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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Incorporating Wind Turbine Choice in High-Resolution Geospatial Supply Curve and Capacity Expansion Models

To achieve national decarbonization goals, U.S. annual deployment of wind energy will need to increase by at least fivefold compared to the recent past. Modeling and analysis frameworks can help inform where and how wind energy deployment might occur and thereby help enable the achievement of decarbonization goals. However, most prior wind energy modeling and analysis studies rely on generalized representations of wind energy technologies. Since wind energy technology advancements are expected to increase the competitiveness of wind energy, it is important to incorporate more detailed representations of turbine technology into wind energy modeling. Here we present a new method that incorporates wind turbine choice into the technology representation of land-based wind energy in long-term planning models. Our method integrates three previously published modeling and analysis capabilities: 1) bottom-up cost modeling to estimate future technology costs, 2) geospatial modeling to represent siting decisions, and 3) power sector modeling to evaluate potential deployment. We refer to this approach as a "customized turbine choice" methodology because it creates a composite turbine scenario by choosing from multiple wind turbine technologies—using site-specific optimized turbine layout and selecting the least-cost technology at each location. We demonstrate the capabilities of this new modeling pipeline by examining how the selection of four different wind turbine configurations might evolve from 2021 through 2040. Our results show that using our customized turbine choice methodology could lead to higher estimates for wind future deployment, which indicates that more simplified modeling might underestimate the role that wind energy could play in meeting decarbonization goals. Future research is needed to further explore the implications of turbine choice and to better inform technology researchers, original equipment manufacturers, and other wind industry stakeholders about the market potential of different wind turbine technologies.

17 WIND ENERGY↗
DOE OSTI2021

City Decision Analysis Resources and Tools

The City Decision Analysis at Any Scale Workshop was held February 17-18, 2021. This brochure was created to provide participants with a collection of tools and resources that support planning and implementation of clean energy goals for communities and businesses.

ACES↗
DOE OSTI2023

NREL Planning Resources for States

This presentation summarizes some NREL resources and capabilities that states might want to access to help with decarbonization planning. It describes three types of resources: already-available, public datasets describing technology costs and future grid evolution; jurisdiction-specific integration studies that require directly partnering with NREL; and an envisioned new data product comprising state-specific standard scenarios that could be collaboratively funded by the states.

annual technology baseline↗
DOE OSTI2023

ResStock: Annual Baseline Results with Component Loads

The ResStock Analysis Tool was developed by NREL with support from the U.S. Department of Energy to provide a new approach to large-scale residential analysis by combining large public and private data sources, statistical sampling, detailed sub hourly building simulations, and high-performance computing. This combination achieves unprecedented granularity and accuracy in modeling the diversity of the housing stock and the distributional impacts of building technologies in different communities. The annual baseline energy results from a national-scale ResStock run use typical meteorological year 3 (TMY3) files for energy simulations. Results include heating and cooling loads for individual components of each building. Component loads describe the heating/cooling load that can be attributed to specific elements of a home, such as heat transfer through walls or internal gains. Additionally, these results include the standard ResStock outputs for housing characteristics and numerous energy outputs by end-use and fuel. A snapshot of the ResStock version used to produce this data, including a configuration file for the run can be found using the Source Code resource link.

Array↗
DOE OSTI2026

ComStock Measure Documentation: High-Efficiency Rooftop Unit

Building on the 3-year End-Use Load Profiles project to calibrate and validate the U.S. Department of Energy's ResStock and ComStock models, this work produces national data sets that enable cities, states, utilities, and other stakeholders to answer a broad range of questions regarding their commercial building stock. ComStock is a highly granular, bottom-up model that uses various data sources, statistical sampling methods, and advanced building energy simulations to estimate the annual subhourly energy consumption of the commercial building stock across the United States. The "baseline" model intends to represent the U.S. commercial building stock as it existed in 2018. The methodology of the baseline model is discussed in the ComStock Reference Documentation. The goal of this work is to develop energy efficiency and demand flexibility measures that cover market-ready technologies and study their mass adoption impact on the baseline building stock. "Measures" refers to various "what-if" scenarios that can be applied to buildings. The results for the baseline and measure scenario simulations are published in public data sets that provide insights into building stock characteristics, operational behaviors, utility bill impacts, and annual and sub-hourly energy usage by fuel type and end use. This report describes the modeling methodology for a single ComStock measure scenario - high-efficiency rooftop unit (RTU) - and briefly introduces key results. The full public data set can be accessed on the Comstock data lake or via the Data Viewer at comstock.nlr.gov. The public data set enables users to create custom aggregations of results for their use case (e.g., filter to a specific county or building type).

