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The additional impact of emission-reduction measures in North China (NC) during autumn and winter on the air quality of downwind regions is an interesting but less addressed topic. The mass concentrations of routine air pollutants, the chemical compositions, and sources of fine particles (PM2.5) for January 2018, 2019, and 2020 at a megacity of Central China were identified, and meteorology-isolated by a machine-learning technique. Their variations were classified according to air mass direction. An unexpectedly sharp increase in emission-related PM2.5 by 22.7% (18.0 mug m-3) and 25.7% (19.4 mug m-3) for air masses from local and NC in 2019 was observed compared to those of 2018. Organic materials exhibited the highest increase in PM2.5 compositions by 6.90 mug m-3 and 6.23 mug m-3 for the air masses from local and NC. PM2.5 source contributions related to emission showed an upsurge from 1.39 mug m-3 (biomass burning) to 24.9 mug m-3 (secondary inorganic aerosol) in 2019 except for industrial processes, while all reduced in 2020. From 2018 to 2020, the emission-related contribution of coal combustion to PM2.5 increased from 10.0% to 19.0% for air masses from the local area. To support the priority natural gas quotas in northern China, additional coal in cities of southern China was consumed, raising related emissions from transportation activities and road dust in urban regions, as well as additional biofuel consumption in suburban or rural regions. All these activities could explain the increased primary PM2.5 and related precursor NO2. This study gave substantial evidence of air pollution control measures impacting the downwind regions and promote the necessity of air pollution joint control across the administration.Copyright © 2023 Elsevier Ltd
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Background: Evidence suggests association between long-term exposure to air pollutants and increased risk of becoming infected with SARS-CoV- 2, the causative agent of COVID-19, and increased severity of COVID-19. However, it remains unclear whether breathing more polluted air over many years affects susceptibility to infection or only affects disease severity, with uncertainty around the intensity of these associations. It has been estimated that anthropogenic emissions have contributed to over 10% of the over 660 million cases of SARS-CoV-2 and the over 7.5 million COVID-19 deaths reported worldwide over the course of the pandemic. Furthermore, as the world continues to warm and if air pollution levels increase, then so might the burden of respiratory infectious disease, including COVID-19. Method(s): Here we explore the potential impact of long-term exposure to increasing levels of particulate matter 2.5 microns or less in diameter (PM2.5) (+1 to +5 mug/m3) assuming an association on either (1) SARS-CoV-2 susceptibility or (2) COVID-19 disease severity by projecting SARS-CoV-2 infections and COVID-19-related hospital admissions over a two-year period. Simulations were conducted using a SARS-CoV-2 transmission model in a global setting capturing age and comorbidity risk, considering seasonality, emerging variants, and vaccination and treatment options. We model linear, log, and log10 relationships between these associations. Result(s): We show that if long-term exposure to higher levels of air pollution only affects COVID-19 severity, then as expected, the projected number of COVID-19-related hospitalisations would proportionally increase. However, if exposure directly affects the susceptibility of becoming infected, then while infections would be higher, hospitalizations would also be even higher due to the potential for onward transmission. This aligns with associations between air pollution and other respiratory infections and their associated health outcomes. Conclusion(s): The anticipated additional impact air pollution is having on the public health burden of respiratory infectious disease, like COVID-19, should be considered in strategic action plans to mitigate and adapt to changing levels of air pollution. It is important to better understand at which point air pollution affects SARS-CoV-2 infection acquisition through to disease progression, to enable improved protection and to better support those most vulnerable. Modelled impact of air pollution on COVID-19. The projected cumulative impact of long-term exposure to incrementally higher PM2.5 levels (+1 to +5 mug/m3) affecting either SARS-CoV-2 susceptibility or COVID-19 disease severity on cumulative SARS-CoV-2 infections and COVID-19-related hospital admissions over a two-year period in a global setting of 100,000 people. Age and comorbidity risk are captured, seasonality considered, and it is assumed SARS-CoV-2 variants of concern (with 10% more infectious and 20% more immune-evading than the previous variant, and Omicron-level severity) emerge every six months, and COVID-19 vaccination and treatment (monoclonalantibody PrEP and antivirals) are implemented for all those eligible. While the associations between PM2.5 exposure and either SARS-CoV-2 susceptibility or COVID-19 disease severity remains unclear and there is much uncertainty around estimated assumptions, here we show a modelled log10 relationship between these two potential associations. COVID-19: coronavirus disease 2019. PM2.5: particulate matter 2.5 microns or less in diameter. PrEP: pre-exposure prophylaxis. SARS-CoV-2: severe acute respiratory syndrome coronavirus 2.
