Nature Environment and Pollution Technology

Activity Concentrations of Natural Radionuclides and Ingestion Radiological Risk in Common Medicinal Plants from Iraq

The increasing use of medicinal plants as natural alternatives to pharmaceutical drugs has raised concerns about contamination by naturally occurring radioactive materials and the potential health risks associated with their consumption. This study aimed to determine the activity concentrations of U-238, Th-232, and K-40 in commonly consumed medicinal plants and to assess the associated radiological risks resulting from their ingestion. Twenty medicinal plant samples were collected from four herbal shops in Al-Diwaniyah City, Iraq, and analyzed using gamma-ray spectrometry with a NaI(Tl) detector on a dry-weight basis. The mean activity concentrations were 3.90 ± 0.39 Bq.kg-1 for U-238, 13.03 ± 1.16 Bq.kg-1 for Th232, and 548.99 ± 12.65 Bq.kg-1 for K-40. The results showed that the activity concentrations of U-238 and Th-232 were below the global average values reported by UNSCEAR, whereas the activity concentration of K-40 exceeded these values in most samples because of natural uptake and agricultural practices. All calculated radiological hazard indices, including radium equivalent activity and excess lifetime cancer risk, were within the recommended safety limits. Overall, the findings confirm that the investigated medicinal plants are radiologically safe for consumption under normal conditions of use while emphasizing the need for regular monitoring to support long-term public health protection.

Zainab Hadi Rajih and Osamah Nawfal Oudah

Modeling Temporal Persistence in Daily Pan Evaporation Using Interpretable Machine Learning

Accurate prediction of daily pan evaporation (Ep) is critical for irrigation management and water resource planning, yet it remains challenging due to strong temporal variability and persistence. Most available models are based primarily on contemporaneous meteorological variables and do not account for the inherent memory of evaporation. This paper systematically explores the impact of temporal memory on daily Ep by explicitly separating evaporation persistence from meteorological memory through a machine learning framework. A Categorical Boosting (CatBoost) model was used to analyze multi-year data from a semi-arid to sub-humid area in western-central India. The model used lagged Ep and meteorological variables at 1-, 3-, 7-, and 14-day timescales. The coefficient of determination (R²), root mean square error (RMSE), and mean absolute error (MAE) were used to evaluate model performance, while Random Forest and XGBoost were used for benchmarking. Feature importance and SHAP analyses provided interpretability. The findings indicate that the inclusion of a 1-day lag of pan evaporation substantially improves predictive performance, with RMSE decreasing to 0.83 mm. This improvement indicates strong short-term persistence in day-to-day evaporation. Longer evaporation lags degrade performance, whereas lagged meteorological variables provide modest additional improvement beyond evaporation memory. CatBoost demonstrated the most balanced performance among the evaluated models. Overall, the findings confirm that short-term evaporation persistence dominates temporal dependence in daily Ep, with meteorological memory playing a secondary role, thereby offering a physically interpretable and efficient framework for data-driven evaporation modeling.

Jaydeep Kale and Sanjaykumar Sharma

Three Decades of Urban Heat Dynamics in Patna, India: A Remote Sensing-Based Hotspot Analysis

Rapid urbanization in tropical cities has intensified surface thermal stress, yet the longterm persistence and spatial structure of urban heat remain poorly understood, particularly in rapidly expanding cities of the Global South. This study investigates three decades (1995–2025) of urban thermal dynamics in Patna, India, with a focus on identifying longterm temperature trends, examining their relationship with vegetation greenness and built-up expansion, and assessing the spatial persistence of urban heat hotspots. Using a longitudinal remote sensing framework, Land Surface Temperature (LST) was analyzed alongside the Normalized Difference Vegetation Index (NDVI) and Normalized Difference Built-up Index (NDBI), derived from multi-decadal Landsat imagery processed in a cloudbased environment. A comprehensive spatiotemporal analytical approach integrating nonparametric trend analysis, correlation testing, hotspot persistence mapping, and multivariate regression modeling was employed to capture both temporal trajectories and spatial stability of urban warming. Results reveal a statistically significant increase in mean LST at a rate of approximately 0.13°C yr?¹, accompanied by a strong and monotonic rise in built-up intensity, while vegetation greenness exhibits high interannual variability without a significant longterm trend. Spatial analysis identifies a marked regime shift around the mid-2000s, after which high-temperature zones persistently dominate more than 95% of the urban area, with no observed reversals over the subsequent two decades. Regression results confirm builtup expansion as the sole statistically significant predictor of long-term surface warming at the city scale. Collectively, the findings suggest that Patna has experienced a sustained shift toward long-term dominance of high-temperature zones, indicating increasing persistence of urban heat across the city. The study provides robust empirical evidence of long-term urban heat persistence in a tropical city and offers a transferable analytical framework for identifying sustained thermal risk to support climate-sensitive urban planning and adaptation strategies.

