Spatiotemporal variations and reduction of air pollutants during the COVID-19 pandemic in a megacity of Yangtze River Delta in China

Measurement of the vertical distributions of atmospheric pollutants using an uncrewed aerial vehicle platform in Xi'an, China

Vertical observations of atmospheric pollutants play crucial roles in a comprehensive understanding of the distribution characteristics and transport of atmospheric pollutants. A hexacopter uncrewed aerial vehicle equipped with miniature monitors was employed to measure the vertical distribution of atmospheric pollutants within a height of 1000 m at a rural site in Xi'an, China, in 2021. The concentrations of carbon monoxide (CO) and particulate matter (PM) showed generally decreasing trends with increasing height. The ozone (O3) concentration showed a general increasing trend with height followed by a gradual decreasing trend. Vertical decrements of PM2.5 and CO from 0 to 1000 m were significantly (p < 0.05) lower on observation days during summer (14.0 ± 8.1 μg m-3 and 8.7 ± 6.6 ppb, respectively), compared with those in winter (78.3 ± 14.1 μg m-3 and 34.8 ± 17.3 ppb, respectively). The horizontal transport of PM and CO mostly occurred in the morning and at night during winter observations at an altitude of 400-500 m. During the winter haze, the PM and CO profile concentrations below 500 m increased substantially with the decrease in the height of the thermal inversion layer. Vertical O3 transportation was observed in the afternoon and evening during summer, and a ∼37.7% (11.6 ppb) increase in ground-level O3 was observed in relation to vertical transport from the upper atmosphere. The results provide insights into the vertical distribution and transport of atmospheric pollutants in rural areas near cities.

Research on ozone formation sensitivity based on observational methods: Development history, methodology, and application and prospects in China

Observation-based method for O3 formation sensitivity research is an important tool to analyze the causes of ground-level O3 pollution, which has broad application potentials in determining the O3 pollution formation mechanism and developing prevention and control strategies. This paper outlined the development history of research on O3 formation sensitivity based on observational methods, described the principle and applicability of the methodology, summarized the relative application results in China and provided recommendations on the prevention and control of O3 pollution in China based on relevant study results, and finally pointed out the shortcomings and future development prospects in this field in China. The overview study showed that the O3 formation sensitivity in some urban areas in China in recent years presented a gradual shifting tendency from the VOC-limited regime to the transition regime or the NOx-limited regime due to the implementation of the O3 precursors emission reduction policies; O3 pollution control strategies and precursor control countermeasures should be formulated based on local conditions and the dynamic control capability of O3 pollution control measures should be improved. There are still some current deficiencies in the study field in China. Therefore, it is recommended that a stereoscopic monitoring network for atmospheric photochemical components should be further constructed and improved; the atmospheric chemical mechanisms should be vigorously developed, and standardized methods for determining the O3 formation sensitivity should be established in China in the near future.

Influence of pollution control measures on the reduction of black carbon in an urban site of megacity, Tianjin, China based on ground-monitored and MERRA-2 reanalysis data

The concentration of particulate matter (PM) has been reduced significantly with the implementation of air pollution control plans in Tianjin. However, as an important component of PM that can lead to global warming and adverse health effects, the influence of pollution control measures (PCM) on black carbon (BC) has been less studied. In this study, ten years of BC concentration satellite-based reanalysis data were collected from MERRA-2 (Modern-Era Retrospective Analysis for Research and Applications, Version 2), and their reliability was verified using ground-monitored BC data. Using the proposed Kolmogorov-Zurbenko and artificial neural network (KZ-ANN) model, the influences of meteorology and emission measures were separated. The results indicated that the overall meteorological conditions were not conducive to BC diffusion, especially in autumn and winter with low temperature, surface solar radiation, boundary layer height, and high atmospheric pressure, all of which increased the BC concentration. This study also found that although a significant reduction in BC emissions was observed in Tianjin (the total emissions of BC in 2020 dropped by 52 % compared with the level in 2013), the change in emission-influenced BC was relatively low (the concentration of emission-influenced BC in 2022 dropped by only 2.39 % compared to that in 2013). The reduction of emission-influenced BC concentration during the air pollution prevention control and action plan (APPC) was higher than the level during of the three-year action plan for winning the blue sky defense war (abbreviated as the Blue Sky Defense War). In addition, the lockdown measures during the Corona Virus Disease 2019 (COVID-19) did not have beneficial effect on the reduction of emission-influenced BC concentration. This phenomenon can be explained by the long-range transport of BC from surrounding areas, which was also proven by the results of the backward trajectory analysis. Therefore, efforts on emissions reduction in Tianjin were diminished. It is necessary to cooperate with the governments in surrounding areas to implement joint BC control measures, especially in autumn and winter.

Characterizing accumulation and negative effects of aerosol particles on the leaves of urban trees

Urban vegetation can alleviate particulate matter (PM) pollution. Many studies examined the PM retention efficiencies of different plant species, but the PM changes retained on leaf surfaces and their effects on plant leaves have rarely been explored. In this study, two common urban greening tree species of the Yangtze River Delta (i.e., Broussonetia papyrifera and Osmanthus fragrans) were selected to explore the compositions of retained PM and assess their adverse impacts on leaf functional traits. Compared with B. papyrifera, O. fragrans with higher wax content was more efficient in particle accumulation, specifically fine (Φ ≤ 2.5 μm) and coarse (2.5 < Φ ≤ 10 μm) particles. The number density and mass concentration of retained PM on plant leaves tended to increase during the accumulation period. Plant species and accumulation time were two major factors to influence particle retention efficiency. Interestingly, the accumulation of particle retention influenced leaf functional traits, such as photosynthesis rate, stomatal conductance, and transpiration rate. The microscopic observations of PM on leaves confirmed that the toxic components of the retained particles potentially caused leaf injury and stomatal damage. Therefore, the acclimation mechanisms of plants responding to the retained urban aerosols should be paid attention in highly polluted areas.

Long-term spatiotemporal evolution and coordinated control of air pollutants in a typical mega-mountain city of Cheng-Yu region under the "dual carbon" goal

Clarifying the spatiotemporal distribution and impact mechanism of pollution is the prerequisite for megacities to formulate relevant air pollution prevention and control measures and achieve carbon neutrality goals. Chongqing is one of the dual-core key megacities in Cheng-Yu region and as a typical mountain-city in China, environmental problems are complex and sensitive. This research aims to investigate the exceeding standard levels and spatio-temporal evolution of criteria pollutants between 2014 and 2020. The results indicated that PM10, PM2.5, CO and SO2 were decreased significantly by 45.91%, 52.86%, 38.89% and 66.67%, respectively. Conversely, the concentration of pollutant O3 present a fluctuating growth and found a "seesaw" phenomenon between it and PM. Furthermore, PM and O3 are highest in winter and summer, respectively. SO2, NO2, CO, and PM showed a "U-shaped", and O3 showed an inverted "U-shaped" seasonal variation. PM and O3 concentrations are still far behind the WHO, 2021AQGs standards. Significant spatial heterogeneity was observed in air pollution distribution. These results are of great significance for Chongqing to achieve "double control and double reduction" of PM2.5 and O3 pollution, and formulate a regional carbon peaking roadmap under climate coordination. Besides, it can provide an important platform for exploring air pollution in typical terrain around the world and provide references for related epidemiological research.Implications: Chongqing is one of the dual-core key megacities in Cheng-Yu region and as a typical mountain city, environmental problems are complex and sensitive. Under the background of the "14th Five-Year Plan", the construction of the "Cheng-Yu Dual-City Economic Circle" and the "Dual-Carbon" goal, this article comprehensively discussed the annual and seasonal excess levels and spatiotemporal evolution of pollutants under the multiple policy and the newest international standards (WHO,2021AQG) backgrounds from 2014 to 2020 in Chongqing. Furthermore, suggestions and measures related to the collaborative management of pollutants were discussed. Finally, limitations and recommendations were also put forward.Clarifying the spatiotemporal distribution and impact mechanism of pollution is the prerequisite for cities to formulate relevant air pollution control measures and achieve carbon neutrality goals. This study is of great significance for Chongqing to achieve "double control and double reduction" of PM2.5 and O3 pollution, study and formulate a regional carbon peaking roadmap under climate coordination and an action plan for sustained improvement of air quality.In addition, this research can advanced our understanding of air pollution in complex terrain. Furthermore, it also promote the construction of the China national strategic Cheng-Yu economic circle and build a beautiful west. Moreover, it provides scientific insights for local policymakers to guide smart urban planning, industrial layout, energy structure, and transportation planning to improve air quality throughout the Cheng-Yu region. Finally, this is also conducive to future scientific research in other regions of China, and even megacities with complex terrain in the world.

