Characterizing source impacts and trend of air pollution

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The overall goal of air quality management is to protect human health and our environment. Thus, risk reduction strategies should be implemented, and those initiatives should be guided by a good understanding of the underlying physical/chemical mechanisms. Presently, the two missing links are: 1) major sources and their contributions to ambient air quality Quantitative identification of sources and contributions is difficult because observed concentrations usually originate from multiple emission sources, including power generation, industrial facilities, and vehicular exhaust. Furthermore, both the absolute and relative contributions of each source may change significantly over time due to advancement in technology as well as emission control measures. 2) the degree of success of past control measures In most Canadian cities, air quality has been gradually improving over the past 20 years. However, there have been few systematic examinations of the relationship between the changing air quality and the emission reduction that has occurred during the same time period. Future, the potential impact of climate change on air quality should be considered in long-term air quality management. NSERC funding will support efforts to improve our knowledge and assist management decisions through a novel approach which synthesizes datasets from different government branches and develops new tools. A comprehensive air quality dataset will be created by incorporating all major air pollutants monitored by the national or provincial networks in the past 25 years, including particulate matter, ozone, sulfur dioxide, nitrate, sulphate, ammonia, nitrogen oxides, volatile organic compounds, polycyclic aromatic hydrocarbons, and mercury. Emission inventory and weather parameters during the past 25 years will also be utilized. The long-term trend of air quality in Canadian cites will be evaluated using those data and statistical approaches. The characterization of major air pollution sources and their contributions to ambient air quality will be achieved by using the same data and applying modeling tools. New knowledge on trend of air quality and source-receptor relationships will be created, taking into consideration air pollutant levels, quantity of emission, interaction among pollutants, weather conditions, climate change, and implemented policy. The findings will be of interest to the general public, scientists, and government agencies by improving our understanding of the complex relationship between emission and air quality. Further, a data-driven air quality assessment approach will be developed. The method can be easily and widely used by researchers, practitioners, and regulators for air quality management to evaluate the control measures implemented and to develop future mitigation strategies in Canada and in other countries.