scholarly journals Association between air pollution and COVID-19 mortality and morbidity

2021 ◽  
Author(s):  
Karolina Semczuk-Kaczmarek ◽  
Anna Rys-Czaporowska ◽  
Janusz Sierdzinski ◽  
Lukasz Dominik Kaczmarek ◽  
Filip Marcin Szymanski ◽  
...  
Keyword(s):  
Air Pollution ◽  
Respiratory Diseases ◽  
Average Concentration ◽  
Cumulative Number ◽  
Annual Average ◽  
Mortality And Morbidity ◽  
Increased Risk ◽  
Annual Average Concentration ◽  
Official Data

AbstractCoronavirus disease (COVID-19) pandemic is affecting the world unevenly. One of the highest numbers of cases were recorded in the most polluted regions worldwide. The risk factors for severe COVID-19 include diabetes, cardiovascular, and respiratory diseases. It has been known that the same disease might be worsened by chronic exposure to air pollution. The study aimed to determine whether long-term average exposure to air pollution is associated with an increased risk of COVID-19 cases and deaths in Poland. The cumulative number of COVID-19 cases and deaths for each voivodeship (the main administrative level of jurisdictions) in Poland were collected from March 4, 2020, to May 15, 2020. Based on the official data published by Chief Inspectorate of Environmental Protection voivodeship-level long-term exposure to main air pollution: PM2.5, PM10, NO2, SO2, O3 (averaged from 2013 to 2018) was established. There were statistically significant correlation between COVID-19 cases (per 100,000 population) and annual average concentration of PM2.5 (R2 = 0.367, p = 0.016), PM10 (R2 = 0.415, p = 0.009), SO2 (R2 = 0.489, p = 0.003), and O3 (R2 = 0.537, p = 0.0018). Moreover, COVID-19 deaths (per 100,000 population) were associated with annual average concentration of PM2.5 (R2 = 0.290, p = 0.038), NO2 (R2 = 0.319, p = 0.028), O3 (R2 = 0.452, p = 0.006). The long-term exposure to air pollution, especially PM2.5, PM10, SO2, NO2, O3 seems to play an essential role in COVID-19 prevalence and mortality. Long-term exposure to air pollution might increase the susceptibility to the infection, exacerbates the severity of SARS-CoV-2 infections, and worsens the patients’ prognosis. The study provides generalized and possible universal trends. Detailed analyzes of the phenomenon dedicated to a given region require taking into account data on comorbidities and socioeconomic variables as well as information about the long-term exposure to air pollution and COVID-19 cases and deaths at smaller administrative level of jurisdictions (community or at least district level).

scholarly journals Toxic Heavy Metals in Sediments of Mahul Creek near Mumbai, India

2014 ◽  
Vol 15 ◽  
pp. 69-78
Author(s):  
Pravin U. Singare ◽  
M.V.A. Ansari ◽  
N.N. Dixit
Keyword(s):  
Heavy Metals ◽  
Average Concentration ◽  
Economic Prosperity ◽  
Toxic Heavy Metals ◽  
Short Term ◽  
Annual Average ◽  
Industrial Growth ◽  
Annual Average Concentration ◽  
One Year

The present study was performed for the period of one year from January 2013 to December 2013 in order to understand the level of toxic heavy metals in the sediments of Mahul Creek near Mumbai. The annual average concentration of heavy metals like Cr, Zn, Cu, Ni, Pb, Cd, As and Hg was found to be 277.5, 121.7, 100.3, 63.8, 21.5, 14.6, 10.4 and 4.9 ppm respectively. It is feared that this heavy metals accumulated in the creek sediments may enter the water thereby creating threat to the biological life of an aquatic ecosystem. The results of present study indicates that the existing situation if mishandled can cause irreparable ecological harm in the long term well masked by short term economic prosperity due to extensive industrial growth

scholarly journals Long-Term Exposure to PM2.5, Facemask Mandates, Stay Home Orders and COVID-19 Incidence in the United States

