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1. Integrated Mechanistic Engineering Models and Macroeconomic Input-Output approach to Model Physical Economy for Evaluating the Impact of transition to Circular Economy

   https://doi.org/10.1039/D1EE00544H  

   Vunnava, Venkata Sai ; Singh, Shweta ( January 2021 , Energy & Environmental Science)

   null (Ed.)

   Sustainable transition to low carbon and zero waste economy requires a macroscopic evaluation of opportunities and impact of adopting emerging technologies in a region. However, a full assessment of current physical flows and wastes is a tedious task, thus leading to lack of comprehensive assessment before scale up and adoption of emerging technologies. Utilizing the mechanistic models developed for engineering and biological systems with macroeconomic framework of Input-Output models, we propose a novel integrated approach to fully map the physical economy, that automates the process of mapping industrial flows and wastes in a region. The approach is demonstrated by mapping the agro-based physical economy of the state of Illinois, USA by using mechanistic models for 10 sectors, which have high impact on waste generation. Each model mechanistically simulates the material transformation processes in the economic sector and provides the material flow information for mapping. The model for physical economy developed in the form of a Physical Input-Output Table (PIOT) captures the interindustry physical interactions in the region and waste flows, thus providing insights into the opportunities to implement circular economy strategies i.e., adoption of recycling technologies at large scale. In Illinois, adoption of technologies for industrial waste-water & hog manure recycling will have the highest impact by reducing > 62 % of hog industry waste, > 99 % of soybean hull waste, and > 96 % of dry corn milling (corn ethanol production) waste reduction. Small % reduction in fertilizer manufacturing waste was also observed. The physical economy model revealed that Urea sector had the highest material use of 5.52E+08 tons and green bean farming with lowest material use of 1.30E+05 tons for the year modeled (2018). The mechanistic modeling also allowed to capture elemental flows across the physical economy with Urea sector using 8.25E+07 tons of carbon per operation-year (highest) and bean farming using 3.90E+04 tons of elemental carbon per operation-year (least). The approach proposed here establishes a connection between engineering and physical economy modeling community for standardizing the mapping of physical economy that can provide insights for successfully transitioning to a low carbon and zero waste circular economy. 

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2. Extreme Weather Events and the Performance of Critical Utility Infrastructures: A Case Study of Hurricane Harvey

   https://doi.org/10.1007/s41885-023-00139-9  

   Rafi, Shahnawaz ; Meng, Sisi ; Santos, Joost ; Mozumder, Pallab ( December 2023 , Economics of Disasters and Climate Change)

   Extreme weather events have significant economic and social impacts, disrupting essential public services like electricity, phone communication, and transportation. This study seeks to understand the performance and resilience of critical infrastructure systems in Houston, Texas, using Hurricane Harvey (2017) as a case study. We surveyed 500 Houston Metropolitan Statistical Area residents after Hurricane Harvey’s landfall about disruption experience in electricity, water, phone/cellphone, internet, public transportation, workplace, and grocery stores. Our household survey data revealed the proportion and duration of disruption in each system. Approximately 70% of respondents reported experiencing electricity outages, while half (51%) had no access to water for up to six days. Two-thirds of surveyed households lacked internet access, and 50% had their phone services disconnected. Additionally, around 71% of respondents were unable to commute to work, and 73% were unable to purchase groceries for their families during this period. We incorporated the household survey responses into the Dynamic Inoperability Input-Output Model (DIIM) to estimate inoperability and economic losses across interconnected sectors. The projected economic loss was estimated to be in the range of $6.7- $9.7 billion when sensitivity analysis is performed with respect to the number of working days. Understanding the resilience of each sector and the inherent interdependencies among them can provide beneficial insight to policymakers for disaster risk management, notably preparedness and recovery planning for future events. 

