scholarly journals Spatio-Temporal Analysis of the Impact of Airborne Pollen, Ambient Air Pollution, and Land Cover on the Sales of Medications Used to Treat Asthma and Allergies, in 8 Cities, in Metropolitan France

2020 ◽  
Vol 145 (2) ◽  
pp. AB113
Author(s):  
Karen Hernandez ◽  
Julie Prud'homme ◽  
Stéphane Sclison ◽  
Isabella Annesi-Maesano
Keyword(s):  
Air Pollution ◽  
Land Cover ◽  
Airborne Pollen ◽  
Ambient Air ◽  
Temporal Analysis ◽  
Ambient Air Pollution ◽  
Spatio Temporal ◽  
The Impact

Ambient Air Pollution and Cardiac Malformations; A Register-Based Spatio-temporal Analysis

Epidemiology ◽  
2009 ◽  
Vol 20 ◽  
pp. S232
Author(s):  
Payam Dadvand ◽  
Judith Rankin ◽  
Stephen Rushton ◽  
Tanja Pless-Mulloli
Keyword(s):  
Air Pollution ◽  
Ambient Air ◽  
Temporal Analysis ◽  
Ambient Air Pollution ◽  
Cardiac Malformations ◽  
Spatio Temporal

scholarly journals Air pollution and out-of-hospital cardiac arrest risk

2020 ◽  
Vol 41 (Supplement_2) ◽  
Author(s):  
L Moderato ◽  
D Lazzeroni ◽  
A Biagi ◽  
T Spezzano ◽  
B Matrone ◽  
...  
Keyword(s):  
Air Pollution ◽  
Cardiac Arrest ◽  
Ambient Air ◽  
Ambient Air Pollution ◽  
External Temperature ◽  
Pm 2.5 ◽  
Pm10 And Pm2.5 ◽  
Short Term Exposure ◽  
The Impact ◽  
Hospital Cardiac Arrest

Abstract Introduction Out-of-hospital cardiac arrest (OHCA) is a leading cause of death worldwide; it accounts for up to 50% of all cardiovascular deaths.It is well established that ambient air pollution triggers fatal and non-fatal cardiovascular events. However, the impact of air pollution on OHCA is still controversial. The objective of this study was to investigate the impact of short-term exposure to outdoor air pollutants on the incidence of OHCA in the urban area of Piacenza, Italy, one of the most polluted area in Europe. Methods From 01/01/2010 to 31/12/2017 day-by-day PM10 and PM2.5 levels, as well as climatic data, were extracted from Environmental Protection Agency (ARPA) local monitoring stations. OHCA were extracted from the prospective registry of Community-based automated external defibrillator Cardiac arrest “Progetto Vita”. OHCA data were included: audio recordings, event information and ECG tracings. Logistic regression analysis was used to estimate the association between the risk of OHC, expressed as odds ratios (OR), associated with the PM10 and PM2.5 levels. Results Mean PM10 levels were 33±29 μg/m3 and the safety threshold (50 μg/m3) recommended by both WHO and Italian legislation has been exceeded for 535 days (17.5%). Mean PM 5 levels were 33±29 μg/m3. During the follow-up period, 880 OHCA were recorded on 750 days; the remaining 2174 days without OHCA were used as control days. Mean age of OHCA patients was 76±15 years; male gender was prevalent (55% male vs 45% female; <0.001). Concentration of PM10 and PM 2.5 were significantly higher on days with the occurrence of OHCA (PM10 levels: 37.7±22 μg/m3 vs 32.7±19 μg/m3; p<0.001; PM 2.5 levels: 26±16 vs 22±15 p<0.001). Risk of OHCA was significantly increased with the progressive increase of PM10 (OR: 1.009, 95% CI 1.004–1.015; p<0.001) and PM2.5 levels (OR 1.012, 95% CI 1.007–1.017; p<0.001). Interestingly, the above mentioned results remain independent even when correct for external temperature or season (PM 2.5 levels: p=0.01 – PM 10 levels: p=0.002), Moreover, dividing PM10 values in quintiles, a 1.9 fold higher risk of cardiac arrest has been showed in the highest quintile (Highest quintile cut-off: <48μg/m3) Conclusions In large cohort of patients from a high pollution area, both PM10 and PM2.5 levels are associated with the risk of Out-of-hospital cardiac arrest. PM10 and PM2.5 levels and risk of OHCA Funding Acknowledgement Type of funding source: None

scholarly journals Quantifying the Health and Wealth Benefits of Reducing Point Source Pollution: The Case of the Sugar Industry in Pakistan

