Comparing urban food system characteristics and actions in US and Indian cities from a multi‐environmental impact perspective: Toward a streamlined approach

Food action plans in many global cities articulate interest in multiple objectives including reducing in‐ and trans‐boundary environmental impacts (water, land, greenhouse gas (GHG)). However, there exist few standardized analytical tools to compare food system characteristics and actions across cities and countries to assess trade‐offs between multiple objectives (i.e., health, equity) with environmental outcomes. This paper demonstrates a streamlined model applied for analysis of four cities with varying characteristics across the United States and India, to quantify system‐wide water, energy/GHG, and land impacts associated with multiple food system actions to address health, equity, and environment. Baseline diet analysis finds key differences between countries in terms of meat consumption (Delhi 4; Pondicherry 16; United States 59, kg/capita/year), and environmental impact of processing of the average diet (21%, 19%, <1%, <1% of community‐wide GHG‐emissions for New York, Minneapolis, Delhi, and Pondicherry). Analysis of supply chains finds city average distance (food‐miles) varies (Delhi 420; Pondicherry 200; United States average 1,640 km/t‐food) and the sensitivity of GHG emissions of food demand to spatial variability of energy intensity of irrigation is greater in Indian than US cities. Analysis also finds greater pre‐consumer waste in India versus larger post‐consumer accumulations in the United States. Despite these differences in food system characteristics, food waste management and diet change consistently emerge as key strategies. Among diet scenarios, all vegetarian diets are not found equal in terms of environmental benefit, with the US Government's recommended vegetarian diet resulting in less benefit than other more focused targeted diet changes.     

The influence of consumer behavior on the environmental footprint of passenger car tires

Understanding the influence of consumer behavior on the life cycle of products can provide further insights into effective mitigation strategies. Here, we developed a stochastic model to quantify the influence of consumer behavior on midpoint and endpoint impacts of European passenger car tires. The life cycle included resource extraction, production, use, and end-of-life stages of a passenger car tire with a functional unit of driving 50,000 km. The combined influence of variability in the lifetime, rolling resistance, size and inflation pressure of the tire, and mass and engine efficiency of the car on a range of environmental footprints was assessed via Monte Carlo simulations. We found that differences in consumer behavior can change the environmental impacts of tires with a factor 1.6 to 2.1 (95th/5th percentile). Environmental savings over the life cycle of tires are effectively achievable by stimulating the use of smaller cars and fuel-efficient tires with longer lifetimes. We found that a shift in consumer behavior specifically related to tires can result in mitigations of the tire's life cycle impacts ranging from 13% for human toxicity to 26% for climate change. Our findings show that a detailed variability analysis can provide case-specific and realistic recommendations to mitigate environmental footprints.     

Quantifying drivers of variability in life cycle greenhouse gas emissions of consumer products—a case study on laundry washing in Europe

Purpose

Variability in consumer behaviour can significantly influence the environmental performance of products and their associated impacts and this is typically not quantified in life cycle assessments. The goal of this paper is to demonstrate how consumer behaviour data can be used to understand and quantify the variability in the greenhouse gas emissions from domestic laundry washing across Europe.

Methods

Data from a pan-European consumer survey of product usage and washing habits was combined with internal company data on product format greenhouse gas (GHG) footprints and in-home measurement of energy consumption of laundry washing as well as literature data to determine the GHG footprint of laundry washing. The variability associated with four laundry detergent product formats and four wash temperature settings in washing machines were quantified on a per wash cycle basis across 23 European countries. The variability in GHG emissions associated with country electricity grid mixes was also taken into account. Monte Carlo methods were used to convert the variability in the input parameters into variability of the life cycle GHG emissions. Rank correlation analysis was used to quantify the importance of the different sources of variability.

