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.     

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.     

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.     

Contribution of Urban Water Supply to Greenhouse Gas Emissions in China

Greenhouse gas (GHG) emissions from energy use in the water sector in China have not received the same attention as emissions from other sectors, but interest in this area is growing. This study uses 2011 data to investigate GHG emissions from electricity use for urban water supply in China. The objective is to measure the climate cobenefit of water conservation, compare China with other areas on a number of emissions indicators, and assist in development of policy that promotes low‐emission water supply. Per capita and per unit GHG emissions for water supplied to urban areas in China in 2011 were 24.5 kilograms carbon dioxide equivalent (kg CO₂‐eq) per capita per year and 0.213 kg CO₂‐eq per cubic meter, respectively. Comparison of provinces within China revealed that GHG emissions for urban water supply as a percentage of total province‐wide emissions from electricity use correlate directly with the rate of leakage and water loss within the water distribution system. This highlights controlling leakage as a possible means of reducing the contribution of urban water supply to GHG emissions. An inverse correlation was established between GHG emissions per unit water and average per capita daily water use, which implies that water demand tends to be higher when per unit emissions are lower. China's high emission factor for electricity generation inflates emissions for urban water supply. Shifting from emissions‐intensive electricity sources is crucial to reducing emissions in the water supply sector.     

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.     

能源活动CO2排放不同核算方法比较和减排策略选择

能源活动CO₂排放是温室气体排放的最重要部分,这部分CO₂排放量的核算是温室气体清单编制和减排方案制定的关键和基础。采用直接法、电热终端法和隐含终端法核算了2009年中国能源消费的CO₂排放量,对不同核算法的CO₂排放部门分布、部门排放强度进行了比较,明确不同核算方法的差异和适用范围。采用电热终端法的核算结果定量分析了各产业部门和工业行业的经济增长和排放强度变化对中国能源活动CO₂排放增长的影响。结果表明,中国2009年隐含终端CO₂排放量为65.6亿t,略高于直接和电热终端CO₂排放量62.2亿t。3种核算方法的CO₂排放部门分布和排放强度有明显的差异:电、热力生产与供应业的直接排放占比为45.2%,而电热终端CO₂排放仅占4.5%;制造业的直接法、电热终端法和隐含终端法核算的CO₂排放占比分别为35.3% 、61.1%和65.5%,是终端能源消费CO₂排放最主要的部门;制造业、电热力生产与供应业和交通运输业的电热终端CO₂排放强度分别为2.166、1.72和1.622 t CO₂/万元GDP,是排放强度较高的部门。在产业部门中,制造业的色金属冶炼及压延加工业、非金属矿物制品业等5个行业以9.8%的经济增长贡献,排放了52.4%的CO₂,是产业结构调整、技术和工程减排的重点;服务业以7.2%的CO₂排放,贡献了38.4%的经济增长,应作为中国低碳经济优先发展的产业。     

Analysing the water and greenhouse gas effects of soya bean‐based biodiesel in five different regions

Bioenergy may have significant lower greenhouse gas (GHG) emission intensities compared to fossil alternatives, but concerns are raised that bioenergy would contribute to additional water scarcity. Therefore, the GHG intensity, water intensity and water‐related risks are analysed simultaneously for conventional diesel and soya bean‐based biodiesel from Argentina, Brazil, Unites States (U.S.), Thailand and Iran on a life cycle basis. The water‐related risks are estimated with a water scarcity—consumption matrix, which was recently developed. Results show that a significant share (9%‐38%) of the GHG emissions in all biodiesel cases is caused by soil N₂O emissions. In addition, the ranges in water consumption intensity for soya bean‐based biodiesel are considerably larger than for fossil fuels. However, whether this leads to high water‐related risks depends on the local water scarcity. Soya bean‐based biodiesel from Argentina has low water‐related risks to all nodes of the supply chain due to low local water stress combined with a low direct water consumption intensity (20 L/GJ_fuel). In addition, high GHG emission reduction (71%) and a low‐specific eutrophication potential (0.04 kg PO₄^3?/GJ_fuel) are achieved. The indirect water consumption intensity is estimated at 120–420 L/GJ for soya bean‐based biodiesel, which is significant if the soya beans are rainfed, like in Argentina and Brazil. If irrigation is required, indirect water consumption is dwarfed by irrigation water. Overall, it is concluded that soya bean‐based biodiesel can have significant lower GHG emission intensity than fossil diesel, without causing additional water stress in the supply chain if they are produced in water abundant areas and good agricultural practices are used. The used method shows disaggregated water‐related risks for the different nodes of the supply chain to acknowledge the regional nature of water scarcity and enables decision makers to identify “hot spots” and take targeted actions.     

