Dental enamel as biomarker for environmental contaminants in relevant industrialized estuary areas in São Paulo,Brazil

Heavy metal contamination is a long-standing and very well-known public health problem, and its exposure can cause damage to several organs of human body, especially on the central nervous system of young children and teenagers. The aim of this article is to evaluate lead, cadmium, and manganese contamination in 125 children from 6 to 13 years old living in contaminated areas during the period from 2006 to 2009 (São Vicente, Cubatão Downtown, Bertioga and Cubatão Pilões/Água Fria). This estuary area is the most important example of environmental degradation by chemicals from industrial sources. This is a cross-sectional study through clinical examinations and dental enamel tests. All mothers from these children lived in the area since before the pregnancy. Lead, cadmium, and manganese levels (μg/g) were measured on dental enamel samples through graphite furnace atomic absorption spectrometry, searching for the occurrence of heavy metals. The mean lead concentrations were 139.48 μg/g in Cubatão Pilões/Água Fria, 170.45 μg/g in Cubatão Downtown, 213.52 μg/g in São Vicente, and 151.89 μg/g in Bertioga. The mean cadmium concentrations were 10.83 μg/g in Cubatão Pilões/Água Fria, 12.58 μg/g in Cubatão Downtown, 10.92 μg/g in São Vicente, and 14.57 μg/g in Bertioga. The mean manganese concentrations were 23.49 μg/g in Cubatão Pilões/Água Fria, 30.90 μg/g in Cubatão Downtown, 41.46 μg/g in São Vicente, and 42.00 μg/g in Bertioga. Dental surface enamel may be used as an efficient biomarker of past environmental exposure to lead, manganese, and cadmium which are associated to well-known sources of heavy metal contamination. The results suggest that the evaluated children were exposed to sources of lead, cadmium, and manganese since before their conceptions. Although Bertioga initially was chosen as a control area of this study, it was also was verified to have heavy metal contamination on examined children.     

Nitrogen fertility and abiotic stresses management in cotton crop: a review

This review outlines nitrogen (N) responses in crop production and potential management decisions to ameliorate abiotic stresses for better crop production. N is a primary constituent of the nucleotides and proteins that are essential for life. Production and application of N fertilizers consume huge amounts of energy, and excess is detrimental to the environment. Therefore, increasing plant N use efficiency (NUE) is important for the development of sustainable agriculture. NUE has a key role in crop yield and can be enhanced by controlling loss of fertilizers by application of humic acid and natural polymers (hydrogels), having high water-holding capacity which can improve plant performance under field conditions. Abiotic stresses such as waterlogging, drought, heat, and salinity are the major limitations for successful crop production. Therefore, integrated management approaches such as addition of aminoethoxyvinylglycine (AVG), the film antitranspirant (di-1-p-menthene and pinolene) nutrients, hydrogels, and phytohormones may provide novel approaches to improve plant tolerance against abiotic stress-induced damage. Moreover, for plant breeders and molecular biologists, it is a challenge to develop cotton cultivars that can tolerate plant abiotic stresses while having high potential NUE for the future.     

Proximate composition and mineral contents in the body wall of two species of sea cucumber from Oman Sea

The proximate composition and mineral contents of Stichopus horrens and Holothuria arenicola from Chabahar Bay were analyzed and investigated. During the present study, we aimed to demonstrate the nutritive value. The approximate percent composition of moisture, protein, fat, and ash were 92.8, 3.47, 0.4, and 3.33% in S. horrens and 93, 4.4, 0.6, and 2% in H. arenicola, respectively. Atomic absorption spectrophotometry of the ashes indicated the body wall of two species of sea cucumbers contained higher amounts of both macro minerals (92.5 mg/100 g Mg in S. horrens and 115 mg/100 g Mg in H. arenicola; 106.25 mg/100 g Ca in S. horrens and 83.25 mg/100 g Ca in H. arenicola) and trace elements (521.781 mg/100 g Fe in S. horrens; 60.354 mg/100 g Fe in H. arenicola, and 0.096 mg/100 g Zn in S. horrens; 0.04 mg/100 g Zn in H. arenicola). For both species, there were high content of protein and essential mineral. Also, they have low content of fat in the body wall of two species in the experiment.     

