A project scheduling optimization model for reducing construction dust emissions based on variability in meteorological conditions

Dust emissions from construction activities are one of the main sources of atmospheric particulate pollution, which can pose serious health risks and environmental impacts. Meteorological conditions such as wind speed, humidity, and temperature affect dust emissions per unit activity level through various mechanisms, and these conditions typically exhibit cyclical variations. This study proposes a novel scheduling optimization model to reduce construction dust emissions based on variability in meteorological conditions. Unlike in previous studies, the segmented linear function is introduced to characterize the temporal dynamics of dust emission factors driven by meteorological fluctuations. The model minimizes dust emissions and project costs and is validated through two real-scale projects where emission factors are based on historical measurements. The results demonstrate significant emission reduction without increasing project duration and cost. Further sensitivity analyses reveal that increased cost, extended deadlines, flexible commencement time, or refined time-scale emission factors enhance mitigation effects. This paper can provide decision-making references for construction entities to reduce dust emissions through project scheduling and suggestions for the government to improve related policies such as taxation.