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Sulfur dioxide (SO 2 ) is still the critical environmental issue in China. The central government adopts the top-down strategy for SO 2 control. However, due to its large size and imbalanced economic development, regional disparity exists and inequity is generated. Under this condition, it requires a region-specific control policy to reach the SO 2 mitigation target effectively and efficiently. To date, there have been few studies in this area. Consequently, this study investigates the regional disparity of SO 2 emission, reduction potential and abatement cost in China's 32 regions by employing the GAINS China model, and analyzes the inequity issues and policy challenges. Results show that up to 2030, applying with flue gas desulfurization (FGD) and limestone injection technology (LINJ), China's SO 2 emissions would be reduced by 51.33% as compared to no policy scenario. Regional disparity is evident in term of reduction potential and unit abatement cost. Regions with larger scale of industry and power generation (e.g. eastern areas) and lower quality of coal (e.g. Heilongjiang province) present a larger reduction potential and lower unit abatement cost. What is more, as the result of the imbalance between middle-western and eastern regions, inequity is highlighted. Certain poor areas (like Guizhou province) have to deal with heavy SO 2 emissions and higher abatement cost per GDP with their limited budgets. Future challenges of promoting cost-effective pollution control strategy considering regional condition are discussed in-depth. Our findings are critical for relative flexible policy making. [ABSTRACT FROM AUTHOR]

Reliable forecast of municipal solid waste (MSW) generation is crucial for sustainable and efficient waste management. Big data analysis is a novel method to forecast MSW more accurately. Thus, this study employs five kinds of supervised machine learning approaches including linear regression, polynomial regression, support vector machine, random forest, and extreme gradient boosting (XGBoost) to examine their forecast performances. China's MSW generation from 2020 to 2060 under five shared socioeconomic pathways (SSPs) is further predicted and the mechanisms between MSW generation and socioeconomic features are explored. Results show that population and GDP are two dominant indicators in MSW prediction, and XGBoost model is proved to be effective in MSW forecast. MSW generation of China in 2060 is estimated to be 464–688 megatons under different SSPs scenarios, about four to six times of that in 2000. SSP3 that has the most population, least GDP and the highest climate change challenges is the only scenario showing a potential of MSW peak during the study period. The key for MSW increase is mainly the increase of per capita MSW caused by GDP. Finally, several policy recommendations are raised to reduce the overall MSW generation. • China's MSW generation under SSPs is predicted using machine learning methods. • Population and GDP are identified to be two dominant factors in MSW prediction. • XGBoost is proved to be superior to other prediction models. • The highest MSW generation appears under the fossil-fueled development pathway. • Per capita MSW but not GDP should be restricted for fast developing countries. [ABSTRACT FROM AUTHOR]

With a growing demand for crop products in China, a great deal of local resources and industrial inputs are consumed including agricultural machineries, chemical fertilizers, pesticides, and energies, which results in many environmental issues such as resource depletion, water pollution, soil erosion and contamination, and CO2 emissions. Thus, this study evaluated the trend of sustainability of China's crop production from 1997 to 2016 in terms of emergy and further explored the driving forces using decomposition analysis methods. The results showed that the total emergy used (U) increased by 50% from 7.82 × 1023 in 1997 to 1.17 × 1024 solar emergy Joule (sej) in 2016. Meanwhile, the values of the emergy sustainability index (ESI) were all smaller than one with a declining trend year by year, indicating that China's crop production system is undergoing an unsustainable development pattern. From the results of the ESI decomposition, the renewable resource factor (R/GDP) and land use factor (L/A) are two key factors impeding the sustainable development of the crop production system. Therefore, the increased capacity of renewable resources and enough labor forces engaged in crop production will be the key strategies for its sustainable development. [ABSTRACT FROM AUTHOR]

Abstract China's demand for crop products is increasing, leading to a great deal of consumption of local resources and industrial inputs such as agricultural machineries, chemical fertilizers, pesticides and energies. Many environmental problems also occurred, such as water pollution, soil erosion and contamination, and CO 2 emissions. Therefore, it is imperative to assess crop production's sustainability and identify the key driving forces of its rapid development so that the proper mitigation policies can be proposed. An emergy analysis method was employed due to its advantage of linking economic development with natural ecosystem service. Emergy sustainability index was chosen as the key indicator to measure crop production performances in 31 Chinese provinces for the period 2006–2015. The results demonstrate that the EYRs in 31 Chinese provinces are entirely keeping around 1 and the maximum and minimum values of ELR are respectively 1.71 in Guizhou and 8.29 in Tibet. Under this circumstance, the mean ESI values in 30 Chinese provinces are all less than 1, except Guizhou. This indicates that most Chinese provinces will have to improve their crop production toward sustainable agricultural development. Then, a logarithmic Mean Divisia Index (LMDI) decomposition method was applied to identify the key driving forces that affect the evolution of ESI. The change of ESI (ΔESI) was decomposed into five factors: Scale and intensity factor (I), which depends on emergy density; Non-renewable resources factor (T), which depends on the density of non-renewable resources emergy; Productivity of labor factor (P), which depends on the productivity of labor; Renewable resources factor (E), which depends on intensity of renewable resources and number of Labor (G), which depends on labor inputs. The decomposition analysis results indicate that labor and renewable resources are the major factors affecting China's sustainable crop production, while other factors also have certain impacts. Such findings can provide valuable policy insights so that more appropriate crop production policies can be prepared by considering the local realities. Highlights • Emergy sustainability index of 30 provinces are all less than 1, except Guizhou. • Labor factor is mostly maximum positive-contributors for promoting sustainability. • Renewable resources factor is mostly maximum negative-contributors. • Most provinces need to improve their crop production toward sustainable agriculture. • Increasing farmer's ratio is vital for sustainable crop production of 31 provinces. [ABSTRACT FROM AUTHOR]

