The Air Quality System (AQS) database contains measurements of air pollutant concentrations from throughout the United States and its territories. The measurements include both criteria air pollutants and hazardous air pollutants.

The AQS Data Mart is a database that contains all of the information from the AQS system. It is a storehouse of air quality information that allows users to make queries of unlimited quantities of data. The Data Mart also includes information from the EPA?s substance and facility registry systems.

This GIS dataset contains points which depict air quality monitors within EPA's Air Quality System (AQS) monitoring network. This dataset is updated weekly to reflect the most recent changes in the monitoring network. The monitors are generally operated by State, local, and tribal air pollution control agencies using procedures specified by the U.S. EPA. These agencies collect the data, quality assure it, and then submit it to the EPA Air Quality System (AQS). The GIS dataset includes monitor information and links to download historic air quality data at each monitor.

Each daily summary file contains data for every monitor (sampled parameter) in our database for each day. This dataset shows Ozone at all monitoring locations throughout the year 2017.

The AQS Data Mart is a database containing all of the information from AQS. It has every measured value the EPA has collected via the national ambient air monitoring program. It also includes the associated aggregate values calculated by EPA (8-hour, daily, annual, etc.). The AQS Data Mart is a copy of AQS made once per week and made accessible to the public through web-based applications. The intended users of the Data Mart are air quality data analysts in the regulatory, academic, and health research communities. It is intended for those who need to download large volumes of detailed technical data stored at EPA and does not provide any interactive analytical tools. It serves as the back-end database for several Agency interactive tools that could not fully function without it: AirData, AirCompare, The Remote Sensing Information Gateway, the Map Monitoring Sites KML page, etc.

AQS must maintain constant readiness to accept data and meet high data integrity requirements, thus is limited in the number of users and queries to which it can respond. The Data Mart, as a read only copy, can allow wider access.

The most commonly requested aggregation levels of data (and key metrics in each) are:

Sample Values (2.4 billion values back as far as 1957, national consistency begins in 1980, data for 500 substances routinely collected) The sample value converted to standard units of measure (generally 1-hour averages as reported to EPA, sometimes 24-hour averages) Local Standard Time (LST) and GMT timestamps Measurement method Measurement uncertainty, where known Any exceptional events affecting the data NAAQS Averages NAAQS average values (8-hour averages for ozone and CO, 24-hour averages for PM2.5) Daily Summary Values (each monitor has the following calculated each day) Observation count Observation per cent (of expected observations) Arithmetic mean of observations Max observation and time of max AQI (air quality index) where applicable Number of observations > Standard where applicable Annual Summary Values (each monitor has the following calculated each year) Observation count and per cent Valid days Required observation count Null observation count Exceptional values count Arithmetic Mean and Standard Deviation 1st - 4th maximum (highest) observations Percentiles (99, 98, 95, 90, 75, 50) Number of observations > Standard Site and Monitor Information FIPS State Code (the first 5 items on this list make up the AQS Monitor Identifier) FIPS County Code Site Number (unique within the county) Parameter Code (what is measured) POC (Parameter Occurrence Code) to distinguish from different samplers at the same site Latitude Longitude Measurement method information Owner / operator / data-submitter information Monitoring Network to which the monitor belongs Exemptions from regulatory requirements Operational dates City and CBSA where the monitor is located Quality Assurance Information Various data fields related to the 19 different QA assessments possible

Querying BigQuery tables

You can use the BigQuery Python client library to query tables in this dataset in Kernels. Note that methods available in Kernels are limited to querying data. Tables are at bigquery-public-data.epa_historical_air_quality.[TABLENAME]. Fork this kernel to get started.

Acknowledgements

Data provided by the US Environmental Protection Agency Air Quality System Data Mart.

[Text Source: AirData Program, https://www.epa.gov/airdata/ ]

The AirData website gives you access to air quality data collected at outdoor monitors across the United States, Puerto Rico, and the U. S. Virgin Islands. The data comes primarily from the AQS (Air Quality System) database. You can choose from several ways of looking at the data:

• download data into a file (or view it on the screen)
• output the data into one of AirData’s standard reports
• create graphical displays using one of the visualization tools
• investigate monitor locations using an interactive map

AirData assists a wide range of people, from the concerned citizen who wants to know how many unhealthy air quality days there were in his county last year to air quality analysts in the regulatory, academic, and health research communities who need raw data.

Full Metadata This U.S. EPA Office of Air and Radiation (OAR) - Office of Air Quality Planning and Standards (OAQPS) web service contains the following air quality monitoring network point location layers: CO (carbon monoxide), Lead, Lead-TSP(LC) (lead, total suspended particulates, local conditions), Lead-PM10(LC) (lead, particluate matter up to 10um in size, local conditions), NO2 (nitrogen dioxide), Ozone, PM10 (particulate matter up to 10um in size), PM2.5 (particulate matter up to 2.5um in size), SO2 (sulfur dioxide), PM2.5 Chemical Speciation Network, IMPROVE (Interagency Monitoring of Protected Visual Environments), NATTS (National Air Toxics Trends Stations), NCORE (Multipollutant Monitoring Network). Layers are drawn at all scales. Security classification: Public. Access constraints: None. Use constraints: None. Please check sources, scale, accuracy, currency and other available information. Please confirm that you are using the most recent copy of both data and metadata. Acknowledgement of the EPA would be appreciated.

