PDF(Pubmed)
Abstract：
Driven by industrialization and urbanization, urban air pollution can increase respiratory, heart, and cerebrovascular diseases, and thus mortality rates; as such, it is necessary to improve air quality through the consideration of individual pollutants and emission sources. In Republic of Korea, national and local governments have installed urban and roadside air quality monitoring systems. However, stations are lacking outside metropolitan regions, and roadside stations are sparsely distributed, limiting comparisons of pollutant concentrations with vehicle traffic and floating population levels. Local governments have begun using mobile laboratories (MLs) to supplement the fixed measurement network and investigate road pollution source characteristics based on their spatiotemporal distribution; however, the collected data cannot be used effectively if they are not visualized. Here, we propose a method to collect and visualize global information system (GIS)-based air quality data overlayed with environmental variables to support air quality management measures. Spatiotemporal analyses of ML-derived data from Bucheon, Korea, confirmed that particulate and gaseous pollutant concentrations were high during typical commuting hours, at intersections, and at a specially managed road. During commuting hours, the maximum PM10 concentration reached 200.7 µg/m3 in the Nae-dong, Gyeongin-ro, and Ojeong-dong ready-mix concrete complex areas, and the maximum PM2.5 concentration was 161.7 µg/m3. The maximum NOx, NO2, and NO levels of 1.34 ppm, 0.18 ppm, and 1.18 ppm, respectively, were also detected during commuting hours. These findings support the need for targeted management of air pollution in this region, and highlight the benefit of comprehensively comparing road levels, driving speed, and traffic levels when identifying hotspots of air pollution. Such analyses will contribute to the development of air quality management measures customized to regional characteristics.
摘要：
在工业化和城市化的推动下，城市空气污染会增加呼吸，心,和脑血管疾病，因此死亡率；因此，有必要通过考虑单个污染物和排放源来改善空气质量。在大韩民国,国家和地方政府已经安装了城市和路边空气质量监测系统。然而,大都市地区以外缺乏车站，路边车站分布稀疏，限制污染物浓度与车流量和流动人口水平的比较。地方政府已开始使用移动实验室（MLs）来补充固定的测量网络，并根据其时空分布调查道路污染源特征；但是，如果不可视化，则无法有效使用收集的数据。这里,我们提出了一种方法来收集和可视化基于全球信息系统（GIS）的空气质量数据，并覆盖环境变量，以支持空气质量管理措施。来自Bucheon的ML衍生数据的时空分析，韩国,确认在典型的通勤时间内，颗粒物和气态污染物浓度很高，在十字路口，在一条特别管理的道路上。在通勤时间，Nae-dong的最大PM10浓度达到200.7µg/m3，庆金罗,和Ojeong-dong预拌混凝土复杂区域，最大PM2.5浓度为161.7µg/m3。最大NOx,NO2和NO含量为1.34ppm，0.18ppm,和1.18ppm，分别,在通勤时间也被检测到。这些发现支持有针对性地管理该地区的空气污染的必要性，突出全面比较道路等级的好处，行驶速度,以及确定空气污染热点时的交通水平。此类分析将有助于制定针对区域特征的空气质量管理措施。
