Economic Implications of Air Quality Monitoring: A Video Analysis Approach

Xiao Sun^*

• The University of Queensland, Brisbane, Australia

The economic implications of air quality monitoring have become a critical concern in environmental economics, particularly in balancing economic growth with sustainable environmental policies. Traditional methods of assessing air quality and its economic impact rely heavily on stationary sensor networks and survey-based economic models, which often suffer from spatial limitations, delayed data availability, and high operational costs. These approaches fail to capture real-time variations in pollution levels and their immediate economic consequences.To address these challenges, we propose a novel video analysis approach integrated with an Eco-Regulated Market Dynamics Model (ERMDM) to enhance air quality assessment and its economic evaluation. Our method leverages advanced computer vision techniques to extract pollution indicators from video footage, combined with a dynamic market-based regulatory framework that incorporates stochastic environmental fluctuations, intertemporal optimization, and policy-induced market responses. By embedding environmental constraints into economic decision-making, the proposed model effectively balances industrial productivity with ecological sustainability. Experimental validation demonstrates that our approach provides more accurate, real-time assessments of air quality impacts on economic activities, enabling policymakers to design adaptive taxation strategies and market-driven permit allocation mechanisms. This fusion of video analysis with environmental economic modeling presents a transformative solution for sustainable economic policy formulation in response to air quality fluctuations.