Decrease In NO2 Concentration Research Articles

Spatio-temporal evaluation of air pollution using ground-based and satellite data during COVID-19 in Ecuador

The concentration of gases in the atmosphere is a topic of growing concern due to its effects on health, ecosystems etc. Its monitoring is commonly carried out through ground stations which offer high precision and temporal resolution. However, in countries with few stations, such as Ecuador, these data fail to adequately describe the spatial variability of pollutant concentrations. Remote sensing data have great potential to solve this complication. This study evaluates the spatiotemporal distribution of nitrogen dioxide (NO2) and ozone (O3) concentrations in Quito and Cuenca, using data obtained from ground-based and Sentinel-5 Precursor mission sources during the years 2019 and 2020. Moreover, a Linear Regression Model (LRM) was employed to analyze the correlation between ground-based and satellite datasets, revealing positive associations for O3 (R2 = 0.83, RMSE = 0.18) and NO2 (R2 = 0.83, RMSE = 0.25) in Quito; and O3 (R2 = 0.74, RMSE = 0.23) and NO2, (R2 = 0.73, RMSE = 0.23) for Cuenca. The agreement between ground-based and satellite datasets was analyzed by employing the intra-class correlation coefficient (ICC), reflecting good agreement between them (ICC ≥0.57); and using Bland and Altman coefficients, which showed low bias and that more than 95% of the differences are within the limits of agreement. Furthermore, the study investigated the impact of COVID-19 pandemic-related restrictions, such as social distancing and isolation, on atmospheric conditions. This was categorized into three periods for 2019 and 2020: before (from January 1st to March 15th), during (from March 16th to May 17th), and after (from March 18th to December 31st). A 51% decrease in NO2 concentrations was recorded for Cuenca, while Quito experienced a 14.7% decrease. The tropospheric column decreased by 27.3% in Cuenca and 15.1% in Quito. O3 showed an increasing trend, with tropospheric concentrations rising by 0.42% and 0.11% for Cuenca and Quito respectively, while the concentration in Cuenca decreased by 14.4%. Quito experienced an increase of 10.5%. Finally, the reduction of chemical species in the atmosphere as a consequence of mobility restrictions is highlighted. This study compared satellite and ground station data for NO2 and O3 concentrations. Despite differing units preventing data validation, it verified the Sentinel-5P satellite's effectiveness in anomaly detection. Our research's value lies in its applicability to developing countries, which may lack extensive monitoring networks, demonstrating the potential use of satellite technology in urban planning.

Trans-boundary spatio-temporal analysis of Sentinel 5P tropospheric nitrogen dioxide and total carbon monoxide columns over Punjab and Haryana Regions with COVID-19 lockdown impact.

This study conducts a spatio-temporal analysis of tropospheric nitrogen dioxide (NO2) and total carbon monoxide (CO) concentrations in the Punjab and Haryana regions of India and Pakistan, using datasets from the Sentinel 5-Precursor (S5P) satellite. These regions, marked by diverse economic growth factors including population expansion, power generation, transportation, and agricultural practices, face similar challenges in atmospheric pollution, particularly evident in major urban centers like Delhi and Lahore, identified as pollution hotspots. The study also spotlights pollution associated with power plants. In urban areas, tropospheric NO2 levels are predominantly elevated due to vehicular emissions, whereas residential activities mainly contribute to CO pollution. However, precisely attributing urban CO sources is complex due to its longer atmospheric residence time and intricate circulation patterns. Notably, the burning of rice crop residue in November significantly exacerbates winter pollution episodes and smog, showing a more pronounced correlation with total CO than with tropospheric NO2 levels. The temporal analysis indicates that the months from October to December witness peak pollution, contrasted with the relatively cleaner period during the monsoon months of July to September. The severe pollution in the OND quarter is attributed to factors such as variations in boundary layer height and depletion of OH radicals. Furthermore, the study highlights the positive impact of the COVID-19 lockdown on air quality, with a significant decrease in NO2 concentrations during April, 2020 (Delhi: 59%, Lahore: 58%). However, the reduction in total CO columns was less significant. The study also correlates lockdown stringency with tropospheric NO2 columns (R2: 0.37 for Delhi, 0.25 for Lahore, 0.22 for Rawalpindi/Islamabad), acknowledging the influence of various meteorological and atmospheric variables. The research highlights the significant impact of crop residue burning on winter pollution levels, particularly on total CO concentrations. The study also shows the notable effect of the COVID-19 lockdown on air quality, significantly reducing NO2 levels. Additionally, it explores the correlation between lockdown stringency and tropospheric NO2 columns, considering various meteorological factors.

