Global trends and scenarios for terrestrial biodiversity and ecosystem services from 1900 to 2050.

Based on an extensive model intercomparison, we assessed trends in biodiversity and ecosystem services from historical reconstructions and future scenarios of land-use and climate change. During the 20th century, biodiversity declined globally by 2 to 11%, as estimated by a range of indicators. Provisioning ecosystem services increased several fold, and regulating services decreased moderately. Going forward, policies toward sustainability have the potential to slow biodiversity loss resulting from land-use change and the demand for provisioning services while reducing or reversing declines in regulating services. However, negative impacts on biodiversity due to climate change appear poised to increase, particularly in the higher-emissions scenarios. Our assessment identifies remaining modeling uncertainties but also robustly shows that renewed policy efforts are needed to meet the goals of the Convention on Biological Diversity.

Enhanced Deep-Learning Model for Carbon Footprints of Chemicals.

Millions of chemicals have been designed; however, their product carbon footprints (PCFs) are largely unknown, leaving questions about their sustainability. This general lack of PCF data is because the data needed for comprehensive environmental analyses are typically not available in the early molecular design stages. Several predictive tools have been developed to estimate the PCF of chemicals, which are applicable to only a narrow range of common chemicals and have limited predictive ability. Here, we propose FineChem 2, which is based on a novel transformer framework and first-hand industry data, for accurately predicting the PCF of chemicals. Compared to previous tools, FineChem 2 demonstrates significantly better predictive power, and its applicability domains are improved by ∼75% on a diverse set of chemicals on the global market, including the high-production-volume chemicals identified by regulators, daily chemicals, and chemical additives in food and plastics. In addition, through better interpretability from the attention mechanism, FineChem 2 may successfully identify PCF-intensive substructures and critical raw materials of chemicals, providing insights into the design of more sustainable molecules and processes. Therefore, we highlight FineChem 2 for estimating the PCF of chemicals, contributing to advancements in the sustainable transition of the global chemical industry.

Legacy and Emerging Plasticizers and Stabilizers in PVC Floorings and Implications for Recycling.

Hazardous chemicals in building and construction plastics can lead to health risks due to indoor exposure and may contaminate recycled materials. We systematically sampled new polyvinyl chloride floorings on the Swiss market (n = 151). We performed elemental analysis by X-ray fluorescence, targeted and suspect gas chromatography-mass spectrometry analysis of ortho-phthalates and alternative plasticizers, and bioassay tests for cytotoxicity and oxidative stress, and endocrine, mutagenic, and genotoxic activities (for selected samples). Surprisingly, 16% of the samples contained regulated chemicals above 0.1 wt %, mainly lead and bis(2-ethylhexyl) phthalate (DEHP). Their presence is likely related to the use of recycled PVC in new flooring, highlighting that uncontrolled recycling can delay the phase-out of hazardous chemicals. Besides DEHP, 29% of the samples contained other ortho-phthalates (mainly diisononyl and diisodecyl phthalates, DiNP and DiDP) above 0.1 wt %, and 17% of the samples indicated a potential to cause biological effects. Considering some overlap between these groups, they together make up an additional 35% of the samples of potential concern. Moreover, both suspect screening and bioassay results indicate the presence of additional potentially hazardous substances. Overall, our study highlights the urgent need to accelerate the phase-out of hazardous substances, increase the transparency of chemical compositions in plastics to protect human and ecosystem health, and enable the transition to a safe and sustainable circular economy.

Global site-specific health impacts of fossil energy, steel mills, oil refineries and cement plants.

Climate change and particulate matter air pollution present major threats to human well-being by causing impacts on human health. Both are connected to key air pollutants such as carbon dioxide (CO[Formula: see text]), primary fine particulate matter (PM[Formula: see text]), sulfur dioxide (SO[Formula: see text]), nitrogen oxides (NO[Formula: see text]) and ammonia (NH[Formula: see text]), which are primarily emitted from energy-intensive industrial sectors. We present the first study to consistently link a broad range of emission measurements for these substances with site-specific technical data, emission models, and atmospheric fate and effect models to quantify health impacts caused by nearly all global fossil power plants, steel mills, oil refineries and cement plants. The resulting health impact patterns differ substantially from far less detailed earlier studies due to the high resolution of included data, highlighting in particular the key role of emission abatement at individual coal-consuming industrial sites in densely populated areas of Asia (Northern and North-Eastern India, Java in Indonesia, Eastern China), Western Europe (Germany, Belgium, Netherlands) as well as in the US. Of greatest health concern are the high SO[Formula: see text] emissions in India, which stand out due to missing flue gas treatment and cause a particularly high share of local health impacts despite a limited number of emission sites. At the same time, the massive infrastructure and export capacity build-up in China in recent years is taking a substantial toll on regional and global health and requires more stringent regulation than in the rest of the world due to unfavorable environmental conditions and high population densities. The current phase-out of highly emitting industries in Europe is found not to have started with sites having the greatest health impacts. Our detailed site-specific emission and impact inventory is able to highlight more effective alternatives and to track future progress.

