Search

This study analyzed the differences in ozone (O3) sensitivity in four different urban areas in China from February 2019 to January 2020 based on data on various near-surface pollutants from passive multi-axis differential optical absorption spectroscopy (MAX-DOAS) sites and nearby China National Environmental Monitoring Center (CNEMC) sites. Across the four cities, the nitrogen dioxide (NO2) and formaldehyde (HCHO) concentrations varied seasonally. Xianghe consistently displayed the lowest NO2 levels, suggesting reduced emissions compared to other cities. Guangzhou, a city with a robust economy and a high level of vehicle ownership, exhibited higher concentrations in spring. Summer brought elevated HCHO levels in Guangzhou, Xianghe, and Shenyang due to intensified photochemical processes. Autumn and winter showed higher HCHO concentrations in Guangzhou and Xianghe compared to Lanzhou and Shenyang. Overall, Guangzhou recorded the highest annual averages, due to its developed economy, while Xianghe's lower NO2 levels were offset by the elevated HCHO due to higher O3 values. The analysis delved into primary and secondary HCHO sources across seasons and used carbon monoxide (CO) and O3 data. Xianghe showcased the dominance of secondary sources in summer and autumn, while Lanzhou was characterized by primary dominance throughout the year. Shenyang mirrored Xianghe's evolution due to industrial emissions. In Guangzhou, due to the high levels of vehicular traffic and sunlight conditions, secondary sources predominantly influenced HCHO concentrations. These findings highlight the interplay between primary and secondary emissions in diverse urban settings. This study explored O3 sensitivity variations across seasons. Xianghe exhibited a balanced distribution among volatile organic compound (VOC)-limited conditions, nitrogen oxide (NOx)-limited conditions, and transitional influences. Lanzhou was mainly affected by VOC-limited conditions in winter and NOx-limited conditions in other seasons. Shenyang's sensitivity varied with the seasons and was primarily influenced by transitions between VOCs and NOx in autumn and NOx-limited conditions otherwise. Guangzhou experienced varied influences. During periods of high O3 pollution, all regions were affected by NOx-limited conditions, indicating the necessity of NOx monitoring in these areas, especially during summer in all regions and during autumn in Xianghe and Guangzhou. [ABSTRACT FROM AUTHOR]

Pollutant transport has a substantial impact on the atmospheric environment in megacity clusters. However, owing to the lack of knowledge of vertical pollutant structure, quantification of transport processes and understanding of their impacts on the environment remain inadequate. In this study, we retrieved the vertical profiles of aerosols, nitrogen dioxide (NO 2), and formaldehyde (HCHO) using multi-axis differential optical absorption spectroscopy (MAX-DOAS) and analyzed three typical transport phenomena over the North China Plain (NCP) and Yangtze River Delta (YRD). We found the following: (1) the main transport layers (MTL) of aerosols, NO 2 , and HCHO along the southwest–northeast transport pathway in the Jing-Jin-Ji region were approximately 400–800, 0–400, and 400–1200 m, respectively. The maximum transport flux of HCHO appeared in Wangdu (WD), and aerosol and NO 2 transport fluxes were assumed to be high in Shijiazhuang (SJZ), both urban areas being significant sources feeding regional pollutant transport pathways. (2) The NCP was affected by severe dust transport on 15 March 2021. The airborne dust suppressed dissipation and boosted pollutant accumulation, decreasing the height of high-altitude pollutant peaks. Furthermore, the dust enhanced aerosol production and accumulation, weakening light intensity. For the NO 2 levels, dust and aerosols had different effects. At the SJZ and Dongying (DY) stations, the decreased light intensity prevented NO 2 photolysis and favored NO 2 concentration increase. In contrast, dust and aerosols provided surfaces for heterogeneous reactions, resulting in reduced NO 2 levels at the Nancheng (NC) and Xianghe (XH) stations. The reduced solar radiation favored local HCHO accumulation in SJZ owing to the dominant contribution of the primary HCHO. (3) Back-and-forth transboundary transport between the NCP and YRD was found. The YRD-to-NCP and NCP-to-YRD transport processes mainly occurred in the 500–1500 and 0–1000 m layers, respectively. This transport, accompanied by the dome effect of aerosols, produced a large-scale increase in PM 2.5 , further validating the haze-amplifying mechanism. [ABSTRACT FROM AUTHOR]

