Metadata fields
Metadata fields can be used to filter data.
These fields affect behavior only in the visualization and analysis modes (Dashboard, Report and Library) and must be specified in the subsections.
For the latest release of GHOST, the following metadata fields are supported:
Parameter |
Description |
Default |
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Version of GHOST. |
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reference ID for station. |
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WIGOS station identifier (WSI). |
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Name of the local timezone that the measuring station is located in. This is automatically generated using Timezone Finder Python package (taking longitude and latitude as inputs). |
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Geodetic latitude of measuring instrument, in decimal degrees North, following the stated horizontal datum. |
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Geodetic longitude of measuring instrument, in decimal degrees East, following the stated horizontal datum. |
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Altitude of the ground level at the station, relative to the stated vertical datum, in metres. |
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Height above the ground of the inlet/instrument/sampler, in metres. |
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Altitude of the inlet/instrument/sampler, relative to the stated vertical datum, in metres. |
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The ellipsoidal model of the earth used as a basis for 2D and 3D geographic coordinate systems. |
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Name of the horizontal datum used in defining geodetic latitudes and longitudes on the Earth’s surface. The datum is set when positioning an ellipsoid model of the Earth to an anchor point. If not explicitely stated then this is assumed to be ‘World Geodetic System 1984’. |
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Name of the vertical datum used to define vertical elevation on the Earth. The datum is a surface of zero elevation to which other heights can be reference against. If not explicitely stated then this is assumed to be ‘tidal - mean sea level’. |
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Name of the projected coordinate system of the original provided station position x, y coordinates. If the original coordinates are not projected, then this is set as ‘geographic’. |
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Distance to the nearest building of the inlet/instrument/sampler, in metres. |
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Distance to the street kerb of the inlet/instrument/sampler, in metres. |
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Distance to the nearest road junction of the inlet/instrument/sampler, in metres. |
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Distance to the main emission source (see variable: “main_emission_source”) of the inlet/instrument/sampler, in kilometres. |
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The declaration of the emissions from domestic heating for a representative area of approximately 1 km². |
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The emissions from road traffic for a section of road representative of at least 100 m. |
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The emissions from industry for a representative area of approximately 1 km². |
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The average height of the building facade adjacent to the station (in metres) at the location of the station. |
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Width of the street where measurements are being made (if applicable), in metres. |
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Type of street where measurements are being made (if applicable). |
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Average daytime speed of the passing traffic where measurements are being made (if applicable), in kilometres per hour. |
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Average number of vehicles passing daily. |
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Data level of data reported. This varies per network. If data level is variable per measurement, and not static per reported file, then this is set as “variable”. If there is no reported data level this is set as “none” |
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Name of the climatology of which the observations pertain to. |
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Name of station where the measurement was conducted. |
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Name of the city the station is located in. |
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Name of the country the station is located in. |
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Name of the first (i.e. largest) country administrative division in which the station lies, e.g. countries within soverign state, state, province, county etc. These are defined for the purposes of managing of land and the affairs of people. This is automatically generated using Reverse Geocoder Python package (taking longitude and latitude as inputs). |
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Name of the second (i.e. second largest) country administrative division in which the station lies, e.g. countries within soverign state, state, province, county etc. These are defined for the purposes of managing of land and the affairs of people. This is automatically generated using Reverse Geocoder Python package (taking longitude and latitude as inputs). |
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Population size of the nearest urban settlement. |
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Radius of representativity of the measurements made (i.e. for what distance scale around the sampling point would the measurements be very similar?), given in kilometres. A quantitative version of the “measurement_scale” classification. |
