Impact of Power Generation Mix on Life Cycle Assessment and Carbon Footprint Greenhouse Gas Results

The mix of electricity consumed in any stage in the life cycle of a product, process, or industrial sector has a significant effect on the associated inventory of emissions and environmental impacts because of large differences in the power generation method used. Fossil‐fuel‐fired or nuclear‐centralized steam generators; large‐scale and small‐scale hydroelectric power; and renewable options, such as geothermal, wind, and solar power, each have a unique set of issues that can change the results of a life cycle assessment. This article shows greenhouse gas emissions estimates for electricity purchase for different scenarios using U.S. average electricity mix, state mixes, state mixes including imports, and a sector‐specific mix to show how different these results can be. We find that greenhouse gases for certain sectors and scenarios can change by more than 100%. Knowing this, practitioners should exercise caution or at least account for the uncertainty associated with mix choice.     

The Carbon Footprint of Norwegian Seafood Products on the Global Seafood Market

Greenhouse gas emissions caused by food production are receiving increased attention worldwide. A problem with many studies is that they only consider one product; methodological differences also make it difficult to compare results across studies. Using a consistent methodology to ensure comparability, we quantified the carbon footprint of more than 20 Norwegian seafood products, including fresh and frozen, processed and unprocessed cod, haddock, saithe, herring, mackerel, farmed salmon, and farmed blue mussels. The previous finding that fuel use in fishing and feed production in aquaculture are key inputs was confirmed. Additional key aspects identified were refrigerants used on fishing vessels, product yield, and by‐product use. Results also include that product form (fresh or frozen) only matters when freezing makes slower transportation possible. Processing before export was favorable due to the greater potential to use by‐products and the reduced need for transportation. The most efficient seafood product was herring shipped frozen in bulk to Moscow at 0.7 kilograms CO₂ equivalents per kilogram (kg CO₂‐eq/kg) edible product. At the other end we found fresh gutted salmon airfreighted to Tokyo at 14 kg CO₂‐eq/kg edible product. This wide range points to major differences between seafood products and room for considerable improvement within supply chains and in product choices. In fisheries, we found considerable variability between fishing methods used to land the same species, which indicates the importance of fisheries management favoring the most resource‐efficient ways of fishing. Both production and consumption patterns matter, and a range of improvements could benefit the carbon performance of Norwegian seafood products.     

Environmental Damage Assessment of Carbon Capture and Storage

An end‐point life cycle impact assessment is used to evaluate the damages of electricity generation from fossil fuel‐based power plants with carbon dioxide capture and storage (CCS) technology. Pulverized coal (PC), integrated gasification combined cycle (IGCC), and natural gas combined cycle (NGCC) power plants are assessed for carbon dioxide (CO₂) capture, pipeline transport, and storage in a geological formation. Results show that the CCS systems reduce the climate change‐related damages but increase the damages from toxicity, acidification, eutrophication, and resource consumption. Based on the currently available damage calculation methods, it is concluded that the benefit of reducing damage from climate change is larger than the increases in other damage categories, such as health effects from particulates or toxic chemicals. CCS significantly reduces the overall environmental damage, with a net reduction of 60% to 70% in human health damage and 65% to 75% in ecosystem damage. Most of the damage is due to fuel production and combustion processes. The energy and infrastructure demands of CCS cause increases in the depletion of natural resources by 33% for PC, 19% for IGCC, and 18% for NGCC power plants, mostly due to increased fossil fuel consumption.     

Life Cycle Inventory Analysis of the Wood Pallet Repair Process in the United States

This study developed gate‐to‐gate life cycle inventory (LCI) data for the repair of 48 by 40 inch (1,219 by 1,016 millimeter [mm]) stringer‐class wood pallets in the United States. Data were collected from seven wood pallet repair facilities. Approximately 1.98 FBM (foot, board measure) (4.67E‐03 cubic meters) of lumber were used for repairing each 48 by 40 inch (1,219 by 1,016 mm) stringer‐class wood pallet, the majority (97%) recovered from damaged pallets received by the pallet repair facilities. Repair equipment powered by electricity made the largest contribution to greenhouse gas (GHG) emissions. Steel nails used for the pallet repair had the largest contribution to GHG emissions among the material inputs, while use of recovered lumber yielded the largest GHG emissions credits. Overall, the repair process for a 48 by 40 inch (1,219 by 1,016 mm) stringer‐class wood pallet had GHG credits rather than a positive GHG emission due to the GHG offsets from co‐products.     