Diurnal Variations in High Time-Resolved Molecular Distributions and Formation Mechanisms of Biogenic Secondary Organic Aerosols at Mt. Huang, East China

The molecular characteristics and formation mechanism of biogenic secondary organic aerosols (BSOAs) in the forested atmosphere are poorly known. Here, we report the temporal variations in and formation processes of BSOA tracers derived from isoprene, monoterpenes, and β caryophyllene in PM2.5 samples collected at the foot of Mt. Huang (483 m a. s. l) in East China during the summer of 2019 with a 3 h time resolution. The concentrations of nearly all of the detected species, including organic carbon (OC), elemental carbon (EC), levoglucosan, and SIA (sum of SO42-, NO3-, and NH4+), were higher at night (19:00-7:00 of the next day) than in the daytime (7:00-19:00). In addition, air pollutants that accumulated by the dynamic transport of the mountain breeze at night were also a crucial reason for the higher BSOA tracers. Most of the BSOA tracers exhibited higher concentrations at night than in the daytime and peaked at 1:00 to 4:00 or 4:00 to 7:00. Those BSOA tracers presented strong correlations with O3 in the daytime rather than at night, indicating that BSOAs in the daytime were primarily derived from the photo-oxidation of BVOCs with O3. The close correlations of BSOA tracers with SO42- and particle acidity (pHis) suggest that BSOAs were primarily derived from the acid-catalyzed aqueous-phase oxidation. Considering the higher relative humidity and LWC concentration at night, the promoted aqueous oxidation was the essential reason for the higher concentrations of BSOA tracers at night. Moreover, levoglucosan exhibited a robust correlation with BSOA tracers, especially β-caryophyllinic acid, suggesting that biomass burning from long-distance transport exerted a significant impact on BSOA formation. Based on a tracer-based method, the estimated concentrations of secondary organic carbon (SOC) derived from isoprene, monoterpenes, and β caryophyllene at night (0.90 ± 0.57 µgC m-3) were higher than those (0.53 ± 0.34 µgC m-3) in the daytime, accounting for 14.5 ± 8.5% and 12.2 ± 5.0% of OC, respectively. Our results reveal that the BSOA formation at the foot of Mt. Huang was promoted by the mountain-valley breezes and anthropogenic pollutants from long-range transport.

A machine learning-based study on the impact of COVID-19 on three kinds of pollution in Beijing-Tianjin-Hebei region

Large-scale restrictions on anthropogenic activities in China in 2020 due to the Corona Virus Disease 2019 (COVID-19) indirectly led to improvements in air quality. Previous studies have paid little attention to the changes in nitrogen dioxide (NO₂), fine particulate matter (PM_2.5) and ozone (O₃) concentrations at different levels of anthropogenic activity limitation and their interactions. In this study, machine learning models were used to simulate the concentrations of three pollutants during periods of different levels of lockdown, and compare them with observations during the same period. The results show that the difference between the simulated and observed values of NO₂ concentrations varies at different stages of the lockdown. Variation between simulated and observed O₃ and PM_2.5 concentrations were less distinct at different stages of lockdowns. During the most severe period of the lockdowns, NO₂ concentrations decreased significantly with a maximum decrease of 65.28 %, and O₃ concentrations increased with a maximum increase of 75.69 %. During the first two weeks of the lockdown, the titration reaction in the atmosphere was disrupted due to the rapid decrease in NO₂ concentrations, leading to the redistribution of Ox (NO₂ + O₃) in the atmosphere and eventually to the production of O₃ and secondary PM_2.5. The effect of traffic restrictions on the reduction of NO₂ concentrations is significant. However, it is also important to consider the increase in O₃ due to the constant volatile organic compounds (VOCs) and the decrease in NOx (NO+NO₂). Traffic restrictions had a limited effect on improving PM_2.5 pollution, so other beneficial measures were needed to sustainably reduce particulate matter pollution. Research on COVID-19 could provide new insights into future clean air action.

Air pollution in heavy industrial cities along the northern slope of the Tianshan Mountains, Xinjiang: characteristics, meteorological influence, and sources

The spatiotemporal characteristics, relationship with meteorological factors, and source distribution of air pollutants (January 2017-December 2021) were analyzed to better understand the air pollutants on the northern slope of the Tianshan Mountains (NSTM) in Xinjiang, a heavily polluted urban agglomeration of heavy industries. The results showed that the annual mean concentrations of SO₂, NO₂, CO, O₃, PM_2.5, and PM₁₀ were 8.61-13.76 μg m^-3, 26.53-36.06 μg m^-3, 0.79-1.31 mg m^-3, 82.24-87.62 μg m^-3, 37.98-51.10 μg m^-3, and 84.15-97.47 μg m^-3. The concentrations of air pollutants (except O₃) showed a decreasing trend. The highest concentrations were in winter, and in Wujiaqu, Shihezi, Changji, Urumqi, and Turpan, the concentrations of particulate matter exceeded the NAAQS Grade II during winter. The west wind and the spread of local pollutants both substantially impacted the high concentrations. According to the analysis of the backward trajectory in winter, the air masses were mainly from eastern Kazakhstan and local emission sources, and PM₁₀ in the airflow had a more significant impact on Turpan; the rest of the cities were more affected by PM_2.5. Potential sources included Urumqi-Changj-Shihezi, Turpan, the northern Bayingol Mongolian Autonomous Prefecture, and eastern Kazakhstan. Consequently, the emphasis on improving air quality should be on reducing local emissions, strengthening regional cooperation, and researching transboundary transport of air pollutants.

Assessing the effects of short-term traffic restriction policies on traffic-related air pollutants

The implementation of short-term traffic restriction policies (TRPs) during major events positively influences the traffic emission reduction. However, few studies explore the impact of diesel vehicle emissions on air quality during short-term TRP. In particular, the intertwined influences of short-term TRP and Spring Festival remains unclear. Based on Beijing 2022 Olympic Games, this study analyzed the spatiotemporal changes in urban air quality and diesel vehicle emission during short-term TRP. The results showed that the TRPs and Spring Festival contributed equally to the improvement of air quality and reduction of diesel vehicle emissions. The "interruption-recovery" pattern of short-term TRPs is characterized by a longer duration and a slower decline/recovery rate. Additionally, the individual contribution rate of diesel vehicle emissions to urban air pollutants was 15-20 % higher than that of meteorological factors during short-term TRPs.

The effectiveness of traffic and production restrictions on urban air quality: A rare opportunity for investigation

Traffic and production restrictions are two important emergency measures for controlling urban air pollution. The lockdown policies implemented during the COVID-19 pandemic period are nearly equivalent to the policies of traffic and production restriction, which provides a rare opportunity to quantitatively evaluate the effectiveness of these emergency measures. Taking Wuhan, China as the study area, this paper firstly verified the changes in six air pollutants and analyzed their change rules in different lockdown periods using statistical methods. Then the structural breakpoints in air pollutants were detected via regression discontinuity design model. To comprehensively understand the effects of restrictions on air pollution, the influences of meteorological conditions on air pollution were also investigated. The results illustrated that the concentrations of PM_2.5, PM₁₀ and NO₂ decreased significantly during lockdown period. By comparing with the RDD coefficients of PM_2.5 (-34.46), PM₁₀ (-37.11) and NO₂ (-19.15), the lockdown had little effect on CO (-0.32). The traffic and production restrictions had no apparent effects on SO₂. Although O₃ showed an increasing trend, the increase was not limited to the lockdown period, meaning that the traffic and production restrictions had less effect on the increasing trend of O₃ concentration. Moreover, the structural breakpoints were verified in four air pollutants (PM_2.5, PM₁₀, NO₂, and CO), and the structural breakpoints were caused by lockdown instead of the Spring Festival. The results also indicated that the meteorological conditions were not the main reasons for the changes in air pollutants during the lockdown period. This paper reveals how the traffic and production restrictions affect urban air pollution and provides a strong implementation basis for the air pollution control policy.Implications: The traffic and production restrictions are two important emergency measures for controlling heavy urban air pollution. However, these two measures have never been implemented in a large area like a city for a long enough period, so the effectiveness of these two measures has never been estimated quantitatively at a city level. The lockdown policies implemented during the COVID-19 pandemic are nearly equivalent to the policies of traffic and production restriction, which provides a rare opportunity to quantitatively evaluate the effectiveness of these emergency measures. Thus, this study measured the effectiveness of production and traffic restrictions on different air pollutants. This study provides the following implications: (1) the dominant factors for air pollution changes during the lockdown are traffic and production restriction instead of meteorological conditions; (2) the production and traffic restriction policies are effective for reducing concentrations of PM_2.5, PM₁₀ and NO₂, while having less effect on O₃ and CO concentrations; (3) the sharp changes in air pollutants in 2020 are unlikely to be caused by the Spring Festival. These findings are crucial for making more comprehensive policies for protecting urban air quality.

Impact of COVID-19 restrictions on air quality and surface urban heat island effect within the main urban area of Urumqi, China

The outbreak of coronavirus in 2019 (COVID-19) posed a serious global threat. However, the reduction in man-made pollutants during COVID-19 restrictions did improve the ecological environment of cities. Using multi-source remote sensing data, this study explored the spatiotemporal variations in air pollutant concentrations during the epidemic prevention and control period in Urumqi and quantitatively analyzed the impact of different air pollutants on the surface urban heat island intensity (SUHII) within the study area. Urumqi, located in the hinterland of the Eurasian continent, northwest of China, in the central and northern part of Xinjiang was selected as the study area. The results showed that during COVID-19 restrictions, concentrations of air pollutants decreased in the main urban area of Urumqi, and air quality improved. The most evident decrease in NO2 concentration, by 77 ± 1.05% and 15 ± 0.98%, occurred in the middle of the first (January 25 to March 20, 2020) and second (July 21 to September 1, 2020) COVID-19 restriction periods, respectively, compared with the corresponding period in 2019. Air pollutant concentrations and the SUHIIs were significantly and positively correlated, and NO2 exhibited the strongest correlation with the SUHIIs. We revealed that variations in the air quality characteristics and thermal environment were observed in the study area during the COVID-19 restrictions, and their quantitative relationship provides a theoretical basis and reference value for improving the air and ecological environment quality within the study area.

