Stream Samples Research Articles

Advancing chemical lability assessments of organic matter using a synthesis of FT-ICR MS data across diverse environments and experiments

Patterns in Fourier transform ion cyclotron resonance mass spectrometry (FT-ICR MS) data provide perspective on how organic matter (OM) character is shaped by natural processes. Here, we reevaluate and update the molecular lability boundary (MLB) approach to assess OM lability using a synthesis of FT-ICR MS data. Now included are MLBL (biolability) indices (i.e., the OM proportion of hydrogen-to-carbon ratios ≥ 1.5) of freshwaters, plant litter and biochar leachates, soils, and oils across the US, trends in OM and dissolved OM (DOM) lability from laboratory experiments examining isolated microbial, photochemical, and thermal degradation, and biogeochemical interpretations of biolability patterns across ecosystems influenced by human activity (e.g., fertilizer addition and agricultural management). Photo-processing increased the hydrogen saturation of OM, describing products of higher biolability (>MLBL values). DOM MLBL values decreased during microbial and thermal degradation processes. Laboratory experiments with isolated treatments showed larger changes in MLBL than exhibited by field samples from systems managed by humans. We interpret changes in N- and/or S-containing DOM above the MLB as the production or use of heterogeneously biolabile material. We interpret heterogeneously labile DOM composition to indicate autochthonous production, biomass growth, nutrient accumulation, or biological degradation in stream and soil samples. The most recent data in our synthesis suggest that the MLB approach should be reframed to provide lability indices for biotic, thermal, and photochemical processes. A broader perspective on lability provides a useful tool to decompose large, complex, and process-driven DOM data into more simple and informative indicators of trends in ecosystem form and function.

A review of the zone broadening contributions in free-flow electrophoresis.

The broadening of analyte streams, as they migrate through a free-flow electrophoresis (FFE) channel, often limits the resolving power of FFE separations. Under laminar flow conditions, such zonal spreading occurs due to analyte diffusion perpendicular to the direction of streamflow and variations in the lateral distance electrokinetically migrated by the analyte molecules. Although some of the factors that give rise to these contributions are inherent to the FFE method, others originate from non-idealities in the system, such as Joule heating, pressure-driven crossflows, and a difference between the electrical conductivities of the sample stream and background electrolyte. The injection process can further increase the stream width in FFE separations but normally influencing all analyte zones to an equal extent. Recently, several experimental and theoretical works have been reported that thoroughly investigate the various contributions to stream variance in an FFE device for better understanding, and potentially minimizing their magnitudes. In this review article, we carefully examine the findings from these studies and discuss areas in which more work is needed to advance our comprehension of the zone broadening contributions in FFE assays.

Fixed-Time System Identification Using Concurrent Learning.

This article presents a fixed-time (FxT) system identifier for continuous-time nonlinear systems. A novel adaptive update law with discontinuous gradient flows of the identification errors is presented, which leverages concurrent learning (CL) to guarantee the learning of uncertain nonlinear dynamics in a fixed time, as opposed to asymptotic or exponential time. More specifically, the CL approach retrieves a batch of samples stored in a memory, and the update law simultaneously minimizes the identification error for the current stream of samples and past memory samples. Rigorous analyses are provided based on FxT Lyapunov stability to certify FxT convergence to the stable equilibria of the gradient descent flow of the system identification error under easy-to-verify rank conditions. The performance of the proposed method in comparison with the existing methods is illustrated in the simulation results.

