Journal of Environmental Health Science and Engineering最新文献

Abstract

The final and most crucial step in obtaining clean water is disinfection. More innovative methods of water disinfection have recently been sought. Water disinfection is a promising application for nanoparticles as disinfectants. As a contribution to the literature, biofilm and metal-containing nanoparticles as antiadhesion inhibitors were used in conjunction with ultrasound in this study. The microbroth dilution test was used to reveal the microbiological antibacterial activities of different concentrations of AgNO3 and CuCl2 containing nanoparticles against the Escherichia coli ATCC 25,922 strain, which is an indicator bacterium in water systems. Antibiofilm activities were then investigated using biofilm attachment and biofilm inhibition tests. The inhibitory effect of nanoparticle ultrasonic waves on biofilm contamination was determined using a novel approach. Human keratinocyte cells (HaCaT cell line) were used in cell culture studies after water disinfection, and their cytotoxic effects were demonstrated using the MTT assay. The findings suggest that the nanoparticles utilized might be a viable choice for water disinfection applications. Furthermore, employing ultrasound at low doses with nanoparticles resulted in greater results. One feasible option is to employ nanoparticles to cleanse water without producing cytotoxicity.

In this work, the amount and physical and chemical characteristics of airborne microplastics (MPs) pollution in dust samples in Sistan, located in the eastern part of Iran, is reported. Sampling stations were selected according to the wind direction and population density. MPs were collected by a static dust sampler and analyzed by optical microscopy and FT-IR spectroscopy. Results showed that the distribution frequency of MPs in residential and non-residential areas was 6 to 11 pieces per 100 g (pcs/100 g) with an average abundance of 9.8 pcs/100 g. Fragmented MPs were approximately consisted 64% of total MPs and their sizes were in the range of 0.9–3.8 mm. Polyethylene (49%), polystyrene (21%) and polyester (18%) were the main MPs presented in the dust samples. It was observed that population density and wind direction were the most important parameters affecting MPs pollution in dust.

Introduction

The amount of fibers in the lungs is considered to reflect the cumulative intensity of past asbestos exposure, and bronchoalveolar lavage (BAL) has been proposed to be a good indicator of the presence and quantity of asbestos particles in the lungs. This study evaluated the asbestos concentration in BAL fluids of asbestos-exposed and unexposed pulmonary patients and the environment of Ahvaz city.

Methods

This prospective study was conducted on 80 patients underwent diagnostic fiberoptic bronchoscopy referred to Imam Khomeini Hospital in Ahvaz, Iran, in 2019. Patients with Lung diseases were divided into three groups based on CT scan results: normal (n = 32), lung cancer (n = 40) and Interstitial lung disease (n = 8). The analysis of asbestos fiber concentration in BAL fluid was carried out by Scanning Electron Microscope (SEM).

Results

The positive asbestos test was detected in 69% of all subjects, including 64% of whom had asbestos-related jobs and 74.5% of those with non-related jobs (p = 0.240). The concentrations of asbestos fiber in the BAL in normal patients, lung cancer and interstitial fibrosis (ILD) were 8.13 ± 5.38, 9.66 ± 7.30 and 6.31 ± 1.98 f/ml, respectively (P = 0.492). There was no significant difference between the asbestos levels and exposure history (P = 0.877). The mean concentration of asbestos in the ambient air during the current year was 2.69 ± 0.57 f/ml (2.26–3.70), and the correlation between asbestos levels in BAL and the air was not significant (r = 0.147; P = 0.243).

Conclusions

The exposure of different occupational and non-occupational groups to this carcinogenic substance indicates the need for environmental and individual control measures to reduce and prevent asbestos exposure.

Abstract

Abstract

Wastewater stabilization ponds (WSPs) rely on the metabolic activities of the inhabiting microbiota to treat wastewater. A selected consortium of Chlorella vulgaris and Chlorella protothecoides were used to manipulate the natural resident microalgae assemblage to improve the treatment performance of a domestic wastewater pond treatment system in a coastal region. Since information is lacking about the resulting influence on the composition or succession of the phytoplankton or associated microbiota assemblage, the current study aimed to determine how dosing with the microalgae C. vulgaris and C. protothecoides change the efficiency of wastewater effluent treatment, as well as the composition and succession of the natural occurring phytoplankton and microbial assemblage throughout WSP system. After a year of specific microalgae inoculations, the effluent in part complied with the standards set by the Department of Water Affairs and Forestry (DWAF) and the USA, Environmental Protection Agency (EPA). The cyanobacteria Microcystis aeruginosa dominated the sixth (75%) and seventh pond (97%) before the inoculation with C. vulgaris and C. protothecoide commenced. After 12 inoculation events C. vulgaris and C. protothecoides were dominant in ponds three to seven while the dominant microbial groups were Bacteroidetes, Cyanobacteria, Firmicutes, Planctomycetes, Proteobacteria, Spirochaetes, Synergistetes and Verrucomicrobia. After the microalgae treatment, the WSP effluent were more compliant regarding to the set guidelines for effluent than prior to microalgae treatment. Based on the ability of the C. vulgaris and C. protothecoides to improve the effluent water quality, it was evident that the consortium of microalgae can be use improve domestic wastewater effluent in rural nutrient sensitive catchments.

In recent years, artificial intelligence (AI) techniques have been recognized as powerful techniques. In this work, AI techniques such as artificial neural networks (ANNs), support vector machines (SVM), adaptive neuro-fuzzy inference system (ANFIS), genetic algorithms (GA), and particle swarm optimization (PSO), used in water and wastewater treatment processes, are reviewed. This paper describes applications of the mentioned AI techniques for the modelling and optimization of electrochemical processes for water and wastewater treatment processes. Most research in the mentioned scope of study consists of electrooxidation, electrocoagulation, electro-Fenton, and electrodialysis. Also, ANNs have been the most frequent technique used for modelling and optimization of these processes. It was shown that most of the AI models have been built with a relatively low number of samples (< 150) in data sets. This points out the importance of reliability and robustness of the AI models derived from these techniques. We show how to improve the performance and reduce the uncertainty of these developed black-box data-driven models. From the perspectives of both experiment and theory, this review demonstrates how AI techniques can be effectively adapted to electrochemical processes for water and wastewater treatment to model and optimize these processes.

Introduction

The relationship between pesticide exposure and the occurrence of many chronic diseases, including cancer, is confirmed by literature data.

Methods

In this review, through the analysis of more than 70 papers, we explore an increase in oxidative stress level caused by exposure to environmental pollutants and the protective effects of plant-origin antioxidants.

Results and discussion

One of the molecular mechanisms, by which pesticides affect living organisms is the induction of oxidative stress. However, recently many plant-based dietary ingredients with antioxidant properties have been considered as a chemopreventive substances due to their ability to remove free radicals. Such a food component must meet several conditions: eliminate free radicals, be easily absorbed and function at an appropriate physiological level. Its main function is to maintain the redox balance and minimize the cellular damage caused by ROS. Therefore, it should be active in aqueous solutions and membrane domains. These properties are characteristic for phenolic compounds and selected plant hormones. Phenolic compounds have proven antioxidant properties, while increasing number of compounds from the group of plant hormones with a very diverse chemical structure turn out to act as antioxidants, being potential food ingredients that can eliminate negative effects of pesticides.