Environmental Monitoring and Assessment最新文献

This study assessed blood levels and interrelationships of toxic (Pb, Cd, Cr) and essential (Fe, Zn, Cu, Co, Ca) metals in adult male residents of a rural coal mining area (rCMA, n = 63) and an unexposed agricultural area (rAA, n = 60). All participants were healthy, disease-free, and had lived in their respective locations for over five years. Mean blood concentrations of Pb, Cd, Fe, Cu, and Co were significantly higher in rCMA than in rAA (p < 0.05). Among toxic metals, Pb showed the highest apparent absorption and retention. Pb and Cd were strongly correlated in both groups (r = 0.50–0.60, p < 0.0001), and, in rCMA, both metals exhibited negative associations with Fe and Ca, suggesting interference with essential mineral metabolism. Iron was inversely associated with Zn and positively correlated with Co, indicating potential nutrient imbalances, including Zn deficiency, under elevated Fe exposure. These results demonstrate that chronic, low-level exposure to multiple environmental metals can alter essential nutrient dynamics even when individual metal concentrations remain below toxic thresholds. The findings underscore the importance of incorporating multi-metal interaction into environmental health monitoring and developing targeted nutritional strategies for populations in industrially impacted regions.

Graphical Abstract

Land-use changes profoundly affect soil physical and chemical properties, influencing ecosystem functions and sustainability in tropical landscapes. This study evaluated soil properties across five land-use systems in Selangor, Malaysia: secondary forest, Pinus caribaea plantation, Swietenia macrophylla plantation, pasture, and oil palm plantation. Soil morphology, physicochemical attributes, mineralogical properties, and charge characteristics were assessed across soil depths. Principal Component Analysis (PCA) was employed to derive a PCA-based Soil Quality Index (SQI_PCA), integrating key soil indicators to quantify overall soil health. Results showed significant variations in soil texture, organic matter, total carbon, total nitrogen, cation exchange capacity, and exchangeable cations across land-use types and depths. Mahogany plantations exhibited the highest SQI_PCA, reflecting superior nutrient retention and organic matter accumulation, whereas secondary forests and pine plantations had the lowest indices, indicating greater soil degradation and acidity. Partial indices revealed that soils could be chemically fertile but physically degraded, highlighting the importance of multidimensional soil assessment. These findings underscore the influence of land-use practices on soil quality and provide valuable insights for sustainable land management and restoration strategies in tropical ecosystems.

Quantitative data on coastal land use changes are essential for effective resource management and sustainable development. In this study, we examined land use and land cover (LULC) changes, along with erosion and accretion, in the climate-sensitive Sundarbans of India using satellite imagery from 1973 to 2022. Over this period, approximately 478 km² of land was lost to erosion, while 408 km² were gained through accretion. Although single cropping remains the predominant land use system, the areas dedicated to settlements and aquaculture grew 7 times and 2.4 times, respectively. The double-cropped area expanded by 75.8%, while the mangrove area remained unchanged. Among all land use categories, single-cropped land was found to be the most vulnerable to loss. The soil salinity area of the arable land, calculated using the canopy response salinity index (CRSI) from satellite imagery, rose from 2246.2 km² to 2669 km² in the 30 years since 1989. Using a machine learning algorithm (cellular automata-artificial neural network (CA-ANN)), which incorporated both anthropogenic factors and projected temperature and rainfall data as explanatory variables, we estimated that by 2049, the settlement area will increase by 31.6%, aquaculture will expand by 30%, and vegetation cover will decrease by 12.6%, compared to 2019 levels. The LULC change trend and coastline dynamics are expected to further exacerbate land degradation as the model predicts an increase in soil salinity by 5% over the same period. The results help farmers and policymakers to develop effective land management plans to enhance community readiness and resilience against vulnerabilities.

This study investigates the influence of hydrological and morphological characteristics on the in situ thermal conditions within floodplain wetlands of the Murshidabad district, West Bengal, India. Using multi-temporal Landsat imagery and geospatial analysis, the study quantified changes in wetland area, water depth, hydroperiod, and spatial structure from phase I to phase II, and examined their relationship with land surface temperature (LST) patterns. Results reveal a substantial decline in wetland extent over 58% reduction in both pre- and post-monsoon periods accompanied by increased fragmentation and loss of stable core habitats. Hydrological analysis indicates a marked shift toward ephemeral conditions, with a significant decrease in areas of high water presence frequency and persistent hydroperiods. Thermal analysis demonstrates a clear warming trend, with maximum LST increasing by up to 2.65 °C, and showing a weakening correlation between hydrological parameters and cooling effects over time. Geographically weighted regression further highlights the declining influence of wetland hydrology on local temperature regulation. These findings underscore the critical role of intact, hydrologically stable wetlands in mitigating thermal extremes and emphasize the urgent need for conservation and restoration strategies to sustain wetland ecosystem services and enhance climate resilience in floodplain regions.