Toward sustainable reprocessing and valorization of sulfidic copper tailings: Scenarios and prospective LCA.

There has been increasing attention recently to reprocessing of mining waste, which aims to recover potentially valuable materials such as metals and other byproducts from untapped resources. Mining waste valorization may offer environmental advantages over traditional make-waste-dispose approaches. However, a quantitative environmental assessment for large-scale reprocessing, accounting for future trends and a broad set of environmental indicators, is still lacking. This article assesses the life cycle impacts and resource recovery potential associated with alternative waste management through mine tailings reprocessing at a regional scale. Sulfidic copper tailings in the EU were selected as a case study. We perform prospective life cycle assessments of future reprocessing scenarios by considering emerging resource recovery technologies, market supply & demand forecasts, and energy system changes. We find that some reprocessing and valorization technologies in future scenarios may have reduction potentials for multiple impact indicators. However, results for indicators such as climate change and energy-related impacts suggest that specific scenarios perform sub-optimally due to energy/resource-intensive processes. The environmental performance of reprocessing of tailings is influenced by technology routes, secondary material market penetration, and choices of displaced products. The trade-off between climate change and energy related impacts, on the one hand, and toxicity impacts, on the other hand, requires critical appraisal by decision makers when promoting alternative tailings reprocessing. Implementing value recovery strategies for building material production, can save up to 3 Mt. CO2-eq in 2050 compared to business as usual, helping the copper sector mitigate climate impacts. Additional climate mitigation efforts in demand-side management are needed though to achieve the 1.5 °C climate target. This work provides a scientific basis for decision-making toward more sustainable reprocessing and valorization of sulfidic tailings.

Net-zero transition of the global chemical industry with CO2-feedstock by 2050: feasible yet challenging.

Carbon capture, utilization and storage (CCUS) have been projected by the power and industrial sectors to play a vital role towards net-zero greenhouse gas emissions. In this study, we aim to explore the feasibility of a global chemical industry that fully relies on CO2 as its carbon source in 2050. We project the global annual CO2 demand as chemical feedstock to be 2.2-3.1 gigatonnes (Gt), well within the possible range of supply (5.2-13.9 Gt) from the power, cement, steel, and kraft pulp sectors. Hence, feedstock availability is not a constraint factor for the transition towards a fully CO2-based chemical industry on the global basis, with the exception of few regions that could face local supply shortages, such as the Middle East. We further conduct life cycle assessment to examine the environmental benefits on climate change and the trade-offs of particulate matter-related health impacts induced by carbon capture. We conclude that CO2 captured from solid biomass-fired power plants and kraft pulp mills in Europe would have the least environmental and health impacts, and that India and China should prioritize low-impact regional electricity supply before a large-scale deployment of CCUS. Finally, two bottom-up case studies of China and the Middle East illustrate how the total regional environmental and health impacts from carbon capture can be minimized by optimizing its supply sources and transport, requiring cross-sectoral cooperation and early planning of infrastructure. Overall, capture and utilization of unabatable industrial waste CO2 as chemical feedstock can be a feasible way for the net-zero transition of the industry, while concerted efforts are yet needed to build up the carbon-capture-and-utilization value chain around the world.

Can Forest Management Practices Counteract Species Loss Arising from Increasing European Demand for Forest Biomass under Climate Mitigation Scenarios?

