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Results: Monitored Ambient Concentration

You can view information in a table format about the 1996 annual average ambient concentrations of 32 air toxics derived from the Air Toxics Data Archive, a compendium of monitoring data from a wide variety of sources. This data was used in the model-to-monitor comparison for a subset of the 32 priority toxic pollutants.

Download an Air Toxics Monitoring Data Table
Excel Spreadsheet:
 

Variable List for Air Toxics Monitoring Data
CNTYNAME: Name of the county in which the monitor is located (e.g., Sonoma). This variable is formatted in the SAS database as a 60-character field.
FIPCNTY: Three-digit Federal Information Processing Standard (FIPS) code for the county where the monitor is located. This code is used in combination with the state FIPS code to specify a US county uniquely.
FIPSTATE: Two-digit Federal Information Processing Standard (FIPS) code for the state where the monitor is located.
MMU: Annual average of all concentration measurements, calculated as described below, using a value equal to the minimum detection limit for all measurements below the minimum detection limit.
MU: Annual average of all concentration measurements, calculated as described below, using a value equal to one-half of the minimum detection limit for all measurements below the minimum detection limit. POLL_ID: Pollutant identification code used for tracking the pollutant in the various sub- databases. This variable is identical to the compound's Chemical Abstract Service's Registry Number (CAS #), if one exists (e.g., 50000). If not, it is identical to the pollutant code from the Aeromatic Information Retrieval System (AIRS) code for the pollutant, if one exists (e.g., 43502). If the pollutant has neither a CAS # nor an AIRS pollutant code, a code was assigned for purposes of tracking the compound in the SAS database (e.g., mixture8).
PRG_NUM: Program identification code used for tracking the sampling program in the various sub-databases. For programs in the air toxics data archive that are located in a single state, the program identification code begins with the standard 2-letter abbreviation for the state (e.g., CA01). For AIRS data and for archive programs located in multiple states, the program identification code begins with the letters "US" (e.g., US01).
STNAME_C: Name of the US state where the monitor was located.
YEAR: Year during which measurements were made.
ZMU: Annual average of all concentration measurements, calculated as described below, using a value of zero for all measurements below the minimum detection limit.
_SITE_ID: A code that uniquely identifies a single monitor when used in combination with the program identification code (PRG_NUM). For sites in AIRS, this field is composed of the 5-digit state and county FIPS codes (e.g., 01001) plus the 4-digit AIRS assigned identification (e.g., 0009). This field does not include the 1-digit Priority Occurrence Code (POC).
FIPCNTY: Three-digit Federal Information Processing Standard (FIPS) code for the county where the monitor is located. This code is used in combination with the state FIPS code to uniquely specify a US county.
FIPSTATE: Two-digit Federal Information Processing Standard (FIPS) code for the state where the monitor is located.
PRG_NUM: Program identification code used for tracking the sampling program in the various sub-databases. For programs in the air toxics data archive that are located in a single state, the program identification code begins with the standard 2-letter abbreviation for the state (e.g., CA01). For AIRS data and for archive programs located in multiple states, the program identification code begins with the letters "US" (e.g., US01).
SITEADDR: Street address of monitor location (if available).
SITENAME: Text description of the site location (if available).
SITE_LAT: Estimate of geographic north latitude of the site location in decimal degrees. This information may be derived in several different ways, as indicated by the site location code (SITE_LOC), described below.
SITE_LON: Estimate of geographic east longitude of site location in decimal degrees. This information may be derived in several different ways, as indicated by the site location code (SITE_LOC), described below.
SITE_LOC: Indicates derivation of SITE_LAT and SITE_LON, as follows, in order of priority for available information.
  1. = contributor supplied coordinates
  2. = coordinates from AIRS online
  3. = coordinates derived from street address matching with US Census' Topographically Integrated Geographic Encoding and Referencing system (TIGER) files
  4. = coordinates of the city centroid from the US Census files
  5. = coordinates of the county centroid from the US Census files
  6. = coordinates estimated from a digital or paper map
  7. = insufficient information to geolocate
POLL_CAS: This variable is identical to the pollutant's Chemical Abstract Service's Registry Number (CAS #), if one exists (e.g., 50000).
POLLNAME: This variable contains the pollutant's name.
PRG_NAME: This variable contains the program name and sometimes a brief description of the program objective.

Procedure for Calculating Annual Averages
Annual averages were calculated using the following methodology.
  1. A measurement is considered below the minimum detection limit (MDL) if either it is indicated as being below the MDL (e.g., value of B888 in the data archive), or if it is specified with a numeric value that is lower than the reported MDL value for that pollutant/monitor/time combination. If there is no reported MDL, the lowest reported value for the pollutant/monitor combination is assumed to be the "plausible MDL". Measurements below the actual or plausible MDL were assigned one of 3 values depending on the averaging statistic being calculated.
    1. One-half the value of the actual or plausible MDL (MU statistic)
    2. The value of the actual or plausible MDL (MMU statistic)
    3. Zero (ZMU statistic)
  2. For each pollutant/monitor combination, an annual average was calculated stepwise from temporal averages of shorter durations, as indicated below. At each step the data set is assessed for completeness and retained for further processing only if the completeness criteria are met for the given averaging period.
    1. Daily average. A day is complete if the total number of hours monitored for that day is 18 or more (i.e., 75 % of 24 hours). For example, 18 hourly averages, 3 six-hour averages or 3 eight-hour averages will satisfy the daily completeness criteria.
    2. Quarterly average. Calendar quarters are Winter (Jan-March), Spring (April-June), Summer (July-Sept), and Fall (Oct-Dec). A calendar quarter is complete if it has 75 % or more complete days out of the expected number of daily samples for that quarter, and if there are at least 5 complete days in the quarter. To determine the expected number of daily samples, the most frequently occurring sampling interval (days from one sample to the next sample) was used; in cases of ties, the minimum sampling interval was applied.
    3. Seasonal average. The seasons are composed of 2 quarters: Winter/Fall and Spring/Summer. A season is complete is it has at least 1 complete quarter.
    4. Annual average. An annual data set is complete if it has 2 complete seasons.

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