Peak cement-related CO2 emissions and the changes in drivers in China

In order to fight against the climate change, China has set a series of emission reduction policies for super‐emitting sectors. The cement industry is the major source of process‐related emissions, and more attention should be paid to this industry. This study calculates the process‐related, direct fossil fuel–related, and indirect electricity‐related emissions from China's cement industry. The study finds that China's cement‐related emissions peaked in 2014. The emissions are, for the first time, divided into seven parts based on the cement used in different new building types. The provincial emission analysis finds that developed provinces outsourced their cement capacities to less developed regions. This study then employs index decomposition analysis to explore the drivers of changes in China's cement‐related emissions. The results show that economic growth was the primary driver of emission growth, while emission intensity and efficiency were two offsetting factors. The changes in the construction industry's structure and improvement in efficiency were the two major drivers that contributed to the decreased emissions since 2014

The consumption-based black carbon emissions of China's megacities

A growing body of literature discusses the CO2 emissions of cities. Still, little is known about black carbon (BC), a short-lived warming agent. Identifying the drivers of urban BC emissions is crucial for targeting cleanup efforts. A consumption-based approach enables all emissions to be allocated along the production chain to the product and place of final consumption, whereas a production approach attributes emissions to the place where goods and services are produced. In this study, we calculate the production-based and consumption-based emissions in 2012 in four Chinese megacities: Beijing, Shanghai, Tianjin and Chongqing. The results show that capital formation is the largest contributor, accounting for 37%–69% of consumption-based emissions. Approximately 44% of BC emissions related to goods consumed in Chongqing and more than 60% for Beijing, Shanghai and Tianjin occur outside of the city boundary. The large gap between consumption and production-based emissions can be attributed to the great difference in embodied emission intensities. Therefore, collaborative efforts to reduce emission intensity can be effective in mitigating climate change for megacities as either producers or consumers

The Slowdown in China's Carbon Emissions Growth in the New Phase of Economic Development

China's CO2 emissions have plateaued under its commitment to reaching peak carbon emissions before 2030 in order to mitigate global climate change. This commitment is aligned with China's turn toward more sustainable development, named “the new normal” phase. This study aims to explore the role of possible socioeconomic drivers of China's CO2 emission changes by using structural decomposition analysis (SDA) for 2002–2017. The results show deceleration of China's annual emissions growth from 10% (2002–2012) to 0.3% (2012–2017), which is mainly caused by gains in energy efficiency, deceleration of economic growth, and changes in consumption patterns. Gains in energy efficiency are the most important determinants, offsetting the increase by 49% during 2012–2017. The recent moderation of emission growth is also attributed to China's decelerating annual growth rate of gross domestic product (GDP) per capita from 12% (2002–2012) to 6% (2012–2017) and to the economic transformation to consumption-led patterns in the new normal phase

Regional development and carbon emissions in China

China announced at the Paris Climate Change Conference in 2015 that the country would reach peak carbon emissions around 2030. Since then, widespread attention has been devoted to determining when and how this goal will be achieved. This study aims to explore the role of China’s changing regional development patterns in the achievement of this goal. This study uses the logarithmic mean Divisia index (LMDI) to estimate seven socioeconomic drivers of the changes in CO2 emissions in China since 2000. The results show that China’s carbon emissions have plateaued since 2012 mainly because of energy efficiency gains and structural upgrading (i.e., industrial structure, energy mix and regional structure). Regional structure, measured by provincial economic growth shares, has drastically reduced CO2 emissions since 2012. The effects of these drivers on emissions changes varied across regions due to their different regional development patterns. Industrial structure and energy mix resulted in emissions growth in some regions, but these two drivers led to emissions reduction at the national level. For example, industrial structure reduced China’s CO2 emissions by 1.0% from 2013-2016; however, it increased CO2 emissions in the Northeast and Northwest regions by 1.7% and 0.9%, respectively. By studying China’s plateauing CO2 emissions in the new normal stage at the regional level, it is recommended that regions cooperate to improve development patterns

