Wastewater Reduction Research Articles

Efficient reduction of Cr(VI) and elimination of total Cr with S-bridged Ni3S2/MoS2 nanowire electrode

Electrochemical reduction of Cr(VI) is eco-friendly and cost-effective for eliminating the environmental risk of Cr-contaminated water. Herein, a novel Ni3S2/MoS2 nanowire electrode with a unique stem-leaf structure was synthesized for this purpose. Self-supported ultra-long Ni3S2 nanowires bearing MoS2 nanoflakes were in-situ grown from Ni foam with a hydrothermal method, in which Ni3S2 and MoS2 grow accompanied with each other by sharing some S atoms. Consequently, highly conductive out-stretched MoS2 nanoflakes wrap the Ni3S2 nanowires, providing aligned pathways for directional electron transfer and huge networks for the efficient reduction of Cr(VI) and high uptake of generated Cr(OH)3. The highest Cr(VI) removal rate attained at − 1.2 V approaches 0.005 mg/cm2 min, and elimination efficiency of total Cr is high up to 90.81 %. Although the adsorbed Cr(OH)3 on Ni3S2/MoS2 decreases the activity after repeated runs, the electrode can be restored by a simple pickling process with dilute acid, which has promising application prospects in the electrochemical reduction of Cr-contained wastewater.

Crop Water Requirement Predication in Automated Drip Irrigation System Using IoT

The project "Crop Water Requirement Prediction in Automated Drip Irrigation System using IoT" aims to develop a system that optimizes water usage in agricultural irrigation by predicting crop water requirements. By employing IoT devices, sensors, and data analytics techniques, the system aims to enhance water efficiency, reduce water waste, and improve crop yield.The system utilizes soil moisture sensors to measure real-time soil moisture levels and collects weather data from external sources. These inputs are processed and analyzed using data analytics techniques to predict crop water requirements based on specific crop information and growth stages. An automated drip irrigation system, controlled by IoT devices, delivers water directly to the plant's root zones based on the predicted water requirements.The project's objectives include evaluating the accuracy of crop water requirement predictions, assessing water savings achieved compared to traditional irrigation methods, and monitoring crop health and yield. The collected data is analyzed to gain insights into irrigation strategies, weather conditions, and resource optimization. The user interface provides a convenient way for farmers to monitor and control the system, ensuring an asvaluable tool for enhancing driver safety.

SnS2-covalent organic framework Z-scheme van der Waals heterojunction for enhanced photocatalytic reduction of uranium (VI) in rare earth tailings wastewater

Uranium removal by photocatalytic reduction is one of the most promising methods to reduce radioactive contamination in wastewater. Herein, a Z-scheme van der Waals heterojunction photocatalyst (SnS2COF) was synthesized in situ by combining covalent organic frameworks (COF) with semiconductor (SnS2) for U (VI) reduction in rare earth tailings wastewater. The synthesis method of van der Waals heterojunction is simple and solves the problem of no hanging bond in composite components. In this heterojunction, large areas of van der Waals interaction form high-speed electron transport channels. In addition, it is deduced that SnS2COF fits the Z-scheme heterojunction electron transport mode through the theoretical calculation of the ground state and excited state electron density difference and the related band structure. Under the photoexcitation, the direction of electron flow is reversed, which further promotes the separation of the photogenerated electron (e−)-hole (h+) under the action of the built-in electric field, maintains the high reducibility of the conduction band, and avoids the photocorrosion of SnS2. Compared with inorganic-inorganic heterojunction, SnS2COF has a wider light absorption range, more active sites, and higher e−-h+ separation and transfer efficiency. Therefore, it had a higher U (VI) reduction removal capacity, up to 1123.3 mg g−1, far surpassing the SnS2 and COF counterparts under ultraviolet/visible light. And the U (VI) removal rate reached 98.5 % in rare earth tailings wastewater. The design concept of organic–inorganic heterojunction materials provides an alternative strategy for improving the photocatalytic performance.

