An Exploration of the Relationship between Socioeconomic and Well‐Being Variables and Household Greenhouse Gas Emissions

This research reports on a multivariate analysis that examined the relationship between direct greenhouse gas (GHG) emissions and socioeconomic and well‐being variables for 1,920 respondents living in Halifax Regional Municipality, Nova Scotia, Canada, using results from the Halifax Space‐Time Activity Research Project. The unique data set allows us to estimate direct GHG emissions with an unprecedented level of specificity based on household energy use survey data and geographic positioning system–verified personal travel data. Of the variables analyzed, household size, income, community zone, age, and marital status are all statistically significant predictors of direct GHG emissions. Birthplace, ethnicity, educational attainment, perceptions of health, life satisfaction, job satisfaction, happiness, volunteering, or community belonging did not seem to matter. In addition, we examined whether those reporting energy‐efficient behaviors had lower GHG emissions. No significant differences were discovered among the groups analyzed, supporting a growing body of research indicating a disconnect between environmental attitudes and behaviors and environmental impact. Among the predictor variables, those reporting to be married, young, low income, and living in households with more people have correspondingly lower direct GHG emissions than other categories in respective groupings. Our finding that respondents with lifestyles that generate higher GHG emissions did not report to be healthier, happier, or more connected to their communities suggest that individuals can experience similar degrees of well‐being regardless of the amount of GHG emissions associated with his or her respective lifestyle.     

A Hybrid Approach for Assessing the Multi‐Scale Impacts of Urban Resource Use: Transportation in Phoenix,Arizona

Life cycle assessment (LCA) and urban metabolism (UM) are popular approaches for urban system environmental assessment. However, both approaches have challenges when used across spatial scales. LCA tends to decompose systemic information into micro‐level functional units that mask complexity and purpose, whereas UM typically equates aggregated material and energy flows with impacts and is not ideal for revealing the mechanisms or alternatives available to reduce systemic environmental risks. This study explores the value of integrating UM with LCA, using vehicle transportation in the Phoenix metropolitan area as an illustrative case study. Where other studies have focused on the use of LCA providing upstream supply‐chain impacts for UM, we assert that the broader value of the integrated approach is in (1) the ability to cross scales (from micro to macro) in environmental assessment and (2) establishing an analysis that captures function and complexity in urban systems. The results for Phoenix show the complexity in resource supply chains and critical infrastructure services, how impacts accrue well beyond geopolitical boundaries where activities occur, and potential system vulnerabilities.     

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

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

Alternatives for natural‐gas‐based heating systems: A quantitative GIS‐based analysis of climate impacts and financial feasibility

The heating of buildings currently produces 6% of global greenhouse gas emissions. Sustainable heating technologies can reduce heating‐related CO₂ emissions by up to 90%. We present a Python‐based GIS model to analyze the environmental and financial impact of strategies to reduce heating‐related CO₂ emissions of residential buildings. The city‐wide implementation of three alternatives to natural gas are evaluated: high‐temperature heating networks, low‐temperature heating networks, and heat pumps. We find that both lowering the demand for heat and providing more sustainable sources of heat will be necessary to achieve significant CO₂‐emission reductions. Of the studied alternatives, only low‐temperature heating networks and heat pumps have the potential to reduce CO₂ emissions by 90%. A CO₂ tax and an increase in tax on the use of natural gas are potent policy tools to accelerate the adoption of low‐carbon heating technologies.     

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.     

Comparative Energy, Environmental, and Economic Analysis of Traditional and E-commerce DVD Rental Networks

This study is a comparative life-cycle assessment (LCA) of two competing digital video disc (DVD) rental networks: the e-commerce option, where the customer orders the movies online, and the traditional business option, where the customer goes to the rental store to rent a movie. The analytical framework proposed is for a customer living in the city of Ann Arbor, Michigan in the United States. The primary energy and environmental performance for both networks are presented using a multicriterion LCA. The package selected by the traditional network is responsible for 67% of the difference in total energy consumption of the two alternatives. Results show that the e-commerce alternative consumed 33% less energy and emitted 40% less CO2 than the traditional option. A set of sensitivity analyses test the influence of distance traveled, transportation mode, and reuse of DVD and DVD packaging on the final results. The mode of transportation used by the customer in the traditional business model also affects global emissions and energy consumption. The customer walking to the store is by far the best option in the traditional network; however, the e-commerce option performed comparatively better despite all transportation modes tested. A novel economic indicator, ESAL, is used to compare different transportation modes based on the level of stress exerted on the pavement. The two networks are compared on the basis of cost accounting; consistent with its energy and environmental advantages, the e-commerce network also exerts lesser economic impact, by $1.17, for the functional unit tested.     

