Solid Fuels Research Articles

Unveiling factors influencing choice of clean cooking solutions among households: a systematic review of literature

Nearly half of the global population rely on solid polluting fuels such as firewood, charcoal, animal and plant wastes for cooking. Continued reliance on such fuels and technologies has severe negative health, environmental, and development impacts. Using a systematic literature review methodology, this study sought to unveil factors influencing choice of clean cooking solutions among households. This study adopted a systematically literature review approach to systematically identify, evaluate and synthesize articles in the field of clean cooking solutions. Systematic literature review is a rigorous and replicable methodology that is designed to identify, appraise and synthesize already existing literature on specific question or sub questions. In this study, the procedures suggested by Liberati et al. and Moher et al. based on preferred reporting items for systematic reviews and meta-analysis (PRISMA) approach. Seventy-four articles were synthesized and many factors influencing the choice of cooking solutions were identified alongside the existing gaps.

Unclean but affordable solid fuels effectively sustained household energy equity.

Extensive use of traditional solid fuels necessitates a clean transition to modern energy, yet rising costs hinder equitable progress, presenting a challenge that remains underexplored. Here we quantify household energy inequities in China and evaluate shifts during the cooking and heating transition by compiling data from nationwide questionnaire surveys and statistic datasets. We find that by meeting 42.6% of household energy needs at low costs, solid fuels sustain equitable energy consumption across different income groups, being measured by the Concentration Index (CI). However, energy burden inequity remains substantially with the CI value increases by up to 43% during the transition, particularly when moving away from biomass for cooking. Switching to electric heating with natural gas cooking would limit such increases by only 15.5%. The study underscores the negative equity impacts of solid fuel cessation, advocating for phased transitions and targeted subsidies to ensure a just clean energy transition.

From Fossil Fuels to Renewables: Clustering European Primary Energy Production from 1990 to 2022

This study examines the structural shifts in primary energy production across European countries from 1990 to 2022, focusing on changes in energy sources and their implications for energy security and sustainability. Set against a backdrop of evolving geopolitical landscapes, economic pressures, and climate policies, including significant recent impacts such as the conflict in Ukraine, this research highlights the critical importance of a stable and diversified energy supply. The analysis utilizes the k-means clustering method, examining countries for which data are available in the Eurostat database and considering primary energy sources as defined by the Standard International Energy Product Classification (SIEC), including solid fossil fuels, natural gas, crude oil, nuclear energy, renewable energy sources, peat, and non-renewable waste. By categorizing European nations into clusters based on their energy production profiles, the study reveals substantial transitions from fossil fuel-based systems to those increasingly dominated by renewable energy sources. While some countries have made significant progress in integrating renewables, others remain heavily dependent on traditional energy sources such as coal and natural gas. The findings underscore the growing role of natural gas as a bridge fuel and the relatively stable contribution of nuclear energy in certain regions. A key outcome is the observed disparity between energy production and consumption across Europe, with many large economies facing a persistent deficit in domestic energy production, resulting in a high reliance on energy imports, particularly of natural gas and oil. This dependency poses significant challenges to energy security, especially given recent geopolitical disruptions and market fluctuations. The paper also discusses the environmental implications of these energy trends, emphasizing the vital role of renewable energy in achieving the European Union’s decarbonization goals.

Particulate matter pollution and older adult health: global trends and disparities, 1991–2021