Forests are home to many species and provide biomass for material and energy. Here, we modeled the potential global species extinction risk from future scenarios of climate mitigation and EU28 forest management. We considered the continuation of current practices, the adoption of closer-to-nature management (low-intensity practices), and set-asides (conversion to unharvested forestland) on portions of EU28 forestland under two climate mitigation pathways as well as the consequences for the wood trade. Expanding set-aside to more than 25% of EU28 currently managed forestland by 2100 increased the global extinction risk compared to the continuation of current practices. This outcome stems from a projected increase in EU forest biomass imports, partially from biodiversity-vulnerable regions to compensate for a decrease in domestic harvest. Conversely, closer-to-nature management on up to 37.5% of EU28 forestland lowered extinction risks. Increasing the internal production and partially sourcing imported biomass from low-intensity managed areas lowered the species extinction footprint even further. However, low-intensity practices could not entirely compensate for the increased extinction risk under a high climate mitigation scenario with greater demand for lignocellulosic crops and energywood. When developing climate mitigation strategies, it is crucial to assess forest biomass supply chains for the early detection of extinction risks in non-EU regions and for developing strategies to prevent increase of global impacts.

Environmental trade-offs for using low-noise pavements: Life cycle assessment with noise considerations.

Noise mitigation is the main advantage of semi-dense asphalt (SDA) pavements compared to traditional pavements such as stone-mastic asphalt (SMA), but noise is not quantitatively considered in traditional life cycle assessment (LCA). This article performs a comprehensive LCA for SMA and SDA including noise considerations. State-of-the-art sound emission and acoustical ageing models were used to determine the road traffic noise. The latest Swiss dose-response curves and current noise exposure data were used to evaluate health impacts due to noise. Additionally, traditional LCA is also included for assessing the greenhouse gas emissions, non-renewable cumulative energy demand and health impacts of non-noise processes. The results show that SDA causes around 70 % higher greenhouse gases and energy demand than SMA, primarily due to its shorter service life. However, the noise impacts in disability adjusted life years (DALYs) are higher by two to three orders of magnitude than non-noise processes, and the use of SDA can reduce 40 % of the total DALYs. It is shown that road traffic noise plays a significant role in the LCA of pavements. The trade-off between greenhouse gas and energy related impacts, on the one hand, and health effects, on the other hand, requires critical consideration by decision makers when promoting low-noise pavements.

Global Sensitivity Analysis of Background Life Cycle Inventories.

In recent years many Life Cycle Assessment (LCA) studies have been conducted to quantify the environmental performance of products and services. Some of these studies propagated numerical uncertainties in underlying data to LCA results, and several applied Global Sensitivity Analysis (GSA) to some parts of the LCA model to determine its main uncertainty drivers. However, only a few studies have tackled the GSA of complete LCA models due to the high computational cost of such analysis and the lack of appropriate methods for very high-dimensional models. This study proposes a new GSA protocol suitable for large LCA problems that, unlike existing approaches, does not make assumptions on model linearity and complexity and includes extensive validation of GSA results. We illustrate the benefits of our protocol by comparing it with an existing method in terms of filtering of noninfluential and ranking of influential uncertainty drivers and include an application example of Swiss household food consumption. We note that our protocol obtains more accurate GSA results, which leads to better understanding of LCA models, and less data collection efforts to achieve more robust estimation of environmental impacts. Implementations supporting this work are available as free and open source Python packages.

Regionalized Life Cycle Inventories of Global Sulfidic Copper Tailings.

Worldwide, an issue of copper production is the generation of mine waste with varying characteristics. This waste can pollute natural environments, and in particular, the heavy metal emissions of the tailings may pose long-term consequences. Currently, life cycle assessments of mine tailings are hampered by both limited data availability in the metal production value chain and lack of appropriate methodologies. We collect data from 431 active copper mine sites using a combination of information available from the market research and technical handbooks to develop site-specific life cycle inventories for disposal of tailings. The approach considers the influences of copper ore composition and local hydrology for dynamically estimating leached metals of tailings at each site. The analysis reveals that together, copper tailings from the large (i.e., porphyry) and medium-size copper deposits (i.e., volcanogenic massive sulfide and sediment-hosted) contribute to more than three quarters of the total global freshwater ecotoxicity impacts of copper tailings. This strongly correlates with hydrological conditions, leading to high infiltration rates. The generated inventories vary locally, even within single countries, showcasing the importance of site-specific models. Our study provides site-specific, dynamic emission models and thus improves the accuracy of tailing's inventories and toxicity-related impacts.

Limited utilization options for secondary plastics may restrict their circularity.

