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At least 883 records · Page 49

Designing the Protocols for Programmable Ammonia Catalysis

Programmable catalysis can provide a more energy-efficient and cost-effective route to enhancing commercial ammonia production, a key process in the advancement of renewable energy technologies and the manufacture of fertilizers and basic chemicals. This work explores the computational discovery of optimal forcing protocols to drive such dynamic catalysis models. By employing matrix-free time-stepper methods, coupled with an optimization approach, that integrates Bayesian optimization with a Bayesian continuation strategy to efficiently discover the periodic steady states of such periodically forced systems, we enable the discovery of complex optimal catalyst strain waveforms, while ensuring robust solver convergence. We demonstrate the flexibility of our approach to discover optimized forcing protocols under varying physical constraints on strain modulation or other catalyst operating parameters. We show that these can have a temporal structure more complex than simple step functions. In order to detect undesirable catalytic loops that may correlate with overall reduced performance, we perform a study using graph-theoretical analysis to investigate the dynamics of catalytic kinetic networks formed.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Development of Data-Driven Models for Performance Prediction and Chemical Dosing of a Full-Scale Controlled Phosphorus Precipitation Reactor

This study evaluated the use of data-driven models to improve control of a struvite precipitation reactor that removes phosphorus from wastewater while producing a fertilizer product. The researchers developed predictive models for influent orthophosphate concentration, effluent orthophosphate concentration, and phosphorus removal using operational data from a full-scale MagPrex™ reactor at a water resource recovery facility in Denver, Colorado. Model predictions were used to recommend magnesium chloride dosing adjustments needed to achieve a target effluent phosphorus concentration. Several machine learning approaches were tested, with ridge regression providing the best predictions for influent orthophosphate concentration and phosphorus removal, and XGBoost providing the best predictions for effluent orthophosphate concentration. Simulation results indicated that the decision-support approach could correctly identify dosing adjustments in most cases and reduce chemical use. Full-scale implementation achieved lower accuracy due to changing operating conditions and limited historical data in some operating ranges. Here, the results demonstrate the potential of data-driven tools to support phosphorus recovery process control while also identifying practical limitations that affect deployment in full-scale systems.

42 ENGINEERING↗

Membrane Contactors for Ammonia Recovery from Anaerobic Digester Centrate: Pretreatment and Process Optimization

Haber-Bosch process allows for the production of modern fertilizers and is crucial for meeting increasing demands for agricultural production. The process requires large amounts of natural gas and contributes to global warming. An alternative to the Haber-Bosch process utilizes membrane contactors to recover nitrogen from the anaerobic digester centrate. In previous studies, high recoveries have been achieved, but membrane fouling decreased the performance and required maintenance to clean the membranes. Furthermore, this study investigated the effect of a settling and ultrafiltration system to pretreat centrate from an anaerobic digester to prevent fouling of the membrane contactor system. The system achieved high recoveries of over 90% for 10 cycles without any performance decline. Tests with increasing distillate concentrations of ammonium sulfate up to 165,000 mg/L-N could not identify a significant decline in membrane performance either. This allows for concentration up to crystallization in a single stage.

09 BIOMASS FUELS↗

Direct Observation and Analysis of Low-Energy Magnons with Raman Spectroscopy in Atomically Thin NiPS 3

van der Waals (vdW) magnets have rapidly emerged as a fertile playground for fundamental physics and exciting applications. Despite the impressive developments over the past few years, technical limitations pose a severe challenge to many other potential breakthroughs. High on the list is the lack of suitable experimental tools for studying spin dynamics on atomically thin samples. Here, Raman scattering techniques are employed to directly observe the low-lying magnon (~1 meV) even in bilayer NiPS 3 . Further, the advantage is that it offers excellent energy resolutions far better on low-energy sides than most inelastic neutron spectrometers can offer. More importantly, with appropriate theoretical analysis, the polarization dependence of the Raman scattering by those low-lying magnons also provides otherwise hidden information on the dominant spin-exchange scattering paths for different magnons. By comparing with high-resolution inelastic neutron scattering data, these low-energy Raman modes are confirmed to be indeed of magnon origin. Because of the different scattering mechanisms involved in inelastic neutron and Raman scattering, this information is fundamental in pinning down the final spin Hamiltonian. This work demonstrates the capability of Raman spectroscopy to probe the genuine two-dimensional spin dynamics in atomically thin vdW magnets, which can provide insights that are obscured in bulk spin dynamics.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Printed Potentiometric Ammonium Sensors for Agriculture Applications