BackgroundParticulate matter pollution (PMP) is a major global health concern, with the older adult being particularly vulnerable. This study aimed to analyze global trends in PMP-related deaths and disability-adjusted life years (DALYs) among the older adult from 1991 to 2021.MethodsUsing data from the Global Burden of Disease Study 2021, we examined the impacts of ambient particulate matter pollution (APMP) and household air pollution from solid fuels (HAP-SF). We analyzed trends across different regions, socioeconomic development levels, age groups, and genders.ResultsAPMP-related older adult deaths increased from 1,745,000 to 3,850,000, and DALYs from 32,000,000 to 70,000,000. However, age-standardized mortality rate decreased from 384 to 337 per 100,000. HAP-SF-related deaths decreased from 2,700,000 to 2,100,000, and DALYs from 54,000,000 to 42,000,000. Age-standardized mortality rate for HAP-SF declined from 580 to 188 per 100,000. High APMP burden was concentrated in Asia, Africa, and the Middle East, while high HAP-SF burden was found in parts of Africa and South Asia. East Asia had the highest APMP-related older adult deaths (1,680,000) with an age-standardized mortality rate (ASMR) of 619 per 100,000. For HAP-SF, South Asia bore the heaviest burden with 1,020,000 deaths and an ASMR of 616 per 100,000. Females consistently experienced higher age-standardized DALYs rate than males for both APMP and HAP-SF across all regions and years. APMP burden showed a weak negative correlation with the Socio-demographic Index (SDI) at the regional level (r = −0.25, p < 0.001) but no significant correlation at the country level. HAP-SF burden exhibited strong negative correlations with SDI at both regional (r = −0.74, p < 0.001) and country levels (r = −0.83, p < 0.001).ConclusionDespite overall improvements, PMP continues to significantly impact older adult health globally, with substantial regional and gender disparities. These findings emphasize the need for targeted interventions, particularly in developing regions, and continued global efforts in air quality improvement and clean energy promotion.

Recent Progress on the Materials of Oxygen Ion-Conducting Solid Oxide Fuel Cells and Experimental Analysis of Biogas-Assisted Electrolysis over a LSC Anode

In this work, the recent achievements in the application of solid oxides fuel cells (SOFCs) are discussed. This paper summarizes the progress in two major topics: the materials for the electrolytes, anode, and cathode, and the fuels used, such as hydrocarbon, alcohol, and solid carbon fuels. Various aspects related to the development of new materials for the main components of the materials for electrocatalysts and for solid electrolytes (e.g., pure metals, metal alloys, high entropy oxides, cermets, perovskite oxides, Ruddlesden–Popper phase materials, scandia-stabilized-zirconia, perovskite oxides, and ceria-based solid electrolytes) are reported in a coherent and explanatory way. The selection of appropriate material for electrocatalysts and for solid electrolyte is crucial to achieve successful commercialization of the SOFC technology, since enhanced efficiency and increased life span is desirable. Based on the recent advancements, tests were conducted in a biogas-fueled Ni-YSZ/YSZ/GDC/LSC commercial cell, to elucidate the suitability of the LSC as an anode. Results obtained encourage the application of LSC as an anode in actual SOFC and SOFEC systems. Thus, H2-SOFC demonstrated a satisfying ASR value, while, for biogas-assisted electrolysis, the current values slightly increased compared to the methane-SOFEC, and for a 50/50 biogas mixture of methane and carbon dioxide, the corresponding value presented the higher increase.

Effects of household air pollution and healthy lifestyle associated with gestational diabetes mellitus

This study investigated the effect of household air pollution on pregnant women with GDM, and assessed the modifying effect of a healthy lifestyle on this relationship. Household solid fuel exposure was defined as using solid fuels (coal, crop residue, and wood) for cooking and heating. Four individually modifiable lifestyle factors were assessed in early pregnancy: body mass index, diet, sleep, and vitamin D supplementation. Multifactorial logistic regression modeling was used to assess the relationship between household air pollution and GDM. A stratified analysis and additive interaction tested the effects of healthy lifestyle scores. After adjusting for potential confounders, we found that using solid fuels for heating was significantly associated with an increased risk of GDM (adjusted OR = 1.60, 95% CI 1.18–2.18). GDM risk showed a decreasing trend in the medium versus the high score group when compared to the low score group, with a consistent trend regardless of household fuel type used (adjusted OR = 0.39, 95% CI 0.27–0.57) (adjusted OR = 0.12, 95% CI 0.05–0.28), respectively. Importantly, when the healthy lifestyle score increased, exposure to household air pollution was no longer associated with a higher GDM risk. There was a negative additive interaction between exposure to household solid fuels exposure and a healthy lifestyle (FERI: −5.10 [−16.48, −2.04]; AP: −1.29 [−2.80, −0.39]; SI: −0.37 [−0.20, −0.67]). We determined that exposure to household air pollution may be an important GDM risk factor. In addition, A healthy lifestyle may have a protective effect on women with GDM exposed to indoor fuel air pollution.