2021 ◽  
Vol 13 (23) ◽  
pp. 13252
Author(s):  
Sanaullah Panezai ◽  
Ubaid Ali ◽  
Alam Zeb ◽  
Muhammad Rafiq ◽  
Ayat Ullah ◽  
...  
Keyword(s):  
Air Pollution ◽  
Sugar Industry ◽  
Ambient Air ◽  
Respiratory Illness ◽  
Production Method ◽  
Ambient Air Pollution ◽  
World Health ◽  
Primary Data ◽  
Reduced Form ◽  
The Impact

Air pollution is among the major causes of death and disease all around the globe. The prime impact of ambient air pollution is on the lungs through the respiratory system. This study aims to estimate the health cost due to air pollution from a Sugar Mill in the Mardan district of Khyber Pakhtunkhwa, Pakistan. To determine the impact of pollution on respiratory illness, primary data were collected from 1141 individuals from 200 households living within a 3 km radius of the mill. The Household Production Method was used to drive the reduced-form Dose–Response Function and the Mitigation Cost Function for assessing the impact of pollution on health and then estimating the monetary cost associated with mitigating such illnesses. The results indicate that about 60% of the respondents living in the surrounding area of the mill suffered from different respiratory illnesses. The study estimates that by reducing the suspended particulate matter (SPM) level by 50%, the expected annual welfare gains to an individual living within a 3 km radius of the mill are US $20.21. The whole community residing within a 3 km radius of the mill will enjoy an estimated welfare gain of PKR. 70.67 million (US $0.511 million). If the pollution standard limits prescribed by the World Health Organization are followed, the expected monetary benefits to all the individuals living within a 3 km radius of the mill are PKR. 114.48 million (US $0.27 million) annually.

Physical factors of influence in the interactions between rainfall, evapotranspiration and soil moisture driving the spatio-temporal evolution of drought patterns in the Ebro Basin (NE Spain).

2021 ◽  
Author(s):  
Jaime Gaona ◽  
Pere Quintana-Seguí ◽  
Maria José Escorihuela
Keyword(s):  
Soil Moisture ◽  
Land Cover ◽  
Iberian Peninsula ◽  
Land Surface ◽  
Temporal Analysis ◽  
Drought Indices ◽  
Surface Model ◽  
Physical Factors ◽  
Spatio Temporal ◽  
The Impact

<p>Droughts in the Iberian Peninsula are a natural hazard of great relevance due to their recurrence, severity and impact on multiple environmental and socioeconomic aspects. The Ebro Basin, located in the NE of the Iberian Peninsula, is particularly vulnerable to drought with consequences on agriculture, urban water supply and hydropower. This study, performed within the Project HUMID (CGL2017-85687-R), aims at evaluating the influence of the climatic, land cover and soil characteristics on the interactions between rainfall, evapotranspiration and soil moisture anomalies which define the spatio-temporal drought patterns in the basin.</p><p>The onset, propagation and mitigation of droughts in the Iberian Peninsula is driven by anomalies of rainfall, evapotranspiration and soil moisture, which are related by feedback processes. To test the relative importance of such anomalies, we evaluate the contribution of climatic, land-cover and geologic heterogeneity on the definition of the spatio-temporal patterns of drought. We use the Köppen-Geiger climatic classification to assess how the contrasting climatic types within the basin determine differences on drought behavior. Land-cover types that govern the partition between evaporation and transpiration are also of great interest to discern the influence of vegetation and crop types on the anomalies of evapotranspiration across the distinct regions of the basin (e.g. forested mountains vs. crop-dominated areas). The third physical characteristic whose effect on drought we investigate is the impact of soil properties on soil moisture anomalies.</p><p>The maps and time series used for the spatio-temporal analysis are based on drought indices calculated with high-resolution datasets from remote sensing (MOD16A2ET and SMOS1km) and the land-surface model SURFEX-ISBA. The Standardized Precipitation Index (SPI), the EvapoTranspiration Deficit Index (ETDI) and the Soil Moisture Deficit Index (SMDI) are the three indices chosen to characterize the anomalies of the corresponding rainfall (atmospheric), evapotranspiration (atmosphere-land interface) and soil moisture (land) anomalies (components of the water balance). The comparison of the correlations of the indices (with different time lags) between contrasting regions offers insights about the impact of climate, land-cover and soil properties in the dominance, the timing of the response and memory aspects of the interactions. The high spatial and temporal resolution of remote sensing and land-surface model data allows adopting time and spatial scales suitable to investigate the influence of these physical factors with detail beyond comparison with ground-based datasets.</p><p>The spatial and temporal analysis prove useful to investigate the physical factors of influence on the anomalies between rainfall, evapotranspiration and soil moisture. This approach facilitates the physical interpretation of the anomalies of drought indices aiming to improve the characterization of drought in heterogeneous semi-arid areas like the Ebro River Basin.</p>

