Key Socio-economic Factors Research Articles

Playing with fire: Socioeconomic factors and deliberate wildfires in Texas

Deliberately setting fires, also known as arson, is one of the primary causes of human-caused wildfires in the US. Arson fires pose a significant threat, contributing to the human-caused wildfire problem in the southern US. Since more than 90% of wildfires in the South are human-caused, it is particularly important to examine the factors that influence the distribution of arson wildfires in this region. While most research has combined arson fires together with other human-caused wildfires, a smaller body of studies has focussed specifically on fires started by arson. The focus of this study is to understand the key factors associated with the distribution of intentional wildfires in Texas. We examine the relationship between a combination of key socioeconomic factors and environmental factors and, arson wildfires using Negative Binomial models. As expected, our results indicate that road density, unemployment rate, and crime rate are positively associated with arson fires, and the number of law enforcement officers and wage rate are negatively associated with arson wildfire incidences. The higher percentage of forest cover in a county and higher temperature regimes are also positively associated with arson fire occurrences. As such, we conclude that arson wildfires are more likely in areas with high accessibility to wildlands. Similarly, counties with high unemployment rates and consequently high crime rates are more likely to suffer from arson wildfires. Our results clearly show that a higher presence of law enforcement officers in a county deter arsonists. Similarly, financial well-being as indicated by the higher wage rates in a county plays an apparent role in curbing arson wildfire occurrences. Thus, the results from this study provide valuable insights to policymakers, land managers, and fire prevention specialists to develop targeted interventions aimed at reducing arson risk in Texas and beyond.

Determinants of Healthcare Expenditure: A Cross-Sectional Analysis at the Country Level

This study examines the determinants of healthcare expenditure through a cross-sectional analysis of 153 countries using 2018 data. The research employs a classical linear regression model to identify key socioeconomic and demographic factors influencing healthcare spending per capita, expressed in PPP (Purchasing Power Parity). The results show that GDP per capita, public health expenditure as a percentage of GDP, physician availability, and out-of-pocket healthcare costs are statistically significant determinants of healthcare spending. Specifically, the analysis highlights the non-linear relationship between GDP and healthcare expenditure, where wealthier nations tend to spend disproportionately more on healthcare. Public investment in healthcare and the availability of medical professionals also play crucial roles in shaping national healthcare expenditures. Out-of-pocket expenses by households further increase overall healthcare costs, especially in countries with lower public funding. The proposed model explains 96.5% of the variation in healthcare expenditure, suggesting that the selected variables are strong predictors of healthcare spending. These findings provide valuable insights for policymakers, particularly in the context of balancing public healthcare financing and improving access to medical services while managing overall costs.

Innovations for Holistic and Sustainable Transitions

Energy system planning has evolved from a narrow focus on engineering and supply works towards addressing more complex, multifactorial challenges. Increasingly challenged by climate change, extreme events, economic shocks, and altered supply demand patterns, the analysis of energy systems requires holistic approaches based on data-driven models, taking into account key socio-economic factors. We draw insights from reviewing the literature, indicating the need to cover the following major gaps: the shift to transdisciplinary approaches, incorporating environmental system analysis; resilient and sustainable energy designs based on flexible portfolios of renewable mixes; the integration of socio-economic aspects, economic analyses and behavioural models to ensure energy systems are not only technically sound but socially acceptable and viable; the need for stakeholder engagement considering the human angle in energy security and behavioural shifts. Responding to these pressing challenges and emerging needs, the Global Climate Hub (GCH) initiative, operating under the UN Sustainable Development Solutions Network, offers a conceptual framework, leveraging transdisciplinary approaches. In this Concept Paper, we present for the first time the idea of the GCH as a framework that we believe has the potential to address the modern holistic needs for energy system analysis and policymaking. By setting the conceptual/theoretical ground of our suggested approach, we aim to provide guidance for innovative combinations of cutting-edge models, socio-economic narratives, and inclusive interaction with relevant stakeholders for the development and the long-term implementation of sustainable pathways.

