Significant variation in air quality in South Indian cities during COVID-19 lockdown and unlock phases.

With the spread of COVID-19 pandemic worldwide, the Government of India had imposed lockdown in the month of March 2020 to curb the spread of the virus furthermore. This shutdown led to closure of various institutions, organizations, and industries, and restriction on public movement was also inflicted which paved way to better air quality due to reduction in various industrial and vehicular emissions. To brace this, the present study was carried out to statistically analyze the changes in air quality from pre-lockdown period to unlock 6.0 in South Indian cities, namely, Bangalore, Chennai, Coimbatore, and Hyderabad, by assessing the variation in concentration of PM2.5, PM10, NO2, and SO2 during pre-lockdown, lockdown, and unlock phases. Pollutant concentration data was obtained for the selected timeframe (01 March 2020-30 November 2020) from CPCB, and line graph was plotted which had shown visible variation in the concentration of pollutants in cities taken into consideration. Analysis of variance (ANOVA) was applied to determine the mean differences in the concentration of pollutants during eleven timeframes, and the results indicated a significant difference (F (10,264) = 3.389, p < 0.001). A significant decrease in the levels of PM2.5, PM10, NO2, and SO2 during the lockdown phases was asserted by Tukey HSD results in Bangalore, Coimbatore, and Hyderabad stations, whereas PM10 and NO2 significantly increased during lockdown period in Chennai station. In order to understand the cause of variation in the concentration of pollutants and to find the association of pollutants with meteorological parameters, the Pearson correlation coefficient was used to study the relationship between PM2.5, PM10, NO2, and SO2 concentrations, temperature, rainfall, and wind speed for a span of 15 months, i.e., from January 2020 to March 2021. At a significant level of 99.9%, 99%, and 95%, a significant correlation among the pollutants, rainfall had a major impact on the pollutant concentration in Bangalore, Coimbatore, Hyderabad, and Chennai followed by wind speed and temperature. No significant influence of temperature on the concentration of pollutants was observed in Bangalore station.

Changes in Air Quality and Drivers for the Heavy PM2.5 Pollution on the North China Plain Pre- to Post-COVID-19.

Under the clean air action plans and the lockdown to constrain the coronavirus disease 2019 (COVID-19), the air quality improved significantly. However, fine particulate matter (PM2.5) pollution still occurred on the North China Plain (NCP). This study analyzed the variations of PM2.5, nitrogen dioxide (NO2), sulfur dioxide (SO2), carbon monoxide (CO), and ozone (O3) during 2017-2021 on the northern (Beijing) and southern (Henan) edges of the NCP. Furthermore, the drivers for the PM2.5 pollution episodes pre- to post-COVID-19 in Beijing and Henan were explored by combining air pollutant and meteorological datasets and the weighted potential source contribution function. Results showed air quality generally improved during 2017-2021, except for a slight rebound (3.6%) in NO2 concentration in 2021 in Beijing. Notably, the O3 concentration began to decrease significantly in 2020. The COVID-19 lockdown resulted in a sharp drop in the concentrations of PM2.5, NO2, SO2, and CO in February of 2020, but PM2.5 and CO in Beijing exhibited a delayed decrease in March. For Beijing, the PM2.5 pollution was driven by the initial regional transport and later secondary formation under adverse meteorology. For Henan, the PM2.5 pollution was driven by the primary emissions under the persistent high humidity and stable atmospheric conditions, superimposing small-scale regional transport. Low wind speed, shallow boundary layer, and high humidity are major drivers of heavy PM2.5 pollution. These results provide an important reference for setting mitigation measures not only for the NCP but for the entire world.

Effects of Air Pollution on Chemosensory Dysfunction in COVID-19 Patients.

