A Supply‐Use Approach to Waste Input‐Output Analysis

In this article, we extend Namakura and Kondo's waste input‐output (WIO) framework by incorporating a supply‐use formalism, resulting in waste supply‐use tables (WSUTs). We present the theoretical underpinnings of the WSUT and, in particular, the transition from Nakamura and Kondo's WIO form to the new WSUT form. Further, we offer a mathematical proof of the equivalence of WIO and WSUT multipliers. We illustrate the workings of the WSUT calculus using economic and waste data for the Australian economy in 2008–2009.     

Towards a Circular Economy in Australian Agri‐food Industry: An Application of Input‐Output Oriented Approaches for Analyzing Resource Efficiency and Competitiveness Potential

The food industry in Australia (agriculture and manufacturing) plays a fundamental role in contributing to socioeconomic sectors nationally. However, alongside the benefits, the industry also produces environmental burdens associated with the production of food. Sectorally, agriculture is the largest consumer of water. Additionally, land degradation, greenhouse gas emissions, energy consumption, and waste generation are considered the main environmental impacts caused by the industry. The research project aims to evaluate the eco‐efficiency performance of various subsectors in the Australian agri‐food systems through the use of input‐output–oriented approaches of data envelopment analysis and material flow analysis. This helps in establishing environmental and economic indicators for the industry. The results have shown inefficiencies during the life cycle of food production in Australia. Following the principles of industrial ecology, the study recommends the implementation of sustainable processes to increase efficiency, diminish undesirable outputs, and decrease the use of nonrenewable inputs within the production cycle. Broadly, the research outcomes are useful to inform decision makers about the advantages of moving from a traditional linear system to a circular production system, where a sustainable and efficient circular economy could be created in the Australian food industry.     

Supply versus use designs of environmental extensions in input–output analysis: Conceptual and empirical implications for the case of energy

Input–output analysis is one of the central methodological pillars of industrial ecology. However, the literature that discusses different structures of environmental extensions (EEs), that is, the scope of physical flows and their attribution to sectors in the monetary input–output table (MIOT), remains fragmented. This article investigates the conceptual and empirical implications of applying two different but frequently used designs of EEs, using the case of energy accounting, where one represents energy supply while the other energy use in the economy. We derive both extensions from an official energy supply–use dataset and apply them to the same single‐region input–output (SRIO) model of Austria, thereby isolating the effect that stems from the decision for the extension design. We also crosscheck the SRIO results with energy footprints from the global multi‐regional input–output (GMRIO) dataset EXIOBASE. Our results show that the ranking of footprints of final demand categories (e.g., household and export) is sensitive to the extension design and that product‐level results can vary by several orders of magnitude. The GMRIO‐based comparison further reveals that for a few countries the supply‐extension result can be twice the size of the use‐extension footprint (e.g., Australia and Norway). We propose a graph approach to provide a generalized framework to disclosing the design of EEs. We discuss the conceptual differences between the two extension designs by applying analogies to hybrid life‐cycle assessment and conclude that our findings are relevant for monitoring of energy efficiency and emission reduction targets and corporate footprint accounting.     

Linking city‐level input–output table to urban energy footprint: Construction framework and application

Multiregion input–output (MRIO) models have become increasingly important in economic and environmental analysis. However, the current resolution of most MRIO models fails to capture the heterogeneity between subregions, especially in cities. The lack of city‐level MRIO tables has impeded the accomplishment of city‐level studies and hampered the understanding of the relationship between urban growth and consumption, and teleconnections to other regions. In this paper, we propose a partial survey‐based multiple‐layer framework for MRIO table compilation of a Chinese province that distinguishes city‐based regions. This framework can effectively address a large number of data processes and retain consistency between layers. Using the framework, we first compile a nested Hebei‐China city‐level MRIO table and then apply city‐level energy footprint accounting of the North China urban agglomeration. Our results present the critical role of Hebei cities in energy supply in 2012 and quantify energy use embodied in goods for the domestic trade. Tangshan, Shijiazhuang, and Handan are distinctive cities in the energy supply chain of other regions, for both less developed and developed regions. This multiple‐layer framework represents a feasible approach for developing subregional‐level MRIO models and offers the possibility to analyze global trade at the subregional level with limited data. The data and results from the analysis in this article are available for download from China Emission Accounts and Datasets.     