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3. Caribbean Resilience of Infrastructure in the United States Virgin Islands

   https://doi.org/10.13140/RG.2.2.15862.14405  

   Wentworth, Maggie ; Arnold, Jacob ; Lehr, Matthew ; Meadows, Allison ; Leopard, Bailey ; Pawlick, Max ; Stanley, Madison ; Vaughn, David ( January 2020 , CEDC Summit 2020)

   f. Analyzing the US Virgin Islands’ resilience in relation to their infrastructure in the case of natural disasters - The U.S. Virgin Islands are comprised of four islands in the Caribbean: St. Croix, St. Thomas, St. John, and Water Island. With the high frequency of hurricanes in the Caribbean region, these islands commonly experience infrastructure disruptions. Worse, disasters such as Irma and Maria in 2017 make total losses far from unexpected. The islands have also seen a history of economic and political turmoil, rendering their infrastructure insufficient for resisting such devastating events and the lower class more susceptible to disruptions. These factors combined posits the need for resilient infrastructure to be established on the islands. Resilient infrastructure involves bolstering the utilities that are required for modern life, such as clean water, power, and transportation, such that they maintain the highest output possible when disrupted by a disaster and can be easily and effectively restored to their status quo. Our work this semester focused on assessing the infrastructure on the islands to energy options could be better implemented. This has involved gathering as much quantitative and qualitative data on the USVI as possible. This was done in order to perform a rigorous analysis on which sections of the network are most necessary for the interconnected systems network together to function; these sections are known as critical points. Only so much data is available overseas, however, so to complete our assessment we will identify what we need to fill in the gaps in our data by working in collaboration with the University of the Virgin Islands. We are constructing an accurate disaster model of the USVI infrastructure and determine its critical points as well as make recommendations for additional hazard and mitigation plans. We will then focus on getting these recommendations to the right positions of power, which could lead to establishing resilient infrastructure on the island and pave the way to a more sustainable future. In the future, we hope to create a cooperative learning bond with the University of the Virgin Islands so that future applications of the project can proceed. 

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4. Energy use for urban water management by utilities and households in Los Angeles

   https://doi.org/10.1088/2515-7620/ab5e20  

   Porse, Erik ; Mika, Kathryn B. ; Escriva-Bou, Alvar ; Fournier, Eric D. ; Sanders, Kelly T. ; Spang, Edward ; Stokes-Draut, Jennifer ; Federico, Felicia ; Gold, Mark ; Pincetl, Stephanie ( January 2020 , Environmental Research Communications)

   Reducing energy consumption for urban water management may yield economic and environmental benefits. Few studies provide comprehensive assessments of energy needs for urban water sectors that include both utility operations and household use. Here, we evaluate the energy needs for urban water management in metropolitan Los Angeles (LA) County. Using planning scenarios that include both water conservation and alternative supply options, we estimate energy requirements of water imports, groundwater pumping, distribution in pipes, water and wastewater treatment, and residential water heating across more than one hundred regional water agencies covering over 9 million people. Results show that combining water conservation with alternative local supplies such as stormwater capture and water reuse (nonpotable or indirect potable) can reduce the energy consumption and intensity of water management in LA. Further advanced water treatment for direct potable reuse could increase energy needs. In aggregate, water heating represents a major source of regional energy consumption. The heating factor associated with grid-supplied electricity drives the relative contribution of energy-for-water by utilities and households. For most scenarios of grid operations, energy for household water heating significantly outweighs utility energy consumption. The study demonstrates how publicly available and detailed data for energy and water use supports sustainability planning. The method is applicable to cities everywhere.

    

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5. Integrating household survey with inoperability input–output model of critical infrastructure systems: A case study of Hurricane Sandy

   https://doi.org/10.1111/risa.14257  

   Santos, Joost ; Meng, Sisi ; Mozumder, Pallab ( November 2023 , Risk Analysis)

   Critical infrastructures are ubiquitous and their interdependencies have become more complex leading to their uncertain behaviors in the aftermath of disasters. The article develops an integrated economic input–output model that incorporates household‐level survey data from Hurricane Sandy, which made its landfall in 2012. In this survey, 427 respondents who were living in the state of New Jersey during Hurricane Sandy were used in the study. The integration of their responses allowed us to show the probability and duration of various types of critical infrastructure failures due to a catastrophic hurricane event and estimate the economic losses across different sectors. The percentage of disruption and recovery period for various infrastructure systems were extracted from the survey, which were then utilized in the economic input–output model comprising of 71 economic sectors. Sectors were then ranked according to: (i) inoperability, the percentage in which a sector is disrupted relative to its ideal level, and (ii) economic loss, the monetary worth of business interruption caused by the disaster. With the combined infrastructure disruptions in the state of New Jersey, the model estimated an economic loss of $36 billion, which is consistent with published estimates. Results from this article can provide insights for future disaster preparedness and resilience planning.

    

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