Deep optimization of water quality index and positive matrix factorization models for water quality evaluation and pollution source apportionment using a random forest model.

Effective evaluation of water quality and accurate quantification of pollution sources are essential for the sustainable use of water resources. Although water quality index (WQI) and positive matrix factorization (PMF) models have been proven to be applicable for surface water quality assessments and pollution source apportionments, these models still have potential for further development in today's data-driven, rapidly evolving technological era. This study coupled a machine learning technique, the random forest model, with WQI and PMF models to enhance their ability to analyze water pollution issues. Monitoring data of 12 water quality indicators from six sites along the Minjiang River from 2015 to 2020 were used to build a WQI model for determining the spatiotemporal water quality characteristics. Then, coupled with the random forest model, the importance of 12 indicators relative to the WQI was assessed. The total phosphorus (TP), total nitrogen (TN), chemical oxygen demand (CODCr), dissolved oxygen (DO), and five-day biochemical oxygen demand (BOD5) were identified as the top five significant parameters influencing water quality in the region. The improved WQI model constructed based on key parameters enabled high-precision (R2 = 0.9696) water quality prediction. Furthermore, the feature importance of the indicators was used as weights to adjust the results of the PMF model, allowing for a more reasonable pollutant source apportionment and revealing potential driving factors of variations in water quality. The final contributions of pollution sources in descending order were agricultural activities (30.26%), domestic sewage (29.07%), industrial wastewater (26.25%), seasonal factors (6.45%), soil erosion (6.19%), and unidentified sources (1.78%). This study provides a new perspective for a comprehensive understanding of the water pollution characteristics of rivers, and offers valuable references for the development of targeted strategies for water quality improvement.

Enhancing phosphorus source apportionment in watersheds through species-specific analysis.

Phosphorus (P) is a pivotal element responsible for triggering watershed eutrophication, and accurate source apportionment is a prerequisite for achieving the targeted prevention and control of P pollution. Current research predominantly emphasizes the allocation of total phosphorus (TP) loads from watershed pollution sources, with limited integration of source apportionment considering P species and their specific implications for eutrophication. This article conducts a retrospective analysis of the current state of research on watershed P source apportionment models, providing a comprehensive evaluation of three source apportionment methods, inventory analysis, diffusion models, and receptor models. Furthermore, a quantitative analysis of the impact of P species on watersheds is carried out, followed by the relationship between P species and the P source apportionment being critically clarified within watersheds. The study reveals that the impact of P on watershed eutrophication is highly dependent on P species, rather than absolute concentration of TP. Current research overlooking P species composition of pollution sources may render the acquired results of source apportionment incapable of assessing the impact of P sources on eutrophication accurately. In order to enhance the accuracy of watershed P pollution source apportionment, the following prospectives are recommended: (1) quantifying the P species composition of typical pollution sources; (2) revealing the mechanisms governing the migration and transformation of P species in watersheds; (3) expanding the application of traditional models and introducing novel methods to achieve quantitative source apportionment specifically for P species. Conducting source apportionment of specific species within a watershed contributes to a deeper understanding of P migration and transformation, enhancing the precise of management of P pollution sources and facilitating the targeted recovery of P resources.

Effect of microbial communities on nitrogen and phosphorus metabolism in rivers with different heavy metal pollution.

Small urban and rural rivers usually face heavy metal pollution as a result of urbanization and industrial and agricultural activities. To elucidate the metabolic capacity of microbial communities on nitrogen and phosphorus cycle in river sediments under different heavy metal pollution backgrounds, this study collected samples in situ from two typical rivers, Tiquan River and Mianyuan River, with different heavy metal pollution levels. The microbial community structure and metabolic capacity of nitrogen and phosphorus cycles of sediment microorganisms were analyzed by high-throughput sequencing. The results showed that the major heavy metals in the sediments of the Tiquan River were Zn, Cu, Pb, and Cd with the contents of 103.80, 30.65, 25.95, and 0.44 mg/kg, respectively, while the major heavy metals in the sediments of the Mianyuan River were Cd and Cu with the contents of 0.60 and 27.81 mg/kg, respectively. The dominant bacteria Steroidobacter, Marmoricola, and Bacillus in the sediments of the Tiquan River had positive correlations with Cu, Zn, and Pb while are negatively correlated with Cd. Cd had a positive correlation with Rubrivivax, and Cu had a positive correlation with Gaiella in the sediments of the Mianyuan River. The dominant bacteria in the sediments of the Tiquan River showed strong phosphorus metabolic ability, and the dominant bacteria in the sediments of the Mianyuan River showed strong nitrogen metabolic ability, corresponding to the lower total phosphorus content in the Tiquan River and the higher total nitrogen content in the Mianyuan River. The results of this study showed that resistant bacteria became dominant bacteria due to the stress of heavy metals, and these bacteria showed strong nitrogen and phosphorus metabolic ability. It can provide theoretical support for the pollution prevention and control of small urban and rural rivers and have positive significance for maintaining the healthy development of rivers.