Socioeconomic impact assessment of China's CO2 emissions peak prior to 2030

China is the largest emitter of carbon emissions in the world. In this paper, we present an Integrated Model of Economy and Climate (IMEC), an optimization model based on the input-output model. The model is designed to assess the tradeoff between emission deceleration and economic growth. Given that China's projected average growth rate will exceed 5% over the next two decades, we find that China may reach its peak CO2 emissions levels by 2026. According to this scenario, China's carbon emissions will peak at 11.20 Gt in 2026 and will then decline to 10.84 Gt in 2030. Accordingly, approximately 22 Gt of CO2 will be removed from 2015 to 2035 relative to the scenario wherein China's CO2 emissions peak in 2030. While this earlier peaking of carbon emissions will result in a decline in China's GDP, several sectors, such as Machinery and Education, will benefit. In order to reach peak CO2 emissions by 2026, China needs to reduce its annual GDP growth rate to less than 4.5% by 2030 and decrease energy and carbon intensity levels by 43% and 45%, respectively, from 2015 to 2030

Energy consumption and CO2 emissions in Tibet and its cities in 2014

Because of its low level of energy consumption and the small scale of its industrial development, the Tibet Autonomous Region has historically been excluded from China's reported energy statistics, including those regarding CO2 emissions. In this paper, we estimate Tibet's energy consumption using limited online documents, and we calculate the 2014 energy-related and process-related CO2 emissions of Tibet and its seven prefecture-level administrative divisions for the first time. Our results show that 5.52 million tons of CO2 were emitted in Tibet in 2014; 33% of these emissions are associated with cement production. Tibet's emissions per capita amounted to 1.74 tons in 2014, which is substantially lower than the national average, although Tibet's emission intensity is relatively high at 0.60 tons per thousand yuan in 2014. Among Tibet's seven prefecture-level administrative divisions, Lhasa City and Shannan Region are the two largest CO2 contributors and have the highest per capita emissions and emission intensities. The Nagqu and Nyingchi regions emit little CO2 due to their farming/pasturing-dominated economies. This quantitative measure of Tibet's regional CO2 emissions provides solid data support for Tibet's actions on climate change and emission reductions

A multi-regional input-output table mapping China's economic outputs and interdependencies in 2012.

Multi-regional input-output (MRIO) models are one of the most widely used approaches to analyse the economic interdependence between different regions. We utilised the latest socioeconomic datasets to compile a Chinese MRIO table for 2012 based on the modified gravity model. The MRIO table provides inter-regional and inter-sectoral economic flows among 30 economic sectors in China's 30 regions for 2012. This is the first MRIO table to reflect China's economic development pattern after the 2008 global financial crisis. The Chinese MRIO table can be used to analyse the production and consumption structure of provincial economies and the inter-regional trade pattern within China, as well as function as a tool for both national and regional economic planning. The Chinese MRIO table also provides a foundation for extensive research on environmental impacts by linking industrial and regional output to energy use, carbon emissions, environmental pollutants, and satellite accounts

Linking city-level input-output table to urban energy footprint: Construction framework and application

Multiregion input–output (MRIO) models have become increasingly important in economic and environmental analysis. However, the current resolution of most MRIO models fails to capture the heterogeneity between subregions, especially in cities. The lack of city‐level MRIO tables has impeded the accomplishment of city‐level studies and hampered the understanding of the relationship between urban growth and consumption, and teleconnections to other regions. In this paper, we propose a partial survey‐based multiple‐layer framework for MRIO table compilation of a Chinese province that distinguishes city‐based regions. This framework can effectively address a large number of data processes and retain consistency between layers. Using the framework, we first compile a nested Hebei‐China city‐level MRIO table and then apply city‐level energy footprint accounting of the North China urban agglomeration. Our results present the critical role of Hebei cities in energy supply in 2012 and quantify energy use embodied in goods for the domestic trade. Tangshan, Shijiazhuang, and Handan are distinctive cities in the energy supply chain of other regions, for both less developed and developed regions. This multiple‐layer framework represents a feasible approach for developing subregional‐level MRIO models and offers the possibility to analyze global trade at the subregional level with limited data. The data and results from the analysis in this article are available for download from China Emission Accounts and Datasets