Satellite unravels recent changes in atmospheric nitrogen oxides emissions from global ocean shipping

Nitrogen dioxide (NO2) in the lower marine atmosphere, mainly emitted by maritime shipping, plays a crucial role in air pollution formation and global human health. However, few measurements of marine atmospheric NO2 hinder knowledge of trace gas trends and atmospheric chemistry evolution due to shipping emissions. In this study, we use long-term satellite observations of tropospheric NO2 column from the European TROPOspheric Monitoring Instrument (TROPOMI) and the Chinese Environmental trace gases Monitoring Instrument (EMI) to analyze marine atmospheric NO2 variations, especially during the global COVID-19 pandemic and escalating geopolitical crises. First, we demonstrate the detection of NO2 enhancements along shipping routes, including the North Atlantic route, the North Pacific route, and the Cape route, indicating significant emissions of atmospheric NO2 from on-ocean shipping. Second, we observe and quantify the response of marine atmospheric NO2 concentrations to major shipping events, such as the Suez Canal blockage, the Los Angeles-Long Beach port congestion, and the Russia-Ukraine war, resulting in local NO2 concentration variations of approximately 40% decrease to 70% increase. Long-term analysis reveals reduced NO2 concentrations in most coastal ports and maritime shipping routes during the COVID-19 lockdown, with reductions exceeding 50% or durations lasting up to 200 days. However, some rapidly developing ports, such as Beibu Gulf (China) and Dakar (Senegal), did not experience a decrease in NO2 concentrations, suggesting that local authorities need to pay more attention to these fast-growing yet underestimated emission sources. In addition, by excluding the impact of meteorology using statistical models, we find that the current Emission Control Area (ECA) policies have effectively reduced NO2 concentrations in Chinese coastal ports. These results contribute to understanding spatiotemporal characteristics of marine atmospheric NO2, including ports and open-sea shipping routes, and guide further ECA policies to control marine NO2 pollution.

Consideration of Altered Anthropogenic Behavior during the First Lockdown and Its Effects on Air Pollutants and Land Surface Temperature in European Cities

Substantial reductions in human and economic activities such as road traffic for several months in 2020 were one of the consequences of the Coronavirus pandemic. This unprecedented change in urban metabolism also affected temperature and air pollutants. This study investigates the effects of the first COVID-19 lockdown across 43 cities in Europe. It determines the influence of anthropogenic activities on nitrogen dioxide (NO2), ozone (O3), and particulate matter (PM2.5), as well as on land surface temperature (LST) and the surface urban heat island intensity (SUHII) using satellite, modeled, and mobility data. Our findings show that there are great temporal and spatial differences and distinct patterns between the cities regarding the magnitude of change in the variables under study. In general, the results indicate a substantial decrease in NO2 concentrations in most of the studied cities compared with the reference period of 2015–2019. However, reductions could not be attributed to mobility changes such as less traffic at transit stations, contrary to the results of previous studies. O3 levels increased during the first lockdown in accordance with the decreasing NO2 concentrations. The PM pattern was inconsistent over time and space. Similar to the NO2 results, no relation to the altered mobility behavior was found. No clear signal could be detected for LST and the SUHII, likely due to dominating meteorological influences.

Assessment of variations in air quality in cities of Ecuador in relation to the lockdown due to the COVID-19 pandemic

This study analyzes the effect of lockdown due to COVID-19 on the spatiotemporal variability of ozone (O3), sulfur dioxide (SO2), and nitrogen dioxide (NO2) concentrations in different provinces of continental Ecuador using satellite information from Sentinel – 5P. The statistical analysis includes data from 2018 to March 2021 and was performed based on three periods defined a priori: before, during, and after lockdown due to COVID-19, focusing on the provinces with the highest concentrations of the studied gases (hotspots). The results showed a significant decrease in NO2 concentrations during the COVID-19 lockdown period in all the study areas: the Metropolitan District of Quito (DMQ) and the provinces of Guayas and Santo Domingo de los Tsáchilas. In the period after lockdown, NO2 concentrations increased by over 20% when compared to the pre-lockdown period, which may be attributable to a shift towards private transportation due to health concerns. On the other hand, SO2 concentrations during the lockdown period showed irregular, non-significant variations; however, increases were observed in the provinces of Chimborazo, Guayas, Santa Elena, and Morona Santiago, which could be partly attributed to the eruptive activity of the Sangay volcano during 2019–2020. Conversely, O3 concentrations increased by 2–3% in the study areas; this anomalous behavior could be attributed to decreased levels of NOx, which react with ozone, reducing its concentration. Finally, satellite data validation using the corresponding data from monitoring stations in the DMQ showed correlation values of 0.9 for O3 data and 0.7 for NO2 data, while no significant correlation was found for SO2.

