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/

Introduction

Air pollution Statistics: The air pollution problem is by far the most significant environmental health issue around the world and causes an estimated 7.7 million deaths each year. Climate change and air pollution are closely linked since every major pollutant has an impact on climate and many have common causes with greenhouse gases. Enhancing the quality of air can lead to improved health, development, and environmental benefits.

According to UNEP Pollution Action Note, the global condition of pollution in the air, its major sources, the effects of the air pollution on health as well as the national efforts to address this problem. The tiny particles that pollute the air are mostly derived from human activities such as burning fossil fuels for transportation, waste-burning electricity agriculture, and the major source of ammonia and methane as well as the mining and chemical industries. Let's look into air pollution and its impact.

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.

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.

Air pollution levels in cities vary greatly around the world, though they are typically higher in developing regions. In 2024, the cities of Jakarta and Cairo had an average PM2.5 concentrations of **** and **** micrograms per cubic meter (μg/m³) respectively. By comparison, PM2.5 levels in London and New York were less than ***** μg/m³. Nevertheless, pollution levels in these four major cities are all higher than the World Health Organization's healthy limit, which are set at an annual average of less than **** μg/m³. There are many sources of air pollution, such as energy production, transportation, and agricultural activities.

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

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/

The Transport Operations (Marine Pollution) Act 1995 and regulations protect Queensland's marine and coastal environment by minimising deliberate and negligent discharges of ship-sourced pollutants into coastal waters.

Under the Transport Operations (Marine Pollution) Act 1995 the master of a ship must report a discharge or probable discharge of any pollutant without delay to Maritime Safety Queensland or the Australian Maritime Safety Authority. Pollutants are defined as harmful substances and includes oil, chemicals, and sewage and garbage. Even minor instances of marine pollution must be reported.

The data files below contain reported marine pollution or suspected marine pollution in coastal waters.

For a full breakdown of each column in this dataset please refer to the supporting document – Field Descriptions.

The National Air Pollution Surveillance (NAPS) program is the main source of ambient air quality data in Canada. The NAPS program, which began in 1969, is now comprised of nearly 260 stations in 150 rural and urban communities reporting to the Canada-Wide Air Quality Database (CWAQD). Managed by Environment and Climate Change Canada (ECCC) in collaboration with provincial, territorial, and regional government networks, the NAPS program forms an integral component of various diverse initiatives; including the Air Quality Health Index (AQHI), Canadian Environmental Sustainability Indicators (CESI), and the US-Canada Air Quality Agreement. Once per year, typically autumn, the Continuous data set for the previous year is reported on ECCC Data Mart. Beginning in March of 2020 the impact of the COVID-19 pandemic on NAPS Operations has resulted in reduced data availability for some sites and parameters. For additional information on NAPS data products contact the NAPS inquiry centre at RNSPA-NAPSINFO@ec.gc.ca Last updated March 2023. Supplemental Information Monitoring Program Overview The NAPS program is comprised of both continuous and (time-) integrated measurements of key air pollutants. Continuous data are collected using gas and particulate monitors, with data reported every hour of the year, and are available as hourly concentrations or annual averages. Integrated samples, collected at select sites, are analyzed at the NAPS laboratory in Ottawa for additional pollutants, and are typically collected for a 24 hour period once every six days, on various sampling media such as filters, canisters, and cartridges. Continuous Monitoring Air pollutants monitored continuously include the following chemical species: • carbon monoxide (CO) • nitrogen dioxide (NO2) • nitric oxide (NO) • nitrogen oxides (NOX) • ozone (O3) • sulphur dioxide (SO2) • particulate matter less than or equal to 2.5 (PM2.5) and 10 micrometres (PM10) Each provincial, territorial, and regional government monitoring network is responsible for collecting continuous data within their jurisdiction and ensuring that the data are quality-assured as specified in the Ambient Air Monitoring and Quality Assurance/Quality Control Guidelines. The hourly air pollutant concentrations are reported as hour-ending averages in local standard time with no adjustment for daylight savings time. These datasets are posted on an annual basis. Integrated Monitoring Categories of chemical species sampled on a time-integrated basis include: • fine (PM2.5) and coarse (PM10-2.5) particulate composition (e.g., metals, ions), and additional detailed chemistry provided through a subset of sites by the NAPS PM2.5 speciation program; • semi-volatile organic compounds (e.g., polycyclic aromatic hydrocarbons such as benzo[a]pyrene); • volatile organic compounds (e. g., benzene) The 24-hour air pollutant samples are collected from midnight to midnight. These datasets are generally posted on a quarterly basis. Data Disclaimer NAPS data products are subject to change on an ongoing basis, and reflect the most up-to-date and accurate information available. New versions of files will replace older ones, while retaining the same location and filename. The ‘Data-Donnees’ directory contains continuous and integrated data sorted by sampling year and then measurement. Pollutants measured, sampling duration and sampling frequency may vary by site location. Additional program details can be found at ‘ProgramInformation-InformationProgramme’ also in the data resources section. Citations National Air Pollution Surveillance Program, (year accessed). Available from the Government of Canada Open Data Portal at open.canada.ca.