Implications of emissions timing on the cost‐effectiveness of greenhouse gas mitigation strategies: application to forest bioenergy systems

Conventional cost‐effectiveness calculations ignore the implications of greenhouse gas (GHG) emissions timing and thus may not properly inform decision‐makers in the efficient allocation of resources to mitigate climate change. To begin to address this disconnect with climate change science, we modify the conventional cost‐effectiveness approach to account for emissions timing. GHG emissions flows occurring over time are translated into an ‘Equivalent Present Emission’ based on radiative forcing, enabling a comparison of system costs and emissions on a consistent present time basis. We apply this ‘Present Cost‐Effectiveness’ method to case studies of biomass‐based electricity generation (biomass co‐firing with coal, biomass cogeneration) to evaluate implications of forest carbon trade‐offs on the cost‐effectiveness of emission reductions. Bioenergy production from forest biomass can reduce forest carbon stocks, an immediate emissions source that contributes to atmospheric greenhouse gases. Forest carbon impacts thereby lessen emission reductions in the near‐term relative to the assumption of biomass ‘carbon neutrality’, resulting in higher costs of emission reductions when emissions timing is considered. In contrast, conventional cost‐effectiveness approaches implicitly evaluate strategies over an infinite analytical time horizon, underestimating nearer term emissions reduction costs and failing to identify pathways that can most efficiently contribute to climate change mitigation objectives over shorter time spans (e.g. up to 100 years). While providing only a simple representation of the climate change implications of emissions timing, the Present Cost‐Effectiveness method provides a straightforward approach to assessing the cost‐effectiveness of emission reductions associated with any climate change mitigation strategy where future GHG reductions require significant initial capital investment or increase near‐term emissions. Timing is a critical factor in determining the attractiveness of any investment; accounting for emissions timing can better inform decisions related to the merit of alternative resource uses to meet near‐, mid‐, and long‐term climate change mitigation objectives.     

Wood pellets,what else? Greenhouse gas parity times of European electricity from wood pellets produced in the south‐eastern United States using different softwood feedstocks

Several EU countries import wood pellets from the south‐eastern United States. The imported wood pellets are (co‐)fired in power plants with the aim of reducing overall greenhouse gas (GHG) emissions from electricity and meeting EU renewable energy targets. To assess whether GHG emissions are reduced and on what timescale, we construct the GHG balance of wood‐pellet electricity. This GHG balance consists of supply chain and combustion GHG emissions, carbon sequestration during biomass growth and avoided GHG emissions through replacing fossil electricity. We investigate wood pellets from four softwood feedstock types: small roundwood, commercial thinnings, harvest residues and mill residues. Per feedstock, the GHG balance of wood‐pellet electricity is compared against those of alternative scenarios. Alternative scenarios are combinations of alternative fates of the feedstock materials, such as in‐forest decomposition, or the production of paper or wood panels like oriented strand board (OSB). Alternative scenario composition depends on feedstock type and local demand for this feedstock. Results indicate that the GHG balance of wood‐pellet electricity equals that of alternative scenarios within 0–21 years (the GHG parity time), after which wood‐pellet electricity has sustained climate benefits. Parity times increase by a maximum of 12 years when varying key variables (emissions associated with paper and panels, soil carbon increase via feedstock decomposition, wood‐pellet electricity supply chain emissions) within maximum plausible ranges. Using commercial thinnings, harvest residues or mill residues as feedstock leads to the shortest GHG parity times (0–6 years) and fastest GHG benefits from wood‐pellet electricity. We find shorter GHG parity times than previous studies, for we use a novel approach that differentiates feedstocks and considers alternative scenarios based on (combinations of) alternative feedstock fates, rather than on alternative land uses. This novel approach is relevant for bioenergy derived from low‐value feedstocks.     