New insights into pollution source analysis using receptor models in the upper Yangtze river basin: Effects of land use on source identification and apportionment.

To effectively control pollution and improve water quality, it is essential to accurately analyze the potential pollution sources in rivers. The study proposes a hypothesis that land use can influence the identification and apportionment of pollution sources and tested it in two areas with different types of water pollution and land use. The redundancy analysis (RDA) results showed that the response mechanisms of water quality to land use differed among regions. In both regions, the results indicated that the water quality response relationship to land use provided important objective evidence for pollution source identification, and the RDA tool optimized the procedure of source analysis for receptor models. Positive matrix decomposition (PMF) and absolute principal component score-multiple linear regression (APCS-MLR) receptor models identified five and four pollution sources along with their corresponding characteristic parameters. PMF attributed agricultural nonpoint sources (23.8%) and domestic wastewater (32.7%) as the major sources in regions 1 and 2, respectively, while APCS-MLR identified mixed sources in both regions. In terms of model performance parameters, PMF demonstrated better-fit coefficients (R2) than APCS-MLR and had a lower error rate and proportion of unidentified sources. The results show that considering the effect of land use in the source analysis can overcome the subjectivity of the receptor model and improve the accuracy of pollution source identification and apportionment. The results of the study can help managers clarify the priorities of pollution prevention and control, and provide a new methodology for water environment management in similar watersheds.

A method for researching the eutrophication and N/P loads of plateau lakes: Lugu Lake as a case.

Lugu Lake is one of the best plateau lakes in China in terms of water quality, but in recent years the eutrophication of Lugu Lake has accelerated due to high nitrogen and phosphorus loads. This study aimed to determine the eutrophication state of Lugu Lake. Specifically, the spatio-temporal variations of nitrogen and phosphorus pollution during the wet and dry seasons were investigated in Lianghai and Caohai, and the primary environmental effect factors were defined. Adopting the endogenous static release experiments and the exogenous improved export coefficient model, a novel approach (a combination of internal and external sources) was developed for the estimation of nitrogen and phosphorus pollution loads in Lugu Lake. It was indicated that the order of nitrogen and phosphorus pollution in Lugu Lake was Caohai > Lianghai and dry season > wet season. Dissolved oxygen (DO) and chemical oxygen demand (CODMn) were the main environmental factors causing nitrogen and phosphorus pollution. Endogenous nitrogen and phosphorus release rates in Lugu Lake were 668.7 and 42.0 t/a, respectively, and exogenous nitrogen and phosphorus input rates were 372.7 and 30.8 t/a, respectively. The contributions of pollution sources, in descending order, were sediment > land-use categories > residents and livestock breeding > plant decay, of which sediment nitrogen and phosphorus loads accounted for 64.3 % and 57.4 %, respectively. Regulating the endogenous release of sediment and obstructing the exogenous input from shrubland and woodland are emphasized for the management of nitrogen and phosphorus contamination in Lugu Lake. Thus, this study can serve as a theoretical foundation and technical guide for eutrophication control in plateau lakes.

Ecological risk assessment and identification of the distinct microbial groups in heavy metal-polluted river sediments.