Physicochemical characteristics,mutagenicity and genotoxicity of airborne particles under industrial and rural influences in Northern Lebanon

In this work, the main objectives were to assess the mutagenic and genotoxic effects of fine particulate matter collected in an industrial influenced site in comparison with a non-industrial influenced one (rural site) and to relate the particulate matter (PM) composition to the observed genotoxic effects. At the industrial influenced site, higher concentrations of phosphates, trace metals, and polycyclic aromatic hydrocarbons (PAHs) in particles could be related to the contributions of quarries, fertilizer producer, cement plants, and tires burning. Gasoline and diesel combustion contributions were evidenced in particles collected at both sites. Particles collected under industrial influence showed a higher mutagenic potential on three tested strains of Salmonella typhimurium (TA98, YG1041, and TA102), and especially on the YG1041, compared to particles from the rural site. Furthermore, only particles collected in the vicinity of the industrial site showed a tendency to activate the SOS responses in Escherichia coli PQ37, which is indicative of DNA damage as a result of exposure of the bacteria cells to the action of mutagenic samples. The mutagenicity and genotoxicity of the industrial PM_2.5–0.3 particulates may be attributed to its composition especially in organic compounds. This study showed that proximity of industries can affect local PM composition as well as PM genotoxic and mutagenic potential.     

Hexabromocyclododecanes in soils and plants from a plastic waste treatment area in North China: occurrence,diastereomer- and enantiomer-specific profiles,and metabolization

Plastic waste is a source of organic contaminants such as hexabromocyclododecanes (HBCDs). HBCDs have been found to cause developmental and reproductive toxicity; it is important to investigate the occurrence and metabolization of HBCDs in the soil environments with plastic waste contamination. This work analyzed HBCDs and their metabolites in soil and plant samples collected from Xinle and Dingzhou—the major plastic waste recycling centers in North China. Results showed that total HBCD concentrations in soils followed the order: plastic waste treatment site (11.0–624 ng/g) > roadside (2.96–85.4 ng/g) ≥ farmland (8.69–55.5 ng/g). HBCDs were detected in all the plant samples with total concentrations ranging from 3.47 to 23.4 ng/g. γ-HBCD was the dominant congener in soils, while α-HBCD was preferentially accumulated in plants. Compositions of HBCD isomers in soils and plants were significantly different (P < 0.05) among sampling sites and among plant species. HBCDs in farmland soil and all plant samples exhibited high enantio-selectivity based on the enantiomeric fractions (EFs). Furthermore, metabolites of pentabromocyclododecenes (PBCDEs) were frequently identified in soils, and mono-OH-HBCDs were the most common ones in plants. This study for the first time provides evidences of HBCD contamination in the soil-plant system caused by plastic waste, their stereo-selectivity, and metabolization behavior, improving our understanding of the environmental behavior and fate of HBCDs.     

Distribution of polybrominated diphenyl ethers in breast milk,cord blood and placentas: a systematic review

Polybrominated diphenyl ethers (PBDEs) have been extensively used as flame retardants in consumer products. PBDEs rapidly bioaccumulate in the environment, food, wild animals and humans. In this review, we investigated the harmful effects of PBDEs on humans, especially in early life, and summarised the levels of PBDEs in human biological samples (breast milk, cord blood and placentas). In addition, we described the spatiotemporal distribution of PBDEs in this review. PBDE levels in breast milk, cord blood and placentas were generally higher in North America than in other regions, such as Asia, Europe, Oceania and Africa. However, high levels of PBDEs in human biological samples were detected at e-waste recycling sites in South China, East China and South Korea. This finding suggests that newborns living in e-waste regions are exposed to high levels of PBDEs during prenatal and postnatal periods. The time trends of PBDE concentration differed according to the region. Few studies have investigated PBDE levels in humans from 1967 to 2000, but they increased rapidly after 2000. PBDE concentration peaked at approximately 2006 globally. Compared with other PBDE congeners, BDE-47, BDE-153 and BDE-209 were the major components, but the detection rate of BDE-209 was lower than those of others. Future studies should focus on determining the BDE-209 concentration, which requires the implementation of different analytical approaches. Additionally, the levels of PBDEs in human samples and the environment should be monitored, especially in e-waste recycling regions.

Open image in new window

Graphical abstract The figures described the spatial distribution of the lowest (Fig. a1) and highest concentration of ∑PBDE (Fig. a2) in different countries by 2006 and described the spatial distribution of the lowest (Fig. b1) and highest concentration of ∑PBDE (Fig. b2) in different countries from 2007 to 2015. All the figures indicated that the levels of PBDEs in North America were substantially higher than those in many regions of Europe, Asia, Oceania, or Africa. Comparing Fig. a1–b1 or Fig. a2–b2, increasing trends were observed in some countries, especially in some regions in China, Korea and Canada.

