Inventory-based estimates of C flux have been developed for US agriculture (West et al. 2011), US forests (Zheng et al. 2011 and McKinley et al. 2011), and for North American agriculture and forest lands (Hayes et al. 2012). These estimates combine C uptake, harvest and removal, and C release to generate regional C flux estimates. These estimates differ from carbon biomass or stock estimates which often only represent the net C uptake component of the flux. The inventory-based C flux method of estimation has evolved over the past 5 years, as noted by the recent aforementioned citations, and has been used successfully as input to biogeochemical models, atmospheric transport models, and economic models. Estimates have also been used as independent data sets for comparison with other methods (King et al. 2012). The usefulness of this new method is evident. What is needed now is an expansion of the method for global use. The purpose of this proposed research is to develop a global C budget for agricultural carbon uptake and release, as was done for the US by West et al. (2011). A global US C budget, together with satellite remote sensing of land cover, will provide a gridded global C flux for agricultural lands. This product can be used as input to the NASA Flux Pilot Study and by models currently engaged in the Study. The proposed method combines aforementioned methods of spatially explicit C uptake and release with a NASA-generated global data set on human consumption of agricultural commodities (Imhoff et al. 2004, 2006) for use in the CASA model (Potter et al. 1993, Williams et al. 2012) and other Pilot Study models. Datasets generated will also be commensurate with those used in the DOE Integrated Assessment (IA) program, which allows for future economic projections of land use and human population to be linked with carbon fluxes generated with NASA models.
Measurement Approaches:
Remote Sensing
Modeling
Synthesis
Project Associations:
CMS
CMS Primary Theme:
Land-Atmosphere Flux
CMS Science Theme(s):
Land Biomass
Land-Atmosphere Flux
Decision Support
Other Keywords: emperical, inventory-based estimates of net carbon exchange from global agricultural systems
Contact Support to request an email list of project participants.
Project URL(s):
None provided.
Data Products:
Product Title: Carbon release by human.
Time Period: 2005-2010
Description: - Develop a global gridded dataset for cropland carbon fluxes using global- and country-level inventory data on crop yields.
Status: Planned
CMS Science Theme(s): Land-Atmosphere Flux
Keywords: Source (; anthropogenic)
Spatial Extent: Global
Spatial Resolution: 0.05°
Temporal Frequency: Annually
Input Data Products: MODIS PFT v5.1 land cover (cropland, grassland, and shrubland areas)
Algorithm/Models Used: Combination of IPCC, EPA, FAO, and empirical carbon dynamics developed under the NACP MCI program. Downscaling algorithms documented in 2014 paper (see below).
Evaluation: Evaluation with other existing datasets on cropland, livestock, and human spatial distributions and emissions. Additional evaluations are expected in the future with atmospheric inversion estimates.
Intercomparison Efforts/Gaps: Inherent intercomparison with inventory (FAO) and NASA SEDAC data
Uncertainty Estimates: Standard deviation was generated using PDF functions around all major input variables. SD is provided at province and grid cell level.
Uncertainty Categories: Deterministic
Application Areas: - GHG emissions inventory; - Land management
Relevant Policies/Programs: IPCC GPG, NASA FPP, NASA Carnegie Ames Stanford Approach (CASA) model, DOE Integrated Assessment program, US Farm Bill, CAP
Potential Users: EPA, USDA Farm Service Agency, CMS flux teams, United Nations Environment Programme – Global Environmental Facility, UNFCCC, FAO, NGOs: World Wildlife Fund, The Nature Conservancy, & Natural Resource Defense Council
Stakeholders:
Current Application Readiness Level: 5
Start Application Readiness Level: 3
Target Application Readiness Level: 6
Future Developments: - Publish results in 2015.; - Collaborate with Bowman-01 and Collatz-02 teams to improve CMS flux projects.
Limitations: - Food intake data is not available for all geopolitical areas, whereas Food supply is available. supply has been scaled to intake where necessary.
