Renewable Energy Production Research Articles

Chemical emissions from offshore wind farms: From identification to challenges in impact assessment and regulation.

Offshore wind energy may offer many advantages: next to the aim of renewable energy production, offshore wind farms (OWFs) enable multi-purpose opportunities with nature conservation and aquaculture. OWFs may also affect the marine ecosystem. The environmental impact of OWFs is starting to be investigated regarding the effect of novel habitat introduction, underwater noise, electromagnetic fields, or exclusion of fisheries. However, the impact of chemical emissions from OWFs remains largely unknown. It is essential to account for these emissions at an early stage, to comprehensively assess the environmental impact with the objective of developing a future fit-for-purpose regulatory framework to protect the marine environment. This review compiled a literature-based list of potential OWF-related chemical emissions containing >200 organic and inorganic contaminants, including polymers. Compounds are categorised according to data source and emission type. Major gaps in assessing the impact of the compounds are identified, including challenges in environmental monitoring, numerical modelling and assessing the toxicity of individual and mixtures of chemical contaminants on marine organisms and humans consuming potential OWF aquaculture products. A risk-based prioritisation is essential to target the compounds of higher concern and overcome costs linked to assessing a wide variety of chemical contaminants. Although some countries have regulations to reduce OWF chemical emissions, standardized impact assessments or monitoring requirements for OWF-based chemical contaminants have not been established. This stresses the importance of providing more detailed information on occurrence, distribution and impact of OWF chemical emissions as an essential step towards sound ecosystem-based management of OWF installations.

Learning from leading indicators to predict long-term dynamics of hourly electricity generation from multiple resources.

Learning from leading indicators to predict long-term dynamics of hourly electricity generation from multiple resources.

Aphanizomenon flos-aquae: A Biorefinery for Health and Energy—Unleashing Phycocyanin’s Power and Biogas Potential

This study presents a biorefinery approach for Aphanizomenon flos-aquae, demonstrating its potential as a dual source for phycocyanin and biogas. The antioxidant capacity of the extract was evaluated using the ABTS•+ assay, while flow cytometry determined its cytotoxic effects on breast cancer (HCC1806) and brain glioma (U-118 MG) cell lines, comparing pure C-phycocyanin to the non-purified extract. The non-purified extract scavenged 77% of ABTS•+ radicals at 2.4 mg/mL, compared to 22% for pure C-phycocyanin. In U-118 MG cells, pure C-phycocyanin accounted for 55.5% of the 29.9 ± 6.1% total mortality observed with the non-purified extract at 0.75 mg/mL. HCC1806 cytotoxicity (80.9 ± 5.1% at 1 mg/mL) was attributed to synergistic effects of other extract components. The spent biomass was valorized through anaerobic digestion for biogas production, enhancing process sustainability. At a 2:1 inoculum-to-substrate ratio, the anaerobic digestion of the spent biomass yielded 447 ± 18 mL CH4/gVS, significantly higher than the 351 ± 19 mL CH4/gVS from the initial biomass. LCA estimated the environmental impacts of the A. flos-aquae biorefinery for phycocyanin production, targeting the cosmetic, food, and nutraceutical sectors, and highlighting the benefits of spent biomass valorization to produce biogas within a circular economy framework. This integrated approach demonstrates the potential of A. flos-aquae for the sustainable production of high-value compounds and renewable energy.

Effects of Mixture Ratios on Co-Pyrolysis of Sludge with Cow and Chicken Manure

Abstract This study investigates the co-pyrolysis behavior of sludge mixed with cow and chicken manure at varying fractions, analyzed at a constant heating rate of 5°C/min. To optimize energy recovery, the objective is to assess how mixture composition influences weight loss profiles, thermal degradation patterns, and enthalpy release. The results indicate that the mixture ratio significantly affects pyrolysis performance. For sludge-cow manure mixtures, the highest enthalpy release was observed at 30% sludge and 70% cow manure, achieving a 117% increase compared to pure sludge. Similarly, for sludge-chicken manure mixtures, the optimal ratio of 40% sludge and 60% chicken manure resulted in a 60% enhancement in enthalpy release. Mixtures with higher sludge content exhibited reduced energy output due to their thermal properties, elevated moisture levels, and increased inorganic content, which hindered efficient thermal decomposition. Thermal analysis revealed distinct decomposition trends. Differential Scanning Calorimetry (DSC) and mass loss data showed that lower sludge content led to sharper decomposition peaks at lower temperatures (300-350°C), while higher sludge content resulted in broader, delayed peaks (400-550°C). Time-dependent analysis confirmed that mixtures with lower sludge content decomposed more rapidly, whereas higher sludge content caused prolonged thermal degradation, requiring greater energy input for breakdown. These findings highlight the importance of optimizing sludge-to-manure ratios for efficient energy recovery. Using co-pyrolysis as a waste management strategy, organic waste can be converted into high-value energy resources. This approach enhances renewable energy production and contributes to environmental sustainability by reducing waste accumulation and promoting resource efficiency.

