Reduction In NO2 Research Articles

Well-planned greenery improves air urban quality - Modelling the effect of altered airflow and pollutant deposition

Urban air quality is influenced by vegetation through alterations in airflow and pollutant deposition processes. We investigated these interactions by integrating the Vegetation Impact Dynamic Assessment model (VIDA) with the Large-Eddy Simulation model PALM. Our analysis focus on nitrogen dioxide (NO₂) and particulate matter (PM) concentrations at the local scale, considering three tree genera. Our findings reveal the necessity of accounting for both gaseous pollutants and particles separately due to their differing mechanisms of deposition onto leaves. The coupled PALM-VIDA model demonstrates a significant reduction in PM levels across the modelling domain and within street canyons when deposition to vegetation is incorporated. Reduction in NO₂ through deposition to vegetation is lower but human NO2 exposure can still be decreased if tree species selection and placement leads to desirable effects on air flow. Sparse tree arrangements or species with sparse crowns facilitate ventilation and are often better at reducing NO₂ concentrations in street canyons compared to denser vegetation with higher deposition but negative effects on ventilation. Our study informs urban planning and green infrastructure design, underscoring the multifaceted role of urban greenery in air pollution mitigation strategies. Its main conclusion is that both deposition processes and the influence of air mixing and ventilation need to be considered to accurately assess the effects of urban trees on local air quality. Ill-considered placement and species selection may cause a net increase in pollutants underneath the trees. However, careful planning can address this risk and instead improve overall air quality.

Characterization of air pollution and associated health risks in Gansu Province, China from 2015 to 2022

Air pollution poses a major threat to both the environment and public health. The air quality index (AQI), aggregate AQI, new health risk–based air quality index (NHAQI), and NHAQI-WHO were employed to quantitatively evaluate the characterization of air pollution and the associated health risk in Gansu Province before (P-I) and after (P-II) COVID-19 pandemic. The results indicated that AQI system undervalued the comprehensive health risk impact of the six criteria pollutants compared with the other three indices. The stringent lockdown measures contributed to a considerable reduction in SO2, CO, PM2.5, NO2 and PM10; these concentrations were 43.4%, 34.6%, 21.4%, 17.4%, and 14.2% lower in P-II than P-I, respectively. But the concentration of O3 had no obvious improvement. The higher sandstorm frequency in P-II led to no significant decrease in the ERtotal and even resulted in an increase in the average ERtotal in cities located in northwestern Gansu from 0.78% in P-I to 1.0% in P-II. The cumulative distribution of NHAQI-based population-weighted exposure revealed that 24% of the total population was still exposed to light pollution in spring during P-II, while the air quality in other three seasons had significant improvements and all people were under healthy air quality level.

Time series analysis of COVID-19 stringency measures on the spatio- temporal dynamics of air pollution

Introduction: Execution of COVID-19 lockdown measures caused variations in air pollution worldwide. This paper investigates the impact of COVID-19 stringency measures on the spatio-temporal dynamics of air pollution in Mumbai, India, using a comprehensive two-and-a-half-year pandemic period dataset. Materials and methods: We classified the pandemic period into 7 phases and 21 sub-phases based on the severity of the Oxford COVID-19 Government Response Tracker (OxCGRT) Stringency Index (SI). Optimized Hotspot analysis (OHS) and Ordinary Least Square Regression models explored the spatio-temporal fluctuations and the effect of stringency measures on air quality. Results: The R2 value varied; with the best model R2 of 0.61 for Particulate Matters (PM10) and Nitrogen dioxide (NO2) and lowest of 0.23 for Sulfur dioxide (SO2). A 10-point increase in SI caused a 3-7% reduction in air pollutants. Substantial reduction in average PM10, PM2.5, NO2, and Carbon monoxide (CO) was observed throughout the COVID-19 phases. Meteorology and SI collectively caused maximum reduction of 82.6%, 72.7%, 53.8%, 52.2%, 49.1%, 28.4% for NO2, PM2.5, PM10, NH3, CO, and SO2 respectively, during complete or extreme lockdown phases. Except SO2, seasonality significantly influenced the pollutant concentrations. Winter was the worst period while monsoon was the best. OHS identified central Mumbai wards as hotspots and areas close to the national park as coldspots. Conclusion: PM10, NO2 and CO were more affected by SI measures than NH3 and SO2. For a rapid emergency response to high PM10, implementation of SI, very high (≥ 80 score) and above is advised. Findings of this study have significant public health policy implications, especially among global south nations.

