Based on the China high resolution emission gridded data (1 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 1 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 partitioning 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 benchmarking research on city CO2 emissions should be conducted, and a Top Runner system of city CO2 emission reduction should be established. 相似文献
Municipal solid waste landfills pose a threat on environment and human health, especially old landfills which lack facilities for collection and treatment of landfill gas and leachate. Consequently, missing information about emission flows prevent site-specific environmental risk assessments. To overcome this gap, the combination of waste sampling and analysis with statistical modeling is one option for estimating present and future emission potentials. Optimizing the tradeoff between investigation costs and reliable results requires knowledge about both: the number of samples to be taken and variables to be analyzed.This article aims to identify the optimized number of waste samples and variables in order to predict a larger set of variables. Therefore, we introduce a multivariate linear regression model and tested the applicability by usage of two case studies. Landfill A was used to set up and calibrate the model based on 50 waste samples and twelve variables. The calibrated model was applied to Landfill B including 36 waste samples and twelve variables with four predictor variables.The case study results are twofold: first, the reliable and accurate prediction of the twelve variables can be achieved with the knowledge of four predictor variables (Loi, EC, pH and Cl). For the second Landfill B, only ten full measurements would be needed for a reliable prediction of most response variables. The four predictor variables would exhibit comparably low analytical costs in comparison to the full set of measurements. This cost reduction could be used to increase the number of samples yielding an improved understanding of the spatial waste heterogeneity in landfills.Concluding, the future application of the developed model potentially improves the reliability of predicted emission potentials. The model could become a standard screening tool for old landfills if its applicability and reliability would be tested in additional case studies. 相似文献
Objective: Road traffic suicides typically involve a passenger car driver crashing his or her vehicle into a heavy vehicle, because death is almost certain due to the large mass difference between these vehicles. For the same reason, heavy-vehicle drivers typically suffer minor injuries, if any, and have thus received little attention in the research literature. In this study, we focused on heavy-vehicle drivers who were involved as the second party in road suicides in Finland.
Methods: We analyzed 138 road suicides (2011–2016) involving a passenger car crashing into a heavy vehicle. We used in-depth road crash investigation data from the Finnish Crash Data Institute.
Results: The results showed that all but 2 crashes were head-on collisions. Almost 30% of truck drivers were injured, but only a few suffered serious injuries. More than a quarter reported sick leave following their crash. Injury insurance compensation to heavy-vehicle drivers was just above €9,000 on average. Material damage to heavy vehicles was significant, with average insurance compensation paid being €70,500. Three out of 4 truck drivers reported that drivers committing suicide acted abruptly and left them little opportunity for preventive action.
Conclusions: Suicides by crashing into heavy vehicles can have an impact on drivers’ well-being; however, it is difficult to see how heavy-vehicle drivers could avoid a suicide attempt involving their vehicle. 相似文献