Reactive buffering window trajectory segmentation: RBW-TS

Mobility data of a moving object, called trajectory data, are continuously generated by vessel navigation systems, wearable devices, and drones, to name a few. Trajectory data consist of samples that include temporal, spatial, and other descriptive features of object movements. One of the main challenges in trajectory data analysis is to divide trajectory data into meaningful segments based on certain criteria. Most of the available segmentation algorithms are limited to processing data offline, i.e., they cannot segment a stream of trajectory samples. In this work, we propose an approach called Reactive Buffering Window - Trajectory Segmentation (RBW-TS), which partitions trajectory data into segments while receiving a stream of trajectory samples. Another novelty compared to existing work is that the proposed algorithm is based on multidimensional features of trajectories, and it can incorporate as many relevant features of the underlying trajectory as needed. This makes RBW-TS general and applicable to numerous domains by simply selecting trajectory features relevant for segmentation purposes. The proposed online algorithm incurs lower computational and memory requirements. Furthermore, it is robust to noisy samples and outliers. We validate RBW-TS on three use cases: (a) segmenting human-movement trajectories in different modes of transportation, (b) segmenting trajectories generated by vessels in the maritime domain, and (c) segmenting human-movement trajectories in a commercial shopping center. The numerical results detailed in the paper demonstrate that (i) RBW-TS is capable of detecting the true breakpoints of segments in all three usecases while processing a stream of trajectory points; (ii) despite low memory and computational requirements, the performance in terms of the harmonic mean of purity and coverage is comparable to that of state-of-the-art batch and online algorithms; (iii) RBW-TS achieves different levels of accuracy depending on the various internal parameter estimation methods used; and (iv) RBW-TS can tackle real-world trajectory data for segmentation purposes.

Output regulation of stochastic sampled-data systems with post-processing internal model

This paper deals with the output regulation problem (ORP) of a linear time-invariant (LTI) system in the presence of sporadically sampled measurement streams with the inter-sampling intervals following a stochastic process. Under such sporadically available measurement streams, a regulator consisting of a hybrid observer, continuous-time post-processing internal model, and stabilizer are proposed, which resets with the arrival of new measurements. The resulting system exhibits a deterministic behavior except for the jumps that occur at random sampling times and therefore the overall closed-loop system can be categorized as a piecewise deterministic Markov process (PDMP). In existing works on ORPs with aperiodic sampling, the requirement of boundedness on inter-sampling intervals precludes extending the solution to the random sampling intervals with possibly unbounded support. Using the Lyapunov-like theorem for the stability analysis of stochastic systems, we offer sufficient conditions to ensure that the overall closed-loop system is mean exponentially stable (MES) and the objectives of the ORP are achieved under stochastic sampling of measurement streams. The resulting LMI conditions lead to a numerically tractable design of the hybrid regulator. Finally, with the help of an illustrative example, the effectiveness of the theoretical results are verified.

Unveiling relationships between ecosystem services and aquatic communities in urban streams

River and stream ecosystems within cities can provide important Ecosystem Services (ES) to urban population along with the maintenance of biodiversity. Increasing urbanization with land use change can affect biodiversity, impacting ES provision, but the relationships between biota and ES are complex and poorly understood. This study aims to explore relationships between aquatic biodiversity (communities’ composition and structure), urbanization and ES provided by urban streams. Nine streams were surveyed within a city area (up to 8 km of the city centre) focusing on common biological indicators (i.e., macroinvertebrates and diatoms), as well as several indicators of Provisioning (N = 7), Regulation (N = 14) and Cultural (N = 23) services for this type of ecosystem. Urban stream sampling sites were also assessed in terms of their urbanization degree, according to the surrounding imperviousness area (IMD). Pearson correlations showed trends of negative relationships between IMD and both Provisioning and Regulating services. Yet, urbanization effects on the biota seemed to be mitigated due to enhanced hidromorphological site features. The community structure and composition of invertebrates and diatoms was differently associated to ES (BIOENV analysis). Whereas macroinvertebrate communities related specifically with Provisioning and Regulating indicators, the diatom responded just to regulating indicators. Overall, this study showed that aquatic biodiversity is linkable with ES provided by urban streams, and such relationship depends on specific ES indicators mainly for Provisioning and Regulating services. Additionally, macroinvertebrate communities can be used as a suitable indicator for the potential of streams in supplying Provisioning and Regulating ecosystem services. This shows that their indicator value goes beyond their known potential as indicators of structural and functional integrity of river ecosystems. These results also reinforce the need to protect nature associated to running water ecosystems in urbanized areas, as they provide green and blue solutions for the sustainability of cities.

