THIS DATA ASSET NO LONGER ACTIVE: This is metadata documentation for the Region 7 Air Compliance Complaint Database (ACCD) which logs all air pollution complaints received by Region 7. It contains information about the complaint along with how the complaint was addressed. The Air and Waste Management Division is the primary managing entity for this database. This work falls under objectives for EPA's 2003-2008 Strategic Plan (Goal 1) for Clean Air & Global Climate Change, which are to achieve healthier outdoor air.

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 csv file provides air pollution data information for Florida and Districts for 2017, 2018, 2019 and 2020. Through the FDOT Source Book Special Edition 2020 report, users can drill down the air pollution data at the statewide and District level. The report's link is: https://sourcebook-2020-se-fdot.hub.arcgis.com/Florida remains within acceptable EPA standards for ozone concentration and fine particulate matter (PM 2.5).Data source: Environmental Protection Agency (EPA) Air Data. For any additional information, please contact the Forecasting and Trends Office (FTO) at 850-414-5396.

The NCAR Upper Air Database (UADB) contains global observations beginning in the 1920s and extends to a near current date. Upper air soundings from about 50 different sources have been consolidated into products that are well documented and provide the longest possible, duplicate-free, station time series. Historical sampling methods have been accounted for by creating two product lines, one with soundings that have wind (UADB-Wind) and another with temperature and humidity (UADB-TRH) measurements. This approach maximizes the amount of data consolidated, and when profiles have simultaneous temperature, humidity, and wind measurements, they are replicated in both products. The first consolidation step was compositing stations with identical WMO station numbers across all data sources. The UADB-TRH product has nearly 1100 stations that report for 20 years or more, and over 400 stations have time series of 50 years or longer. The UADB-Wind product has about 1600 stations that report for 20 years or more, and over 500 stations have soundings for at least 50 years. Next stations with different WMO station numbers, but that are located at identical latitudes and longitudes, or nearly so (within 40 kilometers) were combined, accounting for WMO station number changes and small position relocations. The result is that even longer station time series are created; extensions occur at over 240 and 250 locations in the UADB-TRH and UADB-Wind products, respectively. The composited and combined products are both available.

The Historical Ambient Air Quality Data Inventory contains measured and estimated data on ambient air pollution for use in assessing air quality, assisting in designating attainment/non-attainment areas, evaluating state implementation plans for non-attainment areas, performing modeling for permit review analysis, and other air quality functionsThe statutory authority leading to the collection of this information comes from Title I, Part A of the Clean Air Act. Sustance classes include Criteria Air Pollutants, Hazardous Air Pollutants, and Greenhouse Gases. Data no longer collected, current Ambient Air Quality Data Inventory uses higher geographic density and more robust methods of measurement.

Based on the latest meteorological and air quality modeling data from the Environmental Protection Department, air quality forecasts for the island and outlying islands are provided three times a day. The department issues air quality forecasts at 10:30, 16:30, and 22:00 daily, with updates every half an hour as the forecast operations are adjusted.

