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The Qilian Mountains (QLM) are an essential ecological security barrier in northwest China. Identifying the driven pattern of vegetation change is crucial for ecological protection and restoration in the QLM. Based on high-resolution vegetation coverage (VC) data in the QLM from 1990 to 2018, linear trend analysis was employed to examine the spatiotemporal dynamics of VC in the QLM, while correlation analysis was utilized to establish relationships between VC change and environmental factors. Multiple correlation analysis and residual analysis were adopted to recognize the climatically and anthropogenically driven pattern of VC change. The results showed that VC in the QLM presented a remarkable upward trend in volatility from 1990 to 2018. The significant increase areas accounted for 59.32% of the total, mainly distributed in the central and western QLM, and the significant decrease areas accounted for 9.18%, mostly located in the middle and eastern QLM. VC change showed a significant positive correlation with precipitation change and annual average temperature, while it exhibited a significant negative correlation with annual average precipitation, current VC status, livestock density, and slope. Climate change played a leading role in the increase of VC, and the impact of precipitation was significantly higher than that of temperature. Affected by climate change, the VC of alpine steppes and temperate steppes increased the most. Under the human interference, VC decreased significantly in 9.2% of the region, of which shrubs fell the most, followed by alpine meadows and forests. This study can provide certain guidance for local ecological protection and restoration efforts. [ABSTRACT FROM AUTHOR]

In recent decades, carbon sequestration (CS) capacity in Northern China has changed significantly, but the main factors leading to the spatial heterogeneity of CS change were still unclear. In this study, we analyzed the spatio‐temporal characteristics of CS change from 2000 to 2020 in Northern China, and further used correlation analysis and multiple linear regression model (MLR) to identify the main factors leading to the spatial differentiation of CS change. Furthermore, we adopted random forest model (RF) to compare the importance of these factors and geographically weighted regression (GWR) to spatially illustrate the heterogeneity of their influence on CS change. Our results showed that the most obvious increases of CS were concentrated in the Loess Plateau, Yanshan Mountains and Taihang Mountains. After eliminating redundant and low‐impact variables, we screened six factors that can well predict the spatial differentiation of CS change in Northern China. Based on the selected predictors, the MLR could explain 62.9% of the spatial variation of CS change, while the RF and GWR could explain 82.2% and 65.7% under the same predictors, respectively. Meanwhile, the spatial feature of each predictor's influence on CS change showed obvious differences. Among all predictors, afforestation was the most important factor leading to the spatial variation of CS change, and aridity index had the largest contribution among the climatic factors. In addition, we found that aridity index and potential evapotranspiration could explain better than commonly used precipitation and temperature. This study deepens the understanding of the spatial heterogeneity of CS change in Northern China and provides further suggestions for improving regional CS capacity. [ABSTRACT FROM AUTHOR]

Meeting ecological water requirements (EWRs) is important for maintaining watershed system stability in many arid and semi-arid areas. Rainfall–runoff relationships under changing climate conditions could have many adverse effects on EWRs. The inherent uncertainties in water resource management and potential variations in EWRs should be considered to obtain suitable water allocation strategies under climate change. In this study, an integrated approach was proposed through incorporation of copula functions and a Markov Chain Monte Carlo (MCMC) simulation into a chance-constrained programming (CCP) model. The proposed approach had several advantages for water resource allocation under variable climatic conditions with respect to the following: (a) tackling correlated features of rainfall and watershed inflow under climate change based on copula–MCMC simulations, (b) obtaining runoff distributions using the copula sampling method under multiple climate change scenarios, (c) analyzing fluctuations in EWRs based on variable monthly flows and diverse runoff distributions, and (d) obtaining desired water allocation strategies through the developed CCP model with consideration of EWRs and water shortage risk. Application of the developed method to water resource management in the city of Dalian (China) indicated that the EWRs in the watersheds of Dalian would exhibit large variations under changing climatic conditions. Moreover, in comparison with the supply in 2025, an increase in water supply transferred from the Dahuofang Reservoir (Hun River) would be 6942–33,772, 6942–25,472, and 2849–14,259 Mt with risk tolerance levels of 20%, 50%, and 80%, respectively. [ABSTRACT FROM AUTHOR]