Spatio-Temporal Data Mining for Air Pollution Problems

2011 ◽  
pp. 1815-1822 ◽  
Author(s):  
Seoung Bum Kim ◽  
Chivalai Temiyasathit ◽  
Sun-Kyoung Park ◽  
Victoria C.P. Chen
Keyword(s):  
Data Mining ◽  
Air Pollution ◽  
Real Data ◽  
Ambient Air ◽  
Ambient Air Pollution ◽  
Temporal Data Mining ◽  
Area Of Interest ◽  
Mining Methods ◽  
Spatio Temporal ◽  
Temporal And Spatial Characteristics

Vast amounts of data are being generated to extract implicit patterns of ambient air pollution. Because air pollution data are generally collected in a wide area of interest over a relatively long period, such analyses should take into account both temporal and spatial characteristics. Furthermore, combinations of observations from multiple monitoring stations, each with a large number of serially correlated values, lead to a situation that poses a great challenge to analytical and computational capabilities. Data mining methods are efficient for analyzing such large and complicated data. Despite the great potential of applying data mining methods to such complicated air pollution data, the appropriate methods remain premature and insufficient. The major aim of this chapter is to present some data mining methods, along with the real data, as a tool for analyzing the complex behavior of ambient air pollutants.

Ambient air pollution and health

2016 ◽  
Author(s):  
John Reid ◽  
Giovanni Leonardi ◽  
Alex G. Stewart
Keyword(s):  
Air Pollution ◽  
Geographical Information Systems ◽  
Ambient Air ◽  
Geographical Information ◽  
Ambient Air Pollution ◽  
Background Information ◽  
Traffic Density ◽  
Pollution Indices ◽  
Guideline Values ◽  
The Impact

This chapter describes the impact of air pollution, including particulate matter and nitrogen oxides, on human health, through a case scenario where an increase in respiratory disease has been associated with changes in traffic density and increases in pollution indices. Background information on pollutants and air quality measurements is given based on WHO criteria. The importance of multidisciplinary input to such investigations is emphasized, involving specialists in toxicology and environmental science, as well as health protection staff. The role of geographical information systems in mapping air pollution levels to identify localities where guideline values are exceeded is emphasized, together with health impact assessments to monitor public health outcomes. The complex local, social, and political aspects that may arise are considered, and so endure engagement and communication with different interest groups. The final part clearly outlines currently unanswered questions and how they should be studied and managed in the future.

The impact of the congestion charging scheme on ambient air pollution concentrations in London

2009 ◽  
Vol 43 (34) ◽  
pp. 5493-5500 ◽  
Author(s):  
R.W. Atkinson ◽  
B. Barratt ◽  
B. Armstrong ◽  
H.R. Anderson ◽  
S.D. Beevers ◽  
...  
Keyword(s):  
Air Pollution ◽  
Ambient Air ◽  
Ambient Air Pollution ◽  
The Impact ◽  
Congestion Charging ◽  
Pollution Concentrations
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