Conventional Water Quality Parameters Research Articles

The presence of microplastics in Surabaya coastal area and its correlation with conventional water quality parameters

Abstract Microplastic’s existence has gained much attention due to its toxicity and harmful effects on marine life. One of the microplastic behaviours in the environment is to absorb hydrophobic pollutants. This behaviour might increase the toxicity of microplastics, affect the concentration of contaminants, and harm the environment. Kenjeran coastal area is a hotspot for human activities in Surabaya City, such as tourist, military training, and fishing activities. Therefore, the Kenjeran coastal area has a high potential to be polluted by plastics and microplastics. This study aimed to identify the abundance and polymer types of microplastics, as well as their correlations with chemical oxygen demand (COD) and total suspended solids (TSS) concentrations in the seawater of the Kenjeran coastal area. Sampling was conducted at three different points in March and April 2024. The average abundance of microplastics obtained was 63-102 particles/L. Meanwhile, the polymer types obtained were polyethylene, polystyrene, ethylene vinyl acetate, and polycarbonate. The correlation test results show that microplastic abundances do not have a significant correlation with COD and TSS concentration in seawater. This study can be used for further research in emerging pollutants and decision-making processes regarding plastic management from the source to the sea.

A new view into the characterization of dissolved organic matter composition in lakes and traceability studies

With the booming socio-economic development and accelerated urbanisation, the problem of water pollution is becoming more and more prominent, which not only puts great pressure on nature, but also poses a serious threat to the production and life of human beings. Therefore, the study of dissolved organic matter fractions in lakes and their accurate traceability is the key to alleviate the ecological pressure. In this study, the three-dimensional fluorescence spectral properties, characteristic parameters and fluorescence characteristics of dissolved organic matter in water bodies were analyzed in depth using Changdang Lake in China as an example. Three methods, peak-finding method, Tucker coefficient and self-organised neural network, were prominently used for the analysis. Combined with conventional water quality parameters, Combined with conventional water quality parameters, this method further reveals the correlation between DOM composition and surrounding pollution sources in Changdang Lake. The results showed that there were four main components of dissolved organic matter in the lake body of Changdang Lake, of which C1, C2 and C4 were humic substances and C3 was protein. In addition, the fluorescence characteristic parameters of Changdang Lake, FI, ranged from 1.64 to 1.75, BIX, ranged from 0.95 to 1.05, and HIX, ranged from 0.5 to 0.65, which indicated that the increment of dissolved organic matter in Changdang Lake was mainly a mixture of endogenous and exogenous inputs. Through the joint interpretation of peak discovery, data presentation and result visualisation, it was found that these fluorescence fractions were extremely similar to those of the surrounding aquaculture and textile printing and dyeing. The results of this study not only provide effective data support for the local environmental protection department of Changdang Lake, but also provide a useful reference for pollution traceability in other lake basins.

Exploring the impacts of steroid estrogens load and aeration intensity on the performance, membrane fouling characteristics, and bacterial community structure of the anoxic-oxic membrane bioreactor

Steroid estrogens (SEs) are typical endocrine-disrupting compounds, and they are inadequately eliminated in most wastewater treatment plants (WWTPs), contributing significantly to their environmental prevalence. In an effort to optimize the performance of membrane bioreactor (MBR) in mitigating SEs alike micropollutants, this study investigated the influences of influent loads of three typical SEs (estrone (E1), 17β-estradiol (E2), and 17α-ethynyestradiol (EE2)) and the aeration intensity on the pollutants removal performance, membrane fouling characteristics, and bacterial community structure in a lab-scale anoxic/oxic-MBR (A/O-MBR) process. The presence of SEs shed minimal impacts on the performance of A/O-MBR process as indicated by conventional water quality parameters due to gradual microbial acclimation. However, the presence and the rising input of SEs accelerated membrane fouling as a result of the enhanced EPS excretion and PN/PS ratio and the reduced floc size. The moderate aeration intensity was preferred from the perspectives of conventional pollutants removal, SEs biodegradation, biomass accumulation, and membrane fouling mitigation. Evolution of bacterial community structure and predominant genera were identified at different SEs loads and aeration intensities, with Candidatus Competibacter and Ferruginibacter detected as the predominant genera at different SEs input loads and Thiothrix, Azospira, and Saprospiraceae_norank at different aeration intensities with identical SEs input. The results demonstrated the potential of A/O-MBR as a promising barrier against SEs alike micropollutants through the regulation and control of aeration intensity.

