The main objective of this paper is to propose K-Nearest-Neighbor (KNN) algorithm for predicting NOx emissions from natural gas electrical generation turbines. The process of producing electricity is dynamic and rapidly changing due to many factors such as weather and electrical grid requirements. Gas turbine equipment are also a dynamic part of the electricity generation since the equipment characteristics and thermodynamics behavior change as turbines age and equipment degrade gradually. Regular maintenance of turbines are also another dynamic part of the electrical generation process, affecting performance of equipment as parts and components may be upgraded over time. This analysis discovered using KNN, trained on a relatively small dataset produces the most accurate prediction rates in comparison with larger historical datasets. This observation can be explained as KNN finds the historical K nearest neighbor to the current input parameters and approximates a rated average of similar observations as prediction. This paper incorporates ambient weather conditions, electrical output as well as turbine performance factors to build a machine learning model predicting NOx emissions. The model can be used to optimize the operational processes for harmful emissions reduction and increasing overall operational efficiency. Latent algorithms such as Principle Component Algorithms (PCA) have been used for monitoring the equipment performance behavior change which deeply influences process paraments and consequently determines NOx emissions. Typical statistical methods of performance evaluations such as multivariate analysis, clustering and residual analysis have been used throughout the paper. This paper incorporates ambient weather conditions, electrical output as well as turbine performance factors to build a machine learning model predicting NOx emissions. The model can be used to optimize the operational processes for harmful emissions reduction and increasing overall operational efficiency. Latent algorithms such as Principle Component Algorithms (PCA) have been used for monitoring the equipment performance behavior change which deeply influences process paraments and consequently determines NOx emissions. Typical statistical methods of performance evaluations such as multivariate analysis, clustering and residual analysis have been used throughout the paper.

Bed Sediment is a dynamic and complex material that plays an important role in the aquatic ecosystems and provides habitat from a highly various community of organisms. To address the major issue, this study, which its substantive subject done for the first time in Iran, aimed to assess the current status of Darreh-rood river's health and quality using SOD rate and its associated factors including Texture, fine-PSD, TOC and TP of bed sediments along with some basic field parameters of river-water. All required samples were collected from 10 sampling points in due course. SOD data with regard to related factors were calculated and analyzed. The rates of SOD ranged from 0.69 to 1.57 g O2/m2/day. Moreover, this index was classified in varied quality domains. Afterwards, a predictive equation was determined among SOD rate and its associated parameters using MATLAB software. Finally, the Results showed that the river quality and health suitability in research area are in categories slightly clean and slightly degraded, in targeted zones during the study period. Also, the increase in TOC and TP concentrations together with a decrease in sediment particle size was led to an increase in SOD-rate accordingly. In conclusion, the consequences of this study under Survivability-based Adaptive Management (SAM) perspective can be used as a rapid diagnostic tool to support water policy decision-makers and other stakeholders to promote the best practices for protecting the health conditions of riverine systems, focusing on selecting the appropriate points for discharging the wastewaters into the receiving water-bodies.

The critical parameters namely initial pH, time and current density largely impact the process efficiency of electrocoagulation (EC). Few works have been done on observing the interaction of these critical parameters and the possible combined effect on the overall pollutant removal efficiency. Therefore, the knowledge of the combined effect of critical parameter interaction would enhance the optimization of EC parameters to attain maximum efficiency with limited resources. Using aluminium electrodes with interelectrode distance of 10 mm on synthetic wastewater, representing biotreated palm oil mill effluent (BPOME), with a set range of initial pH, current density, and time of 3-8, 40-160 mA/cm2 and 15 to 60 minutes, respectively, the effect of the three critical variables was investigated. The optimum Chemical Oxygen Demand (COD) removal of 71.5% was determined at pH 6, current density of 160 mA/cm2 (with current 1.75 A) at EC time of 15 minutes. The experiment was validated with real BPOME, resulting in the removal efficiency of 60.7 % COD, 99.91 % turbidity, 100 % total suspended solids (TSS) and 95.7 % colour. Removal of a large quantity of pollutants in a time span of 15 minutes with optimized parameters in EC is notable for a wastewater treatment alternative that requires no extensive use of chemicals. The interaction of parameters observed in this study indicated a synergistic contribution of initial pH and current density in removing maximum wastewater COD in 15 minutes of EC.

