Evaluating the environmental performance of producing soil and surfaces through industrial symbiosis

Industrial symbiosis (IS), where different entities collaborate in the management of energy, utilities, materials, or services, has been identified as an approach to improve resource efficiency and circularity in industry. This article assesses the environmental performance of an IS network with firms involved in waste management, soil, surfaces, paper, lumber, and energy. The aim is to highlight the environmental performance of an IS network and pay particular attention to the improved performance for products in the IS network. Life cycle assessment is used to compare the current IS network with a reference scenario and a potential future development. The results suggest that there are significant benefits from the IS network. Large reductions in greenhouse gas (GHG) emissions and abiotic resource depletion were identified. Furthermore, large reductions in local impacts, namely eutrophication and acidification impacts are illustrated. It was shown that all firms in the network benefit from the synergies involved, with a large share of the benefits stemming from the facilitated exchanges with the waste management company. The replacement of conventional products and energy streams with bio‐based counterparts from within the network is of significant importance. Finally, the results point to the importance of the facilitation of by‐product synergies, and the significant value this creates in the region, with large potential to improve the environmental performance of firms and their products.     

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.     

Industrial symbiosis in the forestry sector: A case study in southern Brazil

Industrial symbiosis (IS) is an important concept in the field of industrial ecology that has disseminated worldwide as a practice to decrease the ecological impact of industrial processes through the exchange of by‐products and waste between units in a system. The forestry industry is the main economic activity in the region of Lages in southern Brazil. IS relationships have expanded with the use of waste material from wood processing and strengthened cooperation between companies in different sectors. The aims of this article were to: a) quantify the level of IS in the system, b) identify the benefits of IS for participants, and c) explain why the network further developed IS to the formation of an industrial ecosystem. A questionnaire was administered during visits to 24 forestry companies in order to analyze their products and processes, commercial relations, positive impacts, and local insertion. The industrial symbiosis indicator (ISI) was determined using waste stream data from the system to represent the level of symbiosis among the companies in this region. The results show that the companies participate in a symbiotic network, mainly involving the exchange of chips, bark, sawdust and shavings. In most cases, these exchanges occur between nearby companies, constituting an extensive industrial ecosystem.     

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.     

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.     

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.     

Material Flow Optimization in By‐product Synergy Networks

By‐product synergy (BPS) is an industrial ecology practice that involves utilization of industrial by‐products as feedstocks for other industrial processes. A novel decision support tool is developed to analyze BPS networks that involve material processing and transport among regional clusters of companies. Mathematical programming techniques are used to determine the optimal network design and the material flows that minimize total cost or environmental impacts. This methodology is incorporated into a graphical software package called Eco‐Flow?. The tool has been applied to model and analyze available synergies in an existing BPS network centered in Kansas City, Missouri. A base case, which assumes no synergies, is compared with the optimal BPS solution found by Eco‐Flow?. The results for Kansas City suggest that when companies in the network cooperate to optimize the system profitability, up to $15 million per year of savings are possible. The findings also indicate that the BPS approach would result in 29% reduction in total cost, 25.8% reduction in average company cost, 30% reduction in carbon dioxide (CO₂) emissions, and 37% reduction in waste to landfill. The modeling approach is being extended to better represent the dynamics of industrial and ecological processes.     

Effects of Using Heterogeneous Prices on the Allocation of Impacts from Electricity Use: A Mixed‐Unit Input‐Output Approach

Economic input‐output life cycle assessment (IO‐LCA) models allow for quick estimation of economy‐wide greenhouse gas (GHG) emissions associated with goods and services. IO‐LCA models are usually built using economic accounts and differ from most process‐based models in their use of economic transactions, rather than physical flows, as the drivers of supply‐chain GHG emissions. GHG emissions estimates associated with input supply chains are influenced by the price paid by consumers when the relative prices between individual consumers are different. We investigate the significance of the allocation of GHG emissions based on monetary versus physical units by carrying out a case study of the U.S. electricity sector. We create parallel monetary and mixed‐unit IO‐LCA models using the 2007 Benchmark Accounts of the U.S. economy and sector specific prices for different end users of electricity. This approach is well suited for electricity generation because electricity consumption contributes a significant share of emissions for most processes, and the range of prices paid by electricity consumers allows us to explore the effects of price on allocation of emissions. We find that, in general, monetary input‐output models assign fewer emissions per kilowatt to electricity used by industrial sectors than to electricity used by households and service sectors, attributable to the relatively higher prices paid by households and service sectors. This fact introduces a challenging question of what is the best basis for allocating the emissions from electricity generation given the different uses of electricity by consumers and the wide variability of electricity pricing.     

