Clean Fuels Research Articles

Household polluting cooking fuels and intrinsic capacity among older population: A harmonized nationwide analysis in India and China

BackgroundsHousehold polluting cooking fuels, as an important changeable behavior, are related to various detrimental health effects among the elderly. There is limited research on the association between polluting cooking fuel use and intrinsic capacity (IC) as an indicator of healthy aging. This study aimed to evaluate the above-mentioned association in India and China, where polluting cooking fuel use is common. MethodsWe enrolled 33,803 participants aged ≥60 years from two nationally representative studies: the Longitudinal Aging Study in India and the China Health and Retirement Longitudinal Study. Polluting cooking fuel use was defined as a self-report of using wood, coal, kerosene, crop residue, or dung. IC was measured by five aspects, including locomotion, cognition, vitality, sensory, and psychological capacity. The random-effects mixed linear regression and logistic regression with population weighting were performed. Multivariable-adjusted model and propensity score were used to adjust for potential confounders. ResultsA total of 47.54 % and 59.32 % of elderly adults reported primary cooking using polluting fuels in India and China, respectively. Using polluting cooking fuels was consistently associated with IC decline; particularly, cognitive capacity was the most susceptible domain. In India, participants using polluting fuels had a 1.062 (95 % confidence interval [CI]: 1.047–1.078) times risk for IC deficits, whereas more prominent results were observed in China (odds ratio [OR]: 2.040, 95 % CI: 1.642–2.533). Such harmful effects might be alleviated by transferring from polluting to clean fuels. Additionally, the duration of polluting fuel use was also positively associated with IC deficits. ConclusionThis study provided substantial public implications on healthy aging for the elderly population at a global scale, strengthening the importance of health education and policy efforts to accelerate the transition from polluting to clean fuels.

Evaluation of the preference for and viability of clean cookstove adoption in rural Tanzania

BackgroundSustainable Development Goal (SDG) 7 calls for “universal access to affordable, reliable, modern energy services” for the 2.6 billion individuals lacking access to clean cooking fuels and stoves. Low- and middle-income countries are designing policies towards clean fuels, but often prioritize World Health Organization defined ‘clean’ fuels and stoves to urban areas. As clean solutions are explored, it remains unclear what rural households prefer as their clean alternative.MethodsThis study conducted household energy surveys with main cooks across four villages in Shirati, Tanzania to understand rural household preferences within the viable clean fuels. Data analysis includes descriptive statistics and a generalized linear model with the Poisson family and log link to estimate prevalence ratios, all of which were conducted in Microsoft Excel and STATA 16.1.ResultsThe results revealed that while 83% of households (n = 187) stacked a combination of firewood, charcoal, liquified petroleum gas (LPG), and/or kerosene, 82% [95% Confidence Interval: 74%, 89%] of households stated a preference to use LPG. We found that aggregate expenditure on LPG was less than daily purchases of charcoal and firewood. Our analysis found that all villages had a higher prevalence of stacking firewood, charcoal, and LPG, than areas further from the main trading center. Both areas with trading posts had a lower prevalence of using only firewood.ConclusionsHousehold preference should be systematically incorporated into clean cooking policy decisions. Our results imply that LPG should not be pursued only in urban contexts. We discuss how preference affect adoption and the need to include user preferences to meet universal clean cooking access (SDG 7).

Spatial variation and determinants of solid fuel use in Ethiopia; Mixed effect and spatial analysis using 2019 Ethiopia Mini Demographic and Health Survey dataset.