Routine Estimation of Dissolved Organic Matter Sources Using Fluorescence Data and Linear Least Squares

Dissolved organic matter (DOM) is an important component of the biogeochemistry and ecosystem function of streams and rivers. Unlike inorganic nitrogen nutrients, organic nitrogen (DON) nutrients can vary considerably depending on the contributions of various sources. The properties of DOM in natural waters have been measured using fluorescence spectroscopy, which is inexpensive compared to more sophisticated chemical analysis and is fast enough to enable its use in routine water quality monitoring. However, estimating the contributions of DOM sources to surface waters from fluorescence data in a similarly efficient manner remains an area of active research. In this study, we develop a simple linear regression method for estimating the relative amounts of DOM sources in a stream or river sample. The regression estimates are more accurate than those of previous approaches and are orders of magnitude faster to compute. Codes and data to implement the method are provided for a variety of computing environments to facilitate use for water quality and research applications.

Wide-spread microbial sulfate reduction (MSR) in northern European freshwater systems: Drivers, magnitudes and seasonality

Microbial sulfate reduction (MSR), which transforms sulfate into sulfide through the consumption of organic matter, is an integral part of sulfur and carbon cycling. Yet, the knowledge on MSR magnitudes is limited and mostly restricted to snap-shot conditions in specific surface water bodies. Potential impacts of MSR have consequently been unaccounted for, e.g., in regional or global weathering budgets. Here, we synthesize results from previous studies on sulfur isotope dynamics in stream water samples and apply a sulfur isotopic fractionation and mixing scheme combined with Monte Carlo simulations to derive MSR in entire hydrological catchments. This allowed comparison of magnitudes both within and between five study areas located between southern Sweden and the Kola Peninsula, Russia. Our results showed that the freshwater MSR ranged from 0 to 79 % (interquartile range of 19 percentage units) locally within the catchments, with average values from 2 to 28 % between the catchments, displaying a non-negligible catchment-average value of 13 %. The combined abundance or deficiency of several landscape elements (e.g., the areal percentage of forest and lakes/wetlands) were found to indicate relatively well whether or not catchment-scale MSR would be high. A regression analysis showed specifically that average slope was the individual element that best reflected the MSR magnitude, both at sub-catchment scale and between the different study areas. However, the regression results of individual parameters were generally weak. The MSR-values additionally showed differences between seasons, in particular in wetland/lake dominated catchments. Here MSR was high during the spring flood, which is consistent with the mobilization of water that under low-flow winter periods have developed the needed anoxic conditions for sulfate-reducing microorganisms. This study presents for the first time compelling evidence from multiple catchments of wide-spread MSR at levels slightly above 10 %, implying that the terrestrial pyrite oxidation may be underestimated in global weathering budgets.

Spatio-temporal variations in oxygen and deuterium isotope of different water sources in Sikkim Himalayas: An understanding towards regional scale basin hydrology

The glaciated Himalayan region is the third largest storehouse of freshwater in its frozen form that feeds several mega river systems. Especially the north-eastern Himalayas, where the snow and glacial stock depend on various moisture sources. This study presents a detailed investigation of water sources in the Teesta watershed in terms of oxygen (δ18O) and deuterium (δD/δ2H) values. The study helped understand the Spatio-temporal variability in the isotopic composition of water and moisture sources. Progressive depletion of δ18O values in the stream water as moving towards the non-renewable glacial source indicates orographic ascent attributed to cooling and subsequent rainout. This effect is profound in the case of the western tributary above Chungthang, the Lachen Chu river. The computed d-excess values suggest the dominance of mid-latitude westerlies in the high-altitude perennial streams of the west and north Sikkim. Also, a deterministic Monte Carlo-based three endmember δ18O-d-excess mixing model is developed to quantify the contribution of source endmembers such as snowmelt, rainfall, and glacial melt in the river streams and waterfalls of the Rathong river as well as Lachen Chu and Lachung Chu rivers above their confluence at Chungthang. With the model being iterated 10,000 times for each waterfall and stream sample, the results have been obtained at the mean, 25th, 75th and 95th percentiles. The model results in the mean glacial ice-melt contribution between 40% and 47% in different seasons, with the standard deviation between ± 3.5% and ± 10%.