Date When Product Available: Available when published
Product Title: CMS: Carbon Fluxes from Global Agricultural Production and Consumption, 2005-2011
Start Date: 01/2005End Date: 12/2011 (2005-2011)
Description: This data set provides global estimates of carbon fluxes associate with annual crop net primary production (NPP) and harvested biomass, annual uptake and release by humans and livestock, and the total annual estimate of net carbon exchange (NCE) derived from these carbon fluxes. NCE estimates are for the combined crop plant harvest and consumption/expiration of fodder by livestock and of food by humans. Estimation of carbon uptake and release from global agricultural production and consumption required compilation and analysis of inventory data from various sources for the years 2005-2011. The flux estimates were spatially distributed to a global 0.05-degree resolution grid using MODIS land cover data. The quantities of carbon flux in each gridcell are represented in two ways: (1) where the quantities of carbon distributed to each gridcell were divided by the total gridcell area, resulting in average carbon fluxes per unit of total area (g C/m2/yr), and (2), where annual carbon fluxes associated with a source were summed over all types for the gridcell (Mg C/yr). The total surface area of the grid cells is provided.There are eight data files in netCDF format (.nc4) with this data set -- two files (per area and per gridcell) for each of the four flux source types. Data for all years are in each .nc4 file.
Input Data Products: The basis of these calculations was annual harvested biomass (Y) of 92 crops for years 1961-2011, which was compiled from FAOSTAT (FAO, 2013) for all reporting nations.
Algorithm/Models Used:
Evaluation:
Intercomparison Efforts/Gaps:
Uncertainty Estimates:
Uncertainty Categories:
Application Areas: The spatial distribution of these fluxes may be used for global carbon monitoring, estimation of regional uncertainty, and for use as input to Earth system models.
Relevant Policies/Programs: IPCC GPG, NASA FPP, NASA Carnegie Ames Stanford Approach (CASA) model, DOE Integrated Assessment program, US Farm Bill, CAP
Potential Users: Global or regional models with needs to improve agriculture biomass estimates, the amount of biomass removed from the field vs remaining as residue, and the approximate location of cropland carbon release.
Stakeholders:
Current Application Readiness Level: 6
Start Application Readiness Level:
Target Application Readiness Level:
Future Developments:
Limitations: There is no incorporation of soil carbon in the global agricultural carbon budget.
Archived Data Citation: Wolf, J., T.O. West, Y. Le Page, G. Kyle, X. Zhang, G.J. Collatz, and M.L. Imhoff. 2015. CMS: Carbon Fluxes from Global Agricultural Production and Consumption, 2005-2011. ORNL DAAC, Oak Ridge, Tennessee, USA. DOI: 10.3334/ORNLDAAC/1279
Bounding Coordinates:
West Longitude:
-180.00000
East Longitude:
180.00000
North Latitude:
83.64000
South Latitude:
-59.46000
Product Title: CMS: Land Cover Projections (5.6-km) from GCAM v3.1 for Conterminous USA, 2005-2095
Start Date: 01/2005End Date: 12/2095 (2005-2095)
Description: The data provided are annual land cover projections for years 2005 through 2095 generated by the Global Change Assessment Model (GCAM) Version 3.1. For the conterminous USA, the GCAM global gridded results were downscaled to ~5.6 km (0.05 degree) resolution. For each 5.6 x 5.6 km area, the annual land cover percentage comprised by each of the nineteen different land cover classes/plant functional types (PFTs) of the Community Land Model (CLM) (Table 1) are provided.Results are reported for GCAM runs of three scenarios of future human efforts towards climate mitigation as related to global carbon emissions, radiative forcing, and land cover change. Specific scenario conditions were 1) a reference scenario with no explicit climate mitigation efforts that reaches a radiative forcing level of over 7 W/m2 in 2100, 2) the 2.6 mitigation pathway (MP) scenario which is a very low emission scenario with a mid-century peak in radiative forcing at ~3 W/m2, declining to 2.6 W/m2 in 2100, and 3) the 4.5 MP scenario which stabilizes radiative forcing at 4.5 W/m2 (~ 650 ppm CO2-equivalent) before 2100.These downscaled land cover projections can be used to derive spatially explicit estimates of potential shifts in croplands, grasslands, shrub lands, and forest lands in each future climate scenario.Data are presented as three NetCDF v4 files (.nc4), one for each future climate scenario -- 2.6 MP, 4.5 MP, and GCAM reference).
Status: Archived
CMS Science Theme(s): Land-Atmosphere Flux
Keywords: Disturbance (; land cover change)
Spatial Extent: CONUS
Spatial Resolution: 0.05° (~5.6 km)
Temporal Frequency: Annually
Input Data Products: MODIS PFT v5.1 land cover (cropland, grassland, and shrubland areas)
Algorithm/Models Used: Based on algorithms consistent with current state-of-the-art land cover change models (community land model).