产业园区温室气体排放清单

温室气体排放所导致的全球气候变化是国际社会长期关注的热点问题,它严重限制了人类社会的发展并威胁着人类的生存。产业园区通常集中了一个区域主要的生产要素与生产能力,也代表着特定产业在该区域的发展水平,理应作为发展低碳经济的基础单元和减少温室气体排放的重要控制点,也可以成为解决区域资源、环境问题的突破口。明确了产业园区温室气体排放的系统边界和内部结构,梳理了产业园区全生命周期温室气体排放行为,综合考虑产业园区能源消耗、工业生产、物质材料消耗、仪器设备投入、废弃物处理处置、景观绿化等过程,建立产业园区温室气体排放核算方法,并对案例园区进行了清单分析。结果表明:案例园区整个生命周期的温室气体排放量为1872177 t CO2-eq,其中运行管理阶段占全生命周期排放的比例最高,为95.35%。建设阶段的温室气体排放总量中建筑材料消耗引起的排放占到96.95%,主要集中在建筑工程、内部装修工程和外部装饰工程3个环节。运行管理阶段电力消耗、热力消耗和污水处理过程的排放量占到总量的98.69%。根据核算及分析结果提出了案例园区在建设和运行管理阶段实现温室气体减排的建议。     

Energy Use and Greenhouse Gas Emissions of Air‐Source Heat Pump and Innovative Ground‐Source Air Heat Pump in a Cold Climate

This article compares climate impacts of two heat‐pump systems for domestic heating, that is, energy consumption for space heating of a residential building. Using a life cycle approach, the study compared the energy use and greenhouse gas (GHG) emissions of direct electric heating, a conventional air‐source heat pump, and a novel ground‐source air heat pump innovated by a citizen user, to assess whether such user innovation holds benefit. The energy use of the heat pumps was modeled at six temperature intervals based on duration curves of outdoor temperature. Additionally, two heat pump end‐of‐life scenarios were analyzed. Probabilistic uncertainty analysis was applied using a Monte Carlo simulation. The results indicated that, in ideal conditions, that is, assuming perfect air mixing, the conventional air‐source heat pump's emissions were over 40% lower and the ground‐air heat pump's emissions over 70% lower than in the case of direct electric heating. Although proper handling of the refrigerant is important, total leakage from the retirement of the heat‐pump appliance would increase GHG emissions by just 10%. According to the sensitivity analysis, the most influential input parameters are the emission factor related to electricity and the amount of electricity used for heating.     

Life Cycle Assessment of End‐of‐Life Management Options for Construction and Demolition Debris

A life cycle assessment (LCA) of various end‐of‐life management options for construction and demolition (C&D) debris was conducted using the U.S. Environmental Protection Agency's Municipal Solid Waste Decision Support Tool. A comparative LCA evaluated seven different management scenarios using the annual production of C&D debris in New Hampshire as the functional unit. Each scenario encompassed C&D debris transport, processing, separation, and recycling, as well as varying end‐of‐life management options for the C&D debris (e.g., combustion to generate electricity versus landfilling for the wood debris stream and recycling versus landfilling for the nonwood debris stream) and different bases for the electricity generation offsets (e.g., the northeastern U.S. power grid versus coal‐fired power generation). A sensitivity analysis was also conducted by varying the energy content of the C&D wood debris and by examining the impact of basing the energy offsets on electricity generated from various fossil fuels. The results include impacts for greenhouse gas (GHG) emissions, criteria air pollutants, ancillary solid waste production, and organic and inorganic constituents in water emissions. Scenarios with nonwood C&D debris recycling coupled with combustion of C&D wood debris to generate electricity had lower impacts than other scenarios. The nonwood C&D debris recycling scenarios where C&D wood debris was landfilled resulted in less overall impact than the scenarios where all C&D debris was landfilled. The lowest impact scenario included nonwood C&D debris recycling with local combustion of the C&D wood debris to generate electricity, providing a net gain in energy production of more than 7 trillion British thermal units (BTU) per year and a 130,000 tons per year reduction in GHG emissions. The sensitivity analysis revealed that for energy consumption, the model is sensitive to the energy content of the C&D wood debris but insensitive to the basis for the energy offset, and the opposite is true for GHG emissions.     