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The name of the network which reports data for the specific station in question. |
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String pair of associated network name and station reference. Format: network1:station_reference1;network2:station_reference2 |
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Standardised network provided classification, describing type of area a measurement station is situated in. |
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Standardised network provided classification, categorising the type of air measured by a station. |
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Standardised network provided classification, describing the main emission source influencing air measured at a station. |
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Standardised network provided classification, describing the dominant land use in the area of the reporting station. |
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Standardised network provided classification, describing the location of the station in relation to nearby buildings and trees. |
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Standardised network provided classification, describing the regional dispersion characteristics or topographic situation on a scale of several kilometres affecting the station. |
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Standardised network provided classification, a denotation of the geographic scope of the air quality measurements made. |
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European Soil Data Centre (ESDAC) Iwahashi landform classification. The classification presents relief classes which are classified using an unsupervised nested-means algorithms and a three part geometric signature. Slope gradient, surface texture and local convexity are calculated based on the SRTM30 digital elevation model, within a given window size and classified according to the inherent data set properties. This is a dynamic landform classification method. Native resolution of 0.0083 x 0.0083 degrees. A correction for coastal sites is made: if the native class is “water”, then the modal classification of the neighbouring grid boxes is used instead (lowest code kept preferentially in case of a tie). If the site is truly an “ocean” site, all the surrounding gridcells will be water also, and therefore the class will be maintained as “water”. |
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Modal European Soil Data Centre (ESDAC) Iwahashi landform classification in radius of 5km around station location. |
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Modal European Soil Data Centre (ESDAC) Iwahashi landform classification in radius of 25km around station location. |
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European Soil Data Centre (ESDAC) Meybeck landform classification. The classification presents relief classes which are calculated based on the relief roughness. Roughness and elevation are classified based on a digital elevation model according to static thresholds, with a given window size. This is a static landform classification method. Native resolution of 0.0083 x 0.0083 degrees. A correction for coastal sites is made: if the native class is “water”, then the modal classification of the neighbouring grid boxes is used instead (lowest code kept preferentially in case of a tie). If the site is truly an “ocean” site, all the surrounding gridcells will be water also, and therefore the class will be maintained as “water”. |
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Modal European Soil Data Centre (ESDAC) Meybeck landform classification in radius of 5km around station location. |
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Modal European Soil Data Centre (ESDAC) Meybeck landform classification in radius of 25km around station location. |
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Global Human Settlement Layer (GHSL) settlement model classification (technical label: GHS_SMOD_POPMT_GLOBE_R2019A). The classification delineates and classify settlement typologies via a logic of population size, population and built-up area densities as a refinement of the ‘degree of urbanization’ method described by EUROSTAT. The classification is derived by using the GHS_POP_MT_GLOBE_R2019A and GHS_BUILT_LDSMT_GLOBE_R2018A products. The GHS Settlement Model grid is an improvement of the GHS Settlement Grid (R2016A) introducing a more detailed classification of settlements in two levels, also called ‘refined degree of urbanization’. The Settlement Model is provided at detailed level (Second Level - L2). The First Level, as a porting of the Degree of Urbanization adopted by EUROSTAT can be obtained aggregating L2. Native resolution of 1.0 x 1.0 kilometres. |
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Modal Global Human Settlement Layer (GHSL) settlement model classification in radius of 5km around station location. |
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Modal Global Human Settlement Layer (GHSL) settlement model classification in radius of 25km around station location. |
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Joly-Peuch European classification code (range of 1-10) designed to objectively stratify stations between those displaying rural and urban signatures (most rural == 1, most urban == 10). This classification is objectively made per species. The species that this is done for are: O3, NO2, SO2, CO, PM10, PM2.5. See reference here: https://www.sciencedirect.com/science/article/abs/pii/S1352231011012088 |