Avinash Kumar Singh and Manoj Kumar

Dispersion Modeling of SO? and NO? Emissions Using AERMOD on Ambient Air Quality at Steam Power Plant PT.X in Southeast Sulawesi, Indonesia

This study aims to analyze SO2 and NO2 concentrations around the PT.X power plant through direct measurements, model their distribution patterns using AERMOD, and evaluate the model’s performance using RMSE, MBE, and R statistical tests. Monitoring was conducted at two monitoring points (PLTU PT.X Area and Nii Tanasa Village) over four 1-hour intervals (morning, afternoon, evening, night) using an Impinger Air Sampler. The results show that the highest field-measured SO2 (39.95 µg m?³) and NO2 (14.82 µg m?³) occurred during the afternoon, whereas AERMOD predicted peak concentrations at night, reaching SO2 (31.87 µg m?³) and NO2 (10.56 µg m?³) at the PLTU PT.X monitoring point, indicating stable atmospheric conditions. Pollutant distribution aligns with the prevailing north-northeast winds, with concentrations decreasing with distance and remaining within regulatory limits. Statistical validation for SO2 and NO2 yielded RMSE values of 14 µg m?³ and 5.37 µg m?³, MBE of -10.44 µg m?³ and -4.32 µg m?³, and R of 0.36 and 0.12, respectively. These values reflect the inherent challenges of aligning short-term field data with long-term dispersion modeling. It is concluded that spatial proximity to emission sources is the primary factor determining concentration patterns. While acknowledging temporal limitations for full-scale validation, the AERMOD model serves as a valuable preliminary screening tool for these distribution patterns. These findings provide an initial overview to inform decision-making and support the development of effective emission mitigation and environmental management strategies for the surrounding areas.

Nur Miftahuljannah , Sumarni Hamid Aly and Muralia Hustim

Fish Diversity and Habitat Complexity: The Role of Macrophytes and Physicochemical Parameters in Urban and Rural Tropical Lakes

This study highlights the impact of urbanization, agricultural runoff, and invasive species on freshwater ecosystems and aquatic biodiversity. It presents a comparative ecological assessment of two freshwater lakes in Vellore District, Tamil Nadu, India: Katpadi Lake (urban) and Saina Palayam Lake (rural). A total of 15 fish species were documented across both lakes, with Oreochromis niloticus identified as an exotic invasive species. The fish community was dominated by Cypriniformes (60%), demonstrating ecological adaptability. Diversity indices such as Shannon (H?) and Simpson (1–D) showed slight variations between the lakes. Katpadi Lake had higher total dissolved solids and conductivity, indicating greater anthropogenic influence. Ten macrophyte species, including submerged, floating-leaved, and emergent types, were observed, with their distribution differing between urban and rural sites, reflecting habitat and water-quality differences. Macrophyte diversity was greater in Saina Palayam Lake, linking habitat complexity to higher fish diversity. Submerged species such as Najas marina and Myriophyllum spicatum likely enhance habitat quality for native species. The rural wetland recorded nitrate and phosphate concentrations of 3 mg L?1 and 0.13 mg L?1, respectively, indicating measurable nutrient enrichment, while higher hardness, chloride, and ammonia levels in Katpadi Lake point to urban pollution. The findings underscore the importance of integrated monitoring of fish, macrophytes, and water quality to conserve and manage freshwater biodiversity across different environmental contexts.

I. Annie Pushpa, K. Maheshkumar, V. Deepak Samuel and N. Nirmal Magadalenal

Household Behavioral Compliance in Waste Management Using the Extended Theory of Planned Behavior

Despite the expansion of waste management infrastructure and regulations, behavioral compliance with proper waste management practices remains inconsistent, particularly in developing-country contexts. This study investigates the factors influencing household compliance with waste management practices by extending the Theory of Planned Behavior (TPB) to incorporate motivational and deterrence-related mechanisms. A quantitative research design was employed using survey data collected from 106 household respondents and analyzed through Partial Least Squares Structural Equation Modeling (PLS-SEM) using SmartPLS 4. The measurement and structural models were evaluated to assess construct validity, reliability, and the significance of the hypothesized relationships. The PLS-SEM results revealed that motivation was the strongest predictor of behavioral compliance (? = 0.499, p < 0.001). These findings indicate that motivation is the strongest predictor of behavioral compliance, while perceptions of the waste management system also exert a significant positive influence. Penalty awareness does not directly affect compliance but significantly enhances motivation, suggesting an indirect deterrence mechanism. In contrast, attitudes toward waste management practices do not demonstrate a significant effect on compliance behavior. Furthermore, the study contributes to the literature by empirically validating an extended TPB framework in a developing-country setting such as the Philippines and demonstrating the importance of integrating penalty- and motivation-related constructs in explaining behavioral compliance. The policy implications of this study emphasize the need for behavior-centered governance strategies that complement infrastructure investments through visible enforcement, motivational interventions, and improved public perceptions of waste management systems.

