Publications

ABSTRACT: Expanding the domestic bioeconomy can help diversify the use of national resources and reduce emissions. Evaluating the sustainability of a growing bioeconomy, however, is inherently complex since it spans several sectors and supply chains. It requires a comprehensive, integrated analysis framework to assess the developments across the traditional sustainability dimensions. Further, the assessment of bioeconomy developments requires a robust baseline of historic data and trends. In this paper, we analyze the evolution of the biofuel portion of the US bioeconomy, focusing on two fuels that had an exponential growth in the last two decades: corn ethanol and soybean biodiesel. For this purpose, we created a novel time series of harmonized environmentally-extended input-output (EEIO) tables based on a publicly available model from the US Environmental Protection Agency and expanded its disaggregation to reflect the main supply chains of the biofuels sectors. The EEIO time series provides the historical evolution of these biofuels relative to the rest of the economy as well as on an energy-unit basis. We find that, except for energy use, the broader US economy declined in both resource intensity and most environmental impacts when normalized per one million dollars of gross domestic product. Deviating from this trend are freshwater ecotoxicity and human toxicity, mainly attributable to the expansion of commodity crops and the increase of domestic oil and gas extraction respectively. We also find that the biofuel industry's total socioeconomic, resource use and environmental impacts grew with their production increases over time. However, the industry's maturation and scale-up, combined with higher feedstock yields, contributed to a reduction of most impacts on an energy-unit basis over time.

KEYWORDS: Environmentally-extended input-output, Input-output life cycle assessment, Bioeconomy, Biofuels, Corn ethanol, Soybean biodiesel

ABSTRACT: The current availability of longer series of input-output tables, as well as the release of global input-output databases, has fostered a growing literature analyzing changes in the economic structure and their drivers. In this paper, we take advantage of these time-series by proposing a methodology designed to trace the contribution of different drivers of the change in interindustrial relationships over time. Based on the Temporal Leontief Inverse (TLI), the Extended TLI (ETLI) decomposes the economy-wide effects of changes in direct interindustrial links between years, isolating the impact of different determinants of economic (environmental, energy, etc.) spillovers according to the interests of the researcher. For example, one can explore how the multipliers of a particular industry were affected by changes in technology of other sectors and in the own sector; by changes in trade patterns in specific countries; by indirect changes in intraregional production chains in foreign nations; etc. The ETLI is illustrated by uncovering certain hidden effects not captured in a previous application of the original TLI to the Chicago region between 1980-1997.

KEYWORDS: Temporal Inverse, Input-Output, Time Series, Technological Change, Structural Change

ABSTRACT: Chemical recycling and upcycling of plastics will be critical technologies to address the plastic pollution challenge. Given multiple process options for recycling plastics, rigorous process analysis is necessary to identify challenges that must be overcome for a technology to reach an industrial scale. For PET recycling, several chemical recycling strategies have been proposed and, in some cases—chemo-catalytic and thermal approaches—are being scaled up. Given that PET exhibits labile ester bonds that are also common in natural biological systems, the research community is vigorously pursuing the engineering of esterase enzymes to depolymerize PET. This study applies process analysis to highlight drivers that the community can focus on to accelerate the development of a biological PET depolymerization process and also provides a basis to compare current and future enzyme-based approaches for PET-recycling to chemo-catalytic and thermal methods.

KEYWORDS: PETase, cutinase, esterase, techno-economic analysis, life cycle assessment, supply chain modeling, environmentally extended input-output analysis, socioeconomic impacts of recycling, enzymatic PET depolymerization, plastics recycling

ABSTRACT: This paper showcases the suitability of an environmentally extended input–output framework to provide macroeconomic analyses of an expanding bioeconomy to allow for adequate evaluation of its benefits and trade-offs. It also exemplifies the framework’s applicability to provide early design stage evaluations of emerging technologies expected to contribute to a future bioeconomy. Here, it is used to compare the current United States (U.S.) bioeconomy to a hypothetical future containing additional cellulosic ethanol produced from two near-commercial pathways. We find that the substitution of gasoline with cellulosic ethanol is expected to yield socioeconomic net benefits, including job growth and value added, and a net reduction in global warming potential and nonrenewable energy use. The substitution fares comparable to or worse than that for other environmental impact categories including human toxicity and eutrophication potentials. We recommend that further technology advancement and commercialization efforts focus on reducing these unintended consequences through improved system design and innovation. The framework is seen as complementary to process-based technoeconomic and life cycle assessments as it utilizes related data to describe specific supply chains while providing analyses of individual products and portfolios thereof at an industrial scale and in the context of the U.S. economy.