Advances in the process-based models of constructed wetlands and a way forward for integrating emerging organic contaminants.

This research examines advancements in the development of process-based models of constructed wetlands (CWs) tailored for simulating conventional water quality parameters (CWQPs). Despite the promising potential of CWs for emerging organic contaminant (EOC) removal, the available CW models do not yet integrate EOC removal processes. This study explores the need and possibility of integrating EOCs into existing CW models. Nevertheless, a few researchers have developed process-based models of other wastewater treatment systems (e.g., activated sludge systems) to simulate certain EOCs. The EOC removal processes observed in other wastewater treatment systems are analogous to those in CWs. Therefore, the corresponding equations governing these processes can be tailored and integrated into existing CW models, similarly to what was done successfully in the past for CWQPs. This study proposed the next generation of CW models, which outlines 12 areas for future work: integrating EOC removal processes; ensuring data availability for model calibration and validation; considering quantitative and sensitive parameters; quantifying microorganisms in CWs; modifying biofilm dynamics models; including pH, aeration, and redox potential; integrating clogging and plant sub-models; modifying hydraulic sub-model; advancing computer technology and programming; and maintaining a balance between simplicity and complexity. These suggestions provide valuable insights for enhancing the design and operational features of current process-based models of CWs, facilitating improved simulation of CWQPs, and integration of EOCs into the modelling framework.

Implementasi Modul Water Quality Meter pada Komunitas Petani Udang Vaname Jawa Timur

Vannamei shrimp is one of the leading commodities in fisheries aquaculture, due to its competitive price and the ability to be mass-produced with high stocking densities. Many coastal communities in East Java capitalize on this opportunity by engaging in vannamei shrimp cultivation. However, most shrimp farmers still measure pond water quality using conventional methods and record water quality parameters on paper, which is highly inefficient. With this issue in mind, the author sought to engage in community service by inviting representatives from the East Java vannamei shrimp farming community. The method involved delivering lectures and interactive discussions with shrimp farmers to understand their perceptions and insights regarding pond water quality, followed by the handover of modules, and subsequently evaluating the modules' usage by the shrimp farmers. As a result of this community service, we introduced a tool to assist traditional shrimp pond farmers in monitoring water quality, in the form of a "Water Quality Meter" module integrated with a website accessible via smartphones and laptops. The "Water Quality Meter" module was designed with a system to portable monitor pond water quality using Internet of Things (IoT) technology, where data obtained by microcontrollers is transmitted to a database to determine the quality value of pond water. Evaluation results indicate that farmers can use the module effectively, and data collected on the website shows that pond water quality for the farmers remains within normal ranges. Shrimp farmers directly benefit from using the module, as the shrimp pond monitoring process becomes more practical and accurate.

Assessing the Influence of Agricultural Nonpoint Source Pollution on Water Quality in Central Kentucky’s Headwater Streams

This study addresses the pressing issue of nonpoint source water pollution in Kentucky, particularly associated with large-scale agriculture. Centered on the outer bluegrass region of Central Kentucky, the research examines the water quality of headwater streams during the agricultural season. The approach involves geospatial land cover classification using aerial imagery. Water quality data were collected during the agricultural growing season from May to October 2018. Land cover classification utilized ERDAS Imagine 2016 and ESRI ArcGIS 10.6 GIS software, while conventional water quality parameters were measured with a YSI ProDSS® multiparameter water probe and a Marsh-McBirney Flo-Mate 2000 flow meter. Statistical analyses show significant differences in stream water chemistry, suggesting the impact of agricultural nonpoint source pollution. Forested streams exhibited more varied conditions, indicating a potentially better environment. As agricultural land percentage increased, water chemistry variation suggested a measurable threshold for changes. Significant differences in water quality between agricultural and forested streams highlight the potential benefits of expanding riparian zones beyond regulations. Enlarging these zones is proposed as a strategy to mitigate nonpoint source pollution in Kentucky’s waterways.

