Effects Of Water Quality Parameters Research Articles

Effect of water quality parameters and climatic influences on reproductive phenology of Macrognathus pancalus in wetland ecosystem: recommending a long-term management approach and conservation policy.

The study conducted an investigation into the reproductive biology of M. pancalus and assessed the influence of water quality parameters and environmental factors on the spawning pattern within the Gajner Beel ecosystem in Bangladesh. A total of 1218 individuals of M. pancalus (46.39% males and 53.61% females) were collected monthly from the Gajner Beel during January to December 2018 using various fishing gears. The total length (TL) of each individual was measured using digital slide calipers, and the whole body weight (BW) was measured using an electronic balance. Fulton's conditions factor (KF) showed significant differences between males and females. The calculated Lm were 11.11 cm, 11.30 cm, and 11.10 cm based on maximum length, gonadosomatic index (GSI), and the logistic model. The spawning season extended from May through August, with June and July being peak months. The average total fecundity was 1495.52 ± 840.24, with a range of 370 to 4069. During peak spawning season, the average temperature and rainfall were 27°C and 370 mm, respectively. Rainfall, dissolved oxygen, total alkalinity, and pH all had a significant (p < 0.01) positive effect whereas temperature and TDS all had a significant (p > 0.01) negative effect on GSI. Annual air temperature in the study area increased by 0.053 °C/year, with a regression coefficient value (r2 = 0.1695), while annual mean rainfall decreased by 5.97mm/year (r2 = 0.076). This research will contribute to the development of conservation and management approaches of Mastacembelidae fish in relation to current climate variability in sub-tropical waters.

Use of random forest for assessing the effect of water quality parameters on the biological status of surface waters

The Water Framework Directive aims to reach good status in European surface waters by 2027. Despite the efforts taken already, the ecological status of surface waters has hardly improved during the last decades. In order to find efficient measures, there is an urgent need to improve our knowledge in understanding the linkage between the anthropogenic factors and the indicators of the ecological status assessment. Due to the complexity of the ecosystems, basic statistical methods (such as linear regression) cannot help in finding relationships between the biological quality elements and the supporting water chemistry parameters. The paper demonstrates that in these cases a machine learning data-driven method can be a promising tool for supporting biological classification. With random forest, the Gini index was used for ranking physico-chemical variables based on their influence on biological elements. Variables that have the biggest Gini index were selected for predicting the biological status of phytoplankton, phytobenthos and macrophytes. Binary classification and predictions were performed on a five-class scale. Predictions tended to be fairly good (errors varied within 8–60%, median 33.3%). A comparative analysis was also made with logistic regression, however, in some cases it led to slightly worse or slightly better predictions. We concluded that due to significant errors, the biological status assessment cannot be replaced completely by model predictions, but the method is sufficient to fill in certain gaps in the data and can help in the planning of biological monitoring systems. The evaluation was performed with Hungarian river and water quality database.

The effects of water quality parameters, water level changes, and mixing on zooplankton community dynamics in a tropical high-mountain Lake Ardibo, Ethiopia.

The diversity and abundance of the zooplankton community are affected by changes in physico-chemical parameters, trophic interactions, water level changes, and periodic mixing. In this study, the influence of environmental variables, water level changes, and periodic mixing on zooplankton distribution and abundance was seasonally studied for Lake Ardibo from October 2020 to September 2021 collected from 3 sites. Results on the physico-chemical variables indicated that all variables, except turbidity, varied significantly (p < 0.05) in all sampling seasons. A total of 33 zooplankton species were recorded, comprising 18 rotifers, 11 cladocerans, and 4 cyclopoid copepods. Zooplankton abundance significantly varied seasonally with peak abundance (4232.13 ind. L-1) recorded in the dry season and lowest numbers (402.42 ind. L-1) during the long rainy period. Redundancy analysis (RDA) results indicated that total phosphorus, ammonia, water temperature, silicon dioxide, and conductivity were the most significant driving forces for the seasonal successions in the abundance and distribution of zooplankton communities. Cyclopoid copepod abundance was significantly (p < 0.05) higher in the dry season, which could be correlated with the partial mixing (atelomixis) phenomenon that occurred during the dry period.