Revisiting the Non-linear Relationship between oil price uncertainty and renewable energy transitions: global empirical evidence

ABSTRACT This article empirically examines the relationship between oil price uncertainty (OPU) and renewable energy transition (RET), based on a global dataset covering 71 countries from 1980 to 2022. Our benchmarking analysis shows that the effect of OPU on RET features an N-shaped pattern, which is consistently observed in the transitions of both renewable energy production and consumption. The heterogeneity analysis reveals that the N-shaped relationship between OPU and RET is significant among OECD countries, but not in non-OECD countries, indicating that more developed economies respond to oil price shocks by accelerating the transition to renewable energy. Resource-rich countries subject to the resource curse have a lower speed of renewable energy transition. Countries with high levels of renewable energy development exhibit a diversified energy mix, resulting in lower sensitivity to oil price volatility. Additionally, human capital and green innovation play key moderating roles, facilitating the emergence of the N-shaped relationship between OPU and RET. These findings provide novel insights into energy governance for policymakers aiming to enhance energy security and address climate risk, by underscoring the importance of long-term planning, differentiated policy design based on national characteristics, and strategic investments in human capital and green innovation to support sustainable energy transitions.

From Wind to Power: Unlocking Latvia's Renewable Energy Potential for Climate Neutrality

The European Union has set an ambitious goal to achieve climate neutrality by 2050. To meet this target, it is essential to significantly increase renewable energy production. However, electricity generation from renewable energy sources is intermittent, meaning energy can only be produced when the respective resources (e.g., sun, wind, favorable hydrological conditions) are available. This often does not align with the electricity consumption demand curve and to meet the demand, electricity must be generated from fossil energy sources. In Latvia, according to 2024 data, the largest share of electricity is generated by hydropower plants (53 %), followed by thermal generation (29 %), with natural gas accounting for most of this share. Meanwhile, only 4 % of total electricity production comes from wind energy, which is a low figure considering Latvia's geographical conditions and wind energy potential. However, several large-scale wind power projects with a combined capacity of 700 MW are currently in the planning stages. The implementation of all planned projects could make a significant contribution to achieving the EU's climate goals. In the energy sector, meteorological data plays a crucial role in calculating and forecasting the availability of renewable energy resources and energy production potential. To assess electricity generation from planned wind farms, calculations were carried out to determine the potential wind energy available. To estimate wind speed at a height of 185 meters, available wind speed data from ground measurement stations were adjusted using the logarithmic function most frequently employed in literature. The calculations provided an estimate of the potential electricity generation from wind farms, with results visually represented by calendar months. The findings indicate that the total electricity output from wind farms could increase by 2383 GWh/year, allowing decreased use of natural gas during spring and consequently reducing GHG emissions. The data shows that during winter and spring months, the available electricity exceeds the electricity demand. Consequently, it is essential to find solutions to balance electricity consumption and production loads, ensuring the efficient use of valuable renewable electricity. Such solutions include energy storage, for example, battery energy storage systems or converting electricity into other energy carriers, such as hydrogen. Results can further be used to identify the most suitable methods for electricity storage.

Review of Biogas Production and Bio-Methane Potential of Fish Solid Waste and Fish Waste