Results and discussion

Both inter-country differences in background electricity mix as well as intra-country variation in consumer behaviour are important for determining the variability in life cycle GHG emissions of laundry detergents. The average GHG emissions related to the laundry washing process in the 23 European countries in 2014 was estimated to be 5?×?10² g CO_2?eq/wash cycle, but varied by a factor of 6.5 between countries. Intra-country variability is between a factor of 3.5 and 5.0 (90% interval). For countries with a mainly fossil-based electricity system, the dominant source of variability in GHG emissions results from consumer choices in the use of washing machines. For countries with a relatively low-carbon electricity mix, variability in life cycle GHG emissions is mainly determined by laundry product-related parameters.

Conclusions

The combination of rich data sources enabled the quantification of the variability in the life cycle GHG emissions of laundry washing which is driven by a variety of consumer choices, manufacturer choices and infrastructural differences of countries. The improved understanding of the variability needs to be balanced against the cost and challenges of assessing of consumer habits.

     

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.     

Environmental Footprints and Scenario Analysis for Assessing the Impacts of the Agri‐Food Industry on a Regional Economy: A Case Study in Spain

The study of the environmental footprints of various sectors and industries is increasingly demanded by institutions and by society. In this context, the regional perspective is becoming particularly important, and even more so in countries such as Spain, where the autonomous communities have the primary responsibility for implementing measures to combat environmental degradation and promote sustainable development, in coordination with national strategies. Taking as a case study a Spanish region, Aragon, and significant economic sectors, including agriculture and the food industry, the aim of this work is twofold. First, we calculate the associated environmental footprints (of emissions and water) from the dual perspectives of production (local impacts) and consumption (final destination of the goods produced by the agri‐food industry). Second, through a scenarios analysis, based on a general equilibrium model designed and calibrated specifically for the region, we evaluate the environmental implications of changes in the agri‐food industry (changes in the export and import pattern, as well as in consumer behavior). This model provides a flexible approximation to the environmental impacts, controlling for a wider range of behavioral and economic interactions. Our results indicate that the agri‐food industry has a significant impact on the environment, especially on water resources, which must be responsibly managed in order to maintain the differential advantage that a regional economy can have, compared to other territories.     

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.     

The Impacts of Dietary Change on Greenhouse Gas Emissions,Land Use,Water Use,and Health: A Systematic Review

Food production is a major driver of greenhouse gas (GHG) emissions, water and land use, and dietary risk factors are contributors to non-communicable diseases. Shifts in dietary patterns can therefore potentially provide benefits for both the environment and health. However, there is uncertainty about the magnitude of these impacts, and the dietary changes necessary to achieve them. We systematically review the evidence on changes in GHG emissions, land use, and water use, from shifting current dietary intakes to environmentally sustainable dietary patterns. We find 14 common sustainable dietary patterns across reviewed studies, with reductions as high as 70–80% of GHG emissions and land use, and 50% of water use (with medians of about 20–30% for these indicators across all studies) possible by adopting sustainable dietary patterns. Reductions in environmental footprints were generally proportional to the magnitude of animal-based food restriction. Dietary shifts also yielded modest benefits in all-cause mortality risk. Our review reveals that environmental and health benefits are possible by shifting current Western diets to a variety of more sustainable dietary patterns.     

Elephant (Loxodonta africana) footprints as habitat for aquatic macroinvertebrate communities in Kibale National Park,south‐west Uganda

This is the first study where elephant footprints as habitat for aquatic macroinvertebrate communities were assessed. Preliminary observations during the dry season in Kibale Forest, Uganda, indicated that water‐filled footprints constituted the majority of stagnant ponds. Consequently, this study aimed at giving an overview of the diversity and ecology of those habitats and the capacity of elephants as ecosystem engineers. The fauna and abiotic factors (age, size, substrate, organic matter, pH, canopy cover, temperature, conductivity) of 30 water‐filled natural elephant footprints were sampled, resulting in the record of 61 morphospecies among 27 families/orders. Species composition was dominated by Hydrophilidae and Dytiscidae and influenced by environmental variables, such as age and organic matter. To study the colonization process, 18 artificial footprints were created within different distances from the water source. After 5 days, 410 specimens were collected, with higher species richness in artificial footprints closer to a natural water source. We conclude that colonization of water‐filled footprints is fast, they constitute important habitats with high diversity and variability, and they act as stepping stones for dispersal and add to the ability of elephants as ecosystem engineers. We emphasize the importance of elephants as a key species in ecosystem dynamics and conservation practice.     