AQS data is a publicly available dataset, which is part of this study. This data can be found on EPA website https://aqs.epa.gov/aqsweb/airdata/download_files.html (accessed on 1 April 2023). PA data is a 3rd party data and restrictions apply to the availability of these data. Data was obtained from Purple Air and are available from PurpleAir API https://community.purpleair.com/t/making-api-calls-with-the-purpleair-api/180 (accessed on 1 April 2023) with the permission of Purple Air. HMS smoke plume data is publicly available and can be downloaded at Office of Satellite and Product Operations website https://www.ospo.noaa.gov (accessed on 1 April 2023). The codes to download and analyze data in this paper is available at this GitHub repo https://github.com/hyang199723/PAFusion (uploaded on 30 June 2023). This dataset is associated with the following publication: Yang, H., S. Ruiz-Suarez, B. Reich, Y. Guan, and A. Rappold. A data fusion approach to assessing the contribution of wildland fire smoke to fine particulate matter in California. Remote Sensing. MDPI, Basel, SWITZERLAND, 15(17): 1, (2023).

The Environmental Protection Agency (EPA) provides air pollution data about ozone and particulate matter (PM2.5) to CDC for the Tracking Network. The EPA maintains a database called the Air Quality System (AQS) which contains data from approximately 4,000 monitoring stations around the country, mainly in urban areas. Data from the AQS is considered the "gold standard" for determining outdoor air pollution. However, AQS data are limited because the monitoring stations are usually in urban areas or cities and because they only take air samples for some air pollutants every three days or during times of the year when air pollution is very high. CDC and EPA have worked together to develop a statistical model (Downscaler) to make modeled predictions available for environmental public health tracking purposes in areas of the country that do not have monitors and to fill in the time gaps when monitors may not be recording data. This data does not include "Percent of population in counties exceeding NAAQS (vs. population in counties that either meet the standard or do not monitor PM2.5)". Please visit the Tracking homepage for this information.View additional information for indicator definitions and documentation by selecting Content Area "Air Quality" and the respective indicator at the following website: http://ephtracking.cdc.gov/showIndicatorsData.action

This EPA GeoPlatform Online web map provides foundational map layers for the EPA AirData Air Quality Monitors web mapping application (https://epa.maps.arcgis.com/apps/webappviewer/index.html?id=5f239fd3e72f424f98ef3d5def547eb5).This web map contains points which depict air quality monitors within EPA's Air Quality System (AQS) monitoring network. The layers are updated weekly to reflect the most recent changes in the monitoring network. The monitors are generally operated by State, local, and tribal air pollution control agencies using procedures specified by the U.S. EPA. These agencies collect the data, quality assure it, and then submit it to the EPA Air Quality System (AQS). The layers include monitor information and links to download historic air quality data at each monitor.Layers in this web map show active and inactive monitors from these monitoring networks:CO - ActiveCO - InactiveLead - ActiveLead - InactiveLead - TSP(LC) - ActiveLead - TSP(LC) - InactiveLead - PM10(LC) - ActiveLead - PM10(LC) - InactiveNO2 - ActiveNO2 - InactiveOzone - ActiveOzone - InactivePM10 - ActivePM10 - InactivePM2.5 - NAAQS/AQI - ActivePM2.5 - NAAQS/AQI - InactivePM2.5 - Additional AQI - ActivePM2.5 - Additional AQI - InactiveSO2 - ActiveSO2 - InactivePM2.5 Chemical Speciation Network - ActivePM2.5 Chemical Speciation Network - InactiveIMPROVE (Interagency Monitoring of Protected Visual Environments) - ActiveIMPROVE (Interagency Monitoring of Protected Visual Environments) - InactiveNATTS (National Air Toxics Trends Stations) - ActiveNATTS (National Air Toxics Trends Stations) - InactiveNCORE (Multipollutant Monitoring Network) - ActiveNCORE (Multipollutant Monitoring Network) - InactiveNear Road - ActiveNear Road - InactivePAMS - ActivePAMS - InactiveAdditional layers are included to provide context:Nonattainment Areas:Lead, 2008Ozone, 2008Ozone, 1997PM10, 1987PM2.5, 2012PM2.5, 2006PM2.5, 1997SO2, 2010American Indian Reservations and Off-Reservation Trust LandsClass 1 areas under the Clean Air Act

The average of N100 which is the sum of hours over 100 ppb in a given month and captures peak events of high exposure or acute exposure. Updated through 2018. Data used are sourced from the EPA's Air Quality System Data Mart: https://aqs.epa.gov/aqsweb/airdata/download_files.html