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All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

The Diurnal Dynamics of Gross Primary Productivity Using Observations From the Advanced Baseline Imager on the Geostationary Operational Environmental Satellite‐R Series at an Oak Savanna Ecosystem

Gross primary productivity (GPP) is the largest flux in the global carbon cycle and satellite-based GPP estimates have long been used to study the trends and interannual variability of GPP. With recent updates to geostationary satellites, we can now explore the diurnal variability of GPP at a comparable spatial resolution to polar-orbiting satellites and at temporal frequencies comparable to eddy covariance (EC) tower sites. We used observations from the Advanced Baseline Imager on the Geostationary Operational Environmental Satellite-R series (GOES-R) to test the ability of subdaily satellite data to capture the shifts in the diurnal course of GPP at an oak savanna EC site in California, USA that is subject to seasonal soil moisture declines. We compared three methods to estimate GPP: (a) a light-use efficiency model, (b) a linear relationship between the product of near-infrared reflectance of vegetation and photosynthetically active radiation (LIN-NIR v P) and EC tower GPP, and (c) a light response curve (LRC-NIR v P) between NIR v P and EC GPP. The LRC-NIR v P achieved the lowest mean absolute error for winter (2 µmol CO 2 m –2 s –1 ), spring (2.51 µmol CO 2 m –2 s –1 ), summer (1.43 µmol CO 2 m –2 s –1 ), and fall (1.35 µmol CO 2 m –2 s –1 ). The ecosystem experienced the largest shift in daily peak GPP in relation to the peak of incoming solar radiation toward the morning hours during the dry summers. The LRC-NIRvP and the light-use efficiency model were in agreement with these patterns of a shift in peak daily GPP toward the morning hours during summer. Our results can help develop diurnal estimates of GPP from geostationary satellites that are sensitive to fluctuating environmental conditions during the day.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Alternating Conditional Expectations: Introducing a Non‐Parametric Statistical Method to Interpret Long‐Term Greenhouse Gas Flux Measurements Over Semi‐Arid and Wetland Ecosystems

Abstract We explore the potential of using a non‐parametric statistical method called Alternating Conditional Expectations, ACE, to quantify functional relationships in biogeosciences. Here, ACE is used to quantify the non‐linear and multi‐faceted responses of greenhouse gas fluxes to a set of biophysical forcings, when the shapes of those response surfaces are unknown. We evaluated the statistical method over two contrasting ecosystems and two contrasting time steps. One case involved quantifying the biophysical controls of water vapor and carbon dioxide (CO 2 ) fluxes over a semi‐arid oak savanna using daily integrated fluxes. The other case evaluated the responses of CO 2 and methane (CH 4 ) flux measurements to a set of biophysical forcings at a restored tidal wetland using thirty‐minute averages. The statistical model, based on 4 independent variables, explained up over 90% of the variation in daily integrated flux densities of water vapor and net carbon dioxide exchange at the savanna site. This fit was defined by distinct non‐linear responses to such drivers as gross primary production, photosynthetically active radiation, air temperature, vapor pressure deficit and soil moisture. At the tidal wetland site, we evaluated net carbon dioxide and methane fluxes with short‐term measurements to capture the influence of rising and falling tides and seasonality in biological activity. The statistical model defined the shape of the forcing of fluxes due to the roles of carbon exudates, water table depth, oxygen level in the water column, temperature and vegetation status. The statistical fits of the greenhouse gas fluxes were less precise than the savanna case. The fetch varies on a run‐to‐run basis as it is comprised of a heterogeneous mosaic of open water and vegetation. Furthermore, it is difficult to monitor the environmental conditions of the archaea and bacteria in the sediments that produce methane and carbon dioxide.

Environmental Sciences & Ecology↗
DOE OSTI2025

Environmental Factors Associated With Fall Phytoplankton Blooms in the Northern Bering and Chukchi Seas