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Koppen-Geiger classification, classifying the global climates into 5 main groups (30 total groups with subcategories). Native resolution of 0.0083 x 0.0083 degrees. A correction for coastal sites is made: if the native class is “water”, then the modal classification of the neighbouring grid boxes is used instead (lowest code kept preferentially in case of a tie). If the site is truly an “ocean” site, all the surrounding gridcells will be water also, and therefore the class will be maintained as “water”. See citation: Beck, H.E., N.E. Zimmermann, T.R. McVicar, N. Vergopolan, A. Berg, E.F. Wood: Present and future Köppen-Geiger climate classification maps at 1-km resolution, Nature Scientific Data, 2018. |
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Modal Koppen-Geiger classification in radius of 5km around station location. |
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Modal Koppen-Geiger classification in radius of 25km around station location. |
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Majority land use class from the Moderate Resolution Imaging Spectroradiometer (MODIS) Land Cover Climate Modeling Grid (CMG) MCD12C1 version 6, using the International Geosphere-Biosphere Programme (IGBP) classification. Native resolution of 0.05 x 0.05 degrees. See dataset user guide here: https://lpdaac.usgs.gov/documents/101/MCD12_User_Guide_V6.pd. A correction for coastal sites is made: if the native class is “water bodies”, then the modal classification of the neighbouring grid boxes is used instead (lowest code kept preferentially in case of a tie). If the site is truly an “ocean” site, all the surrounding gridcells will be water also, and therefore the class will be maintained as “water”. |
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Modal land use in radius of 5km around the station location from the Moderate Resolution Imaging Spectroradiometer (MODIS) Land Cover Climate Modeling Grid (CMG) MCD12C1 version 6, using the International Geosphere-Biosphere Programme (IGBP) classification. |
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Modal land use in radius of 25km around the station location from the Moderate Resolution Imaging Spectroradiometer (MODIS) Land Cover Climate Modeling Grid (CMG) MCD12C1 version 6, using the International Geosphere-Biosphere Programme (IGBP) classification. |
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Majority land use class from the Moderate Resolution Imaging Spectroradiometer (MODIS) Land Cover Climate Modeling Grid (CMG) MCD12C1 version 6, using the University of Maryland (UMD) classification. Native resolution of 0.05 x 0.05 degrees. See dataset user guide here: https://lpdaac.usgs.gov/documents/101/MCD12_User_Guide_V6.pd. A correction for coastal sites is made: if the native class is “water bodies”, then the modal classification of the neighbouring grid boxes is used instead (lowest code kept preferentially in case of a tie). If the site is truly an “ocean” site, all the surrounding gridcells will be water also, and therefore the class will be maintained as “water”. |
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Modal land use in radius of 5km around the station location from the Moderate Resolution Imaging Spectroradiometer (MODIS) Land Cover Climate Modeling Grid (CMG) MCD12C1 version 6, using the University of Maryland (UMD) classification. |
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Modal land use in radius of 25km around the station location from the Moderate Resolution Imaging Spectroradiometer (MODIS) Land Cover Climate Modeling Grid (CMG) MCD12C1 version 6, using the University of Maryland (UMD) classification. |
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Majority Leaf Area Index class from the Moderate Resolution Imaging Spectroradiometer (MODIS) Land Cover Climate Modeling Grid (CMG) MCD12C1 version 6. Native resolution of 0.05 x 0.05 degrees. See dataset user guide here: https://lpdaac.usgs.gov/documents/101/MCD12_User_Guide_V6.pd. A correction for coastal sites is made: if the native class is “water bodies”, then the modal classification of the neighbouring grid boxes is used instead (lowest code kept preferentially in case of a tie). If the site is truly an “ocean” site, all the surrounding gridcells will be water also, and therefore the class will be maintained as “water”. |
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Modal Leaf Area Index in radius of 5km around the station location from the Moderate Resolution Imaging Spectroradiometer (MODIS) Land Cover Climate Modeling Grid (CMG) MCD12C1 version 6. |
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Modal Leaf Area Index in radius of 25km around the station location from the Moderate Resolution Imaging Spectroradiometer (MODIS) Land Cover Climate Modeling Grid (CMG) MCD12C1 version 6. |
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World Meteorological Organization (WMO) region of station. The available regions are: Africa, Asia, South America, “Northern America, Central America and the Caribbean”, South-West Pacific, Europe and Antarctica. |
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Terrestrial Ecoregions of the World (TEOW) World Wildlife Foundation (WWF) classification. There are 825 terrestrial ecoregions. Ecoregions are relatively large units of land containing distinct assemblages of natural communities and species, with boundaries that approximate the original extent of natural communities prior to major land-use change. See citation: Olson, D. M., Dinerstein, E., Wikramanayake, E. D., Burgess, N. D., Powell, G. V. N., Underwood, E. C., DAmico, J. A., Itoua, I., Strand, H. E., Morrison, J. C., Loucks, C. J., Allnutt, T. F., Ricketts, T. H., Kura, Y., Lamoreux, J. F., Wettengel, W. W., Hedao, P., Kassem, K. R. 2001. Terrestrial ecoregions of the world: a new map of life on Earth. Bioscience 51(11):933-938. |
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Terrestrial Ecoregions of the World (TEOW) World Wildlife Foundation (WWF) classification. There are 8 biogeographical realms. See citation: Olson, D. M., Dinerstein, E., Wikramanayake, E. D., Burgess, N. D., Powell, G. V. N., Underwood, E. C., DAmico, J. A., Itoua, I., Strand, H. E., Morrison, J. C., Loucks, C. J., Allnutt, T. F., Ricketts, T. H., Kura, Y., Lamoreux, J. F., Wettengel, W. W., Hedao, P., Kassem, K. R. 2001. Terrestrial ecoregions of the world: a new map of life on Earth. Bioscience 51(11):933-938. |
