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Yalin Lei
School of Economics and Management, China University of Geosciences, Beijing, 100083, China

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Journal article
Published: 05 July 2021 in Resources Policy
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Mining industry is the basic industry of the national economy. However, in recent years, listed mining companies have suffered serious financial risks due to special reasons such as poor spot market liquidity of their products, strong policy dependence, and long investment payback periods. In the previous studies, most of the financial crisis prediction focused on the whole industry and manufacturing industry. The research on the financial risk of mining enterprises focuses more on how to adjust R&D activities, environmental performance to improve the financial performance of enterprises. There is still a lot of room for in-depth research on the systematic prevention and early warning of financial risks of listed mining companies. At the same time, in terms of research methods, many scholars used multivariate discriminant model, logistic regression model and support vector machine model. Compared with the Back-Propagation (BP) neural network model, these model methods have more or less defects. Therefore, we take mining listed companies as the research object, select the financial data of China's A-share mining listed companies in 2018, and construct the BP neural network financial early warning model, trying to provide more practical means for the financial risk early warning of mining companies. The research conclusions of this paper are as follows: (1) The BP neural network financial early warning model constructed in this paper has high prediction accuracy, which can be well used in the practice of financial early warning of mining listed companies; (2) The financial situation of China's A-share mining listed companies in 2018 is generally in a good state. The companies with good financial status can effectively control the cost and have good debt paying ability while earning income; (3) For companies with financial status that require early warning, the root cause is mainly that they do not pay attention to the risk of bad debt losses, which makes current credit sales income and accounts receivable are at high levels, and they also do not have good profitability.

ACS Style

Xiaojun Sun; Yalin Lei. Research on financial early warning of mining listed companies based on BP neural network model. Resources Policy 2021, 73, 102223 .

AMA Style

Xiaojun Sun, Yalin Lei. Research on financial early warning of mining listed companies based on BP neural network model. Resources Policy. 2021; 73 ():102223.

Chicago/Turabian Style

Xiaojun Sun; Yalin Lei. 2021. "Research on financial early warning of mining listed companies based on BP neural network model." Resources Policy 73, no. : 102223.

Journal article
Published: 06 May 2021 in Resources Policy
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Analyzing a policy's implementation efficiency and the factors influencing it can help improve the policy. Because China's resource tax policy varies by province, it is more meaningful to consider the implementation efficiency from the provincial level. Using provincial panel data of China from 2009 to 2017, this study measures the efficiency of tax resource policies utilizing the slacks-based measure integrating the data envelopment analysis (SBM-DEA) method containing the undesired output. Then, the Tobit model is used to verify the factors affecting the efficiency. The results show that the annual average efficiency of resource tax in China is between 0.4 and 0.7, with obvious regional and provincial differences due to scale efficiency. However, the comprehensive efficiency of resource tax policies in most provinces is fluctuating and rising, indicating that resource tax policies can gradually play a role. Further examining the influencing factors shows that the pollution treatment cost, the proportion of secondary industry, and energy consumption have a significant positive effect on efficiency, while the level of economic development has an obvious negative effect. Finally, to formulate plans to fully leverage their tax advantages, all provincial governments should consider the differences in efficiency.

ACS Style

Yuhang Ji; Yalin Lei; Li Li; An Zhang; Sanmang Wu; Qun Li. Evaluation of the implementation effects and the influencing factors of resource tax in China. Resources Policy 2021, 72, 102126 .

AMA Style

Yuhang Ji, Yalin Lei, Li Li, An Zhang, Sanmang Wu, Qun Li. Evaluation of the implementation effects and the influencing factors of resource tax in China. Resources Policy. 2021; 72 ():102126.

Chicago/Turabian Style

Yuhang Ji; Yalin Lei; Li Li; An Zhang; Sanmang Wu; Qun Li. 2021. "Evaluation of the implementation effects and the influencing factors of resource tax in China." Resources Policy 72, no. : 102126.

Journal article
Published: 05 May 2021 in Journal of Cleaner Production
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As an important grain production base in China, the Yellow River basin (YRB) plays an important role in China's economic development and ecological security. However, with increasing agricultural water environmental problems and deteriorating water quality, the agricultural water situation in the YRB is grim. Under the background of comprehensively promoting the high-quality development of the YRB, improving agricultural water efficiency can reduce the constraint effect of insufficient water resources on agriculture and improve the water ecological environment, which will help achieve coordinated social, economic and environmental development. In this study, agricultural water efficiency of nine provinces in the YRB from 2008 to 2017 was measured by the super-efficient slack-based measured Data Envelopment Analysis (SBM-DEA) method with unexpected outputs, spatial autocorrelation analysis and the Malmquist index, and the key influencing factors were identified by the spatial Tobit regression model. The results showed that the agricultural water efficiency of nine provinces in the YRB was increasing, with large differences among provinces and little spatial correlation, presenting a spatial distribution with the lower reaches higher than the middle reaches and the middle reaches higher than the upper reaches; the change in the Malmquist index of agricultural water showed an increasing trend, which was mainly determined by the technical progress. Additionally, the economic development level and water resource endowment had positive effects on agricultural water efficiency, while government expenditure and urbanization level had significant negative correlation with agricultural water efficiency.