Machine learning based modeling of households: A regionalized bottom‐up approach to investigate consumption‐induced environmental impacts

As major drivers of economy, households induce a large share of worldwide environmental impacts. The variability of local consumption patterns and associated environmental impacts needs to be quantified as an important starting point to devise targeted measures aimed at reducing household environmental footprints. The goal of this article is the development and appraisal of a comprehensive regionalized bottom‐up model that assesses realistic environmental profiles for individual households in a specific region. For this purpose, a physically based building energy model, the results of an agent‐based transport simulation, and a data‐driven household consumption model were interlinked within a new probability‐based classification framework and applied to the case of Switzerland. The resulting model predicts the demands in about 400 different consumption areas for each Swiss household by considering its particular circumstances and produces a realistic picture of variability in household environmental footprints. An analysis of the model results on a municipal level reveals per‐capita income, population density, buildings' age, and household structure as possible drivers of municipal carbon footprints. While higher‐emission municipalities are located in rural areas and tend to show higher shares of older buildings, lower‐emission communities have larger proportions of families and can be found in highly populated regions by trend. However, the opposing effects of various variables observed in this analysis confirm the importance of a model that is able to capture regional distinctions. The overall model constitutes a comprehensive information base supporting policymakers in understanding consumption patterns in their region and deriving environmental strategies tailored to their specific population.     

Environmental analysis of packaging‐derived changes in food production and consumer behavior

This study analyzed the environmental impacts of packaging‐derived changes in food production and consumer behavior to assist packaging designers in making environmentally conscious decisions. Packaging can be functionalized to prevent food loss and waste (FLW), for example, extending the expiration date and apportioning the package size, but it can generate additional environmental impacts from changes in food and packaging production. Previous studies assessed additional impacts from packaging production; however, the effects of packaging functionalization are yet to be connected with food production and consumer behavior. To examine the effect of functionalization on these aspects, we analyzed packaging‐derived changes in food production for milk and cabbage products. The case study compared products with functionalized packaging that permits a longer expiration date or a smaller portion size to their base‐case products. Our results showed that the packaging‐derived changes increased the global warming potential (GWP) of food production more than other processes did. Thus, changes in food production weakened the effectiveness of the packaging functionalization to decrease the GWP. Moreover, the analysis of consumer behavior scenarios showed that consumers’ perception of the expiration date decisively influences the effectiveness of packaging functionalization. When consumers discarded food after the expiration date, provided they consumed in small quantities, the packaging functionalization reduced FLW. From the scenario analysis, we identified appropriate combinations of packaging functionalization and consumer behaviors to effectively decrease total GWP. With our expanded analysis, packaging designers can understand the effectiveness of their decisions on the product life cycle in reducing FLW and environmental impacts.     

Variability in greenhouse gas footprints of the global wind farm fleet

While technological characteristics largely determine the greenhouse gas (GHG) emissions during the construction of a wind farm and meteorological circumstances the actual electricity production, a thorough analysis to quantify the GHG footprint variability (in g CO₂eq/kWh electricity produced) between wind farms is still lacking at the global scale. Here, we quantified the GHG footprint of 26,821 wind farms located across the globe, combining turbine-specific technological parameters, life-cycle inventory data, and location- and temporal-specific meteorological information. These wind farms represent 79% of the 651 global wind (GW) capacity installed in 2019. Our results indicate a median GHG footprint for global wind electricity of 10 g CO₂eq/kWh, ranging from 4 to 56 g CO₂eq/kWh (2.5th and 97.5th percentiles). Differences in the GHG footprint of wind farms are mainly explained by spatial variability in wind speed, followed by whether the wind farm is located onshore or offshore, the turbine diameter, and the number of turbines in a wind farm. We also provided a metamodel based on these four predictors for users to be able to easily obtain a first indication of GHG footprints of new wind farms considered. Our results can be used to compare the GHG footprint of wind farms to one another and to other sources of electricity in a location-specific manner.     