Plastic recycling can provide environmental benefits by avoiding the detrimental impacts of alternative disposal pathways and enabling the substitution of primary materials. However, most studies aiming at increasing recycling rates have not investigated how the resulting secondary materials can be utilized in product manufacturing. This study assesses the future substitution potential of primary with secondary plastics, building on a material flow system of 11 plastic types in 54 product subsegments in Switzerland in 2017 with a recycling rate of 9%. In a prospective material flow analysis of a scenario for 2025, the collection rate of the plastic fractions collected in 2017 is increased to 80%. The secondary material flows are allocated to suitable uptaking product subsegments using a linear optimization. The maximum share of secondary materials utilizable in each product subsegment is estimated, whereby three sub-scenarios involving high, moderate and low allowed secondary material shares are modelled. Depending on plastic type and scenario, 21% to 100% of the secondary material gained can substitute for primary material, covering 11% to 17% of the total material demand. While the overall recycling rate could reach 23%, taking into account only the uptaken secondary materials a true recycling rate of only 17% results in the moderate applicability sub-scenario. Based on these results, the secondary material uptake can be said to constitute a limiting factor for increased future recycling. Therefore, thorough consideration of the possible secondary material application is a prerequisite for designing and assessing future recycling systems or for setting recycling rate targets.

A novel machine-learning approach for evaluating rebounds-associated environmental footprint of households and application to cooperative housing.

Multiple environmental policies aim to increase resource efficiency and reduce consumption of goods and services with high environmental impact. This may lead to cost-savings and, consequently, additional consumption with environmental impacts (rebound effects). In this study, a supervised machine-learning model (i.e. an application of random forest regression) is developed to quantify consumption rebound effects. In contrast to previous approaches, it is a versatile method, which allows to estimate any income-related rebound at household level considering specific household properties and the entire profile of consumption. Socio-economic properties (e.g. income, age group) of the households are used as the independent properties for the regressor to detect the dependent consumption expenses of the households. Thus, this method can be used as a bottom-up study for understanding rebounds and developing targeted measures to prevent or reduce rebound effects. To illustrate the application of the method, it is applied to the case of cooperative housing in Switzerland. In addition to environmental goals, the cooperative aims to provide affordable housing, and the reduced rent increases the disposable income of tenants. The results show that households tend to spend the 'extra' income on housing (e.g. for larger apartments) and travel. For the former, the cooperative already has a policy in place regulating the apartment area permitted per person, which delimits induced environmental impacts. For the latter, households with lower income particularly spend their extra-money on purchase and operation of vehicles, while higher-income groups rather spend it on recreation and package holidays. Travel, housing, clothing and personal care products have highest emissions per Swiss Franc (∼0.3-0.6 kg CO2-eq/CHF). Thus, it is recommended to provide incentives for shifting these expenses to other consumption, to avoid jeopardizing environmental goals. The method was also used for a range of other applications e.g. rebounds due to energy-efficient devices to illustrate its versatility.

Deep Dive into Plastic Monomers, Additives, and Processing Aids.

A variety of chemical substances used in plastic production may be released throughout the entire life cycle of the plastic, posing risks to human health, the environment, and recycling systems. Only a limited number of these substances have been widely studied. We systematically investigate plastic monomers, additives, and processing aids on the global market based on a review of 63 industrial, scientific, and regulatory data sources. In total, we identify more than 10'000 relevant substances and categorize them based on substance types, use patterns, and hazard classifications wherever possible. Over 2'400 substances are identified as substances of potential concern as they meet one or more of the persistence, bioaccumulation, and toxicity criteria in the European Union. Many of these substances are hardly studied according to SciFinder (266 substances), are not adequately regulated in many parts of the world (1'327 substances), or are even approved for use in food-contact plastics in some jurisdictions (901 substances). Substantial information gaps exist in the public domain, particularly on substance properties and use patterns. To transition to a sustainable circular plastic economy that avoids the use of hazardous chemicals, concerted efforts by all stakeholders are needed, starting by increasing information accessibility.

The environmental performance of enhanced metal recovery from dry municipal solid waste incineration bottom ash.