According to UNSD, World Bank, and WHO, a 2020 joint report, 3 billion people who used solid fuel were found in low and middle-income countries. The burning of such type of fuel emits a variety of pollutants such as PM2.5, PM10, CO, NO2, organic compounds, and other substances which a had wide range of public health problems The evidence from the WHO report, indoor air pollution was attributed to around 3.2 million deaths each year in 2020, and more than 237 000 deaths of children under the age of five. This study aims to investigate solid fuel prevalence, predictors, and spatial variation in Ethiopia. This study was conducted in Ethiopia based on the fifth Ethiopian Demographic and Health Surveys 2019 dataset. 8,663 households were successfully interviewed at a response rate of 99%. Weighted by sampling weight was done to do a reliable statistical analysis. Fuel type was used as the outcome variable whereas sex of household head (male or female), wealth index (poor, middle, and rich), educational status (no education, primary, secondary, higher), having television and radio, a separate room used as a kitchen, were individual predictor variables and community level education(lower/higher), residence(urban/rural), community level media exposure (exposed/unexposed), region (pastoralist, semi-pastoralist, Agrarian, and City administration) were community level variables. All the above analyses were conducted using Excel Microsoft 2016, STATA 14, ArcGIS 10.7, and SaTScan 10.1 software. The majority (72.62%) of household heads were males. The overall national level of solid fuel use was 87.13% (95% CI (86.4%-87.82%)). From this 87.13% of solid fuel use, 18.60% accounts for urban and 68.53% for rural parts of the country. Educational status, having television, accessing electricity, and wealth index were individual-level variables community-level education, type of residence, and region were community-level variables significantly associated factors towards solid fuel use in our study. Global (z-score = 33.109144, P-value <0.0001), local (hot spot, cluster, and outlier), and Spatial Scan statistical analyses revealed that there was a major geographical variation in solid fuel use across Ethiopia. Based on this finding, the prevalence of solid fuel use was higher in Ethiopia. Educational status, having television, accessing electricity, and wealth index were individual-level variables and community-level education, type of residence, and region were community-level variables statistically significant factors in determining fuel choice for cooking. There was significant spatial variation in the prevalence of solid-fuel use across the country. In order to addressing such heavily dependent on solid fuel use, responsible bodies like health policy makers, national and international organizations, and public health researchers should work on showing health problems of solid fuel use and the means of increasing clean fuel use. Substantial policy modifications are desirable to reach access to clean fuels and technologies (SDG 7.1.2) by 2030 to address health inequities.

Shaping Methods of Metal–Organic Frameworks for Natural Gas Storage

The eco-friendly advantages of cleaner fuels such as natural gas have been extensively documented. However, the practical utilization of these fuels is restricted by the limitations of existing gas storage technologies. In this discussion, this paper evaluates the broad spectrum of possibilities that gas fuels present for transforming the energy sector, while also addressing the hindrances posed by current storage technologies that impede this transition. This paper scrutinizes the practical implications of natural gas storage, employing crystalline, porous metal-organic frameworks (MOFs) while referring to the latest benchmark outcomes and ultimate storage objectives in this domain. Specifically, this delve into the industrial constraints posed by the typically powdered form of MOFs and emphasize the recent advancements in MOF shaping. In contrast to their unprocessed powder condition, the features of MOFs as shaped in this study are examined, and a full review of several structuring methods is provided. The industrial usage of MOFs in applications involving gas processing is anticipated to be accelerated by this research.

Moving Beyond Clean Cooking Energy adoption: Using Indian ACCESS panel data to understand solid fuel suspension

Household solid fuel use has adverse impacts on health and the environment. The Indian government's Pradhan Mantri Ujjwala Yojana (PMUY) subsidy promoted the adoption of Liquid Petroleum Gas (LPG) by millions of Indian households. There is little knowledge, however, regarding decision-making to reduce solid fuel use after adopting cleaner fuels. Leveraging panel data on household energy use in rural India we jointly estimated LPG adoption and consumption to study the reduction in solid fuel use. Our results indicate that exclusive LPG use increased from 4.5% to 17.8% between 2015 and 2018 while fuel stacking (use of multiple fuels) doubled from 18% to 39%. The household's wealth index, self-reported higher social strata, business ownership, head of household's educational level, and the proportion of LPG-using households in the village were positively associated with LPG consumption and suspension of solid fuels. Distance to LPG refill delivery, household size and PMUY subsidy were negatively associated with LPG share though LPG share was positively associated with the interaction of PMUY with wealth index. Policy efforts should target sustained LPG consumption by making refill delivery more accessible and implementing a pro-poor refill subsidy as well as general poverty alleviation (e.g., by creating income generation opportunities).

