Natural Disaster Risk Research Articles

Low power computation of transoceanic wave propagation for tsunami hazard mitigation

This paper proposes the use of specialized hardware accelerator based on the Field Programmable Gates Array (FPGA) microchip to compute tsunami wave propagation to assess and manage risks of marine natural disasters, namely, tsunami waves caused by underwater earthquakes. After a sufficiently strong seismic event, many countries and research centres launch extensive computations to estimate the tsunami wave parameters in certain parts of the coast to determine if a declaration of a tsunami alarm is warranted. This requires high computating powers which leads to higher energy costs. The paper demonstrates how an FPGA–based special Calculator (architecture of which has been earlier proposed by the authors), installed on a Personal Computer (PC) could be used to calculate the propagation of a tsunami wave over the entire Pacific Ocean, from the subduction zone offshore Kamchatka Peninsula and Kuril Islands to the coast of Chile. Such calculations offer reliable results within a few minutes and make it possible to obtain the distribution of expected tsunami wave heights along the coast. If the obtained results indicate a danger to the population or possible distruction of infrastructure, it becomes paramount to carry out more detailed calculations to accurately estimate the wave parameters at specific locations along the coast where negative consequences are expected. This requires cluster and/or supercomputer systems, which consume significant energy and hence are expensive. In case the modelling results indicate small values of maximum wave heights at populated coastal areas, population of the near–shore regions can be immediately informed about low amplitude tsunami wave; more detailed studies are not needed. This hence leads to noticeable savings in energy consumption. The paper presents a calculation of the propagation of a tsunami wave across the Pacific Ocean on a personal computer using a FPGA–based hardware acceleration of a computer code execution.

Urban forest and sustainability: the historical perspective of Limbe in the Southwest Region of Cameroon

ABSTRACT Projected rapid urbanisation and climate change will increase the risk of natural disasters in fragile coastal African cities. Strategically planning and managing the urban forest can help to build resilience. This study aimed to document urban forest development and sustainability in Cameroon using the city of Limbe as a baseline through the classification of urban forest elements; description of their developmental history and assessment of the level of sustainability to inform strategic planning. Data was collected using a forest ethnology approach. Two groups of stakeholders’ representatives of public institutions (Group 1), Non-Governmental Organisations and educated indigenes (Group 2) provided oral histories of tree planting. Face to face interviews with 15 stakeholders were conducted guided by semi-structured questionnaires. From these results, there are four types of urban forest. Limbe Botanical Garden (LBG) developed during the colonial era was the most prominent. Municipal authorities by law should create different types of urban forest but their actions have been limited to Roadside Trees (RT) planting. The absence of budget, policy and inventory was responsible for the low level of urban forest sustainability. Increasing awareness of the effectiveness of urban forest nature-based solutions in tackling deadly landslides and floods in Limbe can promote urban forest sustainability.

Drought disaster risk assessment and yield insurance pricing of maize: a case study of Liaoning Province, China

Starting from the ‘four-factors’ theory of natural disaster risk formation, the study first selects indices that represent hazard, vulnerability, exposure, and emergency response and recovery capability to construct the drought risk assessment index system. Then the natural disaster risk index method is employed to evaluate the risk of maize drought disasters in Liaoning. Finally, the pure premium rate for maize yield insurance is determined based on the risk assessment results and the Copula function. The results show that: (1) The hazard, vulnerability, and exposure index in northwestern Liaoning are high, while emergency response and recovery capability is relatively low. Therefore, northwestern Liaoning is identified as a high-risk area for drought risk. (2) There exists a negative correlation between the drought risk index and maize yield in most areas of Liaoning; that is, higher drought risk is associated with lower maize yield. (3) Under the same coverage level, pure rates are higher in the northwestern and eastern Liaoning and relatively lower in the southwestern and southeastern Liaoning. Under different coverage levels, higher coverage corresponds to increased pure rates. The results can offer valuable guidance and benchmarks for relevant departments in Liaoning Province to assess the impact of drought risk on agriculture.