Carbon Accounting in Harvested Wood Products: Assessment Using Material Flow Analysis Resulting in Larger Pools Compared to the IPCC Default Method

Increasing the amount of carbon stored in harvested wood products (HWPs) is an internationally recognized measure to mitigate climate change. Several approaches and tiers of methods may be used to analyze the contribution of HWP in terms of greenhouse gas emissions and removals at a regional and national level. The Intergovernmental Panel on Climate Change (IPCC) provides guidelines on three tiers of methods for estimating annual carbon stock changes in the carbon pool of HWPs. These tiers mostly differ by the availability of input data and the level of HWP aggregation. In this case study for the Czech Republic, we have applied the production approach and alternative tiers of accounting methods, which are described in the IPCC guidelines, including the default method (tier 2) and the most advanced method (tier 3). We used country‐specific data and material flow analysis to trace the carbon flow over the entire forest‐based sector, including only the domestic harvest and the primary and secondary wood products manufactured within the country. The results of this study show that the carbon stored in the HWP pool could be underestimated if simpler methods and default values nonspecific to the country are applied. At the national level, applying the tier 3 method resulted in a 15.8% higher annual carbon inflow in the pool of HWPs compared to the tier 2 IPCC default method. This means that the advanced method reveals an apparently higher carbon sink in HWPs. A documented increase of carbon storage might bring additional credits to reporting countries, and, more important, it could promote the use of long‐life HWPs to mitigate climate change.     

Effect of Change of Forest Carbon Storage on Net Carbon Dioxide Balance of Wood Use for Energy in Japan

This study analyzed the net carbon dioxide (CO₂) emission reductions between 2005 and 2050 by using wood for energy under various scenarios of forest management and energy conversion technology in Japan, considering both CO₂ emission reductions from replacement of fossil fuels and changes in carbon storage in forests. According to our model, wood production for energy results in a significant reduction of carbon storage levels in forests (by 46% to 77% in 2050 from the 2005 level). Thus, the net CO₂ emission reduction when wood is used for energy becomes drastically smaller. Conventional tree production for energy increases net CO₂ emissions relative to preserving forests, but fast‐growing tree production may reduce net CO₂ emissions more than preserving forests does. When wood from fast‐growing trees is used to generate electricity with gas turbines, displacing natural gas, the net CO₂ emission reduction from the combination of fast‐growing trees and electricity generation with gas turbines is about 58% of the CO₂ emission reduction from electricity generation from gas turbines alone in 2050, and an energy conversion efficiency of around 20% or more is required to obtain net reductions over the entire period until 2050. When wood is used to produce bioethanol, displacing gasoline, net reductions are realized after 2030, provided that heat energy is recovered from residues from ethanol production. These results show the importance of considering the change in carbon storage when estimating the net CO₂ emission reduction effect of the wood use for energy.     

Data for the Carbon Footprinting of Rendering Operations

This article presents a tool and data for calculation of the carbon footprint of rendering operations in North America, quantifying Scope 1 (direct) and Scope 2 (indirect) greenhouse gas emissions. Scope 3 (life cycle) emissions are not included. According to the sample data, in one year an average‐size rendering plant in North America processes 100,000 tonnes (t) of meat by‐products, fallen animals, and restaurant grease and produces 40,000 t of marketable fats and proteins. A plant of this size emits directly about 20,000 t of carbon dioxide (CO₂), mostly by burning fuels to operate cookers that destroy pathogens, drive off moisture, and separate the fat and protein. Another 4,000 t of CO₂ is emitted by utility companies to provide electricity for the rendering process. These direct and indirect emissions are equivalent to about 30% of the CO₂ that would be released if all of the carbon in the rendered raw material were decomposed into CO₂.     