The growing amounts of fish waste from South Africa’s fishing and aquaculture sectors pose environmental challenges and present opportunities for renewable energy production. South Africa’s current energy mix heavily relies on coal, with renewable sources representing only a fraction of the total supply. The country’s waste management is also constrained by the large volumes of organic waste sent to landfills, increasing greenhouse gas emissions and pollution. The review synthesizes findings from various studies on the anaerobic digestion of fish waste, assessing its feasibility, efficiency, and ecological advantages as an energy source. Fish waste, high in proteins and lipids, shows promise as an effective feedstock for biogas production, particularly when codigested with other organic materials to improve microbial activity and methane output. However, the variability in results across studies highlights the need for standardized methodologies and consistent reporting, as differences in study designs and digestion parameters affect outcomes. Key limitations identified include the heterogeneity in research approaches, inconsistent biogas yield reporting, and a lack of thorough sustainability evaluations, which hinder the generalizability of findings. The review recommends further empirical studies to optimize the anaerobic digestion of fish waste tailored to South Africa’s specific context. The methodological quality of the reviewed studies supports a JBI Grade B recommendation, indicating moderate promise for fish waste as a renewable energy resource. In conclusion, fish waste represents a valuable yet underutilized resource for renewable energy that aligns with South Africa’s energy and waste reduction objectives. Expanding biogas production from fish waste could help decrease reliance on fossil fuels, reduce greenhouse gas emissions, and divert organic waste from landfills. Policymakers and energy practitioners are urged to explore fish waste digestion within the renewable energy framework. At the same time, future research should focus on optimizing co-digestion processes and addressing logistical and regulatory challenges. This review lays the groundwork for future research and policy efforts to harness fish waste for sustainable biogas production.

A convolutional state-space framework for wind turbine fault diagnosis using hierarchical feature extraction and dynamic state modeling on SCADA system

ABSTRACT Wind turbines are the backbone of renewable energy production but are often subject to mechanical failure that reduces efficiency and increases maintenance costs, as well as downtime. Traditional non-destructive testing and fault diagnosis approaches such as vibration analysis are inflexible and non-adaptive; on the other hand, deep learning-based methods lack interpretability of their practices. To tackle these issues, we present a fault diagnosis framework that combines 1D-CNN and Dynamic state-space model (DSSM) for 1D vibration signals from faulty turbine states. This novel modelling approach combines both local and temporal dependencies which helps improve interpretability and enables real-time fault detection. The efficacy of our approach is validated on a series of wind turbine fault conditions, showing competitive performance compared to classical machine learning models and deep learning models by achieving an average of 97% accuracy across all conditions, with high fault classification accuracy at different operational conditions as well.

Scenario Modelling for Municipal Energy Transition in the Baltic Sea Region

Abstract – In the context of the EU Green Deal and the Paris Agreement, the transition to renewable energy sources and the deployment of energy storage systems are fundamental for a sustainable and low-emission tomorrow. However, given the diversity of municipalities in terms of resources, infrastructure, and socio-economic conditions at local energy transition level, main actors face numerous challenges related to the implementation of new renewable energy generation projects, lack of capacity to initiate, install, and develop new projects, for which the underlying unifying factor is economic and lack of knowledge/specialists. Hence there is a need for a modelling platform that can model scenarios for the deployment of different energy generation/storage technologies in municipalities, thus saving financial resources and assessing risks and potential before the actual deployment. This research paper is a follow-up to previous publications in which the authors characterized Baltic Sea region municipalities through benchmarking and identified their storage potential and engagement in the energy transition. The focus of this case study, however, is the development of a modelling platform using systems dynamics approach to provide local public authorities support in decision-making for energy system planning. The model was validated and piloted in six municipalities – Tukums, Gulbene, Wejherowo, Tomellila, Mikolajki Pomorskie and Taurage. A scenario modelling approach based on existing municipal parameters was used for piloting. The study reveals the outcomes of different simulated scenarios in each of the municipalities and provides insights and resources to address the challenges of energy storage deployment. The study analyses the potential and means of municipalities to move towards an energy transition, but each municipality is different, and one approach does not fit all. The findings mainly address renewable energy production, storage, costs and emissions. The results of the pilots are a useful tool for municipalities to understand possible actions to reduce emissions, become more sustainable to meet EU targets whilst maintaining a stable and reliable energy supply.

A participatory approach for developing a geospatial toolkit for mapping the suitability of California’s Multibenefit Land Repurposing Program (MLRP) in support of groundwater sustainability

