Optimization on Ventilation Time in Winter Based on Energy, Thermal Comfortable and Air Quality in Severe Cold Single-Residential Dwellings of Northeast China

In Northeast China’s severe cold regions, increasingly airtight rural dwellings face a critical challenge: traditional biomass-fueled heating and cooking generate severe indoor particulate matter (PM) pollution, creating a sharp trade-off between maintaining thermal comfort and ensuring safe indoor air quality through ventilation. While multi-objective optimization is widely applied to urban buildings, its use to develop practical, behavior-based ventilation strategies for resource-constrained rural dwellings in this context represents a significant research gap. This study integrates field measurements of occupant behavior and environmental parameters from 192 households with a coupled thermal-PM2.5 predictive model. The NSGA-II genetic algorithm was employed to perform a multi-objective optimization, balancing PM reduction against thermal comfort. The optimization reveals that short, high-intensity ventilation bursts are allowed. A typical optimized event can reduce post-cooking PM2.5 concentrations to near-guideline levels while maintaining the indoor temperature within the residents’ adaptive comfort zone. This research provides the first evidence-based, region-specific natural ventilation guidelines for these dwellings. The findings offer a practical, no-cost strategy to mitigate health risks from indoor air pollution without significant energy penalties, providing a theoretical basis for future smart ventilation system design.