Evolution and trends of new energy vehicle policy research hotspots: an analysis based on a Citespace knowledge graph.

New energy vehicle (NEV) policies involve extensive and complex aspects. NEV policies have been an important issue of academic interest in the academic research community. The current research of the NEV policy has the key significance of inducing experience and guiding the future. This study conducts a comprehensive bibliometric analysis through quantitative research methods to summarize the development and evolution of NEV policy in recent years. Using Citespace visualization tools, we reviewed 2919 papers collected from the Web of Science, identified three stages in the development of the research field, and summarized features relevant to the policy in history. The most influential countries, institutions, authors, keywords, and references have been examined. Through burst detection and cluster analysis, we analyzed historical trends and trajectories in this area of research. In the data we collected, a number of indicators are related to China, indicating that China's NEV policy has a representative significance in the field of NEV policy research. Consequently, we further collected the relevant research from China, in order to summarize the policy reasons behind the rapid development of NEVs in China, and help researchers to have a better understanding of the frontiers of NEVs.

China's agricultural GHG emission efficiency: regional disparity and spatial dynamic evolution.

Improving China's agricultural greenhouse gases (GHG) emission efficiency has become an important way to cope with climate change in an ecologically-and ethically responsible manner. In this paper, we use a global slacks-based inefficiency model to evaluate the agricultural greenhouse gases (GHG) emission efficiency levels in China during 2000-2015. The regional disparity of China's GHG emission efficiency is examined by using a Dagum Gini coefficient. A spatial Markov chain technique is also employed to investigate the spatial dynamic evolution of agricultural GHG emission efficiency. The results show that: (1) China's agricultural GHG emission efficiency increased steadily during the study period; a certain gap in efficiency among provinces and regions also exists. (2) Between-group disparity is the main source of the overall regional disparities in China's agricultural GHG emission efficiency. The disparities between regions are on the rise, while the disparities within regions are relatively stable. (3) China's agricultural GHG emission efficiency demonstrates significant spatial dependence. This study provides policy implications for the sustainable development of China's agricultural sector.

Causation analysis and governance strategy for hazardous cargo accidents at ports: Case study of Tianjin Port's hazardous cargo explosion accident.

As an important part of the global shipping industry, hazardous cargo transportation at ports is concerned by countries around the world due to the great hazards and high risks during its operations. However, multiple hazardous cargo accidents have occurred at ports in recent years. The explosion accident of hazardous cargoes at Tianjin Port, China, in 2015 is a typical case. It is a topic worth in-depth study to figure out how to analyze the causation factors of such accident and propose effective governance strategies against them. This article takes the hazardous cargo explosion at Tianjin Port of China as the subject and systematically analyzes the causation factors of the accident based on the Fault Tree Analysis (FTA) method. It proposes a strategy for governing hazardous cargoes at the port. The analysis results show that the hazardous cargo explosion at the port has complicated causation factors, among which management and human factors play a predominant role in the overall accident causation structure. Other factors include environmental factors and cargo & facility factors. Finally, the corresponding safety governance strategy is proposed based on the structural relationship of various accident causation factors in the above analysis. This study can offer guidance for port enterprises to reduce hazardous cargo accidents at ports and provide an important basis for port authorities to formulate strategies on emergency management and emergency decision-making of hazardous cargo accidents at ports.

Sustainable municipal waste management strategies through life cycle assessment method: A review.

Increasing amounts of municipal solid waste (MSW) has gained widely concern on reduction, utilization and minimizing environmental impacts associated with waste management. Life cycle assessment (LCA) has been used to evaluate total environmental impact of municipal waste management (MSWM) options in strategy-planning and decision-making process. The exiting LCA studies have covered a large range of detailed focus from waste treatment technology to applied modelling methods in LCA of MSWM, yet an important concern for stakeholders, the relationship between practical management strategies and their LCA results, has not been comprehensively summarized. This paper reviews recent LCA studies focusing on MSWM system in 45 cases from both developing and developed regions to promote evolution of the MSWM system through modification of waste management strategies. Selected literatures conducted LCA with system boundary covering the whole MSWM system rather than single treatment process or specific type of waste. This review has explored distribution and evolution of LCA studies in waste management field and summarized critical parameters (system boundary, functional unit, assessment approach and data uncertainty) for conducting LCA of MSWM system. Comparison results from 45 worldwide cases indicated 33%-154% environmental benefit in Global warming potential (GWP) impact with implement of integrated solid waste management system to replace single landfill, incineration, or open dumping treatment. Key issues with upgrading of MSWM system have been highlighted to raise concern, i.e., the importance of targeted management strategy on organic and recyclable waste, the growing contribution of waste collection and transportation to the total environmental impact, as well as promoting multi-impacts assessment for MSWM system to achieve environmentally effective, economically affordable, and socially acceptable. Rather than focus on technical factors, results from this study indicated the key influences from understanding local limitation, environmental concern, management chain and comprehensive impact, providing useful strategies on improving MSWM with generalization results of LCA studies.