Evaluation: Evaluation with historic land cover change in the Midwestern US.
Intercomparison Efforts/Gaps:
Uncertainty Estimates: Uncertainty in the model downscaling procedure was evaluated by comparing model projections for years 2005 - 2010 against historical land cover change in the US using MODIS PFT data and national inventory statistics. An evaluation of the downscaling method indicates that it is able to reproduce recent changes in cropland and grassland distributions (West et al. 2014). No formal statistical uncertainty is associated with the data set.
Uncertainty Categories:
Application Areas: - GHG emissions inventory; - Land management
These downscaled data can be applied to analyses of environmental impacts at sub-regional and landscape scales and may provide relevant insights into the potential impacts of socio-economic and environmental drivers on future changes in land cover.
Relevant Policies/Programs: IPCC GPG, NASA FPP, NASA Carnegie Ames Stanford Approach (CASA) model, DOE Integrated Assessment program, US Farm Bill, CAP
Potential Users: carbon cycle scientists, those interested in climate change and land cover change
Stakeholders:
Current Application Readiness Level: 6
Start Application Readiness Level: 3
Target Application Readiness Level: 6
Future Developments: - Publish results in 2014.; - This is completed and documents the spatial distribution methods used in our global flux estimates.
Limitations: The limitation here is that we can not know exactly where lands will change. However, we can estimate the regions where land cover change is expected and we can approximate the spatial distribution of land-cover change. We have compared this against historic land-cover change estimates from inventory data and from MODIS.
Archived Data Citation: West, T.O. and Le Page, Y. 2014. CMS: Land Cover Projections (5.6-km) from GCAM v3.1 for Conterminous USA, 2005-2095. ORNL DAAC, Oak Ridge, Tennessee, USA. DOI: 10.3334/ORNLDAAC/1216
Bounding Coordinates:
West Longitude:
-124.69000
East Longitude:
-67.09000
North Latitude:
49.35000
South Latitude:
25.25000
Product Title: CMS: Carbon Fluxes from Global Agricultural Production and Consumption, 2005-2011
Start Date: 01/2005End Date: 12/2011 (2005-2010)
Description: This data set provides global estimates of carbon fluxes associate with annual crop net primary production (NPP) and harvested biomass, annual uptake and release by humans and livestock, and the total annual estimate of net carbon exchange (NCE) derived from these carbon fluxes. NCE estimates are for the combined crop plant harvest and consumption/expiration of fodder by livestock and of food by humans. Estimation of carbon uptake and release from global agricultural production and consumption required compilation and analysis of inventory data from various sources for the years 2005-2011. The flux estimates were spatially distributed to a global 0.05-degree resolution grid using MODIS land cover data. The quantities of carbon flux in each gridcell are represented in two ways: (1) where the quantities of carbon distributed to each gridcell were divided by the total gridcell area, resulting in average carbon fluxes per unit of total area (g C/m2/yr), and (2), where annual carbon fluxes associated with a source were summed over all types for the gridcell (Mg C/yr). The total surface area of the grid cells is provided.There are eight data files in netCDF format (.nc4) with this data set -- two files (per area and per gridcell) for each of the four flux source types. Data for all years are in each .nc4 file.
Status: Archived
CMS Science Theme(s): Land-Atmosphere Flux
Keywords: Source (; terrestrial)
Spatial Extent: Global
Spatial Resolution: 0.05°
Temporal Frequency: Annually
Input Data Products: MODIS PFT v5.1 land cover (cropland, grassland, and shrubland areas)
Algorithm/Models Used: Combination of IPCC, EPA, FAO, and empirical carbon dynamics developed under the NACP MCI program. Downscaling algorithms documented in 2014 paper (see below).
Evaluation: Evaluation with other existing datasets on cropland, livestock, and human spatial distributions and emissions. Additional evaluations are expected in the future with atmospheric inversion estimates.
Intercomparison Efforts/Gaps: Inherent intercomparison with inventory (FAO livestock) and MODIS data
Uncertainty Estimates: Standard deviation was generated using PDF functions around all major input variables. SD is provided at province and grid cell level.