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2026

ComStock Measure Documentation: Variable-Speed Pumps

Building on the 3-year End-Use Load Profiles project to calibrate and validate the U.S. Department of Energy's ResStock and ComStock models, this work produces national data sets that enable cities, states, utilities, and other stakeholders to answer a broad range of questions regarding their commercial building stock. ComStock is a highly granular, bottom-up model that uses various data sources, statistical sampling methods, and advanced building energy simulations to estimate the annual subhourly energy consumption of the commercial building stock across the United States. The "baseline" model intends to represent the U.S. commercial building stock as it existed in 2018. The methodology of the baseline model is discussed in the ComStock Reference Documentation. The goal of this work is to develop energy efficiency and demand flexibility measures that cover market-ready technologies and study their mass adoption impact on the baseline building stock. "Measures" refers to various "what-if" scenarios that can be applied to buildings. The results for the baseline and measure scenario simulations are published in public data sets that provide insights into building stock characteristics, operational behaviors, utility bill impacts, and annual and sub-hourly energy usage by fuel type and end use. This report describes the modeling methodology for a single ComStock measure scenario - variable speed pumps - and briefly introduces key results. The full public data set can be accessed on the ComStock data lake or via the Data Viewer at comstock.nlr.gov. The public data set enables users to create custom aggregations of results for their use case (e.g., filter to a specific county or building type).

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2026

ComStock Measure Documentation: Fan Static Pressure Reset for Multizone Variable Air Volume Systems

This report assesses the potential for nationwide adoption of a duct static pressure reset in MZ VAV systems in appropriate applications. Building on the 3-year End-Use Load Profiles project to calibrate and validate the U.S. Department of Energy’s ResStock™ and ComStock™ models, this work produces national datasets that enable cities, states, utilities, and other stakeholders to answer a broad range of questions regarding their commercial building stock. ComStock is a highly granular, bottom-up model that uses various data sources, statistical sampling methods, and advanced building energy simulations to estimate the annual sub-hourly energy consumption of the commercial building stock across the United States. The “baseline” model intends to represent the U.S. commercial building stock as it existed in 2018. The methodology of the baseline model is discussed in the ComStock Reference Documentation. The goal of this work is to develop energy efficiency and demand flexibility measures that cover market-ready technologies and study their mass-adoption impact on the baseline building stock. “Measures” refers to various “what-if” scenarios that can be applied to buildings. The results for the baseline and measure scenario simulations are published in public datasets that provide insights into building stock characteristics, operational behaviors, utility bill impacts, and annual and sub-hourly energy usage by fuel type and end use. This report describes the modeling methodology for a single ComStock measure scenario—Fan Static Pressure Reset for Multizone Variable Air Volume (VAV) Systems—and briefly introduces key results. The full public dataset can be accessed on the ComStock data lake or via the Data Viewer at comstock.nrel.gov. The public dataset enables users to create custom aggregations of results for their use case (e.g., filter to a specific county or building type).

