Characterizing the effect of traffic density on ambient CO, NO2, and PM2.5 in Tehran, Iran: an hourly land-use regression model

References

• Abbaspour, M., and A. Soltaninejad. 2004. “Design of an Environmental Assessment Model on the Effect of Vehicle Emission in Greater Tehran on Air Pollution with Economic sensitivity.” International Journal of Environmental Science & Technology 1 (1): 27–38.10.1007/BF03325813
   Google Scholar
• Aguilera, I., J. Sunyer, R. Fernández-Patier, G. Hoek, A. Aguirre-Alfaro, K. Meliefste, M. T. Bomboi-Mingarro, M. J. Nieuwenhuijsen, D. Herce-Garraleta, and B. Brunekreef. 2007. “Estimation of Outdoor NOx, NO2, and BTEX Exposure in a Cohort of Pregnant Women Using Land Use Regression Modeling.” Environmental Science & Technology 42 (3): 815–821.
   Web of Science ®Google Scholar
• Air Quality Control Company. 2017. Tehran’s Air Quality Report 1395. Tehran.
   Google Scholar
• Amini, H., S. M. Taghavi-Shahri, S. B. Henderson, K. Naddafi, R. Nabizadeh, and M. Yunesian. 2014. “Land Use Regression Models to Estimate the Annual and Seasonal Spatial Variability of Sulfur Dioxide and Particulate Matter in Tehran, Iran.” Science of the Total Environment 488–489: 343–353.10.1016/j.scitotenv.2014.04.106
   PubMed Web of Science ®Google Scholar
• Arhami, M., N. Kamali, and M. M. Rajabi. 2013. “Predicting Hourly Air Pollutant Levels using Artificial Neural Networks Coupled with Uncertainty Analysis by Monte Carlo Simulations.” Environmental Science and Pollution Research 20 (7): 4777–4789.10.1007/s11356-012-1451-6
   PubMed Web of Science ®Google Scholar
• Basagaña, X., M. Rivera, I. Aguilera, D. Agis, L. Bouso, R. Elosua, and M. Foraster. 2012. “Effect of the Number of Measurement Sites on Land Use Regression Models in Estimating Local Air Pollution.” Atmospheric Environment 54: 634–642.10.1016/j.atmosenv.2012.01.064
   Web of Science ®Google Scholar
• Beelen, R., G. Hoek, D. Vienneau, M. Eeftens, K. Dimakopoulou, X. Pedeli, and M. Y. Tsai. 2013. “Development of NO2 and NOx Land Use Regression Models for Estimating Air Pollution Exposure in 36 Study Areas in Europe – The ESCAPE project.” Atmospheric Environment 72: 10–23.10.1016/j.atmosenv.2013.02.037
   Web of Science ®Google Scholar
• Crouse, D. L., M. S. Goldberg, and N. A. Ross. 2009. “A Prediction-Based Approach to Modelling Temporal and Spatial Variability of Traffic-Related Air Pollution in Montreal, Canada.” Atmospheric Environment 43 (32): 5075–5084.10.1016/j.atmosenv.2009.06.040
   Web of Science ®Google Scholar
• de Hoogh, K., M. Wang, M. Adam, C. Badaloni, R. Beelen, M. Birk, and G. Cesaroni. 2013. “Development of Land Use Regression Models for Particle Composition in Twenty Study Areas in Europe.” Environmental Science & Technology 47 (11): 5778–5786.10.1021/es400156t
   PubMed Web of Science ®Google Scholar
• Dhondt, S., C. Beckx, B. Degraeuwe, W. Lefebvre, B. Kochan, T. Bellemans, L. I. Panis, C. Macharis, and K. Putman. 2012. “Health Impact Assessment of Air Pollution Using a Dynamic Exposure Profile: Implications for Exposure and Health Impact Estimates.” Environmental Impact Assessment Review 36: 42–51.10.1016/j.eiar.2012.03.004
   Web of Science ®Google Scholar
• Dons, E., M. Van Poppel, B. Kochan, G. Wets, and L. I. Panis. 2013. “Modeling Temporal and Spatial Variability of Traffic-Related Air Pollution: Hourly Land Use Regression Models for Black Carbon.” Atmospheric Environment 74: 237–246.10.1016/j.atmosenv.2013.03.050
   Web of Science ®Google Scholar
• Florio, L., and L. Mussone. 1996. “Neural-Network Models for Classification and Forecasting of Freeway Traffic Flow Stability.” Control Engineering Practice 4 (2): 153–164.