This study assesses the environmental performance of the municipal solid waste (MSW) incineration bottom ash (IBA) treatment plant in Hinwil, Switzerland, a large-scale industrial plant, which also serves as a full-scale laboratory for new technologies and aims at an optimal recovery of metals in terms of quantity and quality. Based on new mass-flow data, we perform a life cycle assessment that includes the recovery of iron, stainless steel, aluminium, copper, lead, silver and gold. Fraction-specific modelling allows for investigating the effect of the metal fraction quality on the subsequent secondary metal production as well as examining further metal recycling potentials in the residual IBA. In addition, the implications on the landfill emissions of IBA residues to water were quantified. The impact assessment considered climate change, eco- and human toxicity and abiotic resource depletion as indicators. Results indicate large environmental savings for every impact category, due to primary metal substitution and reduction of long-term emissions from landfills. Metal product substitution contributes between 75% and >99% to these savings in a base scenario (1'000-year time horizon), depending on the impact category. Reductions in landfill emissions become important only when a much longer time horizon was adopted. The metal-based analysis further illustrates that recovering heavy non-ferrous metals - especially copper and gold - leads to large environmental benefits. Compared to the total net savings of energy recovery (215 kg CO2-eq per tonne of treated waste, average Swiss plant), enhanced metal recovery may save up to 140 kg CO2-eq per tonne of treated waste.

Globally Regionalized Monthly Life Cycle Impact Assessment of Particulate Matter.

This work provides a globally regionalized approach for quantifying particulate matter (PM2.5) health impacts. Atmospheric transport and pollutant chemistry of primary particulate matter, sulfur dioxide (SO2), nitrogen oxide (NOx), and ammonia (NH3) from stack emissions were modeled and used to calculate monthly high-resolution maps of global characterization factors that can be used for life cycle impact assessment (LCIA) and risk assessment. These characterization factors are applied to a global data set of coal power emissions. The results show large regional and temporal differences in health impacts per kg of emission and per amount of coal power generation (5-1300 DALY TWh-1). While small emission reductions of PM2.5 and SO2 from coal power lead to similar health benefits across densely populated areas of Asia and Europe, we find that larger emission reductions result in up to three times higher health benefits in parts of Asia because of the nonlinear health responses to pollution exposure changes. Hence, many regions in Asia benefit disproportionately much from large coal power PM2.5 and SO2 emission reductions. NOx emission reductions can lead to equally high health benefits, where unfavorable atmospheric conditions coincide with elevated NH3 background pollution and large population (e.g., in Central Europe, Indonesia, or Japan but also numerous other places).

Bending the curve of terrestrial biodiversity needs an integrated strategy.

Increased efforts are required to prevent further losses to terrestrial biodiversity and the ecosystem services that it  provides1,2. Ambitious targets have been proposed, such as reversing the declining trends in biodiversity3; however, just feeding the growing human population will make this a challenge4. Here we use an ensemble of land-use and biodiversity models to assess whether-and how-humanity can reverse the declines in terrestrial biodiversity caused by habitat conversion, which is a major threat to biodiversity5. We show that immediate efforts, consistent with the broader sustainability agenda but of unprecedented ambition and coordination, could enable the provision of food for the growing human population while reversing the global terrestrial biodiversity trends caused by habitat conversion. If we decide to increase the extent of land under conservation management, restore degraded land and generalize landscape-level conservation planning, biodiversity trends from habitat conversion could become positive by the mid-twenty-first century on average across models (confidence interval, 2042-2061), but this was not the case for all models. Food prices could increase and, on average across models, almost half (confidence interval, 34-50%) of the future biodiversity losses could not be avoided. However, additionally tackling the drivers of land-use change could avoid conflict with affordable food provision and reduces the environmental effects of the food-provision system. Through further sustainable intensification and trade, reduced food waste and more plant-based human diets, more than two thirds of future biodiversity losses are avoided and the biodiversity trends from habitat conversion are reversed by 2050 for almost all of the models. Although limiting further loss will remain challenging in several biodiversity-rich regions, and other threats-such as climate change-must be addressed to truly reverse the declines in biodiversity, our results show that ambitious conservation efforts and food system transformation are central to an effective post-2020 biodiversity strategy.

Assessing Impacts on the Natural Resource Soil in Life Cycle Assessment: Methods for Compaction and Water Erosion.