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2026

ComStock Measure Documentation: Thermostat Setbacks During Unoccupied Periods

This report assesses the potential for nationwide adoption of thermostat setbacks in appropriate applications. Building on the 3-year End-Use Load Profiles project to calibrate and validate the U.S. Department of Energy’s ResStock™ and ComStock™ models, this work produces national datasets that enable cities, states, utilities, and other stakeholders to answer a broad range of questions regarding their commercial building stock. ComStock is a highly granular, bottom-up model that uses various data sources, statistical sampling methods, and advanced building energy simulations to estimate the annual sub-hourly energy consumption of the commercial building stock across the United States. The “baseline” model intends to represent the U.S. commercial building stock as it existed in 2018. The methodology of the baseline model is discussed in the ComStock Reference Documentation. The goal of this work is to develop energy efficiency and demand flexibility measures that cover market-ready technologies and study their mass-adoption impact on the baseline building stock. “Measures” refers to various “what-if” scenarios that can be applied to buildings. The results for the baseline and measure scenario simulations are published in public datasets that provide insights into building stock characteristics, operational behaviors, utility bill impacts, and annual and sub-hourly energy usage by fuel type and end use. This report describes the modeling methodology for a single ComStock measure scenario— Thermostat Setbacks During Unoccupied Periods—and briefly introduces key results. The full public dataset can be accessed on the ComStock data lake or via the Data Viewer at comstock.nrel.gov. The public dataset enables users to create custom aggregations of results for their use cases (e.g., filter to a specific county or building type).

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2021

Design and dispatch optimization of packaged ice storage systems within a connected community

The traditional implementation of cool thermal energy storage (CTES) must be reimagined within the context of a dynamic grid and smart buildings operating as connected communities. As most buildings do not operate central chillers or connect to district cooling loops, this necessitates a broader use of packaged CTES. Our objective is to begin answering the question of how such packaged CTES should be implemented within a connected community. We do so by presenting a simulation–optimization workflow employing building energy modeling software and a mixed-integer linear program to design and dispatch a packaged CTES technology to achieve minimum total annual cost. We demonstrate this methodology on a seven-building case study using current utility rates and find that total annual cooling energy costs can be reduced by 17.8% compared to baseline, after accounting for the cost of storage. We perform three parametric sensitivity studies to evaluate modeling assumptions and obtain the prioritization of storage procurement as a function of annualized life-cycle cost of storage. We find that a community optimization approach provides significantly different results than individual building optimizations and provides greater savings compared to baseline.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2024

Lambda baryon production in neutrino-nucleus interactions and light signals reconstruction in the Short-Baseline Near Detector

The field of neutrino physics is nowadays entering the era of precision measurements, with new detectors capable of capturing neutrino interactions with unprecedented detail and high intensity neutrino beams. Liquid Argon Time Projection Chambers (LArTPCs) have become one of the main neutrino detection technologies, providing excellent imaging capabilities and particle identification. The Short-Baseline Near Detector (SBND) at Fermilab is a LArTPC experiment designed to capture neutrinos from the Booster Neutrino Beam (BNB). Its proximity to the beam target (110\,m) and large size (112\,ton) enable the recording of millions of neutrino interactions annually. SBND provides the highest statistics worldwide for neutrino-argon cross-section measurements, facilitating the study of rare channels like Cabibbo-suppressed quasielastic hyperon production. Specifically, this thesis focuses on neutral $\Lambda$ baryon production for which only tens of events have been observed up to date. Our work introduces a novel selection strategy leveraging LArTPC imaging capabilities to identify the distinctive decay signatures of $\Lambda$ baryons, enhancing sensitivity to this channel. Besides being a very mature technology, LArTPCs are an evolving technology. Part of the focus of the new developments lies in harnessing the potential of scintillation light signals. The Photon Detection System (PDS) in SBND has been designed to provide an efficient detection of the scintillation light, representing a major R\&D opportunity in the LArTPC community. Its design provides a high and more uniform light yield, an excellent timing resolution and an independent 3D reconstruction of the events, including the drift coordinate, using exclusively the light signals. This work presents the first comprehensive study of the SBND PDS capabilities. The new developments in the simulation and reconstruction of the light signals in SBND are presented. The whole chain is applied to accurately tag neutrino events through timing information, with a predicted resolution $\mathcal{O}$(2\,ns), and ultimately retrieve the pulse structure of the BNB.