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 (PM2.5) 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 PM2.5 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 PM2.5. 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 PM2.5 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.

COVID-19 Pandemic: Impacts on Air Quality during Partial Lockdown in the Metropolitan Area of São Paulo

Air pollution has become one of the factors that most affect the quality of life, human health, and the environment. Gaseous pollutants from motor vehicles have a significantly harmful effect on air quality in the Metropolitan Area of São Paulo (MASP)—Brazil. Motor vehicles emit large amounts of particulate matter (PM), carbon monoxide (CO), nitrogen oxides (NOx), and volatile organic compounds (VOCs), the last three acting as the main tropospheric ozone (O3) precursors. In this study, we evaluated the effects of these pollutants on air quality in the MASP during the partial lockdown that was imposed to ensure the social distancing necessitated by the COVID-19 pandemic. We compared the monthly data for nitrogen dioxide (NO2) from the Ozone Monitoring Instrument (OMI) and CO, SO2, and BC from MERRA-2 for the period between April and May 2020 (during the pandemic) with the average for the same period for the (pre-pandemic) years 2017 to 2019 in the southeast region of Brazil. The meteorological and pollutant concentration data from the CETESB air quality monitoring stations for the MASP were compared with the diurnal cycle of three previous years, with regard to the monthly averages of April and May (2017, 2018, and 2019) and the same period in 2020, when the partial lockdown was first imposed in southeast Brazil. Our findings showed that there was a decrease in NO2 concentrations ranging from 10% to more than 60% in the MASP and the Metropolitan Area of Rio de Janeiro (MARJ), whereas in the Metropolitan Area of Belo Horizonte and Vitoria (MABH and MAV, respectively), there was a reduction of around 10%. In the case of the concentrations of CO and BC from MERRA-2, there was a considerable decrease (approx. 10%) during the period of partial lockdown caused by COVID-19 throughout almost the entire state of São Paulo, particularly in the region bordering the state of Rio de Janeiro. The concentration of SO2 from MERRA-2 was 5 to 10% lower in the MASP and MARJ and the west of the MABH, and there was a decrease of 30 to 50% on the border between the states of São Paulo and Rio de Janeiro, while in the MAV region, there was an increase in pollutant levels, as this region was not significantly affected by the COVID-19 pandemic. Sharp reductions in the average hourly concentrations of CO (38.8%), NO (44.9%), NO2 (38.7%), and PM2.5 (6%) were noted at the CETESB air quality monitoring stations in the MASP during the partial lockdown in 2020 compared with the hourly average rate in the pre-pandemic period. In contrast, there was an increase of approximately 16.0% in O3 concentrations in urban areas that are seriously affected by vehicular emissions, which is probably related to a decrease in NOx.

MUNICH v2.0: a street-network model coupled with SSH-aerosol (v1.2) for multi-pollutant modelling

Abstract. A new version of a street-network model, the Model of Urban Network of Intersecting Canyons and Highways version 2.0 (MUNICH v2.0), is presented. The comprehensive aerosol model SSH-aerosol is implemented in MUNICH v2.0 to simulate the street concentrations of multiple pollutants, including secondary aerosols. The implementation uses the application programming interface (API) technology so that the SSH-aerosol version may be easily updated. New parameterisations are also introduced in MUNICH v2.0, including a non-stationary approach to model reactive pollutants, particle deposition and resuspension, and a parameterisation of the wind at roof level. A test case over a Paris suburb is presented for model evaluation and to illustrate the impact of the new functionalities. The implementation of SSH-aerosol leads to an increase of 11 % in PM10 concentration because of secondary aerosol formation. Using the non-stationary approach rather than the stationary one leads to a decrease in NO2 concentration of 16 %. The impact of particle deposition on built surfaces and road resuspension on pollutant concentrations in the street canyons is low.

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.

