Modeling Corn Ethanol and Climate

New fuel regulations based on life cycle greenhouse gas (GHG) emissions have focused renewed attention on life cycle models of biofuels. The BESS model estimates 25% lower life cycle GHG emissions for corn ethanol than does the well-known GREET model, which raises questions about which model is more accurate. I develop a life cycle metamodel to compare the GREET and BESS models in detail and to explain why the results from these models diverge. I find two main reasons for the divergence: (1) BESS models a more efficient biorefinery than is modeled in the cases to which its results have been compared, and (2) in several instances BESS fails to properly count upstream emissions. Adjustments to BESS to account for these differences raise the estimated global warming intensity (not including land use change) of the corn ethanol pathway considered in that model from 45 to 61 g CO₂e MJ⁻¹. Adjusting GREET to use BESS's biorefinery performance and coproduct credit assumptions reduces the GREET estimate from 64 to 61 g CO₂e MJ⁻¹. Although this analysis explains the gap between the two models, both models would be improved with better data on corn production practices and by better treatment of agricultural inputs.     

Contribution of N2O to the greenhouse gas balance of first-generation biofuels

In this study, we analyze the impact of fertilizer‐ and manure‐induced N₂O emissions due to energy crop production on the reduction of greenhouse gas (GHG) emissions when conventional transportation fuels are replaced by first‐generation biofuels (also taking account of other GHG emissions during the entire life cycle). We calculate the nitrous oxide (N₂O) emissions by applying a statistical model that uses spatial data on climate and soil. For the land use that is assumed to be replaced by energy crop production (the ‘reference land‐use system’), we explore a variety of options, the most important of which are cropland for food production, grassland, and natural vegetation. Calculations are also done in the case that emissions due to energy crop production are fully additional and thus no reference is considered. The results are combined with data on other emissions due to biofuels production that are derived from existing studies, resulting in total GHG emission reduction potentials for major biofuels compared with conventional fuels. The results show that N₂O emissions can have an important impact on the overall GHG balance of biofuels, though there are large uncertainties. The most important ones are those in the statistical model and the GHG emissions not related to land use. Ethanol produced from sugar cane and sugar beet are relatively robust GHG savers: these biofuels change the GHG emissions by −103% to −60% (sugar cane) and −58% to −17% (sugar beet), compared with conventional transportation fuels and depending on the reference land‐use system that is considered. The use of diesel from palm fruit also results in a relatively constant and substantial change of the GHG emissions by −75% to −39%. For corn and wheat ethanol, the figures are −38% to 11% and −107% to 53%, respectively. Rapeseed diesel changes the GHG emissions by −81% to 72% and soybean diesel by −111% to 44%. Optimized crop management, which involves the use of state‐of‐the‐art agricultural technologies combined with an optimized fertilization regime and the use of nitrification inhibitors, can reduce N₂O emissions substantially and change the GHG emissions by up to −135 percent points (pp) compared with conventional management. However, the uncertainties in the statistical N₂O emission model and in the data on non‐land‐use GHG emissions due to biofuels production are large; they can change the GHG emission reduction by between −152 and 87 pp.     

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.     

Soil greenhouse gas fluxes and global warming potential in four high-yielding maize systems

