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Intro -- Preface -- Contents -- Contributors -- Chapter 1: Introducing Life Cycle Impact Assessment -- 1 Introduction -- 1.1 Historical Overview -- 2 Purpose and Structure -- 3 Characterisation Principles -- 3.1 Characterisation Framework -- 3.2 Impact Scores -- 3.3 Midpoint Versus Endpoint Indicators -- 3.4 Potential Impacts -- 3.5 Best Estimates -- 3.6 Spatial Differentiation -- 3.7 Linear, Average or Marginal Modelling -- 3.8 Uncertainty -- 4 Reading Guide to This Volume in the Book Series `LCA Compendium´ -- References -- Chapter 2: Selection of Impact Categories and Classification of LCI Results to Impact Categories -- 1 Introduction -- 2 History of Selection of Impact Categories and Classification -- 3 The Purpose of Selection of Impact Categories and Classification -- 4 Selection of Impact Categories -- 4.1 Different Ways of Defining Impact Categories -- 4.2 Default List of Impact Categories -- 5 Assignment of LCI Results to Impact Categories (Classification) -- 5.1 Identification of LCI Results That Relate to More Than One Impact Category -- 5.2 Handling Missing Information -- 6 Conclusions and Research Recommendations -- References -- Chapter 3: Climate Change -- 1 Impact Pathway -- 2 Contributing Substances -- 3 Scale, Spatial Variability, and Temporal Variability -- 4 Midpoint Methodologies -- 5 Endpoint Methodologies -- 6 New Developments and Research Needs -- References -- Chapter 4: Stratospheric Ozone Depletion -- 1 Stratospheric Ozone Chemistry -- 2 Anthropogenic Emissions -- 2.1 Halocarbon Emissions -- 2.2 Nitrous Oxide Emissions -- 2.3 Carbon Dioxide and Methane Emissions -- 3 Effects on Human Health and Ecosystems -- 4 Spatial and Temporal Variability -- 4.1 Spatial Variation -- Box 4.1 Commonly Used Metrics for Analysis of Ozone-Affecting Substances -- 4.2 Evolving Conditions Over Time.

This book offers a detailed presentation of the principles and practice of life cycle impact assessment. As a volume of the LCA compendium, the book is structured according to the LCIA framework developed by the International Organisation for Standardisation (ISO)passing through the phases of definition or selection of impact categories, category indicators and characterisation models (Classification): calculation of category indicator results (Characterisation); calculating the magnitude of category indicator results relative to reference information (Normalisation); and converting indicator results of different impact categories by using numerical factors based on value-choices (Weighting). Chapter one offers a historical overview of the development of life cycle impact assessment and presents the boundary conditions and the general principles and constraints of characterisation modelling in LCA. The second chapter outlines the considerations underlying the selection of impact categories and the classification or assignment of inventory flows into these categories. Chapters three through thirteen exploreall the impact categories that are commonly included in LCIA, discussing the characteristics of each followed by a review of midpoint and endpoint characterisation methods, metrics, uncertainties and new developments, and a discussion of research needs. Chapter-length treatment is accorded to Climate Change; Stratospheric Ozone Depletion; Human Toxicity; Particulate Matter Formation; Photochemical Ozone Formation; Ecotoxicity; Acidification; Eutrophication; Land Use; Water Use; and Abiotic Resource Use. The final two chapters map out the optional LCIA steps of Normalisation and Weighting.

Climate change poses a significant threat to global biodiversity, but freshwater fishes have been largely ignored in climate change assessments. Here, we assess threats of future flow and water temperature extremes to ~11,500 riverine fish species. In a 3.2 °C warmer world (no further emission cuts after current governments' pledges for 2030), 36% of the species have over half of their present-day geographic range exposed to climatic extremes beyond current levels. Threats are largest in tropical and sub-arid regions and increases in maximum water temperature are more threatening than changes in flow extremes. In comparison, 9% of the species are projected to have more than half of their present-day geographic range threatened in a 2 °C warmer world, which further reduces to 4% of the species if warming is limited to 1.5 °C. Our results highlight the need to intensify (inter)national commitments to limit global warming if freshwater biodiversity is to be safeguarded.

