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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
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.
Data provided by the US Environmental Protection Agency Air Quality System Data Mart.
https://data.gov.tw/licensehttps://data.gov.tw/license
Provide the air quality index (AQI) for each station per hour.
This indicator shows how many days per year were assessed to have air quality that was worse than “moderate” in Champaign County, according to the U.S. Environmental Protection Agency’s (U.S. EPA) Air Quality Index Reports. The period of analysis is 1980-2023, and the U.S. EPA’s air quality ratings analyzed here are as follows, from best to worst: “good,” “moderate,” “unhealthy for sensitive groups,” “unhealthy,” “very unhealthy,” and "hazardous."[1]
In 2023, the number of days rated to have air quality worse than moderate was the highest in the 21st century at 13. This is likely due to the air pollution created by the unprecedented Canadian wildfire smoke in Summer 2023.
While there has been no consistent year-to-year trend in the number of days per year rated to have air quality worse than moderate, the number of days in peak years had decreased from 2000 through 2022. Where peak years before 2000 had between one and two dozen days with air quality worse than moderate (e.g., 1983, 18 days; 1988, 23 days; 1994, 17 days; 1999, 24 days), the year with the greatest number of days with air quality worse than moderate from 2000-2022 was 2002, with 10 days. There were several years between 2006 and 2022 that had no days with air quality worse than moderate.
This data is sourced from the U.S. EPA’s Air Quality Index Reports. The reports are released annually, and our period of analysis is 1980-2023. The Air Quality Index Report websites does caution that "[a]ir pollution levels measured at a particular monitoring site are not necessarily representative of the air quality for an entire county or urban area," and recommends that data users do not compare air quality between different locations[2].
[1] Environmental Protection Agency. (1980-2023). Air Quality Index Reports. (Accessed 4 June 2024).
[2] Ibid.
Source: Environmental Protection Agency. (1980-2023). Air Quality Index Reports. https://www.epa.gov/outdoor-air-quality-data/air-quality-index-report. (Accessed 4 June 2024).
In 2021, the French ATMO index calculated at the air quality monitoring station located in the 4th arrondissement in Paris reported an average air quality for 77 percent of the days of the year. The fact that the air quality seems to have worsened between 2020 and 2021 is an effect of the introduction of the new ATMO index. In reality, France's air quality has been improving in the last decade.
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This dataset contains quality assured and DOEE-certified air quality data collected from the District’s five air monitoring network sites. The dataset covers a three-year period and includes hourly concentration data points from the Environmental Protection Agency (EPA)’s criteria pollutants, air toxics, and speciation. It also includes hourly surface meteorology data points.
In 2023, the air quality index in Indonesia reached 88.67, which means that the air quality is acceptable. However, there may be a risk for some people, particularly those who are unusually sensitive to air pollution. Among all provinces in the country, Jakarta had the poorest air quality index that stood at 68.46. Over the last two decades, Indonesia's air quality has significantly changed, from 1998 to 2016, the country went from being one of the cleaner countries in the world to one of the twenty most polluted.
https://data.gov.tw/licensehttps://data.gov.tw/license
The Air Quality Index (AQI) for each monitoring station is provided hourly. The original data version is announced on the Air Quality Monitoring Network website https://airtw.moenv.gov.tw
Dataset contains information on New York City air quality surveillance data. Air pollution is one of the most important environmental threats to urban populations and while all people are exposed, pollutant emissions, levels of exposure, and population vulnerability vary across neighborhoods. Exposures to common air pollutants have been linked to respiratory and cardiovascular diseases, cancers, and premature deaths. These indicators provide a perspective across time and NYC geographies to better characterize air quality and health in NYC. Data can also be explored online at the Environment and Health Data Portal: http://nyc.gov/health/environmentdata.
New Delhi was the most polluted city in India in 2024, based on an average air quality index (AQI) of 169. The seven most polluted cities in India in 2024 all had AQI levels above 150. An AQI between 151 and 200 is classified as unhealthy. Air pollution in India India was the third most polluted country in the world in 2023, behind only Bangladesh and Pakistan. The South Asian country recorded an average annual fine particulate matter (PM2.5) concentration of 54 micrograms per cubic meter of air (µg/m3) that year, more than 10 times above the World Health Organization’s recommended limit. Health effects of air pollution Exposure to air pollution can lead to a range of health issues, such as strokes, respiratory conditions, and cardiovascular disease. Air pollution is attributable to millions of premature deaths every year around the world, with India one of the most affected countries.