This study investigates environmental drivers of fall phytoplankton blooms in the Arctic, focusing on the northern Bering and Chukchi seas. Random Forests models were used to analyze covariates of fall phytoplankton blooms from 2013 to 2018, incorporating shipboard, remote sensing, and modeled environmental properties. Four regional models and one comprehensive all-station model considered fall as well as midsummer conditions. Midsummer properties included suspended particulate matter, chlorophyll-a, and the proportion of degraded pheophytin to chlorophyll-a used as a proxy for bloom stage. Open water duration was one of the highest ranked factors in predicting fall blooms. Open water duration also influences the stage of midsummer (July) blooms as indicated by pheophytin proportions, which in turn were the highest-ranked factor for predicting fall bloom events in the Chirikov Basin (northern Bering Sea between St. Lawrence Island and the Bering Strait) and the Chukchi Sea. Wind direction, specifically easterly winds, was an important predictor in the northern Bering Sea. Maximum wind speed ranked highly at stations located within the nutrient-poor Alaska Coastal Current in the Chukchi Sea. However, stormy days, average and maximum wind speeds generally ranked low in importance as a predictor of fall bloom events. Other parameters, including photosynthetic active radiation, modeled nutrient concentrations, mixed layer depth, and time since sea ice breakup date showed strong but regionally varying relationships with fall blooms. Altogether, results from these Random Forests models suggest that high wind events and storms in the absence of sea ice provide an incomplete narrative for initiating fall bloom events.

Gaffey, C. B. [Clark University, Worcester, MA (Un↗
DOE OSTI2026

Rapid organic carbon spiraling in a headwater stream linked with streamflow, biogeochemistry, and canopy phenology

Headwater streams are abundant worldwide and important to global biogeochemical cycles, serving as critical processors and transporters of C. C spiraling is a useful way to understand the retention and mineralization of organic C (OC) in streams. However, analyses of seasonal and interannual variability in OC spiraling are currently limited. In this study, we aimed to understand the temporal patterns and driving mechanisms of OC spiraling, which will inform our understanding of future OC changes under climate change. We used 7 y of daily data in a small headwater stream (Walker Branch, Tennessee, USA) to assess seasonal and interannual variability in OC spiraling length (S OC ) and mineralization velocity (v fOC ), as well as their potential related variables. On average, S OC in Walker Branch was ~10× shorter than in previously studied small streams, indicating strong connections between the water column and the benthic environment where OC mineralization mostly takes place. OC spiraling was faster during the more biologically active periods of spring and autumn compared with more elongated OC spiraling in summer and winter, when OC retention was lower and downstream transport was higher. Gross primary production (GPP) was most strongly related to S OC and v fOC . Photosynthetically active radiation (PAR) and NO 3 − were also positively and negatively related to v fOC , respectively. Trends toward earlier and longer canopy cover and reduced GPP and PAR may result in longer S OC and slower v fOC , reducing localized instream processing of OC and potentially shunting more OC downstream. However, long-term observations indicate reduced NO 3 − at Walker Branch, suggesting opposing effects to those of GPP and PAR, leading to faster v fOC and greater OC retention. Time-series analyses of OC spiraling in streams can enhance our understanding of current and future responses of OC processing and downstream transport to climate change, as well as implications for downstream OC dynamics.

biological activity↗
DOE OSTI2020

Radiance-based NIR v as a proxy for GPP of corn and soybean

Substantial uncertainty exists in daily and sub-daily gross primary production (GPP) estimation, which dampens accurate monitoring of the global carbon cycle. Here we find that near-infrared radiance of vegetation (NIR v,Rad ), defined as the product of observed NIR radiance and normalized difference vegetation index (NDVI), can accurately estimate corn and soybean GPP at daily and half-hourly time scales, benchmarked with multi-year tower-based GPP at three sites with different environmental and irrigation conditions. Overall, NIR v,Rad explains 84% and 78% variations of half-hourly GPP for corn and soybean, respectively, outperforming NIR reflectance of vegetation (NIR v,Ref ), enhanced vegetation index (EVI), and far-red solar-induced fluorescence (SIF760). The strong linear relationship between NIR v,Rad and absorbed photosynthetically active radiation by green leaves (APAR green ), and that between APAR green and GPP, explain the good NIR v,Rad -GPP relationship. The NIR v,Rad -GPP relationship is robust and consistent across sites. The scalability and simplicity of NIR v,Rad indicate a great potential to estimate daily or sub-daily GPP from high-resolution and/or long-term satellite remote sensing data.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Impacts of abiotic and biotic factors on tundra productivity near Utqiaġvik, Alaska

