This dataset provides geospatial polygon boundaries for marine bivalve shellfish harvest area classification in Canada (British Columbia, New Brunswick, Newfoundland and Labrador, Nova Scotia, Prince Edward Island and Quebec). These data represent the five classification categories of marine bivalve shellfish harvest areas (Approved; Conditionally Approved; Restricted; Conditionally Restricted; and Prohibited) under the Canadian Shellfish Sanitation Program (CSSP). Data are collected by Environment and Climate Change Canada (ECCC) for the purpose of making applicable classification recommendations based on pollution source assessment and water quality survey results. ECCC recommendations are reviewed and adopted by Regional Interdepartmental Shellfish Committees prior to regulatory implementation by Fisheries and Oceans Canada (DFO). These geographic data are for illustrative purposes only; they show shellfish harvest area classifications that may be superseded at any time by regulatory orders issued by DFO, which place areas in Closed Status, due to conditions such as sewage overflows or elevated biotoxin levels. For further information about the current status and boundary coordinates for areas under Prohibition Order, please contact your local DFO office.

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.

Monitoring activities have collected bulk suspended sediment samples using continuous flow centrifuges and Phillips Tube samplers in the Lower Athabasca River and tributaries respectively. Further, in the absence of pre-development monitoring for this region, high fidelity dated lake sediment cores were used to assess the natural range in contaminant deposition to this region and to obtain a historical perspective of contaminant loadings. All sediments (suspended river and lake cores) have been analyzed in the laboratory for sediment quality variables as per Appendix B in the Integrated Monitoring Plan (cores were also analyzed for paleo indicators of ecosystem health such as diatoms). In addition, as the Lower Athabasca river bed sediments are known to shift and migrate downstream, bathymetric maps of the bed-channel morphology over time was also completed. This will allow for estimates of bed sediment transport downstream for the period of survey, and be useful in calibration/validation of sediment and contaminant numerical transport models.

This map shows the projected average change in mean temperature (°C) for 2081-2100, with respect to the reference period of 1986-2005 for RCP4.5. The median projected change across the ensemble of CMIP5 climate models is shown. For more maps on projected change, please visit the Canadian Climate Data and Scenarios (CCDS) site: https://climate-scenarios.canada.ca/?page=download-cmip5.

Gridded monthly, seasonal and annual anomalies derived from daily total precipitation is available at a 50km resolution across Canada. The Canadian gridded data (CANGRD) are interpolated from adjusted precipitation (i.e., AHCCD datasets). Adjusted precipitation data incorporate adjustments to the original station data to account for discontinuities from non-climatic factors, such as instrument changes or station relocation. The anomalies are the percentage difference between the value for a given year or season and a baseline value (defined as the average over 1961-1990 as the reference period). The yearly and seasonal relative precipitation anomalies were computed for the years 1948 to 2014. The data will be updated as time permits.

Multi-model ensembles of sea ice concentration based on projections from twenty-eight Coupled Model Intercomparison Project Phase 5 (CMIP5) global climate models are available for 1900-2100. Specifically, the 5th, 25th, 50th, 75th and 95th percentiles of the monthly, seasonal and annual ensembles of sea ice concentration as represented as the percentage (%) of grid cell area, are available for the historical time period, 1900-2005, and for emission scenarios, RCP2.6, RCP4.5 and RCP8.5, for 2006-2100. 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.

Statistically downscaled multi-model ensembles of projected change (also known as anomalies) in minimum temperature (°C) are available at a 10km spatial resolution for 1951-2100. Statistically downscaled ensembles are based on output from twenty-four Coupled Model Intercomparison Project Phase 5 (CMIP5) global climate models (GCM). Daily minimum temperature from GCM outputs were downscaled using the Bias Correction/Constructed Analogues with Quantile mapping version 2 (BCCAQv2). A historical gridded minimum temperature dataset of Canada (ANUSPLIN) was used as the downscaling target. Projected change in minimum temperature (°C) is with respect to the reference period of 1986-2005. Seasonal and annual averages of projected minimum temperature change to 1986-2005 are provided. Specifically, the 5th, 25th, 50th, 75th and 95th percentiles of the downscaled ensembles of minimum 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 statistically downscaled mean minimum 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 downscaled 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.

Seasonal and annual multi-model ensembles of projected relative change (also known as anomalies) in mean precipitation based on an ensemble of twenty-nine Coupled Model Intercomparison Project Phase 5 (CMIP5) global climate models are available for 1901-2100. Projected relative change in mean precipitation is with respect to the reference period of 1986-2005 and expressed as a percentage (%). The 5th, 25th, 50th, 75th and 95th percentiles of the ensembles of mean precipitation 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 precipitation (%) 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.

The National Pollutant Release Inventory (NPRI) is Canada's public inventory of pollutant releases (to air, water and land), disposals and transfers for recycling. This file is a geodatabase (GDB) that shows the locations of all facilities that reported to the NPRI in the current reporting year. The data are also available in a virtual globe format : https://open.canada.ca/data/en/dataset/d9be6bec-47e5-4835-8d01-d2875a8d67ff 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

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 file contains facility-specific data reported to the NPRI listed by media of release and by disposal and transfer. Facilities are categorized by industrial sector and total reported quantities. The data are for the most recent reporting year. 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