Technology has made the life of Bangladeshi people very flexible with new inventions. In most cases, here the people depend on these technological devices. These devices, along with various facilities, have also invited a series of problems mostly due to the lack of proper management. The Bangladeshi citizens often leave electronic devices that went bad or became unusable, in landfills, rivers, canals, and open spaces. As these devices possess a variety of toxic substances, dumping huge amounts of electronic waste can pollute the environment and threaten human health. Around 2.7 million metric tons of e-waste are generated each year in Bangladesh. Only 20-30% of this waste is recycled while the rest amount is released in landfills, rivers, canals, and open spaces posing a serious threat to the health and environment. Bangladesh has experienced rapid advancement in the technological sectors over the years. Therefore, it is a must to take steps necessary for avoiding the future jeopardized situation because of e-waste. The present e-waste management in Bangladesh experiences a number of drawbacks such as challenges in incentivization, unhygienic conditions of informal recycling, insufficient law and policy, less awareness, and lack of enthusiasm on part of the corporate to address the critical issues. In spite of the alarming levels of e-pollution in the country, the concerned authorities are yet to take any effective step or formulate any legislation to prevent the existing e-pollution. Moreover, the prevailing environmental laws are not adequate to address the issue and its application is still largely absent.

In this study, the removal of nitrogen from effluent of ammonia plant by Chlorella vulgaris and Spirulina platensis was investigated. For this purpose, microalgae were cultivated in three diluting percentage of the wastewater (1, 3, and 5%) at 29±1 ◦C and light intensity at surface of culture were adjusted to 150 µmol photon / (m2. s). The results showed that Spirulina platensis is more capable than Chlorella vulgaris to grow in high levels of total nitrogen concentration. Also, maximum biomass production rate happened in 1% diluted samples for Chlorella vulgaris and 3% for Spirulina platensis. Furthermore, Chlorella vulgaris reduce total nitrogen concentration up to 55%. This value for Spirulina platensis was about 96%. However, for both species the removal of nitrogen in 1% diluted wastewater was maximum. According to the results of diluted wastewater of ammonia plant, it is a suitable culture medium for microalgae and it can be used to remove the nitrogen before entering the wastewater in nature.

Mineralogy studies can help understand the interactions of geographical, environmental, and geological factors. Considering frequent occurrence of urinary tract stones in the south and west of Iran, the present paper examines trace elements, like heavy metals, in 53 urine stone samples collected from patients in Lorestan Province. It investigates the mineralogy of the stones, using X-ray diffraction. The samples are then classified into five mineral groups (calcium oxalate, urate, cysteine, calcium oxalate-urate, and calcium oxalate/phosphate). Results from this analysis are confirmed by SEM images, showing the crystalline form of the mineral phases. The microscopic studies show that only the mineral group of calcium oxalate (whewellite) could be detected in thin sections, prepared from urinary tract stone samples. The main and trace elements in each group are determined through ICP-MS method with the results showing that calcium is the most abundant substance in urinary tract stones, compared to other elements. This is caused by the role of calcium in most basic functions of cell metabolism. The correlation between magnesium and strontium is 0.64, originated from the placement of high amounts of strontium in calcium oxalate minerals. The positive correlation between sodium and calcium also indicates that sodium is replaced by calcium due to the similarity of the ionic radius in the crystal structure. Results from this study can help us find the causes behind the frequent occurrence of urinary tract stones in Lorestan Province.

In current study, the enhanced efficiency of copper (Cu) phytoremediation potential of Calendula officinalis L. was investigated in a Cu-spiked calcareous soil, using foliar and soil application of humic acid. For this purpose, in a greenhouse experiment, seedlings of C. officinalis were transferred to Cu-spiked soils (0, 250 and 500 mg/kg) and treated separately with soil (soil drench) and foliar (spraying plant leaves) humic acid applications at different levels (0, 10, 20 μM). The humic acid treatments were applied 2 weeks after transferring plant, and eventually the various biochemical-physiological traits and phytoremediation indices of Cu in C. officinalis were measured at (specific) time points. According to the results, C. officinalis grew normally without any toxicity signs in Cu-spiked soils, however with increasing the Cu levels, the dry weight biomass decreased and antioxidant enzymes activities increased. Both foliar and soil humic acid application in Cu-spiked soils increased dry weight biomass, photosynthetic pigment contents, Cu concentration, and bioconcentration factor (BCF). Furthermore, the application of this organic substance, obviously moderated the Cu stress since the antioxidant enzymes activities reduced compared to the control. Based on the results, the obtained translocation factor (TF) and BCF values of Cu, which were >1, indicated that this plant is a Cu-hyperaccumulator, which could extract Cu via phytoextraction mechanism. Generally, the results of this study showed that, among the humic acid treatments, application of 20 μM (especially soil drench application) had the best effect on increasing Cu phytoremediation efficiency in the studied soil and it recommended to enhance the efficiency of Cu phytoremediation in calcareous soils.

