The biological impact of a treated produced water (PW) was investigated under controlled laboratory conditions in the blue mussel, Mytilus edulis. Mussel health status was assessed using an integrated biomarker approach in combination with chemical analysis of both water (with SPMDs), and mussel tissues. Acyl-CoA oxidase activity, neutral lipid accumulation, catalase activity, micronuclei formation, lysosomal membrane stability in digestive cells and haemocytes, cell-type composition in digestive gland epithelium, and the integrity of the digestive gland tissue were measured after 5week exposure to 0%, 0.01%, 0.1%, 0.5% and 1% PW. The suite of biomarkers employed were sensitive to treated PW exposure with significant sublethal responses found at 0.01–0.5% PW, even though individual chemical compounds of PW were at extremely low concentrations in both water and mussel tissues. The study highlights the benefits of an integrated biomarker approach for determining the potential effects of exposure to complex mixtures at low concentrations. Biomarkers were integrated in the Integrative Biological Response (IBR/n) index.

The growing pollution mainly caused by the discharge of industrial, sanitary, and agricultural wastes has become one of the main current environmental issues. Thus, the use of bioindicators has become an important tool for investigating environmental imbalance. In this context, microorganisms have shown to be important for the identification of altered environments because of their ubiquity and their ability to grow in inhospitable habitats. Yeasts of the genus Candida are potential bioindicators because of their ability to survive in contaminated freshwater environments. Besides, they are more frequently recovered than fecal coliforms. It is noteworthy that the nonspecific activity of efflux pumps, which help in cellular detoxification processes, may be associated with the presence of chemical compounds in contaminated environments. Thus, the activity of efflux pumps may be the main mechanism involved in the resistance to azole derivatives in Candida spp. and the assessment of their activity may also be a tool for environmental monitoring. As a result, the phenotypical and molecular evaluation of this antifungal resistance in Candida species has been pointed as a promising tool for monitoring the quality of aquatic environments. Hence, the objective of this study was to collect and systematize data pointing to an alternative use of Candida spp. as bioindicators by assessing the occurrence of azole resistance among environmental Candida as a strategy to monitor the quality of freshwater environments.

Exposure to micropollutants can pose a serious risk to both the environment and human health. Although sewage treatment works (STWs) aim to reduce levels of pollutants in municipal wastewater discharges, they have become a significant point source of dangerous substances to the aquatic environment. With increasing regulation on pollution prevention, it has become essential to assess STW source inputs in order to control pollutant discharge into the environment. This paper has therefore focussed on developing calculations to estimate micropollutant levels in STW influents. The analysis was carried out using information from published literature, the Water Industry, and monitored influent data. Results demonstrated that, where monitoring data were available for metals and organic pollutants, STW influent could be adequately estimated and validated, with accuracy between 77% and 100%. In addition, based on these calculations and using data for over 600 STWs in England, our analysis showed that compounds such as di(2-ethylhexyl) phthalate, lead and linear alkylbenzenesulfonate could reach influent levels that could be challenging for conventional wastewater treatment removal.

We are exposed to various chemical compounds present in the environment, cosmetics, and drugs almost every day. Mutagenicity is a valuable property that plays a significant role in establishing a chemical compound’s safety. Exposure and handling of mutagenic chemicals in the environment pose a high health risk; therefore, identification and screening of these chemicals are essential. Considering the time constraints and the pressure to avoid laboratory animals’ use, the shift to alternative methodologies that can establish a rapid and cost-effective detection without undue over-conservation seems critical. In this regard, computational detection and identification of the mutagens in environmental samples like drugs, pesticides, dyes, reagents, wastewater, cosmetics, and other substances is vital. From the last two decades, there have been numerous efforts to develop the prediction models for mutagenicity, and by far, machine learning methods have demonstrated some noteworthy performance and reliability. However, the accuracy of such prediction models has always been one of the major concerns for the researchers working in this area. The mutagenicity prediction models were developed using deep neural network (DNN), support vector machine, k-nearest neighbor, and random forest. The developed classifiers were based on 3039 compounds and validated on 1014 compounds; each of them encoded with 1597 molecular feature vectors. DNN-based prediction model yielded highest prediction accuracy of 92.95% and 83.81% with the training and test data, respectively. The area under the receiver’s operating curve and precision-recall curve values were found to be 0.894 and 0.838, respectively. The DNN-based classifier not only fits the data with better performance as compared to traditional machine learning algorithms, viz., support vector machine, k-nearest neighbor, and random forest (with and without feature reduction) but also yields better performance metrics. In current work, we propose a DNN-based model to predict mutagenicity of compounds.

