Analyzing the effects of air pollution on life expectancy in Tehran, Iran
Abstract The present paper aims to analyze twenty-one-year long-term data of life expectancy and levels of $ PM_{10} $, $ PM_{2.5} $, CO, $ O_{3} $, $ SO_{2,} $ and $ NO_{2} $ pollutants in Tehran, Iran, to investigate the correlation between air pollution and life expectancy. Data are analyzed usin...
Ausführliche Beschreibung
Gespeichert in:
| Autor*in: |
Ghaedrahmati, S. [verfasserIn] |
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| Format: |
E-Artikel |
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| Sprache: |
Englisch |
| Erschienen: |
2022 |
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| Schlagwörter: |
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| Anmerkung: |
© Islamic Azad University (IAU) 2021 |
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| Übergeordnetes Werk: |
Enthalten in: International journal of environmental science and technology - Tehran : Islamic Azad University, 2004, 19(2022), 8 vom: 29. Jan., Seite 7009-7018 |
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| Übergeordnetes Werk: |
volume:19 ; year:2022 ; number:8 ; day:29 ; month:01 ; pages:7009-7018 |
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| DOI / URN: |
10.1007/s13762-021-03877-z |
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| Katalog-ID: |
SPR047585862 |
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| 520 | |a Abstract The present paper aims to analyze twenty-one-year long-term data of life expectancy and levels of $ PM_{10} $, $ PM_{2.5} $, CO, $ O_{3} $, $ SO_{2,} $ and $ NO_{2} $ pollutants in Tehran, Iran, to investigate the correlation between air pollution and life expectancy. Data are analyzed using the Pearson correlation coefficient and regression model. The regression analysis of the data used is performed to understand how the level of life expectancy alters by changing any of the above-mentioned pollutants and keeping constant the other independent variables. Enter Method is used for regression analysis. The level of life expectancy in Tehran was 70.18 years in 2000 and increased to 77.53 in 2020. Calculation of 21-year long-term data on air pollution index indicates no uniform and linear trend, but the trend of life expectancy is increasing. According to the adjusted R-squared calculation, it is concluded that 89.1% of the changes in the dependent variable (life expectancy) are explained by independent variables (air pollutants), which is a large value and is considered a fit model. The result of regression analysis of variance for statistical hypotheses also reveals that the Sig value is less than 0.05, thereby confirming the hypothesis of linear correlation between the two variables. However, the correlation coefficient is not a simple linear function, and the increase in life expectancy should be sought in the growth of other control variables such as improved health, treatment, nutrition, and quality of life. | ||
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10.1007/s13762-021-03877-z doi (DE-627)SPR047585862 (SPR)s13762-021-03877-z-e DE-627 ger DE-627 rakwb eng Ghaedrahmati, S. verfasserin (orcid)0000-0001-5774-7154 aut Analyzing the effects of air pollution on life expectancy in Tehran, Iran 2022 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © Islamic Azad University (IAU) 2021 Abstract The present paper aims to analyze twenty-one-year long-term data of life expectancy and levels of $ PM_{10} $, $ PM_{2.5} $, CO, $ O_{3} $, $ SO_{2,} $ and $ NO_{2} $ pollutants in Tehran, Iran, to investigate the correlation between air pollution and life expectancy. Data are analyzed using the Pearson correlation coefficient and regression model. The regression analysis of the data used is performed to understand how the level of life expectancy alters by changing any of the above-mentioned pollutants and keeping constant the other independent variables. Enter Method is used for regression analysis. The level of life expectancy in Tehran was 70.18 years in 2000 and increased to 77.53 in 2020. Calculation of 21-year long-term data on air pollution index indicates no uniform and linear trend, but the trend of life expectancy is increasing. According to the adjusted R-squared calculation, it is concluded that 89.1% of the changes in the dependent variable (life expectancy) are explained by independent variables (air pollutants), which is a large value and is considered a fit model. The result of regression analysis of