• Energy Research

There are substantial differences in carbon footprints across households. This study applied an environmentally extended multiregional input–output approach to estimate household carbon footprints for 12 different income groups of China’s 30 regions. Subsequently, carbon footprint Gini coefficients were calculated to measure carbon inequality for households across provinces. We found that the top 5% of income earners were responsible for 17% of the national household carbon footprint in 2012, while the bottom half of income earners caused only 25%. Carbon inequality declined with economic growth in China across space and time in two ways: first, carbon footprints showed greater convergence in the wealthier coastal regions than in the poorer inland regions; second, China’s national carbon footprint Gini coefficients declined from 0.44 in 2007 to 0.37 in 2012. We argue that economic growth not only increases income levels but also contributes to an overall reduction in carbon inequality in China.

Knowing the carbon emission baseline of a region is a precondition for any mitigation effort, but the baselines are highly dependent on the system boundaries for which they are calculated. On the basis of sectoral energy statistics and a nested provincial and global multi-regional input–output model, we calculate and compare four different system boundaries for China's 30 provinces and major cities. The results demonstrate significant differences in the level of emissions for the different system boundaries. Moreover, the associated emissions with each system boundary varies with the regional development level, i.e. richer areas outsource more emissions to other areas, or in other words boundary 4 emissions are higher than boundary 1 emissions for rich areas and vice versa for poor areas. Given these significant differences it is important to be aware of the implications the choice of an accounting system might have on outcomes.

AbstractAs energy saving and emission reduction become a global action, the disparity in energy intensity between different regions is a new rising problem that stems a country's or region's energy‐saving potential. Here we collect China's provincial panel data (1995–2017) of primary and final energy consumption to evaluate China's unequal and polarized regional pattern in energy intensity, decompose the inequality index into contributing components, and investigate possible driving factors behind the unequal pattern both regionally and structurally, for the first time. The results show that China's interprovince disparities in energy intensity increase and are exacerbated by the enlarging disparities in energy intensity between the least developed and most developed regions of China. The causes for this phenomenon are as follows: (i) rather loose regulatory measures on mitigating coal consumption; (ii) inferior energy processing technology in areas specializing in energy‐intensive industries; (iii) increasing interregional energy fluxes embodied in trade; and (iv) separate jurisdictions at provincial administrative levels. These factors can synthetically result in unintended spillover to areas with inferior green technologies, suggesting an increasingly uneven distribution of energy‐intensive and carbon‐intensive industries and usage of clean energy. The results reveal the necessities of regional coordination and cooperation to achieve a green economy.

Recycling, renewables and a reinvigorated domestic energy market will allow China to lead the world in low-carbon development, say Zhu Liu and colleagues.

AbstractAs the biggest CO2 emitter in the world, China attracted lots of concerns. With high population densities and economic activity clustering, cities are the focus for CO2 emission reduction and sustainable development. However, barriers come from the lack of methodology as well as data support. In this study we take the method from the intergovernmental panel on climate change (IPCC), and developed the method by using energy balance, national energy statistics been adopting as data, where Shanghai was taken to be a case as one of the most populous cities in China. The results showed that there is 188.32 million tons of CO2 emission in Shanghai during 2008, and there are 14 kinds of energy consumed by pre-established 8 different sectors, coal as the uppermost energy for the total energy consumption, and industry and energy productions are the main contributors to CO2 emission.

Abstract China is the largest contributor of global CO2 emissions, to date more than quarter of the world total CO2 is from China. Well known on the fossil fuel combustion and cement production as the major emission sources, however, “non-fossil fuel CO2 emissions” are rarely reported by literature (except the emission from cement production). As China becomes the center for global manufacturing, it is critical to understand the magnitude and dynamics of China’s non-fossil fuel CO2 emissions so effective mitigation policy can be addressed. Here we collected data for all kinds of industrial processes CO2 emissions, and based on available data we calculated the CO2 emissions from the production of lime, plate glass, ammonia, calcium carbide, soda ash, ethylene, ferroalloys, alumina, lead and zinc in 2003–2018. We found that China’s CO2 emissions from these ten industrial processes reached 466 Mt CO2 in 2016, which is equivalent to 5% of China’s total CO2 emissions (9000 Mt CO2) from fossil fuel combustion and cement production process. The 466 Mt CO2 is approximate to total fossil fuel CO2 emissions from Brazil, the world top 11 CO2 emitter. The CO2 emissions from these ten industrial production processes show a fast increase before 2014, and fluctuate in 2014–2018. Quantifying such emission is critical for understanding the global carbon budget and developing a suitable climate policy given the significant magnitude and recent dynamics of China’s non-fossil fuel CO2 emissions.