Life Cycle Impacts of Natural Fiber Composites for Automotive Applications: Effects of Renewable Energy Content and Lightweighting

This study examines the life cycle energy demand and greenhouse gas (GHG) emissions associated with substituting natural cellulose and kenaf in place of glass fibers in automotive components. Specifically, a 30 wt% glass‐fiber composite component weighing 3 kilograms (kg) was compared to a 30 wt% cellulose fiber composite component (2.65 kg) and 40 wt% kenaf fiber composite component (2.79 kg) for six cars, crossovers, and sport utility vehicles. The use‐phase fuel consumption of the baseline and substitute components, with and without powertrain resizing, were determined using a mass‐induced fuel consumption model based on U.S. Environmental Protection Agency test records. For all vehicles, compared to the baseline glass fiber component, using the cellulose composite material reduced life cycle energy demand by 9.2% with powertrain resizing (7.2% without) and reduced life cycle GHG emissions by 18.6% with powertrain resizing (16.3% without), whereas the kenaf composite component reduced energy demand by 6.0% with powertrain resizing (4.8% without) and GHG emissions by 10.7% with powertrain resizing (9.2% without). For both natural fiber components, the majority of the life cycle energy savings is realized in the use‐phase fuel consumption as a result of the reduced weight of the component.     

Greenhouse Gas Emission Estimates of U.S. Dietary Choices and Food Loss

Dietary behavioral choices have a strong effect on the environmental impact associated with the food system. Here, we consider the greenhouse gas (GHG) emissions associated with production of food that is lost at the retail and consumer level, as well as the potential effects on GHG emissions of a shift to dietary recommendations. Calculations are based on the U.S. Department of Agriculture's (USDA) food availability data set and literature meta‐analysis of emission factors for various food types. Food losses contribute 1.4 kilograms (kg) carbon dioxide equivalents (CO₂‐eq) capita^?1day^?1 (28%) to the overall carbon footprint of the average U.S. diet; in total, this is equivalent to the emissions of 33 million average passenger vehicles annually. Whereas beef accounts for only 4% of the retail food supply by weight, it represents 36% of the diet‐related GHG emissions. An iso‐caloric shift from the current average U.S. diet to USDA dietary recommendations could result in a 12% increase in diet‐related GHG emissions, whereas a shift that includes a decrease in caloric intake, based on the needs of the population (assuming moderate activity), results in a small (1%) decrease in diet‐related GHG emissions. These findings emphasize the need to consider environmental costs of food production in formulating recommended food patterns.     

Greenhouse Gas Emissions Payback for Lightweighted Vehicles Using Aluminum and High‐Strength Steel

In this article we consider interactions between life cycle emissions and materials flows associated with lightweighting (LW) automobiles. Both aluminum and high‐strength steel (HSS) lightweighting are considered, with LW ranging from 6% to 23% on the basis of literature references and input from industry experts. We compare the increase in greenhouse gas (GHG) emissions associated with producing lightweight vehicles with the saved emissions during vehicle use. This yields a calculation of how many years of vehicle use are required to offset the added GHG emissions from the production stage. Payback periods for HSS are shorter than for aluminum. Nevertheless, achieving significant LW with HSS comparable to aluminum‐intensive vehicles requires not only material substitution but also the achievement of secondary LW by downsizing of other vehicle components in addition to the vehicle structure. GHG savings for aluminum LW varies strongly with location where the aluminum is produced and whether secondary aluminum can be utilized instead of primary. HSS is less sensitive to these parameters. In principle, payback times for vehicles lightweighted with aluminum can be shortened by closed‐loop recycling of wrought aluminum (i.e., use of secondary wrought aluminum). Over a 15‐year time horizon, however, it is unlikely that this could significantly reduce emissions from the automotive industry, given the challenges involved with enabling a closed‐loop aluminum infrastructure without downcycling automotive body structures.     

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.     