A machine learning based regression methods to predicting syngas composition for plasma gasification system

Plasma gasification is considered a promising technology that converts waste into energy through an environmentally friendly process. This research focuses on predicting the outputs of this process, utilizing ML regression techniques. Data from previous studies involving different solid fuels were collected, and four regression techniques Random Forest Regression, Gaussian Process Regression, Decision Tree Regression, and Support Vector Regression were employed to predict the levels of CO2, CO, N2, O2, H2, and CH4 in the plasma gasification process. The experimental dataset was gathered using a microwave gasifier with varying air flow rates (50–100 sL/min) and plasma power (3–6 kW). GPR a coefficient of determination (R2) values exceeding 0.983 for all outputs and low NRMSE and MSLE values (<0.082 and <0.00123, respectively). RFR also performed well, with R2 values >0.98 for all outputs except CH4 and CO2. SVR exhibited the least favorable performance, while DTR showed intermediate results. Plasma gasification Machine Learning modeling has proven to enable the prediction of the high-complexity chemical reaction chain in gasification. These models hold promise for applications in simulation environments and can be integrated into microcontroller-based systems for practical use for optimization and control. By this means, the cost of plasma gasification processes would be reduced, and so the plasma gasification system would be more flexible.

High-fidelity modelling of unburnt coal flow in an industry-scale blast furnace using a hybrid CFD-DEM method

Solid fuels, such as coal or biochar, can be injected into a blast furnace for low-carbon ironmaking. However, unburnt coal or biochar powders may accumulate in the coke bed, potentially reducing bed permeability and compromising furnace stability. Current CFD-DEM methods struggle to simulate systems with significant size differences between coke particles and coal or biochar powders, where the diameter ratio dck/dcl is 100–200 times. In this work, a novel multi-resolution hybrid CFD-DEM model is developed to simulate gas-unburnt powders-coke particles flow dynamics within and around the raceway with high fidelity. The model’s accuracy is validated by comparing the simulated evolution of the raceway cavity shape with experimental results. Subsequently, the hybrid model is used to simulate unburnt powder flow through the raceway and the adjacent coke bed (dck/dcl = 100), comparing its performance with conventional smoothed CFD-DEM models. The effects of gas inlet velocity and powder wettability are also analysed. Results show that the hybrid CFD-DEM model effectively simulates detailed pore fluid flow in the coke bed, which the smoothed model fails to capture, demonstrating the hybrid model’s superiority. Increasing gas inlet velocity enlarges the raceway cavity, intensifies high-speed pore flows, and accelerates powder transport into the coke bed. Additionally, higher cohesion energy density (kCED) reduces powder penetration, aligns the peak holdup position and penetration angle, and decreases permeability at key probe positions. This work provides an effective and efficient numerical tool to help understand and optimise the injection operation in blast furnaces.

Ignition study of hypergolic solid fuels through counterflow experiment using hydrogen peroxide spray