Effects of Phosphate-Enriched Nutrient in the Polyculture of Nile Tilapia and Freshwater Prawn in an Aquaponic System

Aquaponic systems are made up of hydroponic beds and recycled aquaculture systems. The significant elements that determine how effectively an aquaponic system operates are the nitrogen cycle (nitrification) and the phosphorus cycle (phosphate). Because some research indicates that aquaponics systems are primarily deficient in phosphorus, phosphate-enriched nutrients were added to raise the phosphorus levels. During an eight-week experimental period, the effects of water quality parameters and microbiology, animal and plant growth performance, chlorophyll compounds in lettuce, and the bacterial community were analyzed. Phosphate concentration (1.604 ± 1.933 mg L−1) and ammonia-oxidizing bacteria (AOB) (1.19 × 102 ± 1.30 CFU mL−1) give significant positive reactions to the added nutrients. However, the prawn survival rate (17.00 ± 0.63%) showed a significantly negative response to nutrition modification containing phosphate, and the percentage of bacterial pathogens became more dominant (pathogen 40.51%; N_bacteria 35.05%; probiotics 24.44%). This study shows that adding phosphate increases phosphorus levels in an aquaponics system and changes the microbial community and species growth performance.

Development of a quality-based irrigation water security index

This paper introduces a new concept for water security, the Irrigation Water Security Quality-based Index. Through this concept, the irrigation water security is presented based on quantity and quality. The effect of water quality parameters on agriculture productivity, soil deterioration, and public health was evaluated. The probability of harm was used in the risk analysis and assessment. The developed index was applied to evaluate the Egyptian irrigation system, 10% reduction in the Nile’s supply, and four adaptation scenarios as an illustrative example. Drainage water reuse is adopted in Egypt to provide a sufficient supply and improve the water security. However, this improved water security doesn’t consider the water’s quality. The current Egyptian condition and 10% Nile reduction showed water insecurity. Expanding drainage and sewage water treatment improved the developed index to high security levels. This highlights the importance of drainage water treatment in attaining a sustainable high water security level.

Temporal patterns of algae in different urban lakes and their correlations with environmental variables in Xi'an, China

Urban lakes were critical in aquatic ecology environments, but how environmental factors affected the distribution and change characteristics of algal communities in urban lakes of Xi'an city was not clearly. Here, we investigated the algal community structure of six urban lakes in Xi'an and evaluated the effects of water quality parameters on algae. The results indicated that the significant differences on physicochemical parameters existed in different urban lakes. The maximum concentration of total phosphorus in urban lakes was (0.18 ± 0.01) mg/L and there was a phenomenon of phosphorus limitation. In addition, 51 genera of algae were identified and Chlorella sp. was the dominant algal species, which was affiliated with Chlorophyta. Network analysis elucidated that each lake had a unique algal community network and the positive correlation was dominant in the interaction between algae species, illustrating that mature microbial communities existed or occupied similar niches. Redundancy analysis illustrated that environmental factors explained 47.35% variance of algal species-water quality correlation collectively, indicating that water quality conditions had a significant influence on the temporal variations of algae. Structural equation model further verified that algal community structure was directly or indirectly regulated by different water quality conditions. Our study shows that temporal patterns of algal communities can reveal the dynamics and interactions of different urban ecosystem types, providing a theoretical basis for assessing eutrophication levels and for water quality management.

Spatial and temporal dynamics of actinobacteria in drinking water reservoirs: Novel insights into abundance, community structure, and co-existence model

