Environmental Impacts of Products:Policy Relevant Information and Data Challenges

The research and analysis presented in this special issue shows that the same limited number of consumption categories are consistently revealed to be responsible for the largest share of environmental impact: mobility (automobile and air transport), food (meat, poultry, fish, and dairy followed by plant‐based food), and residential energy use in the house (heating, cooling, electrical appliances, and lighting). It appears that differences in impact per euro between the product groupings are relatively limited, so it is essential to reduce the life‐cycle impacts of products as such, rather than to shift expenditures to less impact‐intensive product groupings. Furthermore, the effectiveness of expenditure on material products to improve quality of life leaves much room for improvement. Environmentally extended input‐output (EEIO) tables probably form, in this field, the most appropriate information support tool for priority setting, prospective assessment of options, scenario analysis, and monitoring. A clear benefit would result from integrating the input–output (IO) tables in the report to Eurostat of the 25 individual countries that make up the European Union (EU), with other officially available information on emissions and resources use, into a 60‐sector EEIO table for the EU. This, obviously, would be the first step toward more detailed tables. Three strategies are suggested to realize the additional, desirable detail of 150 sectors or more, each achievable at an increasing time horizon and with increasing effort: (1) developing further the current CEDA EU25 table; (2) building a truly European detailed input–output table accepting the restrictions of existing data gathering procedures; and (3) as (2), but developing new, dedicated data gathering and classification procedures. In all cases, a key issue is harmonizing classification systems for industry sectors, consumer expenditure categories, and product classifications (as in import/export statistics) in such a way that data sets may adequately be linked to input–output tables.     

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.     

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.     

Hotspot Scenario Analysis

Increasingly, organizations are working to reduce the environmental footprint of their supply chains. The use of environmentally preferable purchasing criteria is one strategy organizations use to address this goal. However, evaluating the environmental performance of these criteria (e.g., recycled content, biodegradable, renewable, and so on) has remained elusive. Life cycle assessment (LCA) can measure the impact reduction potential of sourcing strategies. However, full process‐based LCAs are time‐consuming and costly across multiple criteria of thousands of products and inputs purchased in an organizational setting. A streamlined “hotspot” methodology is presented using a combination of environmentally extended economic input‐output (EEIO) approaches and extant literature to identify hotspots in which to constrain a parameterized process‐based LCA. A case study of breakfast cereal manufacturing is developed to (1) assess the efficiencies associated with the hotspotting approach and (2) demonstrate its applicability in generating comparable decision signals of environmentally preferable sourcing criteria for procurement and supply‐chain managers along the dimensions of global warming potential and water use.     

Effects of Using Heterogeneous Prices on the Allocation of Impacts from Electricity Use: A Mixed‐Unit Input‐Output Approach

Economic input‐output life cycle assessment (IO‐LCA) models allow for quick estimation of economy‐wide greenhouse gas (GHG) emissions associated with goods and services. IO‐LCA models are usually built using economic accounts and differ from most process‐based models in their use of economic transactions, rather than physical flows, as the drivers of supply‐chain GHG emissions. GHG emissions estimates associated with input supply chains are influenced by the price paid by consumers when the relative prices between individual consumers are different. We investigate the significance of the allocation of GHG emissions based on monetary versus physical units by carrying out a case study of the U.S. electricity sector. We create parallel monetary and mixed‐unit IO‐LCA models using the 2007 Benchmark Accounts of the U.S. economy and sector specific prices for different end users of electricity. This approach is well suited for electricity generation because electricity consumption contributes a significant share of emissions for most processes, and the range of prices paid by electricity consumers allows us to explore the effects of price on allocation of emissions. We find that, in general, monetary input‐output models assign fewer emissions per kilowatt to electricity used by industrial sectors than to electricity used by households and service sectors, attributable to the relatively higher prices paid by households and service sectors. This fact introduces a challenging question of what is the best basis for allocating the emissions from electricity generation given the different uses of electricity by consumers and the wide variability of electricity pricing.     

SILVA: a comprehensive online resource for quality checked and aligned ribosomal RNA sequence data compatible with ARB

Sequencing ribosomal RNA (rRNA) genes is currently the method of choice for phylogenetic reconstruction, nucleic acid based detection and quantification of microbial diversity. The ARB software suite with its corresponding rRNA datasets has been accepted by researchers worldwide as a standard tool for large scale rRNA analysis. However, the rapid increase of publicly available rRNA sequence data has recently hampered the maintenance of comprehensive and curated rRNA knowledge databases. A new system, SILVA (from Latin silva, forest), was implemented to provide a central comprehensive web resource for up to date, quality controlled databases of aligned rRNA sequences from the Bacteria, Archaea and Eukarya domains. All sequences are checked for anomalies, carry a rich set of sequence associated contextual information, have multiple taxonomic classifications, and the latest validly described nomenclature. Furthermore, two precompiled sequence datasets compatible with ARB are offered for download on the SILVA website: (i) the reference (Ref) datasets, comprising only high quality, nearly full length sequences suitable for in-depth phylogenetic analysis and probe design and (ii) the comprehensive Parc datasets with all publicly available rRNA sequences longer than 300 nucleotides suitable for biodiversity analyses. The latest publicly available database release 91 (August 2007) hosts 547 521 sequences split into 461 823 small subunit and 85 689 large subunit rRNAs.     