Greenhouse Gas Emissions Reduction Opportunities for Concrete Pavements

Concrete pavements are a vital part of the transportation infrastructure, comprising nearly 25% of the interstate network in the United States. With transportation authorities and industry organizations increasingly seeking out methods to reduce their carbon footprint, there is a need to identify and quantitatively evaluate the greenhouse gas (GHG) emission reduction opportunities that exist in the concrete pavement life cycle. A select few of these opportunities are explored in this article in order to represent possible reduction approaches and their associated cost‐effectiveness: reducing embodied emissions by increasing fly ash content and by avoiding overdesign; increasing albedo by using white aggregates; increasing carbonation by temporarily stockpiling recycled concrete aggregates; and reducing vehicle fuel consumption by adding an extra rehabilitation. These reduction strategies are evaluated for interstate, arterial, collector, and local road designs under urban and rural scenarios. The results indicate that significant GHG emission reductions are possible, with over half of the scenarios resulting in 10% reductions, compared to unimproved baseline designs. Given the right conditions, each scenario has the potential to reduce GHG emissions at costs comparable to the current price of carbon.     

Carbon Footprint Assessment of a Paperback Book

This study presents the carbon footprint of a paperback book for which the cover and inside papers were produced in the United States and printed in Canada. The choice of paper mills for both cover and page papers was based on criteria such as percentage of recycled content in the pulp mix, transport distances (pulp mill to paper mill, paper mill to print), and technologies. The cradle‐to‐gate assessment of greenhouse gas (GHG) emissions follows recognized guidelines for carbon footprint assessment. The results show that the production of 400,000 books, mainly distributed in North America, would generate 1,084 tonnes carbon dioxide equivalent (CO₂‐eq), or 2.71 kilograms (kg) CO₂‐eq per book. The impact of using deinked market pulp (DMP) is shown here to be detrimental, accounting for 54% of total GHG emissions and being 32% higher than reference virgin Kraft pulp. This supports findings that DMP mill GHG emissions strongly correlate with the carbon intensity of the power grid supplying the pulp mill and that virgin Kraft mills that reuse wood residue and black liquor to produce heat and electricity can achieve lower GHG emissions per tonne of pulp produced. Although contrary to common thinking, this is consistent with the Paper Task Force 2002 conclusion for office paper (the closest paper grade to writing paper or fine paper) (EDF 2002a). To get a cradle‐to‐grave perspective, three different end‐of‐life (EOL) scenarios were analyzed, all of which included a harvested wood product (HWP) carbon storage benefit for 25 years. The GHG offset concept within the context of the book editor's “carbon‐neutral” paper claims is also discussed.     

Life Cycle–based Assessment of Energy Use and Greenhouse Gas Emissions in Almond Production,Part I: Analytical Framework and Baseline Results

This first article of a two‐article series describes a framework and life cycle–based model for typical almond orchard production systems for California, where more than 80% of commercial almonds on the world market are produced. The comprehensive, multiyear, life cycle–based model includes orchard establishment and removal; field operations and inputs; emissions from orchard soils; and transport and utilization of co‐products. These processes are analyzed to yield a life cycle inventory of energy use, greenhouse gas (GHG) emissions, criteria air pollutants, and direct water use from field to factory gate. Results show that 1 kilogram (kg) of raw almonds and associated co‐products of hulls, shells, and woody biomass require 35 megajoules (MJ) of energy and result in 1.6 kg carbon dioxide equivalent (CO₂‐eq) of GHG emissions. Nitrogen fertilizer and irrigation water are the dominant causes of both energy use and GHG emissions. Co‐product credits play an important role in estimating the life cycle environmental impacts attributable to almonds alone; using displacement methods results in net energy and emissions of 29 MJ and 0.9 kg CO₂‐eq/kg. The largest sources of credits are from orchard biomass and shells used in electricity generation, which are modeled as displacing average California electricity. Using economic allocation methods produces significantly different results; 1 kg of almonds is responsible for 33 MJ of energy and 1.5 kg CO₂‐eq emissions. Uncertainty analysis of important parameters and assumptions, as well as temporary carbon storage in orchard trees and soils, are explored in the second article of this two‐part article series.     