KEYWORDS: Circular carbon economy, Biobased fuels and materials, Life cycle assessment, Input−output analysis, United States

ABSTRACT: Climate change and increasing world population will directly impact the global food supply chain linkages. In the United States, agricultural production requires less irrigated water than before but it still accounts for a third of total water withdrawals. To better understand the evolution of its water use, we perform a structural decomposition analysis of water withdrawals across eight different crops and six livestock categories and differentiate the trends over 1995–2005 vs 2005–2010 to account for the role of the economic crisis in the second period. Based on USGS data, the results show that both periods experienced an overall decline in water withdrawals in the production of all crops except oilseeds. This trend is driven by a decrease in water intensity, reflecting greater efficiency of irrigation systems, and by reduced local per capita income in the second period. However, increased foreign demand for water-intensive sectors like oilseeds from NAFTA and Asian partners mitigated the decline. Results indicate also a decreasing water use in livestock production partially due to a shift from red to white meat consumption in the country. Arguably, recent tariff wars and border closures have greatly reduced the virtual water embodied in American exports.

KEYWORDS: Agribusiness, Water use, United States, Structural decomposition analysis

ABSTRACT: Population growth and the uncertain hazards that accompany climate change have put increasing pressure on the management and sustainability of water. It has a direct impact on agriculture and its domestic and international supply chain linkages. As one of the largest agricultural producers in the world, the European Union (EU) is particularly sensitive to changes in water availability. Therefore, we perform a structural decomposition analysis based on the recently released EXIOBASE 3 database to examine in depth how changes in water input coefficients, in final demand and in technology have affected changes in water use across crops. Crop production consumes 99% of the direct water in agriculture. Our results show that the largest EU crop producers have experienced an increase in water use that is mostly driven by changes in technology. On the other hand, several Mediterranean countries, where water scarcity has been a problem for years, have decreased their water consumption mostly thanks to an improvement in their water intensity. Results by crop are consistent with those at the aggregated level except for vegetables of which water use changes have been primarily driven by changes in final demand and water intensity.

KEYWORDS: Agriculture, Water use, European Union, Structural decomposition analysis

ABSTRACT: The growing fragmentation of production processes and expansion of international trade in the last decades have increased the scope and complexity of value-added chains worldwide causing a rearrangement of sectoral linkages intra- and inter-regionally. In terms of economic spillovers, this implies that a dollar entering a particular economy nowadays follows a different path than a decade before, permeating in longer interregional feedback loops and creating additional multiplier effects outside its region of origin. However, it also implies that the environmental burden that such this dollar generates has changed in scale and spatial distribution. In this paper, we explore the evolution of these “paths” over the period 1997–2008 and highlight the main drivers of observed structural changes that contribute to the surge or decline of the spatial distribution of economic spillovers and greenhouse gases emissions. We specifically study the effects of an increase in income in the United States, the country with the largest trade volume in the world. We introduce an extended version of the Temporal Leontief Inverse (TLI) framework that allows tracing the evolutionary path of the American households' multiplier in a quasi-dynamic fashion, isolating the contribution of expenditure patterns, income, trade and foreign structural change to the temporal evolution. We find similar growing multiplier effects inside and outside the US due to services and manufacturing respectively, but a declining local environmental burden due to changes in interindustry relations inside the US with declining manufacturing and a reduced emission intensity. We also highlight the fragmentation process with declining foreign intraregional spillovers and increasing trade spillovers.