Toward a Carbon Dioxide Neutral Industrial Park

The industrial park of Herdersbrug (Brugge, Flanders, Belgium) comprises 92 small and medium‐sized enterprises, a waste‐to‐energy incinerator, and a power plant (not included in the study) on its site. To study the carbon dioxide (CO₂) neutrality of the park, we made a park‐wide inventory for 2007 of the CO₂ emissions due to energy consumption (electricity and fossil fuel) and waste incineration, as well as an inventory of the existing renewable electricity and heat generation. The definition of CO₂ neutrality in Flanders only considers CO₂ released as a consequence of consumption or generation of electricity, not the CO₂ emitted when fossil fuel is consumed for heat generation. To further decrease or avoid CO₂ emissions, we project and evaluate measures to increase renewable energy generation. The 21 kilotons (kt) of CO₂ emitted due to electricity consumption are more than compensated by the 25 kt of CO₂ avoided by generation of renewable electricity. Herdersbrug Industrial Park is thus CO₂ neutral, according to the definition of the Flemish government. Only a small fraction (6.6%) of the CO₂ emitted as a consequence of fossil fuel consumption (heat generation) and waste incineration is compensated by existing and projected measures for renewable heat generation. Of the total CO₂ emission (149 kt) due to energy consumption (electricity + heat generation) and waste incineration on the Herdersbrug Industrial Park in 2007, 70.5% is compensated by existing and projected renewable energy generated in the park. Forty‐seven percent of the yearly avoided CO₂ corresponds to renewable energy generated from waste incineration and biomass fermentation.     

Energy and Carbon Management Systems

This article examines an important class of information system that serves as the foundation for corporate energy and greenhouse gas (GHG) accounting: energy and carbon management systems (ECMS). Investors, regulators, customers, and employees increasingly demand that organizations provide information about their organizational energy use and GHG emissions. However, there is little transparency about how organizations use ECMS to meet such demands. To shed light on ECMS implementation and application, we collected extensive qualitative interview data from two service‐sector organizations: one that uses a spreadsheet‐based ECMS and another that implemented an ECMS provided by a third‐party vendor. Our analysis of collected data revealed numerous challenges in the areas of business processes, managerial capabilities, data capture and integration, and data quality. Though our study is built on only two organizations and requires confirmation in large‐sample surveys, we provide several recommendations for organizations regarding ECMS. We also provide suggestions for future studies to build on our tentative results.     

Increasing Precision in Greenhouse Gas Accounting Using Real‐Time Emission Factors

For many companies, the greenhouse gas (GHG) emissions associated with their purchased and consumed electricity form one of the largest contributions to the GHG emissions that result from their activities. Currently, hourly variations in electricity grid emissions are not considered by standard GHG accounting protocols, which apply a national grid emission factor (EF), potentially resulting in erred estimates for the GHG emissions. In this study, a method is developed that calculates GHG emissions based on real‐time data, and it is shown that the use of hourly electricity grid EFs can significantly improve the accuracy of the GHG emissions that are attributed to the purchased and consumed electricity of a company. A model analysis for the electricity delivered to the Spanish grid in 2012 reveals that, for companies operating during the day, GHG emissions calculated by the real‐time method are estimated to be up to 5% higher (and in some special cases up to 9% higher) than the emissions calculated by the conventional method in which a national grid EF is applied, whereas for companies operating during nightly hours, GHG emissions are estimated to be as low as 3% below the GHG emissions determined by the conventional method. A significant error can therefore occur in the organizational carbon footprint (CF) of a company and, consequently, also in the product CF. It is recommended that hourly EFs be developed for other countries and power grids.     

Global Warming Potential of Carbon Dioxide Emissions from Biomass Stored in the Anthroposphere and Used for Bioenergy at End of Life

There is growing interest in understanding how storage or delayed emission of carbon in products based on bioresources might mitigate climate change, and how such activities could be credited. In this research we extend the recently introduced approach that integrates biogenic carbon dioxide (CO₂) fluxes with the global carbon cycle (using biogenic global warming potential [GWP_bio]) to consider the storage period of harvested biomass in the anthroposphere, with subsequent oxidation. We then examine how this affects the climate impact from a bioenergy resource. This approach is compared to several recent methods designed to address the same problem. Using both a 100‐ and a 500‐year fixed time horizon we calculate the GWP_bio factor for every combination of rotational and anthropogenic storage periods between 0 and 100 years. The resulting GWP_bio factors range from ?0.99 (1‐year rotation and 100‐year storage) to +0.44 (100‐year rotation and 0‐year storage). The approach proposed in this study includes the interface between biomass growth and emissions and the global carbon cycle, whereas other methods do not model this. These results and the characterization factors produced can determine the climate change benefits or impacts associated with the storage of biomass in the anthroposphere, and the subsequent release of biogenic CO₂ with the radiative forcing integrated in a fixed time window.     