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Terrestrial Ecoregions of the World (TEOW) World Wildlife Foundation (WWF) classification. There are 14 biomes. See citation: Olson, D. M., Dinerstein, E., Wikramanayake, E. D., Burgess, N. D., Powell, G. V. N., Underwood, E. C., DAmico, J. A., Itoua, I., Strand, H. E., Morrison, J. C., Loucks, C. J., Allnutt, T. F., Ricketts, T. H., Kura, Y., Lamoreux, J. F., Wettengel, W. W., Hedao, P., Kassem, K. R. 2001. Terrestrial ecoregions of the world: a new map of life on Earth. Bioscience 51(11):933-938. |
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University of Maryland Baltimore County (UMBC) anthrome classification, describing the anthropogenic land use (for the year 2000). There are 20 distinct classifications. Native resolution of 0.0833 x 0.0833 degrees. A correction for coastal sites is made: if the native anthrome class is “water”, then the modal classification of the neighbouring grid boxes is used instead (lowest code kept preferentially in case of a tie). If the site is truly an “ocean” site, all the surrounding gridcells will be water also, and therefore the class will be maintained as “water”. |
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University of Maryland Baltimore County (UMBC) modal anthrome classification in radius of 5km around station location. |
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University of Maryland Baltimore County (UMBC) modal anthrome classification in radius of 25km around station location. |
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EDGAR v4.3.2 annual average BC emissions, in kilograms per squared metre per second. Native resolution of 0.1 x 0.1 degrees. |
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EDGAR v4.3.2 annual average CO emissions, in kilograms per squared metre per second. Native resolution of 0.1 x 0.1 degrees. |
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EDGAR v4.3.2 annual average NH3 emissions, in kilograms per squared metre per second. Native resolution of 0.1 x 0.1 degrees. |
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EDGAR v4.3.2 annual average NMVOC emissions, in kilograms per squared metre per second. Native resolution of 0.1 x 0.1 degrees. |
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EDGAR v4.3.2 annual average NOx emissions, in kilograms per squared metre per second. Native resolution of 0.1 x 0.1 degrees. |
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EDGAR v4.3.2 annual average OC emissions, in kilograms per squared metre per second. Native resolution of 0.1 x 0.1 degrees. |
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EDGAR v4.3.2 annual average PM10 emissions, in kilograms per squared metre per second. Native resolution of 0.1 x 0.1 degrees. |
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EDGAR v4.3.2 annual average biogenic PM2.5 emissions, in kilograms per squared metre per second. Native resolution of 0.1 x 0.1 degrees. |
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EDGAR v4.3.2 annual average fossil fuel PM2.5 emissions, in kilograms per squared metre per second. Native resolution of 0.1 x 0.1 degrees. |
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EDGAR v4.3.2 annual average SO2 emissions, in kilograms per squared metre per second. Native resolution of 0.1 x 0.1 degrees. |
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Altitude from ASTER v3 digital elevation model, relative to EGM96 geoid vertical datum, in metres. The dataset was generated using 1,880,306 Level-1A scenes (taken from the NASA TERRA spacecraft) acquired between March 1, 2000 and November 30, 2013. The ASTER GDEM was created by stacking all individual cloud-masked scene DEMs and non-cloud-masked scene DEMs, then applying various algorithms to remove abnormal data. A statistical approach is not always effective for anomaly removal in areas with a limited number of images. Several existing reference DEMs were used to replace residual anomalies caused by the insufficient number of stacked scenes. In addition to ASTER GDEM, the ASTER Global Water Body Database (ASTWBD) was generated as a by-product to correct elevation values of water body surfaces like sea, rivers, and lakes. The ASTWBD was applied to GDEM to provide proper elevation values for water body surfaces. The sea and lake have a flattened elevation value. The river has a stepped-down elevation value from the upper stream to the lower stream. Native resolution of 1 arc second ~= 30m at the equator. |
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Altitude from ETOPO1 digital elevation model, relative to sea level vertical datum, in metres. Over Antarctica and Greenland the elevation given is on top of the ice sheets. Native resolution of 1 arc minute. A correction for coastal sites is made: if the derived altitude is <= -5 m, the maximum altitude of the neighbouring grid boxes will be used instead. If all neighbouring grid boxes have altitudes <= -5 m, the original value will be retained. |
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Altitude difference between the ETOPO1_altitude, and the minimum ETOPO1 altitude in a radius of 5km around the station location, in metres. |
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Global Human Settlement Layer (GHSL) built up area density (technical label: GHS_BUILT_LDSMT_GLOBE_R2018A), in units of built-up area percent per gridcell (0-100). The product is a multitemporal information layer on built-up presence as derived from Landsat image collections (GLS1975, GLS1990, GLS2000, and ad-hoc Landsat 8 collection 2013/2014). Native resolution of 0.25 x 0.25 kilometres. |
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Global Human Settlement Layer (GHSL) average built up area density in a radius of 5km around the station location. |
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Global Human Settlement Layer (GHSL) average built up area density in a radius of 25km around the station location. |
