Preprint Article Version 1 Preserved in Portico This version is not peer-reviewed

Mapping Global Surface HCHO Distribution with Confidential Interval by Satellite Observation

Version 1 : Received: 24 May 2021 / Approved: 25 May 2021 / Online: 25 May 2021 (08:58:59 CEST)

How to cite: Jin, B.; Guan, J.; Ding, Y.; Wang, W.; Li, G. Mapping Global Surface HCHO Distribution with Confidential Interval by Satellite Observation. Preprints 2021, 2021050595 (doi: 10.20944/preprints202105.0595.v1). Jin, B.; Guan, J.; Ding, Y.; Wang, W.; Li, G. Mapping Global Surface HCHO Distribution with Confidential Interval by Satellite Observation. Preprints 2021, 2021050595 (doi: 10.20944/preprints202105.0595.v1).

Abstract

Formaldehyde (HCHO) is one of the most important carcinogenic air contaminants. However, the lack of global surface concentration of HCHO monitoring is currently hindering researches on outdoor HCHO pollution. Traditional methods are either too naïve or data-demanding for a global scale research. To alleviate this issue, we trained two fully-connected neural networks respectively for deriving point and interval estimation of surface HCHO concentration in 2019, where vertical column density data from TROPOMI, in-situ data from HAPs (harmful air pollutants) monitoring network and ATom mission are utilized. Our result shows that the global surface HCHO average concentration is 2.30 μg/m3. Furthermore, in terms of regions, the concentration in Amazon Basin, North China, South-east Asia, Bay of Bengal, Central and Western Africa are among the highest. Our study makes up for the global shortage of surface HCHO monitoring and helps people have a clearer understanding of surface concentration distribution of HCHO. In addition, with the help of quality-driven algorithm, interval estimation of surface HCHO concentration is believed to bring confidence to our results. As an early work adopting interval estimation in AI-driven atmospheric pollutant research and the first to map global HCHO surface distribution, our paper will pave way for rigorous study on global ambient HCHO health risk and economic loss, thus providing basis for pollutant controlling policies worldwide.

Subject Areas

surface formaldehyde; neural network model; interval estimation; TROPOMI; global distribution

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