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An investigation on the attenuation effect of air pollution on regional solar radiation

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  • Zhang, Chunxiao
  • Shen, Chao
  • Yang, Qianru
  • Wei, Shen
  • Lv, Guoquan
  • Sun, Cheng

Abstract

Due to the continuous increase of environmental pollution in recent years, the high concentration of particulate matters in air has greatly reduced the amount of solar radiation that can reach the earth, and this reduction has a direct effect on the use of solar energy in buildings. To quantify this attenuation effect, historical meteorological data collected from five regions, namely, Beijing, Tianjin, Jinan, Xi’an and Zhengzhou, in China from 2014 to 2016 were used to investigate the correlation between clearness index (reflecting available radiation) and air quality index (reflecting pollution level). The analysis results have revealed that higher air quality index would result in lower clearness index, and the sunny days gave higher decreasing rate than cloudy days. For all five regions, their monthly clearness index attenuation showed higher values in winter than that in summer. The monthly solar radiation attenuation, however, showed an opposite trend, due to higher solar altitude in summer. Additionally, different regions had different annual solar radiation attenuation ratio, with Tianjin giving the highest of 6.56% (651.17 MJ/m2), followed by Beijing (3.92%, 410.08 MJ/m2), Xi’an (4.94%, 510.42 MJ/m2), Zhengzhou (3.99%, 427.64 MJ/m2) and Jinan (2.69%, 284.66 MJ/m2).

Suggested Citation

  • Zhang, Chunxiao & Shen, Chao & Yang, Qianru & Wei, Shen & Lv, Guoquan & Sun, Cheng, 2020. "An investigation on the attenuation effect of air pollution on regional solar radiation," Renewable Energy, Elsevier, vol. 161(C), pages 570-578.
    • Handle: RePEc:eee:renene:v:161:y:2020:i:c:p:570-578
    DOI: 10.1016/j.renene.2020.07.146
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    References listed on IDEAS

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    3. Lu, Yunbo & Wang, Lunche & Zhu, Canming & Zou, Ling & Zhang, Ming & Feng, Lan & Cao, Qian, 2023. "Predicting surface solar radiation using a hybrid radiative Transfer–Machine learning model," Renewable and Sustainable Energy Reviews, Elsevier, vol. 173(C).
    4. Kong, Xiangfei & Zhang, Lanlan & Li, Han & Wang, Yongzhen & Fan, Man, 2022. "Effect of solar energy concentrating and phase change cooling on energy and exergy performance improvement of photovoltaic/thermal systems," Renewable Energy, Elsevier, vol. 197(C), pages 1251-1263.
    5. Jia, Dongyu & Yang, Liwei & Lv, Tao & Liu, Weiping & Gao, Xiaoqing & Zhou, Jiaxin, 2022. "Evaluation of machine learning models for predicting daily global and diffuse solar radiation under different weather/pollution conditions," Renewable Energy, Elsevier, vol. 187(C), pages 896-906.
    6. Cheng, Xinghong & Ye, Dong & Shen, Yanbo & Li, Deping & Feng, Jinming, 2022. "Studies on the improvement of modelled solar radiation and the attenuation effect of aerosol using the WRF-Solar model with satellite-based AOD data over north China," Renewable Energy, Elsevier, vol. 196(C), pages 358-365.
    7. Zhang, Chunxiao & Shen, Chao & Wei, Shen & Zhang, Yingbo & Sun, Cheng, 2021. "Flexible management of heat/electricity of novel PV/T systems with spectrum regulation by Ag nanofluids," Energy, Elsevier, vol. 221(C).

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