The Nexus Between COVID-19 Factors and Air Pollution.

Background and Objective: There have been significant effects of the current coronavirus-19 (COVID-19) infection outbreak on many facets of everyday life, particularly the environment. Despite the fact that a number of studies have already been published on the topic, an analysis of those studies' findings on COVID-19's effects on environmental pollution is still lacking. The goal of the research is to look into greenhouse gas emissions and air pollution in Bangladesh when COVID-19 is under rigorous lockdown. The specific drivers of the asymmetric relationship between air pollution and COVID-19 are being investigated. Methods: The nonlinear relationship between carbon dioxide ( C O 2 ) emissions, fine particulate matter ( P M 2 . 5 ) , and COVID-19, as well as its precise components, are also being investigated. To examine the asymmetric link between COVID-19 factors on C O 2 emissions and P M 2 . 5 , we employed the nonlinear autoregressive distributed lag (NARDL) model. Daily positive cases and daily confirmed death by COVID-19 are considered the factors of COVID-19, with lockdown as a dummy variable. Results: The bound test confirmed the existence of long-run and short-run relationships between variables. Bangladesh's strict lockdown, enforced in reaction to a surge of COVID-19 cases, reduced air pollution and dangerous gas emissions, mainly C O 2 , according to the dynamic multipliers graph.

Statistical Analysis for Understanding PM2.5 Air Quality and the Impacts of COVID-19 Social Distancing in Several Provinces and Cities in Vietnam.

Air pollution, especially in urban regions, is receiving increasing attention in Vietnam. Consequently, this work aimed to study and analyze the air quality in several provinces and cities in the country focusing on PM2.5. Moreover, the impacts of COVID-19 social distancing on the PM2.5 level were investigated. For this purpose, descriptive statistic, Box and Whisker plot, correlation matrix, temporal variation, and trend analysis were conducted. R-based program and the R package "openair" were employed for the calculations. Hourly PM2.5 data were obtained from 8 national air quality monitoring sites. The study results indicated that provinces and cities in the North experienced more PM2.5 pollution compared to the Central and South. PM2.5 concentrations at each monitoring site varied significantly. Among monitoring sites, the northern sites showed high PM2.5 correlations with each other than the other sites. Seasonal variation was observed with high PM2.5 concentration in the dry season and low PM2.5 concentration in the wet season. PM2.5 concentration variation during the week was not so different. Diurnal variation showed that PM2.5 concentration rose at peak traffic hours and dropped in the afternoon. There was mainly a decreasing trend in PM2.5 concentration over the studied period. The COVID-19 pandemic has contributed to PM2.5 reduction. In the months implemented social distancing for preventing the epidemic, PM2.5 concentration declined but it would mostly increase in the following months. This study provided updated and valuable assessments of recent PM2.5 air quality in Vietnam.

Spectral selective composite mask media for personal cooling and efficient PM 2.5 removal

Face masks are commonly used to protect an individual's respiratory system from inhaling fine particulate matter (PM2.5) in polluted air, as well as the airborne pathogens, especially during the ongoing coronavirus disease 2019 (COVID-19) pandemic. However, all conventional masks with anti-PM2.5 function suffer from insufficient facial thermal comfort, particularly in a hot and humid environment. Herein, we demonstrated a novel infrared-transmittance visible-opaque PM2.5 media for radiative cooling utilizing rutile titanium dioxide particle-embedded polyamide 6 (PA6-TiO2). The transmission of visible light and infrared and PM2.5 removal performance of composite media containing a variety of microstructures, such as TiO2 particles of varying sizes, shapes, and contents, were numerically examined to determine the optimal ranges. Then the PA6-TiO2 media was effectively electrospun by controlling the arrangement of fibers and the morphology of TiO2 particles. By transmitting more than 85% of the thermal radiation from the human body and selectively blocking solar irradiance, the developed PA6-TiO2(flower-shaped) media cooled the simulative skin by 10.3°C as compared with commercial masks under strong solar irradiance. Additionally, they demonstrated a high PM2.5 removal efficiency of 95.3%, a low air resistance of 22.5 Pa (at 5.3 cm/s), and a sound water vapor transmission rate of 0.0169 g cm−2 h−1. This study presents an effective strategy for making thermally comfortable anti-PM2.5 masks, which will significantly benefit the public health prevention and control. © The Author(s) 2022.