BACKGROUND: In some patients, coronavirus disease 2019 (COVID-19) is accompanied by loss of smell and taste, and this has been reportedly associated with exposure to air pollutants. This study investigated the relationship between the occurrence of chemosensory dysfunction in COVID-19 patients and air pollutant concentrations in Korea. METHODS: Information on the clinical symptom of chemosensory dysfunction, the date of diagnosis, residential area, age, and sex of 60,194 confirmed COVID-19 cases reported to the Korea Disease Control and Prevention Agency from January 20 to December 31, 2020 was collected. In addition, the daily average concentration of air pollutants for a week in the patients' residential area was collected from the Ministry of Environment based on the date of diagnosis of COVID-19. A binomial logistic regression model, using age and gender, standardized smoking rate, number of outpatient visits, 24-hour mean temperature and relative humidity at the regional level as covariates, was used to determine the effect of air pollution on chemosensory dysfunction. RESULTS: Symptoms of chemosensory dysfunction were most frequent among patients in their 20s and 30s, and occurred more frequently in large cities. The logistic analysis showed that the concentration of particulate matter 10 (PM10) and 2.5 (PM2.5) up to 2 days before the diagnosis of COVID-19 and the concentration of sulfur dioxide (SO2), nitrogen dioxide (NO2), carbon monoxide (CO), and ozone (O3) at least 7 days before the diagnosis of COVID-19 affected the development of chemosensory dysfunction. In the logistic regression model adjusted for age, sex, standardized smoking rate, number of outpatient visits, and daily average temperature and relative humidity, it was found that an increase in the interquartile range of PM10, PM2.5, SO2, NO2, and CO on the day of diagnosis increased the incidence of chemosensory dysfunction 1.10, 1.10, 1.17, 1.31, and 1.19-fold, respectively. In contrast, the O3 concentration had a negative association with chemosensory dysfunction. CONCLUSION: High concentrations of air pollutants such as PM10, PM2.5, SO2, NO2, and CO on the day of diagnosis increased the risk of developing chemosensory dysfunction from COVID-19 infection. This result underscores the need to actively prevent exposure to air pollution and prevent COVID-19 infection. In addition, policies that regulate activities and products that create high amounts of harmful environmental wastes may help in promoting better health for all during COVID-19 pandemic.

The impact of COVID-19 lockdown on air pollution in Europe and North America: a systematic review.

BACKGROUND: Multiple studies report reductions in air pollution associated with COVID-19 lockdowns. METHODS: We performed a systematic review of the changes observed in hazardous air pollutants known or suspected to be harmful to health, including nitrogen dioxide (NO2), nitrogen oxides (NOx), carbon monoxide (CO), sulfur dioxide (SO2), ozone (O3) and particulate matter (PM). We searched PubMed and Web of Science for studies reporting the associations of lockdowns with air pollutant changes during the COVID-19 pandemic in Europe and North America. RESULTS: One hundred nine studies were identified and analyzed. Several pollutants exhibited marked and sustained reductions. The strongest was NO2 (93% of 89 estimated changes were reductions) followed by CO (88% of 33 estimated pollutant changes). All NOx and benzene studies reported significant reductions although these were based on fewer than 10 estimates. About three-quarters of PM2.5 and PM10 estimates showed reductions and few studies reported increases when domestic fuel use rose during COVID-19 lockdowns. In contrast, O3 levels rose as NOx levels fell. SO2 and ammonia (NH3) had mixed results. In general, greater reductions appeared when lockdowns were more severe, as well as where baseline pollutant levels were higher, such as at low-elevation and in densely populated areas. Substantial and robust reductions in NO2, NO, CO, CO2, PM2.5, PM10, benzene and air quality index pollution occurred in association with COVID-19 lockdowns. O3 levels tended to increase, while SO2 and NH3 had mixed patterns. CONCLUSIONS: Our study shows the profound impact of human activity levels on air pollution and its potential avoidability.

The impact of air pollution on COVID-19 incidence, severity, and mortality: A systematic review of studies in Europe and North America.

BACKGROUND: Air pollution is speculated to increase the risks of COVID-19 spread, severity, and mortality. OBJECTIVES: We systematically reviewed studies investigating the relationship between air pollution and COVID-19 cases, non-fatal severity, and mortality in North America and Europe. METHODS: We searched PubMed, Web of Science, and Scopus for studies investigating the effects of harmful pollutants, including particulate matter with diameter ≤2.5 or 10 µm (PM2.5 or PM10), ozone (O3), nitrogen dioxide (NO2), sulfur dioxide (SO2) and carbon monoxide (CO), on COVID-19 cases, severity, and deaths in Europe and North America through to June 19, 2021. Articles were included if they quantitatively measured the relationship between exposure to air pollution and COVID-19 health outcomes. RESULTS: From 2,482 articles screened, we included 116 studies reporting 355 separate pollutant-COVID-19 estimates. Approximately half of all evaluations on incidence were positive and significant associations (52.7%); for mortality the corresponding figure was similar (48.1%), while for non-fatal severity this figure was lower (41.2%). Longer-term exposure to pollutants appeared more likely to be positively associated with COVID-19 incidence (63.8%). PM2.5, PM10, O3, NO2, and CO were most strongly positively associated with COVID-19 incidence, while PM2.5 and NO2 with COVID-19 deaths. All studies were observational and most exhibited high risk of confounding and outcome measurement bias. DISCUSSION: Air pollution may be associated with worse COVID-19 outcomes. Future research is needed to better test the air pollution-COVID-19 hypothesis, particularly using more robust study designs and COVID-19 measures that are less prone to measurement error and by considering co-pollutant interactions.