Towards a Legal Regulation of Insurance Against Natural Disasters in Jordanian Legislation

Objectives: The current study aims at clarifying the legal solutions that can overcome the serious damage caused by natural disasters, within the framework of insurance contracts, and to clarify the mechanisms that enable insurance companies to cover natural disasters' risks. Theoretical Framework: In the first section, the concept of the insurance contract against natural disasters is explained, in the second section, the effects of the insurance contract against natural disasters are addressed while the third section, the confronting the effects of natural disasters' mechanisms are discussed. Methodology: This analytical comparative study addresses insurance against natural disasters in Jordanian legislation by reviewing and comparing the related legal texts in the compared legislations. Results: The study revealed a group of results, the most important among which include that introducing special system for insurance against natural disasters in Jordanian legislation requires that its content be based on the idea of social solidarity and also, the reinsurance process is also one of the means that can contribute to reducing the serious effects resulting from the occurrence of natural disasters. Recommendations: In light of the results revealed, the study concludes with a group of recommendations among which the necessity of formulating a special system for compulsory insurance of real estate properties built on the land of the Hashemite Kingdom of Jordan against the risks of natural disasters, in addition to the necessity of this system adopting a mechanism based on distributing the burden of compensating for damages resulting from the occurrence of these disasters on insurance companies on the one hand and reinsurance companies on the other hand, with the necessity of providing the necessary support from the state in this area.

Research on Natural Disaster Risk Assessment and Real Estate Site Selection Strategies Based on EWM-RSR Algorithm and Arcgis

Research on Natural Disaster Risk Assessment and Real Estate Site Selection Strategies Based on EWM-RSR Algorithm and Arcgis

Research on Underwriting Decision-Making of Insurance Companies in Areas with Frequent Extreme Weather Based on Comprehensive Evaluation Method

The purpose of this research is to develop an insurance company underwriting model by pre-processing and model construction of collected data in order to assess whether to underwrite insurance in extreme weather-prone areas and to analyse the factors that influence underwriting decisions. In this paper, data such as insurance company payout rate, number of insured, homeowners' income in selected areas, health insurance coverage, year of construction of historical landmarks, GDP per capita, and tourism income were processed, and minimum-maximum normalisation and zero-mean normalisation were used to eliminate differences in feature magnitude. In the model construction, the logistic regression model and BP neural network were used to derive the underwriting probability, and the three main factors of natural disaster risk assessment, payout rate, and homeowner influence were introduced, and the relationship between these factors and the underwriting probability was described by the logistic distribution function, which determined that the underwriting probability should be underwritten when the underwriting probability Pi≥0.5. The natural disaster risk assessment model selects disaster factors, disaster environment and disaster receptors as assessment indicators, constructs the CEDP model, and calculates the weights using the AHP model, the Topsis model and the CPITIC weighting method, and carries out fuzzy clustering analysis on the CEDP index of 25 regions to classify the risk into five levels. For insurer profits, solvency, premium income and claims ratios were analysed, ratios based on annual claims to total premiums were calculated, and the impact of homeowners' incomes, property and historic buildings on underwriting decisions was assessed. Insurance company underwriting decision factors in areas prone to extreme weather are ultimately determined.

Collaborative governance and integrated risk management framework of natural disasters

PurposeThis study aims to align the objectives of key stakeholders by developing an integrated framework for high-impact natural disaster risk management. High-impact natural disasters have emerged as one of the most challenging policy issues.Design/methodology/approachThe authors have applied the thematic text analysis for analysing the list of questions essential to develop an integrated framework. For theory, the authors have used the theoretical framework of collaborative governance.FindingsThe current work explains how to identify key stakeholders. Furthermore, it describes the framework to fit stakeholders' actions into the actionable components of risk management. Additionally, this framework also helps the firms that fall under the category of the industries “in the proximity of risks” and “the support industries” in modifying their role in the context of natural disaster risk.Research limitations/implicationsThe limitation of this framework is that the authors relied on commonly occurring natural disaster risks to develop the framework. Therefore, risk-specific aspects are less likely to be thoroughly covered in this framework. However, this limitation is not directly impacting the goal of this study. Additionally, in the future more comprehensive framework with the additional element in the existing framework can overcome these limitations.Practical implicationsThe findings of the study offer insights that can be useful for policymakers in developing various preventive strategies. Managers can use the results and align their objectives with policy goals.Social implicationsSocially, if communities try to design local risk management strategies, this framework would be helpful.Originality/valueThis study illustrates the role of objective alignment in high-impact risk management. This study is crucial in extending current knowledge on high-impact natural disaster risk management.

