Assessment of NO2 levels as an air pollutant and its statistical modeling using meteorological parameters in Tehran, Iran
In the present study, air quality analyses for NO<sub>2</sub> were conducted in Tehran, capital of Iran. The measurements were taken in four different locations to provide average data in the city. The average concentrations were calculated diurnally, monthly and seasonally. Results exhi...
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| Format: | Article |
| Language: | English |
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University of Guilan
2019-09-01
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| Series: | Caspian Journal of Environmental Sciences |
| Subjects: | |
| Online Access: | https://cjes.guilan.ac.ir/article_3665_089f0458e6abeeec18872222b1896ad7.pdf |
| _version_ | 1818527858506596352 |
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| author | M. Masoudi F. Behzadi M. Sakhaei |
| author_facet | M. Masoudi F. Behzadi M. Sakhaei |
| author_sort | M. Masoudi |
| collection | DOAJ |
| description | In the present study, air quality analyses for NO<sub>2</sub> were conducted in Tehran, capital of Iran. The measurements were taken in four different locations to provide average data in the city. The average concentrations were calculated diurnally, monthly and seasonally. Results exhibited that the highest NO<sub>2</sub> concentration occurs generally in the early morning and early night, while the least in the afternoon and after mid-night. Monthly NO2 concentrations displayed the highest value in April, while the least in June and July. The seasonal concentrations exhibited the least amounts in summer, while the highest in autumn. Relationships between the air pollutant and some meteorological parameters were also calculated statistically using the daily average data. The wind data (velocity, direction), relative humidity, temperature, sunshine periods, dew point and rainfall were considered as independent variables. The relationships between pollutant concentrations and meteorological parameters were expressed by multiple linear and nonlinear regression equations for both annual and seasonal conditions using SPSS software. RMSE test displayed that the stepwise, among different prediction models, is the best option. |
| first_indexed | 2024-12-11T06:41:49Z |
| format | Article |
| id | doaj.art-b3768fbea39d4816b859c46a2d04bb57 |
| institution | Directory Open Access Journal |
| issn | 1735-3033 1735-3866 |
| language | English |
| last_indexed | 2024-12-11T06:41:49Z |
| publishDate | 2019-09-01 |
| publisher | University of Guilan |
| record_format | Article |
| series | Caspian Journal of Environmental Sciences |
| spelling | doaj.art-b3768fbea39d4816b859c46a2d04bb572022-12-22T01:17:13ZengUniversity of GuilanCaspian Journal of Environmental Sciences1735-30331735-38662019-09-0117322723610.22124/cjes.2019.36653665Assessment of NO2 levels as an air pollutant and its statistical modeling using meteorological parameters in Tehran, IranM. Masoudi0F. Behzadi1M. Sakhaei2Department of Natural Resources and Environmental Engineering, Shiraz University, IranDepartment of Natural Resources and Environmental Engineering, Shiraz University, IranDepartment of Natural Resources and Environmental Engineering, Shiraz University, IranIn the present study, air quality analyses for NO<sub>2</sub> were conducted in Tehran, capital of Iran. The measurements were taken in four different locations to provide average data in the city. The average concentrations were calculated diurnally, monthly and seasonally. Results exhibited that the highest NO<sub>2</sub> concentration occurs generally in the early morning and early night, while the least in the afternoon and after mid-night. Monthly NO2 concentrations displayed the highest value in April, while the least in June and July. The seasonal concentrations exhibited the least amounts in summer, while the highest in autumn. Relationships between the air pollutant and some meteorological parameters were also calculated statistically using the daily average data. The wind data (velocity, direction), relative humidity, temperature, sunshine periods, dew point and rainfall were considered as independent variables. The relationships between pollutant concentrations and meteorological parameters were expressed by multiple linear and nonlinear regression equations for both annual and seasonal conditions using SPSS software. RMSE test displayed that the stepwise, among different prediction models, is the best option.https://cjes.guilan.ac.ir/article_3665_089f0458e6abeeec18872222b1896ad7.pdfno2air pollutionmeteorological parametersregression model |
| spellingShingle | M. Masoudi F. Behzadi M. Sakhaei Assessment of NO2 levels as an air pollutant and its statistical modeling using meteorological parameters in Tehran, Iran Caspian Journal of Environmental Sciences no2 air pollution meteorological parameters regression model |
| title | Assessment of NO2 levels as an air pollutant and its statistical modeling using meteorological parameters in Tehran, Iran |
| title_full | Assessment of NO2 levels as an air pollutant and its statistical modeling using meteorological parameters in Tehran, Iran |
| title_fullStr | Assessment of NO2 levels as an air pollutant and its statistical modeling using meteorological parameters in Tehran, Iran |
| title_full_unstemmed | Assessment of NO2 levels as an air pollutant and its statistical modeling using meteorological parameters in Tehran, Iran |
| title_short | Assessment of NO2 levels as an air pollutant and its statistical modeling using meteorological parameters in Tehran, Iran |
| title_sort | assessment of no2 levels as an air pollutant and its statistical modeling using meteorological parameters in tehran iran |
| topic | no2 air pollution meteorological parameters regression model |
| url | https://cjes.guilan.ac.ir/article_3665_089f0458e6abeeec18872222b1896ad7.pdf |
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