Artificial Neural Network Modeling on PM10, PM2.5, and NO2 Concentrations between Two Megacities without a Lockdown in Korea, for the COVID-19 Pandemic Period of 2020

The mutual relationship among daily averaged PM₁₀, PM_2.5, and NO₂ concentrations in two megacities (Seoul and Busan) connected by the busiest highway in Korea was investigated using an artificial neural network model (ANN)-sigmoid function, for a novel coronavirus (COVID-19) pandemic period from 1 January to 31 December 2020. Daily and weekly mean concentrations of NO₂ in 2020 under neither locked down cities, nor limitation of the activities of vehicles and people by the Korean Government have decreased by about 15%, and 12% in Seoul, and Busan cities, than the ones in 2019, respectively. PM ₁₀ (PM_2.5) concentration has also decreased by 15% (10%), and 12% (10%) in Seoul, and Busan, with a similar decline of NO₂, causing an improvement in air quality in each city. Multilayer perception (MLP), which has a back-propagation training algorithm for a feed-forward artificial neural network technique with a sigmoid activation function was adopted to predict daily averaged PM₁₀, PM_2.5, and NO₂ concentrations in two cities with their interplay. Root mean square error (RMSE) with the coefficient of determination (R²) evaluates the performance of the model between the predicted and measured values of daily mean PM₁₀, PM_2.5, and NO_2, in Seoul were 2.251 with 0.882 (1.909 with 0.896; 1.913 with 0.892), 0.717 with 0.925 (0.955 with 0.930; 0.955 with 0.922), and 3.502 with 0.729 (2.808 with 0.746; 3.481 with 0.734), in 2 (5; 7) nodes in a single hidden layer. Similarly, they in Busan were 2.155 with 0.853 (1.519 with 0.896; 1.649 with 0.869), 0.692 with 0.914 (0.891 with 0.910; 1.211 with 0.883), and 2.747 with 0.667 (2.277 with 0.669; 2.137 with 0.689), respectively. The closeness of the predicted values to the observed ones shows a very high Pearson r correlation coefficient of over 0.932, except for 0.818 of NO₂ in Busan. Modeling performance using IBM SPSS-v27 software on daily averaged PM₁₀, PM_2.5, and NO₂ concentrations in each city were compared by scatter plots and their daily distributions between predicted and observed values.

Effect of restricted emissions during COVID-19 on atmospheric aerosol chemistry in a Greater Cairo suburb: Characterization and enhancement of secondary inorganic aerosol production

To prevent the rapid spreading of the COVID-19 pandemic, the Egyptian government had imposed partial lockdown restrictions which led emissions reduction. This served as ideal conditions for a natural experiment, for study the effect of partial lockdown on the atmospheric aerosol chemistry and the enhanced secondary inorganic aerosol production in a semi-desert climate area like Egypt. To achieve this objective, SO₂, NO₂, and PM_2.5 and their chemical compositions were measured during the pre-COVID, COVID partial lockdown, and post-COVID periods in 2020 in a suburb of Greater Cairo, Egypt. Our results show that the SO₂, NO₂, PM_2.5 and anthropogenic elements concentrations follow the pattern pre-COVID > post-COVID > COVID partial lockdown. SO₂ and NO₂ reductions were high compared with their secondary products during the COVID partial lockdown compared with pre-COVID. Although, PM_2.5, anthropogenic elements, NO₂, SO₂, SO₄ ^2-, NO₃ ^-, and NH₄ ⁺ decreased by 39%, 38-55%, 38%, 32.9%. 9%, 14%, and 4.3%, respectively, during the COVID partial lockdown compared with pre-COVID, with the secondary inorganic ions (SO₄ ^2-, NO₃ ^-, and NH₄ ⁺) being the dominant components in PM_2.5 during the COVID partial lockdown. Moreover, the enhancement of NO₃ ^- and SO₄ ^2- formation during the COVID partial lockdown was high compared with pre-COVID. SO₄ ^2- and NO₃ ^- formation enhancements were significantly positive correlated with PM_2.5 concentration. Chemical forms of SO₄ ^2- and NO₃ ^- were identified in PM_2.5 based on their NH₄ ⁺/SO₄ ^2- molar ratio and correlation between NH₄ ⁺ and both NO₃ ^- and SO₄ ^2-. The particles during the COVID partial lockdown were more acidic than those in pre-COVID.

Lockdown during COVID-19 pandemic: A case study from Indian cities shows insignificant effects on persistent property of urban air quality

The influence of reduction in emissions on the inherent temporal characteristics of PM_2.5 and NO₂ concentration time series in six urban cities of India is assessed by computing the Hurst exponent using Detrended Fluctuation Analysis (DFA) during the lockdown period (March 24–April 20, 2020) and the corresponding period during the previous two years (i.e., 2018 and 2019). The analysis suggests the anticipated impact of confinement on the PM_2.5 and NO₂ concentration in urban cities, causing low concentrations. It is observed that the original PM_2.5 and NO₂ concentration time series is persistent but filtering the time series by fitting the autoregressive process of order 1 on the actual time series and subtracting it changes the persistence property significantly. It indicates the presence of linear correlations in the PM_2.5 and NO₂ concentrations. Hurst exponent of the PM_2.5 and NO₂ concentration during the lockdown period and previous two years shows that the inherent temporal characteristics of the short-term air pollutant concentrations (APCs) time series do not change even after withholding the emissions. The meteorological variations also do not change over the three time periods. The finding helps in developing the prediction models for future policy decisions to improve urban air quality across cities.

Changes in physical and chemical properties of urban atmospheric aerosols and ozone during the COVID-19 lockdown in a semi-arid region

The synergistic response of urban atmospheric aerosols and ozone (O₃) to reduction of anthropogenic emissions is complicated and still needs further study. Thus, the changes in physical and chemical properties of urban atmospheric aerosols and O₃ during the Coronavirus Disease 2019 (COVID-19) lockdown were investigated at three urban sites and one rural site in Lanzhou with semi-arid climate. Fine particulate matter (PM_2.5) decreased at four sites by ∼ 20% while O₃ increased by >100% at two urban sites during the COVID-19 lockdown. Both primary emissions and secondary formation of PM_2.5 decreased during the lockdown. Significant increase in both sulfur and nitrogen oxidation ratios was found in the afternoon, which accounted for 48.7% of the total sulfate and 40.4% of the total nitrate, respectively. The positive matrix factorization source apportionment revealed increased contribution of secondary formation and decreased contribution of vehicle emissions. Aerosol scattering and absorption decreased by 33.6% and 45.3%, resulting in an increase in visibility by 30% and single scattering albedo (SSA) at 520 nm slightly increased by 0.02. The enhanced O₃ production was explained by increased volatile organic compounds to nitrogen oxides ratio, decreased aerosol, as well as increased SSA. The primary emissions of secondary aerosol precursors significantly decreased while Ox (i.e., NO₂ and O₃) exhibited little change. Consequently, Ox to CO ratio, PM_2.5 to elemental carbon (EC) ratio, secondary inorganic aerosols to EC ratio, and secondary organic carbon to EC ratio increased, confirming enhanced secondary aerosol production efficiency during the lockdown. Positive feedback among O₃ concentration, secondary aerosol formation, and SSA was revealed to further promote O₃ production and secondary aerosol formation. These results provide scientific guidance for collaborative management of O₃ and particulate matter pollution for cities with semi-arid climate.

Air Pollution Increased the Demand for Gym Sports under COVID-19: Evidence from Beijing, China

Air pollution may change people's gym sports behavior. To test this claim, first, we used big data crawler technology and ordinary least square (OLS) models to investigate the effect of air pollution on people' gym visits in Beijing, China, especially under the COVID-19 pandemic of 2019-2020, and the results showed that a one-standard-deviation increase in PM2.5 concentration (fine particulate matter with diameters equal to or smaller than 2.5 μm) derived from the land use regression model (LUR) was positively associated with a 0.119 and a 0.171 standard-deviation increase in gym visits without or with consideration of the COVID-19 variable, respectively. Second, using spatial autocorrelation analysis and a series of spatial econometric models, we provided consistent evidence that the gym industry of Beijing had a strong spatial dependence, and PM2.5 and its spatial spillover effect had a positive impact on the demand for gym sports. Such a phenomenon offers us a new perspective that gym sports can be developed into an essential activity for the public due to this avoidance behavior regarding COVID-19 virus contact and pollution exposure.

Deposition-mediated phytoremediation of nitrogen oxide emissions

The growing global population and use of natural resources lead to significant air pollution. Nitrogen oxide emissions is a potential killer threatening human health requiring focus and remediation using vegetation being efficient and cheap. Here we review the mechanisms of removing nitrogen oxides by dry deposition of plants, discussing the principle of leaf absorption of pollutants and factors affecting the removal of nitrogen oxides providing a theoretical basis for the selection of urban greening vegetation.

Molecular characteristics, sources and environmental risk of aromatic compounds in particulate matter during COVID-2019: Nontarget screening by ultra-high resolution mass spectrometry and comprehensive two-dimensional gas chromatography

Aromatic compounds, including many polycyclic aromatic hydrocarbons (PAHs), are suspected carcinogens and may originate from different sources. To investigate the impact of anthropogenic emission reductions on unknown aromatic compounds in particulate matter, we collected samples during the pre-COVID period in 2020, the COVID-19 lockdown period in 2020, and the same period as the lockdown in 2019. Besides the 16 PAHs, other aromatic compounds were analyzed by Fourier transform ion cyclotron resonance mass spectrometry and comprehensive two-dimensional gas chromatography-time-of-flight mass spectrometry. Four main compound classes were identified: CH, CHO, CHNO, and CHOS. Hierarchical cluster analysis showed the aromatic compounds varied during the different periods. Compared with before the pandemic, the relative abundances of aromatic compounds with low degrees of unsaturation and long alkyl chains (e.g., alkylbenzenes) increased. These compounds probably mainly arose from fossil fuel combustion and petrochemical industry emissions. The CHO compounds, which were dominated by those with high degrees of oxidation, might originate from secondary organic aerosols. Aromatic aldehydes (e.g., cyclamen aldehyde) and benzoates (e.g., 2-ethylhexyl benzoate) probably with high toxicity deserve more attention. During lockdown, nitro derivatives of condensed PAHs were the main CHNO compounds, and the numbers of homologs decreased perhaps because of significant reductions in NO_x and PAHs. CHOS compounds with long carbon chains and low degrees of unsaturation were predominant and the numbers of homologs increased. Five compounds (e.g. 1,3-dimethyl pyrene) were predicted to possibly exhibit persistent and bio-accumulated by EPI Suite model, which need further research. The results provide insight on aromatic compounds and their source appointment in atmospheric particulate matter.

