Environmental Monitoring and Assessment最新文献

Anthropogenic particles (AP) were assessed at 12 coastal sites in Nuevo Gulf (NG), Patagonia, Argentina, a semi-enclosed basin subject to significant human pressure. The highest average concentration of AP in coastal seawater was recorded in the Puerto Madryn (PMY) area (6.6 AP L⁻¹), nearly double that observed at the remaining nine sites farther from the urban center (3.2 AP L⁻¹). Conversely, high average concentrations of AP in intertidal sediments were widely distributed across the gulf (overall average 87.8 AP kg⁻¹ dw). The physical and chemical properties of AP were similar between matrices. Fibers were the most common shape, predominantly blue, followed by transparent and black, with an average length of 783.4 μm. The dominant polymer types were polyethylene terephthalate, signature dye only, and anthropogenic cellulose. Puerto Madryn appears to be the primary source of AP pollution in NG, likely from textile and maritime activities. The results suggest that high-frequency wind variability disperses AP in multiple directions despite the predominant surface cyclonic gyre.

This study examined nutrient and pollutant accumulation in edible crops grown on a solid waste dumpsite in Mbale, Uganda, to highlight the nutritional benefits and toxicological risks from this food production. Previously, the dumpsite was categorized into three sampling zones based on topography, waste type, human activity, and other environmental conditions. A total of 31 crop types were sampled, yielding 192 edible plant parts, which were then analyzed for 20 essential and non-essential elements. Leafy vegetables, root tubers, fruits, cereals, seeds, and lemongrass exhibited high levels of essential macronutrients and crucial micronutrients, in addition to toxic elements. The concentrations of aluminum (Al), nickel (Ni), chromium (Cr), lead (Pb), mercury (Hg), and certain nutrients exceeded the allowable consumption limits as per the FAO and WHO guidelines, in Table 2. Crops significantly, contained either: (i) high concentrations of potassium (K), calcium (Ca), magnesium (Mg), and phosphorus (P), (ii) high K levels, (iii) increased sodium (Na) content, (iv) mainly Al and iron (Fe) or (v) an average concentration of manganese (Mn), copper (Cu), barium (Ba), and zinc (Zn). The accumulation varied based on crop species, plant parts, sample site location, and site-specific conditions, with leafy crops exhibiting between 50 and 75% higher elemental content compared to other types or parts. Significant differences were observed in Cr, Zn, and Ba concentrations across the three zones, with higher Cr found at the dump centre, Zn at the slope, and Ba at the riverbank. Regardless, consumers of Mbale dumpsite crops are exposed to both beneficial and toxic elements. These findings should be simplified into local languages and shared through educational materials and community outreach. This will raise public awareness, promote safer agricultural practices, and guide policy interventions to protect food safety and public health in communities that rely on crops grown on waste dumpsites.

Chemical sensors have become essential tools for real-time detection of hazardous substances in complex environmental systems. This review synthesizes recent advances in sensor technologies, focusing on innovations in materials, architectures, and integrated platforms for detecting pollutants such as heavy metals, volatile organic compounds (VOCs), pesticides, and chemical warfare agents. Emerging sensor designs, ranging from electrochemical and optical systems to photonic crystal fibers, have achieved significant improvements in sensitivity, selectivity, and portability. The incorporation of advanced materials, including metal–organic frameworks (MOFs), carbon-based nanomaterials, and molecularly imprinted polymers, has expanded sensing capabilities across air, water, and soil. Applications increasingly rely on smart, networked systems powered by wireless communication, artificial intelligence, and Internet of Things (IoT) frameworks to enable autonomous, scalable environmental monitoring. Despite these advances, critical challenges remain in sensor stability, cross-sensitivity, reproducibility, environmental robustness, data interpretation, calibration, and large-scale deployment. Addressing these limitations is essential for realizing the full potential of chemical sensors in environmental governance, public health protection, and rapid hazard response.

