Environmental and Earth Sciences

Abstract: Aeration diffusers in wastewater treatment plants are designed under a two factor protocol: deliver the actual oxygen requirement at the lowest practical energy. This paper argues that the protocol is incomplete, because the same design choices that improve oxygen transfer and energy, namely lower dissolved oxygen setpoints, finer bubbles and deeper submergence, also change nitrous oxide (N₂O) emission and bioaerosol release. A structured review of the literature found the four factors studied separately or in pairs, but no protocol that brings all four into diffuser design. The paper assembles the governing equations and links them through the field oxygen transfer efficiency, which fixes the air flow rate, then proposes an integrated protocol with a composite objective subject to the oxygen demand constraint. An illustrative example for a 1,000 m³ tank, using assumed dissolved N₂O concentrations, shows that the option preferred by the conventional protocol, fine bubble aeration at a setpoint of 1.0 mg/L, has the lowest energy use (422 kWh/d) but the highest total carbon footprint (1,743 kg CO₂e/d), because the added N₂O outweighs the energy saving. The ranking reverses once the dissolved N₂O ratio between the two setpoints exceeds about 1.23, an increase of more than about 23%, and published simulations suggest that threshold is likely to be exceeded. The ranking of fine against coarse bubbles depends on an uncalibrated bubble size exponent, so the bioaerosol results are reported as a parametric family in that exponent rather than as predictions. A staged measurement programme is set out to calibrate and verify the protocol.

Abstract: Rice (Oryza sativa) is a high water-demand crop, with yield strongly dependent on irrigation water availability, particularly in the semi-arid Riverina region of Australia. Enhancing the drought resilience of rice production therefore requires improved water management strategies, such as Aerobic Rice (AR) as an alternative to the traditional Continuous Flooding (CF) strategy. To better characterize AR water-saving potential, the main components of the water balance were measured under these systems. Net irrigation was measured using the Agriflo XCi ultrasonic Doppler sensor, and evapotranspiration (ET) with the LI-710 Eddy Covariance sensor. Three commercial-scale rice farms during the 2024–2025 season in the Riverina region were monitored. The analysis focused on three aspects: (i) rice crop development, (ii) water management and water balance, and (iii) rice performance and water productivity indicators. Water savings associated with AR were estimated at 18.4% in a side-by-side comparison. In addition, final harvested yield increased by 5.5%, resulting in a 29.5% increase in water productivity. ET from the AR paddock was 6.5% higher than under CF. Nevertheless, AR reduced Deep Percolation (DP) by 59.0% compared with CF. Two other CF paddocks were also monitored across the region, and water use from 13.0 to 14.5 ML ha^-1 has been observed as the baseline irrigation water requirement for permanent ponded rice paddocks in this region. These findings provide evidence that AR can deliver meaningful water savings while improving water productivity in commercial-scale rice paddocks in this semi-arid region of Riverina.

Abstract: Groundwater overexploitation can promote land deformation and earth-fissure development in semi-arid aquifers, particularly where hydrogeological conditions vary spatially. This study evaluated the relationship between groundwater extraction pressure, groundwater drawdown, and earth-fissure occurrence in the Valle de Santiaguillo aquifer, Durango, Mexico. Earth fissures were characterized using UAV-based Structure-from-Motion photogrammetry, while groundwater extraction pressure and drawdown were analyzed in a GIS environment. A 60 × 60 m spatial grid was used to integrate predictor variables, and binary logistic regression was applied to model fissure occurrence. Two major fissures with a combined mapped length of 946 m were identified. Groundwater extraction pressure was significantly associated with fissure occurrence (OR = 4.91, 95% CI: 2.06–11.73), whereas the groundwater drawdown gradient showed a stronger association (OR = 64.56, 95% CI: 10.50–397.39). The model showed good discrimination (AUC = 0.854). Fissure-associated cells occurred mainly under intermediate-to-high extraction and drawdown conditions rather than at max-imum values. These results suggest that spatial contrasts in groundwater-level decline may provide a useful indicator of earth-fissure susceptibility in overexploited aquifers.

