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1.
Objectives: The accuracy of self-reported driving exposure has questioned the validity of using self-reported mileage to inform research questions. Studies examining the accuracy of self-reported driving exposure compared to objective measures find low validity, with drivers overestimating and underestimating driving distance. The aims of the current study were to (1) examine the discrepancy between self-reported annual mileage and driving exposure the following year and (2) investigate whether these differences depended on age and annual mileage.

Methods: Two estimates of drivers’ self-reported annual mileage collected during vehicle installation (obtained via prestudy questionnaires) and approximated annual mileage driven (based upon Global Positioning System data) were acquired from 3,323 participants who participated in the Strategic Highway Research Program 2 (SHRP2) Naturalistic Driving Study.

Results: A Wilcoxon signed rank test showed that there was a significant difference between self-reported and annual driving exposure during participation in SHRP 2, with the majority of self-reported responses overestimating annual mileage the following year, irrespective of whether an ordinal or ratio variable was examined. Over 15% of participants provided self-reported responses with over 100% deviation, which were exclusive to participants underestimating annual mileage. Further, deviations in reporting differed between participants who had low, medium, and high exposure, as well as between participants in different age groups.

Conclusions: These findings indicate that although self-reported annual mileage is heavily relied on for research, such estimates of driving distance may be an overestimate of current or future mileage and can influence the validity of prior research that has utilized estimates of driving exposure.  相似文献   

