Statistical Estimation of Dose-response Functions of Respiratory Diseases and Societal Costs of Haze-related Air Pollution in Brunei Darussalam

2003 ◽  
Vol 160 (1-2) ◽  
pp. 279-293 ◽  
Author(s):  
K.A. Anaman ◽  
N. Ibrahim
Keyword(s):  
Air Pollution ◽  
Dose Response ◽  
Statistical Estimation ◽  
Respiratory Diseases ◽  
Response Functions ◽  
Societal Costs ◽  
Brunei Darussalam

scholarly journals Impacts of air pollution and climate on materials in Athens, Greece

2016 ◽  
Author(s):  
John Christodoulakis ◽  
Chris G. Tzanis ◽  
Costas A. Varotsos ◽  
Martin Ferm ◽  
Johan Tidblad
Keyword(s):  
Air Pollution ◽  
Air Quality ◽  
Mass Loss ◽  
Dose Response ◽  
Quality Parameters ◽  
Air Pollutant ◽  
Response Functions ◽  
Experimental Database ◽  
Environmental Air ◽  
The Relationship

Abstract. For more than 10 years now the National and Kapodistrian University of Athens, Greece, contributes to the UN/ECE ICP Materials programme for monitoring of the corrosion/soiling levels of different kind of materials due to environmental air-quality parameters. In this paper we present the results obtained from the analysis of such observational data that were collected in Athens during the period 2003–2012. According to these results the corrosion/soiling of the particular exposed materials tend to decrease over the years, except for the case of copper. Based on this long experimental database applicable to multi-pollutant situation of the Athens basin we present dose response functions (DRFs) considering, that "dose" stands for the air pollutant concentration, "response" for the material mass loss (normally per annum) and the "function" the relationship derived by the best statistical fit to the data.

Environmental and Hygienic Assessment of Ambient Air Pollution in Oil-Producing and Oil-Refining Areas of the Republic of Bashkortostan and Population Health Status

2020 ◽  
pp. 26-32
Author(s):  
Z.B. Baktybaeva ◽  
R.A. Suleymanov ◽  
T.K. Valeev ◽  
N.R. Rahmatullin ◽  
E.G. Stepanov ◽  
...  
Keyword(s):  
Air Pollution ◽  
Carbon Monoxide ◽  
Health Status ◽  
Nitrogen Dioxide ◽  
Population Health ◽  
Respiratory Diseases ◽  
Ambient Air ◽  
Oil Refining ◽  
Disease Rates ◽  
Total Suspended Particles

Introduction. High density of oil-producing and refining facilities in certain areas of Bashkortostan significantly affects the environment including ambient air quality in residential areas. Materials and methods. We analyzed concentrations of airborne toxicants (sulfur and nitrogen oxides, nitrogen and carbon oxides, hydrogen sulfide, ammonia, xylenes, toluene, phenol and total suspended particles) and population health status in the cities of Ufa, Sterlitamak, Salavat, Blagoveshchensk, and the Tuymazinsky District in 2007–2016. Pearson's correlation coefficients (r) were used to establish possible relationships between medico-demographic indicators and air pollution. Results. Republican fuel and energy enterprises contributed the most to local air pollution levels. Gross emissions from such enterprises as Bashneft-Ufaneftekhim and Bashneft-Navoil reached 43.69–49.77 thousand tons of pollutants per year. The levels of some air pollutants exceeded their maximum permissible concentrations. Elevated concentrations of ammonia, total suspended particles, nitrogen dioxide, and carbon monoxide were registered most frequently. High rates of congenital abnormalities, respiratory diseases in infants (aged 0-1), general mortality and morbidity of the population were observed in some oil-producing and refining areas. The correlation analysis proved the relationship between the concentration of carbon monoxide and general disease rates in adults based on hospital admissions (r = 0.898), general incidence rates in children (r = 0.957), and blood disease rates in infants (r = 0.821). Respiratory diseases in children correlated with nitrogen dioxide emission levels (r = 0.899). Conclusions. Further development of oil-producing, petrochemical and oil-refining industries should be carried out taking into account socio-economic living conditions of the population.

scholarly journals Development of dose-response functions for historic paper degradation using exposure to natural conditions and multivariate regression

2019 ◽  
Vol 168 ◽  
pp. 108944 ◽  
Author(s):  
Gianluca Pastorelli ◽  
Shuo Cao ◽  
Irena Kralj Cigić ◽  
Costanza Cucci ◽  
Abdelrazek Elnaggar ◽  
...  
Keyword(s):  
Dose Response ◽  
Multivariate Regression ◽  
Response Functions ◽  
Natural Conditions ◽  
Paper Degradation ◽  
Historic Paper

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

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Ram Kumar Singh ◽  
Martin Drews ◽  
Manuel De la Sen ◽  
Prashant Kumar Srivastava ◽  
Bambang H. Trisasongko ◽  
...  
Keyword(s):  
Air Pollution ◽  
Air Quality ◽  
Global Economy ◽  
Respiratory Diseases ◽  
Environmental Pollutants ◽  
Atmospheric Pollutants ◽  
Geospatial Technology ◽  
The World ◽  
Community Transmission ◽  
Global Threat

AbstractThe 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.

Investigating the Spread of Coronavirus Disease via Edge-AI and Air Pollution Correlation

2021 ◽  
Vol 21 (4) ◽  
pp. 1-10
Author(s):  
V. Gomathy ◽  
K. Janarthanan ◽  
Fadi Al-Turjman ◽  
R. Sitharthan ◽  
M. Rajesh ◽  
...  
Keyword(s):  
Machine Learning ◽  
Air Pollution ◽  
Mortality Rate ◽  
Respiratory Diseases ◽  
Past Research ◽  
Viral Disease ◽  
Machine Learning Method ◽  
Learning Method ◽  
Death Rates ◽  
Using Data

Coronavirus Disease 19 (COVID-19) is a highly infectious viral disease affecting millions of people worldwide in 2020. Several studies have shown that COVID-19 results in a severe acute respiratory syndrome and may lead to death. In past research, a greater number of respiratory diseases has been caused by exposure to air pollution for long periods of time. This article investigates the spread of COVID-19 as a result of air pollution by applying linear regression in machine learning method based edge computing. The analysis in this investigation have been based on the death rates caused by COVID-19 as well as the region of death rates based on hazardous air pollution using data retrieved from the Copernicus Sentinel-5P satellite. The results obtained in the investigation prove that the mortality rate due to the spread of COVID-19 is 77% higher in areas with polluted air. This investigation also proves that COVID-19 severely affected 68% of the individuals who had been exposed to polluted air.

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