Associations between long-term exposure to air pollution and kidney function utilizing electronic healthcare records: a cross-sectional study

BackgroundChronic kidney disease (CKD) affects more than 38 million people in the United States, predominantly those over 65 years of age. While CKD etiology is complex, recent research suggests associations with environmental exposures.MethodsOur primary objective is to examine creatinine-based estimated glomerular filtration rate (eGFRcr) and diagnosis of CKD and potential associations with fine particulate matter (PM2.5), ozone (O3), and nitrogen dioxide (NO2) using a random sample of North Carolina electronic healthcare records (EHRs) from 2004 to 2016. We estimated eGFRcr using the serum creatinine-based 2021 CKD-EPI equation. PM2.5 and NO2 data come from a hybrid model using 1 km2 grids and O3 data from 12 km2 CMAQ grids. Exposure concentrations were 1-year averages. We used linear mixed models to estimate eGFRcr per IQR increase of pollutants. We used multiple logistic regression to estimate associations between pollutants and first appearance of CKD. We adjusted for patient sex, race, age, comorbidities, temporality, and 2010 census block group variables.ResultsWe found 44,872 serum creatinine measurements among 7,722 patients. An IQR increase in PM2.5 was associated with a 1.63 mL/min/1.73m2 (95% CI: -1.96, -1.31) reduction in eGFRcr, with O3 and NO2 showing positive associations. There were 1,015 patients identified with CKD through e-phenotyping and ICD codes. None of the environmental exposures were positively associated with a first-time measure of eGFRcr < 60 mL/min/1.73m2. NO2 was inversely associated with a first-time diagnosis of CKD with aOR of 0.77 (95% CI: 0.66, 0.90).ConclusionsOne-year average PM2.5 was associated with reduced eGFRcr, while O3 and NO2 were inversely associated. Neither PM2.5 or O3 were associated with a first-time identification of CKD, NO2 was inversely associated. We recommend future research examining the relationship between air pollution and impaired renal function.

Machine learning elucidates ubiquity of enhanced ozone air pollution in China linked to the spring festival effect

Emissions' impact on ozone pollution is a focal point in atmospheric chemistry. The Chinese Spring Festival (CSF) effect offers a unique opportunity to study short-term emission reductions realistically. We conducted a comprehensive analysis using data from the national air quality observation platform and TROPOMI satellite observations of tropospheric formaldehyde (HCHO) and nitrogen dioxide (NO2) column concentrations before and during the CSF from 2015 to 2022. Satellite observations during the Spring Festival revealed a 13% reduction in HCHO and a 9% reduction in NO2 compared to the pre-CSF period. To comprehend the CSF effect on ozone precursor emissions, a random forest model accounting for meteorological effects was employed. CSF-induced emission reductions led to NO2 concentration decreases of −24.1%, −17.5%, −9.9%, and −12.6% in the Yangtze River Delta (YRD), Pearl River Delta (PRD), Beijing-Tianjin-Hebei (BTH), and Sichuan Basin (SCB), respectively. Conversely, BTH and YRD regions experienced substantial emission-driven ozone concentration increases of 6.7% and 4.9%. Assessing regional ozone generation sensitivity during the CSF, the BTH, YRD, and SCB fell within the VOC-limited regime. Our study underscores the CSF effect's significant impact on ozone pollution. Given the non-linear relationship between ozone and its precursors, it emphasizes the necessity of adopting synergistic abatement strategies to mitigate the escalating ozone pollution.

