Use of Stationary and Mobile Measurements to Study Power Plant Emissions

Abstract

Chak K. Chan is with the Department of Chemical Engineering, Hong Kong University of Science and Technology, Clear Water Bay, Hong Kong.

This paper presents a technique to study air pollution by combining high spatial resolution data obtained by a mobile platform and those measured by conventional stationary stations. Conventional stations provide time-series point data but cannot yield information that is distant from the sites. This can be complemented or supplemented by mobile measurements in the vicinity of the conventional sites. Together, the combined dataset yields a clearer and more precise picture of the dispersion and the transformation of pollutants in the atmosphere in a fixed time frame. Several experiments were conducted in the years 2002–2003 to track the impact of power plant plumes on ground receptors in the immediate vicinity (within a radius of 30 km) of the plants, using a combined mobile and stationary dataset. The mobile data allowed the identification of emissions from coal-fired and gasfired power plants. Coal-fired power plants were the major source of sulfur dioxide (SO₂), whereas nitrogen oxides (NO_x) emitted from the gas-fired power plant played an important role in the formation of ozone (O₃) at ground level. The mobile data showed that two particle size distribution regimes were detected: one had a dominant accumulation mode at 0.40–0.65 μm and the other at 0.65–1 μm. The existence of particles characterized by their mode at 0.65–1 μm and formed by in-cloud processes suggests that vehicular emissions were not the important source. Other local sources, such as power plants (elevated emission), were the likely sources, because Hong Kong does not have much manufacturing industry.