Abstract Earlier snowmelt, warmer temperatures and herbivory are among the factors that influence high-latitude tundra productivity near the town of Utqiaġvik in northern Alaska. However, our understanding of the potential interactions between these factors is limited. MODIS observations provide cover fractions of vegetation, snow, standing water, and soil, and fractional absorption of photosynthetically active radiation by canopy chlorophyll (fAPAR chl ) per pixel. Here, we evaluated a recent time-period (2001–2014) that the tundra experienced large interannual variability in vegetation productivity metrics (i.e. fAPAR chl and APAR chl ), which was explainable by both abiotic and biotic factors. We found earlier snowmelt to increase soil and vegetation cover, and productivity in June, while warmer temperatures significantly increased monthly productivity. However, abiotic factors failed to explain stark decreases in productivity during August of 2008, which coincided with a severe lemming outbreak. MODIS observations found this tundra ecosystem to completely recover two years later, resulting in elevated productivity. This study highlights the potential roles of both climate and herbivory in modulating the interannual variability of remotely retrieved plant productivity metrics in Arctic coastal tundra ecosystems.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Tapping into the physiological responses to mistletoe infection during heat and drought stress

Mistletoes are important co-contributors to tree mortality globally, particularly during droughts. In Australia, mistletoe distributions are expanding in temperate woodlands, while their hosts have experienced unprecedented heat and drought stress in recent years. We investigated whether the excessive water use of mistletoes increased the probability of xylem emboli in a mature woodland during the recent record drought that was compounded by multiple heatwaves. Additionally, we continuously recorded transpiration ($T_{SLA}$) of infected and uninfected branches from two eucalypt species over two summers, monitored stem and leaf water potentials ($\Psi $) and used hydraulic vulnerability curves to estimate percent loss in conductivity (PLC) for each species. Variations in weather (vapor pressure deficit, photosynthetically active radiation, soil water content), host species and % mistletoe foliage explained 78% of hourly $T_{SLA}$. While mistletoe acted as an uncontrollable sink for water in the host even during typical summer days, daily $T_{SLA}$ increased up to 4-fold in infected branches on hot days, highlighting the previously overlooked importance of temperature stress in amplifying water loss in mistletoes. The increased water use of mistletoes resulted in significantly decreased host $\Psi _{\rm{leaf}}$ and $\Psi _{\rm{trunk}}$. It further translated to an estimated increase of up to 11% PLC for infected hosts, confirming greater hydraulic dysfunction of infected trees that place them at higher risk of hydraulic failure. However, uninfected branches of Eucalyptus fibrosa F.Muell. had much tighter controls on water loss than uninfected branches of Eucalyptus moluccana Roxb., which shifted the risk of hydraulic failure towards an increased risk of carbon starvation for E. fibrosa. The contrasting mechanistic responses to heat and drought stress between both co-occurring species demonstrates the complexity of host–parasite interactions and highlights the challenge in predicting species-specific responses to biotic agents in a warmer and drier climate.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Normalized Solar-Induced Fluorescence Responds Earlier Than Vegetation Indices to the 2019 North China Plain Drought

Recently, solar-induced chlorophyll fluorescence (SIF) from satellites has shown potential for evaluating vegetation status and stress responses. Fluorescence quantum yield ($Φ_F$) is essentially linked to vegetation stress. However, the complex physiological and structural responses of SIF and $Φ_F$ to drought need further study. This study normalized SIF as SIFn to account for angular variations and fluctuations in photosynthetically active radiation (PAR), aiming for more accurate drought monitoring. SIFn anomalies were compared to historical baselines (2019–2021 averages) of vegetation indices (VIs), raw SIF, and $Φ_F$ during a 2019 drought in the North China Plain (NCP). Here, the results show SIFn provides an effective method for drought monitoring, showing the earliest decline compared to raw SIF, VIs, and $Φ_F$. In the first two weeks of drought, SIFn decreased by 8.2%, 7.0%, 12.5%, and 8.2% across the four NCP subdivisions. SIFn outperformed other indicators, proving sensitive to early drought detection. SIFn was also examined for tracking drought alleviation by rainfall. The uncertainty under different viewing geometries was quantified. SIFn anomalies showed a strong correlation with rainfall anomalies (R: 0.45 ~ 0.52) and meteorological factors like PAR (R: 0.80 ~ 0.84) and relative humidity (R:0.52 ~ 0.54). The correlation of near-infrared reflectance (NIRv) and $Φ_F$ anomalies with SIF was weak during drought onset (R: 0.16 ~ 0.32) but strong at the end (R: 0.83 ~ 0.87). These suggest both canopy structure (mainly characterized by NIRv) and vegetation chlorophyll ($Φ_F$) are impacted by drought and influence SIF at different stages.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Environmental controls on the light use efficiency of terrestrial gross primary production