MXene based immobilized microorganism for chemical oxygen demand reduction of oilfield wastewater and heavy oil viscosity reduction to enhance recovery

The high energy consumption drawbacks of thermal recovery of heavy oil are becoming increasingly apparent, contrary to the goal of being green, environmentally friendly and low carbon. In this work, a carrier was designed for the immobilization of Bacillus subtilis using lecithin(PC)-modified magnetized Ti2C3 MXenes (PC-g-Fe3O4/Ti2C3) for heavy oil exploitation, which effectively reduced the chemical oxygen demand (COD) of oilfield wastewater and viscosity of heavy oil. According to orthogonal tests, the ideal temperature for immobilizing Bacillus subtilis was 38 °C, the ideal pH was 7, the desired mineralization was less than 20,000 ppm, the COD removal rate was over 80 %, and the heavy oil's viscosity was reduced by 77.5 %, and the carrier could be recycled and reused. As the results of the displacement experiment showed, the microbial oil drive with the carrier (PC-g-Fe3O4/Ti2C3) could enhance the recovery of heavy oil by 28.39 %, which was due to the reduction of COD and viscosity of the heavy oil in the reinjection water. So, PC-g-Fe3O4/Ti2C3 has excellent potential for use in the oil field because it is very effective, affordable, and ecologically benign.

Reservoir Advanced Process Control for Hydroelectric Power Production

The present work is in the framework of water resource control and optimization. Specifically, an advanced process control system was designed and implemented in a hydroelectric power plant for water management. Two reservoirs (connected through a regulation gate) and a set of turbines for energy production constitute the main elements of the process. In-depth data analysis was carried out to determine the control variables and the major issues related to the previous conduction of the plant. A tailored modelization process was conducted, and satisfactory fitting performances were obtained with linear models. In particular, first-principles equations were combined with data-based techniques. The achievement of a reliable model of the plant and the availability of reliable forecasts of the measured disturbance variables—e.g., the hydroelectric power production plan—motivated the choice of a control approach based on model predictive control techniques. A tailored methodology was proposed to account for model uncertainties, and an ad hoc model mismatch compensation strategy was designed. Virtual environment simulations based on meaningful scenarios confirmed the validity of the proposed approach for reducing water waste while meeting the water demand for electric energy production. The control system was commissioned for the real plant, obtaining significant performance and a remarkable service factor.

Carbon Reduction and Pollutant Abatement by a Bio-Ecological Combined Process for Rural Sewage.

In order to explore the treatment effect of a bio-ecological combined process on pollution reduction and carbon abatement of rural domestic wastewater under seasonal changes, the rural area of Lingui District, Guilin City, Guangxi Province, China was selected to construct a combined process of regulating a pond, biological filter, subsurface flow constructed wetland, and ecological purification pond. The influent water, effluent water, and the characteristics of pollutant treatment in each unit were investigated. The results showed that the average removal rates of COD, TN, and NH3-N in summer were 87.57, 72.18, and 80.98%, respectively, while they were 77.46, 57.52, and 64.48% in winter. There were significant seasonal differences in wastewater treatment results in Guilin. Meanwhile, in view of the low carbon:nitrogen ratio in the influent and the poor decontamination effect, the method of adding additional carbon sources such as sludge fermentation and rice straw is proposed to strengthen resource utilization and achieve carbon reduction and emission reduction. The treatment effect of ecological units, especially constructed wetland units, had a high contribution rate of TN treatment, but it was greatly impacted by seasons. The analysis of the relative abundance of the microbial community at the phylum level in constructed wetlands revealed that Proteobacteria, Acidobacteria, Chloroflexi, Firmicutes, Bacteroidetes, Planctomycetota, and Actinobacteria were the dominant phyla. The relative abundance of microbial communities of Proteobacteria, Chloroflexi, and Acidobacteria decreased to a large extent from summer to winter, while Firmicutes, Bacteroidetes, and Planctomycetota increased to varying degrees. These dominant bacteria played an important role in the degradation of pollutants such as COD, NH3-N, and TN in wetland systems.