Consumption‐based Material Flow Accounting

In 2007, imports accounted for approximately 34% of the material input (domestic extraction and imports) into the Austrian economy and almost 60% of the GDP stemmed from exports. Upstream material inputs into the production of traded goods, however, are not yet included in the standard framework of material flow accounting (MFA). We have reviewed different approaches accounting for these upstream material inputs, or raw material equivalents (RME), positioning them in a wider debate about consumption‐based perspectives in environmental accounting. For the period 1995–2007, we calculated annual RME of Austria's trade and consumption applying a hybrid approach. For exports and competitive imports, we used an environmentally extended input‐output model of the Austrian economy, based on annual supply and use tables and MFA data. For noncompetitive imports, coefficients for upstream material inputs were extracted from life cycle inventories. The RME of Austria's imports and exports were approximately three times larger than the trade flows themselves. In 2007, Austria's raw material consumption was 30 million tonnes or 15% higher than its domestic material consumption. We discuss the material composition of these flows and their temporal dynamics. Our results demonstrate the need for a consumption‐based perspective in MFA to provide robust indicators for dematerialization and resource efficiency analysis of open economies.     

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.     

A Hybrid‐Unit Energy Input‐Output Model to Evaluate Embodied Energy and Life Cycle Emissions for China's Economy

We develop a hybrid‐unit energy input‐output (I/O) model with a disaggregated electricity sector for China. The model replaces primary energy rows in monetary value, namely, coal, gas, crude oil, and renewable energy, with physical flow units in order to overcome errors associated with the proportionality assumption in environmental I/O analysis models. Model development and data use are explained and compared with other approaches in the field of environmental life cycle assessment. The model is applied to evaluate the primary energy embodied in economic output to meet Chinese final consumption for the year 2007. Direct and indirect carbon dioxide emissions intensities are determined. We find that different final demand categories pose distinctive requirements on the primary energy mix. Also, a considerable amount of energy is embodied in the supply chain of secondary industries. Embodied energy and emissions are crucial to consider for policy development in China based on consumption, rather than production. Consumption‐based policies will likely play a more important role in China when per capita income levels have reached those of western countries.     

Disaggregating the Power Generation Sector for Input‐Output Life Cycle Assessment

The electric power industry plays a critical role in the economy and the environment, and it is important to examine the economic, environmental, and policy implications of current and future power generation scenarios. However, the tools that exist to perform the life cycle assessments are either too complex or too aggregated to be useful for these types of activities. In this work, we build upon the framework of existing input‐output (I‐O) models by adding data about the electric power industry and disaggregating this single sector into additional sectors, each representing a specific portion of electric power industry operations. For each of these disaggregated sectors, we create a process‐specific supply chain and a set of emission factors that allow calculation of the environmental effects of that sector's output. This new model allows a much better fit for scenarios requiring more specificity than is possible with the current I‐O model.     

Identifying Lowest‐Emission Choices and Environmental Pareto Frontiers for Wastewater Treatment Wastewater Treatment Input‐Output Model based Linear Programming

This article proposes a linear programming model that is based on the wastewater treatment input‐output model (W²IO) to identify the lowest‐emission choice among alternative feasible options for wastewater treatment; this model can be considered as an application of the waste input‐output linear programming model (WIO‐LP) to wastewater issues. Using the data of the Tokyo metropolitan W²IO table, I apply this model to obtain the optimal wastewater treatment options under alternative scenarios. The Pareto frontiers of environmental loads are derived to show the trade‐off relationships among various types of environmental load and the effect of the introduction of high‐temperature incineration of dewatered sludge on the generation of environmental loads. The main conclusion of the study is that when all three types of environmental load (landfill level, global warming potential, and chemical oxygen demand) are considered, the introduction of high‐temperature incineration causes the widening of the Pareto frontier of environmental loads and also causes it to move closer to the origin.     

Measuring Progress towards a Circular Economy: A Monitoring Framework for Economy‐wide Material Loop Closing in the EU28

The concept of a circular economy (CE) is gaining increasing attention from policy makers, industry, and academia. There is a rapidly evolving debate on definitions, limitations, the contribution to a wider sustainability agenda, and a need for indicators to assess the effectiveness of circular economy measures at larger scales. Herein, we present a framework for a comprehensive and economy‐wide biophysical assessment of a CE, utilizing and systematically linking official statistics on resource extraction and use and waste flows in a mass‐balanced approach. This framework builds on the widely applied framework of economy‐wide material flow accounting and expands it by integrating waste flows, recycling, and downcycled materials. We propose a comprehensive set of indicators that measure the scale and circularity of total material and waste flows and their socioeconomic and ecological loop closing. We applied this framework in the context of monitoring efforts for a CE in the European Union (EU28) for the year 2014. We found that 7.4 gigatons (Gt) of materials were processed in the EU and only 0.71 Gt of them were secondary materials. The derived input socioeconomic cycling rate of materials was therefore 9.6%. Further, of the 4.8 Gt of interim output flows, 14.8% were recycled or downcycled. Based on these findings and our first efforts in assessing sensitivity of the framework, a number of improvements are deemed necessary: improved reporting of wastes, explicit modeling of societal in‐use stocks, introduction of criteria for ecological cycling, and disaggregated mass‐based indicators to evaluate environmental impacts of different materials and circularity initiatives. This article met the requirements for a gold – gold JIE data openness badge described at http://jie.click/badges .     