Spatial and temporal characteristics of air pollutants and their health effects in China during 2019-2020

This work presents the temporal and spatial characteristics of the major air pollutants and their associated health risks in China from 2019 to 2020, by using the monitoring data from 367 cities. The annual average PM_2.5, PM₁₀, NO₂, SO₂, CO, and O₃ concentrations decreased by 10.9%, 13.2%, 9.3%, 10.1%, 9.4%, and 5.5% from 2019 to 2020. National average PM_2.5 concentration in 2020 met the standard of 35 μg/m³, and that of O₃ decreased from 2019. COVID-19 lockdown affected NO₂ level dramatically, yet influences on PM_2.5 and O₃ were less clear-cut. Positive correlations between PM_2.5 and O₃ were found, even in winter in all five key regions, e.g., Jing-Jin-Ji (JJJ), FenWei Plain (FWP), Yangtze River Delta (YRD), Pearl River Delta (PRD) and Chengdu-Chongqing Region (CCR), indicating importance of secondary production for both PM_2.5 and O₃. Large seasonal variability of PM_2.5-SO₂ correlation indicates a varying role of SO₂ to PM_2.5 pollution in different seasons; and generally weak correlations in winter between PM_2.5 and NO₂ or SO₂ reveal the complexity of secondary formation processes to PM_2.5 pollution in winter. Multilinear regression analysis between PM_2.5 and SO₂, NO₂ and CO demonstrates that PM_2.5 is more sensitive to the change of NO₂ than SO₂ in JJJ, FWP, PRD and CCR, suggesting a priority of NO_x emission control for future PM_2.5 reduction. Furthermore, the new World Health Organization Air Quality Guidelines (WHO AQG2021) were adopted to calculate the excess health risks (ER) as well as the health-risk based air quality index (HAQI_WHO) of the pollutants. Such assessment points out the severity of air pollution associated health risks under strict standards: 40.0% of days had HAQI_WHO>100, while only 14.4% days had AQI>100. PM_2.5 ER was generally larger than O₃ ER, but O₃ ER in low PM_2.5 region (PRD) and during summer became more serious. Notably, NO₂ ER became even more important than PM_2.5 due to its strict limit of WHO AQG2021. Overall, our results highlight the increasing importance of O₃ in both air quality evaluation and health risk assessment, and the importance of coordinated mitigation of multiple pollutants (mainly PM_2.5, O₃ and NO₂) in protecting the public health.

Urban air quality changes resulting from the lockdown period due to the COVID-19 pandemic

This work aims to quantify potential pollution level changes in an urban environment (Madrid city, Spain) located in South Europe due to the lockdown measures for preventing the SARS-CoV-2 transmission. Polluting 11 species commonly monitored in urban zones were attended. Except for O3, a prompt target pollutant levels abatement was reached, intensely when implanted stricter measures and moderately along those measures' relaxing period. In the case of TH and CH4, it is evidenced a progressive diminution over the lockdown period. While the highest decreasing average changes relapsed on NOx (NO2: - 40.0% and NO: - 33.3%) and VOCs (C7H8: - 36.3% and C6H6: - 32.8%), followed by SO2 (- 27.0%), PM10 (- 19.7%), CO (- 16.6%), CH4 (- 14.7%), TH (- 11.6%) and PM2.5 (- 10.1%), the O3 level slightly raised 0.4%. These changes were consistently dependent on the measurement station location, emphasizing urban background zones for SO2, CO, C6H6, C7H8, TH and CH4, suburban zones for PM2.5 and O3, urban traffic sites for NO and PM10, and keeping variations reasonably similar at all the stations in the case of NO2. Those pollution changes were not translated in variations on geospatial pattern, except for NO, O3 and SO2. Although the researched urban atmosphere improvement was not attributable to meteorological conditions' variations, it was in line with the decline in traffic intensity. The evidenced outcomes might offer valuable clues to air quality managers in urban environments regarding decision-making in favor of applying punctual severe measures for quickly and considerably relieving polluting high load occurred in urban environments.

Supplementary Information

The online version contains supplementary material available at 10.1007/s13762-022-04464-6.

The regional impact of the COVID-19 lockdown on the air quality in Ji'nan, China

A number of strict lockdown measures were implemented in the areas most affected by COVID-19 in China, including Ji’nan city, from 24 January to 7 February 2020. Due to these forced restrictions, the pollution levels in cities across the country drastically decreased within just a few days. Since traffic pollution and industrial emissions are important factors affecting regional air quality, congestion has a significant impact on the environment. Therefore, using the aid of air quality data for six pollutants (PM₁₀, PM_2.5, SO₂, NO₂, CO and O₃) from 11 monitoring stations (located in urban, suburban and urban-industrial regions) across Ji’nan, we employed the air quality index (AQI) to investigate the spatial pattern of air quality in the pre-COVID-19 (pre-COVID) and COVID-19-related lockdown (COVID lockdown) periods. The results showed that air quality significantly improved during the COVID lockdown period. Among the selected pollutants, compared to the corresponding pre-COVID levels, the greatest reduction was observed for the concentration of NO₂ (54.02%), while the smallest reduction was observed for the concentration of SO₂ (27.92%). The PM_2.5 (38.73%), PM₁₀ (44.92%) and CO (30.60%) levels also decreased during the COVID lockdown period; only the O₃ concentration increased (37.42%) during this period. Overall, air quality improved by approximate improvements of 37.33% during the COVID lockdown period. Approximately 35.48%, 37.01% and 43.43% in the AQI were observed in urban, suburban and urban-industrial regions, respectively. Therefore, the AQI exhibited remarkable regional differences in Ji'nan. This study demonstrates the contributions of the transportation sector and local emissions to improving air quality in typical urban areas, and these research results can provide guidance for the further monitoring of air pollution in northern Chinese cities.

Does Technological Innovation Curb O3 Pollution? Evidence from Three Major Regions in China

At the end of 2020, when China’s three-year Blue Sky Protection Campaign was successfully concluded, the main pollutants, led by O₃, increased instead of decreasing, creating a new air pollution problem. In this paper, the impact of the technological innovation level on O₃ pollution and its inter-regional differences across three major regions from 2014 to 2019 are studied using the dynamic spatial Durbin model. Generally, in terms of ozone pollution showing significant spatial correlation, technological innovations in China are still not effective in curbing ozone pollution. Furthermore, technological innovation is a key factor affecting ozone pollution, and it is heterogeneous, demonstrating that the impact of technological innovation on O₃ pollution is different among regions. Technological innovation in Beijing–Tianjin–Hebei significantly reduces local O₃ pollution with spillover, while technological innovation in the Yangtze River Delta instead significantly exacerbates local O₃ pollution, and the impact of technological innovation on O₃ pollution in the Fenwei Plain is not significant. Third, other factors in O₃ pollution also differ between regions, with the number of cars and the amount of foreign capital actually utilized being the main factors. Therefore, we should pay attention to the spillover of O₃ pollution and technological innovation and strengthen regional cooperation according to our own characteristics to effectively suppress O₃ pollution. Finally, the findings of this paper are representative, which provides a possible reference for other similar national or regional studies.

Influence of Rural Development of River Tourism Resources on Physical and Mental Health and Consumption Willingness in the Context of COVID-19

This study took the Three Gorges Dam as an example and discussed the influence of river regulation decisions on the sustainable development of surrounding villages. The study used mixed research methods, snowball sampling, and convenience sampling to obtain samples. The questionnaire samples were analyzed by basic statistical tests, t-test, and structural equation modeling (SEM). The respondents’ opinions were collected through semi-structured interviews and finally the results were discussed by multivariate analysis. The findings were that even though the villages were not well developed in terms of economy, environment, and natural ecology, as long as the community security could be stable, the living could be safe and convenient, people’s daily life patterns and leisure behaviors could be maintained, and people could stabilize their minds and emotions and maintain physical and mental health in order to meet their living needs and reduce the burden. There would be time and funds to invest in leisure, tourism activities, and consumption behavior. If the above consumption patterns are continued, people will gain positive perceptions, stimulating people’s willingness to invest in property purchases or to make travel plans again.

Temporal characteristics and spatial heterogeneity of air quality changes due to the COVID-19 lockdown in China

Previous studies have evaluated the impact of lockdown measures on air quality during the COVID-19 pandemic in China, but few have focused on the temporal characteristics and spatial heterogeneity of the impact across all 337 prefecture cities. In this study, we estimated the impact of the lockdown measures on air quality in each of 337 cities using the Regression Discontinuity in Time method. There was a short-term influence from January 24th to March 31th in 2020. The 337 cities could be divided into six categories showing different response and resilience patterns to the epidemic. Fine particulate matter (PM_2.5) in 89.5% of the cities was sensitive to the lockdown measures. The change of air pollutants showed high spatial heterogeneity. The provinces with a greater than 20% reduction in PM_2.5 and PM₁₀ and greater than 40% reduction in NO₂ during the impact period were mainly concentrated southeast of the "Hu Line". Compared to the no-pandemic scenario, the national annual average concentration of PM_2.5, NO₂, PM₁₀, SO₂, and CO in 2020 were decreased by 6.3%, 10.6%, 7.4%, 9.0%, and 12.5%, respectively, while that of O₃ increased by 1.1%.This result indicates that 2020 can still be used as a baseline for setting and allocating air improvement targets for the next five years.