Household exposure to the risk of cooking smoke: Evidence from Sub-Saharan Africa

BackgroundIn Sub-Saharan Africa, the place of cooking and choice of fuel for cooking have detrimental effects on health due to excessive exposure to smoke. This study explores household-level exposure to the risk of cooking smoke and its associated determinants. MethodsUsing a quantitative approach, we pooled the most recent waves of the Demographic Health Survey dataset yielding 442,339 households from 33 countries in Sub-Saharan Africa. In this study, we first construct disaggregated measures of smoke exposure risk, determine the extent of households’ vulnerability to this risk, and investigate the associated determinants. We used the ordered probit regression to examine the socio-demographic and economic determinants of the levels of household smoke exposure risk in SSA. ResultsWe found evidence that 67 % of households cook indoors while 86 % use smoke-producing fuels for cooking which, may indicate a high level of vulnerability to smoke exposure. As expected, 53 % of households have a high risk of smoke exposure. Our findings reveal factors such as wealth, size, educational level, and age of household heads as the key determinants of the disaggregated smoke exposure risk measures. For robustness, we grouped households by their rural-urban locations to establish evidence of the determinants. ConclusionsThe study identifies socio-economic characteristics as essential variables in determining a household's level of exposure to cooking smoke risk in SSA. We, therefore, propose to policymakers in the sub-region to improve the accessibility to clean cooking fuels, especially to all rural households. In this light, we recommend the promotion, subsidization, and enforcement of policies to encourage households to use clean cooking fuels.

Quantile time-frequency connectedness among G7 stock markets and clean energy markets

The rapid growth of clean energy markets as a distinct asset class has attracted significant investor attention. This study examines the interdependence between G7 stock markets and clean energy indices, specifically Renewable Energy Generation (REG), Energy Efficiency (EE), Advanced Materials (AM), and Clean Fuels (CF). Using a state-of-the-art volatility connectedness network and Maximum Overlaps Discrete Wavelet Transform (MODWT), we investigate the quantile time-frequency connectedness among the markets. Our findings reveal strong volatility linkages among all markets, with the exception of Clean Fuels, which has the least connection. We also observe higher dynamic spillover effects under extreme market conditions than normal conditions, with the US market being the most important transmitter of spillovers under bullish markets. Additionally, we highlight the importance of considering the time-varying nature of connectedness, emphasizing the heterogeneity between short-run, medium-run, and long-run transmission. Our study's implications suggest that investors should consider the dynamic nature of spillovers and connectedness when constructing portfolios containing clean energy and G7 stock market assets. The results also imply that the US market's performance has a substantial impact on other markets under bullish conditions, and that Clean Fuels may present an attractive investment opportunity for diversification purposes due to its relative independence.

Evaluating algorithms of decision tree, support vector machine and regression for anode side catalyst data in proton exchange membrane water electrolysis

Nowadays, due to the various type of problems stemmed from using chemical compounds and fossil fuels which have widely influence on whole environment including acid rain, polar ice melting and etc., number of researches have been leading on replacing the nonrenewable energy sources with renewable ones in order to produce clean fuels. Among these, hydrogen emerges as a quintessential clean fuel, garnering substantial attention for its potential to be synthesized from the electric power generated by renewable sources like nuclear and solar energies. This is achieved through the employment of a proton exchange membrane water electrolysis (PEMWE) system, widely recognized as one of the most proficient and economically viable technologies for effecting the separation of H2O into H+ and OH−. In this study, the important affecting parameters on the anode side of catalyst in PEMWE and analyzed them by machine-learning (ML) algorithms through developing a data science (DS) procedure were discussed. Various machine learning models were subjected to comparison, wherein the Decision Tree models, specifically those configured with maximum depths of 3 and 4, emerged as the optimal choices, attaining a perfect 100% accuracy across both Dataset 1 and Dataset 2. Moreover, notable enhancements in accuracy values were observed for the Support Vector Machine (SVM) model, registering increments from 0.79 to 0.82 for Dataset 1 and 2, respectively. In stark contrast, the remaining models experienced a decrement in their accuracy scores. This phenomenon underscores the pivotal role played by the data generation process in rendering the models more faithful to real-world scenarios.

Bio-Inspired Supramolecular Self-Assembled Carbon Nitride Nanostructures for Photocatalytic Water Splitting.