Uncertainty Categories: Deterministic
Application Areas: - GHG emissions inventory; - Land management
Relevant Policies/Programs: IPCC GPG, NASA FPP, NASA Carnegie Ames Stanford Approach (CASA) model, DOE Integrated Assessment program, US Farm Bill, CAP
Potential Users: EPA, USDA Farm Service Agency, CMS flux teams, United Nations Environment Programme – Global Environmental Facility, UNFCCC, FAO, NGOs: World Wildlife Fund, The Nature Conservancy, & Natural Resource Defense Council
Stakeholders:
Current Application Readiness Level: 5
Start Application Readiness Level: 3
Target Application Readiness Level: 6
Future Developments: - Publish results in 2015.; - Collaborate with Bowman-01 and Collatz-02 teams to improve CMS flux projects.
Limitations: - methane carbon coefficients changing. We are already planning for a future update.
Archived Data Citation: Wolf, J., T.O. West, Y. Le Page, G. Kyle, X. Zhang, G.J. Collatz, and M.L. Imhoff. 2015. CMS: Carbon Fluxes from Global Agricultural Production and Consumption, 2005-2011. ORNL DAAC, Oak Ridge, Tennessee, USA. DOI: 10.3334/ORNLDAAC/1279
Bounding Coordinates:
West Longitude:
-180.00000
East Longitude:
180.00000
North Latitude:
83.64000
South Latitude:
-59.46000
Product Title: CMS: Carbon Fluxes from Global Agricultural Production and Consumption, 2005-2011
Start Date: 01/2005End Date: 12/2011 (2005-2010)
Description: This data set provides global estimates of carbon fluxes associate with annual crop net primary production (NPP) and harvested biomass, annual uptake and release by humans and livestock, and the total annual estimate of net carbon exchange (NCE) derived from these carbon fluxes. NCE estimates are for the combined crop plant harvest and consumption/expiration of fodder by livestock and of food by humans. Estimation of carbon uptake and release from global agricultural production and consumption required compilation and analysis of inventory data from various sources for the years 2005-2011. The flux estimates were spatially distributed to a global 0.05-degree resolution grid using MODIS land cover data. The quantities of carbon flux in each gridcell are represented in two ways: (1) where the quantities of carbon distributed to each gridcell were divided by the total gridcell area, resulting in average carbon fluxes per unit of total area (g C/m2/yr), and (2), where annual carbon fluxes associated with a source were summed over all types for the gridcell (Mg C/yr). The total surface area of the grid cells is provided.There are eight data files in netCDF format (.nc4) with this data set -- two files (per area and per gridcell) for each of the four flux source types. Data for all years are in each .nc4 file.
Input Data Products: MODIS PFT v5.1 land cover (cropland, grassland, and shrubland areas)
Algorithm/Models Used: Combination of IPCC, EPA, FAO, and empirical carbon dynamics developed under the NACP MCI program. Downscaling algorithms documented in 2014 paper (see below).
Evaluation: Evaluation with other existing datasets on cropland, livestock, and human spatial distributions and emissions. Additional evaluations are expected in the future with atmospheric inversion estimates.
Intercomparison Efforts/Gaps: Intercomparison with existing global agricultural flux estimates and with individual flux components.
Uncertainty Estimates: Standard deviation was generated using PDF functions around all major input variables. SD is provided at province and grid cell level.
Uncertainty Categories: Deterministic
Application Areas: - GHG emissions inventory; - Land management
Relevant Policies/Programs: IPCC GPG, NASA FPP, NASA Carnegie Ames Stanford Approach (CASA) model, DOE Integrated Assessment program, US Farm Bill, CAP
Potential Users: EPA, USDA Farm Service Agency, CMS flux teams, United Nations Environment Programme – Global Environmental Facility, UNFCCC, FAO, NGOs: World Wildlife Fund, The Nature Conservancy, & Natural Resource Defense Council
Stakeholders:
Current Application Readiness Level: 5
Start Application Readiness Level: 3
Target Application Readiness Level: 6
Future Developments: - Publish results in 2015.; - Collaborate with Bowman-01 and Collatz-02 teams to improve CMS flux projects.