Impact of urban spatial factors on NO2 concentration based on different socio-economic restriction scenarios in U.S. cities

The impact of socio-economic restriction measures in the United States showed a significant reduction in nitrogen dioxide (NO2) emissions due to the changes in commuting patterns, travel restrictions, and reduced social and economic activities. The data from 60 observation stations across different states representing of different urban settings were used to assess the impacts of dynamic changes in human mobility and static emission sources on NO2 concentrations. Two predictive models, Seasonal Autoregressive Integrated Moving Average with eXogenous (SARIMAX) and Long Short-Term Memory (LSTM), were used to forecast NO2 concentrations under a counterfactual scenario in the assumption of no lockdown was implemented. The predicted concentrations were then compared to the observed concentrations to evaluate the difference between the two scenarios, during lockdown and after lockdown by using the last five-years (2015–2019) average as baseline. Results showed that reduction in NO2 varied across stations due to a combination of factors such as human mobility, population density, income, local climate, and stationary sources of NO2 emissions in the neighbourhood. The stations located in high-income regions with higher population density experienced a greater reduction in mobility, resulting in a greater variation in NO2 levels during both periods. In contrast, stations in densely populated low-income regions experienced lower variation in mobility and NO2 levels during the lockdown period but showed recovery during the post-lockdown period. Stations located outside the city with very low population density experienced no significant reduction in NO2 emissions. The study highlights the disparities in NO2 reduction and income inequality exposed by the pandemic, which may have scientific impacts on air quality and health disparities.

Assessing the Impact of COVID-19 Lockdown on Air Pollutants and Wildfires in China

This research paper focuses on the impact of COVID-19 lockdown on air pollutants and wildfires in various provinces of China. The study uses machine learning techniques to analyze the association between lockdown restrictions and the subsequent decline in air pollution emissions, which in turn led to a reduction in fire count (FC). The frequency and severity of wildfires have been rising in China, with major negative effects on the country's air quality. Globally unprecedented responses to the COVID-19 epidemic have included lockdowns and limitations on human activity. The purpose of this study is to evaluate how the COVID-19 lockdown has affected air pollutants and wildfires in China. Specially, the focus is on the reduction in ozone (O3), nitrogen dioxide (NO2), and carbon monoxide (CO) levels in the air. Satellite images were used before and during the lockdown to gauge the impact. The observed reduction in NO2, O3 and CO concentrations during the COVID-19 lockdown demonstrate the potential advantages of taking action to reduce air pollution. The study tries to find connections between the incidence of wildfires and the subsequent emission of air pollutants using machine learning methods. The study creates maps showing the influence of lockdown restrictions on the levels of air pollutants and the number of fires by analyzing historical data on air pollution measurements. These findings highlight the significance of sustainable practices, environmental regulations and offer insightful information regarding the interaction between human activities, air pollutants and wildfires in China.

The impact of COVID-19 lockdowns on urban photochemistry as inferred from TROPOMI