2021 ◽  
Vol 18 (12) ◽  
pp. 6274
Author(s):  
Fang Fang ◽  
Lina Mu ◽  
Yifang Zhu ◽  
Jianyu Rao ◽  
Jody Heymann ◽  
...  
Keyword(s):  
United States ◽  
Negative Binomial ◽  
State Level ◽  
The United States ◽  
Average Concentration ◽  
Annual Average ◽  
Annual Average Concentration ◽  
Pm2.5 Exposure ◽  
Binomial Models

Long-term PM2.5 exposure might predispose populations to SARS-CoV-2 infection and intervention policies might interrupt SARS-CoV-2 transmission and reduce the risk of COVID-19. We conducted an ecologic study across the United States, using county-level COVID-19 incidence up to 12 September 2020, to represent the first two surges in the U.S., annual average of PM2.5 between 2000 and 2016 and state-level facemask mandates and stay home orders. We fit negative binomial models to assess COVID-19 incidence in association with PM2.5 and policies. Stratified analyses by facemask policy and stay home policy were also performed. Each 1-µg/m3 increase in annual average concentration of PM2.5 exposure was associated with 7.56% (95% CI: 3.76%, 11.49%) increase in COVID-19 risk. Facemask mandates and stay home policies were inversely associated with COVID-19 with adjusted RRs of 0.8466 (95% CI: 0.7598, 0.9432) and 0.9193 (95% CI: 0.8021, 1.0537), respectively. The associations between PM2.5 and COVID-19 were consistent among counties with or without preventive policies. Our study added evidence that long-term PM2.5 exposure increased the risk of COVID-19 during each surge and cumulatively as of 12 September 2020, in the United States. Although both state-level implementation of facemask mandates and stay home orders were effective in preventing the spread of COVID-19, no clear effect modification was observed regarding long-term exposure to PM2.5 on the risk of COVID-19.

scholarly journals A global association between Covid-19 cases and airborne particulate matter at regional level

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Angelo Solimini ◽  
F. Filipponi ◽  
D. Alunni Fegatelli ◽  
B. Caputo ◽  
C. M. De Marco ◽  
...  
Keyword(s):  
Air Pollution ◽  
Particulate Matter ◽  
Negative Binomial ◽  
Numerical Models ◽  
Regional Level ◽  
Pollution Level ◽  
Observation Data ◽  
Cumulative Number ◽  
Mixed Effect

AbstractEvidences of an association between air pollution and Covid-19 infections are mixed and inconclusive. We conducted an ecological analysis at regional scale of long-term exposure to air-borne particle matter and spread of Covid-19 cases during the first wave of epidemics. Global air pollution and climate data were calculated from satellite earth observation data assimilated into numerical models at 10 km resolution. Main outcome was defined as the cumulative number of cases of Covid-19 in the 14 days following the date when > 10 cumulative cases were reported. Negative binomial mixed effect models were applied to estimate the associations between the outcome and long-term exposure to air pollution at the regional level (PM10, PM2.5), after adjusting for relevant regional and country level covariates and spatial correlation. In total we collected 237,749 Covid-19 cases from 730 regions, 63 countries and 5 continents at May 30, 2020. A 10 μg/m3 increase of pollution level was associated with 8.1% (95% CI 5.4%, 10.5%) and 11.5% (95% CI 7.8%, 14.9%) increases in the number of cases in a 14 days window, for PM2.5 and PM10 respectively. We found an association between Covid-19 cases and air pollution suggestive of a possible causal link among particulate matter levels and incidence of COVID-19.

scholarly journals Long-term effects of fine particulate matter exposure on the progression of arterial stiffness

2021 ◽  
Vol 20 (1) ◽  
Author(s):  
Dianqin Sun ◽  
Yue Liu ◽  
Jie Zhang ◽  
Jia Liu ◽  
Zhiyuan Wu ◽  
...  
Keyword(s):  
Arterial Stiffness ◽  
Health Management ◽  
Ankle Brachial Index ◽  
Population Data ◽  
Average Concentration ◽  
Air Pollutant ◽  
Stiffness Index ◽  
Long Term Effects ◽  
Annual Average