Biodiversity and ecosystem service losses driven by land-use change are expected to intensify as a growing and more affluent lobal population requires more agricultural and forestry products, and teleconnections in the global economy lead to increasing remote environmental responsibility. By combining global biophysical and economic models, we show that, between the years 2000 and 2011, overall population and economic growth resulted in increasing total impacts on bird diversity and carbon sequestration globally, despite a reduction of land-use impacts per unit of gross domestic product (GDP). The exceptions were North America and Western Europe, where there was a reduction of forestry and agriculture impacts on nature accentuated by the 2007–2008 financial crisis. Biodiversity losses occurred predominantly in Central and Southern America, Africa and Asia with international trade an important and growing driver. In 2011, 33% of Central and Southern America and 26% of Africa's biodiversity impacts were driven by consumption in other world regions. Overall, cattle farming is the major driver of biodiversity loss, but oil seed production showed the largest increases in biodiversity impacts. Forestry activities exerted the highest impact on carbon sequestration, and also showed the largest increase in the 2000–2011 period. Our results suggest that to address the biodiversity crisis, governments should take an equitable approach recognizing remote responsibility, and promote a shift of economic development towards activities with low biodiversity impacts.

Scenario-based biodiversity modelling is a powerful approach to evaluate how possible future socio-economic developments may affect biodiversity. Here, we evaluated the changes in terrestrial biodiversity intactness, expressed by the mean species abundance (MSA) metric, resulting from three of the shared socio-economic pathways (SSPs) combined with different levels of climate change (according to representative concentration pathways [RCPs]): a future oriented towards sustainability (SSP1xRCP2.6), a future determined by a politically divided world (SSP3xRCP6.0) and a future with continued global dependency on fossil fuels (SSP5xRCP8.5). To this end, we first updated the GLOBIO model, which now runs at a spatial resolution of 10 arc-seconds (~300 m), contains new modules for downscaling land use and for quantifying impacts of hunting in the tropics, and updated modules to quantify impacts of climate change, land use, habitat fragmentation and nitrogen pollution. We then used the updated model to project terrestrial biodiversity intactness from 2015 to 2050 as a function of land use and climate changes corresponding with the selected scenarios. We estimated a global area-weighted mean MSA of 0.56 for 2015. Biodiversity intactness declined in all three scenarios, yet the decline was smaller in the sustainability scenario (-0.02) than the regional rivalry and fossil-fuelled development scenarios (-0.06 and -0.05 respectively). We further found considerable variation in projected biodiversity change among different world regions, with large future losses particularly for sub-Saharan Africa. In some scenario-region combinations, we projected future biodiversity recovery due to reduced demands for agricultural land, yet this recovery was counteracted by increased impacts of other pressures (notably climate change and road disturbance). Effective measures to halt or reverse the decline of terrestrial biodiversity should not only reduce land demand (e.g. by increasing agricultural productivity and dietary changes) but ...

Scenario‐based biodiversity modelling is a powerful approach to evaluate how possible future socio‐economic developments may affect biodiversity. Here, we evaluated the changes in terrestrial biodiversity intactness, expressed by the mean species abundance (MSA) metric, resulting from three of the shared socio‐economic pathways (SSPs) combined with different levels of climate change (according to representative concentration pathways [RCPs]): a future oriented towards sustainability (SSP1xRCP2.6), a future determined by a politically divided world (SSP3xRCP6.0) and a future with continued global dependency on fossil fuels (SSP5xRCP8.5). To this end, we first updated the GLOBIO model, which now runs at a spatial resolution of 10 arc‐seconds (~300 m), contains new modules for downscaling land use and for quantifying impacts of hunting in the tropics, and updated modules to quantify impacts of climate change, land use, habitat fragmentation and nitrogen pollution. We then used the updated model to project terrestrial biodiversity intactness from 2015 to 2050 as a function of land use and climate changes corresponding with the selected scenarios. We estimated a global area‐weighted mean MSA of 0.56 for 2015. Biodiversity intactness declined in all three scenarios, yet the decline was smaller in the sustainability scenario (−0.02) than the regional rivalry and fossil‐fuelled development scenarios (−0.06 and −0.05 respectively). We further found considerable variation in projected biodiversity change among different world regions, with large future losses particularly for sub‐Saharan Africa. In some scenario‐region combinations, we projected future biodiversity recovery due to reduced demands for agricultural land, yet this recovery was counteracted by increased impacts of other pressures (notably climate change and road disturbance). Effective measures to halt or reverse the decline of terrestrial biodiversity should not only reduce land demand (e.g. by increasing agricultural productivity and dietary changes) but ...