Heavy metals that enter marine environment and remain in the water as well as the sediments are accumulated by aquatic organisms, thus becoming highly good indicators to monitor metal accumulation in the long run. Metals are potentially harmful to humans and most organisms at varied levels of exposure and absorption. Northern East Mediterranean Sea is a crucial region as it is an area, shared by numerous aquatic species with pollutant factors such as heavy marine traffic, transportation ports, industry plants, iron and steel works, oil pipeline installation, and other small factories. While the previous part of this review (Review of heavy metal accumulation on aquatic environment in Northern East Mediterranean Sea part I: some essential metals) evaluated the data from previous studies concerning toxic effects of selected essential metals on seawater, sediment, and different tissues of aquatic animals, collected from different areas in Northern East Mediterrenean Sea since the 1990s, the present part intends to evaluate the data from previous studies on toxic effects of selected non-essential metals. For this purpose, 94 articles and 6 theses have been examined and a good deal of information has been gathered to open a forward-looking view of the studied area’s pollution. Althought there has not been any harmonization, when comparing heavy metals investigations in the bay, all studies have shown that consumption of aquatic species from the region causes no problem to human health.

Even though solid waste management has become a major public health and environmental concern in urban areas of Ethiopia, only 2% of the population receive solid waste management services. The primary objective of this study is to assess solid waste management practices of Bahir Dar City. The technique of multistage random sampling has been employed to draw 350 households for this study, with both quantitative and qualitative primary data put into good use. Finally, the quantitative data has been analyzed by means of descriptive statistics with the results indicating that 78% of the respondents feel that the current solid waste management service is far below the required level; whereas, 22% of the respondents show satisfaction with the existing waste management service. The municipality has planned to provide solid waste management service for the residents once a week, but the survey results demonstrate that only 29% of the sample households received solid waste management services weekly, indicating that the performance of solid waste management service is low. Among 350 households, a sum of 66.6% practice illegal solid waste disposal with the remaining 33.4% waiting until solid waste collectors come to the area to take the waste away. Therefore, participation of urban households, micro and small enterprises, and governmental and non-governmental organizations plays a great role to upgrade the existing low status of solid waste management services.

In the present investigation, 41 soil samples were subjected to single step chemical partitioning to assess the lithogenic and non-lithogenic portions of metals in Tehran's soils. The share of various studied metals in the anthropogenic portion ranges from as low as 0.2% to as high as 85% of bulk concentration. Geo-accumulation index (Igeo) showed that Cd falls within "heavily contaminated" soils. It might be inferred that Ni, Cu, Cr, Zn, Co and Ca fall within "Deficient to minimal" class in accordance with enrichment factor (EF) classification.. Enrichment factor values (to some extents) match with the chemical partition studies results (except for Ni and Cr). The very low Ca content of soil samples could be indicative of low biological productivity in the Tehran's soil. Also the very low concentrations of Mn could be indicative of reducing environment in soils of Tehran.

The association of the emergence of bacterial resistance to clinical environments is common; however, aquatic environments, especially the polluted ones, also play a key role in this regard. Aquatic environments can act as facilitator for the exchange of mobile elements, responsible for resisting antibiotics. They even may stimulate the emergence and selection of these elements through contaminants or the natural competition between bacterial phyla. Currently there is a large number of highly-reliable resistance genes, which is selected in aquatic environments, mostly due to several types of pollution, such as the mcr-1 gene that causes resistance to one of the antibiotics, available in the market, namely colistin. Thus, the present review aims to show a range of impacts capable of selecting bacterial resistance in the environment, thus clarifying this environment's role in dispersion of resistance.

Emphasis on sustainable development and the need to protect the environment as well as the adverse effects of environmental pollution on the quality of life have made environmental protection one of the main concerns of economic policymakers. For this purpose, approaches to improve the quality of the environment and the factors affecting it have triggered extensive theoretical and empirical studies over the past few decades. These issues have caught the attention of economic analysts. Accordingly, the main objective of this study is to investigate pollution determinants in developing countries from 1996 to 2016, using  Bayesian Model Averaging Method. Given the fact that the weighted mean square coefficient of GDP is positive, the Environmental Kuznets Curve (EKC) Hypothesis can be confirmed with a high degree of certainty. The probability of  this variable's effect is 0.98%, being partially a component of each of the 10 optimal models which highlights the great importance of this variable to explain the environmental performance. Energy consumption variables for each unit of GDP and value added of industry sector are placed in the second and third ranks with effectiveness  probability of 0.89 and 0.85, respectively. They also have a negative impact on environmental performance. Thus, energy consumption per unit of GDP is considered one of the elements of 8 out of 10 optimal models, while the value added of the industrial sector is an element of 7 out of 10 models. This highlights the relative importance of these variables in explaining environmental performance.