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DOE OSTI2020

Implementation and verification of PyNE R2S with DAG-OpenMC

The mesh-based Rigorous-Two-Step (R2S) method has been widely used in the accurate estimation of the shutdown dose rate (SDR) of fusion systems. Several mesh-based R2S code has been implemented based on Monte Carlo particle transport code MCNP5 or DAG-MCNP5 and inventory calculation code such as FISPACT-II, ALARA or ACAB. Recently, the OpenMC, a community-developed Monte Carlo particle transport code, implemented the photon particle transport capability, which enables OpenMC to be used in R2S. In this paper, PyNE R2S is extended with the support of DAG-OpenMC, i.e., OpenMC with DAGMC. Modifications that allow PyNE to read the flux result in the state point file of OpenMC has been implemented to PyNE R2S workflow. A custom source routine of OpenMC that reads the photon source file from PyNE R2S and sampling photon particle in OpenMC photon transport has been implemented in OpenMC. With these modifications, PyNE R2S is now capable of performing R2S calculations with both DAG-MCNP5 and DAG-OpenMC. The ITER FNG dose rate benchmark problem has been used to validate the code. The FNG neutron source has been modified for neutron transport with DAG-OpenMC. The shutdown dose rate of 19 cooling times has been calculated and compared with the experimental data and the computational results of other R2S codes. The results of PyNE R2S with DAG-OpenMC show satisfactory agreement with the experimental data and other computational results. Therefore, we consider PyNE R2S with DAG-OpenMC is a reliable code to calculate the SDR of fusion systems.

fusion↗

NASA NTRS2011

Volatile Analyzer for Lunar Polar Missions

One of the major questions remaining for the future exploration of the Moon by humans concerns the presence of volatiles on our nearest neighbor in space. Observational studies, and investigations involving returned lunar samples and using robotic spacecraft infer the existence of volatile compounds particularly water [1]. It seems very likely that a volatile component will be concentrated at the poles in circumstances where low-temperatures exist to provide cryogenic traps. However, the full inventory of species, their concentration and their origin and sources are unknown. Of particular importance is whether abundances are sufficient to act as a resource of consumables for future lunar expeditions especially if a long-term base involving humans is to be established. To address some of these issues requires a lander designed specifically for operation at a high-lunar latitude. A vital part of the payload needs to be a volatile analyzer such as the Gas Analysis Package specifically designed for identification quantification of volatile substances and collecting information which will allow the origin of these volatiles to be identified [1]. The equipment included, particularly the gas analyzer, must be capable of operation in the extreme environmental conditions to be encountered. No accurate information yet exists regarding volatile concentration even for sites closer to the lunar equator (because of contamination). In this respect it will be important to understand (and thus limit) contamination of the lunar surface by extraneous material contributed from a variety of sources. The only data for the concentrations of volatiles at the poles comes from orbiting spacecraft and whilst the levels at high latitudes may be greater than at the equator, the volatile analyzer package under consideration will be designed to operate at the highest specifications possible and in a way that does not compromise the data.

Gibons, Everett K.↗

NASA NTRS2018

Overview of Primitive Object Volatile Explorer (PrOVE) CubeSat or Smallsat Concept

Here we describe the Primitive Object Volatile Explorer (PrOVE), a smallsat mission concept to study the surface structure and volatile inventory of comets in their perihelion passage phase when volatile activity is near peak. CubeSat infrastructure imposes limits on propulsion systems, which are compounded by sensitivity to the spacecraft disposal state from the launch platform and potential launch delays. We propose circumventing launch platform complications by using waypoints in space to park a deep space SmallSat or CubeSat while awaiting the opportunity to enter a trajectory to flyby a suitable target. In our Planetary Science Deep Space SmallSat Studies (PSDS3) project, we investigated scientific goals, waypoint options, potential concept of operations (ConOps) for periodic and new comets, spacecraft bus infrastructure requirements, launch platforms, and mission operations and phases. Our payload would include two low-risk instruments: a visible image (VisCAM) for 5-10 m resolution surface maps; and a highly versatile multispectral Comet CAMera (ComCAM) will measure 1) H2O, CO2, CO, and organics non-thermal fluorescence signatures in the 2-5 μm MWIR, and 2) 7-10 and 8-14 μm thermal (LWIR) emission. This payload would return unique data not obtainable from ground-based telescopes and complement data from Earth-orbiting observatories. Thus, the PrOVE mission would (1) acquire visible surface maps, (2) investigate chemical heterogeneity of a comet nucleus by quantifying volatile species abundance and changes with solar insolation, (3) map the spatial distribution of volatiles and determine any variations, and (4) determine the frequency and distribution of outbursts.

