Faculty of Architecture and Urban Planning, Chongqing University, Chongqing, China.
Chongqing Real Estate Trading Centre, Chongqing, China.
Front Public Health. 2022 Apr 4;10:860107. doi: 10.3389/fpubh.2022.860107. eCollection 2022.
Ground-received solar radiation is affected by several meteorological and air pollution factors. Previous studies have mainly focused on the effects of meteorological factors on solar radiation, but research on the influence of air pollutants is limited. Therefore, this study aimed to analyse the effects of air pollution characteristics on solar radiation. Meteorological data, air quality index (AQI) data, and data on the concentrations of six air pollutants (O, CO, SO, PM, PM, and NO) in nine cities in China were considered for analysis. A city model (model-C) based on the data of each city and a unified model (model-U) based on national data were established, and the key pollutants under these conditions were identified. Correlation analysis was performed between each pollutant and the daily global solar radiation. The correlation between O and daily global solar radiation was the highest ( = 0.575), while that between SO and daily global solar radiation was the lowest. Further, AQI and solar radiation were negatively correlated, while some pollution components (e.g., O) were positively correlated with the daily global solar radiation. Different key pollutants affected the solar radiation in each city. In Shenyang and Guangzhou, the driving effect of particles on the daily global solar radiation was stronger than that of pollutants. However, there were no key pollutants that affect solar radiation in Shanghai. Furthermore, the prediction performance of model-U was not as good as that of model-C. The model-U showed a good performance for Urumqi ( = 0.803), while the difference between the two models was not particularly significant in other areas. This study provides significant insights to improve the accuracy of regional solar radiation prediction and fill the gap regarding the absence of long-term solar radiation monitoring data in some areas.
地面接收的太阳辐射受到多种气象和空气污染因素的影响。先前的研究主要集中在气象因素对太阳辐射的影响上,但对空气污染物影响的研究有限。因此,本研究旨在分析空气污染特征对太阳辐射的影响。分析了气象数据、空气质量指数(AQI)数据以及中国九个城市的六种空气污染物(O、CO、SO、PM、PM 和 NO)浓度的数据。建立了基于每个城市数据的城市模型(模型-C)和基于全国数据的统一模型(模型-U),并确定了这些条件下的关键污染物。对每个污染物与日总太阳辐射之间进行了相关分析。O 与日总太阳辐射之间的相关性最高(=0.575),而 SO 与日总太阳辐射之间的相关性最低。此外,AQI 与太阳辐射呈负相关,而一些污染成分(如 O)与日总太阳辐射呈正相关。不同的关键污染物会影响每个城市的太阳辐射。在沈阳和广州,颗粒对日总太阳辐射的驱动作用强于污染物。然而,上海没有影响太阳辐射的关键污染物。此外,模型-U 的预测性能不如模型-C。模型-U 对乌鲁木齐的表现较好(=0.803),而在其他地区,两个模型之间的差异并不特别显著。本研究为提高区域太阳辐射预测的准确性提供了重要的见解,并填补了一些地区缺乏长期太阳辐射监测数据的空白。