Abstract: Climate-smart irrigation (CSI) brings productivity and livelihoods together with adaptation, resilience and, where feasible, mitigation. Judging whether irrigation is climate-smart is complicated by the different purposes of irrigation decisions and the scales at which their consequences become visible. This focused integrative review distinguishes actors from the decision perspectives through which success is judged. It examines six non-hierarchical perspectives: user/livelihood, service/operational, resource stewardship/allocation, public-policy/societal, public/development investment, and commercial/market. Three decision situations illustrate their interactions. Improved irrigation efficiency may benefit farmers without increasing basin water availability; solar irrigation may reduce operational emissions while changing groundwater-use incentives; and scarcity allocation brings competing needs, rights and resource risks into the same decision. These situations demonstrate why success within one decision context does not necessarily establish climate-smart performance. The review examines the scale and boundaries of supporting evidence and distinguishes demonstrated outcomes from indirect evidence and enabling conditions. The six perspectives are not criteria every irrigation decision must satisfy. Their value lies in revealing when a decision depends on consequences, conditions or evidence outside the immediate decision position. CSI can be judged more clearly through what irrigation decisions achieve, for whom, under what conditions, at what scale and with what climate relevance.

Abstract: Microbial fuel cells (MFCs) offer a sustainable approach for simultaneous azo dye removal and bioelectricity generation from wastewater. In the present study, the effect of methyl orange (MO) dye concentration on the performance of an earthen membrane cylindrical MFC was evaluated under long-term operation. Five MFC configurations, in duplicate, were operated with acetate-fed anodes for 22 operational cycles with dye concentrations ranging from 20 to 100 mg L⁻¹. Throughout the study, stable decolourisation was observed with maximum dye removal efficiencies of 90.0%, 88.1%, 87.8%, 86.9%, and 86.0% at 20, 40, 60, 80, and 100 mg L⁻¹ MO, respectively. The highest power density obtained was 48 mW m⁻² for an MO concentration of 60 mg L⁻¹. Reduced power generation at higher dye concentrations (>60 mg L⁻¹) may be due to inhibitory effects on microbial electron transfer. Considering decolourisation, power output and coulombic efficiency together, 60 mg L⁻¹ was identified as the optimal MO concentration, whereas up to 100 mg L⁻¹ could still be decolourised by >85% at the cost of lower power output. The results indicate that low-cost earthen membrane cylindrical MFCs are a potential technology for sustainable wastewater treatment and can effectively decolourise MO while recovering bioenergy under prolonged operation.

Abstract: Chile’s Monitoreo de Extracciones Efectivas (MEE) network reports pumping rate and water level at abstraction wells. We propose a daily, well-specific stress index that combines current pumping rate, reported water level and their 30-day gradients through robust standardization with the median and median absolute deviation, and per-well percentile normalization. Mann–Kendall screening classified 5689 wells; 42 wells were then selected to cover the four combinations of increasing or decreasing pumping and rising or declining water level, and 41 met the minimum record length. Episodes were defined as index values of at least 0.50 for at least five consecutive days. Wells with decreasing pumping and rising water level had the lowest mean High–Critical fraction (12.9%) and episode frequency (2.6 per well-year); wells with increasing pumping and declining water level had the highest (18.8% and 3.9), although bootstrap intervals overlapped. Regime extremes were stable under weight changes of 0.05 but sensitive to the gradient window, and a prospective replay agreed with the retrospective alert state on 89.5% of days. Predefined rules applied to eight wells implied 1.5–4.8 activations and 4.6–12.7 setpoint changes per year. The index has not been validated against operational failures and does not estimate sustainable yield; it is intended for screening and operator review.

Abstract: Coastal aquifer responses to tides can be simulated using coupled groundwater flow and solute transport models, but repeated numerical simulations are computationally costly. We developed a Deep Operator Network (DeepONet) surrogate for an idealized two-dimensional coastal aquifer simulated with SUTRA. The model maps tidal amplitude and landward hydraulic head to transient pressure head and concentration fields. Supervised, physics-regularized, and physics-only training strategies were compared, and the supervised model was evaluated at higher tidal amplitudes using few shot adaptation. On test simulations within source-range, the supervised model achieved pooled RMSEs of 5.87×10⁻³ m for pressure head and 5.75×10⁻⁴ for concentration. Adding continuous physics constraints did not improve agreement with the numerical reference, and lower physics residuals did not necessarily correspond to smaller field errors. Prediction accuracy decreased outside the source range, whereas adaptation with two higher-amplitude simulations reduced pressure-head and concentration RMSEs by 36.8% and 68.5%, respectively. The surrogate reconstructed a complete 72-h response in approximately 0.018 s, compared with approximately 15 s for the numerical simulation. These results demonstrate the potential of DeepONet as a computationally efficient surrogate for tide-driven coastal aquifer simulations while showing the dependence of physics-based regularization and adaptation on training data and forcing-space coverage.