KEYWORDS: Temporal Leontief Inverse, Time-series analysis, Trade, Consumption-based accounting, Greenhouse gases emissions

ABSTRACT: The purpose of this study is to provide broader understanding of the significant role that the pension system has in the Spanish economy by estimating the sectoral production, employment and income sustained by pensioners' consumption. Based on input–output tables by the World Input–Output Database and consumption data from the Household Budget Survey by the Spanish Statistical Office, a demoeconomic model is applied to quantify the direct impacts, indirect impacts from interindustry links and induced impacts from income–consumption connections over a nine-year period (2006–2014). Then, the factors driving the evolution of total output, employment and value added during such period have been examined by using structural decomposition analysis. The growing participation of consumption by pensioner households in final demand had proven crucial during the 2008 crisis to alleviate the negative trend in production and employment derived from the collapse in consumption suffered by the rest of households.

KEYWORDS: Pensions, Income distribution, Employment, Household consumption

ABSTRACT: The recent upward trend in the direct costs of natural disasters is a reflection of both an increase in asset densities and the concentration of economic activities in hazard-prone areas. Although losses in physical infrastructure and lifelines are usually spatially concentrated in a few areas, their effects tend to spread geographically and temporally due to the more spatially disperse nature of production chains and the timing and length of disruptions. Since the 1980’s, several techniques have been proposed to model higher-order economic impacts of disruptive events, most of which are based on the input-output framework. However, their contributions are fragmented in different models, and, still missing, is a more comprehensive accounting of production scheduling, seasonality in industrial linkages and demographics dynamics post-event. In this paper, the Generalized Dynamic Input-Output (GDIO) framework is presented and its theoretical basis derived. It integrates previous contributions in terms of intertemporal dynamics, explicit intratemporal modeling of production and market clearing, inventory depletion/formation and expectation’s adjustment. Moreover, we add to the literature by introducing induced effects via a demo-economic extension to study the impact of displacement and unemployment post-disaster, the impact of disruption timing via seasonal input-output tables, and production chronology via the sequential interindustry model.

KEYWORDS: Natural disasters, Production chain disruptions, Input-output, Higher-order effects

ABSTRACT: Due to the concentration of assets in disaster-prone zones, changes in risk landscape and in the intensity of natural events, property losses have increased considerably in recent decades. While measuring these stock damages is common practice in the literature, the assessment of the economic ripple effects due to business interruption is still limited and available estimates tend to vary significantly across models. This paper focuses on the most popular input-output models for disaster impact evaluation. It starts with the traditional Leontief model and then compares its assumptions and results with more complex methodologies (rebalancing algorithms, the sequential interindustry model, the dynamic inoperability input-output model and its inventory counterpart). While the estimated losses vary across models, all the figures are based on the same event, the 2007 Chehalis river flood that impacted three rural counties in Washington State. Given that the large majority of floods take place in rural areas, this paper gives the practitioner a thorough review of how future events can be assessed and guidance on model selection.

KEYWORDS: Flood, Economic Impact, Input-Output Analysis

ABSTRACT: Atmospheric rivers (ARs) account for more than 75 % of heavy precipitation events and nearly all of the extreme flooding events along the Olympic Mountains and western Cascade mountains of western Washington state. In a warmer climate, ARs in this region are projected to become more frequent and intense, primarily due to increases in atmospheric water vapor. However, it is unclear how the changes in water vapor transport will affect regional flooding and associated economic impacts. In this work, we present an integrated modeling system to quantify the atmospheric-hydrologic-hydraulic and economic impacts of the December 2007 AR event that impacted the Chehalis river basin in western Washington. We use the modeling system to project impacts under a hypothetical scenario where the same December 2007 event occurs in a warmer climate. This method allows us to incorporate different types of uncertainty including: a) alternative future radiative forcings, b) different responses of the climate system to future radiative forcings and c) different responses of the surface hydrologic system. In the warming scenario, AR integrated vapor transport increases, however, these changes do not translate into generalized increases in precipitation throughout the basin. The changes in precipitation translate into spatially heterogeneous changes in sub-basin runoff and increased streamflow along the entire Chehalis main stem. Economic losses due to stock damages increased moderately, but losses in terms of business interruption were significant. Our integrated modeling tool provides communities in the Chehalis region with a range of possible future physical and economic impacts associated with AR flooding.