ACS Style

Jingxue Wei; Yalin Lei; Huajun Yao; Jianping Ge; Sanmang Wu; Lingna Liu. Estimation and influencing factors of agricultural water efficiency in the Yellow River basin, China. Journal of Cleaner Production 2021, 308, 127249 .

AMA Style

Jingxue Wei, Yalin Lei, Huajun Yao, Jianping Ge, Sanmang Wu, Lingna Liu. Estimation and influencing factors of agricultural water efficiency in the Yellow River basin, China. Journal of Cleaner Production. 2021; 308 ():127249.

Chicago/Turabian Style

Jingxue Wei; Yalin Lei; Huajun Yao; Jianping Ge; Sanmang Wu; Lingna Liu. 2021. "Estimation and influencing factors of agricultural water efficiency in the Yellow River basin, China." Journal of Cleaner Production 308, no. : 127249.

Journal article
Published: 21 April 2021 in Science of The Total Environment
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To address the CO2 emissions issue, China promised to increase its nationally determined contributions, trying to reach a CO2 emissions peak by 2030. For optimizing emission reduction policies, it is important to clarify the CO2 linkage structure and transfer characteristics. Previous research mainly focused on the calculation and comparison of CO2 linkage at the national level or the regional level and lacked inter-provincial sector-sector transfer analysis. This study uses hypothetical extraction method (HEM) to calculate the inter-provincial sectoral linkages of embodied CO2 in 2012 and 2015, providing a new perspective for sectoral CO2 linkage studies in China. We use net transfer to reveal the impact of provincial trade on the embodied CO2 emissions, and identify key CO2 emitter sectors. Combined with complex networks, we describe the clustering feature visualized and identify the transfer media sectors. The results are as follows: (1) the key sectors with large linkage are mainly the heavy industries located in North China. The electricity industry has the largest net CO2 outflow as the energy supplier, whereas the construction industry has the largest net inflow as the driving sector. (2) The CO2 transfer networks present closely connected and spatial clustering features, reflecting the embodied CO2 linkage between geographically adjacent sectors closer. (3) The important media sectors are mostly located in northwest China with small industrial scale and linkage degrees, such as the transport equipment industry in Shanxi. Emission reduction policies should be overall planned and tailored to local conditions. Consequently, possible policy implications of the results are discussed, which could provide additional insights for CO2 mitigation.

ACS Style

Yuying Wang; Yalin Lei; Fengyan Fan; Li Li; Lingna Liu; Hongtao Wang. Inter-provincial sectoral embodied CO2 net-transfer analysis in China based on hypothetical extraction method and complex network analysis. Science of The Total Environment 2021, 786, 147211 .

AMA Style

Yuying Wang, Yalin Lei, Fengyan Fan, Li Li, Lingna Liu, Hongtao Wang. Inter-provincial sectoral embodied CO2 net-transfer analysis in China based on hypothetical extraction method and complex network analysis. Science of The Total Environment. 2021; 786 ():147211.

Chicago/Turabian Style

Yuying Wang; Yalin Lei; Fengyan Fan; Li Li; Lingna Liu; Hongtao Wang. 2021. "Inter-provincial sectoral embodied CO2 net-transfer analysis in China based on hypothetical extraction method and complex network analysis." Science of The Total Environment 786, no. : 147211.

Research article
Published: 04 March 2020 in Environmental Science and Pollution Research
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Counterpart cooperation is a major innovative measure in China’s strategy for revitalizing north-eastern China. While promoting economic progress, regional counterpart cooperation should also focus on low-carbon economy and sustainable development. Under the background of China’s proposed innovative cooperation strategy, using a multi-regional input-output (MRIO) model and structural decomposition analysis (SDA), this study takes Jilin province and its counterpart Zhejiang province as an example and decomposes the change in carbon emission intensity (CEI), which is a widely used indicator to measure regional carbon emission performance. The decomposition spans the years 2007 to 2012, at the level of two provinces and departments. By comparing the factors that drive and inhibit CEI in the two provinces, it was found that the production technology effect in Jilin province primarily drove the growth in CEI, while in Zhejiang province, the opposite occurred. Second, the structural effects of agriculture and heavy industry in Jilin province accounted for the largest proportion of this change, and the pulling effect on the increase in CEI in Jilin was significantly higher than that in Zhejiang province. Third, the scale effect of agricultural demand in Zhejiang province was much higher than that in Jilin province, and the same trend was observed for the scale effect of heavy industrial exports.

ACS Style

Dongrui Li; Yalin Lei; Li Li; Lingna Liu. Study on industrial selection of counterpart cooperation between Jilin province and Zhejiang province in China from the perspective of low carbon. Environmental Science and Pollution Research 2020, 27, 16668 -16676.