Abstract: Piped water is the main source of household water in Trinidad, yet service problems are widely reported while the national utility is under financial strain. Additionally, very little survey evidence exists on how consumers rate the service or whether they would pay more for improvements. This study used an online questionnaire, distributed through email, social media and mobile messaging, to which 107 adults aged 18–60 responded; perceptions, coping behaviour and willingness to pay (WTP) were examined with descriptive statistics, chi-square tests and rank correlations. Only 26.2% of respondents were on a scheduled supply. Low pressure (34.3% of reported problems), discoloured water (27.6%) and supply interruptions (16.6%) were the most frequently reported problems, while odour was rarely cited (3.9%). Satisfaction with water quality was moderate (44.9% satisfied, 41.1% neutral, 14.0% dissatisfied), and 38.3% of households treated water at home. Only 22.4% (95% CI 15.6–31.2%) were definitely willing to pay a higher monthly fee, 35.5% were unsure and 42.1% were not; among those indicating an amount, 70.0% would accept an increase of no more than 5%. The main reasons for declining were the belief that quality should improve at no extra cost (58.2%) and lack of trust in the water authority (55.7%), rather than inability to pay (16.5%). WTP rose with household income, from 0% in the lowest band to 50.0% above TT$20,000 per month, but was not significantly associated with residence, household size, satisfaction or home treatment. Willingness to pay for better piped water is therefore limited, conditional on trust in the provider and concentrated among higher-income households, so visible service improvements, transparent accountability and income-sensitive tariff design appear to be preconditions for price-based funding of upgrades.

Abstract: Estimating organic carbon fluxes in data-limited tropical island catchments is constrained by sparse discharge records and concentration measurements. For the Changhua River, Hainan Island, we compared three calendar-month runoff-coefficient models based on the mean, median, and geomet-ric mean with a linear model incorporating current- and previous-month precipitation. Models were fitted to monthly records from 2011–2023 and evaluated against all 12 months of 2024. Holdout root mean square errors were 42.669, 39.544, 38.382, and 31.801 mm, respectively. The dual-precipitation model performed best, with a Nash–Sutcliffe efficiency of 0.763 and a percentage bias of −10.220%. Its fixed parameters were applied to September–November 2025 precipitation. The resulting monthly equivalent runoff coefficients were transferred to Ningyuan and Lingshui using their precipitation and drainage areas. Estimated runoff volumes were multiplied by equally weighted mean concentrations from three October–November surveys. Conditional dissolved or-ganic carbon exports were 2763.373, 730.024, and 655.773 t C for Changhua, Ningyuan, and Lingshui, respectively; corresponding particulate organic carbon exports were 571.135, 201.645, and 441.045 t C. These estimates depend on unverified catchment transferability and concentration rep-resentativeness, particularly for unsampled September. They apply to a limited observation period and do not establish annual carbon budgets or carbon sequestration.

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Adsorption isotherm parameters are widely used to characterize biosorbent performance and are often interpreted as intrinsic properties of the adsorbent. However, the extent to which these parameters depend on biosorbent concentration remains insufficiently understood. Here, the adsorption of Ni²⁺ and Cd²⁺ by Chlorella vulgaris was systematically investigated over a broad range of biomass concentrations by determining complete adsorption isotherms independently at each biomass level. Increasing biomass concentration consistently decreased the specific adsorption capacity and shifted the adsorption isotherms toward lower apparent saturation capacities for both metal ions. Langmuir and Freundlich models were fitted using both linearized and nonlinear regression. Despite differences in the absolute parameter values obtained by the fitting approaches, all models revealed the same biomass-dependent trend. In particular, the Langmuir maximum adsorption capacity (q_max) and Freundlich adsorption coefficient (K_F) decreased systematically with increasing biomass concentration. These results demonstrate that biomass concentration influences the experimentally observed adsorption behaviour and the isotherm parameters derived from it. Consequently, q_max and K_F should not be interpreted as universal material constants without considering the biomass concentration at which they were determined. Biomass concentration should therefore be reported and considered when comparing biosorption isotherms across independent studies.