Cities are increasingly linked to domestic and foreign markets during rapid globalization of trade. While transboundary carbon footprints of cities have been recently highlighted, we still have limited understanding of how carbon emission linkages between sectors are reshaping urban carbon footprints through time. In this study, we propose an integrated input‐output approach to trace the dynamics of various types of carbon emission linkages associated with a city. This approach quantifies full linkages in the urban carbon system from both production‐ and consumption‐based perspectives. We assess the dynamic roles that economic sectors and activities play in manipulating multiscale linkages induced by local, domestic, and international inputs. Using Beijing as a case study, we find that imports from domestic and foreign markets have an increasing impact on the city's carbon footprint with more distant linkages during the period from 1990 to 2012. The manufacturing‐related carbon emission linkages have been increasingly transferred outside the urban boundary since 2005, while the linkages from the energy sector to services sectors remain important in Beijing's local economy. Applying systems thinking to input‐output linkage analysis provides important details on when and how carbon emission linkages evolved in cities, whereby sector‐oriented and activity‐oriented carbon mitigation policies can be formulated. Plain Language Summary: Cities are increasingly linked to domestic and foreign markets during rapid globalization of trade. In this study, we propose an integrated approach to answer the question: what drives the carbon emissions from urban activities? We assess the dynamic roles that economic sectors and activities play in manipulating carbon flows related to local, domestic, and international inputs. Using Beijing as a case study, we find that imports from domestic and foreign markets have an increasing impact on the city's carbon flows from 1990 to 2012. The manufacture‐related carbon emission has been increasingly transferred outside the urban boundary since 2005, and the connection of energy sector with services sectors remains important in Beijing's local economy. This study provides important details on when and how carbon emission alters in cities, whereby informed carbon mitigation policies can be formulated. Key Points: New indices are proposed to quantify the dynamic carbon emission linkages for a cityManufacturing‐related carbon emission linkages have been increasingly transferred outside the city of Beijing since 2005Carbon emission linkages from the energy sector to services sectors remain important in Beijing's local economy during urbanization [ABSTRACT FROM AUTHOR]

This study uses the HD and Ecolab modules of MIKE to simulate the hydrodynamic and water quality and predict the influence of shoreline changes in Bohai Bay, China. The study shows that shoreline changes weaken the residual current and generate a counter-clockwise circulation south of Huanghua Port, thereby resulting in weak water exchange capacity and low pollutant-diffusing capacity. Shoreline changes reduce the area of Bohai Bay, resulting in a smaller tidal prism and further weakening the water exchange capacity. This situation is not conducive to the diffusion of pollutants, and therefore may lead to increased water pollution in the bay. Shoreline changes hinder the spread of runoff, weaken the dilution effect of the river on seawater, and block the spread of coastal residual current, thereby resulting in increased salinity near the reclamation area. Shoreline changes lead to an increase in PO4-P concentration and decrease in DIN concentration. The value of N/P near the project decreases, thereby weakening the phosphorus-limited effect. [ABSTRACT FROM AUTHOR]

Industrial symbiosis is the quintessential characteristic of an eco-industrial park. To divide parks into different types, previous studies mostly focused on qualitative judgments, and failed to use metrics to conduct quantitative research on the internal structural or functional characteristics of a park. To analyze a park's structural attributes, a range of metrics from network analysis have been applied, but few researchers have compared two or more symbioses using multiple metrics. In this study, we used two metrics (density and network degree centralization) to compare the degrees of completeness and dependence of eight diverse but representative industrial symbiosis networks. Through the combination of the two metrics, we divided the networks into three types: weak completeness, and two forms of strong completeness, namely 'anchor tenant' mutualism and 'equality-oriented' mutualism. The results showed that the networks with a weak degree of completeness were sparse and had few connections among nodes; for 'anchor tenant' mutualism, the degree of completeness was relatively high, but the affiliated members were too dependent on core members; and the members in 'equality-oriented' mutualism had equal roles, with diverse and flexible symbiotic paths. These results revealed some of the systems' internal structure and how different structures influenced the exchanges of materials, energy, and knowledge among members of a system, thereby providing insights into threats that may destabilize the network. Based on this analysis, we provide examples of the advantages and effectiveness of recent improvement projects in a typical Chinese eco-industrial park (Shandong Lubei). [ABSTRACT FROM AUTHOR]

The theory, methodologies, and case studies in the field of industrial symbiosis have been developing for nearly 30 years. In this paper, we trace the development history of industrial symbiosis, and review its current theoretical and methodological bases, as well as trends in current research. Based on the research gaps that we identify, we provide suggestions to guide the future development of this approach to permit more comprehensive analyses. Our theoretical review includes key definitions, a classification system, and a description of the formation and development mechanisms. We discuss methodological studies from the perspective of individual industrial metabolic processes and network analysis. Analyzing specific metabolic processes can help to characterize the exchanges of materials and energy, and to reveal the ecological performance and economic benefits of the symbiosis. Network analysis methods are increasingly being used to analyze both the structural and functional characteristics of a system. Our suggestions for future research focus on three aspects: how to quantitatively classify industrial symbiosis systems, monitor the dynamics of a developing industrial symbiosis system, and analyze its internal attributes more deeply. [ABSTRACT FROM AUTHOR]

Energy resources have environmental impact through their entire lifecycle. The evaluation of the environmental impacts of the energy lifecycle can contribute to decision making regarding energy management. In this paper, the lifecycle assessment (LCA) method is introduced to calculate the environmental impact loads of different types of energy resources (including coal, oil, natural gas, and electricity) used in urban regions. The scope of LCA includes the production, transportation, and consumption processes. The pollutant emission inventory is listed, and the environmental impact loads are acquired through the calculation of environmental impact potentials, normalization, and weighted assessment. The evaluation method is applied to Beijing, China, revealing that photochemical oxidant formation and acidification are the primary impact factors in the lifecycle of all energy resources and that the total environmental impact load increased steadily from 132.69 million person equivalents (PE) in 1996 to 208.97 million PE in 2010. Among the energy types, coal contributes most to the environmental impact, while the impacts caused by oil, natural gas, and electricity have been growing. The evaluation of the environmental impact of the urban energy lifecycle is useful for regulating energy structures and reducing pollution, which could help achieve sustainable energetic and environmental development. [ABSTRACT FROM AUTHOR]

