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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 CO 2 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 CO 2 will be removed from 2015 to 2035 relative to the scenario wherein China's CO 2 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 CO 2 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. [ABSTRACT FROM AUTHOR]

The total factor carbon emission performance has been largely used to investigate the effectiveness of climate policies and to support the design of carbon reduction strategies. Despite the important information that this indicator is providing in relation to historical and cross-country trends, no previous studies have been specifically devoted to analyze the persistent and the transient components of the total factor carbon emission performance. By disaggregating the time-variant and the time-invariant elements of the carbon dioxide emission changes, this paper adopts, for the first time, a new methodological approach to decompose the components of the total factor carbon emission performance indicator. Using panel data for selected 30 Chinese provinces for the time-period 1997–2017, this paper combines the environmental production technology, the Shephard distance function, and the stochastic frontier models to measure and investigate the spatio-temporal evolution of the total factor carbon emission performance and to evaluate the effectiveness of Chinese policies. By providing a better understanding of the total factor carbon dioxide emission performance, the proposed methodology is suitable to be replicated across regions, and provides an important opportunity for international comparisons and for the design of coordinated carbon reduction strategies. ⁃ An innovative approach is presented to decompose the persistent and transient TFCP ⁃ TFCP of China is affected by persistent inefficiency with regional disparities ⁃ The economic determinants of persistent and transient TFCP are investigated ⁃ Industrialisation, FDI, technology progress are key determinants of persistent TFCP [ABSTRACT FROM AUTHOR]

Understanding the causes of growing carbon transfers between developing countries is likely to be the first step in their mitigation. With this in mind, the current paper uses multi-regional input-output analysis to investigate CO 2 emissions and value-added embodied in China-Brazil trade. We propose the use of value-added exports, rather than gross exports, to more accurately estimate the economic benefits of trade. We find enormous increases in both CO 2 emissions and value-added embodied in exports for China and Brazil between 2000 and 2014. During this period, China's position as a net CO 2 emissions and net value-added exporter vis-à-vis Brazil deepens. Major sources of increasing embodied CO 2 exports for China were the basic materials and electricity industries and for Brazil were the basic materials, agriculture and mining industries. Estimates of net carbon intensities reveal advantages for China in electronics and for Brazil in agriculture and mining. Structural decomposition analysis shows that the changing consumption in China and Brazil as well as the changing structure of intermediate exports from China to Brazil were important sources of increasing embodied CO 2 emissions. This latter finding was possible due to the method proposed in this paper of decomposing the production structure into the domestic, export and import production structures. In line with the key findings, various implications and emission abatement policies are discussed. [ABSTRACT FROM AUTHOR]

The power sector plays a significant role in China's energy transition and emission reduction strategy. Considering that the aggregation of the power sector from different sources in input-output (IO) tables will lead to the "aggregation bias problem", it is vital that we disaggregate the power sector using IO tables when analyzing and comparing the driving forces of embodied carbon emission changes in the power sector. This paper first disaggregates the power sector into seven subsectors; then, it uses structural decomposition analysis (SDA) to analyze the driving forces of embodied carbon emission changes in each subsector and allocates embodied emissions that occur from 2007 to 2015 according to the demand categories. The results show that the embodied carbon emissions from each clean energy sector were relatively lower than those from thermal power during the study period. Consumption volume was the main driving factor for the embodied carbon emission increments. From 2012 to 2015, the production structure was mainly responsible for the embodied emission increases in each clean energy sector, indicating that the embodied carbon emissions caused by power equipment updates or reconstruction processes should receive more attention. In addition, the embodied carbon emission changes induced by urban residential consumption on the thermal power showed a plateaued trend from 2007 to 2015. This paper provides support for the formulation of emission reduction measures and the low-carbon structural transformation of the power sector. [ABSTRACT FROM AUTHOR]