Hydrogeochemical investigation of irrigation water in the vicinity of metallic ore deposits in Kiraz‐İzmir, Turkey: Understanding the crucial nexus between “geology and food safety”

AbstractThe increasing drought due to climate change poses a threat to issues such as safe and accessible drinking water, food safety, and protection from diseases. The provision of water supply is vital for agricultural and livestock activities, which are commonly practiced around natural ore deposits. Examining traditional “irrigation water quality” methods alone is insufficient; investigating potentially toxic metal content in the region's waters is vital, especially around metallic ore deposits. This study focused on the Kiraz district in Turkey, known for its agricultural activities, to assess the impact of geogenic water pollution on irrigation water quality and its implications for food safety and human health. Geology determines nutrient availability, water resources, and land suitability for agriculture. Conventional irrigation water quality parameters indicate groundwater suitability for irrigation in the study area, considering Na%, sodium adsorption ratio, residual sodium carbonate, permeability index, Kelly ratio, magnesium hazard, and potential salinity. However, when examining the potential toxic metal content in the region, it was determined that the values of Al ranged from 96 to 8676 ppb, Ni values ranged from 27 to 360 ppb, and Sb concentrations varied between 9 and 53 432 ppb. Utilizing geogenically contaminated water for irrigation and its indiscriminate use in livestock, dairy, and food industries can lead to foodborne illnesses (cancer, endocrine disruptors, tuberculosis, antimony spots, thyroid tumors, goiter, neurologic and cardiovascular diseases) that endanger human health. The use of low‐quality water throughout the agricultural sector and food production chain increases food safety risks.

Real-time organic compound monitoring in advanced oxidation process (AOP) of anaerobic digestion effluent: introduction of UV-VIS spectrum representative index by discrete Fourier transform.

Anaerobic digestion effluent from sewage treatment plants (STP) poses a challenge to the operator because of its high organic matter and inorganic nitrogen concentrations, which require an effective process for biological treatment. This study aimed to introduce a UV-VIS spectrum representative index by discrete Fourier transform (DFT) and apply UV-Vis spectrophotometric techniques for real-time organic compound monitoring in the AOP process using anaerobic digestion tank effluent wastewater. The effect of advanced oxidation on the organic compounds of effluent using ozonation was examined. In this research, after treating secondary treated water with the UV-AOP process and anaerobic digestion effluent with ozone microbubble systems, changes in organic substances were expressed by the UV-Vis spectrum and compared with conventional water quality parameters. The anaerobic digestion process effluent was treated through ozone oxidation, had a high curve, and fell gently from 230 to 667 nm. Discrete Fourier transform (DFT) was applied to obtain representative values from the obtained spectrum. From among the coefficients obtained by analyzing the UV-Vis spectrum through DFT, an expected value was selected, and the correlation between CODMn and a3 was the highest (correlation function = 0.694, RSQ = 0.482). Therefore, a linear regression analysis was performed to determine which water quality factor it was related to.