2.
Background, Aim and Scope Air quality is an field of major concern in large cities. This problem has led administrations to introduce plans and regulations to reduce pollutant emissions. The analysis of variations in the concentration of pollutants is useful when evaluating the effectiveness of these plans. However, such an analysis cannot be undertaken using standard statistical techniques, due to the fact that concentrations of atmospheric pollutants often exhibit a lack of normality and are autocorrelated. On the other hand, if long-term trends of any pollutant’s emissions are to be detected, meteorological effects must be removed from the time series analysed, due to their strong masking effects. Materials and Methods The application of statistical methods to analyse temporal variations is illustrated using monthly carbon monoxide (CO) concentrations observed at an urban site. The sampling site is located at a street intersection in central Valencia (Spain) with a high traffic density. Valencia is the third largest city in Spain. It is a typical Mediterranean city in terms of its urban structure and climatology. The sampling site started operation in January 1994 and monitored CO ground level concentrations until February 2002. Its geographic coordinates are W0°22′52″ N39°28′05″ and its altitude is 11 m. Two nonparametric trend tests are applied. One of these is robust against serial correlation with regards to the false rejection rate, when observations have a strong persistence or when the sample size per month is small. A nonparametric analysis of the homogeneity of trends between seasons is also discussed. A multiple linear regression model is used with the transformed data, including the effect of meteorological variables. The method of generalized least squares is applied to estimate the model parameters to take into account the serial dependence of the residuals of this model. This study also assesses temporal changes using the Kolmogorov-Zurbenko (KZ) filter. The KZ filter has been shown to be an effective way to remove the influence of meteorological conditions on O3 and PM to examine underlying trends. Results The nonparametric tests indicate a decreasing, significant trend in the sampled site. The application of the linear model yields a significant decrease every twelve months of 15.8% for the average monthly CO concentration. The 95% confidence interval for the trend ranges from 13.9% to 17.7%. The seasonal cycle also provides significant results. There are no differences in trends throughout the months. The percentage of CO variance explained by the linear model is 90.3%. The KZ filter separates out long, short-term and seasonal variations in the CO series. The estimated, significant, long-term trend every year results in 10.3% with this method. The 95% confidence interval ranges from 8.8% to 11.9%. This approach explains 89.9% of the CO temporal variations. Discussion The differences between the linear model and KZ filter trend estimations are due to the fact that the KZ filter performs the analysis on the smoothed data rather than the original data. In the KZ filter trend estimation, the effect of meteorological conditions has been removed. The CO short-term componentis attributable to weather and short-term fluctuations in emissions. There is a significant seasonal cycle. This component is a result of changes in the traffic, the yearly meteorological cycle and the interactions between these two factors. There are peaks during the autumn and winter months, which have more traffic density in the sampled site. There is a minimum during the month of August, reflecting the very low level of vehicle emissions which is a direct consequence of the holiday period. Conclusions The significant, decreasing trend implies to a certain extent that the urban environment in the area is improving. This trend results from changes in overall emissions, pollutant transport, climate, policy and economics. It is also due to the effect of introducing reformulated gasoline. The additives enable vehicles to burn fuel with a higher air/fuel ratio, thereby lowering the emission of CO. The KZ filter has been the most effective method to separate the CO series components and to obtain an estimate of the long-term trend due to changes in emissions, removing the effect of meteorological conditions. Recommendations and Perspectives Air quality managers and policy-makers must understand the link between climate and pollutants to select optimal pollutant reduction strategies and avoid exceeding emission directives. This paper analyses eight years of ambient CO data at a site with a high traffic density, and provides results that are useful for decision-making. The assessment of long-term changes in air pollutants to evaluate reduction strategies has to be done while taking into account meteorological variability  相似文献   
3.
Long-term stationary studies on the ecology of the northern mole vole (Ellobius talpinus Pall.), performed by the mark–recapture method from 1985 to 1997, have provided original data on population dynamics and structure. The analysis shows that, to reveal cyclic fluctuations of population size in this species, the period of three years should be taken as a unit of time for estimating the duration of one phase. The 12-year population cycle in E. talpinus has four distinct phases: an increase, a peak, a decline, and a minimum. At each phase, the population is characterized by certain features of family structure, age composition, birth and death rates, and the composition of migrants.  相似文献   
4.
5.
岩溶地下河污染物运移模型对比研究   总被引:4,自引:0,他引:4  
两区模型(TRM)和暂时存储模型(TSM)为两种常用的岩溶地下河(管道)污染物运移模型,为了更好表征岩溶地下河污染物运移过程,开展模型对比研究.采用两种模型拟合室内管道示踪实验穿透曲线,从概念模型框架、模型优缺点、参数校正过程和物理意义、参数敏感性等方面对比分析两种模型的异同.结果表明,OTIS软件提供TSM的数值解,而CXTFIT软件提供TRM的解析解,但两者均能通过下游不同位置的穿透曲线分段表征地下河不同阶段的污染物运移过程.两种模型的物理意义相近,均可近似描述岩溶地下河中溶质的暂时性存储现象,较好地拟合溶质运移曲线.采用TSM可校正得到暂时存储区的横截面积,但采用TRM只能获得非流动区所占的比例.两种模型中弥散系数和传质/交换系数的敏感度较低,并且弥散系数的变化对穿透曲线拖尾无显著影响.研究结果为岩溶地下河污染物运移模型的选取与应用提供了依据.  相似文献   
6.
目的通过地面环境试验研究气动热引起的瞬态高温环境对飞行器结构的影响。方法设计基于石英灯和离心机的瞬态高温-加速度复合试验系统,研究温度和加速度同步控制系统的结构和原理,分析无制冷装置环境下瞬态高温控制的难点,提出基于模糊PI控制器的温度控制策略。结果通过MATLAB仿真验证,设计的模糊PI控制器相比传统的PI控制器能够有效提高温度控制的动态性能与精确性。结论将基于模糊PI控制的瞬态加热控制策略应用于瞬态高温控制是可行、有效的,能为地面气动热模拟环境试验提供技术保障。  相似文献   
7.
京津冀西北典型区域地下水位时空演变及驱动因素   总被引:1,自引:0,他引:1  
京津冀西北地区是北京、天津重要的水源涵养区和生态屏障,也是“京津冀协同发展”战略重要的支撑区域。为揭示京津冀西北地区地下水位时空演变规律及其驱动因素,以张家口地区为研究区域,选取1981—2015年56个地下水位观测井连续观测数据、水文地质相关资料、气象数据、地下水资源开采数据和社会经济数据,对研究区内坝上高原、柴宣盆地、涿怀盆地和蔚阳盆地四个地貌单元地下水位时空演变规律和驱动因素进行分析。结果表明:张家口地区四个地貌单元及下辖各区县地下水位呈整体下降趋势,且下降速率逐步加快。35年间坝上高原水位降幅3.59 m<蔚阳盆地水位降幅3.6 m<涿怀盆地水位降幅7.17 m<柴宣盆地水位降幅20.41 m。张家口地区四个地貌单元地下水位动态变化与降雨量、蒸发量、气温等自然因素相关性较差,但与第一产业产值、常用耕地面积、有效灌溉面积、粮食总产量、蔬菜总产量、猪牛羊肉总产量、第二产业产值、第三产业产值和年末总人口等社会经济因素存在显著的相关性。在主成分分析中四个地貌单元前两个主成分的累计方差贡献率均>80%,其中第一个主成分主要为蔬菜总产量、猪牛羊肉总产量、年末总人口和第一、第二、第三产业产值等社会经济因素,不同地貌单元均可解释66%以上,表明社会经济因素是造成张家口地区地下水位持续下降的主要驱动因素。研究成果可为该地区未来社会经济的可持续发展和区域水资源的合理利用、调配以及京津冀西北地区水源涵养和生态功能保持提供理论依据。  相似文献   
8.
采用自主设计的生物质燃烧实验装置,在不同燃烧状态(明燃、阴燃)下,对大兴安岭林区5种典型乔木树种的不同部位(枝、叶、皮)燃烧释放PM2.5中的水溶性元素特性进行研究.结果显示,不同树种间PM2.5的排放因子差异显著,排放范围为(2.408±0.854)~(9.227±1.172)g/kg.5种乔木树种燃烧释放PM2.5中主要检测到Mg、Ca、K等16 种元素,其中Ca、K、Zn、Mg 4种元素的排放因子明显大于其它元素.不同树种间元素排放因子差异较大,针叶树的排放因子一般高于阔叶树.除Cd元素外,不同器官间排放的元素总量无明显差异.不同树种不同器官燃烧释放PM2.5中水溶性元素的占比顺序较为一致,其中Ca、K、Zn和Mg 4种元素的排放因子在枝、叶、皮中均较高.此外,燃烧状态对元素排放特征影响较大,Li、Mg、Ca等7种元素的排放因子均表现为明燃显著高于阴燃.  相似文献   
9.
This paper discusses the REAP1 model and its application for the analysis of CO2 reduction and waste management policies for Japanese petrochemicals. The pros and cons of this modelling approach in comparison to other tools is elaborated. This is followed by a discussion of the model code and the modelling results. The results show that CO2 policies can have significant impacts on waste flows and waste policies can have significant CO2 benefits. As a consequence both effects must be considered in policy assessment. Pricing instruments are recommended instead of regulations because of the complex physical relations in the materials life cycle that extend beyond sector boundaries. A taxation approach is superior to a subsidy approach because rebound effects can be avoided.  相似文献   
10.
以海南省文昌市典型的胶—茶—鸡农林复合模式为研究对象 ,以单作胶园、胶茶间作园为对照 ,采用定量研究与定性分析相结合的方法 ,研究其物质循环规律。结果表明 ,胶—茶—鸡农林复合系统的氮、磷输入、输出量最大 ,系统外物质投入率比另两系统明显减少 ,系统内养分循环量增加 ,因此 ,该系统具有较合理的物质循环结构。  相似文献   
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