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Global Human Settlement Layer (GHSL) max built up area density in a radius of 5km around the station location. |
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Global Human Settlement Layer (GHSL) max built up area density in a radius of 25km around the station location. |
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Global Human Settlement Layer (GHSL) population density (technical label: GHS_POP_MT_GLOBE_R2019A), in populus per squared kilometre. It depicts the distribution of population, expressed as the number of people per cell. Residential population estimates for target years 1975, 1990, 2000 and 2015 provided by CIESIN GPWv4.10 were disaggregated from census or administrative units to grid cells, informed by the distribution and density of built-up as mapped in the GHSL global layer per corresponding epoch. Native resolution of 0.25 x 0.25 kilometres. |
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Global Human Settlement Layer (GHSL) average population density in a radius of 5km around the station location. |
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Global Human Settlement Layer (GHSL) average population density in a radius of 25km around the station location. |
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Global Human Settlement Layer (GHSL) max population density in a radius of 5km around the station location. |
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Global Human Settlement Layer (GHSL) max population density in a radius of 25km around the station location. |
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Gridded Population of the World (GPW) population density, in populus per squared kilometre, from either version 3 and 4 of the provided gridded datasets, dependent on the data year: v3 (1990-2000), v4 (2000-2015). Native resolution of 0.04166 x 0.04166 for v3 data; native resolution of 0.0083 x 0.0083 degrees for v4 data. |
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Gridded Population of the World (GPW) average population density in a radius of 5km around the station location. |
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Gridded Population of the World (GPW) average population density in a radius of 25km around the station location. |
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Gridded Population of the World (GPW) maximum population density in a radius of 5km around the station location. |
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Gridded Population of the World (GPW) maximum population density in a radius of 25km around the station location. |
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National Oceanic and Atmospheric Administration (NOAA), Defense Meteorological Satellite Program - Operational Linescane System (DMSP-OLS) version 4 nighttime stable lights. Native resolution of 0.0083 x 0.0083 degrees. The values represent a brightness index ranging from 0 to 63. The sensor saturates at a value of 63. |
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National Oceanic and Atmospheric Administration (NOAA), Defense Meteorological Satellite Program - Operational Linescane System (DMSP-OLS) version 4 average nighttime stable lights in 5km radius around the station location. The values represent a brightness index ranging from 0 to 63. The sensor saturates at a value of 63. |
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National Oceanic and Atmospheric Administration (NOAA), Defense Meteorological Satellite Program - Operational Linescane System (DMSP-OLS) version 4 average nighttime stable lights in 25km radius around the station location. The values represent a brightness index ranging from 0 to 63. The sensor saturates at a value of 63. |
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National Oceanic and Atmospheric Administration (NOAA), Defense Meteorological Satellite Program - Operational Linescane System (DMSP-OLS) version 4 maximum nighttime stable lights in 5km radius around the station location. The values represent a brightness index ranging from 0 to 63. The sensor saturates at a value of 63. |
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National Oceanic and Atmospheric Administration (NOAA), Defense Meteorological Satellite Program - Operational Linescane System (DMSP-OLS) version 4 maximum nighttime stable lights in 25km radius around the station location. The values represent a brightness index ranging from 0 to 63. The sensor saturates at a value of 63. |
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AURA Ozone monitoring instrument (OMI) level3 column annual average NO2, in molecules per squared centimetres. Native resolution of 0.25 x 0.25 degrees. |
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AURA Ozone monitoring instrument (OMI) level3 column cloud screened (where cloud fraction is less than 30 percent) annual average NO2, in molecules per squared centimetres. Native resolution of 0.25 x 0.25 degrees. |
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AURA Ozone monitoring instrument (OMI) level3 tropospheric column annual average NO2, in molecules per squared centimetres. Native resolution of 0.25 x 0.25 degrees. |
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AURA Ozone monitoring instrument (OMI) level3 tropospheric column cloud screened (where cloud fraction is less than 30 percent) annual average NO2, in molecules per squared centimetres. Native resolution of 0.25 x 0.25 degrees. |
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Proximity to the coastline provided by the NASA Goddard Space Flight Center (GSFC) Ocean Color Group, in kilometres, produced using the Generic Mapping Tools package. Native resolution of 0.01 x 0.01 degrees. Negative distances represent locations over land (including land-locked bodies of water), while positive distances represent locations over the ocean. There is an uncertainty of up to 1 km in the computed distance at any given point. |
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Standardised primary sampling type. |
