Photochemical model evaluation of the surface ozone impact of a power plant in a heavily industrialized area of southwestern Spain

The characterization and evaluation of the impact that an industry is likely to have on the surrounding ozone levels is one of many problems confronting air quality managers and should be taken into consideration when authorizing its installation. The correct management of an environment, in terms of monitoring existing industries and planning new activities, requires adequate knowledge of the processes sustained by the industrial emissions therein. This paper explores the improvements in air quality management arising from taking into account the uncertainties involved in the photochemical modeling of the impact of an industry on surface ozone levels. For this, we evaluate the impact on ozone levels of a power plant located in an industrial area of southwestern Spain (Huelva). The evaluation takes into account the effects of both emissions' uncertainty and the non-linear chemistry between ozone and its precursors, thus providing a probable range of increase over the normative values (hourly and 8-hourly maximums) defined in the European Directive. The proposed methodology is easily applicable by air quality managers. Advanced modeling techniques were used for the power plant assessment, MM5 atmospheric modeling system, and air quality model CAMx. The results from meteorology and ozone forecasts have shown acceptable agreement with the observations. The spatial distribution of the impact is found to be strongly determined by mesoscale meteorological processes, which are reinforced by the local orography; there is also a marked temporal evolution. The industrial plume is observed to induce a decrease (or maintenance) of the ozone levels near the emission source (0-10km), and an increase in the ozone concentrations farther away (with maximums between 10 and 50km). In fact, in the meteorological episodes with a predominance of local breeze circulations, impacts have been detected at distances of more than 100km from the emission source. Sensitivity of the power plant impact to variations in ozone precursor emissions is described, and the scenarios and the points in the domain presenting higher sensitivity and registering larger impacts are also identified. The results show that the largest impacts take place in emission scenarios where the NO(x) has been reduced with respect to the base case scenario. In contrast, in scenarios where the VOC emissions are reduced with respect to the base case scenario, the impact is smaller or remains unchanged. This is important in areas like the study case, where there is a high percentage of biogenic VOC emissions and the industrial areas are close to natural protected areas and agricultural fields.