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.

With the changing climate conditions, marine traffic along Canada’s coastal regions has increased over the past couple of decades and the need to improve our state of preparedness for oil-spill-related emergencies is critical. Baseline coastal information, such as shoreline form, substrate, and vegetation type, is required for prioritizing operations, coordinating onsite spill response activities (i.e. Shoreline Cleanup Assessment Technique [SCAT]), and providing information for wildlife and ecosystem management. Between 2010 and 2017, georeferenced high-definition videography and photos were collected for various study sites across coastal Canada. The study areas include Beaufort Sea, Mackenzie Delta channels and Banks Island in the western Canadian Arctic; James Bay, Hudson Bay, Nunavik, Resolute Bay, Victoria Strait, Baffin Island and Coronation Gulf in the eastern Canadian Arctic; Labrador, Bay of Fundy and Chedabucto Bay in Atlantic Canada and Kitimat, Haida Gwaii and Burrard Inlet in the northern Pacific. Data was collected during ice-free and low tide conditions (where applicable) between July and September. Low-altitude helicopter surveys were conducted at each study site to capture video of the shoreline characteristics. In addition to acquiring videography, ground-based observations were recorded in several locations for validation. Shoreline segmentation was then carried out by manual interpretation of the oblique videography and the photos aided by ancillary data. This involved splitting and classifying the shoreline vectors based on homogeneity of the upper intertidal zone. Detailed geomorphological information (i.e. shoreline type, substrate, slope, height, accessibility etc.) describing the upper intertidal, lower intertidal, supratidal and backshore zones was extracted from the video and entered into a geospatial database using a customized data collection form. In addition, biological characteristics like biobands, water features, fauna, human use etc. observed along the coast were recorded. The data was also validated through ground samples (when available) and a second interpreter QA (quality analysis) was performed on each dataset (excluding Nunavik) to ensure high quality and consistency. The final dataset contains segments ranging in length from 150 metres to 2500 metres. In total, from 2010 to 2017, within the 14 study sites, about 26,150 km of shoreline were mapped.

The Canadian Environmental Sustainability Indicators program provides data and information to track Canada's performance on key environmental sustainability issues. The Polybrominated diphenyl ethers in fish and sediment indicators identify the drainage regions where concentrations are below or above the Federal Environmental Quality Guidelines (the guidelines) for polybrominated diphenyl ethers (PBDEs) in fish and sediment. The guidelines were developed under the Chemicals Management Plan and are used in this report to evaluate whether, and the degree to which, concentrations in the environment exceed the guidelines. These indicators provide information on the presence of PBDEs in the environment and on the progress of strategies and policies to reduce or control their occurrence in the environment. Information is provided to Canadians in a number of formats including: static and interactive maps, charts and graphs, HTML and CSV data tables and downloadable reports. See the supplementary documentation for the data sources and details on how the data were collected and how the indicator was calculated. Information is provided to Canadians in a number of formats including: static and interactive maps, charts and graphs, HTML and CSV data tables and downloadable reports. See the supplementary documentation for the data sources and details on how the data were collected and how the indicator was calculated.

This database contains model output files that were used in the 2021 Arctic Monitoring and Assessment Programme (AMAP) Assessment Report on Short-lived Climate Forcers (SLCFs) and subsequent journal publications. The datasets are stored here: http://crd-data-donnees-rdc.ec.gc.ca/CCCMA/products/AMAP/ Type0 model files are basic historical simulations. Types 1 and 2 are model sensitivity simulations with regionally perturbed emissions and type 3 are future simulations under varying emission scenarios. Please see the file "AMAPdatabaseREADME.xlxs" at the data location for further explanation.

This dataset contains monthly and annual statistics of extreme wave parameters for the Arctic, and projected increases (in probability and magnitude) in potential wave-driven coastal erosion and flooding along Arctic coastlines. The WAVEWATCH III wave model was driven by surface winds and sea ice concentrations simulated by five global climate models participated in the Coupled Climate Model Comparison Phase 5 (CMIP5) project for the historical period (1979-2005) and for the future period 2081-2100 under the emission scenario RCP8.5.

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.