AMA Style

Dongrui Li, Yalin Lei, Li Li, Lingna Liu. Study on industrial selection of counterpart cooperation between Jilin province and Zhejiang province in China from the perspective of low carbon. Environmental Science and Pollution Research. 2020; 27 (14):16668-16676.

Chicago/Turabian Style

Dongrui Li; Yalin Lei; Li Li; Lingna Liu. 2020. "Study on industrial selection of counterpart cooperation between Jilin province and Zhejiang province in China from the perspective of low carbon." Environmental Science and Pollution Research 27, no. 14: 16668-16676.

Journal article
Published: 09 February 2020 in Ecological Indicators
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The ecological footprint (EF) describes the complex relationship between the eco-environment and economic development. EF dynamics can better reflect the appropriation of natural resources in various countries or regions compared with previous studies. This paper identified six dominant factors including population, per capita GDP, three major industrial added values, and energy consumption using grey correlation model for the EF changes of the Beijing-Tianjin-Hebei (Jing-Jin-Ji) region from 1996 to 2015. Then, we predicted the EF of the Jing-Jin-Ji region from 2016 to 2020 based on support vector machine model. (1) Since 1996, the EF and per capita EF of the overall Jing-Jin-Ji region have increased, of which those of Hebei Province and Tianjin increased while Beijing decreased. (2) Energy consumption dominated the EF of Jing-Jin-Ji region. The population of Beijing had a high correlation coefficient of 0.735 with the local EF, and the degree of correlation between the EF and per capita GDP was 0.812 in Hebei Province. In Tianjin, the added value of the tertiary industry was closely correlated with its EF, with a correlation coefficient of 0.741. (3) The EF of the Jing-Jin-Ji region will reach 778.30 million hectares by 2020, an increase of 10% compared with the value in 2015. Finally, suggestions for the development of industrial structure and energy consumption are listed for the sustainable development of Jing-Jin-Ji region.

ACS Style

Lingna Liu; Yalin Lei. Dynamic changes of the ecological footprint in the Beijing-Tianjin-Hebei region from 1996 to 2020. Ecological Indicators 2020, 112, 106142 .

AMA Style

Lingna Liu, Yalin Lei. Dynamic changes of the ecological footprint in the Beijing-Tianjin-Hebei region from 1996 to 2020. Ecological Indicators. 2020; 112 ():106142.

Chicago/Turabian Style

Lingna Liu; Yalin Lei. 2020. "Dynamic changes of the ecological footprint in the Beijing-Tianjin-Hebei region from 1996 to 2020." Ecological Indicators 112, no. : 106142.

Journal article
Published: 23 November 2019 in Science of The Total Environment
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Controlling CO2 emissions (CEs) is an important measure to mitigate global climate change. In recent years, the research on household consumption and its environmental impact has become a research hotspot in the field of sustainable development. Taking 2000–2014 as the research period, this paper studies the indirect CO2 emissions of household consumption (ICEs-HC) in China by using the Multi-region Input-Output model. Then the structural decomposition analysis method is used to analyze the driving factors of ICEs-HC. The results show that: (1) During the study period, ICEs-HC in China showed an increasing trend. The total ICEs-HC increased by 1.90 times, and the per capita ICEs-HC increased by 1.76 times. (2) ICEs-HC in China are concentrated mainly in Commercial and Public Services (CPS), Electricity, Gas, Steam and Air Conditioning Supply (EGSA), and Manufacture of Food and Tobacco (MFT), which accounted for 26.63%, 17.69% and 13.52%, respectively, of the total emissions in 2014. (3) China has been in the position of net outflow of ICEs-HC. (4) The growth of per capita household consumption is the main factor promoting the growth of ICEs-HC in China, and the reduction of carbon intensity in various countries is the main factor in restraining ICEs-HC in China. This study shows that ICEs-HC in China are likely to rise, and the government should not only constantly improve the level of household consumption, but also actively adjust the industrial structure and optimize the consumption structure to alleviate CEs effectively.

ACS Style

Qiuping Li; Sanmang Wu; Yalin Lei; Shantong Li. Dynamic features and driving forces of indirect CO2 emissions from Chinese household: A comparative and mitigation strategies analysis. Science of The Total Environment 2019, 704, 135367 .

AMA Style

Qiuping Li, Sanmang Wu, Yalin Lei, Shantong Li. Dynamic features and driving forces of indirect CO2 emissions from Chinese household: A comparative and mitigation strategies analysis. Science of The Total Environment. 2019; 704 ():135367.

Chicago/Turabian Style

Qiuping Li; Sanmang Wu; Yalin Lei; Shantong Li. 2019. "Dynamic features and driving forces of indirect CO2 emissions from Chinese household: A comparative and mitigation strategies analysis." Science of The Total Environment 704, no. : 135367.