Single particle inductively coupled plasma mass spectrometry: A new method to detect geochemical anomalies in stream sediments

Single particle inductively coupled plasma mass spectrometry (spICP-MS) offers a new tool to explore for concealed mineral deposits. Through detection of metal nanoparticles (NPs) present in stream sediments, subtle geochemical anomalies may be identified farther from their source. Geochemical exploration with spICP-MS lowers the detection limit substantially from conventional ICP-MS for insoluble elements of interest. Analyzing only 197Au signal generated by individual NPs rather than an integrated signal, which can have a significant contribution from detector noise, resulted in a 53-fold reduction in detection limit compared to a digestion/quadrupole ICP-MS determination (21 ng∗L−1 to 0.39 ng∗L−1). Method development included analysis of dilute suspensions of manufactured 50 nm Au particles and three stream sediment samples (5–15 g sonicated in 20 mL 25 μM 11-mercaptoundeconoic acid). Au and Ag NPs were identified in the two sites downstream from a known area of mineralization, whereas none were detected in a background stream sediment site. Average particle numbers and masses of Au and Ag were highest in the sample closest to known mineralization. Additional results indicated that use of surfactant is an important contribution to the procedure. This pilot study of three sites provides a proof of concept in the analysis of spICP-MS for determination of Au and Ag in stream sediment samples, which could augment or improve current cyanide/acid dissolution/ICPMS methods for the ultra-trace concentration range.

Geochemical Survey and Estimation of Baseline Concentrations of Major and Trace Elements in Stream Water, Uttar Pradesh, India: Implication for Environmental Studies

Abstract Stream water plays an important role in the development of habitats. It is one of the important sources of water used for drinking and irrigation in the region. Before using, it is necessary to test the quality of all types of surface water available for various use. A geochemical study of stream water has been conducted in parts of Pratapgarh, Raebareli, and Allahabad districts of Uttar Pradesh to assess its suitability for domestic purposes and establish the baseline concentration of major ions, trace and REEs. 20 samples of stream water from different locations of 1st or 2nd order streams were collected during post-monsoon period, from 18th to 31st October 2021. Different hydrochemical parameters such as pH, electrical conductivity (EC), temperature, dissolved oxygen (DO), salinity, total dissolved solids (TDS), major cations and anions were analysed. In order to obtain maximum quality and purity of water, the stream water samples were analyzed by ICP-MS analytical method in the chemical lab for 47 trace elements including REEs contents. The obtained values of each parameter have been compared with the standard values recommended by BIS and WHO. The value of each element except uranium has been found to be within the desirable and permissible limits prescribed by BIS (2012) and WHO (2006). Selenium and arsenic have been found to be marginally exceed the permissible limits. The pH values of all stream waters in the study area range from 7.14 to 8.86 with an average value of 7.86 indicating an alkaline nature of stream water. The concentration of uranium in stream water varied from 1.5 ppb to 48.67 ppb with a mean value of 7.9 ppb. It is observed that wherever concentration of uranium in the samples increased, the pH as well as the bicarbonate level increased accordingly. Correlation coefficient revealed that uranium is strongly correlated with bicarbonate (r=0.67), moderately with sodium (r=6.1), and low positively correlated with the concentration of pH (r=0.34), EC (r=0.52), and salinity (r=0.52), indicates the same origin. Water quality index (WQI) of water was determined for suitability of drinking purpose, revealed that 65% water samples fall in excellent category and 30% water samples fall in good category while only 5% water sample are in poor category. Trilinear plot of sample shows that most of the stream water samples are Ca-Mg-HCO3 type.