Crop intensification is often thought to increase greenhouse gas (GHG) emissions, but studies in which crop management is optimized to exploit crop yield potential are rare. We conducted a field study in eastern Nebraska, USA to quantify GHG emissions, changes in soil organic carbon (SOC) and the net global warming potential (GWP) in four irrigated systems: continuous maize with recommended best management practices (CC‐rec) or intensive management (CC‐int) and maize–soybean rotation with recommended (CS‐rec) or intensive management (CS‐int). Grain yields of maize and soybean were generally within 80–100% of the estimated site yield potential. Large soil surface carbon dioxide (CO₂) fluxes were mostly associated with rapid crop growth, high temperature and high soil water content. Within each crop rotation, soil CO₂ efflux under intensive management was not consistently higher than with recommended management. Owing to differences in residue inputs, SOC increased in the two continuous maize systems, but decreased in CS‐rec or remained unchanged in CS‐int. N₂O emission peaks were mainly associated with high temperature and high soil water content resulting from rainfall or irrigation events, but less clearly related to soil NO₃‐N levels. N₂O fluxes in intensively managed systems were only occasionally greater than those measured in the CC‐rec and CS‐rec systems. Fertilizer‐induced N₂O emissions ranged from 1.9% to 3.5% in 2003, from 0.8% to 1.5% in 2004 and from 0.4% to 0.5% in 2005, with no consistent differences among the four systems. All four cropping systems where net sources of GHG. However, due to increased soil C sequestration continuous maize systems had lower GWP than maize–soybean systems and intensive management did not cause a significant increase in GWP. Converting maize grain to ethanol in the two continuous maize systems resulted in a net reduction in life cycle GHG emissions of maize ethanol relative to petrol‐based gasoline by 33–38%. Our study provided evidence that net GHG emissions from agricultural systems can be kept low when management is optimized toward better exploitation of the yield potential. Major components for this included (i) choosing the right combination of adopted varieties, planting date and plant population to maximize crop biomass productivity, (ii) tactical water and nitrogen (N) management decisions that contributed to high N use efficiency and avoided extreme N₂O emissions, and (iii) a deep tillage and residue management approach that favored the build‐up of soil organic matter from large amounts of crop residues returned.     

Greenhouse gas mitigation in agriculture

Agricultural lands occupy 37% of the earth's land surface. Agriculture accounts for 52 and 84% of global anthropogenic methane and nitrous oxide emissions. Agricultural soils may also act as a sink or source for CO2, but the net flux is small. Many agricultural practices can potentially mitigate greenhouse gas (GHG) emissions, the most prominent of which are improved cropland and grazing land management and restoration of degraded lands and cultivated organic soils. Lower, but still significant mitigation potential is provided by water and rice management, set-aside, land use change and agroforestry, livestock management and manure management. The global technical mitigation potential from agriculture (excluding fossil fuel offsets from biomass) by 2030, considering all gases, is estimated to be approximately 5500-6000Mt CO2-eq.yr-1, with economic potentials of approximately 1500-1600, 2500-2700 and 4000-4300Mt CO2-eq.yr-1 at carbon prices of up to 20, up to 50 and up to 100 US$ t CO2-eq.-1, respectively. In addition, GHG emissions could be reduced by substitution of fossil fuels for energy production by agricultural feedstocks (e.g. crop residues, dung and dedicated energy crops). The economic mitigation potential of biomass energy from agriculture is estimated to be 640, 2240 and 16 000Mt CO2-eq.yr-1 at 0-20, 0-50 and 0-100 US$ t CO2-eq.-1, respectively.     

Uncertainty Analysis in Biofuel Systems

This article evaluates the implications of uncertainty in the life cycle (LC) energy efficiency and greenhouse gas (GHG) emissions of rapeseed oil (RO) as an energy carrier displacing fossil diesel (FD). Uncertainties addressed include parameter uncertainty as well as scenario uncertainty concerning how RO coproduct credits are accounted for (uncertainty due to modeling choices). We have carried out an extensive data collection to build an LC inventory accounting for parameter uncertainty. Different approaches for carbon stock changes associated with converting set‐aside land to rapeseed cultivation have been considered, which result in different values: from ?0.25 t C/ha.yr (carbon uptake by the soil in tonnes per hectare year) to 0.60 t C/ha.yr (carbon emission). Energy renewability efficiency and GHG emissions of RO are presented, which show the influence of parameter versus scenario uncertainty. Primary energy savings and avoided GHG emissions when RO displaces FD have also been calculated: Avoided GHG emissions show considerably higher uncertainty than energy savings, mainly due to land use (nitrous oxide emissions from soil) and land use conversion (carbon stock changes). Results demonstrate the relevance of applying uncertainty approaches; emphasize the need to reduce uncertainty in the environmental life cycle modeling, particularly GHG emissions calculation; and show the importance of integrating uncertainty into the interpretation of results.     

