Heavy metals contamination of rainwater is a function of the adsorbed metals present in the particulates of the atmosphere in which the rain was formed from and rainwater chemistry is an alternative way of monitoring urban air pollution for predominant metal species. Three distinct sampling sites (residential, industrial and commercial) were investigated in the south western part of Nigeria for one year. After acid digestion, quantification was done using a double-beam Atomic Absorption Spectrophotometer (AAS). The obtained results showed that heavy metals were predominantly present as free metal ion in the commercial and industrial areas but Mn and As mainly occurred in the suspended fraction. Residential area presented major fractions as bound to organic complexes except Cu and Cd which were principally available as suspended fraction. The health risks associated with the intake of the studied rainwaters indicated susceptibility to possible carcinogens upon consumption due to total RI > 10-4. Ecological risk assessment equally shown a very high level of ecological risks related with the metals due to RI ˃ 600. Sequel upon this, there is need for better sensitization of the citizenry to the sources and control of these pollutants.

The use of plastics as a biofilter medium is an environment-friendly and effective technology for reducing pollutants in liquid waste. The main objective is to analyze the ability of biofilters with plastic media to remove pollutants in wastewater by looking at several parameters. Various types of data were developed and analyzed to answer specific goals set through the search engines EBSCO, Scopus, and ProQuest by examining several parameters, including wastewater source, research scale, research period, temperature, media type, media thickness, and pollutant removal. The obtained data were processed to determine the distribution of the descriptions. Data related to biofiltration using plastic media was obtained from 152 articles, with only 14 articles in the search category. These findings show that all types of plastic media are effective for biofilm attachment and bacterial growth, resulting in a very large removal of pollutants present in liquid waste. Biofilters with plastic media are also known to be able to remove contaminants such as Chemical Oxygen Demand, biological oxygen demand, total organic carbon, nitrogen, phosphorus, ammonia nitrogen, hydrogen sulfide, toluene, ammonia, diethanolami, phenol, total suspended solids, and Escherichia coli. Synthetic wastewater (35.71%) was the most common wastewater source. Research related to biofiltration using plastic as the medium is mostly carried out on a laboratory scale with a total of 64.30% and using units of the day as an indicator of changes in a total of 71.42%, with an average experimental temperature of 29.1 °C.

The development of suitability species models look for the availability to growth in a study area. These models can be used for different targets. In this research, a suitability model of Eucalyptus has been developed to soils contaminated by trace elements management. Guadiamar Green Corridor has been selected due to the huge data available regarding trace elements, forestry species and so on. Logistic regression (LR) and Random Forest (RF), as popular machine learning model, were applied in a geodatabase from Guadiamar Green Corridor with more of 20 years of data. This database is composed by soil physical and chemical variables, climate (temperature min and max, annual precipitation), forestry species. The results show the poor performance of LR and RF applied directly over the unbalanced training set. However, when Up-sampling or SMOTE are applied, both procedures improve its sensitivity, however, RF show more improve that LR. The methodology applied can help to determine the potential distribution of Eucalyptus in similar Mediterranean areas and extended to different areas according to Soil, Climate and Trace Elements data. Finally, the models developed under this research work can be used to reduce human and environmental health by trace elements taking into account local conditions but also climate change scenarios.

Natural quartz mineral was examined as a new sorbent for Hg(II) removal from synthetic wastewater systems. Batch adsorption experiments of Hg(II)  onto quartz mineral were conducted under various conditions such as solution pH, sorbent dosage, contact time, initial Hg(II)  concentration. Adsorption experiments results of Hg(II) by quartz mineral showed good achievement after 180 min with 1.0 g/L sorbent mass at pH of 2.0, agitation speed of 200 rpm and a temperature of 25°C. Moreover, the Hg(II) concentration was directly related to increases the adsorption capacity, the maximum Hg(II) uptake by quartz  sample was 16.52 mg/g for 80 mg/L (C0 (Hg(II)].  Langmuir isotherm and pseudo-second-order kinetics (R2 > 0.99) were found to be the most appropriate models to describe the adsorption of Hg(II) by quartz mineral. The intra-particle diffusion model and the calculated Dubinin–Radushkevich adsorption energy (Eads = 0.78 kJmol-1), confirms a physisorption adsorption reaction occurring in three stages.

Perfluorinated chemicals (PFCs) are widely used in industrial and commercial applications, leading to their release into the environment. The rapid industrialization and growing population in India make it a suitable case study to investigate PFOS contamination in environmental matrices. The purpose of this study is to investigate PFOS concentrations in river water and groundwater from several locations along the Bharathapuzha river basin and estimate PFOS intakes through drinking water. The highest PFOS level detected in the surface water is 1.3 ng/L and groundwater is 1.0 ng/L, which is significantly lower than the level of PFOS detected in major rivers of many developed countries. It is possible to attribute the low PFOS concentration to factors such as high annual precipitation, reduced industrial and municipal wastewater discharge, and relatively low emissions per capita in a region where agriculture is a major part of the economy. In addition, the daily intake of PFOS through drinking water in all age groups was below the safety threshold for cancer risk.