Ammonium (NH 4 + ) concentration is critical to both nutrient availability and nitrogen (N) loss in soil ecosystems but can be highly variable across spatial and temporal scales. For this reason, effectively informing agricultural practices such as fertilizer management and understanding of mechanisms of soil N loss require sensor technologies to monitor ammonium concentrations in real time. Our work investigates the performance of fully printed ammonium ion-selective sensors used in diverse soil environments. Ammonium sensors consisting of a printed ammonium ion-selective electrode and a printed Ag/AgCl reference were fabricated and characterized in aqueous solutions and three different soil types (sand, peat, and clay) under the range of ion concentrations likely to be present in soil (0.01–100 mM). The response of ammonium sensors was further evaluated under variable gravimetric moisture content in the soil to reflect their reliability under field conditions. Ammonium sensors demonstrated a sensitivity of 53.6 ± 5.1 mV/decade when tested in aqueous solution, and a sensitivity of 55.7 ± 11 mV/dec, 57.5 ± 4.1 mV/dec, and 43.7 ± 4 mV/dec was measured in sand, clay, and peat soils, respectively.

60 APPLIED LIFE SCIENCES↗

Supply Cost and Life-Cycle Greenhouse Gas Footprint of Dry and Ensiled Biomass Sorghum for Biofuel Production

Here we discuss Biomass sorghum as a promising feedstock for cellulosic biorefineries because of its high yield and drought tolerance. However, the difficulty of effectively drying sorghum in some regions means that it may require different handling than previously studied grassy feedstocks. This study compares the delivered cost and life-cycle greenhouse gas (GHG) footprint of field drying and baling, module storage (wrapped, densely packed biomass), pelletizing, and ensiling. Ensiling has not been widely considered for use in bioenergy production. For farms within 66 km of the biorefinery, ensiled biomass is of the lowest cost and GHG strategy despite additional cost and energy demand for hauling wet biomass. Field drying and baling, if feasible, is the most cost-effective option for sorghum between 66 km and 104 km, beyond which pellets are preferable. A 2000 bone-dry-metric ton (bdt)/day biorefinery can source sorghum with 18 bdt/ha yield cultivated on 5% of surrounding land at costs ranging from $\$$122 (silage) to $\$$167 (pellets)/bdt and a life-cycle GHG footprint of 111 (silage) to 179 kg CO2e/bdt (pellets). With 28 bdt/ha biomass yield, 10% cultivation of surrounding land, and low fertilizer application, costs can range from $\$$66 (silage) to $\$$85 (pellets)/ bdt and GHG footprint of 43 (silage) to 96 kg CO2e (pellets)/bdt.

09 BIOMASS FUELS↗

A Pathway Analysis Framework for Evaluating the Economic and Environmental Viability of Biomass-Based Plastic Production

Plastic production from fossil feedstocks (e.g., naphtha, coal, and natural gas) is not sustainable and causes known environmental impacts such as global warming. A possible solution is to shift production pathways to use biomass, which is a sustainable feedstock that can sequester atmospheric carbon dioxide. This study presents an optimization-based pathway analysis framework for evaluating the carbon footprints of the production of mainstream plastics from biomass and fossil feedstocks. We use the modeling framework to quickly navigate complex interdependencies that exist between the production pathways of different plastics and to determine pathways of minimum production cost under a range of carbon pricing scenarios. The framework interprets carbon prices as an exogenous taxation scheme or an endogenous negative value perceived by producers. The proposed approach reveals the biomass feedstock quantities needed to displace fossil counterparts and the plastics and technologies that should be prioritized. The framework can also be used for evaluating system-wide trade-offs between production costs and carbon footprints that arise from pathway interdependencies. We also evaluate hidden environmental impacts associated with the large-scale use of biomass as a feedstock, such as land use and water eutrophication that results from a significant increase in fertilizer use. Therefore, it is important to highlight that there are trade-offs between decarbonization and other environmental issues. Here, the proposed framework provides an integrative platform for basic techno-economic and life-cycle data that can be used for analyzing diverse scenarios and determining necessary technology targets (e.g., yields, footprints, and costs) to achieve required levels of decarbonization.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Converting Wind Energy to Ammonia at Lower Pressure

