Chen L.,Nankai University |
Chen L.,State Environmental Protection Key Laboratory of Urban Ambient Air Particulate Matter Pollution and Control |
Chen L.,Tianjin Normal University |
Bai Z.,Nankai University |
And 11 more authors.
Journal of Environmental Sciences | Year: 2010
Land use regression (LUR) model was employed to predict the spatial concentration distribution of NO2 and PM10 in the Tianjin region based on the environmental air quality monitoring data. Four multiple linear regression (MLR) equations were established based on the most significant variables for NO2 in heating season (R2 = 0.74), and non-heating season (R2 = 0.61) in the whole study area; and PM10 in heating season (R2 = 0.72), and non-heating season (R2 = 0.49). Maps of spatial concentration distribution for NO2 and PM10 were obtained based on the MLR equations (resolution is 10 km). Intercepts of MLR equations were 0.050 (NO2, heating season), 0.035 (NO2, non-heating season), 0.068 (PM10, heating season), and 0.092 (PM10, non-heating season) in the whole study area. In the central area of Tianjin region, the intercepts were 0.042 (NO2, heating season), 0.043 (NO2, non-heating season), 0.087 (PM10, heating season), and 0.096 (PM10, non-heating season). These intercept values might imply an area's background concentrations. Predicted result derived from LUR model in the central area was better than that in the whole study area. R2 values increased 0.09 (heating season) and 0.18 (non-heating season) for NO2, and 0.08 (heating season) and 0.04 (non-heating season) for PM10. In terms of R2, LUR model performed more effectively in heating season than non-heating season in the study area and gave a better result for NO2 compared with PM10. © 2010 The Research Centre for Eco-Environmental Sciences, Chinese Academy of Sciences.
Lu B.,State Environmental Protection Key Laboratory of Urban Ambient Air Particulate Matter Pollution and Control |
Lu B.,Nankai University |
Kong S.-F.,State Environmental Protection Key Laboratory of Urban Ambient Air Particulate Matter Pollution and Control |
Kong S.-F.,Nankai University |
And 6 more authors.
Meitan Xuebao/Journal of the China Coal Society | Year: 2011
A dilution sampling system was used to collect fly ashes in stack gas from coal-fired boilers while a re-suspended sampling chamber was adopted to collect ashes captured by emission control devices. Chemical profiles for TSP and PM10 were established by the two methods. The main chemical components for particulate matter from coal-fired boilers are TC, OC, Si, Al, Ca, Na, Mg, Fe and SO4 2-. Si and TC are the most abundant species in TSP and PM10 profiles. As for trace elements, Cr, Zn, As, Pb and Cu are enriched in PM10 when compared to raw coal. There exist diversities for profiles obtained from boilers with wet and dry dust removal devices. Coefficient of divergence analysis indicate that profiles for dilution stack sampling and re-suspended sampling methods are different.