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Weekly Pattern of PM

Weekly Pattern of PM. Background and Rationale Weekly Pattern of PM10 in Northeast Weekly Pattern of PM10 in West Conclusions Resource Links. Contact: Rudolf Husar, rhusar@mecf.wustl.edu. Background and Rationale. There is a measurable weekly cycle of PM at most monitoring sites.

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Weekly Pattern of PM

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  1. Weekly Pattern of PM Background and Rationale Weekly Pattern of PM10 in Northeast Weekly Pattern of PM10 in West Conclusions Resource Links Contact: Rudolf Husar, rhusar@mecf.wustl.edu

  2. Background and Rationale • There is a measurable weekly cycle of PM at most monitoring sites. • The weekly periodicity of PM is explicitly attributable to the weekly cycling of emission sources and it is not influenced by weather. • Hence, the weekly cycle can reveal certain features of PM emissions such as weekday peak at industrial sites and weekend peak at recreational sites. • At this time the weekly cycle has been analyzed for PM10 but not for PM2.5.

  3. Weekly Pattern of PM10 in Northeast Within urban areas (e.g. Boston) the daily average PM10 concentration in the city center during the week is 10-20% higher than on weekends. At remote monitoring sites (e.g. Thomaston, ME), the overall concentrations are lower and there is no discernable weekly cycle.

  4. Weekly Pattern of PM10 in West In some urban areas, such as Tacoma, WA, the amplitude of the PM10 cycle may be up to 50% of the weekly average. At Yosemite NP and Oceanside, CA, the highest concentrations occur on Sundays.

  5. Conclusions • At remote locations, the PM10 concentration is uniform during the entire week. • Urban centers have have higher concentrations during the workweek and reduced values on weekends. • At recreational locations, the PM10 concentration may peak during the weekend. • The existence of a weekly cycle of PM in urban and at some rural areas is evidence that the PM concentrations are influenced by human activities.

  6. Resource Links • Workbook Table of Contents • Comment and Feedback Page • Applications / Reports • Data sets used in the Applications • Methods and tools used in the Applications

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