Clark, Pamela S.↗

NASA NTRS2018

Overview of Primitive Volatile Explorer (PrOVE) Cubesat or Smallsat Concept

Here we describe the Primitive Object Volatile Explorer (PrOVE), a smallsat mission concept to study the surface structure and volatile inventory of comets in their perihelion passage phase when volatile activity is near peak. CubeSat infrastructure imposes limits on propulsion systems, which are compounded by sensitivity to the spacecraft disposal state from the launch platform and potential launch delays. We propose circumventing launch platform complications by using waypoints in space to park a deep space SmallSat or CubeSat while awaiting the opportunity to enter a trajectory to flyby a suitable target. In our Planetary Science Deep Space SmallSat Studies (PSDS3) project, we investigated scientific goals, waypoint options, potential concept of operations (ConOps) for periodic and new comets, spacecraft bus infrastructure requirements, launch platforms, and mission operations and phases. Our payload would include two low-risk instruments: a visible image (VisCAM) for 5-10 m resolution surface maps; and a highly versatile multispectral Comet CAMera (ComCAM) will measure 1) H2O, CO2, CO, and organics non-thermal fluorescence signatures in the 2-5 µm MWIR, and 2) 7-10 and 8-14 µm thermal (LWIR) emission. This payload would return unique data not obtainable from ground-based telescopes and complement data from Earth-orbiting observatories. Thus, the PrOVE mission would (1) acquire visible surface maps, (2) investigate chemical heterogeneity of a comet nucleus by quantifying volatile species abundance and changes with solar insolation, (3) map the spatial distribution of volatiles and determine any variations, and (4) determine the frequency and distribution of outbursts.

Zucherman, Aaron↗

NASA NTRS1973

Testing the usefulness of ERTS-1 imagery for inventorying wildland resources in northern California

The usefulness of ERTS-1 imagery for inventorying wildland resources in northern California is discussed. Studies are being conducted in two large wildland areas, namely, the Feather River Watershed and the Northern Coastal Zone. The 2.5 million-acre Feather River headwaters area in northern California is the keystone watershed for the California Water Project, one of the most extensive and ambitious water resource developments ever attempted. Consequently, accurate and timely information on the quantity, quality and distribution of timber, forage, water and recreational resources is of immediate importance to each public agency and private group managing this vast, but inaccessible, wildland area. The Northern Coastal Zone (consisting of the counties of Marin, Sonoma, Mendicino, Humbolt and Del Norte) is relatively rural, with an economy based on agriculture, timber, commercial fishing and tourism. However, it is expected that intensive resource use resulting from increasing population will soon become a serious problem unless wise land use planning is undertaken. Thus, this coastal region is particularly well suited to investigations of the ways in which ERTS-1 imagery and other supporting data may be used in conducting land use evaluations.

