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The National Pollutant Release Inventory (NPRI) is Canada's legislated, publicly accessible inventory of pollutant releases (to air, water and land), disposals and transfers for recycling. It is a key resource for: identifying pollution prevention priorities; supporting the assessment and risk management of chemicals, and air quality modelling; helping develop targeted regulations for reducing releases of toxic substances and air pollutants; encouraging actions to reduce the release of pollutants into the environment; and improving public understanding. The NPRI comprises: Information reported by facilities and published by Environment and Climate Change Canada under the authority of Sections 46 – 50 of the Canadian Environmental Protection Act, 1999 (CEPA 1999); and Comprehensive emission summaries and trends for key air pollutants, based on facility-reported data and emission estimates for other sources such as motor vehicles, residential heating, forest fires and agriculture. For the latest reporting year, 7,708 facilities reported to the NPRI on more than 300 listed substances. Comprehensive air pollutant emission summaries and trends were compiled by Environment and Climate Change Canada for criteria air contaminants (the main pollutants contributing to smog, acid rain and/or poor air quality), selected heavy metals and persistent organic pollutants.
The Physical Oceanography Distributed Active Archive Center (PO.DAAC) is an element of the Earth Observing System Data and Information System (EOSDIS). The EOSDIS provides science data to a wide community of users for NASA's Science Mission Directorate. Since the launch of NASA's first ocean-observing satellite, Seasat, in 1978, PO.DAAC has become the premier data center for measurements focused on ocean surface topography (OST), sea surface temperature (SST), ocean winds, sea surface salinity (SSS), gravity, ocean circulation and sea ice.In addition to providing access to its data holdings, PO.DAAC acts as a gateway to data stored at other ocean and climate archives. This and other tools and services enable PO.DAAC to support a wide user community working in areas such as ocean and climate research, applied science and industry, natural resource management, policy making, and general public consumption.
The datacommons@psu was developed in 2005 to provide a resource for data sharing, discovery, and archiving for the Penn State research and teaching community. Access to information is vital to the research, teaching, and outreach conducted at Penn State. The datacommons@psu serves as a data discovery tool, a data archive for research data created by PSU for projects funded by agencies like the National Science Foundation, as well as a portal to data, applications, and resources throughout the university. The datacommons@psu facilitates interdisciplinary cooperation and collaboration by connecting people and resources and by: Acquiring, storing, documenting, and providing discovery tools for Penn State based research data, final reports, instruments, models and applications. Highlighting existing resources developed or housed by Penn State. Supporting access to project/program partners via collaborative map or web services. Providing metadata development citation information, Digital Object Identifiers (DOIs) and links to related publications and project websites. Members of the Penn State research community and their affiliates can easily share and house their data through the datacommons@psu. The datacommons@psu will also develop metadata for your data and provide information to support your NSF, NIH, or other agency data management plan.
MODES focuses on the representation of the inertio-gravity circulation in numerical weather prediction models, reanalyses, ensemble prediction systems and climate simulations. The project methodology relies on the decomposition of global circulation in terms of 3D orthogonal normal-mode functions. It allows quantification of the role of inertio-gravity waves in atmospheric varibility across the whole spectrum of resolved spatial and temporal scales. MODES is compiled by using gfortran although other options have been succesfully tested. The application requires the use of the netcdf and (optionally) grib-api libraries.