Abstract: China's extraordinary economic growth, industrialization and urbanization coupled with inadequate investment in basic water supply and treatment infrastructures, have resulted in increasing industrial water pollution. However, due to imbalanced development, industrial wastewater emissions present significant regional disparity. Industrial wastewater management disparity requires more in-depth study on both spatial and temporal patterns across different regions for identification of appropriate and effective mitigation policies while considering practical and localized realities. This paper addresses this issue and contributes to new knowledge by analyzing the spatial-temporal characteristics and driving forces of industrial wastewater emission variations in China's 31 provinces during the years 1995–2010. Using the Logarithmic Mean Divisia Index (LMDI) method, the results show that economic factors are the main driving factors of industrial wastewater emission changes in all provinces during the study period. It is also found that technology improvement considerably offsets emission increases. Using these research findings, both general and specific measures for controlling industrial wastewater emissions are offered so that the overall industrial water efficiency can be improved, in China and potentially elsewhere. [Copyright &y& Elsevier]

Abstract: With material and energy flow features, iron/steel industry has unique advantage in the industrial symbiosis (IS) formation to realize environmental and economic benefit simultaneously. The quantification of the scale and significance of IS benefits is valuable for IS promotion, while there is much few attention to it, especially in China. Under this circumstance, this paper evaluates and compares the number, scale and the related environmental/economic gains of IS activities in iron/steel-centered industrial areas in Liuzhou and Jinan in China, and Kawasaki in Japan. Results show that: in Liuzhou, there are three symbiosis activities between industries. The annual by-product/waste exchange is more than 2 million ton/y, gaining economic revenue more than 36.55 million USD for the iron/steel company. In Jinan, seven symbiotic links are between industries, and two are between urban community and iron/steel plant. The total by-product/waste exchange is over 8 million ton/y and the economic gains account to 158 million USD. In Kawasaki, iron/steel industry relates to four symbiotic links, the total by-product/waste exchange amount is about 500 kton/y, with the economic gains over 54 million USD. The form and the complexity of the IS network are different in the three cases. IS in Liuzhou and Jinan are with the features of large number and scale, but single types. While in Kawasaki, IS includes not only traditional exchanges between iron/steel plant and the other industries, but also the innovative utilization of urban refuse by industrial area. Finally, from the perspective of technology, legislative framework and support policy, circular technology inventory, integrated waste management system, information platform and national subsidies are needed to support the ever-improvement of IS promotion in China's iron/steel industry. [Copyright &y& Elsevier]

• Quantifying the impact of emission is crucial to grasp provincial performance. • The emergy and LMDI methods were used to quantify EIN and identify key factors. • The reducing of intensity of fertilizer N is key factor to restrain EIN growth. • The sustainability of crop farming in 31 regions are declined by quantifying NPS. Sustainable crop production is a significant challenge in China. To achieve this goal, it is necessary to evaluate environmental impacts related to the sustainable development of crop production by integrating scientific and practical indicators. Therefore, this study employed emergy and index decomposition analysis approaches to assess the environmental impacts of non-point source pollution and the overall performance of crop production in China's 31 provinces. First, the emergy flow of emission impacts and two new indicators, the emergy sustainability index and the emergy-based pollutant-producing coefficient, were proposed to comprehensively measure crop production performance from 2012 to 2015. The results demonstrated that the environmental impacts of non-point source pollution (EIN) were predominantly attributed to total nitrogen and phosphorus contents and mulching film residuals, which substantially increased the total emergy used and reduced the sustainability of crop production in each province. The ratio of EIN plus purchased resources (F) to total emergy used (U) were consistently greater than 80% in all 31 provinces, while the ratio of local resources including the emergy of local renewable (R) and non-renewable resources (N) to the total emergy was relatively small, accounting for less than 20% in all provinces. Then, a logarithmic mean Divisia index decomposition method was applied to identify the key driving forces influencing the evolution of EIN. The decomposition analysis indicated that the economy factor had a major promoting effect on EIN growth in all provinces except Beijing and Shanghai. Intensity and technology factors had a limiting effect on EIN growth. These findings provide valuable insights for developing appropriate crop production policies that consider local conditions. [ABSTRACT FROM AUTHOR]