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.     

A network approach for inferring species associations from co‐occurrence data

Positive and negative associations between species are a key outcome of community assembly from regional species pools. These associations are difficult to detect and can be caused by a range of processes such as species interactions, local environmental constraints and dispersal. We integrate new ideas around species distribution modeling, covariance matrix estimation, and network analysis to provide an approach to inferring non‐random species associations from local‐ and regional‐scale occurrence data. Specifically, we provide a novel framework for identifying species associations that overcomes three challenges: 1) correcting for indirect effects from other species, 2) avoiding spurious associations driven by regional‐scale distributions, and 3) describing these associations in a multi‐species context. We highlight a range of research questions and analyses that this framework is able to address. We show that the approach is statistically robust using simulated data. In addition, we present an empirical analysis of > 1000 North American tree communities that gives evidence for weak positive associations among small groups of species. Finally, we discuss several possible extensions for identifying drivers of associations, predicting community assembly, and better linking biogeography and community ecology.     

Input‐Output‐based Life Cycle Inventory

An input‐output‐based life cycle inventory (IO‐based LCI) is grounded on economic environmental input‐output analysis (IO analysis). It is a fast and low‐budget method for generating LCI data sets, and is used to close data gaps in life cycle assessment (LCA). Due to the fact that its methodological basis differs from that of process‐based inventory, its application in LCA is a matter of controversy. We developed a German IO‐based approach to derive IO‐based LCI data sets that is based on the German IO accounts and on the German environmental accounts, which provide data for the sector‐specific direct emissions of seven airborne compounds. The method to calculate German IO‐based LCI data sets for building products is explained in detail. The appropriateness of employing IO‐based LCI for German buildings is analyzed by using process‐based LCI data from the Swiss Ecoinvent database to validate the calculated IO‐based LCI data. The extent of the deviations between process‐based LCI and IO‐based LCI varies considerably for the airborne emissions we investigated. We carried out a systematic evaluation of the possible reasons for this deviation. This analysis shows that the sector‐specific effects (aggregation of sectors) and the quality of primary data for emissions from national inventory reporting (NIR) are the main reasons for the deviations. As a rule, IO‐based LCI data sets seem to underestimate specific emissions while overestimating sector‐specific aspects.     

Insights on the Use of Hybrid Life Cycle Assessment for Environmental Footprinting

Establishing a comprehensive environmental footprint that indicates resource use and environmental release hotspots in both direct and indirect operations can help companies formulate impact reduction strategies as part of overall sustainability efforts. Life cycle assessment (LCA) is a useful approach for achieving these objectives. For most companies, financial data are more readily available than material and energy quantities, which suggests a hybrid LCA approach that emphasizes use of economic input‐output (EIO) LCA and process‐based energy and material flow models to frame and develop life cycle emission inventories resulting from company activities. We apply a hybrid LCA framework to an inland marine transportation company that transports bulk commodities within the United States. The analysis focuses on global warming potential, acidification, particulate matter emissions, eutrophication, ozone depletion, and water use. The results show that emissions of greenhouse gases, sulfur, and particulate matter are mainly from direct activities but that supply chain impacts are also significant, particularly in terms of water use. Hotspots were identified in the production, distribution, and use of fuel; the manufacturing, maintenance, and repair of boats and barges; food production; personnel air transport; and solid waste disposal. Results from the case study demonstrate that the aforementioned footprinting framework can provide a sufficiently reliable and comprehensive baseline for a company to formulate, measure, and monitor its efforts to reduce environmental impacts from internal and supply chain operations.     

Considering Variations in Waste Composition during Waste Input‐Output Modeling

Concentrations of pollutants vary in wastes from different sources. However, existing waste input‐output (WIO) models do not take these differing concentrations into account. This article proposes a new category of model, which we are calling a waste input‐output model at the substance level (WIOS model). The WIOS model considers variations in waste composition. These variations potentially affect the life cycle inventory of the waste treatment stage. The proposed model is expected to produce more accurate results than existing WIO models that do not consider variations in the composition of wastes. In addition, the proposed model provides a method to trace substances undergoing waste treatment. In this article, use of the WIOS model is illustrated by simulating the overall environmental loads of total organic carbon from wastewater treatment at a facility in Germany. The results show that variations in the composition of wastes entering treatment significantly affect the modeled estimates of total environmental loads caused by wastewater treatment. In addition, the results of the proposed model are different from results given by existing hybrid input‐output WIO models that do not consider variations in the composition of wastewater as it undergoes treatment.     

