The response patterns of microbial functional genes involved in biogeochemical cycles to cadaver decay is a central topic of recent environmental sciences. However, the response mechanisms and pathways of the functional genes associated with the carbon (C) and nitrogen (N) cycling to cadaveric substances such as cadaverine and putrescine remain unclear. This study explored the variation of functional genes associated with C fixation, C degradation and N cycling and their influencing factors under cadaverine, putrescine and mixed treatments. Our results showed only putrescine significantly increased the alpha diversity of C fixation genes, while reducing the alpha diversity of N cycling genes in sediment. For the C cycling, the mixed treatment significantly decreased the total abundance of reductive acetyl-CoA pathway genes (i.e., acsB and acsE) and lig gene linked to lignin degradation in water, while only significantly increasing the hydroxypropionate-hydroxybutylate cycle (i.e., accA) gene abundance in sediment. For the N cycling, mixed treatment significantly decreased the abundance of the nitrification (i.e., amoB), denitrification (i.e., nirS3) genes in water and the assimilation pathway gene (i.e., gdhA) in sediment. Environmental factors (i.e., total carbon and total nitrogen) were all negatively associated with the genes of C and N cycling. Therefore, cadaverine and putrescine exposure may inhibit the pathway in C fixation and N cycling, while promoting C degradation. These findings can offer some new insight for the management of amine pollution caused by animal cadavers.
As an inland dryland lake basin, the rivers and lakes within the Lake Bosten basin provide scarce but valuable water resources for a fragile environment and play a vital role in the development and sustainability of the local societies. Based on the Google Earth Engine (GEE) platform, combined with the geographic information system (GIS) and remote sensing (RS) technology, we used the index WI2019 to extract and analyze the water body area changes of the Bosten Lake basin from 2000 to 2021 when the threshold value is -0.25 and the slope mask is 8°. The driving factors of water body area changes were also analyzed using the partial least squares-structural equation model (PLS-SEM). The result shows that in the last 20 years, the area of water bodies in the Bosten Lake basin generally fluctuated during the dry, wet, and permanent seasons, with a decreasing trend from 2000 to 2015 and an increasing trend between 2015 and 2019 followed by a steadily decreasing trend afterward. The main driver of the change in wet season water bodies in the Bosten Lake basin is the climatic factors, with anthropogenic factors having a greater influence on the water body area of dry season and permanent season than that of wet season. Our study achieved an accurate and convenient extraction of water body area and drivers, providing up-to-date information to fully understand the spatial and temporal variation of surface water body area and its drivers in the basin, which can be used to effectively manage water resources.
This study aimed to address the pressing issue of plastic pollution in aquatic ecosystems by assessing the prevalence and distribution of microplastics (MPs) in water and riverbank sediments of the Pekalongan River, a vital water source in Indonesia. From the present findings, MP concentrations in water ranged from 45.2 to 99.1 particles/L, while sediment concentrations ranged from 0.77 to 1.01 particles/g. This study revealed that fragment and film MPs constituted 30.1 % and 25.4 % of the total, respectively, with MPs measuring <1 mm and constituting 51.4 % of the total. Colored MPs, particularly blue and black MPs, accounted for 34 % of the total. The primary polymer components, as determined via Fourier transform infrared spectroscopy, were identified as polystyrene, polyester, and polyamide. In response to the escalating plastic waste crisis caused by single-use plastics, Pekalongan's local government implemented refuse segregation and recycling programs as part of its efforts to transition toward zero-waste practices.