Investigation on molecular characteristics of organic compounds during a full-scale landfill leachate treatment process based on non-targeted analysis

In this study, a new methodology for evaluating full-scale landfill leachate treatment processes by non-targeted analysis using comprehensive two-dimensional gas chromatography quadrupole time-of-flight mass spectrometry (GC × GC-QTOF-MS) was proposed. The method revealed the chemical complexity of organic compounds in landfill leachate samples at the molecular level and evaluated the removal efficiency of the anaerobic-anoxic-oxic (A2O) - membrane bioreactor (MBR) - nanofiltration (NF) treatment process in conjunction with multi-level classification of organic compounds. Results showed that the results of non-targeted analysis combined with multi-level classification of organic compounds had a significant correlation with the conventional water quality parameters and can be used to evaluate the treatment process. A total of 2508 organic compounds were detected in 6 samples. 17 emerging contaminants (ECs) with known potentially hazards were detected, including Diisobutyl Phthalate (DIBP), which is toxic to male reproduction and development, and 4-Tert-Butylphenol, which causes endocrine disruption in animals. The removal rate of organic compounds by this full-scale landfill leachate treatment processes reached 79.14%. The anaerobic tank played a crucial role with 64.98% contribution. For compounds, the removal rate of heterocyclics was as high as 94.67%, and the removal rate of aliphatics was poor, only 63.49%. This treatment process had almost perfect removal effect on the steroids in alicyclics and phenols in aromatics, but poor treatment effect on saturated alkanes in aliphatics and naphthenes in alicyclics. This study provides a methodology for accurate assessment of the molecular level of treatment processes, new insights for process optimization in waste treatment plants, and data support for the detection of emerging contaminants. The environmental hazards of landfill leachate can be further evaluated in the future in conjunction with ecotoxicity assessment studies.

Irrigation suitability and health risk assessment of groundwater resources in the Firozabad industrial area of north-central India: An integrated indexical, statistical, and geospatial approach

The recent global upsurge in anthropogenic activities has resulted in a decline in the quality of water. This by extension has resulted in increased ubiquity of water pollution in terms of sources. The application of traditional water quality assessment methods usually involves the use of conventional water quality parameters and guideline values. This may be associated with bias and errors during the computation of various sub-indices. Hence, to overcome this limitation, it is critical to have a visual appraisal of the water quality in terms of source and human health risks exposure for sustainable water resource management and informed decision-making. Therefore, the present study has integrated multiple water quality assessment indices, spatio-temporal, and statistical models to assess the suitability of fifty groundwater samples (n = 50) within the Firozabad industrial area for irrigation and drinking; as well as the likely health risks from oral intake and dermal contact by inhabitants. Electrical conductivity (mean = 1,576.6 μs/cm), total hardness (mean = 230.9 mg/L), dissolved sodium (mean = 305.1 mg/L) chloride (mean = 306.1 mg/L) and fluoride (mean = 1.52 mg/L) occurred in the water at concentrations above the recommended standards; attributed influxes from agricultural and industrial wastewater. The pollution index of groundwater and water quality index revealed that 100% of the groundwater samples are extremely polluted; this was also supported by the joint multivariate statistical analyses. The majority of the irrigational water quality indices (sodium adsorption ratio, Kelly’s Ratio, permeability index, percent sodium) revealed that the long-term use of the groundwater for irrigation in the area will result in reduced crop yield unless remedial measures are put in place. Higher Hazard index (HI > 1) for nitrate and fluoride ingestion was recorded in water for the children population compared to adult; an indication that the children population is more predisposed to health risks from the oral intake of water. Generally, risk levels from ingestion appear to increase in the western and north-eastern parts of the study area. From the findings of this study, it is highly recommended that adequate agricultural practices, land use, and water treatment regulatory strategies be put in place for water quality sustainability for enhanced agricultural production and human health protection.

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.

Wetland plant-derived biochar enhances the diclofenac treatment performance in vertical subsurface flow constructed wetlands