Several chemical compounds are being studied for their capacities to cause imbalances in several biological systems. Some of those are able to affect the endocrine system and are known as endocrine disruptors. Many negative effects can be induced in the organisms by the action of these chemicals, highlighting the capacity to cause a decrease in the fertility rate, sex inversion, and problems in embryonic development and even cancer in humans. Those contaminants can be found in different environmental conditions, in groundwater, sediments, residual waters, sludges, and even in drinking water. The purpose of this review is to provide a general overview of the main estrogenic endocrine disruptors and their effects on living organisms, showing the most frequently used tools to detect these contaminants in environmental matrices. According to the data found, there is a need to develop more studies and improve the techniques, in order to effectively determine the mechanism of action of these contaminants and, thus, establish appropriate strategies for their removal from the environment and reduce their actions on living beings.

Nuisance odors generation from waste and wastewater treatment plants are a cause of public discomfort and complaints. This situation impairs the air quality and represents a growing social and public health problem, especially in developing countries. Several modeling approaches have been developed and successfully implemented in the frame of a wastewater treatment plant for both the biological treatment and physicochemical processes. The mathematical modeling of the odor generation process is still considered a quite complex issue, mainly due to the fact that olfactory nuisance can be caused by many different chemical compounds and the perception of odors is influenced by subjective thresholds. Moreover, the impact of odor sources on air quality is highly conditioned by complex atmospheric dispersion processes. This review presents a critical state-of-art and assessment where information related to odor emissions impact studies as well as modeling applications are compiled and discussed.

Environmental pollution analysis should be present in scientific research. The more organized the environmental laws of a particular place, the smaller the risks imputed to the ecosystem. The environmental damages that irregular waste from industrial effluents can cause are notorious. However, Brazil lacks extensive legal regulation, which is an embryonic legal matter. There is no specific law regulating a National Industrial Effluent Policy, dealing with the treatment and final disposal of these chemical compounds. Until a solid legal structure has been formalized on the treatment and final disposal of industrial effluents in Brazil, it is necessary that scientific researches optimize techniques capable of causing lower environmental impacts, so as to avoid possible pollution to the bodies of water. This article defends the argument that it is possible to elaborate legislation on the treatment and final disposal of industrial effluents in Brazil, through the application of engineering techniques, specifically through numerical simulation, by using the discrete elements method or particles method. The present case study is the Camaçari Petrochemical Pole, state of Bahia, which is the largest integrated industrial complex in the Southern Hemisphere, composed of more than 90 companies in the chemical and petrochemical areas. All the effluents from this locality are treated by CETREL (Liquid Effluent Treatment Plant). Particle analysis was performed in CETREL tanks to illustrate how numerical simulations can be applied to investigate the treatment of industrial effluents and, consequently, to affirm the importance of developing procedures and norms for this matter. It is believed that this article brings relevant information to support a future law that regulates a Brazilian National Policy of Industrial Effluents.

Background Modern societies depend on environmental sustainability and on new generations of individuals well-trained by environmental research and teaching institutions. In the past, significant contributions to the identification, assessment, and management of chemical stressors with legal consequences have been made. Main Features Within this article, we intend to elucidate the merits and the emerging challenges of chemicals-related environmental sciences. The manuscript is supported by more than 70 professors and university academics of leading institutions in Germany, Switzerland, Austria, and other countries in Europe, but addresses topics of global concern. Results and Discussion Many environmental problems of pollutants remain to be addresses, since new chemical compounds or classes of new compounds are continuously developed and brought to the market and sooner or later “emerge” in the environment. Further issues are the inclusion of transformation products and chemical mixtures in environmental risk assessment, the long-term presence of xenobiotics bound to soils and sediments, as well as an understanding of the ecological relevance of ecotoxicological end points. Conclusion and Perspectives We point out the need for a strong academic research and education system in chemicals-related environmental sciences to ministries, politicians, and research funding institutions and we propose to create specific units in the national funding bodies that address basic and interdisciplinary research in this field.

According to literature data, some of the main factors which significantly affect the quality of the indoor environment in residential households or apartments are human activities such as cooking, smoking, cleaning, and indoor exercising. The paper presents a literature overview related to air quality in everyday use spaces dedicated to specific purposes which are integral parts of residential buildings, such as kitchens, basements, and individual garages. Some aspects of air quality in large-scale car parks, as a specific type of indoor environment, are also discussed. All those areas are characterized by relatively short time use. On the other hand, high and very high concentration levels of xenobiotics can be observed, resulting in higher exposure risk. The main compounds or group of chemical compounds are presented and discussed. The main factors influencing the type and amount of chemical pollutants present in the air of such areas are indicated.