Hypergolic solid fuels provide rapid and reliable ignition for hybrid rockets, offering significant advantages over conventional methods. However, a practical experimental approach is necessary to study ignition and combustion behavior under realistic oxidizer flow conditions. This study introduced a novel counterflow spray experiment using 90 % rocket-grade hydrogen peroxide sprays applied to low-density-polyethylene-based fuel pellets embedded with sodium borohydride and manganese acetate tetrahydrate. The results showed that sodium borohydride caused vigorous reactions, damaging the pellets, while the addition of manganese acetate tetrahydrate moderated this effect. Hypergolic ignition and sustained combustion were achieved at oxidizer mass flow rates of 0.38–0.57 g/s, with ignition delay times of 15 to 30 ms, consistent with droplet test results. In addition, reignition was successful under the same flow conditions, although the char layer formed on pellet surface after the first ignition limited the surface additive reactivity, leading to longer ignition delay times. 3D surface analysis provided quantitative data on surface roughness across various fuel compositions and flow rates. This novel counterflow spray experiment is expected to be both effective and simple, with the ability to offer valuable insights into hypergolic ignition and combustion process.

Health implications of cooking energy transition: Evidence from rural China

Abstract The transition towards advanced residential energy sources is a pressing priority for many countries. Despite this, solid fuels remain the dominant form of cooking energy for rural households in developing countries. This study investigates the physical and mental health impacts of cooking energy choices by using endogenous switching models to address selection bias associated with cooking energy adoption and to distinguish the health impacts of different types of cooking energy. Using a country-representative household survey data in China, our results indicate that adopting advanced forms of energy, not only enhances physical health in terms of reducing the rates of chronic diseases but also improves mental health. We further delve into the heterogenous impacts of advanced energy adoption across different groups and find that women, old adults, and economically disadvantaged groups are more likely to experience greater mental health benefits compared to their counterparts, while the opposite results are observed for the physical health. Additionally, we differentiate the health impacts by distinguishing between various energy types. This study provides insights for policy making aimed at improving public health and promoting health equality, contributing to efforts towards achieving sustainable development goals by prioritizing clean and efficient residential energy solutions.

Development of Predictive Models for Energy Demand and CO2 Emission Trends for Households in Makurdi Metropolis

This study aimed at developing predictive models for energy demand and CO2 emission trends for households in Makurdi metropolis. As part of the study, households were randomly selected to represent a reasonable spread. Four major emission sources: electricity; transportation; solid waste and cooking fuels were considered, and data on the sources were obtained using records from relevant departments as well as questionnaires, surveys, and interviews of the occupants. This data was analyzed and used to calculate the CO2 emissions of the households using IPCC standard guidelines and formulae. The CO2 emission and energy demand predictive models were also developed using Design Expert 13. The ANOVA for the CO2 emission and energy demand shows a significant model (Significance F value of ≤ 0.0001) and a high R-squared value of 0.9981 and 0.9802 respectively. This indicates the adequacy of the models, and they can therefore be used to predict the CO2 and energy demand of households in Makurdi metropolis. The limitation remains the imbalance in living standards across the respective areas of the metropolis which definitely impacts on the demand and use of energy. It will be useful for policy makers and implementers in ensuring sustainable energy demand planning and CO2 emissions mitigation.

Thermogravimetric Analysis of Combustion of Semi-Coke Obtained from Coniferous Wood and Mixtures on Their Basis

Coal remains one of the most used solid fuels for heat and electricity generation but burning coal releases large amounts of CO2 into the urban atmosphere in addition to harmful substances. In order to reduce the consumption of solid fossil fuels, it is necessary to search for fuels capable of replacing coal in terms of its thermal and environmental characteristics. One of the best alternative fuels is biomass, which is considered carbon neutral, but its thermal characteristics are worse than those of solid fossil fuels. In this work, an alternative to coal was studied for the first time, which was semi-coke, obtained by gasification at a temperature of 700–900 °C, the heat of combustion of which turned out to be higher than that of biomass before thermal treatment by 75%. We also studied fuel mixtures based on the resulting semi-coke. The aim of the work is to determine the main characteristics of combustion of semi-coke obtained from coniferous wood and mixtures based on them. The method of thermogravimetric analysis in oxidising medium at a heating rate of 20 °C/min was applied for the research. According to the results of this analysis, the ignition and burnout temperatures were determined, the combustion index was determined, the duration of coke residue combustion was determined, and synergetic interactions between the mixture components influencing the combustion characteristics were established. It was found that the ignition temperature of semi-coke is more than 50% higher than that of biomass and the burnout temperature is 10% higher. Adding 50% of biomass to semi-coke increases the combustion index by more than 30% and decreases the ignition temperature and burnout temperature. The mixture components synergistically interact with each other during combustion to reduce the value of maximum mass loss rate. It was found that the atomic ratios of O/C and H/C in semi-coke are lower than in biomass before gasification.