Unexpected rise of atmospheric secondary aerosols from biomass burning during the COVID-19 lockdown period in Hangzhou, China

After the global outbreak of COVID-19, the Chinese government took many measures to control the spread of the virus. The measures led to a reduction in anthropogenic emissions nationwide. Data from a single particle aerosol mass spectrometer in an eastern Chinese megacity (Hangzhou) before, during, and after the COVID-19 lockdown (5 January to February 29, 2020) was used to understand the effect lockdown had on atmospheric particles. The collected single particle mass spectra were clustered into eight categories. Before the lockdown, the proportions of particles ranked in order of: EC (57.9%) < K-SN (13.6%) < Fe-rich (10.2%) < ECOC (6.7%) < K-Na (6.6%) < OC (3.4%) < K-Pb (1.0%) < K-Al (0.7%). During the lockdown period, the EC and Fe-rich particles decreased by 42.8% and 93.2% compared to before lockdown due to reduced vehicle exhaust and industrial activity. By contrast, the K-SN and K-Na particles containing biomass burning tracers increased by 155.2% and 45.2% during the same time, respectively. During the lockdown, the proportions of particles ranked in order of: K-SN (39.7%) < EC (38.1%) < K-Na (11.0%) < ECOC (7.7%) < OC (1.2%) < K-Pb (0.9%) < Fe-rich (0.8%) < K-Al (0.6%). Back trajectory analysis indicated that both inland (Anhui and Shandong provinces) and marine transported air masses may have contributed to the increase in K-SN and K-Na particles during the lockdown, and that increased number of fugitive combustion points (i.e., household fuel, biomass combustion) was a contributing factor. Therefore, the results imply that regional synergistic control measures on fugitive combustion emissions are needed to ensure good air quality.

Temporal and Spatial Distribution Analysis of Atmospheric Pollutants in Chengdu-Chongqing Twin-City Economic Circle

In order to study the temporal and spatial distribution characteristics of atmospheric pollutants in cities (districts and counties) in the Chengdu–Chongqing Twin-city Economic Circle (CCEC) and to provide a theoretical basis for atmospheric pollution prevention and control, this paper combined Ambient Air Quality Standards (AAQS) and WHO Global Air Quality Guidelines (GAQG) to evaluate atmospheric pollution and used spatial correlation to determine key pollution areas. The results showed that the distribution of atmospheric pollutants in CCEC presents a certain law, which was consistent with the air pollution transmission channels. Except for particulate matter with an aerodynamic diameter equal to or less than 2.5 μm (PM_2.5) and ozone (O₃), other pollutants reached Grade II of AAQS in 2020, among which particulate matter with an aerodynamic diameter equal to or less than 10 μm (PM₁₀), PM_2.5, sulfur dioxide (SO₂), nitrogen dioxide (NO₂) and carbon monoxide (CO) have improved. Compared with the air quality guidelines given in the GAQG, PM₁₀, PM_2.5, NO₂ and O₃ have certain effects on human health. The spatial aggregation of PM₁₀ and PM_2.5 decreased year by year, while the spatial aggregation of O₃ increased with the change in time, and the distribution of NO₂ pollution had no obvious aggregation. Comprehensive analysis showed that the pollution problems of particulate matter, NO₂ and O₃ in CCEC need to be further controlled.

Exploring chemical changes of the haze pollution during a recent round of COVID-19 lockdown in a megacity in Northeast China

COVID-19 rebounded in China in January 2021, with Heilongjiang as one of the worst-affected provinces. This resulted in a new round of lockdown in Harbin, the capital city of Heilongjiang, from 20 January to 22 February of 2021. A field campaign was conducted to explore the responses of haze pollution in Harbin to the lockdown. Levoglucosan was used to reflect biomass burning emissions, while the molar ratio of sulfur (the sum of sulfur dioxide and sulfate) to nitrogen (the sum of nitrogen dioxide and nitrate), i.e., R_S/N, was used as an indicator for the relative importance of coal combustion and vehicle emissions. Based on a synthesis of the levoglucosan and R_S/N results, reference period was selected with minimal influences of non-lockdown-related emission variations. As indicated by the almost unchanged sulfur dioxide concentrations, coal combustion emissions were relatively stable throughout the lockdown and reference periods, presumably because the associated activities, e.g., heating supply, power generation, etc., were usually uninterruptible. On the other hand, as suggested by the increase of R_S/N, vehicle emissions were considerably reduced during lockdown, likely due to the stay-at-home orders. Compared to results from the reference samples, the lockdown period exhibited higher levels of ozone and various indicators for secondary aerosol formation, pointing to an enhancement of secondary pollution. In addition, photochemistry-related reactions in aqueous phase appeared to be present during the lockdown period, which have not been reported in the frigid atmosphere over Northeast China.

Network approach reveals the spatiotemporal influence of traffic on air pollution under COVID-19

Air pollution causes widespread environmental and health problems and severely hinders the quality of life of urban residents. Traffic is critical for human life, but its emissions are a major source of pollution, aggravating urban air pollution. However, the complex interaction between traffic emissions and air pollution in cities and regions has not yet been revealed. In particular, the spread of COVID-19 has led various cities and regions to implement different traffic restriction policies according to the local epidemic situation, which provides the possibility to explore the relationship between urban traffic and air pollution. Here, we explore the influence of traffic on air pollution by reconstructing a multi-layer complex network base on the traffic index and air quality index. We uncover that air quality in the Beijing-Tianjin-Hebei (BTH), Chengdu-Chongqing Economic Circle (CCS), and Central China (CC) regions is significantly influenced by the surrounding traffic conditions after the outbreak. Under different stages of the fight against the epidemic, the influence of traffic in some regions on air pollution reaches the maximum in stage 2 (also called Initial Progress in Containing the Virus). For the BTH and CC regions, the impact of traffic on air quality becomes bigger in the first two stages and then decreases, while for CC, a significant impact occurs in phase 3 among the other regions. For other regions in the country, however, the changes are not evident. Our presented network-based framework provides a new perspective in the field of transportation and environment and may be helpful in guiding the government to formulate air pollution mitigation and traffic restriction policies.

The Effect of Coronavirus 2019 Disease Control Measures on the Incidence of Respiratory Infectious Disease and Air Pollutant Concentrations in the Yangtze River Delta Region, China

The Yangtze River Delta is one of the top five Chinese regions affected by COVID-19, as it is adjacent to Hubei Province, where COVID-19 first emerged. We investigated the impact of COVID-19 non-pharmaceutical interventions (NPIs) on changes in respiratory infectious diseases (RIDs) incidence and air quality in the Yangtze River Delta by constructing two proportional tests and fitting ARIMA and linear regression models. Compared with the pre-COVID-19 period, the average monthly incidence of seven RIDs decreased by 37.80% (p < 0.001) and 37.11% (p < 0.001) during the COVID-19 period and the post-vaccination period, respectively, in Shanghai, and decreased by 20.39% (p < 0.001) and 22.86% (p < 0.001), respectively, in Zhejiang. Similarly, compared with the pre-COVID-19 period, the monthly overall concentrations of six air pollutants decreased by 12.7% (p = 0.003) and 18.79% (p < 0.001) during the COVID-19 period and the post-vaccination period, respectively, in Shanghai, and decreased by 12.85% (p = 0.008) and 15.26% (p = 0.001), respectively, in Zhejiang. Interestingly, no significant difference in overall incidence of RIDs and concentrations of air quality was shown between the COVID-19 period and the post-vaccination period in either Shanghai or Zhejiang. This study provides additional evidence that the NPIs measures taken to control COVID-19 were effective in improving air quality and reducing the spread of RIDs. However, a direct causal relationship has not been established.

Changes in air quality in-taxis and in working conditions of taxi drivers pre- and post-lockdown, during the COVID-19 pandemic in the Paris area

We evaluated the impact of the lockdown restriction measures in the Paris area on the variation of in-vehicle ultrafine particle (UFP) and black carbon (BC) concentrations between the pre- and post-lockdown period and professional drivers' working conditions and practices. The study was conducted with 33 taxi drivers. UFP and BC were measured inside their vehicles with DiSCmini^® and microAeth^® , respectively, on two typical working days pre- and post-lockdown. Job characteristics were self-reported. Our results showed that post-lockdown, both the number of clients and journey duration significantly decreased. Taxi drivers opened their windows significantly more and reduced the use of air recirculation. UFP decreased significantly by 32% and BC by 31% post-lockdown, with a weaker positive correlation compared to pre-lockdown. The reduction of in-vehicle UFP was due mainly to the reduction of traffic flow and ventilation settings, though the latter probably varied according to traffic conditions. The variation of in-vehicle BC also tended to be related to the decrease in traffic flow post-lockdown. We emphasize the role of traffic emissions on in-vehicle air pollution and that preventive measures such ventilation settings would help to minimize the exposure of professional drivers and passengers to air pollutants.

Impact of the COVID-19 pandemic on coastal environment: positive or negative? A 1-year study on litter in Caspian coasts

Litter is one of the major environmental problems. These wastes cause adverse health, environmental, and even economic effects. One of the consequences of the COVID-19 pandemic is the impact on litter composition and density due to its changes in lifestyle and consumption patterns. In this study, the effect of the COVID-19 pandemic on the composition and density of litter on the ten southern beaches of the Caspian Sea in Iran in 1 year was investigated. The results showed that the density of the litters was in the range of 36.5–306 items/m2. The highest and lowest proportions of the COVID-related litters on the locations studied were 2.54 and 5.95%, respectively. The indexes in the areas studied showed that the COVID-19 pandemic has reduced the density of the litter in 90% of the beaches studied by changing the style of citizens, but the emergence of new dumping related to COVID-19 has increased the potential for health and environmental hazards caused by litters. The effects of the COVID-related litters increased the clean environment index by 5 to 12% on the beaches. This study shows that the impact of social phenomena such as a pandemic on litter and its results can be used for the better management of municipal solid wastes, including litter in similar situations in the future.