The control of taste and odor (T&O) in drinking water reservoirs is the main challenge for water supply. T&O is mainly derived from actinobacteria during non-algal blooms. However, few studies have investigated the actinobacterial community in reservoirs, especially the effects of water quality parameters on actinobacteria. This study analyzed the environmental driving force of the actinobacterial community composition and change in time and space through structural equations and network in drinking water reservoirs. The results showed a high abundance of actinobacteria, up to 2.7 × 104 actinobacteria per 1 L, in the hypolimnion of the Lijiahe reservoir in September, which is one order of magnitude greater than that in the Jinpen reservoir. The two drinking water reservoirs had similar dominant genera, mainly Sporichthya sp., and Mycobacterium sp., and difference in the actinobacterial proportions. However, there was a large difference at the dominant species. Rhodococcus fascians (4.02%) was the dominant species in the Lijiahe reservoir, while Mycobacterium chlorophenolicum (6.64%) was the dominant species in the Jinpen reservoir. Network analysis revealed that the structure of the network in the Lijiahe reservoir was more unstable; thus, it was vulnerable to environmental disturbances. In addition, a low abundance of species may play a critical role in the actinobacterial community structure of aquatic ecosystems. Structural equation modeling analysis suggested that water temperature, dissolved oxygen, and nutrition were the dominant factors affecting the abundance and community of actinobacteria. Overall, these findings broaden the understanding of the distribution and co-existence of actinobacterial communities in drinking water reservoirs and provide valuable clues for the biological controls of T&O and reservoir management.

Optimization of Bi2O3/TS-1 preparation and photocatalytic reaction conditions for low concentration Erythromycin wastewater treatment based on artificial neural network

At present, it is a challenge to degrade antibiotics of low concentrations in wastewater environment, highly effective and eco-friendly photocatalytic processes were considered promising technologies for this degradation. In this work, Bi2O3-loaded titanium silicalite-1 molecular sieve (Bi2O3/TS-1) composites were prepared and used to degrade low-concentration erythromycin (ERM) in wastewater. The content of active components and the dose of photocatalyst are key operating parameters with major effects on photocatalytic efficiency. The optimal parameters (Bi content and photocatalyst dose) were determined through artificial neural network simulating the relationship between key operating parameters and removal efficiency (RE). The maximum RE (98.02%) was measured under optimal operating parameters (Bi % = 5.5%, catalyst dosage = 0.6 g/L). The effects of water quality parameters (such as pH and ERM concentration) were also studied under optimal experimental conditions. Artificial intelligence was used in this work to achieve optimal control of catalyst preparation and photocatalytic reaction conditions. This study provides a useful strategy for the preparation of nanocatalysts and the practical application of high-efficiency photocatalytic reactions.

Influence of water quality parameters on the removal of triclosan and ibuprofen in vertical subsurface flow constructed wetlands using multivariate analysis

The main objective of this study was to apply multivariate analysis, such as principal component analysis (PCA), to determine the influence of water quality parameters on the removal of triclosan (TCS) and ibuprofen (IB) in vertical subsurface flow constructed wetlands (VSSFs). For this purpose, two VSSFs were operated under TCS and IB concentrations of 10 μg/L. One VSSF system was planted with Agapanthus africanus and the other was left unplanted and used as a control. To determine the influence of water quality parameters on TCS and IB removal, the removal efficiencies for TCS, IB, organic matter and nutrients in VSSF systems were determined. Using these data, PCA was performed. The TCS and IB removal efficiencies in VSSF systems were found to vary between 60%–85% and 50%–84%, respectively. Regarding the effects of water quality parameters on TCS and IB removal, PCA showed that TCS removal has a strong association with the oxidation–reduction​ potential. This result confirms that aerobic conditions for VSSF systems promote the removal of the TCS compound. For the case of IB, an association between IB and biological oxygen demand removal was observed. However, this relation was found to be not significant. This study reveals that PCA allows us to determine the association between different variables in VSSF systems. Moreover, this work will serve as the basis for future research for optimizing the performance for removing TCS and IB by focusing on the improvement of aerobic conditions.

