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.

The AU-AIR is a multi-modal aerial dataset captured by a UAV. Having visual data, object annotations, and flight data (time, GPS, altitude, IMU sensor data, velocities), AU-AIR meets vision and robotics for UAVs.

Ambient air quality monitoring is undertaken in the ACT to both support both the National Environment Protection Measures and an Air Quality Index (AQI) to better communicate the ambient air quality to the ACT Community.

Unverified data in this dataset. The data displayed may have undergone no or only preliminary quality assurance checks. These data may require modification as a result of calibration changes, power failures, instrument failures etc.

This asset provides data on regional air quality, including trace level SO2, nitric acid, ozone, carbon monoxide, and NOy; and particulate sulfate, nitrate, and ammonium from 1989 to present. Precipitation and meteorology are provided from 1989 to 2011.

This dataset deals with pollution in the U.S. Pollution in the U.S. has been well documented by the U.S. EPA.

Includes four major pollutants (Nitrogen Dioxide, Sulphur Dioxide, Carbon Monoxide and Ozone).

• State Code : The code allocated by US EPA to each state
• County code : The code of counties in a specific state allocated by US EPA
• Site Num : The site number in a specific county allocated by US EPA
• Address: Address of the monitoring site
• State : State of monitoring site
• County : County of monitoring site
• City : City of the monitoring site
• Date Local : Date of monitoring

The four pollutants (NO2, O3, SO2 and O3) each has 5 specific columns. For instance, for NO2:

• NO2 Units : The units measured for NO2
• NO2 Mean : The arithmetic mean of concentration of NO2 within a given day
• NO2 AQI : The calculated air quality index of NO2 within a given day
• NO2 1st Max Value : The maximum value obtained for NO2 concentration in a given day
• NO2 1st Max Hour : The hour when the maximum NO2 concentration was recorded in a given day

Source: Kaggle

https://www.kaggle.com/sogun3/uspollution

source This dataset was taken from UCI Machine Learning Repository: https://archive.ics.uci.edu/ml/index.php

Content The dataset contains 9358 instances of hourly averaged responses from an array of 5 metal oxide chemical sensors embedded in an Air Quality Chemical Multisensor Device. The device was located on the field in a significantly polluted area, at road level,within an Italian city. Data were recorded from March 2004 to February 2005 (one year)representing the longest freely available recordings of on field deployed air quality chemical sensor devices responses.

Ground Truth hourly averaged concentrations for CO, Non Metanic Hydrocarbons, Benzene, Total Nitrogen Oxides (NOx) and Nitrogen Dioxide (NO2) and were provided by a co-located reference certified analyzer. Evidences of cross-sensitivities as well as both concept and sensor drifts are present as described in De Vito et al., Sens. And Act. B, Vol. 129,2,2008 (citation required) eventually affecting sensors concentration estimation capabilities.

Attribute Information:

• 0-Date (DD/MM/YYYY)
• 1-Time (HH.MM.SS)
• 2-True hourly averaged concentration CO in mg/m^3 (reference analyzer)
• 3-PT08.S1 (tin oxide) hourly averaged sensor response (nominally CO targeted)
• 4-True hourly averaged overall Non Metanic HydroCarbons concentration in microg/m^3 (reference analyzer)
• 5-True hourly averaged Benzene concentration in microg/m^3 (reference analyzer)
• 6-PT08.S2 (titania) hourly averaged sensor response (nominally NMHC targeted)
• 7-True hourly averaged NOx concentration in ppb (reference analyzer)
• 8-PT08.S3 (tungsten oxide) hourly averaged sensor response (nominally NOx targeted)
• 9-True hourly averaged NO2 concentration in microg/m^3 (reference analyzer)
• 10-PT08.S4 (tungsten oxide) hourly averaged sensor response (nominally NO2 targeted)
• 11-PT08.S5 (indium oxide) hourly averaged sensor response (nominally O3 targeted)
• 12-Temperature in °C
• 13-Relative Humidity (%)
• 14-AH Absolute Humidity

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 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.