43 PARTICLE ACCELERATORS↗
DOE OSTI2026

Calibration of urban building energy model using smart meter data for district peak load prediction

Urban building energy modeling (UBEM) is a powerful approach to assessing baseline building energy performance and retrofits with new technologies across building stocks in cities. However, the accuracy of UBEM is often constrained by the limited availability of reliable data about building characteristics and operations, such as envelope efficiency levels, HVAC system performance, and end-use load patterns. Existing research has performed UBEM calibration using annual or monthly energy consumption data, which falls short when higher-resolution time series applications are needed, such as peak load prediction for utility operation planning. This study presents a new framework for calibrating building energy models at urban scale using smart meter data, targeting the accurate prediction of summer peak electricity loads to support robust grid planning. The framework first integrates various data sources to enhance baseline input assumptions for building models, and then calibrates the baseline models through a pattern-matching approach. A case study using CityBES and two years of AMI data from over 9000 residential customers in Portland, Oregon, demonstrated the workflow and its effectiveness. The calibrated models achieved a daily peak load mean absolute percentage error of 2.6 % during the heatwave in the calibration year, and 2.0 % in the validation year using another year of AMI data. Using the calibrated models, we analyzed the demand flexibility potential of the district building stock as an application of UBEM calibration. The findings affirm the appropriate use of UBEM for peak electric load forecasting and demand side management at the utility distribution system level.

AMI data↗
DOE OSTI2026

Scenario-based analysis of electric vehicle adoption in the United States: Technology, infrastructure, and electricity pricing

This work investigates the impact of battery technology advancement, charging infrastructure development, and time-of-use (TOU) electricity pricing on vehicle adoption by 6 powertrain types in the United States through 2050. Using the Market Acceptance of Advanced Automotive Technologies (MA3T) model, we simulate 15 scenarios, examining individual cost factors and their combinations. We assess outcomes through market share, consumer surplus, and energy consumption. Results show that battery cost reductions are the strongest driver of EV adoption, increasing 2050 battery electric vehicle (BEV) share by 27 percentage points over baseline, raising annual consumer surplus by $511 per household, and reducing cumulative energy consumption by 16,610 trillion Btu. These gains are two to five times larger than those from other individual factors. Reducing home charging installation costs produces moderate impact, while TOU pricing alone yields only small gains, raising 2050 BEV market share by 1–2 percentage points. However, when cost factor improvements are combined, their effects are amplified beyond simple additivity. Pairing modest battery cost reductions with charging installation cost reductions and TOU pricing results in the largest 2050 BEV sales combined impact. The analysis demonstrates that moderate progress targeting multiple cost barriers may be more impactful than focusing on any single barrier.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2026

Zero-CO Residential Natural Gas Furnace

Residential natural gas furnaces are widely used in the US homes. Manufacturers dedicate significant design and testing resources to meet requirements of design standards. One area of these standards is controlling flue gas carbon monoxide (CO) emissions. To more effectively reduce CO emissions at the flue, we developed a novel catalyst-assisted approach that integrated a low Pt/Rh loading acidic gas reduction (AGR) catalyst with three-way catalyst (TWC) or diesel oxidation catalyst (DOC) components. Compact catalysts were fabricated and assembled into tubular components, which can be seamlessly incorporated into the primary heat exchanger of a representative commercially available condensing furnace. The retrofitted furnace was demonstrated and tested following ANSI/ASHRAE Standard 103-2017. Experimental results showed that both AGR/TWC and AGR/DOC configurations achieved near-zero CO emissions under steady-state and cold-start conditions, compared with up to 500 ppm at a cold start and 17 ppm in a steady state in the OEM furnace. The catalyst-assisted furnaces also exhibited an annual fuel utilization efficiency improvement of more than 1.5% relative to the baseline unit, with a manageable pressure drop of 2.0−2.5 in. of water column. These results demonstrate that the catalyst-assisted approach can effectively eliminate CO emissions and improve energy efficiency. The technology has broad applicability for residential and commercial gas-fired heating systems.

