In this work, we study  the short-term dynamics of the Surface  Air Temperature (SAT) using data obtained  from a  meteorological station in Bogotá from 2009 to 2019  and using  time series.  The data that we used correspond to the  monthly mean of the historical registers of SAT and three  pollutants. A descriptive analysis of  the data follows. Then, some predictions are obtained from two different approaches:  (i) a univariate analysis of SAT through a  SARIMA model, which shows a good fit; and  (ii) a multivariate analysis of SAT and  pollutants  using a SVAR model. Suitable transformations were first applied on the original dataset to work with stationary time series. Subsequently, A SARIMA model and a VAR(2) with its associated SVAR model are estimated. Furthermore, we obtain one-year forecasts for the logarithm of SAT in both models. Our forecasts simulate the natural fluctuation of SAT, presenting peaks and valleys in months when SAT is high and low, respectively. The SVAR model allows us to identify certain shocks that affect the instant relationships among variables. These relations were studied by the impulse-response function and the VAR model variance decomposition. Although the statistical methods used in this study are classical, they continue being widely used in the environmental field, presenting god fits, and the results obtained in this study are consistent with  environmental theories.

Aerosols are tiny particles (liquid or solid) suspended in the atmosphere. They play a significant rolein climate dynamics directly or indirectly. Aerosol Optical Depth (AOD) and Angstrom Exponent(AE) are significant parameters to study the concentration and size or type of aerosol over an area,respectively. In this article, we utilized three years of AOD and AE parameters derived from moderateresolution imaging spectroradiometer (MODIS) satellite during the period January, 2013 to December,2015 over Ethiopia. In order to study the spatiotemporal pattern of aerosols, we choose three areas(Debretabour, Gojjam and Addis Ababa) over Ethiopian highlands, which are representative of nonindustrial, agricultural and industrial areas respectively. Further we compare continental aerosols withmarine aerosols from Djibouti. Our results clearly depicts the aerosol distribution over Ethiopia ishighly variable spatially and temporally. The results indicates that the urban and biomass aerosols aredominate over Addis Ababa, and Gojjam respectively, whereas dust and biomass aerosols are presentover Debretabour, while Djibouti is loaded by sea spray aerosols. The seasonal variability of AOD isfound to be maximum during the kiremt (summer) and minimum during bega (winter) over all areas(continental and marine).

Air pollution is a global issue and meteorological factors play an important role in its transportationand regional concentration. The current research is aimed to analyse the variations in meteorologicalparameters in a seasonal and geographical location context in the Jiangsu province of China, and itscorrelation with the six criteria air pollutants, and air quality index (AQI). The present analysis willsupplement the limited understanding on the relation between the regions prevalent climatic conditionsand atmospheric pollution. The meteorological data analysis showed Suzhou city located in thesouthern region of the Jiangsu province with high average temperature, relative humidity, and rainfall.Maximum values of temperature, UV index, sunshine, relative humidity, and rainfall occurred duringsummer, while air pressure in winter. High values of all meteorological parameters occurred in thenorthern and southern region of the province. The data correlation study revealed AQI to havenegative correlation with most meteorological parameters, and positive correlation with air pressure inall cities.

Iron removal from aqueous solution via ultrasound-assisted adsorption using Typha australis leaves as low cost adsorbent had been studied. The effects of various experimental parameters like mass of the Typha australis adsorbent and contact time have been investigated using a batch experiment. The adsorption kinetic data were analyzed using the Pseudo First Order (PFO) and Pseudo Second Order (PSO) models. The adsorption modeling was carried out using the Langmuir, Freundlich and Redlich-Peterson adsorption models. For kinetic study, the adsorption process fitted the PSO model and agreed with chemisorption. Both the Langmuir and Redlich–Peterson models were found to fit the adsorption isotherm data well, but the Redlich– Peterson model was better. The maximum adsorption capacity from the Langmuir model (qmax) was 0.84 mg/g. The results of the present work showed that the Typha australis leaf, without any treatment has a good potential for iron removal from aqueous solutions via ultrasound-assisted adsorption.

A monthly temporal monitoring of the physico-chemical parameters of the leachate from the Greater Casablanca “Mediouna” open-air landfill in Morocco over a period of 13 months was carried out to show their variability over time. This monitoring also highlights the effect of rainfall on leachate quality through fluctuations observed in wet and dry periods. Indeed, the leachate was sampled from a collector that drains a mixture of young and mature leachate. Several physico-chemical parameters were studied: pH, temperature, conductivity, organic matter (BOD5 and COD), total matter (TS, TVS), nitrogen (N-NO2-, N-NO3-, N-NH4+, TKN), total phosphorus (Tp), salts (Cl-, SO42-) and metals (Cd, Co, Cr, Ca, Cu, Fe, K, Mg, Mn, Ni, Pb, Zn). As a result, significant concentrations were recorded throughout the monitoring for the majority of the parameters, showing a high aggressiveness of the leachate. Also, statistically significant relationships were observed between the different parameters. On the other hand, the leachate pollution index (LPI) was calculated to determine the overall potential of leachate pollution. The identification and study of the behaviour of the physico-chemical parameters is very useful for the design of an adequate leachate treatment plant for the Greater Casablanca landfill "Mediouna", taking into consideration the extreme values recorded during the monitoring period, in order to avoid any malfunctioning due to an underestimation of the pollution.