Abundance, Source Apportionment and Health Risk Assessment of Polycyclic Aromatic Hydrocarbons and Nitro-Polycyclic Aromatic Hydrocarbons in PM2.5 in the Urban Atmosphere of Singapore

In this study, the levels of fine particulate matter (PM2.5), polycyclic aromatic hydrocarbons (PAHs) and nitro-PAHs (NPAHs) in PM2.5 samples were determined from 2020 to 2021 in Singapore. For analysis convenience, the sampling period was classified according to two monsoon periods and the inter-monsoon period. Considering Singapore's typically tropical monsoon climate, the four seasons were divided into the northeast monsoon season (NE), southwest monsoon season (SW), presouthwest monsoon season (PSW) and prenortheast monsoon season (PNE)). The PM2.5 concentration reached 17.1 +/- 8.38 mu g/m(3), which was slightly higher than that in 2015, and the average PAH concentration continuously declined during the sampling period compared to that reported in previous studies in 2006 and 2015. This is the first report of NPAHs in Singapore indicating a concentration of 13.1 +/- 10.7 pg/m(3). The seasonal variation in the PAH and NPAH concentrations in PM2.5 did not obviously differ owing to the unique geographical location and almost uniform climate changes in Singapore. Diagnostic ratios revealed that PAHs and NPAHs mainly originated from local vehicle emissions during all seasons. 2-Nitropyrene (2-NP) and 2-nitrofluoranthene (2-NFR) in Singapore were mainly formed under the daytime OH-initiated reaction pathway. Combined with airmass backward trajectory analysis, the Indonesia air mass could have influenced Singapore's air pollution levels in PSW. However, these survey results showed that no effect was found on the concentrations of PAHs and NPAHs in PM2.5 in Indonesia during SW because of Indonesia's efforts in the environment. It is worth noting that air masses from southern China could impact the PAH and NPAH concentrations according to long-range transportation during the NE. The results of the total incremental lifetime cancer risk (ILCR) via three exposure routes (ingestion, inhalation and dermal absorption) for males and females during the four seasons indicated a low long-term potential carcinogenic risk, with values ranging from 10(-10) to 10(-7). This study systematically explains the latest pollution conditions, sources, and potential health risks in Singapore, and comprehensively analyses the impact of the tropical monsoon system on air pollution in Singapore, providing a new perspective on the transmission mechanism of global air pollution.

Ambient Fine Particulate Matter and COVID-19 in India

We examine the correlation between COVID-19 case activity and air pollution in two cities of Delhi and Mumbai in India. Data regarding air quality index (AQI) of PM2.5 and PM10 from Delhi and Mumbai were collected between July and November 2020. Within the same time period, confirmed cases and daily deaths due to COVID-19 in these two cities were also recorded. AQI levels in Delhi were worst in November (PM2.5: 446 ± 144.6 µg/m3;PM10: 318 ± 131.7 µg/m3) and were significantly higher as compared to Mumbai (PM2.5: 130 ± 41.2 µg/m3;PM10: 86 ± 21.2 µg/m3). This correlated with greater number of cases and higher mortality in Delhi (cases: 6243;deaths: 85) relative to Mumbai (cases: 1526;deaths: 35) during the same time period. This observational study shows that air pollution is associated with poor outcomes in patients with COVID-19. There is an urgent unmet need for appropriate public health measures to decrease air pollution along with strict policy change. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

Impact of Air Quality Variations on COVID-19 Determinants: A Study of Four Selected Cities of India