Fast production of hydrogen and oxygen in large amounts at an economic rate is the need of the hour to cater to the needs of the most awaited hydrogen energy, a futuristic renewable energy solution. Production of hydrogen through simple water splitting via visible light photocatalytic approach using sunlight is considered as one of the most promising and sustainable approaches for generating clean fuels. For this purpose, a variety of catalytic techniques and novel catalysts have been investigated. Among these catalysts, carbon nitride is presently deemed as one of the best candidates for the visible light photocatalysis due to its unique molecular structure and adequate visible-range bandgap. Its bandgap can be further engineered by structural and morphological manipulation or by doping/hybridization. Among numerous synthetic approaches for carbon nitrides, supramolecular self-assembly is one of the recently developed elegant bottom-up strategies as it is bio-inspired and provides a facile and eco-friendly route to synthesize high surface area carbon nitride with superior morphological features and other semiconducting and catalytic properties. The current review article broadly covers supramolecular self-assembly synthesis of carbon nitride nanostructures and their photocatalytic water-splitting applications and provides a comprehensive outlook on future directions.

Unique structure and thermal reduction performance of a novel doping modified porous ceria

H2/CO clean fuels produced by solar-driven thermochemical H2O/CO2 splitting provides an alternative to fossil fuels as well as mitigates global warming. The success of this technology relies on the advancements of redox materials, and ceria has been regarded as a promising one for its some advantages. In this study, a new porous framework ceria was developed, which has the characteristics of two-stage pores, the porosity up to 90%. To promote the thermal reduction process, the ceria is modified by heterogeneous metal ions doping, which can cause lattice distortion and improve thermal reduction performance significantly. The effects of heterogeneous metal ions on structure and thermal reduction performance were explored.

Synergistic Effect of Nickel Nanoparticles Dispersed on MOF-Derived Defective Co3O4 In Situ Grown over TiO2 Nanowires toward UV and Visible Light Driven Photothermal CO2 Methanation.

Catalytic CO2 hydrogenation is an effective approach to producing clean fuels, but this process is expensive, in addition to the low efficiency of catalysts. Thus, photothermal CO2 hydrogenation can effectively utilize solar energy for CH4 production. Metal-organic framework (MOF) derived materials with a controlled structure and morphology are promising to give a high number of active sites and photostability in thermal catalytic reactions. For the first time, a novel heterostructure catalyst was synthesized using a facile approach to in situ grow MOF-derived 0D Co3O4 over 1D TiO2 nanowires (NWs). The original 3D dodecahedral structure of the MOF is engineered into novel 0D Co3O4 nanospheres, which were uniformly embedded over Ni-dispersed 1D TiO2 NWs. In situ prepared 10Ni-7Co3O4@TiO2 NWs-I achieved an excellent photothermal CH4 evolution rate of 8.28 mmol/h at 250 °C under low-intensity visible light, whereas UV light treatment further increased activity by 1.2-fold. UV irradiations promoted high CH4 production while improving the susceptibility of the catalyst to visible light irradiation. The photothermal effect is prominent at lower temperatures, due to the harmonization of both solar and thermal energy. By paralleling with mechanically assembled 10Ni-7Co3O4/TiO2 NWs-M, the catalytic performance of the in situ approach is far superior, attributing to the morphological transformation of 0D Co3O4, which induced intimate interfacial interactions, formation of oxygen vacancies and boosted photo-to-thermal effects. The co-existence of metallic/metal oxide Ni-Co provided beneficial synergies, enhanced photo-to-thermal effects, and improved charge transfer kinetics of the composite. This work uncovers a facile approach to engineering the morphology of MOF derivatives for efficient photothermal CO2 methanation.

Enhanced Long‐Term Stability of a Photosensitizer with a Hydroxamic Acid Anchor in Dye‐Sensitized Photocatalytic Hydrogen Generation

