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China produces and consumes a large amount of batteries annually, which leads to many waste batteries needing to be recycled. The collection and recycling system of primary, alkaline secondary, and lithium-ion secondary batteries in China is particularly poor, and waste battery recycling enterprises generally sustain economic losses if they solely use waste batteries as raw materials. Increasing the profits of waste battery recycling systems is a key problem that needs to be considered. This article quantitatively analyzes waste battery generation in China by using annual sales data and probable lifetime distribution of various batteries. The results show that the rapid growth of battery usage has led to an increased generation of waste batteries and the percentage of different types of waste batteries is changing over time. In 2013, the total quantity of all waste batteries in the medium lifetime scenario reached 570 kilotons, of which primary, alkaline secondary, and lithium-ion secondary waste batteries accounted for approximately 36%, 28%, and 35%, respectively. Based on a real-world case study of a typical domestic waste battery recycling enterprise in China, material flow analysis and cost-benefit analysis were conducted to study the development of the recycling process of comingled waste batteries. Through scenario analysis, we conclude that increasing the use of waste batteries as raw materials and the recycling of other materials that are less valuable reduces the profits of the waste battery recycling enterprise. Higher profits can be achieved by adding the production of high value-added downstream products and government support. At the same time, the essential role of the government in developing a waste battery recycling system was identified. Finally, relevant suggestions are made for improvements in both the government and enterprise sectors. [ABSTRACT FROM AUTHOR]

Abstract With the rapid development of the economy and society, the number of waste household appliances in China has increased. Although the scale of China's waste household appliance industry continues to expand, the recovery rate is relatively low compared with developed countries. As waste household appliances are important recycling resources that have potential environmental risks and a high resource value, the effective recovery, recycling and utilization of these appliances are necessary to build a circular economy system, ease environmental crises and realize sustainable development in China. An agent-based model of a waste household appliance recovery system was established in this study by using complex adaptive system theory and agent-based modeling method. The simulation of agents' behavior and scenario analysis were performed using this model, and the results were analyzed to study the evolutionary trends of the industry under different policy scenarios. Based on the exploration and interpretation of the optimal scenario, policy suggestions are proposed for different parts of the system. Highlights • An agent-based model of the waste appliance recovery system is established. • Simulation of agent behavior and development trends of the system are studied. • Scenario analyses are performed under different policy conditions. • Recovery rate, pollution and policy cost are considered and balanced in the model. • Practical policy implications are proposed according to simulation results. [ABSTRACT FROM AUTHOR]

The depletion of traditional energy sources and severe environmental pollution are hindrances in meeting the increasing energy demands of the growing global population. Solar photovoltaic (PV) technology has been widely applied in China to replace traditional energy. The factors that affect the development of the PV industry in China are complex. This research sheds light on the development process of the PV industry in China by considering the PV installed capacity as an indicator of industrial development. A quantitative evaluation method was established to assess the PV industry and its influencing factors by developing a driving force model. This model combines the methods of factor quantification and multiple regression analysis by considering demand, market, policy, technology, and enterprise factors. The results show that from 2006 to 2008, policy factors played the most important role accounting for about 50% of the total impact, and since 2009, the impacts of technology and demand factors are more significant in the PV industry from the aspects of supply and demand accounting for 36% and 32%, respectively. The future trends of PV industry are predicted based on the evolution of the influencing factors. If guided by existing policies, the PV installed capacity will stabilize at 403 GW in 2025. The emphasis on energy storage technology in the future will also significantly promote the PV industry enabling it to reach 773 GW, and thereby, reduce about 0.87 billion tonnes of carbon dioxide emissions in that year compared to that with coal-based thermal power generation. This study provides a theoretical basis for multiple factor analysis in the photovoltaic industry and a deeper understanding for policy makers to coordinate the structure of energy generation in China in the future. • A driving force model of China's photovoltaic industry is established. • Factors influencing the annual photovoltaic install capacity and their contributions are determined. • Photovoltaic industry is a good form of industrial development. • Future trends in photovoltaic industry in different scenarios are explored. • Practical policy recommendations are proposed based on factor and trend analysis. [ABSTRACT FROM AUTHOR]

Excessive anthropogenic activities have led to high-level ammonia loss and volatilization, which is regarded as a key factor in Chinese haze formation. In this study, a comprehensive analysis of ammonia emission estimations is accomplished at both temporal (1980–2016) and spatial (provincial) scales using a mass-balanced model, and emission projections through 2030 are also studied in different development scenarios. The results show that the ammonia emissions increased from 4.7 Tg N yr−1 in 1980 to 11 Tg N yr−1 in 2016, which is an approximately 2.4-fold increase. The cropland and livestock emissions are the largest contributors, as most reports show approximately 80% contributions; however, nonagriculture sources of fuel combustion, waste treatment and ammonia escape have grown rapidly in recent years, accounting for 14% in 2016. The spatial differences also reveal the complex heterogeneity in Chinese provinces. In addition, the emission intensities of major agriculture and non-agriculture sources are 0–80 kg N ha−1 yr−1 and over 100 kg N ha−1 yr−1, respectively, indicating a higher degree of ammonia concentration from non-agriculture emissions, which should attract wide concern. In terms of scenario analysis, emissions would reach 12.8 Tg N yr−1 in 2030 under the currently developed model and 7.3 Tg N yr−1 under a series of reduction policies; the spatial analysis also shows that the North China Plain has a 2.1 Tg N yr−1 reduction potential. The results of this study provide new insights into ammonia emission estimations and a better understanding of the environmental impacts of ammonia emitted from different sources. Excessive anthropogenic activities have led to high-level ammonia loss and volatilization, which is regarded as a key factor in Chinese haze formation. In this study, a comprehensive analysis of ammonia emission estimations is accomplished at both temporal (1980–2016) and spatial (provincial) scales using a mass-balanced model, revealing the temporal-spatial differences of the complex heterogeneity in China. In addition, the high-resolution sectorial emission pattern is also revealed by land-use model, indicating a higher degree of ammonia concentration from non-agriculture emissions, which should attract wider concern. Scenario analyses are also studied to reveal the emission tendency in different development scenario. The results of this study provide new insights into ammonia emission estimations and a better understanding of the environmental impacts of ammonia emitted from different sources. Unlabelled Image • Temporal and spatial variations in the ammonia emission were quantified. • The nonagriculture emissions show higher emission intensity with agriculture. • The ammonia emission to 2030 show different trends in scenario analysis. [ABSTRACT FROM AUTHOR]

While the economy and society of China are developing rapidly, various ecological and environmental problems continue to emerge. The problem of air pollution is becoming an issue of increasing concern. Since 2013, Beijing, Tianjin, and Hebei Provinces have collaborated to control air pollution and have achieved certain success. However, the air pollution problem in the capital, Beijing, remains severe. In this study, a quantitative evaluation and analysis method is established for assessing urban air quality and its influencing factors by developing a driving force model. The model combines multiple regression and principal component analysis to account for social, economic, meteorological, and regional factors. The influencing factors with the highest contributions are regional transmission, energy consumption, and industrial structure. This model is used to project the future trend of the air quality in Beijing based on the evolution of the influencing factors, aimed to provide a theoretical basis for policies improving Beijing's air quality. • A driving force model of the air quality in Beijing is established. • Factors influencing the annual air quality and their contributions are determined. • Future trends in air quality in different scenarios are explored. • Practical policy implications are proposed based on factor and trend analyses. [ABSTRACT FROM AUTHOR]