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      The association between meteorological factors and road traffic injuries: a case analysis from Shantou city, China

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          Abstract

          Few studies examined the associations of meteorological factors with road traffic injuries (RTIs). The purpose of the present study was to quantify the contributions of meteorological factors to RTI cases treated at a tertiary level hospital in Shantou city, China. A time-series diagram was employed to illustrate the time trends and seasonal variation of RTIs, and correlation analysis and multiple linear regression analysis were conducted to investigate the relationships between meteorological parameters and RTIs. RTIs followed a seasonal pattern as more cases occurred during summer and winter months. RTIs are positively correlated with temperature and sunshine duration, while negatively associated with wind speed. Temperature, sunshine hour and wind speed were included in the final linear model with regression coefficients of 0.65 (t = 2.36, P = 0.019), 2.23 (t = 2.72, P = 0.007) and −27.66 (t = −5.67, P < 0.001), respectively, accounting for 19.93% of the total variation of RTI cases. The findings can help us better understand the associations between meteorological factors and RTIs, and with potential contributions to the development and implementation of regional level evidence-based weather-responsive traffic management system in the future.

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          Injuries.

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            Risk factors associated with traffic violations and accident severity in China.

            With the recent economic boom in China, vehicle volume and the number of traffic accident fatalities have become the highest in the world. Meanwhile, traffic accidents have become the leading cause of death in China. Systematically analyzing road safety data from different perspectives and applying empirical methods/implementing proper measures to reduce the fatality rate will be an urgent and challenging task for China in the coming years. In this study, we analyze the traffic accident data for the period 2006-2010 in Guangdong Province, China. These data, extracted from the Traffic Management Sector-Specific Incident Case Data Report, are the only officially available and reliable source of traffic accident data (with a sample size>7000 per year). In particular, we focus on two outcome measures: traffic violations and accident severity. Human, vehicle, road and environmental risk factors are considered. First, the results establish the role of traffic violations as one of the major risks threatening road safety. An immediate implication is: if the traffic violation rate could be reduced or controlled successfully, then the rate of serious injuries and fatalities would be reduced accordingly. Second, specific risk factors associated with traffic violations and accident severity are determined. Accordingly, to reduce traffic accident incidence and fatality rates, measures such as traffic regulations and legislation-targeting different vehicle types/driver groups with respect to the various human, vehicle and environment risk factors-are needed. Such measures could include road safety programs for targeted driver groups, focused enforcement of traffic regulations and road/transport facility improvements. Data analysis results arising from this study will shed lights on the development of similar (adjusted) measures to reduce traffic violations and/or accident fatalities and injuries, and to promote road safety in other regions. Copyright © 2013 Elsevier Ltd. All rights reserved.
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              Effects of meteorology and secondary particle formation on visibility during heavy haze events in Beijing, China.

              The causes of haze formation in Beijing, China were analyzed based on a comprehensive measurement, including PBL (planetary boundary layer), aerosol composition and concentrations, and several important meteorological parameters such as visibility, RH (relative humidity), and wind speed/direction. The measurement was conducted in an urban location from Nov. 16, 2012 to Jan. 15, 2013. During the period, the visibility varied from >20 km to less than a kilometer, with a minimum visibility of 667 m, causing 16 haze occurrences. During the haze occurrences, the wind speeds were less than 1m/s, and the concentrations of PM2.5 (particle matter with radius less than 2.5 μm) were often exceeded 200 μg/m(3). The correlation between PM2.5 concentration and visibility under different RH values shows that visibility was exponentially decreased with the increase of PM2.5 concentrations when RH was less than 80%. However, when RH was higher than 80%, the relationship was no longer to follow the exponentially decreasing trend, and the visibility maintained in very low values, even with low PM2.5 concentrations. Under this condition, the hygroscopic growth of particles played important roles, and a large amount of water vapor acted as particle matter (PM) for the reduction of visibility. The variations of meteorological parameters (RH, PBL heights, and WS (wind speed)), chemical species in gas-phase (CO, O3, SO2, and NOx), and gas-phase to particle-phase conversions under different visibility ranges were analyzed. The results show that from high visibility (>20 km) to low visibility (<2 km), the averaged PBL decreased from 1.24 km to 0.53 km; wind speeds reduced from 1m/s to 0.5m/s; and CO increased from 0.5 ppmv to 4.0 ppmv, suggesting that weaker transport/diffusion caused the haze occurrences. This study also found that the formation of SPM (secondary particle matter) was accelerated in the haze events. The conversions between SO2 and SO4 as well as NOx to NO3(-) increased, especially under high humidity conditions. When the averaged RH was 70%, the conversions between SO2 and SO4 accounted for about 20% concentration of PM2.5, indicating that formation of secondary particle matter had important contribution for the haze occurrences in Beijing.
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                Author and article information

                Journal
                Sci Rep
                Sci Rep
                Scientific Reports
                Nature Publishing Group
                2045-2322
                17 November 2016
                2016
                : 6
                : 37300
                Affiliations
                [1 ]State Key Laboratory of Infectious Disease Prevention and Control, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, National Institute for Communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention , Beijing, China
                [2 ]Injury Prevention Research Center, Shantou University Medical College , No. 22 Xinling Road, Shantou, Guangdong, 515041, China
                [3 ]First Affiliated Hospital of Shantou University Medical College , Guangdong, China
                [4 ]School of Population Health, University of Auckland , Private Bag 92019, Auckland, New Zealand
                Author notes
                [*]

                These authors contributed equally to this work.

                Article
                srep37300
                10.1038/srep37300
                5112526
                27853316
                6cddd27b-d0bd-4455-b044-c7ccbcc7f21a
                Copyright © 2016, The Author(s)

                This work is licensed under a Creative Commons Attribution 4.0 International License. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder to reproduce the material. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/

                History
                : 18 May 2016
                : 27 October 2016
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