With rapid economic development and energy consumption growth, China has become the largest energy consumer in the world. Impelled by extensive international concern, there is an urgent need to analyze the characteristics of energy consumption and related carbon emission, with the objective of saving energy, reducing carbon emission, and lessening environmental impact. Focusing on urban ecosystems, the biggest energy consumer, a method for estimating energy consumption and related carbon emission was established at the urban sector scale in this paper. Based on data for 1996–2010, the proposed method was applied to Beijing in a case study to analyze the consumption of different energy resources (i.e., coal, oil, gas, and electricity) and related carbon emission in different sectors (i.e., agriculture, industry, construction, transportation, household, and service sectors). The results showed that coal and oil contributed most to energy consumption and carbon emission among different energy resources during the study period, while the industrial sector consumed the most energy and emitted the most carbon among different sectors. Suggestions were put forward for energy conservation and emission reduction in Beijing. The analysis of energy consumption and related carbon emission at the sector scale is helpful for practical energy saving and emission reduction in urban ecosystems. [ABSTRACT FROM AUTHOR]

With the growth of energy consumption, energy-related environmental pollution has become increasingly serious, which in turn causes enormous economic loss because of public health damage, corrosion of materials, crop yield reduction, and other factors. Evaluating economic loss caused by energy-related environmental pollution can contribute to decision making in energy management. A framework for evaluating economic loss from environmental pollution produced during energy production, transportation, and consumption is proposed in this paper. Regarding SO, PM, and solid waste as the main pollutants, economic losses from health damage, materials corrosion, crop yield reduction, and solid waste pollution are estimated based on multiple concentration-response relationships and dose-response functions. The proposed framework and evaluation methods are applied to Beijing, China. It is evident that total economic loss attributable to energy-related environmental pollution fluctuated during 2000-2011 but had a general growth trend, with the highest value reaching 2.3 × 10 CNY (China Yuan) in 2006. Economic loss caused by health damage contributes most to the total loss among the four measured damage types. The total economic loss strongly correlates with the amount of energy consumption, especially for oil and electricity. Our evaluation framework and methods can be used widely to measure the potential impact of environmental pollution in the energy lifecycle. [ABSTRACT FROM AUTHOR]

Urban public health is an important global issue, and receives extensive attention. It is necessary to compare urban public health status among different cities, so that each city can define its own health patterns and limiting factors. The following assessment indicators were established to evaluate urban public health status: living conditions, physical health, education and culture, environmental quality, and social security. A weighted-sum model was used in combination with these indicators to compare the urban public health status in four cities-Beijing, New York, London, and Tokyo-using data for 2000-2009. Although the urban public health level of Beijing was lower than that of the other cities, it showed the greatest increase in this level over the study period. Different patterns of urban public health were identified: London had the most balanced, steady pattern (almost all factors performed well and developed stably); New York and Tokyo showed balanced, but unsteady patterns (most factors remained high, though social security and environmental quality fluctuated); Beijing had the most unbalanced, unsteady pattern (the different factors were at different levels, and education and culture and social security fluctuated). For enhanced urban public health status, environmental quality and education and culture clearly need to be improved in Beijing. This study demonstrates that a comparison of different cities is helpful in identifying limiting factors for urban public health and providing an orientation for future urban development. [ABSTRACT FROM AUTHOR]

Regarding the basic roles of urban ecosystem health assessment (i.e., discovering the comprehensive health status, and diagnosing the limiting factors of urban ecosystems), the general framework integrating comprehensive evaluation and detailed analysis is established, from both bottom-up and top-down directions. Emergy-based health indicators are established to reflect the urban ecosystem health status from a biophysical viewpoint. Considering the intrinsic uncertainty and relativity of urban ecosystem health, set pair analysis is combined with the emergy-based indicators to fill the general framework and evaluate the relative health level of urban ecosystems. These techniques are favorable for understanding the overall urban ecosystem health status and confirming the limiting factors of concerned urban ecosystems from biophysical perspective. Moreover, clustering analysis is applied by combining the health status with spatial geographical conditions. Choosing 26 typical Chinese cities in 2005, relative comprehensive urban ecosystem health levels were evaluated. The higher health levels of Xiamen, Qingdao, Shenzhen, and Zhuhai are in particular contrast to those of Wuhan, Beijing, Yinchuan, and Harbin, which are relatively poor. In addition, the conditions of each factor and related indicators are investigated through set pair analysis, from which the critical limiting factors of Beijing are confirmed. According to clustering analysis results, the urban ecosystems studied are divided into four groups. It is concluded that the proposed framework of urban ecosystem health assessment, which integrates comprehensive evaluation and detailed analysis and is fulfilled by emergy synthesis and set pair analysis, can serve as a useful tool to conduct diagnosis of urban ecosystem health. [ABSTRACT FROM AUTHOR]