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Standardised name of the primary sampling instrument (if no specific instrument is used, or known, this is the standardised primary sampling type). |
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Volume (litres) of fluid which passes to the primary sampling instrument, per unit time (minutes), as given in instrumental manual/documentation. Can be a range: e.g. 1.0-3.0. |
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Volume (litres) of fluid which passes to the primary sampling instrument, per unit time (minutes), as given in metadata. Can be a range: e.g. 1.0-3.0. |
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Miscellaneous details regarding assumptions made in the standardisation of the primary sampling type/instrument. |
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Path to the location in the esarchive of the manual for the specific primary sampling instrument. |
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Further associated details regarding the specifics of the primary sampling instrument/type. |
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Standardised sample preparation types utilised in the measurement process. Multiple types are separated by “;”. |
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Standardised sample preparation techniques utilised in the measurement process. Multiple names are separated by “;”. |
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Miscellaneous details regarding assumptions made in the standardisation of the sample preparation types/techniques. Multiple details specific to different types are separated by “;”. |
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Further associated details regarding the specifics of the sample preparation types/techniques. Multiple details specific to different types are separated by “;”. |
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Standardised name of the measurement methodology. |
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Standardised name of the measuring instrument. |
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Standardised name of the measuring instrument sampling type. |
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Volume (litres) of fluid which passes to the measuring instrument, per unit time (minutes), as given in instrumental manual/documentation. Can be a range: e.g. 1.0-3.0. |
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Volume (litres) of fluid which passes to the measuring instrument, per unit time (minutes), as given in metadata. Can be a range: e.g. 1.0-3.0. |
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Miscellaneous details regarding assumptions made in the standardisation of the measurement methodology/instrument. |
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Path to the location in the esarchive of the manual for the specific measuring instrument. |
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Further associated details regarding the specifics of the measurement methodology/instrument. |
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Units that the measured parameter are natively reported in. |
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Lower limit of detection of measurement methodology, as given in metadata. |
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Lower limit of detection of measurement methodology, as given in the instrumental manual/documentation. |
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Upper limit of detection of measurement methodology, as given in metadata. |
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Upper limit of detection of measurement methodology, as given in the instrumental manual/documentation. |
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Measurement uncertainty (±), as given in metadata. In principal this refers to the inherent uncertainty on every measurement as a function of the quadratic addition of the accuracy and precision metrics (at the same confidence interval), but is often reported incosistently e.g. being solely determined from random errors (i.e. just the measurement precision). It can be given in absolute terms; as a percentage; the greater of either an absolute value or percentage (i.e. 25.0/0.5%); or a percentage quantity after a fixed limit (i.e. 0.5%>=50). |
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Measurement uncertainty (±), as given in the instrumental manual/documentation. In principal this refers to the inherent uncertainty on every measurement as a function of the quadratic addition of the accuracy and precision metrics (at the same confidence interval), but is often reported incosistently e.g. being solely determined from random errors (i.e. just the measurement precision). This can be given in absolute terms; as a percentage; the greater of either an absolute value or percentage (i.e. 25.0/0.5%); or a percentage quantity after a fixed limit (i.e. 0.5%>=50). |
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Measurement accuracy (±), as given in metadata. Accuracy describes the difference between the measurement and the actual value of the part that is measured. It includes: Bias (a measure of the difference between the true value and the observed value of a part – If the “true” value is unknown, it can be calculated by averaging several measurements with the most accurate measuring equipment available) and Linearity (a measure of how the size of the part affects the bias of a measurement system – It is the difference in the observed bias values through the expected range of measurement). This can be given as in absolute terms; as a percentage; the greater of either an absolute value or percentage (i.e. 25.0/0.5%); or a percentage quantity after a fixed limit (i.e. 0.5%>=50). |