Lauer, D. T.↗

NASA NTRS1999

The Meteorological Experiment on the Mars Surveyor '98 Polar Lander

When it lands on Mars on December 3, 1999, the Mars Surveyor '98 Mars Polar Lander (MPL) will provide the first opportunity to make in-situ measurements of the near-surface weather climate, and volatile inventory in the Martian south polar region. To make the most of this opportunity, the MPL's Mars Volatiles and Climate Surveyor (MVACS) payload includes the most comprehensive complement of meteorological instruments ever sent to Mars. Like the Viking and the Mars Pathfinder Lander, the MVACS Meteorological (Met) package includes sensors for measuring atmospheric pressures, temperatures, and wind velocities. This payload also includes a 2-channel tunable diode laser spectrometer for in-situ measurements of the atmospheric water vapor abundance near the ground, and improved instruments for measuring the relative abundances of oxygen isotopes (in water vapor and CO2) and a surface temperature probe for measuring the surface and sub-surface temperatures. This presentation will provide a brief overview of the environmental conditions anticipated at the surface in the Martian regions. We will then provide an over-view of the MVACS Met instrument and describe the MET sensors in detail, including their principle of operation, range, resolution, accuracy, sampling strategy, heritage, accommodation on the Lander, and their control and data handling system. Finally, we will describe the operational sequences, resource requirements, and the anticipated data volumes for each of the Met instruments.

Crisp, D.↗

NASA NTRS2010

Anthropogenic Air Pollution Observed Near Dust Source Regions in Northwestern China During Springtime 2008

Trace gases and aerosols were measured in Zhangye (39.082degN, 100.276degE, 1460 m a.s. 1.), a rural site near the Gobi deserts in northwestern China during spring 2008. Primary trace gases (CO:265 ppb; SO2:3.4 ppb; NO(*y): 4.2 ppb; hereafter results given as means of hourly data) in the area were lower than in eastern China, but still indicative of marked anthropogenic emissions. Sizable aerosol mass concentration (153 micro-g/cu m) and light scattering (159/Mm at 500 nm) were largely attributable to dust emissions, and aerosol light absorption (10.3/Mm at 500 nm) was dominated by anthropogenic pollution. Distinct diurnal variations in meteorology and pollution were induced by the local valley terrain. Strong daytime northwest valley wind cleaned out pollution and was replaced by southeast mountain wind that allowed pollutants to build up overnight. In the afternoon, aerosols had single scattering albedo (SSA, 500 mn) of 0.95 and were mainly of supermicron particles, presumably dust, while at night smaller particles and SSA of 0.89-0.91 were related to Pollution. The diverse local emission sources were characterized: the CO/SO2, CO/NO(y), NO(y)/SO2 (by moles), and BC/CO (by mass) ratios for small point sources such as factories were 24.6-54.2, 25.8-35.9, 0.79-1.31, and 4.1-6.1 x 10(exp -3), respectively, compared to the corresponding inventory ratios of 43.7-71.9, 23.7-25.7, 1.84-2.79, and 3.4-4.0 x 10(exp -3) for the industrial sector in the area. The mixing between dust and pollution can be ubiquitous in this region. During a dust storm shown as an example, pollutants were observed to mix with dust, causing discernible changes in both SSA and aerosol size distribution. Further interaction between dust and pollutants during transport may modify the properties of dust particles that are critical for their large-scale impact on radiation, clouds, and global biogeochemical cycles.

Li, Can↗

DOE OSTI2024

Hydropower Infrastructure – LAkes, Reservoirs, and RIvers (HILARRI)

HILARRI is a database of links between major datasets of operational hydropower dams and powerplants, and inland water bodies. These connections are critical for conducting large-scale analysis of hydropower infrastructure and their associated natural and engineered water systems. Features include: – Dams from the National Inventory of Dams (2024) and the Global Reservoir and Dam Database (GRanD v1.3) – Hydropower plants from the Existing Hydropower Assets dataset (EHA 2024) These hydropower infrastructure features are linked to several major datasets that provide hydrologic and hydraulic information relevant for analysis of hydropower systems that includes the integral water resources. That information comes from: – Products from the National Hydrography Dataset (NHD) – NHDPlusV2 Medium Resolution river network flowlines, – NHD waterbodies (limited to lakes and reservoirs), – NHD Watershed Boundary Dataset (HUC12-level for the Conterminous United States (CONUS)) – NHD High Resolution waterbodies – HydroLAKES water bodies (lakes and reservoirs) – LAGOS-US lakes and reservoirs – EPA National Lakes Assessment (2007, 2012, 2017, and 2022) – The Reservoir Sedimentation Database (RESSED) Unique identifiers are used to facilitate joining to the original full datasets. For example, characteristics of NHD flowlines such as estimated average flow rate can be joined from the NHDPlusV2 dataset to a dam or power plant listed in HILARRI based on the ID field, “COMID”, that is common to both datasets. HILARRI only includes basic information about identifiers, location, and data quality or usage notes. It does not contain the attributes or time series data associated with these sites. The HILARRI dataset incorporates information from several datasets to facilitate more effective and accurate analysis of hydropower infrastructure and their associated waterbodies. For example, dams were checked against the most recent American Rivers Dam Removal Database to identify and flag facilities that may no longer exist. Additionally, dams that are listed multiple times in the NID are identified and flagged to avoid double-counting when analyzing and summarizing information. Other quality flags include certainty of operational hydropower (i.e., if one or more datasets indicates hydropower at a particular location), whether an associated water body is accurate or composed of multiple polygons, or whether there is a known issue with reported characteristics in one of the underlying datasets. These additional data flags are designed to increase confidence in data usage for individual to large-scale analyses.

