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Li Ma
College of Resources and Environment, University of Chinese Academy of Sciences, Beijing 100049, China

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Journal article
Published: 14 August 2021 in Sustainability
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As the biggest renewable energy installation and generation country globally, it is important to deeply understand China’s wind power production determinants and draw implications for energy policy. This paper analyzes local electricity deployment, electricity consumption, investment in wind power, and price of wind power electricity on-grid apart from traditional GDP and CO2 factors in the panel data regression model, and some interesting results are found. The investment of installation and the price of wind power electricity on-grid have negative impacts on wind power generation, while local electricity consumption and inter-provincial power transmission capacity significantly impact wind power generation positively. GDP and CO2 emission per capita have negative and positive impacts on wind power production, respectively. As for different wind power zones, the most influencing factors are local electricity consumption. Hence, this paper concludes that local absorbing capacity is still an important limiting factor to Chinese renewable energy development. At last, some policies are suggested to enhance the local absorbing capacity of renewable energy.

ACS Style

Li Ma; Die Xu. Toward Renewable Energy in China: Revisiting Driving Factors of Chinese Wind Power Generation Development and Spatial Distribution. Sustainability 2021, 13, 9117 .

AMA Style

Li Ma, Die Xu. Toward Renewable Energy in China: Revisiting Driving Factors of Chinese Wind Power Generation Development and Spatial Distribution. Sustainability. 2021; 13 (16):9117.

Chicago/Turabian Style

Li Ma; Die Xu. 2021. "Toward Renewable Energy in China: Revisiting Driving Factors of Chinese Wind Power Generation Development and Spatial Distribution." Sustainability 13, no. 16: 9117.

Journal article
Published: 28 October 2020 in Cities
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Understanding the processes and mechanisms of the spatial spread of epidemics is essential for making reasonable judgments on the development trends of epidemics and for adopting effective containment measures. Using multi-agent network technology and big data on population migration, this paper constructed a city-based epidemic and mobility model (CEMM) to stimulate the spatiotemporal of COVID-19. Compared with traditional models, this model is characterized by an urban network perspective and emphasizes the important role of intercity population mobility and high-speed transportation networks. The results show that the model could simulate the inter-city spread of COVID-19 at the early stage in China with high precision. Through scenario simulation, the paper quantitatively evaluated the effect of control measures “city lockdown” and “decreasing population mobility” on containing the spatial spread of the COVID-19 epidemic. According to the simulation, the total number of infectious cases in China would have climbed to 138,824 on February 2020, or 4.46 times the real number, if neither of the measures had been implemented. Overall, the containment effect of the lockdown of cities in Hubei was greater than that of decreasing intercity population mobility, and the effect of city lockdowns was more sensitive to timing relative to decreasing population mobility.

ACS Style

Ye Wei; Jiaoe Wang; Wei Song; Chunliang Xiu; Li Ma; Tao Pei. Spread of COVID-19 in China: analysis from a city-based epidemic and mobility model. Cities 2020, 110, 103010 -103010.

AMA Style

Ye Wei, Jiaoe Wang, Wei Song, Chunliang Xiu, Li Ma, Tao Pei. Spread of COVID-19 in China: analysis from a city-based epidemic and mobility model. Cities. 2020; 110 ():103010-103010.

Chicago/Turabian Style

Ye Wei; Jiaoe Wang; Wei Song; Chunliang Xiu; Li Ma; Tao Pei. 2020. "Spread of COVID-19 in China: analysis from a city-based epidemic and mobility model." Cities 110, no. : 103010-103010.

Research article
Published: 12 June 2020 in Environmental Science and Pollution Research
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Achieving the win-win goal of economic development and carbon intensity reduction, especially through industrial restructuring, is a challenge involving uncertainty and complexity. Determining which industry is green and whether it should be encouraged or limited at different stages of economic development are key issues. The relationship between industrial structure and carbon intensity was systematically analyzed in 21 industrial sectors from 1971 to 2014 in eight developed countries, with different levels of economic development, using an extended dynamic threshold model. The results indicated that there is a relationship between industrial composition and carbon intensity, and the impact trajectory of industrial structure on carbon intensity can be classified into four categories: contaminated, pollution-clean, cleaning hysteresis, and enhanced cleaning. Each type of sectoral relationship between GDP and carbon intensity would change at certain economic levels. The change points for most sectors were US$ 525 and US$ 3904 GDP per capita, which represent the points at which a country enters the mid-industrialization and high-tech industrialization stages, respectively. Therefore, the government and enterprises must upgrade their industrial structure as the national GDP increases, adjust the proportion of sectors operating according to the industrial characteristics, and improve production technology through environmental regulation.