Implementation of smart irrigation using IoT and Artificial Intelligence

Water management is crucial for agriculture, as it is the primary source of irrigation for crops. Effective water management can help farmers to improve crop yields, reduce water waste, and increase resilience to drought. This can include practices such as precision irrigation, using sensors and technology to deliver water only where and when it is needed, and conservation tillage, which helps to reduce evaporation and retain moisture in the soil. Additionally, farmers can implement water-saving techniques such as crop selection, crop rotation, and soil conservation to reduce their water use. Thus, studies aimed at saving the use of water in the irrigation process have increased over the years. This research suggests using advanced technologies such as IoT and AI to manage irrigation in a way that maximizes crop yield while minimizing water consumption, in line with Agriculture 4.0 principles. Using sensors in controlled environments, data on plant growth was quickly collected. Thanks to the analysis and training of these data between several models among them, we find the K-Nearest Neighbors (KNN), Support Vector Machine (SVM) and Naive Bayes (NB), the KNN has shown interesting results with 98.4 accuracy rate and 0.016 root mean squared error (RMSE).

Microcontroller-based Sonar Ultrasonic Water Level Control System with Closed-loop Control Approach

This study proposes a microcontroller-based closed-loop water level control system that utilizes a sonar ultrasonic sensor to monitor and regulate water levels in a tank. The system operates by continuously checking the water level in the tank and adjusting the valve’s opening and closure times to maintain the desired water level. The closed-loop control approach employed by the system offers a precise water level control solution that can significantly reduce water waste in water pumping systems. The paper also assesses the theoretical and experimental response of an open-loop water level control system. The findings demonstrate that the closed-loop system outperforms the open-loop system, indicating the effectiveness of the proposed approach in maintaining water levels in a tank. The proposed system is not only applicable to water pumping systems but can also be used to manage the flow of hot and cold water from home water heaters. Additionally, the system can be utilized in various industries that require level or flow control, with particular emphasis on the production of distilled water, juice, and milk.

Technologies to reduce water waste during land leaching and cultivation of industrial crops

More than half of Uzbekistan's irrigated land is saline to some degree. The drying up of the Aral Sea has intensified this process. For many years, chronic salt storms in the northern part of the country have sprayed large quantities of salt onto agricultural land, leading to increased salinization. These processes cause the water required to flush saline soils year after year. The problem is exacerbated by water shortages worldwide, including in Central Asia. This requires the leaching of saline soils and a multiplication of the water used in crop cultivation. Therefore, alternative use of water resources in our country is one of the most important issues for agriculture. The introduction of salt leaching and cultivation in farms based on outdated technologies and the low efficiency of new technologies (bio-solvent washing, etc.) in the production of new salt leaching and cultivation remain a negative obstacle for the economic development of farms and the country as a whole. The analysis shows that in our country, billions of cubic meters of water are used to flush saline soils and cultivate agricultural crops. Still, only 60% of this water reaches the fields where crops are grown, while the rest of it disappears into the irrigation systems and irrigation processes (canals, ditches, and branch lines). When providing water resources for soil salinization and cultivation using trapezoidal canals, part of the water flowing through them dissolves and filters the mineral and organic fertilizers in the soil due to air pressure and gravity; as a result, up to 30% of water is lost (wasted). In this paper, the water resources for soil washing and crop cultivation are replaced by a parabolic excavator with a trapezoidal boom, designed to save up to 30% of water resources.

Domestic wastewater reduction using constructed wetlands

Domestic wastewater is household liquid waste that comes from sinks, bathrooms, and wastewater from washing machines. In Johan Pahlawan Sub-district, West Aceh District, the community and government's concern is still low towards achieving environmental health where the coverage of wastewater management has not been optimized. This is shown by people who do not manage wastewater properly. One of the alternative domestic wastewater management technologies is the concept of constructed wetlands with phytoremediation techniques. This study aims to determine the efficiency of reducing wastewater concentrations using phytoremediation with Eichhornia Crassipes plants, Pandanus amaryllifolius plants and Scirpus grossus plants. After the phytoremediation process with the concept of CWs-SF and CWs-SSF, it shows that the use of pandanus has not been effective in reducing contaminant levels in domestic wastewater. While Eichhornia Crassipes and Scirpus grossus plants are much better at reducing wastewater concentrations. The efficiency of reducing BOD values with a contact time of 3 to 9 days can reduce BOD levels by 80%-91%, COD and TSS can reduce the wastewater to 89%-90%, the temperature of the wastewater has been qualified with Eichhornia Crassipes and wlingen plants with 290C, and the pH of the wastewater has increased to 7.5-8.

