Objective: Electric bike/moped-related road traffic injuries have become a burgeoning public health problem in China. The objective of this study was to identify the prevalence and potential risk factors of electric bike/moped-related road traffic injuries among electric bike/moped riders in southern China.
Methods: A cross-sectional study was used to interview 3,151 electric bike/moped riders in southern China. Electric bike/moped-related road traffic injuries that occurred from July 2014 to June 2015 were investigated. Data were collected by face-to-face interviews and analyzed between July 2015 and June 2017.
Results: The prevalence of electric bike/moped-related road traffic injuries among the investigated riders was 15.99%. Electric bike/moped-related road traffic injuries were significantly associated with category of electric bike (adjusted odds ratio [AOR] = 1.36, 95% confidence interval [CI], 1.01–1.82), self-reported confusion (AOR = 1.77, 95% CI, 1.13–2.78), history of crashes (AOR = 6.14, 95% CI, 4.68–8.07), running red lights (AOR = 3.57, 95% CI, 2.42–5.25), carrying children while riding (AOR = 1.96, 95% CI, 1.37–2.85), carrying adults while riding (AOR = 1.68, 95% CI, 1.23–2.28), riding in the motor lane (AOR = 2.42, 95% CI, 1.05–3.93), and riding in the wrong traffic direction (AOR = 1.63, 95% CI, 1.13–2.35). In over 77.58% of electric bike/moped-related road traffic crashes, riders were determined by the police to be responsible for the crash. Major crash-causing factors included violating traffic signals or signs, careless riding, speeding, and riding in the wrong lane.
Conclusion: Traffic safety related to electric bikes/moped is becoming more problematic with growing popularity compared with other 2-wheeled vehicles. Programs need to be developed to prevent electric bike/moped-related road traffic injuries in this emerging country. 相似文献
The present study aims to better understand the relationship between energy intensity and its determinants including energy price, technological progress, economic structure, and energy mix using the autoregressive distributed lag(ARDL) bounds approach and vector error correction model technique. Based on China's time series over 1985-2014, the ARDL bounds approach yields empirical evidence that confirms the existence of long run relationship between energy price, technological progress, economic structure, energy mix, and energy intensity. The results show that technological progress is an important driver for the declining energy intensity in short and long run. Energy price has not been demonstrated as an important role in decreasing energy intensity in the short run. The high share of coal use in total energy use may be responsible for China's high energy intensity.However, the relative change in economic sectors plays a minor role in energy intensity reduction during the past years. In the long run, technological progress, energy mix and energy prices Granger cause energy intensity, but not vice versa except for the energy mix. 相似文献
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