Diclofenac (DFC) is a pharmacologically active compound frequently detected in various receiving waters. To improve the efficiency of constructed wetlands in removing DFC, biochar (BC) is added as a substrate. The study mainly involved the effect of adding wetland plant-derived BC to vertical subsurface flow constructed wetlands (VSF-CWs) on the DFC removal process. In addition, the study discussed the effects of the initial DFC concentration (0.05–1.00 mg L−1), pH (5.5–8.5), and hydraulic retention times (HRTs, 1–7 d) on the removal process and fluctuations in the microbial community. Preliminary results of the study showed optimal removal (>90%) achieved at an initial DFC concentration of 0.75–1 mg L−1, a pH of 6.5–7.5, and an HRT of 7 d. Moreover, no significant effects on the removal efficiency of conventional water quality parameters were observed. Non-metric multidimensional scaling results revealed a reshaped community structure, which was altered by the initial DFC concentration. DFC concentration is a key factor in the variation of microbial communities and controls the quantitative evolution of the species in experimental units. Therefore, the addition of BC to CWs effectively enhanced the removal efficiency of DFC and provided a viable and effective improvement of the CWs.

Initial Deployment of a Mobile Sensing System for Water Quality in Urban Canals

Although water quality has extensively improved over the last decade, recreational uses of the canal network in Amsterdam are limited by variations in water quality associated with stormwater runoff and episodic harmful algal blooms. The current systems for monitoring water quality are based on a stationary network of sampling points, offline testing methods, and online measurements of conventional water quality parameters on board a boat that continuously navigates the urban canal network. Here we describe the development and deployment of online algal sensors on board the boat, including a prototype LED-induced fluorescence instrument for algal identification and quantification. We demonstrate that by using only a single patrol vessel, we are able to achieve enough sampling coverage to observe spatiotemporal heterogeneity of algal and chemical water quality within the canal network. The data provide encouraging evidence that opportunistic measurements from a small number of mobile platforms can enable high-resolution mapping and can be used to improve the monitoring of water quality across the city compared to the current network of fixed sampling locations. We also discuss the challenges of operating water quality sensors for long-term autonomous monitoring.

Spatiotemporal variations and ecological risks of typical antibiotics in rivers inflowing into Taihu Lake, China

Antibiotics have become a global public concern due to the widespread presence of antibiotic-resistant bacteria and genes. This study investigated the spatial and seasonal variation of conventional water quality parameters and 10 selected antibiotics in rivers inflowing into Taihu Lake. The results showed that total nitrogen, as a pollution driver factor, varied with the seasons, and higher concentrations of pollutants were generally found in the dry season compared with the wet season. For antibiotics, seven of them were detected in surface waters (n = 66) with detection frequencies (DFs) of 1.52–100% and eight antibiotics with DFs of 2.56–100% in sediments (n = 39). Sulfamethoxazole (SMZ, median: 1.47 ng/L), trimethoprim (TMP, median: 0.35 ng/L), and roxithromycin (ROX, median: 0.47 ng/L) with 100% DFs followed by erythromycin (ERY, median: 0.56 ng/L) with a DF of 90.91% accounted for a median percentage of 44.54%, 9.08%, 20.42%, and 13.16% of the ΣABs concentrations in surface waters. In contrast, enrofloxacin (ENR, median: 0.54 ng/g) and ROX (median: 0.29 ng/g) with 100% DFs accounted for a median percentage of 58.21% and 31.71% of the ΣABs concentrations in sediments. Antibiotics in surface waters were mainly related to T, DO, TN and NH3–N, but were mainly related to T, pH and TN for antibiotics in sediments. Furthermore, most of the detected antibiotics showed higher concentrations and more species of antibiotics in winter than in summer or autumn. Similarly, the ecological risk values of antibiotics showed higher in winter than in the other two seasons, whereas the overall risk levels were considered acceptable.

Fluorescence analysis of centralized water supply systems: Indications for rapid cross-connection detection and water quality safety guarantee

Better insight into non-potable reclaimed water and drinking water can produce more reliable risk assessment and help to achieve sustainable water reuse in the long-term. This study illustrates the effectiveness of fluorescence excitation-emission matrix (EEM) for rapid cross-connection detection. Based on samples collected from three different sites of China, it is identified that the overall fluorescence intensity was 6–31 times of reclaimed to drinking water in water samples at all FRI regions. This is shown to be highly sensitive over conventional water quality parameters. Furthermore, based on parallel factor analysis (PARAFAC), humic acid and tryptophan are considered as the main components contributing to fluorescence both in secondary and tertiary effluents. Total fluorescence intensities as well as fluorescence peaks of EEM pairs were investigated. Under different mixing scenarios, it is found that the signal is distinguishable as low as 20% of reclaimed water. This study also offers possibility of exploring portable devices with identified fluorescence peaks in EEM regions for risk prevention and water quality monitoring at end user sites.