Journal article
Published: 23 September 2019 in Applied Energy
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Emission accounting can help to identify main CO2 emitters and inform emission mitigation policymaking. Previous studies have proved that the application of different accounting principles results in different emission levels, thus bring different policy implications, while the emissions enabled by primary inputs (or income-based emission) have been overlooked in studies for carbon mitigation in China. Understanding the role of primary inputs in CO2 emissions is a prerequisite to create efficient supply-side mitigation policies. Here, we conduct a quantitative study of China’s provincial production-, consumption-, and income-based CO2 emissions in a unified multi-regional input-output analysis framework. The results are compared from the three perspectives for 30 provinces in China to help the government identify the main policy targets from production, demand, and supply sides. We found that 64% and 35% of China’s emissions are transferred among provinces driven by final demands and primary inputs, respectively. Mitigation policies in heavily industrialized provinces, such as Hebei, Liaoning, and Henan, where the production-based emissions are higher than the consumption- and income-based emissions, should be focused on production side. Similarly, policies in eastern coastal developed provinces and resource-abundant provinces should be focused on demand- and supply-side, respectively. Moreover, we found that tertiary industries, which previous studies generally regard as low-carbon industries, are the major contributors to China’s income-based CO2 emissions with a total of 2026 Mt or 31% of China’s total income-based CO2 emissions. Thus, expanding tertiary industries without reducing their industrial linkages to carbon-intensive industries is not conducive to China’s emission reduction.

ACS Style

Weiming Chen; Yalin Lei; Kuishuang Feng; Sanmang Wu; Li Li. Provincial emission accounting for CO2 mitigation in China: Insights from production, consumption and income perspectives. Applied Energy 2019, 255, 113754 .

AMA Style

Weiming Chen, Yalin Lei, Kuishuang Feng, Sanmang Wu, Li Li. Provincial emission accounting for CO2 mitigation in China: Insights from production, consumption and income perspectives. Applied Energy. 2019; 255 ():113754.

Chicago/Turabian Style

Weiming Chen; Yalin Lei; Kuishuang Feng; Sanmang Wu; Li Li. 2019. "Provincial emission accounting for CO2 mitigation in China: Insights from production, consumption and income perspectives." Applied Energy 255, no. : 113754.

Journal article
Published: 01 September 2019 in Science of The Total Environment
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The Strategies of Reviving the Old Industrial Bases provide opportunities for low-carbon transition in Northeast China, which is one of the earliest regions to industrialize and the largest rustbelt in China, but study on the impacts of its socioeconomic factors on CO2 emissions is still in short, though it is essential for guiding the pathways to achieve low-carbon socioeconomic transition. We adopted the structural decomposition analysis (SDA) to identify the main contributors to emissions increase in Heilongjiang province during 2002-2012, which is the heartland of Northeast revitalization. The results show that the increase in CO2 emissions was mainly driven by growth in per-capita final demand, which generated 203.8 Mt (153.6%) upstream CO2 emissions between 2002 and 2012. Changes in production structure and final demand structure had smaller impacts on CO2 emissions increase (36.1 Mt and 27.0 Mt). However, the positive influences were largely overwhelmed by change in emission intensity, which avoided 135.4 Mt (-102%) CO2 emissions. Therefore, appropriate measures related to energy structure optimization and efficiency improvement should be implemented. Especially, increasing the proportion of wind, solar and biomass energy in Heilongjiang, where renewable energy is abundant, would reduce the CO2 emissions significantly. In addition, domestic export took the lead position in driving the CO2 emissions in Heilongjiang, accounting for 37.6%-43.1% annual emissions between 2002 and 2012. Thus, some financial instrument, such as tax relief for less carbon intensive exports could be adopted to prompt upstream suppliers to decarbonize their production processes.

ACS Style

Weiming Chen; Yalin Lei; Sanmang Wu; Li Li. Opportunities for low-carbon socioeconomic transition during the revitalization of Northeast China: Insights from Heilongjiang province. Science of The Total Environment 2019, 683, 380 -388.

AMA Style

Weiming Chen, Yalin Lei, Sanmang Wu, Li Li. Opportunities for low-carbon socioeconomic transition during the revitalization of Northeast China: Insights from Heilongjiang province. Science of The Total Environment. 2019; 683 ():380-388.

Chicago/Turabian Style

Weiming Chen; Yalin Lei; Sanmang Wu; Li Li. 2019. "Opportunities for low-carbon socioeconomic transition during the revitalization of Northeast China: Insights from Heilongjiang province." Science of The Total Environment 683, no. : 380-388.

Journal article
Published: 01 June 2019 in Applied Energy
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ACS Style

Li Li; Yuli Shan; Yalin Lei; Sanmang Wu; Xiang Yu; Xiyan Lin; Yupei Chen. Decoupling of economic growth and emissions in China’s cities: A case study of the Central Plains urban agglomeration. Applied Energy 2019, 244, 36 -45.

AMA Style

Li Li, Yuli Shan, Yalin Lei, Sanmang Wu, Xiang Yu, Xiyan Lin, Yupei Chen. Decoupling of economic growth and emissions in China’s cities: A case study of the Central Plains urban agglomeration. Applied Energy. 2019; 244 ():36-45.

