Elementary flow mapping across life cycle inventory data systems: A case study for data interoperability under the Global Life Cycle Assessment Data Access (GLAD) initiative.

Purpose: Limited availability of life cycle assessment (LCA) data poses a significant challenge to its mainstream adoption, rendering it a central issue within the LCA community. The Global LCA Data Access (GLAD) network aims to increase the accessibility and interoperability of LCA data and offers benefits for different use cases. GLAD is an intergovernmental collaboration involving different stakeholders organized into working groups.

Food waste end-of-life management for the United States: Parameterized life cycle inventory datasets.

A life cycle inventory (LCI) dataset for food waste management was developed using secondary data from scientific literature and government reports. EPA reports on food waste management were used as the basis for collecting literature to review. Unit process parameters from the reviewed literature are compiled and combined with engineering calculations to generate LCI for food management pathways.

Dataset of 2012-2020 U.S. National- and State-Level Greenhouse Gas Emissions by Sector.

The dataset contains ∼1.1 million records of total greenhouse gases directly emitted annually by economic sectors and households in the US from 2012-2020. Data are given for 16 unique greenhouse gases by 118 aggregate sectors for each state, and as totals by these aggregate sectors as well as by 540 detailed sectors at the national level.

StatelO - Open Source Economic Input-Output Models for the 50 States of the United States of America.

Subnational input-output (IO) tables capture industry- and region-specific production, consumption, and trade of commodities and serve as a common basis for regional and multi-regional economic impact analysis. However, subnational IO tables are not made available by national statistical offices, especially in the United States (US), nor have they been estimated with transparent methods for reproducibility or updated regularly for public availability. In this article, we describe a robust StateIO modeling framework to develop state and two-region IO models for all 50 states in the US using national IO tables and state industry and trade data from reliable public sources such as the US Bureau of Economic Analysis.

Derivation and assessment of regional electricity generation emission factors in the USA.

Purpose: Electricity production is one of the largest sources of environmental emissions-especially greenhouse gases (GHGs)-in the USA. Emission factors (EFs) vary from region to region, which requires the use of spatially relevant EF data for electricity production while performing life cycle assessments (LCAs). Uncertainty information, which is sought by LCA practitioners, is rarely supplied with available life cycle inventories (LCIs).

FLOWSA: A Python Package Attributing Resource Use, Waste, Emissions, and Other Flows to Industries.

Quantifying industry consumption or production of resources, wastes, emissions, and losses-collectively called flows-is a complex and evolving process. The attribution of flows to industries often requires allocating multiple data sources that span spatial and temporal scopes and contain varied levels of aggregation. Once calculated, datasets can quickly become outdated with new releases of source data.

Incorporating New Technologies in EEIO Models.

We propose a methodology to add new technologies into Environmentally Extended Input-Output (EEIO) models based on a Supply and Use framework. The methodology provides for adding new industries (new technologies) and a new commodity under the assumption that the new commodity will partially substitute for a functionally-similar existing commodity of the baseline economy. The level of substitution is controlled by a percentage (%) as a variable of the model.

A System for Standardizing and Combining U.S. Environmental Protection Agency Emissions and Waste Inventory Data.

The U.S. Environmental Protection Agency (USEPA) provides databases that agglomerate data provided by companies or states reporting emissions, releases, wastes generated, and other activities to meet statutory requirements.

: An Open-Source R Package for Building and Using US Environmentally-Extended Input-Output Models.

is an open-source R package that builds USEEIO models, a family of environmentally-extended input-output models of US goods and services used for life cycle assessment, environmental footprint estimation, and related applications. USEEIO models have gained a wide user base since their initial release in 2017, but users were often challenged to prepare required input data and undergo a complicated model building approach. To address these challenges, was created.

USEEIO v2.0, The US Environmentally-Extended Input-Output Model v2.0.

USEEIO v2.0 is an environmental-economic model of US goods and services that can be used for life cycle assessment, footprinting, national prioritization, and related applications. This paper describes the development of the model and accompanies the release of a full model dataset as well as various supporting datasets of national environmental totals by US industry.

Data engineering for tracking chemicals and releases at industrial end-of-life activities.

Performing risk evaluation is necessary to determine whether a chemical substance presents an unreasonable risk of injury to human health or the environment across its life cycle stages. Data gathering, reconciliation, and management for supporting risk evaluation are time-consuming and challenging, especially for end-of-life (EoL) activities due to the need for proper reporting and traceability. A data engineering framework using publicly-available databases to track chemicals in waste streams generated by industrial activities and transferred to other facilities across different U.

Analyzing Economy-Scale Solid Waste Generation Using the United States Environmentally-Extended Input-Output Model.

The United States Environmentally-Extended Input-Output (USEEIO) model includes commercial enterprises from 386 industrial sectors of the economy. The purpose of this work is to model the commercial generation of three streams of solid waste from USEEIO sectors: hazardous waste, non-hazardous waste excluding construction, and non-hazardous waste from construction. The waste accounts cover 536 waste materials, with commercial non-hazardous waste presently limited to municipal solid waste and construction and demolition debris.

Purpose-Driven Reconciliation of Approaches to Estimate Chemical Releases.