variance for statistical hypotheses also reveals that the Sig value is less than 0.05, thereby confirming the hypothesis of linear correlation between the two variables. However, the correlation coefficient is not a simple linear function, and the increase in life expectancy should be sought in the growth of other control variables such as improved health, treatment, nutrition, and quality of life. Air pollution risk (dpeaa)DE-He213 Air pollutants (dpeaa)DE-He213 Life expectancy (dpeaa)DE-He213 Air quality index (dpeaa)DE-He213 Hajilou, M. (orcid)0000-0002-5697-6665 aut Enthalten in International journal of environmental science and technology Tehran : Islamic Azad University, 2004 19(2022), 8 vom: 29. Jan., Seite 7009-7018 (DE-627)510463398 (DE-600)2230399-6 1735-2630 nnns volume:19 year:2022 number:8 day:29 month:01 pages:7009-7018 https://dx.doi.org/10.1007/s13762-021-03877-z lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 19 2022 8 29 01 7009-7018 |
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10.1007/s13762-021-03877-z doi (DE-627)SPR047585862 (SPR)s13762-021-03877-z-e DE-627 ger DE-627 rakwb eng Ghaedrahmati, S. verfasserin (orcid)0000-0001-5774-7154 aut Analyzing the effects of air pollution on life expectancy in Tehran, Iran 2022 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © Islamic Azad University (IAU) 2021 Abstract The present paper aims to analyze twenty-one-year long-term data of life expectancy and levels of $ PM_{10} $, $ PM_{2.5} $, CO, $ O_{3} $, $ SO_{2,} $ and $ NO_{2} $ pollutants in Tehran, Iran, to investigate the correlation between air pollution and life expectancy. Data are analyzed using the Pearson correlation coefficient and regression model. The regression analysis of the data used is performed to understand how the level of life expectancy alters by changing any of the above-mentioned pollutants and keeping constant the other independent variables. Enter Method is used for regression analysis. The level of life expectancy in Tehran was 70.18 years in 2000 and increased to 77.53 in 2020. Calculation of 21-year long-term data on air pollution index indicates no uniform and linear trend, but the trend of life expectancy is increasing. According to the adjusted R-squared calculation, it is concluded that 89.1% of the changes in the dependent variable (life expectancy) are explained by independent variables (air pollutants), which is a large value and is considered a fit model. The result of regression analysis of variance for statistical hypotheses also reveals that the Sig value is less than 0.05, thereby confirming the hypothesis of linear correlation between the two variables. However, the correlation coefficient is not a simple linear function, and the increase in life expectancy should be sought in the growth of other control variables such as improved health, treatment, nutrition, and quality of life. Air pollution risk (dpeaa)DE-He213 Air pollutants (dpeaa)DE-He213 Life expectancy (dpeaa)DE-He213 Air quality index (dpeaa)DE-He213 Hajilou, M. (orcid)0000-0002-5697-6665 aut Enthalten in International journal of environmental science and technology Tehran : Islamic Azad University, 2004 19(2022), 8 vom: 29. Jan., Seite 7009-7018 (DE-627)510463398 (DE-600)2230399-6 1735-2630 nnns volume:19 year:2022 number:8 day:29 month:01 pages:7009-7018 https://dx.doi.org/10.1007/s13762-021-03877-z lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 19 2022 8 29 01 7009-7018 |
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10.1007/s13762-021-03877-z doi (DE-627)SPR047585862 (SPR)s13762-021-03877-z-e DE-627 ger DE-627 rakwb eng Ghaedrahmati, S. verfasserin (orcid)0000-0001-5774-7154 aut Analyzing the effects of air pollution on life expectancy in Tehran, Iran 2022 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © Islamic Azad University (IAU) 2021 Abstract The present paper aims to analyze twenty-one-year long-term data of life expectancy and levels of $ PM_{10} $, $ PM_{2.5} $, CO, $ O_{3} $, $ SO_{2,} $ and $ NO_{2} $ pollutants in Tehran, Iran, to investigate the correlation between air pollution and life expectancy. Data are analyzed using the Pearson correlation coefficient and regression model. The regression analysis of the data used is performed to understand how the level of life expectancy alters by changing any of the above-mentioned pollutants and keeping constant the other independent variables. Enter Method is used for regression analysis. The level of life expectancy in Tehran was 70.18 years