A CROSS SECTIONAL STUDY OF ASYMPTOMATIC BACTERIURIA IN TYPE 2 DIABETES MELLITUS AND THEIR ANTIBIOTIC SUSCEPTIBILITY

Background: Diabetes is a metabolic disease characterized by hyperglycemia because of defect in insulin secretion or action or both. Asymptomatic bacteriuria (ASB) is common in diabetics and elderly which predisposes them to severe urinary tract infections. Reports on prevalence, etiology, antibiotic susceptible pattern are sparse in southern India. This study aimed to determine the prevalence of asymptomatic bacteriuria in patients with type 2 Diabetes mellitus Material & Method: This cross sectional study was conducted among the diabetic patients presenting to inpatient and outpatient ward in department of general medicine AVMC&H with ailments other than urinary tract infection were included. patients with symptoms of UTI, vulvovaginitis, pregnancy, recent history of hospitalization, recent urinary tract instrumentation, use of antimicrobial in last 14 days or UTI in recent past were excluded. Mid stream urine samples were collected from consented subjects. Urine samples were processed and examined for the various pathogens using the standard microbiological procedures. The spectrum of organisms causing asymptomatic bacteriuria and their antibiotic susceptibility prole. All data were collected by the investigator and was analysed statistically to nd the level of signicance of the study using SPSS v21. Results: In the present study total of 150 diabetic patients fullling inclusion criteria are included, with mean age of 55.6±10yrs, among them 66 were female and 84 were male patients. The isolates found to be in 50 patients (33.33%) out of 150 patients. Among the isolates, majority were with Escherichia Coli 52%, followed with 22% showing Klebsiella pneumoniae, 16% with Enterococcus species, 6% with proteus and 2% with Coagulase negative staphylococcus. Conclusion:The present study document 33.33% of the patients showing the asymptomatic bacteriuria. Among the isolates Escherichia coli was the most common organism among the patients with ASB. The presence of isolates was also correlated with the poor glycaemic control among the study participants, as one of the risk factor for ASB. Most isolates showed multiple resistance, indicating the need to speed up sensitization against antibiotic abuse

The Behaviour of Sheep around a Natural Waterway and Impact on Water Quality during Winter in New Zealand.

Access of livestock, such as cattle, to waterways has been shown to be a cause of poor water quality due to pugging damage and excretion entering the water. In New Zealand, regulations require that cattle, deer, and pigs are excluded from accessing waterways, but there are no such requirements for sheep. The current study utilised 24 h video cameras, global positioning system units, and triaxial accelerometers to observe the interaction of Romney ewes (n = 40) with a natural waterway. Ewes were either restricted (week 1) or given access to a reticulated water trough (week 2). Proximity data showed that ewes spent more time within 3 m of the waterway when the trough was unrestricted than when restricted (14.1 ± 5.7 and 10.8 ± 5.1 min/ewe/day, respectively; p < 0.05). Ewes travelled shorter distances on the steeper areas of paddock than flatter areas. Similarly, ewes showed a spatial preference for the flat and low sloped areas of the paddock. Concentrations of suspended sediment and total phosphorus were higher during access to a reticulated water trough which coincided with the week with more rainy days. Phosphorus and E. coli concentrations in the stream water samples were the above recommended Australian and New Zealand Environment and Conservation Council water quality guidelines, especially after rainy days, but did not appear to be directly related to sheep activity. Overall, the results suggest that during winter, ewes interacted very little with the waterway and were thus unlikely to influence the levels of nutrient and pathogens in the waterway.