Renewable wind energy can be used to make ammonia. However, wind-generated ammonia costs about twice that made from a traditional fossil-fuel driven process. To reduce the production cost, we replace the conventional ammonia condensation with a selective absorber containing metal halides, e.g., calcium chloride, operating at near synthesis temperatures. With this reaction-absorption process, ammonia can be synthesized at 20 bar from air, water, and wind-generated electricity, with rates comparable to the conventional process running at 150–300 bar. In our reaction-absorption process, the rate of ammonia synthesis is now controlled not by the chemical reaction but largely by the pump used to recycle the unreacted gases. The results suggest an alternative route to distributed ammonia manufacture which can locally supply nitrogen fertilizer and also a method to capture stranded wind energy as a carbon-neutral liquid fuel.

10 SYNTHETIC FUELS↗

Electrolyte Engineering for Efficient Electrochemical Nitrate Reduction to Ammonia on a Titanium Electrode

Nitrates from agricultural runoff and industrial waste streams are a notorious waste product and hazardous pollutant. Traditional electrochemical water remediation approaches aim to solve this problem by converting nitrates to environmentally benign N 2 while minimizing the production of environmentally hazardous side products such as ammonia and nitrous oxide in a process known as “denitrification”. We modify this concept and outline an opportunity to optimize the conversion of nitrates into ammonia, which is also a key commodity product used as a fertilizer, potential fuel, and chemical precursor. The electrochemical conversion of nitrates to ammonia recycles the fixed nitrogen and offers an appealing and supplementary alternative to the energy- and resource-intensive Haber-Bosch process. In this study, we investigated the effect of varying electrochemical conditions (pH, nitrate concentration, and applied potential) on the selective reduction of nitrate to ammonia at a titanium cathode. We observed that high concentrations of both protons and nitrate ions are needed to achieve high selectivity, reaching a peak of 82% Faradaic efficiency to ammonia at an applied potential of -1 V versus RHE and a partial current density to NH 3 of -22 mA/cm 2 , using 0.4 M [NO 3 – ] at pH ~0.77. The Ti electrode, as a poor hydrogen evolution catalyst with notable corrosion resistance, provides a large window of operating conditions to achieve high selectivity in the reduction of nitrate anions. Stability of the system was evaluated, and we found a high Faradaic efficiency throughout the course of an 8 h experiment. After electrochemical testing, titanium hydride was observed at the cathode surface. We also show a preliminary technoeconomic study, indicating that it may be feasible to employ an electrochemical strategy for the production of ammonium nitrate.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Ammonia Electrosynthesis from Nitrate Using a Ruthenium–Copper Cocatalyst System: A Full Concentration Range Study

Electrochemical synthesis of ammonia via the nitrate reduction reaction (NO3RR) has been intensively researched as an alternative to the traditional Haber–Bosch process. Most research focuses on the low concentration range representative of the nitrate level in wastewater, leaving the high concentration range, which exists in nuclear and fertilizer wastes, unexplored. The use of a concentrated electrolyte (≥1 M) for higher rate production is hampered by poor hydrogen transfer kinetics. Herein, we demonstrate that a cocatalytic system of Ru/Cu 2 O catalyst enables NO3RR at 10.0 A in 1 M nitrate electrolyte in a 16 cm 2 flow electrolyzer, with 100% faradaic efficiency toward ammonia. Detailed mechanistic studies by deuterium labeling and operando Fourier transform infrared (FTIR) spectroscopy allow us to probe the hydrogen transfer rate and intermediate species on Ru/Cu 2 O. Ab initio molecular dynamics (AIMD) simulations reveal that adsorbed hydroxide on Ru nanoparticles increases the density of the hydrogen-bonded water network near the Cu 2 O surface, which promotes the hydrogen transfer rate. Finally, our work highlights the importance of engineering synergistic interactions in cocatalysts for addressing the kinetic bottleneck in electrosynthesis.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Pyrochlore NaYbO2: A Potential Quantum Spin Liquid Candidate