A comprehensive geochemical study was conducted in the Sibuti River estuary by considering water, suspended solids (SS), and sediment samples from 36 stations during southwest monsoon (SWM) and northeast monsoon (NEM). In this study, the distribution of in situ parameters, major ions, nutrients, trace metals, and isotopes (δD, δ18O) were analyzed in water samples, whereas sediments and SS were studied for trace metals. The distribution revealed that suspended solids were the major carrier of Cd, Zn, and Mn, whereas sediments worked as a major source of Co, Cr, Ba, Se, Cu, and Pb. Na-Cl water type and ion exchange dominated the lower part of the estuary during both seasons. However, the mixed mechanism of Ca-Cl, Ca-Mg-Cl, and higher weathering indicated reverse ion exchange in the intermediate and upper parts of the estuary. Isotopic signatures of δD and δ18O in estuarine water indicate that the precipitation over the Limbang area dominates during SWM, whereas higher evaporation was confirmed during NEM. The factor analysis revealed that seawater influence in the estuary majority controlled the water chemistry irrespective of seasons. Major ions were mainly regulated by the tidal influence during the low flow time of the river (SWM), whereas the mixing mechanism of weathering and seawater controlled the concentrations during NEM. Nutrients such as NO3, SO42-, NH3, and NH4+ mainly originated from the agricultural fields and nitrification along with ammonification were responsible for the recycling of such nutrients. Trace metals except Cd were found to be geogenic in nature and originating mainly from the oxidation of pyrites present in the sandstone and mudstones of the Sibuti Formation. Redox condition was catalyzed by microorganisms near the river mouth, whereas Al-oxyhydroxides and Fe-oxyhydroxides complexes in the intermediate and upper part under oxygenated conditions controlled the absorption of metals. Overall, the estuary was found to be absorptive in nature due to ideal pH conditions and was confirmed by the saturation index (SI) of minerals.
The concentration, distribution, and risk assessment of parabens were determined in the surface water of the Terengganu River, Malaysia. Target chemicals were extracted via solid-phase extraction, followed by high-performance liquid chromatography analysis. Method optimization produced a high percentage recovery for methylparaben (MeP, 84.69 %), ethylparaben (EtP, 76.60 %), and propylparaben (PrP, 76.33 %). Results showed that higher concentrations were observed for MeP (3.60 μg/L) as compared with EtP (1.21 μg/L) and PrP (1.00 μg/L). Parabens are ubiquitously present in all sampling stations, with >99 % of detection. Salinity and conductivity were the major factors influencing the level of parabens in the surface water. Overall, we found no potential risk of parabens in the Terengganu River ecosystem due to low calculated risk assessment values (risk quotient
Contamination of water systems with endocrine disrupting chemicals (EDCs) is becoming a major public health concern due to their toxicity and ubiquity. The intrusion of EDCs into water sources and drinking water has been associated with various adverse health effects on humans. However, there is no comprehensive overview of the occurrence of EDCs in Malaysia's water systems. This report aims to describe the occurrence of EDCs and their locations. Literature search was conducted electronically in two databases (PubMed and Scopus). A total of 41 peer-reviewed articles published between January 2000 and May 2021 were selected. Most of the articles dealt with pharmaceuticals (16), followed by pesticides (7), hormones (7), mixed compounds (7), and plasticisers (4). Most studies (40/41) were conducted in Peninsular Malaysia, with 60.9% in the central region and almost half (48.8%) in the Selangor State. Only one study was conducted in the northern region and East Malaysia. The Langat River, the Klang River, and the Selangor River were among the most frequently studied EDC-contaminated surface waters, while the Pahang River and the Skudai River had the highest concentrations of some of the listed compounds. Most of the risk assessments resulted in a hazard quotient (HQ) and a risk quotient (RQ) 1 in the Selangor River. An RQ > 1 for combined pharmaceuticals was found in Putrajaya tap water. Overall, this work provides a comprehensive overview of the occurrence of EDCs in Malaysia's water systems. The findings from this review can be used to mitigate risks and strengthen legislation and policies for safer drinking water.
Rivers are the main sources of freshwater supply for the world population. However, many economic activities contribute to river water pollution. River water quality can be monitored using various parameters, such as the pH level, dissolved oxygen, total suspended solids, and the chemical properties. Analyzing the trend and pattern of these parameters enables the prediction of the water quality so that proactive measures can be made by relevant authorities to prevent water pollution and predict the effectiveness of water restoration measures. Machine learning regression algorithms can be applied for this purpose. Here, eight machine learning regression techniques, including decision tree regression, linear regression, ridge, Lasso, support vector regression, random forest regression, extra tree regression, and the artificial neural network, are applied for the purpose of water quality index prediction. Historical data from Indian rivers are adopted for this study. The data refer to six water parameters. Twelve other features are then derived from the original six parameters. The performances of the models using different algorithms and sets of features are compared. The derived water quality rating scale features are identified to contribute toward the development of better regression models, while the linear regression and ridge offer the best performance. The best mean square error achieved is 0 and the correlation coefficient is 1.
