Objective: The Multidimensional Driving Style Inventory (MDSI) has been widely used in assessing the associations between driving styles and traffic violations and accidents in different cultural contexts. Due to the lack of a valid instrument to assess driving style, studies concerning driving style and its influence factors are limited in China. Thus, this study aimed to adapt and validate a Chinese version of the MDSI.
Methods: Seven hundred and sixty drivers aged from 19 to 60 years old were asked to complete the MDSI and a personality scale (trait anger, sensation seeking, altruism, and normlessness). Exploratory factory analysis (EFA) and confirmatory factor analysis (CFA) were used to obtain the factorial structure of the MDSI. The external validity of the MDSI was then evaluated by examining the associations between driving styles and personality traits, demographic variables, and traffic violations and crashes.
Results: EFA revealed a 6-factor structure of the MDSI (i.e., risky, anxious, angry, distress reduction, careful, and dissociative driving styles). CFA confirmed that the model fit of the MDSI was acceptable. The MDSI factors were moderately or weakly correlated with trait anger, sensation seeking, altruism, and normlessness. Significant gender and age differences in driving styles were found. Moreover, drivers who had traffic violations or crashes in the past year scored higher on risky and angry driving styles and lower on careful driving style than those who had not have traffic violations or crashes.
Conclusions: The Chinese version of the MDSI proved to be a reliable, valid, and highly useful instrument. It could be used to assess Chinese drivers who are at risk due to their maladaptive driving styles. 相似文献
Environmental Science and Pollution Research - The Huainan mining area is rich in coal resources and has sparse vegetation and many collapsed waterways. Large-scale and long-term underground coal... 相似文献
Lawn and garden equipment are a significant source of emissions of volatile organic compounds (VOCs) and other pollutants in suburban and urban areas. Emission estimates for this source category are typically prepared using default equipment populations and activity data contained in emissions models such as the U.S. Environmental Protection Agency's (EPA) NONROAD model or the California Air Resources Board's (CARB) OFFROAD model. Although such default data may represent national or state averages, these data are unlikely to reflect regional or local differences in equipment usage patterns because of variations in climate, lot sizes, and other variables. To assess potential errors in lawn and garden equipment emission estimates produced by the NONROAD model and to demonstrate methods that can be used by local planning agencies to improve those emission estimates, this study used bottom-up data collection techniques in the Baltimore metropolitan area to develop local equipment population, activity, and temporal data for lawn and garden equipment in the area. Results of this study show that emission estimates of VOCs, particulate matter (PM), carbon monoxide (CO), carbon dioxide (CO2), and nitrogen oxides (NO(x)) for the Baltimore area that are based on local data collected through surveys of residential and commercial lawn and garden equipment users are 24-56% lower than estimates produced using NONROAD default data, largely because of a difference in equipment populations for high-usage commercial applications. Survey-derived emission estimates of PM and VOCs are 24 and 26% lower than NONROAD default estimates, respectively, whereas survey-derived emission estimates for CO, CO2, and NO(x) are more than 40% lower than NONROAD default estimates. In addition, study results show that the temporal allocation factors applied to residential lawn and garden equipment in the NONROAD model underestimated weekend activity levels by 30% compared with survey-derived temporal profiles. 相似文献
A novel electrolytic groundwater remediation process, which used the H2 continuously generated at cathode to achieve in situ catalytic hydrodechlorination, was developed for the treatment of 2,4-dichlorophenol (2,4-DCP) in groundwater. Catalytic hydrodechlorination using Pd supported on bamboo charcoal and external H2 showed that 2,4-DCP was completely dechlorinated to phenol within 30 min at pH ? 5.5. In a divided electrolytic system, the catalytic hydrodechlorination of 2,4-DCP in cathodic compartment by H2 generated at the cathode under 20 and 50 mA reached 100% at 120 and 60 min, respectively. Two column experiments with influent pHs of 5.5 (unconditioned) and 2 were conducted to evaluate the feasibility of this process. The 2,4-DCP removal efficiencies were about 63% and nearly 100% at influent pHs of 5.5 and 2, respectively. Phenol was solely produced by 2,4-DCP hydrodechlorination, and was subsequently degraded at the anode. A low pH could enhance the hydrodechlorination, but was not necessarily required. This study provides the preliminary results of a novel effective electrolytic process for the remediation of groundwater contaminated by chlorinated aromatics. 相似文献