The search for quantum spin liquids (QSL) and chemical doping in such materials to explore superconductivity have continuously attracted intense interest. Here, we report the discovery of a potential QSL candidate, pyrochlore-lattice β-NaYbO2. Colorless and transparent NaYbO2 single crystals, layered α-NaYbO2 (∼250 μm on edge) and octahedral β-NaYbO2 (∼50 μm on edge), were grown for the first time. Synchrotron X-ray single-crystal diffraction unambiguously determined that the newfound β-NaYbO2 belongs to the three-dimensional pyrochlore structure characterized by the R3̅m space group, corroborated by synchrotron X-ray and neutron powder diffraction and pair distribution function. Magnetic measurements revealed no long-range magnetic order or spin glass behavior down to 0.4 K with a low boundary spin frustration factor of 17.5, suggesting a potential QSL ground state. Under high magnetic fields, the potential QSL state was broken and spins order. Our findings reveal that NaYbO2 is a fertile playground for studying novel quantum states.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Systematic Tuning and Multifunctionalization of Covalent Organic Polymers for Enhanced Carbon Capture

Porous covalent polymers are attracting increasing interest in the fields of gas adsorption, gas separation, and catalysis due to their fertile synthetic polymer chemistry, large internal surface areas, and ultrahigh hydrothermal stabilities. While precisely manipulating the porosities of porous organic materials for targeted applications remains challenging, we show how a large degree of diversity can be achieved in covalent organic polymers by incorporating multiple functionalities into a single framework, as is done for crystalline porous materials. In this work, we synthesized 17 novel porous covalent organic polymers (COPs) with finely tuned porosities, a wide range of Brunauer–Emmett–Teller (BET) specific surface areas of 430–3624 m 2 g –1 , and a broad range of pore volumes of 0.24–3.50 cm 3 g –1 , all achieved by tailoring the length and geometry of building blocks. Furthermore, we are the first to successfully incorporate more than three distinct functional groups into one phase for porous organic materials, which has been previously demonstrated in crystalline metal–organic frameworks (MOFs). COPs decorated with multiple functional groups in one phase can lead to enhanced properties that are not simply linear combinations of the pure component properties. For instance, in the dibromobenzene-lined frameworks, the bi- and multifunctionalized COPs exhibit selectivities for carbon dioxide over nitrogen twice as large as any of the singly functionalized COPs. These multifunctionalized frameworks also exhibit a lower parasitic energy cost for carbon capture at typical flue gas conditions than any of the singly functionalized frameworks. Despite the significant improvement, these frameworks do not yet outperform the current state-of-art technology for carbon capture. Nonetheless, the tuning strategy presented here opens up avenues for the design of novel catalysts, the synthesis of functional sensors from these materials, and the improvement in the performance of existing covalent organic polymers by multifunctionalization.

mathematical methods↗

Reaction Mechanism and Kinetics for Ammonia Synthesis on the Fe(111) Surface

Here, the Haber-Bosch industrial process for synthesis of ammonia (NH 3 ) from hydrogen and nitrogen produces the millions of tons of ammonia gas annually needed to produce nitrates for fertilizers required to feed the earth’s growing populations. This process has been optimized extensively, but it still uses enormous amounts of energy (2% of the world’s supply), making it essential to dramatically improve its efficiency. To provide guidelines to accelerate this improvement, we used quantum mechanics to predict reaction mechanisms and kinetics for NH 3 synthesis on Fe(111)—the best Fe single crystal surface for NH 3 synthesis. We predicted the free energies of all reaction barriers for all steps in the mechanism and built these results into a kinetic Monte Carlo model for predicting steady state catalytic rates to compare with single-crystal experiments at 673 K and 20 atm. We find excellent agreement with a predicted turnover frequency (TOF) of 17.7 s –1 per 2 × 2 site (5.3 × 10 –9 mol/cm2/sec) compared to TOF = 10 s –1 per site from experiment.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Mechanistic Insights into Electrochemical Nitrogen Reduction Reaction on Vanadium Nitride Nanoparticles