Predicting community rank‐abundance distributions under current and future climates

Understanding influences of environmental change on biodiversity requires consideration of more than just species richness. Here we present a novel framework for understanding possible changes in species' abundance structures within communities under climate change. We demonstrate this using comprehensive survey and environmental data from 1748 woody plant communities across southeast Queensland, Australia, to model rank‐abundance distributions (RADs) under current and future climates. Under current conditions, the models predicted RADs consistent with the region's dominant vegetation types. We demonstrate that under a business as usual climate scenario, total abundance and richness may decline in subtropical rainforest and shrubby heath, and increase in dry sclerophyll forests. Despite these opposing trends, we predicted evenness in the distribution of abundances between species to increase in all vegetation types. By assessing the information rich, multidimensional RAD, we show that climate‐driven changes to community abundance structures will likely vary depending on the current composition and environmental context.     

Broad‐scale patterns in smoke‐responsive germination from the south‐eastern Australian flora

Questions

Fire is a crucial component of many ecosystems. Plants whose seeds germinate in response to smoke may benefit from resource availability in the post‐fire environment. Smoke can influence germination timing and success, as well as seedling vigour, resulting in burgeoning research interest in smoke‐responsive germination. Research in this field has largely focused on four key ‘Mediterranean‐type’ fire‐prone ecosystems: the Mediterranean Basin, South African fynbos, Californian chaparral and Western Australia. There are far fewer studies from south‐eastern Australia, a fire‐prone but not “Mediterranean‐type” region. How does smoke‐responsive germination in this region vary according to ecological, phylogenetic, and methodological variables?

Location

South‐eastern Australia.

Methods

We investigated patterns of smoke‐promoted germination in south‐eastern Australian plants across habitat types, growth forms, fire response strategies, phylogeny, taxonomic levels and smoke application methods. We compiled and interrogated data comprising 303 entries on germination responses to smoke in 233 south‐eastern Australian plant species, from 33 different sources.

Results

Smoke‐responsive germination occurs at a lower rate (~41% of tested species) in south‐eastern Australian flora than it does in fynbos and Western Australian floras, and there is clear patterning within these data. Obligate‐seeding species were more likely to respond, Leguminosae and Rubiaceae were less likely to respond (although we question the generality of these results), while Poaceae were more likely to respond to smoke. Finally, studies using aerosol smoke and studies conducted in situ were most likely to find smoke‐promoted germination.

Conclusions

Obligate seeders and Poaceae may be selected for in habitats with higher fire frequencies, consistent with literature suggesting that short inter‐fire intervals favour grasslands over forests. These findings may be particular to south‐eastern Australia, or more widely applicable; more broad‐scale comparative research will reveal the answer. By synthesizing the south‐eastern Australian smoke germination literature we broaden our understanding beyond the better‐studied Mediterranean‐type floras.

     

Investigating Reasons for Differences in the Results of Environmental,Physical, and Hybrid Input‐Output Models

It is vital to find reasons for differences in the results of environmental input‐output (EIO), physical input‐output (PIO), and hybrid input‐output (HIO) models for industrial and environmental policy analysis. Using EIO, PIO, and HIO models, China's industrial metabolism is calculated. Four reasons were found to account for differences in the results of analysis using EIO, PIO, and HIO models: the manner in which they deal with residential consumption, service sectors, and waste recycling, and the assumption of unique sector prices. The HIO model, which treats residential consumption as sectors of the intermediate delivery matrix, is preferred to the EIO and PIO models for analyzing industrial and environmental policies. Moreover, waste recycling in five sectors—agriculture; the manufacture of paper, printing, and articles for culture, education, and sports activities; the manufacture of nonmetallic mineral products; smelting and pressing of metals; and construction—should be comprehensively considered when using the HIO model to study problems related to these five sectors. Improvements in the EIO, PIO, and HIO models and future work are also discussed.     

The Concept of City Carbon Maps: A Case Study of Melbourne,Australia

Cities are thought to be associated with most of humanity's consumption of natural resources and impacts on the environment. Cities not only constitute major centers of economic activity, knowledge, innovation, and governance—they are also said to be linked to approximately 70% to 80% of global carbon dioxide emissions. This makes cities primary agents of change in a resource‐ and carbon‐constraint world. In order to set meaningful targets, design successful policies, and implement effective mitigation strategies, it is important that greenhouse gas (GHG) emissions accounting for cities is accurate, comparable, comprehensive, and complete. Despite recent developments in the standardization of city GHG accounting, there is still a lack of consistent guidelines regarding out‐of‐boundary emissions, thus hampering efforts to identify mitigation priorities and responsibilities. We introduce a new conceptual framework—based on environmental input‐output analysis—that allows for a consistent and complete reconciliation of direct and indirect GHG emissions from a city. The “city carbon map” shows local, regional, national, and global origins and destinations of flows of embodied emissions. We test the carbon map concept by applying it to the greater metropolitan area of Melbourne, Australia. We discuss the results and limitations of the approach in the light of possible mitigation strategies and policies by different urban stakeholders.