates changes in shoreline evolution caused by changes in wave climate. In particular, a number of nearshore wave climate scenarios corresponding to a ‘present’ (1961–1990) and a future time-slice (2071–2100) are used to drive a beach evolution model to determine monthly and seasonal statistics. To limit the number of variables, an idealised shoreline segment is adopted. The nearshore wave climate scenarios are generated from wind climate scenarios through point wave hindcast and inshore transformation. The original wind forcing comes from regional climate change model experiments of different resolutions and/or driving global climate models, representing different greenhouse-gas emission scenarios. It corresponds to a location offshore the south central coast of England. Hypothesis tests are applied to map the degree of evidence of future change in wave and shoreline statistics relative to the present. Differential statistics resulting from different global climate models and future emission scenarios are also investigated. Further, simple, fast, and straightforward methods that are capable of accommodating a great number of climate change scenarios with limited data reduction requirements are proposed to tackle the problem under consideration. The results of this study show that there are statistically significant changes in nearshore wave climate conditions and beach alignment between current and future climate scenarios. Changes are most notable during late summer for the medium-high future emission scenario and late winter for the medium-low. Despite frequent disagreement between global climate change models on the statistical significance of a change, all experiments agreed in future seasonal trends. Finally, a point of importance for coastal management, material shoreline changes are generally linked to significant changes in future wave direction rather than wave height. Content Type Journal Article Pages 1-33 DOI 10.1007/s10584-010-0011-7 Authors Anna Zacharioudaki, CIMA - Centre for Marine and Environmental Research, University of the Algarve, Hidrotec-ISE, Campus da Penha, Faro, 8005-139 Portugal Dominic E. Reeve, School of Marine Science and Engineering, University of Plymouth, Drake Circus, Plymouth, Devon PL4 8AA, UK Journal Climatic Change Online ISSN 1573-1480 Print ISSN 0165-0009