A framework is presented to address the toolbox of chemical release estimation methods available for manufacturing processes. Although scientists and engineers often strive for increased accuracy, the development of fit-for-purpose release estimates can speed results that could otherwise delay decisions important to protecting human health and the environment. A number of release estimation approaches are presented, with the newest using decision trees for regression and prediction.

CDDPath: A method for quantifying the loss and recovery of construction and demolition debris in the United States.

National generation estimates for seven material types in the construction and demolition debris stream are regularly published in the United States. However, the quantities of these materials in different end-of-life management pathways are not published or otherwise made available. Quantification of end-of-life management pathways is useful for identifying approaches to decrease disposal and increase material recovery.

The creation, management, and use of data quality information for life cycle assessment.

Purpose: Despite growing access to data, questions of "best fit" data and the appropriate use of results in supporting decision making still plague the life cycle assessment (LCA) community. This discussion paper addresses revisions to assessing data quality captured in a new US Environmental Protection Agency guidance document as well as additional recommendations on data quality creation, management, and use in LCA databases and studies.

Approach: Existing data quality systems and approaches in LCA were reviewed and tested.

Exploring the relevance of spatial scale to life cycle inventory results using environmentally-extended input-output models of the United States.

The accuracy of direct and indirect resource use and emissions of products as quantified in life cycle models depends in part upon the geographical and technological representativeness of the production models. Production conditions vary not just between nations, but also within national boundaries. Understanding the level of geographic resolution within large industrial nations needed to reach acceptable accuracy has not been well-tested across the broad spectrum of goods and services consumed.

Critical review of elementary flows in LCA data.

Purpose: Elementary flows are essential components of data used for life cycle assessment. A standard list is not used across all sources, as data providers now manage these flows independently. Elementary flows must be consistent across a life cycle inventory for accurate inventory analysis and must correspond with impact methods for impact assessment.

LCA Capability Roadmap: Product System Model Description and Revision.

Life cycle assessment (LCA) practitioners face many challenges in their efforts to describe, share, review, and revise their product system models; and to reproduce the models and results of others. Current Life cycle inventory modeling techniques have weaknesses in the areas of describing model structure; documenting the use of proxy or non-ideal data; specifying allocation; and including modeler's observations and assumptions -- all affecting how the study is interpreted and limiting the reuse of models. Moreover, LCA software systems manage modeling information in different and sometimes non-compatible ways.

Bridge Processes: A Solution for LCI Datasets Independent of Background Databases.

Introduction: New platforms are emerging that enable more data providers to publish life cycle inventory data.

Background: Providing datasets that are not complete LCA models results in fragments that are difficult for practitioners to integrate and use for LCA modeling. Additionally, when proxies are used to provide a technosphere input to a process that was not originally intended by the process authors, in most LCA software this requires modifying the original process.

USEEIO: a New and Transparent United States Environmentally-Extended Input-Output Model.

National-scope environmental life cycle models of goods and services may be used for many purposes, not limited to quantifying impacts of production and consumption of nations, assessing organization-wide impacts, identifying purchasing hotspots, analyzing environmental impacts of policies, and performing streamlined life cycle assessment. USEEIO is a new environmentally-extended input-output model of the United States fit for such purposes and other sustainable materials management applications. USEEIO melds data on economic transactions between 389 industry sectors with environmental data for these sectors covering land, water, energy and mineral usage and emissions of greenhouse gases, criteria air pollutants, nutrients and toxics, to build a life cycle model of 385 US goods and services.

Life cycle assessment of a commercial rainwater harvesting system compared with a municipal water supply system.

Building upon previously published life cycle assessment (LCA) methodologies, we conducted an LCA of a commercial rainwater harvesting (RWH) system and compared it to a municipal water supply (MWS) system adapted to Washington, D.C. Eleven life cycle impact assessment (LCIA) indicators were assessed, with a functional unit of 1 m of rainwater and municipal water delivery system for toilets and urinals in a four-story commercial building with 1000 employees.

A Comparison of Major Petroleum Life Cycle Models.

Many organizations have attempted to develop an accurate well-to-pump life cycle model of petroleum products in order to inform decision makers of the consequences of its use. Our paper studies five of these models, demonstrating the differences in their predictions and attempting to evaluate their data quality. Carbon dioxide well-to-pump emissions for gasoline showed a variation of 35%, and other pollutants such as ammonia and particulate matter varied up to 100%.

Mining Available Data from the United States Environmental Protection Agency to Support Rapid Life Cycle Inventory Modeling of Chemical Manufacturing.

Demands for quick and accurate life cycle assessments create a need for methods to rapidly generate reliable life cycle inventories (LCI). Data mining is a suitable tool for this purpose, especially given the large amount of available governmental data. These data are typically applied to LCIs on a case-by-case basis.

Identifying/Quantifying Environmental Trade-offs Inherent in GHG Reduction Strategies for Coal-Fired Power.

Improvements to coal power plant technology and the cofired combustion of biomass promise direct greenhouse gas (GHG) reductions for existing coal-fired power plants. Questions remain as to what the reduction potentials are from a life cycle perspective and if it will result in unintended increases in impacts to air and water quality and human health. This study provides a unique analysis of the potential environmental impact reductions from upgrading existing subcritical pulverized coal power plants to increase their efficiency, improving environmental controls, cofiring biomass, and exporting steam for industrial use.