Environmental exposure to active pharmaceutical ingredients (APIs) can have negative effects on the health of ecosystems and humans. While numerous studies have monitored APIs in rivers, these employ different analytical methods, measure different APIs, and have ignored many of the countries of the world. This makes it difficult to quantify the scale of the problem from a global perspective. Furthermore, comparison of the existing data, generated for different studies/regions/continents, is challenging due to the vast differences between the analytical methodologies employed. Here, we present a global-scale study of API pollution in 258 of the world's rivers, representing the environmental influence of 471.4 million people across 137 geographic regions. Samples were obtained from 1,052 locations in 104 countries (representing all continents and 36 countries not previously studied for API contamination) and analyzed for 61 APIs. Highest cumulative API concentrations were observed in sub-Saharan Africa, south Asia, and South America. The most contaminated sites were in low- to middle-income countries and were associated with areas with poor wastewater and waste management infrastructure and pharmaceutical manufacturing. The most frequently detected APIs were carbamazepine, metformin, and caffeine (a compound also arising from lifestyle use), which were detected at over half of the sites monitored. Concentrations of at least one API at 25.7% of the sampling sites were greater than concentrations considered safe for aquatic organisms, or which are of concern in terms of selection for antimicrobial resistance. Therefore, pharmaceutical pollution poses a global threat to environmental and human health, as well as to delivery of the United Nations Sustainable Development Goals.
Rivers, the main source of the domestic water supply in Malaysia, have been threatened by frequent flooding in recent years. This study aims to assess human health risks associated with exposure to concentrated heavy metals in a flood-prone region of Malaysia and investigate the affected individuals' willingness to participate in managing water resources. Hazard indices and cancer risks associated with water contamination by heavy metals have been assessed following the method prescribed by the US Environmental Protection Agency. Yearly data of heavy metal contamination (Cd, Cr, Pb, Zn, Fe), water quality parameters (DO, BOD, COD, pH), and climatic information (annual rainfall, annual temperature) have been collected from the Department of Environment and Meteorological Department of Malaysia, respectively. The inductively coupled plasma mass spectrometry technique has been used by the department of environment for analyzing heavy metal concentration in river water samples. In this study, data from a stratified random sample of households in the affected region were analyzed, using partial least squares structural equation modeling, to predict the link between individuals' perceptions and attitudes about water resources and their willingness to engage in water management program. The health risk estimation indicated that the hazard index values were below the acceptable limit, representing no non-carcinogenic risk to adults and children residing in the study area via oral intake and dermal adsorption of water. However, the calculated value for cancer risk signified possible carcinogenic risks associated with Pb and Cd. In general, contamination due to pollution and flooding tends to increase in the basin region, and appropriate management is needed. The results identified perceived water quality as a significant factor influencing people's attitudes toward involvement in water management programs. As in many developing countries, there is no legal provision guaranteeing public representation in water management in Malaysia. The conclusion discusses the importance of these for the literature and for informing future policy actions.
The prolonged persistence of toxic arsenic (As) in environment is due to its non-biodegradable characteristic. Meanwhile, several studies have reported higher concentrations of As in Langat River. However, it is the first study in Langat River Basin, Malaysia, that As concentrations in drinking water supply chain were determined simultaneously to predict the health risks of As ingestion. Water samples collected in 2015 from the four stages of drinking water supply chain were analysed for As concentration by inductively coupled plasma mass spectrometry. Determined As concentrations along with the time series data (2004-2015) were significantly within the maximum limit 0.01 mg/L of drinking water quality standard set by World Health Organization. The predicted As concentration by auto-regression moving average was 3.45E-03 mg/L in 2020 at 95% level based on time series data including climatic control variables. Long-term As ingestion via household filtration water at Langat Basin showed no potential lifetime cancer risk (LCR) 9.7E-06 (t = 6.68; p = 3.37E-08) as well as non-carcinogenic hazard quotient (HQ) 4.8E-02 (t = 6.68; p = 3.37E-08) risk at 95% level. However, the changing landscape, ex-mining ponds and extensive use of pesticides for palm oil plantation at Langat Basin are considered as the major sources of increased As concentration in Langat River. Therefore, a two-layer water filtration system at Langat Basin should be introduced to accelerate the achievement of sustainable development goal of getting safe drinking water supply.