The transport of pollutants has a substantial impact on the atmospheric environment in megacity clusters. However, owing to the lack of knowledge of the vertical pollutant structure, our quantification of transport processes and understanding of their impacts on the environment remain inadequate. In this study, we retrieved the vertical profiles of aerosol, NO2, and HCHO using multi-axis differential optical absorption spectroscopy (MAX-DOAS) and analyzed three typical transport phenomena. We found as follows: (1) The main transport layer (MTL) of aerosol, NO2 and HCHO along the southwest–northeast transport pathway in the Jing-Jin-Ji region were approximately 400–800 m, 0–400 m and 400–1400 m, respectively. The maximum transport flux of HCHO appeared in Wangdu (WD), oppositely, the minimum transport fluxes of aerosol and NO2 also occurred in this station. (2) The North China Plain (NCP) was usually affected by severe dust transport. The transported dust suppressed dissipation and boosted pollutant accumulation, converting the vertical profiles into an exponential shape. Furthermore, dust can indirectly affect trace gas concentrations by weakening optical intensity. For stations with higher optical intensity, the reduced NO2 levels were closely associated with its heterogeneous reactions on dust and aerosol surfaces. Comparatively, for other stations with low solar radiation, the decreased optical intensity favored NO2 concentration increase by inhibiting NO2 photolysis. The reduced solar radiation favored local HCHO accumulation in Shijiazhuang (SJZ) due to the dominant contribution of primary HCHO. (3) A back-and-forth transboundary transport between the NCP and Yangtze River Delta (YRD) was found. The YRD-to-NCP and NCP-to-YRD transport processes mainly occurred in the 500–1500 m and 0–1000 m layers, respectively. This transport, accompanied by the dome effect of aerosol, produced a large-scale PM2.5 concentration increase, further validating the haze-amplifying mechanism by practical observations. [ABSTRACT FROM AUTHOR]

Since the COVID-19 outbreak in 2020, China's air pollution has been significantly affected by control measures on industrial production and human activities. In this study, we analyzed the temporal variations of NO2 concentrations during the COVID-19 lockdown and post-epidemic era in 11 Chinese megacities by using satellite and ground-based remote sensing as well as in situ measurements. The average satellite tropospheric vertical column density (TVCD) of NO2 by TROPOMI decreased by 39.2–71.93% during the 15 days after Chinese New Year when the lockdown was at its most rigorous compared to that of 2019, while the in situ NO2 concentration measured by China National Environmental Monitoring Centre (CNEMC) decreased by 42.53–69.81% for these cities. Such differences between both measurements were further investigated by using ground-based multi-axis differential optical absorption spectroscopy (MAX-DOAS) remote sensing of NO2 vertical profiles. For instance, in Beijing, MAX-DOAS NO2 showed a decrease of 14.19% (versus 18.63% by in situ) at the ground surface, and 36.24% (versus 36.25% by satellite) for the total tropospheric column. Thus, vertical discrepancies of atmospheric NO2 can largely explain the differences between satellite and in situ NO2 variations. In the post-epidemic era of 2021, satellite NO2 TVCD and in situ NO2 concentrations decreased by 10.42–64.96% and 1.05–34.99% compared to 2019, respectively, possibly related to the reduction of the transportation industry. This study reveals the changes of China's urban NO2 pollution in the post-epidemic era and indicates that COVID-19 had a profound impact on human social activities and industrial production. [ABSTRACT FROM AUTHOR]

NO 2 and O 3 simulations have great uncertainties during the COVID-19 epidemic, but their biases and spatial distributions can be improved with NO 2 assimilations. This study adopted two top-down NO X inversions and estimated their impacts on NO 2 and O 3 simulation for three periods: the normal operation period (P1), the epidemic lockdown period following the Spring Festival (P2), and back to work period (P3) in the North China Plain (NCP). Two TROPOspheric Monitoring Instrument (TROPOMI) NO 2 retrievals came from the Royal Netherlands Meteorological Institute (KNMI) and the University of Science and Technology of China (USTC), respectively. Compared to the prior NO X emissions, the two TROPOMI posteriors greatly reduced the biases between simulations with in situ measurements (NO 2 MREs: prior 85%, KNMI -27%, USTC -15%; O 3 MREs: Prior -39%, KNMI 18%, USTC 11%). The NO X budgets from the USTC posterior were 17-31% higher than those from the KNMI one. Consequently, surface NO 2 levels constrained by USTC-TROPOMI were 9-20% higher than those by the KNMI one, and O 3 is 6-12% lower. Moreover, USTC posterior simulations showed more significant changes in adjacent periods (surface NO 2 : P2 vs P1, -46%, P3 vs P2, +25%; surface O 3 : P2 vs P1, +75%, P3 vs P2, +18%) than the KNMI one. For the transport flux in Beijing (BJ), the O 3 flux differed by 5-6% between the two posteriori simulations, but the difference of NO 2 flux between P2 and P3 was significant, where the USTC posterior NO 2 flux was 1.5-2 times higher than the KNMI one. Overall, our results highlight the discrepancies in NO 2 and O 3 simulations constrained by two TROPOMI products and demonstrate that the USTC posterior has lower bias in the NCP during COVD-19., Competing Interests: The authors declare no competing financial interest., (© 2022 The Authors. Published by American Chemical Society.)