13 HYDRO ENERGY↗

DOE OSTI2020

Deeper snow increases the net soil organic carbon accrual rate in moist acidic tussock tundra: 210Pb evidence from Arctic Alaska

The net change in the carbon inventory of arctic tundra remains uncertain as global warming leads to shifts in arctic water and carbon cycles. To better understand the response of arctic tundra carbon to changes in winter precipitation amount, we investigated soil depth profiles of carbon concentration and radionuclide activities ( 7 Be, 137 Cs, 210 Pb, and 241 Am) in the active layer of a twenty-two-year winter snow depth manipulation experiment in moist acidic tussock tundra at Toolik Lake, Alaska. Depth correlations of cumulative carbon dry mass (g cm -2 ) vs. unsupported 210 Pb activity (mBq g -1 ) were examined using a modified constant rate of supply (CRS) model. Results were best fit by two-slope CRS models indicating an apparent step temporal increase in the accumulation rate of soil organic carbon. Most of the best-fit model chronologies indicated that the increase in carbon accumulation rate apparently began and persisted after snow fence construction in 1994. The inhomogeneous nature of permafrost soils and their relatively low net carbon accumulation rates make it challenging to establish robust chronologic records. Nonetheless, the data obtained in this study support a decadal-scale increase in net soil organic carbon accumulation rate in the active layer of arctic moist acidic tussock tundra under conditions of increased winter precipitation.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2020

Using Robotic Manipulators for Radioactive Waste Inspection - 20090

The global nuclear industry has a growing volume of nuclear waste which needs to be scanned, sorted according to its activity and material type, then processed into the correct waste packages for long term storage and disposal. It is vital that there is a detailed understanding of the waste inventory stored in long term waste containers, as knowledge of their contents could predict or prevent any adverse effects in storage. The numerous 'scan and sort' tables which are currently used at many different facilities around the world to sort waste into their correct containers are human operated and require very slow gamma scanning procedures combined with educated guesswork to manually sort the waste. This often leads to excessive conservatisms, with placement of lower activity wastes in higher activity containers, which in turn costs significantly more to store. In the United Kingdom it costs UK Pounds 46 k per cubic meter to store intermediate level waste compared to just UK Pound 2.9 k per cubic meter to store low level waste according to a 2008 Department of Energy and Climate Change report in the UK. A proposed solution to this problem, is the use of a robotic manipulator to automatically inspect the 'scan and sort table' in order to produce an accurate 3D model of the table's waste contents and attach an overlaid radiation map. The radiation map contains spectrometry data and can in consequence be used to distinguish and locate specific radioisotopes. The 3D model should be as accurate as possible in order to allow for a second robot arm with an attached gripper to grasp the objects and place them into their designated long-term storage container. Various scanning procedures are explored in this study including basic raster scanning, adaptive raster scanning and point sampling. The optimal solution will in practice be defined by the required application and activity level of the wastes being inspected. The results presented in this study indicate that it is possible to produce a centimeter accurate 3D model of a mixed assortment of components on a nuclear waste 'scan and sort' table. In addition, it was shown that the waste objects emitting radiation could be accurately identified and located, with an overlaid radiation map. This study is applicable across the nuclear waste management sector. Many of the ideas and concepts developed in this study are applicable in other decommissioning settings for example, dismantling of legacy gloveboxes or routine inspection of nuclear waste packages in storage. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

