重庆理工大学学报2024，Vol.38Issue(5)：308-317,10.DOI:10.3969/j.issn.1674-8425(z).2024.03.034
结合大气污染特征的VOCs聚集区识别方法
A method for identifying VOCs aggregation areas based on the characteristics of air pollution
摘要
Abstract
To achieve precise perception and recognition of VOCs aggregation areas, this paper proposes a VOCs aggregation area recognition method combining air pollution characteristics. First, the regional grid is partitioned and the IDW spatial interpolation method is employed to obtain the VOCs grid dataset. Second, HYSPLIT is used to calculate the trajectory of the backward air mass and VGG is introduced to extract trajectory features. The same dataset is input into the TCN-BiLSTM model to predict the VOCs concentration in each grid. Finally, the clustering area is identified based on the predicted results. In Beilin District in Xi'an, the concentration values of VOCs is predicted and the identification results of aggregation areas are visualized. Our results show the combined prediction model effectively improves the recognition accuracy. The MAE, MSE, RMSE, and R2 of the VOCs concentration prediction results are 6.657, 103.657, 10.181, and 0.976 respectively, which are superior to those of the comparison model. Through ablation experiments, it proves a consideration of the characteristics of air mass pollution effectively improves the accuracy of VOCs prediction and achieves accurate perception and recognition of VOCs aggregation areas.关键词
VOCs聚集/污染区域识别/浓度预测/大气污染特征/深度学习Key words
aggregation of VOCs/identification of contaminated areas/concentration prediction/characteristics of atmospheric pollution/deep learning分类
资源环境引用本文复制引用
陆秋琴,田园,黄光球..结合大气污染特征的VOCs聚集区识别方法[J].重庆理工大学学报,2024,38(5):308-317,10.基金项目
陕西省哲学社会科学研究专项"我省实现双碳目标转型成本及操作风险研究"(2022HZ1555) （2022HZ1555）