Changes in temporal pattern and spatial distribution of environmental pollutants in 8 Asian countries owing to COVID-19 pandemic.

This study investigated the changes in air pollutant's concentration, spatio-temporal distribution and sensitivity of changes in air pollutant's concentration during pre and post COVID-19 outbreak. We employed Google Earth Engine Platform to access remote sensing datasets of air pollutants across Asian continent. Air pollution and cumulative confirmed-COVID cases data of Asian countries (Afghanistan, Bangladesh, China, India, Iran, Iraq, Pakistan, and Saudi Arabia) have been collected and analyzed for 2019 and 2020. The results indicate that aerosol index (AI) and nitrogen dioxide (NO2) is significantly reduced during COVID outbreak i.e. in year 2020. In addition, we found significantly positive (P < 0.05, 95% confidence interval, two-tailed) correlation between changes in AI and NO2 concentration for net active-COVID case increment in almost each country. For other atmospheric gases i.e. carbon monoxide (CO), formaldehyde (HCHO), ozone (O3), and Sulfur dioxide (SO2), insignificant and/or significant negative correlation is also observed. These results suggest that the atmospheric concentration of AI and NO2 are good indicators of human activities. Furthermore, the changes in O3 shows significantly negative correlation for net active-COVID case increment. In conclusion, we observed significant positive environmental impact of COVID-19 restrictions in Asia. This study would help and assist environmentalist and policy makers in restraining air pollution by implementing efficient restrictions on human activities with minimal economic loss.

Effects of meteorological factors and air pollutants on the incidence of COVID-19 in South Korea.

Air pollution and meteorological factors can exacerbate susceptibility to respiratory viral infections. To establish appropriate prevention and intervention strategies, it is important to determine whether these factors affect the transmission of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Therefore, this study examined the effects of sunshine, temperature, wind, and air pollutants including sulfur dioxide (SO2), carbon monoxide (CO), ozone (O3), nitrogen dioxide (NO2), particulate matter ≤2.5 µm (PM2.5), and particulate matter ≤10 µm (PM10) on the age-standardized incidence ratio of coronavirus disease (COVID-19) in South Korea between January 2020 and April 2020. Propensity score weighting was used to randomly select observations into groups according to whether the case was cluster-related, to reduce selection bias. Multivariable logistic regression analyses were used to identify factors associated with COVID-19 incidence. Age 60 years or over (odds ratio [OR], 1.29; 95% CI, 1.24-1.35), exposure to ambient air pollutants, especially SO2 (OR, 5.19; 95% CI, 1.13-23.9) and CO (OR, 1.17; 95% CI, 1.07-1.27), and non-cluster infection (OR, 1.28; 95% CI, 1.24-1.32) were associated with SARS-CoV-2 infection. To manage and control COVID-19 effectively, further studies are warranted to confirm these findings and to develop appropriate guidelines to minimize SARS-CoV-2 transmission.

Analysis of changes in air pollution quality and impact of COVID-19 on environmental health in Iran: application of interpolation models and spatial autocorrelation.