Sulfate in streams and groundwater in a cold region (Yukon Territory, Canada): Evidence of weathering processes in a changing climate

Analyses of the sulfur (S) and oxygen (O) stable isotope ratios (δ34SSO4 and δ18OSO4) of dissolved sulfate in streams and groundwater in Yukon Territory (YT, Canada) indicates that the dominant source of this major ion is oxidation of sulfide minerals. In these streams, sulfate has a large range in δ34SSO4 values (−19 to +10‰), which is consistent with the lower portion of the documented range for δ34S of sulfides in bedrock in YT (∼ −35 to +55‰). Furthermore, the large majority of the δ18OSO4 data plot within the expected field for sulfide oxidation in cross-plots of δ18OSO4 versus the O isotope ratios of ambient water (δ18OH2O). δ18OSO4 values plotting above that field were likely affected by microbial sulfate reduction, a process that enriches residual sulfate in both 34S and 18O. The stable isotope data indicate that dissolution of marine-evaporite gypsum, which has higher δ34SSO4 and δ18OSO4 values compared to all stream and groundwater samples, is a minor to negligible source of sulfate in the YT streams. Association of sulfate with other solutes indicates release of various metals from sulfide minerals, and suggests dominance of silicate weathering in response to oxidation of the sulfides. Variations in sulfate concentrations in YT streams are largely related to geology, while terrain and climate, including extent of permafrost, are also important factors. Long-term monitoring of sulfate concentrations in YT streams indicates increasing concentrations over time, in both streams impacted by mining, and in streams that have not been affected much by historical in-catchment industrial activities. Increases were largest in streams in northern and central-south YT in the presence of thawing continuous to discontinuous permafrost.

National-scale investigation of dual nitrate isotopes and chloride ion in South Korea: Nitrate source apportionment for stream water

Nitrate sources in surface water have been identified using dual-isotope compositions of nitrate with various tools to efficiently manage the water quality at the local scale. Correlation between Cl and NO3 has also been used to identify NO3. In this study, we assess the reliability of the dual-isotope approach and Cl in terms of nitrate source apportionment. To this end, we collected stream water samples throughout South Korea to estimate nitrate sources in streams and determine whether the land-use pattern was closely related to nitrate sources. The δ15N–NO3 ranging from −1.3 to 14.8‰ showed a spatial distribution that was lower in mountain ranges (<7‰) than plain areas (>8‰). The Cl concentration in this national-scale distribution was also assessed. The relationship between the proportion of Cl and δ15N–NO3 classifies nitrate sources into areas characterized by three land-use patterns: (1) agricultural and business areas, (2) forests in highlands, and (3) lowland forests, of which (1) had proportions of Cl >50%, while (2) and (3) were <50%. The samples in (3) showed δ15N–NO3 values > 6‰, similar to those of (1). Deuterium excess of samples was negatively correlated (R2 = 0.53) with δ15N–NO3, accounting for the fact that δ15N–NO3 reflected land-use patterns. Samples were dominantly affected by agriculture-derived sources and domestic sewage showed NO3/Cl of <0.4 and δ15N–NO3 of >6‰. These results suggest that nitrate source apportionment should be comprehensively evaluated considering the dual-isotope approach, land-use patterns, and Cl proportions.

Assessment of blend uniformity in a stream sampler device using Raman spectroscopy

This study describes the first implementation of Raman spectrometer in a stream sampler for the in-line monitoring of low drug concentration in poor flowability powder blends. Raman spectra were continuously acquired as the powder blends flowed through the stream sampler operating with a paddle wheel speed of 10 RPM and used to develop the calibration models. A calibration model was developed to quantify caffeine concentration from 1.50 to 4.50% w/w using Partial Least Squares Regression (PLS-R). Three test set blends were used to assess the prediction errors of the calibration model. Caffeine concentration was predicted for the test set blends with a root mean square error of prediction of 0.21% w/w and a low bias of −0.03% w/w. The calibration model showed good prediction performance with an estimated sample mass of 83 mg. Variographic analysis demonstrated the low process variance of the real-time spectral acquisition through minimum practical error and sill values. The results showed the ability of the Raman spectrometer coupled with the stream sampler to monitor low drug concentration for poor flowability blends.