Labor Embodied in Trade

Global production chains carry environmental and socioeconomic impacts embodied in each traded good and service. Even though labor and energy productivities tend to be higher for domestic production in high‐income countries than those in emerging economies, this difference is significantly reduced for consumption, when including imported products to satisfy national demand. The analysis of socioeconomic and environmental aspects embodied in consumption can shed a light on the real level of productivity of an economy, as well as the effects of rising imports and offshoring. This research introduces a consumption‐based metric for productivity, in which we evaluate the loss of productivity of developed nations resulting from imports from less‐developed economies and offshoring of labor‐intensive production. We measure the labor, energy, and greenhouse gas emissions footprints in the European Union's trade with the rest of the world through a multiregional input‐output model. We confirm that the labor footprint of European imports is significantly higher than the one of exports, mainly from low‐skilled, labor‐intensive primary sectors. A high share of labor embodied in exports is commonly associated with low energy productivities in domestic industries. Hence, this reconfirms that the offshoring of production to cheaper and low‐skilled, labor‐abundant countries offsets, or even reverts, energy efficiency gains and climate‐change mitigation actions in developed countries.     

Advancements in Input‐Output Models and Indicators for Consumption‐Based Accounting

The use of global, multiregional input‐output (MRIO) analysis for consumption‐based (footprint) accounting has expanded significantly over the last decade. Most of the global studies on environmental and social impacts associated with consumption or embodied in international trade would have been impossible without the rapid development of extended MRIO databases. We present an overview of the developments in the field of MRIO analysis, in particular as applied to consumption‐based environmental and social footprints. We first provide a discussion of research published on various global MRIO databases and the differences between them, before focusing on the virtual laboratory computing infrastructure for potentially making MRIO databases more accessible for collaborative research, and also for supporting greater sectoral and regional detail. We discuss work that includes a broader range of extensions, in particular the inclusion of social indicators in consumption‐based accounting. We conclude by discussing the need for the development of detailed nested MRIO tables for investigating linkages between regions of different countries, and the applications of the rapidly growing field of global MRIO analysis for assessing a country's performance toward the United Nations Sustainable Development Goals.     

Life Cycle Assessment of Advanced Industrial Wastewater Treatment Within an Urban Environment

A dissolved air flotation (DAF) system upgrade was proposed for an urban paper mill to recycle effluent. To understand the influence of operating variables on the environmental impacts of greenhouse gas (GHG) emissions and water consumption, a dynamic supply chain model was linked with life cycle assessment (LCA) to produce an environmental inventory. Water is a critical natural resource, and understanding the environmental impacts of recycling water is paramount in continued development of sustainable supply chains involving water. The methodology used in this study bridged the gap between detailed process models and static LCA modeling so that operating variables beyond discrete scenario analysis could be investigated without creating unnecessarily complex models. The model performed well in evaluating environmental impacts. It was found that there was no single optimum operating regime for all environmental impacts. For a mill discharging 80 cubic meters of effluent per hour (m³/hour), GHGs could be minimized with a DAF capacity of 17.5 m³/hour, while water consumption could be minimized with a DAF capacity of 25 m³/hour, which allowed insight into where environmental trade‐offs would occur. The study shows that more complexity can be achieved in supply chain modeling without requiring a full technical model. It also illustrates the need to consider multiple environmental impacts and highlights the trade‐off of GHG emissions with water consumption in water recycling. The supply chain model used in this water treatment case study was able to identify the environmental trade‐offs from the operating variables selected.     