Reliance on groundwater during drought cycles is a common cause of overdraft conditions, particularly in regions dominated by irrigated agriculture. Groundwater overdraft is evidenced by declining water table levels, widespread well failure, and land subsidence. Given the severity of these outcomes, natural resource managers are under increasing pressure to create economic and equitable sustainability plans in response to human water demands and climate change impacts. This work describes the development of a novel toolkit (software) designed to support multicriteria decisions centered around restoring groundwater sustainability in overdrafted regions. The toolkit was developed collaboratively with participants in California’s Multibenefit Land Repurposing Program (MLRP), which aims to repurpose irrigated agricultural land to reduce groundwater extraction while providing multiple benefits. The toolkit integrates existing spatial data layers using a Web-based, open-source package (Shiny R) to assess the suitability of land for repurposing. We used fuzzy logic to create six land repurposing suitability indices for (1) enhancing groundwater recharge, (2) minimizing negative impacts to the agricultural economy, (3) increasing renewable energy production, (4) increasing wildlife habitat restoration and conservation, (5) mitigating local flood risk, and (6) reducing environmental health risks in disadvantaged communities. These indices (or subsets) can be combined as weighted averages to create user-specified multibenefit scenarios. The resulting output can be inspected locally to screen prospective land parcels based on their repurposing potential, or holistically to prioritize specific areas in the context of regional land repurposing strategies. We illustrate the development, application, and possible uses of the toolkit in the context of two critically overdrafted groundwater subbasins, Tule and Kaweah, both located in California’s San Joaquin Valley. The methods described are transferable to other overdrafted regions assuming that adequate geospatial data is available. Given its Web-accessibility and user-controlled weighting scheme, the MLRP toolkit can facilitate regional coordination of resource agencies and stakeholders and help to maximize multiple benefits of land repurposing while achieving groundwater sustainability.

Net Zero Energy Buildings

Net Zero Energy Buildings (NZEBs) have emerged as a cornerstone in sustainable development, aiming to balance energy consumption with renewable energy production. This paper explores the principles, technological strategies, and practical implementations of NZEBs. By integrating insights from case studies and theoretical frameworks, the study provides a comprehensive understanding of the challenges and solutions in achieving energy efficiency in buildings. The findings aim to inform architects, engineers, and policymakers about advancing the built environment’s sustainability.

A Systematic Roadmap for Energy Transition: Bridging Governance and Community Engagement in Ecuador

This study develops a comprehensive roadmap for Ecuador’s energy transition using a hybrid governance model that balances top–down and bottom–up approaches. By integrating national directives with local participation, this framework aims to enhance energy consumption and drive sustainable transitions. This research employs a mixed methodology, combining bibliometric analysis and governance structure assessment to evaluate Ecuador’s centralized energy system and its challenges. A three-phase strategy is proposed: Phase 1 introduces short-term interventions such as efficiency improvements and public awareness campaigns. Phase 2 focuses on decentralization, fostering local renewable energy production and community involvement. Phase 3 envisions a fully decentralized system where local entities operate autonomously within a supportive regulatory framework. The central research question is, how can a balanced governance framework foster sustainable ECB in Ecuador? By aligning national policies with local needs, this approach enhances policy adaptability, inclusivity, and long-term sustainability. Anticipated outcomes include improved energy efficiency, reduced reliance on fossil fuels, and increased community engagement in decision making. The findings contribute to global discussions on energy governance, demonstrating how hybrid models can facilitate sustainable energy transitions, particularly in developing countries with historically centralized systems.

Influence of Fluorine Doping on Rutile TiO2 Nanostructures for Visible-Light-Driven Photocatalysis: A DFT + U Study.

In this work, a density functional theory (DFT) with Hubbard correction (U) approaches implemented through the Quantum ESPRESSO code is utilized to investigate the effects of fluorine (F) doping on the structural, electronic, and optical properties of rutile TiO2. Rutile TiO2 is a promising material for renewable energy production and environmental remediation, but its wide bandgap limits its application to the UV spectrum, which is narrow and expensive. To extend the absorption edge of TiO2 into the visible light range, different concentrations of F were substituted at oxygen atom sites. The structural analysis reveals that the lattice constants and bond lengths of TiO2 increased with F concentrations. Ab initio molecular dynamics simulations (AIMD) at 1000 K confirm that both pristine and F-doped rutile TiO2 maintains structural integrity, indicating excellent thermal stability essential for high-temperature photocatalytic applications. Band structure calculations show that pure rutile TiO2 has a bandgap of 3.0 eV, which increases as the F concentration rises, with the 0.25 F-doped structures exhibiting an even larger bandgap, preventing it from responding to visible light. The absorption edge of doped TiO2 shifts towards the visible region, as shown by the imaginary part of the dielectric function. This research provides valuable insights for experimentalists, helping them understand how varying F concentrations influence the properties of rutile TiO2 for photocatalytic applications.

