Sannigrahi Srikanta, Kumar Prashant, Molter Anna, Zhang Qi, Basu Bidroha, Basu Arunima Sarkar, Pilla Francesco
School of Architecture, Planning and Environmental Policy, University College Dublin Richview, Clonskeagh, Dublin, D14 E099, Ireland.
Global Centre for Clean Air Research (GCARE), Department of Civil and Environmental Engineering, Faculty of Engineering and Physical Sciences, University of Surrey, Guildford, GU2 7XH, United Kingdom; Department of Civil, Structural & Environmental Engineering, Trinity College Dublin, Dublin, Ireland.
Environ Res. 2021 May;196:110927. doi: 10.1016/j.envres.2021.110927. Epub 2021 Mar 4.
Clean air is a fundamental necessity for human health and well-being. Anthropogenic emissions that are harmful to human health have been reduced substantially under COVID-19 lockdown. Satellite remote sensing for air pollution assessments can be highly effective in public health research because of the possibility of estimating air pollution levels over large scales. In this study, we utilized both satellite and surface measurements to estimate air pollution levels in 20 cities across the world. Google Earth Engine (GEE) and Sentinel-5 Precursor TROPOspheric Monitoring Instrument (TROPOMI) application were used for both spatial and time-series assessment of tropospheric Nitrogen Dioxide (NO) and Carbon Monoxide (CO) statuses during the study period (1 February to May 11, 2019 and the corresponding period in 2020). We also measured Population-Weighted Average Concentration (PWAC) of particulate matter (PM and PM) and NO using gridded population data and in-situ air pollution estimates. We estimated the economic benefit of reduced anthropogenic emissions using two valuation approaches: (1) the median externality value coefficient approach, applied for satellite data, and (2) the public health burden approach, applied for in-situ data. Satellite data have shown that ~28 tons (sum of 20 cities) of NO and ~184 tons (sum of 20 cities) of CO have been reduced during the study period. PM, PM, and NO are reduced by ~37 (μg/m), 62 (μg/m), and 145 (μg/m), respectively. A total of ~1310, ~401, and ~430 premature cause-specific deaths were estimated to be avoided with the reduction of NO, PM, and PM. The total economic benefits (Billion US$) (sum of 20 cities) of the avoided mortality are measured as ~10, ~3.1, and ~3.3 for NO, PM, and PM, respectively. In many cases, ground monitored data was found inadequate for detailed spatial assessment. This problem can be better addressed by incorporating satellite data into the evaluation if proper quality assurance is achieved, and the data processing burden can be alleviated or even removed. Both satellite and ground-based estimates suggest the positive effect of the limited human interference on the natural environments. Further research in this direction is needed to explore this synergistic association more explicitly.
清洁空气是人类健康和福祉的基本必需品。在新冠疫情封锁期间，对人类健康有害的人为排放已大幅减少。由于有可能在大尺度上估算空气污染水平，用于空气污染评估的卫星遥感在公共卫生研究中可能非常有效。在本研究中，我们利用卫星和地面测量来估算全球20个城市的空气污染水平。谷歌地球引擎（GEE）和哨兵-5前体对流层监测仪器（TROPOMI）被用于研究期间（2019年2月1日至5月11日以及2020年相应时期）对流层二氧化氮（NO）和一氧化碳（CO）状况的空间和时间序列评估。我们还使用网格化人口数据和现场空气污染估计值来测量颗粒物（PM和PM）以及NO的人口加权平均浓度（PWAC）。我们使用两种估值方法来估算减少人为排放带来的经济效益：（1）适用于卫星数据的中位数外部性价值系数法，以及（2）适用于现场数据的公共卫生负担法。卫星数据显示，在研究期间，NO减少了约28吨（20个城市的总和），CO减少了约184吨（20个城市的总和）。PM、PM和NO分别减少了约37（μg/m）、62（μg/m）和145（μg/m）。据估计，随着NO、PM和PM的减少，分别避免了约1310例、401例和430例特定病因的过早死亡。避免的死亡所带来的总经济效益（十亿美元）（20个城市的总和），对于NO、PM和PM分别约为10、3.1和3.3。在许多情况下，发现地面监测数据不足以进行详细的空间评估。如果能实现适当的质量保证，并减轻甚至消除数据处理负担，将卫星数据纳入评估可以更好地解决这个问题。卫星和地面估计都表明有限的人类干扰对自然环境具有积极影响。需要在这个方向上进行进一步研究，以更明确地探索这种协同关联。