In the global COVID-19 epidemic, humans are faced with a new challenge. The concept of quarantine as a preventive measure has changed human activities in all aspects of life. This challenge has led to changes in the environment as well. The air quality index is one of the immediate concrete parameters. In this study, the actual potential of quarantine effects on the air quality index and related variables in Tehran, the capital of Iran, is assessed, where, first, the data on the pollutant reference concentration for all measuring stations in Tehran, from February 19 to April 19, from 2017 to 2020, are monitored and evaluated. This study investigated the hourly concentrations of six particulate matters (PM), including PM2.5, PM10, and air contaminants such as nitrogen dioxide (NO2), sulfur dioxide (SO2), ozone (O3), and carbon monoxide (CO). Changes in pollution rate during the study period can be due to reduced urban traffic, small industrial activities, and dust mites of urban and industrial origins. Although pollution has declined in most regions during the COVID-19 quarantine period, the PM2.5 rate has not decreased significantly, which might be of natural origins such as dust. Next, the air quality index for the stations is calculated, and then, the interpolation is made by evaluating the root mean square (RMS) of different models. The local and global Moran index indicates that the changes and the air quality index in the study area are clustered and have a high spatial autocorrelation. The results indicate that although the bad air quality is reduced due to quarantine, major changes are needed in urban management to provide favorable conditions. Contaminants can play a role in transmitting COVID-19 as a carrier of the virus. It is suggested that due to the rise in COVID-19 and temperature in Iran, in future studies, the effect of increased temperature on COVID-19 can be assessed.

2020 COVID-19 lockdown and the impacts on air quality with emphasis on urban, suburban and rural zones.

Air quality improvements pollution changes due to COVID-19 restrictions have been reported for many urban developments and large metropolitan areas, but the respective impacts at rural and remote zones are less frequently analysed. This study evaluated air pollution changes across all Portugal (68 stations) considering all urban, suburban and rural zones. PM10, PM2.5, NO2, SO2, ozone was analysed in pre-, during, and post-lockdown period (January-May 2020) and for a comparison also in 2019. NO2 was the most reduced pollutant in 2020, which coincided with decreased traffic. Significant drop (15-71%) of traffic related NO2 was observed specifically during lockdown period, being 55% for the largest and most populated region in country. PM was affected to a lesser degree (with substantial differences found for largely populated areas (Lisbon region ~ 30%; North region, up to 49%); during lockdown traffic-related PM dropped 10-70%. PM10 daily limit was exceeded 50% less in 2020, with 80% of exceedances before lockdown period. SO2 decreased by 35%, due to suspended industrial productions, whereas ozone concentrations slightly (though not significantly) increased (83 vs. 80 µg m-3).

Impact of the State of Emergency during the COVID-19 Pandemic in 2020 on Asthma Exacerbations among Children in Kobe City, Japan.

The coronavirus disease (COVID-19) pandemic altered environmental factors. We studied the impact of these changes on asthma exacerbation (AE) by comparing the AE-related environmental factors between COVID-19 (2020) and pre-COVID-19 (2011-2019) eras. Between 2011 and 2020, 278,465 children (<16 years old) visited our emergency department, and 7476 were diagnosed with AE. The number of patients showed spring and fall peaks in 2011-2019. Multivariate analyses showed significant positive relationships of the number of AE patients with the average temperature among all patients and 0-5-year-olds and with sulfur dioxide (SO2) levels in 2011-2019 among 0-5-year-olds. Although the spring peak in the number of patients was not observed in 2020 after declaration of a state of emergency, the fall peak was again observed after the state of emergency was lifted. No changes in average temperature were detected, but SO2 was significantly reduced following declaration of the state of emergency in 2020. Therefore, SO2 reduction might have contributed to the disappearance of the peak of AE. However, a fall peak was observed again in 2020, although SO2 levels continued to be low. These data suggest that person to person interaction seems to be associated with AE, presumably due to unknown viral infections.

Environmental spatial heterogeneity of the impacts of COVID-19 on the top-20 metropolitan cities of Asia-Pacific.

This study investigated the environmental spatial heterogeneity of novel coronavirus (COVID-19) and spatial and temporal changes among the top-20 metropolitan cities of the Asia-Pacific. Remote sensing-based assessment is performed to analyze before and during the lockdown amid COVID-19 lockdown in the cities. Air pollution and mobility data of each city (Bangkok, Beijing, Busan, Dhaka, Delhi, Ho Chi Minh, Hong Kong, Karachi, Mumbai, Seoul, Shanghai, Singapore, Tokyo, Wuhan, and few others) have been collected and analyzed for 2019 and 2020. Results indicated that almost every city was impacted positively regarding environmental emissions and visible reduction were found in Aerosol Optical Depth (AOD), sulfur dioxide (SO2), carbon monoxide (CO), and nitrogen dioxide (NO2) concentrations before and during lockdown periods of 2020 as compared to those of 2019. The highest NO2 emission reduction (~ 50%) was recorded in Wuhan city during the lockdown of 2020. AOD was highest in Beijing and lowest in Colombo (< 10%). Overall, 90% movement was reduced till mid-April, 2020. A 98% reduction in mobility was recorded in Delhi, Seoul, and Wuhan. This analysis suggests that smart mobility and partial shutdown policies could be developed to reduce environmental pollutions in the region. Wuhan city is one of the benchmarks and can be replicated for the rest of the Asian cities wherever applicable.