Governments across the world are making considerable efforts in confronting COVID-19, from nationwide lockdowns to hygiene measures and maintaining social distancing. But at the same time, role of aerosols or/and the high concentrations of fine particulate matter or/and AQI levels in infection transmission and increasing the prevalence, morbidity and mortality of pandemic has been largely unexplored specifically in India where pollution attains peak in October and November every year. In the present study, we collected data regarding air quality index and COVID-19 determinants of four Indian cities : Bangalore, Delhi, Mumbai and Shillong from 1 October 2020 to 16 November 2020. We performed an analysis of variance on the regression model to estimate and quantify the strength of relationship between COVID-19 determinants and air pollution index (AQI). Results show that AQI has a significant impact on both response variables, that is COVID-19 cases as well as mortality (p < 0.05 at 95% confidence level) in Delhi, Mumbai and Bangalore (p < 0.05) but in Shillong no impact of AQI on COVID-19 cases and AQI (p = 0.343), as well as deaths (p = 0.664), was observed. We conclude that it is both conceivable and reasonable to suspect the role of increased AQI levels in aggravating COVID-19 morbidity and mortality. Thus, we recommend that critical meteorological conditions, like haze/smog caused by factors, like stubble burning or firing crackers should be predicted and monitored more systematically as they may lead to deterioration of respiratory problems. As the whole world is striving to fight against the deadly pandemic, it is extremely imperative to focus not only on human health as a part of response but also on global planetary health. Short term measures that can minimize supplementary risks, like adverse weather situations including pollution, poor air quality should be considered more meticulously and judiciously so that new flares of COVID-19 morbidity and mortality can be restricted. © 2022 - Kalpana Corporation.

Impact of COVID-19 Lockdown on Oxidative Potential of Particulate Matter: Case of Athens (Greece).

This work evaluates the aerosol oxidative potential (OP) and its changes from modified air pollution emissions during the COVID-19 lockdown period in 2020, with the intent of elucidating the contribution of aerosol sources and related components to aerosol OP. For this, daily particulate matter (PM) samples at an urban background site were collected and analyzed with a chemical (acellular) assay based on Dithiothreitol (DTT) during the COVID-19 restriction period in Athens (Greece). The obtained time-series of OP, PM2.5, organic matter (OM) and SO42- of the pre-, post- and lockdown periods were also compared to the data of the same time periods during the years 2017-2019. Even though all traffic-related emissions have been significantly reduced during the lockdown period (by 30%), there is no reduction in water-soluble OP, organics and sulfate concentrations of aerosol during 2020. The results reveal that the decrease in traffic was not sufficient to drive any measurable change on OP, suggesting that other sources-such as biomass burning and secondary aerosol from long-range transport, which remained unchanged during the COVID lockdown-are the main contributors to OP in Athens, Greece.

Seasonal Variation in Chemical Composition of Total Suspended Particles During the COVID-19 Pandemic in the Source Area of Urumqi River, Tianshan, China

The research of atmospheric aerosol in mountain glacier areas has attracted more and more people's attention. For the first time, a field observation study of total suspended particles (TSPs) for four seasons from September 2019 to August 2020 was carried out at the Tianshan Glaciological Station in the source area of Urumqi River, East Tianshan Mountains, China. The TSPs presented typical seasonal characteristics of high in autumn and low in winter, with the annual average value of 181 +/- 170 mu g m(-3). Concentrations of Ca2+, SO42-, NO3-, Cl-, NH4+ and K+, OC, EC were elevated in autumn. The influence of stationary source emissions was stronger than mobile sources, which was explained by the average ratio of NO3-/SO42- (0.31 +/- 0.17). The concentration of secondary organic carbon (SOC) was higher in summer and autumn, especially in summer, indicating that secondary formation processes of organic aerosols were frequent in summer. Impact of fossil fuel combustion sources were evident over the Glaciers, corroborated by the diagnostic mass ratios of OC/EC (0-21.4, 3.38) and K+/EC (0-0.31, 0.08). The factor analysis illustrated that aerosols were mainly affected by rock salt, dust, coal combustion, and automobile exhaust. The local sources made significant contributions to TSPs in the source of Urumqi River by the results of Results of Hybrid Single Particle Lagrangian Integrated Trajectory (HYSPLIT) model and potential source contribution function (PSCF).

