Characterizing spatial variations of city-wide elevated PM10 and PM2.5 concentrations using taxi-based mobile monitoring

Yu Ting Yu; Sheng Xiang; Rongbin Li; Shaojun Zhang; K Max Zhang; Shuchun Si; Xiaomeng Wu; Ye Wu

doi:10.1016/j.scitotenv.2022.154478

Characterizing spatial variations of city-wide elevated PM₁₀ and PM_2.5 concentrations using taxi-based mobile monitoring

Sci Total Environ. 2022 Jul 10:829:154478. doi: 10.1016/j.scitotenv.2022.154478. Epub 2022 Mar 10.

Authors

Yu Ting Yu¹, Sheng Xiang², Rongbin Li³, Shaojun Zhang⁴, K Max Zhang⁵, Shuchun Si⁶, Xiaomeng Wu¹, Ye Wu⁷

Affiliations

¹ School of Environment, State Key Joint Laboratory of Environment Simulation and Pollution Control, Tsinghua University, Beijing 100084, PR China.
² School of Environment, State Key Joint Laboratory of Environment Simulation and Pollution Control, Tsinghua University, Beijing 100084, PR China. Electronic address: xiangsheng@tsinghua.edu.cn.
³ Jinan Ecological Environment Protection Grid Supervision Center, Jinan 250101, PR China.
⁴ School of Environment, State Key Joint Laboratory of Environment Simulation and Pollution Control, Tsinghua University, Beijing 100084, PR China; State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex, Beijing 100084, PR China; Beijing Laboratory of Environmental Frontier Technologies, School of Environment, Tsinghua University, Beijing, 100084, China.
⁵ Sibley School of Mechanical and Aerospace Engineering, Cornell University, Ithaca, NY 14853, USA.
⁶ School of physics, Shandong University, Jinan 250100, PR China.
⁷ School of Environment, State Key Joint Laboratory of Environment Simulation and Pollution Control, Tsinghua University, Beijing 100084, PR China; State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex, Beijing 100084, PR China; Beijing Laboratory of Environmental Frontier Technologies, School of Environment, Tsinghua University, Beijing, 100084, China. Electronic address: ywu@tsinghua.edu.cn.

PMID: 35283133
DOI: 10.1016/j.scitotenv.2022.154478

Abstract

The spatial distribution of elevated particulate matter (PM) concentrations represents a public health concern due to its association with adverse health effects. In this study, a city-wide spatial variability of PM (PM₁₀ and PM_2.5) concentrations in Jinan, China is evaluated using a combination of measurements from 1700 fixed sites and taxi-based mobile monitoring (300 taxis recruited). The taxi fleet provides high spatial resolution and minimizes temporal sampling uncertainties that a single mobile platform cannot address. A big dataset of PM concentrations covering three land-use domains (roadway, community and open-field) and pollution episodes is derived from the taxi-based mobile monitoring (~3 × 10⁷ pairs of PM₁₀ and PM_2.5). The ability of taxi-based mobile monitoring to characterize location-specific concentrations is assessed. We applied an "elevation ratio" to identify the elevated PM concentrations and quantified the ratios at 30-m road segments. Higher PM concentrations occurred during haze episode with lower elevation ratios in all land-use domains compares to non-haze episode. Different characteristics (distribution and range) of the elevation ratios are shown in different land-use domains which highlight the potential local emission hotspots and could have transformative implications for environmental management, thus, contribute to the effectiveness of pollution control strategy.

Keywords: Air quality; Elevation ratio; Land-use domains; Low-cost sensors; Particulate matters.

MeSH terms

Air Pollutants* / analysis
Air Pollution* / analysis
Cities
Environmental Monitoring
Particulate Matter / analysis

Substances

Air Pollutants
Particulate Matter