Spatial and temporal variations in environmental impacts of heavy metal emissions from China's non-ferrous industry: An enterprise-specific assessment

In China, the non-ferrous metal industry is the sector with the highest emissions of arsenic, cadmium, mercury and lead, causing serious impacts on human health and the ecosystem. However, current heavy metal emission inventories are inadequate for figuring out their exposures and associated environmental impacts due to the lack of detailed data. Here, we constructed a high-resolution, enterprise-specific, and long-term dataset detailing heavy metal emissions from the non-ferrous industry in China from 1981 to 2020, using comprehensive enterprise information. Furthermore, an environmental impact assessment was performed using the characterization factors of the IMPACT World + model. Results show that: (1) from 1981 to 2020, the total heavy metal emissions of China's non-ferrous industry reached 144,697 tons (t), with atmospheric emissions (104,524 t) exceeding aquatic ones (40,173 t). (2) The industry's emissions showed a rising and then declining trend, with significant spatial heterogeneity, where heavy metal emissions concentrated in the central and western parts of Yunnan, the southern part of Hunan, the northern part of Guangxi, Henan along the Yellow River, the intersection of Gansu and Shaanxi, the central and eastern parts of Liaoning, and the eastern part of Inner Mongolia. (3) The environmental impact on human health was 1.19 × 107 DALY, and the value of ecosystem quality was 7.26 × 109 species·yr. The top 10 % of enterprises with the largest environmental impacts contributed over 60 % of human health risks and 62 % of ecosystem quality impacts. Improving the removal efficiency of heavy metals by 10 % within the four major industry classes could lead to a 9.92 % reduction in human health impacts and a 9.77 % reduction in ecosystem quality impacts within the non-ferrous metals industry. The findings of this study can provide insights for pollution control, environmental risk reduction, and sustainable development in the non-ferrous metals industry.

Diversity of forest structures important for biodiversity is determined by the combined effects of productivity, stand age, and management

In forests, the amount and diversity of structural features with high value for biodiversity, such as large trees and dead wood, are affected by productivity, stand age, and forest management. For efficient conservation of forest biodiversity, it is essential to understand the combined effects of these drivers. We used data from the Swedish National Forest Inventory to study the combined effects of productivity, stand age, and management for wood production on structures with high value for biodiversity: tree species richness, large living trees, dead wood volume, and specific dead wood types. Forest management changed the relationship between productivity and amount or diversity of some of the structures. Most structures increased with productivity and stand age, but decreased due to management. The negative effect of management was greatest for structures occurring mainly in high-productivity forests, such as deciduous dead wood. Thus, biodiversity conservation should target high-productivity forests to preserve these structures.

Environmental and biodiversity performance of a novel single cell protein for rainbow trout feed

Seafood has an important role to play to achieve a sustainable food system that provides healthy food to a growing world population. Future seafood production will be increasingly reliant on aquaculture where feed innovation is essential to reduce environmental impacts and minimize feed and food competition. This study aimed to investigate whether a novel single cell protein feed ingredient based on Paecilomyces variotii grown on a side stream from the forest industry could improve environmental sustainability of farmed rainbow trout (Oncorhynchus mykiss) by replacing the soy protein concentrate used today. A Life Cycle Assessment including commonly addressed impacts but also the rarely assessed biodiversity impacts was performed. Furthermore, feeding trials were included for potential effects on fish growth, i.e., an assessment of the environmental impacts for the functional unit 'kg feed required to produce 1 kg live-weight rainbow trout'. Results showed that the best experimental diet containing P. variotii performed 16-73 % better than the control diet containing soy protein concentrate in all impact categories except for energy demand (21 % higher impact). The largest environmental benefits from replacing soy protein with P. variotii in rainbow trout diets was a 73 % reduction of impact on biodiversity and halved greenhouse gas emissions. The findings have high relevance for the aquaculture industry as the production scale and feed composition was comparable to commercial operations and because the effect on fish growth from inclusion of the novel ingredient in a complete diet was evaluated. The results on biodiversity loss from land use change and exploitation through fishing suggest that fishery can dominate impacts and exclusion thereof can greatly underestimate biodiversity impact. Finally, a novel feed ingredient grown on side streams from the forest industry has potential to add to food security through decreasing the dependence on increasingly scarce agricultural land resources.