This dataset contains Water pollution level statistics in 2000. Data from Water FootPrint Network. Follow datasource.kapsarc.org for timely data to advance energy economics research.

The Air Quality Dataset provides a comprehensive overview of atmospheric pollution levels across various locations in Poland from 2017 to 2023. It features extensive measurements of numerous air pollutants captured through an extensive network of air quality monitoring stations throughout the country. The dataset includes both hourly (1g) and daily (24g) averages of the recorded pollutants, offering detailed temporal resolution to study short-term peaks and long-term trends in air quality.

Pollutants Measured:

1. Gaseous Pollutants: Carbon Monoxide (CO), Nitrogen Dioxide (NO2), Nitric Oxide (NO), Nitrogen Oxides (NOx), Sulfur Dioxide (SO2), Ozone (O3), and Benzene (C6H6).
2. Particulate Matter: PM10, PM2.5; and specific elements and compounds bound to PM10 such as Lead (Pb), Arsenic (As), Cadmium (Cd), Nickel (Ni), among others.
3. Polycyclic Aromatic Hydrocarbons (PAHs) associated with PM10: Benzo[a]anthracene (BaA), Benzo[b]fluoranthene (BbF), Benzo[j]fluoranthene (BjF), Benzo[k]fluoranthene (BkF), Benzo[a]pyrene (BaP), Indeno[1,2,3-cd]pyrene (IP), Dibenzo[a,h]anthracene (DBahA).
4. Additional Chemicals: Including various volatile organic compounds (VOCs) like ethylene, toluene, xylene variants, aldehydes, and hydrocarbons.

Features of the Dataset:

Locations: Data from numerous air quality monitoring stations distributed across various urban, suburban, and rural areas in Poland.
Time Resolution: Measurements are provided in both hourly and daily intervals, catering to different analytical needs.
Coverage Period: This dataset encompasses data from 2017 to the year, 2023, enabling analysis over multiple years to discern trends and assess the effectiveness of air quality management policies.
Deployment of Deposition Sampling: Concentrations of certain pollutants in wet and dry deposition forms, noted with 'cdepoz' (cumulative deposition), providing insights into the deposition rates of airborne pollutants.

Potential Applications:

Environmental Research: Study the impact of various pollutants on air quality, health, and the environment.
Policy Making: Assist policymakers in evaluating the effectiveness of past regulations and planning future actions to improve air quality.
Public Health: Correlate pollutant exposure levels with health outcomes, helping public health professionals to mitigate risks associated with poor air quality.

Data Format:

The dataset is structured in a tabular format with each row representing an observation time (either hourly or daily) and columns representing different pollutants and their concentrations at various monitoring stations.

This dataset is an essential resource for researchers, policymakers, environmental agencies, and health professionals who need a detailed and robust dataset to understand and combat air pollution in Poland.

Source of data: Chief Inspectorate of Environmental Protection (GIOS)

The historic weather dataset for Cracow and Warsaw

The historic weather dataset for Cracow and Warsaw with suburbs, covering daily observations from 2019 to August 2024, would encompass a range of atmospheric and meteorological data points collected over the defined time period and locations. Here’s a description of what such a dataset might include and signify: Key Characteristics:

Locations: The cities of Cracow and Warsaw, along with their suburbs. The dataset would likely specify the exact areas or measurements stations.
Time Frame: Daily records from January 1, 2019, to August, 2024, providing a comprehensive view of weather variations through different seasons and years.
Data Granularity: Daily data would allow trends such as temperature fluctuations, precipitation patterns, and weather anomalies to be studied in considerable detail.