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Measurement accuracy (±), as given in the instrumental manual/documentation. Accuracy describes the difference between the measurement and the actual value of the part that is measured. It includes: Bias (a measure of the difference between the true value and the observed value of a part – If the “true” value is unknown, it can be calculated by averaging several measurements with the most accurate measuring equipment available) and Linearity (a measure of how the size of the part affects the bias of a measurement system – It is the difference in the observed bias values through the expected range of measurement). This can be given as in absolute terms; as a percentage; the greater of either an absolute value or percentage (i.e. 25.0/0.5%); or a percentage quantity after a fixed limit (i.e. 0.5%>=50). |
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Measurement precision (±), as given in metadata. Precision describes the variation you see when you measure the same part repeatedly with the same device. It includes the following two types of variation: Repeatability (variation due to the measuring device – it is the variation observed when the same operator measures the same part repeatedly with the same device) and Reproducibility (variation due to the operators and the interaction between operator and part – It is the variation of the bias observed when different operators measure the same parts using the same device). This can be given as in absolute terms; as a percentage; the greater of either an absolute value or percentage (i.e. 25.0/0.5%); or a percentage quantity after a fixed limit (i.e. 0.5%>=50). |
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Measurement precision (±), as given in instrumental manual/documentation. Precision describes the variation you see when you measure the same part repeatedly with the same device. It includes the following two types of variation: Repeatability (variation due to the measuring device – it is the variation observed when the same operator measures the same part repeatedly with the same device) and Reproducibility (variation due to the operators and the interaction between operator and part – It is the variation of the bias observed when different operators measure the same parts using the same device). This can be given as in absolute terms; as a percentage; the greater of either an absolute value or percentage (i.e. 25.0/0.5%); or a percentage quantity after a fixed limit (i.e. 0.5%>=50). |
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Zero drift of measuring instrument per unit of time, as given in metadata. Zero drift (or baseline drift) refers to the shifting of the whole calibration by the same amount caused by slippage or due to undue warming up of the electronic circuits. It is reported as the maximum possible drift per unit of time in absolute terms; as a percentage; the greater of either an absolute value or percentage (i.e. 25.0/0.5%/day); or a percentage quantity after a fixed limit (i.e. 0.5%>=50/day). |
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Zero drift of measuring instrument per unit of time, as given in instrumental manual/documentation. Zero drift (or baseline drift) refers to the shifting of the whole calibration by the same amount caused by slippage or due to undue warming up of the electronic circuits. It is reported as the maximum possible drift per unit of time in absolute terms; as a percentage; the greater of either an absolute value or percentage (i.e. 25.0/0.5%/day); or a percentage quantity after a fixed limit (i.e. 0.5%>=50/day). |
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Span drift of measuring instrument per unit of time, as given in metadata. Span drift (or sensitivity drift) refers to when there is proportional change in the indication of an instrument all along the upward scale, hence higher calibrations end up being shifted more than lower calibrations. It is reported as the maximum possible drift per unit of time in absolute terms; as a percentage; the greater of either an absolute value or percentage (i.e. 25.0/0.5%/day); or a percentage quantity after a fixed limit (i.e. 0.5%>=50/day). |
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Span drift of measuring instrument per unit of time, as given in instrumental manual/documentation. Span drift (or sensitivity drift) refers to when there is proportional change in the indication of an instrument all along the upward scale, hence higher calibrations end up being shifted more than lower calibrations. It is reported as the maximum possible drift per unit of time in absolute terms; as a percentage; the greater of either an absolute value or percentage (i.e. 25.0/0.5%/day); or a percentage quantity after a fixed limit (i.e. 0.5%>=50/day). |
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Zonal drift of measuring instrument per unit of time, as given in metadata. Zonal drift refers to when drift occurs only over a portion of the full scale or span of an instrument, while the remaining portion of the scale remains unaffected. It is reported as the maximum possible drift per unit of time in absolute terms; as a percentage; the greater of either an absolute value or percentage (i.e. 25.0/0.5%/day); or a percentage quantity after a fixed limit (i.e. 0.5%>=50/day). |
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Zonal drift of measuring instrument per unit of time, as given in instrumental manual/documentation. Zonal drift refers to when drift occurs only over a portion of the full scale or span of an instrument, while the remaining portion of the scale remains unaffected. It is reported as the maximum possible drift per unit of time in absolute terms; as a percentage; the greater of either an absolute value or percentage (i.e. 25.0/0.5%/day); or a percentage quantity after a fixed limit (i.e. 0.5%>=50/day). |
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Measurement resolution, as given in metadata. The measurement resolution is defined as the smallest change or increment in the measured quantity that the instrument can detect. However it is often reported inconsistently, often being simply the number of digits an instrument can display, which does not relate to the actual physical resolution of the instrument. |