Renewable production of ammonia, a building block for most fertilizers, via the electrochemical nitrogen reduction reaction (ENRR) is desirable; however, a selective electrocatalyst is lacking. Here we show that vanadium nitride (VN) nanoparticles are active, selective, and stable ENRR catalysts with an ENRR rate and a Faradaic efficiency (FE) of 3.3 × 10 –10 mol s –1 cm –2 and 6.0% at -0.1 V within 1 h, respectively. ENRR with 15 N 2 as the feed produces both 14 NH 3 and 15 NH 3 , which indicates that the reaction follows a Mars–van Krevelen mechanism. Ex situ X-ray photoelectron spectroscopy characterization of fresh and spent catalysts reveals that multiple vanadium oxide, oxynitride, and nitride species are present on the surface and identified VN0.7O0.45 as the active phase in the ENRR. Operando X-ray absorption spectroscopy and catalyst durability test results corroborate this hypothesis and indicate that the conversion of VN 0.7 O0.45 to the VN phase leads to catalyst deactivation. We hypothesize that only the surface N sites adjacent to a surface O are active in the ENRR. Finally, an ammonia production rate of 1.1 × 10 –10 mol s –1 cm –2 can be maintained for 116 h, with a steady-state turnover number of 431.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Changes in Wood Biomass and Crop Yields in Response to Projected CO 2 , O 3 , Nitrogen Deposition, and Climate

As the world's population increases, so will the demand for food and timber resources. Though carbon dioxide (CO 2 ) fertilization and, to a lesser extent, nitrogen (N) deposition are expected to increase future resource production, changes in ozone (O 3 ) and climate have the potential to decrease production due to increased phytotoxic damage, drought, and heat stress. To determine how crop and timber production may change in the future, we use the Community Land Model version 4.5 with prognostic crops to simulate responses of wood biomass and crop yields to CO 2 , O 3 , N deposition, and climate under Representative Concentration Pathway 8.5 forcings. Generally, rising CO 2 increases wood biomass and crop yields, while projected climate change causes decreases. Small projected changes in O 3 and N deposition do not strongly affect yields, though additional research is needed on future O 3 and N deposition trends and impacts. By the end of the 21st century, global wood biomass increases by ~16% due to the dominating impact of CO 2 . The positive effect of CO 2 on future crop yields is muted by the negative impacts of climate, with a ~5% net global increase. Future projections suggest that rice and wheat yields typically increase under the combination of future forcings, whereas soy and corn yields are regionally variable. While short-term resource management strategies can benefit from planting heat-tolerant species and cultivars, technological advances and intensification, among other management strategies not included here, must be employed to meet the future demand for these resources.

54 ENVIRONMENTAL SCIENCES↗

The Community Land Model Version 5: Description of New Features, Benchmarking, and Impact of Forcing Uncertainty

The Community Land Model (CLM) is the land component of the Community Earth System Model (CESM) and is used in several global and regional modeling systems. In this paper, we introduce model developments included in CLM version 5 (CLM5), which is the default land component for CESM2. We assess an ensemble of simulations, including prescribed and prognostic vegetation state, multiple forcing data sets, and CLM4, CLM4.5, and CLM5, against a range of metrics including from the International Land Model Benchmarking (ILAMBv2) package. CLM5 includes new and updated processes and parameterizations: (1) dynamic land units, (2) updated parameterizations and structure for hydrology and snow (spatially explicit soil depth, dry surface layer, revised groundwater scheme, revised canopy interception and canopy snow processes, updated fresh snow density, simple firn model, and Model for Scale Adaptive River Transport), (3) plant hydraulics and hydraulic redistribution, (4) revised nitrogen cycling (flexible leaf stoichiometry, leaf N optimization for photosynthesis, and carbon costs for plant nitrogen uptake), (5) global crop model with six crop types and time-evolving irrigated areas and fertilization rates, (6) updated urban building energy, (7) carbon isotopes, and (8) updated stomatal physiology. New optional features include demographically structured dynamic vegetation model (Functionally Assembled Terrestrial Ecosystem Simulator), ozone damage to plants, and fire trace gas emissions coupling to the atmosphere. Conclusive establishment of improvement or degradation of individual variables or metrics is challenged by forcing uncertainty, parametric uncertainty, and model structural complexity, but the multivariate metrics presented here suggest a general broad improvement from CLM4 to CLM5.