Abstract Gross primary production (GPP) by terrestrial ecosystems is a key quantity in the global carbon cycle. The instantaneous controls of leaf‐level photosynthesis are well established, but there is still no consensus on the mechanisms by which canopy‐level GPP depends on spatial and temporal variation in the environment. The standard model of photosynthesis provides a robust mechanistic representation for C 3 species; however, additional assumptions are required to “scale up” from leaf to canopy. As a consequence, competing models make inconsistent predictions about how GPP will respond to continuing environmental change. This problem is addressed here by means of an empirical analysis of the light use efficiency (LUE) of GPP inferred from eddy covariance carbon dioxide flux measurements, in situ measurements of photosynthetically active radiation (PAR), and remotely sensed estimates of the fraction of PAR (fAPAR) absorbed by the vegetation canopy. Focusing on LUE allows potential drivers of GPP to be separated from its overriding dependence on light. GPP data from over 100 sites, collated over 20 years and located in a range of biomes and climate zones, were extracted from the FLUXNET2015 database and combined with remotely sensed fAPAR data to estimate daily LUE. Daytime air temperature, vapor pressure deficit, diffuse fraction of solar radiation, and soil moisture were shown to be salient predictors of LUE in a generalized linear mixed‐effects model. The same model design was fitted to site‐based LUE estimates generated by 16 terrestrial ecosystem models. The published models showed wide variation in the shape, the strength, and even the sign of the environmental effects on modeled LUE. These findings highlight important model deficiencies and suggest a need to progress beyond simple “goodness of fit” comparisons of inferred and predicted carbon fluxes toward an approach focused on the functional responses of the underlying dependencies.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Environmental control on the distribution of metabolic strategies of benthic microbial mats in Lake Fryxell, Antarctica

Ecological theories posit that heterogeneity in environmental conditions greatly affects community structure and function. However, the degree to which ecological theory developed using plant- and animal-dominated systems applies to microbiomes is unclear. Investigating the metabolic strategies found in microbiomes are particularly informative for testing the universality of ecological theories because microorganisms have far wider metabolic capacity than plants and animals. We used metagenomic analyses to explore the relationships between the energy and physicochemical gradients in Lake Fryxell and the metabolic capacity of its benthic microbiome. Statistical analysis of the relative abundance of metabolic marker genes and gene family diversity shows that oxygenic photosynthesis, carbon fixation, and flavin-based electron bifurcation differentiate mats growing in different environmental conditions. The pattern of gene family diversity points to the likely importance of temporal environmental heterogeneity in addition to resource gradients. Overall, we found that the environmental heterogeneity of photosynthetically active radiation (PAR) and oxygen concentration ([O2]) in Lake Fryxell provide the framework by which metabolic diversity and composition of the community is structured, in accordance with its phylogenetic structure. The organization of the resulting microbial ecosystems are consistent with the maximum power principle and the species sorting model.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Leaf-scale carbon assimilation simulated by the multi-assumption architecture & testbed for process sensitivity analysis

Raw and processed output from the Multi-Assumption Architecture & Testbed (MAAT, https://github.com/walkeranthonyp/MAAT, tag: v1.2.1_walker2020; Walker et al., 2018). The dataset contains leaf-scale carbon assimilation data from three MAAT simulations and their post-processing and plotting scripts. Simulation 1, labelled "FvC_4proc_proc," is a four-process, process sensitivity analysis (Dai et al., 2017) of carbon assimilation based on the Farquhar et al. (1980) photosynthesis model, and its variant proposed by Collatz et al. (1991). Simulation 2, labelled "FvC_4proc_salt," is a 14 parameter sensitivity analysis (Saltelli et al., 2010) of carbon assimilation based on the Farquhar and Collatz photosynthesis models. Simulation 3, labelled "FvC," is a factorial combination of the alternative process representations and parameter values presented in those original papers across a factorial combination of incident photosynthetically active radiation (50-2000 µmol m-2 s-1, in increments of 50) and atmospheric CO2 concentration (50-1500 µmol m-2 s-1, in increments of 50). Additional scripts/functions for post-processing and plotting are part of the MAAT repository. These data were generated to evaluate and compare the Farquhar and Collatz models of leaf-scale photosynthesis across a range of CO2 and incident light conditions. Analysis of results can be found in Walker et al. (2020). This dataset is comprised of R scripts to process data and produce figures; .RDS files, a binary format specific to R and read with the 'readRDS' function, to store raw MAAT output; R and bash scripts (.bs) that help to run a MAAT simulation, .XML files that are output from MAAT describing a run, and .csv files which contain the calculated sensitivity indexes published in Walker et al. (2020).