This United States Environmental Protection Agency (US EPA) feature layer represents site data, updated hourly concentrations and Air Quality Index (AQI) values for the last 24 hours received from each monitoring site that reports to AirNow. NOTE: Time Animation is enabled by default on this layer.Map and forecast data are collected using federal reference or equivalent monitoring techniques or techniques approved by the state, local or tribal monitoring agencies. To maintain "real-time" maps, the data are displayed after the end of each hour. Although preliminary data quality assessments are performed, the data in AirNow are not fully verified and validated through the quality assurance procedures monitoring organizations used to officially submit and certify data on the EPA Air Quality System (AQS).This data sharing, and centralization creates a one-stop source for real-time and forecast air quality data. The benefits include quality control, national reporting consistency, access to automated mapping methods, and data distribution to the public and other data systems. The U.S. Environmental Protection Agency, National Oceanic and Atmospheric Administration, National Park Service, tribal, state, and local agencies developed the AirNow system to provide the public with easy access to national air quality information. State and local agencies report the Air Quality Index (AQI) for cities across the US and parts of Canada and Mexico. AirNow data are used only to report the AQI, not to formulate or support regulation, guidance or any other EPA decision or position.About the AQIThe Air Quality Index (AQI) is an index for reporting daily air quality. It tells you how clean or polluted your air is, and what associated health effects might be a concern for you. The AQI focuses on health effects you may experience within a few hours or days after breathing polluted air. EPA calculates the AQI for five major air pollutants regulated by the Clean Air Act: ground-level ozone, particle pollution (also known as particulate matter), carbon monoxide, sulfur dioxide, and nitrogen dioxide. For each of these pollutants, EPA has established national air quality standards to protect public health. Ground-level ozone and airborne particles (often referred to as "particulate matter") are the two pollutants that pose the greatest threat to human health in this country.A number of factors influence ozone formation, including emissions from cars, trucks, buses, power plants, and industries, along with weather conditions. Weather is especially favorable for ozone formation when it’s hot, dry and sunny, and winds are calm and light. Federal and state regulations, including regulations for power plants, vehicles and fuels, are helping reduce ozone pollution nationwide.Fine particle pollution (or "particulate matter") can be emitted directly from cars, trucks, buses, power plants and industries, along with wildfires and woodstoves. But it also forms from chemical reactions of other pollutants in the air. Particle pollution can be high at different times of year, depending on where you live. In some areas, for example, colder winters can lead to increased particle pollution emissions from woodstove use, and stagnant weather conditions with calm and light winds can trap PM2.5 pollution near emission sources. Federal and state rules are helping reduce fine particle pollution, including clean diesel rules for vehicles and fuels, and rules to reduce pollution from power plants, industries, locomotives, and marine vessels, among others.How Does the AQI Work?Think of the AQI as a yardstick that runs from 0 to 500. The higher the AQI value, the greater the level of air pollution and the greater the health concern. For example, an AQI value of 50 represents good air quality with little potential to affect public health, while an AQI value over 300 represents hazardous air quality.An AQI value of 100 generally corresponds to the national air quality standard for the pollutant, which is the level EPA has set to protect public health. AQI values below 100 are generally thought of as satisfactory. When AQI values are above 100, air quality is considered to be unhealthy-at first for certain sensitive groups of people, then for everyone as AQI values get higher.Understanding the AQIThe purpose of the AQI is to help you understand what local air quality means to your health. To make it easier to understand, the AQI is divided into six categories:Air Quality Index(AQI) ValuesLevels of Health ConcernColorsWhen the AQI is in this range:..air quality conditions are:...as symbolized by this color:0 to 50GoodGreen51 to 100ModerateYellow101 to 150Unhealthy for Sensitive GroupsOrange151 to 200UnhealthyRed201 to 300Very UnhealthyPurple301 to 500HazardousMaroonNote: Values above 500 are considered Beyond the AQI. Follow recommendations for the Hazardous category. Additional information on reducing exposure to extremely high levels of particle pollution is available here.Each category corresponds to a different level of health concern. The six levels of health concern and what they mean are:"Good" AQI is 0 to 50. Air quality is considered satisfactory, and air pollution poses little or no risk."Moderate" AQI is 51 to 100. Air quality is acceptable; however, for some pollutants there may be a moderate health concern for a very small number of people. For example, people who are unusually sensitive to ozone may experience respiratory symptoms."Unhealthy for Sensitive Groups" AQI is 101 to 150. Although general public is not likely to be affected at this AQI range, people with lung disease, older adults and children are at a greater risk from exposure to ozone, whereas persons with heart and lung disease, older adults and children are at greater risk from the presence of particles in the air."Unhealthy" AQI is 151 to 200. Everyone may begin to experience some adverse health effects, and members of the sensitive groups may experience more serious effects."Very Unhealthy" AQI is 201 to 300. This would trigger a health alert signifying that everyone may experience more serious health effects."Hazardous" AQI greater than 300. This would trigger a health warnings of emergency conditions. The entire population is more likely to be affected.AQI colorsEPA has assigned a specific color to each AQI category to make it easier for people to understand quickly whether air pollution is reaching unhealthy levels in their communities. For example, the color orange means that conditions are "unhealthy for sensitive groups," while red means that conditions may be "unhealthy for everyone," and so on.Air Quality Index Levels of Health ConcernNumericalValueMeaningGood0 to 50Air quality is considered satisfactory, and air pollution poses little or no risk.Moderate51 to 100Air quality is acceptable; however, for some pollutants there may be a moderate health concern for a very small number of people who are unusually sensitive to air pollution.Unhealthy for Sensitive Groups101 to 150Members of sensitive groups may experience health effects. The general public is not likely to be affected.Unhealthy151 to 200Everyone may begin to experience health effects; members of sensitive groups may experience more serious health effects.Very Unhealthy201 to 300Health alert: everyone may experience more serious health effects.Hazardous301 to 500Health warnings of emergency conditions. The entire population is more likely to be affected.Note: Values above 500 are considered Beyond the AQI. Follow recommendations for the "Hazardous category." Additional information on reducing exposure to extremely high levels of particle pollution is available here.