KEYWORDS: Atmospheric rivers, Input-Output Analysis, Climate Change

ABSTRACT: The input–output framework has evolved dramatically since its initial formulation. New analytical techniques and extensions have allowed a more comprehensive assessment of the economy and expanded its applicability. Nonetheless, the core of the framework has remained unchanged: an annually compiled input–output table, which conveys monetary flows between sectors in a region in a particular year. Hence, the technical coefficients derived from it are ‘average’ input compositions, neglecting fluctuations in production capacity, seasonality and temporal shocks within that period. This paper develops a consistent methodology to disaggregate the annual input–output table in its time dimension in order to estimate intra-year input–output matrices with distinct technical structures for a particular year. The main advantages in relation to the annual model are to allow seasonal effects to be studied within the input–output framework, to better understand the process of coefficient change and to offer a more comprehensive dynamic view of production.

KEYWORDS: Input–output, temporal disaggregation, intra-year tables

ABSTRACT: Despite regulatory measures restricting industrial and agricultural operations from pouring pollutants into lakes, streams, and rivers, around 1.1 trillion m3 of wastewater were still disposed in waterways around the world in 2009 and this amount continues to grow. Several studies have analyzed the determinants of gray water increase at local level, but so far none has explored them in an international context to highlight the role of global value added chains and the dichotomy between developed and developing nations. In order to provide insights on the dynamics of water pollution worldwide, this paper analyzes the main drivers of gray water discharge during the 1995–2009 period and the effort on reducing gray water compared to other environmental externalities. Based on the World Input-Output Database, a structural decomposition analysis (SDA) of gray water generation shows that domestic demand for food is the main driver of gray water changes in all countries, while relocation of industrial activities to developing nations has disproportionally transferred this burden from developed countries' manufacturing industries. We highlight that while national policies should target water pollution from the agri-food sector within each country, water discharges from manufacturing sectors in global value chains need to be regulated from an international perspective. Besides the empirical evidence on water pollution drivers currently lacking in the environmental literature, this paper also introduces a novel hybrid multiplicative-additive SDA that overcomes the issue of distributing large interaction terms in standard additive models and allows simulating mitigation scenarios. It portrays the heterogeneity among sectors of how environmental abatement policies affect water and air pollution.

KEYWORDS: Gray water footprint, Water pollution, WIOD, Input-output, Structural decomposition analysis

ABSTRACT: Access to high quality spatial data raises fundamental questions about how to select the appropriate scale and unit of analysis. Studies that evaluate the impact of conservation programs have used multiple scales and areal units: from 5x5 km grids; to 30m pixels; to irregular units based on land uses or political boundaries. These choices affect the estimate of program impact. The bias associated with scale and unit selection is a part of a well-known dilemma called the modifiable areal unit problem (MAUP). We introduce this dilemma to the literature on impact evaluation and then explore the tradeoffs made when choosing different areal units. To illustrate the consequences of the MAUP, we begin by examining the effect of scale selection when evaluating a protected area in Mexico using real data. We then develop a Monte Carlo experiment that simulates a conservation intervention. We find that estimates of treatment effects and variable coefficients are only accurate under restrictive circumstances. Under more realistic conditions, we find biased estimates associated with scale choices that are both too large or too small relative to the data generating process or decision unit. In our context, the MAUP may reflect an errors in variables problem, where imprecise measures of the independent variables will bias the coefficient estimates toward zero. This problem may be pronounced at small scales of analysis. Aggregation may reduce this bias for continuous variables, but aggregation exacerbates bias when using a discrete measure of treatment. While we do not find a solution to these issues, even though treatment effects are generally underestimated. We conclude with suggestions on how researchers might navigate their choice of scale and aerial unit when evaluating conservation policies.

KEYWORDS: MAUP, Monte-Carlo, Conservation Program Evaluation