Sharing the light, impact of solar parks on plant productivity, soil microbes and soil organic matter

Societal Impact StatementSolar parks enable renewable energy production at a large scale, thereby reducing greenhouse gas emissions. However, the effects of this change in land use on vegetation and soil health are still largely unknown. In this study, we determined the impacts of solar parks on vegetation, soil biota and soil carbon between and below solar panels. We found lower plant and microbial biomass below the panels, while no differences in soil carbon pools were observed. The results stress the urgent need to design future solar parks that prevent soil degradation while still producing the renewable energy needed to combat climate change.Summary Solar parks, large‐scale arrays of photovoltaic panels, are a unique land use and play an important role in the renewable energy transition. However, the solar panels create shade and change the microclimate, potentially affecting plant growth and carbon inputs to the soil. These changes can influence key soil properties critical to long‐term carbon storage and overall soil health. This study investigated the impact of commercial solar parks on plant productivity and the colonisation of roots by mycorrhizal fungi, soil organic matter (SOM), soil microbial community biomass and composition and litter decomposition in 17 solar parks with contrasting shading levels across the Netherlands. Soil samples and plant biomass samples were collected between and below the solar panels. The microclimate (temperature, moisture) was measured continuously over the growing season and cumulative solar irradiation during the growing season in relation to the solar panels was modelled. Results show that above‐ and below‐ground plant biomass as well as mycorrhizal colonisation were significantly lower below than between panels, while we did not find differences for SOM, carbon stocks and hot water extractable carbon. Plant productivity related negatively to the extent of light interception by the panels. Furthermore, fungal and bacterial biomass and the F:B ratio were lower below compared to between the panels while decomposition rates did not differ. The severe decrease of plant biomass inputs in combination with maintained rates of decomposition are expected to result in decreased SOM stocks and soil health over time and suggest the need for guidelines for ecologically sound solar park designs to prevent soil damage.

Enhancing Biomass Production of Chlorella vulgaris in Anaerobically Digested Swine Wastewater Using Carbon Supplementation and Simultaneous Lipid Production

This study investigated anaerobically digested swine wastewater (ADSW) as a nutrient source for Chlorella vulgaris FACHB-8 cultivation under mixotrophic conditions with carbon supplementation. The microalgal strain was grown in ADSW supplemented with six carbon sources, followed by concentration optimization. Under optimized conditions (20 g/L glucose), FACHB-8 demonstrated a high biomass productivity (271.31 mg/L/day) and a specific growth rate of 0.42 per day. The system achieved an 88.70% total nitrogen removal and an 82.93% total phosphorus removal. The biomass contained 45.59% lipids, 29.72% proteins, and 13.05% carbohydrates, with fatty acid methyl esters showing balanced proportions of saturated (50.77%) and unsaturated fatty acids (49.23%). These findings highlight the potential of glucose-based mixotrophic cultivation for simultaneous wastewater treatment, renewable biomass production, and value-added lipid production. This work proposes a scalable swine wastewater treatment system that synergizes bioremediation and renewable energy production via carbon-enhanced microalgae cultivation, offering a dual-functional strategy for sustainable livestock wastewater reuse.

Self-triggered load frequency control using T-S fuzzy ADP method for unknown power systems.

Self-triggered load frequency control using T-S fuzzy ADP method for unknown power systems.

Acoustic exposure reveals variation in curtailment effectiveness at reducing bat fatality at wind turbines

AbstractAs the global transition to renewable energy generation continues, so does the need to reduce wind turbine‐related bat mortality. Curtailing turbine operation to prevent rotor movement at low wind speeds not only lowers risk but also decreases renewable energy production. Adjusting curtailment criteria according to seasonal patterns in bat activity could reduce energy loss, but determining whether the resulting curtailment alternative sufficiently lowered risk to bats would require a more sensitive measure of bat mortality than carcass counts can provide. We deployed turbine‐mounted acoustic bat detectors at two wind energy facilities to (1) explore seasonal and spatial variation in bat activity in and near the rotor‐swept zone of turbines, (2) confirm the efficacy of acoustic exposure to turbine operation as a measure of bat fatality risk, and (3) evaluate seasonal variation in reduction in acoustic exposure among curtailment alternatives with varying cut‐in wind speeds. Biweekly distribution of acoustic bat activity was similar among facilities, and acoustic exposure to rotating turbine blades was closely correlated with bat fatality estimates, corroborating previous studies. Curtailment strategies with higher cut‐in speeds reduced the percentage of acoustic exposure by a consistent margin across biweekly intervals, but differences in the rate of acoustic exposure among strategies were far greater during late summer and early fall, when bat activity levels were highest. In other words, the relative protectiveness of curtailment strategies did not vary greatly throughout the year, but the choice of curtailment strategy during periods of high bat activity could substantially affect bat fatality rates. Small changes in cut‐in speed (e.g., 0.5 m/s) resulted in clear reductions in acoustic exposure that were measurable at biweekly intervals, providing sensitive feedback on curtailment effectiveness. Site‐specific data from turbine‐mounted acoustic detectors could therefore provide more sensitive feedback on curtailment effectiveness than carcass searches, which cannot typically detect differences in fatality rates among curtailment strategies with similar cut‐in speeds. Acoustic exposure also provides useful practical feedback for wind energy facility operators on how best to design curtailment strategies around site‐specific patterns in bat activity and balance the simultaneous goals of generating renewable energy and protecting bats.