Healthy air for healthy minds

Abstract Background The adverse health effects from exposure to air pollution is increasingly known. A recent report shows that at least 95% of the world’s population breathe air containing dangerous levels of pollutants. According to estimates from the World Health Organization (WHO), ambient air pollution is related to 4.2 million deaths every year. Less is known about the association between indoor air (especially particulate matter 2.5 and volatile organic compounds (VOC) pollution and mental health conditions. Many sources of indoor air pollution exist, such as pressed wood products, pesticides, secondhand smoke, stoves, heaters, overcrowding and fireplaces. Aims We aim to synthesize knowledge on the effects of particulate matter 2.5 in indoor air and mental health conditions. Methods We systematically reviewed the association of indoor air pollution with mental health conditions using the databases Pubmed and EMBASE. Results Exposure to indoor air pollutants is associated with increased anxiety and depression and less cognitive performance. These results are robust; however, the impact of PM2.5 is larger for less-educated and female respondents. Females cook with solid fuels and biomass more often. Physical exposure and gender factors overlap in the exposure to indoor air pollutants. Discussion Poor indoor air quality should be part of a comprehensive assessment of factors influencing mental health and cognition. Neuroinflammation might explain the effects of poor air on mental health and cognition. Further research is needed to combine research on the social determinants of mental health and the effects of indoor air. Studies in different settings such as home, work, and hospitals are needed to better understand the specific exposures of indoor air pollution and mental health conditions in different population groups.

Mitigating household air pollution exposure through kitchen renovation

Globally, over three billion people rely on traditional solid fuels for cooking and heating, leading to significant household air pollution and critical public health concerns. While transitioning to clean energy carriers faces challenges of accessibility and affordability—especially among low-income, rural populations—alternative strategies like kitchen layout modifications and the use of ventilation fans may effectively reduce exposure to pollutants. Here, we analyze factors influencing the adoption of separated kitchens and mechanical ventilation and evaluate changes in human exposure to PM2.5 under different kitchen renovation scenarios by conducting a nationwide survey of household kitchen characteristics in rural China. We found that although 82% of rural households have kitchens separated from other rooms, only 34% use mechanical ventilation. The adoption of ventilation fans is significantly influenced by income and education levels. We estimate that widespread implementation of ventilation fans and separated kitchen designs could prevent approximately 67400 premature deaths annually, resulting in a health benefit of about USD 19 billion per year—substantially exceeding the costs involved. These findings suggest that cost-effective kitchen renovations offer enormous potential for substantial health benefits and present a practical solution compared to the challenges of clean energy transitions in rural areas.

Numerical study of a chemical looping combustion system: Effects of fuel type and particle size distributions on the operating performance

Chemical looping combustion (CLC) using biomass offers a promising pathway for achieving negative carbon emissions. However, the different properties of coal and biomass affect reaction performance, which has not been fully explored in the CLC system. Additionally, the effects of particle size distributions (PSDs) of solid fuels and oxygen carriers (OCs) are inadequately addressed. In this study, a 3D reactive model using the computational particle fluid dynamics (CPFD) method is developed to investigate the effects of PSDs of both solid fuels and oxygen carriers on operating performance with coal and biomass as fuels. Results indicate that the average residence time in FR of coal and biomass particles is 0.86 s and 0.68 s, respectively, but biomass outperforms coal in reaction efficiency. For coal-fueled CLC, the average residence time is 0.46 s for coal particles with diameters of 100–200 μm, whereas it reaches 0.86 s for coal diameters of 300–700 μm. However, the reaction performance is better with smaller coal sizes due to char gasification being the rate-limiting step. In comparison, for biomass-fueled CLC, the reaction efficiency remains consistent across various particle sizes under the specified conditions due to the rapid release of volatile components and the low content of char. Additionally, it is found that the OC conversion ratio is mainly determined by their residence time in the zones with relatively higher concentrations of the combustible gas in FR. Employing OCs with overly wide PSDs such as 300–800 μm can compromise the material seal above the AR, increase the risk of gas leakage and decrease the separation efficiency of the inertial separator.