Movement restrictions were imposed in 2020 to mitigate the spread of Covid-19. These lock-down episodes provide a unique opportunity to study the sensitivity of urban photochemistry to temporary emission reductions and test air quality models. This study uses Tropospheric Monitoring Instrument (TROPOMI) nitrogen dioxide/carbon monoxide (NO2/CO) ratios in urban plumes in combination with an exponential fitting procedure to infer changes in the NOx lifetime (τNOx) during Covid-19 lock-downs in the cities of Denver, Chicago, New York, Riyadh, Wuhan and Sao Paulo compared with the year before.The strict lockdown policy in Wuhan led to a 65–80% reduction in NO2, compared to 30–50% in the other cities that were studied. In New York and Wuhan, CO concentration was reduced by 10–15%, whereas over Riyadh, Denver, Chicago, and Sao Paulo the CO background concentration increased by 2–5 ppb. τNOx has been derived for calm (0.0 < U (m/s) < 3.5) and windy (5.0 < U (m/s) < 8.5) days to study the influence of wind speed. We find reductions in τNOx during Covid-19 lockdowns in all six megacities during calm days. The largest change in τNOx during calm days is found for Sao-Paulo (31.8 ± 9.0%), whereas the smallest reduction is observed over Riyadh (22 ± 6.6%). During windy days, reductions in τNOx are observed during Covid-19 lockdowns in New York and Chicago. However, over Riyadh τNOx is almost similar for windy days during the Covid-19 lockdown and the year before.Ground-based measurements and the Chemistry Land-surface Atmosphere Soil Slab (CLASS) model have been used to validate the TROPOMI-derived results over Denver. CLASS simulates an enhancement of ozone (O3) by 4 ppb along with reductions in NO (38.7%), NO2 (25.7%) and CO (17.2%) during the Covid-19 lockdown in agreement with the ground-based measurements. In CLASS, decreased NOx emissions reduce the removal of OH in the NO2 + OH reaction, leading to higher OH concentrations and decreased τNOx. The reduction in τNOx inferred from TROPOMI (28 ± 9.0%) is in agreement with CLASS. These results indicate that TROPOMI derived NO2/CO ratios provide useful information about urban photochemistry and that changes in photochemical lifetimes can successfully be detected.

Impacts of net zero policies on air quality in a metropolitan area of the United Kingdom: Towards world health organization air quality guidelines

Climate change and air pollution are closely interlinked since carbon dioxide and air pollutants are co-emitted from fossil fuel combustion. Net Zero (NZ) policies aiming to reduce carbon emissions will likely bring co-benefits in air quality and associated health. However, it is unknown whether regional NZ policies alone will be sufficient to reduce air pollutant levels to meet the latest 2021 World Health Organisation (WHO) guidelines. Here, we carried out high resolution air quality modelling for in the West Midlands region, a typical metropolitan area in the UK, to quantify the effects of different NZ policies on air quality. Results show that NZ policies will significantly improve air quality in the West Midlands, with up to 6 μg m−3 (21%) reduction in annual mean NO2 (mostly through the electrification of vehicle fleet, EV) and up to 1.4 μg m−3 (12%) reduction in annual mean PM2.5 projected for 2030 relative to levels under a “business as usual” (BAU) scenario. Under BAU, 2030 PM2.5 concentrations in most wards would be below 10 μg m−3 whilst under the Net Zero scenario, those in all wards would be below 10 μg m−3. This means that the ward averages in the West Midlands would meet the UK PM2.5 of 10 μg m−3target a decade early under the Net Zero scenario. However, no ward-level-averaged annual mean PM2.concentrations meet the 2021 WHO Air Quality guideline level of 5 μg m−3 under any scenario. Similarly for NO2 only 18 wards (8% of the region's population) are predicted to have NO2 concentrations below the 2021 WHO guideline level (10 μg m−3). Decarbonisation policies linked to Net Zero deliver substantial regional air quality benefits, but are not in isolation sufficient to deliver clean air with air pollutant levels low enough to meet the 2021 WHO guidelines.

Changes in Tropospheric Nitrogen Dioxide Vertical Column Densities over Japan and Korea during the COVID-19 Using Pandora and MAX-DOAS

We investigated the impact of human activity during COVID-19 on the tropospheric nitrogen dioxide vertical column density (NO2 TropVCD) at three urban sites (Gwangju and Busan in Korea and Yokosuka in Japan) and one remote site (Cape Hedo in Japan) from Multi-Axis Differential Optical Absorption Spectroscopy (MAX-DOAS) and Pandora. Compared to the monthly mean NO2 TropVCD from 2015 to 2018 and in 2019, the values were lower in 2020 due to social distancing in Korea and Japan. High negative relative changes were observed from May to September (−30% to −18%) at the three urban sites; Cape Hedo, a remote site, did not show a significant difference in relative changes between previous years and 2020, suggesting that only anthropogenic emission sources decreased dramatically. In the case of Yokosuka, the 15-day moving average of the NO2 TropVCD exhibited a good relationship with transportation (R = 0.48) and industry (R = 0.54) mobility data. In contrast, the NO2 TropVCD at the Korean sites showed a moderate to low correlation with the industrial sector and insignificant correlations with transportation. The differences in correlations might be caused by the different social distancing policies in Korea (voluntary) and Japan (mandatory). By applying generalized boosted models to exclude meteorological and seasonal effects associated with NO2 TropVCD variations, we revealed that the decreasing trend from 2019 to 2020 was much steeper than that from 2015 to 2020 (a factor of two), and a significant change was identified in January 2020, when the first cases of COVID-19 were observed in both Korea and Japan. This result confirmed that the reduction in NO2 can be largely explained by the NOx emission reduction resulting from social distancing for COVID-19 rather than annual meteorological differences; however, in December 2020, NO2 recovered suddenly to its previous level due to an increase in human activities.