Limitations: - Emission data is constantly improving, and the data products will need to be periodically updated to reflect these changes.; - Coarse spatial resolution, using MODIS rather than Landsat.; - No incorporation of soil carbon data.; - Methane carbon coeffic
Archived Data Citation: Wolf, J., T.O. West, Y. Le Page, G. Kyle, X. Zhang, G.J. Collatz, and M.L. Imhoff. 2015. CMS: Carbon Fluxes from Global Agricultural Production and Consumption, 2005-2011. ORNL DAAC, Oak Ridge, Tennessee, USA. DOI: 10.3334/ORNLDAAC/1279
Bounding Coordinates:
West Longitude:
-180.00000
East Longitude:
180.00000
North Latitude:
83.64000
South Latitude:
-59.46000
Product Title: CMS: Carbon Fluxes from Global Agricultural Production and Consumption, 2005-2011
Start Date: 01/2005End Date: 12/2011 (2005-2010)
Description: This data set provides global estimates of carbon fluxes associate with annual crop net primary production (NPP) and harvested biomass, annual uptake and release by humans and livestock, and the total annual estimate of net carbon exchange (NCE) derived from these carbon fluxes. NCE estimates are for the combined crop plant harvest and consumption/expiration of fodder by livestock and of food by humans. Estimation of carbon uptake and release from global agricultural production and consumption required compilation and analysis of inventory data from various sources for the years 2005-2011. The flux estimates were spatially distributed to a global 0.05-degree resolution grid using MODIS land cover data. The quantities of carbon flux in each gridcell are represented in two ways: (1) where the quantities of carbon distributed to each gridcell were divided by the total gridcell area, resulting in average carbon fluxes per unit of total area (g C/m2/yr), and (2), where annual carbon fluxes associated with a source were summed over all types for the gridcell (Mg C/yr). The total surface area of the grid cells is provided.There are eight data files in netCDF format (.nc4) with this data set -- two files (per area and per gridcell) for each of the four flux source types. Data for all years are in each .nc4 file.
Status: Archived
CMS Science Theme(s): Land Biomass; Land-Atmosphere Flux
Keywords: Sink (; terrestrial)
Spatial Extent: Global
Spatial Resolution: 0.05°
Temporal Frequency: Annually
Input Data Products: MODIS PFT v5.1 land cover (cropland area)
Algorithm/Models Used: Combination of IPCC, EPA, FAO, and empirical carbon dynamics developed under the NACP MCI program. Downscaling algorithms documented in 2014 paper (see below).
Evaluation: Evaluation with other existing datasets on cropland, livestock, and human spatial distributions and emissions. Additional evaluations are expected in the future with atmospheric inversion estimates.
Intercomparison Efforts/Gaps: Inherent intercomparison with inventory (FAO and USDA NASS) and MODIS data
Uncertainty Estimates: A range of values have been collected in a meta-analysis for each parameter used in estimating crop growth and associated carbon content. These values will be used to generate PDFs which will constitute the Monte Carlo analysis.
Uncertainty Categories: Deterministic
Application Areas: - GHG emissions inventory; - Land management
Relevant Policies/Programs: IPCC GPG, NASA FPP, NASA Carnegie Ames Stanford Approach (CASA) model, DOE Integrated Assessment program, US Farm Bill, CAP
Potential Users: EPA, USDA Farm Service Agency, CMS flux teams, United Nations Environment Programme – Global Environmental Facility, UNFCCC, FAO, NGOs: World Wildlife Fund, The Nature Conservancy, & Natural Resource Defense Council
Stakeholders:
Current Application Readiness Level: 5
Start Application Readiness Level: 3
Target Application Readiness Level: 6
Future Developments: - Publish results in 2015.; - Collaborate with Bowman-01 and Collatz-02 teams to improve CMS flux projects.
Limitations: - Emission data is constantly improving, and the data products will need to be periodically updated to reflect these changes.; - Coarse spatial resolution, using MODIS rather than Landsat.; - No incorporation of soil carbon data.