Relationship between Scientific Management Practices Followed by Fish Farmers with their Socio-economic Profile Characteristics

This study investigates the relationship between the adoption of scientific management practices by fish farmers and their socio-economic profile characteristics in the Raichur district of Karnataka, India. Using an ex-post-facto research design, data were collected from 120 fish farmers across eight villages. The results indicate that 36.28% of farmers adopted scientific management practices at a medium level, while 33.72% and 30.00% reported low and high adoption levels, respectively. Key socio-economic factors influencing adoption included education, social participation, extension orientation, and mass media utilization. These findings underscore the need for targeted interventions to enhance adoption rates and improve fish farming productivity, thereby supporting rural economies. This revised abstract maintains the essential details while improving clarity and focus.

‘Leave no child behind’: investigating the undernutrition divide among Roma and non-Roma children in the Western Balkans

ABSTRACT Childhood undernutrition affects both physical and cognitive growth and is strongly associated with morbidity and mortality. United Nations’ pledge to ‘leave no one behind’ requires prioritizing policies that address inequalities and reach the most marginalized communities. Yet, undernutrition among Roma children is widely higher than that among children of the majority of the population, particularly in the Western Balkans. In light of this, we explore the determinants of the gap in undernutrition among Roma and non-Roma children in four Western Balkan countries, using several rounds of Multiple Indicator Cluster Surveys data. In the countries considered in this study, the prevalence of undernutrition among Roma children is nearly three times higher than that among non-Roma children. Even after controlling for key socioeconomic and demographic factors, Roma children remain particularly vulnerable to undernutrition. While the probability of stunting decreases in the non-Roma population as age progresses, it remains persistently high at all ages among Roma children. Our findings provide valuable insights for policymakers seeking to develop effective interventions to address the issue of undernutrition among marginalized communities.

Investigating the determinants of household energy consumption in Nigeria: insights and implications

BackgroundThe present study draws motivation from the United Nations Sustainable Development Goals and explores the nexus between access to modern cooking energy sources, responsible energy consumption, climate change mitigation, and economic growth. Using 2018 demographic and health survey data, the study examines the influence of key socioeconomic and demographic factors on household choice of cooking energy in Nigeria.ResultsThe empirical results show that traditional energy sources are dominant among Nigerian households (74.24%) compared to modern energy sources (25.76%). Regarding energy demographics, male-headed households show more usage of modern energy sources (19.86%) compared to female-headed households (5.90%). Regional analysis reveals that the northwest region predominantly uses traditional energy sources (18.60% of the share of total traditional energy sources), while the southwest region shows the greatest usage of modern energy sources (10.52% of the share of total modern energy sources). Binary logistic regression analysis reveals the positive and statistically significant influence of wealth index, education, and geopolitical region on the likelihood of utilizing modern energy sources. Conversely, household size and place of residence indicate an inverse relationship with the likelihood of adopting modern energy sources.ConclusionsThese findings have important policy implications for energy efficiency, environmental sustainability, and improving the quality of life in Nigeria, which is currently plagued with significant energy poverty, especially in rural communities.

Factors affecting continuous participation in follow-up evaluations during a lifestyle intervention programme for type 2 diabetes prevention: The Feel4Diabetes-study.

Community- and school-based lifestyle interventions are an efficient method of preventing type 2 diabetes in vulnerable populations. Many participants, however, fail to complete the necessary follow-ups. We investigated factors affecting the continuous participation in follow-up evaluations during the Feel4Diabetes-study, a multilevel intervention programme implemented across Europe. Socioeconomic, sociodemographic and clinical factors were assessed for 2702 participants within six participating countries: Bulgaria and Hungary (low-to-middle-income countries, LMIC), Belgium and Finland (high-income countries, HIC) and Greece and Spain (high-income countries under austerity measures, HICAM). Statistically significant differences were detected with respect to sex, control group, education level, employment status, BMI and blood pressure measurements (systolic and diastolic blood pressure). Post hoc analysis revealed significant differences within socioeconomic regions. Higher levels of education were associated with significantly lower attrition in HIC (p < 0.05) and HICAM (p < 0.001), higher employment status was associated with lower attrition in HICAM (p < 0.001) and being female was associated with lower attrition in LMIC (p < 0.001). Surprisingly, the intervention group exhibited higher-than-expected attrition in HIC (p < 0.001) and HICAM (p = 0.003), and lower attrition in LMIC (p = 0.007). When tested together in the same multivariable predictive model, all sociodemographic and socioeconomic variables along with higher BMI retained their statistical significance, while systolic and diastolic blood pressure failed to remain significant. Key socioeconomic and sociodemographic factors along with BMI play a significant role in determining continuous participation in follow-up evaluations during school- and community-based intervention programmes.