Airborne black carbon variations during the COVID-19 lockdown in the Yangtze River Delta megacities suggest actions to curb global warming

Airborne black carbon is a strong warming component of the atmosphere. Therefore, curbing black carbon emissions should slow down global warming. The 2019 coronavirus pandemic (COVID-19) is a unique opportunity for studying the response of black carbon to the varied human activities, in particular due to lockdown policies. Actually, there is few knowledge on the variations of black carbon in China during lockdowns. Here, we studied the concentrations of particulate matter (PM_2.5) and black carbon before, during, and after the lockdown in nine sites of the Yangtze River Delta in Eastern China. Results show 40-60% reduction of PM_2.5 and 40-50% reduction of black carbon during the lockdown. The classical bimodal peaks of black carbon in the morning and evening rush hours were highly weakened, indicating the substantial decrease of traffic activities. Contributions from fossil fuels combustion to black carbon decreased about 5-10% during the lockdown. Spatial correlation analysis indicated the clustering of the multi-site black carbon concentrations in the Yangtze River Delta during the lockdown. Overall, control of emissions from traffic and industrial activities should be efficient to curb black carbon levels in the frame of a 'green public transit system' for mega-city clusters such as the Yangtze River Delta.

SUPPLEMENTARY INFORMATION

The online version contains supplementary material available at 10.1007/s10311-021-01327-3.

Disentangling drivers of air pollutant and health risk changes during the COVID-19 lockdown in China

The COVID-19 restrictions in 2020 have led to distinct variations in NO₂ and O₃ concentrations in China. Here, the different drivers of anthropogenic emission changes, including the effects of the Chinese New Year (CNY), China's 2018-2020 Clean Air Plan (CAP), and the COVID-19 lockdown and their impact on NO₂ and O₃ are isolated by using a combined model-measurement approach. In addition, the contribution of prevailing meteorological conditions to the concentration changes was evaluated by applying a machine-learning method. The resulting impact on the multi-pollutant Health-based Air Quality Index (HAQI) is quantified. The results show that the CNY reduces NO₂ concentrations on average by 26.7% each year, while the COVID-lockdown measures have led to an additional 11.6% reduction in 2020, and the CAP over 2018-2020 to a reduction in NO₂ by 15.7%. On the other hand, meteorological conditions from 23 January to March 7, 2020 led to increase in NO₂ of 7.8%. Neglecting the CAP and meteorological drivers thus leads to an overestimate and underestimate of the effect of the COVID-lockdown on NO₂ reductions, respectively. For O₃ the opposite behavior is found, with changes of +23.3%, +21.0%, +4.9%, and -0.9% for CNY, COVID-lockdown, CAP, and meteorology effects, respectively. The total effects of these drivers show a drastic reduction in multi-air pollutant-related health risk across China, with meteorology affecting particularly the Northeast of China adversely. Importantly, the CAP's contribution highlights the effectiveness of the Chinese government's air-quality regulations on NO₂ reduction.

Modelling the effect of local and regional emissions on PM2.5 concentrations in Wuhan, China during the COVID-19 lockdown

PM_2.5 concentrations in Wuhan, China decreased by 36.0% between the period prior to the COVID-19 pandemic (1–23 January, 2020) and the COVID-lockdown period (24 January to 29 February, 2020). However, decreases in PM_2.5 concentration due to regional PM_2.5 transport driven by meteorological changes, and the relationship between the PM_2.5 source and receptor, are poorly understood. Therefore, this study assessed how changes in meteorology, local emissions, and regional transport from external source emissions contributed to the decrease in Wuhan's PM_2.5 concentration, using FLEXPART-WRF and WRF-Chem modelling experiments. The results showed that meteorological changes in central China explain up to 22.2% of the total decrease in PM_2.5 concentrations in Wuhan, while the remaining 77.8% was due to air pollutant emissions reduction. Reduction in air pollutant emissions depended on both local and external sources, which contributed alomst equally to the reduction in PM_2.5 concentrations (38.7% and 39.1% of the total reduction, respectively). The key emissions source areas affecting PM_2.5 in Wuhan during the COVID-lockdown were identified by the FLEXPART-WRF modeling, revealing that regional-joint control measures in key areas accounted for 89.3% of the decrease in PM_2.5 concentrations in Wuhan. The results show that regional-joint control can be enhanced by identifying key areas of emissions reduction from the source–receptor relationship of regional PM_2.5 transport driven by meteorology under the background of East Asian monsoon climate change.

Characteristics and sources of amine-containing particles in the urban atmosphere of Liaocheng, a seriously polluted city in North China during the COVID-19 outbreak

The Chinese government issued an unprecedentedly strict lockdown policy to control the spread of the novel coronavirus disease 2019 (COVID-19), significantly mitigating air pollution because of the dramatic reduction of industrial and traffic emissions. To explore the impact of COVID-19 lockdown (LCD) on organic aerosols, the mixing states and evolution processes of amine-containing particles were studied using a single particle aerosol mass spectrometer from January to March 2020 in Liaocheng, which is a seriously polluted city in North China. The counts and percentages of amine-containing particles in total obtained particles during the pre-LCD (547832, 29.8 %) were higher than those during the LCD (283983, 20.7 %) and post-LCD (102026, 18.4 %), mainly due to the reduced emission strength of amines and suppressed gas-to-particle partitioning of amines during the LCD and post-LCD. ⁷⁴(C₂H₅)₂NH₂⁺ was the most abundant amine marker, which accounted for 98.2 %, 98.4 %, and 96.7 % of all amine-containing particles during the pre-LCD, LCD, and post-LCD, respectively. Correlation analysis and temporal variations indicated that the gas-to-particle partitioning of amines was facilitated by the stronger acidic environment and lower temperature, while the effect of RH and aerosol liquid water content was minor. The A-OC particles were the most abundant type (accounting for ~40 %) throughout the observation period. The temporal profiles and correlation analysis suggested that the impact of the increased O₃ on the amines and their oxidation products (e.g., trimethylamine oxide) was minor. The identified particle types, correlation analysis, and the potential source contribution function results implied that the amine-containing particles were mainly derived from local and surrounding sources during the LCD, while those were mainly affected by long-range transport during the pre-LCD and post-LCD. Our results could deepen the comprehension of the sources and atmospheric processing of amines in the urban area of North China during the COVID-19 outbreak.

Declining carbon emission/concentration during COVID-19: A critical review on temporary relief

In December 2019 the deadly pandemic COVID-19 traumatized mankind through its lethal impact. To seize the outbreak, nationwide/region-based lockdown strategies were adopted by most of the COVID-19 affected countries. This in turn resulted in restricted transportation via surface, water, and air, as well as significantly reduced working hours of the industry sectors, so on and so forth. The obvious outcome was a sudden discernible decline in atmospheric adulteration. Accordingly, the anthropogenic emissions at the global and regional/local scales were examined during the lockdown period by several researchers using both or either satellite-based and ground-based monitoring. Among several other air-contaminants, carbon has a dominant toxicological profile causing adverse health effects and thereby attracting researches interest in carbon-release probing during the systematic confinement period imposed by the ruling authorities across the globe. The results of those studies indicated a confirmed decline in carbon emission/concentration making the air more breathable for the period. In this review, the studies related to anthropogenic emissions of carbon during the lockdown period are accounted for by compiling the recently reported data from published articles.

Impact of the first induced COVID-19 lockdown on air quality in Israel

The coronavirus disease 2019 (COVID-19) induced a lockdown that has resulted in a sharp reduction in air and motor traffic and industrial activities. This in turn led to a reduction in air pollution around the world. It is important to quantify the extent of that reduction in order to estimate the weight of the impact of air and motor traffic and industrial activities over the total variation of air quality. An assessment of the extent of air pollution is aimed at facilitating the crafting of policies toward the reduction of pollution and the improvement in air quality. The aim of this paper is to evaluate the impact of the COVID-19 outbreak on air pollution in Israel. Particularly, we focus on Haifa and Greater Tel-Aviv (Gush-Dan), two regions with high air pollution, while examining different types of air monitoring stations. The period to which we refer to is March 8, 2020, to May 2, 2020. The results reveal two main findings: (1) During the COVID-19 lockdown, pollution emissions decreased relative to the same period in 2019. The biggest reduction was observed in NO _x , which, on average, was 41%. Surprisingly, ground-level ozone (O ₃) increased, and appeared to behave similarly to the ozone weekend effect. (2) The total percentage variation in pollution emission that was explained by the lockdown was at most 26%. By adding the meteorological conditions (which included measures of wind direction, wind speed, and temperature) as a factor in addition to the lockdown effect, this percent increased to 47%.