We analyzed 125 samples collected from Joypurhat district, Bangladesh, in this study. Average inorganic arsenic (IAs) content obtained from collected polished rice, tomato, potato, radish, and arum leaves 0.31 - 0.91, 0.24 - 0.61, 0.49 - 0.88, 0.40 - 0.93, and 0.30 - 0.69 mg/kg, respectively. This report summarized that almost every agronomic sample contains arsenic; the As contents remain within the permissible limit set by FAO/WHO’s guideline (1.00 mg/kg) except for the rice sample. The As concentration for the rice sample was significantly higher (0.31 - 0.91) than the prescribed limit (0.20 mg/kg). But, the As level for water (mean range, 0.10 - 0.72 mg/l), sediment (0.13 - 0.53 mg/kg), and soil samples (24.1 - 43.1 mg/kg) also significantly surpassed the permissible level. The present study is alarming for water samples, where the highest IAs concentration (0.72 mg/l) is 72 times [14 times] higher than WHO/FAO’s [Bangladesh’s] allowable limit (0.01mg/l) [0.05 mg/l]. All agronomic fields contain higher IAs (25.50 - 43.10 mg/kg) than the world standard limit (10 mg/kg). Statistical Igeo confirmed the moderate pollution of the entire agronomic field of Joypurhat except for the river’s sediment. Again, EF values ensured the anthropogenic pollution by the moderately severe enrichment of As for the 65% agronomic field and significant enrichment of As for the 35% agronomic field. Hazard estimation results revealed the privileged possibility of non-carcinogenic [carcinogenic] health hazards to regular polished rice [water] consumers. So, present study suggests that authorities should take necessary steps to prevent contamination/upcoming health risks.

Laboratory wastewater is categorized as hazardous waste that should not be released into the environment since it poses a serious threat to environmental safety. In the present study, the use of Sulphate-Reducing Bacteria (SRB) colonies in an anaerobic reactor to treat heavy metals-containing laboratory wastewater was examined. SRB was initially cultivated with the treatment of fermented compost and Postgate's medium before being attached to the laboratory-size anaerobic reactor to treat laboratory waste containing heavy metal. Within the 15 days of initial incubation under the room temperature of 28 °C, we discovered that SRB optimally grew on the medium with the composition of 5% Postgate B solution, 30% fermented compost liquid, and 5% active suspension liquid, with a total population of cell colonies was 1.2 x 105 CFU/ml. After SRB colonies from the most optimum medium were affixed to the reactor, the reactor attained 89% of lead (Pb) removal, 69.78% of iron (Fe) removal, and 48.93% of copper (Cu) removal for 15 days treatment periods. On the 21st days of treatment time, the removal efficiency increased significantly to 91.57%, 78.09%, and 83.56% of Pb, Fe, and Cu removed, respectively.

The presence of volatile organic compounds in the indoor environment and their unwanted effects on human health are inevitable. That's why different methods have been proposed to remove them from air. The present study examines using photocatalytic reaction system along with TiO2 particles coated on stainless steel webnet to study direct conversion of toluene using a new design. The study was carried out using UV radiation in a dynamic concentrator system. SEM and XRD analyses were performed to characterize prepared catalysts. Here, the aim was to employ photocatalytic oxidation (PCO) to optimize removal efficiency and elimination capacity using response surface methodology (RSM). To this end, initial concentration and flow rate were selected as independent variables. High removal efficiency and elimination capacity were realized using optimal settings. The findings indicated that PCO process with a new design other than RSM was an option to treat air pollution containing volatile organic compounds.

The pollution generated by metallic trace elements discharged by mines into the environment can become a very worrying source of contamination for soil, water and plants. The characterization of the chemical properties of metals in mine tailings and soils is of crucial importance to assess the risk of their potential mobility and therefore their bioavailability. In this paper, the bioavailability of metallic trace elements  in agricultural soils in the vicinity of the Draa Lasfar mine in the northwest of Marrakech city (Morocco) was studied by determining the contents of Cd, Cu, Pb and Zn in soils and in two plants: wheat (main food for the human population) and couch grass (main food for livestock). The results showed that these metals move from agricultural land to plants. They also showed that couch grass seems to strongly absorb and accumulate metallic trace elements present in the soil; it removes considerable amounts of metallic trace elements from the soil with its deeply penetrating root system.

The present study aims to provide baseline information on the temporal characteristics of PM2.5 and PM10 concentration time series variations, mainly on the cross-correlation between PM2.5 and PM10, using the improved mathematical and nonlinear methods. Firstly, the fractal theory such as fractal dimension is used to detect the pollution level in PM2.5 and PM10 time series. Secondly, the Multifractal Detrending Moving-Average Analysis (MFDMA) is used to analyze the multifractal characteristics of PM2.5 and PM10 concentrations. Thirdly, Multifractal Detrending Moving-Average cross-correlation Analysis (MFXDMA) is used to study the cross-correlation between PM2.5 and PM10 concentrations measured from January 1 to December 31, 2020, along the Boulevard de la Marina, one of the major roads in Cotonou. The results have indicated that: (1) PM10 and PM2.5 concentration time series are characterized by a fractal dimension, which can permit to detect the pollution levels and to analyze the differences in emissions sources; (2) there is a significant multifractal structure in the PM2.5 and PM10 concentration data and their fluctuations are long-range correlated, however, the multifractal properties and self-memory characteristics change with the months; (3) generally, the multifractal degree and the complexity of PM10 are much stronger than those of PM2.5. However, they present a similar multifractality degree in some months of the year; (4) except, in February, the cross-correlation between PM2.5 and PM10 time series in the months of the year presents multifractal characteristics with positive persistence; (5) the cross-correlation multifractal features show monthly variation. This paper provides the inter-relationship between air PM2.5 and PM10 time series which may help taking steps in controlling the air quality and management of the Cotonou port area environment.