Development of land use regression model to estimate particulate matter (PM10) and nitrogen dioxide (NO2) concentrations in Peninsular Malaysia
Nowadays, exposure modelling has become the preferred method for assessing human air pollution exposure due to its capability to predict air pollution under various conditions. The land use regression model (LUR) is a widely conducted model utilized to estimate air pollutants especially in unmonitor...
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| Format: | Article |
| Language: | English |
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Elsevier
2024-01-01
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| Series: | Atmospheric Environment: X |
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| Online Access: | http://www.sciencedirect.com/science/article/pii/S259016212400011X |
| _version_ | 1797267214654504960 |
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| author | Wan Nurul Farah Wan Azmi Thulasyammal Ramiah Pillai Mohd Talib Latif Rafiza Shaharudin Shajan Koshy |
| author_facet | Wan Nurul Farah Wan Azmi Thulasyammal Ramiah Pillai Mohd Talib Latif Rafiza Shaharudin Shajan Koshy |
| author_sort | Wan Nurul Farah Wan Azmi |
| collection | DOAJ |
| description | Nowadays, exposure modelling has become the preferred method for assessing human air pollution exposure due to its capability to predict air pollution under various conditions. The land use regression model (LUR) is a widely conducted model utilized to estimate air pollutants especially in unmonitored locations. However, the application of the model is still lacking in developing countries, especially in the Southeast Asia region. Therefore, this study was conducted to develop the LUR model to estimate PM10 and NO2 concentrations in Peninsular Malaysia. Multiple linear regression with a supervised forward stepwise was used to develop the models, and the models were validated using the leave-out-one cross-validation (LOOCV) approach. Results showed that the LUR model of PM10 explained 58.5% variation, while the NO2 LUR model described 86.8% variation. The difference value of PM10 model R2 and LOOCV R2 were between 0.1% and 1.2 %, and the NO2 models were between 0.01% and 0.08% depicting the robust stability of the models. Both models indicated that increased road and industrial areas significantly influence PM10 and NO2 concentrations. Nevertheless, more studies on the LUR model should be conducted in developing countries to assess the model's applicability in the region. |
| first_indexed | 2024-03-07T22:54:44Z |
| format | Article |
| id | doaj.art-d940aea144ab4c5aae27e744885fca7d |
| institution | Directory Open Access Journal |
| issn | 2590-1621 |
| language | English |
| last_indexed | 2024-04-25T01:13:02Z |
| publishDate | 2024-01-01 |
| publisher | Elsevier |
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| series | Atmospheric Environment: X |
| spelling | doaj.art-d940aea144ab4c5aae27e744885fca7d2024-03-10T05:12:44ZengElsevierAtmospheric Environment: X2590-16212024-01-0121100244Development of land use regression model to estimate particulate matter (PM10) and nitrogen dioxide (NO2) concentrations in Peninsular MalaysiaWan Nurul Farah Wan Azmi0Thulasyammal Ramiah Pillai1Mohd Talib Latif2Rafiza Shaharudin3Shajan Koshy4Environmental Health Research Centre, Institute for Medical Research, National Institutes of Health, Ministry of Health Malaysia, 40170, Shah Alam, Selangor, Malaysia; School of Biosciences, Faculty of Health and Medical Sciences, Taylor's University, 47500, Subang Jaya, Selangor, Malaysia; Corresponding author. Environmental Health Research Centre, Institute for Medical Research, Ministry of Health Malaysia, 40170, Shah Alam, Selangor, Malaysia.Faculty of Data Science and Information Technology, INTI International University, 71800, Nilai, Negeri Sembilan, MalaysiaDepartment of Earth Sciences and Environment, Faculty of Science and Technology, Universiti Kebangsaan Malaysia, 43600, Bangi, Selangor, MalaysiaEnvironmental Health Research Centre, Institute for Medical Research, National Institutes of Health, Ministry of Health Malaysia, 40170, Shah Alam, Selangor, MalaysiaSchool of Medicine, Faculty of Health and Medical Sciences, Taylor's University, 47500, Subang Jaya, Selangor, MalaysiaNowadays, exposure modelling has become the preferred method for assessing human air pollution exposure due to its capability to predict air pollution under various conditions. The land use regression model (LUR) is a widely conducted model utilized to estimate air pollutants especially in unmonitored locations. However, the application of the model is still lacking in developing countries, especially in the Southeast Asia region. Therefore, this study was conducted to develop the LUR model to estimate PM10 and NO2 concentrations in Peninsular Malaysia. Multiple linear regression with a supervised forward stepwise was used to develop the models, and the models were validated using the leave-out-one cross-validation (LOOCV) approach. Results showed that the LUR model of PM10 explained 58.5% variation, while the NO2 LUR model described 86.8% variation. The difference value of PM10 model R2 and LOOCV R2 were between 0.1% and 1.2 %, and the NO2 models were between 0.01% and 0.08% depicting the robust stability of the models. Both models indicated that increased road and industrial areas significantly influence PM10 and NO2 concentrations. Nevertheless, more studies on the LUR model should be conducted in developing countries to assess the model's applicability in the region.http://www.sciencedirect.com/science/article/pii/S259016212400011XAir pollutionLURSpatial analysisExposure assessmentSoutheast Asia |
| spellingShingle | Wan Nurul Farah Wan Azmi Thulasyammal Ramiah Pillai Mohd Talib Latif Rafiza Shaharudin Shajan Koshy Development of land use regression model to estimate particulate matter (PM10) and nitrogen dioxide (NO2) concentrations in Peninsular Malaysia Atmospheric Environment: X Air pollution LUR Spatial analysis Exposure assessment Southeast Asia |
| title | Development of land use regression model to estimate particulate matter (PM10) and nitrogen dioxide (NO2) concentrations in Peninsular Malaysia |
| title_full | Development of land use regression model to estimate particulate matter (PM10) and nitrogen dioxide (NO2) concentrations in Peninsular Malaysia |
| title_fullStr | Development of land use regression model to estimate particulate matter (PM10) and nitrogen dioxide (NO2) concentrations in Peninsular Malaysia |
| title_full_unstemmed | Development of land use regression model to estimate particulate matter (PM10) and nitrogen dioxide (NO2) concentrations in Peninsular Malaysia |
| title_short | Development of land use regression model to estimate particulate matter (PM10) and nitrogen dioxide (NO2) concentrations in Peninsular Malaysia |
| title_sort | development of land use regression model to estimate particulate matter pm10 and nitrogen dioxide no2 concentrations in peninsular malaysia |
| topic | Air pollution LUR Spatial analysis Exposure assessment Southeast Asia |
| url | http://www.sciencedirect.com/science/article/pii/S259016212400011X |
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