CCSP Workshop, November 2005 Abstracts Posters: Carbon (P-CA), Sub-Theme 2: Emissions, Budgets, & Processes
| Home
CCSP Workshop, November 2005 Abstracts Posters: Carbon (P-CA), Sub-Theme 2: Emissions, Budgets, & Processes |
|
|
|
|
Page updated 5 December 2005 Call for Contributed Presentations
Now available in PDF format: Abstract Book [7.4 Mb] (posted 10 November 2005) |
 |
Abstracts for PostersCarbon (P-CA)Sub-Theme 2: Emissions, Budgets, & ProcessesP-CA2.1Nutrient Management to Enhance Carbon Sequestration in Piedmont Forests of the Southeastern U.S.
Peter Kapeluck Clemson University, SC David Van Lear Clemson University, SC Christopher Post Clemson University, SC Impacts of alternative forest nutrient management practices on potential C sequestration are poorly understood. In the South Eastern U.S., soils in the Piedmont physiographic province are severely eroded and contain low quantities of soil C as a result of agricultural activity. Conversion of degraded croplands to forests likely has increased terrestrial carbon stocks, although the magnitude of this increase and the impact of forest management on it are unclear because of the lack of long-term data and the high variability in existing soil and plant data. This study examines the potential for carbon sequestration in loblolly pine forests to determine which conventional management practices lead to the most soil carbon sequestration and least adverse environmental impacts at the pedon and watershed scales. Treatment conditions include harvesting during dormant versus active growing seasons, burning versus no burning after harvest, and natural-regeneration versus reseeding (i.e., plantation) of the stand. Burning alters nutrien availability and decomposing roots act as slow-release fertilizer. Data from long-term experiments are used to develop alternative methods to enhance carbon sequestration in terrestrial ecosystems as one component of a carbon management strategy. P-CA2.2Unaccounted Soil Carbon Stocks
Elena Mikhailova, Clemson University, eleanam@clemson.edu Christopher Post, Clemson University Kim Magrini-Bair, National Renewable Energy Laboratory Current estimates of world soil carbon stocks are incomplete and inadequate, because most of them are based on actual soil data down to 1 m depth only and were obtained by outdated methods. Thus, soil carbon stocks are severely underestimated. Soil orders such as Alfisol, Aridisol, Mollisol, Ultisol, Vertisol and others contain significant amounts of soil inorganic carbon in the form of carbonates, which often rich maximum content below 1-m depth. Most current soil databases also lack information on soil bulk density, stable carbon geochemistry of soil organic and inorganic P-CA2.3Estimating Soil C Changes for the US 1605B Program
Keith Paustian, Colorado State University, keithp@nrel.colostate.edu John Brenner, USDA/NRCS, Stephen Ogle, Colorado State University Mark Easter, Colorado State University Kendrick Killian, Colorado State University Jill Schuler, USDA/NRCS Steve Williams, Colorado State University A system for voluntary reporting of greenhouse gas emission reductions was established as part of the US policy for addressing global climate change issues. The system is administered by the USDOE and has recently been revised and improved as part of the Administration's Climate Change Initiative. Emission reductions through agricultural activities, including soil C sequestration and reductions in on-farm fuel usage, are included in the reporting system. The system employs a web-based, menu driven interface, in which producers can designate their location and supply background information on previous land use and management. A variety of management alternatives can be chosen and estimates of C emissions and/or sequestration rates, including statistically-based uncertainty estimates, are provided. Future improvements to the system are under development, including a wider array of management options, defined at finer geographic scale and inclusion of N2O emissions. P-CA2.4Practical Applications of Uncertainty Analysis for National Greenhouse Gas Inventories
Michael Gillenwater, Environmental Resources Trust, mgillenwater@ert.net Fran Sussman ICF Consulting, Inc. Jonathan Cohen, ICF Consulting, Inc. International policy makers and climate researchers use greenhouse gas emissions inventory estimates in a variety of ways. Because of the varied uses of the inventory data, as well as the high uncertainty surrounding some of the source category estimates, considerable effort has been devoted to understanding the causes and magnitude of uncertainties in national emission inventories. In this paper we focus on two aspects of the rationale for quantifying uncertainty: (a) the uses of the quantified uncertainty estimates for policy (for example, as a means of adjusting inventories used to determine compliance with international commitments) and (b) the direct benefits of the process of investigating uncertainties in terms of improvements in inventory quality. We find that there are particular characteristics that an uncertainty