{"facets":[{"admin":false,"displayName":"Record type","fieldName":"recordType","hierarchical":false,"results":[{"active":false,"count":14,"name":"Dataset","url":"http://data.inms.international:443/inms/documents?facet=recordType%7CDataset"},{"active":false,"count":15,"name":"Model","url":"http://data.inms.international:443/inms/documents?facet=recordType%7CModel"},{"active":false,"count":3,"name":"Third-party dataset","url":"http://data.inms.international:443/inms/documents?facet=recordType%7CThird-party%20dataset"}]},{"admin":false,"displayName":"Pollutant","fieldName":"inmsPollutant","hierarchical":false},{"admin":false,"displayName":"Model Type","fieldName":"modelType","hierarchical":false},{"admin":false,"displayName":"Demonstration Region","fieldName":"inmsDemonstrationRegion","hierarchical":false},{"admin":false,"displayName":"Project","fieldName":"inmsProject","hierarchical":false}],"numFound":32,"order":"asc","page":2,"prevPage":"http://data.inms.international:443/inms/documents","results":[{"catalogue":"inms","description":"The Common Agricultural Policy Regional Impact Analysis (CAPRI) modelling system is a large-scale comparative static, global multi-commodity,  partial equilibrium model for the agricultural sector. It has been developed for policy impact assessment of the European Common Agricultural Policy (CAP) and other policies affecting agriculture from global to regional and farm type scale, focusing on Europe .\n\nCAPRI simulates changes in global agricultural trade and EU supply of agricultural commodities under given technological, economic and policy constraints. Strengths of CAPRI include the possibility of good representation of EU policies, the detailed description of farm management in EU supply models, and the bio-physical approach based on nutrient mass-flow approach, including life-cycle assessment with regard to GHGs (operational) and nitrogen (operational end 2017) for agricultural commodities.\n\nThe code for the model is stored at Bonn University. For access contact Adrian Leip who will forward the request. \n","documentType":"CEH_MODEL","identifier":"dbab4238-3736-4797-859a-0fe8c41f28e9","incomingCitationCount":0,"keyword":["INMS"],"metadataDate":"2024-11-04T09:22:18.000Z","recordType":"Model","resourceIdentifier":["https://catalogue.ceh.ac.uk/id/0f717c5c-653f-4992-8dc5-56bf4d880d3c","https://data.inms.international/id/dbab4238-3736-4797-859a-0fe8c41f28e9"],"resourceType":"Model","shortenedDescription":"The Common Agricultural Policy Regional Impact Analysis (CAPRI) modelling system is a large-scale comparative static, global multi-commodity,  partial equilibrium model for the agricultural sector. It has been developed for policy impact assessment of the European Common…","state":"published","title":"CAPRI Modelling System (Common Agricultural Policy Regionalised Impact)","version":1.0,"view":["public","leav","inms-users"]},{"catalogue":"inms","description":"GAINS estimates emissions of air pollutants and greenhouse gases in future scenarios based on (1) projections of activity data and (2) rate of implementation of emission reducing technologies. An optimization algorithm allows to minimize costs of measures when intending to arrive at a given ecological “endpoint” (human health, biodiversity, GHG level etc.). \n\nMore than 200 individual abatement technologies and abatement costs are individually defined and implemented in connection with specific “target” emitted compound, interference with other compounds considered. Costs are computed as a function of investments, interest rates and country specific labour/energy/ commodity costs; co-benefits can be integrated in cost factors (e.g. negative energy costs).