The application of organophosphorus pesticides (OPPs) increased gradually because of the rise in global food demand that triggered the agriculture sector to increase the production, leading to OPP residues in the surface water. This study elucidated the presence of OPPs and estimated its ecological risk in the riverine ecosystem of the urbanised Linggi River, Negeri Sembilan, Malaysia. The OPP concentration in surface water was determined using solid-phase extraction method and high-performance liquid chromatography coupled with diode array detection. Further, the ecological risk was estimated by using the risk quotient (RQ) method. The three OPPs, i.e. chlorpyrifos, diazinon, and quinalphos were detected with mean concentrations of 0.0275 µg/L, 0.0328 µg/L, and 0.0362 µg/L, respectively. The OPPs were at high risk (in general and worst cases) under acute exposure. The estimated risk of diazinon was observed as medium for general (RQm = 0.5857) and high for worst cases (RQex = 4.4678). Notably, the estimated risk for chlorpyrifos was high for both general and worst cases (RQm = 1.9643 and RQex = 11.5643) towards the aquatic ecosystem of the Linggi River. Chronic risk of quinalphos remains unknown because of the absence of toxicity endpoints. This study presented clear knowledge regarding OPP contamination and possible risk for aquatic ecosystems. Hence, OPPs should be listed as one of the main priority contaminants in pesticide mitigation management in the future.
Contamination by endocrine disrupting compounds (EDCs) concerns the security and sustainability of a drinking water supply system and human exposure via water consumption. This study analyzed the selected EDCs in source (river water, n = 10) and supply (tap water, n = 155) points and the associated risks. A total of 14 multiclass EDCs was detected in the drinking water supply system in Malaysia. Triclosan (an antimicrobial agent) and 4-octylphenol (a plasticizer) were only detected in the tap water (up to 9.74 and 0.44 ng/L, respectively). Meanwhile, chloramphenicol and 4-nonylphenol in the system were below the method detection limits. Bisphenol A was observed to be highest in tap water at 66.40 ng/L (detection: 100%; median concentration: 0.28 ng/L). There was a significant difference in triclosan contamination between the river and tap water (p
In this study, the microcrystalline cellulose/metal-organic framework 199 hybrid (MCC/MOF-199) was applied as sorbent for the dispersive micro-solid phase-extraction (D-μSPE) of chlorophenols. The D-μSPE method combined with high-performance liquid chromatography- ultraviolet detection (HPLC-UV) was employed to determine of four chlorophenols including 2-chlorophenol (2-CP), 4-chlorophenol (4-CP), 2,3-dichlorophenol (2,3-DCP), and 2,5-dichlorophenol (2,5-DCP) in aqueous. The main parameters of the D-μSPE process that influence the extraction (i.e. the amount of sorbent, elution condition, extraction time, and pH) were investigated and optimized. Based on the outputs, the presence of MCC on the surface of MOF-199 leads to improve the properties of MOF-199 and the MCC/MOF-199 has the highest sorption capacity, durability, and porosity in comparison with MCC and MOF-199. According to the validation study at the optimized conditions, the linearity for the analytes was achieved in the range from 0.1 to 200 ng mL-1 for 2-CP and 4-CP and 0.15 to 200 ng mL-1 for 2,3-DCP and 2,5-DCP with correlation coefficients between 0.9928 and 0.9965. The limits of detection calculated at S/N=3 were in the range of 0.03-0.05 ng mL-1. Besides, the relative standard deviations (RSDs) for three spiking levels (0.2, 10,100 ng mL-1) do not exceed 6.8% and extraction recoveries are between 81.0% and 88.3%. Finally, the D-μSPE-HPLC-UV method was successfully applied to the analysis of CPs in real water samples (mineral, river and wastewater samples) with good recoveries (95.8 to 99.5%) and satisfactory precisions (RSD < 6.8%).
