Search Results (3,421)

Accurate forecasting of energy consumption in buildings is essential for achieving energy efficiency and reducing carbon emissions. However, many existing models rely on limited input variables and overlook the complex influence of indoor environmental quality (IEQ). In this study, we assess the performance of hybrid machine learning ensembles for predicting hourly energy demand in a smart office environment using high-frequency IEQ sensor data. Environmental variables including carbon dioxide concentration (CO₂), particulate matter (PM_2.5), total volatile organic compounds (TVOCs), noise levels, humidity, and temperature were recorded over a four-month period. We evaluated two ensemble configurations combining support vector regression (SVR) with either Random Forest or LightGBM as base learners and Ridge regression as a meta-learner, alongside single-model baselines such as SVR and artificial neural networks (ANN). The SVR combined with Random Forest and Ridge regression demonstrated the highest predictive performance, achieving a mean absolute error (MAE) of 1.20, a mean absolute percentage error (MAPE) of 8.92%, and a coefficient of determination (R²) of 0.82. Feature importance analysis using SHAP values, together with non-parametric statistical testing, identified TVOCs, humidity, and PM_2.5 as the most influential predictors of energy use. These findings highlight the value of integrating high-resolution IEQ data into predictive frameworks and demonstrate that such data can significantly improve forecasting accuracy. This effect is attributed to the direct link between these IEQ variables and the activation of energy-intensive systems; fluctuations in humidity drive HVAC energy use for dehumidification, while elevated pollutant levels (TVOCs, PM_2.5) trigger increased ventilation to maintain indoor air quality, thus raising the total energy load. Full article

Sewage sludge (SS) is commonly applied as a soil amendment. This practice has raised concern about the dissemination of emerging pollutants (EPs). EPs include compounds such as flame retardants, plasticizers, pharmaceuticals, and personal care products, among others, which may pose risks to human health and ecosystems. The complexity of the SS matrix, combined to the absence of an international legislation framework, makes it necessary to evaluate the techniques available for detecting these contaminants. Detection is typically performed using sensitive analytical techniques; however, the extraction strategy selected remains a crucial step. This review aims to compile different methodologies for the determination of EPs in SS, focusing on extraction strategies reported between 2010 and 2025. Ultrasound-assisted extraction (UAE), pressurized liquid extraction (PLE), and microwave-assisted extraction (MAE) are the most widely used strategies for EPs. UAE is considered the most preferable option, as it enables the extraction of a wide range of compounds without the need for expensive equipment. Among novel techniques, the quick, easy, cheap, effective, rugged, and safe (QuEChERS) method is especially promising, as it is applicable to multiple target compounds. This review provides up-to-date information that can support the development of routine and standardized methodologies for the characterization of EPs in SS. Full article

Metro carriages, as enclosed transport microenvironments, have been understudied regarding pollution characteristics and health risks from ACs, especially during high-temperature summers that amplify exposure. This study applied NTS techniques for the first time across three major Chengdu metro lines, systematically identifying sixteen ACs, including hazardous species such as acetophenone, benzonitrile, and benzoic acid that are often overlooked in conventional BTEX-focused monitoring. The TAC concentration reached 41.40 ± 5.20 µg/m³, with half of the compounds exhibiting significant increases during peak commuting periods. Source apportionment using diagnostic ratios and PMF identified five major contributors: carriage material emissions (36.62%), human sources (22.50%), traffic exhaust infiltration (16.67%), organic solvents (16.55%), and industrial emissions (7.66%). Although both non-cancer (HI) and cancer (TCR) risks for all population groups were below international thresholds, summer tourists experienced higher exposure than daily commuters. Notably, child tourists showed the greatest vulnerability, with a TCR of 5.83 × 10⁻⁷, far exceeding that of commuting children (1.88 × 10⁻⁷). Benzene was the dominant contributor, accounting for over 50% of HI and 70% of TCR. This study presents the first integrated NTS and quantitative risk assessment to characterise ACs in summer metro environments, revealing a broader range of hazardous compounds beyond BTEX. It quantifies population-specific risks, highlights children’s heightened vulnerability. The findings fill critical gaps in ACs exposure and provide a scientific basis for improved air quality management and pollution mitigation strategies in urban rail transit systems. Full article