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.     

Environmental Damage Assessment of Carbon Capture and Storage

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

Transforming the Cement Industry into a Key Environmental Infrastructure for Urban Ecosystem: A Case Study of an Industrial City in China

Under the dual pressure of environmental constraints and increasingly thin profit margins, the cement industry in China is in a predicament. To alleviate the environmental and the economic pressure of the cement industry and to tackle the problem of delayed environmental infrastructure construction, this article introduced an urban ecosystem in which the cement industry was transformed into an effective complement to environmental infrastructure. The Xinfeng Cement Industrial Park in China, which has a production capacity of 5 million tonnes per annum (Mt/a) of clinker, was chosen as a case study. Our methodology involved proposing technologies to develop an efficient cement plant‐centered urban ecosystem; evaluating its environmental and economic performance; identifying barriers in its promotion; and proposing supportive policies. Results showed that the city's waste recycling ratio rose from about 50% to 70%, saving 0.6 Mt/a of coal equivalent and reducing about 3.0 Mt/a of resulting carbon dioxide (CO₂) emissions. The life span of the city's landfill site was extended by about 30 years. The total investment was 3.2 billion yuan (about US$480 million), 1 with an average payback period of 3 years. The Xinfeng Cement Industrial Park was transformed from an energy‐intensive consumer and a significant CO₂ emitter to a key industrial waste recycler, a crucial municipal waste co‐processor, an important new building material supplier, and a potential energy producer. Last, the “not‐in‐my‐back‐yard” (NIMBY) effect from constructing new environmental infrastructure was also avoided.     

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

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

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.     

A Comparative Study of Environmental Impacts of Two Delivery Systems in the Business‐to‐Customer Book Retail Sector

China has the highest carbon dioxide (CO₂) emissions in the world. In China, logistics accounts for a significant portion of the total energy use and CO₂ emissions in business‐to‐customer (B2C) retailing. This study focuses on the environmental impacts of B2C delivery in China, focusing on the book retail industry. Mathematical models are proposed based on the practical operations of the “e‐commerce networked delivery” (END) system and the “sustainable networked delivery” (SND) system. The energy consumption and CO₂ emissions per book are then determined and compared for the two systems. Furthermore, we contrast the findings with those of similar studies conducted for other countries and provide explanations for the differences. The results show that (1) in general, in China, the SND system is better than the END system in terms of environmental impacts; (2) the END system in China generates fewer environmental impacts than those in the United States and the United Kingdom, while the SND system in China has greater environmental impacts than that in the United States; and (3) the wide use of vehicles such as electric bicycles that have low energy consumption rates contributes to the reduction of environmental impacts per book in both the END and SND systems in China. The limitations of the study and suggestions for future research are also discussed.     

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.     

Mapping the Influence of Food Waste in Food Packaging Environmental Performance Assessments

Scrutiny of food packaging environmental impacts has led to a variety of sustainability directives, but has largely focused on the direct impacts of materials. A growing awareness of the impacts of food waste warrants a recalibration of packaging environmental assessment to include the indirect effects due to influences on food waste. In this study, we model 13 food products and their typical packaging formats through a consistent life cycle assessment framework in order to demonstrate the effect of food waste on overall system greenhouse gas (GHG) emissions and cumulative energy demand (CED). Starting with food waste rate estimates from the U.S. Department of Agriculture, we calculate the effect on GHG emissions and CED of a hypothetical 10% decrease in food waste rate. This defines a limit for increases in packaging impacts from innovative packaging solutions that will still lead to net system environmental benefits. The ratio of food production to packaging production environmental impact provides a guide to predicting food waste effects on system performance. Based on a survey of the food LCA literature, this ratio for GHG emissions ranges from 0.06 (wine example) to 780 (beef example). High ratios with foods such as cereals, dairy, seafood, and meats suggest greater opportunity for net impact reductions through packaging‐based food waste reduction innovations. While this study is not intended to provide definitive LCAs for the product/package systems modeled, it does illustrate both the importance of considering food waste when comparing packaging alternatives, and the potential for using packaging to reduce overall system impacts by reducing food waste.     