DOE OSTI2026

Data from: Coupled machine learning-ecosystem ensemble models substantially improve predictions of nitrous oxide (N 2 O) fluxes from US croplands

Nitrous oxide (N₂O) is a potent and persistent greenhouse gas, with rising atmospheric concentrations driven in part by inefficient use of synthetic nitrogen (N) fertilizers in agriculture. Predicting soil N₂O emissions is challenging due to high spatial and temporal variability arising from complex soil biogeochemical processes. Process-based ecosystem models and standalone machine learning (ML) approaches without extensive site-specific calibration often miss high emission episodes. Here, we show how an Ensemble Modeling System (EMS) based on outputs from an ensemble of ecosystem models coupled to an ensemble of ML models can improve predictions and understanding of N2O fluxes from US cropland. Trained and validated on approximately 12,000 N2O chamber measurements at 17 U.S. Midwest sites (six crops, 35 management practices), the EMS accurately predicted daily fluxes of N2O at both training (R² = 0.84, RMSE = 16.4 g N ha⁻¹ d⁻¹) and held-out testing sites (R² = 0.84, RMSE = 6.2 g N ha⁻¹ d⁻¹). Analyses identified six dominant N₂O drivers: soil organic carbon (SOC), NH₄⁺, NO₃⁻, water-filled pore space (WFPS), soil temperature, and biomass production. Wet, warm soils produced large N₂O peaks only with sufficient SOC and mineral N; in low-SOC soils, fluxes remained low. Incorporating these drivers into process-based models might significantly improve their predictive capacity. The EMS demonstrates a strong potential to predict N₂O fluxes at unseen sites, enabling more reliable regional inventories, improved gap-filling where measurements are sparse, and enhanced understanding of mechanisms to advance targeted mitigation strategies in food, feed, and bioenergy crops.

agricultural sciences↗

DOE OSTI2023

Quantification of oil and gas methane emissions in the Delaware and Marcellus basins using a network of continuous tower-based measurements

Abstract. According to the United States Environmental Protection Agency (US EPA), emissions from oil and gas infrastructure contribute 30 % of all anthropogenic methane (CH4) emissions in the US. Studies in the last decade have shown emissions from this sector to be substantially larger than bottom-up assessments, including the EPA inventory, highlighting both the increased importance of methane emissions from the oil and gas sector in terms of their overall climatological impact and the need for independent monitoring of these emissions. In this study we present continuous monitoring of regional methane emissions from two oil and gas basins using tower-based observing networks. Continuous methane measurements were taken at four tower sites in the northeastern Marcellus basin from May 2015 through December 2016 and five tower sites in the Delaware basin in the western Permian from March 2020 through April 2022. These measurements, an atmospheric transport model, and prior emission fields are combined using an atmospheric inversion to estimate monthly methane emissions in the two regions. This study finds the mean overall emission rate from the Delaware basin during the measurement period to be 146–210 Mg CH4 h−1 (energy-normalized loss rate of 1.1 %–1.5 %, gas-normalized rate of 2.5 %–3.5 %). Strong temporal variability in the emissions was present, with the lowest emission rates occurring during the onset of the COVID-19 pandemic. Additionally, a synthetic model–data experiment performed using the Delaware tower network shows that the presence of intermittent sources is not a significant source of uncertainty in monthly quantification of the mean emission rate. In the Marcellus, this study finds the overall mean emission rate to be 19–28 Mg CH4 h−1 (gas-normalized loss rate of 0.30 %–0.45 %), with relative consistency in the emission rate over time. These totals align with aircraft top-down estimates from the same time periods. In both basins, the tower network was able to constrain monthly flux estimates within ±20 % uncertainty in the Delaware and ±24 % uncertainty in the Marcellus. The results from this study demonstrate the ability to monitor emissions continuously and detect changes in the emissions field, even in a basin with relatively low emissions and complex background conditions.