This research examines the compounding risks of global environmental change, including climate change, environmental law, biodiversity loss, and pollution, which threaten the stability of economic systems worldwide. While digital technology and global governance regulation are increasingly being proposed as solutions, their synergistic potential in advancing economic sustainability has been less explored. How can these technologies mitigate environmental risks while promoting sustainable and equitable development, aligning with the Sustainable Development Goals? We analyze policy global environmental data from the World Bank and the United Nations, as well as literature reviews on digital interventions, artificial intelligence, and smart databases. Global environmental change presents economic stability and rule of law threats, and innovative governance responses are needed. This study evaluates the potential for digital technology to be leveraged to enhance climate resilience and regulatory systems and address key implementation, equity, and policy coherence deficits. Policy recommendations for aligning economic development trajectories with planetary boundaries emphasize that proactive digital governance integration is indispensable for decoupling growth from environmental degradation. However, fragmented governance and unequal access to technologies undermine scalability. Successful experiences demonstrate that integrated policies, combining incentives, data transparency, and multilateral coordination, deliver maximum economic and environmental co-benefits, matching digital innovation with good governance. We provide policymakers with an action plan to leverage technology as a multiplier of sustainability, prioritizing inclusive governance structures to address implementation gaps and inform legislation. Full article

Emerging and persistent contaminants (EPCs) were detected at high concentrations in Chiang Mai’s Mae Kha Canal, identifying urban waterways as important sources of pollution in the Ping River system in northern Thailand. Maximum levels of metformin (20,000 ng/L), fexofenadine (15,900 ng/L), gabapentin (12,300 ng/L), sucralose (38,000 ng/L), and acesulfame (23,000 ng/L) point to inadequately treated wastewater as a plausible contributor. Downstream enrichment patterns relative to upstream sites highlight the cumulative impact of urban runoff. Five compounds—acesulfame, gemfibrozil, fexofenadine, TBEP, and caffeine—consistently emerged as reliable tracers of urban wastewater, forming a distinct chemical fingerprint of the riverine exposome. Median EPC concentrations were highest in Mae Kha, lower in other urban canals, and declined with distance from the city, reflecting spatial gradients in urban density and pollution intensity. Although most detected concentrations fell below predicted no-effect thresholds, ibuprofen frequently approached or exceeded ecotoxicological benchmarks and may represent a compound of ecological concern. Non-targeted analysis revealed a broader “chemical cocktail” of unregulated substances—illustrating a witches’ brew of pollution that likely escapes standard monitoring efforts. These findings demonstrate the utility of wide-scope surveillance for identifying key compounds, contamination hotspots, and spatial gradients in mixed-use watersheds. They also highlight the need for integrated, long-term monitoring strategies that address diffuse, compound mixtures to safeguard freshwater ecosystems in rapidly urbanizing regions. Full article

Concern over the presence of pharmaceutical waste in the environment has prompted research into the management of emerging organic micropollutants (EOMs). In response, sustainable technologies have been applied as alternatives to reduce the effects of these contaminants. This study investigated the capacity of filamentous fungi isolated from iron mine soil in the Amazon region to biodegrade the drug chloroquine diphosphate. An initial screening assessed the growth of four fungal strains on solid media containing chloroquine diphosphate: Trichoderma pseudoasperelloides CBMAI 2752, Penicillium rolfsii CBMAI 2753, Talaromyces verruculosus CBMAI 2754, and Penicillium sp. cf. guaibinense CBMAI 2758. Among them, Penicillium sp. cf. guaibinense CBMAI 2758 was selected for further testing in liquid media. A Box–Behnken factorial design was applied with three variables, pH (5, 7, and 9), incubation time (5, 10, and 15 days), and chloroquine diphosphate concentration (50, 75, and 100 mg·L⁻¹), totaling 15 experiments. The samples were analyzed by gas chromatography–mass spectrometry (GC-MS). The most effective conditions for chloroquine biodegradation were pH 7, 100 mg·L⁻¹ concentration, and 10 days of incubation. Four metabolites were identified: one resulting from N-deethylation M1 (N4-(7-chloroquinolin-4-yl)-N1-ethylpentane-1,4-diamine), two from carbon–carbon bond cleavage M2 (7-chloro-N-ethylquinolin-4-amine) and M3 (N1,N1-diethylpentane-1,4-diamine), and one from aromatic deamination M4 (N1-ethylbutane-1,4-diamine) by enzymatic reactions. The toxicity analysis showed that the products obtained from the biodegradation of chloroquine were less toxic than the commercial formulation of this compound. These findings highlight the biotechnological potential of Amazonian fungi for drug biodegradation and decontamination. Full article