Assessment of indoor air pollution in causing respiratory illness among women residing in rural areas of Mysuru

Introduction: The use of inefficient and harmful fuels and technology within and outside the home is the primary cause of indoor air pollution. Approximately 2.4 billion people on the planet still cook over open flames and inefficient stoves using solid fuels and kerosene. The availability of cleaner cooking options varies more in rural than in metropolitan settings. Therefore, there is a need to determine the prevalence of indoor air pollution among rural women, its association with respiratory disorders, and the frequency of respiratory illnesses among rural women residing in houses with or without indoor air pollution. Materials and methods: This analytical cross-sectional study was done for a period of six months from June to November 2020. The study conducted in 210 households living in the rural field practice areas of JSS Medical College, Mysuru. For the selection of villages, a multistage random sampling technique was used. Three villages are selected from the rural setting: Suttur, Hadinaru, and Kadakola. The households were included by probability proportionate to the size sampling technique. Pre-tested, semi-structured, phase and content validated questionnaires were used to obtain the details on socio-demographic characteristics, meter values of indoor air pollutants like Particulate Matters (PM1, PM2.5, PM10) and Volatile Organic Compounds (VOCs), respectively with the factors affecting respiratory illness and the episodes of the illness. Data was entered in Microsoft Excel and analyzed using descriptive and inferential statistics using SPSS V.26. Results: The prevalence of indoor air pollution in the present study was 13.3%. In the homes of rural women, there was a statistically significant variation in the concentration of the three particulate matter sources that cause indoor air pollution. Additionally, among the women living in rural families, there was a statistically significant difference in the concentration of PM10 that caused respiratory disease. Conclusion: The current study demonstrated the higher concentrations of pollutants such as PM10, PM2.5, and PM1.0, as well as their significant relation with indoor air pollution in rural families. To prevent indoor air pollution and its health risks, clean energy must be used for household needs.

A concise review towards a novel target specific multi-source unsupervised transfer learning technique for GDP estimation using CO2 emission data

Though economic growths of most of the nations have seen exponential rise due to industrialization, it has also caused proportional increase in their carbon emissions. This paper exploits this proportionate relationship of carbon emission with GDP to predict the per-capita GDP of those nations whose GDP values are missing in the world bank database. The reason behind the same was, those countries were either war-torn or politically isolated/unstable. To achieve the objective of predicting the missing GDP values of those countries from their carbon emissions, this paper exploits the non-linear relationship among the carbon emissions from solid fuels, liquid fuels, and gaseous fuels. It is so because even the differential utilization of these fuels impact economy differently. Use of traditional solid fuel for cooking points toward energy poverty, and access to clean cooking gas indicates higher living standard. However, the available data from the war-torn or isolated countries are very little, and hence insufficient for building a robust predictive machine learning model. So, this paper employs multi-source unsupervised transfer learning to precisely estimate the missing per-capita GDP of those nations. It suitably enlarges the training domains for the prediction models to be more robust. We empirically evaluate the proposed methodology for different regression techniques to estimate the missing GDP values of eleven different nations belonging to diverse strata of economies viz. developed economies, developing, and/or least developing economies. Proposed methodology profoundly improves the prediction preciseness of these regression techniques in estimating the missing per-capita GDP of the considered nations.

Household residential energy choices in green transition: insights from a household survey in rural China.