in 2000 and increased to 77.53 in 2020. Calculation of 21-year long-term data on air pollution index indicates no uniform and linear trend, but the trend of life expectancy is increasing. According to the adjusted R-squared calculation, it is concluded that 89.1% of the changes in the dependent variable (life expectancy) are explained by independent variables (air pollutants), which is a large value and is considered a fit model. The result of regression analysis of variance for statistical hypotheses also reveals that the Sig value is less than 0.05, thereby confirming the hypothesis of linear correlation between the two variables. However, the correlation coefficient is not a simple linear function, and the increase in life expectancy should be sought in the growth of other control variables such as improved health, treatment, nutrition, and quality of life. Air pollution risk (dpeaa)DE-He213 Air pollutants (dpeaa)DE-He213 Life expectancy (dpeaa)DE-He213 Air quality index (dpeaa)DE-He213 Hajilou, M. (orcid)0000-0002-5697-6665 aut Enthalten in International journal of environmental science and technology Tehran : Islamic Azad University, 2004 19(2022), 8 vom: 29. Jan., Seite 7009-7018 (DE-627)510463398 (DE-600)2230399-6 1735-2630 nnns volume:19 year:2022 number:8 day:29 month:01 pages:7009-7018 https://dx.doi.org/10.1007/s13762-021-03877-z lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 19 2022 8 29 01 7009-7018 |
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10.1007/s13762-021-03877-z doi (DE-627)SPR047585862 (SPR)s13762-021-03877-z-e DE-627 ger DE-627 rakwb eng Ghaedrahmati, S. verfasserin (orcid)0000-0001-5774-7154 aut Analyzing the effects of air pollution on life expectancy in Tehran, Iran 2022 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © Islamic Azad University (IAU) 2021 Abstract The present paper aims to analyze twenty-one-year long-term data of life expectancy and levels of $ PM_{10} $, $ PM_{2.5} $, CO, $ O_{3} $, $ SO_{2,} $ and $ NO_{2} $ pollutants in Tehran, Iran, to investigate the correlation between air pollution and life expectancy. Data are analyzed using the Pearson correlation coefficient and regression model. The regression analysis of the data used is performed to understand how the level of life expectancy alters by changing any of the above-mentioned pollutants and keeping constant the other independent variables. Enter Method is used for regression analysis. The level of life expectancy in Tehran was 70.18 years in 2000 and increased to 77.53 in 2020. Calculation of 21-year long-term data on air pollution index indicates no uniform and linear trend, but the trend of life expectancy is increasing. According to the adjusted R-squared calculation, it is concluded that 89.1% of the changes in the dependent variable (life expectancy) are explained by independent variables (air pollutants), which is a large value and is considered a fit model. The result of regression analysis of variance for statistical hypotheses also reveals that the Sig value is less than 0.05, thereby confirming the hypothesis of linear correlation between the two variables. However, the correlation coefficient is not a simple linear function, and the increase in life expectancy should be sought in the growth of other control variables such as improved health, treatment, nutrition, and quality of life. Air pollution risk (dpeaa)DE-He213 Air pollutants (dpeaa)DE-He213 Life expectancy (dpeaa)DE-He213 Air quality index (dpeaa)DE-He213 Hajilou, M. (orcid)0000-0002-5697-6665 aut Enthalten in International journal of environmental science and technology Tehran : Islamic Azad University, 2004 19(2022), 8 vom: 29. Jan., Seite 7009-7018 (DE-627)510463398 (DE-600)2230399-6 1735-2630 nnns volume:19 year:2022 number:8 day:29 month:01 pages:7009-7018 https://dx.doi.org/10.1007/s13762-021-03877-z lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 19 2022 8 29 01 7009-7018 |