   Web of Science ®Google Scholar
• Gilbert, N. L., M. S. Goldberg, B. Beckerman, J. R. Brook, and M. Jerrett. 2005. “Assessing Spatial Variability of Ambient Nitrogen Dioxide in Montreal, Canada, with a Land-use Regression Model.” Journal of the Air & Waste Management Association 55 (8): 1059–1063.
   Web of Science ®Google Scholar
• Henderson, S. B., B. Beckerman, M. Jerrett, and M. Brauer. 2007. “Application of Land Use Regression to Estimate Long-Term Concentrations of Traffic-Related Nitrogen Oxides and Fine Particulate Matter.” Environmental Science & Technology 41 (7): 2422–2428.10.1021/es0606780
   PubMed Web of Science ®Google Scholar
• Hochadel, M., J. Heinrich, U. Gehring, V. Morgenstern, T. Kuhlbusch, E. Link, H. E. Wichmann, and U. Krämer. 2006. “Predicting Long-Term Average Concentrations of Traffic-Related Air Pollutants Using GIS-Based Information.” Atmospheric Environment 40 (3): 542–553.10.1016/j.atmosenv.2005.09.067
   Web of Science ®Google Scholar
• Hoek, G., K. Meliefste, J. Cyrys, M. Lewné, T. Bellander, M. Brauer, P. Fischer, U. Gehring, J. Heinrich, P. van Vliet, and B. Brunekreef. 2002. “Spatial Variability of Fine Particle Concentrations in Three European areas.” Atmospheric Environment 36 (25): 4077–4088.
   Web of Science ®Google Scholar
• Hoek, G., R. Beelen, K. de Hoogh, D. Vienneau, J. Gulliver, P. Fischer, and D. Briggs. 2008. “A Review of Land-Use Regression Models to Assess Spatial Variation of Outdoor Air Pollution.” Atmospheric Environment 42 (33): 7561–7578.10.1016/j.atmosenv.2008.05.057
   Web of Science ®Google Scholar
• Kauth, R. J., and G. S. Thomas. 1976. “The Tasselled Cap–A Graphic Description of the Spectral-Temporal Development of Agricultural Crops as Seen by Landsat.” LARS Symposia. 159.
   Google Scholar
• Mavko, M. E., B. Tang, and L. A. George. 2008. “A Sub-Neighborhood Scale Land Use Regression Model for Predicting NO2.” Science of the Total Environment 398 (1–3): 68–75.10.1016/j.scitotenv.2008.02.017
   PubMed Web of Science ®Google Scholar
• Meng, X., Q. Fu, Z. Ma, L. Chen, B. Zou, Y. Zhang, W. Xue et al. 2016. “Estimating Ground-level PM 10 in a Chinese City by Combining Satellite Data, Meteorological Information and a Land Use Regression Model.” Environmental Pollution 208: 177–184.
   PubMed Web of Science ®Google Scholar
• Rapidminer Studio ( version 7.4.00). 2017. OSX. RapidMiner GmbH.
   Google Scholar
• Rashidi, T. H., P. Kanaroglou, E. Toop, H. Maoh, and X. Liu. 2015. “Emissions and Built Form–an Analysis of Six Canadian Cities.” Transportation Letters 7 (2): 80–91.10.1179/1942787514Y.0000000036
   Web of Science ®Google Scholar
• Ross, Z., P. B. English, R. Scalf, R. Gunier, S. Smorodinsky, S. Wall, and M. Jerrett. 2006. “Nitrogen Dioxide Prediction in Southern California Using Land Use Regression Modeling: Potential for Environmental Health Analyses.” Journal of Exposure Science and Environmental Epidemiology 16 (2): 106.