58 GEOSCIENCES↗

Modeling the Sources and Transport Processes During Extreme Ammonia Episodes in the U.S. Corn Belt

Abstract Atmospheric ammonia (NH 3 ) is the primary form of reactive nitrogen (N r ) and a precursor of ammonium (NH 4 + ) aerosols. Ammonia has been linked to adverse impacts on human health, the loss of ecosystem biodiversity, and plays a key role in aerosol radiative forcing. The midwestern United States is the major NH 3 source in North America because of dense livestock operations and the high use of synthetic nitrogen fertilizers. Here, we combine tall‐tower (100 m) observations in Minnesota and Weather Research and Forecasting model coupled with Chemistry (WRF‐Chem) modeling to investigate high and low NH 3 emission episodes within the U.S. Corn Belt to improve our understanding of the distribution of emission sources and transport processes. We examined observations and performed model simulations for cases in February through November of 2017 and 2018. The results showed the following: (1) Peak emissions in November 2017 were enhanced by above‐normal air temperatures, implying a Q 10 (i.e., the change in NH 3 emissions for a temperature increase of 10°C) of 2.5 for emissions. (2) The intensive livestock emissions rom northern Iowa, approximately 400 km away from the tall tower, accounted for 17.6% of the abundance in tall‐tower NH 3 mixing ratios. (3) Ammonia mixing ratios in the innermost domain 3 frequently (i.e., 336 hr, 48% of November 2017) exceeded 5.3 ppb, an important air quality health standard. (4) In November 2017, simulated NH 3 net ecosystem exchange (the difference between NH 3 emissions and dry deposition) accounted for 60–65% of gross NH 3 emissions for agricultural areas and was 2.8–3.1 times the emissions of forested areas. (5) We estimated a mean annual NH 3 net ecosystem exchange of 1.60 ± 0.06 nmol · m −2 · s −1 for agricultural lands and −0.07 ± 0.02 nmol · m −2 · s −1 for forested lands. These results imply that future warmer fall temperatures will enhance agricultural NH 3 emissions, increase the frequency of dangerous NH 3 episodes, and enhance dry NH 3 deposition in adjacent forested lands.

Hu, Cheng↗

Assessing Impacts of Plant Stoichiometric Traits on Terrestrial Ecosystem Carbon Accumulation Using the E3SM Land Model

Carbon (C) enters into the terrestrial ecosystems via photosynthesis and cycles through the system together with other essential nutrients (i.e., nitrogen [N] and phosphorus [P]). Such a strong coupling of C, N, and P leads to the theoretical prediction that limited nutrient availability will limit photosynthesis rate, plant growth, and future terrestrial C dynamics. However, the lack of reliable information about plant tissue stoichiometric constraints remains a challenge for quantifying nutrient limitations on projected global C cycling. In this study, we harmonized observed plant tissue C:N:P stoichiometry from more than 6,000 plant species with the commonly used plant functional type framework in global land models. Using observed C:N:P stoichiometry and the flexibility of these ratios as emergent plant traits, we show that observationally constrained fixed plant stoichiometry does not improve model estimates of present-day C dynamics compared with unconstrained stoichiometry. However, adopting stoichiometric flexibility significantly improves model predictions of C fluxes and stocks. The 21st century simulations with RCP8.5 CO 2 concentrations show that stoichiometric flexibility, rather than baseline stoichiometric ratios, is the dominant controller of plant productivity and ecosystem C accumulation in modeled responses to CO 2 fertilization. The enhanced nutrient limitations and plant P use efficiency mainly explain this result. This study is consistent with the previous consensus that nutrient availability will limit xfuture land carbon sequestration but challenges the idea that imbalances between C and nutrient supplies and fixed stoichiometry limit future land C sinks. We show here that it is necessary to represent nutrient stoichiometric flexibility in models to accurately project future terrestrial ecosystem carbon sequestration.

54 ENVIRONMENTAL SCIENCES↗