Evaluation of Long-Term Modeling Fine Particulate Matter and Ozone in China During 2013-2019

Air quality in China has been undergoing significant changes due to the implementation of extensive emission control measures since 2013. Many observational and modeling studies investigated the formation mechanisms of fine particulate matter (PM2.5) and ozone (O-3) pollution in the major regions of China. To improve understanding of the driving forces for the changes in PM2.5 and O-3 in China, a nationwide air quality modeling study was conducted from 2013 to 2019 using the Weather Research and Forecasting/Community Multiscale Air Quality (WRF/CMAQ) modeling system. In this study, the model predictions were evaluated using the observation data for the key pollutants including O-3, sulfur dioxide (SO2), nitrogen dioxide (NO2), and PM2.5 and its major components. The evaluation mainly focused on five major regions, that is , the North China Plain (NCP), the Yangtze River Delta (YRD), the Pearl River Delta (PRD), the Chengyu Basin (CY), and the Fenwei Plain (FW). The CMAQ model successfully reproduced the air pollutants in all the regions with model performance indices meeting the suggested benchmarks. However, over-prediction of PM2.5 was noted in CY. NO2, O-3,O- and PM2.5 were well simulated in the north compared to the south. Nitrate (NO3-) and ammonium (NH4+) were the most important PM2.5 components in heavily polluted regions. For the performance on different pollution levels, the model generally over-predicted the clean days but underpredicted the polluted days. O-3 was found increasing each year, while other pollutants gradually reduced during 2013-2019 across the five regions. In all of the regions except PRD (all seasons) and YRD (spring and summer), the correlations between PM2.5 and O-3 were negative during all four seasons. Low-to-medium correlations were noted between the simulated PM2.5 and NO2, while strong and positive correlations were established between PM2.5 and SO2 during all four seasons across the five regions. This study validates the ability of the CMAQ model in simulating air pollution in China over a long period and provides insights for designing effective emission control strategies across China.

Maternal Secondhand Smoke Exposure Enhances Macrosomia Risk Among Pregnant Women Exposed to PM2.5: A New Interaction of Two Air Pollutants in a Nationwide Cohort.

Background: Fine particulate matter (PM2.5) is one of the most common outdoor air pollutants, and secondhand smoking (SHS) is an important source of inhalable indoor air pollution. Previous studies were controversial and inconsistent about PM2.5 and SHS air pollutants on neonatal birth weight outcomes, and no studies assessed the potential interactive effects between PM2.5 and SHS on birth weight outcomes. Purpose: To investigate the interaction between gestational PM2.5 and SHS air pollution exposure on the risk of macrosomia among pregnant women and examine the modifying effect of SHS exposure on the association of PM2.5 air pollution and birth weight outcomes during pregnancy. Methods: Research data were derived from the National Free Preconception Health Examination Project (NFPHEP), which lasted 3 years from January 1, 2010, to December 31, 2012. At least 240,000 Chinese women from 220 counties were enrolled in this project. PM2.5 exposure concentration was obtained using a hindcast model specific for historical PM2.5 estimation from satellite-retrieved aerosol optic depth. Different interaction models about air pollution exposure on birth weight outcomes were established, according to the adjustment of different confounding factors and different pregnancy stages. The establishment of interaction models was based on multivariable logistic regression, and the main confounding factors were maternal age at delivery and pre-pregnancy body mass index (BMI) of participants. SHS subgroups analysis was conducted to further confirm the results of interaction models. Results: In total, 197,877 participants were included in our study. In the full-adjusted interaction model, maternal exposure to PM2.5 was associated with an increased risk of macrosomia in whole, the first-, second-, and third trimesters of pregnancy (p < 0.001). The interactive effect was statistically significant between maternal exposure to PM2.5 and SHS on the risk of macrosomia in the whole (interaction p < 0.050) and the first-trimester pregnancy (interaction p < 0.050), not in the second (interaction p > 0.050) or third trimester (interaction p > 0.050) of pregnancy. The higher frequency of SHS exposure prompted the stronger interaction between the two air pollutants in the whole pregnancy and the first-trimester pregnancy. Conclusions: In the whole and first-trimester pregnancy, maternal exposure to SHS during pregnancy enhanced the risk of macrosomia among pregnant women exposed to PM2.5 air pollutants, and the interaction became stronger with the higher frequency of SHS exposure.