\n","documentType":"CEH_MODEL","identifier":"289b4b74-3284-4c5d-a9f7-1b22bf51421a","incomingCitationCount":0,"inmsScale":["Global"],"keyword":["Global","Greenhouse Gases","Air Pollution","INMS"],"metadataDate":"2024-11-04T09:36:31.000Z","recordType":"Model","resourceIdentifier":["https://catalogue.ceh.ac.uk/id/951d2c32-3d30-4e87-958a-65378ec1858c","https://data.inms.international/id/289b4b74-3284-4c5d-a9f7-1b22bf51421a"],"resourceType":"Model","shortenedDescription":"GAINS estimates emissions of air pollutants and greenhouse gases in future scenarios based on (1) projections of activity data and (2) rate of implementation of emission reducing technologies. An optimization algorithm allows to minimize costs of measures when intending…","state":"published","title":"GAINS Global","version":1.0,"view":["public","leav","inms-users"]},{"authorAffiliation":["Potsdam Institute  for Climate Impact Research"],"authorOrcid":["https://orcid.org/0000-0002-8242-6712"],"availability":"Unknown","catalogue":"inms","dataFormat":["NetCDF"],"description":"This dataset provides MAGPIE runs for seven Integrated Nitrogen Management System (INMS) scenarios from 2000 to 2100, with 10 years interval.\n\nThe last historical year is 2020.\n\nThe climate scenarios are represented as combination of SSP-RCP-N (shared socioeconomic pathways - representative concentration pathways - nitrogen pathways) :\n\n1) Business as usual (SSP5-RCP8.5 Low N ambition)\n2) Low N regulation (SSP2-RCP4.5 Low N ambition)\n3) Medium N regulation (SSP2-RCP4.5 Moderate N ambition)\n4) High N regulation (SSP2-RCP4.5 High N ambition)\n5) Best Case (SSP1-RCP4.5 High N ambition)\n6) Best Case + (SSP1-RCP4.5 High N ambition with ambitious diet shift and food loss/waste reductions)\n7) Bioenergy (SSP1-RCP2.6 High N ambition with low meat & dairy diet)","documentType":"GEMINI_DOCUMENT","identifier":"6ca8bc1e-c491-451f-a216-0f4869227dc4","incomingCitationCount":0,"inmsScale":["Global"],"keyword":["INMS","Global"],"keywordsOther":["Global"],"keywordsProject":["INMS"],"licence":"Non-Open government licence","locations":["POLYGON((-180 -90, -180 90, 180 90, 180 -90, -180 -90))"],"metadataDate":"2025-12-15T15:57:49.000Z","orcid":["https://orcid.org/0000-0002-8242-6712"],"organisation":["INMS","Potsdam Institute  for Climate Impact Research"],"recordType":"Dataset","resourceIdentifier":["https://data.inms.international/id/6ca8bc1e-c491-451f-a216-0f4869227dc4"],"resourceType":"Dataset","shortenedDescription":"This dataset provides MAGPIE runs for seven Integrated Nitrogen Management System (INMS) scenarios from 2000 to 2100, with 10 years interval.\n\nThe last historical year is 2020.\n\nThe climate scenarios are represented as combination of SSP-RCP-N (shared socioeconomic…","state":"published","supplementalDescription":["More information on the open-source model MAgPIE can be found at the link below.","Please cite the model using the following references:","Bodirsky, B. L. et al. Reactive nitrogen requirements to feed the world in 2050 and potential to mitigate nitrogen pollution. Nature Communications 5, (2014)."],"supplementalName":["Dietrich, J. P. et al. MAgPIE 4 – a modular open-source framework for modeling global land systems. Geoscientific Model Development 12, 1299–1317 (2019).","Dietrich, J. P. et al. MAgPIE - An Open Source land-use modeling framework - Version 4.3.0. (2020).","Bodirsky, B. L. et al. N2O emissions from the global agricultural nitrogen cycle – current state and future scenarios. Biogeosciences 9, 4169–4197 (2012)."],"title":"Results of the Model of Agricultural Production and its Impact on the Environment (MAgPIE) for seven Integrated Nitrogen Management System (INMS) global scenarios, 2000-2100","version":1.0,"view":["bodirsky@pik-potsdam.de","public","ccaporusso@gmx.com"]},{"authorAffiliation":["PBL Netherlands Environmental Assessment Agency","PBL Netherlands Environmental Assessment Agency "],"availability":"Unknown","catalogue":"inms","dataFormat":["NetCDF"],"description":"This dataset provides global and regional estimates of all components of nitrogen budgets in agricultural and natural ecosystems with a temporal resolution of five years that for the past and future period that goes from 2000 to 2100 at a 10 years interval. The last historical year is 2010.