Soil Greenhouse Gas Emissions in Response to Corn Stover Removal and Tillage Management Across the US Corn Belt

In-field measurements of direct soil greenhouse gas (GHG) emissions provide critical data for quantifying the net energy efficiency and economic feasibility of crop residue-based bioenergy production systems. A major challenge to such assessments has been the paucity of field studies addressing the effects of crop residue removal and associated best practices for soil management (i.e., conservation tillage) on soil emissions of carbon dioxide (CO₂), nitrous oxide (N₂O), and methane (CH₄). This regional survey summarizes soil GHG emissions from nine maize production systems evaluating different levels of corn stover removal under conventional or conservation tillage management across the US Corn Belt. Cumulative growing season soil emissions of CO₂, N₂O, and/or CH₄ were measured for 2–5 years (2008–2012) at these various sites using a standardized static vented chamber technique as part of the USDA-ARS’s Resilient Economic Agricultural Practices (REAP) regional partnership. Cumulative soil GHG emissions during the growing season varied widely across sites, by management, and by year. Overall, corn stover removal decreased soil total CO₂ and N₂O emissions by -4 and -7 %, respectively, relative to no removal. No management treatments affected soil CH₄ fluxes. When aggregated to total GHG emissions (Mg CO₂?eq ha^?1) across all sites and years, corn stover removal decreased growing season soil emissions by ?5?±?1 % (mean?±?se) and ranged from -36 % to 54 % (n?=?50). Lower GHG emissions in stover removal treatments were attributed to decreased C and N inputs into soils, as well as possible microclimatic differences associated with changes in soil cover. High levels of spatial and temporal variabilities in direct GHG emissions highlighted the importance of site-specific management and environmental conditions on the dynamics of GHG emissions from agricultural soils.     

Land management change greatly impacts biofuels’ greenhouse gas emissions

Harvesting corn stover for biofuel production may decrease soil organic carbon (SOC) and increase greenhouse gas (GHG) emissions. Adding additional organic matter into soil or reducing tillage intensity, however, could potentially offset this SOC loss. Here, using SOC and life cycle analysis (LCA) models, we evaluated the impacts of land management change (LMC), that is, stover removal, organic matter addition, and tillage on spatially explicit SOC level and biofuels’ overall life cycle GHG emissions in US corn–soybean production systems. Results indicate that under conventional tillage (CT), 30% stover removal (dry weight) may reduce baseline SOC by 0.04 t C ha^?1 yr^?1 over a 30‐year simulation period. Growing a cover crop during the fallow season or applying manure, on the other hand, could add to SOC and further reduce biofuels’ life cycle GHG emissions. With 30% stover removal in a CT system, cover crop and manure application can increase SOC at the national level by about 0.06 and 0.02 t C ha^?1 yr^?1, respectively, compared to baseline cases without such measures. With contributions from this SOC increase, the life cycle GHG emissions for stover ethanol are more than 80% lower than those of gasoline, exceeding the US Renewable Fuel Standard mandate of 60% emissions reduction in cellulosic biofuels. Reducing tillage intensity while removing stover could also limit SOC loss or lead to SOC gain, which would lower stover ethanol life cycle GHG emissions to near or under the mandated 60% reduction. Without these organic matter inputs or reduced tillage intensity, however, the emissions will not meet this mandate. More efforts are still required to further identify key practical LMCs, improve SOC modeling, and accounting for LMCs in biofuel LCAs that incorporate stover removal.     

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.     

Surfactants Based on Renewable Raw Materials

Under the European Commission's European Climate Change Programme, a group of experts studied the possibilities of using more renewable raw materials as chemical feedstock and assessed the related potential for greenhouse gas (GHG) emission reduction. Surfactants were among the products studied. Surfactants are currently produced from both petro-chemical feedstocks and renewable resources (oleochemical surfactants). Assuming, in a first step, that total surfactant production in the European Union remains constant until 2010, it was estimated that the amount of oleochemical surfactants could be increased from about 880 kilotons (kt) in 1998 to approximately 1, 100 kt in 2010 (an increase of 24%). This substitution reduces the life-cycle CO₂ emissions from surfactants by 8%; the theoretical maximum potential for total substitution is 37%. Because the surfactant market is expected to grow, the avoided emissions will probably exceed 8% of the current life-cycle CO₂ emissions from surfactants. If compared to the CO₂ emissions from the total industrial sector and, even more so, if compared to the total economy, the relative savings are much lower (0.02% to 0.09%). This leads to the conclusion that the increased production and use of biobased surfactants should be part of an overall GHG emission reduction strategy consisting of a whole range of measures addressing both energy demand and supply. This article also discusses policies and measures designed to increase the use of biobased surfactants.     