Carbon Monitor est un ensemble de données en temps quasi réel pour les émissions quotidiennes de CO2 avec une couverture mondiale de 6 secteurs principaux (énergie, industrie, transport terrestre, aviation, transport résidentiel et international).Ici, nous fournissons les données annuelles de 2019 et 2020.Visitez notre site Web pour plus d'informations : https://carbonmonitor.org Carbon Monitor es un conjunto de datos casi en tiempo real para las emisiones diarias de CO2 con cobertura global de 6 sectores principales (energía, industria, transporte terrestre, aviación, transporte residencial e internacional).Aquí, proporcionamos los datos de todo el año de 2019 y 2020.Visite nuestro sitio web para obtener más información: https://carbonmonitor.org Carbon Monitor is a near real-time dataset for daily CO2 emissions with global coverage from 6 main sectors (power, industry, ground transportation, aviation, residential and international shipping).Here, we provide the whole year data of 2019 and 2020.Visit our website for more information: https://carbonmonitor.org كربون مونيتور هي مجموعة بيانات شبه آنية لانبعاثات ثاني أكسيد الكربون اليومية مع تغطية عالمية من 6 قطاعات رئيسية (الطاقة والصناعة والنقل البري والطيران والشحن السكني والدولي). نقدم هنا بيانات العام بأكمله لعامي 2019 و 2020.قم بزيارة موقعنا الإلكتروني لمزيد من المعلومات: https://carbonmonitor.org

China committed itself to reduce the carbon intensity of its economy (the amount of CO2 emitted per unit of GDP) by 40-45% during 2005-2020. Yet, between 2002 and 2009, China experienced a 3% increase in carbon intensity, though trends differed greatly among its 30 provinces. Decomposition analysis shows that sectoral effciency gains in nearly all provinces were offset by movement towards a more carbon-intensive economic structure. Such a sectoral shift seemed to be heavily affected by the growing role of investments and capital accumulation in China's growth process which has favoured sectors with high carbon intensity. Panel data regressions show that changes in carbon intensity were smallest in sectors dominating the regional economy (so as not to endanger these large sectors, which are the mainstay of the provincial economy), whereas scale and convergence effects played a much smaller role.

As part of the Paris Agreement, China pledged to peak its CO2 emissions by 2030. In retrospect, the commitment may have been fulfilled as it was being made: China’s emissions peaked in 2013 at a level of 9.53 Gigatons of CO2, and declined in each year from 2014 to 2016. However, the prospect for maintenance of the continued reductions depend the relative contributions of different changes in China. Here we quantitatively evaluate the drivers of the peak and decline of China’s CO2 emissions between 2007 and 2016 using the latest available energy, economic, and industry data. We find that slowing economic growth in China has it easier to reduce emissions. Nevertheless, the decline is largely associated with changes in industrial structure and a decline in the share of coal used for energy. Decreasing energy intensity (energy per unit GDP) and emissions intensity (emissions per unit energy) also contributed to the decline. Based on an econometric (cumulative sum) test, we confirm that there is a clear structural break in China’s emission pattern from 2015. We conclude that the decline of Chinese emissions is structural and is likely to be sustained if the nascent industrial and energy system transitions continue.

AbstractSpatiotemporal changes in China's carbon emissions during the 11th and 12th Five‐Year Plan periods are quantified for the first time through a reconstructed nationwide high‐resolution gridded data set. The hot spots of carbon emissions in China have expanded by 28.5% (toward the west) in the north and shrunk by 18.7% in the south; meanwhile, the emission densities in North and South China have increased by 15.7% and 49.9%, respectively. This suggests a clear transition to a more intensive economic growth model in South China as a result of the energy conservation and emission reduction policies, while the expanded carbon hot spots in North China are mainly dominated by the Grand Western Development Program. The results also show that China's carbon emissions exhibit a typical spatially intensive, high‐emission pattern, which has undergone a slight relaxation (up to 3%) from 2007 to 2012 due to a typical urbanization process.