Archived Data Citation: Wolf, J., T.O. West, Y. Le Page, G. Kyle, X. Zhang, G.J. Collatz, and M.L. Imhoff. 2015. CMS: Carbon Fluxes from Global Agricultural Production and Consumption, 2005-2011. ORNL DAAC, Oak Ridge, Tennessee, USA. DOI: 10.3334/ORNLDAAC/1279
Bounding Coordinates:
West Longitude:
-180.00000
East Longitude:
180.00000
North Latitude:
83.64000
South Latitude:
-59.46000
Publications:
Wolf, J., West, T. O., Le Page, Y., Kyle, G. P., Zhang, X., Collatz, G. J., Imhoff, M. L. 2015. Biogenic carbon fluxes from global agricultural production and consumption. Global Biogeochemical Cycles. 29(10), 1617-1639. DOI: 10.1002/2015GB005119
West, T. O., Le Page, Y., Huang, M., Wolf, J., Thomson, A. M. 2014. Downscaling global land cover projections from an integrated assessment model for use in regional analyses: results and evaluation for the US from 2005 to 2095. Environmental Research Letters. 9(6), 064004. DOI: 10.1088/1748-9326/9/6/064004
King, A. W., Hayes, D. J., Huntzinger, D. N., West, T. O., Post, W. M. 2012. North American carbon dioxide sources and sinks: magnitude, attribution, and uncertainty. Frontiers in Ecology and the Environment. 10(10), 512-519. DOI: 10.1890/120066
Li, Z., Liu, S., Tan, Z., Bliss, N. B., Young, C. J., West, T. O., Ogle, S. M. 2014. Comparing cropland net primary production estimates from inventory, a satellite-based model, and a process-based model in the Midwest of the United States. Ecological Modelling. 277, 1-12. DOI: 10.1016/j.ecolmodel.2014.01.012
Ogle, S. M., Davis, K., Lauvaux, T., Schuh, A., Cooley, D., West, T. O., Heath, L. S., Miles, N. L., Richardson, S., Breidt, F. J., Smith, J. E., McCarty, J. L., Gurney, K. R., Tans, P., Denning, A. S. 2015. An approach for verifying biogenic greenhouse gas emissions inventories with atmospheric CO
2
concentration data. Environmental Research Letters. 10(3), 034012. DOI: 10.1088/1748-9326/10/3/034012
Post, W. M., Izaurralde, R. C., West, T. O., Liebig, M. A., King, A. W. 2012. Management opportunities for enhancing terrestrial carbon dioxide sinks. Frontiers in Ecology and the Environment. 10(10), 554-561. DOI: 10.1890/120065
Schuh, A. E., Lauvaux, T., West, T. O., Denning, A. S., Davis, K. J., Miles, N., Richardson, S., Uliasz, M., Lokupitiya, E., Cooley, D., Andrews, A., Ogle, S. 2013. Evaluating atmospheric CO2inversions at multiple scales over a highly inventoried agricultural landscape. Global Change Biology. 19(5), 1424-1439. DOI: 10.1111/gcb.12141
West, T. O., Brown, M. E., Duren, R. M., Ogle, S. M., Moss, R. H. 2014. Definition, capabilities and components of a terrestrial carbon monitoring system. Carbon Management. 4(4), 413-422. DOI: 10.4155/CMT.13.36
Zeng, N., Zhao, F., Collatz, G. J., Kalnay, E., Salawitch, R. J., West, T. O., Guanter, L. 2014. Agricultural Green Revolution as a driver of increasing atmospheric CO2 seasonal amplitude. Nature. 515(7527), 394-397. DOI: 10.1038/nature13893
Zhang, X., Sahajpal, R., Manowitz, D. H., Zhao, K., LeDuc, S. D., Xu, M., Xiong, W., Zhang, A., Izaurralde, R. C., Thomson, A. M., West, T. O., Post, W. M. 2014. Multi-scale geospatial agroecosystem modeling: A case study on the influence of soil data resolution on carbon budget estimates. Science of The Total Environment. 479-480, 138-150. DOI: 10.1016/j.scitotenv.2014.01.099
Archived Data Citations:
Wolf, J., T.O. West, Y. Le Page, G. Kyle, X. Zhang, G.J. Collatz, and M.L. Imhoff. 2015. CMS: Carbon Fluxes from Global Agricultural Production and Consumption, 2005-2011. ORNL DAAC, Oak Ridge, Tennessee, USA. DOI: 10.3334/ORNLDAAC/1279
West, T.O. and Le Page, Y. 2014. CMS: Land Cover Projections (5.6-km) from GCAM v3.1 for Conterminous USA, 2005-2095. ORNL DAAC, Oak Ridge, Tennessee, USA. DOI: 10.3334/ORNLDAAC/1216