How the Volume of Traffic Affected Air Quality During the Extreme Event of COVID-19 Lockdown in a Small City

The extreme traffic measures during the COVID-19 lockdown provided a unique opportunity to gain better insight into the relationship between traffic characteristics and NO2 concentrations in Maribor, a small Slovenian city. NO2, traffic and meteorological data were statistically processed in detail for March and April 2018, 2019 and 2020 to get a historical insight and to exclude the specifics of the lockdown period. The extreme event resulted in an average reduction of road traffic of 42%. The decrease in the number of passenger cars ranged from 33.9 to 60.3% per day with the largest decrease on the motorway. Daily averages of heavy goods traffic declined on the motorway and the expressway by 24.6% and 7%, respectively. Traffic characteristics were reflected in a 24–27% decrease in NO2 concentrations at the urban station. The change is smaller than the change in traffic volume, which could be explained by the change in the composition of the vehicle fleet due to the increase in NO2-dominant traffic sources, e.g. diesel heavy goods vehicles. The presented results are relevant for improving air quality and sustainable mobility management in small cities. They highlight the important role of reorganisation of heavy goods traffic in urban logistics.

Investigating effect of COVID-19 on NO2 density using remote sensing products (case study: Tehran province)

The first case of COVID-19 was detected in Iran on February 19, 2020. From the beginning of the pandemic, some restrictions have been imposed to reduce the spread of the pandemic, which have led to the reduction or temporary closure of some industrial, construction, and transportation sectors. These sectors are typically some sources of pollutants induced to the atmosphere. The purpose of this study was to investigate the impact of the restrictions caused by the pandemic, on the concentration of nitrogen dioxide (NO2) in the atmosphere of Tehran province. Average daily and monthly NO2 concentrations from the TROPOMI sensor of Sentinel-5P satellite before and after the pandemic (i.e., February 20 to August 19, 2020, and February 20 to August 19, 2019) were used. The results showed that the average NO2 concentration in the mentioned period in 2020 was equal to 168.09 μmol/m2, which compared to 2019 (195.11 μmol/m2), had a decrease of 13.85%. Therefore, the imposed restrictions to reduce the prevalence of COVID-19 in Tehran province have an impact on the temporary decrease in NO2 concentration. It is recommended that after the end of the pandemic and the reconstruction of economic and industrial activities, measures will be taken to monitor the urban environmental loads and improve the air quality.

COVID-19 Lockdown Unravels the Complex Interplay between Environmental Conditions and Human Activity

During the COVID-19 epidemic, draconian countermeasures forbidding nonessential human activities have been adopted in several countries worldwide, providing an unprecedented setup for testing and quantifying the current impact of humankind on climate and for driving potential sustainability policies in the postpandemic era from a perspective of complex systems. In this study, we consider heterogeneous sources of environmental and human activity observables, considered as components of a complex socioenvironmental system, and apply information theory, network science, and Bayesian inference to analyze their structural relations and nonlinear dynamics between January 2019 and August 2020 in northern Italy, i.e., before, during, and after the national lockdown. The topological structure of a complex system strongly impacts its collective behavior; therefore, mapping this structure is essential to fully understand the functions of the system as a whole and its fragility to unexpected disruptions or shocks. To this aim, we unravel the causal relationships between the 16 environmental conditions and human activity variables, mapping the backbone of the complex interplay between intervening physical observables—such as NO2 emissions, energy consumption, intervening climate variables, and different flavors of human mobility flows—to a causal network model. To identify a tipping point during the period of observation, denoting the presence of a regime shift between distinct network states (i.e., before and during the shock), we introduce a novel information-theoretic method based on statistical divergence widely used in statistical physics. We find that despite a measurable decrease in NO2 concentration, due to an overall decrease in human activities, locking down a region as a climate change mitigation is an insufficient remedy to reduce emissions. Our results provide a functional characterization of socioenvironmental interdependent systems, and our analytical framework can be used, more generally, to characterize environmental changes and their interdependencies using statistical physics.