Solving the multifunctionality dilemma in biorefineries with a novel hybrid mass–energy allocation method

Processing biomass into multifunctional products can contribute to food, feed, and energy security while also mitigating climate change. However, biorefinery products nevertheless impact the environment, and this influence needs to be properly assessed to minimize the burden. Life cycle assessment (LCA) is often used to calculate environmental footprints of products, but distributing the burdens among the different biorefinery products is a challenge. A particular complexity arises when the outputs are a combination of energy carrying no mass, and mass carrying no energy, where neither an allocation based on mass nor on energy would be appropriate. A novel hybrid mass–energy (HMEN) allocation scheme for dealing with multifunctionality problems in biorefineries was developed and applied to five biorefinery concepts. The results were compared to results of other allocation methods in LCA. The reductions in energy use and GHG emissions from using the biorefinery's biofuels were also quantified. HMEN fairly distributed impacts among biorefinery products and did not change the order of the products in terms of the level of the pollution caused. The allocation factors for HMEN fell between mass and economic allocation factors and were comparable to energy allocation factors. Where the mass or the energy allocation failed to attribute burdens, HMEN addressed this shortcoming by assigning impacts to nonmass or to nonenergy products. Under the partitioning methods and regardless of the feedstock used, bioethanol reduced GHG by 72–98% relative to gasoline. The GHG savings were 196% under the substitution method, but no GHG savings occurred for sugar beet bioethanol under the surplus method. Bioethanol from cellulosic crops had lower energy use and GHG emissions than from sugar beet, regardless of the allocation method used. HMEN solves multifunctional problems in biorefineries and can be applied to other complex refinery systems. LCA practitioners are encouraged to further test this method in other case studies.     

Economic Assessment of Greenhouse Gas Emissions Reduction by Vehicle Lightweighting Using Aluminum and High‐Strength Steel

The life cycle greenhouse gas (GHG) reduction benefits of vehicle lightweighting (LW) were evaluated in a companion article. This article provides an economic assessment of vehicle LW with aluminum and high‐strength steel. Relevant cost information taken from the literature is synthesized, compiled, and formed into estimates of GHG reduction costs through LW. GHG emissions associated with vehicle LW scenarios between 6% and 23% are analyzed alongside vehicle life cycle costs to achieve these LW levels. We use this information to estimate the cost to remove GHG emissions per metric ton by LW, and we further calculate the difference between added manufacturing cost and fuel cost savings from LW. The results show greater GHG savings derived from greater LW and added manufacturing costs as expected. The associated production costs are, however, disproportionately higher than the fuel cost savings associated with higher LW options. A sensitivity analysis of different vehicle classes confirms that vehicle LW is more cost‐effective for larger vehicles. Also, the cost of GHG emissions reductions through lightweighting is compared with alternative GHG emissions reduction technologies for passenger vehicles, such as diesel, hybrid, and plug‐in hybrid electric powertrains. The results find intensive LW to be a competitive and complementary approach relative to the technological alternatives within the automotive industry but more costly than GHG mitigation strategies available to other industries.     

Effects of E-Commerce on Greenhouse Gas Emissions: A Case Study of Grocery Home Delivery in Finland

In this article, we present a literature review of the general and environmental effects of e-commerce in various parts of the demand-supply chain. These are further translated into effects on greenhouse gas (GHG) emissions in the food production and consumption system. The literature study revealed many opportunities for e-commerce to reduce GHG emissions in the food production and consumption system. Some possibly negative effects were also identified. Electronic grocery shopping (e-grocery) home delivery service was chosen as the subject of a case study because of its direct and indirect potential for reducing the GHG emissions in the food production and consumption system.
GHG emission reduction potential through the implementation of various e-grocery home delivery strategies was quantified. Depending on the home delivery model used, it is possible to reduce the GHG emissions generated by grocery shopping by 18% to 87% compared with the situation in which household members go to the store themselves. We estimate that the maximum theoretical potential of e-grocery home delivery service for reducing the GHG emissions of Finland is roughly 0.3% to 1.3%; however, the current and estimated future market potential is much smaller, because the estimated market share of e-grocery services is only 10% by 2005. Narrowing the gap between the theoretical and the actual potential requires a model that would simultaneously provide additional value to the consumer and be profitable to companies. To be able to achieve significant reductions in GHG emissions, system-level innovations and changes are required. Further research is needed before conclusions can be reached as to whether e-commerce and e-grocery are useful tools in that respect.     