estimate should have if it is to be used for policy purposes: (1) it should be comparable across countries; (2) it should be relatively objective or at least subject to review and verification; (3) it should not be subject to gaming by countries acting in their own self-interest; (4) it should be administratively feasible to estimate and use; (5) the quality of uncertainty estimate should be high enough to warrant the additional compliance costs its use in an adjustment factor may impose on countries; and (6) it should attempt to address all types of uncertainty. Currently, uncertainly estimates for national greenhouse gas inventories do not have these characteristics. For example, the information used to develop quantitative uncertainty estimates for national inventories is quite often based on expert judgments, which are, by definition, subjective rather than objective. Although it is not clear that uncertainty estimates will adequately exhibit these characteristics, if they did, the design of any adjustment scheme would require that policy makers (1) identify clear environmental goals; (2) define these goals precisely in terms of relationships among important variables (such as emissions estimate, commitment level, or statistical confidence); and (3) develop quantifiable adjustment mechanisms that reflect these environmental goals. We recommend that countries implement an investigation-focused (i.e., qualitative) uncertainty analysis that will (1) provide the type of information necessary to develop more substantive, and potentially useful, quantitative uncertainty estimates—regardless of whether those quantitative estimates are used for policy purposes—and (2) provide information needed to understand the likely causes of uncertainty in inventory data and thereby point to ways to improve inventory quality (i.e., accuracy, transparency, completeness, and consistency). P-CA2.5Spatiotemporally Explicit Maps of Anthropogenic CO 2 Emissions for NACP
Marc Fischer, Lawrence Berkeley National Laboratory, MLFischer@lbl.gov Kevin Gurney, Colorado State University, keving@atmos.colostate.edu Scott Denning, Colorado State University, denning@atmos.colostate.edu Steve Knox, Colorado State University, stevek@nrel.colostate.edu Gregg Marland, Oak Ridge National Laboratory, marlandgh@ornl.gov Dennis Ojima, Colorado State University, Dennis@nrel.colostate.edu Lynn Price, Lawrence Berkeley National Laboratory, LKPrice@lbl.gov Jayant Sathaye, Lawrence Berkeley National Laboratory, JASathaye@lbl.gov Inverse model studies of biospheric CO2 exchange at the global and regional scales require accurate spatially and temporally resolved estimates of CO2 emissions from fossil fuel combustion and other human activities. In this project, we will estimate CO2 emissions by generating and applying CO2 emissions factors to underlying variables in EPA National Emission Inventory (NEI) data. Initial maps have been produced by scaling CO or NOX emissions by regionally specific factors so that annually integrated emissions match annual "top-down" emissions of anthropogenic CO2. To refine and extend the initial estimates, we will use the Consolidated Community Emissions Processing Tool (CONCEPT) framework to extract NEI estimates of fuel use or other variables for each source category in the major energy use sectors (i.e., industry, electricity, transportation, and buildings) for the US, and to the extent possible Canada and Mexico. We will estimate CO2 emission factors for each source category, estimate CO2 emissions for specific sources (for which accurate CO2 emissions are available), integrate to state and national levels and again compare results with "top-down" estimates of CO2 emissions at the state and national scales. The results of this work will support the North American Carbon program (NACP) objectives by providing a P-CA2.6Time Series Calibrated Carbon Emissions and Atmospheric Response
Clifford E. Singer, Center for Science, Technology, and Security Policy, American Association for the Advancement of Science, 1200 New York Ave. NW, Washington, DC 20005, csinger@uiuc.edu Data on population, gross domestic product (GDP), and a combination of nine non-renewable and renewable energy source use rates have been interpolated back to 1700 and disaggregated into 220 reporting regions and used to calibrate a utility optimization model of carbon emissions. Re-aggregating into a tropical/subtropical group (with high rates of population growth and low per capita GDP) and a temperate group (with lower population growth rates and higher average per capita GDP) does not reveal empirical evidence for convergence of per capita GDP or per capita carbon emissions between the two groups. The calibration approach allows for the effect on energy and carbon use of fossil carbon depletion, and for a log-linear relationship between production efficiencies and a logistic function of time that is also calibrated against the data set. With continuing recent linear decrease of the carbon intensity of energy production with cumulative carbon use, this approach automatically