Diurnal and weekly patterns of primary pollutants in Beijing under COVID-19 restrictions.

Restrictions on movement in Beijing to limit the COVID-19 epidemic tended to reduce the emissions of primary pollutants. However, changes in pollutant concentrations are also affected by chemical transformation and meteorology. Decreases in concentrations were also not as obvious in Beijing when compared with Hubei Province, where lockdown was especially strict. Declines in concentrations between 2019 and 2020 are evident for both NO2 (37.0 to 26.2 µg m-3) and SO2 (5.86 to 4.15 µg m-3), but there was little evidence of change for PM2.5 (50.0 to 53.8 µg m-3) and CO (0.71 to 0.74 mg m-3). Despite this, Fourier analysis revealed that the weekly cycle of PM2.5 evident in 2019 was not apparent in 2020. In 2019, CO showed both diurnal and weekly signals, but these were absent under the restrictions of 2020. This suggests that while concentrations may remain relatively constant, the temporal distribution of pollutants can show subtle changes under restrictions imposed in attempts to limit the spread of the coronavirus.

Ambient air pollution, meteorology, and COVID-19 infection in Korea.

The outbreak of novel pneumonia coronavirus disease has become a public health concern worldwide. Here, for the first time, the association between Korean meteorological factors and air pollutants and the COVID-19 infection was investigated. Data of air pollutants, meteorological factors, and daily COVID-19 confirmed cases of seven metropolitan cities and nine provinces were obtained from 3 February 2020 to 5 May 2020 during the first wave of pandemic across Korea. We applied the generalized additive model to investigate the temporal relationship. There was a significantly nonlinear association between daily temperature and COVID-19 confirmed cases. Each 1°C increase in temperature was associated with 9% (lag 0-14; OR = 1.09; 95% CI = 1.03-1.15) increase of COVID-19 confirmed cases when the temperature was below 8°C. A 0.01 ppm increase in NO2 (lag 0-7, lag 0.14, and lag 0-21) was significantly associated with increases of COVID-19 confirmed cases, with ORs (95% CIs) of 1.13 (1.02-1.25), 1.19 (1.09-1.30), and 1.30 (1.19-1.41), respectively. A 0.1 ppm increase in CO (lag 0-21) was associated with the increase in COVID-19 confirmed cases (OR = 1.10, 95% CI = 1.04-1.16). There was a positive association between per 0.001 ppm of SO2 concentration (lag 0, lag 0-7, and lag 0-14) and COVID-19 confirmed cases, with ORs (95% CIs) of 1.13 (1.04-1.22), 1.20 (1.11-1.31), and 1.15 (1.07-1.25), respectively. There were significantly temporal associations between temperature, NO2 , CO, and SO2 concentrations and daily COVID-19 confirmed cases in Korea.

Highlighting the compound risk of COVID-19 and environmental pollutants using geospatial technology.

The new COVID-19 coronavirus disease has emerged as a global threat and not just to human health but also the global economy. Due to the pandemic, most countries affected have therefore imposed periods of full or partial lockdowns to restrict community transmission. This has had the welcome but unexpected side effect that existing levels of atmospheric pollutants, particularly in cities, have temporarily declined. As found by several authors, air quality can inherently exacerbate the risks linked to respiratory diseases, including COVID-19. In this study, we explore patterns of air pollution for ten of the most affected countries in the world, in the context of the 2020 development of the COVID-19 pandemic. We find that the concentrations of some of the principal atmospheric pollutants were temporarily reduced during the extensive lockdowns in the spring. Secondly, we show that the seasonality of the atmospheric pollutants is not significantly affected by these temporary changes, indicating that observed variations in COVID-19 conditions are likely to be linked to air quality. On this background, we confirm that air pollution may be a good predictor for the local and national severity of COVID-19 infections.

Short-term health effects of air quality changes during the COVID­19 pandemic in the City of Novi Sad, the Republic of Serbia.

