Carbon dioxide emissions from cities in China based on high resolution emission gridded data

Based on the China high resolution emission gridded data （I km spatial resolution）, this article is aimed to create a Chinese city carbon dioxide （CO2） emission data set using consolidated data sources as well as normalized and standardized data processing methods. Standard methods were used to calculate city CO2 emissions, including scope I and scope 2. Cities with higher CO2 emissions are mostly in north, northeast, and eastern coastal areas. Cities with lower CO2 emissions are in the western region. Cites with higher CO2 emissions are clustered in the Jing-Jin-Ji Region （such as Beijing, Tianjin, and Tangshan）, and the Yangtze River Delta region （such as Shanghai and Suzhou）. The city per capita CO2 emission is larger in the north than the south. There are obvious aggregations of cities with high per capita CO2 emission in the north. Four cities among the top 10 per capita emissions （Erdos, Wuhai, Shizuishan, and Yinchuan） cluster in the main coal production areas of northern China. This indicates the significant impact of coal resources endowment on city industry and CO2 emissions. The majority （77%） of cities have annual CO2 emissions below 50 million tons. The mean annual emission, among all cities, is 37 million tons. Emissions from service-based cities, which include the smallest number of cities, are the highest. Industrial cities are the largest category and the emission distribution from these cities is close to the normal distribution. Emissions and degree of dispersion, in the other cities （excluding industrial cities and service-based cities）, are in the lowest level. Per capita CO2 emissions in these cities are generally below 20 t/person （89%） with a mean value of 11 t/person. The distribution interval of per capita CO2 emission within industrial cities is the largest among the three city categories. This indicates greater differences among per capita CO2 emissions of industrial cities. The distribution interval of per capita CO2 emission of other cities is the lowest, indicating smaller differences of per capita CO2 emissions among this city category. Three policy suggestions are proposed： first, city CO2 emission inventory data in China should be increased, especially for prefecture level cities. Second, city responsibility for emission reduction, and partition- ing the national goal should be established, using a bottom-up approach based on specific CO2 emission levels and potential for emission reductions in each city. Third, comparative and bench- marking research on city CO2 emissions should be conducted, and a Top Runner system of city CO2 emission reduction should be established.

City level CO_(2) and local air pollutants co-control performance evaluation: A case study of 113 key envir on mental protection cities in China

‘Co-control',or synergistically reducing CO_(2)and local air polluta nt emissions,is an important strategy for cities to achieve'low carb on'and'blue sky'simultaneously.However,there were few studies to evaluate and compare the level of co-control of CO_(2) and local air pollutants in cities year.The present study proposed qualitative and quantitative methods to evaluate the level of co-control of CO_(2)and three local air pollutant(SO_(2).NOX,and particulate matter PM)emissions in key environmental protection cities in China over two periods(2012-2015 and 2015-2018).Statistical analysis found that,though three local air pollutant emissions positively correlated with CO_(2) emission,no significantly positive correlation was found between local air pollutants emission reductions and CO_(2) emission reductions,indicating that co-control effects were poor in general.By using the co-control effect coordinate system,qualitative evaluation showed that less than half of the sample cities could achieve co-control of the total amount of CO_(2) and local air pollutants.By employing the indicator of emission reduction equivalence(EReq),quantitative evaluation showed that the co-control level of the sample cities improved in 2015-2018 compared with 2012-2015.Further regression analysis showed that,reducing coal consumption and economic development significantly enhanced the co-control performance of the observed cities.The present case study proved that the proposed methods for evaluation and comparison of the city co-control performance works well,and can be used in other countries and regions to promote global cities racing to carbon and local air pollutants co-control.

Study on carbon emission in prefecture-level cities of china

The study on greenhouse gas inventory in urban China lags far behind the global level. The important factor that curbs the carbon inventory of cities of China is inventory methodology and scope. Given the insufficiency of Chinese cities carbon inventory, a system and accounting model （scopel＋ scope2） as well as principles and boundaries were proposed for China. The carbon emissions in scopel and scopel＋ scope2 were calculated in Chinese prefecture-level cities. The EDGAR dataset was used for the calculation of scopel carbon emissions in cities in China and the level of uncertainty was analyzed as well. The results showed that the direct carbon emission of cities in China was about 31.65% of China total emissions. The scopel＋ scope2 carbon emissions in cities of China were calculated based on the GIS and RS model. The results showed that the sum of direct （scopel） and indirect （scope2） carbon emissions of cities in China accounted for 38.80% of total China carbon emissions.

Specific patterns of XC02 observed by GOSAT during 2009-2016and assessed with model simulations over China

Spatiotemporal patterns of column-averaged dry air mole fraction of CO2(XCO2)have not been well characterized on a regional scale due to limitations in data availability and precision.This paper addresses these issues by examining such patterns in China using the long-term mapping XCO2 dataset(2009-2016)derived from the Greenhouse gases Observing SATellite(GOSAT).XCO2 simulations are also constructed using the high-resolution nested-grid GEOS-Chem model.The following results are found:Firstly,the correlation coefficient between the anthropogenic emissions and XCO2 spatial distribution is nearly zero in summer but up to 0.32 in autumn.Secondly,on average,XCO2 increases by 2.08 ppm every year from2010 to 2015,with a sharp increase of 2.6 ppm in 2013.Lastly,in the analysis of three typical regions,the GOSAT XCO2 time series is inbetter agreement with the GEOS-Chem simulation of XCO2 in the Taklimakan Desert region(the least difference with bias 0.65±0.78 ppm),compared with the northern urban agglomerationregion(-1.3±1.2 ppm)and the northeastern forest region(-1.4±1.4 ppm).The results are likely attributable to uncertainty in both the satellite-retrieved XCO2 data and the model simulation data.