Atmospheric models today represent all significant aerosol components. Atmospheric aerosols play an important role in the air, globally through their action on the Earth's radiation balance and locally through their effects on health in heavily polluted areas, they vary considerably in their properties that affect the way they absorb and disperse radiation, and they can thus have a cooling or warming effect, they impact on the formation and life of clouds is one example. Among the main sectors of activity releasing emissions of PM10 (fine particles with a diameter of less than 10 µm) and a diameter of less than 2.5 µm (PM2.5) is the industrial sector, in particular the extraction industry of building materials. The aerosols emitted by this type of industry are composed mainly of a mixture of dust, sulphates, carbon black and nitrates, is clearly perceptible in many continental regions of the northern hemisphere. Improvements in in situ, satellite and surface measurements are needed. However, the mechanisms by which aerosols interact with the environment are extremely complex and still poorly understood. This study is based on satellite atmospheric models to have spatiotemporal variability of concentrations of fine particles smaller than 10 µm in diameter (PM10) and smaller than 2.5 µm in diameter (PM2.5) at the level of the western Rif part of Morocco, home to a large number of extraction quarries and thus offering a high-resolution particle capture system (PM10 and PM2.5).

Global fire cases in recent years and their vast damages are vivid reasons to study the wildfires more deeply. A 25-year period natural wildfire database and a wide array of environmental variables are used in this study to develop an artificial neural network model with the aim of predicting potential fire spots. This study focuses on non-human reasons of wildfires (natural) to compute global warming effects on wildfires. Among the environmental variables, this study shows the significance of temperature for predicting wildfire cases while other parameters are presented in a next study. The study area of this study includes all natural forest fire cases in United States from 1992 to 2015. The data of eight days including the day fire occurred and 7 previous days are used as input to the model to forecast fire occurrence probability of that day. The climatic inputs are extracted from ECMWF. The inputs of the model are temperature at 2 meter above surface, relative humidity, total pressure, evaporation, volumetric soil water layer, snow melt, Keetch–Byram drought index, total precipitation, wind speed, and NDVI. The results show there is a transient temperature span for each forest type which acts like a threshold to predict fire occurrence. In temperate forests, a 0.1-degree Celsius increase in temperature relative to 7-day average temperature before a fire occurrence results in prediction model output of greater than 0.8 for 4.75% of fire forest cases. In Boreal forests, the model output for temperature increase of less than 1 degree relative to past 7-day average temperature represents no chance of wildfire. But the non-zero fire forest starts at 2 degrees increase of temperature which ends to 2.62% of fire forest cases with model output of larger than 0.8. It is concluded that other variables except temperature are more determinant to predict wildfires in temperate forests rather than in boreal forests.

A large anthropogenic source of mercury pollution is mercury-dependent artisanal and small-scale gold mining (ASGM). Thabeikkyin Township is a small-scale gold mining township located in Pyin Oo Lwin District in the Mandalay Region, Myanmar. The villages of Thabeikkyin Township engage in gold ore crushing, screening, refining, and other mining activities for a living. Miners in this area commonly use mercury for gold recovery by heating amalgam at their homes, gold shops, on the street, and near the riverbank. The evaporated mercury is released into the atmosphere during the heating process and then transported and deposited in the surrounding environments, resulting in the mercury pollution of air, water, soil, etc. To assess atmospheric mercury pollution, a preliminary study on the environmental mercury contamination from ASGM was conducted in Thabeikkyin Township. High mercury concentrations were observed in plant samples collected near the refining sites, ranging 0.33–6.51 ug/g, compared with 0.02 ug/g in Wet Thay Village, where no mercury use was reported. Correlation coefficients between Hg and other heavy metals showed that no heavy metal concentration significantly correlated with that of Hg. The results indicated that the atmospheric environment in the ASGM area of Thabeikkyin Township was contaminated with mercury originating from ASGM, which could very likely deteriorate the health of surrounding residents.