Chicago/Turabian Style

Li Li; Yuli Shan; Yalin Lei; Sanmang Wu; Xiang Yu; Xiyan Lin; Yupei Chen. 2019. "Decoupling of economic growth and emissions in China’s cities: A case study of the Central Plains urban agglomeration." Applied Energy 244, no. : 36-45.

Research article
Published: 04 April 2019 in Environmental Science and Pollution Research
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Carbon capture and storage (CCS) could be an effective measurement for carbon emission reduction in China. This paper summarizes the development of power sector in 2020, 2030, and 2050, and it classifies 18 scenarios including with and without CCS, respectively, in G1:low, G2:middle, and G3:high in 2020, 2030, and 2050. It adopts China’s input-output table (IO table) and analyzes the different mitigation strategies for power sector. In particular, this paper builds a new China’s input-output table based on aggregating the sectors in IO table and disaggregating the power sector into 11 different technologies which are coal-fire power, coal-fire power with CCS, natural gas power, natural gas power with CCS, hydropower, nuclear power, wind power, solar power, biomass power, geothermal power, and ocean power. Through input-output model, this paper estimates gross value added (GVA) and employment effects of different scenarios of different technologies in power sector in China. It finds that the differences of GVA and employment effects among different scenarios are large. In CCS scenarios, the coal-fire power with CCS contribute 1.48–1.63 × 1010 RMB in 2020, 1.09–1.55 × 1010 RMB in 2030, and 0.85–1.20 × 1010 RMB in 2050 for gross value added. Meanwhile, the employments of coal-fire power with CCS can add the jobs of 11,966–17,159 in 2020; 10,419–16,228 in 2030; and 8977–12,571 in 2050. CCS sector contributes the higher employment than in the renewable power sectors. Meanwhile, coal mining industry, equipment manufacturing industry, and metallic industry take main contribution to the employment of CCS sector.

ACS Style

Yong Jiang; Yalin Lei; Xin Yan; Yongzhi Yang. Employment impact assessment of carbon capture and storage (CCS) in China’s power sector based on input-output model. Environmental Science and Pollution Research 2019, 26, 15665 -15676.

AMA Style

Yong Jiang, Yalin Lei, Xin Yan, Yongzhi Yang. Employment impact assessment of carbon capture and storage (CCS) in China’s power sector based on input-output model. Environmental Science and Pollution Research. 2019; 26 (15):15665-15676.

Chicago/Turabian Style

Yong Jiang; Yalin Lei; Xin Yan; Yongzhi Yang. 2019. "Employment impact assessment of carbon capture and storage (CCS) in China’s power sector based on input-output model." Environmental Science and Pollution Research 26, no. 15: 15665-15676.

Journal article
Published: 21 March 2019 in Journal of Cleaner Production
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As the capital economic circle, Jing-Jin-Ji (Beijing-Tianjin-Hebei) faces a serious shortage of land resources and a deterioration of the ecological environment owing to economic development. Alleviating ecological pressure has become a focus issue in the region. Extant studies have mainly focused on the ecological carrying capacity of individual regions, while research on the ecological dependency relationship between various regions has been lacking. In this article, the authors analyze the embodied ecological footprint transfer between Jing-Jin-Ji and China’s other provinces by using a multi-regional input–output method. According to results, the metal/non-metallic mineral and agriculture industries in Jing-Jin-Ji exported a large amount of embodied ecological footprint to eastern coastal areas. However, the ecological footprint outflow of Jing-Jin-Ji can be attributed to Hebei province, with Beijing and Tianjin showing some net inflow. In interior Jing-Jin-Ji, Hebei has transferred a large number of embodied ecological footprints to Beijing and Tianjin, but Hebei has not achieved equivalent economic benefits. Thus, Jing-Jin-Ji should further increase its dependence on ecological resources in other provinces; Hebei should especially reduce metal and agriculture product exports. Meanwhile, an ecological compensation system should be established to use the funds provided by Beijing and Tianjin to support the transformation of economic growth mode in Hebei.

ACS Style

Lei Zhan; Yalin Lei; Li Li; Jianping Ge. Interprovincial transfer of ecological footprint among the region of Jing-Jin-Ji and other provinces in China: A quantification based on MRIO model. Journal of Cleaner Production 2019, 225, 304 -314.

AMA Style

Lei Zhan, Yalin Lei, Li Li, Jianping Ge. Interprovincial transfer of ecological footprint among the region of Jing-Jin-Ji and other provinces in China: A quantification based on MRIO model. Journal of Cleaner Production. 2019; 225 ():304-314.

Chicago/Turabian Style

Lei Zhan; Yalin Lei; Li Li; Jianping Ge. 2019. "Interprovincial transfer of ecological footprint among the region of Jing-Jin-Ji and other provinces in China: A quantification based on MRIO model." Journal of Cleaner Production 225, no. : 304-314.