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.     

Fuel Economy and Greenhouse Gas Emissions Labeling for Plug‐In Hybrid Vehicles from a Life Cycle Perspective

Fuel economy has been an effective indicator of vehicle greenhouse gas (GHG) emissions for conventional gasoline‐powered vehicles due to the strong relationship between fuel economy and vehicle life cycle emissions. However, fuel economy is not as accurate an indicator of vehicle GHG emissions for plug‐in hybrid (PHEVs) and pure battery electric vehicles (EVs). Current vehicle labeling efforts by the U.S. Environmental Protection Agency (EPA) and Department of Transportation have been focused on providing energy and environmental information to consumers based on U.S. national average data. This article explores the effects of variations in regional grids and regional daily vehicle miles traveled (VMT) on the total vehicle life cycle energy and GHG emissions of electrified vehicles and compare these results with information reported on the label and on the EPA's fuel economy Web site. The model results suggest that only 25% of the life cycle emissions from a representative PHEV are reflected on current vehicle labeling. The results show great variation in total vehicle life cycle emissions due to regional grid differences, including an approximately 100 gram per mile life cycle GHG emissions difference between the lowest and highest electric grid regions and up to a 100% difference between the state‐specific emission values within the same electric grid regions. Unexpectedly, for two regional grids the life cycle GHG emissions were higher in electric mode than in gasoline mode. We recommend that labels include stronger language on their deficiencies and provide ranges for GHG emissions from vehicle charging in regional electricity grids to better inform consumers.     

Exploring the Use of Ecological Footprint in Life Cycle Impact Assessment

Ecological footprint (EF) is a metric that estimates human consumption of biological resources and products, along with generation of waste greenhouse gas (GHG) emissions in terms of appropriated productive land. There is an opportunity to better characterize land occupation and effects on the carbon cycle in life cycle assessment (LCA) models using EF concepts. Both LCA and EF may benefit from the merging of approaches commonly used separately by practitioners of these two methods. However, few studies have compared or integrated EF with LCA. The focus of this research was to explore methods for improving the characterization of land occupation within LCA by considering the EF method, either as a complementary tool or impact assessment method. Biofuels provide an interesting subject for application of EF in the LCA context because two of the most important issues surrounding biofuels are land occupation (changes, availability, and so on) and GHG balances, two of the impacts that EF is able to capture. We apply EF to existing fuel LCA land occupation and emissions data and project EF for future scenarios for U.S. transportation fuels. We find that LCA studies can benefit from lessons learned in EF about appropriately modeling productive land occupation and facilitating clear communication of meaningful results, but find limitations to the EF in the LCA context that demand refinement and recommend that EF always be used along with other indicators and metrics in product‐level assessments.     

Life cycle assessment of biofuels: Energy and greenhouse gas balances

The promotion of biofuels as energy for transportation in the industrialized countries is mainly driven by the perspective of oil depletion, the concerns about energy security and global warming. However due to sustainability constraints, biofuels will replace only 10 to 15% of fossil liquid fuels in the transport sector. Several governments have defined a minimum target of GHG emissions reduction for those biofuels that will be eligible to public incentives, for example a 35% emissions reduction in case of biofuels in Members States of the European Union. This article points out the significant biases in estimating GHG balances of biofuels stemming from modelling choices about system definition and boundaries, functional unit, reference systems and allocation methods. The extent to which these choices influence the results is investigated. After performing a comparison and constructive criticism of various modelling choices, the LCA of wheat-to-bioethanol is used as an illustrative case where bioethanol is blended with gasoline at various percentages (E5, E10 and E85). The performance of these substitution options is evaluated as well. The results show a large difference in the reduction of the GHG emissions with a high sensitivity to the following factors: the method used to allocate the impacts between the co-products, the type of reference systems, the choice of the functional unit and the type of blend. The authors come out with some recommendations for basing the estimation of energy and GHG balances of biofuels on principles such as transparency, consistency and accuracy.     