Effects of humic acid on the nitrogen utilization efficiency and microbial communities in aquaponic systems

Aquaponic systems consisting of recirculating aquaculture systems and hydroponic beds. Raft-floating aquaponics integrated with a moving-bed biofilm reactor (MBBR) was established. Humic acid (HA) was added to the aquaponic systems to promote nutrient recovery. An elementary analyzer was used to determine the nitrogen content of fish, plants, and sediments to calculate the NUE. High-throughput sequencing and quantitative polymerase chain reaction (qPCR) were conducted to reveal the influence of HA on microbial communities and nitrification genes. During an 80 day experimental period, the effects of water quality parameters, nitrogen utilization efficiency (NUE), and microbial communities in variable concentrations of HA-based aquaponic systems were compared. Among the HA-based systems, the one with an optimal concentration of 15 ppm indicated the best performance. In HA-based aquaponic systems with 15 ppm concentration, the maximum concentrations of total ammonia nitrogen and NO2−–N were 6.02 mg/L and 12.693 mg/L, which were significantly lower than those in aquaponic systems with 0 ppm and 30 ppm. However, the accumulation of nitrate in the HA-based aquaponic systems with 15 ppm was greater than that in the others. The NUE of the 15 ppm HA-based aquaponic system was 58.34%, which was significantly higher than that of the 0 ppm (50.83%) and the 30 ppm (47.25%) systems. Consequently, the threshold concentration of HA was established as 15 ppm. The microbial communities of different HA-based systems revealed the presence of denitrifying and nitrifying microbial populations for nitrogen recovery in moving bed biofilm reactors (MBBRs); higher levels of these microbial populations thrived in the 15 ppm HA system than in the other systems. However, there was no significant difference in microbial communities from root samples. The highest copies of amoA and nxrB were found at 15 ppm for both MBBRs and roots, indicating that the addition of HA to the aquaponic systems yielded more products and improved water quality and NUE by changing the composition of microbial communities based on the threshold for HA input concentration. This study provided that HA show enormous potential for an interesting research and the development of green technologies for biological wastewater treatment and bioremediation.

The formation kinetics and control of biofilms by three dominant fungi species isolated from groundwater

Filamentous fungi can enter drinking water supply systems in various ways, and exist in suspended or sessile states which threatens the health of individuals by posing a high risk of invasive infections. In this study, the biofilms formation kinetics of the three genera of fungal spores, Aspergillus niger (A. niger), Penicillium polonicum (P. polonicum) and Trichoderma harzianum (T. harzianum) isolated from the groundwater were reported, as well as the effects of water quality parameters were evaluated. In addition, the efficiency of low- concentrations of chlorine-based disinfectants (chlorine, chlorine dioxide and chloramine) on controlling the formation of fungal biofilms was assessed. The results showed that the biofilms formation of the three genera of fungi could be divided into the following four phases: induction, exponential, stationary and sloughing off. The optimum conditions for fungal biofilms formation were found to be neutral or weakly acidic at 28 °C with rich nutrition. In fact, A. niger, P. polonicum, and T. harzianum were not observed to form mature biofilms in actual groundwater within 120 hr. Carbon was found to have the maximum effect on the fungal biofilms formation in actual groundwater, followed by nitrogen and phosphorus. The resistance of fungal species to disinfectants during the formation of biofilms decreased in the order: A. niger > T. harzianum > P. polonicum. Chlorine dioxide was observed to control the biofilms formation with maximum efficiency, followed by chlorine and chloramine. Consequently, the results of this study will provide a beneficial understanding for the formation and control of fungal biofilms.

Linking environmental with biological data: Low sampling frequencies of chemical pollutants and nutrients in rivers reduce the reliability of model results

Linking environmental and biological data using ecological models can provide crucial knowledge about the effects of water quality parameters on freshwater ecosystems. However, a model can only be as reliable as its input data. Here, the influence of sampling frequency of temporal variable environmental input data on the reliability of model results when linked to biological data was investigated using Threshold Indicator Taxa Analysis (TITAN) and species sensitivity distributions (SSDs). Large-scale biological data from benthic macroinvertebrates and matching water quality data including four metals and four nutrients of up to 559 site-year combinations formed the initial data sets. To compare different sampling frequencies, the initial water quality data sets (n = 12 samples per year, set as reference) were subsampled (n = 10, 8, 6, 4, 2 and 1), annual mean values calculated and used as input data in the models. As expected, subsampling significantly reduced the reliability of the environmental input data across all eight substances. For TITAN, the use of environmental input data with a reduced reliability led to a considerable (1) loss of information because valid taxa were no longer identified, (2) gain of unreliable taxon-specific change points due to false positive taxa, and (3) bias in the change point estimation. In contrast, the reliability of the SSD results appeared to be much less reduced. However, closer examination of the SSD input data indicated that existing effects were masked by poor model performance. The results confirm that the sampling frequency of water quality data significantly influences the reliability of model results when linked with biological data. For studies limited to low sampling frequencies, the discussion provides recommendations on how to deal with low sampling frequencies of temporally variable water quality data when using them in TITAN, in SSDs, and in other ecological models.