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

SPRUCE Whole Ecosystem Warming (WEW) Environmental Data and Water Table Summaries, Marcell Experimental Forest, Minnesota, 2015-2024

This data set contains observations of photosynthetically active radiation (PAR), precipitation, soil temperature, soil volumetric water content, air temperature, relative humidity, and normalized water table depth that are summarized on a daily, weekly, monthly, and annual basis for each of the SPRUCE plots. Observations span 2015-2024. This dataset draws on several datasets (Hanson et al. 2016; Hanson et al. 2020; and Warren, unpublished data) and compiles these environmental observations into useful formats for data analysis. These environmental metrics can be used to understand the environmental conditions inside SPRUCE environmental chambers throughout the durations of the experiment and can be paired with other data for modeling and analysis. R code used to generate these files is provided as part of the data package. This dataset contains four data files in comma separate (.csv) format and a compressed folder (*.zip) containing three R (*.r) scripts. Additional metadata are provided: one data dictionary and a file-level metadata file in comma separate (.csv) format and a user guide in PDF (*.pdf) format. User note: Users must cite the original dataset/s along with this dataset when publishing any analyses using this dataset. Details on the dataset used to compile each variable are available in the header row of the files and in the user guide.

air temperature↗
DOE OSTI2026

Patch-level CO2 and CH4 fluxes and porewater concentrations in experimental wetlands, 5 and 10 PPT saltwater intrusion simulations, Louisiana 2023-2024

This dataset containes carbon dioxide (CO2) and methane (CH4) flux measurements collected from wetland vegetation patches dominated by Typha domingensis and Panicum hemitomon to assess greenhouse gas flux responses to experimental saltwater intrusion (SWI) pulses. Measurements were conducted before, during, and after simulated SWI events at target salinities of approximately 5 parts per thousand (ppt) with durations of 6, 10, and 17 days and 10 ppt with a duration of 48 days, alongside a control wetland (with no salinity added, flood manipulation only). These data were generated to evaluate how the magnitude and duration of SWI alter wetland carbon exchange and related biogeochemical and plant responses. This data package includes flux measurements from the wetland surface (i.e, soil/water surface and enclosed vegetation) and from the soil/water surface only; porewater and surface water concentrations of CO2 and CH4; salinity, pH, electrical conductivity collected in porewater (at 5, 10, and 20 cm soil depths) and in surface water; soil redox potential; leaf spectral indices, leaf vapor pressure deficit, stomatal conductance; water level, salinity, and photosynthetically active radiation; and aboveground biomass.

EARTH SCIENCE > AGRICULTURE > SOILS > SOIL RESPIRA↗
DOE OSTI2020

Leaf isoprene and monoterpene emission data-set across hyperdominant tree genera in the Amazon basin

This data package contains the analyzed data used to support the publication "Leaf isoprene and monoterpene emission distribution across hyperdominant tree genera in the Amazon basin," Phytochemistry, in-press. Data was collected from 162 trees across four sites in the Amazon. For all leaf samples studied for volatile isoprenoid emissions, branch cuttings were conducted in the upper canopy with sun exposed leaves with the assistance of a tree climber utilizing a pole pruner or directly accessed from flux towers. Large branches were removed from the upper canopy (up to 0.5-1.0 meter in length) and rapidly recut on the ground under water to maintain the transpiration stream. Net photosynthesis and isoprene and monoterpene emission rates were quantified from leaves during controlled changes in photosynthetically active radiation (PAR) using a commercial leaf photosynthesis system (LI-6400XT, LI-COR Inc., USA) interfaced with a gas chromatograph-mass spectrometer (GC-MS, 5975C series, Agilent Technologies, USA). For detailed methods and raw data, refer to the publication and related material cited in Dataset References.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Simulated tree recruitment at PA-BCI under four precipitation scenarios

