Evaluating the relationships among economic growth, energy consumption, air emissions and air environmental protection investment in China

Zhang, Xiaohong; Wu, Liqian; Zhang, Rong; Deng, Shihuai; Zhang, Yanzong; Wu, Jun; Li, Yuanwei; Lin, Lili; Li, Li; Wang, Yinjun; Wang, Lilin

doi:10.1016/j.rser.2012.10.029

Cited by 149 publications

(63 citation statements)

References 94 publications

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“…However, even if this may lead to a decrease of environmental impacts in more educated countries (e.g., industrialized civilizations), mostly a shifting of burdens occur towards less educated countries, as production processes likely to be outsourced. Consequently, education at the end of the global supply chains is needed, as environmental protection is dependent on a certain knowledge [47][48][49]. In connection with the defined AoPs environmental stability is highly relevant, as at least social well-being is strongly influenced by this endpoint [50].…”

Section: Environmental Stabilitymentioning

confidence: 99%

Impact Pathways to Address Social Well-Being and Social Justice in SLCA—Fair Wage and Level of Education

Neugebauer

Traverso²,

Scheumann

et al. 2014

Sustainability

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Section: Environmental Stabilitymentioning

confidence: 99%

Impact Pathways to Address Social Well-Being and Social Justice in SLCA—Fair Wage and Level of Education

Neugebauer

Traverso²,

Scheumann

et al. 2014

Sustainability

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“…In low atmospheric dispersion conditions (i.e., low wind speed), PM 2.5 concentration is more likely positively correlates with centralization of landscape (i.e., the Jing-Jin-Ji region and Chengdu-Chongqing urban agglomeration). That means the aggregated landscape enhances the centralized emission of PM 2.5 , which tends to worsen the air pollution because of the low atmosphere self-purification capacity [76,77]. By contrast, the climate conditions are characterized by high dispersion (i.e., the high wind speed) in the Yangtze River Delta, the Pearl River Delta, the Chang-Zhu-Tan and Guanzhong urban agglomerations.…”

Section: Discussionmentioning

confidence: 99%

Scale- and Region-Dependence in Landscape-PM2.5 Correlation: Implications for Urban Planning

2017

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Under rapid urbanization, many cities in China suffer from serious fine particulate matter (PM 2.5 ) pollution. As the emission sources or adsorption sinks, land use and the corresponding landscape pattern unavoidably affect the concentration. However, the correlation varies with different regions and scales, leaving a significant gap for urban planning. This study clarifies the correlation with the aid of in situ and satellite-based spatial datasets over six urban agglomerations in China. Two coverage and four landscape indices are adopted to represent land use and landscape pattern. Specifically, the coverage indices include the area ratios of forest (F_PLAND) and built-up areas (C_PLAND). The landscape indices refer to the perimeter-area fractal dimension index (PAFRAC), interspersion and juxtaposition index (IJI), aggregation index (AI), Shannon's diversity index (SHDI). Then, the correlation between PM 2.5 concentration with the selected indices are evaluated from supporting the potential urban planning. Results show that the correlations are weak with the in situ PM 2.5 concentration, which are significant with the regional value. It means that land use coverage and landscape pattern affect PM 2.5 at a relatively large scale. Furthermore, regional PM 2.5 concentration negatively correlate to F_PLAND and positively to C_PLAND (significance at p < 0.05), indicating that forest helps to improve air quality, while built-up areas worsen the pollution. Finally, the heterogeneous landscape presents positive correlation to the regional PM 2.5 concentration in most regions, except for the urban agglomeration with highly-developed urban (i.e., the Jing-Jin-Ji and Chengdu-Chongqing urban agglomerations). It suggests that centralized urbanization would be helpful for PM 2.5 pollution controlling by reducing the emission sources in most regions. Based on the results, the potential urban planning is proposed for controlling PM 2.5 pollution for each urban agglomeration.

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“…Both Borrego et al [27] and Martinez [28] have found that advanced technology and plans, in terms of monitoring and assessment, help improve air quality. In addition, some scholars have proposed that air quality could be improved effectively through a series of measures, such as industrial structure optimization, energy structure improvement, technological progress, environmental protection investment increase and energy-saving [29][30][31][32][33][34].…”

Section: Introductionmentioning

confidence: 99%

Impact of Energy Consumption on Air Quality in Jiangsu Province of China

Zhong

Yin

et al. 2018

Sustainability

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Air quality has become an important sustainability concern for China's highly developed economic regions. Taking Jiangsu Province as a case, this study investigates the effect of energy consumption on air quality when both considering and not considering control variables, such as industrial structure, energy consumption structure and energy efficiency from 2006 to 2015 and further explores the influence of the related policies on air quality and the relationship between energy consumption and air quality. One important finding is that the relationship between energy consumption and the air quality index of Jiangsu Province shows a U-shaped curve and it is now in the increasing part of the curve, which reveals the effectiveness of controlling energy consumption in improving air quality. Another important finding is that, when considering the effect of related polices, there is still a U-shaped curve relationship between energy consumption and air quality index, with the opening of curve becoming bigger and the influence of energy consumption on air quality becoming more obvious. Moreover, although air quality is improved whether considering policies separately or together, the effect of combined policies is better than is the effect of a separate policy. This not only reflects the effectiveness of related polices but also shows the importance of policy coordination. Furthermore, a 1% optimization of industrial structure inhibits air quality index by 0.0054%, while the relationship of energy efficiency and energy consumption structure with air quality is inconsistent with theoretical analysis. This implies that, in practice, there is still room for improvement in both energy saving and emission reduction and even in air quality improvement. This study may help the stakeholders, whether from Jiangsu Province, other provinces in China or other countries at the global level, identify the impacts of energy consumption on air quality and formulate effective energy saving and air quality improvement policies in conjunction with their economic characteristics.

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Evaluating the relationships among economic growth, energy consumption, air emissions and air environmental protection investment in China

Cited by 149 publications

References 94 publications

Impact Pathways to Address Social Well-Being and Social Justice in SLCA—Fair Wage and Level of Education

Impact Pathways to Address Social Well-Being and Social Justice in SLCA—Fair Wage and Level of Education

Scale- and Region-Dependence in Landscape-PM2.5 Correlation: Implications for Urban Planning

Impact of Energy Consumption on Air Quality in Jiangsu Province of China

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