Regional material flow accounts for China: Examining China's natural resource use at the provincial and national level

Over the last three decades, China has experienced the most dynamic economic development lifting living standards and resulting in fast‐growing use of natural resources. In the past, the focus has been on national MFA accounts which do not do justice to the second largest economy, home to 19% of the world population and having 30% of global material use. In this research, we calculate material extraction for China at the regional level during 1995–2015 using the most recent available statistical data and applying the most up‐to‐date international calculation methods. In particular, we combine a bottom‐up and top‐down approach for constructing the dataset of China's economically used Domestic Extraction (DEU) in an integrated way. This approach also improves the Chinese national material flow accounts and allows us to present a reliable database of DE of materials for China to date. Our new dataset provides the basis for calculating material footprints and environmental impacts of China's regions. The dataset enables us to evaluate regional resource efficiency trends in China. We find that during the past two decades, China's material use has grown strongly from 11.7 billion tonnes in 1995 to 35.4 billion tonnes in 2015. Material use has accelerated between 2000 and 2010 but slowed down between 2010 and 2015 reflecting the economic contraction caused by the Global Financial Crisis which reduced the global demand for China's manufacturing and a reorientation of China's economic policy settings toward quality of growth. Unsurprisingly, different regions play different roles in the supply chain of materials, achieving different economic performances resulting in very diverse material efficiency outcomes. This information is important to allow for a targeted policy approach to increase resource efficiency, reduce environmental impacts of resource use, and grow wellbeing in China with large positive implications for global sustainability. This study provides the basis for the development of relevant resource management policies for different regions in the future.     

Modeling the circular economy in environmentally extended input–output: A web application

Global environmental and resource problems ask for new ways of managing the production and consumption of resources. The implementation of new paradigms, such as the circular economy, requires decision‐makers at multiple levels to make complex decisions. For this, clear analyses and modeling of scenarios are of utmost importance. Meanwhile, as the sophistication of databases and models increases so does the need for user‐friendly tools to use them. The RaMa‐Scene web platform reduces these barriers by allowing users to visualize easily diverse impacts of implementing circular‐economy interventions. This online web platform makes use of the multi‐regional environmentally extended input–output database EXIOBASE version 3 in monetary units, which has been modified to show explicit transactions of raw materials from recycling activities.     

Combining Multiregional Input‐Output Analysis with a World Trade Model for Evaluating Scenarios for Sustainable Use of Global Resources,Part I: Conceptual Framework

Consumption in a particular country often entails resource extraction, production, and environmental degradation in remote locations. This fact has stimulated a growing body of empirical analysis using input‐output (I‐O) databases and techniques to reveal and quantify the underlying linkages. Two lines of research rooted in I‐O economics, multiregional input‐output (MRIO) analysis and I‐O modeling of the world economy, describe and analyze these relationships, the first for the past, increasingly in the form of footprints and the underlying pathways, and the latter under alternative scenarios about possible courses of action in the future. The article shows how organizing such scenario outcomes into an MRIO database can extend the reach of MRIO analysis to the future while simultaneously supplementing the capabilities of the world trade modeling framework. We describe the compilation of an MRIO database from the results of scenario analysis using the world trade model (WTM) in a companion article (Part II, Implementation); the subsequent application of MRIO techniques to this database permits the evaluation of prospects for the future. We also address several overlooked challenges, namely, the need to include factor endowments and distances between potential trade partners in an MRIO database, the representation of sectors providing transport of internationally traded goods, and the manipulation of mixed physical and money units when both quantities and prices are endogenous.     

Methods of remote homology detection can be combined to increase coverage by 10% in the midnight zone

MOTIVATION: A recent development in sequence-based remote homologue detection is the introduction of profile-profile comparison methods. These are more powerful than previous technologies and can detect potentially homologous relationships missed by structural classifications such as CATH and SCOP. As structural classifications traditionally act as the gold standard of homology this poses a challenge in benchmarking them. RESULTS: We present a novel approach which allows an accurate benchmark of these methods against the CATH structural classification. We then apply this approach to assess the accuracy of a range of publicly available methods for remote homology detection including several profile-profile methods (COMPASS, HHSearch, PRC) from two perspectives. First, in distinguishing homologous domains from non-homologues and second, in annotating proteomes with structural domain families. PRC is shown to be the best method for distinguishing homologues. We show that SAM is the best practical method for annotating genomes, whilst using COMPASS for the most remote homologues would increase coverage. Finally, we introduce a simple approach to increase the sensitivity of remote homologue detection by up to 10%. This is achieved by combining multiple methods with a jury vote. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.     