Urban Flooding Disaster Risk Assessment Utilizing the MaxEnt Model and Game Theory: A Case Study of Changchun, China

This research employs the maximum entropy (MaxEnt) model alongside game theory, integrated with an extensive framework of natural disaster risk management theory, to conduct a thorough analysis of the indicator factors related to urban flooding. This study conducts an assessment of the risks associated with urban flooding disasters using Changchun city as a case study. The validation outcomes pertaining to urban flooding hotspots reveal that 88.66% of the identified flooding sites are situated within areas classified as high-risk and very high-risk. This finding is considered to be more reliable and justifiable when contrasted with the 77.73% assessment results derived from the MaxEnt model. Utilizing the methodology of exploratory spatial data analysis (ESDA), this study applies both global and local spatial autocorrelation to investigate the disparities in the spatial patterns of flood risk within Changchun. This study concludes that urban flooding occurs primarily in the city center of Changchun and shows a significant agglomeration effect. The region is economically developed, with a high concentration of buildings and a high percentage of impervious surfaces. The Receiver Operating Characteristic (ROC) curve demonstrates that the MaxEnt model achieves an accuracy of 90.3%. On this basis, the contribution of each indicator is analyzed and ranked using the MaxEnt model. The primary determinants affecting urban flooding in Changchun are identified as impervious surfaces, population density, drainage density, maximum daily precipitation, and the Normalized Difference Vegetation Index (NDVI), with respective contributions of 20.6%, 18.1%, 13.1%, 9.6%, and 8.5%. This research offers a scientific basis for solving the urban flooding problem in Changchun city, as well as a theoretical reference for early warnings for urban disaster, and is conducive to the realization of sustainable urban development.

Modeling Flood Hazards in Ambon City Watersheds: Case Studies of Wai Batu Gantung, Wai Batu Gajah, Wai Tomu, Wai Batu Merah and Wai Ruhu

Flood hazard modeling in watersheds is an important step in natural disaster risk mitigation, especially in vulnerable areas such as Ambon City. This research focused on the Wai Batu Gantung, Wai Batu Gajah, Wai Tomu, Wai Batu Merah, and Wai Ruhu watersheds, using JRC Global Surface Water Mapping Layers data, NASA SRTM Digital Elevation 30 m data, and USGS Landsat 8 Level 2, Collection 2, Tier 1 data analyzed on the Google Earth Engine (GEE) platform. Prediction of built-up land in flood-prone areas was conducted by utilizing flood history analysis, hydrological modeling, and flood zone mapping. The results show that flood hazard modeling provides a better understanding of flood risk, assists in the development of safer land use planning, and increases public awareness of flood risk in Ambon City. It is hoped that the results of this research can contribute to flood risk management and sustainable regional development in the future.

Vietnamese migrants’ engagement in disaster risk reduction: The relevance of social capital

Researchers commonly employ the concept of social capital to examine how people engage with disaster risk reduction. This approach has generated useful knowledge to improve the effectiveness of disaster risk reduction for the general population. However, disaster risk reduction knowledge and practices designed for the general population might not speak to Vietnamese migrants because they do not reflect Vietnamese cultural practices and norms. This paper contributes to the literature by presenting findings from a narrative inquiry into Vietnamese migrants’ experiences of disaster risk reduction in the Wellington Region, Aotearoa New Zealand. The participants’ narratives suggest that Vietnamese migrants employ bonding and bridging social capital to gain knowledge about natural hazards and disaster risk reduction. Their disaster risk reduction reflects certain socio-cultural norms and values as well as family and gender dynamics among Vietnamese migrants. The findings also indicate that, for Vietnamese migrants who do not have well-established social networks, social capital-based disaster risk reduction might be less effective.

Natural Disaster Risk Mapping in Realizing Sustainable Environmental Management in the East Rembang Region, Indonesia

Natural Disaster Risk Mapping in Realizing Sustainable Environmental Management in the East Rembang Region, Indonesia