AbstractClimate change mitigation on a global scale will only be possible through the achievement of ambitious decarbonisation goals, requiring an energy transition that involves switching from fossil fuels to clean fuels such as hydrogen. The photocatalytic approach is one of the most studied methods for directly converting sunlight into hydrogen. In this work, we present the synthesis, characterization, and application of the PTZ1‐HA dye, which was obtained by replacing the terminal conventional carboxylic anchoring moieties of a previously studied phenothiazine‐based dye (PTZ1) with hydroxamic acid functionalities. The photoinduced performance of the two dyes as photosensitizers was compared in both dye‐sensitized solar cells and dye‐sensitized photocatalytic systems. PTZ1‐HA‐sensitized photocatalysts showed improved stability in hydrogen generation due to the introduction of the hydroxamic acid as an alternative anchor group, which was shown to slow down hydrolysis in aqueous media. Even though the light harvesting ability of PTZ1‐HA was lower than that of PTZ1, the higher stability of PTZ1‐HA‐sensitized devices allowed for improved photocatalytic generation of H2 over prolonged periods. The superior long‐term efficiency of the hydroxamic acid based dye is important in view of potential practical applications.

Research on Full Premixed Combustion and Emission Characteristics of Non-Electric Gas Boiler

NOx has become one of the main culprits causing the global greenhouse effect, and excessive emissions of NOx can also cause some common diseases in humans. The denitrification of power plant boilers has been 100% popularized, and their denitrification efficiency has reached national and local environmental requirements (such as Selective Catalytic Reduction, SCR). However, small gas boilers, due to their use of relatively clean fuels, have relatively low NOx emissions. But, local environmental protection departments have weak supervision of small clean fuel boilers, and these equipment generally lack specialized denitrification equipment, resulting in NOx emissions still not meeting standards. In addition, there are many small gas boilers, resulting in high total emissions. The fully premixed burner of a small gas boiler has the effect of suppressing NOx production during combustion. This study designed a surface porous burner with different combustion intensities at different positions. The experimental results and numerical calculations show that for horizontal combustion, the burner has different intake rates at different axial positions, enabling uniform combustion throughout the entire furnace, with NOx emissions below 30 mg/Nm3. The numerical simulation results show that the NOx emissions are 26.6 mg/m3. The calculated results are in good agreement with the actual situation. The generation of NOx is mainly thermal, with a maximum error of 15.4% between the calculated and experimental values. The difference between the calculated value of O and the experimental one is 5.1%. It can be seen that numerical simulation has considerable accuracy.

Quantifying national household air pollution (HAP) exposure to PM2.5 in rural and urban areas

According to WHO (World Health Organization), in 2020, 14% of people in global urban areas relied on polluting solid fuels and technologies, compared with 52% of the rural population. The health impacts of such inequality are massive. It was estimated that 3.2 million premature deaths per year (2020), particularly in low-income and middle-income countries due to household air pollution (HAP). Several studies provide estimates of the exposure to fine particulate matter (PM2.5) from household air pollution (HAP-PM2.5) for users of different fuel/cookstove types in rural and urban areas. However, hardly any studies estimate the population-weighted exposure to HAP-PM2.5 at the global scale. A Bayesian hierarchical model was developed to estimate PM2.5 exposure coefficients and their uncertainties for an annual average of HAP-PM2.5 personal exposure. The predicted HAP-PM2.5 exposure at the user level was used to estimate the national-level exposure for the population living in urban and rural areas. The results suggest that switching from polluting solid fuels (biomass, charcoal, coal) to cleaner fuels (gas and electricity) for heating and cooking can potentially reduce the national-level HAP-PM2.5 personal exposure on average by 53%. However, there exists a significant disparity between rural and urban areas, partly reflecting inequality in energy access. More specifically, switching from polluting solid fuels for heating and cooking to cleaner fuels can reduce the personal exposure to HAP-PM2.5 in rural areas by 54% and in urban areas by 38%. The study indicates that increased access to clean fuels and improved stove interventions are needed to achieve the goals of universal energy access and equality between urban and rural areas.

Maximizing efficiency and environmental benefits of an algae biodiesel-hydrogen dual fuel engine through operational parameter optimization using response surface methodology

The utilization of clean and renewable fuels has become increasingly significant in the power generation and transportation sectors. Dual-fuel engines that employ hydrogen and algal biodiesel are potential alternatives. This study investigated the impact of pilot fuel injection pressures and engine loads on the performance and emissions of an algal biodiesel-hydrogen dual-fuel engine. The engine was optimized using response surface methodology under various operating conditions. The highest brake thermal efficiency (28.71 %) was obtained at 240 bar pilot fuel injection pressure and 100 % engine load, significantly reducing carbon monoxide and hydrocarbon emissions. The optimum parameters were identified using response surface methodology at 67.63 % engine load and 245.48 bar pilot fuel injection pressure, with a high model fit (R2) range of 88.89 %–99.59 % and composite desirability of 96.1 %. The potential for optimizing algal biodiesel-hydrogen dual-fuel engines to achieve greater efficiency and environmental benefits is highlighted in this work, as is the relevance of applying response surface methods to optimize engine performance.