Fine particulate matter (PM_2.5) poses a critical threat to air quality and public health in India, influenced by rapid urbanization, industrialization, and diverse meteorological conditions. This study examines the spatial, seasonal, and temporal variations of PM_2.5 across India from 1980 to 2020, using long-term emission inventories and atmospheric data. The Indo-Gangetic Plain consistently exhibits the highest PM_2.5 concentrations due to dense population, industrial activities, biomass burning, and agricultural practices, while central and eastern India show moderate levels, and southern and northeastern regions remain relatively clean. Seasonal analysis highlights peak pollution during winter and post-monsoon periods, driven by temperature inversions, low boundary layer heights, and crop residue burning, whereas monsoon rains reduce particulate concentrations. Over four decades, PM_2.5 levels have increased steadily, with residential, commercial, and agricultural waste-burning sectors contributing the majority of emissions. High PM_2.5 exposure correlates with elevated health risks, including respiratory diseases, premature mortality, and economic costs, particularly in densely populated northern regions. The study findings indicate that integrated mitigation strategies—such as emission control, promotion of clean energy, and improved transport and industrial policies, combined with regional air quality management—are essential to reduce PM_2.5-related impacts in India. These insights can help policymakers and stakeholders develop targeted interventions to protect human health and achieve sustainable air quality across the country.

Concern over agricultural nutrient contamination is rising in arid Central Asia where a shortage of freshwater resources under climate change exacerbates water supply problems. This study assesses how nutrient loading in the Zarafshan River Basin is affected by the application of nitrogen, phosphorus, and potassium (NPK) fertilizers. We evaluated fertilizer use and river nutrient concentrations using QSWAT hydrological modeling, GIS-based spatial analysis, and long-term water quality data. The model was calibrated and validated for discharge using SWAT-CUP on a monthly time step. The model results were evaluated using the R² and NSE statistical coefficients, which were 0.78 and 0.76 during the calibration period, and 0.75 and 0.73 during the validation period, respectively, which proved the model’s accuracy. While P and K correlations were weak and not statistically significant, N fertilizer application demonstrated a statistically significant, moderate positive correlation with TN_min (mineral total nitrogen) in river water (ρ = 0.30, p < 0.05). For nutrient export, 37.1% of the basin was in high-risk zones. Modeled monthly averages for the upstream and downstream nitrogen (NO₃) loads were 598 kg and 60,318 kg/month per subbasin, respectively. These results highlight nitrogen, in contrast to phosphorus and potassium, as one of the dominant contributors to non-point source pollution, demanding targeted nutrient management in agricultural zones.

This study provides the first assessment of microplastics (MPs) pollution in the commercially important bivalve Meretrix aurora across estuarine and coastal environments on the southeast coast of India, comparing the Punnakayal Estuary (Site 1) and the Tuticorin Coast (Site 2). MPs concentrations were assessed in bivalve tissues (n = 75 per site), surface water (n = 3), and intertidal sediments (n = 3). Bivalve tissues were digested with KOH, while water and sediment samples underwent oxidative digestion combined with NaCl density separation. Results showed higher MPs loads in M. aurora from the urbanized Tuticorin Coast (0.81 ± 0.16 items/individual) compared to the Punnakayal Estuary (0.44 ± 0.12 items/individual), even though Tuticorin displayed lower MPs levels in water and sediment. Fibres dominated the ingested particles (> 60%), and nearly 80% were < 1 mm. FTIR spectra revealed polyethylene (PE) and polyamide (PA) as the most common polymers, pointing to packaging and fishing activities as key sources. The elevated MPs abundance in edible bivalves highlights potential risks to coastal food webs and human consumers. Overall, these findings establish M. aurora as a reliable bioindicator of MPs contamination and emphasize the urgent need for improved waste management and comprehensive monitoring in Indian coastal waters.

Graphical abstract

Heavy metal pollution can alter animal behaviors in ways that can significantly reduce fitness. However, the direct influence of exposure to highly polluted environments on behavioral traits has rarely been studied in the field. Here, we investigated the effects on behavior of heavy metal accumulation by analyzing four primary heavy metals—Mercury (Hg), Copper (Cu), Zinc (Zn), and Cadmium (Cd)—extracted from feathers of six passerine bird species from a heavily polluted subtropical region in southwest China. We examined the correlations between these heavy metals’ concentrations and three behavioral traits assessed during handling: breath rate, distress calls, and handling aggression. We recorded contrasting patterns across species and elements so that negative effects of heavy metals were masked to some extent by divergent tendencies across taxa. Only a marginally significant negative correlation between Cd concentration and the number of distress calls at handling (p = 0.09) was apparent overall, although this was significant in 4 of 6 species (p < 0.03). Thus, our results suggest that in heavy metal-polluted areas, exposure to potentially toxic metals such as Cd and Pb, which often co-occur and show strong correlations, could reduce the anti-predator responses of birds, indicating that the behavioral effects of heavy metals may vary depending on both species and the combined influence of different elements. As altering aggressive defensive behaviors in either direction (too much or too little) could adversely affect bird fitness, more studies are needed to understand the species-specific patterns. This study provides a foundation for future research on behavioral responses to handling obtained non-destructively to assess heavy metal contamination in polluted regions.