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As an important source of pollutants in Beijing, biomass burning (BB) aerosols emitted by BB have a strong absorption and scattering effect on surface solar radiation (SSR). However, the existence of meteorological factors has a powerful impact on the estimation of the BB aerosol radiation effect. In this paper, a deweathered technique based on machine learning is presented to quantitatively isolate the influence of weather conditions from the radiative effect of BB aerosols. Furthermore, the seasonal trend of SSR is constrained by removing the general seasonal changes by the detrending method. The BB event on October 7–11, 2014, in Beijing was used as a case to validate the effectiveness of the proposed method. Experimental results show that meteorological factors aggravate the influence of BB events on SSR. Specifically, during the BB event, meteorological factors led to an additional increase of 10.9% in diffuse radiation and an additional decrease of 17.5%, 13.1%, 181.3%, 9.7% and 86.9% in global radiation, net radiation, horizontal direct radiation, reflected radiation and vertical direct radiation, respectively. After isolating the impact of meteorological factors on SSR in the BB event, we found that the average effects of BB aerosols on global radiation, net radiation, diffuse radiation, horizontal direct solar radiation, reflected radiation and vertical direct solar radiation during the BB event were −35.6 Wm−2 (−3.1 MJm−2day−1), −14.1 Wm−2 (−1.2 MJm−2day−1), 20.7 Wm−2 (1.8 MJm−2day−1), −67.3 Wm−2 (−5.8 MJm−2day−1), −8.9 Wm−2 (−0.8MJm−2day−1), and −132.9 Wm−2 (−11.5 MJm−2day−1), respectively. In conclusion, the weather normalization and detrended methods in this study provide a new idea for the accurate estimation of the impact of aerosols on SSR. This provides a quantitative reference for further understanding the impacts of atmospheric pollution on SSR. • The impact of meteorology on surface solar radiation is decoupled by weather normalization. • The seasonal trend of surface solar radiation in this study is removed by the detrending method. • The diffuse radiation increased up to 20.7 Wm−2 during the biomass burning (BB) event. • The global radiation decreased by 36.5 Wm−2 due to BB aerosols. [ABSTRACT FROM AUTHOR]

Emergency responses to the COVID-19 pandemic led to major changes in travel behaviours and economic activities in 2020. Machine learning provides a reliable approach for assessing the contribution of these changes to air quality. This study investigates impacts of health protection measures upon air pollution and traffic emissions and estimates health and economic impacts arising from these changes during two national 'lockdown' periods in Oxford, UK. Air quality improvements were most marked during the first lockdown with reductions in observed NO 2 concentrations of 38% (SD ± 24.0%) at roadside and 17% (SD ± 5.4%) at urban background locations. Observed changes in PM 2.5, PM 10 and O 3 concentrations were not significant during first or second lockdown. Deweathering and detrending analyses revealed a 22% (SD ± 4.4%) reduction in roadside NO 2 and 2% (SD ± 7.1%) at urban background with no significant changes in the second lockdown. Deweathered-detrended PM 2.5 and O 3 concentration changes were not significant, but PM 10 increased in the second lockdown only. City centre traffic volume reduced by 69% and 38% in the first and second lockdown periods. Buses and passenger cars were the major contributors to NO 2 emissions, with relative reductions of 56% and 77% respectively during the first lockdown, and less pronounced changes in the second lockdown. While car and bus NO 2 emissions decreased during both lockdown periods, the overall contribution from buses increased relative to cars in the second lockdown. Sustained NO 2 emissions reduction consistent with the first lockdown could prevent 48 lost life-years among the city population, with economic benefits of up to £2.5 million. Our findings highlight the critical importance of decoupling emissions changes from meteorological influences to avoid overestimation of lockdown impacts and indicate targeted emissions control measures will be the most effective strategy for achieving air quality and public health benefits in this setting. [Display omitted] • Roadside NO 2 concentrations reduced by 22% in the first lockdown period only. • NO 2 emissions from buses and cars reduced by 56% and 77% during the first lockdown. • PM 10 concentrations increased signficantly during the second lockdown only. • Lockdown related NO 2 reductions could save 48 life-years and up to £2.5 million. • Targeted emissions control measures are needed to deliver public health benefits. [ABSTRACT FROM AUTHOR]