   PubMed Web of Science ®Google Scholar
• Ryan, P. H., and G. K. LeMasters. 2007. “A Review of Land-Use Regression Models for Characterizing Interurban Air Pollution Exposure.” Inhalation Toxicology 19 (sup1): 127–133.10.1080/08958370701495998
   PubMed Web of Science ®Google Scholar
• Sahsuvaroglu, T., A. Arain, P. Kanaroglou, N. Finkelstein, B. Newbold, M. Jerrett, B. Beckerman, J. Brook, M. Finkelstein, and N. L. Gilbert. 2006. “A Land Use Regression Model for Predicting Ambient Concentrations of Nitrogen Dioxide in Hamilton, Ontario, Canada.” Journal of the Air & Waste Management Association 56 (8): 1059–1069.10.1080/10473289.2006.10464542
   Web of Science ®Google Scholar
• Setton, E., J. D. Marshall, M. Brauer, K. R. Lundquist, P. Hystad, P. Keller, and D. Cloutier-Fisher. 2010. “The Impact of Daily Mobility on Exposure to Traffic-Related Air Pollution and Health Effect Estimates.” Journal of Exposure Science and Environmental Epidemiology 21 (1): 42–48.
   PubMed Web of Science ®Google Scholar
• Shahbazi, H., M. Reyhanian, V. Hosseini, and H. Afshin. 2016. “The Relative Contributions of Mobile Sources to Air Pollutant Emissions in Tehran, Iran: An Emission Inventory Approach.” Emission Control Science and Technology 2 (1): 44–56.10.1007/s40825-015-0031-x
   Google Scholar
• Smith, B. L., and M. J. Demetsky. 1994. “Short-term Traffic Flow Prediction: Neural Network Approach.” Transportation Research Board 1453: 98–104.
   Google Scholar
• Su, J. G., M. Jerrett, B. Beckerman, D. Verma, M. A. Arain, P. Kanaroglou, D. Stieb, M. Finkelstein, and J. Brook. 2010. “A Land Use Regression Model for Predicting Ambient Volatile Organic Compound Concentrations in Toronto, Canada.” Atmospheric Environment 44 (29): 3529–3537.10.1016/j.atmosenv.2010.06.015
   Web of Science ®Google Scholar
• Wang, X. Y., and K. C. Wang. 2014. “Estimation of Atmospheric Mixing Layer Height from Radiosonde Data.” Atmospheric Measurement Techniques 7 (6): 1701–1709.10.5194/amt-7-1701-2014
   Web of Science ®Google Scholar
• Weichenthal, S., K. Van Ryswyk, A. Goldstein, M. Shekarrizfard, and M. Hatzopoulou. 2016. “Characterizing the Spatial Distribution of Ambient Ultrafine Particles in Toronto, Canada: A Land Use Regression Model.” Environmental Pollution 208: 241–248.10.1016/j.envpol.2015.04.011
   PubMed Web of Science ®Google Scholar
• Werner, M. 2001. “Shuttle Radar Topography Mission (SRTM) Mission Overview.” Frequenz 55 (3–4): 75–79.
   Web of Science ®Google Scholar
• Wolf, K., J. Cyrys, T. Harciníková, J. Gu, T. Kusch, R. Hampel, A. Schneider, and A. Peters. 2017. “Land Use Regression Modeling of Ultrafine Particles, Ozone, Nitrogen Oxides and Markers of Particulate Matter Pollution in Augsburg, Germany.” Science of the Total Environment 579: 1531–1540.10.1016/j.scitotenv.2016.11.160
   PubMed Web of Science ®Google Scholar
• Yazdi, M. N., M. Delavarrafiee, and M. Arhami. 2015. “Evaluating Near Highway Air Pollutant Levels and Estimating Emission Factors: Case Study of Tehran, Iran.” Science of the Total Environment 538: 375–384.10.1016/j.scitotenv.2015.07.141
   PubMed Web of Science ®Google Scholar
• Zheng, W., D. H. Lee, and Q. Shi. 2006. “Short-Term Freeway Traffic Flow Prediction: Bayesian Combined Neural Network Approach.” Journal of Transportation Engineering 132 (2): 114–121.10.1061/(ASCE)0733-947X(2006)132:2(114)
   Web of Science ®Google Scholar