Simulated recruitment rates are provided for four tropical tree plant functional types (PFTs) which vary in drought and shade tolerance, at Barro Colorado Island, Panama (PA-BCI). Recruitment rates are predicted using the Tree Recruitment Scheme (TRS; Hanbury-Brown et al., 2022) and model data output from the Ecosystem Demography model version 2 with hydrodynamics (ED2; Medvigy et al., 2009, Powell et al., 2018). Predictions of recruitment are provided under four precipitation scenarios: “BASE” = recycled 2008-2014 observed meteorology (Faybishenko & Paton, 2021), “SYN-ENSO” = two exceptionally strong El Niño events within 30 years (Powell et al., 2018), “WET” = 30% increase in precipitation compared to BASE, and DRY-DS = dry season (January–April) precipitation reduced by 75% compared to BASE. In addition to recruitment rates, this dataset provides TRS predictions of PFT-specific seed bank and seedling pool dynamics (tracked in units of carbon) and ED predictions of understory photosynthetically active radiation and soil matric potential at 6 cm soil depth.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Data Fusion to Enhance Quality Control and Analysis with Instruments at the Marine and Coastal Research Laboratory

Deploying environmental monitoring instruments in the marine environment can be challenging, facing challenges around device survivability, biofouling and corrosion, and consistent data collection. This project explores the use of data fusion – the process of integrating multiple data sources to produce more consistent, accurate, and useful information – to build a consistent long-term monitoring system at the Marine and Coastal Research Laboratory (MCRL) in Sequim, Washington. Unused instruments that had been acquired from past projects were inventoried and deployments planned on the MCRL pier and floating dock. A total of 8 instruments were deployed including a tide gauge, hydrophone, acoustic Doppler current profiler (ADCP), photosynthetically active radiation (PAR) sensors, meteorological station, and three water quality sensors. Deployments were planned to be well-protected around the pier structure and a maintenance schedule was created for cleaning and recalibration. An automated data pipeline was created to aggregate data on edge computers that push data to Amazon Web Services (AWS) cloud storage every 15 minutes, performing automated quality control and data transformations using the Time Series Data Analytical Toolkit (TSDAT). Continued efforts are underway to maintain this system into the future, take a data-driven approach to maintenance scheduling, improve the reliability of the system, and share the data with a variety of end-users.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

BTRIC Technical Support for Appalachia: FY 2023 Summary Report on Net Negative Carbon Building Demonstration with AgPod

This study investigates the effects of various concentrations of carbon dioxide (CO 2 ) on the photosynthesis and biomass accumulation of crops growing in an Agricultural Pod (AgPod). The initial test crop was kale. It has been found that increasing the CO 2 concentration in the AgPod promotes higher photosynthetic rates in kale plants up to 1300 ppm (highest CO 2 concentration). An interesting finding was that net photosynthetic rates of kale leaves remain unsaturated until unusually high levels of photosynthetically active radiation (PAR, > 1200 µmolm-2s-1) and CO 2 concentration (> 1100 ppm) are reached. Such high levels of saturating PAR and CO 2 concentration values rarely occur under natural conditions, suggesting a promising potential for carbon capture via enriched greenhouse crop production. This task is one part of an overall plan to incorporate an AgPod to utilize carbon captured from the atmosphere to achieve net negative carbon emissions in a small neighborhood or community.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

BTRIC Technical Support for Appalachia: FY 2024 Summary Report on Net Negative Carbon Building Demonstration with AgPod

This report investigates the effects of various concentrations of CO 2 on the photosynthesis and biomass accumulation of crops growing in an AgPod, using kale as the test crop. In the first year of the study, increasing the CO 2 concentration in the AgPod was found to promote higher photosynthetic rates in kale plants up to 1,300 ppm (the highest CO 2 concentration measured). An interesting finding was that net photosynthetic rates of kale leaves remain unsaturated until reaching unusually high levels of photosynthetically active radiation (PAR, > 1,200 µmol m -1 s -1 ) and CO 2 concentration (> 1,100 ppm). Such high levels of saturating PAR and CO 2 concentration values rarely occur under natural conditions, suggesting a promising potential for carbon capture via enriched controlled environment agriculture (ECEA). During the second year of the study, a second crop was planted to confirm the actual effects on growth with increased CO 2 concentrations. Our results suggest that growing kale plants in the AgPod system at higher CO 2 levels resulted in a successful and highly productive crop, up to three times the amount grown at 415 CO 2 . Further, the kale plants grown under higher CO 2 conditions (1000 ppm) are not CO 2 saturated and can potentially further improve yield at even higher CO 2 environments.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