Global fine-scale changes in ambient NO2 during COVID-19 lockdowns

Nitrogen dioxide (NO2) is an important contributor to air pollution and can adversely affect human health1–9. A decrease in NO2 concentrations has been reported as a result of lockdown measures to reduce the spread of COVID-1910–20. Questions remain, however, regarding the relationship of satellite-derived atmospheric column NO2 data with health-relevant ambient ground-level concentrations, and the representativeness of limited ground-based monitoring data for global assessment. Here we derive spatially resolved, global ground-level NO2 concentrations from NO2 column densities observed by the TROPOMI satellite instrument at sufficiently fine resolution (approximately one kilometre) to allow assessment of individual cities during COVID-19 lockdowns in 2020 compared to 2019. We apply these estimates to quantify NO2 changes in more than 200 cities, including 65 cities without available ground monitoring, largely in lower-income regions. Mean country-level population-weighted NO2 concentrations are 29% ± 3% lower in countries with strict lockdown conditions than in those without. Relative to long-term trends, NO2 decreases during COVID-19 lockdowns exceed recent Ozone Monitoring Instrument (OMI)-derived year-to-year decreases from emission controls, comparable to 15 ± 4 years of reductions globally. Our case studies indicate that the sensitivity of NO2 to lockdowns varies by country and emissions sector, demonstrating the critical need for spatially resolved observational information provided by these satellite-derived surface concentration estimates.

653 The impact of the COVID-19 pandemic on hospitalizations for acute myocardial infarction: the experience of the Clinical Cardiology Unit, University Hospital of Cagliari

AimsDuring the COVID-19 pandemic, hospitalization rates for acute myocardial infarction (AMI) decreased worldwide. The aim of the study is to evaluate the impact of the COVID-19 pandemic on the admission rate for AMI to our academic hospital, to monitor the trend during the reopening phase and to evaluate if whether changes in air pollution may have influenced hospitalization rates for AMI in Sardinia and Northern Italy.Methods and resultsWe compared the admission rate for AMI in our department and, by analysing the density of nitrogen dioxide (1/cm2), the state of air pollution in Sardinia and Northern Italy in different periods: the national lockdown (9 March–3 May 2020), the 8 weeks before the start of the lockdown, the 8 weeks after the end of the lockdown and the corresponding time period in 2019 (from 9 March to 3 May 2019). A marked decline in AMI admissions was observed during the lockdown period in comparison with the 8 weeks before the start of the lockdown (−47%, 95% CI: 37.5–56.7, P < 0.0001) and the corresponding period in 2019 (−52.8%, 95% CI: 43–65, P < 0.0001). There was a significant reduction in hospitalizations for NSTEMI during the lockdown period in comparison with the 8 weeks before the start of lockdown (−71.8%, 95% CI: 62.3–79.6, P < 0.0001) and the corresponding time period in 2019 (−70.5%, 95% CI: 60.9–78.5, P < 0.0001). Similar trends were seen in the group of STEMI patients, but the fall in admissions was less than that of NSTEMI patients. During the lockdown period, the hospitalizations for STEMI fell by 31.5% (95% CI: 23.2–41.4, P = 0.19) and 49% (95% CI: 39.4–58.6, 47 vs. 24 admissions, P = 0.009) in comparison to the 8 weeks before the start of lockdown and the corresponding period in 2019, respectively. We observed a rise in AMI admissions during the 8 weeks after the lockdown (+47%, 95% CI: 37.5–56.7, P < 0.0001), for both NSTEMI (+71.2%, 95% CI: 61.7–79.1, P < 0.0001) and STEMI (+33.4%, 95% CI: 24.9–43.1, P = 0.15). In Sardinia the relative change in nitrogen dioxide density during the time of lockdown was negligible with little or no impact on the environment (−19%, 95% CI: 12.5–27.7, P = 0.65), if we consider it occurred within a range of very low values of nitrogen dioxide (11.5 ± 3 e 14.1 ± 5 μmol/m2). In contrast, in Northern Italy during the lockdown there was a marked decrease in NO2 concentration in comparison with the 8 weeks before the start of lockdown (−53%, 95% CI: 43–62.4, 25.1 ± 16.2 e 54.2 ± 43.5 μmol/m2, P < 0.0001).ConclusionsSince air pollution did not change substantially in our region, the environment factor cannot explain the decline in the number of admissions for AMI we recorded during the lockdown. Fear of contagion is the most plausible reason for the drop of hospitalizations for AMI during the lockdown period.

Environmental implications of reduced electricity consumption in Wuhan during COVID-19 outbreak: A brief study.

