印度班加罗尔主干道上的两轮车CO和PM10暴露评估

Ashwin Sabapathy, K. Ragavan, S. Saksena
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引用次数: 6

摘要

本研究使用个人采样器调查了印度班加罗尔市6条标准化主干道沿线早高峰时段(9:00-11:00)和下午非高峰时段(13:00-15:00)两轮车对CO和PM10的暴露情况。还监测了当地一条远离主要道路的无车辆街道的背景水平,以确定车辆交通对辐射的实际贡献。选择道路延伸段,比较两种类型的路线-不同建筑形式特征的内动脉和外动脉的暴露。结果表明,平均背景PM10和CO浓度远低于预期的两轮车暴露的平均值。虽然PM10暴露于内动脉高于外动脉(p=0.007),但CO的差异要大得多(p<0.001)。由于拉伸段的平均运行速度具有可比性,因此PM10和CO的变化可能归因于拉伸段的不同车辆组成和构建形式特征,但这需要通过进一步的调查来验证。非峰PM10暴露低于晨峰PM10暴露(p=0.02)。然而,尽管平均运行速度相当,但非高峰时段和早高峰时段的CO暴露并没有太大差异(p=0.138),并且表明即使在非高峰时段交通量较低也会导致高暴露。各种双变量模型的结果表明,在班加罗尔,平均跑步速度是CO暴露的良好预测因子(r2 =0.56),但仅是PM10暴露的次要预测因子(r2 =0.18)。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
An Assessment of Two-Wheeler CO and PM10 Exposures Along ArterialMain Roads in Bangalore City, India
This study investigated 2-wheeler exposures to CO and PM10 along six standardized arterial main road stretches in Bangalore city in India during morning peak (9:00-11:00) and afternoon non-peak hours (13:00-15:00) using personal samplers. Background levels on a local street carrying no traffic and away from main roads were also monitored to determine the actual contributions of vehicular traffic to exposure. Road stretches were selected to compare exposures on two types of routes - inner arterials and outer arterials with different built form characteristics. Results indicate that average background PM10 and CO concentrations were much lower than the respective averages of the 2-wheeler exposures as expected. While PM10 exposures for inner arterials were higher than for outer arterials (p=0.007), differences were much larger for CO (p<0.001). Since the average run speeds were comparable for the stretches, the variations in PM10 and CO could be attributed to different vehicular compositions and built form characteristics of the stretches, but this needs to be verified through further investigation. PM10 exposures during non- peaks were lower than during morning peaks (p=0.02). However, CO exposures were not very different between non-peak hours and morning peak hours (p=0.138) despite comparable average run speeds and shows that even lower traffic volumes during non-peak hours result in high exposures. Results of various bivariate models indicate that average run speed is a good predictor of CO exposures (R 2 =0.56) but is only a minor predictor of PM10 exposures (R 2 =0.18) in Bangalore.
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