The City of Montreal measures air quality in the form of a numerical value called the “Air Quality Index (AQI).” This data set provides access to daily AQI values, updated every hour, approximately 50 minutes after the hour. For example, the 13:00 data is available around 13:50, for all three resources. Note: The AQI systems don't change the time: they always use Eastern Standard Time (EST) and not Eastern Daylight Time (EDT). Thus, in the example above, around 13:50 EDT, the most recent data available will be from 12:00 EDT. Historical values, updated daily, are available here. The station list and sectors linked to RSQA data are also available.
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OpenAQ has collected 231,965,688 air quality measurements from 8,469 locations in 65 countries. Data are aggregated from 105 government level and research-grade sources. https://medium.com/@openaq/where-does-openaq-data-come-from-a5cf9f3a5c85 Note: this dataset is temporary not updated. We're currently working to update it as soon as possible.Disclaimers:- Some records contain encoding issues on specific characters; those issues are present in the raw API data and were not corrected.- Some dates are set in the future: those issues also come from the original data and were not corrected.
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The Air Quality Health Index (AQHI) is a scale designed to help quantify the quality of the air in a certain region on a scale from 1 to 10. When the amount of air pollution is very high, the number is reported as 10+. It also includes a category that describes the health risk associated with the index reading (e.g. Low, Moderate, High, or Very High Health Risk). The AQHI is calculated based on the relative risks of a combination of common air pollutants that are known to harm human health, including ground-level ozone, particulate matter, and nitrogen dioxide. The AQHI formulation captures only the short term or acute health risk (exposure of hour or days at a maximum). The formulation of the AQHI may change over time to reflect new understanding associated with air pollution health effects. The AQHI is calculated from data observed in real time, without being verified (quality control).
In 2015, zero percent of the days in the year was recorded to be in the unhealthy range. Air quality in 2013 and 2015 was affected by transboundary smoke haze from land and forest fires. Singapore also experienced a full-year of good and moderate air quality (in terms of PSI) in the years 2007, 2008, 2018 and 2020.
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Air Quality Index: Nakhon Pathom: Mueang Nakhon Pathom District: PM2.5: High data was reported at 34.000 mcg/Cub m in 15 Mar 2025. This records an increase from the previous number of 33.000 mcg/Cub m for 14 Mar 2025. Air Quality Index: Nakhon Pathom: Mueang Nakhon Pathom District: PM2.5: High data is updated daily, averaging 33.000 mcg/Cub m from Oct 2020 (Median) to 15 Mar 2025, with 1619 observations. The data reached an all-time high of 147.000 mcg/Cub m in 08 Jan 2025 and a record low of 7.000 mcg/Cub m in 08 Aug 2022. Air Quality Index: Nakhon Pathom: Mueang Nakhon Pathom District: PM2.5: High data remains active status in CEIC and is reported by Air Quality and Noise Management Bureau. The data is categorized under Global Database’s Thailand – Table TH.ESG.E001: Air Quality Index. [COVID-19-IMPACT]
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Air quality data is collected from the Allegheny County Health Department monitors throughout the county. This data must be verified by qualified individuals before it can be considered official. The following data is unverified. This means that any electrical disruption or equipment malfunction can report erroneous monitored data.
For more information about the Health Department's Air Quality Program or to view a live version of the dashboard, please visit the ACHD website: https://alleghenycounty.us/Health-Department/Programs/Air-Quality/Air-Quality.aspx
Support for Health Equity datasets and tools provided by Amazon Web Services (AWS) through their Health Equity Initiative.
As of February 2025, the average monthly air quality index in Shanghai stood at 34, within the “Good” category, as one of the months with better air quality compared to earlier of the year. Air Pollution in Shanghai Shanghai was doing relatively better than Beijing in terms of air quality, despite with a higher population than Beijing. The Ministry of ecology and environment has stated in 2015 that the main source of air pollution in Shanghai was dust, mobile sources and industrial production, as opposed to motorized vehicles in Beijing, Shenzhen and Guangzhou. What can be done about poor air quality in China? In recent years, air pollution had gradually become the top environmental concern to Chinese citizens. With the emergence of the public’s health concerns, the Chinese government also introduced plans to ease the air pollution, including setting a target for fine particulate matter, the completion of construction and renovation of pollution control facilities, introducing vehicle control, and renewing the fleet of public buses. Since 2001, China has invested over one percent of GDP annually on pollution control.
