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All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Assessing the large-scale drivers of precipitation in the northeastern United States via linear orthogonal decomposition

This study examines the linear orthogonal modes associated with monthly precipitation in the northeastern United States, from CESM1 LENS (35 ensemble members, 1979–2005) and two reanalysis datasets (ERA5, 1950–2018 and NOAA-CIRES-DOE 20CRv3, 1950–2015). Calendar months are aggregated together, and any linear trends in data are removed. Using region-averaged precipitation anomaly time series and monthly anomalies for several global 2D atmospheric fields, a linear orthogonal decomposition method is implemented to iteratively extract time series (based on field and geographic location) of absolute maximum correlation. Linear modes associated with this method are then projected onto the full set of 2D fields to provide physical insight into the mechanisms involved in generating precipitation. In this region, the first mode is associated with vapor transport from the Atlantic seaboard, the second mode is characterized by westward vapor transport associated with extratropical cyclones, and the third mode captures vapor transport from the Gulf of Mexico during the fall and winter. However, the third mode is less robust in the spring and summer. Results are generally consistent across the datasets, and applying multiple linear regression with the linear modes to predict the precipitation anomalies produces R-squared values of around 0.54–0.65 for CESM1 LENS, and around 0.58–0.88 for reanalysis, with the lowest values generally in the spring and late summer. The influence of low-frequency climate variability on the modes is considered for CESM1 LENS, and the modes in late winter can be predicted with some success via a combination of several, prominent large-scale teleconnection patterns.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Understanding the Cascade: Removing GCM Biases Improves Dynamically Downscaled Climate Projections

Polarization surrounding bias correction (BC) in creating climate projections arises from its lack of physicality. Here, we perform and analyze 18 dynamical downscaling simulations (with and without BC) to better understand the physical impacts of BC, applied before downscaling, on regional climate output across the western United States. Without BC, downscaled precipitation is systematically and unrealistically wet biased compared to a hierarchy of observationally based datasets over the 1980–2014 period due to cascading mean–state Global Climate Model (GCM) biases: (a) overly strong lower–tropospheric lapse rates (5 K/km), (b) overly cold (2 K) tropospheric temperatures, and (c) anomalous mid–tropospheric cyclonic vorticity advection. With BC, downscaled precipitation (snow) biases are virtually eliminated (halved). Identified GCM biases are common to the broader Coupled Model Intercomparison Project ensemble. Physical effects of BC on the quality of the regionalized projections, pending an evaluation of BC's distortion of the downscaled climate response, may motivate its broader application by dynamical downscalers.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Future precipitation increase constrained by climatological pattern of cloud effect

The fractional increase in global mean precipitation (?P ¯/P ¯) is a first-order measure of the hydrological cycle intensification under anthropogenic warming. However, ?P ¯/P ¯ varies by a factor of more than three among model projections, hindering credible assessments of the associated climate impacts. The uncertainty in ?P ¯/P ¯ stems from uncertainty in both hydrological sensitivity (global mean precipitation increase per unit warming) and climate sensitivity (global mean temperature increase per forcing). Here, by investigating hydrological and climate sensitivities in a unified surface-energy-balance perspective, we find that both sensitivities are significantly correlated with surface shortwave cloud feedback, which is further linked to the climatological pattern of cloud shortwave effect. The observed pattern of cloud effect thus constrains both sensitivities and consequently constrains ?P ¯/P ¯. The 5%-95% uncertainty range of ?P ¯/P ¯ from 1979-2005 to 2080-2100 under the high-emission (moderate-emission) scenario is constrained from 6.34±3.53% (4.19±2.28%) in the raw ensemble-model projection to 7.03±2.59% (4.63±1.71%). The constraint thus suggests a higher most-likely ?P ¯/P ¯ and reduces the uncertainty by ~25%, providing valuable information for impact assessments.

