Seasonal and annual trends of mean surface air temperature change (degrees Celsius) for 1948-2016 based on Canadian gridded data (CANGRD) are available at a 50km resolution across Canada. Temperature trends represent the departure from a mean reference period (1961-1990). CANGRD data are interpolated from adjusted and homogenized climate station data (i.e., AHCCD datasets). Homogenized climate data incorporate adjustments to the original station data to account for discontinuities from non-climatic factors, such as instrument changes or station relocation.

The Regional Deterministic Air Quality Analysis (RDAQA) is an objective analysis of surface pollutants which combines numerical forecasts from the Regional Air Quality Deterministic Prediction System (RAQDPS) and hourly observational data from monitoring surface networks over North America in order to produce a better description of the air quality at every hour. Chemical constituents include 03, SO2, and NO2 gases, as well as fine particulate matter PM2.5 (2.5 micrometers in diameter or less) and coarse particulate matter PM10 (10 micrometers in diameter or less). Geographical coverage is Canada and the United States. Data is available only for the surface level, at a horizontal resolution of 10 km. The products are presented as historical, annual or monthly, averages which highlight long-term trends in cumulative effects on the environment.

The Regional Air Quality Deterministic Prediction System FireWork (RAQDPS-FW) carries out physics and chemistry calculations, including emissions from active wildfires, to arrive at deterministic predictions of chemical species concentration of interest to air quality, such as fine particulate matter PM2.5 (2.5 micrometers in diameter or less). Geographical coverage is Canada and the United States. Data is available at a horizontal resolution of 10 km. While the system encompasses more than 80 vertical levels, data is available only for the surface level. The products are presented as historical, annual or monthly, averages which highlight long-term trends in cumulative effects on the environment.

A cross-country summary of the averages and extremes for the month, including precipitation totals, max-min temperatures, and degree days. This data is available from stations that produce daily data.

Unverified raw hourly air pollutant monitoring and meteorological data collected by the Ministry of Environment and Climate Change Strategy. These data sets contain **air quality data from 2025 to the most recent hourly readings** and **meteorological data from 2023 to the most recent hourly readings** from air quality monitoring stations across B.C, up to the latest hour in Pacific Standard Time (PST). This does not include data originating from Metro Vancouver and Fraser Valley Regional Districts. For current conditions for Metro Vancouver and Fraser Valley Regional Districts please visit https://gis.metrovancouver.org/maps/air/ This data is not quality-assured. Historical quality-assured air data is available here: https://catalogue.data.gov.bc.ca/dataset/77eeadf4-0c19-48bf-a47a-fa9eef01f409 Please subscribe using the following link if you want to receive the updates on the datasets: https://www2.gov.bc.ca/gov/content/environment/air-land-water/air/air-quality/current-air-quality-data __Please click on VIEW resource to access__ __For data files directing to a FTP site, please copy the FTP link to File Explorer (anonymous login), Finder or equivalent, or use a FTP client such as FileZilla to access the FTP link. If using File Explorer, Finder, or equivalent, copy the files requested from the FTP folder to a local location to download.__ ##### Data files are available for: ##### #### Current Air Quality Data: * Air Quality Health Index (Learn more about this index: http://www.env.gov.bc.ca/epd/bcairquality/readings/aqhi-table.xml) * Carbon monoxide (CO) in parts per million (ppm) * Hydrogen sulfide (H2S) and Total reduced sulfur (TRS) in ppb * Nitric oxide (NO) in parts per billion (ppb) * Nitrogen dioxide (NO2) in ppb * Sulfur dioxide (SO2) in ppb * Ground-level ozone (O3) in ppb * PM2.5 (particulate matter with diameter of 2.5 micrometres or less) in micrograms per cubic metre (ug/m3) * PM10 (particulate matter with diameter of 10 micrometres or less) in ug/m3 * THC (total hydrocarbons) in ppm #### Current Meteorological Data: * Air Temperature (TEMP) in degrees Celsius (°C) * Relative Humidity (HUMIDITY) in percent (%) * Wind Speed (WSPD) in meters per second (m/s) * Wind Direction (WDIR) in degrees from true north/azimuth (°) * Precipitation (PRECIP) in millimeters (mm) * Snow depth (SNOW) in centimeters (cm) * Barometric Pressue (PRESSURE) in kilopascals (kPA) or millibars (mb) * Water Vapor Pressure (VAPOUR) in kilopascals (kPA) or millibars (mb) #### Monitoring Locations * Locations of all current and historical air and meteorological stations including Latitude and Longitude

