National Exposure Research Laboratory, Office of Research and Development, U. S. Environmental Protection Agency, Durham, NC 27711, USA.
Int J Environ Res Public Health. 2017 Dec 15;14(12):1581. doi: 10.3390/ijerph14121581.
An important factor in evaluating health risk of near-road air pollution is to accurately estimate the traffic-related vehicle emission of air pollutants. Inclusion of traffic parameters such as road length/area, distance to roads, and traffic volume/intensity into models such as land use regression (LUR) models has improved exposure estimation. To better understand the relationship between vehicle emissions and near-road air pollution, we evaluated three traffic density-based indices: Major-Road Density (MRD), All-Traffic Density (ATD) and Heavy-Traffic Density (HTD) which represent the proportions of major roads, major road with annual average daily traffic (AADT), and major road with commercial annual average daily traffic (CAADT) in a buffered area, respectively. We evaluated the potential of these indices as vehicle emission-specific near-road air pollutant indicators by analyzing their correlation with black carbon (BC), a marker for mobile source air pollutants, using measurement data obtained from the Near-road Exposures and Effects of Urban Air Pollutants Study (NEXUS). The average BC concentrations during a day showed variations consistent with changes in traffic volume which were classified into high, medium, and low for the morning rush hours, the evening rush hours, and the rest of the day, respectively. The average correlation coefficients between BC concentrations and MRD, ATD, and HTD, were 0.26, 0.18, and 0.48, respectively, as compared with -0.31 and 0.25 for two commonly used traffic indicators: nearest distance to a major road and total length of the major road. HTD, which includes only heavy-duty diesel vehicles in its traffic count, gives statistically significant correlation coefficients for all near-road distances (50, 100, 150, 200, 250, and 300 m) that were analyzed. Generalized linear model (GLM) analyses show that season, traffic volume, HTD, and distance from major roads are highly related to BC measurements. Our analyses indicate that traffic density parameters may be more specific indicators of near-road BC concentrations for health risk studies. HTD is the best index for reflecting near-road BC concentrations which are influenced mainly by the emissions of heavy-duty diesel engines.
评估近路空气污染健康风险的一个重要因素是准确估计与交通相关的空气污染物车辆排放。将道路长度/面积、与道路的距离以及交通量/强度等交通参数纳入土地利用回归(LUR)模型等模型中,可以改善暴露评估。为了更好地理解车辆排放与近路空气污染之间的关系,我们评估了三个基于交通密度的指标:主要道路密度(MRD)、全交通密度(ATD)和重交通密度(HTD),分别代表缓冲区内主要道路、主要道路年平均日交通量(AADT)和主要道路商业年平均日交通量(CAADT)的比例。我们通过分析它们与黑碳(BC)的相关性来评估这些指标作为特定于车辆排放的近路空气污染物指标的潜力,黑碳是移动源空气污染物的标志物,使用从近路暴露和城市空气污染物影响研究(NEXUS)获得的测量数据进行分析。一天中的平均 BC 浓度变化与交通量的变化一致,交通量分别分为高峰时段(早高峰和晚高峰)和其余时段的高、中、低三个等级。BC 浓度与 MRD、ATD 和 HTD 的平均相关系数分别为 0.26、0.18 和 0.48,而与两个常用交通指标(距主要道路的最近距离和主要道路的总长度)的-0.31 和 0.25 相比。HTD 仅在其交通计数中包含重型柴油车辆,因此与所有近路距离(50、100、150、200、250 和 300 m)的分析均具有统计学显著的相关系数。广义线性模型(GLM)分析表明,季节、交通量、HTD 和距主要道路的距离与 BC 测量值高度相关。我们的分析表明,交通密度参数可能是健康风险研究中近路 BC 浓度的更具体指标。HTD 是反映主要受重型柴油发动机排放影响的近路 BC 浓度的最佳指标。