Research on social and economic factors influencing regional mortality patterns in China

Regional population mortality correlates with regional socioeconomic development. This study aimed to identify the key socioeconomic factors influencing mortality patterns in Chinese provinces. Using data from the Seventh Population Census, we analyzed mortality patterns by gender and urban‒rural division in 31 provinces. Using a functional regression model, we assessed the influence of fourteen indicators on mortality patterns. Main findings: (1) China shows notable gender and urban‒rural mortality variations across age groups. Males generally have higher mortality than females, and rural areas experience elevated mortality rates compared to urban areas. Mortality in individuals younger than 40 years is influenced mainly by urban‒rural factors, with gender becoming more noticeable in the 40–84 age group. (2) The substantial marginal impact of socioeconomic factors on mortality patterns generally becomes evident after the age of 45, with less pronounced differences in their impact on early-life mortality patterns. (3) Various factors have age-specific impacts on mortality. Education has a negative effect on mortality in individuals aged 0–29, extending to those aged 30–59 and diminishing in older age groups. Urbanization positively influences the probability of death in individuals aged 45–54 years, while the impact of traffic accidents increases with age. Among elderly people, the effect of socioeconomic variables is smaller, highlighting the intricate and heterogeneous nature of these influences and acknowledging certain limitations.

Selection of Key Socio-Economic Factors for Establishing Relese Criteria Patients after Radioioidine Therapy

Purpose: To assess the association between socioeconomic factors and release criteria after iodine-131 radionuclide therapy in different countries. Material and methods: 15 countries and 104 socioeconomic characteristics were selected for the study. The association between characteristics and the residual activity level at which a patient may be released for different countries was established according to the value of Pearson product moment correlation coefficient (r&gt;0.3). A linear regression model was constructed for the selected characteristics using Microsoft Excel analysis package. The model was used to calculate the acceptable activity level at which a patient may be released for Russia. Results: A fundamental difference between the model used for calculation of release criteria after radionuclide therapy with iodine-131 in Russia and the model recommended by the Nuclear Regulatory Commission was shown: the use of the effective half-life in the second one. Replacing the physical halflife by the effective half life allows increasing the discharge criteria of patients after therapy with Na131I by 30 %. A moderate correlation was found between the value of acceptable activity at patient discharge after radioactive iodine therapy and the following socioeconomic characteristics: scientific activity (r=0.32), quality of higher education (r=0.36), Global Health Security Index (r=0.34), length of roads (r=0.36), population growth rate (r=0.36), average housing area (r=0.38), and average salary per year (r=–0.33). A linear regression was constructed using the factors listed above. The following recommended value of activity and effective dose rate at patient discharge from hospital was obtained: 0.6 GBq and 30 µSv/hour. Conclusion: The study demonstrates that the release criteria for radioactive iodine therapy used in the Russian Federation (0.4 GBq and 20 µSv/h) do not correspond to the standard of living achieved in Russia, which is reflected by the socio-economic factors considered in the paper. The proposed arguments raise the task of revising the currently used model with a consequent increase in the discharge criteria. It was observed that the release criteria in the world are independent of some factors that are directly related to population exposure. The need to develop a unified objective algorithm for establishing release criteria, which takes into account different socio-economic status of states and can be applied for different radionuclides and radiopharmaceuticals, including innovative ones, has been identified.