Gao, Zhiming [ORNL] (ORCID:0000000271397995)↗
DOE OSTI2023

Comparative feedstock analysis in Setaria viridis L. as a model for C 4 bioenergy grasses and panicoid crop species

Second generation feedstocks for bioethanol will likely include a sizable proportion of perennial C4 grasses, principally in the Panicoideae clade. The Panicoideae contain agronomically important annual grasses including Zea mays L. (maize), Sorghum bicolor (L.) Moench (sorghum), and Saccharum officinarum L. (sugar cane) as well as promising second generation perennial feedstocks including Miscanthus × giganteus and Panicum virgatum L. (switchgrass). The underlying complexity of these polyploid grass genomes is a major limitation for their direct manipulation and thus driving a need for rapidly cycling comparative model. Setaria viridis (green millet) is a rapid cycling C4 panicoid grass with a relatively small and sequenced diploid genome and abundant seed production. Stable, transient, and protoplast transformation technologies have also been developed for Setaria viridis making it a potentially excellent model for other C4 bioenergy grasses. Here, the lignocellulosic feedstock composition, cellulose biosynthesis inhibitor response and saccharification dynamics of Setaria viridis are compared with the annual sorghum and maize and the perennial switchgrass bioenergy crops as a baseline study into the applicability for translational research. A genome-wide systematic investigation of the cellulose synthase-A genes was performed identifying eight candidate sequences. Two developmental stages; (a) metabolically active young tissue and (b) metabolically plateaued (mature) material are examined to compare biomass performance metrics.

09 BIOMASS FUELS↗
DOE OSTI2022

A multi-product landscape life-cycle assessment approach for evaluating local climate mitigation potential

Increasing demand for land-based climate mitigation requires more efficient management of agricultural landscapes for competing objectives. Here we develop methods for assessing trade-offs and synergies between intensification and carbon-sequestering conservation measures in annual crop production landscapes using the DayCent ecosystem model and the Greenhouse Gases, Regulated Emissions, and Energy Use in Technologies (GREET) life-cycle assessment (LCA) model. We compiled county-scaled crop yields, fertilizer application rates, and tillage intensity for a corn–soybean farming case study landscape in the US state of Iowa. Using DayCent, we estimated a baseline soil organic carbon (SOC) accrual rate of 0.29 Mg C ha -1 y -1 driven by historical increases in crop productivity and reductions in tillage intensity. We then simulated the effects of management interventions targeted toward intensification (stover removal) and SOC sequestration (tillage intensity reduction and winter cover crop addition) individually and in combination. We propose a new multi-product landscape–LCA approach that analyzes marginal changes in corn grain, corn stover, and soybean production from the landscape in terms of their value for biofuel production (corn ethanol, soy biodiesel, and cellulosic ethanol from stover) and associated net displacement of conventional fossil-derived fuel use. This enables us to evaluate both intensification and sequestration effects in common CO 2 -equivalent mitigation units. We also used DayCent-simulated yields under the different land management scenarios to estimate farm-level costs and revenues. Our results show that intensification via collecting 30% of corn stover for biofuel production would increase the total greenhouse gas (GHG) mitigation potential of this landscape by 0.93 Mg CO 2 e ha -1 y -1 and provide $49 ha -1 y -1 of additional net revenue from biomass sales, but would reduce the baseline SOC accumulation rate by approximately 40%. In contrast, integrated approaches that include co-adoption of winter cover cropping and/or tillage intensity reduction would result in increased rates of SOC accumulation above the baseline, achieving simultaneous improvements in both farm profits and the overall GHG mitigation potential of the landscape.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Multi-technology building system retrofits for utility incentive programs: Savings, costs and baseline considerations

Utility incentive programs are an important channel to support the deployment of energy efficiency in buildings. To date, these programs have largely been limited to single-component strategies. However, many utilities are now motivated to identify and develop multi-component system retrofits to achieve deeper energy savings, which are essential to achieving broader energy and greenhouse gas reduction goals in the buildings sector. In this paper we present the energy savings, demand reductions, and cost-effectiveness of 16 systems retrofit packages in six utility regions in the United States. These results are being used by these utilities to inform and develop incentive programs for systems retrofits. Our analysis shows that packages with proven lighting and HVAC measures can provide 5–22% whole building annual energy savings, and 13–22% annual energy costs savings, using utility incentive program baselines (code and existing building). The packages are reasonably cost effective for replace-on-burnout but generally not for a retrofit scenario prior to end of equipment life. Demand response can increase both the energy savings and energy cost savings, further improving the cost effectiveness of these packages. We analyzed the impact of using existing building vs. code baselines for calculating savings, showing that the choice of baseline in developing utility incentive programs has a substantial impact on the attributable energy savings to a program, with significant implications for the overall viability of a program (generally savings against existing building condition are higher and improve project and program cost-effectiveness).