Role of angiotensin-converting enzyme 2 in fine particulate matter-induced acute lung injury.

Fine particulate matter (PM2.5) pollution poses significant health concerns worldwide and can cause respiratory diseases. However, how it causes health problems is still poorly understood. Angiotensin-converting enzyme (ACE)2 is a terminal carboxypeptidase implicated in the functions of renin-angiotensin system (RAS) and plays a crucial role in the control of lung inflammation. To investigate whether ACE2 functions in PM2.5-induced lung inflammation, wild-type (WT) C57BL/6J mice and ACE2 knock-out (KO) mice were intratracheally instilled with PBS or PM2.5 suspension for 3 consecutive days, respectively. The concentrations of cytokines in bronchoalveolar lavage fluid (BALF) were determined by ELISA. The expression of ACE2 and ACE and activation of inflammatory signaling pathways in lung tissues were evaluated by immunofluorescence staining and Western blotting. We found that PM2.5 exposure increased ACE2 expression. Loss of ACE2 significantly elevated the levels of total proteins, total cells, and the concentrations of MCP-1, IL-1ß in BALF after PM2.5 challenge. Additionally, loss of ACE2 enhanced lung pathologies, airway resistance, and inflammatory signaling activation. Collectively, loss of ACE2 exacerbates PM2.5-induced acute lung injury in mice.

Smoke and COVID-19 case fatality ratios during California wildfires

Recent evidence has shown an association between wildfire smoke and COVID-19 cases and deaths. The San Francisco Bay Area, in California (USA), experienced two major concurrent public health threats in 2020: the COVID-19 pandemic and dense smoke emitted by wildfires. This provides a unprecedented context to unravel the role of acute air pollution exposure on COVID-19 severity. A smoke product provided by the National Oceanic and Atmospheric Association Hazard Mapping System was used to identify counties exposed to heavy smoke in summer and fall of 2020. Daily COVID-19 cases and deaths for the United States were downloaded at the County-level from the CDC COVID Data Tracker. Synthetic control methods were used to estimate the causal effect of the wildfire smoke on daily COVID-19 case fatality ratios (CFRs), adjusting for population mobility. Evidence of an impact of wildfire smoke on COVID-19 CFRs was observed, with precise estimates in Alameda and San Francisco. Up to 58 (95% CI: 29, 87) additional deaths for every 1000 COVID-19 incident daily cases attributable to wildfire smoke was estimated in Alameda in early September. Findings indicated that extreme weather events such as wildfires smoke can drive increased vulnerability to infectious diseases, highlighting the need to further study these colliding crises. Understanding the environmental drivers of COVID-19 mortality can be used to protect vulnerable populations from these potentially concomitant public health threats.

Fine particulate matter air pollution and under-5 children mortality in China: A national time-stratified case-crossover study.