Zhou, Wenyu↗
NASA NTRSDate not supplied

Building Capacity to Use Earth Observations for Agriculture and Food Security Applications: A Summary of NASA’s DEVELOP Program and Projects in Central and South America

NASA’s DEVELOP program engages individuals and organizations in 10-week feasibility studies to apply NASA Earth observations (EO) to decision makers’ needs. Since 2018, DEVELOP conducted 21 projects in Central and South America, eight of those in collaboration with Sistema de la Integración Centroamericana (SICA) and its member state partner agencies. These projects addressed a diverse set of community needs across multiple themes, including two feasibility studies that focused on monitoring drought and precipitation patterns and their impacts on agriculture in Guatemala, Honduras, El Salvador, and Nicaragua using EO from Terra MODIS and GPM. This poster introduces DEVELOP, its approach to capacity building, key partnerships, and project results highlighting the capabilities of EO for enhanced decision making in the area of agriculture and food security.

Capacity Building↗
DOE OSTI2022

Mesoscale Convective Systems Simulated by a High–Resolution Global Nonhydrostatic Model Over the United States and China

Mesoscale convective systems (MCSs) contribute a large fraction of warm-season precipitation and generate hazardous weather with substantial socio-economic impacts. Uncertainties in convection parameterizations in climate models limit our understanding of MCS characteristics and reliability of future projection. We examine the MCS simulation from the global 14-km Nonhydrostatic ICosahedral Atmospheric Model (NICAM) without cumulus parameterization against satellite observation from Global Precipitation Measurement (GPM) during 2001-2008. We focus on MCSs over the central U.S. and eastern China where MCSs prevail from March to August. A process-oriented tracking method incorporating both cloud and precipitation criteria is used to identify and track MCSs. About 140/100 MCSs initiate in the central U.S./eastern China per warm season and most of them initiate east of high mountains and in coastal regions. The frequency distribution of MCS lifetime is well captured in NICAM. But the simulated MCSs have stronger precipitation, smaller precipitation area, and larger cold cloud system than observed in both regions, which may be caused by weak entrainment as it is not well resolved at 14 km resolution. Here, the simulated MCS number is also underestimated in summer. By examining the climatological and MCS large-scale environments, the significant underestimation of MCS number in summer over the central U.S. may be attributed to the large climatological dry bias in the atmosphere. For China, mean moisture in summer is well simulated but deficiency in capturing the dynamic condition related to the coastal topography for triggering convection may have contributed to underestimation of MCS even in a sufficiently moist environment.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Implicit learning of convective organization explains precipitation stochasticity

Accurate prediction of precipitation intensity is crucial for both human and natural systems, especially in a warming climate more prone to extreme precipitation. Yet, climate models fail to accurately predict precipitation intensity, particularly extremes. One missing piece of information in traditional climate model parameterizations is subgrid-scale cloud structure and organization, which affects precipitation intensity and stochasticity at coarse resolution. Here, using global storm-resolving simulations and machine learning, we show that, by implicitly learning subgrid organization, we can accurately predict precipitation variability and stochasticity with a low-dimensional set of latent variables. Using a neural network to parameterize coarse-grained precipitation, we find that the overall behavior of precipitation is reasonably predictable using large-scale quantities only; however, the neural network cannot predict the variability of precipitation (R 2 ~ 0.45) and underestimates precipitation extremes. The performance is significantly improved when the network is informed by our organization metric, correctly predicting precipitation extremes and spatial variability (R 2 ~ 0.9). The organization metric is implicitly learned by training the algorithm on a high-resolution precipitable water field, encoding the degree of subgrid organization. The organization metric shows large hysteresis, emphasizing the role of memory created by subgrid-scale structures. We demonstrate that this organization metric can be predicted as a simple memory process from information available at the previous time steps. These findings stress the role of organization and memory in accurate prediction of precipitation intensity and extremes and the necessity of parameterizing subgrid-scale convective organization in climate models to better project future changes of water cycle and extremes.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2019