Capital in the American carbon,energy, and material footprint

Stocks of fixed capital play a vital role in fulfilling basic human needs and facilitating industrial production. Their build‐up requires great quantities of energy and materials, and generates greenhouse gas emissions and other pollution. Capital stocks influence economic production and environmental pollution through their construction and over subsequent decades through their use. We perform an environmental footprint analysis of total consumption, capital investment, and capital consumption in the United States for 2007 and 2012. In 2012, capital consumption accounted for 13%, 19%, and 40% of total carbon, energy, and material footprints, respectively. Housing, federal defense, state and local government education and other services (including household consumption of roads), personal transport fuels, and hospitals are the consumption sectors with largest capital footprints. These sectors provide fundamental needs of shelter, transport, education, and health, underlying the importance of capital services. Endogenizing capital causes the biggest proportional increase to footprints of sectors with low environmental multipliers. This work builds upon existing input‐output models of production and consumption in the United States, and provides a capital‐inclusive database of carbon, energy, and material footprints and multipliers for 2007 and 2012. This article met the requirements for a gold – gold JIE data openness badge described at http://jie.click/badges .     

Linking social identity,risk perception,and behavioral psychology to understand predator management by livestock producers

Human behaviors can determine the success of efforts to restore predators to ecosystems. While behaviors such as lethal predator control may impede predator restoration, other land management practices can facilitate coexistence between predators and humans. Socio‐psychological theories provide useful tools for understanding and improving these human behaviors. We explore three frameworks to understand what shapes Australian livestock graziers' behaviors with regards to management of the threat that dingoes pose to livestock. These frameworks are the theory of reasoned action (incorporating values and beliefs about dingoes), the social identity approach, and perception of risk. We distributed a survey to Australian graziers by mail and online (n = 138) which allowed recording of information on these three frameworks and their engagement in lethal dingo control. Among the respondents, we found that all three frameworks were linked with lethal dingo control when assessed individually, but when combined in a hierarchical regression, only social identity (specifically, identifying as an “environmentalist” or “pest controller”) was significant in predicting behavior. This result reveals the strength of social norms and normative beliefs over perceived risk in shaping behavior. As such, social identity is a useful metric for predicting and understanding environmental management behavior. Determining what these social identities mean in a given context is important for identifying how to implement behavior change to promote evidence‐based management that facilitates restoration of wildlife such as predators to landscapes where conflict with humans occurs.     

Environmental Sustainability of Fluid Milk Delivery Systems in the United States

Beverage producers in the United States choose packaging based on cost and consumer preference. Monolayer high‐density polyethylene (HDPE) and gable‐top carton containers have long dominated the U.S. fluid milk market, but pressure for more sustainable packaging is increasing. We present a broad discussion on environmental sustainability of 18 fluid milk containers through life cycle assessment. Because different container types require unique milk processing, distribution, and disposal and incur or avoid milk losses, fluid milk delivery systems (FMDSs) are evaluated, rather than containers in isolation. By assessing FMDSs, a complete measure of containers’ environmental sustainability was obtained. Despite conservative assumptions about milk losses, differences in container size, milk processing, distribution, and container recycling, pair‐wise cradle‐to‐grave comparisons of FMDSs show there are no superior FMDSs. But, 500‐ to 1,000‐milliliter FMDSs are potentially superior to ≥half gallon if they prevent milk losses. Thus, the future of FMDSs in the United States depends on the industry's ability to prevent distribution (12%) and consumption milk losses (20% to 35%). Farm‐gate‐to‐grave comparisons showed that chilled HDPE FMDSs are superior to other plastic and chilled paperboard FMDSs for climate‐change impact, but the result is inconclusive for chilled HDPE to ambient (unrefrigerated) paperboard or plastic pouch FMDS comparisons. Plastic pouch FMDSs show potential to reduce nonrenewable fossil energy, but need to be recyclable. Ambient FMDSs are superior to chilled FMDSs for water depletion. Eight‐ounce paperboard FMDSs are superior to 8‐ounce plastic FMDSs. Thus, alternative FMDSs may improve environmental sustainability of the U.S. postfarm fluid milk supply chain.     