Abstract: Rain gauge network design requires both information retention and observations that support consequential decisions. We connect joint entropy, total correlation and value of information (VOI) using rainfall-network results for the Rio das Velhas basin, Brazil, and an analytical decision model. The study considers 39 observed gauges, including 28 within the basin, and 101 interpolated candidate locations. Configurations of 10, 12 and 15 gauges retain 85.6%, 88.2% and 90.8% of the reference joint entropy of 7.29 bits; the 15-gauge configuration retains more than 90% with 46.4% fewer stations. Annual-rainfall contours and mapped VOI classes complement these network-size comparisons. Under a stated two-state utility model, a low-rainfall prior of 0.20 and symmetric message reliability of 0.80 yield an expected value of sample information (EVSI) of 10.4 utility units, compared with a perfect-information bound of 19.0. Closed-form sensitivity analysis identifies the prior and reliability ranges in which messages change the preferred action. At a prior of 0.05, the same message model provides 0.0561 bits of mutual information but zero EVSI because both messages lead to the same action. The results distinguish information retained by a network from information that changes management choices. They support screening compact networks by entropy and evaluating their decision benefit under explicit probabilities, consequences and observation performance.

Abstract: Drinking water quality in industrializing regions is deteriorating due to the unregulated discharge of chemical effluents. Perfluorooctanoic acid is a highly persistent, bioaccumulative contaminant linked to severe toxicological outcomes, yet regulatory guidelines in regional water networks remain unavailable. This study optimized an extraction methodology to detect and quantify perfluorooctanoic acid contamination across municipal tap water and deep tube well groundwater infrastructure in Punjab, Pakistan, alongside assessing community health profiles. Drinking water samples were collected across active industrial estates and quantified using High-Performance Liquid Chromatography. Concurrently, a structured questionnaire was administered to residents within the study zones to evaluate water quality perceptions and waterborne disease prevalence. Chromatographic analysis revealed extensive aquifer contamination, reaching maximum concentrations of 33.83 milligrams per liter in tap water and 33.92 milligrams per liter in deep tube wells, vastly exceeding international health advisories. The community survey indicated a high prevalence of local health disorders, with diarrhea reported by 50% of respondents, followed by hepatitis at 25% and typhoid at 15%. These findings underscore an urgent need for implementing advanced membrane treatment interventions, establishing mandatory local regulatory thresholds, and executing public awareness campaigns to safeguard regional public health.

Abstract: Leakage diagnosis in water distribution networks is constrained by sparse instrumentation, uncertain models, and leak concurrency. We present a physics-informed spatio-temporal graph neural network evaluated end-to-end on the open Battle of the Leakage Detection and Isolation Methods (BattLeDIM) and L-Town benchmark (782 junctions, 905 pipes, 33 pressure sensors). Message passing operates on a conductance-weighted hydraulic Laplacian, trained by self-supervised sensor masking to reconstruct nodal pressure fields and latent pipe flows, embedding Hazen-Williams energy and mass-balance residuals in the loss under learned uncertainty weighting. Pressure at withheld sensors is reconstructed to 0.29 meters. A seeded ablation shows physical constraints degrade reconstruction accuracy by 0.10 meters of head while reducing nodal continuity violations by over five orders of magnitude, rendering the inferred state hydraulically admissible. Residuals feed two complementary detectors. A level-based statistic saturates under concurrent leakage; pairing it with a two-window onset contrast raises detection from 13 to 22 of 23 ground-truth leaks (95.7 %, 95 % confidence interval 79.0–99.2 %), with median detection times of 29 hours for abrupt and 74 hours for incipient events, releasing 96 % of annual leaked volume after detection. Localization transfers poorly from simulation, with a median error of 857 meters and only three leaks meeting the joint 300 meters criterion due to signal superposition under concurrency.

Abstract: The 2026 Super El Niño is the strongest in a decade, and the June-July-August Sea Surface Temperature is the warmest on record. A series of large snowfall events hit the Central Chilean Andes in July 2026. We use a combination of shorter period-of-record automated daily snow depth (d_s) and snow water equivalent (SWE) data with longer period-of-record manual monthly snowcourse (d_s and SWE) data to assess how rare the July snowstorms were. The return period statistical analysis showed that the snow accumulation was relatively uncommon with an 8- to 40-year recurrence for the more northerly sites.