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 .     

An Australian Multi‐Regional Waste Supply‐Use Framework

The production of waste creates both direct and indirect environmental impacts. A range of strategies are available to reduce the generation of waste by industry and households, and to select waste treatment approaches that minimize environmental harm. However, evaluating these strategies requires reliable and detailed data on waste production and treatment. Unfortunately, published Australian waste data are typically highly aggregated, published by a variety of entities in different formats, and do not form a complete time‐series. We demonstrate a technique for constructing a multi‐regional waste supply‐use (MRWSU) framework for Australia using information from numerous waste data sources. This is the first MRWSU framework to be constructed (to the authors' knowledge) and the first sub‐national waste input‐output framework to be constructed for Australia. We construct the framework using the Industrial Ecology Virtual Laboratory (IELab), a cloud‐hosted computational platform for building Australian multi‐regional input‐output tables. The structure of the framework complies with the System of Environmental‐Economic Accounting (SEEA). We demonstrate the use of the MRWSU framework by calculating waste footprints that enumerate the full supply chain waste production for Australian consumers.     

A classification of disulfide patterns and its relationship to protein structure and function

We report a detailed classification of disulfide patterns to further understand the role of disulfides in protein structure and function. The classification is applied to a unique searchable database of disulfide patterns derived from the SwissProt and Pfam databases. The disulfide database contains seven times the number of publicly available disulfide annotations. Each disulfide pattern in the database captures the topology and cysteine spacing of a protein domain. We have clustered the domains by their disulfide patterns and visualized the results using a novel representation termed the "classification wheel." The classification is applied to 40,620 protein domains with 2-10 disulfides. The effectiveness of the classification is evaluated by determining the extent to which proteins of similar structure and function are grouped together through comparison with the SCOP and Pfam databases, respectively. In general, proteins with similar disulfide patterns have similar structure and function, even in cases of low sequence similarity, and we illustrate this with specific examples. Using a measure of disulfide topology complexity, we find that there is a predominance of less complex topologies. We also explored the importance of loss or addition of disulfides to protein structure and function by linking classification wheels through disulfide subpattern comparisons. This classification, when coupled with our disulfide database, will serve as a useful resource for searching and comparing disulfide patterns, and understanding their role in protein structure, folding, and stability. Proteins in the disulfide clusters that do not contain structural information are prime candidates for structural genomics initiatives, because they may correspond to novel structures.     

Building Inventory and Refurbishment Scenario Database Development for Switzerland

Material usage and the related embodied environmental impact have grown in significance in the built environment. Therefore, cities and governments need to develop strategies to reduce both the consumption of resources during usage phase as well as the embodied impact of the current building stock. This article proposes a new component‐based building inventory database as a basis to develop such strategies using building stock modeling. The developed database clusters the building stock according to building typology (single‐family houses, multifamily houses, and office buildings), age, and the main construction systems of the different building components. Based on the component makeup, it lists the necessary material input and waste output for different refurbishment options for each building component. The advantages of the proposed database structure are shown based on two applications for the developed database for Switzerland. The component‐based database allows optimization of refurbishment strategies not only from an energetic perspective, but also with respect to materials, both on the input (sourcing of materials) and the output (waste streams) level. The database structure makes it possible to continuously extend the data set by adding new refurbishment options or add data such as component‐specific lifetimes, costs, or labor intensities of the refurbishment options. In combination with an aligned economic model, this would give an even more holistic view, impact, and feasibility of different refurbishment scenarios both in environmental and economic terms.     

When Do Allocations and Constructs Respect Material,Energy, Financial,and Production Balances in LCA and EEIO?

Conservation of mass and energy are essential to physical accounting, just as price and market balances are essential to economic accounting. These principles guide data collection and inventory compilation in industrial ecology. The resulting balanced surveys, however, can rarely be used directly for life cycle assessment (LCA) or environmentally extended input‐output (EEIO) analysis; some modeling is necessary to recast coproductions by multifunctional activities as monofunctional unit processes (a.k.a. Leontief production functions or technical “recipes”). This modeling is done with allocations in LCA and constructs in input‐output. In this article, we ask how these models respect or perturb the balances of the original inventory. Which allocations or constructs, applied to what type of data set, have the potential to simultaneously respect its multiple physical, financial, and market balances? Our analysis builds upon the recent harmonization of allocations and constructs and the ongoing development of multilayered supply and use inventory tables. We derive the necessary and sufficient conditions for balanced models, investigate the role of data aggregation, and clarify these models' relation to system expansion. We find that none of the modeling families in LCA and EEIO are balanced in general, but special data characteristics can allow for the respect of multiple balances. An analysis of these special cases allows for clear guidance for data compilation and methods integration.     

