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The majority of the total greenhouse gas (GHG) emissions in China are energy-related. Thus, full understanding of energy-related GHG emissions is crucial for local governments to establish a baseline for tracking emission trends and developing mitigation strategies. In this paper, we present a survey-based GHG emission accounting method for sectoral energy consumption and apply it in Xiaolan, a typical town of Zhongshan. The method combines scope and sectoral analyses on the basis of local statistical approach, and pays more attention to data collection process. Scenarios of core findings in the study are list as below: (1) The energy-related GHG emissions of Xiaolan in 2010 was 2,072,444 tons of carbon dioxide equivalents (CO 2 e). Of this, 31.83% was Scope 1 emissions (direct emissions) and 68.17% was Scope 2 emissions (indirect emissions); (2) Emissions from “manufacturing”, “residents”, and “power, gas & water production and supply” made up 90.27%, among which, “manufacturing” represents the biggest emitting sector as 69.09%; (3) In 2010, the per capita GHG emissions was lower than that in most of the other Chinese cities, but higher than several Asian cities including Amman and Tokyo. Some strategic approaches to reduce GHG emissions were proposed: (1) save energy and improve energy efficiency; (2) optimize energy structure and develop low-carbon energy; (3) update manufacturing structure; (4) improve GHG emission management for the resident sector. Finally, we identified a number of key research issues to advance the town level GHG emission method for future research needs. This paper provides a useful method to understand and profile GHG emissions for towns. [ABSTRACT FROM AUTHOR]

Alleviating global climate change requires the development and adoption of green innovation. This study compares the impact of cooperative and independent green innovation on carbon reduction based on the panel data covering 252 cities in China from 2003 to 2019. We examine the heterogeneous impacts of cooperative green innovation across units, and explain the transmission mechanism. The two-way fixed effects model and interaction model are adopted. Results show that: (1) Cooperative green innovation can reduce carbon emissions more effectively than independent green innovation. A 1% increase in cooperative green patents (inventions) will reduce carbon emissions by 0.023% (0.037%), while independent green patents or inventions play a weak role. (2) For research and development (R&D) partners, firms' cooperative green innovation has a stronger positive effect on carbon reduction than research organizations. The carbon reduction effect of cooperative green innovation is better for listed firms and universities. (3) Mechanism analysis shows cooperative green innovation can reduce carbon emissions by improving the industrial structure and decreasing energy intensity. These effects are stronger when cities have more talent, funds and higher marketability. (4) We also find that listed firms' cooperative green inventions with a ten-year lag can still reduce carbon emissions effectively. Cooperative green innovation is conducive to carbon reduction among eastern and central cities of China. [Display omitted] • This paper explores the impact of green innovation on carbon reduction from the new perspective of cooperation. • Cooperative green innovation is more effective than independent green innovation in carbon reduction. • Cooperative green innovation of listed firms and universities is more conducive to carbon reduction. • Cooperative green innovation can optimize the industrial structure and decrease energy intensity for better carbon reduction. • Cooperative green innovation with more talent, funds and market has better carbon reduction effect. [ABSTRACT FROM AUTHOR]

The issue of climate change has become an increasing concern for the international community. At the same time, climate change and, particularly, global warming affects the amount of energy required in China and the structure of this demand, thereby influencing the amount of CO 2 (carbon dioxide) emissions produced. To investigate the possible influence of climate change on China's CO 2 emissions, this paper utilizes the degree-day method to calculate the heating degree days (HDD) and cooling degree days (CDD) in 29 provinces in China from 1995 to 2011. A series of appropriate econometric models are subsequently estimated to measure the impact of climate change on CO 2 emissions per capita. To enhance the explanatory power of the estimation results, several indicators, such as income per capita, industry structure, urbanization rate and population density, are incorporated in the estimation equations as control variables. The estimation results indicate that the feedback effect of climate change on China's carbon emissions is statistically significant but not large in magnitude. During the sample period between 1995 and 2011, approximately 1.687% of China's increased total CO 2 emissions could be attributed to climate change. Moreover, the impacts of climate change on different regions of China are notably different. For example, the influence of HDD on CO 2 emissions per capita are most significant in the middle and southern regions, while the impacts of CDD are most significant in the eastern and northern regions. However, there is no obvious evidence that climate change has affected CO 2 emissions in the western region. [ABSTRACT FROM AUTHOR]