Likely Data Fields:

Each record in the dataset might contain:

DATE_VALID_STD: Representing each day within the date range specified (from 2019-01-01 to 2024-08-20 for Cracow and Warsaw suburbs).
Temperature Fields (Min, Max, Avg): Temperature readings at specified intervals, likely in Celsius, providing insight into daily and seasonal temperature patterns and extremes.
Humidity Fields (Min, Max, Avg): Relative and specific humidity readings to assess moisture levels in the air, which have implications for weather conditions, comfort levels, and health.
Precipitation: Data on rainfall, snowfall, and total snow depth, essential for understanding water cycle dynamics, agricultural planning, and urban water management in these areas.
Wind Measurements: May include minimum, average, and maximum speeds and perhaps prevailing directions, useful in sectors like aviation, construction, and event planning.
Pressure and Tendency: Barometric pressure readings at different measurement standards to help predict weather changes.
Radiation and Cloud Cover: D...

In 2021, the number of deaths due to air pollution in Japan was estimated at **** thousand. Since 2010, the number of deaths has risen, making Japan one of the countries with a high number of deaths attributable to air pollution exposure.
Health risks and sources of air pollution The most common air pollutant is particulate matter with a diameter of *** micrometers or less, also called PM ***. The air pollutants can invade the lungs and cause asthma, cancer, heart diseases, allergies, and other health conditions. A major cause of air pollution is fossil fuel combustion, which is produced from power plants and industrial facilities. In Japan, fossil fuels such as petroleum and coal had the largest share of the primary energy supply. Another cause is carbon dioxide emissions from the transport sector since PM *** is generated from sources such as automobile exhaust fumes. Therefore, most pollution areas are highly populated, urban areas. Measures to improve air quality in Japan In 2020, the Tokyo government announced its intention to improve the air quality with stricter air pollution regulations. The new target for Tokyo's level of PM *** is set at ** micrograms or less per cubic meter by fiscal year 2030. To decrease air pollution, Japan aims to reduce its use of fossil fuels and increase its nuclear and renewable energy share. Renewables accounted for a share of primary energy supply of almost **** percent, whereas nuclear energy made up about ***** percent in 2018. In recent years, these measures began to show their effect as figures for the total annual greenhouse gas emissions indicated a decline.

Environmental monitoring stations (EMS) were installed in Campbelltown and Liverpool's CBD in December 2020. The EMS measures weather data and pollutants data. This dataset stores pollutants related measures:nitrogendioxide (NO2 measured in ppb)carbonmonoxide (CO in ppb)ozone (O3 in ppb)particulate matter 10 (PM10 in µg/m³)particulate matter 2.5 (PM2.5 in µg/m³)Associated Air Quality Index is calculated based on a number of parameters. Data in this dataset is presented in the Quality of Place dashboard.Please note this data is indicative as sensors may from time to time provide incorrect data due to wear and tear or unforeseen circumstances.

Annual emissions of various air pollutants in the United States have experienced dramatic reductions over the past half a century. As of 2024, emissions of nitrogen oxides (NOx) had reduced by more than ** percent since 1970 to *** million tons. Sulfur dioxide (SO₂) emissions have also fallen dramatically in recent decades, dropping from ** million tons to *** million tons between 1990 and 2024. Air pollutants can pose serious health hazards to humans, with the number of air pollution related deaths in the U.S. averaging ****** a year.

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

United States US: Mortality Rate Attributed to Household and Ambient Air Pollution: Age-standardized: Male data was reported at 17.000 NA in 2016. United States US: Mortality Rate Attributed to Household and Ambient Air Pollution: Age-standardized: Male data is updated yearly, averaging 17.000 NA from Dec 2016 (Median) to 2016, with 1 observations. United States US: Mortality Rate Attributed to Household and Ambient Air Pollution: Age-standardized: Male data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s United States – Table US.World Bank.WDI: Health Statistics. Mortality rate attributed to household and ambient air pollution is the number of deaths attributable to the joint effects of household and ambient air pollution in a year per 100,000 population. The rates are age-standardized. Following diseases are taken into account: acute respiratory infections (estimated for all ages); cerebrovascular diseases in adults (estimated above 25 years); ischaemic heart diseases in adults (estimated above 25 years); chronic obstructive pulmonary disease in adults (estimated above 25 years); and lung cancer in adults (estimated above 25 years).; ; World Health Organization, Global Health Observatory Data Repository (http://apps.who.int/ghodata/).; Weighted average;

This dataset Contains Saudi Arabia Emissions of Air or Water Pollutants for the period 2010-2018. Data from General Authority for Statistics. Follow datasource.kapsarc.org for timely data to advance energy economics research.Units: Ozone (o3) concentration level in atmosphere, Carbon monoxide (CO) concentration level, Sulphur oxides (SO2) concentration level, Nitrogen oxides (NO2) concentration level.