Effects of water quality on phytoplankton biomass in Balu river, Dhaka, Bangladesh

The Balu River is a peripheral river of Dhaka Metropolis and like other rivers its water quality is also highly vulnerable towards pollution. In the present study, effects of water quality parameters on the phytoplankton biomass have been studied for six climatic seasons of the year. The results obtained were compared with two other rivers of Dhaka Metropolis namely, Buriganga and Turag. Balu River showed water quality characters almost comparable with two other rivers. The phytoplankton biomass as chlorophyll a (chl-a) was found to be correlated directly with air and water temperature and alkalinity of the water. However, a weak positive correlation was obtained between chl-a and Secchi depth and free CO2 concentration. Nitrate nitrogen showed weak negative correlation with chl-a and phaeopigment and phytoplankton total density. High fluctuation was observed in the concentration of DO (0.20 - 4.50 mg/l) and free CO2 (0.06 - 2.90 mg/l) throughout the seasons. Soluble reactive phosphorus ranged from 30 - 1248 μg/l and chl-a ranged from 6.77 - 32.60 μg/l. Phytoplankton density ranged 1178 - 7409×103 ind./l over the study year. Water color ranged from light blue to dark black. The depth of visibility as Secchi depth varied from 15.24 - 81.28 cm whilst the water depth of the studied station Paschim Gaon of Balu River ranged from 4.57 - 7.92 m. Air and water temperature ranged from 25.4 - 36.5°C and 23.4 - 32.3°C, respectively.&#x0D; J. Biodivers. Conserv. Bioresour. Manag. 2020, 6(1): 37-46

The performance of Chlorella vulgaris growth on mass-scale cultivation

Phytoplankton have many benefits, including as a primary producer, natural food, bioindicator, and water pollution treatment. For this reason, their availability needs to be managed, one of which is through cultivation. The purpose of this study was to analyze the mass scale cultivation of Chlorella vulgaris. The research was conducted at the Technical Implementation Unit of Freshwater and Brackish Water Aquaculture, Situbondo, using a descriptive method. The data were analyzed statistically using MS. Excel 2016 software, and a multiple linear regression test was carried out to determine the effect of water quality parameters on the growth of C. vulgaris using the SPSS 16.0 application. The cultivation process started from strain preparation, water preparation, tank and culture media preparation, inoculation, fertilization, and then harvesting. The initial density of C. vulgaris used was 145x104 Cell. mL-1 in tank 1 and 188x104 Cell. mL-1 in tank 2. The results showed that the cell density value of C. vulgaris increased every day until it entered the exponential phase, namely on the 4th day of the culture activity, which was 507 x 104 in tank 1 and 536 x 104 Cell. mL-1 in tank 2. Furthermore, the value of water quality parameters that affected the growth of C. vulgaris in tank 1 and tank 2 was dissolved oxygen of 4.82-6.97 mg. L-1, pH 8.2-9.1, transparency of 20-45 cm, temperature was 26.8-28.2 oC, nitrate of 0.10-0.50 mg. L-1, phosphate of 0.75-2 mg. L-1, and salinity of 30-39 ppt.

Variation in palladium and water quality parameters and their relationship in the urban water environment.

