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We have found 87 datasets for the keyword "fine particles". You can continue exploring the search results in the list below.
Datasets: 103,466
Contributors: 42
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87 Datasets, Page 1 of 9
Regional Air Quality Deterministic Prediction System (RAQDPS)
The Regional Air Quality Deterministic Prediction System (RAQDPS) takes into account physical and chemical processes to produce deterministic forecasts of the concentration of chemical species of interest to air quality. These chemical constituents include gases such as O3, SO2, NO, and NO2, in addition to fine particles PM2.5 (diameter of 2.5 micrometers or less) and coarse particles PM10 (diameter of 10 micrometers or less). The PM2.5 and PM10 now include the contribution of wildfire emissions as well as anthropogenic and biogenic emission sources. The forecasts are available for the present up to 72 hours in the future twice a day (run 00 UTC and 12 UTC). The geographic domain of the RAQDPS covers most of North America with a horizontal resolution of 10km.
Maritime region grain size data
Fisheries and Oceans Canada (DFO) Maritime Science Branch has collected grain size data from sediment and water column samples using bottle samples, sediment cores, and sediment grabs as part of numerous research projects not only in the Atlantic provinces, but also worldwide. The data collected by DFO focuses on the fine grained (<1mm) particles as these are both a source of food and means of contaminant transport. Grain size data are used to study the fate and distribution of complimentary chemistries like heavy metals, pesticides, hydrocarbons, aquaculture waste as well as a variety of physical processes such as the resuspension and transport of sediment.
Project: RSQA Nomad Station
As part of special projects, the Air Quality Monitoring Network (RSQA) measures the concentrations of pollutants at the nomadic station. Its objective is to deepen our knowledge of ambient air quality. As its name indicates, this station will change location at the end of each measurement campaign, which may last from 12 to 24 months.The Nomad station continuously measures: ozone (O3), fine particles (PM2.5), carbon monoxide (CO), sulfur dioxide (SO2), nitrogen oxides (NOx), elemental carbon (CE) and ultrafine particles (PUF); as well as spot measurements of breathable particles (PM10) and total suspended particles (PST) with metal analysis on the latter.**This third party metadata element was translated using an automated translation tool (Amazon Translate).**
Regional Deterministic Air Quality Analysis(RDAQA)
Regional Deterministic Air Quality Analysis (RDAQA) is an objective analysis of surface pollutants that combines numerical forecasts from the Regional Air Quality Deterministic Prediction System (RAQDPS) with hourly observations from various monitoring networks in North America, including the Canadian measurement networks operated by the provinces, territories and certain cities, as well as the various American networks in the context of the AIRNow program administered by US/EPA (US Environmental Protection Agency). RDAQA analysis provides the best description of current air quality conditions, and is used to inform the public, meteorologists in the various Environment and Climate Change Canada forecasting offices, Health Canada and other users about the distribution of air pollutants near the ground, and the performance of forecasting models. Each hour, a preliminary product is available approximately one hour after the observation measurement time, while final and Firework products are available approximately two hours after the measurement time. The preliminary and final products contain analysis of the chemical constituents O3, SO2, NO, NO2, PM2.5 (fine particles with diameters of 2.5 micrometers or less) and PM10 (coarse particles with diameters of 10 micrometers or less), while the Firework product contains analysis of PM2.5 and PM10.
Air quality – Peak fine particulate matter concentrations at monitoring stations
The Canadian Environmental Sustainability Indicators (CESI) program provides data and information to track Canada's performance on key environmental sustainability issues. The Air quality indicators track ambient concentrations of fine particulate matter, ground-level ozone, sulphur dioxide, nitrogen dioxide and volatile organic compounds at the national, regional and urban area levels and at local monitoring stations. 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.Canadian Environmental Sustainability Indicators: https://www.canada.ca/environmental-indicators
Pollution from wildfires Cumulative Effects products
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.
Water Erosion Risk
This map displays the risk of soil degradation by water in the agricultural region of Alberta. Water erosion is a concern because it reduces soil quality by removing soil particles and nutrients, and reduces water quality if these particles are carried into nearby water bodies. The map uses five classes to describe the water erosion risk on bare, unprotected mineral soil: negligible, low, moderate, high and severe.This resource was created using ArcGIS, originally published as a print map in 1993 .
Wind Erosion Risk
This map displays the risk of soil degradation by wind in the agricultural region of Alberta. Wind erosion is a concern because it reduces soil quality by removing soil nutrients, smaller soil particles and organic matter. Wind erosion can reduce air quality during extreme erosion events and also reduce water quality if eroded particles drift into streams and lakes. The map uses five classes to describe the wind erosion risk on bare, unprotected mineral soil: negligible, low, moderate, high and severe. This resource was created using ArcGIS. It was originally published as a print map in 1989.
Networks and Studies
Air Monitoring Networks and Studies produce data that represent a wide variety of observations and measurements. Multiple data types (also called collections) can be produced by a single network and data collections can have contributions from multiple networks. The data are organised as follows: 1. Atmospheric Gases, 2. Atmospheric Particles, 3. Atmospheric Precipitation Chemistry, 4. Combined Atmospheric Gases and Particles 5. Special Studies of Atmospheric Gases, Particles and Precipitation Chemistry Networks and Studies contributing to the Canadian National Atmospheric Chemistry Database and Analysis system (NAtChem) are from Canadian federal and provincial networks (past and present) and also include U.S. historical networks (these data are not available elsewhere). Information about these contributing networks, for each of these collection and product groups, can be found in each network's description documentation.
Soil Texture
This map illustrates the distribution of soil parent material textures in the agricultural region of Alberta. Soil texture is defined by the relative proportions of the sand, silt and clay particles present. Soil textures are identified by classes using the Soil Texture Triangle illustrated below. The Soil Texture Triangle identifies the textural class of a soil at the intersection of the percent sand (x-axis) and the percent clay (y-axis). The percent silt of the soil is the remainder to add up to 100 percent. This resource was created in 2002 using ArcGIS.
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