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This study assessed surface water quality changes in Tien Giang province, Vietnam, during 2019–2023 using the water quality index (WQI), principal component analysis (PCA), and cluster analysis (CA). Researchers measured eleven parameters (temperature, pH, TSS, DO, BOD, COD, NH₄⁺-N, NO₃^--N, PO₄^3--P, Cl^-, and coliform) at 34 monitoring stations. Results indicated a marked decline in water quality over time, especially severe organic and microbial pollution during 2022–2023. During 2019–2020, water quality was mainly good to very good, with over 85% of stations stable; this temporarily improved in 2021 (44.12% very good). From 2022, VN_WQI ranged from 9–94, with poor, heavily polluted, and very heavily polluted stations increasing sharply; by 2023, 91.18% of stations recorded poor water quality. This decline was driven primarily by a more than fourteen-fold increase in mean coliform density between 2021 and 2023, together with persistently elevated BOD and COD, despite a concurrent improvement in dissolved oxygen. CA identified four groups with distinct pollution levels: Group I (S17, S19, S20) was most severely polluted; Groups II and IV showed large fluctuations; Group III (S34, Ly Quan canal) had the best water quality. PCA extracted four principal components explaining 77% of the total variance. The main factors affecting water quality included agricultural activities (cultivation, livestock, aquaculture), domestic and industrial wastewater, and saltwater intrusion. These findings provide a scientific basis for spatially prioritized pollution control and for rationalizing the provincial monitoring network, which is particularly relevant following the 2025 merger of Tien Giang into Dong Thap province.

Abstract: The GEOGloWS ECMWF Streamflow Service represents a paradigm shift in global hydrological forecasting by implementing Hydrology as a Service (HaaS), providing operational river discharge predictions for every river reach worldwide. This review examines the technical architecture, validation performance, and diverse applications of the GEOGloWS system, which centralizes computational resources at the European Centre for Medium-Range Weather Forecasts (ECMWF) to deliver 15-day ensemble streamflow forecasts and historical simulations since 1979 through open web services. The system addresses critical gaps in hydrological data availability, particularly benefiting hydromet services, local governments, and NGOs in data-scarce regions. Regional validation studies across Australia, Brazil, Colombia, Dominican Republic, Peru, Bhutan, and the Nile Basin demonstrate the system's global applicability, while bias correction methodologies significantly improve forecast accuracy. Applications span flood early warning systems, water resource management, transboundary river monitoring, and decision support for emergency management. Despite challenges including bias in ungauged basins, computational constraints, and the need for local calibration, GEOGloWS establishes a foundation for democratizing access to hydrological information. Future directions include enhanced spatial resolution, improved bias correction techniques, integration with Earth observation data, and expanded capacity building for operational implementation in developing regions.

Abstract: The national water network is a component of China’s infrastructure, and coordinating ecological security with economic development is important for its construction. Taking the Chao’er River to West Liao River Water Diversion Project, part of the three-horizontal and three-vertical Inner Mongolia water network, as a case study, this paper analyzes the main receiving areas, Tongliao and Xing’an League. Using panel data from 2019–2025, a matching degree model incorporating water resource, ecological, and economic dimensions was constructed. The Gini coefficient and coupling coordination degree were combined to assess spatial matching and its evolution before and after project operation, and optimization scenarios for current water allocation are proposed. After operation, water–economy and economy–ecology bivariate matching was generally good, while water–ecology matching remained low, a common weakness in both jurisdictions. Trivariate matching shifted from severe disorder through near disorder toward marginal coordination, with spatial differences: Tongliao showed low-level, strongly fluctuating matching, whereas Xing’an was stable but structurally imbalanced, constrained by a low comprehensive evaluation index. Differentiated pathways are proposed, including strengthened emergency ecological water replenishment in Tongliao and rebalancing the three subsystems, especially improving water use efficiency in Xing’an. These findings support project optimization and water network construction in comparable pastoral areas.