Assessing the socio-economic factors affecting household waste generation and recycling behavior in Chennai: A survey-based study

This research paper investigates the socio-economic factors influencing household waste generation and recycling behavior in Chennai, India. The rapid urbanization and economic growth in Chennai have led to increased waste management challenges, making it imperative to understand the specific dynamics at play. The primary objectives of this study are to identify the key socio-economic factors affecting waste generation and recycling and to assess their implications for waste management policies. To achieve these objectives, a cross-sectional survey-based research design was employed. Data was collected through structured questionnaires administered to a sample of 500 households, encompassing various income levels, education backgrounds, and demographics. Statistical analysis, including multiple regression and logistic regression, was used to analyze the data. The key findings of this study indicate that monthly income significantly influences waste generation, with lower-income households producing more waste on average. Education level emerged as a predictor of recycling behavior, with higher-educated households exhibiting higher recycling rates. Additionally, the joint influence of income, education, age group, and gender on waste-related behaviors underscores the complex nature of socio-economic dynamics in waste management. These findings have significant implications for policy development. Tailored interventions are necessary to address income disparities and promote recycling awareness among different socio-economic groups. Furthermore, the study highlights the environmental and health impacts of socio-economic disparities in waste management, emphasizing the need for inclusive and sustainable waste practices.

Economic Evaluation of Ewanrigg Botanical Gardens in Zimbabwe Using an Individual Travel Cost Approach

Economists face an environmental goods and services valuation dilemma as natural resources are considered to be common pool resources with no markets. If markets exist they are mostly imperfect which results in undervaluation or overvaluation of natural resources. This study estimated the imputed recreational use value of Ewanrigg Botanical Gardens in Zimbabwe from 2015‑2017 using the Individual Travel Cost Method (ITC) which elicits the consumer surplus and deduces an optimum entry fee. It investigated key socioeconomic factors which influence visits to Ewanrigg Botanical Gardens. A questionnaire survey was conducted on 54 visitors to Ewanrigg Botanical Gardens during the period of the research to solicit for primary data. The primary data were analysed using the Ordinary Least Squares model to obtain a predictive model of visits to Ewanrigg Botanical Gardens. Using the ITC Method the total consumer surplus which equates to the recreational use value of Ewanrigg Botanical Gardens was USD19 142.16/peak period/year. Travel costs, income and employment status were the major factors driving visitation rates to Ewanrigg Botanical Gardens at an optimum entry fee of USD7.81. To maximise profits for self-sustenance of Ewanrigg Botanical Gardens, the Zimbabwe Parks and Wildlife Authority should concentrate on marketing efforts to individuals of higher income and solid employment status and those proximal to the botanical gardens as these incur less travel costs and can afford entry fees. For posterity, the use of ITC Method to ascertain economic value allows for the true valuation of natural resources and is justifiable for the allocation of funds by central government for the management and maintenance of artificial heritage sites such as Ewanrigg Botanical Gardens in developing African countries.

Education, employment, and income among people living with cystic fibrosis across three decades – A matched cohort study using Danish health registries

BackgroundPast and ongoing advancements in cystic fibrosis (CF) care warrant long-term analysis of the societal impact of the condition. This study aims to evaluate changes in key socioeconomic factors across three decades among people living with CF (pwCF), compared with both the general population and an early-onset chronic disease population. MethodsThis nationwide, registry-based, matched cohort study included all pwCF ≥ 18 years in Denmark in the years 1990, 2000, 2010, and 2018. Each person living with CF was matched to five individuals in the general population and five individuals living with type 1 diabetes or juvenile arthritis based on age, sex, and municipality. ResultsThe Danish adult CF population increased nearly fourfold from 88 in 1990 to 331 in 2018, and mean age increased by ten years. The educational level of pwCF was similar to the two comparator cohorts, while pwCF were less often in employment and more often permanently outside the labor force. Personal and household income levels of the CF cohort were higher than those of the comparator cohorts. ConclusionsThe disadvantage in employment for pwCF remained, but, over time, the societal profiles of the one-year CF cohorts increasingly converged with those of the comparator cohorts, indicative of improved clinical management, extended life expectancy, and the supportive role of the Danish welfare system in reducing health inequalities. Further research should be done to evaluate the effects of the newly introduced modulator therapies on employment, considering the broader societal impact and impact on quality of life.

