Natural colors particularly animal-based colorants are employed in the field of cosmetics, food, and flavors and also gaining popularity in textiles, due to their soothing nature. In this study, the microwave-assisted extraction of colorant from cochineal insects for dyeing of bio-mordanted silk has been carried out. Acidic, methanolic, and acidified methanol solubilized media were used to extract the natural colorant from cochineal under microwave irradiation for 1–6 min. Bio-mordants have been employed at optimized conditions to make the process greener and sustainable. It is found that acid solubilized extract of pH 4, employed at 55 °C for 55 min containing 5 g/100 mL of Glauber’s salt as exhausting agent has given high color strength onto microwave-treated silk fabric. Suggested ISO standards for colorfastness have revealed that bio-mordants have given excellent color depth and excellent rating of fastness properties, compared with chemical mordants used. It is found that microwave treatment has not only improved the dyeing behavior of colorant extracted from cochineal in acid solubilized medium but also enhanced the color characteristics onto bio-mordanted silk fabric.

The organophosphate pesticide chlorpyrifos (CPF) is defined as a priority pollutant in surface freshwaters according to Directive 2013/39/EU of the European Parliament. The focus of this study was to assess the potential cytotoxic and genotoxic effects of permissible CPF levels on juvenile forms of the common carp. We found that low-level CPF exposure did not induce elevated levels of micronuclei, but significantly increased the frequency of total nuclear abnormalities (NAs) proportional to dose and time; notched, blebbed, lobed and eight-shaped nuclei, nuclear buds, nuclear bridges and binucleated cells were all detected. Decreased frequencies of polychromatic erythrocytes (PCEs) and DNA damage detected by comet assay were also observed, confirming the cytotoxic and genotoxic effects of CPF. Altogether, these data (1) demonstrate that CPF is toxic even at permissible levels, possessing considerable genotoxic and cytotoxic potential in peripheral erythrocytes of exposed fish and (2) validate the assessment of NAs, PCEs and comet assay performance as sensitive biomarkers for the early detection of CPF pollution. These findings can be applied to guide environmental risk assessment and biomonitoring programs.

In this work, activated carbon-supported copper(II) oxide (CuO/AC) was prepared and used to degrade heavy oil refinery wastewater (HORW) by catalytic ozonation with the aim to develop low-cost and high-efficient supported-catalysts for degrading real recalcitrant industrial wastewater. Supported-catalyst CuO/AC was characterized by X-ray diffraction (XRD), N₂-physisorption, scanning electronic microscope (SEM), transmission electron microscope (TEM), and X-ray fluorescence (XRF). The degradation was mainly evaluated by chemical oxygen demand (COD), total organic carbon (TOC), 5-day biochemical oxygen demand (BOD₅), biodegradability and toxicity. Compared with unsupported-catalyst CuO or the mixed system of activated-AC and unsupported-catalyst CuO, supported-catalyst CuO/AC with reduced cost exhibited significantly enhanced activity for degrading HORW (5.0 g CuO-5%/AC, 90 mg/L O₃, and 7.3 pH). TEM analysis showed that the high activity of supported-catalyst CuO-5%/AC might be ascribed to the fact that CuO particles were small and highly dispersed on AC. Mass spectrum spectrometry (MS) analysis revealed that the organic components in HORW were first degraded to small molecule oxidation products, which were then oxidized or mineralized further. The influence of CuO loading, CuO/AC dose, ozone dose and initial pH on the degradation efficiency was also investigated. The results of the present work showed that CuO/AC could be a promising supported-catalyst for catalyzing ozonation degradation of HORW.

The emission of particulate matter from ships does great harm to human health and atmospheric environment. Sulfur emission regulations also affect particulate matter emissions due to fuel change. Particulate matter (PM) emitted from low-speed, two-stroke, large-power diesel engine were studied in test-bed experiments. Experiments were conducted at 25%, 50%, 75%, and 100% load with heavy fuel oil (HFO, 3.36%m/m S) and a lighter marine diesel oil (MDO, 0.1%m/m S). The experiments revealed that using MDO could decrease the mass emission factors (EFs) of PM compared to HFO due to the fuel quality and content; however, there was no obvious difference for the number EFs of PM. The main particle when using HFO consists sulfates and bound water, and the hydrate sulfur increased with the increased engine loads. Then, another 21% is organic carbon (OC). Emission factors for inorganic elements were also studied in particles from combustion of HFO and MDO. The EFs of OC and elemental carbon (EC) were affected by engine loads, fuel type, fuel sulfur content (FSC), and combustion conditions. The size distribution of OC was similar to EC, and there were two clearly peaks for every particulate matter sample. The key effect factor for EFs of PM with marine fossil fuels was FSC.