produces a sensible transition from initial balanced energy and GDP growth to an eventual sustainable state relying on a balanced mix of non-fossil energy sources. Projection of time-series calibrations using this approach gives very limited growth in future global carbon emissions unless and until the historical trends used in the calibration are reversed—e.g. if a "new age of coal" results in an increase in the carbon intensity of energy production as inexpensive fluid fossil fuel resources are depleted and lasts until resulting accumulation of atmospheric carbon triggers an effective agreement on subsequent limitation of carbon emissions. Using temporal averaging to remove short-term temporal autocorrelation and periodic corrections to remove dominant long-term temporal correlations, systematic statistical analysis produces probability distributions for carbon emissions as a function of time. Combining random samples of carbon emissions trajectories with similarly time-series calibrated and sampled parameters from simple linear differential equation models of atmospheric carbon and heat balance yields systematic probability distributions for future change in global average temperature as a function of time. P-CA2.7Carbon America: Providing Regional Carbon Emissions
David Hofmann, NOAA/CMDL, David.J.Hofmann@noaa.gov Pieter Tans, NOAA/CMDL NOAA's Climate Monitoring and Diagnostics Laboratory is well-known for its climate observatories such as Mauna Loa Observatory and its global cooperative carbon dioxide network, currently involving about 100 sampling sites. Not as well known is a pilot project that began over 10 years ago which includes vertical profiling of carbon gases by small charter aircraft and tall (~600 m) communications towers. This project was undertaken because of the necessity to obtain the vertical profile of carbon gases over land in order to sort out diurnal and boundary layer meteorological variations in atmospheric carbon dioxide. This led to a proposal for "Carbon America" a 36-site network of carbon profilers (aircraft and towers), mainly in the U.S., which is now a component of NOAA's Carbon Cycle Atmospheric Observing System. Carbon America is currently about 50% implemented and is expected to be completed by 2008. Data obtained with this network, combined with new meteorological inverse transport models, is expected to lower the uncertainties in the determination of carbon dioxide and methane sources and sinks (emissions and uptake) down to a scale of 500-1,000 km. It is believed that this system can be used to determine a regional CO2 emission inventory as well as keeping track of the North American carbon dioxide uptake by natural processes and engineered carbon sequestration in the future. P-CA2.8Monitoring CO 2 from Space: The NASA Orbiting Carbon Observatory Mission
David Crisp, Jet Propulsion Laboratory, California Institute of Technology, David.Crisp@jpl.nasa.gov The OCO Team Over the past 30 years, only about half of the carbon dioxide (CO2) emitted by fossil fuel combustion and other human activities has remained in the atmosphere. The rest has apparently been absorbed by the land biosphere or oceans. The atmospheric CO2 buildup also varies dramatically from year to year in response to smoothly increasing emission rates. While these properties are clearly revealed by the ground-based CO2 monitoring networks, this network does not have the spatial coverage or resolution needed to identify the CO2 sinks or the processes that control them from year to year. NASA's Orbiting Carbon Observatory (OCO) is being developed to make the first global, space-based observations of atmospheric CO2 with the resolution and accuracy needed to quantify surface sources and sinks on regional scales. As currently planned, OCO will be launched in late 2008. It will fly in a 705-km, nearpolar sun-synchronous orbit that will sample the sunlit hemisphere every 16 days for up to two years. OCO carries a single instrument with three high resolution grating spectrometers designed to measure the absorption of reflected sunlight by CO2 and molecular oxygen (O2) bands at near-infrared wavelengths. Spectra of the CO2 bands near 1.61 and 2.06 microns provide surface-weighted estimates of the CO2 column abundance. Bore-sighted spectra in the 0.76 -micron O2 A-band provide precise estimates of surface pressure as well as constraints on clouds, aerosols, and the surface. The CO2/O2 soundings are analyzed to yield estimates of the columnaveraged CO2 dry air mole fraction, XCO2. A small surface footprint (<3 km2 at nadir) is used to reduce XCO2 biases associated with spatial variations in clouds and surface topography. Thousands of soundings are collected on regional scales each month. A comprehensive ground-based validation program is used to assess random errors and minimize biases in the XCO2 product to ensure precisions of 0.3 to 0.5% (1 to 2 ppm) on regional scales (1000 km by 1000 km) at monthly intervals. While OCO is an exploratory Earth System Science Pathfinder (ESSP) mission designed for a 2-year lifetime, its measurements can be combined with data from the surface CO2 monitoring networks to improve our understanding of the processes that regulate atmospheric CO2 sources and P-CA2.9Methane Emissions from Natural Wetlands in the United States:
Christopher Potter, NASA Ames, cpotter@mail.arc.nasa.gov Steven Klooster, California State University Seth Hiatt, California State University Matthew Fladeland, NASA Ames Peggy Gross, California State University Wetlands are an important natural source of methane to the atmosphere. The amounts of methane emitted from inundated ecosystems in the United States can vary greatly from area to area. Seasonal temperature and carbon content of soils are principal controlling factors. To calculate the effect of wetlands (and their potential conversion to other land uses) on global greenhouse gas emissions, information on area covered by various wetland types is needed, along with verified projections of spatial variation in net methane emissions. Both of these variables are poorly known, and estimates are largely unavailable at the country level. Nationwide satellite data sets for the U.S. have been combined with ecosystem model predictions of monthly net carbon exchange with the atmosphere to produce the first detailed mapping of methane fluxes from natural wetlands on a monthly and annual basis. P-CA2.10Carbon Budgets for Ecosystems of the Continental United States
Christopher Potter, NASA Ames, cpotter@mail.arc.nasa.gov Steven Klooster, California State University Vanessa Genovese, California State University Matthew Fladeland, NASA Ames NASA satellite remote sensing and vegetation-soil modeling are being used to estimate the carbon balance for ecosystems in the continental United States. To support decision making for carbon management, we report on the CQUEST (Carbon Query and Evaluation Support Tools) application, with spatially detailed (< 10 km resolution) terrestrial carbon budgets for regions of U.S. in the 1980s and 1990s. Surface soils and dead woody litter are by far the largest storage pools for carbon across the country, representing more than 35 Pg C with residence times of 25 years or less. The Southeast, Rocky Mountain, and Pacific Northwest regions of the country store the largest pools of ecosystem carbon. Although net primary production was estimated to increase on a nationwide basis during the 1990s to nearly 3.5 Pg C per year, the net terrestrial sink in U.S. ecosystems did not exceed 0.05 Pg C per year between 1982 and 1997. Net ecosystem carbon sinks for the nation were typically small, relative to fossil fuel-related carbon emissions in the U.S. on an annual basis, which makes decision making to protect large surface soil carbon and woody litter pools crucial for maintaining the national carbon balance under future climate shifts. P-CA2.11The U.S.-China Carbon Consortium (USCCC) and Its Contribution to Global Change Studies
Jiquan Chen, University of Toledo, Toledo, OH 43560, jiquan.chen@utoledo.edu
The U.S.-China Carbon Consortium (USCCC) was established in 2003 in Beijing as a collaborative consortium between American and Chinese institutions that have interests in studying the role of managed ecosystems in the global carbon and water cycles, including the Southern Global Change Program of the USDA Forest Service (SGCP), the University of Toledo, North Carolina State University, the Institute of Botany at Chinese Academy of Sciences, Fudan University, Beijing Forestry University, the Chinese Academy of Forestry, Nanjing University, and the Meteorology Administration of China. The overall goal is to develop a network of study sites sponsored by the above institutions in hope that data and results will be shared so that synthesis can be made at inter-continental scale to assess the importance of human influences on carbon and water fluxes in the changing climate. USCCC, governed by a steering committee, will adopt the data sharing policy of Long-Term Ecological Research Networks (LTER) for our future research. The data will be open to all the partitioning members through project Web pages with permission of the institution. Eddy-covariance flux towers are the central infrastructure of all USCCC sites (18 in China and 11 in the eastern U.S.). Our central hypothesis is that human disturbances increase the variability of C sequestration and water cycle of a landscape in time and space primarily via influence of the landscape structure and composition that directly affect the underlying mechanisms. Further, we hypothesize that the human disturbance regimes in the U.S. and China are significantly different, suggesting that models predicting carbon, water and energy are different. Data from several USCCC sites in northern China are members of NASA's NEESPI team (LCLUC Program) and Moisture Isotopes in the Biosphere and Atmosphere (MIBA) of IAEA. Data will be folded into the GOFC/GOLD and NEESPI programs. P-CA2.12Urban and Regional Carbon Management: Comparative Framework of the Global Carbon Project