An Update on GPM and TRMM Data Services at NASA GES DISC

The Goddard Earth Sciences (GES) Data and Information Services Center (DISC) is home to data archives of the NASA-JAXA Global Precipitation Measurement (GPM), the Tropical Rainfall Measuring Mission (TRMM), and other NASA missions and projects. To maximize the use of NASA data products in scientific research and applications as well as for societal benefits, we provide data and information services that make datasets easy to find and use through simplification of data access for users at all levels around the world. Over the years, user-friendly data services have been developed at GES DISC, including data subsetting, format conversion, online visualization and analysis (i.e. Giovanni), user support system, etc. We routinely analyze questions, feedback, and use cases from users and algorithm developers around the world as well as best practices and new technology to improve existing services and formulate new data services. Interaction between users and algorithm developers is an important process for identifying issues in products, collecting user requirements, and improving product quality and usability. Staff members regularly communicate with algorithm developers with user questions and concerns through conferences and workshops. We publish peer-reviewed papers and articles in major Earth science journals and book chapters to describe NASA global and regional precipitation datasets and services with examples. News articles about GPM and TRMM datasets associated with significant events are regularly posted in the GES DISC Web portal and social media. We also actively participate in training activities. In this presentation, we present our latest activities about GPM and TRMM data services, data/service metrics, and future plans at GES DISC.

Liu, Z.↗
NASA NTRS2003

Precipitation Processes developed during ARM (1997), TOGA COARE(1992), GATE(1 974), SCSMEX(1998) and KWAJEX(1999): Consistent 2D and 3D Cloud Resolving Model Simulations

Real clouds and clouds systems are inherently three dimensional (3D). Because of the limitations in computer resources, however, most cloud-resolving models (CRMs) today are still two-dimensional (2D). A few 3D CRMs have been used to study the response of clouds to large-scale forcing. In these 3D simulations, the model domain was small, and the integration time was 6 hours. Only recently have 3D experiments been performed for multi-day periods for tropical cloud system with large horizontal domains at the National Center for Atmospheric Research. The results indicate that surface precipitation and latent heating profiles are very similar between the 2D and 3D simulations of these same cases. The reason for the strong similarity between the 2D and 3D CRM simulations is that the observed large-scale advective tendencies of potential temperature, water vapor mixing ratio, and horizontal momentum were used as the main forcing in both the 2D and 3D models. Interestingly, the 2D and 3D versions of the CRM used in CSU and U.K. Met Office showed significant differences in the rainfall and cloud statistics for three ARM cases. The major objectives of this project are to calculate and axamine: (1)the surface energy and water budgets, (2) the precipitation processes in the convective and stratiform regions, (3) the cloud upward and downward mass fluxes in the convective and stratiform regions; (4) cloud characteristics such as size, updraft intensity and lifetime, and (5) the entrainment and detrainment rates associated with clouds and cloud systems that developed in TOGA COARE, GATE, SCSMEX, ARM and KWAJEX. Of special note is that the analyzed (model generated) data sets are all produced by the same current version of the GCE model, i.e. consistent model physics and configurations. Trajectory analyse and inert tracer calculation will be conducted to identify the differences and similarities in the organization of convection between simulated 2D and 3D cloud systems.

Tao, W.-K.↗
DOE OSTI2022

Divergent responses of soil microorganisms to throughfall exclusion across tropical forest soils driven by soil fertility and climate history

Model projections predict tropical forests will experience longer periods of drought and more intense precipitation cycles under a changing climate. Such transitions have implications for structure-function relationships within microbial communities. We examine how throughfall exclusion might reshape prokaryotic and fungal communities across four lowland forests in Panama with a wide variation in mean annual precipitation and soil fertility. Four sites were established across a 1000 mm span in Mean Annual Precipitation (MAP: 2335–3421 mm). We expected microbial communities at sites with lower MAP to be less sensitive to throughfall exclusion than sites with higher MAP and fungal communities to be more resistant to disturbance than prokaryotes. At each location, partial throughfall exclusion structures were established over 10 × 10 m plots to reduce direct precipitation input. After short-term (~3–9 months) throughfall exclusion, prokaryotic communities showed no change in composition. However, prolonged (12–18 months) throughfall exclusion resulted in divergent prokaryotic community responses, reflecting MAP and soil fertility. We observed the emergence of a “drought microbiome” within infertile sites, whereby the community structure of the experimental throughfall exclusion plots at the lower MAP sites diverged from their respective control sites and converged towards overlapping assemblages. Furthermore, under throughfall exclusion, taxa increasing in relative abundance at the wettest site reflected that endemic to control plots at the lowest MAP site, suggesting a shift toward communities with lifehistory traits selected for under a lower MAP. By contrast, fungal community composition across sites was resilient to throughfall exclusion; however, biomass diverged in response to throughfall exclusion, increasing at two sites while decreasing in the other two. Broadly, our results suggest that microbial communities’ sensitivity to frequent drying and rewetting periods in tropical forest soils will depend on climate history and soil fertility, with infertile sites likely to respond readily to changes in precipitation.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