Roles of metal ions in regulating the formation of a drinking water odorant (2,3,6-trichloroanisole) by Sphingomonas ursincola in drinking water

Haloanisoles (HAs) produced by bacteria have become a nonnegligible taste and odor issue in drinking water. However, the effects of conventional water quality parameters, particularly for metal ions on bacterial HA formation, have rarely been studied. In this study, the effects of six metal ions (Ca2+, Mg2+, Fe3+, Cu2+, Zn2+ and Mn2+) on the formation of 2,3,6-trichloroanisole (2,3,6-TCA) by Shingomons ursincola Z001 (Z001), a typical HA-producing bacterial strain, were explored. The intracellular 2,3,6-TCA produced by Z001 accounted for 87%–96% of the total 2,3,6-TCA. It was found that 1.0–10 mM Ca2+, 1.0–10 mM Mg2+, 0.010 mM Fe3+ and 0.010 mM Zn2+ could promote Z001 to produce more 2,3,6-TCA, while 0.010–0.10 mM Mn2+, 0.010–1.0 mM Cu2+, 0.10 mM Fe3+ and 0.010–1.0 mM Zn2+ reduced 2,3,6-TCA production. The chlorophenol O-methyltransferase (CPOMT) is mainly located in the cytoplasm of Z001 cells. Cell extract experiments demonstrated that Ca2+ and Mg2+ were activators of CPOMT, while Fe3+, Zn2+, Cu2+ and Mn2+ were its inhibitors. Flow cytometry proved that Cu2+ could significantly damage the integrity of cell membrane, leading to the release of 2,3,6-TCA. In addition to CPOMT activity, Mg2+ and Zn2+ may also influence the processes of S-adenosylmethionine cycle. The Z001 cell wall may precipitate Zn2+ and Cu2+ to reduce their toxicities toward CPOMT. According to the obtained findings, strict controls of Ca2+, Mg2+, Fe3+ and Zn2+ during drinking water treatment were proposed to reduce HA contamination.

The influence of aquaculture on the hydro-geochemistry of a neotropical aquatic system

Pollution in the aquatic ecosystem is a central theme in ecological research. We investigated the hydrogeochemical characteristics of the Sa?o Francisco Verdadeiro River, a tributary of a Neotropical reservoir, which is under a strong influence of local agricultural, industrial and urban activities, and direct influence aquaculture in its tributary. Conventional water quality parameters were monitored bi-monthly in the hydrological cycle at seven longitudinal sites. Consistent with the expected pattern, nutrient concentrations were higher for the points (mouth of small creeks from cities and/or agricultural regions) S1, S2 and S4, with TN values of 5.37×10−1, 7.99×10−1 and 8.88×10−1 mg L−1 respectively. Similar behavior presented in the TP contents, with values of 9.66×10−2, 1.51×10−1 and 1.14×10−1 mg L−1 respectively were observed. All parameters were also analyzed by the Principal Component Analysis (PCA), showing similarities between S1, S2, and S4 (more nutrient concentrations) and S3, S5, S6, and S7 (fewer nutrient concentrations). Our findings suggest that the aquaculture activity in fish-cages is not impacting the environment. Conversely, there is strong evidence of punctual and diffuse pollutant sources that contribute significantly to the increase of nutrients in the water, mainly those in the nitrogenate and phosphate forms, resulting in the deterioration of the water quality. The results indicate the need for an integrated management of the river basin aiming at maintaining the environmental quality.