Penelope Canan, Global Carbon Project, National Institute for Environmental Studies, 16-2 Onogawa, Tsukuba 305-8506, Ibaraki, Japan, penelope.canan@nies.go.jp The Global Carbon Project promotes global carbon cycle research that combines natural and social sciences for policy-relevant sustainability science. The "global" becomes place-based at urban and regional scales for carbon management. The GCP's Urban and Regional Carbon Management (URCM) initiative is a comparative, integrated scientific approach to place-based carbon budgets and management strategies across spatial and temporal scales. Three spatial scales are prominent: urban, regional, and cities-in-regions. By understanding the carbon legacies of various development pathways, the URCM aims to identify key opportunities for de-carbonized futures in communities around the world. The GCP is a joint program under the Earth System Science Partnership of the International Geosphere/Biosphere Program, the International Human Dimensions Programme, the World Climate Research Program, and DIVERSITAS. P-CA2.13A Bayesian Synthesis Inversion of Carbon Cycle Observations:
Daniel Ricciuto, Dept. of Meteorology, The Pennsylvania State University, ricciuto@meteo.psu.edu Klaus Keller, Dept. of Geosciences, The Pennsylvania State University Kenneth Davis, Dept. of Meteorology, The Pennsylvania State University Current predictions of CO2 sinks vary widely due to uncertainties about key feedback mechanisms (e.g., the potential increase in global respiration in response to warming). A sound characterization of these prediction uncertainties is crucial for the design of economically efficient carbon management strategies. Current predictions are typically based on a few model scenarios without a probabilistic assessment. Here we use a mechanistically sound and statistically tractable model of the global carbon cycle to (i) assimilate historical observations of atmospheric CO2 concentrations and oceanic CO2 fluxes, (ii) derive probabilistic predictions of future CO2 concentrations and fluxes, and (iii) assess the power of different observing systems to reduce predictive uncertainties. Specifically, we address three key questions: (i) Given current observation systems and prior information regarding carbon cycle parameters, what are the confidence limits of the future sink strength for a CO2 stabilization objective? (ii) How does the observed (but typically neglected) autocorrelation in observations of CO2 mixing ratios affect these predictions, and (iii) What are the abilities of candidate carbon cycle observation systems to reduce the predictive uncertainty? We address these questions using a Bayesian synthesis inversion of a simple coupled climate/carbon cycle model with
historical observations from 1850 to 2000. Assimilated observations include atmospheric CO2 concentration data from the Law Dome ice core P-CA2.14Methodology and Cost of Evaluating Soil Carbon Stocks in a 2-m Soil Profile
Christopher Post, Clemson University, cpost@clemson.edu Elena Mikhailova, Clemson University Kim Magrini-Bair, National Renewable Energy Laboratory Estimates of world soil carbon stocks are incomplete and inadequate, because most of them are based on actual soil data down to 1 m depth only and obtained by outdated methods. Therefore, call for more research in climate change science is justified. This study examines different methodology and costs associated with analyses to improve soil carbon stock estimates using experimental data from Mollisol, one of the most productive soils in the world. Availability of laboratories capable of these analyses and their prices are examined within United States of America using Geographic Information Systems (GIS). Given the dynamic nature of soil carbon reserves due to human influence, there is a need to determine time intervals for re-assessment of soil carbon stocks. P-CA2.15Carbon-Climate System Feedbacks to Natural and Anthropogenic Climate Change
S.C. Doney, Marine Chemistry and Geochemistry, Woods Hole Oceanographic Institution, 266 Woods Hole Rd., Woods Hole, MA 02543, USA, sdoney@whoi.edu I. Fung, Berkeley Atmospheric Sciences Center, University of California, Berkeley, Berkeley, CA 94720, USA, inez@atmos.berkeley.edu K. Lindsay, Climate and Global Dynamics, National Center for Atmospheric Research, P.O. Box 3000, Boulder, CO 80307, USA, klindsay@cgd.ucar.edu J. John, Berkeley Atmospheric Sciences Center, University of California, Berkeley, Berkeley, CA 94720, USA, jasmin@atmos.berkeley.edu A new generation of climate-carbon cycle models is being used to explore the responses and feedbacks of biogeochemistry to climate change. We highlight results from a stable, 1,000-year control simulation and transient experiments (1820-2100) using the Community Climate System Model (CSM 1.4 Carbon). Key findings include: modulation of terrestrial variability and climate change response via soil moisture; oceanic damping (20-25%) of atmospheric CO2 variability at low frequencies (> 20 years); inverse relationship between carbon sink efficiency and fossil fuel emissions; and decreasing in land and ocean carbon storage under climate warming, amplifying climate change. |
|