Integration in a depot‐based decentralized biorefinery system: Corn stover‐based cellulosic biofuel

The current or “conventional” paradigm for producing process energy in a biorefinery processing cellulosic biomass is on‐site energy recovery through combustion of residual solids and biogas generated by the process. Excess electricity is then exported, resulting in large greenhouse gas (GHG) credits. However, this approach will cause lifecycle GHG emissions of biofuels to increase as more renewable energy sources (wind, solar, etc.) participate in grid‐electricity generation, and the GHG credits from displacing fossil fuel decrease. To overcome this drawback, a decentralized (depot‐based) biorefinery can be integrated with a coal‐fired power plant near a large urban area. In an integrated, decentralized, depot‐based biorefinery (IDB), the residual solids are co‐fired with coal either in the adjacent power plant or in coal‐fired boilers elsewhere to displace coal. An IDB system does not rely on indirect GHG credits through grid‐electricity displacement. In an IDB system, biogas from the wastewater treatment facility is also upgraded to biomethane and used as a transportation biofuel. The GHG savings per unit of cropland in the IDB systems (2.7–2.9 MgCO₂/ha) are 1.5–1.6 fold greater than those in a conventional centralized system (1.7–1.8 MgCO₂/ha). Importantly, the biofuel selling price in the IDBs is lower by 28–30 cents per gasoline‐equivalent liter than in the conventional centralized system. Furthermore, the total capital investment per annual biofuel volume in the IDB is much lower (by ~80%) than that in the conventional centralized system. Therefore, utilization of biomethane and residual solids in the IDB systems leads to much lower biofuel selling prices and significantly greater GHG savings per unit of cropland participating in the biorefinery system compared to the conventional centralized biorefineries.     

Evaluation of the effect of accounting method,IPCC v. LCA,on grass-based and confinement dairy systems’ greenhouse gas emissions

Life cycle assessment (LCA) and the Intergovernmental Panel on Climate Change (IPCC) guideline methodology, which are the principal greenhouse gas (GHG) quantification methods, were evaluated in this study using a dairy farm GHG model. The model was applied to estimate GHG emissions from two contrasting dairy systems: a seasonal calving pasture-based dairy farm and a total confinement dairy system. Data used to quantify emissions from these systems originated from a research study carried out over a 1-year period in Ireland. The genetic merit of cows modelled was similar for both systems. Total mixed ration was fed in the Confinement system, whereas grazed grass was mainly fed in the grass-based system. GHG emissions from these systems were quantified per unit of product and area. The results of both methods showed that the dairy system that emitted the lowest GHG emissions per unit area did not necessarily emit the lowest GHG emissions possible for a given level of product. Consequently, a recommendation from this study is that GHG emissions be evaluated per unit of product given the growing affluent human population and increasing demand for dairy products. The IPCC and LCA methods ranked dairy systems’ GHG emissions differently. For instance, the IPCC method quantified that the Confinement system reduced GHG emissions per unit of product by 8% compared with the grass-based system, but the LCA approach calculated that the Confinement system increased emissions by 16% when off-farm emissions associated with primary dairy production were included. Thus, GHG emissions should be quantified using approaches that quantify the total GHG emissions associated with the production system, so as to determine whether the dairy system was causing emissions displacement. The IPCC and LCA methods were also used in this study to simulate, through a dairy farm GHG model, what effect management changes within both production systems have on GHG emissions. The findings suggest that single changes have a small mitigating effect on GHG emissions (<5%), except for strategies used to control emissions from manure storage in the Confinement system (14% to 24%). However, when several management strategies were combined, GHG emissions per unit of product could be reduced significantly (15% to 30%). The LCA method was identified as the preferred approach to assess the effect of management changes on GHG emissions, but the analysis indicated that further standardisation of the approach is needed given the sensitivity of the approach to allocation decisions regarding milk and meat.     