Special issue
Published: 25 February 2019 in Mathematical Geosciences
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Geothermal energy is a clean energy source that can potentially mitigate greenhouse gas emissions, as its use can lead to a lower mitigation cost. However, research on the economic impacts of the geothermal industry is scarce. This paper describes the effect of the geothermal industry, its economic input and output, using Beijing as a case study. This paper adopts the input–output model. The results show that the demand for and input use of the geothermal sector vary greatly across industrial sectors: electricity, heat production, the supply industry and general equipment manufacturing have the greatest direct consumption coefficient for the geothermal industry. When considering direct and indirect demand, it is clear that the geothermal industry has a great effect on different industrial sectors in diverse ways. Its influence coefficient and sensitivity coefficient are 1.2167 (ranked 11th) and 1.2293 (ranked 8th), respectively, revealing that it exerts obvious demand-pulling and supply-pushing effects on the regional economy.

ACS Style

Yong Jiang; Yalin Lei; Jing Liu. Economic Impacts of the Geothermal Industry in Beijing, China: An Input–Output Approach. Mathematical Geosciences 2019, 51, 353 -372.

AMA Style

Yong Jiang, Yalin Lei, Jing Liu. Economic Impacts of the Geothermal Industry in Beijing, China: An Input–Output Approach. Mathematical Geosciences. 2019; 51 (3):353-372.

Chicago/Turabian Style

Yong Jiang; Yalin Lei; Jing Liu. 2019. "Economic Impacts of the Geothermal Industry in Beijing, China: An Input–Output Approach." Mathematical Geosciences 51, no. 3: 353-372.

Research article
Published: 25 January 2019 in Environmental Science and Pollution Research
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Jing-Jin-Ji is the largest and most dynamic economic region in northern China, and its air pollution has attracted much public attention. Scientific evaluation of health losses caused by air pollution can provide decision-making basis for formulation and improvement of pollution reduction policies in the Jing-Jin-Ji region. This paper estimated the adverse effects of particulate matter pollution on health in the Jing-Jin-Ji region in 2016 by using logarithmic linear exposure-response function, and monetized the health effects by adjusting human capital method and disease cost method. The results show non-ignorable health hazards and economic impacts caused by atmospheric particulate pollution. The economic losses relevant to health hazards by PM2.5 in the Jing-Jin-Ji region are 122.40 billion yuan, and those relevant to PM10 are 118.34 billion yuan, accounting for 1.62% and 1.56% of the region’s GDP, respectively. Similar evaluations previously conducted in other countries yielded figures within the same order of magnitude. Considering the difference in economic losses per unit among disease types, the economic losses caused by air pollution in the Jing-Jin-Ji region mainly come from premature deaths. Infants and elderly people are the main victims of particulate matter. Affected by population, pollutant concentration, industrial structure, and other factors, the economic losses of particulate matter pollution in Beijing, Tianjin, Shijiazhuang, Tangshan, and Baoding are large. In order to reduce health hazards and economic impacts caused by particulate matter pollution, this paper put forward to guide the urban population diversion, reduce the outgoing frequency of susceptible groups such as infants and the elderly in haze weather, adopt high-efficiency particulate matter air purifier indoors, and develop public transportation to reduce motor vehicle exhaust emissions. In Tianjin and Hebei, promoting cleaner production in industries such as steel and cement and reducing coal use in the power industry are also suggested.

ACS Style

Fengyan Fan; Yalin Lei; Li Li. Health damage assessment of particulate matter pollution in Jing-Jin-Ji region of China. Environmental Science and Pollution Research 2019, 26, 7883 -7895.

AMA Style

Fengyan Fan, Yalin Lei, Li Li. Health damage assessment of particulate matter pollution in Jing-Jin-Ji region of China. Environmental Science and Pollution Research. 2019; 26 (8):7883-7895.

Chicago/Turabian Style

Fengyan Fan; Yalin Lei; Li Li. 2019. "Health damage assessment of particulate matter pollution in Jing-Jin-Ji region of China." Environmental Science and Pollution Research 26, no. 8: 7883-7895.

Research article
Published: 17 December 2018 in Environmental Science and Pollution Research
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Emission of greenhouse gas is a global environmental problem. In recent years, China has been facing growing international pressure because of its large energy consumption and elevated greenhouse gas emissions. As the capital of China, Beijing is central to the study of carbon emission reduction since its carbon emissions have ranked at the forefront nationwide. The existing literature mainly revolves around carbon emissions of a few specific years, and there is a lack of trend study of multiple years in Beijing. This paper, based on the input-output method, calculates carbon emissions in Beijing by carbon footprints; the changing trend analysis was carried out by researching available statistical data of three years, 2002, 2007, and 2012, from the perspective of the entire city of Beijing and from that of urban and rural residents’ consumption. The reasons for the changing trends of total carbon emission in Beijing have also been analysed using the Structural Decomposition Analysis (SDA) model. Results show that the total direct carbon footprint as well as the urban and rural direct carbon footprints of residents’ consumption in Beijing is all increasing gradually. The direct carbon footprint of urban residents’ consumption is mainly produced by electricity, gasoline, and heating power, while that of rural residents’ consumption is mainly produced by raw coal and electricity. The indirect carbon footprint of residents’ consumption in Beijing is increasing gradually, and that of urban areas is higher than that of rural areas. The compositions of indirect carbon footprints of rural and urban residents’ consumption are consistent, and both come mainly from the transportation and communication industry, housing, food, culture, education, entertainment, etc. The SDA results show that the per capita consumption level is the main driving factor for the increase of the indirect carbon footprint of Beijing residents’ consumption, and the intensity of CO2 emission is the main inhibiting factor. Finally, suggestions for reducing carbon emissions from urban and rural perspectives have been put forward.