Through a facile impregnation–precipitation strategy, chitosan was dispersed on bentonite to prepare an organic/inorganic hybrid composite for Pb²⁺ adsorption. The strong promotion effect of a small amount of highly dispersed chitosan on the Pb²⁺ adsorption capacity of clay minerals was unveiled. With a chitosan loading of 0.4 wt%, the experimental adsorption capacity reached 261.3 mg/g. The good dispersion of chitosan played a crucial role in the high capacity. The large proportion of mesopores in the adsorbent facilitated mass transfer, and thereby adsorption equilibrium states could be achieved within 15 s. The adsorption isotherms were consistent with the Freundlich expression. The Pb²⁺ adsorption capacity was suppressed with the addition of 150 ppm Ca²⁺ and almost eliminated in the presence of 150 ppm Mg²⁺. The adsorption enthalpy change was measured to be − 28.6 kJ/mol and Gibbs free energy change was in the range of − 18.4 to − 16.7 kJ/mol, indicating that this adsorption process was exothermic and spontaneous. The FTIR and XPS results demonstrated that the amino groups on chitosan could bond with Pb²⁺, and contributed to the high adsorption capacity. DFT calculation results showed that the amino and hydroxyl groups in adjacent chitosan units could be tri-coordinated with Pb²⁺, and the energy of system was greatly decreased due to the coordination interaction.

Current research was performed to explore the hepatoprotective potential of Moringa oleifera leaves extract on lead acetate–induced hepatic injury. Twenty-four male Wistar rats were divided equally into 4 groups. The first group was control, while the second, third, and fourth groups were given 200 mg/kg aqueous Moringa extract only, 100 mg/kg lead only, and 100 mg/kg lead plus 200 mg/kg aqueous Moringa leaves extract, respectively, via oral gavage for 4 weeks. Weight gain and feed efficiency ratio were recorded. Serum lipid profiles, liver enzyme activities, and proteins beside hepatic superoxide dismutase activity, reduced glutathione, tumor necrosis factor alpha (TNF-α), and deoxyribonucleic acid fragmentation were assessed. Liver histopathological examination and nuclear factor kappa B (NF-kB) immunohistochemistry were performed. Administration of lead lowered (P < 0.05) weight gain, feed efficiency ratio, and perturbed lipid profile than control. Lead increased liver enzyme activities and TNF-α, while reduced serum proteins and hepatic antioxidant markers compared to control. Lead aggravated hepatic DNA fragmentation beside the presence of histopathological lesions. Co-administration of aqueous Moringa extract with lead significantly alleviated lead-induced adverse effects. The administration of aqueous Moringa extract with its antioxidant significantly restored the lead perturbations through reduction of oxidative stress–induced DNA damage via amelioration of NF-kB and TNF-α which kept hepatocyte integrity and reduced serum hepatic enzyme activities.

Most coal mines in China are opting for deep mining due to the rapid reduction of shallow coal reserves, which increases the risk of water-inrush accidents. Given the limitation of water-inrush coefficient method in evaluating the risk of water inrush from the coal seam floor, we analyzed the permeability resistance of the floor under different lithology combinations, and structural conditions of the lower group coal in Yanzhou mining area, based on the in situ pressure permeability test data. Our comprehensive analysis of the influencing factors of water inrush from the coal seam floor reveals key indices for evaluating the water inrush from the coal seam floor and also recommend values for average water-resistance strength of the different lithology, and structure of the lower coal seam floor of Xinglongzhuang coal mine. Besides, we establish a model based on the water-resistance conditions, and two adjacent lower coal working faces minefields of Xinglongzhuang coal mine in Yanzhou are used for the evaluation. Comparative analysis of water-inrush coefficient method and impermeability resistance condition to evaluate the applicability of safety conditions of coal mining under pressure are also performed. Our results show that the impermeability strength is a better measurement for the water-resistance capacity of the floor. These findings may guide the prevention and control of water disasters in coal mining under pressure in the lower formation of the minefield.