ACS Style

Lin Zhang; Li Ma. The relationship between industrial structure and carbon intensity at different stages of economic development: an analysis based on a dynamic threshold panel model. Environmental Science and Pollution Research 2020, 27, 33321 -33338.

AMA Style

Lin Zhang, Li Ma. The relationship between industrial structure and carbon intensity at different stages of economic development: an analysis based on a dynamic threshold panel model. Environmental Science and Pollution Research. 2020; 27 (26):33321-33338.

Chicago/Turabian Style

Lin Zhang; Li Ma. 2020. "The relationship between industrial structure and carbon intensity at different stages of economic development: an analysis based on a dynamic threshold panel model." Environmental Science and Pollution Research 27, no. 26: 33321-33338.

Journal article
Published: 01 January 2020 in 资源科学
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ACS Style

Fengjun Jin; Li Ma; Die Xu. Environmental stress and optimized path of industrial development in the Yellow River Basin. 资源科学 2020, 42, 127 -136.

AMA Style

Fengjun Jin, Li Ma, Die Xu. Environmental stress and optimized path of industrial development in the Yellow River Basin. 资源科学. 2020; 42 (1):127-136.

Chicago/Turabian Style

Fengjun Jin; Li Ma; Die Xu. 2020. "Environmental stress and optimized path of industrial development in the Yellow River Basin." 资源科学 42, no. 1: 127-136.

Journal article
Published: 01 January 2020 in 资源科学
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ACS Style

Li Ma; Huazheng Tian; Lei Kang. Eco-environmental impact and spatial control of mineral resources exploitation in the Yellow River Basin. 资源科学 2020, 42, 137 -149.

AMA Style

Li Ma, Huazheng Tian, Lei Kang. Eco-environmental impact and spatial control of mineral resources exploitation in the Yellow River Basin. 资源科学. 2020; 42 (1):137-149.

Chicago/Turabian Style

Li Ma; Huazheng Tian; Lei Kang. 2020. "Eco-environmental impact and spatial control of mineral resources exploitation in the Yellow River Basin." 资源科学 42, no. 1: 137-149.

Journal article
Published: 01 January 2019 in JOURNAL OF NATURAL RESOURCES
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ACS Style

Li Ma; Bo Zhang. The spatial distribution and evolution of interprovincial electricity flow in China. JOURNAL OF NATURAL RESOURCES 2019, 34, 348 -354.

AMA Style

Li Ma, Bo Zhang. The spatial distribution and evolution of interprovincial electricity flow in China. JOURNAL OF NATURAL RESOURCES. 2019; 34 (2):348-354.

Chicago/Turabian Style

Li Ma; Bo Zhang. 2019. "The spatial distribution and evolution of interprovincial electricity flow in China." JOURNAL OF NATURAL RESOURCES 34, no. 2: 348-354.

Journal article
Published: 28 February 2018 in Progress in Geography
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ACS Style

毅 刘; Wang Yun; Ma Li; Liu Yi; 云 王; 丽 马. 城镇化研究进展与趋势——基于CiteSpace和HistCite的图谱量化分析. Progress in Geography 2018, 37, 239 -254.

AMA Style

毅 刘, Wang Yun, Ma Li, Liu Yi, 云 王, 丽 马. 城镇化研究进展与趋势——基于CiteSpace和HistCite的图谱量化分析. Progress in Geography. 2018; 37 (2):239-254.

Chicago/Turabian Style

毅 刘; Wang Yun; Ma Li; Liu Yi; 云 王; 丽 马. 2018. "城镇化研究进展与趋势——基于CiteSpace和HistCite的图谱量化分析." Progress in Geography 37, no. 2: 239-254.

Journal article
Published: 20 December 2017 in 资源科学
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ACS Style

丽 马; Ma Li; Zhang Lin; 琳 张. 国际制造业转移与碳转移的时空耦合效应. 资源科学 2017, 39, 2408 -2419.

AMA Style

丽 马, Ma Li, Zhang Lin, 琳 张. 国际制造业转移与碳转移的时空耦合效应. 资源科学. 2017; 39 (12):2408-2419.

Chicago/Turabian Style

丽 马; Ma Li; Zhang Lin; 琳 张. 2017. "国际制造业转移与碳转移的时空耦合效应." 资源科学 39, no. 12: 2408-2419.