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Measurement resolution, as given in instrumental manual/documentation. The measurement resolution is defined as the smallest change or increment in the measured quantity that the instrument can detect. However it is often reported inconsistently, often being simply the number of digits an instrument can display, which does not relate to the actual physical resolution of the instrument. |
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Assumed molecule cross-section for parameter being measured (in cm2/molecule), as given in metadata. This field is only used for parameters being measured using optical methods, where a molecule cross section is assumed for processing the measurement values. Physically it is the effective area of the molecule that photon needs to traverse in order to be absorbed. The larger the absorption cross section, the easier it is to photoexcite the molecule. Can be a range: e.g. 1e-15-1.5e-15. |
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Assumed molecule cross-section for parameter being measured (in cm2/molecule), as given in instrumental manual/documentation. This field is only used for parameters being measured using optical methods, where a molecule cross section is assumed for processing the measurement values. Physically it is the effective area of the molecule that photon needs to traverse in order to be absorbed. The larger the absorption cross section, the easier it is to photoexcite the molecule. Can be a range: e.g. 1e-15-1.5e-15. |
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Description of sampling inlet of the measuring instrument. |
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Name of calibration scale used for the calibration of the measuring instrument. |
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The temperature (in Kelvin) associated with the volume of the sampled gas (which varies with temperature and pressure). This volume is typically normalised in-instrument to a standard temperature and pressure. These standard values typically follow network/continental/global standards (e.g. European Union) for the measured component. If no in-instrument normalisation is done then the reported temperature should be reported as the internal temperature of the instrument (i.e. the measurement conditions). If no numbers are reported explicitly per measurement, then the sample gas temperature is assumed to be the known network standard temperature for the measured component. |
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The pressure (in hPa) associated with the volume of the sampled gas (which varies with temperature and pressure). This volume is typically normalised in-instrument to a standard temperature and pressure. These standard values typically follow network/continental/global standards (e.g. European Union) for the measured component. If no in-instrument normalisation is done then the reported pressure should be reported as the internal pressure of the instrument (i.e. the measurement conditions). If no numbers are reported explicitly per measurement, then the sample gas pressure is assumed to be the known network standard pressure for the measured component. |
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The name of the retrieval algorithm. Remote sensing algorithms are used to retrieve the aerosol optical properties (as aerosol optical depths or single scattering albedo among others) using remote-sensing radiances for multiple wavelengths from ground stations or on satellite platforms. Each algorithm is particularly designed considering the characteristics of the sensor and other ancillary information. |
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Full name of the principal scientific investigator for the specific reported data. |
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Institution of the principal scientific investigator for the specific reported data. |
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Email address of the principal scientific investigator for the specific reported data. |
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Full name of the principal data contact for the specific reported data. |
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Institution of the principal data contact for the specific reported data. |
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Email address of the principal data contact for the specific reported data. |
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Time stamp of metadata updates in integer minutes from 0001-01-01 00:00 UTC. |
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Time stamp of date/time of data download in integer minutes from 0001-01-01 00:00 UTC. |
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Time stamp of date/time of the last data revision in integer minutes from 0001-01-01 00:00 UTC. |
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Extra details provided by the reporting network about the sampling methods employed. |
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Extra details provided by the reporting network about the uncertainties involved with the measurement methods employed. |
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Extra details provided by the reporting network about the operational maintenance done at the station. |
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Extra details provided by the reporting network about the in-network quality assurance of measurements. |
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Extra miscellaneous details provided by the reporting network. |
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Information pertaining to the data licence governing the redistribution/publication of the ingested network data. |
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Warnings accumulated through GHOST processing regarding the data that should be considered. |
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