Influence of Socioeconomic, Demographics, and Prices Factors on Cooking Fuel Choice of Indonesian Households

AbstractThere are differences in the choice of cooking fuel in Indonesian households. Some households still not yet used clean fuel for daily cooking, even though clean energy is crucial and included in the Sustainable Development Goals (SDGs). This study examines the influence of several factors on household's cooking fuel choice using SUSENAS data. This study is based on conceptual framework and theory on several determinant factors, including income, education level of the household head, and energy prices. The testing of the hypothesis used the probit methods. In the estimation results obtained, socioeconomic and demographic factors, namely income, education level of the household head, location of the household in urban areas, positively and significantly impacts the decision to choose clean fuel for cooking. Meanwhile, the price of clean fuel types such as LPG and city gas negatively and significantly impacts the decision to choose clean fuels for cooking in Indonesian households.Keywords: Demographic Factors; Socioeconomics Factors, Energy Prices; Cooking Fuel Choice, Probit

Decarbonising ASEAN coastal shipping: Addressing climate change and coastal ecosystem issues through sustainable carbon neutrality strategies

This study analyzes the impact of ASEAN's goal of achieving carbon neutrality by 2050 on climate change and coastal ecosystems by examining carbon emissions and energy usage from 2019 to 2050 using different scenarios to reduce emissions and meet global temperature goals. This research proposes strategies to reduce carbon emissions and mitigate climate change effects on coastal ecosystems, focusing on evaluating CO2 emissions from ASEAN's coastal shipping sector. Geospatial data was used to analyze ship activity and develop carbon neutrality strategies. Various sources are used to gather data, including the Maritime Portal, exact Earth AIS, FASA and GFW. This study finds that container ships emitted 13.7 × 106 t of CO2 in 2019, with the transportation sector contributing 3.8% of the total greenhouse gas in 2020. Without regulations, CO2 emissions could increase fourfold by 2050. The study recommends implementing policies such as adopting clean fuels, energy efficiency standards and fuel-related regulations to reduce CO2 emissions by 65–80% by 2050. It also emphasizes the importance of cleaner technologies, regulatory considerations and collaboration, which would have positive implications for coastal ecosystems. This study is beneficial to professionals in the maritime and shipping industries, policy makers, environmental consultants, sustainability specialists, and international organizations.

Conversion of Vacuum Residue from Refinery Waste to Cleaner Fuel: Technical and Economic Assessment

Environmental concerns surrounding the use of high-sulfur fuel oil (HFO), a marine fuel derived from refinery vacuum residue, motivate the exploration of alternative solutions. Burning high-sulfur fuel oil (HFO) is a major source of air pollution, acid rain, ocean acidification, and climate change. When HFO is burned, it releases sulfur dioxide (SO2) into the air, a harmful gas that can cause respiratory problems, heart disease, and cancer. SO2 emissions can also contribute to acid rain, which can damage forests and lakes. Several countries and international organizations have taken steps to reduce HFO emissions from ships. For example, the International Maritime Organization (IMO) has implemented a global sulfur cap for marine fuels, which limits the sulfur content of fuel to 0.5% by mass. In addition, there is a worldwide effort to encourage the use of low-carbon gases to help reduce greenhouse gas (GHG) emissions. There are several alternative fuels that can be used in ships instead of HFO, such as liquefied natural gas (LNG), methanol, and hydrogen. These fuels are cleaner and more environmentally friendly than HFO. The aim of this study is to develop a process integration framework to co-produce methanol and hydrogen from vacuum residue while minimizing the sulfur and carbon emissions. Two process models have been developed in this study to produce methanol and hydrogen from vacuum residue. In case 1, vacuum residue is gasified using oxygen—steam and the syngas leaving the gasifier is processed to produce both methanol and hydrogen. Case 2 shares the same process model as case 1 except it is concentrated on mainly methanol production from vacuum residue. Both models are techno-economically compared in terms of methanol and H2 production rates, specific energy requirements, carbon conversion, CO2 specific emissions, overall process efficiencies, and project feasibility while considering the fluctuation of vacuum residue feed price from 0.022 $/kg to 0.11 $/kg. The comparative analysis showed that case 2 offers an 86.01% lower specific energy requirement (GJ) for each kilogram (kg) of fuel produced. The CO2 specific emission also decreased in case 2 by 69.76% compared to case 1. In addition, the calculated total net fuel production cost is 0.453 $/kg and 0.223 $/kg at 0.066 $/kg for case 1 and 2, respectively. Overall, case 2 exhibits better project feasibility compared to case 1 with higher process performance and lower production costs.