An observation approach in evaluation of ozone production to precursor changes during the COVID-19 lockdown

The increase of surface ozone during the Corona Virus Disease 2019 (COVID-19) lockdown in China has aroused great concern. In this study, we combine 1.5 years of measurements for ozone, volatile organic compounds (VOCs), and nitrogen oxide (NO_X) at four sites to investigate the effect of COVID-19 lockdown on surface ozone in Dongguan, an industrial city in southern China. We show that the average concentrations of NO_X and VOCs decreased by 70%-77% and 54%-68% during the lockdown compared to pre-lockdown, respectively. Based on the source apportionment of VOCs, the contribution of industrial solvent use reduced significantly (86%-94%) during the lockdown, and climbed back slowly along with the re-opening of the industry after lockdown. A slight increase in mean ozone concentration (3%-14%) was observed during the lockdown. The rise of ozone was the combined effect of substantial increase at night (58%-91%) and small reduction in the daytime (1%-17%). These conflicting observations in ozone response between day and night to emission change call for a more detailed approach to diagnostic ozone production response with precursor changes, rather than directly comparing absolute concentrations. We propose that the ratio of daily Ox (i.e. ozone + NO₂) enhancement to solar radiation can provide a diagnostic parameter for ozone production response during the lockdown period. Smaller ratio of daily O_X (ozone + NO₂) enhancement to solar radiation during the lockdown were observed from the long-term measurements in Dongguan, suggesting significantly weakened photochemistry during the lockdown successfully reduces local ozone production. Our proposed approach can provide an evaluation of ozone production response to precursor changes from restrictions of social activities during COVID-19 epidemic and also other regional air quality abatement measures (e.g. public mega-events) around the globe.

The Impact of COVID-19 Lockdowns on Air Quality—A Global Review

The outbreak of the COVID-19 pandemic has emerged as a serious public health threat and has had a tremendous impact on all spheres of the environment. The air quality across the world improved because of COVID-19 lockdowns. Since the outbreak of COVID-19, large numbers of studies have been carried out on the impact of lockdowns on air quality around the world, but no studies have been carried out on the systematic review on the impact of lockdowns on air quality. This study aims to systematically assess the bibliographic review on the impact of lockdowns on air quality around the globe. A total of 237 studies were identified after rigorous review, and 144 studies met the criteria for the review. The literature was surveyed from Scopus, Google Scholar, PubMed, Web of Science, and the Google search engine. The results reveal that (i) most of the studies were carried out on Asia (about 65%), followed by Europe (18%), North America (6%), South America (5%), and Africa (3%); (ii) in the case of countries, the highest number of studies was performed on India (29%), followed by China (23%), the U.S. (5%), the UK (4%), and Italy; (iii) more than 60% of the studies included NO2 for study, followed by PM2.5 (about 50%), PM10, SO2, and CO; (iv) most of the studies were published by Science of the Total Environment (29%), followed by Aerosol and Air Quality Research (23%), Air Quality, Atmosphere & Health (9%), and Environmental Pollution (5%); (v) the studies reveal that there were significant improvements in air quality during lockdowns in comparison with previous time periods. Thus, this diversified study conducted on the impact of lockdowns on air quality will surely assist in identifying any gaps, as it outlines the insights of the current scientific research.

Variations in concentration and solubility of iron in atmospheric fine particles during the COVID-19 pandemic: An example from China

Iron (Fe) in the atmosphere can affect atmospheric chemical processes and human health. When deposited into oceans, it can further influence phytoplankton growth. These roles of Fe fundamentally depend on its concentration and solubility. However, the sources of aerosol Fe and controlling factors of Fe solubility in megacities remain poorly understood. The outbreak of the COVID-19 pandemic causes large changes in human activities, which provides a unique opportunity to answer these key issues. Field observations were conducted before, during, and after the COVID-19 lockdown in Hangzhou, China. Our results show that in the COVID-19 lockdown stage, the concentrations of total Fe (Fe_T, 75.0 ng m^-3) and soluble Fe (Fe_S, 5.1 ng m^-3) in PM_2.5 decreased by 78% and 62%, respectively, compared with those (Fe_T 344.7 ng m^-3, Fe_S 13.5 ng m^-3) in the pre-lockdown stage. The sharp reduction (81%) in on-road vehicles was most responsible for the aerosol Fe decrease. Surprisingly, the Fe solubility increased by a factor of 1.9, from 4.2% in the pre-lockdown stage to 7.8% in the COVID-19 lockdown stage. We found that the atmospheric oxidizing capacity was enhanced after lockdown restrictions were implemented, which promoted the formation of more acidic species and further enhanced the dissolution of aerosol Fe.

Substantial changes of chemical composition and sources of fine particles during the period of COVID-19 pandemic in Taiyuan, Northern China

To better understand the effects of COVID-19 on air quality in Taiyuan, hourly in situ measurements of PM_2.5(particulate matter with an aerodynamic diameter less than 2.5 mm) and chemical components (water-soluble ions, organic carbon (OC), elemental carbon (EC), and trace elements) were conducted before (P1: 1 January-23 January 2020) and during (P2: 24 January-15 February 2020) the coronavirus disease 2019 (COVID-19) outbreak. The average concentrations of PM_2.5 dropped from 122.0 μg/m³ during P1 to 83.3 μg/m³ during P2. Compared with P1, except for fireworks burning-related chemical components (K⁺, Mg²⁺, K, Cu, Ba), the concentrations of other chemical components of PM_2.5 decreased by14.9-69.8%. Although the large decrease of some emission sources, fireworks burning still resulted in the occurrence of pollution events during P2. The analysis results of positive matrix factorization model suggested that six PM_2.5 sources changed significantly before and during the outbreak of the epidemic. The contributions of vehicle emission, industrial process, and dust to PM_2.5 decreased from 23.1%, 3.5%, and 4.0% during P1 to 7.7%, 3.4%, and 2.3% during P2, respectively, whereas the contributions of secondary inorganic aerosol, fireworks burning, and coal combustion to PM_2.5 increased from 62.0%, 1.8%, and 5.5% to 71.5%, 9.0%, and 6.2%, respectively. The source apportionment results were also affected by air mass transport. The largest reductions of vehicle emission, industrial process, and dust source were distinctly seen for the air masses from northwest.

SUPPLEMENTARY INFORMATION

The online version contains supplementary material available at 10.1007/s11869-021-01082-y.

The air quality changes and related mortality benefits during the coronavirus disease 2019 pandemic in China: Results from a nationwide forecasting study

Air quality changes during the coronavirus disease 2019 (COVID-19) pandemic in China has attracted increasing attention. However, more details in the changes, future air quality trends, and related death benefits on a national scale are still unclear. In this study, a total of 352 Chinese cities were included. We collected air pollutants (including fine particulate matter [PM_2.5], inhalable particulate matter [PM₁₀], nitrogen dioxide [NO₂], and ozone [O₃]) data for each city from January 2015 to July 2020. Convolutional neural network-quantile regression (CNN-QR) forecasting model was used to predict pollutants concentrations from February 2020 to January 2021 and the changes in air pollutants were compared. The relationships between the socioeconomic factors and the changes and the avoided mortality due to the changes were further estimated. We found sharp declines in all air pollutants from February 2020 to January 2021. Specifically, PM_2.5, PM₁₀, NO₂, and O₃ would drop by 3.86 μg/m³ (10.81%), 4.84 μg/m³ (7.65%), 0.55 μg/m³ (2.18%), and 3.14 μg/m³ (3.36%), respectively. The air quality changes were significantly related to many of the socioeconomic factors, including the size of built-up area, gross regional product, population density, gross regional product per capita, and secondary industry share. And the improved air quality would avoid a total of 7237 p.m._2.5-related deaths (95% confidence intervals [CI]: 4935, 9209), 9484 p.m.₁₀-related deaths (95%CI: 5362, 13604), 4249 NO₂-related deaths (95%CI: 3305, 5193), and 6424 O₃-related deaths (95%CI: 3480, 9367), respectively. Our study shows that the interventions to control COVID-19 would improve air quality, which had significant relationships with some socioeconomic factors. Additionally, improved air quality would reduce the number of non-accidental deaths.

How changes in human activities during the lockdown impacted air quality parameters: A review

The health emergency linked to the spread of COVID-19 has led to important reduction in industrial and logistics activities, as well as to a drastic changes in citizens' behaviors and habits. The restrictions on working activities, journeys and relationships imposed by the lockdown have had important consequences, including for environmental quality. This review aims to provide a structured and critical evaluation of the recent scientific bibliography that analyzed and described the impact of lockdown on human activities and on air quality. The results indicate an important effect of the lockdown during the first few months of 2020 on air pollution levels, compared to previous periods. The concentrations of particulate matter, nitrogen dioxide, sulfur dioxide and carbon monoxide have decreased. Tropospheric ozone, on the other hand, has significantly increased. These results are important indicators that can become decision drivers for future policies and strategies in industrial and logistics activities (including the mobility sector) aimed at their environmental sustainability. The scenario imposed by COVID-19 has supported the understanding of the link between the reduction of polluting emissions and the state of air quality and will be able to support strategic choices for the future sustainable growth of the industrial and logistics sector.

Cause analysis of PM2.5 pollution during the COVID-19 lockdown in Nanning, China

To analyse the cause of the atmospheric PM_2.5 pollution that occurred during the COVID-19 lockdown in Nanning, Guangxi, China, a single particulate aerosol mass spectrometer, aethalometer, and particulate Lidar coupled with monitoring near-surface gaseous pollutants, meteorological conditions, remote fire spot sensing by satellite and backward trajectory models were utilized during 18–24 February 2020. Three haze stages were identified: the pre-pollution period (PPP), pollution accumulation period (PAP) and pollution dissipation period (PDP). The dominant source of PM_2.5 in the PPP was biomass burning (BB) (40.4%), followed by secondary inorganic sources (28.1%) and motor vehicle exhaust (11.7%). The PAP was characterized by a large abundance of secondary inorganic sources, which contributed 56.1% of the total PM_2.5 concentration, followed by BB (17.4%). The absorption Ångström exponent (2.2) in the PPP was higher than that in the other two periods. Analysis of fire spots monitored by remote satellite sensing indicated that open BB in regions around Nanning City could be one of the main factors. A planetary boundary layer-relative humidity-secondary particle matter-particulate matter positive feedback mechanism was employed to elucidate the atmospheric processes in this study. This study highlights the importance of understanding the role of BB, secondary inorganic sources and meteorology in air pollution formation and calls for policies for emission control strategies.