Global water consumption impacts on riverine fish species richness in Life Cycle Assessment

Reduced river discharge and flow regulation are significant threats to freshwater biodiversity. An accurate representation of potential damage of water consumption on freshwater biodiversity is required to quantify and compare the environmental impacts of global value chains. The effect of discharge reduction on fish species richness was previously modeled in life cycle impact assessment, but models were limited by the restricted geographical scope of underlying species-discharge relationships and the small number of species data. Here, we propose a model based on a novel regionalized species-discharge relationship (SDR). Our SDR-based model covers 88 % of the global landmass (2320 river basins worldwide excluding deserts and permanently frozen areas) and is based on a global dataset of 11,450 riverine fish species, simulated river discharge, elevation, and climate zones. We performed 10-fold cross-validation to select the best set of predictors and validated the obtained SDRs based on observed discharge data. Our model performed better than previous SDRs employed in life cycle impact assessment (Kling-Gupta efficiency coefficient about 4 times larger). We provide both marginal and average models with their uncertainty ranges for assessing scenarios of small and large-scale water consumption, respectively, and include regional and global species loss. We conducted an illustrative case study to showcase the method's applicability and highlight the differences with the currently used approach. Our models are useful for supporting sustainable water consumption and riverine fish biodiversity conservation decisions. They enable a more specific, reliable, and complete impact assessment by differentiating impacts on regional riverine fish species richness and irreversible global losses, including up-to-date species data, and providing spatially explicit values with high geographical coverage.

Improvement of ecosystem quality in National Key Ecological Function Zones in China during 2000-2015

Improving ecosystem quality is the ultimate goal of ecological restoration projects and sustainable ecosystem management. However, previous results of ecosystem quality lack comparability among different regions when assessing the effectiveness of ecological restoration projects on the regional or national scales, due to the influence of geographical and climatic background conditions. Here we proposed a new index, ecosystem quality ratio (EQR), by integrating the status of landscape structure, ecosystem services, ecosystem stability, and human disturbance relative to their reference conditions, and assessed the EQR changes in China's counties and National Key Ecological Function Zones (NKEFZs) from 1990 to 2015. The results showed that the average ecosystem quality of China's counties deviated from the reference condition by 28%. EQR decreased by 1.2% during 1990-2000 but increased by 3.7% during 2000-2015. Those counties with increasing EQR in 2000-2015 occupy 64.7%, with obviously increasing counties mainly located in the water conservation, biodiversity maintenance, and water and soil conservation types of NKEFZs. The EQR increase in counties within NKEFZs was 3.65 times that outside of NKEFZs. Remarkable improvement of ecosystem quality occurred in the forest region in Changbai Mountain, biodiversity and soil conservation region in Wuling Mountains, and hilly and gully region of Loess Plateau, where EQR increases mainly resulted from the conversion of farmland to forest or grassland and consequent increases in ecosystem services and stability. The magnitude of EQR enhancement showed a positive relationship with the increase in forest and grassland coverage in NKEFZs. Our results highlight the important role of ecological restoration projects in improving ecosystem quality in China, and demonstrate the feasibility of the new index (EQR) for the assessment of ecosystem quality in terms of ecosystem management and restoration.

Analysis of the spatial characteristics and driving forces determining ecosystem quality of the Beijing-Tianjin-Hebei region

Water shortage is one of the main hinder drivers of sustainable development in the Beijing-Tianjin-Hebei region, and ecological restoration is one of the main means to effectively curb ecological degradation. Addressing ecological degradation in the Beijing-Tianjin-Hebei region has been a major concern of the Chinese government, and this has led to a focus on intensified ecological restoration efforts in this area. However, the effect of these restoration actions is not clear. To understand how ecological restoration is impacting ecological quality in the Beijing-Tianjin-Hebei region, we used geographical information system technology, such as the vegetation index-biomass method and cumulative net primary production (NPP) method, to assess the change in ecosystem quality. We carried out the pixel binary model and Pearson's correlation coefficient analyses to understand the driving forces behind the change. Results showed that from 2000 to 2010, the quality of the Beijing-Tianjin-Hebei ecosystem has been improving, that natural vegetation is slowly re-establishing, and that there has been a slow increase toward climax communities. The change in ecosystem quality is positively correlated with the Sanbei shelterbelt and Beijing-Tianjin Sandstorm control project and negatively correlated with socioeconomic and agricultural factors.

Environmental impact assessment for ornamental plant greenhouse: Life cycle assessment approach for primrose production

Improving the environmental impact is a critical factor in achieving sustainable development in agricultural systems. To achieve this goal, the environmental assessment of agricultural products to identify environmental hot-spots and provide strategies for reducing them is essential. In line with that, the current study is performed to assess the environmental impacts of Primrose greenhouse production in Savojbolagh County, Iran. More specifically, the environmental impacts of Primrose greenhouse production based on the cradle to gate analysis using the life cycle assessment approach are evaluated. According to results, production and combustion of diesel fuel are introduced as the environmental hotspot in non-carcinogens, respiratory inorganics, respiratory organics, terrestrial acid/nutri, aquatic acidification, global warming, and non-renewable energy impact categories. The application of pesticides and fertilizers in the greenhouse has the highest contribution in aquatic ecotoxicity as well as terrestrial ecotoxicity impact categories. Moreover, electricity consumption has the highest impact on carcinogens, and ozone layer depletion impact categories. Based on the outcomes of the life cycle assessment approach, the production of a piece of Primrose leads to damages of 1.48 × 10^-7 DALY (disability-adjusted life year) and 3.41 × 10^-1 PDF.m^-2.yr^-1 (potentially disappeared fraction in square-meters per year) to human health and ecosystem quality, respectively. In addition, the production of each Primrose plant results in primary damages of 2.06 × 10^-1 kg CO_2eq. (equivalent carbon dioxide) and 2.94 MJ (Megajoule) to climate change and resources, respectively. Finally, the weighing of environmental impacts based on IMPACT 2002+ methods shows that the ecosystem quality damage category has a share of 30% in total environmental impacts of one piece of Primrose production. Damages to ecosystem quality are mostly caused by pesticide and fertilizer applications in Primrose greenhouse. Accordingly, it could be concluded that correct management of pesticides and fertilizers can potentially mitigate environmental impacts of Primrose production in a greenhouse.