Paradox of Book and Claim for Carbon Emission Reduction in Maritime Operations Management: Mathematical Models and Numerical Experiments

In recent years, the maritime industry’s carbon emissions have garnered increasing attention, leading to the proposal of various policy measures aimed at mitigating emissions and fostering a green and sustainable maritime sector. Among these measures, the book and claim mechanism, which allows shippers to access low or zero-emission bunkering by purchasing such fuels without physically participating in the refueling process, has emerged as a crucial catalyst for fuel conversion within the maritime industry. While book and claim has gained widespread recognition and facilitated the sale of clean fuels by some bunker suppliers, there has been limited research focused on evaluating its practical efficacy. Thus, we construct two distinct Mixed-Integer Linear Programming (MILP) models—one with the inclusion of the book and claim mechanism and one without—and conduct an analytical comparison of optimal decisions made by bunker suppliers and shippers under different model scenarios. Through numerical experiments, we have uncovered a noteworthy insight: with book and claim, bunker suppliers may set higher prices to maximize total profits due to various price sensitivities among shippers towards clean fuels, thus promoting low-price-sensitive shippers to purchase clean fuels while making it challenging for high-price-sensitive shippers to do so. Consequently, when compared to a scenario without book and claim, the total quantity of clean fuels purchased by shippers in the presence of book and claim may decrease, giving rise to a paradox where the implementation of book and claim inadvertently increases societal carbon emissions. This underscores the imperative for policymakers to conduct comprehensive market research, understand different shippers’ price sensitivities towards clean fuels, and make scientifically sound decisions when considering the implementation of the book and claim mechanism.

Evaluating the relationship between energy poverty and child disability: A multilevel analysis based on low and middle-income countries

The existing literature extensively examines the impact of energy poverty on various developmental outcomes, yet there is a dearth of research investigating the empirical relationship between energy poverty and child disability. Therefore, this study aims to examine the association between household energy poverty and disabilities in children aged 2–4 years. The analysis utilizes data from the nationally representative Multiple Indicator Cluster Surveys conducted between 2017 and 2019 in 15 developing countries, encompassing three countries from South Asia and twelve countries from Sub-Saharan Africa. To measure the severity of children's disabilities, functional domains, including hearing, seeing, walking, fine motor skills, learning, understanding, speaking, and playing, were considered. Energy poverty was assessed using a multidimensional weighted approach, which accounted for access to household energies such as electricity, clean cooking fuels, television, refrigerators, mobile phones, and more. Multilevel regression models were employed to evaluate the adjusted association between energy poverty and child disability. The findings of this study reveal that children residing in energy-poor households face a higher risk of experiencing disabilities compared to those in energy non-poor households. Furthermore, Sub-Saharan Africa exhibits a greater influence of energy poverty on the development of child disabilities compared to South Asia. Sensitivity analysis was conducted using Lewbel's two-stage least squares (2SLS) regression model to predict the standardized disability score derived from principal component analysis. The results consistently indicate that households with limited access to energy are significantly more vulnerable to severe disabilities among children aged 2–4 years. Therefore, to address this issue and enhance the well-being of children and families, governments and development partners in low- and middle-income countries should prioritize policies and programs targeting energy poverty, such as increasing access to modern energy sources, promoting energy efficiency, and implementing specialized social protection initiatives.