Journal article
Published: 08 December 2017 in Progress in Geography
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ACS Style

姣娥 王; Wang Jiaoe; 敬娟 焦; 悦 景; 丽 马; Jiao Jingjuan; Jing Yue; Ma Li. “ 中欧班列”陆路运输腹地范围测算与枢纽识别. Progress in Geography 2017, 36, 1332 -1339.

AMA Style

姣娥 王, Wang Jiaoe, 敬娟 焦, 悦 景, 丽 马, Jiao Jingjuan, Jing Yue, Ma Li. “ 中欧班列”陆路运输腹地范围测算与枢纽识别. Progress in Geography. 2017; 36 (11):1332-1339.

Chicago/Turabian Style

姣娥 王; Wang Jiaoe; 敬娟 焦; 悦 景; 丽 马; Jiao Jingjuan; Jing Yue; Ma Li. 2017. "“ 中欧班列”陆路运输腹地范围测算与枢纽识别." Progress in Geography 36, no. 11: 1332-1339.

Journal article
Published: 04 February 2016 in Journal of Geographical Sciences
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The Pearl River Delta on China’s coast is a region that is seriously threatened by sea level rise and storm surges induced by global climate change, which causes flooding of large areas of farmland and huge agricultural losses. Based on relevant research and experience, a loss evaluation model of farmland yield caused by sea level rise and storm surges was established. In this model, the area of submerged farmland, area of crops, and per unit yield of every type of crop were considered, but the impact of wind, flooding time, changes in land use and plant structure were not considered for long-term prediction. Taking the Pearl River Delta region in Guangdong as the study area, we estimated and analyzed the spatial distribution and loss of farmlands for different scenarios in the years 2030, 2050, and 2100, using a digital elevation model, land-use data, local crop structure, rotation patterns, and yield loss ratios for different submerged heights obtained from field survey and questionnaires. The results show that the proportion of submerged farmlands and losses of agricultural production in the Pearl River Delta region will increase gradually from 2030 to 2100. Yangjiang, Foshan, and Dongguan show obvious increases in submerged farmlands, while Guangzhou and Zhuhai show slow increases. In agricultural losses, vegetables would sustain the largest loss of production, followed by rice and peanuts. The greatest loss of rice crops would occur in Jiangmen, and the loss of vegetable crops would be high in Shanwei and Jiangmen. Although losses of peanut crops are generally lower, Jiangmen, Guangzhou, and Shanwei would experience relatively high losses. Finally, some measures to defend against storm surges are suggested, such as building sea walls and gates in Jiangmen, Huizhou, and Shanwei, enforcing ecological protection to reduce destruction from storm surges, and strengthening disaster warning systems.

ACS Style

Lei Kang; Li Ma; Yi Liu. Evaluation of farmland losses from sea level rise and storm surges in the Pearl River Delta region under global climate change. Journal of Geographical Sciences 2016, 26, 439 -456.

AMA Style

Lei Kang, Li Ma, Yi Liu. Evaluation of farmland losses from sea level rise and storm surges in the Pearl River Delta region under global climate change. Journal of Geographical Sciences. 2016; 26 (4):439-456.

Chicago/Turabian Style

Lei Kang; Li Ma; Yi Liu. 2016. "Evaluation of farmland losses from sea level rise and storm surges in the Pearl River Delta region under global climate change." Journal of Geographical Sciences 26, no. 4: 439-456.

Journal article
Published: 17 December 2013 in Journal of Geographical Sciences
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Understanding the relationship between China’s urbanization and economic development on a provincial scale is of profound theoretical and practical significance. Based on data from 124 countries or regions throughout the world and 31 provinces or autonomous regions in China, applying improved methods using the quadrant map approach, this paper analyzed the spatial pattern of the relationship between China’s urbanization and economic development level. The study identified the following results. (1) The 31 province-level regions fall into six categories: only one region is in the category of sharp over-urbanization, 3 regions are in medium over-urbanization, 11 slight over-urbanization, 8 basic coordination, one medium under-urbanization, and seven slight under-urbanization. (2) There are significant regional differences on a provincial scale in the relationships between urbanization and the level of economic development. (3) The provincial pattern of urbanization and economic development is significantly different between east and west. The eastern coastal areas are mainly over-urbanized, while the central and western regions are mainly under-urbanized. (4) The relationship between urbanization and the level of economic development is similar to the Matthew effect. Hence, two important insights are proposed. First, the phenomenon of over-urbanization in some developed regions should be viewed with some concern and vigilance. Second, urbanization needs to be speeded up moderately in the central and western regions.

ACS Style

Mingxing Chen; Yongbin Huang; Zhipeng Tang; Dadao Lu; Hui Liu; Li Ma. The provincial pattern of the relationship between urbanization and economic development in China. Journal of Geographical Sciences 2013, 24, 33 -45.