The continuous occurrence of steroidal pharmaceutical dexamethasone (DXM) in aqueous environments indicates the need for an efficient removal technology. The frequent detection of DXM in surface water could be substantially reduced by the application of photo-induced advanced oxidation technology. In the present study, Fe²⁺ and UVA-light activated peroxo compounds were applied for the degradation and mineralization of a glucocorticoid, 25.5 µM DXM, in ultrapure water (UPW). The treatment efficacies were validated in real spring water (SW). A 120 min target pollutant degradation followed pseudo first-order reaction kinetics when an oxidant/Fe²⁺ dose 10/1 or/and UVA irradiation were applied. Acidic conditions (a pH of 3) were found to be more favorable for DXM oxidation (≥99%) regardless of the activated peroxo compound. Full conversion of DXM was not achieved, as the maximum TOC removal reached 70% in UPW by the UVA/H₂O₂/Fe²⁺ system (molar ratio of 10/1) at a pH of 3. The higher efficacy of peroxymonosulfate-based oxidation in SW could be induced by chlorine, bicarbonate, and carbonate ions; however, it is not applicable for peroxydisulfate and hydrogen peroxide. Overall, consistently higher efficacies for HO^•-dominated oxidation systems were observed. The findings from the current paper could complement the knowledge of oxidative removal of low-level DXM in real water matrices. Full article

Sorption and advanced oxidative processes (AOPs) are potential strategies for the removal of organic compounds, such as caffeine, from aqueous media. Such strategies tend to be more promising when combined with biopolymeric membranes as sorbents and photocatalyst supports. Therefore, the aim of the present study was to investigate sorption and AOP parameters in the performance of chitosan membranes and chitosan/TiO₂ composite membranes in individual and hybrid systems involving the photolysis, photocatalysis, and sorption of caffeine. Caffeine degradation by photolysis was 19.51 ± 1.14, 28.61 ± 0.05, and 30.64 ± 6.32%, whereas caffeine degradation by photocatalysis with catalytic membrane was 18.33 ± 2.20, 20.83 ± 1.49, and 31.41 ± 3.08% at pH 6, 7, and 8, respectively. In contrast, photocatalysis with the dispersed catalyst achieved degradation of 93.56 ± 2.12, 36.42 ± 2.59, and 31.41 ± 1.07% at pH 6, 7, and 8, respectively. These results indicate that ions present in the buffer solutions affect the net electrical charge on the surface of the composite biomaterial with the change in pH variation, occupying active sorption sites in the structure of the biomaterial, which was characterized by Fourier transform infrared spectrometry, thermogravimetric analysis, differential scanning thermogravimetry, and X-ray diffraction. Thus, it is verified that in a combined process of caffeine removal under UV irradiation and use of chitosan/TiO₂ composite membranes in phosphate-buffered medium, the photolysis mechanism is predominant, with little or no contribution from sorption, and that the TiO₂ catalyst promotes a significant reduction in the percentage of pollutant in the medium only when used dispersed and at low pH. Full article

Internal combustion engine vehicles damage the environment and public health by emitting toxic fumes, such as CO₂ or CO and other trace compounds. The use of electric cars helps to reduce the emission of pollutants into the environment due to the use of batteries with no direct and local emissions. However, accidents of battery electric vehicles pose new challenges, such as thermal runaway. Such accidents can be serious and, in some cases, may result in uncontrolled overheating that causes the battery pack to spontaneously ignite. In particular, the most dangerous vehicles are heavy goods vehicles (HGVs), as they release a large amount of energy that generate high temperatures, poor visibility, and respiratory damage. This study aims to determine the potential consequences of large BEV fires in road tunnels using computational fluid dynamics (CFD). Furthermore, a comparison between a BEV and an ICEV fire shows the differences related to the thermal and the toxic impact. Furthermore, the adoption of a longitudinal ventilation system in the tunnel helped to mitigate the BEV fire risk, keeping a safer environment for tunnel users and rescue services through adequate smoke control. Full article