The Global‐Mean Precipitation Response to CO 2 ‐Induced Warming in CMIP6 Models

Abstract We examine the response of globally averaged precipitation to global warming—the hydrologic sensitivity (HS)—in the Coupled Model Intercomparison Project phase 6 (CMIP6) multi‐model ensemble. Multi‐model mean HS is 2.5% K −1 (ranging from 2.1–3.1% K −1 across models), a modest decrease compared to CMIP5 (where it was 2.6% K −1 ). This new set of simulations is used as an out‐of‐sample test for observational constraints on HS proposed based on CMIP5. The constraint based on clear‐sky shortwave absorption sensitivity to water vapor has weakened, and it is argued that a proposed constraint based on surface low cloud longwave radiative effects does not apply to HS. Finally, while a previously proposed mechanism connecting HS and climate sensitivity via low clouds is present in the CMIP6 ensemble, it is not an important factor for variations in HS. This explains why HS is uncorrelated with climate sensitivity across the CMIP5 and CMIP6 ensembles.

Pendergrass, A. G.↗
DOE OSTI2025

Model Intercomparison of the Impacts of Varying Cloud Droplet–Nucleating Aerosols on the Life Cycle and Microphysics of Isolated Deep Convection

The microphysical impacts of aerosol particles on scattered isolated deep convective cells near Houston, Texas, on 19 June 2013, are examined using multiple cloud-resolving model (CRM) simulations initialized with vertical profiles of low and high concentrations of cloud droplet–nucleating aerosols. These simulations formed part of the Model Intercomparison Project (MIP) conducted by the Deep Convective Working Group of the Aerosol, Cloud, Precipitation and Climate (ACPC) initiative. Each CRM generated a field of convective cells representing those observed during the case study with varying degrees of accuracy. The Tracking and Object-Based Analysis of Clouds (tobac) cell-tracking algorithm was applied to each MIP CRM simulation to track relatively long-lived convective cells (20–60 min). Most of the CRMs produced similar aerosol loading impacts on the warm phase of tracked cell properties with reduced autoconversion and accretion growth of rain, increased cloud water, reduced rainfall, and reduced near-surface evaporation of rain. The sign of aerosol impacts on the warm-phase properties of the convective cells was also quite consistent over cell lifetimes with the greatest magnitude of influence in the first half of the life cycle in most CRMs. In contrast, the ice-phase response to aerosol loading was highly variable among CRMs and included increases or decreases in ice amounts at inconsistent stages of the cell life cycle and midlevel versus upper-level changes in ice. This intermodel variability in ice is indicative both of the complex indirect interactions between aerosols and ice-phase processes in deep convection and their associated parameterizations.

Aerosol-cloud interaction↗
DOE OSTI2022

16S and ITS Amplicon Sequencing Fastq files and metadata from PARCHED Panama Tropical Forest soils, 2019-2020,

