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Discerning Influences

Discerning Influences. Meteorology: explore the affect of meteorological conditions on PM concentrations and composition. Emissions: explore the affect of emissions on PM concentrations and composition. Inter-pollutant relationships: explore the relationships among PM components.

cynthia-strong
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Discerning Influences

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  1. Discerning Influences • Meteorology: explore the affect of meteorological conditions on PM concentrations and composition. • Emissions: explore the affect of emissions on PM concentrations and composition. • Inter-pollutant relationships: explore the relationships among PM components. • Natural Events: explore the affect of natural events (e.g., dust storms, fires) on PM concentrations. PM Data Analysis Workbook: Characterizing PM Key reference:

  2. Emissions PM Data Analysis Workbook: Characterizing PM

  3. Meteorology PM Data Analysis Workbook: Characterizing PM

  4. Formation and Removal PM Data Analysis Workbook: Characterizing PM

  5. Inter-pollutant Relationships PM Data Analysis Workbook: Characterizing PM

  6. Natural PM Events: Dust and Smoke • Dust storms and forest fires are major PM events that occur several times a year over different parts of the US. • Many of these events originate outside the US, e.g. dust from Sahara and the Asian desserts and smoke from forest fires in Central America and Canada. • Exceedances of the NAAQS caused by dust and smoke events are uncontrollable ‘acts of God’. Nevertheless, states are required to provide evidence that such events (outside their jurisdiction) have occurred. PM Data Analysis Workbook: Characterizing PM Key reference: Capita

  7. Natural PM Events • For this reason, control agencies need to be able to detect and document the impact of such events on their control region. The existing tools for such documentation are poorly developed. • The natural PM events are illustrated by two extreme examples: Asian dust impacting on the West Coast and the Central American forest fire smoke impacting the Eastern US. PM Data Analysis Workbook: Characterizing PM Key reference: Capita

  8. During a ten-day period, May 7-17, 1998, smoke from fires in Central America drifted northward into USA and Canada. The smoke caused exceedances of the PM standard, health alerts, and impairment of air traffic, as well as major reductions of visual range. It has been argued that some ozone exceedances in the Eastern US may have been due to ozone generated by the forest fire smoke. Smoke from C. American Forest Fires SeaWiFS View of the Smoke GOES 8 View of the Smoke PM Data Analysis Workbook: Characterizing PM Key reference: Capita

  9. PM10 over the Eastern U.S. during the smoke event 24-hr PM10 concentrations in g/m3 are shown for several cities. The likely smoke impact on these cities is highlighted. The vertical line at … in each figure represents…. PM Data Analysis Workbook: Characterizing PM Key reference: Capita

  10. The Asian Dust Event of April 1998 • On April 15th, 1998 an unusually intense dust storm began in the western Chinese Province of Xinjiang, just in time for the east Asian dust season. • By April 20, the dust front covered a 1000 mile stretch on the east coast of China and within five days it moved across the Pacific. It reached the West Coast by April 25. PM Data Analysis Workbook: Characterizing PM Key reference: Capita

  11. Asian Dust over the West Coast • In Vancouver and in Washington State the PM10 and PM2.5 concentrations reached 100 and 40 g/m3, respectively. • Based on public complaints and monitoring data, the State of Washington issued a ban on open burning on April 29. Thus, a dust cloud from another country impacted activity in the US. PM Data Analysis Workbook: Characterizing PM Key reference: Capita

  12. Methods and Tools PM Data Analysis Workbook: Characterizing PM

  13. Decision Matrix for Spatial and Temporal Analyses Decision matrix to be used to select example projects that will illustrate how others have explored the characterization of PM. To use the matrix, find your technical topic area at the left. Follow this line across to see which example projects illustrate analyses pertaining to the topic area. For each of these projects, go to the next page to see which data and data analysis tools were used. PM Data Analysis Workbook: Characterizing PM

  14. Decision Matrix for Spatial and Temporal Analyses For each of the projects that are of interest to you, follow down the column to see which data and data analysis tools were used. PM Data Analysis Workbook: Characterizing PM

  15. References PM Data Analysis Workbook: Characterizing PM

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