Global economic structure transition boosts PM2.5-related human health impact in Belt and Road Initiative

The Belt and Road Initiative (BRI) is an open platform for international cooperation proposed by China to promote common global development and prosperity. The BRI can promote the optimal allocation of resources and promote in-depth cooperation in international trade. Meanwhile, it can establish a green supply chain cooperation network to help BRI countries achieve green transformation. BRI has made a notable contribution to the rapid growth of cross-border trade. However, it has also brought environmental impacts. Given that little attention has been paid to the trade-embodied particulate matter 2.5 related human health impacts (PM2.5-HHI) throughout the BRI, this study accounts for and traces the embodied PM2.5-HHI flows between the BRI countries and non-Belt and Road Initiative (non-BRI) countries. Moreover, this study also uncovers the critical socioeconomic drivers of PM2.5-HHI changes in BRI countries during 1990–2015, based on the multi-regional input-output based structural decomposition analysis (MRIO-SDA). Results show that, firstly, BRI countries had significantly increased their economic added value by exporting products to the non-BRI countries. They also have brought PM2.5-HHI to themselves. Secondly, the final demand of BRI countries was the largest potential driving force of PM2.5-HHI of BRI countries. Thirdly, the emission intensity change of BRI is the key socioeconomic factor for reducing PM2.5-HHI. While per capita final demand level change of BRI and production structure change of non-BRI are the key socioeconomic factors for increasing PM2.5-HHI. The study's findings on the one hand can help reduce the PM2.5-HHI and impacts of environmental pollution of BRI countries from a global perspective by providing scientific support. On the other hand, they can help provide relevant policy recommendations for the green transformation of BRI and the construction of green BRI.

Evaluating the Impact of Green Gentrification -A Case Study of London

In this research, we utilize the Ordinary Least Squares (OLS) regression method to explore the relationship between green gentrification and key socioeconomic factors within London's urban landscape. Our aim is to delve into the impact of introducing or expanding green spaces on residents' lives, particularly in relation to income, life expectancy, well-being, housing costs, and unemployment rates. Through the use of OLS regression and an extensive dataset sourced from empirical evidence, we quantitatively analyze the connections between green gentrification and variations in these socioeconomic variables across different neighborhoods. Our findings reveal noteworthy associations, highlighting positive correlations between green spaces and well-being, life expectancy, and house prices, while also noting a negative correlation with the unemployment rate. These insights contribute to a comprehensive understanding of the complex dynamics between urban development, environmental enhancements, and societal well-being, emphasizing the potential advantages of green gentrification and endorsing inclusive policies. Grounded in the OLS method, our research strengthens the empirical foundation for informed decision-making among policymakers, urban planners, and researchers dedicated to cultivating sustainable and equitable urban environments.

Health disparities in cervical cancer: Estimating geographic variations of disease burden and association with key socioeconomic and demographic factors in the US.

Despite advances in cervical cancer (CC) prevention, detection, and treatment in the US, health disparities persist, disproportionately affecting underserved populations or regions. This study analyzes the geographical distribution of both CC and recurrent/metastatic CC (r/mCC) in the US and explores potential risk factors of higher disease burden to inform potential strategies to address disparities in CC and r/mCC. We estimated CC screening rates, as well as CC burden (number of patients with CC diagnosis per 100,000 eligible enrollees) and r/mCC burden (proportion of CC patients receiving systemic therapy not in conjunction with surgery or radiation), at the geographic level between 2017-2022 using administrative claims. Data on income and race/ethnicity were obtained from US Census Bureau's American Community Survey. Brachytherapy centers were proxies for guideline-conforming care for locally advanced CC. Associations among demographic, socioeconomic, and healthcare resource variables, with CC and r/mCC disease burden were assessed. Between 2017-2022, approximately 48,000 CC-diagnosed patients were identified, and approximately 10,000 initiated systemic therapy treatment. Both CC and r/mCC burden varied considerably across the US. Higher screening was significantly associated with lower CC burden only in the South. Lower income level was significantly associated with lower screening rates, higher CC and r/mCC burden. Higher proportion of Hispanic population was also associated with higher CC burden. The presence of ≥1 brachytherapy center in a region was significantly associated with a reduction in r/mCC burden (2.7%). CC and r/mCC disparities are an interplay of certain social determinants of health, behavior, and race/ethnicity. Our findings may inform targeted interventions for a geographic area, and further highlight the importance of guideline-conforming care to reduce disease burden.