Abstract: Climate change, rising demand, pollution, and ecosystem degradation are intensifying pressures on water resources and increasing interest in nature-based solutions (NbS). This systematic literature review examines water-related NbS and implementation actors, drivers, and barriers. A Scopus search covered English- and Spanish-language publications from 2010 to 2024, with reporting informed by the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA). Of 186 records initially retrieved, 53 publications from 2017 to 2024 were retained. Descriptive bibliometric analysis and qualitative categorization, supported by VantagePoint version 15.2, identified 12 thematic categories, six driver dimensions, and seven barrier dimensions. Forty-seven publications appeared during 2020–2024, representing 88.7% of the retained corpus. The synthesis encompasses urban blue-green infrastructure, wetlands, river and floodplain restoration, rural landscapes, groundwater management, and related governance approaches. Implementation depends on interactions among public authorities, researchers, businesses, communities, landowners, utilities, and funding organizations. Stable financing, institutional coordination, technical capacity, and meaningful participation emerge as recurring enabling conditions. The findings support context-sensitive planning and comparable long-term monitoring. However, database and subject-area restrictions, heterogeneous study designs, and incomplete reporting of screening and appraisal procedures limit reproducibility and generalization. Publication frequency should not be interpreted as evidence of effectiveness or implementation success.

Abstract: Tropical cities are experiencing rapid urbanization, often without adequate resources to monitor its effects on runoff processes or to support flood forecasting and early warning. This study proposes a low-cost and potentially transferable remote sensing framework to assess the evolution of urban runoff susceptibility in rapidly urbanizing tropical watersheds. The framework combines multi-temporal satellite imagery, urban-adapted spectral indices, supervised Random Forest land use/land cover (LULC) classification, and hydrological analysis based on the Soil Conservation Service Curve Number (SCS-CN) method. It was applied to the Gourou (28 km²) and Bonoumin (46 km²) watersheds in Abidjan, Côte d’Ivoire, for 2002, 2016, and 2024. Spatially distributed runoff was estimated using rainfall scenarios of 30, 70, 100, and 302 mm and subsequently translated into runoff susceptibility indicators. The results reveal substantial urban expansion, particularly in Bonoumin, accompanied by increasing CN values and declining infiltration potential. Under the 30 mm rainfall scenario, the runoff coefficient increased from 0.29 to 0.53 in Bonoumin between 2002 and 2024, reflecting a marked hydrological transformation, while Gourou maintained a comparatively high runoff response throughout the study period. Under the extreme 302 mm scenario, runoff coefficients reached 0.94 in both watersheds in 2024. High and Very High runoff susceptibility classes also expanded substantially under extreme rainfall conditions. Although direct validation against observed discharge was not possible because both watersheds are ungauged, the identified trends are consistent with land-cover changes, previous studies, and the established SCS-CN hydrologic soil-group framework. The proposed framework therefore provides spatially explicit indicators that can support urban planning, flood preparedness, risk management, and early warning in data-scarce tropical cities.

Abstract: Indoor formaldehyde (HCHO) vapor and aqueous hexavalent chromium (Cr(VI)) are pervasive pollutants typically addressed with distinct, purpose-specific materials. In this study, a ternary Cu–Fe–Zn oxide (CuFeZnO) was synthesized via co-precipitation and evaluated as a dual-function material for both photocatalytic HCHO degradation and Cr(VI) adsorption. The catalyst exhibited a narrowed optical band gap of 2.3 eV, compared to 3.2 eV for TiO₂, consistent with enhanced visible-light absorption. Under low-intensity visible irradiation (single 18 W daylight lamp, 8.8 mW cm⁻²), 20 mg of CuFeZnO achieved 92.1% HCHO removal within 2 h, outperforming commercial TiO₂ (P25, 78.2%) and laboratory-synthesized TiO₂ (68.3%) under identical conditions, and retaining 90.8% conversion after seven reuse cycles. For Cr(VI) removal, CuFeZnO achieved 98.98% removal from a 50 mg L⁻¹ solution at pH 8 with a 0.2 g dose. Adsorption kinetics followed a pseudo-second-order model, and equilibrium data were best described by the Freundlich isotherm (R² = 0.992). A double-layer statistical physics model further captured the temperature-dependent equilibrium behavior (298–318 K) with high accuracy (R² = 0.997–0.998), yielding a near-unimolecular site occupancy (n ≈ 0.999 at 298 K) and a maximum adsorption capacity of 111.7 mg g⁻¹. The first-layer adsorption energy increased from 13.4 to 27.6 kJ mol⁻¹ with rising temperature, indicating a physisorption-dominated mechanism. Notably, CuFeZnO achieved comparable or superior HCHO conversion under substantially lower light intensity (18 W) than reported photocatalysts requiring 27–300 W sources. These results demonstrate CuFeZnO as a low-energy, reusable, and multifunctional material for simultaneous air and water remediation.