Due to the COVID-19 outbreak, Wuhan was locked down from 23 January 2020 to 8 April 2020, a total of 76 days. It is well known that the electricity consumption is a direct reflection of human activity. During the lockdown of Wuhan, most of human activities were forbidden. The reduction in human activity would inevitably lead to a reduction in electricity consumption. At the same time, anthropogenic emissions of air pollutants would also be reduced with the reduction of human activity. In this study, the correlation between electricity consumption and air pollutants during lockdown was discussed in detail. The result showed that the drop in pollutants concentrations in January should be attributed to the washout effect of rainfall rather than the lockdown. The decrease of electricity consumption in the secondary industry might play a significant role on the decrease of PM and NO2 concentrations in Wuhan in February 2020. The decrease in NO2 concentration in March should be attributed to the reduction of pollutants emissions from the tertiary industry, which means that more attention should be paid to the control of NO2 emission in the tertiary industry. Due to reduced emissions from local sources, the role of long-range transport sources might be more significant during the lockdown of Wuhan. By PSCF analysis, southeast of Wuhan could be the major potential emission sources of PM, especially in the northern part of Jiangxi province. It was suggested that stricter regulation of pollutants emissions should be implemented in this area.

Impact of the COVID-19 Lockdown on Air Quality Trends in Guiyang, Southwestern China

The absence of motor vehicle traffic and suspended human activities during the COVID-19 lockdown period in China produced a unique experiment to assess the efficiency of air pollution mitigation. Herein, we synthetically analyzed monitoring data of atmospheric pollutants together with meteorological parameters to investigate the impact of human activity pattern changes on air quality in Guiyang, southwestern China. The results show that the Air Quality Index (AQI) during the lockdown period decreased by 7.4% and 23.48% compared to pre-lockdown levels and the identical lunar period during the past 3 years, respectively, which exhibited optimal air quality due to reduced emissions. The sharp decrease in NO2 concentration reduced the “titration” effect and elevated the O3 concentration by 31.94% during the lockdown period. Meteorological conditions significantly impacted air quality, and serious pollution events might also occur under emission reductions. Falling wind speeds and increasing relative humidity were the direct causes of the pollution event on February 1st. The “first rain” increases the hygroscopicity of atmospheric particulate matter and then elevate its concentration, while continuous rainfall significantly impacted the removal of atmospheric particulate matter. As impacted by the lockdown, the spatial distribution of the NO2 concentration sharply decreased on the whole, while the O3 concentration increased significantly. The implications of this study are as follows: Measures should be formulated to prevent O3 pollution when emission reduction measures are being adopted to improve air quality, and an emphasis should be placed on the impact of secondary aerosols formation by gas-particle conversion.

Impact of COVID-19 Lockdown on Air Pollutants in a Coastal Area of the Yangtze River Delta, China, Measured by a Low-Cost Sensor Package

Ningbo is a major coastal city in the Yangtze River Delta region, China, with the largest cargo capacity in the world. We conducted a field campaign in Ningbo to measure the impact of the COVID-19 lockdown on air pollutants including NO2, O3 and CO from 21 January to 23 March 2020, using a home-made low-cost sensor package. The average concentrations of NO2, O3 and CO were observed to be 7.2, 37.5 and 648.5 ppb, respectively, during the lockdown. Compared with the previous year, the concentrations of NO2 and CO decreased by 63.1% and 6.9%, while the concentration of O3 increased by 37.9%. The significant reduction of NO2 concentration may be attributed to the reduced emissions of freighters and heavy trucks with lower port cargo throughput, which led to a decrease of NO concentration. The increase of O3 concentration was probably due to the lower titration of O3 by NO. After the lockdown, the concentrations of O3 and NO2 increased by 15.5% and 143.1%, respectively, compared with those during the lockdown. The temporal variations of the concentrations of NO2, O3 and CO measured by the sensor package were coincident with those obtained by the reference apparatus, which proves the sensor package to be suitable for air quality monitoring in field campaigns. This is the first time that a dramatic decrease in NO2 concentration in a coastal city due to a lockdown has been reported.