A LONGITUDINAL STUDY ON SNAP PARTICIPATION AND SELF-REPORTED HEALTH AMONG DIABETIC AND NON-DIABETIC INDIVIDUALS

Abstract Self-reported health is a strong predictor of future health status, new morbidity, mobility decline, illness recovery, and healthcare utilization. Because self-reported health is rooted in social position and social comparison, it dually reflects individual health perceptions and health inequities, especially among those who experience a social struggle for resources. Food insecurity is associated with higher risk of chronic diseases and higher mortality rates. Interventions such as the supplemental nutrition assistance program (SNAP) were created to help address food insecurity. Although morbidity and mortality risks caused by food insecurity is exacerbated for those with nutrition-centered chronic disease, such as diabetes, limited research has assessed the impact of food insecurity and SNAP participation on health among diabetics. Using Health and Retirement Study data, we explore the effect of SNAP participation and food insecurity on the likelihood of reporting fair or poor health comparing 24,446 diabetes to 69,260 non-diabetics individuals aged 65 and above (2004-2020). Our analysis controls for key socioeconomic factors, including age, gender, race/ethnicity, and wealth, accounting for the complex design of HRS. Our key findings reveal that food insecure diabetics have significantly higher odds of reporting fair/poor health, and diabetic SNAP participants also had significantly higher odds of reporting fair/poor health. Our study demonstrates how food insecurity and diabetes concurrently influence health and how, despite the presence of resources, such as SNAP, there was no improvement in self-reported health. This study is important as it highlights the need for future research on the effects of SNAP participation and self-reported health.

Contribution of socio-economic determinants to the management of sustainable performance: case study of Moroccan companies with Corporate Social Responsibility label

In a dynamic environment marked by significant shifts in production and marketing systems across various industries, companies are compelled to adhere to national and international standards to meet evolving demands from both internal and external stakeholders. These emerging requirements have spurred companies to adopt strategic initiatives, such as emphasizing Corporate Social Responsibility (CSR), as part of their managerial actions. The primary aim is to integrate two key management science themes: indicators derived from management control systems and the management of sustainable performance. Consequently, our focus lies in the socio-economic approach, particularly the socio-economic cost-value of activities, which influences the diversity of indicators on one hand and the management of sustainable performance on the other hand, mediated through their variety. This underscores the importance of managing sustainable performance by utilizing measures and data tied to socio-economic fundamentals, prompting us to formulate our research question as follows: "To what extent does the cost-value of activities impact the management of sustainable performance?" The empirical investigation transitions from simply describing variables within our sample companies to conducting factor analysis via Principal Component Analysis-PCA. This aims to establish a robust factorial structure and subject several constructs to testing, assessing the internal consistency of the model, the quality and reliability of the sample, and the validity of research hypotheses. Our findings align with prior research, indicating that diverse indicators can inform managers about social and environmental practices, fostering positive effects on sustainable firm performance. However, excessive reliance on these indicators may lead to confusion and dispersion within companies. Hence, it's imperative to tailor indicators to the specific context and objectives of each firm, considering industry-specific nuances. Our study demonstrates that leveraging a diverse range of indicators is pivotal for enhancing sustainable performance dimensions and managing socio-economic factors amidst external pressures. Evaluating the measurement model is crucial for validating the reliability and validity of measurement instruments, as well as assessing the structural model's overall quality, which includes tests like coefficient of determination-R², Goodness of fit-GoF, and others. It's important to note that our measurement model encompasses both reflective and formative constructs. The structural model's quality is gauged by its explanatory power, evaluated through R², indicating explained variance in the variables under scrutiny. To address this issue, we chose to examine the connections between key socio-economic factors and the management of sustainable performance in Moroccan companies certified with CSR labels. Through structural equation modeling, we found that effectively managing the cost-value of activities using diverse indicators plays a significant role in enhancing sustainable performance within CSR-certified companies.