玉米秸秆基纤维素乙醇生命周期能耗与温室气体排放分析

生命周期评价是目前分析产品或工艺的环境负荷唯一标准化工具,利用其生命周期分析方法可以有效地研究纤维素乙醇生命周期能耗与温室气体排放问题。为了定量解释以玉米秸秆为原料的纤维素乙醇的节能和温室气体减排潜力,利用生命周期分析方法对以稀酸预处理、酶水解法生产的玉米秸秆基乙醇进行了生命周期能耗与温室气体排放分析,以汽车行驶1 km为功能单位。结果表明：与汽油相比,纤维素乙醇E100 (100％乙醇) 和E10 (乙醇和汽油体积比=1∶9) 生命周期化石能耗分别减少79.63％和6.25％,温室气体排放分别减少53.98％和6.69％;生物质阶段化石能耗占到总化石能耗68.3％,其中氮肥和柴油的生命周期能耗贡献最大,分别占到生物质阶段的45.78％和33.26％;工厂电力生产过程的生命周期温室气体排放最多,占净温室气体排放量的42.06％,提升技术减少排放是降低净排放的有效措施。     

Peak cement‐related CO2 emissions and the changes in drivers in China

In order to fight against the climate change, China has set a series of emission reduction policies for super‐emitting sectors. The cement industry is the major source of process‐related emissions, and more attention should be paid to this industry. This study calculates the process‐related, direct fossil fuel–related, and indirect electricity‐related emissions from China's cement industry. The study finds that China's cement‐related emissions peaked in 2014. The emissions are, for the first time, divided into seven parts based on the cement used in different new building types. The provincial emission analysis finds that developed provinces outsourced their cement capacities to less developed regions. This study then employs index decomposition analysis to explore the drivers of changes in China's cement‐related emissions. The results show that economic growth was the primary driver of emission growth, while emission intensity and efficiency were two offsetting factors. The changes in the construction industry's structure and improvement in efficiency were the two major drivers that contributed to the decreased emissions since 2014.     

Subnational greenhouse gas and land‐based biodiversity footprints in the European Union

Insights into subnational environmental impacts and the underlying drivers are scarce, especially from a consumption‐based perspective. Here, we quantified greenhouse gas (GHG) emissions and land‐based biodiversity losses associated with final consumption in 162 regions in the European Union in 2010. For this purpose, we developed an environmentally extended multi‐regional input–output (MRIO) model with subnational European information on demand, production, and trade structures subdivided into 18 major economic sectors, while accounting for trade outside Europe. We employed subnational data on land use and national data on GHG emissions. Our results revealed within‐country differences in per capita GHG and land‐based biodiversity footprints up to factors of 3.0 and 3.5, respectively, indicating that national footprints may mask considerable subnational variability. The per capita GHG footprint increased with per capita income and income equality, whereas we did not find such responses for the per capita land‐based biodiversity footprint, reflecting that extra income is primarily spent on energy‐intensive activities. Yet, we found a shift from the domestic to the foreign part of the biodiversity footprints with rising population density and income. Because our analysis showed that most regions are already net importers of GHG emissions and biodiversity losses, we conclude that it is increasingly important to address the role of trade in national and regional policies on mitigating GHG emissions and averting further biodiversity losses, both within and outside the region itself. To further increase the policy relevance of subnational footprint analyses, we also recommend the compilation of more detailed subnational MRIO databases including harmonized environmental data.     

Evaluation and Allocation of Greenhouse Gas Reductions in Industrial Symbiosis

Industrial symbiosis (IS) exchanges have been recognized to reduce greenhouse gas (GHG) emission, though methods for quantification of GHG emissions in IS exchanges are varied, and no standardized methods are available. This article proposes a practical approach to quantify total and allocated GHG emissions from IS exchanges by integrating the GHG protocol and life cycle assessment. The proposed method expands the system boundaries to include all IS companies, and the functional flow is set to be the sum of the main products. The total impact of a company is allocated to the main product. Three by‐product impact allocation methods of cutoff, avoidance, and 50/50 are proposed, and the total and distributed impacts of the IS systems in an industrial park are theoretically derived. The proposed method was tested to quantify GHG reduction in a real IS exchange developed between Korea Zinc (a zinc smelter) and Hankook Paper (a paper mill company) in the Ulsan Eco‐Industrial Park initiative. The total reduction of GHG emissions in this IS exchange, 60,522 tonnes of carbon dioxide per year, was the same in the GHG protocol, whereas GHG distribution between two companies depended on the allocation method. Given that the reduction of GHG emissions from IS exchanges is the product of the collaboration of giving companies and receiving companies, the 50/50 allocation method is best from an equivalent‐responsibility and benefit‐sharing perspective. However, this study suggests a more practical implementation approach based on a flexible and negotiable method of allocating the total GHG reduction between stakeholders.