ALBERT

Description: A wide spectrum of accounting frameworks and models is available to describe socioeconomic metabolism (SEM). Despite the common system of study, a large variety of terms and representations of that system are used by different models. This makes it difficult for practitioners to compare and choose a model or model combination that is fit for purpose. To facilitate model comparison, we analyze the system structure of material flow analysis (MFA); life cycle assessment (LCA); supply and use tables (SUTs); Leontief, Ghosh, and waste input-output analysis; integrated assessment models; and computable general equilibrium models. We show that the typical system structure of MFA and LCA is a directed graph. For the other models and some MFA and LCA studies, the system structure is a bipartite directed graph. We demonstrate that bipartite directed graphs and SUTs are equivalent representations of SEM. We show that the system structures of the models above are special cases of a general system structure, which models SEM as a bipartite graph . The general system structure includes industries, markets, the final use phase, products, waste, production factors, resources, and emissions. From the general system structure, we derive an accounting framework in the form of a generalized SUT. The general system structure facilitates the development of clear and unambiguous terminology across models. It helps to identify rules for the correct accounting of waste flows and stock changes. It facilitates model comparison and can serve as a blueprint for a model-independent database of SEM.

Description: The complexity of data and methods in industrial ecology (IE) keeps growing, and the demand for comprehensive and interdisciplinary assessments increases. To keep up with this development, the field needs a data infrastructure that allows researchers to annotate, store, retrieve, combine, and exchange data at low cost, without loss of information, and across disciplines and model frameworks. A consensus-building debate about how to describe the common object of study, socioeconomic metabolism (SEM), is necessary for the development of practical data structures and databases. We review the definitions of basic concepts to describe SEM in IE and related fields such as integrated assessment modeling. We find that many definitions are not compatible, are implicit, and are sometimes lacking. To resolve the conflicts and inconsistencies within the current definitions, we propose a hierarchical system of terms and definitions, a practical ontology , for describing objects, their properties, and events in SEM. We propose a typology of object properties and use sets to group objects into a hierarchical, mutually exclusive, and collectively exhaustive (H-MECE) classification. This grouping leads to a general definition of stocks . We show that a MECE representation of events necessarily requires two complementary concepts: processes and flows , for which we propose general definitions based on sets. Using these definitions, we show that the system structure of any interdisciplinary model of SEM can be formulated as a directed graph . We propose guidelines for semantic data annotation and database design, which can help to turn the vision of a powerful data infrastructure for SEM research into reality.

Description: Abstract Until this day, data in industrial ecology (IE) have been commonly seen as existing within the domain of particular methods or models, such as input–output, life cycle assessment, urban metabolism, or material flow analysis data. This artificial division of data into methods contradicts the common phenomena described by those data: the objects and processes in the industrial system, or socioeconomic metabolism (SEM). A consequence of this scattered organization of related data across methods is that IE researchers and consultants spend too much time searching for and reformatting data from diverse and incoherent sources, time that could be invested into quality control and analysis of model results instead. This article outlines a solution to two major barriers to data exchange within IE: (a) the lack of a generic structure for IE data and (b) the lack of a bespoke platform to exchange IE datasets. We present a general data model for SEM that can be used to structure all data that can be located in the industrial system, including process descriptions, product descriptions, stocks, flows, and coefficients of all kind. We describe a relational database built on the general data model and a user interface to it, both of which are open source and can be implemented by individual researchers, groups, institutions, or the entire community. In the latter case, one could speak of an IE data commons (IEDC), and we unveil an IEDC prototype containing a diverse set of datasets from the literature.

Description: Changes in national and global food demand are commonly explained by population growth, dietary shifts, and food waste. Although nutrition sciences demonstrate that biophysical characteristics determine food requirements in individuals, and medical and demographic studies provide evidence for large shifts in height, weight, and age structure worldwide, the aggregated effects for food demand are poorly understood. Here, a type–cohort–time stock model is applied to analyze the combined effect of biophysical and demographic changes in the adult population of 186 countries between 1975–2014. The average global adult in 2014 was 14% heavier, 1.3% taller, 6.2% older, and had a 6.1% higher energy demand than the average adult in 1975. Across countries, individuals’ weight gains ranged between 6–33%, and energy needs increased between 0.9–16%. Noteworthy, some of the highest and lowest increases coexist within Africa and Asia, signaling the disparities between the countries of these regions. Globally, food energy increased by 129% during the studied period. Population growth contributed with 116%; weight and height gains accounted for 15%; meanwhile, the aging phenomenon counteracted the rise in energy needs by −2%. This net additional 13% demand corresponded to the needs of 286 million adults. Since the effect of biodemographic changes are cumulative, we can expect the observed inertia to extend into the future. This work shows that considering the evolving individual biophysical characteristics jointly with sociodemographic changes can contribute to more robust global resource and food security assessments. Commonly used static and homogenous caloric demand values per capita might lead to misrepresentations of actual needs. What previous analyses could have estimated as increased food availability, sufficiency, or surplus waste might actually be energy sequestered by the mass of the human lot. Based on the discovered trends, feeding nine billion people in 2050 will require significantly more total calories than feeding the same people today.