Research on the Impact of Economic Financialization on Pollution Reduction – Analysis Based on Panel Data of 285 Prefecture-level Cities

As the core content of green China construction, pollution reduction plays an important role in achieving high-quality development. This paper mainly explores the pollution reduction effect of finance in the process of increasing the status of the national economic system, and verifies the indirect role of innovation-driven development in the relationship between economic financialization and pollution reduction. The results show that economic financialization has a significant direct impact on the emission reduction of industrial wastewater and sulfur dioxide, especially in cities with a high degree of financialization. Subsequently, the sample data transformation and the robustness test of green credit policy further support the above conclusions. At the same time, urban innovation capacity has a partial indirect effect on the pollution reduction of economic financialization, while robot use only has an indirect effect on the sulfur dioxide reduction of economic financialization. This study provides a theoretical basis for promoting wider and deeper development of green finance.

Ammonia-Nitrogen Reduction in Low Strength Domestic Wastewater by Polyvinyl Alcohol (PVA) Gel Beads

This study aimed to evaluate the efficacy of polyvinyl alcohol (PVA) gel beads as an immobilized biofilm carrier to enhance the reduction rate of Ammonia-Nitrogen (NH3-N) and Chemical Oxygen Demand (COD) in domestic wastewater. Laboratory scale reactors were developed to assess the reduction levels of ammonia-nitrogen and COD with and without PVA gel beads using optimal and non-optimal treatment mode settings based on operation procedures from the sewage treatment plant in Taman Kajang Utama, Selangor. The treatment method used is an activated sludge sequencing batch reactor with a treatment cycle duration of 288 minutes. The findings showed the ammonia-nitrogen reduction by non-optimal treatment mode is more effective, with a reduced rate of 62.96% to 65.71% compared to optimal treatment mode with a reduced rate of 30.94% and treatment without PVA gel beads (optimal and non-optimal) with a reduced rate of 32.41% to 47.85%. The ammonia-nitrogen reduction rate using PVA gel beads for non-optimal treatment mode was significantly increased from 17.86% to 18.82% and complied with ammonia-nitrogen reduction parameter 10mg/L, Standard A of Environmental Quality (Sewage) Regulations 2009 (EQSR 2009). The rate of COD reduction using the non-optimal treatment mode was also more stable, with a reduced rate of 70.68%. It was also found that the COD reduction rate using PVA gel beads for the non-optimal mode was better than the optimal mode, which was 70.68% compared to 42.0%, and both treatment modes complied with COD reduction parameters 120mg/L, Standard A of EQSR 2009.

Physico-Chemical and Heavy Metal Valences Reduction of Wastewater from The Beverage Industry by Fungi (Penicillium Sp)

This work aimed to characterize beverage wastewater generated in the beverage industry and to assess wastewater treatment plant performance by fungi (Penicillium sp.) and the feasibility of wastewater reuse. Freshly discharged beverage wastewater was collected and analyzed for the physicochemical parameters such as Biological Oxygen Demand (BOD), Chemical Oxygen Demand (COD), Total Dissolved Solid (TDS), Nitrate, Phosphate, Magnesium, Calcium, Iron, Copper, and Zinc by standard methods. At a 7-day interval, 190ml of the sterilized local dye wastewater was inoculated with Penicillium sp. for two weeks, and the physicochemical parameters were determined. The results observed for raw, bio-treated and removal efficiency showed: BOD (280 mg-1, 255 mg-1 , 108 mg-1 and 19.64 %, 61.43 %); COD (540 mg-1, 420 mg-1, 285 mg-1 and 43.75%, 88.13%); Nitrate (130 mg-1, 90 mg-1, 25 mg-1 and 30.77%, 80.77%); Phosphate (48 mg-1, 25 mg-1, 5 mg-1 and 30.91%, 78.18%); Calcium (55 mg-1, 38 mg-1, 12 mg-1 and 30.91%, 78.18%); Iron (29 mg-1, 18 mg-1, 07 mg-1 and 37.93 %, 75.86 %); Copper (0.09 mg-1, 0.07 mg-1, 0.02 mg-1 and 22.22 %, 77.78 %); Zinc (0.08, 0.06, 0.03 mg-1 and 22.5%). Fungi (Penicillium sp.) demonstrated the ability to remove pollutants and other wastes from beverage wastewater. These results indicate that some companies employing treatment methods for their effluents do not remove the parameters and heavy metals.