It has been widely recognized that accelerating green residential energy transition from traditional solid fuels (biomass and coal) to clean and high-efficient energy sources is critical for rural sustainable development. However, little attention has been paid to estimate panel data discrete choice models to analyze the dynamic behavior information of individual households in the process of energy transition. Hence, this paper investigates green residential energy transition using a panel dataset from 3308 rural households in eight provinces of China in 2015 and 2018. The results show that although traditional solid biomass still plays a dominating role in rural residential energy choice, fuel switching from solid fuels to modern clean energy alternatives is taking place. Off-farm employment plays an important role in the transition towards more sustainable energy sources, as households with off-farm employed heads and higher off-farm income level are highly likely to choose superior energy alternatives other than traditional biomass. Besides, the educational level of the household head and household location are also important influencing factors of household residential energy choices. Based on these findings, this paper suggests that job creation in non-farm sectors should be given a priority in future policy design to promote rural green energy transition in residential sector. North-south differences should be taken into account, whereas more policy options for optimizing biomass energy use should be explored.

Порівняння ущільнюваності асфальтобетонної суміші із золою-винесення та вапняковим наповнювачем

Introduction. In Ukraine, about 30 % of all electricity is generated from the combustion of solid fuels — coal, shale, peat. In our country, there are about 15 operating thermal power plants that generate about 5 – 6 million tons of ash and slag waste per year as a secondary product. Thus, the fuel and energy complex waste generated in the furnaces of thermal power plants is a huge accumulation of ash in the form of dusty residues and lumpy sludge, as well as various ash and slag mixtures. These products of high-temperature processing (1 200 – 1 700 ºС) of the mineral part of the fuel are widely used in many countries of the world and, given the global trend towards an increase in the share of the secondary market for the use of waste, it is necessary to predict an increase in the rate of their processing in Ukraine. Problem Statement. The road construction industry is one of the strategic industries of Ukraine, and the issue of quality and availability of basic building materials for road construction is particularly acute now, which is directly related to its high material intensity. The known reserves of high-quality raw materials that could be used as asphalt concrete components are constantly decreasing, so it is necessary to look for alternative sources of raw materials for construction materials and explore the possibility of their use. In this regard, the most effective use of local raw materials is the use of industrial waste, which can be one of the solutions to the problem of lack of raw materials of inorganic origin.

Exploring the relationship between personal exposure to multiple water-soluble components and ROS in size-resolved PMs in solid fuel combustion households

Water-soluble species are the main components of particulate matters (PMs), which have important impacts on visibility, climate change and human health. Here, personal exposure (PE) to size-resolved PMs from housewives using different solid fuels (biomass and coal) was collected during winter in rural Yuncheng city, Fenwei Plain, China. The concentrations of water-soluble organic carbon (WSOC) and reactive oxygen species (ROS) were higher in the biomass group than coal group, whereas the concentrations of water-soluble inorganic ions and water-soluble nitrogen were higher in the coal group than biomass group. Almost all measured water-soluble components in both groups showed a pattern of increasing concentration with decreasing particle size, with more than 50% of WSOC and water-soluble total nitrogen (WSTN) enriched in PM0.25. The Pearson correlation result was in general agreement with the relationship between water-soluble components and ROS found by random forest model. There was a strong positive correlation between ROS and WSOC in PMs in the coal group, especially in PMs <0.25 μm, which may be due to the emission of a large number of transition metals chelated with WSOC from coal combustion. The contribution of Cl− and F− to ROS was greater in the biomass group. NO2− in both coal and biomass groups had a decent positive effect on ROS generation. The strongest positive linear correlation (R = 0.95) between ROS and K+ in total suspended particulates in the biomass group, whereas there was almost no contribution of K+ to ROS when particle size was distinguished or in random forest model, which reflects the specificity of K+ in inducing ROS. The present study provides new insights for a deeper exploration of the relationship between water-soluble components and oxidative potential in PE PMs from domestic combustion sources.