2017
DOI: 10.1016/j.jenvman.2017.03.016
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Atmospheric pollution reduction effect and regional predicament: An empirical analysis based on the Chinese provincial NO x emissions

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Cited by 61 publications
(25 citation statements)
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“…Wang (2016) found that economic scale factors could increase NOx emissions, whereas an energy intensity factor inhibited NOx emissions from 2010 to 2015; furthermore, economic structure optimization and energy structure adjustment have the potential to reduce NOx emissions in China in the future. Ding et al (2017) and Diao et al (2016) both showed that economic growth was the dominant driving force, whereas both technological and energy efficiency factors were the main reasons for NOx emission reductions from 2006 to 2013 in China. Lyu et al (2016) identified economic growth as a primary factor influencing the increase in NOx emissions in China from 1997 to 2012.…”
Section: Accepted Manuscriptmentioning
confidence: 99%
“…Wang (2016) found that economic scale factors could increase NOx emissions, whereas an energy intensity factor inhibited NOx emissions from 2010 to 2015; furthermore, economic structure optimization and energy structure adjustment have the potential to reduce NOx emissions in China in the future. Ding et al (2017) and Diao et al (2016) both showed that economic growth was the dominant driving force, whereas both technological and energy efficiency factors were the main reasons for NOx emission reductions from 2006 to 2013 in China. Lyu et al (2016) identified economic growth as a primary factor influencing the increase in NOx emissions in China from 1997 to 2012.…”
Section: Accepted Manuscriptmentioning
confidence: 99%
“…The average annual growth rate in the proportion of nonfossil fuels accounted for primary energy consumption was 4.63%, meanwhile, the average annual rate of decrease in energy intensity during 2003–2007 was 4.47%; according to the trend of historical development, the proportion of nonfossil fuels accounted for primary energy consumption and energy intensity in 2020 and 2030 can be calculated, furthermore, it is also confirmed the energy intensity decline degree in 2020 and 2030 compared to 2005. In this article, three scenarios are set up, Table include all the factors level in different scenarios, which take 2010 as the reference year, 2020 and 2030 as the target year, to predict the carbon emissions of Chinese Production and Supply of Electric and Heat Power Industry under different scenarios .…”
Section: Resultsmentioning
confidence: 99%
“…The average annual growth rate in the proportion of nonfossil fuels accounted for primary energy consumption was 4.63%, meanwhile, the average annual rate of decrease in energy intensity during 2003-2007 was 4.47%; according to the trend of historical development, the proportion of nonfossil fuels accounted for primary energy consumption and energy intensity in 2020 and 2030 can be calculated, furthermore, it is also confirmed the energy intensity decline degree in 2020 and 2030 compared to 2005. In this article, three scenarios are set up, Table 3 include all the factors level in different scenarios, which take 2010 as the reference year, 2020 and 2030 as the target year, to predict the carbon emissions of Chinese Production and Supply of Electric and Heat Power Industry under different scenarios [29]. Benchmark scenario (BAU): sector's added value growth rate was 7% in 2012-2030, 5% in 2030-2050, and 3% after 2050; on the basis of annual variable rate in 2003-2012, the proportion of nonfossil fuels accounted for primary energy consumption will be 7% in 2020 and 11% in2030, if the annual reduced ratio still constant by 4.47%; compared to 2005, the energy intensity will be declined 2.4% in 2020 and 38.2% in 2030.…”
Section: Emission Reduction Potential Analysis Scenario Settingmentioning
confidence: 99%
“…Sichuan, Guangdong, Hunan, and Chongqing each greatly raised the inequality (see Figure 10), so each should benefit from the end-of-pipe treatment plan which, according to Ding et al [82], has a high effect in reducing NO X emission from car exhaust in urban areas. Regarding the reports of local governments for the 12th FYP [83], Sichuan met the national targets to reduce emission and energy intensity with the aim of green development.…”
Section: Yearmentioning
confidence: 99%
“…Inner Mongolia, Xinjiang, Shanxi, and Ningxia all had less negative contributions in all years. All these provinces are located in the western region and so, based on Ding et al [82], are potential hotspots of NO X emission needing special attention by policy makers and central government to control the local pollution. Figure 11 shows the great difference in within-and between-region inequality (T W and T B ).…”
Section: Yearmentioning
confidence: 99%