In rapidly urbanizing environments, environmental stressors—such as air pollution, noise, heat, and green space depletion—substantially exacerbate public health burdens, contributing to the global rise of non-communicable diseases, particularly hypertension, cardiovascular disorders, and mental health conditions. Despite expanding research on green spaces and health (+76.9%, 2019–2025) and optimization and algorithmic approaches (+63.7%), the compounded and synergistic impacts of these stressors remain inadequately explored or addressed within current urban planning frameworks. This study presents a Mixed Methods Systematic Review (MMSR) to investigate the potential of AI-driven urban design optimizations in mitigating these multi-scalar environmental health risks. Specifically, it explores the complex interactions between urbanization, traffic-related pollutants, green infrastructure, and architectural intelligence, identifying critical gaps in the integration of computational optimization with nature-based solutions (NBS). To empirically substantiate these theoretical insights, this study draws on longitudinal 24 h dynamic blood pressure (BP) monitoring (3–9 months), revealing that chronic exposure to environmental noise (mean 79.84 dB) increases cardiovascular risk by approximately 1.8-fold. BP data (average 132/76 mmHg), along with observed hypertensive spikes (systolic > 172 mmHg, diastolic ≤ 101 mmHg), underscore the inadequacy of current urban design strategies in mitigating health risks. Based on these findings, this paper advocates for the integration of AI-driven approaches to optimize urban environments, offering actionable recommendations for developing adaptive, human-centric, and health-responsive urban planning frameworks that enhance resilience and public health in the face of accelerating urbanization. Full article

Understanding the differential impacts of emission sources of volatile organic compounds (VOCs) on formaldehyde (HCHO) levels is pivotal to effectively mitigating key photochemical radical precursors, thereby enhancing the regulation of atmospheric oxidation capacity (AOC) and ozone formation. This investigation systematically selected and analyzed year-long VOC measurements across three urban zones in Shenzhen, China. Photochemical age correction methods were implemented to develop the initial concentrations of VOCs before source apportionment; then Positive Matrix Factorization (PMF) modeling resolved six primary sources: solvent usage (28.6–47.9%), vehicle exhaust (24.2–31.2%), biogenic emission (13.8–18.1%), natural gas (8.5–16.3%), gasoline evaporation (3.2–8.9%), and biomass burning (0.3–2.4%). A machine learning (ML) framework incorporating Shapley Additive Explanations (SHAP) was subsequently applied to evaluate the influence of six emission sources on HCHO concentrations while accounting for reaction time adjustments. This machine learning-driven nonlinear analysis demonstrated that vehicle exhaust nearly always emerged as the primary anthropogenic contributor in diverse functional zones and different seasons, with gasoline evaporation as another key contributor, while the traditional reactivity metric method, ozone formation potential (OFP), tended to underestimate the role of the two sources. This study highlights the primacy of strengthening emission reduction of transportation sectors to mitigate HCHO pollution in megacities. Full article

Detecting pharmaceuticals in environmental matrices, particularly in wastewater, is crucial due to their potential environmental occurrence and unpredictable ecological and health-related consequences. These substances, often present in trace amounts, require highly sensitive and selective analytical methods for effective monitoring. A modified version of the QuEChERS (Quick, Easy, Cheap, Effective, Rugged, and Safe) method was evaluated to evaluate 18 pharmaceuticals and 2 metabolites in wastewater samples using liquid chromatography with tandem mass spectrometry (LC-MS/MS). The method’s performance was assessed using linearity, recovery, precision, limits of quantification (LOQ) and detection (LOD), and the matrix effect (ME). The final method was based on acetonitrile, Na₂EDTA, citrate buffer, and graphene oxide (GO). Finally, the calibration curves prepared in acetonitrile and the matrix extract showed a correlation coefficient of 0.99. Most of the compounds had LOQ values lower than 0.5 μg⋅mL⁻¹. Recoveries were achieved in the 70–98% range, with RSD lower than 13%. GO allowed the elimination of the ME, which occurred in the range of −11% to 15%. The results indicate that a low-cost and straightforward method is suitable for routinely monitoring pharmaceuticals in wastewater, which is crucial for minimizing the impact of pollutants on aquatic ecosystems. Full article

