Environmental Defense Fund , 257 Park Avenue South , New York , New York 10010 , United States.
Civil and Environmental Engineering , Rice University , 6100 Main Street , Houston , Texas 77005 , United States.
Environ Sci Technol. 2020 Feb 18;54(4):2133-2142. doi: 10.1021/acs.est.9b05523. Epub 2020 Jan 29.
Diverse urban air pollution sources contribute to spatially variable atmospheric concentrations, with important public health implications. Mobile monitoring shows promise for understanding spatial pollutant patterns, yet it is unclear whether uncertainties associated with temporally sparse sampling and instrument performance limit our ability to identify locations of elevated pollution. To address this question, we analyze 9 months of repeated weekday daytime on-road mobile measurements of black carbon (BC), particle number (PN), and nitrogen oxide (NO, NO) concentrations within 24 census tracts across Houston, Texas. We quantify persistently elevated, intermittent, and extreme concentration behaviors at 50 m road segments on surface streets and 90 m segments on highways relative to median statistics across the entire sampling domain. We find elevated concentrations above uncertainty levels (±40%) within portions of every census tract, with median concentration increases ranging from 2 to 3× for NO, and >9× for NO. In contrast, PN exhibits elevated concentrations of 1.5-2× the domain-wide median and distinct spatial patterns relative to other pollutants. Co-located elevated concentrations of primary combustion tracers (BC and NO) near 30% of metal recycling and concrete batch plant facilities within our sampled census tracts are comparable to those measured within 200 m of highways. Our results demonstrate how extensive mobile monitoring across multiple census tracts can quantitatively characterize urban air pollution source patterns and are applicable to developing effective source mitigation policies.
不同的城市空气污染源导致大气浓度具有空间变异性，对公共健康有重要影响。移动监测对于了解空间污染物模式具有很大的潜力，但尚不清楚与时间稀疏采样和仪器性能相关的不确定性是否限制了我们识别污染升高地点的能力。为了解决这个问题，我们分析了德克萨斯州休斯顿市 24 个普查区内 9 个月的重复工作日白天的道路移动监测数据，监测了黑碳（BC）、颗粒物数（PN）和氮氧化物（NO、NO）浓度。我们量化了在街道和高速公路上 50 米和 90 米的道路段中，相对于整个采样区域的中位数统计数据，存在持续升高、间歇性和极端浓度的行为。我们发现，在每个普查区的部分地区，浓度高于不确定性水平（±40%），NO 的中位数浓度增加了 2-3 倍，NO 的中位数浓度增加了>9 倍。相比之下，PN 的浓度比整个区域的中位数高 1.5-2 倍，且与其他污染物相比具有明显的空间模式。在我们采样的普查区内，约 30%的金属回收和混凝土搅拌站附近存在与主要燃烧示踪剂（BC 和 NO）浓度升高的情况，这与在离高速公路 200 米范围内测量到的浓度相当。我们的研究结果表明，在多个普查区内进行广泛的移动监测可以定量描述城市空气污染的源模式，这对于制定有效的源缓解政策是适用的。