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10.1007/s13762-021-03877-z doi (DE-627)SPR047585862 (SPR)s13762-021-03877-z-e DE-627 ger DE-627 rakwb eng Ghaedrahmati, S. verfasserin (orcid)0000-0001-5774-7154 aut Analyzing the effects of air pollution on life expectancy in Tehran, Iran 2022 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © Islamic Azad University (IAU) 2021 Abstract The present paper aims to analyze twenty-one-year long-term data of life expectancy and levels of $ PM_{10} $, $ PM_{2.5} $, CO, $ O_{3} $, $ SO_{2,} $ and $ NO_{2} $ pollutants in Tehran, Iran, to investigate the correlation between air pollution and life expectancy. Data are analyzed using the Pearson correlation coefficient and regression model. The regression analysis of the data used is performed to understand how the level of life expectancy alters by changing any of the above-mentioned pollutants and keeping constant the other independent variables. Enter Method is used for regression analysis. The level of life expectancy in Tehran was 70.18 years in 2000 and increased to 77.53 in 2020. Calculation of 21-year long-term data on air pollution index indicates no uniform and linear trend, but the trend of life expectancy is increasing. According to the adjusted R-squared calculation, it is concluded that 89.1% of the changes in the dependent variable (life expectancy) are explained by independent variables (air pollutants), which is a large value and is considered a fit model. The result of regression analysis of variance for statistical hypotheses also reveals that the Sig value is less than 0.05, thereby confirming the hypothesis of linear correlation between the two variables. However, the correlation coefficient is not a simple linear function, and the increase in life expectancy should be sought in the growth of other control variables such as improved health, treatment, nutrition, and quality of life. Air pollution risk (dpeaa)DE-He213 Air pollutants (dpeaa)DE-He213 Life expectancy (dpeaa)DE-He213 Air quality index (dpeaa)DE-He213 Hajilou, M. (orcid)0000-0002-5697-6665 aut Enthalten in International journal of environmental science and technology Tehran : Islamic Azad University, 2004 19(2022), 8 vom: 29. Jan., Seite 7009-7018 (DE-627)510463398 (DE-600)2230399-6 1735-2630 nnns volume:19 year:2022 number:8 day:29 month:01 pages:7009-7018 https://dx.doi.org/10.1007/s13762-021-03877-z lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 19 2022 8 29 01 7009-7018 |
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Data are analyzed using the Pearson correlation coefficient and regression model. The regression analysis of the data used is performed to understand how the level of life expectancy alters by changing any of the above-mentioned pollutants and keeping constant the other independent variables. Enter Method is used for regression analysis. The level of life expectancy in Tehran was 70.18 years in 2000 and increased to 77.53 in 2020. Calculation of 21-year long-term data on air pollution index indicates no uniform and linear trend, but the trend of life expectancy is increasing. According to the adjusted R-squared calculation, it is concluded that 89.1% of the changes in the dependent variable (life expectancy) are explained by independent variables (air pollutants), which is a large value and is considered a fit model. The result of regression analysis of variance for statistical hypotheses also reveals that the Sig value is less than 0.05, thereby confirming the hypothesis of linear correlation between the two variables. 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Ghaedrahmati, S. |
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Ghaedrahmati, S. misc Air pollution risk misc Air pollutants misc Life expectancy misc Air quality index Analyzing the effects of air pollution on life expectancy in Tehran, Iran |
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Analyzing the effects of air pollution on life expectancy in Tehran, Iran Air pollution risk (dpeaa)DE-He213 Air pollutants (dpeaa)DE-He213 Life expectancy (dpeaa)DE-He213 Air quality index (dpeaa)DE-He213 |
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analyzing the effects of air pollution on life expectancy in tehran, iran |
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Analyzing the effects of air pollution on life expectancy in Tehran, Iran |
| abstract |
Abstract The present paper aims to analyze twenty-one-year long-term data of life expectancy and levels of $ PM_{10} $, $ PM_{2.5} $, CO, $ O_{3} $, $ SO_{2,} $ and $ NO_{2} $ pollutants in Tehran, Iran, to investigate the correlation between air pollution and life expectancy. Data are analyzed using the Pearson correlation coefficient and regression model. The regression analysis of the data used is performed to understand how the level of life expectancy alters by changing any of the above-mentioned pollutants and keeping constant the other independent variables. Enter Method is used for regression analysis. The level of life expectancy in Tehran was 70.18 years in 2000 and increased