Implementing a Dynamic Life Cycle Assessment Methodology with a Case Study on Domestic Hot Water Production

This work contributes to the development of a dynamic life cycle assessment (DLCA) methodology by providing a methodological framework to link a dynamic system modeling method with a time‐dependent impact assessment method. This three‐step methodology starts by modeling systems where flows are described by temporal distributions. Then, a temporally differentiated life cycle inventory (TDLCI) is calculated to present the environmental exchanges through time. Finally, time‐dependent characterization factors are applied to the TDLCI to evaluate climate‐change impacts through time. The implementation of this new framework is illustrated by comparing systems producing domestic hot water (DHW) over an 80‐year period. Electricity is used to heat water in the first system, whereas the second system uses a combination of solar energy and gas to heat an equivalent amount of DHW at the same temperature. This comparison shows that using a different temporal precision (i.e., monthly vs. annual) to describe process flows can reverse conclusions regarding which case has the best environmental performance. Results also show that considering the timing of greenhouse gas (GHG) emissions reduces the absolute values of carbon footprint in the short‐term when compared with results from the static life cycle assessment. This pragmatic framework for the implementation of time in DLCA studies is proposed to help in the development of the methodology. It is not yet a fully operational scheme, and efforts are still required before DLCA can become state of practice.     

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.     

Fast Carbon Footprinting for Large Product Portfolios

Publicly Available Specification 2050‐2011 (PAS 2050), the Green House Gas Product Protocol (GHGPP) standard and forthcoming guideline 14067 from the International Organization for Standardization (ISO) have helped to propel carbon footprinting from a subdiscipline of life cycle assessment (LCA) to the mainstream. However, application of carbon footprinting to large portfolios of many distinct products and services is immensely resource intensive. Even if achieved, it often fails to inform company‐wide carbon reduction strategies because footprint data are disjointed or don't cover the whole portfolio. We introduce a novel approach to generate standard‐compliant product carbon footprints (CFs) for companies with large portfolios at a fraction of previously required time and expertise. The approach was developed and validated on an LCA dataset covering 1,137 individual products from a global packaged consumer goods company. Three novel techniques work in concert in a single approach that enables practitioners to calculate thousands of footprints virtually simultaneously: (i) a uniform data structure enables footprinting all products and services by looping the same algorithm; (ii) concurrent uncertainty analysis guides practitioners to gradually improve the accuracy of only those data that materially impact the results; and (iii) a predictive model generates estimated emission factors (EFs) for materials, thereby eliminating the manual mapping of a product or service's inventory to EF databases. These autogenerated EFs enable non‐LCA experts to calculate approximate CFs and alleviate resource constraints for companies embarking on large‐scale product carbon footprinting. We discuss implementation roadmaps for companies, including further road‐testing required to evaluate the effectiveness of the approach for other product portfolios, limitations, and future improvements of the fast footprinting methodology.     

Using Nested Average Electricity Allocation Protocols to Characterize Electrical Grids in Life Cycle Assessment

This study explored the impacts of electricity allocation protocols on the life cycle greenhouse gas (GHG) emissions of electricity consumption. The selection of appropriate electricity allocation protocols, methodologies that assign pools of electricity generators to electricity consumers, has not been well standardized. This can lead to very different environmental profiles of similar, electricity‐intensive processes. In an effort to better represent the interconnected nature of the U.S. electrical grid, we propose two new protocols that utilize inter‐regional trade information and localized emission factors to combine generating pools that are sub‐ or supersets of one another. This new nested approach increases the likelihood of capturing important inter‐regional electricity trading and the appropriate assignment of generator emissions to consumers of local and regional electricity. We applied the new and existing protocols to the U.S. primary aluminum industry, an industry whose environmental impact is heavily tied to its electricity consumption. Our analysis found GHG emission factors that were dramatically different than those reported in previous literature. We calculated production‐weighted average emission factors of 19.0 and 19.9 kilograms carbon dioxide equivalent per kilogram of primary aluminum ingot produced when using our two nested electricity allocation protocols. Previous studies reported values of 10.5 and 11.0, at least 42% lower than those found by our study.