OBJECTIVES: The objective of this research is to determine the change in outdoor air quality during the COVID­19 related state of emergency resulting in a lockdown and the potential health benefits for the urban population. MATERIAL AND METHODS: During 53 days of the COVID­19 related state of emergency with a lockdown (March 15-May 6, 2020) in the Republic of Serbia, as well as in the corresponding periods of 2018 and 2019, data on the daily sulfur dioxide (SO2), nitrogen dioxide (NO2), ground-level ozone (O3) and particulate matter (PM10 and PM2.5) concentrations were analyzed. The total mortality data were analyzed to estimate the impact of the COVID­19 related lockdown measures on the burden of health in a given population, attributed to the outdoor air quality in the City of Novi Sad, using AirQ+ software. RESULTS: The average daily concentrations of PM2.5, NO2, PM10 and SO2 were reduced by 35%, 34%, 23% and 18%, respectively. In contrast, the average daily concentration of O3 increased by 8%, even if the primary precursors were reducing, thus representing a challenge for air quality management. In the City of Novi Sad, a reduction in the average daily PM2.5 concentration of 11.23 µg/m³ was significant, which resulted in a quantified number of avoided deaths. CONCLUSIONS: Air pollution in the City of Novi Sad had a chance to be improved due to some preventive measures related to the infectious disease (the COVID­19 related lockdown), which in turn was the mitigation measure to air pollution with positive public health effects. The confirmed positive effects of the improved air quality on public health could also include raising collective resistance to mass non-communicable and infectious diseases such as COVID­19 and reducing economic costs. Int J Occup Med Environ Health. 2021;34(2):223-37.

Annual SO2 exposure, asthma, atopy, and lung function in Puerto Rican children.

BACKGROUND: Long-term effects of sulfur dioxide (SO2 ) exposure on children, a vulnerable population, are largely unknown. Further, how long-term SO2 affects Puerto Rican children living in the island of Puerto Rico, a group with high asthma prevalence, is unclear. We evaluated the effects of annual average 1-hour daily maximum SO2 average on asthma, atopy, total immunoglobulin E (IgE), and lung function in Puerto Rican children. METHODS: A cohort of 678 children (351 with asthma, 327 without asthma) was recruited in Puerto Rico from 2009 to 2010. Annual average 1-hour daily maximum SO2 exposure was interpolated utilizing publicly available monitoring data. Multivariable logistic and linear regression was used for the analysis of asthma, atopy (defined as an IgE ≥0.35 IU/mL to at least one of five common aero-allergens), total IgE, and lung function measures (forced vital capacity [FVC], forced expiratory volume in 1 second [FEV1], and FEV1/FVC ratio). RESULTS: Annual SO2 exposure (per 1 ppb) was significantly associated with asthma (odds ratio [OR] = 1.42; 95% confidence interval [CI] = 1.05-1.91) and atopy (OR = 1.35; 95% CI = 1.02-1.78). Such exposure was also significantly associated with lower FEV1/FVC in all children (ß = -1.42; 95% CI = -2.78 to -0.08) and in children with asthma (ß = -2.39; 95% CI= -4.31 to -0.46). Annual SO2 exposure was not significantly associated with total IgE, FEV1, or FVC. CONCLUSIONS: Among Puerto Rican children in Puerto Rico, long-term SO2 exposure is linked to asthma and atopy. In these children, long-term SO2 exposure is also associated with reduced FEV1/FVC, particularly in those with asthma.

"Freedom to Breathe": Youth Participatory Action Research (YPAR) to Investigate Air Pollution Inequities in Richmond, CA.

Air pollution is a major contributor to human morbidity and mortality, potentially exacerbated by COVID-19, and a threat to planetary health. Participatory research, with a structural violence framework, illuminates exposure inequities and refines mitigation strategies. Home to profitable oil and shipping industries, several census tracts in Richmond, CA are among the most heavily impacted by aggregate burdens statewide. Formally trained researchers from the Center for Environmental Research and Children's Health (CERCH) partnered with the RYSE youth justice center to conduct youth participatory action research on air quality justice. Staff engaged five youth researchers in: (1) collaborative research using a network of passive air monitors to quantify neighborhood disparities in nitrogen dioxide (NO2) and sulfur dioxide (SO2), noise pollution and community risk factors; (2) training in environmental health literacy and professional development; and (3) interpretation of findings, community outreach and advocacy. Inequities in ambient NO2, but not SO2, were observed. Census tracts with higher Black populations had the highest NO2. Proximity to railroads and major roadways were associated with higher NO2. Greenspace was associated with lower NO2, suggesting investment may be conducive to improved air quality, among many additional benefits. Youth improved in measures of empowerment, and advanced community education via workshops, Photovoice, video, and "zines".