THE POPULATION OF MILA FACING THE EARTHQUAKE OF AUGUST 07, 2020

The surge in urbanization within regions vulnerable to seismic activity poses a significant escalation in seismic risks. Effective mitigation strategies, reliant on improved architectural practices and behavioral adaptations, are imperative to curtail the toll of seismic events. Seismic vulnerability, intricately intertwined with seismic hazard, building conditions, and populace preparedness, underscores the need for comprehensive risk assessment. Although studies elucidating seismic risk knowledge and behaviors are scant in Algeria, they are more prevalent in Mediterranean regions. This paper delves into the examination of risk culture, discerning both direct and indirect causative factors behind the seismic disaster that befell Mila on August 7, 2020.Employing a research methodology that integrates the method Did You Feel It (DYFI USGS ) with a survey model used in Beirut, Lebanon.The findings offer notable insights for two principal reasons. Firstly, local perceptions of the seismic event's severity surpassed estimates by the US Geological Survey (USGS). Secondly, despite the relatively minor magnitude of seismic effects in the El Kherba neighborhood, the populace displayed inadequate preparedness for future earthquakes. Additionally, site-specific factors exerted substantial influence on crisis outcomes. In this context, the preparedness of Algerian society for seismic risks depends on understanding the phenomenon, recognizing associated hazards, and identifying available resources. Contribution: this study serves as a pivotal resource for fostering proactive local population preparedness and mitigating natural risks. Furthermore, it seeks to augment the efficacy of policies aimed at managing natural disaster risks in Algeria.

Using RS and GIS for risk management of natural disasters consequences: The case of cultural heritage in Jinan city, China

The preservation of cultural heritage is confronted with significant challenges due to its extensive history and the increasing impact of climate change, particularly natural disasters. Instead of solely investing resources in post-disaster restoration efforts, implementing a proactive risk-management strategy for natural disasters is a more effective approach. This study introduces an analytical and evaluative methodology grounded in remote sensing (RS) and geographic information systems (GIS) to bridge the existing gap in understanding natural disaster risks to cultural heritage sites in Jinan, China. By leveraging a combination of RS data and established methodologies such as the Soil Conservation Service Curve Number, Maximum entropy, and the Revised Universal Soil Loss Equation, we conducted an in-depth analysis of the risks posed by various disasters including floods, landslides, earthquakes, and erosion. Furthermore, GIS and the Analytic Hierarchy Process were utilized to facilitate the risk assessment. Detailed disaster risk maps based on these assessments were produced. Our findings revealed that approximately 28.95 % of Jinan's cultural heritage sites face moderate to severe risks from natural disasters. Cultural heritage sites in Changqing District, Gangcheng District, and Laiwu District are particularly vulnerable to such calamities. These outcomes serve as crucial references for enhancing the safeguarding and management of cultural heritage, while informing disaster prevention and mitigation strategies in Jinan.

Accelerated warming of High Mountain Asia predicted at multiple years ahead

High-Mountain Asia (HMA) is an important source of freshwater since it holds the largest reservoir of frozen water outside the polar regions. HMA feeds ten great rivers, ultimately supporting more than 2 billion people. However, the threat of accelerated glacier melt, which is a consequence of unprecedented global warming since the early 1950s, threatens water resources in the surrounding countries. Accurate predictions of the near-term temperature change and synergistic mass loss of glaciers are essential but challenging to implement because of the impacts of internal climate variability. Here, based on large ensembles of state-of-the-art decadal climate prediction experiments, we provide evidence that the internally generated surface air temperature variations in HMA can be predicted multiple years in advance, and the model initialization has robust added value to the decadal prediction skill. Real-time decadal forecasts suggest that the HMA will experience accelerated warming in 2025–2032, where the surface warming will increase by 0.98 °C (0.67 to 1.33 °C; 5 % to 95 % range) relative to the reference period 1991–2020, which is equivalent to 1.75 times the observed warming during 2016–2023. The decadal predictability originates from extratropical Pacific decadal variability modes, which modulate the convective heating in the tropical Pacific and influence HMA via the eastward-propagating atmospheric Kelvin waves. Accelerated warming in the coming decade will likely increase the shrinkage of the glacier volume over the HMA by 1.4 %. This change poses unprecedented challenges, including potential water scarcity, ecosystem disruption, and increased risk of natural disasters, to HMA and surrounding regions.

Determinants influencing tourists’ willingness to visit Türkiye – Impact of earthquake hazards on Serbian visitors’ preferences