Measuring Renewable Energy Productivity in EU Countries with the Hicks-Moorsteen Index

This study aims to investigate the renewable energy (RE) productivity of European Union (EU) countries for 2013-2022. For this purpose, the study focuses on 26 EU member states and uses the Hicks-Moorsteen productivity index (HMPI) method. Because of the analysis, it is determined that Luxembourg, Malta, the Netherlands, Belgium, and Ireland are the leaders in RE productivity, while the RE productivity of other countries, except Hungary, Romania, Latvia, Croatia, and Bulgaria, has increased in the said period. Moreover, the HMPI values of EU countries for 2013-2022 vary between 0.968 and 1.182. When analyzing the annual averages by country, the average HMPI value for the relevant period is 1.040. Considering the index components, the increase in productivity across the EU is primarily driven by technological change (1.025), whereas efficiency change (1.018) contributes less to this increase.

Recent Trends in the Use of Electrode Materials for Microbial Fuel Cells Accentuating the Potential of Photosynthetic Cyanobacteria and Microalgae: A Review

As of 2024, approximately 81.5% of global energy consumption is still derived from non-renewable fossil fuels, such as coal, oil, and natural gas. This highlights the urgent need to transition to alternative energy sources amid the escalating climate crisis. Cyanobacteria and microalgae have emerged as promising biocatalysts in microbial fuel cells (MFCs) for eco-friendly energy production, owing to their photosynthetic abilities and resilience in regard to various environmental conditions. This review explores the potential of cyanobacteria and microalgae to drive bioelectricity generation via metabolic and extracellular electron transfer processes, leveraging their ability to fix carbon and nitrogen, while thriving in challenging environments. Bioengineering and electrode design advances are integrated to enhance the electron transfer efficacy and constancy of cyanobacteria-based MFCs. This approach addresses the growing demand for carbon-neutral energy and can be applied to wastewater treatment and bioremediation scenarios. By synergizing biological innovation with sustainable engineering techniques, this review establishes cyanobacteria and microalgal-driven MFCs as a scalable and eco-friendly platform for next-generation energy systems. The findings lay the groundwork for further exploration of the role of cyanobacteria and microalgae in bridging the gap between renewable energy production and environmental stewardship.

Effects of Airborne Particulate Matter in Biomass Treatment Plants on the Expression of DNA Repair and IL-8 Genes

Biogas plants for sewage and organic waste treatment are rapidly expanding. While these facilities provide valuable benefits, such as renewable energy production and the promotion of circular economy practices, they also emit airborne particles of biological origin, which may pose potential health risks. This study aims to evaluate, by in vitro assay, the cytotoxic and genotoxic potential of PM10 sub-fractions (0.49–10 µm and <0.49 µm) generated in eight different plants, also assessing the endotoxin component using the Limulus Amebocyte Lysate (LAL) assay. Human embryonic lung fibroblasts (HELF) were exposed to organic extracts of particulate matter (PM). Cytotoxic effects (XTT assay) were analyzed, along with the modulation of gene expression involved in DNA repair (ERCC1, XRCC1, XPA, and XPF) and IL-8 production as a marker of inflammatory response. PM10 and endotoxin concentrations varied significantly among the plants (ANOVA, p < 0.01), with PM10 levels ranging from 14 to 18,000 µg/m3 and endotoxin content from 1 to 138 EU/m3. Exposure significantly increased ERCC1 and IL-8 expression by 25% and 53%, respectively (paired t-test, p < 0.01). IL-8 expression correlated with endotoxin exposure (Spearman’s rho = 0.35; p < 0.01). A deeper understanding of the biological component of airborne PM10 can enhance risk assessments for occupational and nearby resident communities’ safety.