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Introduction: Workshop on Analysis of PAMS Data

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Table of Contents

Workshop Objectives
PAMS Data Uses
PAMS Site Types
PAMS Sampling Considerations
Examples
Technical Approach and Introduction to Workshop and Workbook
Assumptions and Limitations
References

Photochemical Assessment Monitoring Stations (PAMS)

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WORKSHOP OBJECTIVES

  • To present, explain, and discuss various methods, procedures, and tools for use in analyzing PAMS and similar aerometric data.
  • To provide a forum for nationwide communication and information transfer on the analysis of PAMS data (and that of supplemental air quality monitoring campaigns and/or field studies)
  • To assist state and local agencies in the use of these methods, procedures, and tools in the analysis of PAMS and similar data sets.
  • To contribute to the general body of knowledge and literature on air quality analysis through demonstration of case studies and examples.

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PAMS DATA USES

  • Corroborate precursor emission inventories
  • Assess changes in emissions; corroborate emissions reductions (SIP control strategy evaluation)
  • Assess ozone and precursor trends
  • Provide input to models; evaluate models (NAAQS attainment and control strategy development)
  • Evaluate population exposure

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PAMS SITE TYPES

Type I: Upwind and background characterization

Type II: Maximum ozone precursor emissions impact

Type III: Maximum ozone concentration

Type IV: Extreme downwind monitoring

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PAMS SAMPLING CONSIDERATIONS

  • Site Location (Types I-IV)
  • Number of Sites
    • Ozone and Precursors
    • Upper-Air Meteorology
  • Sampling Frequency
    • Hydrocarbons
    • Carbonyl Compounds
    • Upper-Air Meteorology
  • Phase-in Options

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EXAMPLES

Figure 1

Carbonyl compounds are sometimes a significant fraction of NMOC and contribute to ozone formation.

Percent of Compounds found at Bermudian Valley, PA and Stratford Lighthouse, CT

Average distribution by time of day of the weight percent of the NMOC attributed to nonmethane hydrocarbons (NMHC), paraffins, olefins, aromatic and unidentified hydrocarbons, and carbonyl compounds at Bermudian Valley, PA and Stratford Lighthouse, CT on episode days (summer 1994). (Lindsey et al., 1995)

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Figure 2

There is large spatial and temporal variability in isoprene concentrations.

Isoprene concentrations at five sites in Massachusetts

Isoprene concentrations at five sites in Massachusetts and the maximum isoprene concentrations measured by aircraft on July 14, 1995 (Level 0, AIRS data - surface; Level 1, NARSTO-Northeast data - aloft).

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Figure 3

Biogenic isoprene concentrations are a function of temperature and sunlight.

Diurnal Variation in Isoprene Concentration, Solar Radiation and Temperature

Three-hour isoprene concentrations and hourly temperature and solar radiation data collected at August 22-29, 1995 (Level 1, AIRS data)

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Figure 4

Differences between modeled and measurement-derived mixing heights may be important.

Time series plot of mixing depths.

Time series plot of mixing depths estimated from Cn2 and Tv data and from a meteorological model for a radar profiler site in Houston, TX for August 18-20, 1993 (Dye et al., 1995a). The agreement between the model, RASS Tv, and Cn2-derived mixing depths is quite good during the growth of the convective boundary layer (CBL - i.e., between 0800 and 1200 CDT). During the later afternoon and at night, discrepancies among all three estimates occurred.

Note that Cn2 mixing depths tend to be more accurate than Tv mixing depths during the day. The opposite is true when the nocturnal inversion layer forms.

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Figure 5

Upper-air wind measurements are needed more than twice per day. Notice the evolution of complex features over the course of 48 hours.

Time series cross section of winds.

Time series cross section of winds, mixing depth, and inversion conditions measured by the radar profiler on July 12-13, 1994 at Bermudian Valley, PA. The thin solid line denotes the height of the mixed layer estimated using Cn2 and RASS temperature data. The thick line denotes the subsidence inversion. The shaded area indicates the region of the nocturnal low-level wind maxima (Lindsey et al., 1995a).

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Figure 6

Mixing depth estimates chart.

Mixing depth estimates based on radar profiler Cn2 and Tv data (Dye et al., 1995) and computed using diagnostic models (CALMET, MIXEMUP, and RAMMET-X) for Schenectady, New York on August 8, 1994. Mixing depths from diagnostic models were provided by S.T. Rao o fhte New York State Department of Environmental Conservation.

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Figure 7

Aloft winds and surface winds are often decoupled. Measurements of both aloft and surface meteorology are necessary to evaluate regional transport potential.

Holbrook Radar Profiler Results

Vector integrated transport distances, resultant wind directions, and recirculation factors, calculated from data collected by the Holbrook radar profiler for the period 19:05 to 06:05 EST on July 13 - July 14, 1995 (Ray et al., 1997).

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Figure 8

On low ozone days, aloft winds showed little recirculation.

Ventalation Analysis on Low Ozone Days

Vector integrated transport distances, resultant wind directions, and recirculation factors (R), calculated from data collected by the southeast Houston (SHE) radar profiler for the period 0600-1700 CDT on August 16, 1993 (SAI et al., 1995)

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Figure 9

On high ozone days, recirculation aloft was important.

Ventalation Analysis on High Ozone Days

Vector integrated transport distances, resultant wind directions, and recirculation factors (R), calculated from data collected by the southeast Houston (SHE) radar profiler for the period 0600-1700 CDT on August 19, 1993 (SAI et al., 1995).

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Figure 10

PAMS VOC data can be compared to emission inventories.

