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Open AccessArticle
Emission Rate Estimation of Industrial Air Pollutant Emissions Based on Mobile Observation
by
Xinlei Cui
Xinlei Cui ,
Qi Yu
Qi Yu *,
Weichun Ma
Weichun Ma and
Yan Zhang
Yan Zhang
Department of Environmental Science and Engineering, Fudan University, Shanghai 200438, China
*
Author to whom correspondence should be addressed.
Atmosphere 2024, 15(8), 969; https://doi.org/10.3390/atmos15080969 (registering DOI)
Submission received: 18 July 2024
/
Revised: 7 August 2024
/
Accepted: 12 August 2024
/
Published: 13 August 2024
Abstract
Mobile observation has been widely used in the monitoring of air pollution. However, studies on pollution sources and emission characteristics based on mobile navigational observation are rarely reported in the literature. A method for quantitative source analysis for industrial air pollutant emissions based on mobile observations is introduced in this paper. NOx pollution identified in mobile observations is used as an example of the development of the method. A dispersion modeling scheme that fine-tuned the meteorological parameters according to the actual meteorological conditions was adopted to minimize the impact of uncertainties in meteorological conditions on the accuracy of small-scale dispersion modeling. The matching degree between simulated and observed concentrations was effectively improved through this optimization search. In response to the efficiency requirements of source resolution for multiple sources, a random search algorithm was first used to generate candidate solution samples, and then the solution samples were evaluated and optimized. Meanwhile, the new index was established to evaluate the quality of candidate samples, considering both numerical error and spatial distribution error of concentration, in order to address the non-uniqueness of the solution in the multi-source problem. Then, the necessity of considering the spatial distribution error of concentration is analyzed with the case study. The average values of NOx emission rates for the two study cases were calculated as 69.8 g/s and 70.8 g/s. The scores were 0.92–0.97 and 0.92–0.99. The results were close to the online monitoring data, and this kind of pollutant emission monitoring based on the mobile observation experiment was initially considered feasible. Additional analysis and clarifications were provided in the discussion section on the impact of uncertainties in meteorological conditions, the establishment of a priori emission inventories, and the interpretation of inverse calculation results.
Share and Cite
MDPI and ACS Style
Cui, X.; Yu, Q.; Ma, W.; Zhang, Y.
Emission Rate Estimation of Industrial Air Pollutant Emissions Based on Mobile Observation. Atmosphere 2024, 15, 969.
https://doi.org/10.3390/atmos15080969
AMA Style
Cui X, Yu Q, Ma W, Zhang Y.
Emission Rate Estimation of Industrial Air Pollutant Emissions Based on Mobile Observation. Atmosphere. 2024; 15(8):969.
https://doi.org/10.3390/atmos15080969
Chicago/Turabian Style
Cui, Xinlei, Qi Yu, Weichun Ma, and Yan Zhang.
2024. "Emission Rate Estimation of Industrial Air Pollutant Emissions Based on Mobile Observation" Atmosphere 15, no. 8: 969.
https://doi.org/10.3390/atmos15080969
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