ACS Style

Zhenting Fan; Yalin Lei; Sanmang Wu. Research on the changing trend of the carbon footprint of residents’ consumption in Beijing. Environmental Science and Pollution Research 2018, 26, 4078 -4090.

AMA Style

Zhenting Fan, Yalin Lei, Sanmang Wu. Research on the changing trend of the carbon footprint of residents’ consumption in Beijing. Environmental Science and Pollution Research. 2018; 26 (4):4078-4090.

Chicago/Turabian Style

Zhenting Fan; Yalin Lei; Sanmang Wu. 2018. "Research on the changing trend of the carbon footprint of residents’ consumption in Beijing." Environmental Science and Pollution Research 26, no. 4: 4078-4090.

Correction
Published: 21 November 2018 in Environmental Science and Pollution Research
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The original publication of this paper contains a mistake. The correct image of figure 4 is shown in this paper. The original article has been corrected.

ACS Style

Qiuping Li; Sanmang Wu; Yalin Lei; Shantong Li; Li Li. Correction to: China’s provincial CO2 emissions and interprovincial transfer caused by investment demand. Environmental Science and Pollution Research 2018, 26, 326 -327.

AMA Style

Qiuping Li, Sanmang Wu, Yalin Lei, Shantong Li, Li Li. Correction to: China’s provincial CO2 emissions and interprovincial transfer caused by investment demand. Environmental Science and Pollution Research. 2018; 26 (1):326-327.

Chicago/Turabian Style

Qiuping Li; Sanmang Wu; Yalin Lei; Shantong Li; Li Li. 2018. "Correction to: China’s provincial CO2 emissions and interprovincial transfer caused by investment demand." Environmental Science and Pollution Research 26, no. 1: 326-327.

Research article
Published: 05 November 2018 in Environmental Science and Pollution Research
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Based on the China's 1997, 2002, 2007, and 2012 multiregional input-output model, this study calculates China's provincial CO2 emissions from investment demand and interprovincial transfer of CO2 emissions caused by investment demand. The findings of this study are as follows: (1) From 1997 to 2012, the CO2 emissions from China's investment demand have seen rapid growth-the CO2 emissions from investment demand has increased by 4.52 times, and the per capita CO2 emissions caused by investment demand has increased by 4.13 times. Investment demand is an important driver of growth of China's CO2 emissions. The proportion of CO2 emissions from investment demand in CO2 emissions from China's three final demands rose from 37.72% in 1997 to 50.68% in 2012. (2) The CO2 emissions from investment demand are relatively large in provinces which have large-scale industries. Affected by investment-driven economic growth, CO2 emissions from investment demand in central, western, and northeastern provinces have increased more rapidly. (3) Large amounts of CO2 are emitted in the less-developed central and western provinces to meet the investment demand of the developed eastern provinces. As China's economy enters the "new normal," economic growth is shifting from investment-driven to consumption-driven, and the growth of CO2 emissions from investment demand will slow down.

ACS Style

Qiuping Li; Sanmang Wu; Yalin Lei; Shantong Li; Li Li. China’s provincial CO2 emissions and interprovincial transfer caused by investment demand. Environmental Science and Pollution Research 2018, 26, 312 -325.

AMA Style

Qiuping Li, Sanmang Wu, Yalin Lei, Shantong Li, Li Li. China’s provincial CO2 emissions and interprovincial transfer caused by investment demand. Environmental Science and Pollution Research. 2018; 26 (1):312-325.

Chicago/Turabian Style

Qiuping Li; Sanmang Wu; Yalin Lei; Shantong Li; Li Li. 2018. "China’s provincial CO2 emissions and interprovincial transfer caused by investment demand." Environmental Science and Pollution Research 26, no. 1: 312-325.

Journal article
Published: 06 September 2018 in Science of The Total Environment
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As the largest energy consumer and CO2-emitting country, China is committed to achieving a low-carbon economy (LCE). This study seeks to understand the spatial evolution of China's LCE provinces and determine which sectors could promote the formation of LCE provinces. Multiregional input-output (MRIO) analysis is applied to filter the LCE provinces and the sectoral structure changes behind the LCE in China from 2002 to 2012. The result shows that approximately 30% of the provinces (i.e., Tianjin, Zhejiang, Jiangsu and Chongqing) become LCE provinces faster than other provinces from 2002 to 2012, and the location of the LCE provinces gradually shifts from coastal to inland regions after 2007. Some sectors (i.e., nonmetal mining, chemical industry and nonmetal manufacturing) gradually become LCE sectors from 2002 to 2012, and these sectors promote the formation and development of LCE provinces. On this basis, this study proposes policy implications regarding the benchmarking of sectors and a sectoral structure that can promote the formation of LCE provinces.

