학술논문

Seasonal differences in SO.sub.2 ground-level impacts from a power plant plume on complex terrain
Document Type
Report
Source
Environmental Monitoring and Assessment. Feb, 2009, Vol. 149 Issue 1-4, p445, 11 p.
Subject
Air quality -- Analysis
Troposphere -- Analysis
Turbulence -- Analysis
Electric power-plants -- Analysis
Power plants -- Analysis
Language
English
ISSN
0167-6369
Abstract
The objective of this study is to describe the seasonal differences in SO.sub.2 ground-level fumigations from a power plant situated on very complex terrain in the Iberian Peninsula within the Western Mediterranean Basin (WMB). The study area extends more than 80 km around the power plant on very complex semi-arid terrain. Considering different plume-rise schemes, by experimentation and modelling this study attempts to characterise the seasonal differences in both the plume footprint 80 km around the power plant and the turbulent regime (diurnal or nocturnal) driving the main contribution to the accumulated plume footprints at different distances from the power plant within a complex terrain region. Two markedly different SO.sub.2 ground-level distributions around the power plant are presented for the typical summer and winter dispersive scenarios in the area. Simulations show that the SO.sub.2 footprint of a plume being advected more than 450 m above ground level in complex terrain is highly dependent on the prevailing meteorological conditions and on the mesoscale perturbations of the synoptic flows within the lower layers of the troposphere. The results obtained show how on complex terrain, despite seasonal meteorological differences and under stable dispersive conditions, the simulated mechanical turbulence leeward of the mountain ranges reproduces highly concentrated SO.sub.2 fumigations on the ground more than 50 km away from the power plant. Besides, under summer convective activity, plume fumigations have been successfully simulated less than 15 km from the power plant. In conclusion, this study shows how measurements from air quality networks together with information obtained from atmospheric transport and diffusion models are able to characterise different transport scenarios. This is a clear advantage for the end-users and decision-makers who manage and optimise the regional air quality networks.