A study of nitrogen dioxide (NO2) periodicity over the United Arab Emirates using wavelet analysis

NO2 and nitric oxide (NO) are the most reactive gases in the atmosphere. The interaction of NOx molecules with oxygen, water and other chemicals leads to the formation of acid rain. The presence of NO2 in the air affects human health and forms a photochemical smog. In this study, we utilize wavelet analysis, namely, the Morlet wavelet, which is a type of continuous wavelet transform, to conduct a spectral analysis of the periodicity of nitrogen dioxide (NO2). The study is conducted using data from 14 weather stations located in diverse geographic areas of the United Arab Emirates (UAE) over a period of two years (2019 and 2020). We explain and relate the significance of human activities to the concentration level of NO2, particularly considering the effect of the COVID-19 lockdown to the periodicity of NO2. The results show that NO2 concentrations in desert areas such as Liwa and Al Quaa were unaffected by the lockdown period (April–July 2020) resulting from the COVID-19 pandemic. The other stations in the urban areas of Abu Dhabi city, Al Dhafra and Al Ain, showed a reduction in NO2 during the lockdown. NO2 is more highly concentrated during winter seasons than during other seasons. The periodicity of NO2 lasted from a few days up to 16 days in most regions. However, some stations located in the Al Dhafra region, such as Al Ruwais and the Gayathi School stations, exhibited a longer period of more than 32 days with a 0.05 significance test. In the Abu Dhabi region, NO2 lasted between 64 and 128 days at the Al Mafraq station. The correlation between the NO2 concentration across several ground stations was studied using wavelet coherence.

Air quality improvement and cognitive function benefit: Insight from clean air action in China

IntroductionEpidemiological evidence suggests associations between long-term exposure to air pollution and accelerated cognitive decline. China implemented a strict clean air action plan in 2013; however, it is unclear whether the improvement of air quality has alleviated cognitive impairment in the population. MethodsFrom the China Health and Retirement Longitudinal Study, 8536 Chinese adults were enrolled in 2011 and followed up in 2015. Satellite-based spatiotemporal models were used to estimate exposure to air pollutants (including particles with diameters ≤1.0 μm [PM1], ≤2.5 μm [PM2.5], ≤10 μm [PM10], nitrogen dioxide [NO2], and ozone [O3]). Cognitive function was evaluated using a structured questionnaire in three dimensions: episodic memory, orientation and attention, and visuoconstruction. The associations between changes in the levels of air pollutants and cognitive function were elucidated by a logistic model. The Bayesian Kernel Machine Regression (BKMR) model was applied to evaluate the cumulative effect of air pollutants. ResultsThe mean (standard deviation) age of all participants was 58.6 (8.7) years. The odds ratio (95% confidence interval) between the highest and the lowest quartile of PM1 exposure reduction for cognitive impairment was 0.46 (0.41, 0.53) after adjusting for confounders. Similar protective effects of cognitive function were observed with the decrease in the level of PM2.5 (0.34 [0.30, 0.39]), PM10 (0.54 [0.48, 0.62]), and NO2 (0.59 [0.51, 0.67]), while the reduction in O3 appeared to be less related to changes in cognitive function (OR: 0.97 [0.85, 1.10]). The protective association of PM1 reduction was stronger in males than in females. Decreased in PM2.5 dominate the cognitive function benefit relative to PM1, PM10, NO2. ConclusionsThe implementation of the clean air action plan led to a significant reduction in PM1, PM2.5, PM10, and NO2, which could slow the decline of cognitive function, while a reduction in O3 may not.