Real-time detection of potable-reclaimed water pipe cross-connection events by conventional water quality sensors using machine learning methods

Risk of cross-connection is becoming higher due to greater construction of potable-reclaimed water dual distribution systems. Cross-connection events can result in serious health concerns and reduce public confidence in reclaimed water. Thus, reliable, cost-effective and real-time online detection methods for early warning are required. The current study carried out pilot-scale experiments to simulate potable-reclaimed water pipe cross-connection events for different mixing ratios (from 30% to 1%) using machine learning methods based on multiple conventional water quality parameters. The parameters included residual chlorine, pH, turbidity, temperature, conductivity, oxidation-reduction potential and chemical oxygen demand. The results showed that correlated variation occurred among water quality parameters at the time of the cross-connection event. A single parameter-based method can be effective at high mixing ratios, but not at low mixing ratios. The direct supporting vector machine (SVM)-based method managed to overcome this drawback, but coped poorly with abnormal readings of water parameter sensors. In that respect, a Pearson correlation coefficient (PCC)-SVM-based method was developed. It provided not only high detection performance under normal conditions, but also remained reliable when abnormal readings occurred. The detection accuracy and true positive rate of this method was still over 88%, and the false positive rate was below 12%, given a sudden variation of an individual water quality parameter. The receiver operating characteristic curves further confirmed the promising practical applicability of this PCC-SVM-based method for early detection of cross-connection events.

Occurrence of microcystin-LR in vegetated lagoons used for urban runoff management

Phytoremediation with aquatic macrophyte has been considered as an eco-friendly technique for controlling harmful cyanobacteria outbreak and proven to be effective. The conventional water quality parameters are frequently measured to evaluate the effectiveness of phytoremediation. However, the concentration of microcystin-leucine-arginine (MC-LR) in different vegetated water still remains uncertain. In this study, the contents of MC-LR in four macrophyte-vegetated lagoons were determined by solid phase extraction and ultra-high-performance liquid chromatography with tandem mass spectrometry technology. Results indicated that MC-LR was found in Nymphaea tetragona lagoon (lagoon-S), Vallisneria spiralis lagoon (lagoon-B) and another Vallisneria spiralis lagoon (lagoon-J). Only in lagoon dominated by Pistia stratiotes L. (lagoon-D), MC-LR concentration was undiscovered regardless of seasonal variation. The levels of MC-LR varied seasonally and were affected by the different vegetated aquatic macrophytes. The results suggest that in addition to conventional physicochemical parameters and indicators of water quality, MC-LR levels should be taken into consideration when the effectiveness of phytoremediation is assessed.

Seasonal Variation of Disinfection Byproduct Precursors in a Large Water Supply

Disinfection byproduct (DBP) precursors originate in large reservoirs from at least three types of sources: (1) watershed or allochthonous, (2) algal or autochthonous, and (3) bottom sediments or benthic. The properties of the bulk natural organic matter (NOM) and the DBP precursor content of that NOM are unique to each source. Knowledge about the relative importance of these three sources would be valuable in understanding the natural variability in DBP precursor occurrence and in managing source waters for the purpose of minimizing DBP precursors. In this study, we used temporal and spatial water quality data from a drinking water reservoir to shed light on autochthonous and benthic sources of NOM and DBP precursors. The Cannonsville Reservoir (New York) was chosen for this work because of its well‐documented water quality. To assist in the data analysis, we developed a series of two‐dimensional contour plots that bring clarity to benthic and near‐surface (algal) processes on water quality. Combining conventional water quality parameters with DBP precursor analysis can facilitate a more comprehensive understanding of limnological factors that define DBP precursor levels. These data were compared with known properties of NOM and related natural biochemical parameters. From this analysis, we conclude that algal‐dominated NOM contributes disproportionately to dihaloacetonitrile formation, whereas watershed‐dominated NOM is especially rich in trihaloacetic acid and trihalomethane precursors as well as ultraviolet‐absorbing substances. The sediment‐dominated precursor behaved like a mix of the other two but most resembled the watershed NOM.