Abstract Background Prior studies have investigated the association of PM2.5 exposure with arterial stiffness measured by ankle-brachial index (ABI) and brachial-ankle pulse wave velocity (baPWV), of which conclusions are inconsistent. Moreover, limited evidence is available on the contributory role of PM2.5 exposure on the arterial stiffness index. Methods We used the population data from the Beijing Health Management Cohort and conducted a longitudinal analysis. The annual average concentration of PM2.5 for 35 air pollutant monitoring sites in Beijing from 2014 to 2018 was used to estimate individual exposure by different interpolation methods. Multivariate logistic regression and linear regression were conducted to assess the association of annual average PM2.5 concentration with the incidence of higher baPWV, the progression of ABI, and baPWV, respectively. Results The association between PM2.5 exposure and incidence of higher baPWV was not significant (OR = 1.11, 95% CI: 0.82–1.50, P = 0.497). There was − 0.16% (95% CI: − 0.43-0.11%) decrease in ABI annually and 1.04% (95% CI: 0.72–1.37%) increase in baPWV annually with each increment of 10 μg/m3 average PM2.5 concentration. Conclusions Long-term exposure to PM2.5 was associated with the progression of arterial stiffness in Beijing. This study suggests that improvement of air quality may help to prevent arterial stiffness.

scholarly journals Heavy Metal Content in Water of Resko Lake (North-West Poland)

2013 ◽  
Vol 13 ◽  
pp. 279-287 ◽  
Author(s):  
Piotr Daniszewski ◽  
Ryszard Konieczny
Keyword(s):  
Surface Water ◽  
Water Samples ◽  
Metal Content ◽  
Research Work ◽  
Average Concentration ◽  
Permissible Limit ◽  
Toxic Heavy Metals ◽  
Annual Average ◽  
North West ◽  
Annual Average Concentration

The present research work deals with the quantification of toxic heavy metals in the water samples collected from Lake of Resko (North-West Poland). While the annual average concentration of Cadmium was calculated as 0.34 ppm in 2008 of the year and 0.28 ppm in 2009 of the year. The values obtained were found to be below the permissible limit of 2.0 ppm set for inland surface water. While the annual average concentration of Chromium was calculated as 1,75 ppm in 2008 of the year and 1.97 ppm in 2009 of the year. Which was very much above the permissible limit of 0.1 ppm set for inland surface water. The observed annual average concentration of Copper in the water was 0.05 ppm in 2008 of the year and 0.06 ppm in 2009 of the year, which was below the permissible limit of 3.0 ppm set for inland surface water. While the annual average concentration of Mercury was calculated as 0.03 ppm in 2008 of the year and 0.04 ppm in 2009 of the year, which was very much above the maximum limit of 0.01 ppm set for inland surface water. The annual average concentration of Nickel in the water samples was observed to be 2.07 ppm in 2008 of the year and 2.09 ppm in 2009 of the year, which is close to the limit of 3.0 ppm set for inland surface water. The annual average concentration of Pb in the water samples was observed to be 0.07 ppm in 2008 of the year and 0.05 ppm in 2009 of the year, which is above the permissible limit of 0.1 ppm set for inland surface water. The results of the present investigation indicate that the annual average concentration of Zn in water samples was 3.02 ppm in 2008 of the year and 2.74 ppm in 2009 of the year, which is above the permissible limit of 5.0 ppm set for inland surface water.

scholarly journals Quantification of mortality and morbidity in general population of heavily-industrialized city of Abadan: Effect of long-term exposure

2021 ◽  
Author(s):  
Akram Ghorbanian ◽  
Ahmad Jonidi Jafari ◽  
Abbas Shahsavani ◽  
Ali Abdolahnejad ◽  
Majid Kermani ◽  
...  
Keyword(s):  
Air Pollution ◽  
Mortality Data ◽  
Air Pollution Control ◽  
Medical Sciences ◽  
Mortality And Morbidity ◽  
Khuzestan Province ◽  
Vice Chancellor ◽  
One Year ◽  
The One

