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China has made remarkable achievements in reducing carbon emissions in recent years. However, there is still much reduction room before achieving carbon neutrality. In Beijing, the capital of China, it is a strategic choice to respond to global climate change by promoting green and low-carbon development. This paper calculates the carbon dioxide emissions of key industries in Beijing and analyzes the temporal evolution trend of carbon emissions. Carbon dioxide emissions in Beijing before 2030 are predicted based on the grey prediction GM (1,1) and BP neural network model. The effects of factors of carbon dioxide emissions are discussed using the threshold regression model under different economic conditions. The results show that energy consumption intensity, GDP per capita, and the ownership of civil cars have a positive impact on carbon dioxide emissions, while the number of permanent residents and urban green space areas have a negative impact on carbon dioxide emissions. These findings of carbon emission prediction and influencing factors contribute to carbon reduction path design. Related policy implications on carbon emission reduction are put forward from the aspects of promoting industrial upgrading, accelerating the construction of advanced economic structures, optimizing transportation structures, and strengthening green building development. [ABSTRACT FROM AUTHOR]

In December 2015, China joined 190 plus nations at Paris in committing to the goal of limiting the rise in global average temperature to ‘well below’ 2°C. Carbon budget analysis indicates that goal will require not only that the European Union and US reduce their emissions by greater than 80% by 2050, but that China at least comes close to doing so as well, if any budget is to be left over for the rest of the world (RoW). Given that RoW emissions are, and will come from, low-income and emerging nations, China’s emission reduction potential is of no small consequence. In this paper, we use the Kaya identity to back out changes in the drivers of CO2 emissions, including gross domestic product (GDP), energy intensity (E/GDP) and the carbon content of energy (C/E), the latter two calculated to be consistent with China’s long-term GDP growth rate forecasts and specified 2050 CO2 emission reduction targets. Our results suggest that even achieving China’s highly optimistic renewable energy targets will be very far from sufficient to reduce China’s CO2 emissions from 9.1 Gt it emitted in 2015 to much below 3 Gt by 2050. Even reducing its emissions to 5 Gt will be challenging, yet this falls far short of what is needed if the world is to meet its ‘well below’ 2°C commitment. Key policy insights Under the Paris Agreement there is great pressure on China to very substantially reduce its emissions by 2050. While China has attached great importance to renewables and nuclear energy development, even achieving the most optimistic targets would not be sufficient to reduce China’s emissions from 9.1 Gt in 2015 to much below 3 Gt by 2050. China’s emission reduction potential falls far short of what is needed if the world is to meet its Paris ‘well below’ 2°C commitment, even if the EU and US reduce their emissions to zero by 2050. Emission cuts consistent with the Paris Agreement will require that China and the world give much greater weight to advancing research and development of scalable low-, zero- and negative-carbon sources and technologies. [ABSTRACT FROM AUTHOR]

In an effort to address climate change, in 2013 China launched the world’s largest government-driven carbon emission reduction programme, the National Low Carbon Industrial Parks Pilot Programme (LCIPPP). This paper analyses this newly developed pilot program. To deepen our understanding of the causes and the impact of industrial park CO 2 emissions, we use the STIRPAT (Stochastic Impacts by Regression on Population, Affluence and Technology) model and data from 20 pilot industrial parks involved in the LCIPPP for the period 2012–2016. This study quantitatively evaluates the effect of CO 2 emissions on output, energy structure, energy intensity, industrial structure, R&D intensity, and population change in different regions and nationally through an elasticity coefficient method. The results confirm that an increase in output and energy intensity is a dominant contributor to the growth of CO 2 emissions whereas an increase of the share of tertiary industry and R&D intensity has significant effects on reducing CO 2 emissions. The elasticity of energy intensity and renewable energy consumption on CO 2 emissions in the eastern region of China is the highest, indicating that using renewable energy to reduce CO 2 emissions for the industrial parks is more effective in the eastern region as compared to the central and western regions of the country. The elasticity of population is significantly negative in both the central and western areas while it is positive in eastern part of China, thereby illustrating that promoting labour intensive industries will be an effective way to reduce CO 2 emissions for the industrial parks in China’s central and western regions. Our study reveals that differentiated low carbon development pathways should be adopted. Concrete policy implications for reducing CO 2 emissions are also provided. [ABSTRACT FROM AUTHOR]

Cities consume large amounts of fossil fuels and this results in significant increase of global anthropogenic greenhouse gases. Using city-level carbon dioxide emission data from Shijiazhuang, a traditional heavy manufacturing city and one of the key cities in Jing-Jin-Ji urban agglomeration in Northern China, this paper employs logarithmic mean Divisia index decomposition method (LMDI) to explore the influence of energy intensity, consumption structure, industry structure, per capita Gross Domestic Product (GDP), and population on Shijiazhuang's total carbon dioxide emissions from 2005 to 2016. The LMDI method is further extended to analyze the impacts of above factors at the industry-segment level. This paper finds that the reduction of energy intensity is the major contributor of decreasing carbon dioxide emissions in Shijiazhuang, whereas the growth of per capita GDP is the main driving force for emission accretion. The dominant industrial segments contributing to increasing emissions in Shijiazhuang City from 2005 to 2016, have changed from CMD (coal mining and dressing), EPSH (electric power, steam and hot water production and supply) to SPFM (smelting and pressing of ferrous metals) and PPC (petroleum processing and coking). The CMD industrial segment shows a significant carbon reducing effort and indicates a strong decoupling status. However, the SPFM and PPC respectively show expansive negative decoupling and weak decoupling status, enlightening a change in the policy focus when Shijiazhuang formulates its emission-reduction plans in the future. This study provides important policy insights for the heavy manufacturing cities in other countries with similar industrial structure, as the industry-based carbon mitigation policies should always be adjusted in different stages of the cities' development according to the change of carbon emission driving industries. [ABSTRACT FROM AUTHOR]