Spatial analysis and risk assessment of urban BTEX compounds in Urmia, Iran.

Land Use Regression models (LUR) are the most common tools to estimate intra-urban air pollutant exposure in epidemiological studies. However, number of available and published models in developing and middle up income countries is still scarce. Here, we developed seasonal and overall LUR models for the spatial distribution of benzene, toluene, ethylbenzene and xylene (BTEX) based on 20 monitoring stations and 166 potentially predictive variables (PPVs) in Urmia, Iran.

Estimate annual and seasonal PM, PM and PM concentrations using land use regression model.

Exposure to ambient particulate matter (PM) can increase mortality and morbidity in urban area. In this study, annual and seasonal spatial pattern of PM, PM and PM pollutants were assessed using land use regression (LUR) models in Sabzevar, Iran. The studied pollutants were measured at 26 monitoring stations of different microenvironments in the study area.

Intra-urban variation of ultrafine particles as evaluated by process related land use and pollutant driven regression modelling.

The microscale intra-urban variation of ultrafine particle concentrations (UFP, diameter Dp<100 nm) and particle number size distributions was studied by two statistical regression approaches. The models were applied to a 1 km2 study area in Braunschweig, Germany. A land use regression model (LUR) using different urban morphology parameters as input is compared to a multiple regression type model driven by pollutant and meteorological parameters (PDR).