Dry Matter Losses and Methane Emissions During Wood Chip Storage: the Impact on Full Life Cycle Greenhouse Gas Savings of Short Rotation Coppice Willow for Heat

A life cycle assessment (LCA) approach was used to examine the greenhouse gas (GHG) emissions and energy balance of short rotation coppice (SRC) willow for heat production. The modelled supply chain includes cutting multiplication, site establishment, maintenance, harvesting, storage, transport and combustion. The relative impacts of dry matter losses and methane emissions from chip storage were examined from a LCA perspective, comparing the GHG emissions from the SRC supply chain with those of natural gas for heat generation. The results show that SRC generally provides very high GHG emission savings of over 90 %. The LCA model estimates that a 1, 10 and 20 % loss of dry matter during storage causes a 1, 6 and 11 % increase in GHG emissions per MWh. The GHG emission results are extremely sensitive to emissions of methane from the wood chip stack: If 1 % of the carbon within the stack undergoes anaerobic decomposition to methane, then the GHG emissions per MWh are tripled. There are some uncertainties in the LCA results, regarding the true formation of methane in wood chip stacks, non-CO₂ emissions from combustion, N₂O emissions from leaf fall and the extent of carbon sequestered under the crop, and these all contribute a large proportion of the life cycle GHG emissions from cultivation of the crop.     

Life Cycle Greenhouse Gas Emissions Reduction From Rigid Thermal Insulation Use in Buildings

Thermal insulation is a strategic product for reducing energy consumption and related greenhouse gas (GHG) emissions from the building sector. This study examines from a life cycle perspective the changes in GHG emissions resulting from the use of two rigid thermal insulation products manufactured and installed from 1971 to 2025. GHG emissions related to insulation production and fugitive releases of blowing agents are modeled and compared with GHG savings from reduced heating loads in North America, Europe, and Asia. Implementation of alternative blowing agents has greatly improved the carbon dioxide 100‐year equivalent (CO₂‐eq) emission performance of thermal insulation. The net average CO₂‐eq savings to emissions ratio for current extruded polystyrene (XPS) and polyisocyanurate (PIR) insulation studied was 48:1, with a broad range from 3 to 1,800. Older insulation products manufactured with chlorofluorocarbons (CFCs) can result in net cumulative GHG emissions. Reduction of CO₂‐eq emissions from buildings is governed by complex interactions between insulation thickness and placement, climate, fuel type, and heating system efficiencies. A series of charts mapping both emissions payback and net savings demonstrate the interactions between these factors and provide a basis for specific policy recommendations to guide effective insulation investments and placement.     

Environmental and economic analysis of the fully integrated biorefinery

Cellulosic biofuel systems have the potential to significantly reduce the environmental impact of the world's transportation energy requirements. However, realizing this potential will require systems level thinking and scale integration. Until now, we have lacked modeling tools for studying the behavior of integrated cellulosic biofuel systems. In this paper, we describe a new research tool, the Biorefinery and Farm Integration Tool (BFIT) in which the production of fuel ethanol from cellulosic biomass is integrated with crop and animal (agricultural) production models. Uniting these three subsystems in a single combined model has allowed, for the first time, basic environmental and economic analysis of biomass production, possible secondary products, fertilizer production, and bioenergy production across various regions of the United States. Using BFIT, we simulate cellulosic ethanol production embedded in realistic agricultural landscapes in nine locations under a collection of farm management scenarios. This combined modeling approach permits analysis of economic profitability and highlights key areas for environmental improvement. These results show the advantages of introducing integrated biorefinery systems within agricultural landscapes. This is particularly true in the Midwest, which our results suggest is a good setting for the cellulosic ethanol industry. Specifically, results show that inclusion of cellulosic biofuel systems into existing agriculture enhances farm economics and reduces total landscape emissions. Model results also indicate a limited ethanol price effect from increased biomass transportation distance. Sensitivity analysis using BFIT revealed those variables having the strongest effects on the overall system performance, namely: biorefinery size, switchgrass yield, and biomass farm gate price.     

