effectiveness of ventilation strategies in reducing indoor pollutant levels in urban buildings in China

This data wasuse to evaluate the effectiveness of ventilation strategies—natural, mechanical, and mixed-mode—in reducing indoor pollutants (PM2.5, CO2, VOCs) across 12 buildings in Beijing and Shanghai over a year. Using field measurements, Computational Fluid Dynamics (CFD) modeling, and machine learning predictions, the results reveal that mechanical ventilation is the most effective in lowering pollutant levels, especially during winter when natural ventilation is limited. Hybrid systems perform well during spring and autumn, optimizing energy efficiency and air quality.

本数据集用于评估自然通风、机械通风及混合模式通风三种通风策略，在为期一年的周期内，于北京与上海的12栋建筑中降低室内污染物（PM2.5、CO₂、挥发性有机物(Volatile Organic Compounds, VOCs)）的有效性。研究采用实地测量、计算流体动力学(Computational Fluid Dynamics, CFD)建模与机器学习预测三种手段，结果显示机械通风在降低污染物浓度方面效果最优，尤其在自然通风受限的冬季。混合通风系统则在春、秋两季表现优异，可同时优化能源效率与室内空气质量。