With the changing climate conditions, marine traffic along Canada’s coastal regions has increased over the past few decades and the need to improve our state of preparedness for oil-spill-related emergencies is critical. Baseline coastal information, such as shoreline form, substrate, and vegetation type, is required for prioritizing operations, coordinating onsite spill response activities (i.e., Shoreline Cleanup Assessment Technique [SCAT]), and providing information for wildlife and ecosystem management. Between 2011 and 2016, georeferenced high-definition videography and photos were collected for various study sites along the east coast. The study areas include Labrador, Bay of Fundy and Chedabucto Bay in Atlantic Canada. Data was collected during ice-free and low tide conditions (where applicable) between July and September. Low-altitude helicopter surveys were conducted at each study site to capture video of the shoreline characteristics. In addition to acquiring videography, ground-based observations were recorded in several locations for validation. Shoreline segmentation was then carried out by manual interpretation of the oblique videography and the photos aided by ancillary data. This involved splitting and classifying the shoreline vectors based on homogeneity of the upper intertidal zone. Detailed geomorphological information (i.e., shoreline type, substrate, slope, height, accessibility etc.) describing the upper intertidal, lower intertidal, supratidal and backshore zones was extracted from the video and entered into a geospatial database using a customized data collection form. In addition, biological characteristics like biobands, water features, fauna, human use etc. observed along the coast were recorded. The data was also validated through ground observations (when available) and a second interpreter QA (quality analysis) was performed on each dataset to ensure high quality and consistency. The final dataset contains segments ranging in length from 150 metres to 2500 metres. In total, from 2011 to 2016, within the 3 study sites, about 1,850 km of shoreline were mapped.

This dataset contains the stable nitrogen (δ15N), carbon (δ13C), oxygen (δ18O), and hydrogen (δ2H) isotope data from 1123 samples of underfur hair of adult polar bears (Ursus maritimus) sampled between 1992 to 2017 from subpopulation boundaries (zone) in the Canadian Arctic and sub-Arctic. Wide-ranging apex predators are among the most challenging of all fauna to conserve and manage. This is especially true of the polar bear, an iconic predator that is hunted in Canada and threatened by global climate change. We used combinations of stable isotopes (13C,15N,2H,18O) in polar bear hair to test the ability of stable isotopic profiles to ‘assign’ bears to (1) predefined managed subpopulations, (2) subpopulations defined by similarities in stable isotope values using quadratic discriminant analysis, and (3) spatially explicit, isotopically distinct clusters derived from interpolated (i.e. ‘kriged’) isotopic landscapes, or ‘isoscapes’, using the partitioning around medoids algorithm. A four-isotope solution provided the highest overall assignment accuracies (~80%) to pre-existing management subpopulations with accuracy rates ranging from ~30–99% (median = 64%). Assignment accuracies of bears to hierarchically clustered ecological groups based on isotopes ranged from ~64–99%. Multivariate assignment to isotopic clusters resulted in highest assignment accuracies of 68% (33–77%), 84% (47–96%) and 74% (53–85%) using two, three and four stable isotope groups, respectively. The resulting spatial structure inherent in the multiple stable isotopic compositions of polar bear tissues is a powerful forensic tool that will, in this case, contribute to the conservation and management of this species. Currently, it is unclear what is driving these robust isotopic patterns and future research is needed to evaluate the processes behind the pattern. Nonetheless, our isotopic approach can be further applied to other apex mammalian predators under threat, such as the large felids, providing that isotopic structure occurs throughout their range.

With the changing climate conditions, marine traffic along Canada’s coastal regions has increased over the past couple of decades and the need to improve our state of preparedness for oil-spill-related emergencies is critical. Baseline coastal information, such as shoreline form, substrate, and vegetation type, is required for prioritizing operations, coordinating onsite spill response activities (i.e. Shoreline Cleanup Assessment Technique [SCAT]), and providing information for wildlife and ecosystem management. Between 2010 and 2016, georeferenced high-definition videography and photos were collected for various study sites along the north coast of Canada. The study areas include Beaufort Sea, Mackenzie Delta channels and Banks Island in the western Canadian Arctic and James Bay, Hudson Bay, Nunavik, Resolute Bay, Victoria Strait, Baffin Island and Coronation Gulf in the eastern Canadian Arctic. Data was collected during ice-free and low tide conditions (where applicable) between July and September. Low-altitude helicopter surveys were conducted at each study site to capture video of the shoreline characteristics. In addition to acquiring videography, ground-based observations were recorded in several locations for validation. Shoreline segmentation was then carried out by manual interpretation of the oblique videography and the photos aided by ancillary data. This involved splitting and classifying the shoreline vectors based on homogeneity of the upper intertidal zone. Detailed geomorphological information (i.e. shoreline type, substrate, slope, height, accessibility etc.) describing the upper intertidal, lower intertidal, supratidal and backshore zones was extracted from the video and entered into a geospatial database using a customized data collection form. In addition, biological characteristics like biobands, water features, fauna, human use etc. observed along the coast were recorded. The data was also validated through ground observations (when available) and a second interpreter QA (quality analysis) was performed on each dataset (excluding Nunavik) to ensure high quality and consistency. The final dataset contains segments ranging in length from 150 metres to 2500 metres. In total, from 2010 to 2016, within the 8 study sites, about 16,800 km of shoreline were segmented.