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2020

Performance Evaluation of Three RTU Energy Efficiency Technologies

This project was part of an effort by CLEAResult and ComEd to evaluate the energy saving potential of emerging technologies in the Chicago area. This project focused on evaluating emerging technologies related to rooftop units (RTUs). An RTU with a single-stage compressor and a constant-speed fan with an induction motor was selected as the baseline for technology comparison. Three retrofit strategies were investigated. The first two involved replacing the single-stage compressor of an RTU by either a two-stage or variable-speed compressor and adding a variable frequency drive (VFD) to the constant speed fan. The use of a multi-/variable-stage compressor improves the part-load efficiency of the compressor which will ultimately result in annual energy savings as well as peak demand shaving in some cases where the design capacity of the RTU is larger than the maximum cooling load of the building space that it is serving. The third technology was the use of a high rotor pole switched reluctance motor (SRM) as a replacement for the constant-speed supply fan. The SRM was applied in single-speed, two-stage and variable-speed compressor RTUs. SRM motors run via reluctance torque. Their stator poles are driven by direct current (DC) power and require an inverter as well as active control when using alternating current (AC) power. This inherent property results in high efficiency over a range of operating conditions. It also exhibits higher efficiency compared to variable frequency drives (VFDs) since its switching frequency is much slower (SCE, 2018).The three technologies investigated are summarized below: 1) Replacing the single-speed compressor with a two-stage compressor and adding a VFD to the supply fan. 2)Replacing the single-speed compressor with a variable-speed compressor and adding a VFD to the supply fan. 3) Replacing the constant-speed induction motor of the supply fan with a high rotor pole SRM. DOE’s building simulation platform EnergyPlus and its graphical user interface OpenStudio were used to evaluate the energy-saving potential of upgrading RTUs, by leveraging experimental data from previous research.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2022

Life cycle analysis of polylactic acids from different wet waste feedstocks

Producing a valuable chemical product through diversion of wet wastes can simultaneously resolve the problems associated with increasing wastes and greenhouse gas emissions from conventional chemical production processes. In this work, we investigated the life-cycle greenhouse gas emissions, water, and fossil-fuel consumption for waste-derived polylactic acids (PLA) from three different waste feedstocks, namely wastewater sludge, food waste, and swine manure, using the Greenhouse Gases, Regulated Emissions, and Energy Use in Technologies (GREET) model. The decarbonization potential of replacing fossil-based resins with the waste-derived polymer was also investigated. The results show that swine manure-to-PLA pathway was the least carbon intensive (—1.4 kgCO 2 e/kg) among the three waste-to-PLA pathways on a cradle-to-grave basis, followed by the food waste case (—1.3 kgCO 2 e/kg) and then by the wastewater sludge case (0.6 kgCO 2 e/kg). In the baseline scenario, all three waste-to-PLA pathways were less carbon intensive than both fossil-based PET and HDPE on a cradle-to-grave basis: 66% (vs. PET) and 56% (vs. HDPE), 171 and 192%, 181 and 205% reduction in GHG emissions for wastewater sludge-, food waste-, and swine manure-to-PLA pathway, respectively. For all sensitivity cases investigated, the food waste- and swine manure-to-PLA pathways were significantly less carbon intensive than their fossil-counterparts. In terms of the annual decarbonization potential of replacing fossil-based PET or HDPE, the wastewater sludge- and food waste-pathway showed higher mitigation potential than the swine manure-pathway: i) 18–28 kilotons CO 2 e-reduction per year for wastewater sludge pathway; ii) 23–26 kTCO 2 e-reduction/yr for food waste pathway; and iii) about 5 kTCO 2 e-reduction/yr for swine manure pathway depending on the type of conventional resin replaced. However, given the abundant availability of the swine manure feedstocks across the United States, the decarbonization potential of swine manure-based pathway can also increase as the plant capacity or the number of plants grow.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