Reductions in nitrogen oxides over the Netherlands between 2005 and 2018 observed from space and on the ground: Decreasing emissions and increasing O3 indicate changing NOx chemistry

Satellite measurements of tropospheric NO2 columns are valuable for monitoring long-term changes in air quality. However, direct linkage of satellite-derived NO2 trends with changes in underlying NOx emissions and NOx surface concentrations is complicated by the contribution of background NO2 to the column, by changes in the chemical regime wherein emissions take place, and by data sampling differences. Here we study the 2005–2018 changes in nitrogen oxides concentrations over the polluted Netherlands. We use the QA4ECV OMI NO2 retrievals, RIVM surface measurements of NO, NO2, and O3, wet deposition fluxes of nitrate, and NOx emissions reported in two European inventories (EMEP and TNO-MACC-III). We interpret the observed changes in concentrations with simulations by CLASS, a box model accounting for boundary layer dynamics and chemistry. Nationally averaged, OMI column NO2 and RIVM surface NO2 concentrations are reduced by 30% and 32% respectively between 2005 and 2018. This is in line with Dutch national NOx emissions from the TNO-MACC-III and EMEP inventories showing decreases of 32%–39%, respectively, between 2005 and 2018. There is no indication that the decrease in NO2 concentrations slows down after 2010. The observed reductions in nitrogen oxides differ between winter and summer and turn out to be modulated by ozone chemistry. The RIVM surface measurements show a stronger reduction in NOx than in NO2, accompanied by an increase in O3 of 4–6 ppbv, which is due to diminished NO-titration following the lower NOx emissions, especially in winter. CLASS simulations confirm that daytime O3 increases have shifted the NO–NO2 equilibrium more towards NO2, explaining the weaker reductions in NO2 (−30%) than in NOx (−40%) concentrations over time. The O3 increases occur both during day and during night, and have likely shortened the NOx lifetimes both in summer (via faster OH + NO2+M during daytime) and in winter (via faster nighttime N2O5 formation and subsequent hydrolysis). Our findings suggest a reduction in anthropogenic NOx emissions of approximately 30% in the southern part of the Netherlands, and propose that interpreting satellite NO2 trends as a proxy for trends in NOx emissions is well-possible over a high-NOx region, but requires careful analysis in terms of changes in the chemical regimes and NOx lifetime.

Analysis of lockdown for CoViD-19 impact on NO2 in London, Milan and Paris: What lesson can be learnt?

Nitrogen dioxide (NO2) can have harmful effects on human health and can act as a precursor for the formation of other air pollutants in urban environment such as secondary PM2.5 and ozone. The lockdown measures for CoViD-19 allowed to simulate on a large scale the massive and prolonged reduction of road traffic (the main source for NO2 in urban environment). This work aims to selectively assess the maximum impact that total traffic blocking measures can have on NO2. For this reason, three megacities (London, Milan and Paris) were chosen which had similar characteristics in terms of climatic conditions, population, policies of urban traffic management and lockdown measures. 52 air quality control units have been used to compare data measured in lockdown and in the same periods of previous years, highlighting a significant decrease in NO2 concentration due to traffic (London: 71.1 % - 80.8 %; Milan: 8.6 % - 42.4 %; Paris: 65.7 % - 79.8 %). In 2020 the contribution of traffic in London, Milan and Paris dropped to 3.3 ± 1.3 μg m−3, 6.1 ± 0.8 μg m−3, and 13.4 ± 1.5 μg m−3, respectively. Despite the significant reduction in the NO2 concentration, in UT stations average NO2 concentrations higher than 40 μg m−3 were registered for several days. In order to reduce the pollution, the limitation of road traffic could be not enough, but a vision also aimed at rethink the vehicles and their polluting effects should be developed.

Modeling the Effect of COVID-19 Lockdown on Mobility and NO2 Concentration in the Lombardy Region

Recent observation and modeling-based studies have shown how air quality has been positively affected by the containment measures enforced due to the COVID-19 outbreak. This work aims to analyze Lombardy’s NO2 atmospheric concentration during the spring lockdown. The region of Lombardy is known for having the largest number of residents in Italy and high levels of pollution. It is also the region where the first European confinement measures were imposed by the Italian government. The modeling suite composed of CAMx (Comprehensive Air Quality Model with Extensions) and WRF (Weather Research and Forecasting model) provides the setting to compare the atmospheric NO2 concentration from mid-February to the end of March with a business as usual situation. The main interest in this work is to investigate the response of NO2 atmospheric concentration to increasingly reduced road traffic. We can simulate, for the first time, a real circumstance of progressively reduced mobility, as well as validating it with measured air quality data. Focusing on the city of Milan, we found that the decrease in NO2 concentration reflects progressively reduced traffic contraction. In the case of a large traffic abatement (71%), the concentration level is reduced by one third. We also find that industrial activities have a relevant impact on NO2 atmospheric concentration, especially in the provinces of Brescia and Bergamo. This study provides an overview of how incisive policies must be implemented to achieve the set environmental targets and protect human health.