Abstract Earthquakes are a rather complex natural phenomenon that cannot be prevented, and their effects can be catastrophic and have profound implications on various economic sectors (especially tourism). This study investigates the relationships between subjective factors (gender, age, education, previous experience, and disaster anxiety), the perceived travel risk, and the travel intention of tourists from Serbia to destinations in Türkiye. The pilot study was done in March 2023 with 110 respondents from the Faculty of Science, Department of Geography, Tourism, and Hotel Management, Novi Sad. After the validation of the instruments, the main survey was conducted in the period from March to June 2023. The subjects of interest were residents of Serbia over the age of 18. The data from this study are analyzed using the confirmatory factor analysis and path analyses. This study aims to enhance the understanding of perceived risk and travel intention, specifically focusing on Türkiye. The assessed outcome relates to how tourists perceive three specific categories of risk when traveling to destinations with a high risk of natural disasters, such as earthquake-prone areas. The findings suggest that older respondents tend to perceive lower physical and financial travel risks, even though the influence of age on the perception of socio-psychological risks was inconclusive. Further results reveal that individuals with prior experience tend to hold a heightened perception of physical, financial, and socio-psychological risks. An examination of the relationship between disaster anxiety and perceived travel risks indicates that physical, financial, and socio-psychological risks exert a negative influence on travel intention. Thus, this study may provide a conceptual foundation for both theoretical and practical implications for the improvement of risk management techniques at a specific travel destination in areas prone to earthquake hazards.

Impact of natural disaster on agriculture in Tuyen Hoa district, Quang Binh province.

Abstract Climate change is a challenge for people whose livelihoods depend on agricultural production. In particular, the agricultural production activities of people in Tuyen Hoa district, Quang Binh province, were affected by natural disasters. Therefore, it is imperative to assess the natural disaster situation in Tuyen Hoa district by examining farmers’ awareness of potential climate and impacts on the crop and livestock sectors. Data related to climate change were provided by the authorities of Tuyen Hoa district communes and then analyzed in combination with local people’s perceptions using Excel software (2019). Quantitative data collected from semi-structured interviews through 241 farmer household surveys in Tuyen Hoa district was processed using computer software called Statistical Package for Social Sciences (SPSS 26) to calculate the potential impact index of natural disasters on agricultural production. Research results show that: (1) natural disasters (storms, tropical depressions, floods, droughts, Soil salinity) appear with high frequency, but landslides and flash floods have low frequency; (2) the risk of natural disasters impacting crop production is greater than livestock farming. Among them, storms, tropical depressions, floods, and droughts have a high impact. Landslides and flash floods have a low impact. (3) Communes located in the southeast of Tuyen Hoa district have a greater risk of natural disaster impacts than the remaining communes. This result will help local managers make appropriate adaptation measures for climate change and natural disasters locally.

Monitoring of vegetation changes based on RS monitoring in Changbai Mountain Nature Reserve

High vegetation cover helps maintain the ecosystem's stability and reduces the risk of soil erosion and natural disasters. Vegetation restoration is essential for the ecological value of Changbai Mountain Nature Reserve. In this study, the interannual changes in vegetation cover in Changbai Mountain Nature Reserve, China, from 2013 to 2022 were studied in depth based on Landsat remote sensing data and land use transfer matrix. The study includes interannual dynamic changes in vegetation types, quantitative analysis of interannual changes in surface vegetation types, and the land use transfer matrix analysis. In addition, the drivers of dynamic changes in vegetation types were analysed. The research indicates a notable advancement in ecological restoration within Changbai Mountain Nature Reserve between 2013 and 2022. There was a substantial reduction in the extent of barren land, which predominantly transitioned into grass and woodland areas. In particular, the year 2022 exhibited a significant increase in grassland area when compared to 2013, with a remarkable expansion of 27.18 square kilometers, primarily concentrated in the central-eastern sector of the study area. The findings of this investigation serve as a valuable scientific foundation for guiding ecological preservation and management decisions within Changbai Mountain Nature Reserve, contributing to a deeper comprehension of the evolving patterns in vegetation cover.

Reducing the negative impact of wildfire disasters through multi-scenario risk analysis of land investment

Natural meteorological and climatological hazards and vulnerable vegetation are frequent triggers of natural disasters, such as wildfires. These cause loss of life and significant economic damage, likely to increase due to climate and socio-economic changes. The increase in wildfires in recent decades has affected the decision-making of technocrats and policy experts and created the need for more sophisticated risk management. This paper develops a theoretical framework for reducing the economic impact of wildfire risk on forests. Also provides insight into land use decisions regarding losses that this increased risk of forest land management can cause. The impact of wildfire risk on economic land value is evaluated by comparing three scenarios, i.e. the deterministic risk-adjusted land expectation value with its risk-free counterparts calculated assuming the stationary risk and predicted increasing risk as time goes by. Also, for this purpose, we evaluate the economically optimal length rotation period pine stands and the risk premium. Fire risk is described as the probability of pine stands destruction due to their age and meteorological conditions in the experimental area Záhorská lowland (western Slovakia). Our findings highlight the importance of alerting forest policymakers to carefully incorporate assessment of the increasing risk of random natural disasters due to climate change into sustainable forest management. The study's results will also help current or future forest owners estimate and evaluate the economic/investing risk when buying or selling forest land.