Model projections predict tropical forests will experience longer periods of drought and more intense precipitation cycles under a changing climate. Such transitions have implications for structure-function relationships within microbial communities. We examine how chronic drying might reshape prokaryotic and fungal communities across four lowland forests in Panama with a wide variation in mean annual precipitation and soil fertility. Four sites were established across a 1000 mm span in mean annual precipitation (2335 to 3300 mm). We expected microbial communities at sites with lower MAP to be less sensitive to chronic drying than sites with higher MAP; while fungal communities to be more resistant to disturbance than prokaryotes. At each location, partial throughfall exclusion structures were established over 10 x 10 m plots to reduce direct precipitation input. Raw demultiplexed sequences (bacteria, archaea, fungal) from soil samples taken from PARCHED Panama Tropical Forest throughfall exclusion experiments. Files that contain 16S are sequences from prokaryotes, ITS indicates sequences from fungi. Compressed fastq files are contained in Field_PARCHED_ITS_fastq_2020.zip, Field_PARCHED_ITS_fastq_2019.zip, Field_PARCHED_16S_fastq_2020.zip, Field_PARCHED_16S_fastq_2019.zip.There are four sites across the isthmus of Panama, each with 4 control and 4 exclusion plots. Throughfall exclusion shelters were built to intercept 50% of throughfall precipitation that hits the soil. Samples were taken on May 2019 and Jan 2020 from 0-10 cm and 10-20 cm depth approximately 9 and 18 months after shelter installation. Metadata and sample IDs for fastq files for 2019 sampling are within Field_PARCHED_Metadata_2019_ITS.csv and Field_PARCHED_Metadata_2019_16S.csv. The metadata for both 16S and ITS fastq files for January 2020 is included in Field_PARCHED_Metadata_2020.csv. No data processing or QA/QC was done on the raw data. Data processing example provided in R notebook file.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1985

Martian atmospheric photochemistry and composition during periods of low obliquity

During periods of low obliquity, previous work has shown that martian CO2 partial pressures decreased to 0.1 mbar; CO2 partial pressures decreased to 0.02 mbar prior to the formation of the Tharsis bulge. The permanent polar caps act as a cold trap and projected global average water vapor abundances drop to possibly as low as 0.00001 precipitable micron. As a result, the odd hydrogen catalytic cycle would not be effective at recombining CO and O back into CO2, and as much as 0.12 mbar of CO and 0.06 mbar of O2 could exist. These increased abundances would radically affect surface oxidation, change the lower atmospheric thermal structure, and completely alter the upper atmosphere.

Lindner, B. L.↗
NASA NTRS2002

In Situ Microphysical Observations in Support of the TRMM/KWAJEX Field Campaign

This project encompasses development of concepts, field investigation techniques and analysis for processes of precipitation in tropical environments. The field work was primarily undertaken during the DC-8 campaign in Kwajelein during the summer of 2001; it was stymied by the inability of the PI to obtain participation in this primary field activity (the associate PI ably carried out the field work but direct involvement of the PI in the field was a major detraction for the subsequent analysis). Insight into the relevant meteorological processes was supplemented by data and investigations of the PI on the NASA DC-8 in CAMEX from Orlando in 1998 together with previous work in hurricane environments and also in laboratory studies on the formation and characteristics of ice at low temperatures.

Hallett. John↗
NASA NTRS2021

Confronting Future Models with Future Satellite Observations of Clouds and Aerosols

The NASA Aerosol, Clouds, Convection and Precipitation (ACCP) Study convened a workshop in November 2020 to understand the future of modeling aerosols, clouds, convection and precipitation, and how satellite data can contribute to that future. ACCP is a project to define a satellite mission to be launched late in the 2020’s to advance cloud and aerosol science, following the recommendations of the latest NASA Decadal Survey. The ACCP modeling workshop goal was to answer the following questions: 1. What will be the critical science questions for clouds and aerosols in 10 years? 2. Where will simulations of clouds and aerosols across scales of space (process models to global) and time (nowcasting to climate prediction) be in 10 years? 3. What data will be available from space? What data would provide the most benefit? 4. What are the state of the art methods for confronting models with cloud and aerosol observations, including assimilation and climatological analysis techniques? The virtual workshop was anchored by a series of pre-recorded talks. Two days of synchronous sessions focused on discussion of the talks, along with small group breakout exercises. After an introduction to the ACCP concept came a panel discussing the future of modeling clouds and aerosols across scales. Participants were then asked to contribute their ideas. On the second day, there were two panel discussions. First came a discussion of the future of satellite observing systems. Second was a discussion of model-data synthesis methods. Finally, participants were asked to develop their own model-data synthesis proposal. The meeting began with an overview of the ACCP mission concept by Graeme Stephens (NASA-JPL). ACCP is a satellite mission for clouds and aerosols, likely anchored by advanced active lidar and radar systems in space, designed to observe detailed aerosol profile and type information, as well as cloud microphysics and dynamics. ACCP will integrate across sensors and observational types to get multi-spectral views of the same scenes, with better resolution than is available today. Launch is scheduled for 2027 or 2029. ACCP is being thought of as a comprehensive mission that may comprise more than one platform and more than one orbit plane (i.e., inclined and polar), with multiple combinations of sensors.