ACS Style

Xin Yan; Jianping Ge; Yalin Lei; Hongyu Duo. China's low-carbon economic transition: Provincial analysis from 2002 to 2012. Science of The Total Environment 2018, 650, 1050 -1061.

AMA Style

Xin Yan, Jianping Ge, Yalin Lei, Hongyu Duo. China's low-carbon economic transition: Provincial analysis from 2002 to 2012. Science of The Total Environment. 2018; 650 ():1050-1061.

Chicago/Turabian Style

Xin Yan; Jianping Ge; Yalin Lei; Hongyu Duo. 2018. "China's low-carbon economic transition: Provincial analysis from 2002 to 2012." Science of The Total Environment 650, no. : 1050-1061.

Journal article
Published: 01 September 2018 in Journal of Cleaner Production
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The cities’ area accounts for only 2% of the world's surface area, but the cities’ population accounts for 50% of the total population and produces more than 80% of the total CO2 emissions. So the cities have a key position in solving the global challenge of climate change. In order to estimate the impacts of city size change and industrial structure change on CO2 emissions, based on the background, the data availability of the CO2 emissions per person, the economic scale, the size of land use, the industrial concentration degree and the industrial structure change in 50 cities in different sizes (the population size between 0.5 million and 1 million, 1-2 million, 2-4 million and more than 4 million) from 2005 to 2014, the paper studies the impact of the city size change and the industrial structure change on CO2 emissions. The results show that the increase in the sizes of cities can bring in the rise of CO2 emissions and the impacts on CO2 emissions in different city sizes are significant. Meanwhile, both industrial agglomeration and industrial structure change have a significant role in the CO2 emissions reduction. The paper finds out that (1) the medium-sized cities produce relatively fewer CO2 emissions than the smaller cities and the bigger cities. As smaller cities are not conducive to save land and also can't play the externalities of industry agglomeration, leading to the reduction in energy efficiency. Bigger cities may produce all kinds of city diseases. The medium-sized cities with the population of 1 million and 2 million can have relatively higher energy efficiency and fewer city diseases, which may produce lower CO2 emissions. (2) economic growth can increase CO2 emissions.(3) the industrial structure change has effects on CO2 emissions, and CO2 emissions from the secondary industry are the largest in the three industries. So, the government should reasonably give priority development of medium-sized cities with the population between 1 million and 2 million, and adjust energy consumption structure and the industrial structure to give priority to the tertiary industry to reduce CO2 emissions in China’s cities.

ACS Style

Li Li; Yalin Lei; Sanmang Wu; Chunyan He; Jiabin Chen; Dan Yan. Impacts of city size change and industrial structure change on CO2 emissions in Chinese cities. Journal of Cleaner Production 2018, 195, 831 -838.

AMA Style

Li Li, Yalin Lei, Sanmang Wu, Chunyan He, Jiabin Chen, Dan Yan. Impacts of city size change and industrial structure change on CO2 emissions in Chinese cities. Journal of Cleaner Production. 2018; 195 ():831-838.

Chicago/Turabian Style

Li Li; Yalin Lei; Sanmang Wu; Chunyan He; Jiabin Chen; Dan Yan. 2018. "Impacts of city size change and industrial structure change on CO2 emissions in Chinese cities." Journal of Cleaner Production 195, no. : 831-838.

Journal article
Published: 20 August 2018 in Resources Policy
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Rare earths (RE) are critical minerals that are used for economic development. Because it has become increasingly important and widely used, the resource tax has been implemented to solve the negative externality of RE exploitation in China. The resource tax on RE in China has evolved over time and includes three stages: 1) establishment (1993–2010), 2) quantitative changes (2011–2014); and change to a volume-based system and qualitative changes in the ad valorem system (2015 to the present). A computable general equilibrium (CGE) model was developed, and the results show that resource tax reforms would increase the price of RE and curb their production and demand. However, these theoretical market responses were short-lived in reality. For the resource tax reforms to have long-term effects, we must also consider factors such as illegal exploitation, the development of China's domestic RE downstream industries and the emergence of RE alternative products. Finally, additional policies should be formulated that are coordinated with existing policies regarding the resource tax.

ACS Style

Jianping Ge; Yalin Lei. Resource tax on rare earths in China: Policy evolution and market responses. Resources Policy 2018, 59, 291 -297.

AMA Style

Jianping Ge, Yalin Lei. Resource tax on rare earths in China: Policy evolution and market responses. Resources Policy. 2018; 59 ():291-297.

Chicago/Turabian Style

Jianping Ge; Yalin Lei. 2018. "Resource tax on rare earths in China: Policy evolution and market responses." Resources Policy 59, no. : 291-297.