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LIU, MIAOMIAO (2) answer(s).
 
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1
ID:   109321


Benchmarks of carbon emissions and policy implications for Chin: case of Nanjing / Jun Bi; Zhang, Rongrong; Wang, Haikun; Liu, Miaomiao   Journal Article
Jun Bi Journal Article
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Publication 2011.
Summary/Abstract The development of urbanization is accelerating in China, and there are great pressures and opportunities in cities to reduce carbon emissions. An emissions inventory is a basic requirement for analyzing emissions of greenhouse gases (GHGs), their potential reduction and to realize low-carbon development of cities. This study describes a method to establish a GHGs emissions inventory in Chinese cities for 6 emission sources including industrial energy consumption, transportation, household energy consumption, commercial energy consumption, industrial processes and waste. Nanjing city was selected as a representative case to analyze the characteristics of carbon emissions in Chinese cities. The results show that carbon emissions in Nanjing have increased nearly 50% during the last decade. The three largest GHGs contributors were industrial energy consumption, industrial processes and transportation, which contributed 37-44%, 35-40% and 6-10%, respectively, to the total GHGs emissions. Per GDP carbon emissions decreased by 55% from 2002 to 2009, and the per capita and per GDP carbon emissions were comparable or even lower than the world average levels. These results have important policy implications for Chinese cities to control their carbon emissions.
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2
ID:   133243


Mitigating greenhouse gas emissions from China's cities: case study of Suzhou / Wang, Hongsheng; Wang, Yunxia; Wang, Haikun; Liu, Miaomiao   Journal Article
Wang, Haikun Journal Article
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Publication 2014.
Summary/Abstract Knowledge of the factors driving greenhouse gas (GHG) emissions from cities is crucial to mitigating China's anthropogenic emissions. In this paper, the main drivers increasing GHG emissions from the Chinese city of Suzhou between 2005 and 2010 were identified and quantitatively analyzed using the Kaya identity and the log-mean Divisia index method. We found that economy and population were the major drivers of GHG emissions in Suzhou, having contributed 162.20% and 109.04%, respectively, to the increase in emissions. A decline in carbon intensity, which was caused by the declining energy intensity and an adjustment to the mixture of power and industrial structures, was the major determinant and accounted for a reduction of 171.24% in GHG emissions. Slowing and maintaining healthy growth rates of economy and population could be the primary and most effective means if Suzhou tries to curb the total emissions over the short term. It may be more realistic for Suzhou to control emissions by optimizing the economic structure for low-carbon industrial development because of the city's relative high energy requirements and low potential to mitigate GHGs by adjusting the energy mixture.
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