54 ENVIRONMENTAL SCIENCES↗

NASA NTRS2022

Could Road Constructions Be More Hazardous Than an Earthquake in Terms of Mass Movement?

Roads can have a significant impact on the frequency of mass wasting events in mountainous areas. However, characterizing the extent and pervasiveness of mass movements over time has rarely been documented due to limitations in available data sources to consistently map such events. We monitored the evolution of a road network and assessed its effect on mass movements for a 11-year window in Arhavi, Turkey. The main road construction projects run in the area are associated with a hydroelectric power plant as well as other road extension works and are clearly associated with the vast majority (90.1%) of mass movements in the area. We also notice that the overall number and size of the mass movements are much larger than in the naturally-occurring comparison area. This means that the sediment load originating from the anthropogenically induced mass movements is larger than its counterpart associated with naturally occurred landslides. Notably, this extra sediment load could cause river channel aggregation, reduce accommodation space and as a consequence, it could lead to an increase in the probability and severity of flooding along the river channel. This marks a strong and negative effect of human activities on the natural course of earth surface processes. We also compare frequency-area distributions of human-induced mass movements mapped in this study and co-seismic landslide inventories from the literature. By doing so, we aim to better understand the consequences of human effects on mass movements in a comparative manner. Our findings show that the damage generated by the road construction in terms of sediment loads to river channels is compatible with the possible effect of a theoretical earthquake with a magnitude greater than Mw=6.0.

Hakan Tanyas↗

NASA NTRS2015

Martian Chlorobenzene Identified by Curiosity in Yellowknife Bay: Evidence for the Preservation of Organics in a Mudstone on Mars

The Sample Analysis at Mars (SAM) instrument on the Curiosity rover is designed to determine the inventory of organic and inorganic volatiles thermally evolved from solid samples using a combination of evolved gas analysis (EGA), gas chromatography mass spectrometry (GCMS), and tunable laser spectroscopy. The first sample analyzed by SAM at the Rocknest (RN) aeolian deposit revealed chlorohydrocarbons derived primarily from reactions between a martian oxychlorine phase (e.g. perchlorate) and terrestrial carbon from N-methyl-N-(tert-butyldimethylsilyl) trifluoroacetamide (MTBSTFA) vapor present in the SAM instrument background. No conclusive evidence for martian chlorohydrocarbons in the RN sand was found. After RN, Curiosity traveled to Yellowknife Bay and drilled two holes separated by 2.75 m designated John Klein (JK) and Cumberland (CB). Analyses of JK and CB by both SAM and the CheMin x-ray diffraction instrument revealed a mudstone (called Sheepbed) consisting of approx.20 wt% smectite clays, which on Earth are known to aid the concentration and preservation of organic matter. Last year at LPSC we reported elevated abundances of chlorobenzene (CBZ) and a more diverse suite of chlorinated hydrocarbons including dichloroalkanes in CB compared to RN, suggesting that martian or meteoritic organic compounds may be preserved in the mudstone. Here we present SAM data from additional analyses of the CB sample and of Confidence Hills (CH), another drill sample collected at the base of Mt. Sharp. This new SAM data along with supporting laboratory analog experiments indicate that most of the chlorobenzene detected in CB is derived from martian organic matter preserved in the mudstone.