Estimating the Greenhouse Gas Balance of Individual Gas‐Fired and Oil‐Fired Electricity Plants on a Global Scale

Life cycle greenhouse gas (LC‐GHG) emissions from electricity generated by a specific resource, such as gas and oil, are commonly reported on a country‐by‐country basis. Estimation of variability in LC‐GHG emissions of individual power plants can, however, be particularly useful to evaluate or identify appropriate environmental policy measures. Here, we developed a regression model to predict LC‐GHG emissions per kilowatt‐hour (kWh) of electricity produced by individual gas‐ and oil‐fired power plants across the world. The regression model uses power plant characteristics as predictors, including capacity, age, fuel type (fuel oil or natural gas), and technology type (single or combined cycle) of the plant. The predictive power of the model was relatively high (R² = 81% for predictions). Fuel and technology type were identified as the most important predictors. Estimated emission factors ranged from 0.45 to 1.16 kilograms carbon dioxide equivalents per kilowatt‐hour (kg CO₂‐eq/kWh) and were clearly different between natural gas combined cycle (0.45 to 0.57 kg CO₂‐eq/kWh), natural gas single cycle (0.66 to 0.85 kg CO₂‐eq/kWh), oil combined cycle power plants (0.63 to 0.79 kg CO₂‐eq/kWh), and oil single cycle (0.94 to 1.16 kg CO₂‐eq/kWh). Our results thus indicate that emission data averaged by fuel and technology type can be profitably used to estimate the emissions of individual plants.     

Uncertainty and Variability in Product Carbon Footprinting

Recent years have seen increasing interest in life cycle greenhouse gas emissions accounting, also known as carbon footprinting, due to drivers such as transportation fuels policy and climate‐related eco‐labels, sometimes called carbon labels. However, it remains unclear whether applications of greenhouse gas accounting, such as carbon labels, are supportable given the level of precision that is possible with current methodology and data. The goal of this work is to further the understanding of quantitative uncertainty assessment in carbon footprinting through a case study of a rackmount electronic server. Production phase uncertainty was found to be moderate (±15%), though with a high likelihood of being significantly underestimated given the limitations in available data for assessing uncertainty associated with temporal variability and technological specificity. Individual components or subassemblies showed varying levels of uncertainty due to differences in parameter uncertainty (i.e., agreement between data sets) and variability between production or use regions. The use phase displayed a considerably higher uncertainty (±50%) than production due to uncertainty in the useful lifetime of the server, variability in electricity mixes in different market regions, and use profile uncertainty. Overall model uncertainty was found to be ±35% for the whole life cycle, a substantial amount given that the method is already being used to set policy and make comparative environmental product declarations. Future work should continue to combine the increasing volume of available data to ensure consistency and maximize the credibility of the methods of life cycle assessment (LCA) and carbon footprinting. However, for some energy‐using products it may make more sense to increase focus on energy efficiency and use phase emissions reductions rather than attempting to quantify and reduce the uncertainty of the relatively small production phase.     

Using Attributional Life Cycle Assessment to Estimate Climate‐Change Mitigation Benefits Misleads Policy Makers

Life cycle assessment (LCA) is generally described as a tool for environmental decision making. Results from attributional LCA (ALCA), the most commonly used LCA method, often are presented in a way that suggests that policy decisions based on these results will yield the quantitative benefits estimated by ALCA. For example, ALCAs of biofuels are routinely used to suggest that the implementation of one alternative (say, a biofuel) will cause an X% change in greenhouse gas emissions, compared with a baseline (typically gasoline). However, because of several simplifications inherent in ALCA, the method, in fact, is not predictive of real‐world impacts on climate change, and hence the usual quantitative interpretation of ALCA results is not valid. A conceptually superior approach, consequential LCA (CLCA), avoids many of the limitations of ALCA, but because it is meant to model actual changes in the real world, CLCA results are scenario dependent and uncertain. These limitations mean that even the best practical CLCAs cannot produce definitive quantitative estimates of actual environmental outcomes. Both forms of LCA, however, can yield valuable insights about potential environmental effects, and CLCA can support robust decision making. By openly recognizing the limitations and understanding the appropriate uses of LCA as discussed here, practitioners and researchers can help policy makers implement policies that are less likely to have perverse effects and more likely to lead to effective environmental policies, including climate mitigation strategies.     