Toxicity Identification Evaluation (TIE) is a useful method for the classification and identification of toxicants in a composite environment water sample. However, its extension to a larger sample size has been restrained owing to the limited throughput of toxicity bioassays. Here we reported the development of a high-throughput method of TIE Phase I. This newly developed method was assisted by the fluorescence-based cellular oxidation (CO) biosensor fabricated with roGFP2-expressing bacterial cells in 96-well microplate format. The assessment of four river water samples from Langat river basin by this new method demonstrated that the contaminant composition of the four samples can be classified into two distinct groups. The entire toxicity assay consisted of 2338 tests was completed within 12 h with a fluorescence microplate reader. Concurrently, the sample volume for each assay was reduced to 50 μL, which is 600 to 4700 times lesser to compare with conventional bioassays. These imply that the throughput of the CO biosensor-assisted TIE Phase I is now feasible for constructing a large-scale toxicity monitoring system, which would cover a whole watershed scale.
This study aimed to assess the effects of major ecotoxic heavy metals accumulated in the Buriganga and Turag River systems on the liver, kidney, intestine, and muscle of common edible fish species Puntius ticto, Heteropneustes fossilis, and Channa punctatus and determine the associated health risks. K was the predominant and reported as a major element. A large concentration of Zn was detected in diverse organs of the three edible fishes compared with other metals. Overall, trace metal analysis indicated that all organs (especially the liver and kidney) were under extreme threat because the maximum permissible limit set by different international health organizations was exceeded. The target hazard quotient and target cancer risk due to the trace metal content were the largest for P. ticto. Thus, excessive intake of P. ticto from the rivers Buriganga and Turag could result in chronic risks associated with long-term exposure to contaminants. Histopathological investigations revealed the first detectable indicators of infection and findings of long-term injury in cells, tissues, and organs. Histopathological changes in various tissue structures of fish functioned as key pointers of connection to pollutants, and definite infections and lesion types were established based on biotic pointers of toxic/carcinogenic effects. The analysis of histopathological alterations is a controlling integrative device used to assess pollutants in the environment.
The study was performed to examine the occurrence of endocrine disrupting chemicals (EDCs), including four steroid estrogens, one plasticizer, and three preservatives in the Mahakam River, Indonesia. The physicochemical analysis of river water and sediment quality parameters were determined as well as the concentration of EDCs. The range of values for pH, total dissolved solids (TDS), dissolved oxygen (DO), biochemical oxygen demand (BOD), total suspended solids (TSS), nitrate, ammonium, phosphate, and oil/grease in river water and sediment were higher than recommended limits prescribed by the World Health Organization's Guidelines for Drinking-water Quality (GDWQ). Bisphenol A (BPA) was the most widely found EDC with the highest concentration level at 652 ng/L (mean 134 ng/L) in the river water and ranged from ND (not detected) to 952 ng/L (mean 275 ng/L) in the sediment. Correlation analysis to investigate the relationship between the EDCs' concentrations in water and sediment also revealed a significant correlation (R2 = 0.93) between the EDCs' concentrations. High concentrations of EDCs are found in urban and residential areas because these compounds are commonly found in both human and animal bodies, resulting in the disposal of EDCs into canals and rivers in urban and suburban areas, as well as livestock manure and waste that is generated from intensive livestock farming around the suburban area.
Soil temperature has a vital importance in biological, physical and chemical processes of terrestrial ecosystem and its modeling at different depths is very important for land-atmosphere interactions. The study compares four machine learning techniques, extreme learning machine (ELM), artificial neural networks (ANN), classification and regression trees (CART) and group method of data handling (GMDH) in estimating monthly soil temperatures at four different depths. Various combinations of climatic variables are utilized as input to the developed models. The models' outcomes are also compared with multi-linear regression based on Nash-Sutcliffe efficiency, root mean square error, and coefficient of determination statistics. ELM is found to be generally performs better than the other four alternatives in estimating soil temperatures. A decrease in performance of the models is observed by an increase in soil depth. It is found that soil temperatures at three depths (5, 10 and 50 cm) could be mapped utilizing only air temperature data as input while solar radiation and wind speed information are also required for estimating soil temperature at the depth of 100 cm.
