A comparison of carbon dioxide (CO2) emission trends among provinces in China

Du, Kerui; Xie, Chunping; Ouyang, Xiaoling

doi:10.1016/j.rser.2017.01.102

Cited by 130 publications

(43 citation statements)

References 46 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…When the developed provinces reach the carbon emission peak, the less-developed areas may reach the peak a few years later. For example, Du et al [33] point out that peak carbon emissions have been achieved only in Beijing and Shanghai at present; therefore, distributing peak carbon emission targets equally to each province is not rational. Instead, to achieve peak carbon emission targets based on overall fairness and recognize regional differences, most scholars believe emission targets should be determined on a regional basis, and it is essential to divide China into the Eastern region, Central region, and Western region to study specific problems according to the geographical orientations.…”

Section: Regional Analysis Of Peak Carbon Emissions In Chinamentioning

confidence: 99%

Peak Carbon Emissions in China: Status, Key Factors and Countermeasures—A Literature Review

Dong

Hua

2018

Sustainability

View full text Add to dashboard Cite

China is continually increasing its efforts to reduce carbon emissions due to dual pressure domestically and internationally. Specifically, China has committed to achieving peak carbon emissions no later than 2030. As an international goal, carbon emission peak in China has generated considerable research interest. However, most scholars only focus on a partial aspect of peak carbon emissions. Through a review of literature from numerous sources, this paper provides a more systematic analysis than previously available of how China can reach its peak carbon emissions as early as possible. This study first elaborates the status of peak carbon emissions in China from regional and sectoral perspectives and summarizes the various predictions. Then, five main driving factors of carbon emission peak in China are investigated, i.e., economic development, urbanization, energy-related issues, foreign direct investment and technology, and transportation. Corresponding to these five factors, some specific and practical recommendations are proposed. Furthermore, regional differences and spatial "spillovers" must be taken into account, thereby achieving a "win-win" solution with respect to the integration of emission mitigation and economic development, as well as reaching the desired target of peak carbon emissions.

show abstract

Section: Regional Analysis Of Peak Carbon Emissions In Chinamentioning

confidence: 99%

Peak Carbon Emissions in China: Status, Key Factors and Countermeasures—A Literature Review

Dong

Hua

2018

Sustainability

View full text Add to dashboard Cite

show abstract

“…Despite a large number of studies adopting CIs as the measure of the carbon emission trends, a few issues still remain underexplored. First, most of the previous studies tend to focus on a specific country [6], a small number of countries [4], or multiple regions [5]. Zhu et al's article, examining the CI trend of 89 countries for three decades, is a rare exception.…”

Section: Introductionmentioning

confidence: 99%

Dynamic Trends of Carbon Intensities among 127 Countries

2017

View full text Add to dashboard Cite

Many countries in the world have been experiencing widely varying rates of change in their carbon intensity (CI) of economic output. The dynamic trend of CI in this research is measured by the progress ratio (PR) from an experience curve (EC) involving 127 countries during the period of 1980-2011. The overall average PR of 88.8% estimated for the total group of 127 indicates a decreasing trend of carbon intensity. This means that each doubling of the cumulative CO 2 emission by this group has reduced carbon intensity by 11.2%. While a majority of 83 countries experienced a decreasing trend with an average PR of 73.1%, the remaining 44 countries have experienced an increasing trend with an average PR of 114.5%. When two different types of EC, classical and kinked, were applied, 73 countries displayed a kinked slope with an average PR of 73.4%, and 54 countries displayed a classical slope with an average PR of 104.2%. Examination of the type of trend and slope of EC suggests the chance of a major improvement of the future CI in the following order: (1) the 35 countries with a classical slope and an increasing trend of CIs; (2) the nine countries with a kinked slope and an increasing trend of CIs; (3) the 19 countries with a classical slope and a decreasing trend of CIs; and (4) the 64 countries with a kinked slope and a decreasing trend of CIs. Further implications from these findings are discussed.

show abstract

“…At the same time, China is facing intense international and domestic pressure to reduce the greenhouse gas and other emissions resulting from its primarily coal-based energy system [2][3][4]. Given these twin pressures of increasing energy demand while controlling emissions, the development of China's shale gas industry has emerged as a strategic national priority [5].…”

Section: Introductionmentioning

confidence: 99%

“…Source: Adapted from Zhao et al [6], Sun [7], EIA [8] and Mlada [9]. 1 Excluding Qinghai-Tibet; 2 Western Canada only.…”

Section: Introductionmentioning

confidence: 99%

“…While considering inter-industry 192 differences, we primarily focused on the research findings of energy-related risk index systems and 193 the feasibility of their application in the shale gas industry (see Table 2). Since our focus is on the risks 194 associated with shale gas industry development, we focused first on three representative studies on 195 this topic: Guo et al [47], Yu [48] and Krupnick et al [2]. Second, we considered studies related to 196 coal, the dominant source of conventional fuel energy in China.…”

mentioning

confidence: 99%

See 1 more Smart Citation

Using BP Neural Networks to Prioritize Risk Management Approaches for China’s Unconventional Shale Gas Industry

Dong

Gehman

et al. 2017

Sustainability

View full text Add to dashboard Cite

This article is motivated by a conundrum: How can shale gas development be encouraged and managed without complete knowledge of the associated risks? To answer this question, we used back propagation (BP) neural networks and expert scoring to quantify the relative risks of shale gas development across 12 provinces in China. The results show that the model performs well with high predictive accuracy. Shale gas development risks in the provinces of Sichuan, Chongqing, Shaanxi, Hubei, and Jiangsu are relatively high (0.4~0.6), while risks in the provinces of Xinjiang, Guizhou, Yunnan, Anhui, Hunan, Inner Mongolia, and Shanxi are even higher (0.6~1). We make several recommendations based on our findings. First, the Chinese government should promote shale gas development in Sichuan, Chongqing, Shaanxi, Hubei, and Jiangsu Provinces, while considering environmental, health, and safety risks by using demonstration zones to test new technologies and tailor China's regulatory structures to each province. Second, China's extremely complex geological conditions and resource depths prevent direct application of North American technologies and techniques. We recommend using a risk analysis prioritization method, such as BP neural networks, so that policymakers can quantify the relative risks posed by shale gas development to optimize the allocation of resources, technology and infrastructure development to minimize resource, economic, technical, and environmental risks. Third, other shale gas industry developments emphasize the challenges of including the many parties with different, often conflicting expectations. Government and enterprises must collaboratively collect and share information, develop risk assessments, and consider risk management alternatives to support science-based decision-making with the diverse parties.

show abstract

A comparison of carbon dioxide (CO2) emission trends among provinces in China

Cited by 130 publications

References 46 publications

Peak Carbon Emissions in China: Status, Key Factors and Countermeasures—A Literature Review

Peak Carbon Emissions in China: Status, Key Factors and Countermeasures—A Literature Review

Dynamic Trends of Carbon Intensities among 127 Countries

Using BP Neural Networks to Prioritize Risk Management Approaches for China’s Unconventional Shale Gas Industry

Contact Info

Product

Resources

About