PM₂.₅ pollution has emerged as a global human health risk. The best measure of its impact is a population’s PM₂.₅ exposure (PPM₂.₅E), an index that simultaneously considers PM₂.₅ concentrations and population spatial density. The spatiotemporal variation of PPM₂.₅E over the Beijing-Tianjin-Hebei (BTH) region, which is the national capital region of China, was investigated using a Bayesian space-time model, and the influence patterns of the anthropic and geographical factors were identified using the GeoDetector model and Pearson correlation analysis. The spatial pattern of PPM₂.₅E maintained a stable structure over the BTH region’s distinct terrain, which has been described as “high in the northwest, low in the southeast”. The spatial difference of PPM₂.₅E intensified annually. An overall increase of 6.192 (95% CI 6.186, 6.203) ×10³ μg/m³ ∙ persons/km² per year occurred over the BTH region from 1998 to 2017. The evolution of PPM₂.₅E in the region can be described as “high value, high increase” and “low value, low increase”, since human activities related to gross domestic product (GDP) and energy consumption (EC) were the main factors in its occurrence. GDP had the strongest explanatory power of 76% (P < 0.01), followed by EC and elevation (EL), which accounted for 61% (P < 0.01) and 40% (P < 0.01), respectively. There were four factors, proportion of secondary industry (PSI), normalized differential vegetation index (NDVI), relief amplitude (RA), and EL, associated negatively with PPM₂.₅E and four factors, GDP, EC, annual precipitation (AP), and annual average temperature (AAT), associated positively with PPM₂.₅E. Remarkably, the interaction of GDP and NDVI, which was 90%, had the greatest explanatory power for PPM₂.₅E ′ s diffusion and impact on the BTH region.

In statistics, the identification of environmental criticalities, one of the primary goals of environmental monitoring and management, translates into the detection of spatial outliers. Detected in relation to purposely defined sets of indicators, both global and local outliers are pivotal in the identification not only of the severity and spread of criticalities, but also of their nature and causes. The present research exemplifies a procedural framework to identify environmental criticalities, using two different approaches for the detection of spatial outliers in river ecosystems related to several sets of parameters (organic C, inorganic C, Ca, Co, Cr, Fe, K, Mg, Mn, N, Na, P, S, Si, V, Zn, Cl⁻, F⁻, NO₃⁻, SO₄²⁻, chlorophyll a, chlorophyll b, pheophytin a, pheophytin b, total carotenoids, pH, and electrical conductivity), including emerging contaminants. To this end, indicator sets diagnostic for specific criticalities, derived from an empirical dataset of water quality parameters, were employed, using detection techniques based on geographically weighted principal component analysis and a modified pairwise Mahalanobis distance–based algorithm. Clear and accurate criticality scenarios were derived, highlighting both the strengths and the limitations of the proposed approach, especially in relation to the classic threshold-based methods.

Evidence suggesting the association between the atmospheric particulate matter (PM) and health problems stress the need for the establishment of policies and actions aiming the improvement of air quality. As a start point, the knowledge of the main PM contributors is fundamental. Receptor models are frequently used for the identification and apportionment of local sources, nevertheless, some features of these models must be considered. For instance, whether the region has sources with similar chemical profiles and/or whether there is source temporal or spatial similarity, which can generate collinearity, affecting the sensibility of the models. In this work, it is presented some study of cases showing some strengths of the chemical mass balance model (CMB), such as to infer specific sources acting over specific locations in a same region, and its weaknesses for separating collinear sources. Besides, this work shows some study of cases reporting that the identification of specific PM markers (organic, inorganic, and crystallographic) and determined in the receptor samples can lead to better sources separation and improvements in the interpretation of the results using positive matrix factorization model. This work also highlights for the importance of the information provided by receptor models, in which should be carefully considered by the environmental agencies for decision-making concerning air quality management.