Air Quality: Particulate Concentration (PM10): Daily Average: Palangkaraya data was reported at 6.510 mcg/Cub m in 25 Sep 2022. This records an increase from the previous number of 5.174 mcg/Cub m for 24 Sep 2022. Air Quality: Particulate Concentration (PM10): Daily Average: Palangkaraya data is updated daily, averaging 6.765 mcg/Cub m from Nov 2020 (Median) to 25 Sep 2022, with 255 observations. The data reached an all-time high of 30.578 mcg/Cub m in 08 Dec 2020 and a record low of 0.144 mcg/Cub m in 21 Sep 2021. Air Quality: Particulate Concentration (PM10): Daily Average: Palangkaraya data remains active status in CEIC and is reported by Meteorological, Climatological, and Geophysical Agency. The data is categorized under High Frequency Database’s COVID-19 Economic Impact Monitor – Table ID.EVA001: Air Quality Statistics. [COVID-19-IMPACT]

AQI: Connecticut: Hartford-West Hartford-East Hartford: PM2.5 data was reported at 51.000 Index in 16 May 2025. This records an increase from the previous number of 35.000 Index for 15 May 2025. AQI: Connecticut: Hartford-West Hartford-East Hartford: PM2.5 data is updated daily, averaging 31.000 Index from Jan 1999 (Median) to 16 May 2025, with 9156 observations. The data reached an all-time high of 166.000 Index in 07 Jun 2023 and a record low of 0.000 Index in 13 Jul 2017. AQI: Connecticut: Hartford-West Hartford-East Hartford: PM2.5 data remains active status in CEIC and is reported by United States Environmental Protection Agency. The data is categorized under Global Database’s United States – Table US.ESG.E: Air Quality Index and Air Pollutants. [COVID-19-IMPACT]

AQI: California: Riverside-San Bernardino-Ontario data was reported at 100.000 Index in 16 May 2025. This records an increase from the previous number of 97.000 Index for 15 May 2025. AQI: California: Riverside-San Bernardino-Ontario data is updated daily, averaging 91.000 Index from Jan 1980 (Median) to 16 May 2025, with 16573 observations. The data reached an all-time high of 1,564.000 Index in 28 May 2022 and a record low of 35.000 Index in 15 Mar 2023. AQI: California: Riverside-San Bernardino-Ontario data remains active status in CEIC and is reported by United States Environmental Protection Agency. The data is categorized under Global Database’s United States – Table US.ESG.E: Air Quality Index and Air Pollutants. [COVID-19-IMPACT]

AQI: Connecticut: Hartford-West Hartford-East Hartford: Ozone data was reported at 61.000 Index in 16 May 2025. This records an increase from the previous number of 32.000 Index for 15 May 2025. AQI: Connecticut: Hartford-West Hartford-East Hartford: Ozone data is updated daily, averaging 36.000 Index from Jan 1980 (Median) to 16 May 2025, with 11805 observations. The data reached an all-time high of 187.000 Index in 22 Jul 2016 and a record low of 1.000 Index in 03 Jan 2023. AQI: Connecticut: Hartford-West Hartford-East Hartford: Ozone data remains active status in CEIC and is reported by United States Environmental Protection Agency. The data is categorized under Global Database’s United States – Table US.ESG.E: Air Quality Index and Air Pollutants. [COVID-19-IMPACT]

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

The BOREAS AFM-05 team collected and processed data from the numerous radiosonde flights during the project. The goals of the AFM-05 team were to provide large scale definition of the atmosphere by supplementing the existing AES aerological network, both temporally and spatially. This data set includes basic upper-air parameters collected from the network of upper-air stations during the 1993, 1994, and 1996 field campaigns over the entire study region.

