In this study,a hybrid model,the convolutional neural network-support vector regression model,was adopted to achieve prediction of the NO_(2)profile in Nanjing from January 2019to March 2021.Given the sudden decline i...In this study,a hybrid model,the convolutional neural network-support vector regression model,was adopted to achieve prediction of the NO_(2)profile in Nanjing from January 2019to March 2021.Given the sudden decline in NO_(2)in February 2020,the contribution of the Coronavirus Disease-19(COVID-19)lockdown,Chinese New Year(CNY),and meteorologi cal conditions to the reduction of NO_(2)was evaluated.NO_(2)vertical column densities(VCDs) from January to March 2020 decreased by 59.05%and 32.81%,relative to the same period in 2019 and 2021,respectively.During the period of 2020 COVID-19,the average NO_(2)VCDs were 50.50%and 29.96%lower than those during the pre-lockdown and post-lockdown pe riods,respectively.The NO_(2)volume mixing ratios(VMRs)during the 2020 COVID-19 lock down significantly decreased below 400 m.The NO_(2)VMRs under the different wind fields were significantly lower during the lockdown period than during the pre-lockdown period This phenomenon could be attributed to the 2020 COVID-19 lockdown.The NO_(2)VMRs be fore and after the CNY were significantly lower in 2020 than in 2019 and 2021 in the same period,which further proves that the decrease in NO_(2)in February 2020 was attributed to the COVID-19 lockdown.Pollution source analysis of an NO_(2)pollution episode during the lockdown period showed that the polluted air mass in the Beijing-Tianjin-Hebei was trans ported southwards under the action of the north wind,and the subsequent unfavorable meteorological conditions(local wind speed of<2.0 m/sec)resulted in the accumulation o pollutants.展开更多
基金supported by the National Natural Science Foundation of China(Nos.U19A2044,42105132,42030609,41975037)the National Key Research and Development Program of China(No.2022YFC3700303)。
文摘In this study,a hybrid model,the convolutional neural network-support vector regression model,was adopted to achieve prediction of the NO_(2)profile in Nanjing from January 2019to March 2021.Given the sudden decline in NO_(2)in February 2020,the contribution of the Coronavirus Disease-19(COVID-19)lockdown,Chinese New Year(CNY),and meteorologi cal conditions to the reduction of NO_(2)was evaluated.NO_(2)vertical column densities(VCDs) from January to March 2020 decreased by 59.05%and 32.81%,relative to the same period in 2019 and 2021,respectively.During the period of 2020 COVID-19,the average NO_(2)VCDs were 50.50%and 29.96%lower than those during the pre-lockdown and post-lockdown pe riods,respectively.The NO_(2)volume mixing ratios(VMRs)during the 2020 COVID-19 lock down significantly decreased below 400 m.The NO_(2)VMRs under the different wind fields were significantly lower during the lockdown period than during the pre-lockdown period This phenomenon could be attributed to the 2020 COVID-19 lockdown.The NO_(2)VMRs be fore and after the CNY were significantly lower in 2020 than in 2019 and 2021 in the same period,which further proves that the decrease in NO_(2)in February 2020 was attributed to the COVID-19 lockdown.Pollution source analysis of an NO_(2)pollution episode during the lockdown period showed that the polluted air mass in the Beijing-Tianjin-Hebei was trans ported southwards under the action of the north wind,and the subsequent unfavorable meteorological conditions(local wind speed of<2.0 m/sec)resulted in the accumulation o pollutants.