0600 CST Composition of Species Groups

Comparison of the 0600 CST ambient- and total emissions-derived relative compositions of paraffins, olefins, aromatic compounds, and other species for the 9x9 cell (18x18 km) area surrounding Galleria (Houston), TX. Note that the composition of aromatic species in the emission inventory is significantly higher than the ambient composition. (Ambient data, Level 1 AIRS; 1993 COAST emission inventory data, TNRCC)

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Figure 11

Receptor modeling results from hourly-resolved PAMS data are useful to compare to emission inventories.

Comparisons between CMB results and Emission Inventory

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Figure 12

Variations in 3-Hour average n-butane weight fractions.

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Figure 13

PAMS data are useful for trend analysis.

Summertime ozone and ozone precursor concentration trends.

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 PAMS DATA CAN BE USED TO MEET A WIDE RANGE OF OBJECTIVES 

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TECHNICAL APPROACH AND INTRODUCTION TO WORKSHOP AND WORKBOOK

  • Conceptual structure of data analysis is based on two major themes:
    • Progression from data, to data validation, to analyses.
    • Progression from simple describe-and-display analyses, to more complicated analyses, and then to analyses which interpret and integrate.
  • Summary of technical topic areas/structure of the workshop and workbook.
  • Working definitions of methods, procedures, and tools.
  • Both the workshop and the workbook are "works in process;"please provide discussions, suggestions, and recommendations for making both better.

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Figure 14

Example Flow Chart

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ASSUMPTIONS AND LIMITATIONS

Methods, Procedures, and Tools

  • Performed literature review of recent data analyses.
  • Used examples from the literature and from new efforts.
  • Workshop and workbook provide examples from as many methods, procedures, and tools as reasonable; selection of a specific method, procedure, or tool does not imply anything beyond suitability to illustrate an issue or specific situation.
  • Time available at workshop and space available in the workbook are limited; therefore, many details are, of necessity, provided in the literature (see references).
  • The reference lists included in the workbook are intended to provide a starting point for a more in-depth look, and are not intended to provide a comprehensive literature review on any specific subject.
  • Many examples could have been used for any given method, procedure, or tool; selection of a specific example does not imply anything beyond suitability to illustrate an issue or specific situation.

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INTRODUCTION REFERENCES

Dye T.S., Lindsey C.G., and Anderson J.A. (1995a) Estimates of mixing depths from "boundary layer" profilers. In Preprints of the 9th Symposium on Meteorological Observations and Instrumentation, Charlotte, NC, March 27-31, STI-94212-1451.

Dye T.S., Roberts P.T., and Korc M.E. (1995b) Observations of transport processes for ozone and ozone precursors during the 1991 Lake Michigan Ozone Study. J. Appl. Meteorol. 34, 1877-1889. (STI-1384).

Fujita E.M., Watson J.G., Chow J.C., and Lu Z. (1994) Validation of the chemical mass balance receptor model applied to hydrocarbon source apportionment in the Southern California Air Study. Environ. Sci. Technol. 28, 1633-1649.

Lindsey C.G., Dye T.S., Main H.H., Korc M.E., Blumenthal D.L., Roberts P.T., Ray S.E., and Arthur M. (1997) Air quality and meteorological data analyses for the 1994 NARSTO-Northeast Air Quality Study. Final report in preparation for Electric Power Research Institute, Palo Alto, CA by Sonoma Technology, Inc., Santa Rosa, CA, STI-94362-1511-FR.

Lindsey C.G., Dye T.S., Blumenthal D.L., Ray S.E., and Arthur M. (1996) Meteorological aspects of summertime ozone episodes in the Northeast. Paper FA 5.8 presented at the 9th Joint Conference on the Applications of Air Pollution Meteorology at the American Meteorological Society 76th Annual Meeting, Atlanta, GA, January 28-February 2, (STI-1549).

Lu Z. and Fujita E.M. (1995) Volatile organic compound source apportionment for the coastal oxidant assessment for Southeast Texas Study. Final report prepared for Texas Natural Resource Conservation Commission, Austin, TX by Desert Research Institute, Reno, NV.

Lurmann F.W. and Main H.H. (1992) Analysis of the ambient VOC data collected in the Southern California Air Quality Study. Report prepared for the California Air Resources Board, Sacramento, CA by Sonoma Technology, Inc., Santa Rosa, CA, STI-99120-1161-FR, Contract No. A823-130, February.

Stoeckenius T.E., Yarwood G., Ligocki M.P., Cohen J.P., Shepard S.B., Looker R.E., Fujita E.M., Main H.H., and Roberts P.T. (1995) Feasibility study for a 1995-1996 Southern California air quality monitoring program. Final report prepared for Coordinating Research Council, Atlanta, GA by Systems Applications International, San Rafael, CA, Desert Research Institute, Reno, NV, and Sonoma Technology, Inc., Santa Rosa, CA, SYSAPP94-94/065, January.

Systems Applications International, Sonoma Technology Inc., EarthTech, Alpine Geophysics, and A.T. Kearney (1995) Gulf of Mexico Air Quality Study. Vol. I: summary of data analysis and modeling. Final report prepared for U.S. Department of the Interior, Minerals Management Service, Gulf of Mexico OCS Region, New Orleans, LA, OCS Study MMS-95-0038.

U.S. Environmental Protection Agency (1994) Photochemical assessment monitoring stations implementation manual. Report prepared by Office of Air Quality Planning and Standards, U.S. Environmental Protection Agency, Research Triangle Park, NC, EPA-454/B-93-051, March.

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