Self-selection out of formal credit markets: evidence from rural Vietnam

PurposeThis paper examines why farmers self-select out of formal credit markets even though they need external funds.Design/methodology/approachWe use probit and Bayesian probit estimators to detect the determinants of self-selection behavior based on a primary dataset of 2,212 rice farmers in Vietnam. After that, we use the multinomial probit (MNP) and Bayesian MNP estimators to reveal the impact of relevant factors on the decision to self-select for farmers belonging to each self-selection category.FindingsThe probit and Bayesian probit estimators show that the decision to self-select depends on household head age, income per capita, farm size, whether or not to have relatives or friends working for banks, the number of previous borrowings, risks related to natural disasters, diseases, and rice price, and the number of banks with which the farmer has relationships. The MNP and Bayesian MNP estimators give further insights into the decision of farmers to self-select in that determinants of the self-selection behavior depend on the reasons to self-select. In concrete, farm size and the number of previous borrowings mitigate the self-selection of farmers who did not apply for loans due to having access to other preferred sources of credit. The self-selection of farmers not applying for loans because of unfavorable loan terms is conditional on household head age, farming experience, income, farm size, the number of previous borrowings, natural disaster risk, and the number of banks the farmer has relationships with. Several factors, including education, income, the distance to the nearest bank, whether or not having relatives or friends working for banks, the number of previous borrowings, risks, and the number of banks the farmer has relationships with, affect the self-selection of farmers not applying for loans because of high borrowing costs. The self-selection of farmers not applying for loans because of complex application procedures depends on income and the number of previous borrowings. Finally, the household head’s age, gender, experience, income, farm size, the amount of trade credit granted, the number of previous borrowings, natural disaster risk, and the number of banks the farmer has relationships with are the determinants of the self-selection of farmers not applying for loans because of a fear not being able to repay.Practical implicationsThis paper fills the knowledge gap by investigating why farmers self-select out of formal credit markets. It provides evidence of how the farmers’ subjective perceptions of rural credit markets contribute to their self-selection.Originality/valueThis paper shows that demand-side constraints are also vital for farmers’ access to bank credit. Improving credit access via easing supply-side constraints may not increase credit uptake without addressing demand-side factors. Given that finding, it recommends policies to improve access to bank credit for farmers regarding the demand side.

Broaden sustainable design and optimization of decarbonized campus Energy systems with scope 3 emissions accounting and social ramification analysis

A holistic approach that considers economic, environmental, and social dimensions is crucial for informed and responsible decision-making in energy system decarbonization. Integrating techno-economic, environmental, and social perspectives, we propose a multi-objective optimization framework for the sustainable design of decarbonized campus energy systems, resonating with the tri-fold principles of Corporate Social Responsibility. This comprehensive approach reveals the techno-economic intricacies inherent in adopting renewable solutions to accommodate cooling, heat, and power demand on university campuses. Our proposed model endeavors to minimize both total annualized costs and the broader spectrum of emissions (Scope 1, 2, and 3) in pursuit of environmental justice. Meanwhile, by merging life cycle assessment (LCA) with economic input-output analysis based on established social LCA databases, we can gauge the potential social impacts associated with these sustainability initiatives. The results serve as a roadmap for designing and operating truly sustainable campus energy systems, pinpointing environmental concerns, suggesting remedial strategies, and spotlighting the resultant social consequences. To showcase the tangible applicability of this holistic modeling framework, we have used real-world data from the main campus of Cornell University, Ithaca, New York State, to develop a case study. Our results show that with a plentiful biogas supply, it is possible to reduce yearly GHG emissions by more than 70%. Even when procurement emissions are left out, Scope 3 emissions still represent 69–82% of the total GHG emissions, dominated by the transportation sector. Turning to sustainable transport options, such as electric vehicles (EVs), can markedly lower these figures. On the socio-economic front, ramping up geothermal drilling could intensify negative social consequences, such as risk of forced labor, conflicts, accidents, and natural disasters, by 29%. These are primarily due to safety issues and the labor demands of earth source heat site preparation, encompassing risks such as forced labor and accidents. As the push for energy decarbonization grows stronger, it is imperative to weigh these downsides against the broader social benefits.