\n\nThe IMAGE-GNM model outputs were run for six different INMS scenarios:\n \nThe climate scenarios are represented as combination of SSP-RCP-N (shared socioeconomic pathways - representative concentration pathways - nitrogen pathways) :\n\n1) Business as usual (SSP5-RCP8.5 Low N ambition)\n2) Low N regulation (SSP2-RCP4.5 Low N ambition)\n3) Medium N regulation (SSP2-RCP4.5 Moderate N ambition)\n4) High N regulation (SSP2-RCP4.5 High N ambition)\n5) Best Case (SSP1-RCP4.5 High N ambition)\n6) Bioenergy (SSP1-RCP2.6 High N ambition with low meat & dairy diet)\n\nThis dataset has a spatial resolution of 0.5 x 0.5 degrees.","documentType":"GEMINI_DOCUMENT","identifier":"d97a8f08-94a4-4143-9714-b50b5b3d9225","incomingCitationCount":0,"keyword":["INMS"],"keywordsOther":["INMS"],"licence":"Non-Open government licence","lineage":" This dataset is the result of IMAGE-GNM output runs. The dataset was created with the IMAGE-GNM model version published by Beusen et al. (2015) in Geoscientific Model Development. Main inputs for IMAGE-GNM are from IMAGE3.2 (https://eartharxiv.org/repository/view/2759/). Validation of the model results with observations are shown in Beusen et al. (2022) in Global Environmental Change (https://doi.org/10.1016/j.gloenvcha.2021.102426).","locations":["POLYGON((-180 -90, -180 90, 180 90, 180 -90, -180 -90))"],"metadataDate":"2025-12-15T15:57:51.000Z","organisation":["PBL Netherlands Environmental Assessment Agency","PBL Netherlands Environmental Assessment Agency "],"recordType":"Dataset","resourceIdentifier":["https://data.inms.international/id/d97a8f08-94a4-4143-9714-b50b5b3d9225"],"resourceType":"Dataset","shortenedDescription":"This dataset provides global and regional estimates of all components of nitrogen budgets in agricultural and natural ecosystems with a temporal resolution of five years that for the past and future period that goes from 2000 to 2100 at a 10 years interval. The last…","state":"published","supplementalName":["Coupling global models for hydrology and nutrient loading to simulate nitrogen and phosphorus retention in surface water – description of IMAGE–GNM and analysis of performance"],"title":"Integrated Model to Assess the Global Environment (IMAGE) Global Nutrient Model (GNM) simulations of past and future (2000-2100) nitrogen budgets and individual budget terms for agricultural and natural ecosystems","version":1.0,"view":["public","inms-users","crimar"]},{"authorAffiliation":["NASA"],"availability":"Unknown","catalogue":"inms","description":"The NASA Goddard Institute for Space Studies (GISS) Earth System Model (ModelE) dataset comprises outputs from a coupled atmosphere-ocean general circulation model used to simulate past, present, and future climate conditions. ModelE integrates key components of the Earth system, including atmosphere, ocean, sea ice, and land surface, with optional modules for atmospheric chemistry, aerosols, and the carbon cycle.\n\nThe dataset typically includes variables such as surface and atmospheric temperature, precipitation, radiation fluxes, winds, humidity, ocean temperature and circulation, sea ice extent, and biogeochemical tracers (e.g., aerosols and greenhouse gases), depending on the specific model configuration and experiment (e.g., CMIP simulations).\n\nMethodologically, ModelE is a physically based, process-driven numerical model that solves equations governing fluid dynamics, thermodynamics, and radiative transfer on a global grid. Simulations are driven by prescribed boundary conditions (e.g., greenhouse gas concentrations, solar forcing) or fully coupled interactions between system components. Many outputs are produced as part of international intercomparison projects such as CMIP, enabling standardized evaluation of climate model performance and projections.","documentType":"GEMINI_DOCUMENT","identifier":"86f223bd-88ab-4a49-af0d-2e8e899e93f8","incomingCitationCount":0,"licence":"Non-Open government licence","locations":["POLYGON((-180 -90, -180 90, 180 90, 180 -90, -180 -90))"],"metadataDate":"2026-03-24T13:16:32.000Z","organisation":["NASA"],"recordType":"Third-party dataset","resourceIdentifier":["https://data.inms.international/id/86f223bd-88ab-4a49-af0d-2e8e899e93f8"],"resourceType":"Third-party dataset","shortenedDescription":"The NASA Goddard Institute for Space Studies (GISS) Earth System Model (ModelE) dataset comprises outputs from a coupled atmosphere-ocean general circulation model used to simulate past, present, and future climate conditions. ModelE integrates key components of the…","state":"published","title":"GISS Earth System Model: ModelE","version":1.0,"view":["public","inms-users","ccaporusso@gmx.com"]},{"authorAffiliation":["International Institute for Applied Systems Analysis (IIASA)"],"authorOrcid":["https://orcid.org/0000-0003-4463-7778"],"availability":"Unknown","catalogue":"inms","dataFormat":["NetCDF"],"description":"This dataset is a model output from the Global Biosphere Management Model (GLOBIOM). It provides global estimates of annual nitrogen cycle in the agricultural sector (including cropland, pasture, and livestock systems) for the period of 2010-2100 with 10 years interval under seven scenarios of nitrogen future described in Kanter et al. (2020), with 2010 as the only historical year.