Short-term exposure to ambient air pollution in association with COVID-19 of two clusters in South Korea.

OBJECTIVES: This study aimed to examine the association between six air pollutants and COVID-19 infection in two main clusters, which accounted for 83% of total confirmed cases in Korea. METHODS: We collected the data on daily confirmed cases between February 24, 2020 and September 12, 2020. Data on six air pollutants (PM2.5 , PM10 , O3 , NO2 , CO and SO2 ) and four meteorological factors (temperature, wind speed, humidity and air pressure) were obtained on seven days prior to the research period. The generalised additive model and the distributed lag nonlinear model were applied to generate the relative risks (RRs) and 95% confidence intervals (CIs) for the associations. Pooled estimates for clusters were obtained by applying a random-effects model. RESULTS: We found that NO2 concentration was positively associated with daily confirmed cases in both Seoul-Gyeonggi and Daegu-Gyeongbuk clusters, with RRs (95% CIs) of 1.22 (1.03-1.44) and 1.66 (1.25-2.19), respectively. However, SO2 concentration was observed to be associated with daily confirmed cases in the Seoul-Gyeonggi cluster only (RR = 1.30, 95% CI = 1.10-1.54), whereas PM2.5 and CO concentrations were observed to be associated with daily confirmed cases in the Daegu-Gyeongbuk cluster only (RR = 1.14, 95% CI = 1.02-1.27 and RR = 1.30, 95% CI = 1.15-1.48, respectively). CONCLUSIONS: Our data found that NO2 concentration was positively associated with daily confirmed cases in both clusters, whereas the effect of PM2.5 , CO and SO2 on COVID-19 infection in two clusters was different.

Significant decrease of lightning activities during COVID-19 lockdown period over Kolkata megacity in India.

The outbreak of COVID-19 has now created the largest pandemic and the World health organization (WHO) has declared social distancing as the key precaution to confront such type of infections. Most of the countries have taken protective measures by the nationwide lockdown. The purpose of this study is to understand the effect of lockdown on air pollutants and to analyze pre-monsoon (April and May) cloud-to-ground and inter-cloud lightning activity in relation to air pollutants i.e. suspended Particulate matter (PM10), Nitrogen dioxides (NO2) Sulfur dioxide (SO2), Ozone (O3) and Aerosol concentration (AC) in a polluted tropical urban megacities like Kolkata. After the strict lockdown the pollutants rate has reduced by more than 40% from the pre-lockdown period in the Kolkata megacity. So, decreases of PM10, NO2, SO2, O3 and AC have a greater effect on cloud lightning flashes in the pre-monsoon period. In the previous year (2019), the pre-monsoon average result shows a strong positive relation between the lightning and air pollutants; PM10 (R2 = 0.63), NO2 (R2 = 0.63), SO2 (R2 = 0.76), O3 (R2 = 0.68) and AC (R2 = 0.83). The association was relatively low during the lock-down period (pre-monsoon 2020) and the R2 values were 0.62, 0.60, 0.71, 0.64 and 0.80 respectively. Another thing is that the pre-monsoon (2020) lightning strikes decreased by 49.16% compared to the average of previous years (2010 to 2019). The overall study shows that the reduction of surface pollution in the thunderstorm environment is strongly related to the reduction of lightning activity where PM10 and AC are the key pollutants in the Kolkata megacity.

Unexpected air pollution with marked emission reductions during the COVID-19 outbreak in China.

The absence of motor vehicle traffic and suspended manufacturing during the coronavirus disease 2019 (COVID-19) pandemic in China enabled assessment of the efficiency of air pollution mitigation. Up to 90% reduction of certain emissions during the city-lockdown period can be identified from satellite and ground-based observations. Unexpectedly, extreme particulate matter levels simultaneously occurred in northern China. Our synergistic observation analyses and model simulations show that anomalously high humidity promoted aerosol heterogeneous chemistry, along with stagnant airflow and uninterrupted emissions from power plants and petrochemical facilities, contributing to severe haze formation. Also, because of nonlinear production chemistry and titration of ozone in winter, reduced nitrogen oxides resulted in ozone enhancement in urban areas, further increasing the atmospheric oxidizing capacity and facilitating secondary aerosol formation.