Study of Organic Acid Pollutant Removal Efficient in Treatment of Industrial Wastewater with HDH Process Using ASPEN Modelling

Due to low efficiency and the material choice limitations of traditional evaporation systems to treat acid wastewater, humidification and dehumidification (HDH) as the core process was applied in the treatment and reduction of wastewater with organic acid pollutant concentrations. The forecasting of pH changes and COD reduction is important for the system’s design. Therefore, a study of the pollutant removal efficiency with different parameters, such as the reaction temperature, air quantity, and flow rate was conducted with ASPEN modeling. In this article, ASPEN modeling was used to simulate the water and acid material transformation in HDH system. The process was composed of blocks, such as RadFrac, heater and split. The analysis was taken with different air quantities, tower diameters, heat loads and flow rates. The analysis indicated that the pH of the maleic acid wastewater changed from 3.0 to 5.7. The relationship between inlet quantity, air quantity, inlet heat and the clean water yield was also shown in the modeling results. Based on these studies, we determined that the model can help engineers solve the key problems of HDH systems, such as heat balance calculation, equipment selection, and the prediction of incoming and outgoing evaporation materials.

A novel process for simultaneous biological nutrient removal and waste activated sludge reduction in one-stage system without aeration

This study presented a novel process for simultaneous biological nutrient removal and waste activated sludge reduction in one-stage municipal wastewater treating system without aeration on the basis of endogenous partial denitrification, anammox and Candidatus Phosphoribacter dominated biological phosphate removal with sludge reduction (EPDA/PSR). The effluent total inorganic nitrogen and phosphate concentrations were 0.1 mg/L and lower than detection limit (0.1 mg/L), respectively, without dosing external carbon sources. Compared with partial denitrification-anammox process, the daily sludge production in EPDA/PSR process reduced by 50.8 %. The percentage of intact cells measured by flow cytometry reduced from 92.4 % to 77.3 % with the increase of aromatic protein, DNA content of supernatant, soluble microbial byproduct-like substance and decline of particle size. The sludge stabilization structure was destructed, and intracellular organics were released, which resulted in the reduction of sludge production. Microbial community structure at transcriptional level indicated that really working Candidatus Phosphoribacter (phosphorus accumulating organisms with fermentation capacity), Candidatus Competibacter (endogenous partial denitrification bacteria) and Candidatus Brocadia (anammox bacteria) reached 68.4 %, 9.84 % and 8.02 %, respectively, and Candidatus Kuenenia (anammox bacteria) did not play a role in EPDA/PSR system. The novel one-stage EPDA/PSR process realized high efficient biological nutrient removal, achieved waste activated sludge reduction and saved 100 % of aeration energy consumption cost and external carbon source dosage cost, which effectively developed internal carbon source and provided a new idea for wastewater treatment.

Removal of Antibiotic Resistance Genes, Class 1 Integrase Gene and Escherichia coli Indicator Gene in a Microalgae-Based Wastewater Treatment System.

