A land use regression model for predicting ambient concentrations of nitrogen dioxide in Hamilton, Ontario, Canada

This paper reports on the development of a land use regression (LUR) model for predicting the intraurban variation of traffic-related air pollution in Hamilton, Ontario, Canada, an industrial city at the western end of Lake Ontario. Although land use regression has been increasingly used to characterize exposure gradients within cities, research to date has yet to test whether this method can produce reliable estimates in an industrialized location. Ambient concentrations of nitrogen dioxide (NO2) were measured for a 2-week period in October 2002 at > 100 locations across the city and subsequently at 30 of these locations in May 2004 to assess seasonal effects. Predictor variables were derived for land use types, transportation, demography, and physical geography using geographic information systems. The LUR model explained 76% of the variation in NO2. Traffic density, proximity to a highway, and industrial land use were all positively correlated with NO2 concentrations, whereas open land use and distance from the lake were negatively correlated with NO2. Locations downwind of a major highway resulted in higher NO2 levels. Cross-validation of the results confirmed model stability over different seasons. Our findings demonstrate that land use regression can effectively predict NO2 variation at the intraurban scale in an industrial setting. Models predicting exposure within smaller areas may lead to improved detection of health effects in epidemiologic studies.     

Valuing power plant flexibility with CCS: the case of post-combustion capture retrofits

An important development in recent years has been increased interest in retrofitting CO₂ capture at existing power plants. In parallel, it has also been suggested that flexible operation of power plants with CO₂ capture could be important in at least some jurisdictions. It is likely that retrofitted power plants could have significant ??built-in?? flexibility, but this potential is often not considered in studies of the economic performance of power plants with CO₂ capture. This paper makes a contribution to filling this gap by developing methods for first order screening analysis of flexible operation of power plants with CO₂ capture and applying them to the case study example of an appropriately integrated retrofit of post-combustion capture at a coal-fired power plant. The quantitative analysis suggests that rich solvent storage could be an attractive option on a short-run basis for some fuel, CO₂ and electricity price combinations. Results from first order analysis can then be used to determine which operating modes should (and shouldn??t) be included in further, more detailed design studies.