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

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

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

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

Energy Cost of Living and Associated Pollution for Beijing Residents

China's remarkable economic growth in the last 3 decades has brought about big improvements in quality of life while simultaneously contributing to serious environmental problems. The aim of all economic activities is, ultimately, to provide the population with products and services. Analyzing environmental impacts of consumption can be valuable for illuminating underlying drivers for energy use and emissions in society. This study applies an environmentally extended input‐output analysis to estimate household environmental impact (HEI) of urban Beijing households at different levels of development. The analysis covers direct and indirect energy use and emissions of carbon dioxide (CO₂), sulfur dioxide (SO₂), and nitrogen oxide (NO_x). On the basis of observations of how HEI varies across income groups, prospects for near‐future changes in HEI are discussed. Results indicate that in 2007, an urban resident in Beijing used, on average, 52 gigajoules of total primary energy supply. The corresponding annual emissions were 4.2 tonnes CO₂, 27 kilograms SO₂, and 17 kilograms NO_x. Of this, only 18% to 34% was used or emitted by the households directly. While the overall expenditure elasticity of energy use is around 0.9, there is a higher elasticity of energy use associated with transport. The results suggest that significant growth in HEI can be expected in the near future, even with substantial energy efficiency improvements.     

Improvements in Life Cycle Energy Efficiency and Greenhouse Gas Emissions of Corn-Ethanol

Corn-ethanol production is expanding rapidly with the adoption of improved technologies to increase energy efficiency and profitability in crop production, ethanol conversion, and coproduct use. Life cycle assessment can evaluate the impact of these changes on environmental performance metrics. To this end, we analyzed the life cycles of corn-ethanol systems accounting for the majority of U.S. capacity to estimate greenhouse gas (GHG) emissions and energy efficiencies on the basis of updated values for crop management and yields, biorefinery operation, and coproduct utilization. Direct-effect GHG emissions were estimated to be equivalent to a 48% to 59% reduction compared to gasoline, a twofold to threefold greater reduction than reported in previous studies. Ethanol-to-petroleum output/input ratios ranged from 10:1 to 13:1 but could be increased to 19:1 if farmers adopted high-yield progressive crop and soil management practices. An advanced closed-loop biorefinery with anaerobic digestion reduced GHG emissions by 67% and increased the net energy ratio to 2.2, from 1.5 to 1.8 for the most common systems. Such improved technologies have the potential to move corn-ethanol closer to the hypothetical performance of cellulosic biofuels. Likewise, the larger GHG reductions estimated in this study allow a greater buffer for inclusion of indirect-effect land-use change emissions while still meeting regulatory GHG reduction targets. These results suggest that corn-ethanol systems have substantially greater potential to mitigate GHG emissions and reduce dependence on imported petroleum for transportation fuels than reported previously.     

The Energy Structure of the Canadian Economy

We developed a model of a national economy in which the phenomena of supply, demand, economic growth, and international trade are represented in terms of energy flows. In examining the structure of the economy, we distinguish between the energy embodied in capital assets used in the production and distribution of energy and that embodied in capital assets and goods that consume energy. Sources used to quantify the energy flows include: end‐use energy data by economic sector; International Energy Agency–style national energy balances, and national input‐output tables. As an example, the Canadian economy for 2008 produced 16.97 exajoules (EJ) of energy, which after net export of 6.16 EJ and other adjustments left a total primary energy consumption of 10.61 EJ. The energy supply and distribution sectors used close to 32% (3.36 EJ) of total primary consumption. Analysis of primary energy consumption shows that 25.14% was embodied in household consumption, 22.85% was consumed directly by households, 7.88% was embodied in government services, and 34.07% was embodied in exports. Of significance to economic growth, 7.14% was embodied in capital in energy demanding sectors, 1.25% in energy consuming personal assets, and 1.52% in supply sector capital. The energy return on energy investment was relatively constant, averaging 5.14 between 1990 and 2008. Capital investments required to decouple the Canadian economy from its dependence on fossil fuels are discerned.     

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.