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Air Quality Index: Northern Thailand: Chiang Rai: Wiang, Muang,: PM2.5: High data was reported at 98.000 mcg/Cub m in 15 Mar 2025. This records an increase from the previous number of 57.000 mcg/Cub m for 14 Mar 2025. Air Quality Index: Northern Thailand: Chiang Rai: Wiang, Muang,: PM2.5: High data is updated daily, averaging 20.000 mcg/Cub m from Mar 2024 (Median) to 15 Mar 2025, with 363 observations. The data reached an all-time high of 275.000 mcg/Cub m in 05 May 2024 and a record low of 6.000 mcg/Cub m in 21 Jul 2024. Air Quality Index: Northern Thailand: Chiang Rai: Wiang, Muang,: PM2.5: High data remains active status in CEIC and is reported by Air Quality and Noise Management Bureau. The data is categorized under Global Database’s Thailand – Table TH.ESG.E001: Air Quality Index.
According to the monitoring data from the Embassy of the United States, there was on average 39 micrograms of PM2.5 particles per cubic meter to be found in the air in Beijing during 2023. The air quality has improved considerably since 2013.
Reasons for air pollution in Beijing
China’s capital city Beijing is one of the most populous cities in China with over 20 million inhabitants. Over the past 20 years, Beijing’s GDP has increased tenfold. With the significant growth of vehicles and energy consumption in the country, Beijing’s air quality is under great pressure from the economic development. In the past, the city had a high level of coal consumption. Especially in winter, in which coal consumption increased due to heating, the air quality could get extremely bad on the days without wind. In spring, the wind from the north would bring sand from Mongolian deserts, resulting in severe sandstorms in Beijing. The bad air quality also affected the air visibility and threatened people’s health. On days with very bad air quality, people wearing masks for protection can be seen on the streets in the city.
Methods to improve air quality in Beijing
Over the past years, the government has implemented various methods to improve the air quality in Northern China. Sandstorms, which were quite common 15 years ago, are now rarely seen in Beijing’s spring thanks to afforestation projects on China’s northern borders. The license-plate lottery system was introduced in Beijing to restrict the growth of private vehicles. Large trucks were not allowed to enter certain areas in Beijing. Above all, the coal consumption in Beijing has been restricted by shutting down industrial sites and improving heating systems. Beijing’s efforts to improve air quality has also been highly praised by the UN as a successful model for other cities. However, there is also criticism pointing out that the improvement of Beijing’s air quality is based on the sacrifice of surrounding provinces (including Hebei), as many factories were moved from Beijing to other regions. Besides air pollution, there are other environmental problems like water pollution that China is facing. The industrial transformation is the key to China’s environmental improvement.
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Air Quality Index: Northern Thailand: Chiang Mai: Chaem Chang Keng, Mae Chaem: PM2.5: Low data was reported at 6.000 mcg/Cub m in 15 Mar 2025. This records an increase from the previous number of 3.000 mcg/Cub m for 14 Mar 2025. Air Quality Index: Northern Thailand: Chiang Mai: Chaem Chang Keng, Mae Chaem: PM2.5: Low data is updated daily, averaging 11.000 mcg/Cub m from Mar 2024 (Median) to 15 Mar 2025, with 232 observations. The data reached an all-time high of 65.000 mcg/Cub m in 07 Apr 2024 and a record low of 1.000 mcg/Cub m in 01 Jul 2024. Air Quality Index: Northern Thailand: Chiang Mai: Chaem Chang Keng, Mae Chaem: PM2.5: Low data remains active status in CEIC and is reported by Air Quality and Noise Management Bureau. The data is categorized under Global Database’s Thailand – Table TH.ESG.E001: Air Quality Index.
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Air Quality Index: Northern Thailand: Chiang Mai: Chang Phueak, Muang: PM2.5: Avg data was reported at 63.540 mcg/Cub m in 15 Mar 2025. This records an increase from the previous number of 39.040 mcg/Cub m for 14 Mar 2025. Air Quality Index: Northern Thailand: Chiang Mai: Chang Phueak, Muang: PM2.5: Avg data is updated daily, averaging 21.000 mcg/Cub m from Jul 2016 (Median) to 15 Mar 2025, with 3003 observations. The data reached an all-time high of 228.000 mcg/Cub m in 23 Mar 2019 and a record low of 5.000 mcg/Cub m in 17 May 2017. Air Quality Index: Northern Thailand: Chiang Mai: Chang Phueak, Muang: PM2.5: Avg data remains active status in CEIC and is reported by Air Quality and Noise Management Bureau. The data is categorized under Global Database’s Thailand – Table TH.ESG.E001: Air Quality Index.
https://creativecommons.org/publicdomain/zero/1.0/https://creativecommons.org/publicdomain/zero/1.0/
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
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.
Data provided by the US Environmental Protection Agency Air Quality System Data Mart.