Palladium (Pd) is widely used in vehicle exhaust catalysts (VECs) to reduce toxic emissions from motor vehicles. The study aimed to quantitatively determine Pd content and water quality parameters, to analyze the variation differences and to explore the effect of water quality parameters on Pd content in the urban water environment system (wet deposition-rainfall runoff-receiving water body-estuary) of the city of Haikou, Hainan Island, China. The method used in this study included microwave digestion under high pressure and temperature, analysis by inductively coupled plasma mass spectrometry, quality control of the experimental procedure and guaranteed recovery (85% -125%). The results showed that the dissolved Pd average content in the urban water environment system was the highest in rainfall runoff (4.93 ng/L), followed by that in the receiving water body (4.56 ng/L), and it was the lowest in wet deposition (0.1 ng/L). The suspended Pd average content was the highest in the estuary (2.83 ng/L), followed by that in rainfall runoff (1.26 ng/L), and it was the lowest in wet deposition (6 × 10-4 ng/L). The particle-water partition ratio of the estuary Pd was the highest (1.26), followed by that of Pd in rainfall runoff (0.26). The particle-water partition ratio of the wet deposition Pd was the lowest (6 × 10-3). The dissolved Pd was correlated with the pH, Cl-, and total suspended solids (TSS) (correlation coefficient = 0.52, -0.68, 0.39, p < 0.05; regression coefficient = 1.27, -1.39, 0.01). The suspended Pd was only correlated with Cl- and TSS (correlation coefficient = -0.36, 0.76, p < 0.05; regression coefficient = -1.45, 0.01). Cl- and TSS were the most closely related to Pd in the water environment system. Although individual factors such as pH, Cl-, and TSS had certain migration and transformation effects on Pd in the wet deposition-rainfall runoff-receiving water body-estuary system, the probability of strong correlations was not high. In particular, Eh was not related to the dissolved nor suspended Pd content (correlation coefficient = 0.14, 0.13), which may be due to the synergistic effect of the multiple physical factors on Pd. This study was helpful to better understand the environmental behavior of Pd and provided important theoretical support for the prevention and protection against urban water environmental pollution.

Simplified chemical chloramine decay model for water distribution systems

This paper, presents a simplified model for predicting chemical chloramine loss in ultrapure water as a function of various measurable parameters, which otherwise requires the simulation of a complex mechanistic model involving the implementation of a number of ordinary differential equations (ODE), using specialised software. The complexity of the mechanistic model is evidenced by its lack of use outside chemical reaction modelling academics. We developed a simplified model as a single-line equation with eight fixed coefficients to predict the first-order decay coefficient. The developed model accurately predicts the first-order chloramine decay coefficient as a function of the water pH (7.5–8.5), chlorine-to-ammonia mass ratio (3.0–4.5), initial chloramine dose (1.5–5.0 mg/L), and alkalinity (up to 200 mg/L CaCO3) at 25 °C in ultrapure water samples. The user either has to input all the above mentioned water quality parameters or can evaluate the relative effect of water quality parameters individually or collectively, by using a relative model. The decay coefficient for temperature between 4 and 35 °C can be obtained by applying Arrhenius equation. To predict the chloramine profile, the initial chloramine concentration has to be decreased slightly (4% when pH < 7.8 to no adjustment at pH > 8.2) before the first order model is applied. Such a model will help in adding the effect of other parameters such as NOM, bromide, and microbiological decay in the future to facilitate easy adaptation by the water utilities.

China national water quality criteria for the protection of freshwater life: Ammonia

Ammonia is one of the two mandatory indexes for China’s water environment pollution control. The current China ammonia water quality standard does not reflect the effect of water quality parameters on ammonia toxicity. The Ministry of Ecology and Environment of China just released the China National Aquatic Life Criteria Report for ammonia. This paper discusses the technical route, formulation process and results of the national ammonia criteria. Based on China’s own technical guidelines, a total of 259 acceptable acute and 44 acceptable chronic data for ammonia were adopted. The temperature of the water body corresponding to the ammonia criteria was divided into 6 grades, and the pH was divided into 12 grades, which constitutes 72 groups of water quality conditions. Based on the empirical formulas recommended by USEPA, the ammonia toxicity data was adjusted, and the optimal fitting model was used to derive the 72 short-term criteria and the 72 long-term criteria for ammonia. In terms of criteria derivation, the method used by the USEPA to extrapolate at the criteria level has been improved and replaced with extrapolation at the species level, making the final criteria value more accurate.