\nThe scenarios are represented as combination of SSP-RCP-N (shared socioeconomic pathways - representative concentration pathways - nitrogen pathways) :\n\nThe climate scenarios are represented as combination of SSP-RCP-N (shared socioeconomic pathways - representative concentration pathways - nitrogen pathways) :\n\n1) Business as usual (SSP5-RCP8.5 Low N ambition)\n2) Low N regulation (SSP2-RCP4.5 Low N ambition)\n3) Medium N regulation (SSP2-RCP4.5 Moderate N ambition)\n4) High N regulation (SSP2-RCP4.5 High N ambition)\n5) Best Case (SSP1-RCP4.5 High N ambition)\n6) Best Case + (SSP1-RCP4.5 High N ambition with ambitious diet shift and food loss/waste reductions)\n7) Bioenergy (SSP1-RCP2.6 High N ambition with low meat & dairy diet)\n\n\nThe data was produced as part of the INMS (International Nitrogen Managements System) project that is implemented by the UN Environment with funding through the Global Environment Facility (GEF) and executed through UK Centre for Ecology & Hydrology (UKCEH).","documentType":"GEMINI_DOCUMENT","identifier":"1f96dfea-b859-4196-a14e-4fb4a499f3f9","incomingCitationCount":0,"keyword":["INMS"],"keywordsProject":["INMS"],"licence":"Non-Open government licence","lineage":"The GLOBIOM model outputs on the nitrogen flows and budgets of agricultural sector for the period of 2000-2100 (historical period of 2000 and 2010, and projections of 2020 to 2100 ) have been produced under the INMS (Towards the Establishment of an International Nitrogen Management System) project. The data is produced on a 2 by 2 degree resolution over the world. Projections of the agricultural nitrogen cycle are produced under the nitrogen scenarios in the Kanter et al. (2020), which presents a framework for nitrogen future with combination of different shared socioeconomic pathways (SSP), representative concentration pathways (RCP), and nitrogen pathways (N). The SSP data can be found in the SSP database (https://tntcat.iiasa.ac.at/SspDb/).\n","locations":["POLYGON((-180 -90, -180 90, 180 90, 180 -90, -180 -90))"],"metadataDate":"2025-12-15T15:57:54.000Z","orcid":["https://orcid.org/0000-0003-4463-7778"],"organisation":["International Institute for Applied Systems Analysis (IIASA)"],"recordType":"Dataset","resourceIdentifier":["https://data.inms.international/id/1f96dfea-b859-4196-a14e-4fb4a499f3f9"],"resourceType":"Dataset","shortenedDescription":"This dataset is a model output from the Global Biosphere Management Model (GLOBIOM). It provides global estimates of annual nitrogen cycle in the agricultural sector (including cropland, pasture, and livestock systems) for the period of 2010-2100 with 10 years interval…","state":"published","supplementalName":["A framework for nitrogen futures in the shared socioeconomic pathways"],"title":"Global Biosphere Management Model (GLOBIOM) global simulations of agricultural nitrogen cycle for the period of 2010-2100 under various SSP-RCP-N (shared socioeconomic pathways - representative concentration pathways - nitrogen pathways ) scenario combinations","version":1.0,"view":["inms-users","crimar","public","changj@iiasa.ac.at","leclere@iiasa.ac.at"]},{"catalogue":"inms","description":"The IMAGE-GNM is a global, spatially explicit, distributed model that couples IMAGE (with the global hydrological model PCRaster Global Water Balance (PCR-GLOBWB)) as the basis for describing flow and retention/removal of N and P delivery from soils to surface waters. IMAGE-GNM is a coupled nutrient input–hydrology–in-stream nutrient retention model to quantitatively track the changes in the global freshwater N and P cycles. It includes the interactions between human-induced changes in climate, hydrology and nutrient loading. The hydrological system incorporates a distributed river model that merges both terrestrial and aquatic