There are currently limited life cycle impact assessment methods existing for assessing impacts on the natural resource soil. In this paper, we develop methods for the assessment of compaction and water erosion impacts within one framework, which can be expanded with additional degradation processes in the future. Our methods assess potential long-term impacts from agricultural activities on the production capacity of soils and are able to distinguish between different management choices such as machinery selection and tillage practices. Characterization factors are provided as global raster data sets at high spatial resolution (∼1 km) and for larger geographic units including uncertainties of spatial aggregation. Uncertainties due to variability of climate and weather are provided where possible. The application of the methods is demonstrated and discussed in a simplified case study. Results show that in a highly mechanized scenario of global agriculture without any conservation measures, long-term yearly soil productivity losses due to compaction and water erosion can amount to up to double-digit percentages for major crops. This confirms the relevance of compaction and water erosion impacts for agricultural LCAs.

Noise footprint from personal land-based mobility.

A large part of the world population is exposed to noise levels that are unhealthy. Yet noise is often neglected when impact assessment studies are conducted and when policy interventions are designed. In this study, we provide a way to calculate the noise footprint of citizens directly determined by their use of private and public transport on land. The study combines the results of the large transport simulation model MATSim applied to Switzerland, with a noise characterization model, N-LCA, developed in the context of life cycle assessment. MATSim results allow tracking the use of private and public transportation by agents in the model. The results after characterization provide a consumption-based noise footprint, thus the total noise and impacts that are caused by the private mobility demand of the citizens of Switzerland. Our results confirm that road transportation is the largest contributor to the total noise footprint of land-based mobility. We also included a scenario with a full transition to an electrified car fleet, which showed the potential for the reduction of impacts, particularly in urban areas, by about 55% as compared to the modeled regime with combustion engines.

Comparing environmental and personal health impacts of individual food choices.

Dietary choices affect personal health and environmental impacts, but little is known about the relation between these outcomes. Here we examine the intake-related health impacts and the food-production related impacts to ecosystems and human health by applying life cycle impact assessment methods to habitual diet data of 1457 European adults. We measured food production impacts for each individual in terms of Disability Adjusted Life Years (DALYs) as calculated by the Recipe 2016 life cycle impact assessment method using secondary production data, which were then compared with their personal health DALYs predicted from the known relationships between dietary choices and disease risk. Across this population cohort, each individual was estimated to lose on average 2.5 ±â€¯0.9 DALYs per lifetime due to sub-optimal dietary intake (with seed and vegetable under-consumption the greatest contributors) and their food choices caused environmental human health impacts of 2.4 ±â€¯1.3 DALYs (particularly due to the damage associated with production of meats, milk, and vegetables). Overall, there was no relationship between a healthier dietary pattern and the environmental human health impacts associated with production of its constituent foods (i.e. healthier diets did not have lower or higher production impacts). This was due to a combination of decreased meat consumption correlating with increased consumption of other foods, as well as the fact that under-consumption of some low impact foods yielded high personal health consequences. However, for specific food items synergies and tradeoffs could be identified. For example, reduced processed meat consumption benefits both personal and environmental health. Every DALY caused by higher whole grain and vegetable production and consumption would be offset by reduced disease risk that equated to an average of 7.7 (5.7 to 10.4) and 1.4 (0.9 to 2.5) lower personal health DALYs, respectively.

A new method for analyzing sustainability performance of global supply chains and its application to material resources.

Supply chains become increasingly globalized. Multi-regional input-output databases contain all the information to assess impacts along the value chain, but standard calculation routines to track the impacts of any sector along the global upstream and downstream value chain are missing. Mapping the impacts of materials has been a particular challenge owing to difficulties with double-counting. This is attributed to the strong intertwining of the material supply chain meaning that different materials occur in the supply chains of other materials. Here, we present a new method which can be applied to any MRIO system to track the impacts of any sector or region without double-counting upstream and downstream the global value chain. We apply this approach to EXIOBASE3 and implement a cutting-edge set of regionalized environmental impact categories and socio-economic indicators. Applied to global material production, our method shows that the issue of double-counting (prevented in this study) would overestimate global impacts of materials by up to 30%. In contrast, assessing only the direct impacts would lead to an underestimation by ~20%. Our evaluation further reveals that 25-35% of global material-related impacts are embodied in trade among ten world regions. Thereby, we identify the major international trade relations of key materials and found a clear trend of industrialized nations causing impacts in less developed economies. It was further revealed that during 1995-2011, the share of materials in total global climate change impacts has remained almost constant at ~50%, but total impacts have significantly increased for minerals and fossils. Our results demonstrate the importance for improved environmental policy strategies that target several stages of the global value chain. The methodology is provided as Matlab tool and can be applied to any material, industrial sector and region to track the related impacts upstream and downstream the global value chain.