Abstract
The real-world monitoring system of air pollution ordinarily collects data about pollutant concentration levels at pollution sources and monitors stations in a high-frequency manner. Inspired atmospheric models, the meteorological conditions could play an important role in building up the data-driven model for dispersing atmospheric pollutants from pollution sources to monitor stations. We propose a varying-coefficient model to analyze how emissions of monitor stations are influenced by pollution sources with changing with the wind speed. To estimate the unknown coefficient curves, we use a spline basis to approximate the functions. The asymptotic properties of the proposed method are studied and show the consistency of the estimator. Inference procedures based on a resampling subject bootstrap is developed to construct the conservative confidence bands. A simulation study is carried out to demonstrate the performance of our method. Illustrated by a real-world dataset of environmental sensors collected in Shenyang, China, the proposed varying-coefficient model reveals that the wind speed changes the dispersion mechanism of atmospheric pollutants between monitor stations and pollution sources.
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Data availability
The data are provided on GitHub at https://github.com/rucwyf/VCMData.
Code Availability
Code upon request.
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Acknowledgements
The authors thank the editor, the associate editor, and the reviewers for their comments that helped significantly improve this work. This research was supported by the National Key R &D Program of China (Grant No. 2018YFC2000302), by Public Computing Cloud, Renmin University of China, and partially by the National Natural Science Foundation of China (Grant No. 11801560).
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Conceptualization and data preparation: HY; Methodology: KH;Simulation and real data analysis:YW and WS;Writing—original draft preparation: KH and WS; Writing—review and editing: KH, YW and HY.
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Handling Editor Pierre Dutilleul.
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He, K., Wang, Y., Su, W. et al. A varying-coefficient regression approach to modeling the effects of wind speed on the dispersion of pollutants. Environ Ecol Stat 29, 433–452 (2022). https://doi.org/10.1007/s10651-022-00535-6
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DOI: https://doi.org/10.1007/s10651-022-00535-6