BACKGROUND: Under-5 mortality rate is an important indicator in Millennium Development Goals and Sustainable Development Goals. To date, no nationally representative studies have examined the effects of fine particulate matter (PM2.5) air pollution on under-5 mortality. OBJECTIVE: To investigate the association of short-term exposure to PM2.5 with under-5 mortality from total and specific causes in China. METHODS: We used the national Maternal and Child Health Surveillance System to identify under-5 mortality cases during the study period of 2009 to 2019. We adopted a time-stratified case-crossover study design at the individual level to capture the effect of short-term exposure to daily PM2.5 on under-5 mortality, using conditional logistic regression models. RESULTS: A total of 61,464 under-5 mortality cases were included. A 10 µg/m3 increase in concentrations of PM2.5 on lag 0-1 d was significantly associated with a 1.15% (95%confidence interval: 0.65%, 1.65%) increase in under-5 mortality. Mortality from diarrhea, pneumonia, digestive diseases, and preterm birth were significantly associated with exposure to PM2.5. The effect estimates were larger for neonatal mortality (<28 days), female children, and in warm seasons. We observed steeper slopes in lower ranges (<50 µg/m3) of the concentration-response curve between PM2.5 and under-5 mortality, and positive associations remained below the 24-h PM2.5 concentration limit recommended by WHO Air Quality Guidelines and China Air Quality Standards. CONCLUSIONS: This nationwide case-crossover study in China demonstrated that acute exposure to PM2.5 may significantly increase the risk of under-5 mortality, with larger effects for neonates, female children, and during warm seasons. Relevant control strategies are needed to remove this roadblock to achieving under-5 mortality targets in developing countries.

Cumulative effects of ambient particulate matter pollution on deaths: A multicity analysis of mortality displacement.

BACKGROUND: Systematic evaluations of the cumulative effects and mortality displacement of ambient particulate matter (PM) pollution on deaths are lacking. We aimed to discern the cumulative effect profile of PM exposure, and investigate the presence of mortality displacement in a large-scale population. METHODS: We conducted a time-series analysis with different exposure-lag models on 13 cities in Jiangsu, China, to estimate the effects of PM pollution on non-accidental, cardiovascular, and respiratory mortality (2015-2019). Over-dispersed Poisson generalized additive models were integrated with distributed lag models to estimate cumulative exposure effects, and assess mortality displacement. RESULTS: Pooled cumulative effect estimates with lags of 0-7 and 0-14 days were substantially larger than those with single-day and 2-day moving average lags. For each 10 µg/m3 increment in PM2.5 concentration with a cumulative lag of 0-7 days, we estimated an increase of 0.50 % (95 % CI: 0.29, 0.72), 0.63 % (95 % CI: 0.38, 0.88), and 0.50 % (95 % CI: 0.01, 1.01) in pooled estimates of non-accidental, cardiovascular, and respiratory mortality, respectively. Both PM10 and PM2.5 were associated with significant increases in non-accidental and cardiovascular mortality with a cumulative lag of 0-14 days. We observed mortality displacement within 30 days for non-accidental, cardiovascular, and respiratory deaths. CONCLUSIONS: Our findings suggest that risk assessment based on single-day or 2-day moving average lag structures may underestimate the adverse effects of PM pollution. The cumulative effects of PM exposure on non-accidental and cardiovascular mortality can last up to 14 days. Evidence of mortality displacement for non-accidental, cardiovascular, and respiratory deaths was found.

Air quality status during 2020 Malaysia Movement Control Order (MCO) due to 2019 novel coronavirus (2019-nCoV) pandemic.

An outbreak of respiratory illness which is proven to be infected by a 2019 novel coronavirus (2019-nCoV) officially named as Coronavirus Disease 2019 (COVID-19) was first detected in Wuhan, China and has spread rapidly in other parts of China as well as other countries around the world, including Malaysia. The first case in Malaysia was identified on 25 January 2020 and the number of cases continue to rise since March 2020. Therefore, 2020 Malaysia Movement Control Order (MCO) was implemented with the aim to isolate the source of the COVID-19 outbreak. As a result, there were fewer number of motor vehicles on the road and the operation of industries was suspended, ergo reducing emissions of hazardous air pollutants in the atmosphere. We had acquired the Air Pollutant Index (API) data from the Department of Environment Malaysia on hourly basis before and during the MCO with the aim to track the changes of fine particulate matter (PM2.5) at 68 air quality monitoring stations. It was found that the PM2.5 concentrations showed a high reduction of up to 58.4% during the MCO. Several red zone areas (>41 confirmed COVID-19 cases) had also reduced of up to 28.3% in the PM2.5 concentrations variation. The reduction did not solely depend on MCO, thus the researchers suggest a further study considering the influencing factors that need to be adhered to in the future.