Visits from the ghost of disturbance past: Information about past disturbance influences lay judgments of ecosystems

While effective techniques are being developed to restore ecosystem function to landscapes following anthropogenic disturbance, there has been a paucity of research on lay judgments of the quality of restored ecosystems. This represents an important research gap because judgments about the health of ecosystems following restoration are likely to influence people's satisfaction with restoration outcomes and processes. Likewise, judgments about ecosystem health following restoration are likely to influence people's perceptions about the acceptability of the activities that led to the disturbance and-ultimately-the need for restoration. Documenting how restored landscapes are perceived in terms of certain qualities-such as scenic beauty and ecosystem health-will ultimately improve our understanding of how the public will interact with them. An experiment was developed to test the effect of information on past natural and anthropogenic disturbances on lay judgments about ecosystem quality. Identical photographs of forest scenes were framed as the aftermath of natural or anthropogenic disturbances. Restored forests following natural disturbances were judged significantly more positively across a broad range of ecosystem qualities than the identical scenes following an anthropogenic disturbance. Disturbances that were natural in origin were, retrospectively and prospectively, more acceptable than anthropogenic disturbances; these results were most strongly observed for individuals endorsing biospheric values. This study offers a new context for research on lay judgments about, and perceptions of, ecosystem health. Results from this research also suggest that intuitive judgments about ecosystem quality will be important metrics by which people evaluate disturbed and restored habitats.

LCIA framework and cross-cutting issues guidance within the UNEP-SETAC Life Cycle Initiative

Increasing needs for decision support and advances in scientific knowledge within life cycle assessment (LCA) led to substantial efforts to provide global guidance on environmental life cycle impact assessment (LCIA) indicators under the auspices of the UNEP-SETAC Life Cycle Initiative. As part of these efforts, a dedicated task force focused on addressing several LCIA cross-cutting issues as aspects spanning several impact categories, including spatiotemporal aspects, reference states, normalization and weighting, and uncertainty assessment. Here, findings of the cross-cutting issues task force are presented along with an update of the existing UNEP-SETAC LCIA emission-to-damage framework. Specific recommendations are provided with respect to metrics for human health (Disability Adjusted Life Years, DALY) and ecosystem quality (Potentially Disappeared Fraction of species, PDF). Additionally, we stress the importance of transparent reporting of characterization models, reference states, and assumptions, in order to facilitate cross-comparison between chosen methods and indicators. We recommend developing spatially regionalized characterization models, whenever the nature of impacts shows spatial variability and related spatial data are available. Standard formats should be used for reporting spatially differentiated models, and choices regarding spatiotemporal scales should be clearly communicated. For normalization, we recommend using external normalization references. Over the next two years, the task force will continue its effort with a focus on providing guidance for LCA practitioners on how to use the UNEP-SETAC LCIA framework as well as for method developers on how to consistently extend and further improve this framework.

Towards a meaningful assessment of marine ecological impacts in life cycle assessment (LCA)

Human demands on marine resources and space are currently unprecedented and concerns are rising over observed declines in marine biodiversity. A quantitative understanding of the impact of industrial activities on the marine environment is thus essential. Life cycle assessment (LCA) is a widely applied method for quantifying the environmental impact of products and processes. LCA was originally developed to assess the impacts of land-based industries on mainly terrestrial and freshwater ecosystems. As such, impact indicators for major drivers of marine biodiversity loss are currently lacking. We review quantitative approaches for cause-effect assessment of seven major drivers of marine biodiversity loss: climate change, ocean acidification, eutrophication-induced hypoxia, seabed damage, overexploitation of biotic resources, invasive species and marine plastic debris. Our review shows that impact indicators can be developed for all identified drivers, albeit at different levels of coverage of cause-effect pathways and variable levels of uncertainty and spatial coverage. Modeling approaches to predict the spatial distribution and intensity of human-driven interventions in the marine environment are relatively well-established and can be employed to develop spatially-explicit LCA fate factors. Modeling approaches to quantify the effects of these interventions on marine biodiversity are less well-developed. We highlight specific research challenges to facilitate a coherent incorporation of marine biodiversity loss in LCA, thereby making LCA a more comprehensive and robust environmental impact assessment tool. Research challenges of particular importance include i) incorporation of the non-linear behavior of global circulation models (GCMs) within an LCA framework and ii) improving spatial differentiation, especially the representation of coastal regions in GCMs and ocean-carbon cycle models.