Impacts of natural and socioeconomic factors on PM2.5 from 2014 to 2017.

The State Council of China had issued the Air Pollution Prevention and Control Action Plan (abbreviated as "Clean Air Actions"), which ended in 2017. To evaluate the implementation effect of the clean air actions and provide the scientific basis on the future control policy, a Geographical Detector was used to quantify the impact of natural and socioeconomic factors on the PM2.5 concentration and its reductions in China from the years of 2014-2017. In terms of the impact on PM2.5 reduction, the industrial sulfur dioxide (SO2) and industrial soot emissions are the only two factors shown significant influences. So the controls of industrial emission were the major policies during the implementation of the Clean Air Actions. In terms of the impact on the PM2.5 concentrations, industrial emission was the strongest socioeconomic factor in the beginning of the Clean Air Actions, but its dominance was then declining. In contrast, the influences of population density had been enhancing and became the greatest factor in the final year. So the new control measures should focus on the urbanization regulation. In addition, the interactions between different socioeconomic factors are proved to bivariate enhance the influences on the PM2.5 concentration levels. Multiple factors should thus be taken into account when any new control policies are going to be established.

Foreign direct investment and education as determinants of environmental quality: The importance of post Paris Agreement (COP21).

This study investigates the effect of foreign direct investment and education on environmental quality for Asian countries by controlling income, energy consumption, and urbanization for the period of 1990-2018. We have applied panel cointegration techniques to probe for long-run associations among the variables. The empirical results indicate the existence of cointegration between the variables. Dynamic ordinary least square and fully modified least square methods are applied to estimate long-run elasticities. The empirical results confirm that environmental quality is sensitive to foreign direct investment, education, and urbanization. Income and energy consumption deteriorate environmental quality by increasing CO2 emissions. In the long-run, bidirectional causal associations are found for emissions- foreign direct investment, emissions-energy use, income- emissions, foreign direct investment -income, and energy-income nexus. Furthermore, there is a unidirectional causality running from education and urbanization to emissions, foreign direct investment, income, and energy use. Policymakers in Asian economies are encouraged to establish policies that increase the education budget, promote the use of green energy, attract foreign direct investment with green technology, and expand cities to limit the urbanization effects on environmental quality.

Increased secondary aerosol contribution and possible processing on polluted winter days in China.

China experiences severe particulate pollution, especially in winter, and determining the characteristics of particulate matter (PM) during pollution events is imperative for understanding the sources and causes of the pollution. However, inconsistencies have been found in the aerosol composition, sources and secondary processing among reported studies. Modern meta-analysis was used to probe the PM chemical characteristics and processing in winter at four representative regions of China, and the first finding was that secondary aerosol formation was the major effect factor for PM pollution. The secondary inorganic species behaved differently in the four regions: sulfate, nitrate, and ammonium increased in the Beijing-Tianjin-Hebei (BTH) and Guanzhong (GZ) areas, but only nitrate increased in the Pearl River Delta (PRD) and Yangtze River Delta (YRD) regions. The increased production of secondary organic aerosol (SOA) was probably caused by aqueous-phase processing in the GZ and BTH regions and by photochemical reactions in the PRD. Finally, we suggest future AMS/ACSM observations should focus on the aerosol characteristics in rural areas in winter in China.

Particle Swarm Optimization With Interswarm Interactive Learning Strategy.

The learning strategy in the canonical particle swarm optimization (PSO) algorithm is often blamed for being the primary reason for loss of diversity. Population diversity maintenance is crucial for preventing particles from being stuck into local optima. In this paper, we present an improved PSO algorithm with an interswarm interactive learning strategy (IILPSO) by overcoming the drawbacks of the canonical PSO algorithm's learning strategy. IILPSO is inspired by the phenomenon in human society that the interactive learning behavior takes place among different groups. Particles in IILPSO are divided into two swarms. The interswarm interactive learning (IIL) behavior is triggered when the best particle's fitness value of both the swarms does not improve for a certain number of iterations. According to the best particle's fitness value of each swarm, the softmax method and roulette method are used to determine the roles of the two swarms as the learning swarm and the learned swarm. In addition, the velocity mutation operator and global best vibration strategy are used to improve the algorithm's global search capability. The IIL strategy is applied to PSO with global star and local ring structures, which are termed as IILPSO-G and IILPSO-L algorithm, respectively. Numerical experiments are conducted to compare the proposed algorithms with eight popular PSO variants. From the experimental results, IILPSO demonstrates the good performance in terms of solution accuracy, convergence speed, and reliability. Finally, the variations of the population diversity in the entire search process provide an explanation why IILPSO performs effectively.