to 77.53 in 2020. Calculation of 21-year long-term data on air pollution index indicates no uniform and linear trend, but the trend of life expectancy is increasing. According to the adjusted R-squared calculation, it is concluded that 89.1% of the changes in the dependent variable (life expectancy) are explained by independent variables (air pollutants), which is a large value and is considered a fit model. The result of regression analysis of variance for statistical hypotheses also reveals that the Sig value is less than 0.05, thereby confirming the hypothesis of linear correlation between the two variables. However, the correlation coefficient is not a simple linear function, and the increase in life expectancy should be sought in the growth of other control variables such as improved health, treatment, nutrition, and quality of life. © Islamic Azad University (IAU) 2021 |
| abstractGer |
Abstract The present paper aims to analyze twenty-one-year long-term data of life expectancy and levels of $ PM_{10} $, $ PM_{2.5} $, CO, $ O_{3} $, $ SO_{2,} $ and $ NO_{2} $ pollutants in Tehran, Iran, to investigate the correlation between air pollution and life expectancy. Data are analyzed using the Pearson correlation coefficient and regression model. The regression analysis of the data used is performed to understand how the level of life expectancy alters by changing any of the above-mentioned pollutants and keeping constant the other independent variables. Enter Method is used for regression analysis. The level of life expectancy in Tehran was 70.18 years in 2000 and increased to 77.53 in 2020. Calculation of 21-year long-term data on air pollution index indicates no uniform and linear trend, but the trend of life expectancy is increasing. According to the adjusted R-squared calculation, it is concluded that 89.1% of the changes in the dependent variable (life expectancy) are explained by independent variables (air pollutants), which is a large value and is considered a fit model. The result of regression analysis of variance for statistical hypotheses also reveals that the Sig value is less than 0.05, thereby confirming the hypothesis of linear correlation between the two variables. However, the correlation coefficient is not a simple linear function, and the increase in life expectancy should be sought in the growth of other control variables such as improved health, treatment, nutrition, and quality of life. © Islamic Azad University (IAU) 2021 |
| abstract_unstemmed |
Abstract The present paper aims to analyze twenty-one-year long-term data of life expectancy and levels of $ PM_{10} $, $ PM_{2.5} $, CO, $ O_{3} $, $ SO_{2,} $ and $ NO_{2} $ pollutants in Tehran, Iran, to investigate the correlation between air pollution and life expectancy. Data are analyzed using the Pearson correlation coefficient and regression model. The regression analysis of the data used is performed to understand how the level of life expectancy alters by changing any of the above-mentioned pollutants and keeping constant the other independent variables. Enter Method is used for regression analysis. The level of life expectancy in Tehran was 70.18 years in 2000 and increased to 77.53 in 2020. Calculation of 21-year long-term data on air pollution index indicates no uniform and linear trend, but the trend of life expectancy is increasing. According to the adjusted R-squared calculation, it is concluded that 89.1% of the changes in the dependent variable (life expectancy) are explained by independent variables (air pollutants), which is a large value and is considered a fit model. The result of regression analysis of variance for statistical hypotheses also reveals that the Sig value is less than 0.05, thereby confirming the hypothesis of linear correlation between the two variables. However, the correlation coefficient is not a simple linear function, and the increase in life expectancy should be sought in the growth of other control variables such as improved health, treatment, nutrition, and quality of life. © Islamic Azad University (IAU) 2021 |
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Analyzing the effects of air pollution on life expectancy in Tehran, Iran |
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https://dx.doi.org/10.1007/s13762-021-03877-z |
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Hajilou, M. |
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| doi_str |
10.1007/s13762-021-03877-z |
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