Managers of water quality and water monitoring programs are often faced with constraints in terms of budget, time, and laboratory capacity for sample analysis. In such situation, the ideal solution is to reduce the number of sampling sites and/or monitored variables. In this case, selecting appropriate monitoring sites is a challenge. To overcome this problem, this study was conducted to statistically assess and identify the appropriate sampling stations of monitoring network under the monitored parameters. To achieve this goal, two sets of water quality data acquired from two different monitoring networks were used. The hierarchical agglomerative cluster analysis (HACA) were used to group stations with similar characteristics in the networks, the time series analysis was then performed to observe the temporal variation of water quality within the station clusters, and the geo-statistical analysis associated Kendall's coefficient of concordance were finally applied to identify the most appropriate and least appropriate sampling stations. Based on the overall result, five stations were identified in the networks that contribute the most to the knowledge of water quality status of the entire river. In addition, five stations deemed less important were identified and could therefore be considered as redundant in the network. This result demonstrated that geo-statistical technique coupled with Kendall's coefficient of concordance can be a reliable method for water resource managers to identify appropriate sampling sites in a river monitoring network.
The environmental reservoirs of sulfonamide (SA) resistome are still poorly understood. We investigated the potential sources and reservoir of SA resistance (SR) in Larut River and Sangga Besar River by measuring the SA residues, sulfamethoxazole resistant (SMXr) in bacteria and their resistance genes (SRGs). The SA residues measured ranged from lower than quantification limits (LOQ) to 33.13 ng L-1 with sulfadiazine (SDZ), sulfadimethoxine (SDM) and SMX as most detected. Hospital wastewater effluent was detected with the highest SA residues concentration followed by the slaughterhouse and zoo wastewater effluents. The wastewater effluents also harbored the highest abundance of SMXr-bacteria (107 CFU mL-1) and SRGs (10-1/16S copies mL-1). Pearson correlation showed only positive correlation between the PO4 and SMXr-bacteria. In conclusion, wastewater effluents from the zoo, hospital and slaughterhouse could serve as important sources of SA residues that could lead to the consequent emergence of SMXr-bacteria and SRGs in the river.
The upper catchment region of the Baram River in Sarawak (Malaysian Borneo) is undergoing severe land degradation due to soil erosion. Heavy rainfall with high erosive power has led to a number of soil erosion hotspots. The goal of the present study is to generate an understanding about the spatial characteristics of seasonal and annual rainfall erosivity (R), which not only control sediment delivery from the region but also determine the quantity of material potentially eroded. Mean annual rainfall and rainfall erosivity range from 2170 to 5167 mm and 1632 to 5319 MJ mm ha-1 h-1 year-1, respectively. Seasonal rainfall and rainfall erosivity range from 848 to 1872 mm and 558 to 1883 MJ mm ha-1 h-1 year-1 for the southwest (SW) monsoon, 902 to 2200 mm and 664 to 2793 MJ mm ha-1h-1year-1 for the northeast (NE) monsoon and 400 to 933 mm and 331 to 1075 MJ mm ha-1 h-1 year-1 during the inter-monsoon (IM) period. Linear regression, Spearman's Rho and Mann Kendall tests were applied. Considering the regional mean rainfall erosivity in the study area, all the methods show an overall non-significant decreasing trend (- 9.34, - 0.25 and - 0.30 MJ mm ha-1 h-1 year-1, respectively for linear regression, Spearman's Rho and Mann Kendall tests). However, during SW monsoon and IM periods, rainfall erosivity showed a non-significant decreasing trend (- 25.45, - 0.52, - 0.40, and - 8.86, - 1.07, - 0.77 MJ mm ha-1 h-1 year-1, respectively) whereas in NE, monsoon season erosivity showed a non-significant increasing trend (14.90, 1.59 and 1.60 MJ mm ha-1 h-1 year-1, respectively). The mean erosivity density ranges from 0.77 to 1.38 MJ ha-1 h-1 year-1 and shows decreasing trend. Spatial distribution pattern of erosivity density indicates significantly higher occurrence of erosive rainfall in the lower elevation portion of the study area. The spatial pattern of mean rainfall erosivity trends (linear, Spearman's Rho and Mann Kendall) suggests that the study area can be divided into two zones with increasing rainfall erosivity trends in the northern zone and decreasing trends in the southern zone. These results can be used to plan conservation measures to reduce sediment delivery from localized soil erosion hotspots.