The Impact of the Lockdown Caused by the COVID-19 Pandemic on the Fine Particulate Matter (PM2.5) Air Pollution: The Greek Paradigm.

INTRODUCTION: Responding to the coronavirus pandemic, Greece implemented the largest quarantine in its history. No data exist regarding its impact on PM2.5 pollution. We aimed to assess PM2.5 levels before, during, and after lockdown (7 March 2020-16 May 2020) in Volos, one of Greece's most polluted industrialized cities, and compare PM2.5 levels with those obtained during the same period last year. Meteorological conditions were examined as confounders. METHODS: The study period was discriminated into three phases (pre-lockdown: 7 March-9 March, lockdown: 10 March-4 May, and post-lockdown period: 5 May-16 May). A wireless sensors network was used to collect PM2.5, temperature, relative humidity, rainfall, and wind speed data every 2 s. RESULTS: The lockdown resulted in a significant drop of PM2.5 by 37.4% in 2020, compared to 2019 levels. The mean daily concentrations of PM2.5 exceeded the WHO's guideline value for 24-h mean levels of PM2.5 35% of the study period. During the strictest lockdown (23 March to 4 May), the mean daily PM2.5 levels exceeded the standard 41% of the time. The transition from the pre-lockdown period into lockdown or post-lockdown periods was associated with lower PM2.5 concentrations. CONCLUSIONS: A reduction in the mean daily PM2.5 concentration was found compared to 2019. Lockdown was not enough to avoid severe exceedances of air pollution in Volos.

PM2.5 Pollution Strongly Predicted COVID-19 Incidence in Four High-Polluted Urbanized Italian Cities during the Pre-Lockdown and Lockdown Periods.

BACKGROUND: The coronavirus disease in 2019 (COVID-19) heavily hit Italy, one of Europe's most polluted countries. The extent to which PM pollution contributed to COVID-19 diffusion is needing further clarification. We aimed to investigate the particular matter (PM) pollution and its correlation with COVID-19 incidence across four Italian cities: Milan, Rome, Naples, and Salerno, during the pre-lockdown and lockdown periods. METHODS: We performed a comparative analysis followed by correlation and regression analyses of the daily average PM10, PM2.5 concentrations, and COVID-19 incidence across four cities from 1 January 2020 to 8 April 2020, adjusting for several factors, taking a two-week time lag into account. RESULTS: Milan had significantly higher average daily PM10 and PM2.5 levels than Rome, Naples, and Salerno. Rome, Naples, and Salerno maintained safe PM10 levels. The daily PM2.5 levels exceeded the legislative standards in all cities during the entire period. PM2.5 pollution was related to COVID-19 incidence. The PM2.5 levels and sampling rate were strong predictors of COVID-19 incidence during the pre-lockdown period. The PM2.5 levels, population's age, and density strongly predicted COVID-19 incidence during lockdown. CONCLUSIONS: Italy serves as a noteworthy paradigm illustrating that PM2.5 pollution impacts COVID-19 spread. Even in lockdown, PM2.5 levels negatively impacted COVID-19 incidence.

Ambient fine particulate matter air pollution and the risk of hospitalization among COVID-19 positive individuals: Cohort study.