Reconciling approaches to biogeographical regionalization: a systematic and generic framework examined with a case study of the Australian continent

Aim To develop a systematic and generic framework for biogeographical regionalizations that can assist in reconciling different approaches and advance their application as a research tool. Location The Australian continent is used as a case study. Methods A review of approaches to biogeographical regionalization revealed two basic methodologies: the integrated survey method and the parametric approach. To help reconcile these different approaches, we propose a simple, four‐step, flexible and generic framework. (1) Identification of the thematic foci from the three main themes (composition and evolutionary legacy; ecosystem drivers; ecosystem responses). (2) Proposal of a theory defining the purpose. (3) Application of a numeric agglomerative classification procedure that requires the user to make explicit assumptions about attributes, the number of classification groups, the spatial unit of analysis, and the metric for measuring the similarity of these units based on their attribute values. (4) Acquisition of spatial estimates of the required input attribute data. For this case study, an agglomerative classification strategy was applied using the functions within patn 3.03, a software package facilitating large‐scale, multivariate pattern analysis. The input data to the classifications were continental coverages of 11 environmental variables and three indices of gross primary productivity stored at a grid cell resolution of c. 250 m. The spatial units of analysis were surface hydrological units (SHU), which were derived from a continental digital elevation model based on the contributing areas to stream segments or the area draining into a local sink where there is no organized drainage. The Minkowski series (Euclidean distance) was selected as the association measure to allow weightings to be applied to the variables. Results Two new biogeographical regionalizations of the Australian continent were generated. The first was an environmental domain classification, based on 11 climatic, terrain and soil attributes. This regionalization can be used to address hypotheses about the relationship between environmental distance and evolutionary processes. The classification produced 151 environmental groups. The second was a classification of primary productivity regimes based on estimates of the gross primary productivity of the vegetation cover calculated from moderate resolution imaging spectroradiometer (MODIS) normalized difference vegetation index (NDVI) data and estimates of radiation. This classification produced 50 groups, and can be used to examine hypotheses concerning productivity regimes and animal life‐history strategies. The productivity classification does not capture all the properties related to biological carrying capacity, process rates and differences in the characteristic biodiversity of ecosystems. Some of these ecologically significant properties are captured by the environmental domain classification. Main conclusions Our framework can be applied to all terrestrial regions, and the necessary data for the analyses presented here are now available at global scales. As the spatial predictions generated by the classifications can be tested by comparison with independent data, the approach facilitates exploratory analysis and further hypothesis generation. Integration of the three themes in our framework will contribute to a more comprehensive approach to biogeography.     

Facilities that make the PDB data collection more powerful

We describe a series of databases and tools that directly or indirectly support biomedical research on macromolecules, with focus on their applicability in protein structure bioinformatics research. DSSP, that determines secondary structures of proteins, has been updated to work well with extremely large structures in multiple formats. The PDBREPORT database that lists anomalies in protein structures has been remade to remove many small problems. These reports are now available as PDF‐formatted files with a computer‐readable summary. The VASE software has been added to analyze and visualize HSSP multiple sequence alignments for protein structures. The Lists collection of databases has been extended with a series of databases, most noticeably with a database that gives each protein structure a grade for usefulness in protein structure bioinformatics projects. The PDB‐REDO collection of reanalyzed and re‐refined protein structures that were solved by X‐ray crystallography has been improved by dealing better with sugar residues and with hydrogen bonds, and adding many missing surface loops. All academic software underlying these protein structure bioinformatics applications and databases are now publicly accessible, either directly from the authors or from the GitHub software repository.     

An analysis of historical trends in classical biological control of arthropods suggests need for a new centralized database in the USA

The documentation of biological control agents targeting arthropods in the United States has historically been subject to less regulation relative to weed biological control releases. This study reviews publicly available databases to track environmental releases of biological control agents targeting arthropods in the United States. It then presents available data for the states with the most releases between 1962 and 2005: Hawaii, California and Florida. These data indicate a clear decline in rates of introduction since 1982 or 1994, depending on the source. Existing record-keeping systems offer incomplete or inconsistent data for evaluation because they were designed with limited goals, attempt to capture excessive detail and are thus impractical, or are insufficiently resourced. Existing databases cannot be used to answer meaningful questions regarding non-target effects of introduced control agents. Current databases are inappropriately designed and insufficiently resourced to meet today's research and regulatory needs. We propose and describe a new database system for classical biological control of arthropods.