BMI and waist circumference in predicting cardiovascular risk factor clustering in Chinese adolescents

Objective: To derive the optimal BMI and waist circumference (WC) cut‐off values to predict clustering of cardiovascular risk factors in Hong Kong Chinese adolescents. Research Methods and Procedures: A total of 2102 Hong Kong Chinese 12 to 19 years of age were recruited. Participants were considered to have clustering of risk factors if at least three of the following risk factors were present: 1) high‐density lipoprotein cholesterol (HDL‐C) ≤1.03 mM, 2) low‐density lipoprotein cholesterol (LDL‐C) ≥2.6 mM, 3) triglyceride (TG) ≥1.24 mM, 4) fasting plasma glucose (FPG) ≥6.1 mM, and 5) age‐, sex‐, and height‐adjusted systolic or diastolic blood pressure (BP) ≥ 90th percentile. Receiver operating characteristics (ROC) curves were generated to identify the optimal age‐adjusted BMI and WC cut‐off values to predict clustering of risk factors in boys and girls separately. These age‐adjusted BMI and WC cut‐offs were transformed to percentile values. Cole's lambda‐mu‐sigma (LMS) method was used to obtain smoothed age‐specific BMI and WC at these percentile values. Results: The areas under ROC curves for BMI in girls and boys were 0.85 [95% confidence interval (CI), 0.77 to 0.92] and 0.76 (95% CI, 0.66 to 0.85), respectively. The respective areas under ROC curves for WC in girls and boys were 0.82 (95% CI, 0.74 to 0.91) and 0.78 (95% CI, 0.68 to 0.87). The optimal BMI thresholds were at the 78th percentile for girls and the 72nd percentile for boys. The respective values for WC were at the 77th percentile for girls and the 76th percentile for boys. The sensitivities and specificities of these cut‐off values ranged from 72% to 80%. Discussion: Age‐ and sex‐specific BMI and WC cut‐off values can be used to identify adolescents with clustering of cardiovascular risk factors.     

Consensus,uncertainties and challenges for perennial bioenergy crops and land use

Perennial bioenergy crops have significant potential to reduce greenhouse gas (GHG) emissions and contribute to climate change mitigation by substituting for fossil fuels; yet delivering significant GHG savings will require substantial land‐use change, globally. Over the last decade, research has delivered improved understanding of the environmental benefits and risks of this transition to perennial bioenergy crops, addressing concerns that the impacts of land conversion to perennial bioenergy crops could result in increased rather than decreased GHG emissions. For policymakers to assess the most cost‐effective and sustainable options for deployment and climate change mitigation, synthesis of these studies is needed to support evidence‐based decision making. In 2015, a workshop was convened with researchers, policymakers and industry/business representatives from the UK, EU and internationally. Outcomes from global research on bioenergy land‐use change were compared to identify areas of consensus, key uncertainties, and research priorities. Here, we discuss the strength of evidence for and against six consensus statements summarising the effects of land‐use change to perennial bioenergy crops on the cycling of carbon, nitrogen and water, in the context of the whole life‐cycle of bioenergy production. Our analysis suggests that the direct impacts of dedicated perennial bioenergy crops on soil carbon and nitrous oxide are increasingly well understood and are often consistent with significant life cycle GHG mitigation from bioenergy relative to conventional energy sources. We conclude that the GHG balance of perennial bioenergy crop cultivation will often be favourable, with maximum GHG savings achieved where crops are grown on soils with low carbon stocks and conservative nutrient application, accruing additional environmental benefits such as improved water quality. The analysis reported here demonstrates there is a mature and increasingly comprehensive evidence base on the environmental benefits and risks of bioenergy cultivation which can support the development of a sustainable bioenergy industry.