     

Insights into the mercury(II) adsorption and binding mechanism onto several typical soils in China

To better understand the Hg(II) adsorption by some typical soils and explore the insights about the binding between Hg(II) and soils, a batch of adsorption and characteristic experiments was conducted. Results showed that Hg(II) adsorption was well fitted by the Langmuir and Freundlich. The maximum adsorption amount of cinnamon soil (2094.73 mg kg^?1) was nearly tenfold as much as that of saline soil (229.49 mg kg^?1). The specific adsorption of Hg(II) on four soil surface was confirmed by X-ray photoelectron spectroscopy (XPS) owing to the change of elemental bonding energy after adsorption. However, the specific adsorption is mainly derived from some substances in the soil. Fourier transform infrared spectroscopy (FTIR) demonstrated that multiple oxygen-containing functional groups (O–H, C=O, and C–O) were involved in the Hg(II) adsorption, and the content of oxygen functional groups determined the adsorption capacity of the soil. Meanwhile, scanning electron microscopy combined with X-ray energy dispersive spectrometer (SEM–EDS) more intuitive revealed the binding of mercury to organic matter, metal oxides, and clay minerals in the soil and fundamentally confirmed the results of XPS and FTIR to further elucidate adsorptive phenomena. The complexation with oxygen-containing functional groups and the precipitation with minerals were likely the primary mechanisms for Hg(II) adsorption on several typical soils. This study is critical in understanding the transportation of Hg(II) in different soils and discovering potential preventative measures.     

Heavy metal pollution in sediments of the largest reservoir (Three Gorges Reservoir) in China: a review

The Three Gorges Dam in China is the world’s largest dam. Upon its completion in 2003, the Three Gorges Reservoir (TGR) became the largest reservoir in China and plays an important role in economic development and national drinking water safety. However, as a sink and source of heavy metals, there is a lack of continuous and comparative data on heavy metal pollution in sediments. This study reviewed all available literatures published on heavy metals in TGR sediments and further provided a comprehensive assessment of the pollution tendency of these heavy metals. The results showed that heavy metal concentrations in TGR sediments varied spatially and temporally. Temporal variations indicated that Hg in tributaries, as well as As, Cd, Cr, Cu, Ni, Pb, and Zn in the mainstream, exhibited a higher probability to exceed background values after the impoundment of TGR. Pollution assessments by contamination factor, geoaccumulation index, and potential ecological risk were similar. High Cd and Hg concentrations in both the mainstream and tributaries are a cause for much concern. However, sediment quality guidelines produced different results, as most previous studies adopted different sampling and measurement strategies. The data inconsistencies and lack of continuity regarding the reservoir confirm the need for a continuous monitoring network and the development of quality criteria relevant to the sediments of the TGR in the future.     

Development of the hybrid cells in series model to simulate ammonia nutrient pollutant transport along the Umgeni River

Discharge of organic waste results in high nutrient pollution of the water bodies which is a major menace to the environment. A high quantity of nutrients such as ammonia causes a reduction in the dissolved oxygen level and induces algal growth in the water bodies. Water quality models have been the tools to evaluate the rate at which streams can disperse the pollutants they receive. Many water quality models are flawed either because of their inadequacy to completely simulate the advection component of the pollutant transport, or because of the limited application of the models, due to inaccurate estimation of model parameters. The hybrid cell in series (HCIS) developed by Ghosh et al. (2004) has been able to overcome such difficulties associated with the mixing cell-based models. Thus, the current study focuses on developing an analytical solution for the pollutant transport of the ammonia concentration through the plug flow, the first and second well-mixed cells of the HCIS model. The HCIS model coupled with the first order kinetic equation for ammonia nutrient was developed to simulate the ammonia pollutant concentration in the water column. The ammonia concentration at various points along the river system was assessed by considering the effects of the transformation of ammonia to nitrite, the uptake of ammonia by the algae, the respiration rate of the algae and the input of benthic source to the ammonia concentration in the water column. The proposed model was tested using synthetic data, and the HCIS-NH₃ model simulations for spatial and temporal variation of ammonia pollutant transport were analysed. The simulated results of the HCIS-NH₃ model agreed with the Fickian-based advection-dispersion equation (ADE) for simulating ammonia concentration solved using an explicit finite difference scheme. The HCIS-NH₃ model also showed a good agreement with the observed data from the Umgeni River, except during rainy periods.     

Model and algorithm for bi-fuel vehicle routing problem to reduce GHG emissions

Because of the harmful effects of greenhouse gas (GHG) emitted by petroleum-based fuels, the adoption of alternative green fuels such as biodiesel and compressed natural gas (CNG) is an inevitable trend in the transportation sector. However, the transition to alternative fuel vehicle (AFV) fleets is not easy and, particularly at the beginning of the transition period, drivers may be forced to travel long distances to reach alternative fueling stations (AFSs). In this paper, the utilization of bi-fuel vehicles is proposed as an operational approach. We present a mathematical model to address vehicle routing problem (VRP) with bi-fuel vehicles and show that the utilization of bi-fuel vehicles can lead to a significant reduction in GHG emissions. Moreover, a simulated annealing algorithm is adopted to solve large instances of this problem. The performance of the proposed algorithm is evaluated on some random instances.