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The proceedings contain 32 papers. The topics discussed include: assessment of workplace indoor fine particle exposure and pulmonary function parameters among ceramic tile industry workers of West India;respiratory morbidities in school children of critically polluted industrial area of Gujarat - a prospective observational study;morbidities among workers of an organochlorine pesticide industry;identifying interventions to reduce NCDs in workplaces in India: a stakeholder's assessment;examining toxic metals in biological samples and residential PM2.5 to evaluate their risk in adolescent children;ergonomics hazard assessment reduction in large scale petrochemical complex, Vadodara;factors associated with work related quality of life among garment factory employees in South India;factors associated with work related quality of life among garment factory employees in South India;and screening for COVID-19 among workers attending medical examinations under occupational health service of an open cast iron ore mine in Jharkhand: a cross-sectional study.
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Introduction Studies on air pollution and COVID-19 are limited to the first pandemic wave (April/June 2020) and by their ecological design. Objectives To investigate the association between airborne pollutants and SARS-CoV-2 incidence up to March 2021 in the Varese city (Lombardy region), with individual-level data on exposures, disease and confounders. Methods Varese citizens aged 18+ years as of Dec31st,2019 were linked by residential address to 2018 average annual exposure to outdoor concentrations of PM2.5, PM10, NO2, NO and O3 modelled using FARM chemical-transport model (linkage coverage: 97.4%). Citizens were linked to Regional datasets for COVID-19 case ascertainment (positive nasophar-yngeal swab specimens) and to define age, sex, residential care home living, population density and comorbidities. We estimated rate ratios and additional number of COVID-19 cases for 1 mg/m3 increase in air pollutants, from single-and bi-pol-lutant Poisson regression models. Results Among the 62.848 residents, we observed 4408 COVID-19 cases. Yearly average PM2.5 exposure was 12.5 mg/m3. Cumulative incidence curves suggest an increased risk for PM2.5>13.5 mg/m3 in correspondence of downtrend periods in the pandemic curve. Age, residential care home living, history of stroke, medications for diabetes, hypertension and obstructive airway disease were independently associated with COVID-19 rate. In single-pollutant multivariate model, 1 mg/m3 increase in PM2.5 was associated with 5.1% increase in COVID-19 rate (95%CI: 2.7%-7.5%), corresponding to 294 additional cases per 100.000 person-years. These figures were confirmed in bi-pollutant models and after excluding subjects in residential care homes. Similar findings were observed for PM10, NO2 and NO. O3 was associated with a 2% decrease in disease rate, the association being reversed in bi-pollutant models. Conclusions In our study, long term exposure to low-levels of air pollutants, especially PM2.5, positively affected COVID-19 incidence. Causality warrants confirmation in future studies;meanwhile, governmental efforts to further reduce air pollution should continue.
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BACKGROUND AND OBJECTIVE: Ecological studies have suggested an association between exposure to particulate matter ≤2.5 µm (PM2.5 ) and coronavirus disease 2019 (COVID-19) severity. However, these findings are yet to be validated in individual-level studies. We aimed to determine the association of long-term PM2.5 exposure with hospitalization among individual patients infected with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). METHODS: We estimated the 10-year (2009-2018) PM2.5 exposure at the residential zip code of COVID-19 patients diagnosed at the University of Cincinnati healthcare system between 13 March 2020 and 30 September 2020. Logistic regression was used to determine the odds ratio (OR) and 95% CI for COVID-19 hospitalizations associated with PM2.5 , adjusting for socioeconomic characteristics and comorbidities. RESULTS: Among the 14,783 COVID-19 patients included in our study, 13.6% were hospitalized; the geometric mean (SD) PM2.5 was 10.48 (1.12) µg/m3 . In adjusted analysis, 1 µg/m3 increase in 10-year annual average PM2.5 was associated with 18% higher hospitalization (OR: 1.18, 95% CI: 1.11-1.26). Likewise, 1 µg/m3 increase in PM2.5 estimated for the year 2018 was associated with 14% higher hospitalization (OR: 1.14, 95% CI: 1.08-1.21). CONCLUSION: Long-term PM2.5 exposure is associated with increased hospitalization in COVID-19. Therefore, more stringent COVID-19 prevention measures may be needed in areas with higher PM2.5 exposure to reduce the disease morbidity and healthcare burden.