Treatment Effect of Corncob and Rice Straw Enhanced Subsurface Flow Constructed Wetland on Low C/N Ratio Wastewater

The lack of carbon sources severely inhibits denitrification in wastewater with a low C/N ratio. Corncob and rice straw were chosen as supplementary carbon sources to bring into the wetland system to supplement the carbon sources needed for denitrification, and the enhancing effects of the two carbon sources on nitrogen removal from the wetland were studied. The cumulative release of carbon was in the order of rice straw[(145.17±9.44) mg·g-1]>corncob[(57.41±5.04) mg·g-1] based on the 11-day pure water extraction and release experiment, whereas the cumulative release of nitrogen was in the order of rice straw[(2.31±0.09) mg·g-1]>corncob[(0.66±0.08) mg·g-1]. The average carbon/nitrogen ratios released and accumulated by corncob and rice straw during the observation period were 94.78 and 63.64, respectively. Corncob was more suited as an additional carbon source than rice straw. COD concentrations in the effluent from the corncob and straw constructed wetlands were found to be below 50 mg·L-1 for the 58-day pilot test of subsurface flow constructed wetlands, except on days 8 to 12. The NO3--N removal rates of the corncob-added built wetlands were 93%-99% over the observation period, with good denitrification performance. In comparison, the lowest NO3--N removal rate of the constructed wetland with the addition of rice straw was only 76.8% at the late stage of operation, and the denitrification rate dropped dramatically. The control group removal rates of NO3--N were only 76.2%-77.7%, indicating a clear lack of carbon sources. The accumulation of NO2--N was also induced by a lack of carbon supply. NO2--N effluent concentrations were 2.5-6 times and 6-26 times higher in the constructed wetlands with rice straw and the control groups, respectively, than those in the wetlands constructed with corncob. The addition of corncob resulted in a more substantial reduction in NO2--N content in the constructed wetland than the addition of rice straw (P<0.05). The TN removal rates of wetlands constructed with corncob and rice straw and the control group were 83.75%-93.49%, 76.59%-78.85%, and 67.85%-72.56%, respectively, with significant differences among the three (P<0.01). Finally, pretreatment with dilute alkali heating raised the cumulative carbon release of corncob to (93.73±17.49) mg·g-1 and the carbon/nitrogen ratio to 175.8, significantly improving the carbon release performance of corncob and demonstrating that it is a suitable source of extra carbon.

Evaluation of air quality effects of the London ultra-low emission zone by state-space modelling

In April 2019, an ultra-low emission zone (uLEZ) was implemented in London to tackle road transport air pollution. In this study, a state-space intervention model is developed for the first time to quantify the effects of this policy on London air quality. For developing this model, hourly NO, NO2, and NOx concentrations at 28 monitoring stations across London for 12 months before the uLEZ intervention and 11 months following it were used. Additionally, this model accounts for the influences of the meteorological variables of temperature, wind speed, and humidity, as well as those of the day of the week and calendar month.The results of this model showed the uLEZ intervention was successful in reducing NO, NO2, and NOx concentrations not just within the zone of implementation but also throughout the wider low emission zone (LEZ) and Greater London area. This intervention made the greatest reduction in NO and NOx in the uLEZ area (19% and 20%, respectively), followed by the LEZ (18% and 17%) and then Greater London (11% and 15%). The reduction in NO2 in the uLEZ and LEZ is similar (11%–12%), with a larger reduction elsewhere in the Greater London area (13%).

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.