This is a PBL module on Air Pollution to be used in an introductory environmental science course to motivate students to analyze related environmental justice issues.Original data was from the US EPA data on "State EJScreen Data at the Block Group Level" (EJSCREEN_2023_BG_StatePct_with_AS_CNMI_GU_VI.csv) which was downloaded from https://www.epa.gov/ejscreen/download-ejscreen-data on December 20, 2023. (Note: Access to the EJSCREEN tool was removed during February 2005).This data was processed and cleaned as described in the data provenance document.Lecture Slides, Activity Sheets and Instructor Notes are available here.The following files are included:Data Provenance and Data Dictionary: Data Provenance and Data Dictionary.pdfR Script for Data Processing: EJSCREEN_Data_Curation_NC_Summarized_by_County.RProcessed Dataset for North Carolina: EJScreen_State_BGLevel_NC_13Columns.csvCurated Data used in the Module - Summarized Dataset for North Carolina (summarized by county): EJScreen_State_BGLevel_NC_Summarized_By_County_13Columns.csvData Dictionary: Data_Dictionary_EJSCREEN_2023_BG_Columns.pdfOriginal Dataset from EPA/EJSCREEN from which Data was Extracted for North Carolina: DS4EJ_EJSCREEN_2023_BG_StatePct_with_AS_CNMI_GU_VI.csv

Aerospace Air Data System Market Outlook

The global Aerospace Air Data System market is poised for significant growth, with an estimated market size of USD 3.5 billion in 2023 and a projected value of USD 5.8 billion by 2032, reflecting a compound annual growth rate (CAGR) of 5.5% over the forecast period. This growth is primarily driven by technological advancements and the increasing demand for more efficient and reliable air data systems in both commercial and military aviation sectors. The integration of advanced systems that facilitate accurate and real-time data collection and processing is becoming indispensable in modern aircraft, which plays a critical role in ensuring flight safety, optimizing fuel consumption, and enhancing overall operational efficiency.

The aerospace industry is witnessing a paradigm shift towards digitalization and automation, which acts as a significant growth driver for the air data system market. The increasing complexity of aircraft systems necessitates the adoption of sophisticated air data systems that can integrate seamlessly with other avionics systems to provide comprehensive and accurate flight information. This drive is further fueled by stringent regulatory requirements aimed at enhancing flight safety and operational efficiency, prompting companies to invest steadily in the development and deployment of advanced air data systems. Moreover, the trend towards reducing the carbon footprint of aviation activities has led to a greater focus on systems that optimize fuel efficiency, further propelling the demand in this sector.

The burgeoning demand for unmanned aerial vehicles (UAVs) in various applications ranging from military operations to commercial uses like agricultural monitoring and delivery services is also contributing significantly to market growth. UAVs, given their diverse operational environments, require precise air data systems to navigate effectively and safely. This has led to increased investments in research and development from companies aiming to enhance the performance and reliability of air data systems in UAVs, thus opening new avenues for growth in the aerospace air data system market.

Another pivotal factor propelling the market forward is the continuous modernization of existing aircraft fleets. Airlines and defense forces worldwide are striving to upgrade their fleets with more advanced and fuel-efficient aircraft. This modernization wave is driving the demand for state-of-the-art air data systems that offer improved reliability and performance. Furthermore, the aftermarket segment is experiencing robust growth as airlines and military organizations look to retrofit their current fleets with the latest technologies to extend their operational life and improve efficiency.

Regionally, the aerospace air data system market is witnessing diverse trends. North America currently dominates the market, driven by the presence of major aerospace companies and significant military aviation activities. However, the Asia Pacific region is expected to exhibit the fastest growth rate during the forecast period, fueled by increasing investments in military aviation and the expansion of commercial aviation in countries like China and India. These dynamics highlight the evolving landscape of the aerospace air data system market across different regions.

Component Analysis

The component segment of the aerospace air data system market is critical, comprising sensors, probes, transducers, and others. Sensors are the most vital components, responsible for the accurate measurement of critical data such as airspeed, altitude, and pressure. The increasing demand for high-precision and reliable sensors is a key growth driver in this segment. As aircraft systems become more sophisticated, there is a corresponding need for sensors that can deliver real-time, accurate data to support complex avionics systems. This demand is particularly strong in military aviation, where high-stakes operations demand the utmost accuracy in data measurement.