Microalgae-based wastewater treatment systems (AWWTS) have recently shown promise in the mitigation of antibiotic resistance genes (ARGs) from municipal wastewater (MWW). However, due to the large number of ARGs that exist in MWW, the use of indirect conventional water quality parameters to monitor ARGs reduction in wastewater would make the process less burdensome and economically affordable. In order to establish a robust relationship between the ARGs and water quality parameters, the current study employed different microalgae strains in monoculture (CM2, KL10) and multi-species combinations (CK and WW) for the MWW treatment under outdoor environmental conditions. The studied genes were quantified in the MWW influents and effluents using real-time PCR. All the cultures substantially improved the physicochemical qualities of the MWW. Out of the 14 genes analyzed in this study, tetO, tetW, tetX and ermB were decreased beyond detection within the first 4 days of treatment in all the cultures. Other genes, including blaCTX, sul1, cmlA, aadA, int1 and uidA were also decreased beyond a 2 log reduction value (LRV). The mobile genetic element, int1, correlated positively with most of the ARGs, especially sul1 (r ≤ 0.99, p < 0.01) and aadA (r ≤ 0.97, p < 0.01). Similarly, the Escherichia coli indicator gene, uidA, correlated positively with the studied genes, especially with aadA, blaCTX, blaTEM and cmlA (r ≤ 0.99 for each, p < 0.01). Some of the studied genes also correlated positively with total dissolved solids (TDS) (r ≤ 0.98, p < 0.01), and/or negatively with total suspended solids (TSS) (r ≤ -0.98, p < 0.01) and pH (r ≤ -0.98, p < 0.01). Among the tested cultures, both monocultures, i.e., KL10 and CM2 were found to be more consistent in gene suppression than their multi-species counterparts. The findings revealed water quality parameters such as TDS, TSS and E. coli as reliable proxies for ARGs mitigation in AWWTS and further highlight the superiority of monocultures over multi-species cultures in terms of gene suppression from the MWW stream.

Wastewater-based epidemiological investigation of SARS-CoV-2 in Porto Alegre, Southern Brazil

Wastewater-based epidemiology (WBE) may be successfully used to comprehensively monitor and determine the scale and dynamics of some infections in the community. We monitored severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) RNA in raw wastewater samples from Porto Alegre, Southern Brazil. The samples were collected and analyzed every week between May 2020 to May 2021. Meanwhile, different social restrictions were applied according to the number of hospitalized patients in the region. Weekly samples were obtained from two wastewater treatment plants (WWTP), named Navegantes and Serraria. To determine the SARS-CoV-2 RNA titers in wastewater, we performed RT-qPCR analysis targeting the N gene (N1). The highest titer of SARS-CoV-2 RNA was observed between epidemiological weeks (EWs) 33–37 (August), 42–43 (October), 45–46 (November), 49–51 (December) in 2020, and 1–3 (January), 7–13 (February to March) in 2021, with viral loads ranging from 1 × 106–3 × 106 genomic copies/Liter. An increase in positive confirmed cases followed such high viral loads. Depending on the sampling method used, positive cases increased in 6–7 days and 15 days after the rise of viral RNA titers in wastewater, with composite sampling methods showing a lower time lag and a higher resolution on the analyses. The results showed a direct relation between strict social restrictions and the loads of detected RNA reduction in wastewater, corroborating the number of confirmed cases. Differences in viral loads between different sampling points and methods were observed, as composite samples showed more stable results during the analyzed period. Besides, viral loads obtained from samples collected at Serraria WWTP were consistently higher than the ones obtained at Navegantes WWTP, indicating differences in local dynamics of SARS-CoV-2 spread in different regions of Porto Alegre. In conclusion, wastewater sampling to monitor SARS-CoV-2 is a robust tool to evaluate the viral loads contributing to hospitalized patients’ data and confirmed cases. In addition, SARS-CoV-2 detection in sewage may inform and alert the government when there are asymptomatic or non-tested patients.

Comparison of Four Plant-Based Bio-Coagulants Performances against Alum and Ferric Chloride in the Turbidity Improvement of Bentonite Synthetic Water