Glavin, D.↗

NASA NTRS2015

Martian Chlorobenzene Identified by Curiosity in Yellowknife Bay: Evidence for the Preservation of Organics in a Mudstone on Mars

Curiosity in Yellowknife↗

NASA NTRS2002

Modeling the Stability of Volatile Deposits in Lunar Cold Traps

There are several mechanisms acting at the cold traps that can alter the inventory of volatiles there. Primarily, the lunar surface is bombarded by meteoroids which impact, melt, process, and redistribute the regolith. Further, solar wind and magnetospheric ion fluxes are allowed limited access onto the regions in permanent shadow. Also, although cold traps are in the permanent shadow of the Sun, there is a small flux of radiation incident on the regions from interstellar sources. We investigate the effects of these space weathering processes on a deposit of volatiles in a lunar cold trap through simulations. We simulate the development of a column of material near the surface of the Moon resulting from space weathering. This simulation treats a column of material at a lunar cold trap and focuses on the hydrogen content of the column. We model space weathering processes on several time and spatial scales to simulate the constant rain of micrometeoroids as well as sporadic larger impactors occurring near the cold traps to determine the retention efficiency of the cold traps. We perform the Monte Carlo simulation over many columns of material to determine the expectation value for hydrogen content of the top few meters of soil for comparison with Lunar Prospector neutron data.

Crider, D. H.↗

NASA NTRS2003

Modeling the Absorbing Aerosol Index

We propose a scheme to model the absorbing aerosol index and improve the biomass carbon inventories by optimizing the difference between TOMS aerosol index (AI) and modeled AI with an inverse model. Two absorbing aerosol types are considered, including biomass carbon and mineral dust. A priori biomass carbon source was generated by Liousse et al [1996]. Mineral dust emission is parameterized according to surface wind and soil moisture using the method developed by Ginoux [2000]. In this initial study, the coupled CCM1 and GRANTOUR model was used to determine the aerosol spatial and temporal distribution. With modeled aerosol concentrations and optical properties, we calculate the radiance at the top of the atmosphere at 340 nm and 380 nm with a radiative transfer model. The contrast of radiance at these two wavelengths will be used to calculate AI. Then we compare the modeled AI with TOMS AI. This paper reports our initial modeling for AI and its comparison with TOMS Nimbus 7 AI. For our follow-on project we will model the global AI with aerosol spatial and temporal distribution recomputed from the IMPACT model and DAO GEOS-1 meteorology fields. Then we will build an inverse model, which applies a Bayesian inverse technique to optimize the agreement of between model and observational data. The inverse model will tune the biomass burning source strength to reduce the difference between modelled AI and TOMS AI. Further simulations with a posteriori biomass carbon sources from the inverse model will be carried out. Results will be compared to available observations such as surface concentration and aerosol optical depth.

Penner, Joyce↗

NASA NTRS1988

Carbon dioxide catastrophes: Past and future menace

Carbon dioxide is important in its role as coupler of the terrestrial biosphere to inorganic chemical processes and as the principal greenhouse gas controlling Earth's surface temperature. The hypothesis that atmospheric CO2 levels have diminished with time, with the resulting cooling effect offsetting an increase in the solar constant, seems firmly established, and it is shown that feedback mechanisms exist which can maintain the terrestrial surface in a relatively narrow temperature range over geological time. Of the factors involved in such CO2 variation, the oceanic reservoir appears the most important. Surface waters are probably in approximate equilibrium with regard to CO2 exchange with the ambient atmosphere in most regions, but data from deep-ocean water sampling indicates that such waters are somewhat undersaturated in the sense that they would tend to absorb CO2 from the atmosphere if brought to the surface without change in composition or temperature. If major impacts into the ocean can result in loss of a substantial portion of the atmospheric CO2 reservoir, then any such future event could imperil the continuation of most higher forms of life on Earth. The most likely candidate for an inverse Nyos global event in previous Earth history is the Cretaceous-Tertiary terminal extinction event. The Cretaceous was characterized by warm, equable temperatures presumably indicative of relatively high CO2 levels and an intense greenhouse heating. Cooling of the oceans in absence of massive transfer of CO2 to the oceanic reservoir in itself would promote a condition of CO2 undersaturation in abyssal waters, and this is made even more extreme by the pattern of ocean water circulation. It is possible to envision a situation in which deep ocean waters were at least occasionally profoundly undersaturated with regard to CO2. Turnover of a major fraction of such an ocean would then remove, on a very short time scale, as much as 90 percent of the atmospheric CO2 inventory.

Baur, Mario E.↗