Spatiotemporal variability/stability analysis of NO2, CO, and land surface temperature (LST) during COVID-19 lockdown in Amman city, Jordan

ABSTRACT The massive lockdown of human socioeconomic activities and vehicle movements due to the COVID-19 pandemic in 2020 has resulted in an unprecedented reduction in pollutant gases such as Nitrogen Dioxide (NO2) and Carbon Monoxide (CO) as well as Land Surface Temperature (LST) in Amman as well as all countries around the globe. In this study, the spatial and temporal variability/stability of NO2, CO, and LST throughout the lockdown period over Amman city have been analyzed. The NO2 and CO column density values were acquired from Sentinel-5p while the LST data were obtained from MODIS satellite during the lockdown period from 20 March to 24 April in 2019, 2020, and 2021. The statistical analysis showed an overall reduction in NO2 in 2020 by around 27% and 48% compared to 2019 and 2021, respectively. However, an increase of 7% in 2021 compared to 2019 was observed because almost all anthropogenic activities were allowed during the daytime. The temporal persistence showed almost constant NO2 values in 2020 over the study area throughout the lockdown period. In addition, a slight decrease in CO (around 1%) was recorded in 2020 and 2021 compared to the same period in 2019. Restrictions on human activities resulted in an evident drop in LST in 2020 by around 13% and 18% less than the 5-year average and 2021 respectively. The study concludes that due to the restrictions imposed on industrial activities and automobile movements in Amman city, an unprecedented reduction in NO2, CO, and LST was recorded.

Air Quality during the COVID–19 Lockdown and Unlock Periods in India Analyzed Using Satellite and Ground-based Measurements

A nationwide lockdown was imposed in India from 24 March 2020 to 31 May 2020 to contain the spread of COVID-19. The lockdown has changed the atmospheric pollution across the continents. Here, we analyze the changes in two most important air quality related trace gases, nitrogen dioxide (NO2) and tropospheric ozone (O3) from satellite and surface observations, during the lockdown (April–May 2020) and unlock periods (June–September 2020) in India, to examine the baseline emissions when anthropogenic sources were significantly reduced. We use the Bayesian statistics to find the changes in these trace gas concentrations in different time periods. There is a strong reduction in NO2 during the lockdown as public transport and industries were shut during that period. The largest changes are found in IGP (Indo-Gangetic Plain), and industrial and mining areas in Eastern India. The changes are small in the hilly regions, where the concentrations of these trace gases are also very small (0–1 × 1015 molec./cm2). In addition, a corresponding increase in the concentrations of tropospheric O3 is observed during the period. The analyses over cities show that there is a large decrease in NO2 in Delhi (36%), Bangalore (21%) and Ahmedabad (21%). As the lockdown restrictions were eased during the unlock period, the concentrations of NO2 gradually increased and ozone deceased in most regions. Therefore, this study suggests that pollution control measures should be prioritized, ensuring strict regulations to control the source of anthropogenic pollutants, particularly from the transport and industrial sectors.Highlights• Most cities show a reduction up to 15% of NO2 during the lockdown• The unlock periods show again an increase of about 40–50% in NO2• An increase in tropospheric O3 is observed together with the decrease in NO2Supplementary InformationThe online version contains supplementary material available at 10.1007/s40710-022-00585-9.

COVID-19 Lockdown in Israel: The Environmental Effect on Ultrafine Particle Content in the Airway.