Impact of the COVID-19 lockdown on roadside traffic-related air pollution in Shanghai, China

The outbreak of COVID-19 has significantly inhibited global economic growth and impacted the environment. Some evidence suggests that lockdown strategies have significantly reduced traffic-related air pollution (TRAP) in regions across the world. However, the impact of COVID-19 on TRAP on roadside is still not clearly understood. In this study, we assessed the influence of the COVID-19 lockdown on the levels of traffic-related air pollutants in Shanghai. The pollution data from two types of monitoring stations-roadside stations and non-roadside stations were compared and evaluated. The results show that NO₂, PM_2.5, PM₁₀, and SO₂ had reduced by ~30-40% at each station during the COVID-19 pandemic in contrast to 2018-2019. CO showed a moderate decline of 28.8% at roadside stations and 16.4% at non-roadside stations. In contrast, O₃ concentrations increased by 30.2% at roadside stations and 5.7% at non-roadside stations. This result could be resulted from the declined NOx emissions from vehicles, which lowered O₃ titration. Full lockdown measures resulted in the highest reduction of primary pollutants by 34-48% in roadside stations and 18-50% in non-roadside stations. The increase in O₃ levels was also the most significant during full lockdown by 64% in roadside stations and 33% in non-roadside stations due to the largest decrease in NO₂ precursors, which promote O₃ formation. Additionally, Spearman's rank correlation coefficients between NO₂ and other pollutants significantly decreased, while the values between NO₂ and O₃ increased at roadside stations.

Air Quality in Southeast Brazil during COVID-19 Lockdown: A Combined Satellite and Ground-Based Data Analysis

With the current COVID-19 pandemic being spread all over the world, lockdown measures are being implemented, making air pollution levels go down in several countries. In this context, the air quality changes in the highly populated and trafficked Brazilian states of São Paulo (SP) and Rio de Janeiro (RJ) were addressed using a combination of satellite and ground-based daily data analysis. We explored nitrogen dioxide (NO2) and fine particulate matter (PM2.5) daily levels for the month of May from 2015–2020. Daily measurements of NO2 column concentrations from the Ozone Monitoring Instrument (OMI) aboard NASA’s Aura satellite were analyzed and decreases of 42% and 49.6% were found for SP and RJ, respectively, during the year 2020 compared to the 2015–2019 average. Besides NO2 column retrievals, ground-based data measured by the Brazilian States Environmental Institutions were analyzed and correlated with satellite retrievals. Correlation coefficients between year-to-year changes in satellite column and ground-based concentrations were 77% and 53% in SP and RJ, respectively. Ground-based data showed 13.3% and 18.8% decrease in NO2 levels for SP and RJ, respectively, in 2020 compared to 2019. In SP, no significant change in PM2.5 was observed in 2020 compared to 2019. To further isolate the effect of emissions reduction due to the lockdown, meteorological data and number of wildfire hotspots were analyzed. NO2 concentrations showed negative and positive correlations with wind speed and temperature, respectively. PM2.5 concentration distributions suggested an influence by the wildfires in the southeast region of the country. Synergistic analyses of satellite retrievals, surface level concentrations, and weather data provide a more complete picture of changes to pollutant levels.

Ambient PM2.5 Estimates and Variations during COVID-19 Pandemic in the Yangtze River Delta Using Machine Learning and Big Data

The lockdown of cities in the Yangtze River Delta (YRD) during COVID-19 has provided many natural and typical test sites for estimating the potential of air pollution control and reduction. To evaluate the reduction of PM2.5 concentration in the YRD region by the epidemic lockdown policy, this study employs big data, including PM2.5 observations and 29 independent variables regarding Aerosol Optical Depth (AOD), climate, terrain, population, road density, and Gaode map Point of interesting (POI) data, to build regression models and retrieve spatially continuous distributions of PM2.5 during COVID-19. Simulation accuracy of multiple machine learning regression models, i.e., random forest (RF), support vector regression (SVR), and artificial neural network (ANN) were compared. The results showed that the RF model outperformed the SVR and ANN models in the inversion of PM2.5 in the YRD region, with the model-fitting and cross-validation coefficients of determination R2 reached 0.917 and 0.691, mean absolute error (MAE) values were 1.026 μg m−3 and 2.353 μg m−3, and root mean square error (RMSE) values were 1.413 μg m−3, and 3.144 μg m−3, respectively. PM2.5 concentrations during COVID-19 in 2020 have decreased by 3.61 μg m−3 compared to that during the same period of 2019 in the YRD region. The results of this study provide a cost-effective method of air pollution exposure assessment and help provide insight into the atmospheric changes under strong government controlling strategies.

Air pollution impacts from COVID-19 pandemic control strategies in Malaysia

Mitigation measures and control strategies relating to novel coronavirus disease 2019 (COVID-19) have been widely applied in many countries in order to reduce the transmission of this pandemic disease. A Movement Control Order (MCO) was implemented in Malaysia starting from the March 18, 2020 as a pandemic control strategy which restricted all movement and daily outdoor activities. To investigate the impact of MCO, air pollutants: particulate matter with an aerodynamic diameter less than 10 μm (PM10), particulate matter with an aerodynamic diameter less than 2.5 μm (PM2.5), sulphur dioxide (SO2), nitrogen dioxide (NO2), ozone (O3) and carbon monoxide (CO) in nine major cities in Malaysia were measured before and during the implementation of the MCO. The non-carcinogenic health risk assessments of the air pollutants are also determined using the United States Environmental Protection Agency (USEPA) Health Risk Assessment method. Overall, NO2 recorded an average percentage reduction of 40% with the highest reduction observed at Kota Kinabalu (62%). The largest reductions of PM10, PM2.5, SO2, O3 and CO were recorded at Kota Kinabalu (17%), Kuantan (9.5%), Alor Star (38%), Kota Bharu (15%), and Ipoh (27%) respectively. All cities had hazard quotient (HQ) values of <1 suggesting no non-carcinogenic health effects. The highest HQ was observed for PM2.5 during the MCO period (4.53E-02) in Kuala Lumpur. An average hazard index (HI) value of 1.44E-01 (before the MCO) and 1.40E-01 (during the MCO) showed higher human health risks before the MCO than during the MCO. This study gives confidence to regulatory bodies that the reduction of human activities significantly reduces air pollution and increases human health and so good air pollution control strategies can provide crucial impacts, especially in reducing air pollution and improving human health.

Environmental impacts of shifts in energy, emissions, and urban heat island during the COVID-19 lockdown across Pakistan

Restrictions on human and industrial activities due to the coronavirus (COVID-19) pandemic have resulted in an unprecedented reduction in energy consumption and air pollution around the world. Quantifying these changes in environmental conditions due to government-enforced containment measures provides a unique opportunity to understand the patterns, origins and impacts of air pollutants. During the lockdown in Pakistan, a significant reduction in energy demands and a decline of ∼1786 GWh (gigawatt hours) in electricity generation is reported. We used satellite observational data for nitrogen dioxide (NO₂), carbon monoxide (CO), sulphur dioxide (SO₂), aerosol optical depth (AOD) and land surface temperature (LST) to explore the associated environmental impacts of shifts in energy demands and emissions across Pakistan. During the strict lockdown period (March 23 to April 15, 2020), we observed a reduction in NO₂ emissions by 40% from coal-based power plants followed by 30% in major urban areas compared to the same period in 2019. Also, around 25% decrease in AOD (at 550 nm) thickness in industrial and energy sectors was observed although no major decrease was evident in urban areas. Most of the industrial regions resumed emissions during the 3rd quarter of April 2020 while the urban regions maintained reduced emissions for a longer period. Nonetheless, a gradual increase has been observed since April 16 due to relaxations in lockdown implementations. Restrictions on transportation in the cities resulted in an evident drop in the surface urban heat island (SUHI) effect, particularly in megacities. The changes reported as well as the analytical framework provides a baseline benchmark to assess the sectoral pollution contributions to air quality, especially in the scarcity of ground-based monitoring systems across the country.

Positive effects of COVID-19 lockdown on air quality of industrial cities (Ankleshwar and Vapi) of Western India

On January 30, 2020, India recorded its first COVID-19 positive case in Kerala, which was followed by a nationwide lockdown extended in four different phases from 25th March to 31st May, 2020, and an unlock period thereafter. The lockdown has led to colossal economic loss to India; however, it has come as a respite to the environment. Utilizing the air quality index (AQI) data recorded during this adverse time, the present study is undertaken to assess the impact of lockdown on the air quality of Ankleshwar and Vapi, Gujarat, India. The AQI data obtained from the Central Pollution Control Board was assessed for four lockdown phases. We compared air quality data for the unlock phase with a coinciding period in 2019 to determine the changes in pollutant concentrations during the lockdown, analyzing daily AQI data for six pollutants (PM10, PM2.5, CO, NO2, O3, and SO2). A meta-analysis of continuous data was performed to determine the mean and standard deviation of each lockdown phase, and their differences were computed in percentage in comparison to 2019; along with the linear correlation analysis and linear regression analysis to determine the relationship among the air pollutants and their trend for the lockdown days. The results revealed different patterns of gradual to a rapid reduction in most of the pollutant concentrations (PM10, PM2.5, CO, SO2), and an increment in ozone concentration was observed due to a drastic reduction in NO2 by 80.18%. Later, increases in other pollutants were also observed as the restrictions were eased during phase-4 and unlock 1. The comparison between the two cities found that factors like distance from the Arabian coast and different industrial setups played a vital role in different emission trends.