Organophosphates are one of the most common pesticides in the world. Among them, one can find malathion that is classified as carcinogenesis, and, as a result, should be appropriately removed since it is highly consumed and possesses a lot of pathogenicity. So far, several processes have been used to remove malathion from aqueous media. The present study investigates its removal by means of Fe3O4 iron oxide nanoparticles. Based on experimental-laboratory studies, using the Response Surface Methodology (RSM), the impact of independent variables such as pH, iron oxide nanoparticle concentration, and contact time on malathion removal efficiency have been investigated. Results show that the pH of the solution is the most important and effective parameter in the process. Optimal conditions of malathion removal based on the appropriate model, obtained from RSM, include 0.4 g/L iron oxide nanoparticles, pH of about 5 (acidic conditions), and contact time of about 1 h with ultraviolet radiation being equal to 82% malathion removal. The process, used in this study, can remove malathion from aqueous solutions according to the so-called conditions, and changing the laboratory conditions can effectively remove it. This process can also be recommended as an economic and scientific method to remove malathion from drinking water.

In this work, Fe3O4-SiO2 nanoparticles were synthesized, characterized, and applied as adsorbent material to remove methyl blue stain from an aqueous solution. The prepared nanoparticles were characterized by X-ray diffraction (XRD), scanning electron microscope (SEM), transmission electron microscope (TEM), and Brunauer–Emmett–Teller (BET) to determine the physical surface properties and correlate them to the adsorption efficiency. In addition, this study investigated the influence of several parameters on the removal percentage and adsorption capacity. Specifically, this study investigated the impact of changing the following parameters: pH (1 – 8), agitation speed (Uspeed; 100 - 350 rpm), initial methyl blue (MB) concentration (1 - 100 mg/L), adsorbent dose (0.05 to 0.15 g), and contact time (10 - 100 min). The characterization study reveals that the prepared material has an excellent surface area (385 ± 5 m2/g) and pore volume (0.31 cm3/g) which enhances the adsorption capacity. In addition, the prepared material showed excellent efficiency where the removal percentage reached 99.0±1% at the optimal operating conditions and the maximum adsorption capacity was 40 mg/g. This study delivers a full elucidation of the adsorption of MB dye by Fe3O4-SiO2 NPs which considers a promising inexpensive adsorbent. It also delivers important insight information about the adsorption process and the influence of each parameter, which fill the lack in this field.

Cities in developing countries like Shiraz in Iran face significant challenges due to a lack of an integrated solid waste management system. Climate change, soil, and water pollution are examples of environmental issues caused by improper Municipal Solid Waste Management Systems (MSWMS) in developing countries. The aim of this study is to find solutions for these environmental problems based on the experiences of developed countries. The data was collected using several methods such as visual observations, studying accessible documents of the current situation of the MSWMS in Shiraz, and participating in an interview with engineers the 'Shiraz Municipality Waste Management Organization' (SMWMO).  Results present the current functional elements of MSWMS in Shiraz, Shiraz waste diversion rate (0.22), and its Zero Waste Index (.015). Moreover, the results present some recommendations to find a way to transform cities like Shiraz into zero-waste cities. Results indicate that establishing zero-waste policies, legal frameworks, and financial strategies as well as convincing private sector involvements in installing waste-to-energy facilities and a proper sanitary landfill to move the city toward optimum recycling and zero landfilling in addition to reducing consumption and maximizing diversion rate and finally sustainable development by the cooperation of government, NGOs and media programs would solve many problems of the MSWMS and would solve environmental issues in many cities.

The problem of pollution of aquatic ecosystems with microplastics has been actively studied by the world scientific community. Most of this research has been devoted to marine ecosystems, whereas scant research has been conducted on fresh water bodies. Lake Baikal (Russia) is a unique natural reservoir. Previous studies devoted to the amount of microplastics in the waters of Lake Baikal were carried out singularly and were not of a systemic character; therefore, previously obtained data does not reflect a complete picture of the state of the lake. Within the framework of this study, our goal was to study the composition and morphological structure of microplastic particles in the ice of Lake Baikal at different distances from the coastline. To do this, a number of ice samples were taken from the upper and lower sides at five different points in South Baikal opposite the village of Bolshiye Koty. Later these samples were analyzed for the types of microplastics and their amount. In the samples taken, two types of microplastics were found—fragments and fibers—with fibers being predominant. The median values of the number of microplastics particles are higher in samples taken at the interface between water and ice, compared to samples taken from the ice surface. Presumably, main part of microplastic fibers found opposite the village of Bolshiye Koty were brought in by a constant circular current from the opposite east coast. In turn, the low number of fragments in the samples may be due to the freezing of the coastline.