How Layers of Context and Material Deprivation Impact Reemployment in Stable or Casual Work

Reemployment for those who are unemployed is both economically and socially important but may be constrained because of the person’s context. The current study investigates key socioeconomic, structural, and individual factors that may impact the likelihood of reemployment for unemployed working age adults over the period of a year. Reemployment is further separated in terms of stability and security by delineating casual versus non-casual reemployment. A multinomial regression analysis of an Australian dataset (n = 375 adults who reported no limitation to their ability to gain employment) found that economic constraints played a substantial role and that the context issues act differently by employment type if reemployed. The results highlight the importance of socio-structural issues, reflecting resource asymmetry. Supportive neighborhoods and material deprivation set the scene, while education enables the pursuit of more stable and secure employment opportunities.

Spatial bayesian approach for socio-economic assessment of pumped hydro storage

Pumped hydro energy storage (PHES) is a key enabler for transitioning to 100 % renewable energy sources. However, PHES site selection is multi-faceted and challenging, including from a socio-economic perspective, due to complex economic issues and the heterogeneity of social factors. To overcome this challenge, this study developed a spatial probabilistic decision-making approach to identify and rank the best PHES sites from a shortlisted number of sites determined from a previous techno-environmental assessment. This model was developed in a participatory environment, where both study evidence and experts’ judgements were utilised to determine the key socio-economic factors, develop the Bayesian Network (BN), and populate the conditional probability tables (CPT). The BN parent node data were retrieved from publicly available sources in a high-resolution spatial and statistical format. An ArcGIS 10.3 tool was utilised to process the data with spatial characteristics, whereas GeNIe 2.5 was used to develop the BN model. Forward propagation, sensitivity, and strength analysis were performed to validate the developed BN model. Application of the spatial-BN model to northern Queensland, Australia reduced the fourteen previously determined techno-environmentally suitable PHES sites, to nine sites that are suitable from a socio-economic perspective for future developments. These nine sites could store and generate over 323 TWh of electricity over their life expectancy and at a levelised cost of 0.040–0.274 AU$/kWh. The developed procedure and model streamline the PHES site selection pre-feasibility process, thereby expediting renewable energy transition.

Incorporating Social and Policy Drivers into Land-Use and Land-Cover Projection

Forestlands in the southeastern U.S. generate a great variety of ecosystem services that contribute to the well-being of humans and nonhumans alike. Despite their importance, forests continue to be lost to other land uses such as agricultural production and urban development. Advancements in remote sensing and machine learning techniques have facilitated land use/land cover (LULC) change projections, but many prior efforts have neglected to account for social and policy dimensions. We incorporated key socio-economic factors, conservation policies, societal preferences, and landscape biophysical features into LULC projection techniques under four different development scenarios. We applied this approach in the Upper Flint watershed, which flows south from the Atlanta, Georgia metropolitan area and is characterized by extensive urbanization and associated deforestation. Our results suggest that incorporating social and policy drivers in future LULC projection approaches leads to more realistic results with higher accuracy levels, offering decision-makers, development planners, and policymakers better opportunities to forecast the effects of anticipated changes on the availability of ESs in the future. Conservation organizations and public agencies can benefit from such analysis to identify regions requiring conservation interventions for prioritizing their conservation efforts. We used publicly available data for the conterminous U.S., hence our approach can be replicable in other study regions within the nation.