This study focuses on the effects of metal pollution, particularly cadmium (Cd) and lead (Pb), on schoolchildren in Gabes region in Tunisia as a case study, which is affected by industrial phosphate transformation pollution since 1976. The objective was to assess the biological impact of metal exposure on children by evaluating levels of these metals in biological matrices between exposed and control groups. The blood and urine samples were analyzed for Cd and Pb using an atomic absorption spectrometer. The results showed significantly higher blood and urinary Cd and blood-Pb levels in children from the exposed area compared to those from the control region (p < 0.001). Interestingly, heavy metals were under admissible limits in agricultural product samples of exposed areas, suggesting that the essential contamination source is atmospheric, not food related. The study also examined hematological markers, revealing a significant reduction in red blood cells, hemoglobin, hematocrit, mean corpuscular hemoglobin concentration, and neutrophils in exposed children compared to controls (p < 0.05). In contrast, monocyte levels were significantly higher in exposed children (p < 0.001). Despite these changes, the average biological parameters in the exposed group fell within normal ranges. This emphasizes the role of heavy metals atmospheric exposure like cadmium and lead as a primary risk factor.

Coal-fired power plants generate coal combustion residuals (CCRs), which are typically disposed of in landfills and surface impoundments that must be monitored to ensure that hazardous constituents such as arsenic (As) and selenium (Se) do not escape into the surrounding environment. Traditional methods for monitoring surface impoundments, such as sampling discharge of all outlets of hydraulic structures to approximate CCR concentrations, are highly resource-intensive and largely manual, posing a significant cost challenge for the stakeholders responsible for them. The use of grass species as bioindicators may offer a more efficient and sustainable method for long-term monitoring of CCR impoundments. In this study, we sought to determine whether three species of grass could serve as effective bioindicators for detecting changes in As and Se soil contamination profiles and provide an evaluation of three technologies used for evaluating plant health. Lolium perenne, Panicum virgatum, and Paspalum notatum were treated with As or Se and monitored with a spectroradiometer and multispectral camera to detect a spectral response to the chemical stress. Metal transfer analysis revealed that there was a significant change in metal concentrations in plant tissue across the grass species and different treatments, with Paspalum virgatum providing the best dose response after a week of Se treatment. Lolium perenne provided a response past the Se toxicity threshold of 5 mg/kg. We then expanded this study to a field scale to determine if our results would translate to an environmentally relevant scale. Unmanned aerial vehicle (UAV) results suggested Lolium perenne was efficient in determining whether CCR was present in soils but lacked sensitivity to differentiate between low and high loadings. Monthly sampling also revealed that metal concentration in plant tissue decreased as plants underwent senescence. Data collected with the UAV proved to be the most proficient method of determining a dose response.

This study aimed to conduct the first integrated ecological assessment of the tropical Kullursandai Reservoir, India, by evaluating the interrelationships between water quality, fish diversity, invasive species, and fishery productivity. Over a 24-month period, we monitored key physico-chemical parameters, conducted comprehensive fish sampling, and analyzed historical catch data. Multivariate statistics, including principal component analysis (PCA), were used to identify dominant environmental drivers. Results revealed distinct seasonal patterns in water quality, with the reservoir maintaining a mesotrophic status. The fish assemblage was dominated by invasive Tilapia (Oreochromis spp.), which collectively constituted nearly half of the total catch, indicating a significant shift in community structure and potential ecological risks. Despite this, fish diversity indices indicated a moderately diverse and structured community. A notable finding was the substantial discrepancy between the theoretical maximum sustainable yield (8.33–12.82 kg/ha/yr) and the actual fishery yield (mean 153 kg/ha/yr), highlighting the role of adaptive management and favorable hydrology. PCA identified three key environmental gradients regulating the ecosystem: mineral-alkalinity, transparency-oxygen, and nutrient enrichment, with phosphorus levels strongly linked to tilapia dominance. Collectively, these results demonstrate that this study provides critical thresholds for guiding nutrient monitoring, invasive species control, and sustainable harvest strategies in tropical reservoirs, underscoring the delicate trade-off between high fishery production and biodiversity conservation.