To assess the health of river ecosystems, it is essential to quantify the ecological risk of heavy metals in river sediments and the structure of microbial communities. As important tributaries of the Tuo River in the upper reaches of the Yangtze River, the Mianyuan River and the Shiting River, are closely related to the economic development and human daily life in the region. This study assessed the ecological risks of heavy-metal-polluted river sediments, the heavy-metal-driven bacterial communities were revealed, and the relationships between the ecological risks and the identical bacterial communities were discussed. The Cd content was significantly greater than the environmental background value, leading to a serious pollution and very high ecological risk at the confluence of the two rivers and the upper reaches of the Mianyuan River. Microbial community analysis showed that Rhodobacter, Nocardioides, Sphingomonas, and Pseudarthrobacter were the dominant bacterial genera in the sediments of the Shiting River. However, the dominant bacterial genera in the Mianyuan River were Kouleothrix, Dechloromonas, Gaiella, Pedomicrobium, and Hyphomicrobium. Mantel test results showed (r = 0.5977, P = 0.005) that the Cd, As, Zn, Pb, Cr, and Cu were important factors that influenced differences in the distribution of sediment bacterial communities Mianyuan and Shiting rivers. A correlation heatmap showed that heavy metals were negatively correlated for most bacterial communities, but some bacterial communities were tolerant and showed a positive correlation. Overall, the microbial structure of the river sediments showed a diverse spatial distribution due to the influence of heavy metals. The results will improve the understanding of rivers contaminated by heavy metals and provide theoretical support for conservation and in situ ecological restoration of river ecosystems.

Regional distribution, properties, treatment technologies, and resource utilization of oil-based drilling cuttings: A review.

Oil-based drilling cuttings (OBDC) are hazardous wastes produced during the extensive use of oil-based drilling mud in oil and gas exploration and development. They have strong mutagenic, carcinogenic, and teratogenic effects and need to be properly disposed of to avoid damaging the natural environment. This paper reviews the recent research progress on the regional distribution, properties, treatment technologies, and resource utilization of OBDC. The advantages and disadvantages of different technologies for removing petroleum pollutants from OBDC were comprehensively analyzed, and required future developments in treatment technologies were proposed.

Novel strategy for controlling colloidal instability during the flocculation pretreatment of landfill leachate.

Flocculation is an economical and effective pretreatment technology for landfill leachate. An iron salt flocculant is often used in landfill leachate pretreatment, but the flocs that are formed are affected by the operation sequence, which subsquently influences flocculation. This study selected three representative landfill leachates (i.e., mature landfill leachate (MLL), biologically treated landfill leachate (BTL), and nanofiltration concentrate leachate (NFCL)). The effect of different operation modes on the removal of organic matter from landfill leachate by flocculation was studied, and a strategy to control colloidal instability is put forward. The results revealed that adjusting the pH value to 9 using NaOH changes the zeta potential of leachate when the leachate and sludge are not separated, which affects electric neutralization in flocculation and colloidal stability. Furthermore, a part of the collected organic matter is released to the leachate again, leading to a decrease in the flocculation pretreatment effect. In this improved flocculation process, the leachate and sludge are first separated, and the pH value of the system is then adjusted to 9. The effect of OH- on electric neutralization is avoided and the remaining Fe3+ can further remove organic matter from leachates. Finally, the UV254 removal efficiencies of MLL, BTL, and NFCL increased by 20.38%, 28.67%, and 22.67%, respectively. In a full-scale application, i.e., an NFCL treatment facility, the UV254 removal efficiency during long-term operation reached 87.50%. Therefore, the colloid instability control strategy this study proposes can provide theoretical and engineering references for the flocculation pretreatment of landfill leachate.

A microwave radiation-enhanced Fe-C/persulfate system for the treatment of refractory organic matter from biologically treated landfill leachate.

In this study, a microwave (MW) radiation enhanced Fe-C/PS system was used to treat refractory organic matter in biologically-treated landfill leachate. The effects of important influencing factors on the refractory organic matter in biologically treated landfill leachate were explored, and the main reactive oxygen species produced in the system were verified. The mechanism by which humus was degraded was investigated by analyzing effectiveness of organics removal in different systems, and comparative analysis was conducted on the Fe-C materials before and after the reaction. The results showed that degradation capacity and reaction rate of the system could be improved with an increase in the Fe-C/PS dosage and MW power, while initial acidic conditions were also conducive to the degradation of organic matter. Under the conditions of an Fe-C of 1 g L-1, PS dosage of 30 mM, MW power of 240 W, and reaction time of 10 min, the UV254, TOC, and CN removal efficiencies were 51.48%, 94.56%, and 51.59%, respectively. In the MW/Fe-C/PS system, a large amount of and a small amount of ˙OH were generated by the thermal activation of PS to remove organic matter. The removal efficiency of organic matter could be further improved via the homogeneous catalytic oxidation and heterogeneous adsorption catalytic oxidation of Fe-C materials. In addition, the MW/Fe-C/PS system was effective for removing refractory organic matter from the leachates from four typical treatment systems: DTRO, SAARB, MBR, and NF. The MW/Fe-C/PS system has the potential to be widely applied for the treatment of landfill leachate.