Environmental Monitoring and Assessment最新文献

The interconnected disturbances induced by coal mining activities significantly alter the groundwater flow system, triggering multi-scale hydrodynamic–hydrochemical co-evolution processes. Based on hydrochemistry, deuterium and oxygen-18 isotopes, Pearson correlation analysis, and Bayesian mixture model methods, this study systematically evaluated the evolution of the groundwater flow system and the hydrochemical processes driven by coal mining in the Nalinhe mining area in the northern Ordos Basin, China. The results showed that the main ions in the groundwater of Quaternary and Cretaceous aquifers are Ca²⁺, Na⁺, HCO₃⁻, and SO₄²⁻, while the main ions in the Jurassic aquifer are SO₄²⁻ and Na⁺. The hydrochemical types vary with depth, transitioning from HCO₃⁻-Ca²⁺ in the Quaternary to HCO₃⁻-Na⁺·Ca²⁺ in the Cretaceous, and finally changing to SO₄²⁻-Na⁺ in the Jurassic. The variance explained by ion composition (52.07%) strongly correlates with rock weathering processes. The Cretaceous aquifer is the primary source of water inflow into mining areas, accounting for 64.25%, while the Quaternary and Jurassic aquifers contribute 18.32% and 17.43%, respectively. In this study, the hydrogeochemical evolution method and Bayesian mixing model were combined to reveal the impact of coal mining activities on groundwater circulation patterns. These findings provide valuable insights for constructing groundwater flow models and effectively managing groundwater inflow in mining regions.

Graphical Abstract

Low-cost particulate matter (PM) sensors are increasingly used for personal and environmental air quality monitoring due to their affordability and accessibility. Recent advancements make these sensors suitable for occupational settings, but their accuracy in such settings remains uncertain. This study calibrated the AirBeam 2 and AirBeam 3 against the Thermo Scientific Personal DataRAM PDR-1500 to assess their efficacy at measuring high PM concentrations, such as those in occupational exposure settings, using engine exhaust and biomass smoke as PM sources. Laboratory calibrations were conducted using a sealed chamber. Linear and polynomial regressions assessed agreement with the PDR-1500, while breakpoint analyses identified thresholds where sensor performance shifted. Field calibrations using the AirBeam 2s evaluated real-world performance and user preferences. The AirBeam 2 exhibited a novel issue where PM₁ readings exceeded PM₂.₅ at concentrations > 50 µg/m³, which was corrected through reprogramming. Polynomial models outperformed linear ones for both devices and the AirBeam 3 performed better with engine exhaust than biomass smoke (linear calibration coefficients 0.192 vs 0.102, respectively), while the AirBeam 2 performed better with biomass smoke than engine exhaust (coefficients 0.323 vs 0.274, respectively). Breakpoints suggested the AirBeam 2s may be better for high concentrations, while the AirBeam 3s were more sensitive at lower concentrations. In the field, the AirBeam 2s recorded lower mean PM concentrations than the PDR-1500 and were more influenced by environmental conditions, yet participants (n = 9) who were recruited to perform field calibrations with both devices preferred the AirBeam. While sensor performance can vary by PM source, concentration, and environmental factors, these findings suggest AirBeams can be a useful option for preliminary occupational exposure assessments after careful calibration and validation prior to use.

Among the many known polycyclic aromatic hydrocarbons (PAHs), anthracene and pyrene are ubiquitously found in our global environment. PAHs are known to have persistent and present harmful health effects. However, their determination and precise quantification are tedious and require expensive and sophisticated methodologies such as GC–MS, HPLC, or mass spectrometry. The study presented here reports a simple and reproducible method which was developed and validated for the detection and quantification of the representative PAHs anthracene and pyrene in n-hexane solutions. In addition, anthracene and pyrene were extracted and quantified using experimental water standards of aqueous anthracene and pyrene and road dust samples from Jashore, Bangladesh, using the developed methodology. The results of this study validated the linearity, accuracy, precision, ruggedness, repeatability, and recoveries following ICH guidelines. The limits of detection (LOD) for anthracene and pyrene were 0.018 mg/L and 0.010 mg/L, respectively, with corresponding limits of quantification (LOQ) of 0.089 mg/L for anthracene and 0.020 mg/L for pyrene. The extraction data revealed that ~ 97.8% and 86.1% of the anthracene and pyrene were extracted from control aqueous samples. The experimental dust sample concentrations ranged from 14.0 to 98.0 mg/kg for anthracene and from 5.0 to 20.0 mg/kg for pyrene based on different sampling locations. The fluorescence intensities of anthracene and pyrene were used for their detection in different aqueous concentrations. The intensity decreases at elevated water to n-hexane fractions, indicating that at the higher water fractions, quenching occurs for both PAHs. Although it is not possible to estimate these two PAHs at very low concentrations, this developed method is nevertheless suitable for rapid detection and measurement of anthracene and pyrene in unknown samples.

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.