Future Models↗
NASA NTRSDate not supplied

High Latitude Atmospheric Rivers: Teleconnections and Impacts

Atmospheric rivers (ARs) are long, narrow synoptic scale features that act as moisture transport vehicles by moving water vapor poleward. They are typically found in storm tracks and often have profound implications for regional hydroclimate. For high latitude locales such as Antarctica and the Arctic, ARs are fewer in number but often have an outsized impact by either producing significant snow accumulation events, or, depending on their thermal characteristics, initiating melt events on ice sheets, ice shelves, and sea ice. In this study, we apply both reanalysis and climate model data to evaluate high latitude ARs for both the Arctic and Antarctic in the context of teleconnections and modes of variability. Specifically, we fold in both MERRA-2 and ERA5 reanalysis as well as historical and climate change simulations from the CESM2 (Community Earth System Model, Version 2) and E3SMv2 (Energy Exascale Earth System Model, v2) with multiple ensemble members to better understand natural variability versus climate change signals. An overview of AR climatology and impacts will be presented, including a baseline uncertainty quantification analysis using data from ARTMIP (the Atmospheric River Tracking Method Intercomparison Project). AR impacts during specific modes of variability will be characterized by diagnosing precipitation and boundary layer temperature associated with Ars influencing the cryosphere. Modes of variability investigated include the SAM (Southern Annular Mode), PDO (Pacific Decadal Oscillation), PSA2 (Pacific South American Mode 2), the IOD (Indian Ocean Dipole), and the AO (Arctic Oscillation).

Atmospheric Rivers↗
NASA NTRS2022

NASA's Earth System Observatory— Atmosphere Observing System

NASA has begun pre-formulation studies for the Earth System Observatory, a constellation of observatories designed to implement the recommendations of the 2017 NASA Earth Science Decadal Survey. For the atmosphere, the Atmosphere Observing System (AOS) will focus on aerosols, clouds, convection, and precipitation, their mutual interactions, and interactions with atmospheric radiation. AOS consists of two projects, one in an inclined orbit to measure sub-daily variability across all times of day, particularly for deep convection and its attendant high clouds, and one in a polar orbit to provide globally distributed observations with more advanced capabilities, coupling to radiation, and an eye toward continuity of key cloud and aerosol data records. This paper describes the AOS science objectives, the architectures of the two projects, planned sub-orbital activities, and relevant applications.

Scott A Braun↗
DOE OSTI2021

Topical Report – Findings on Subtask 2.7 – Wet ESP and Aerosol Testing at Coal Creek Station