Chromium VI is a frequent pollutant of industrial liquid effluents. It is a substance classified as a carcinogen group I. In this study, a Cr VI sorption mechanism was developed by using nanocellulose spheroids (hydrogel) obtained from ivory nut. Cr VI was detected in water by a colorimetric method, using 1, 5-diphenylcarbazide at λ 540 nm. Then, the sorption capacity of nanocellulose spheroids was tested by varying the solution's pH and temperatures. The outcome of the experiment shows that the most efficient pollutant’s adsorption conditions are occur at pH 4 and 25 °C. Removal percentages of Cr VI reached 91.29% (+/-1.36) and 95.33% (+/- 0.86). Additionally, the sorption kinetics showed that the adsorption reaction on the material reaches its equilibrium 20 to 30 minutes after the reaction starts. Finally, an analysis of adsorption isotherms showed a high adjustment with the Langmuir and Freundlinch isotherms. In this frame, this work’s results show that nanocellulose beads are an interesting alternative to efficiently reduce Cr VI from industrial and drinking water.

Exposure to household dust is a common occurrence in all countries and causes various diseases. This study provided information on the number, shape, size distribution, and elemental composition of household dust particles collected in urban homes in Agadir city in Morocco. Moreover, a potential human health risk of exposure has been identified based on current research. Samples were analyzed using computer-controlled scanning electron microscopy and ImageJ image processing program. A total of 3296 particles were analyzed for their size, and 76 particles were classified according to their size and elemental composition. Household dust particles were classified in six types: micro-aggregates (31.6%), biogenic (5.3%), spherical (17.1%), subrounded (7.9%), subangular (11.8%), and angular (26.3%). These particles were determined to have originated from a distant source (Trask classification index between 1 and 2.5). They were large (Skewness asymmetry coefficient > 1), and ranged from 0.2 to 363 µm with an average value of 22.8 ± 0.6 µm in diameter. Dust particles with diameters of 5-10 µm and 10-20 µm were the most abundant, while dust diameters of 10-20 µm, 20-30 µm, and > 100 µm were the highest in volume. The domestic dust deposition rate was 19.8 ± 7.4 g/m2 per year. Household dust is one of the major sources of PM10 in the residential environment (44.6% of the total number of particles), and the studied properties of house dust are highly related to human health. Household dust is a critical element to be considered in the occurrence of respiratory and cardiovascular infections.

Batch adsorption process was employed to remove copper(II) and cadmium(II) ions from contaminated water using dried orange peel powder as a cellulosic adsorbent, which supports circular economy and sustainability. Metal ion concentrations were determined using a flame atomic absorption spectroscopy (FAAS). Effects of pH, sorbate-sorbent contact time, metal ion concentration and adsorbent dose on the removal efficiency of the metal ions was investigated. The adsorption equilibrium was reached at 120 and 150 minutes for Cu(II) ions and Cd(II) ions, respectively. At optimized pH and biosorbent load, 10 mg L-1 of Cu(II) and Cd(II)  ions could be removed to the extent 96.9% and 98.1%, respectively, within 2 hrs. However, the percentage removal of metal ions decreased with increasing their initial concentrations. The observed adsorption data was also interpreted in terms of Langmuir and Freundlich adsorption isotherm models. The calculated equilibrium data fitted more adequately with Freundlich model (higher correlation coefficient, R2) than Langmuir model, indicating heterogeneity of adsorption sites due to different functional groups in cellulose. Cd(II) ions showed less binding affinity and less desorption than Cu(II) ions. The maximum adsorption capacity (qmax) of dried orange peel were 2.78 mg/g and 2.57 mg/g for copper(II) and cadmium(II) ions, respectively.