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

Citywide raster files of annual average predicted surface for nitrogen dioxide (NO2), fine particulate matter (PM2.5), black carbon (BC), and nitric oxide (NO); summer average for ozone (O3) and winter average for sulfure dioxide (SO2). Description: Annual average predicted surface for nitrogen dioxide (NO2), fine particulate matter (PM2.5), black carbon (BC), and nitric oxide (NO); summer average for ozone (O3) and winter average for sulfure dioxide (SO2). File type is ESRI grid raster files at 300 m resolution, NAD83 New York Long Island State Plane FIPS, feet projection. Prediction surface generated from Land Use Regression modeling of December 2008- December 2019 (years 1-11) New York Community Air Survey monitoring data.As these are estimated annual average levels produced by a statistical model, they are not comparable to short term localized monitoring or monitoring done for regulatory purposes. For description of NYCCAS design and Land Use Regression Modeling process see: nyc-ehs.net/nyccas

Air Quality Monitoring Data Dublin City Council measures ambient air quality in Dublin in accordance with Air Quality standards. 'This dataset contains Air Quality Monitoring Data from January to March 2011, consisting five spreadsheets taken from five air monitoring sites around Dublin City that show hourly results for the pollutants Sulphur Dioxide( SO2) , Nitrogen Dioxide (NO2), Carbon Monoxide ( CO) and Particulate Matter (PM2.5 & PM10). The regulations are set by the Clean Air for Europe Directive 2008 (2008/50); from January 1st, 2010 the directive also requires PM2.5 monitoring. There is no real time data for PM10 or PM25'Black smoke monitoring is also carried out as a form of background monitoring using the benchmark of EU Directive 80/779/EEC as a guide however this has been scaled down since the 1990s following the introduction of the coal ban.'Multi-pollutant sites are:'Winetavern Street PM10, NO2, CO, SO2'Coleraine Street- PM2.5, NO2, CO, SO2'Ballyfermot PM10, NO2, SO2'PM10 only sites include:'Phoenix Park'Rathmines'PM2.5 only:'Marino'Black Smoke:'Ringsend'Crumlin'Finglas'Cabra''Annual report published http://www.dublincity.ie/WaterWasteEnvironment/AirQualityMonitoringandNoiseControl/AirPollution/Documents/Annual_report_2009.pdf

OpenAQ is an open-source project to surface live, real-time air quality data from around the world. OpenAQ's mission is to enable previously impossible science, impact policy, and empower the public to fight air pollution. The data includes air quality measurements from 5490 locations in 47 countries. Scientists, researchers, developers, and citizens can use this data to understand current air quality near them. The dataset only includes the most current measurement available for the location (no historical data). This public dataset is hosted in Google BigQuery and is included in BigQuery's 1TB/mo of free tier processing. This means that each user receives 1TB of free BigQuery processing every month, which can be used to run queries on this public dataset. Watch this short video to learn how to get started quickly using BigQuery to access public datasets. What is BigQuery .

This United States Environmental Protection Agency (US EPA) feature layer represents monitoring site data, updated hourly concentrations and Air Quality Index (AQI) values for the latest hour received from monitoring sites that report to AirNow.

The Vietnam Air Quality Data Series 2020 provides air quality values for several cities in Vietnam. Readers can access online data or historical data saved as of January 21, 2021 by zone GMT + 7

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.

A KML file with the location of all real time air quality monitors and the current conditions (air quality index).

Daily air quality data collected by the EPA Air Quality Service (AQS), from 1990-2021. This dataset includes air quality statistics from AQS monitors in the area surrounding Cambridge (Kenmore, Roxbury, Von Hillern, Chelsea). Each contains a parameter code which specifies one of the six pollutants for which the EPA AQS has an Air Quality Index (AQI).

Information on how to interpret AQI values can be found here: https://www.airnow.gov/aqi/aqi-basics/

Indoor air pollutant concentration data is collected for all the seasons in Pune city, India, from internet of things-based system built using low-cost sensors. The raw data contains 1,73,468 records collected from Nov 2020 to July 2022. Air pollutant PM2.5 (Particulate Matter) is measured using GP2Y1010AU0F Dust Smoke Particle Sensor, NO2 (Nitrogen Dioxide), NH3 (Ammonia) and CO (Carbon Monoxide) pollutant measured using MICS-6814 sensor. Ozone (O3) measured using MQ131 Semiconductor Sensor. Temperature, Humidity measured using BME 280 sensor. Measurement units of NH3 is PPM, NO2 in PPM, CO in PPM, PM2.5 in ug/m3, Temperature in Celsius, Pressure in hPa, Humidity in RH, Ozone in PPB. This data can be used for study and evaluations of prediction models, low-cost sensor data and calibration. It can be used for the study of the pollutant’s patterns in COVID-19 pandemic. It will help policymakers to develop policies to monitor air pollution impact.

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

Source: https://catalog.data.gov/dataset/air-quality-measures-on-the-national-environmental-health-tracking-network

The Air Data Systems Market is Segmented by Application (Commercial and Military), Component (Electronic Unit, Probes, and Sensors), and Geography (North America, Europe, Asia-Pacific, Latin America, and the Middle East and Africa). The Report Offers Market Size and Forecast for all the Above Segments in Value (USD).