Growing concerns over the impact of CO 2 emissions from combustion sources on global climate change have prompted numerous research and development projects aimed at developing cost-effective technologies for CO 2 capture. One family of technologies being demonstrated at pilot and full scale globally is postcombustion carbon capture (PCCC) systems that employ amine-based solvents. The captured CO 2 can be compressed and permanently stored underground or used for enhanced oil recovery. The proximity of North Dakota’s lignite-fired fleet of power plants to potential CO 2 storage options creates a unique atmosphere for PCCC within the state. However, the unique components present in lignite flue gas present a challenge for large-scale PCCC at North Dakota power plants by contributing to aerosol formation. Aerosols can negatively impact the long-term performance of amine-based solvents for CO 2 capture. Amine-based solvents are volatile, and flue gas particulate provides nucleation sites where amine vapors can condense as aerosols. Because aerosols cannot be easily captured at the column outlet using conventional technologies, the amine-laden aerosols escape the system and lead to accelerated solvent losses. Moreover, particulate components can chemically react with amines to form degradation products that can permanently deactivate the amine, cause fouling, and lead to hazardous emissions. Many of the elements that have been shown to catalyze solvent degradation are present in lignite coals and can exacerbate solvent replacement economics. Understanding this issue is critical to the implementation of solvent-based CO 2 capture systems as applied to lignite-fired generation systems. The Energy & Environmental Research Center (EERC) designed and carried out this project to fully characterize aerosol behavior with various control technologies installed to better optimize aerosol mitigation technology for CO 2 capture. To meet the goal of this project, the following objectives were identified: Determine the effectiveness of a wet electrostatic precipitator (WESP) on mitigating formation of problematic aerosols at Great River Energy’s Coal Creek Station, upstream of the PCCC system. Determine the effectiveness of the Mitsubishi Heavy Industries (MHI) proprietary amine emission reduction unit (AERU) as a postcapture solvent recovery system for reducing aerosol emissions and extending solvent life downstream of the PCCC system. Determine the impact of aerosols on the efficiency and degradation products of both commercial and advanced solvents within the PCCC system. Work was conducted at Coal Creek Station Unit 1 using a slipstream of flue gas from the outlet of the plant’s flue gas desulfurization (FGD) unit. Flue gas was routed through a pilot-scale FGD unit to remove SO 2 to very low levels (~1 ppm) and then through a direct contact cooler (DCC) to further cool the gas and to remove moisture. The gas exiting the DCC was then optionally routed through a WESP before passing to the CO 2 absorber columns. The MHI solvent was used to scrub CO 2 from the slipstream through a set of two absorber columns. The rich solvent was regenerated in a stripper column by heating to drive off captured CO 2 . Flue gas exiting the absorber column was routed to MHI’s proprietary AERU to recover entrained solvent. The system operated using a catch-and-release method where the CO 2 was separated to provide data on the process, but the captured CO 2 was released back into the host site stack. Particulate was measured, collected, and analyzed from multiple locations throughout the pilot-scale system. Unlike the performance observed in prior work, the inlet FGD and DCC did not remove significant particulate matter from the flue gas. This appears to be due to a difference in the nature of the particulate. The DCC seemed to increase particulate size and count, most likely owing to water condensing onto the surfaces of fly ash particles. When the WESP was operated, it achieved >95% particulate capture. Very little particulate matter or indications of solvent were detected at the AERU outlet. When operating with advanced KS 21 solvent, the particulate material at the AERU outlet was even further decreased. Solvent analysis showed that some species derived from flue gas and ash were slowly concentrating in the solvent over the duration of the test. The levels observed were reported to be within expected ranges and were not of concern to MHI. A high-level techno-economic assessment of installing CO 2 capture at Coal Creek Station suggested that, when using a standard monoethanolamine (MEA)-based solution with simple heat integration, the energy penalty to net generation would be 34%. The bulk of this was due to steam losses for regenerating solvent, followed by parasitic electrical demand for CO 2 compression and then by increased parasitic load for pushing flue gas through the absorber column. These demands could be decreased with a more advanced solvent that exhibits lower heat of regeneration and lower pressure drop than does a simple MEA solution. Further energy could be saved with more thorough heat integration to recover useful energy from the steam used for solvent regeneration. Installing a WESP was predicted to increase the cost of electricity by nearly $5/MWh. This would become cost-effective if solvent losses were roughly 10 times the baseline estimate when not using a WESP but could be returned to baseline by installing the WESP. Piping CO 2 for storage in more favorable geology could help with carbon capture and storage economics. Although storing off-site would necessitate construction of a CO 2 transport pipeline, the cost of this pipeline might be more than offset by reducing the number of wells required, the depths of the wells required, and the electrical demand for the CO 2 compressor. Additional factors that favor off-site storage costs include smaller expected CO 2 plume sizes, which translates to less monitoring and fewer landowner agreements. More detailed assessment of the specific geology in the region under and around Coal Creek Station would be needed to accurately assess the costs and benefits of different storage site options. This subtask was cofunded through the Energy & Environmental Research Center–U.S. Department of Energy Joint Program on Research and Development for Fossil Energy-Related Resources Cooperative Agreement No. DE-FE0024233. Nonfederal funding was provided by the North Dakota Industrial Commission.

Strege, Joshua↗