When Comparing Alternative Fuel‐Vehicle Systems,Life Cycle Assessment Studies Should Consider Trends in Oil Production

Petroleum from unconventional reserves is making an increasingly important contribution to the transportation fuel supply, but is generally more expensive and has greater environmental burdens than petroleum from conventional sources. Life cycle assessments (LCAs) of alternative fuel‐vehicle technologies typically consider conventional internal combustion engine vehicles fueled by gasoline produced from the average petroleum slate used in refineries as a baseline. Large‐scale deployment of alternative fuel‐vehicle technologies will decrease petroleum demand and lead to decreased production at the economic margin (unconventional oil), but this is not considered in most current LCAs. If marginal petroleum resources have larger impacts than average petroleum resources, the environmental benefits of petroleum demand reduction are underestimated by the current modeling approaches. Often, models include some consequential‐based impacts (such as indirect land‐use change for biofuels), but exclude others (such as avoided unconventional oil production). This approach is inconsistent and does not provide a robust basis for public policy and private investment strategy decisions. We provide an example to illustrate the potential scale of these impacts, but further research is needed to establish and quantify these marginal effects and incorporate them into LCAs of both conventional and alternative fuel‐vehicle technologies.     

Evaluation of a Regional Approach to Standards for Plug‐in Battery Electric Vehicles in Future Light‐Duty Vehicle Greenhouse Gas Regulations

Representing the greenhouse gas (GHG) emissions attributable to plug‐in electric vehicles (PEV) in vehicle GHG emissions regulations is complex because of spatial and temporal variation in fueling sources and vehicle use. Previous work has shown that the environmental performance of PEVs significantly varies depending on the characteristics of the electricity grid and how the vehicle is driven. This article evaluates the U.S. Environmental Protection Agency's (EPA's) GHG emissions accounting methodology in current and future standards for new electrified vehicles. The current approach employed by the EPA in their 2017–2025 model year light‐duty vehicle GHG regulation is compared with an accounting mechanism where the actual regional sales of PEVs, and the regional electricity emission factor in the year sold, are used to determine vehicle compliance value. Changes to the electricity grid over time and regional vehicle sales are included in the modeling efforts. A projection of a future GHG regulation past the 2017–2025 rule is used to observe the effect of such a regional regulation. The results showed that the complexity involved in tracking and accounting for regional PEV sales will not dramatically increase the effectiveness of the regulations to capture PEV electricity‐related GHG emissions in the absence of a major policy shift. A discussion of the feasibility and effectiveness of a regional standard for PEVs, and notable examples of region‐specific regulations instated in past energy policies, is also addressed.     

Assessment of risk of GHG emissions from Tehri hydropower reservoir,India

The hydropower reservoirs, considered as a green source of energy, are now found to emit significant quantities of greenhouse gas (GHG) to the atmosphere. This article attempts to predict the vulnerability of Tehri reservoir, India to GHG emissions using the GHG risk assessment tool (GRAT). The GRAT is verified with experimental GHG fluxes. The annual mean CO₂ fluxes from diffusion, bubbling, and degassing were 425.93 ± 122.50, 4.81 ± 1.33, and 7.01 ± 2.77 mg m^?2d^?1, whereas CH₄ fluxes were 23.11 ± 7.08, 4.79 ± 1.08, and 7.41 ± 4.50 mg m^?2d^?1, respectively, during 2011–12. The model found that Tehri reservoir emitted higher CO₂ and CH₄ (i.e., 790 mg m^?2d^?1 and 64 mg m^?2d^?1, respectively) in 2011, which came within vulnerability range causing more climate change impact. By the year 2015, it would scale down to medium risks necessitating no further assessment of GHG. Significant difference between predicted and experimental GHG emission are assessed, which may be due to insufficient data, spatial and temporal variations, decomposition of flooded biomass, limitation of GRAT model, and inadequate methodology. The study reveals that GHG emission from Tehri reservoir is less than predicted by the GRAT.     