aspects and includes groundwater and upland areas,  wetlands, riparian zones and floodplains, and reservoirs.","documentType":"CEH_MODEL","identifier":"9bf0cca0-49d3-4119-afa5-f16a2f2491e9","incomingCitationCount":0,"inmsScale":["Global"],"keyword":["Water Quality","Global","Soil","Nitrogen","Phosphorous","Scenario Model","INMS"],"metadataDate":"2024-11-04T09:31:10.000Z","recordType":"Model","resourceIdentifier":["https://catalogue.ceh.ac.uk/id/29b66950-385f-43d6-8a55-7e431fcad0c9","https://data.inms.international/id/9bf0cca0-49d3-4119-afa5-f16a2f2491e9"],"resourceType":"Model","shortenedDescription":"The IMAGE-GNM is a global, spatially explicit, distributed model that couples IMAGE (with the global hydrological model PCRaster Global Water Balance (PCR-GLOBWB)) as the basis for describing flow and retention/removal of N and P delivery from soils to surface waters.…","state":"published","title":" IMAGE GNM - Integrated Model to Assess the Global Environment - Global Nutrient Model","version":1.0,"view":["public","leav","inms-users"]},{"catalogue":"inms","documentType":"CEH_MODEL","identifier":"d65a5816-585d-4899-9723-bdacd24246db","incomingCitationCount":0,"keyword":["INMS"],"metadataDate":"2024-11-04T09:26:46.000Z","recordType":"Model","resourceIdentifier":["https://catalogue.ceh.ac.uk/id/2788461a-3a34-4350-8b9c-9e2b6025bbba","https://data.inms.international/id/d65a5816-585d-4899-9723-bdacd24246db"],"resourceType":"Model","state":"published","title":"TM5","version":1.0,"view":["public","leav","inms-users"]},{"authorAffiliation":["PBL – Netherlands Environmental  Assessment Agency"],"availability":"Unknown","catalogue":"inms","dataFormat":["TIFF"],"description":"The datasets display the loss of plant biodiversity due to nitrogen deposition in the world in two past years (1970 and 2010) and six modelled scenarios for 2050. \nThe datasets have been created by the GLOBIO 4 model.","documentType":"GEMINI_DOCUMENT","identifier":"3fb43167-0d9b-43ba-bea4-230c64701f10","incomingCitationCount":1,"inmsScale":["Global"],"keyword":["INMS","Global"],"keywordsOther":["Global"],"keywordsProject":["INMS"],"licence":"Non-Open government licence","locations":["POLYGON((-180 -90, -180 90, 180 90, 180 -90, -180 -90))"],"metadataDate":"2025-12-15T15:57:46.000Z","organisation":["UK Centre for Ecology & Hydrology","INMS","PBL – Netherlands Environmental  Assessment Agency"],"recordType":"Dataset","resourceIdentifier":["https://data.inms.international/id/3fb43167-0d9b-43ba-bea4-230c64701f10"],"resourceType":"Dataset","shortenedDescription":"The datasets display the loss of plant biodiversity due to nitrogen deposition in the world in two past years (1970 and 2010) and six modelled scenarios for 2050. \nThe datasets have been created by the GLOBIO 4 model.","state":"published","title":"GLOBIO-terrestrial nitrogen deposition impacts on plant mean species abundance (MSA) for the years 1970, 2010 and 2050","version":1.0,"view":["public","ccaporusso@gmx.com"]},{"authorAffiliation":["European Commission, Joint Research Centre"],"availability":"Unknown","catalogue":"inms","dataFormat":["Comma-separated values (CSV)","NetCDF"],"description":"It includes emissions time series and gridmaps for CO2, CH4 and N2O. Carbon dioxide emissions are provided for the period 1970-2018, and CH4 and N2O for 1970-2015. \nEDGAR aims to inform scientists and policy makers on the evolution of the emission inventories over time for all world countries and to provide the scientific community 0.1degX0.1deg gridmaps representing the emissions sources. \nEmission gridmaps are expressed in ton substance / 0.1degree x 0.1degree / year for the .txt files and in kg substance /m2 /s for the .nc files.","documentType":"GEMINI_DOCUMENT","identifier":"78701875-cfa2-48d6-b8bb-9fd7c4beb966","incomingCitationCount":0,"licence":"Non-Open government licence","lineage":"The emissions in EDGAR are estimated based on the activity data from the international statistics (e.g. IEA, USGS, IFA, FAO etc.) and emissions factors from the official guidebooks such as IPCC and EEA/EMEP, and scientific literature. For emissions distribution on global gridmaps we use proxy data such as population, location of the point sources etc.","locations":["POLYGON((-180 -90, -180 90, 180 90, 180 -90, -180 -90))"],"metadataDate":"2024-11-01T10:28:15.000Z","organisation":["European Commission, Joint Research Centre"],"recordType":"Third-party dataset","resourceIdentifier":["https://data.inms.international/id/78701875-cfa2-48d6-b8bb-9fd7c4beb966"],"resourceType":"Third-party dataset","shortenedDescription":"It includes emissions time series and gridmaps for CO2, CH4 and N2O. Carbon dioxide emissions are provided for the period 1970-2018, and CH4 and N2O for 1970-2015. \nEDGAR aims to inform scientists and policy makers on the evolution of the emission inventories over time…","state":"published","title":"Emissions Database for Global Atmospheric Research (EDGAR) Global Greenhouse Gas Emissions, 1970-2015","version":1.0,"view":["public","inms-users","crimar"]},{"catalogue":"inms","description":"Miterra-Global is an environmental impact assessment model at global scale. The model can be used to assess the effects of the implementation of ammonia (NH3) and nitrate (NO3) measures and policies on the emissions of NH3, (nitrous oxide) N2O, N oxides (NOx), and methane (CH4) to the atmosphere, leaching of N (including nitrate) to ground water and surface waters, and on the phosphorus (P) balance at regional level. The emission and leaching factors are used to calculate greenhouse gas emissions (CO2, CH4, N2O) in a deterministic and annual basis. Model inputs refer to: (1) activity data, such as animal numbers, crop yields and N fertilizer amounts, and (2) spatial environmental data, such as climate and land use.","documentType":"CEH_MODEL","identifier":"5765d43a-458d-48ed-a7b2-5bf1d208ba73","incomingCitationCount":0,"inmsScale":["Global"],"keyword":["Global","Greenhouse Gases","INMS","mitigation practices"],"locations":["POLYGON((-180 -90, -180 90, 180 90, 180 -90, -180 -90))"],"metadataDate":"2024-11-04T09:37:50.000Z","recordType":"Model","resourceIdentifier":["https://catalogue.ceh.ac.uk/id/bb33db1a-324e-4be6-8114-9d7f5bd18c08","https://data.inms.international/id/5765d43a-458d-48ed-a7b2-5bf1d208ba73"],"resourceType":"Model","shortenedDescription":"Miterra-Global is an environmental impact assessment model at global scale. The model can be used to assess the effects of the implementation of ammonia (NH3) and nitrate (NO3) measures and policies on the emissions of NH3, (nitrous oxide) N2O, N oxides (NOx), and methane…","state":"published","title":"MITERRA Global","version":1.0,"view":["inms-users","chantal.hendriks@wur.nl","public","leav"]},{"catalogue":"inms","description":"The EMEP4Earth model framework consists of an atmospheric chemistry transport model which simulates hourly to annual average atmospheric composition and deposition of pollutants, and the weather research and forecast model. Pollutants simulated include PM10, PM2.5, secondary organic aerosols, elemental carbon, secondary inorganic aerosols, SO2, NH3, NOx, and O3. Dry and wet deposition of pollutants are also calculated. \nEMEP4Earth operates at horizontal resolutions ranging from 1°×1° for the global domain down to ~1.1 km2 for specific regional domains (i.e. UK) The model setup is very flexible and can be changed for utilisation in scientific and/or policy applications. The default vertical domain ranges from ~50 m (thickness of the first layer at the surface) up to ~16 km (at the top of the vertical domain - 100 hPa), however setting a more flexible horizontal and vertical resolution is also possible.","documentType":"CEH_MODEL","identifier":"9b8b52fe-df65-48e6-a9f3-25c0a47ff636","incomingCitationCount":0,"keyword":["INMS"],"metadataDate":"2024-11-04T09:28:46.000Z","recordType":"Model","resourceIdentifier":["https://catalogue.ceh.ac.uk/id/e30f10ed-2147-45b6-be94-b94f19487de8","https://data.inms.international/id/9b8b52fe-df65-48e6-a9f3-25c0a47ff636"],"resourceType":"Model","shortenedDescription":"The EMEP4Earth model framework consists of an atmospheric chemistry transport model which simulates hourly to annual average atmospheric composition and deposition of pollutants, and the weather research and forecast model. Pollutants simulated include PM10, PM2.5,…","state":"published","title":"EMEP4Earth (WRF-EMEP global)","version":1.0,"view":["public","leav","inms-users"]}],"rows":20,"url":"http://data.inms.international:443/inms/documents?page=2"}