A Predictive Framework for Air Environmental Impact Evaluation of Industrial PM₁₀ Dispersion Using Atmospheric Modelling

Abstract

Industrial air quality assessment increasingly relies on predictive modelling techniques to evaluate potential environmental impacts prior to project implementation and during routine operations. Although atmospheric dispersion models are extensively applied for regulatory compliance, their integration into Environmental Impact Assessment (EIA) remains largely focused on isolated emission sources, with comparatively limited emphasis on cumulative impacts arising from multiple industrial activities. This study presents a predictive framework for assessing PM₁₀ dispersion by integrating regulatory atmospheric dispersion modelling within an Environmental Impact Assessment approach for a representative industrial facility.
The proposed framework combines emission characterization, site-specific meteorological analysis, terrain representation, numerical dispersion simulation, and environmental impact evaluation to estimate ambient PM₁₀ concentrations resulting from point, area, and transport-related emission sources. Model predictions are interpreted to identify dominant emission contributors, evaluate cumulative particulate loading, and assess compliance with applicable ambient air quality criteria. Rather than serving solely as a regulatory exercise, the modelling outcomes are utilized to support environmental planning, source prioritization, and development of practical mitigation strategies.
The assessment demonstrates that near-surface operational activities exert a greater influence on localized PM₁₀ concentrations than elevated emission sources because of differences in release characteristics and atmospheric dispersion behaviour. Predicted cumulative concentrations indicate acceptable ambient air quality under representative operating conditions while simultaneously identifying operational activities requiring focused emission control. The study highlights the potential of integrating atmospheric dispersion modelling into Environmental Impact Assessment as a practical decision-support framework for sustainable industrial development, environmental compliance, and proactive air quality management.