Combustion of aviation jet fuel emits a complex mixture of pollutants linked to adverse health outcomes among airport personnel and nearby communities. While epidemiological studies showed the detrimental effects of aviation-derived air pollutants on human health, the molecular mechanisms of the interactions of these pollutants with cellular biomolecules like proteins that drive the adverse health effects remain poorly understood. In this study, we performed molecular docking simulations of 272 pollutant–protein complexes using AutoDock Vina 1.2.7 to characterize the binding strength of the pollutants with the selected proteins. We selected 34 aviation-derived pollutants that constitute three chemical categories of pollutants: volatile organic compounds (VOCs), polyaromatic hydrocarbons (PAHs), and organophosphate esters (OPEs). Each pollutant was docked to eight proteins that play critical roles in endocrine, metabolic, transport, and neurophysiological functions, where functional disruption is implicated in disease. The effect of binding of multiple pollutants was analyzed. Our results indicate that aliphatic and monoaromatic VOCs display low (<6 kcal/mol) binding affinities while PAHs and organophosphate esters exhibit strong (>7 kcal/mol) binding affinities. Furthermore, the binding strength of PAHs exhibits a positive correlation with the increasing number of aromatic rings in the pollutants, ranging from nearly 7 kcal/mol for two aromatic rings to more than 15 kcal/mol for five aromatic rings. Analysis of intermolecular interactions showed that these interactions are predominantly stabilized by hydrophobic, pi-stacking, and hydrogen bonding interactions. Simultaneous docking of multiple pollutants revealed the increased binding strength of the resulting complexes, highlighting the detrimental effect of exposure to pollutant mixtures found in ambient air near airports. We provide a priority list of pollutants that regulatory authorities can use to further develop targeted mitigation strategies to protect the vulnerable personnel and communities near airports. Full article

Rapid industrialization and urbanization have progressed in Korea, yet public attention to hazardous pollutants emitted from industrial complexes remains limited. With the increasing coexistence of industrial and residential areas, there is a growing need for real-time monitoring and management plans that account for the rapid dispersion of hazardous air pollutants (HAPs). In this study, we conducted spatiotemporal data collection and analysis for the first time in Korea using real-time measurements obtained through mobile extractive differential optical absorption spectroscopy (Me-DOAS) mounted on a solar occultation flux (SOF) vehicle. The measurements were conducted in the Saha Sinpyeong–Janglim Industrial Complex in Busan, which comprises the Sasang Industrial Complex and the Sinpyeong–Janglim Industrial Complex. BTEX compounds were selected as target volatile organic compounds (VOCs), and real-time measurements of both BTEX and fine particulate matter (PM) were conducted simultaneously. Correlation analysis revealed a strong relationship between PM₁₀ and PM_2.5 (r = 0.848–0.894), indicating shared sources. In Sasang, BTEX levels were associated with traffic and localized facilities, while in Saha Sinpyeong–Janglim, the concentrations were more influenced by industrial zoning and wind patterns. Notably, inter-compound correlations such as benzene–m-xylene and p-xylene–toluene suggested possible co-emission sources. This study proposes a GIS-based, three-dimensional air quality management approach that integrates variables such as traffic volume, wind direction, and speed through real-time measurements. The findings are expected to inform effective pollution control strategies and future environmental management plans for industrial complexes. Full article

Per- and polyfluoroalkyl substances (PFASs) are emerging pollutants of global concern due to their high environmental persistence and bioaccumulative characteristics. This study investigates PFAS concentrations in soils from China through an extensive literature review, covering soil samples from seventeen provinces and the years from 2009 to 2024. It was found that the total concentration of PFAS in soil ranged from 0.25 to 6240 ng/g, with the highest contamination levels observed in coastal provinces, particularly Fujian (620 ng/g) and Guangdong (1090 ng/g). Moreover, Fujian Province ranked the highest among multiple regions with a median PFAS concentration of 15.7 ng/g for individual compounds. Ecological risk assessment, focusing on areas where perfluorooctanoic acid (PFOA) or perfluorooctane sulfonate (PFOS) were identified as the primary soil PFAS compounds, showed moderate ecological risk from PFOA in Shanghai (0.24), while PFOS posed a high ecological risk in Fujian and Guangdong, with risk values of 43.3 and 1.4, respectively. Source analysis revealed that anthropogenic activities, including PFAS production, firefighting foam usage, and landfills, were the primary contributors to soil contamination. Moreover, soil PFASs tend to migrate into groundwater via adsorption and seepage, ultimately entering the human body through bioaccumulation or drinking water, posing health risks. These findings enhance our understanding of PFAS distribution and associated risks in Chinese soils, providing crucial insights for pollution management, source identification, and regulation strategies in diverse areas. Full article