Description: Residential buildings account for about one-third of the final energy demand in Norway. Many cost-effective measures for reducing heat losses in buildings are known, and their implementation may make the building sector one of the largest contributors to climate change mitigation. To determine the sectoral emission reduction potential, we model a complete transformation of the dwelling stock by 2050 by applying both renovation and reconstruction with different energy standards. We propose a new dynamic stock model with an optimization routine to identify and prioritize buildings with the highest energy saving potential. We combine material flow analysis (MFA) and life cycle assessment (LCA) techniques to extend the sectoral boundary beyond direct household emissions. Despite an expected population growth of almost 50% between 2000 and 2050, sectoral carbon emissions in that period may drop between 30% and 40% for scenarios where the stock is completely transformed by either reconstruction or renovation to the passive house standard. Due to its lower upstream impact, renovation leads to a lower sectoral carbon footprint than reconstruction. Full transformation, however, is not sufficient to achieve an emissions reduction of 50% or more, as required on average to limit global warming to 2 degrees Celsius, because hot water generation, appliances, and lighting will dominate the sectoral footprint once the stock has been transformed. A first estimate of the additional impact of realistic energy efficiency and lifestyle changes in the nonheating part of the sector reveals a maximal total reduction potential of about 75%.

Description: Future phosphorus (P) scarcity and eutrophication risks demonstrate the need for systems-wide P assessments. Despite the projected drastic increase in world-wide fish production, P studies have yet to include the aquaculture and fisheries sectors, thus eliminating the possibility of assessing their relative importance and identifying opportunities for recycling. Using Norway as a case, this study presents the results of a current-status integrated fisheries, aquaculture, and agriculture P flow analysis and identifies current sectoral linkages as well as potential cross-sectoral synergies where P use can be optimized. A scenario was developed to shed light on how the projected 2050 fivefold Norwegian aquaculture growth will likely affect P demand and secondary P resources. The results indicate that, contrary to most other countries where agriculture dominates, in Norway, aquaculture and agriculture drive P consumption and losses at similar levels and secondary P recycling, both intra- and cross-sectorally, is far from optimized. The scenario results suggest that the projected aquaculture growth will make the Norwegian aquaculture sector approximately 4 times as P intensive as compared to agriculture, in terms of both imported P and losses. This will create not only future environmental challenges, but also opportunities for cross-sectoral P recycling that could help alleviate the mineral P demands of agriculture. Near-term policy measures should focus on utilizing domestic fish scrap for animal husbandry and/or fish feed production. Long-term efforts should focus on improving technology and environmental systems analysis methods to enable P recovery from aquaculture production and manure distribution in animal husbandry.

Description: A detailed understanding of material stocks in use is essential for anticipating future scrap availability, identifying critical drivers for material use, and developing strategies for resource efficiency. Here, we present a bottom-up assessment of iron and steel stocks in use in urban and rural China for the years 2000 and 2010, including 〉250 subcategories of products and components, and grouping them into five main end-use categories (i.e., buildings, infrastructure, domestic appliances, machinery, and transport equipment). The uncertainty range of the steel content per type of stock, a determinant of the accuracy and usefulness of the stock accounting, is probed by multiple means, including sample analysis. Important findings are that (1) iron and steel stocks in China have climbed to 2.4 tonnes/capita (t/cap) in 2010, up from 0.9 t/cap in 2000. The use of reinforced concrete in construction of the urban built environment was the major driver for stock growth; (2) a rural-urban difference was uncovered, with rural iron and steel stocks of approximately 1.1 t/cap and the urban iron and steel stocks of approximately 3.7 t/cap in 2010. Both are, nevertheless, far below the level of 10 to 16 t/cap observed in highly industrialized and urbanized countries. For this reason, further stock increase is foreseeable as urbanization and industrialization proceeds and quality of life improves; (3) nearly half of the steel stocks were embedded in concrete structures, and 23% were located in the countryside. Only a fraction of these stocks are currently recovered at end of life.