Evaluates pollutant emission heights in industrial parks, indicating strategies for improved air quality.
As industrial parks face increasing pressure to balance economic development with environmental sustainability, optimizing emission strategies becomes critical for achieving sustainable development goals. In this study, a pollutant dispersion module is coupled with the WRF-FDDA-LES (Weather Research and Forecasting four-dimensional data assimilation and large-eddy simulation) to establish a multiscale air quality model for the Pengzhou Industrial Park, Sichuan, China, hereafter referred to as PZ-LESTD. Using PZ-LESTD, the study conducts refined large-eddy simulations of pollutant dispersion from elevated sources in the industrial park on 23 August 2022. The capability of the model in simulating large-scale weather conditions and pollutant transport, together with its performance in refined-grid LES of elevated emission dispersion, is evaluated. Sensitivity experiments with different pollutant emission heights are also carried out. The results demonstrate that the model can satisfactorily reproduce large-scale meteorological variables and pollutant distributions over China and achieve high accuracy in the refined LES simulations. Analysis of the simulated dispersion processes of elevated sources indicates that the current elevated emission strategy in the Pengzhou Industrial Park is effective in mitigating the impact of industrial exhaust on surface air quality in the park and surrounding areas. Sensitivity tests of emission heights reveal that source heights of 20 m to 50 m can significantly reduce impacts on nearby ambient air quality, whereas increasing the source height from 50 m to 160 m results in only minor differences in surface-level pollution, although higher emission sources lead to greater horizontal transport of pollutants. This study provides scientific evidence for sustainable industrial planning and emission management strategies, supporting the transition towards environmentally sustainable industrial parks. The findings contribute to evidence-based policymaking for air pollution prevention and control, facilitating the achievement of sustainable development goals through optimized industrial emission layouts and green industrial transformation.
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Yang et al. (2026) studied this question.
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