Degradation of Triclosan by Co-exposure to Chlorine Dioxide and UV Irradiation

This study investigated the effect of water quality parameters during simultaneous chlorine dioxide disinfection and low pressure ultraviolet (LPUV) irradiation on TCS degradation.The TCS degradation by the co-exposure process was sensitive to chlorine dioxide dosage, concentration of TCS, pH, and NOM.The removal efficiency increases as the pH increases.Neutral and slightly alkaline environments is conductive to promote TCS elimination, The removal rate within 1 minute of pH 5 was only 95.02%.The smaller the removal rate of TCS was decreased as the concentration of humic acid increasing. The higher the concentration of TCS lead to the lower the experimental removal. 2, 4-DCP was generated during UV/ClO2, ClO2 and UV, however, the production of 2, 8-Cl2DD was not detected during UV/ClO2 process.

Genotype by environment interaction across time for Nile tilapia, from juvenile to finishing stages, reared in different production systems

Nile tilapia is one of the most important fish for aquaculture worldwide and it is produced under many different environmental and system conditions. Even though genotype by environment interaction (GEI) can arise due to many factors, most studies with Nile tilapia have focused more on the effects of water quality parameters and pound or cage systems. There is also lack of knowledge on GEI between fish at different ages, as before and after reaching sexual maturity. Therefore, the objective of the current work was to evaluate the magnitude of GEI on body weight in Nile tilapia raised in biofloc technology (BFT), cage and recirculation aquaculture systems (RAS) from 100 to 350 days of age. To evaluate the temporal trend of GEI a multi-trait random regression model (MTRRM) with age as random regression covariable was employed. Higher values of heritability estimates were found around 225 days, with a maximum of 0.4 for BW at RAS. Estimated genetic correlations between BFT and RAS were above 0.7 for almost any combination of ages evaluated. On the other hand, genetic correlations between Cage at ages below 150 days and either BFT or RAS at any other age were positive but lower than 0.6. Results for the estimated ratio of the indirect by direct response to selection were lower for selection performed at very younger ages whereas the desired response is for older ages. However, if the selection is performed around 225 days for either BTF or RAS this ratio is above 0.8 for most of the situations considered. In conclusion, MTRRM is shown to be a powerful statistical tool to assess changes across the time for genetic parameters of interest, such as covariance, correlations, and heritability. Also, the GEI across the three production systems considered was found to be dynamic across the ages evaluated, with stronger effects between Cage and both BFT and RAS if the selection is performed prior to 150 days of age.

Photocatalytic degradation of phenanthrene by graphite oxide-TiO2-Sr(OH)2/SrCO3 nanocomposite under solar irradiation: Effects of water quality parameters and predictive modeling

Polycyclic aromatic hydrocarbons (PAHs) are persistent and harmful pollutants with high priority concern in the environment. To efficiently and energy-savingly remove PAHs from water, this work prepared a novel graphite oxide-TiO2-Sr(OH)2/SrCO3 nanocomposite and evaluated its photocatalytic activity for degradation of phenanthrene (a model PAH) under simulated solar irradiation. The presence of 50 mg/L of the photocatalyst enhanced the pseudo-first-order photodegradation rate constant of phenanthrene by 11.6 times from 0.0005 ± 0.0000 min−1 (control) to 0.0058 ± 0.0004 min−1. Superoxide radicals (O2−) and hydroxyl radicals (OH) were found to be the key reactive species in the photocatalytic process. Based on analysis of intermediates and established photocatalysis chemistry, the degradation pathway was elucidated. The effects of various water quality parameters were investigated, including temperature, pH, ionic strength, humic acid and two surfactants (Tween 80 and sodium dodecyl sulfate (SDS)), and the underlying mechanisms were illustrated. Based on the effects of individual water quality parameters, two predictive models were established by addition or multiplication to predict the photocatalytic degradation rate under complex water matrices. Based on experimental results with seawater and in the presence of three model oil dispersants, the multiplicative model was shown to present a robust and accurate prediction of the phenanthrene photodegradation rate with a predicted correlation coefficient (r2pred.) of 0.9483. This study not only developed a new photocatalyst of high activity under solar light, but also provided useful information for its practical application under various water quality conditions.