Evaluating deep learning time series models for PM2.5 forecasting across diverse horizons

The study area is located at Chengdu, Sichuan Province , encompassing five air quality monitoring stations and two meteorological monitoring stations that provide air quality and meteorological data, respectively. The five air quality monitoring stations consist of Shilidian station (1432A), Shahepu station (1434A), Renmin Park station (1437A), Dashi West station (2880A), Sanwayao station (1433A). Datasets for NO2, CO, SO2, O3, and PM2.5 are collected from the five air quality stations mentioned above, ranging from November 1st 2022 to October 31th 2024. The two meteorological stations, Wenjiang station and Shuangliu station, provided datasets of temperature (T), pressure (P), relative humidity (RH), precipitation (Prec) and wind speed (WS) are collected over the same period. Average values from five air quality stations and the two metrological stations were used to represent the overall spatial quality and meteorological data for the study area, respectively.研究区域位于四川省成都市，共涵盖5个空气质量监测站与2个气象监测站，二者分别提供空气质量与气象观测数据。5个空气质量监测站依次为十里店站（1432A）、沙河铺站（1434A）、人民公园站（1437A）、大石西路站（2880A）以及三瓦窑站（1433A）。本数据集采集了上述5个空气质量监测站在2022年11月1日至2024年10月31日期间的二氧化氮（NO2）、一氧化碳（CO）、二氧化硫（SO2）、臭氧（O3）与PM2.5观测数据。2个气象监测站为温江站与双流站，同期采集了气温（T）、气压（P）、相对湿度（RH）、降水量（Prec）以及风速（WS）的观测数据集。研究分别以5个空气质量监测站的平均数据、2个气象监测站的平均数据，代表研究区域整体的空气质量与气象空间分布特征。