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.

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.

The role of exhaled nitric oxide (FeNO) in the evaluation of lung parenchymal involvement in COVID-19 patients.

The inflammatory balance is an important factor in the clinical course of COVID-19 (SARS-CoV-2) infection, which has affected over 300 million people globally since its appearance in December 2019. This study aimed to evaluate the correlation between exhaled nitric oxide (FeNO) level and parenchymal involvement in COVID-19. The study included 106 patients with the delta variant of COVID-19 identified by real-time PCR as well as 40 healthy control groups between October 2021 and March 2022. The patients were analyzed in three groups: moderate COVID-19 (group 1), severe COVID-19 without macrophage activation syndrome (MAS) (group 2), and severe COVID-19 with MAS (group 3). FeNO and CT scores were significantly higher in groups 2 and 3 at admission and discharge compared to group 1 (p = 0.001 for all). In addition, CT score at admission and CT score and FeNO level at discharge were higher in group 3 than in group 2 (p = 0.001 for all). It was found that the FeNO levels were higher in Groups 2 and 3 than in the control group (p = 0.001) during the admission. FeNO and CT scores showed strong positive correlation at admission and discharge (r = 0.917, p = 0.001; r = 0.790, p = 0.001). In receiver operating characteristic curve analysis for prediction of MAS, FeNO at a cut-off of 10.5 ppb had 66% sensitivity and 71% specificity. COVID-19 causes more severe lung involvement than other viral lower respiratory tract infections, leading to the frequent use of chest CT in these patients. FeNO assessment is a practical and noninvasive method that may be useful in evaluating for parenchymal infiltration in the diagnosis and follow-up of COVID-19 patients.

Nasal nitric oxide is decreased in acute mild COVID-19 and related to viral load.

Gaseous nitric oxide levels from the lungs (FeNO) and from the nose (nNO) have been demonstrated to react to acute infection or influenza vaccination. There are no published data on nNO levels during acute COVID-19, but normal levels of FeNO have been reported in one study. Our aim was to assess if acute mild COVID-19 alters nasal or bronchial NO output at the time of acute infection and at a two-month follow up, and if this is related to symptoms or viral load. This study included 82 subjects with mild acute airway infection who did not need hospitalization: 43 cases (reverse transcription polymerase chain reaction (RT-PCR)-positive for SARS-CoV-2 in routine testing from nasopharynx) and 39 age- (±5 years) and gender-matched controls (RT-PCR-negative for SARS-CoV-2). During acute infection, the cases had lower nNO compared to controls (158 [104-206] vs. 232 [203-279] nl min-1;p< 0.001), but after two months, there was no significant difference between the groups (230 [179-290] vs. 268 [222-320] nl min-1;p= 0.162). There was no difference in FeNO between the groups at either of the visits. Nasal NO correlated with the cycle threshold (Ct) value of the nasopharyngeal RT-PCR test for SARS-CoV-2 (Spearman'srs= 0.550;p< 0.001), that is, nNO was lower with a higher viral load. Nasal NO output was decreased in acute COVID-19 in relation to higher viral load, suggesting that the type and intensity of inflammatory response affects the release of NO from airway mucosa. In these subjects without significant lower airway involvement, there were no clinically relevant findings regarding FeNO.

Exhaled nitric oxide detection for diagnosis of COVID-19 in critically ill patients.

BACKGROUND: COVID-19 may present with a variety of clinical syndromes, however, the upper airway and the lower respiratory tract are the principle sites of infection. Previous work on respiratory viral infections demonstrated that airway inflammation results in the release of volatile organic compounds as well as nitric oxide. The detection of these gases from patients' exhaled breath offers a novel potential diagnostic target for COVID-19 that would offer real-time screening of patients for COVID-19 infection. METHODS AND FINDINGS: We present here a breath tester utilizing a catalytically active material, which allows for the temporal manifestation of the gaseous biomarkers' interactions with the sensor, thus giving a distinct breath print of the disease. A total of 46 Intensive Care Unit (ICU) patients on mechanical ventilation participated in the study, 23 with active COVID-19 respiratory infection and 23 non-COVID-19 controls. Exhaled breath bags were collected on ICU days 1, 3, 7, and 10 or until liberation from mechanical ventilation. The breathalyzer detected high exhaled nitric oxide (NO) concentration with a distinctive pattern for patients with active COVID-19 pneumonia. The COVID-19 "breath print" has the pattern of the small Greek letter omega (). The "breath print" identified patients with COVID-19 pneumonia with 88% accuracy upon their admission to the ICU. Furthermore, the sensitivity index of the breath print (which scales with the concentration of the key biomarker ammonia) appears to correlate with duration of COVID-19 infection. CONCLUSIONS: The implication of this breath tester technology for the rapid screening for COVID-19 and potentially detection of other infectious diseases in the future.

Air quality, Environment and Respiratory Outcomes in Bronchopulmonary Dysplasia, the AERO-BPD cohort study: design and adaptation during the SARS-CoV-2 pandemic.

INTRODUCTION: Almost half of all school-age children with bronchopulmonary dysplasia (BPD) have asthma-like symptoms and more suffer from lung function deficits. While air pollution and indoor respiratory irritants are known to affect high-risk populations of children, few studies have objectively evaluated environmental contributions to long-term respiratory morbidity in this population. This study aimed to examine the role of indoor environmental exposures on respiratory morbidity in children with BPD. METHODS AND ANALYSIS: The Air quality, Environment and Respiratory Ouctomes in BPD (AERO-BPD) study is a prospective, single-centre observational study that will enrol a unique cohort of 240 children with BPD and carefully characterise participants and their indoor home environmental exposures. Measures of indoor air quality constituents will assess the relationship of nitrogen dioxide (NO2), particulate matter (PM2.5), nitric oxide (NO), temperature and humidity, as well as dust concentrations of allergens, with concurrently measured respiratory symptoms and lung function.Adaptations to the research protocol due to the SARS-CoV-2 pandemic included remote home environment and participant assessments. ETHICS AND DISSEMINATION: Study protocol was approved by the Boston Children's Hospital Committee on Clinical Investigation. Dissemination will be in the form of peer-reviewed publications and participant information products. TRIAL REGISTRATION NUMBER: NCT04107701.

Global tropospheric ozone responses to reduced NO x emissions linked to the COVID-19 worldwide lockdowns.

Efforts to stem the transmission of coronavirus disease 2019 (COVID-19) led to rapid, global ancillary reductions in air pollutant emissions. Here, we quantify the impact on tropospheric ozone using a multiconstituent chemical data assimilation system. Anthropogenic NO x emissions dropped by at least 15% globally and 18 to 25% regionally in April and May 2020, which decreased free tropospheric ozone by up to 5 parts per billion, consistent with independent satellite observations. The global total tropospheric ozone burden declined by 6TgO3 (∼2%) in May and June 2020, largely due to emission reductions in Asia and the Americas that were amplified by regionally high ozone production efficiencies (up to 4 TgO3/TgN). Our results show that COVID-19 mitigation left a global atmospheric imprint that altered atmospheric oxidative capacity and climate radiative forcing, providing a test of the efficacy of NO x emissions controls for co-benefiting air quality and climate.

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.