Due to their cost-effectiveness, low toxicity, and naturally renewable properties, bio-coagulants for water treatment are gaining popularity. In this context, four bio-coagulants were tested for their ability in turbidity reduction in a synthetic bentonite suspension: Opuntia ficus indica (OFI) and Moringa oleifera (MO) seeds, two well-established vegetal materials in the domain of bio-coagulation, and Algerian Aloe vera (AV) and Pinus halepensis seeds (PHS), both of which have received very few or no study in turbidity reduction in water and wastewater. A comparative study was conducted with regard to two well-known inorganic coagulants, ferric chloride and Alum. Extraction salts, pH, coagulant dose, initial turbidity, and aging effects were examined. When compared to chemical coagulants, the four bio-coagulants worked very well, removing approximately 100% of the turbidity at natural pH of 7.5 using optimal doses of 1.5, 3, 3, 3.5, 1.5, and 1.5 mL/200 mL for AV, OFI, MO, PHS, Alum, and FeCl3, respectively, at a broad range of pH (2 to 8), and causing no pH alteration of the treated water. Polysaccharides and proteins involved in inter-particle bridging and charge neutralization may be the active coagulation-flocculation molecules. The four bio-coagulants produced less sludge amount than Alum and Ferric chloride. This research not only shows that MO and OFI are effective in eliminating turbidity, but it also highlights the great potential of Algerian AV and PHS seeds as promising bio-coagulants in the treatment of polluted water.

Characterization of Pseudochloris wilhelmii potential for oil refinery wastewater remediation and valuable biomass cogeneration

The microalgae of the genus Pseudochloris/Picochlorum are characterized by fast growth, and wide nutrient (type and concentration) and salinity tolerance, all contributing towards exploration of their use in high-density biomass production and wastewater bioremediation. In this study, removal of nitrogen and phosphorus nutrients from oil refinery wastewater was monitored during growth of the marine eukaryotic microalgae Pseudochloris wilhelmii, with emphasis on biochemical analyses of its biomass quality to evaluate suitability for biodiesel production. A series of growth experiments under various nutrient and light regimes were performed in a temperature range of 20-30°C to evaluate nutrient removal and biomass growth dependence on temperature. The highest removal rate of dissolved inorganic nitrogen reached under the given experimental conditions was 0.823 mmol/(gday) accompanied by the corresponding biomass productivity of 115.2 mg/(Lday). Depending on light and temperature, the final lipid concentration ranged 181.5 – 319.8 mg/L. Furthermore, increase in nutrient load decreased the maximum specific growth rate by 25%, and the maximum specific removal rate of the dissolved inorganic nitrogen by 19%, whereas the duration of bioremediation process was nearly doubled. In contrast, constant light exposure expedited the nitrogen removal, i.e. bioremediation process, by almost 40%, while supporting over three times higher biomass productivity and the highest maximum specific growth rate of 0.528 g/(gday). The conditions favoring the highest nitrogen removal and highest toxicity reduction in oil refinery wastewater are met at 24°C and 130 µmol phot/(m2s). The highest proportion of carbon-binding to the P. wilhelmii biomass was noticed under the same conditions, thus indicating them as the most favorable conditions for hydrocarbon removal as well as for CO2 sequestration. Pseudochloris wilhelmii therefore represents a promising candidate for oil refinery wastewater remediation and valuable biomass cogeneration on a large-scale.

Automated Irrigation for Smart Gardening based on IOT using sensors

The external need of every person in this world is oxygen. Plants play a vital role in maintaining the carbon dioxide and oxygen content of the air. A lot of plants are destroyed every day due to the urbanization process. The number of plantings made will also decrease. In addition to these things, more plants die due to a lack of maintenance. Smart gardening represents the application of modern information and communication technologies to planting. It automatically checks the soil moisture under the tree and plants in the garden and if the moisture is low, it displays a message and automatically pours water to the plants from the water tank to which it is connected. Precise application of the irrigation method is required as there may be a lack of rainfall or there may be dry areas. For this reason, an automated irrigation system is used, which it is suitable for all climatic conditions. The soil moisture sensor will sense the water content and indicate whether to pump water or not. This will help reduce water wastage and also help plant growth even when one is not physically present. Internet of Things (IoT) enables various plant monitoring and selection applications, automatic irrigation decision support, etc. sensor data related to soil moisture and temperature captured and accordingly KNN (K-Nearest Neighbor) classification machine learning algorithm deployed to analyze sensor data for prediction to irrigate the soil with water. It is a fully automated system where devices communicate with each other and use intelligence during irrigation. The main goal of this project is to preserve the nature of plants by constantly monitoring the parameters leading to an increase in the life of plants and humans.