The Air Pollution Tolerance index (APTI) of six plants located within Ikpoba Okha gas flaring site in Oredo Local Government Area of Edo State, Nigeria during wet and dry seasons were assessed. Plant samples for this research work were randomly collected from the vicinity of the flaring site. Six (6) sample of each plant was used for laboratory analysis. The plant parameters assessed include relative water content (RWC), the ascorbic acid content (AAC), total leaf chlorophyll (TLC) and pH extract of the leaves and were used to compute the Air pollution tolerance indices (APTI). Based on the analyzed result, the RWC in Drypetes leonensis, Ficus exasperata Vahl, Chromolaena odorata (Linn) and Gmelina arborea Roxb. ex Smith   species in dry season were higher than those in wet season. Icacina tricantha showed a relatively high level of acidity when compared to others. A. boonei De Wild has the highest ascorbic acid content in the leaves in both seasons. The highest level of chlorophyll contents was recorded in the dry season with Drypetes leonensis having the highest, followed by Icacina trichantha. There was no statistically significant difference in pH and total chlorophyll contents between samples collected in wet and dry season; however, there were significant difference observed in ascorbic acid and RWC in both seasons. APTI in wet and dry season showed a statistically significant difference. This study recommends planting of tolerant species that can acts as bio-indicators especially in gas flaring stations in Nigeria.

Two lab-scale electrodialysis (RED) stacks with different intermembrane spacing were used in this study. Each stack consists of two membrane pairs. Thick intermembrane spacing stack was made of four identical plexiglass sections, with outer dimensions 5 cm * 5 cm * 1.5 cm and an inner cross-section of 3 cm diameter each to construct two diluted solution compartments and two concentrated solution compartments. For the thin intermembrane spacing configuration, four rubber spacers with a thickness of 1 mm and an inner opening of 3 cm each were used instead of these sections. Two copper sheets were used as anode and cathode electrodes. Different solutions with NaCl concentrations of 15,000, 30,000 and 200,000 mg/l were used as a concentrated solution and different solutions with relatively low NaCl concentrations of 25, 1000 and 3600 mg/l were used as a diluted solution. A 30,000 mg/l NaCl solution was used as a diluted solution when the concentrated stream was with NaCl concentration of 200,000 mg/l. The electrode solution was of 15,000 mg/l (~0.25 M) NaCl and 8,000 mg/l (~0.05 M) CuSO4.5H2O. The results of this study confirmed the validity of using RED technology to harvest energy from salinity gradient using saline and freshwater available abundantly particularly in Iraq. An experiment on a synthetic hypersaline oil field co-produced water as a concentrated stream and seawater as a diluted stream showed that the system performance is reproducible and stable. A maximum power density of 0.029 W/m2 could be harvested.

This research aims at developing a new relation to estimate the urban runoffwater quality through urban land use. According to the first phase of this research, sixurban characteristics and land use indices have been defined concerning all parameterswith either direct or indirect impacts on urban water quality: Population, land use type,meteorological factors, local physiographical parameters, urban patterns etc. have beenconsidered when developing the new indices. Three study areas, including different urbanland uses, have been selected in Tehran Metropolitan and urban drains maps andstructures have gone under study to determine the sampling points. Multi-statisticalanalysis, discriminate analysis, and multi-linear regression analysis have been applied forall water quality results and urban indices in each site, with the results revealing verystrong relations between urban land use and water quality variation. Temporarypopulation especially in downtown site has proved to be an effective temporal factor onhow even public transport could not have any significant effects, in case populationdensity has no significant influence on water quality, as all sanitary waste water inselected sites is collected through urban wastewater systems separately. General slop is asignificant factor in hydrocarbons and heavy metals, once they are not alongside thestreets route. All told, this paper recommends reusing urban drained runoff locally beforejoining other regions’ collectors. Here in urban drainage system, collection andaggregation of water could not be an appropriate factor in water quality managementunlike river systems. The model could be employed in urban local water consumptionmanagement in irrigation and public recovery.