Wrapping Up Greenhouse Gas Emissions An Assessment of GHG Emission Reduction Related to Efficient Packaging Use: An Assessment of GHG Emission Reduction Related to Efficient Packaging Use

The use of packaging materials results in greenhouse gas (GHG) emissions through production and transport of materials and packaging and through end-of-life management. In this article, we investigate the potential reduction of GHGs that are related to packaging. For this purpose, we use the dynamic MATTER-MARKAL model in which the western European energy and materials system is modeled. The results show that GHGs related to packaging can technically be reduced by up to 58% in the period 1995–2030. Current European packaging directives will result in a 10% emission reduction. Cost-effective improved material management 1 that includes lightweighting, reusable packages, material recycling, and related strategies can contribute a 22% GHG emission reduction. An additional 13% reduction becomes cost effective when a GHG emission penalty of 100 euros per metric ton 2 (EUR/ton) is introduced (1 EUR 0.9 USD). Generally speaking, improved material management dominates the gains that can be achieved without a penalty or with low GHG emission penalties (up to 100 EUR/ton CO2 equivalent). By contrast, the reduction of emissions in materials production and waste handling dominate when high GHG penalties are applied (between 100 and 500 EUR/ton CO2 equivalent). Given the significant technical potential and the low costs, more attention should be paid to material efficiency improvement in GHG emission reduction strategies.     

A Carbon Footprint of Textile Recycling: A Case Study in Sweden

Global population growth and rising living standards are increasing apparel consumption. Consequently, consumption of resources and generation of textile waste are increasing. According to the Swedish Environmental Protection Agency, textile consumption increased by 40% between the years 2000 and 2009 in Sweden. Given that there is currently no textile recycling plant in Sweden, the aim of this article is to explore the potential environmental benefits of various textile recycling techniques and thereby direct textile waste management strategies toward more sustainable options. Three different recycling techniques for a model waste consisting of 50% cotton and 50% polyester were identified and a life cycle assessment (LCA) was made to assess the environmental performance of them. The recycling processes are: material reuse of textile waste of adequate quality; separation of cellulose from polyester using N‐methylmorpholine‐N‐oxide as a solvent; and chemical recycling of polyester. These are compared to incineration, representing conventional textile waste treatment in Sweden. The results show that incineration has the highest global warming potential and primary energy usage. The material reuse process exhibits the best performance of the studied systems, with savings of 8 tonnes of carbon dioxide equivalents (CO₂‐eq) and 164 gigajoules (GJ) of primary energy per tonne of textile waste. Sensitivity analyses showed that results are particularly sensitive to the considered yields of the processes and to the choice of replaced products. An integration of these recycling technologies for optimal usage of their different features for treatment of 1 tonne of textile waste shows that 10 tonnes CO₂‐eq and 169 GJ of primary energy could be saved.     

Life Cycle–based Assessment of Energy Use and Greenhouse Gas Emissions in Almond Production,Part II: Uncertainty Analysis through Sensitivity Analysis and Scenario Testing

This is the second part of a two‐article series examining California almond production. The part I article describes development of the analytical framework and life cycle–based model and presents typical energy use and greenhouse gas (GHG) emissions for California almonds. This part II article builds on this by exploring uncertainty in the life cycle model through sensitivity and scenario analysis, and by examining temporary carbon storage in the orchard. Sensitivity analysis shows life cycle GHG emissions are most affected by biomass fate and utilization, followed by nitrous oxide emissions rates from orchard soils. Model sensitivity for net energy consumption is highest for irrigation system parameters, followed by biomass fate and utilization. Scenario analysis shows utilization of orchard biomass for electricity production has the greatest potential effect, assuming displacement methods are used for co‐product allocation. Results of the scenario analysis show that 1 kilogram (kg) of almond kernel and associated co‐products are estimated to cause between ?3.12 to 2.67 kg carbon dioxide equivalent (CO₂‐eq) emissions and consume between 27.6 to 52.5 megajoules (MJ) of energy. Co‐product displacement credits lead to avoided emissions of between ?1.33 to 2.45 kg CO₂‐eq and between ?0.08 to 13.7 MJ of avoided energy use, leading to net results of ?1.39 to 3.99 kg CO₂‐eq and 15.3 to 52.6 MJ per kg kernel (net results are calculated by subtracting co‐product credits from the results for almonds and co‐products). Temporary carbon storage in orchard biomass and soils is accounted for by using alternative global warming characterization factors and leads to a 14% to 18% reduction in CO₂‐eq emissions. Future studies of orchards and other perennial cropping systems should likely consider temporary carbon storage.