The spatial structure of aquatic communities is shaped by both environmental filtering and dispersal limitation. In watershed ecosystems, species may disperse through overland and watercourse pathways, and their dispersal abilities can influence their reliance on these pathways. In this study, we examined environmental factors, algae, macroinvertebrates, and zooplankton in a near-natural mountainous watershed. Distance-decay relationships (DDR) and linear regressions (LR) were used to evaluate communities’ similarity with geographic distance and to assess dispersal limitation. Variation partitioning analysis (VPA) quantified the relative contributions of overland and watercourse pathways and examined how macroinvertebrate dispersal ability affects dependence on these pathways. The results indicate that all three aquatic communities experienced significant dispersal limitation, which explained more variation in community structure than environmental filtering. Watercourse pathways accounted for communities’ structure more effectively than overland pathways, while macroinvertebrates with higher dispersal abilities showed lower reliance on watercourse pathways. These findings provide a scientific basis for watershed ecological management and underscore the importance of considering multiple dispersal pathways in studies of community assembly.

Volatile organic compounds (VOCs) are major atmospheric pollutants commonly derived from the fossil fuel combustion. The concentration of VOCs in the atmosphere and its dynamics have widely been used to evaluate their source, formation processes, residence time, and photochemical reactions involved in the atmosphere. However, little is known about the effect of UV degradation of VOCs during their transport from the source to the study area, which always reduces accuracy in the understanding of VOCs’ characteristics in the atmosphere. In the present study, we investigated the fractionation of carbon isotopes (¹³C/¹²C) of toluene (methyl benzene) during UV degradation (254 nm UV-C), a common VOC, in the atmosphere. The observed fractionation (α = 0.9935) confirms that UV-C photodegradation enriches ¹³C in residual toluene, but applying this result to quantify sources or degradation in the atmosphere requires further constraints and assumptions. This correlation thus can be useful for the quantitative illustration of the environmental behavior of toluene (e.g., excretion sources, transfer, UV degradation, deposition) in the atmosphere and biosphere.

CDOM, an important ocean colour product, accounts for 90% of non-water UV absorption in the upper ocean. CDOM absorption triggers photochemical reactions resulting in the release of greenhouse gases and alters microbial bioavailability of organic matter. The three different approaches for retrieving a_dg(λ) from satellite data were validated using a_CDOM(λ) generated from OC-CCI-derived remote sensing reflectance (R_rs) and in situ measured a_CDOM(λ). The multiple linear regression (MLR) model performed better than the two exponential decay models in quantifying CDOM in the UV region. The better performance of R_rs-based algorithms indicated that absorption-based algorithms need considerable improvement when compared to algorithms based on the combined absorption by detrital matter and CDOM (a_dg(λ)). As a result, the absorption-based algorithm was modified as the ASCDOM algorithm, which demonstrated improved retrieval at 275, 355, 38 and 412 nm for a_CDOM(λ). The ASCDOM algorithm’s strong statistical performance highlights its accuracy in retrieving satellite products for water quality evaluations and ocean colour monitoring.

5G is currently under development in Greece, with operators adopting different strategies and rollout schedules. Meanwhile, 4G has reached a highly mature stage, supporting the initial deployment of 5G through NSA (Non-Standalone) architecture. Cellular service is provided by a combination of systems: the legacy 2G system operational mainly in rural areas, the advanced 4G, and the emerging 5G systems, 3G was phased out in 2023. This transitional phase renders the cellular landscape both dynamic and region-specific. Recurrent, large-scale measurement campaigns are essential to effectively track networks development. This study presents findings from a year-long EMF measurement campaign (July 2023-June 2024) in the Peloponnese Region of Greece. Using frequency-selective equipment, the campaign combined spatially distributed short-term ground measurements with long-term monitoring at fixed locations. Data was analyzed by service type (e.g. cellular, WiFi), cellular system (2G/3G/4G/5G), and network operator. All measured electric field values remained well below the stringent Greek safety limits; the highest ground-level measurement was approximately 18 times lower than the limit. The 900 MHz band was identified as the dominant contributor to EMF exposure, followed by the 1800 MHz band used by 4G and 2G networks. 4G contributed the most (53%), while 5G impact was only 3%, reflecting its early stage of deployment in the region. Long-term monitoring revealed peak exposure between 15:00 and 21:00, coinciding with increased network usage. The findings provide reassurance regarding public safety, highlight the value of combining spatial and temporal analysis, and offer baseline data for future studies as 5G networks continue to expand.