State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, Wuhan 430079, China.
Collaborative Innovation Center of Geospatial Technology, Wuhan University, Wuhan 430079, China.
Int J Environ Res Public Health. 2020 Jul 4;17(13):4828. doi: 10.3390/ijerph17134828.
Aiming at improving the air quality and protecting public health, policies such as restricting factories, motor vehicles, and fireworks have been widely implemented. However, fine-grained spatiotemporal analysis of these policies' effectiveness is lacking. This paper collected the hourly meteorological and PM data for three typical emission scenarios in Hubei, Beijing-Tianjin-Hebei (BTH), and Yangtze River Delta (YRD). Then, this study simulated the PM concentration under the same meteorological conditions and different emission scenarios based on a reliable hourly spatiotemporal random forest model (R2 exceeded 0.84). Finally, we investigated the fine-grained spatiotemporal impact of restricting factories, vehicles, and fireworks on PM concentrations from the perspective of hours, days, regions, and land uses, excluding meteorological interference. On average, restricting factories and vehicles reduced the PM concentration at 02:00, 08:00, 14:00, and 20:00 by 18.57, 16.22, 25.00, and 19.07 μg/m3, respectively. Spatially, it had the highest and quickest impact on Hubei, with a 27.05 μg/m3 decrease of PM concentration and 17 day lag to begin to show significant decline. This was followed by YRD, which experienced a 23.52 μg/m3 decrease on average and a 23 day lag. BTH was the least susceptible; the PM concentration decreased by only 8.2 μg/m3. In addition, influenced by intensive human activities, the cultivated, urban, and rural lands experienced a larger decrease in PM concentration. These empirical results revealed that restricting factories, vehicles, and fireworks is effective in alleviating air pollution and the effect showed significant spatiotemporal heterogeneity. The policymakers should further investigate influential factors of hourly PM concentrations, combining with local geographical and social environment, and implement more effective and targeted policies to improve local air quality, especially for BTH and the air quality at morning and night.
针对改善空气质量和保护公众健康，已广泛实施了限制工厂、机动车和烟花等政策。然而，这些政策效果的细粒度时空分析仍存在不足。本研究收集了湖北、京津冀和长三角三个典型排放情景的每小时气象和 PM 数据。然后，基于可靠的每小时时空随机森林模型（R2 超过 0.84），模拟了相同气象条件下不同排放情景下的 PM 浓度。最后，从小时、天、区域和土地利用等角度，排除气象干扰，研究了限制工厂、车辆和烟花对 PM 浓度的细粒度时空影响。平均而言，限制工厂和车辆分别使 02:00、08:00、14:00 和 20:00 的 PM 浓度降低了 18.57、16.22、25.00 和 19.07μg/m3。空间上，对湖北的影响最大、最快，PM 浓度下降了 27.05μg/m3，且 17 天后开始显著下降。其次是长三角，平均下降了 23.52μg/m3，滞后了 23 天。京津冀的敏感性最低，PM 浓度仅下降了 8.2μg/m3。此外，受密集人类活动的影响，耕地、城市和农村土地的 PM 浓度下降幅度更大。这些实证结果表明，限制工厂、车辆和烟花的政策对于缓解空气污染是有效的，且效果具有显著的时空异质性。政策制定者应进一步研究每小时 PM 浓度的影响因素，结合当地地理和社会环境，实施更有效和有针对性的政策，以改善当地空气质量，特别是京津冀地区和早晚空气质量。