Probes are another essential component, designed to capture aerodynamic data that is crucial for the aircraft's performance and safety. With advancements in probe technology, there is an ongoing trend towards developing probes that can withstand extreme environmental conditions while maintaining high accuracy and reliability. This is particularly important for military and commercial aviation, where aircraft are often exposed to harsh climates and varying weather conditions. The evolution of probe technology is, thus, a central focus for companies looking to enhance their product offer

This dataset provides a summary of annual air pollution statistics from 1995 to the current available year for six air pollutants:

• Carbon Monoxide
• Oxides of Nitrogen (NO, NO2, NOx)
• Ozone
• Fine Particulate Matter (PM2.5)
• Sulphur Dioxide
• Total Reduced Sulphur

The annual statistics include percentiles, mean, maximums and also indicate the number of times an air monitoring station exceeded an Ontario annual ambient air quality criteria, where applicable. This information is also available in the annual Air Quality in Ontario Reports. The hourly air pollutant concentration data is posted in near real time on the Air Quality Ontario website: http://www.airqualityontario.com/

GNS Science air particulate matter (APM) research helps improves air quality and health outcomes in New Zealand. We aim to identify where air particulate pollution is coming from, so regional councils can work out ways to stop it. Our science supports better air quality monitoring, management and reduction.

Since 1998 GNS Science has analysed over 40,000 air samples collected from monitoring stations across New Zealand and around the world. GNS Science is the New Zealand representative on the International Atomic Energy Agencies (IAEA) Regional Cooperation Agreement air monitoring programme for Australasia and South East Asia.

DOI: https://doi.org/10.21420/R58Q-FZ78

Cite dataset as: GNS Science. (2020). National Air Particulate Speciation Database [Data set]. GNS Science. https://doi.org/10.21420/R58Q-FZ78

Abstract

To provide annual PM2.5 component concentration data for the contiguous U.S. at resolutions of 50m in urban areas and 1km in non-urban areas for public health research to estimate effects on human health, and for other related research.

Methodology

The Annual Mean PM2.5 Components (EC, NH4, NO3, OC, SO4) 50m Urban and 1km Non-Urban Area Grids for Contiguous U.S., 2000-2019, v1 data set contains annual predictions of the chemical concentrations at a hyper resolution (50m x 50m grid cells) in urban areas and at a high resolution (1km x 1km grid cells) in non-urban areas for the years 2000 to 2019. Particulate matter with an aerodynamic diameter less than 2.5 µm (PM2.5) increases mortality and morbidity. PM2.5 is composed of a mixture of chemical components that vary across space and time. Due to limited hyperlocal data availability, less is known about health risks of PM2.5 components, their U.S.-wide exposure disparities, or which species are driving the biggest intra-urban changes in PM2.5 mass. The national super-learned models were developed across the U.S. for hyperlocal estimation of annual mean elemental carbon, ammonium, nitrate, organic carbon, and sulfate concentrations across 3,535 urban areas at a 50m spatial resolution, and at a 1km resolution for non-urban areas from 2000 to 2019. Using Machine-Learning models (ML), combined with either a Generalized Additive Model (GAM) Ensemble Geographically-Weighted-Averaging (GAM-ENWA) or Super-Learning (SL) and approximately 82 billion predictions across 20 years, hyperlocal super-learned PM2.5 components are now available for further research. The overall R-squared values of 10-fold cross validated models ranged from 0.910 to 0.970 on the training sets for these components, while on the test sets the R-squared values ranged from 0.860 to 0.960. Remarkable spatiotemporal intra-urban and inter-urban variabilities were found in PM2.5 components. The Coordinate Reference System (CRS) for predictions is the World Geodetic System 1984 (WGS84) and the units for the PM2.5 Components are µg/m^3.

Usage

The data are provided in RDS tabular format, a file format native to the R programming language, but can also be opened by other languages such as Python.

This dataset includes sensor measurements collected from an air free-cooled data center testbed with an air free-cooling system in 2018 and 2019.

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.