SOURCE ORIENTED vs RECEPTOR ORIENTED MODELS

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SOURCE ORIENTED vs RECEPTOR ORIENTED MODELS

• Source oriented given source characteristics and
  meteorological data, estimate pollutant
  concentrations at receptor site(s)
• Receptor oriented given measured pollutant
  concentration at receptor site, estimate the
  contributions of different sources, source
  apportionment

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Receptor models

• CMB Chemical Mass Balance
• Factor Analysis (Multivariate methods)
• PCA Principal Component Analysis
• PMF Positive Matrix Factorization

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Chemical Mass Balance Receptor Modelling
Source 1xi1 i1,n
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Receptoryi i1,n
1
Source 3xi3 i1,n
2
Source 2xi2 i1,n
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Chemical Mass Balance Receptor Modelling

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Chemical Mass Balance Receptor Modelling

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Chemical Mass Balance Receptor Modelling Simple
Spreadsheet Implementation

• Electronic spreadsheets like Excel make it easy
  to implement the model in the above form.
• The Solver function in Excel enables the
  minimization operation.
• Graphical tools in Excel enable qualitative
  assessment of model fit and the inputs.

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Chemical Mass Balance Receptor Modelling U.S.
EPAs CMB Model

• There are uncertainties associated with both the
  receptor and source profiles. The measured
  quantities are thus
• The model results then also have uncertainties
  associated with them

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U.S. EPAs CMB Model The effective variance
method

• The CMB model uses an effective variance which
  looks at variances in both the receptor, and
  source profiles weighted by the source
  contributions

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U.S. EPAs CMB8

• The CMB model incorporates the statistics to
  improve our estimate of the source contributions
  by weighting the source and receptor profiles
  according to the uncertainties associated with
  them.
• It also reports the uncertainties associated with
  the source contribution estimates and goodness
  of fit parameters.
• Version 8 is windows based, more user friendly.
• Example Source apportionment for motor vehicle
  related VOCs in micro-environments

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VOC's Associated with Motor Vehicles
Exhaust EmissionsEvaporative Emissions
C1 - C10 RangeAlkanesAlkenesAlkynesCycloalkane
sAromatics
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Chemical Mass Balance Receptor Modelling
Source profile characterization
Fuel
Whole gasoline
Headspace vapor
Individual vehicles
Exhaust emissions - UDDS
Evaporative emissions - SHED
Fleet emission characteristics
Tunnel studies Roadside measurements
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Source Profiles
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ERMD Source Profiles with 17 species
0.45
0.4
0.35
0.3
0.25
Fraction of total
0.2
0.15
0.1
6 GA
0.05
5 LPG
4 CNG
0
3 HOTST
2 COLDST
1 FUEL
Ethylene
Ethane
Propane
n-butane
n-pentane
benzene
3m-pentane
e-benzene
o-xylene
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1994 Fleet Average Emissions with two fuels
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Modelled Species Profile
3m-pentane m-cyclopentanebenzene
cyclohexane iso-octanen-heptane toluene
n-octane e-benzenemp-xylenen-nonane1,2,4-t
m-benzene
ethylene acetylene ethane propane
isobutane isobutylenen-butane 2m-butane
n-pentane 2,3-dm-butane 2m-pentane
Fitting species
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Nose-level Ambient Sampling Schedules
Slater Street Curbside 20 Weekdays in
August-September
2 Stations, 3 Sampling Sessions Morning
730-930Noon 1130-1330Afternoon
1530-1730 (Evening 2200 - 2400)

• 3 Underground Garages
• 12 Weekdays in December-January
• 2 Stations, 2 Sampling sessions in each garage
• A.M. 730 - 930
• P.M. 1500 - 1700

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• Watson, J.D., E. Fujita, J.C. Chow, and B.
  Zielinska. 1998. Northern Front Range Air Quality
  Study Final Report., Desert Research Institute.

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Other receptor models

• CMB applies the mass balance principles to known
  receptor and source compositions to arrive at the
  source contribution estimates.
• Another type of source apportionment analyzes
  multiple measurements at the receptor (I.e. many
  hours of hourly average data) without prior
  knowledge of the sources but attempts to identify
  factors that explain the variation in the
  composition. The factors are then interpreted as
  types of sources.

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Positive Matrix Factorization, PMF
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Positive Matrix Factorization, PMF
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CMB vs PMF, pros and cons

• In CMB the required data are the source profiles,
  or fingerprints, of a list of compounds for all
  potential sources and the corresponding ambient
  measurements. CMB modelling can be done
  individually for each ambient measurement (even a
  single one!) but getting the source profiles for
  locally relevant sources requires much effort.

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CMB vs PMF, pros and cons

• In PMF, many ambient measurements are obtained
  over a long time period. Statistical analysis of
  the trends in the individual measured components
  then leads to the identification of factors"
  that explain the variation. These factors can
  then be identified with potential sources.
  Actual source profile measurements are not
  required. Instead, collecting sufficiently long
  time series data on ambient concentrations
  becomes the critical issue.

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CMB PMF Comparison

• Even a single receptor observation can be
  analyzed by CMB, assuming we have characterized
  the potential sources.
• PMF does not require that we characterize the
  potential sources but it does require sufficient
  observations to identify the potential sources.

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The SPECIATE database

• Source profiles for PM and VOC samples are
  compiled in a database (SPECIATE) which reports
  measurements from different studies.
• The profiles in this database can be extracted
  for use with CMB.