Introduction: In the 21st century, air pollution has become a global and environmental challenge. The increase in cases of illness and mortality due to air pollution is not hidden from anyone. Therefore, in this study, we estimated the mortality rate due to cause by air pollution agents (PM2.5) in the southernmost city of Khuzestan province (Abadan city) at 2018-2019. Materials and methods: To estimate the mortality duo to air pollution, data related to PM2.5 particles daily concentrations was received from the Abadan Environmental Protection Organization. The average 24-h concentrations of PM2.5 were calculated using Excel. Then, mortality data were obtained from the Vice Chancellor for Health, Abadan University of Medical Sciences. Finally, by AirQ+ software, each of the mortality in 2018-2019 in Abadan was estimated. Results: The obtained data indicated that the concentration of PM2.5 particles within the one-year period was higher than the value set by WHO guideline and EPA standard. Which caused the citizens of Abadan to be exposed to PM2.5 more than 8.23 times than the guidelines of the WHO and 5.34 times more than the standard of the EPA. The output of the model used in this study was as follows: natural mortality (462 cases, AP: 38.25%), mortality duo to LC (6 cases, AP: 32.18%), mortality duo to COPD (8 cases, AP: 26.64%), mortality duo to Stroke (86 cases, AP: 71.26%), mortality duo to IHD (183 cases, AP: 68.34%) and mortality duo to ALRI (2 cases, AP: 32.9%). Conclusion: Planning appropriate strategies of air pollution control to reduce exposure and attributable mortalities is important and necessary.

Evaluation and Management of Ambient Air Quality, with Special Reference to China

1980 ◽  
Vol 7 (3) ◽  
pp. 223-228 ◽  
Author(s):  
Yao Zhi-Qi
Keyword(s):  
Air Quality ◽  
Geometric Mean ◽  
Monitoring And Evaluation ◽  
Ambient Air ◽  
Average Concentration ◽  
Quality Indices ◽  
Ambient Air Quality ◽  
Annual Average ◽  
Hygienic Standard ◽  
Annual Average Concentration

Monitoring and evaluation of air quality in urban and industrial areas are essential for air quality management. For evaluating the composite air-quality in the concomitant presence of several pollutants in the atmosphere, many air quality indices have been developed. This paper presents two indices, the ‘composite air-quality index (I1)’ and ‘the standard-exceeding index of air pollution (I2)’ together with their respective sub-indices, for the pollutants monitored and for use in combination.The first index, I1, is based on the annual average concentration measured in a year for each pollutant; it measures the overall composite air-quality. By relating the annual average concentration (Ci) of each pollutant to its hygienic standard (Si), as many (Ci/Si) values as the number of pollutant parameters monitored are found, whereupon I1 is computed as the geometric mean of the maximum and average of all (Ci/Si) values. A greater value of I1 means worse composite air-quality. It is simpler to compute than those more sophisticated ones in the literature, and holds the unique characteristic of considering, and yet not overemphasizing as formula (3) does (Nemerow, 1974), the maximum (Ci/Si) value.

Air Pollution as Risk Factor for Mental Disorders: In Search for a Possible Link with Alzheimer’s Disease and Schizophrenia

2021 ◽  
Author(s):  
Luigi Attademo ◽  
Francesco Bernardini
Keyword(s):  
Mental Health ◽  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Air Pollution ◽  
Risk Factor ◽  
Air Pollutants ◽  
Epidemiological Studies ◽  
Increased Risk ◽  
The Central Nervous System