Mary Ellen Camarillo

Legacy Pesticides in Aquatic Systems: Mechanistic Persistence, Regulatory Lag, and Catchment-Scale Remediation Imperatives

Legacy pesticides remain a persistent environmental challenge despite regulatory bans and reductions in agricultural pesticide use. Continued detections in surface water and groundwater indicate that historical residues stored in soils and sediments contribute to long-term contamination. This review evaluates the mechanistic processes governing legacy pesticide persistence, including adsorption–desorption dynamics, sediment storage, preferential flow pathways, and groundwater recharge behavior. A structured literature synthesis of peer-reviewed studies published between 2000 and 2025 was conducted to assess monitoring trends, physicochemical determinants of persistence, and remediation technologies applicable at the catchment scale. Evidence indicates that exceedances of the 0.1 µg L?¹ regulatory threshold remain frequent in vulnerable agricultural regions because of delayed release from environmental reservoirs rather than ongoing application alone. Adsorption-based technologies, particularly activated carbon systems, show potential for practical mitigation, while biochar amendments and advanced oxidation processes offer complementary treatment pathways. The analysis indicates that regulatory restrictions should be coupled with targeted remediation and soil risk assessment to achieve measurable improvements in water quality. An integrated catchment-level management framework is therefore proposed to address legacy contamination and support sustainable water resource protection.

Pradip T. Salve

Evaluating Green Infrastructure Interventions for Land Surface Temperature Reduction: A PRISMA-Based Systematic Review

Rapid urbanization has intensified land surface temperatures (LST) in cities worldwide, exacerbating the urban heat island effect and increasing risks to thermal discomfort, public health, and energy demand. Green infrastructure (GI), including street trees, urban parks, green roofs, vertical greenery, and blue-green systems, has emerged as a key nature-based strategy for mitigating urban surface heat. This study presents a PRISMA-guided systematic review combined with bibliometric analysis to evaluate the effectiveness of GI interventions in reducing LST within built environments. A comprehensive search of the Web of Science Core Collection identified 211 records, of which 61 peer-reviewed studies published between 2012 and 2026 met the predefined inclusion criteria. Bibliometric analysis using VOSviewer reveals a rapidly expanding research field, characterized by exponential growth (R² = 0.9135) and strong thematic convergence around keywords such as green infrastructure, land surface temperature, urban heat island, and built environment. Keyword co-occurrence mapping identifies multiple interconnected research clusters, highlighting integration across thermal regulation, urban morphology, climate adaptation, and methodological innovation, while also revealing the relative underrepresentation of social and equity-focused dimensions. Geographically, research output is concentrated in Asia, Europe, and Australia, indicating regional imbalances in evidence generation. The systematic synthesis shows that treebased green infrastructure and urban parks consistently produce the largest LST reductions, commonly ranging from 2–4°C, with higher localized reductions, whereas green roofs and vertical greenery systems deliver more localized but critical cooling benefits in high-density urban areas. Cooling effectiveness is strongly context-dependent, shaped by climate zone, urban morphology, vegetation structure, and spatial configuration. Notably, several studies demonstrate that small-scale GI interventions can significantly reduce surface heat stress in informal settlements, suggesting potential equity implications, particularly in heat-vulnerable urban areas, although systematic evidence remains limited. By integrating bibliometric mapping with PRISMA-based content analysis, this review provides a context-sensitive, design-aware, and climate-responsive synthesis to support evidence-based urban heat mitigation and climate-resilient planning.

Avinash Kumar Singh and Manoj Kumar

Acceptance Rate and Publication Time

Acceptance rate: approximately 20%
Initial editorial screening: median 15 days
First editorial decision: median 7 weeks
Online prepublication after acceptance: median 5 weeks
Final Publication: median 5 months after acceptance

Journal Metrics

Scopus CiteScore (2025): 2.1
SCImago Journal Rank (SJR) (2025) = 0.314 | Q3
NAAS Rating (2024) = 5.33

Abstracting and Indexing

Scopus
Directory of Open Access Journals (DOAJ)
Zoological Record (Clarivate)
GEOBASE (Engineering Village)
CAB Abstracts (CABI)
Chemical Abstracts Service (CAS)
AGRIS (FAO)
CNKI Scholar (China National Knowledge Infrastructure)
EBSCO Environment Index
Pollution Abstracts (ProQuest)

All published articles are assigned Crossref DOIs