Sustainable urbanization under sustainable development goals requires quantitative information on urban landscape. Despite having the fastest growth of urban area and poor air quality, Faridabad, a constituent district of National Capital Region, fails to gain much research attention.  Present study based on multi-temporal; freely available satellite image has indicated 3% increase in the built-up against 2% decrease arable land from 2008 to 2018. Further, spatial metrics (Shanon’s entropy, class area (CA), number of patches (NP), largest patch index (LPI)) has indicated scattered development of built-up. Increase CA (11470 ha in 2008 and 13806 ha in 2018) and NP (221 in 2008 and 476 in 2018) have indicated isolated development of built-up with small area coverage. Increase in LPI (12.5% in 2008 and 13.5% in 2018) of built up indicated compact growth of dense built-up in the southern and eastern side leading to the vertical expansion of the city area. Linear expansion of the residential built-up, industrial, and commercial area along the highways, roads and railways and vehicular emission has contributed to the high aerosol concentration. While, in the rural region the high aerosol loading has also been observed because of the extensive use of fertilizer and stubble burning. Present research on land-use land cover changes and its impact on air quality could be contributed significantly in urban policy making for climate change adaptation and mitigation strategies.

The study was conducted to assess surface water quality in Ca Mau peninsula using multivariate statistical analysis. Fifty-one water samples with the parameters of pH, dissolved oxygen (DO), total suspended solids (TSS), biochemical oxygen demand (BOD5), chemical oxygen demand (COD), ammonium (N-NH4+), orthophosphate (P-PO43-) and total coliform were used in the evaluation. Water quality is assessed using national standard and water quality index (WQI). The methods of cluster (CA), discriminant (DA), principal component analysis (PCA) were used to analyze the variation patterns of water quality. The surface water was contaminated with organic matters, suspended solids, nutrients, and microorganisms. DA revealed that DO, TSS, BOD5 and pH contributed 76.91% to the seasonal variation of water quality. Water quality is classified from bad to heavily polluted. CA grouped water quality into 7 clusters and DO, TSS, BOD5, COD and coliform of the clusters 1-3 were significantly higher than those of the clusters 4-7. PCA presented that PC1-PC3 was the main sources affecting water quality, explaining 85.45% of the variation in water quality. The sources of pollution can be human (domestic wastewater, waste from agriculture, fisheries, industry, landfills), natural (hydrological regime, rainwater overflow, river bank erosion). pH, DO, BOD5, COD, TSS, N-NH4+, P-PO43- and coliform have an impact on water quality and need to be continuously monitored. However, for the multivariate statistical method to be more effective, an initial data set with several water quality parameters sampling locations is needed. The current results provide scientific information and support local water quality monitoring activities.

Plastic pollution is a threat to the environment because of its slow degradation rate and high usage. The aim of this study is to isolate plastic degrading microorganisms from soils. The soil samples used for this study were collected from dumpsites filled with plastic and plastic materials and the effectiveness of the degradation of plastic materials was studied over a period of six (6) weeks in broth and agar culture under laboratory conditions by weight determination method. Physicochemical and microbiological analysis was carried out on the various soil samples using standard protocols. The biodegradation of polyvinylchloride (PVC) was done in-vitro using the microorganisms isolated from the soil. Microorganisms that were able to degrade a higher percentage of the plastic materials were; Staphylococcus aureus, Streptococcus sp, Bacillus sp, Escherichia coli Aspergillus niger, Aspergillus flavus and Trichoderma viridae. The total viable count for bacteria and fungi were within the range of 11.8x105 CFU/g to 2.0x1010 CFU/g and 3.3x105 CFU/g to 0.1x1011 CFU/g respectively. Staphylococcus aureus, Streptococcus sp, Bacillus sp, Micrococcus sp, Aspergillus niger, Aspergillus flavus, and Trichoderma viridae, degraded plastic up to 25%, 31.2%, 25% 31.2%, 12%, 10% and 10% respectively. These isolates may be used to actively degrade plastics, thereby reducing the rate of plastic pollution in our ecosystem.

In advanced oxidation processes, the application of ozonation has been immensely used in recent years for the treatment of effluent water from pharmaceutical, textile and chemical industries. In this study, procian blue, a major and vastly used reactive dye in the textile industry was chosen for ozonation. This work investigated the effect of ozonation for the treatment of synthetic textile effluent water. The change of pH values of dye solutions from 2-12 had moderate effect on dye removal. The degradation rate was faster during the initial period of ozonation and reached highest dye removal around 90 minutes. The highest 87% removal of dye was observed for the case of 60 mg/L dye solution at pH 12. At higher pH, the dye degradation increased as the rate of formation of hydroxyl radical increased with pH. Factors influencing on dye degradation like concentration of dye, time of ozonation, and addition of H2O2 with ozone (combined treatment) were also evaluated. The combined treatment (5 g/L of hydrogen peroxide) increased the degradation of dye to 92% as compared to 85% for pure ozonation process of 60 mg/L dye solution of initial pH 10. The procian blue dye degradation followed pseudo-first order kinetics with a value of rate constant 2.48×10-2 /min.

Increasing plastic usage pose a significant threat to the marine environment. Many studies have been conducted to examine the amount and environmental impacts of plastic waste across the world. This study was carried out to investigate the density and quality of plastics on the sea surface and seabed of İskenderun Bay. 35 different seabed sampling and 25 different sea surface sampling were conducted by using İskenderun Technical University R/V ISTE-1 vessel. A total of 1 661 581 m2   and 465 511 m2 swept from the seabed and sea surface were scanned, respectively. As a result of these scans, the amount of plastic waste density per unit area of the seabed was found as  0.126 g / m2 ± 0.011 (p: 0.95), and the amount of plastic waste density per unit area of sea surface was calculated as 0.052 gr ± 0.011 (p: 0.95). Scuba dives conducted in river mouths showed plastic deposition pits at the seabed. Major surface current systems and dominant southern winds were found to be effective in the sea surface distribution of plastic materials.