Environment and Climate Change Canada’s (ECCC) Climate Research Division (CRD) and the Pacific Climate Impacts Consortium (PCIC) previously produced statistically downscaled climate scenarios based on simulations from climate models that participated in the Coupled Model Intercomparison Project phase 5 (CMIP5) in 2015. ECCC and PCIC have now updated the CMIP5-based downscaled scenarios with two new sets of downscaled scenarios based on the next generation of climate projections from the Coupled Model Intercomparison Project phase 6 (CMIP6). The scenarios are named Canadian Downscaled Climate Scenarios–Univariate method from CMIP6 (CanDCS-U6) and Canadian Downscaled Climate Scenarios–Multivariate method from CMIP6 (CanDCS-M6).CMIP6 climate projections are based on both updated global climate models and new emissions scenarios called “Shared Socioeconomic Pathways” (SSPs). Statistically downscaled datasets have been produced from 26 CMIP6 global climate models (GCMs) under three different emission scenarios (i.e., SSP1-2.6, SSP2-4.5, and SSP5-8.5), with PCIC later adding SSP3-7.0 to the CanDCS-M6 dataset. The CanDCS-U6 was downscaled using the Bias Correction/Constructed Analogues with Quantile mapping version 2 (BCCAQv2) procedure, and CanDCS-M6 was downscaled using the N-dimensional Multivariate Bias Correction (MBCn) method. The CanDCS-U6 dataset was produced using the same downscaling target data (NRCANmet) as the CMIP5-based downscaled scenarios, while the CanDCS-M6 dataset implements a new target dataset (ANUSPLIN and PNWNAmet blended dataset).Statistically downscaled individual model output and ensembles are available for download. Downscaled climate indices are available across Canada at 10km grid spatial resolution for the 1950-2014 historical period and for the 2015-2100 period following each of the three emission scenarios.Note: projected future changes by statistically downscaled products are not necessarily more credible than those by the underlying climate model outputs. In many cases, especially for absolute threshold-based indices, projections based on downscaled data have a smaller spread because of the removal of model biases. However, this is not the case for all indices. Downscaling from GCM resolution to the fine resolution needed for impacts assessment increases the level of spatial detail and temporal variability to better match observations. Since these adjustments are GCM dependent, the resulting indices could have a wider spread when computed from downscaled data as compared to those directly computed from GCM output. In the latter case, it is not the downscaling procedure that makes future projection more uncertain; rather, it is indicative of higher variability associated with finer spatial scale.Individual model datasets and all related derived products are subject to the terms of use (https://pcmdi.llnl.gov/CMIP6/TermsOfUse/TermsOfUse6-1.html) of the source organization.

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).

Seasonal and annual multi-model ensembles of projected change (also known as anomalies) in mean temperature (°C) based on an ensemble of twenty-nine Coupled Model Intercomparison Project Phase 5 (CMIP5) global climate models are available for 1901-2100. Projected change in mean temperature (°C) is with respect to the reference period of 1986-2005. The 5th, 25th, 50th, 75th and 95th percentiles of the ensembles of projected change in mean temperature change are available for the historical time period, 1901-2005, and for emission scenarios, RCP2.6, RCP4.5 and RCP8.5, for 2006-2100. Twenty-year average changes in mean temperature (°C) for four time periods (2021-2040; 2041-2060; 2061-2080; 2081-2100), with respect to the reference period of 1986-2005, for RCP2.6, RCP4.5 and RCP8.5 are also available in a range of formats. The median projected change across the ensemble of CMIP5 climate models is provided. Note: Projections among climate models can vary because of differences in their underlying representation of earth system processes. Thus, the use of a multi-model ensemble approach has been demonstrated in recent scientific literature to likely provide better projected climate change information.

Monthly, seasonal and annual trends of daily minimum, mean and maximum surface air temperature change (degrees Celsius) based on homogenized station data (AHCCD) are available. Trends are calculated using the Theil-Sen method using the station’s full period of available data. The availability of temperature trends will vary by station; if more than 5 consecutive years are missing data or more than 10% of the data within the time series is missing, a trend was not calculated.

The National Pollutant Release Inventory (NPRI) is Canada's public inventory of pollutant releases (to air, water and land), disposals and transfers for recycling.The files below contain a map of Canada showing the locations of all facilities that reported releases to air (other than Criteria Air Contaminants (CAC)) to the NPRI. The data are for the most recent reporting year, by reported total quantities of these releases. The map is available in both ESRI REST (to use with ARC GIS) and WMS (open source) formats. For more information about the individual reporting facilities, a dataset is available in a CSV format.Please consult the following resources to enhance your analysis:- Guide on using and Interpreting NPRI Data: https://www.canada.ca/en/environment-climate-change/services/national-pollutant-release-inventory/using-interpreting-data.html - Access additional data from the NPRI, including datasets and mapping products: https://www.canada.ca/en/environment-climate-change/services/national-pollutant-release-inventory/tools-resources-data/exploredata.html