An integrative modeling framework to evaluate the productivity and sustainability of biofuel crop production systems

The potential expansion of biofuel production raises food, energy, and environmental challenges that require careful assessment of the impact of biofuel production on greenhouse gas (GHG) emissions, soil erosion, nutrient loading, and water quality. In this study, we describe a spatially explicit integrative modeling framework (SEIMF) to understand and quantify the environmental impacts of different biomass cropping systems. This SEIMF consists of three major components: (1) a geographic information system (GIS)‐based data analysis system to define spatial modeling units with resolution of 56 m to address spatial variability, (2) the biophysical and biogeochemical model Environmental Policy Integrated Climate (EPIC) applied in a spatially‐explicit way to predict biomass yield, GHG emissions, and other environmental impacts of different biofuel crops production systems, and (3) an evolutionary multiobjective optimization algorithm for exploring the trade‐offs between biofuel energy production and unintended ecosystem‐service responses. Simple examples illustrate the major functions of the SEIMF when applied to a nine‐county Regional Intensive Modeling Area (RIMA) in SW Michigan to (1) simulate biofuel crop production, (2) compare impacts of management practices and local ecosystem settings, and (3) optimize the spatial configuration of different biofuel production systems by balancing energy production and other ecosystem‐service variables. Potential applications of the SEIMF to support life cycle analysis and provide information on biodiversity evaluation and marginal‐land identification are also discussed. The SEIMF developed in this study is expected to provide a useful tool for scientists and decision makers to understand sustainability issues associated with the production of biofuels at local, regional, and national scales.     

Direct and indirect impacts of crop–livestock organization on mixed crop–livestock systems sustainability: a model-based study

Crop–livestock production is claimed more sustainable than specialized production systems. However, the presence of controversial studies suggests that there must be conditions of mixing crop and livestock productions to allow for higher sustainable performances. Whereas previous studies focused on the impact of crop–livestock interactions on performances, we posit here that crop–livestock organization is a key determinant of farming system sustainability. Crop–livestock organization refers to the percentage of the agricultural area that is dedicated to each production. Our objective is to investigate if crop–livestock organization has both a direct and an indirect impact on mixed crop–livestock (MC–L) sustainability. In that objective, we build a whole-farm model parametrized on representative French sheep and crop farming systems in plain areas (Vienne, France). This model permits simulating contrasted MC–L systems and their subsequent sustainability through the following indicators of performance: farm income, production, N balance, greenhouse gas (GHG) emissions (/kg product) and MJ consumption (/kg product). Two MC–L systems were simulated with contrasted crop–livestock organizations (MC₂₀–L₈₀: 20% of crops; MC₈₀–L₂₀: 80% of crops). A first scenario – constraining no crop–livestock interactions in both MC–L systems – permits highlighting that crop–livestock organization has a significant direct impact on performances that implies trade-offs between objectives of sustainability. Indeed, the MC₈₀–L₂₀ system is showing higher performances for farm income (+44%), livestock production (+18%) and crop GHG emissions (−14%) whereas the MC₂₀–L₈₀ system has a better N balance (−53%) and a lower livestock MJ consumption (−9%). A second scenario – allowing for crop–livestock interactions in both MC₂₀–L₈₀ and MC₈₀–L₂₀ systems – stated that crop–livestock organization has a significant indirect impact on performances. Indeed, even if crop–livestock interactions permit improving performances, crop–livestock organization influences the capacity of MC–L systems to benefit from crop–livestock interactions. As a consequence, we observed a decreasing performance trade-off between MC–L systems for farm income (−4%) and crop GHG emissions (−10%) whereas the gap increases for nitrogen balance (+23%), livestock production (+6%) – MJ consumption (+16%) – GHG emissions (+5%) and crop MJ consumption (+5%). However, the indirect impact of crop–livestock organization doesn’t reverse the trend of trade-offs between objectives of sustainability determined by the direct impact of crop–livestock organization. As a conclusion, crop–livestock organization is a key factor that has to be taken into account when studying the sustainability of mixed crop–livestock systems.