Substantial nitrogen oxides emission reduction from China due to COVID-19 and its impact on surface ozone and aerosol pollution

Abstract

A top-down approach was employed to estimate the influence of lockdown measures implemented during the COVID-19 pandemic on NO x emissions and subsequent influence on surface PM 2.5 and ozone in China. The nation-wide NO x emission reduction of 53.4% due to the lockdown in 2020 quarter one in China may represent the current upper limit of China's NO x emission control. During the Chinese New Year Holiday (P2), NO x emission intensity in China declined by 44.7% compared to the preceding 3 weeks (P1). NO x emission intensity increased by 20.3% during the 4 weeks after P2 (P3), despite the unchanged NO 2 column. It recovered to 2019 level at the end of March (P4). The East China (22°N - 42°N, 102°E - 122°E) received greater influence from COVID-19. Overall NO x emission from East China for 2020 first quarter is 40.5% lower than 2019, and in P4 it is still 22.9% below the same period in 2019. The 40.5% decrease of NO x emission in 2020 first quarter in East China lead to 36.5% increase of surface O 3 and 12.5% decrease of surface PM 2.5 . The elevated O 3 promotes the secondary aerosol formation through heterogeneous pathways. We recommend that the complicated interaction between PM 2.5 and O 3 should be considered in the emission control strategy making process in the future.

The global impacts of COVID-19 lockdowns on urban air pollution

“…A variety of baseline inventories were used (Table 4), the most common being the global Emissions Database for Global Atmospheric Research (EDGAR) inventory (Crippa et al, 2020) and the Multi-resolution Emission Inventory for China (He, 2012). Many of the modeling studies adjusted their input emission inventories by scaling all emission sectors relative to changes in ambient or satellite observations (Griffith et al, 2020;Le et al, 2020a;Qiu et al, 2020;Zhang et al, 2020c;Zhang et al, 2021). Others have taken a sectorby-sector approach to scaling emission inventories (Forster et al, 2020;Le Quéré et al, 2020;Liu et al, 2020b;Menut et al, 2020;Yang et al, 2020) In general, by modeling both baseline and COVID-19perturbed emissions scenarios, the effects of meteorology can be isolated from those related to changes in emissions and can then be used to quantitatively assess the impacts of emission changes on the formation of secondary pollutants, such as O 3 and PM 2.5 .…”

“…Other studies have modeled constant or prepandemic emissions during the lockdown period to quantify the expected changes in atmospheric concentrations due to meteorology alone and thereby deduce the fraction of observed changes in air quality that are due to emission changes. Additionally, TROPOMI NO 2 vertical column densities were used to derive top-down scaling factors of NO x emission inventories (Zhang et al, 2020c;Zhang et al, 2021), which were then used to assess impacts on O 3 and PM 2.5 formation (Zhang et al, 2021). Ding et al (2020) use an inverse modeling algorithm to derive top-down NO x emissions in China.…”

“…The median transportation contribution for Annex I countries was 44% (36%-56%), 14% (8%-19%), and 25% (17%-44%) for the NO x , primary PM 2.5 , and CO emissions, respectively, whereas for Annex II countries, it was 29% (5%-49%), 9% (2%-42%), and 35% (1%-75%). Although the contribution of transportation emissions varied for the above pollutants, it is evident that East Asia China (Agarwal et al, 2020), (Bao and Zhang, 2020), a (Bauwens et al, 2020), (Chen et al, 2020c), (Diamond and Wood, 2020), (Forster et al, 2020), (Gautam, 2020a), (Griffith et al, 2020) (Zhang et al, 2021), (Liu et al, 2020b), (Liu et al, 2020c), (Wang et al, 2021), a (Su et al, 2020), (Miyazaki et al, 2020), (Huang and Sun, 2020), (Wang and Zhang, 2020), (Xu et al, 2020b), a (Park et al, 2020) Japan (Ghahremanloo et al, 2020), (Ma and Kang, 2020), a (Fu et al, 2020) South Korea (Fu et al, 2020), (Han et al, 2020), a (Ju et al, 2020), a (Bauwens et al, 2020), (Ma and Kang, 2020), a (Ghahremanloo et al, 2020) Taiwan (Forster et al, 2020) (continued)…”

“…PM 2.5 publications for the percentage change analysis and the absolute concentration change analysis. DOI: https://doi.org/10.1525/elementa.2021.00176.t6Agarwal et al, 2020),(Bao and Zhang, 2020), a (Chauhan and Singh, 2020), a(Chen et al, 2020c), a,(Le et al, 2020a), a,), a (Lian et al, 2020), a (Ma and Kang, 2020), a (Nichol et al, 2020), a (Rodríguez-Urrego and Rodríguez-Urrego, 2020), a (Shakoor et al, 2020), a (Shi and Brasseur, 2020), a (Silver et al, 2020), (Venter et al, 2020), (Wang et al, 2020b), a (Wang et al, 2020c), (Xu et al, 2020c), a (Zhang et al, 2020a), a (Zhao et al, 2020b), a (Zheng et al, 2020), a (Wang et al, 2020e), a(Fu et al, 2020),(Wang et al, 2020f), a(Wang et al, 2020a), a(Chen et al, 2020a), a(Chen et al, 2020d), a(Zhang et al, 2020d),(Wan et al, 2020), a(Lei et al, 2020), a(Xu et al, 2020c), a(Giani et al, 2020),(Yuan et al, 2021), a(Zhang et al, 2021),(Liu et al, 2020b), a(Liu et al, 2020c), a(Su et al…”

Enhancement of nanoparticle formation and growth during the COVID-19 lockdown period in urban Beijing

“…on population movement in February 2020; the period when the restrictions were enforced was also called the lockdown period (LCD). During the LCD period, the NOx emission was reduced by approximately 50% in China, as retrieved by the satellite (Zhang et al, 2021) and ground-based measurements (Huang et al, 2020). The number concentration of Aitken mode particles (~25-100 nm) should also decreased as expected, which related with the traffic emission (Deventer et al, 2018).…”