AMA Style

Mingxing Chen, Yongbin Huang, Zhipeng Tang, Dadao Lu, Hui Liu, Li Ma. The provincial pattern of the relationship between urbanization and economic development in China. Journal of Geographical Sciences. 2013; 24 (1):33-45.

Chicago/Turabian Style

Mingxing Chen; Yongbin Huang; Zhipeng Tang; Dadao Lu; Hui Liu; Li Ma. 2013. "The provincial pattern of the relationship between urbanization and economic development in China." Journal of Geographical Sciences 24, no. 1: 33-45.

Journal article
Published: 19 April 2013 in Journal of Geographical Sciences
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Given the great number of studies focusing on the temporal interaction between economic and environmental subsystems, it is useful to perform a quantitative spatial assessment of these subsystems. In this paper, comprehensive assessment indicators for regional economic development and environmental pollution subsystems are constructed. Then, the degree of coupling and coordination of the regional economy-environment system is calculated for 350 prefectural units in China. It is found that the economic development and environmental pollution in most prefectural units is still at a low level of coupling and coordination. According to the coupling and coordination values, the Chinese territory can be divided into four types of area: economy-environment harmonious area, economy-environment gearing area, economy-environment rivaling area and low coupling degree of economy-environment area. Based on a structural analysis of the industrial sector in the four types of areas, there is a spatial relationship between the regional industrial sector structure and the coupling-coordination level. In the economy-environment harmonious area, the sectors of manufacturing of high-technology and high value-added products, such as communications, computer and electronic equipment, transport equipment and electrical machinery, account for a large proportion of the value of local industrial output. The industrial value of the economy-environment gearing area is concentrated on the manufacturing of machinery and equipment, and contains a few polluting sectors such as ferrous and non-ferrous metallurgy, chemical manufacturing and electricity generation. The economy-environment rivaling area is the type of area where polluting sectors concentrate, such as iron and steel, petrifaction, coal mining, building materials and electricity generation. In the low coupling degree of economy-environment area, its industry is concentrated on the production and processing of primary products.

ACS Style

Li Ma; Fengjun Jin; Zhouying Song; Yi Liu. Spatial coupling analysis of regional economic development and environmental pollution in China. Journal of Geographical Sciences 2013, 23, 525 -537.

AMA Style

Li Ma, Fengjun Jin, Zhouying Song, Yi Liu. Spatial coupling analysis of regional economic development and environmental pollution in China. Journal of Geographical Sciences. 2013; 23 (3):525-537.

Chicago/Turabian Style

Li Ma; Fengjun Jin; Zhouying Song; Yi Liu. 2013. "Spatial coupling analysis of regional economic development and environmental pollution in China." Journal of Geographical Sciences 23, no. 3: 525-537.

Journal article
Published: 23 August 2012 in Natural Hazards
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This paper presents a new method for quantifying vulnerability to natural hazards in China. As an important area of vulnerability research, quantitative assessment of vulnerability has raised much focus in academia. Presently, scholars have proposed a variety of methods for quantitative assessment, which usually create an index of overall vulnerability from a suite of indicators, based on the understanding of the cause or mechanism of vulnerability. However, due to the complex nature of vulnerability, this approach caused some arguments on the indicator selection and the weight set for subindices. A data envelopment analysis–based model for the assessment of the regional vulnerability to natural disasters is presented here to improve upon the traditional methods, and a new approach for the classification of vulnerability is proposed. The vulnerability to natural hazards in China’s mainland is illustrated as a case study. The result shows that the overall level of vulnerability to natural hazards in mainland China is high. The geographic pattern shows that vulnerability is highest in western China, followed by diminishing vulnerability in central China, and lowest vulnerability levels in eastern China. There is a negative correlation between the level of vulnerability and the level of regional economic development.

ACS Style

Jianyi Huang; Yi Liu; Li Ma; Fei Su. Methodology for the assessment and classification of regional vulnerability to natural hazards in China: the application of a DEA model. Natural Hazards 2012, 65, 115 -134.

AMA Style

Jianyi Huang, Yi Liu, Li Ma, Fei Su. Methodology for the assessment and classification of regional vulnerability to natural hazards in China: the application of a DEA model. Natural Hazards. 2012; 65 (1):115-134.

Chicago/Turabian Style

Jianyi Huang; Yi Liu; Li Ma; Fei Su. 2012. "Methodology for the assessment and classification of regional vulnerability to natural hazards in China: the application of a DEA model." Natural Hazards 65, no. 1: 115-134.