As a global problem that has increasingly been causing worldwide concern, air pollution poses a significant and serious environmental risk to health. Risks of cardiovascular and respiratory diseases, as well as various types of cancer, have been consistently associated with the exposure to air pollutants. More recently, various studies have also shown that the central nervous system is also attacked by air pollution. Air pollution appears to be strongly associated with a higher risk of cognitive defects, neurodevelopmental (e.g., schizophrenia) and neurodegenerative (e.g., Alzheimer’s disease) disorders. Subjects with schizophrenia, as well as subjects with Alzheimer’s disease, experience a variety of neuropsychological deficits and cognitive impairments. This determines an adverse effect on social and professional functioning, and it contributes to the long-term disease burden. However, no final conclusions have been drawn on the matter of the direct relationship between schizophrenia and Alzheimer’s disease. In recent years, the topic of urbanicity and mental health has become increasingly important. Urban exposure to environmental toxins and pollution is currently described as a reliable risk factor for schizophrenia and other psychoses, and it has been demonstrated more and more how exposure to air pollutants is associated with increased risk of dementia. Pathways by which air pollution can target and damage the brain, leading to an increased risk for developing schizophrenia and Alzheimer’s disease, are multiple and complex. Results from epidemiological studies suggest potential associations, but are still insufficient to confirm causality. Further studies are needed in order to verify this hypothesis. And if confirmed, the clinical implications could be of substantial relevance for both public and mental health.

scholarly journals Analysis of the distributions of hourly NO<sub>2</sub> concentrations contributing to annual average NO<sub>2</sub> concentrations across the European monitoring network between 2000 and 2014

2017 ◽  
Author(s):  
Christopher S. Malley ◽  
Erika von Schneidemesser ◽  
Sarah Moller ◽  
Christine F. Braban ◽  
W. Kevin Hicks ◽  
...  
Keyword(s):  
Atmospheric Chemistry ◽  
Monitoring Network ◽  
Average Concentration ◽  
Monitoring Site ◽  
The European Union ◽  
Annual Average ◽  
Limit Value ◽  
Annual Average Concentration ◽  
Standard Set ◽  
Human Health Effects

Abstract. Exposure to nitrogen dioxide (NO2) is associated with negative human health effects, both for short-term peak concentrations and from long-term exposure to a wider range of NO2 concentrations. For the latter, the European Union has established an air quality limit value of 40 µg m−3 as an annual average. However, factors such as proximity and strength of local emissions, atmospheric chemistry and meteorological conditions means that there is substantial variation in the hourly NO2 concentrations contributing to an annual average concentration. The aim of this analysis was to quantify the nature of this variation at thousands of monitoring sites across Europe through the calculation of a standard set of chemical climatology statistics. Specifically, at each monitoring site that satisfied data capture criteria for inclusion in this analysis, annual NO2 concentrations, as well as the percentage contribution from each month, hour of the day, and hourly NO2 concentrations divided into 5 µg m−3 bins were calculated. Across Europe, 2010–2014 average annual NO2 concentrations (NO2AA) exceeded the annual NO2 limit value at 8 % of > 2500 monitoring sites. The application of this chemical climatology approach showed that sites with distinct monthly, hour of day, and hourly NO2 concentration bin contributions to NO2AA were not grouped in specific regions of Europe, and within relatively small geographic regions there were sites with similar NO2AA, but with differences in these contributions. Specifically, at sites with highest NO2AA, there were generally similar contributions from across the year, but there were also differences in the contribution of peak vs moderate hourly NO2 concentrations to NO2AA, and from different hours across the day. Trends between 2000 and 2014 for 259 sites indicate that, in general, the contribution to NO2AA from winter months has increased, as has the contribution from the rush-hour periods of the day, while the contribution from peak hourly NO2 concentrations has decreased. The variety of monthly, hour of day and hourly NO2 contribution bin contributions to NO2AA, across cities, countries and regions of Europe indicate that within relatively small geographic areas different interactions between emissions, atmospheric chemistry and meteorology produce variation in NO2AA and the conditions that produce it. Therefore, measures implemented to reduce NO2AA in one location may not be as effective in others. The development of strategies to reduce NO2AA for an area should consider i) the variation in monthly, hour of day and hourly NO2 concentration bin contributions to NO2AA within that area, and ii) how specific mitigation actions will affect variability in hourly NO2 concentrations.

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