BACKGROUND: Ecologic analyses suggest that living in areas with higher levels of ambient fine particulate matter air pollution (PM2.5) is associated with higher risk of adverse COVID-19 outcomes. Studies accounting for individual-level health characteristics are lacking. METHODS: We leveraged the breadth and depth of the US Department of Veterans Affairs national healthcare databases and built a national cohort of 169,102 COVID-19 positive United States Veterans, enrolled between March 2, 2020 and January 31, 2021, and followed them through February 15, 2021. Annual average 2018 PM2.5 exposure, at an approximately 1 km2 resolution, was linked with residential street address at the year prior to COVID-19 positive test. COVID-19 hospitalization was defined as first hospital admission between 7 days prior to, and 15 days after, the first COVID-19 positive date. Adjusted Poisson regression assessed the association of PM2.5 with risk of hospitalization. RESULTS: There were 25,422 (15.0%) hospitalizations; 5,448 (11.9%), 5,056 (13.0%), 7,159 (16.1%), and 7,759 (19.4%) were in the lowest to highest PM2.5 quartile, respectively. In models adjusted for State, demographic and behavioral factors, contextual characteristics, and characteristics of the pandemic a one interquartile range increase in PM2.5 (1.9 µg/m3) was associated with a 10% (95% CI: 8%-12%) increase in risk of hospitalization. The association of PM2.5 and risk of hospitalization among COVID-19 individuals was present in each wave of the pandemic. Models of non-linear exposure-response suggested increased risk at PM2.5 concentrations below the national standard 12 µg/m3. Formal effect modification analyses suggested higher risk of hospitalization associated with PM2.5 in Black people compared to White people (p = 0.045), and in those living in socioeconomically disadvantaged neighborhoods (p < 0.001). CONCLUSIONS: Exposure to higher levels of PM2.5 was associated with increased risk of hospitalization among COVID-19 infected individuals. The risk was evident at PM2.5 levels below the regulatory standards. The analysis identified those of Black race and those living in disadvantaged neighborhoods as population groups that may be more susceptible to the untoward effect of PM2.5 on risk of hospitalization in the setting of COVID-19.

Beyond virology: environmental constraints of the first wave of COVID-19 cases in Italy.

Global warming and air pollution affect the transmission pathway and the survival of viruses, altering the human immune system as well. The first wave of the COVID-19 pandemic dramatically highlights the key roles of climate and air chemistry in viral epidemics. The elongated form of the Italian peninsula and the two major islands (the largest in Europe) is a perfect case study to assess some of these key roles, as the fate of the virus is mirroring the industrialization in the continental part of our country. Fine particulate matter (PM2.5), geography, and climate explain what is happening in Italy and support cleaner air actions to address efficiently other outbreaks. Besides the environmental factors, future works should also address the genetic difference among individuals to explain the spatial variability of the human response to viral infections.

Qualitative and quantitative analyses of impact of COVID-19 on sustainable development goals (SDGs) in Indian subcontinent with a focus on air quality.

Coronavirus disease 2019 (COVID-19) is spreading all over the world in a short time. It originated from Wuhan City of China in the late 2019. Proper vaccines have still been in progress; the spread of the virus is contracted by lockdown and social distancing protocols. These lockdowns resulted in significant benefits, improving the quality of air and reducing the level of environmental pollution. In this context, the study proposes to identify the air quality in the region and its relation with COVID-19-affected people in metropolitan cities of India during COVID-19 lockdowns using a geographical information system (GIS), where over 90% of commercial and industrial sites and 100% school and colleges were closed. The study outcomes highlight the areas encountering high levels of pollution under the pre-lockdown scenario and have seen a higher number of cases. The relation is most evident for PM2.5, which is responsible for respiratory disorders and is the place of attack of SARS-CoV-2. This approach provides comparable outcomes with other decision-making tools. Our primary precedence should be to develop communities to enable people to remain healthy and stay. Healthy societies are crucial not only for people's health, but also for sustainable development. Centered on GIS is concealed; moreover, it is very flexible to use by policymakers.