Inhaled ultrafine particle (UFP) content in exhaled breath condensate (EBC) was observed as an airway inflammatory marker and an indicator of exposure to particulate matter (PM). The exceptional decline in air pollution during the COVID-19 lockdown was an opportunity to evaluate the effect of environmental changes on UFP airway content. We collected EBC samples from 30 healthy subjects during the first lockdown due to COVID-19 in Israel (March–April 2020) and compared them to EBC samples retrieved during April–June 2016 from 25 other healthy subjects (controls) living in the same northern Israeli district. All participants underwent EBC collection and blood sampling. Ambient air pollutant levels were collected from the Israeli Ministry of Environmental Protection’s online database. Data were acquired from the monitoring station closest to each subject’s home address, and means were calculated for a duration of 1 month preceding EBC collection. UFP contents were measured in the EBC and blood samples by means of the NanoSight LM20 system. There was a dramatic reduction in NO, NO2, SO2, and O3 levels during lockdown compared to a similar period in 2016 (by 61%, 26%, 50%, and 45%, respectively). The specific NO2 levels were 8.3 ppb for the lockdown group and 11.2 ppb for the controls (p = 0.01). The lockdown group had higher UFP concentrations in EBC and lower UFP concentrations in serum compared to controls (0.58 × 108/mL and 4.3 × 108/mL vs. 0.43 × 108/mL and 6.7 × 108/mL, p = 0.05 and p = 0.03, respectively). In this observational study, reduced levels of air pollution during the COVID-19 lockdown were reflected in increased levels of UFP airway contents. The suggested mechanism is that low airway inflammation levels during lockdown resulted in a decreased UFP translocation to serum. Further studies are needed to confirm this hypothesis.

Long-term characterization of roadside air pollutants in urban Beijing and associated public health implications

Road traffic constitutes a major source of air pollutants in urban Beijing, which are responsible for substantial premature mortality. A series of policies and regulations has led to appreciable traffic emission reductions in recent decades. To shed light on long-term (2014–2020) roadside air pollution and assess the efficacy of traffic control measures and their effects on public health, this study quantitatively evaluated changes in the concentrations of six key air pollutants (PM2.5, PM10, NO2, SO2, CO and O3) measured at 5 roadside and 12 urban background monitoring stations in Beijing. We found that the annual mean concentrations of these air pollutants were remarkably reduced by 47%–71% from 2014 to 2020, while the concurrent ozone concentration increased by 17.4%. In addition, we observed reductions in the roadside increments in PM2.5, NO2, SO2 and CO of 54.8%, 29.8%, 20.6%, and 59.1%, respectively, indicating the high effectiveness of new vehicle standard (China V and VI) implementation in Beijing. The premature deaths due to traffic emissions were estimated to be 8379 and 1908 cases in 2014 and 2020, respectively. The impact of NO2 from road traffic relative to PM2.5 on premature mortality was comparable to that of traffic-related PM2.5 emissions. The public health effect of SO2 originating from traffic was markedly lower than that of PM2.5. The results indicated that a reduction in traffic-related NO2 could likely yield the greatest benefits for public health.

How Does COVID-19 Lockdown Impact Air Quality in India?

Air pollution is a severe environmental problem in the Indian subcontinent. Largely caused by the rapid growth of the population, industrialization, and urbanization, air pollution can adversely affect human health and environment. To mitigate such adverse impacts, the Indian government launched the National Clean Air Programme (NCAP) in January 2019. Meanwhile, the unexpected city-lockdown due to the COVID-19 pandemic in March 2020 in India greatly reduced human activities and thus anthropogenic emissions of gaseous and aerosol pollutants. The NCAP and the lockdown could provide an ideal field experiment for quantifying the extent to which various levels of human activity reduction impact air quality in the Indian subcontinent. Here, we study the improvement in air quality due to COVID-19 and the NCAP in the India subcontinent by employing multiple satellite products and surface observations. Satellite data shows significant reductions in nitrogen dioxide (NO2) by 17% and aerosol optical depth (AOD) by 20% during the 2020 lockdown with reference to the mean levels between 2005–2019. No persistent reduction in NO2 nor AOD is detectable during the NCAP period (2019). Surface observations show consistent reductions in PM2.5 and NO2 during the 2020 lockdown in seven cities across the Indian subcontinent, except Mumbai in Central India. The increase in relative humidity and the decrease in the planetary boundary layer also play an important role in influencing air quality during the 2020 lockdown. With the decrease in aerosols during the lockdown, net radiation fluxes show positive anomalies at the surface and negative anomalies at the top of the atmosphere over most parts of the Indian subcontinent. The results of this study could provide valuable information for policymakers in South Asia to adjust the scientific measures proposed in the NCAP for efficient air pollution mitigation.