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Ambient Air Particulate Matter (Pm10) Satellite Monitoring and Respiratory Health Effects Assessment Publisher



Mohebbichamkhorami M1 ; Arbabi M1, 2 ; Mirzaei M3 ; Ahmadi A4 ; Hassanvand MS5 ; Rouhi H6
Authors
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Authors Affiliations
  1. 1. Department of Environmental Health Engineering, School of Health, Shahrekord University of Medical Sciences, Shahrekord, Iran
  2. 2. Social Determinants of Health Research Center, Shahrekord University of Medical Sciences, Shahrekord, Iran
  3. 3. Department of Environment, Faculty of Natural Resources and Marine Sciences, Tarbiat Modares University, Tehran, Iran
  4. 4. Modeling in Health Research Center, Shahrekord University of Medical Sciences, Shahrekord, Iran
  5. 5. Centre for Air Pollution Research (CAPR), Institute for Environmental Research (IER), Tehran University of Medical Sciences, Tehran, Iran
  6. 6. Department of pulmonary, School of Medicine, Shahrekord University of Medical Sciences, Shahrekord, Iran

Source: Journal of Environmental Health Science and Engineering Published:2020


Abstract

Purpose: Air particulate matter with an aerodynamic diameter of 10 µm or less (PM10) is one of the main causes of acute exacerbation of chronic obstructive pulmonary disease (AECOPD). This study explored the relationship between PM10 by remote sensing and AECOPD in Chaharmahal-o-Bakhtiari province from 2014 to2018. Method: PM10 concentrations were predicted and validated based on aerosol optical depth (AOD) from 161 images processed by MODIS sensor and ground air quality monitoring station data. Demographic information and spirometric indices of 2038 patients with AECOPD were collected and analyzed from the hospital during the studied periods. SPSS software was used to analyze the relationships between these two categories of information. Results: There was a significant negative relationship between PM10 and FVC, FVC%, FEV1, FEV1%, FEF25-75, FEV1/FVC, PEF, and FEF25FVC indices (p < 0.05). The results showed that over 2014–2018, the annual mean of PM10 concentrations varied from 35 to 52 µg/m3. The result of the regression model showed that the patient’s age, body mass index (BMI), and PM10 concentrations were the most affecting variables on the two important spirometric indices i.e., FVC% and FEV1%. The PM10 concentrations and number of AECOPD patients had a similar pattern during the studied period. The women group, age group above 74 years, normal BMI, and non-smoking patients showed the most sensitivity to the PM10 concentrations. Conclusions: Our findings provide supplementary scientific information on PM10 concentration related to the incidence of AECOPD and as a variable affecting the most important spirometry indicators by providing local decision-makers information needed to set a priority of air pollution control measures as well as health services. © 2020, Springer Nature Switzerland AG.