Interpretable SAM-kNN Regressor for Incremental Learning on High-Dimensional Data Streams

ABSTRACT In many real-world scenarios, data are provided as a potentially infinite stream of samples that are subject to changes in the underlying data distribution, a phenomenon often referred to as concept drift. A specific facet of concept drift is feature drift, where the relevance of a feature to the problem at hand changes over time. High-dimensionality of the data poses an additional challenge to learning algorithms operating in such environments. Common scenarios of this nature can for example be found in sensor-based maintenance operations of industrial machines or inside entire networks, such as power grids or water distribution systems. However, since most existing methods for incremental learning focus on classification tasks, efficient online learning for regression is still an underdeveloped area. In this work, we introduce an extension to the SAM-kNN Regressor that incorporates metric learning in order to improve the prediction quality on data streams, gain insights into the relevance of different input features and based on that, transform the input data into a lower dimension in order to improve computational complexity and suitability for high-dimensional data. We evaluate our proposed method on artificial data, to demonstrate its applicability in various scenarios. In addition to that, we apply the method to the real-world problem of water distribution network monitoring. Specifically, we demonstrate that sensor faults in the water distribution network can be detected by monitoring the feature relevances computed by our algorithm.

Applying Chemical and Statistical Analysis Methods to Evaluate Water and Stream Sediments around the Coal Mine Area in Dazhu, China

In this study, groundwater, stream water, and stream sediment samples were collected from a coal mine area in Dazhu, Southwestern China, and hydrogeochemical, multivariate, and X-ray analyses were conducted to examine the effects of coal mine pollution. The groundwater and stream samples were slightly acidic to alkaline (6.7 to 8.2). Typically, the water samples were dominated by Ca2+ + Mg2+–HCO3− and Ca2+ + Mg2+–Cl−. SO42− originates from gypsum dissolution and pyrite oxidation, and Ca2+ and Mg2+ may be related to the dissolution of carbonate. According to the Chinese standard and World Health Organization guidelines, the water in the coal mine area is of good quality in terms of its physical and chemical properties, except for the concentration of Mn and Fe, with values of 1925.14 μg/L and 12,872.88 μg/L, respectively. A principal component analysis revealed two groups in which the concentration of metals and metalloids in stream sediments are affected by the coal mine drainage. The Mn and Fe average concentration in the downstream Kongjiagou drain sediment samples was 2035.1 ppm and 6%, respectively. These values were higher than the average Mn and Fe concentration in Xiaojiagou at 453.1 ppm and 2.9%, respectively. Both the Mn and Fe concentration were higher than the background values (640 ppm and 4.4%).

Global triangle estimation based on first edge sampling in large graph streams

Global triangle estimation based on first edge sampling in large graph streams

Effect of solid waste landfill leachates on groundwater quality

Water is a universal solvent which is of inevitable use in our daily activities both domestic and industrial. It sources: ground and surface are indispensable to inhabitants of any community. Population increase over the years is directly proportional to the demand of water. And this has affected the composition and quality of waste generated. The need to dispose wastes result in the use of the simplest method, land filling, without due consideration to its effects on the environment. Land filling method is the breeding ground of leachate which contributes negatively to the quality of groundwater sources. This study aimed at assessing the effect of solid waste landfill leachate on ground water quality in the area. Water samples were collected from five different locations around the study dumpsite in Ajakanga, Ibadan. The samples were transported to the laboratory where the water tests on the physical, chemical, biological and bacteriological characteristics were carried out. The physicochemical parameters analyzed included colour, turbidity, pH, conductivity, TS, TDS, and total hardness while the bacteriological and biological parameters included biological oxygen demand (BOD), total viable count, total coliform count and total fungal count. The results observed varied from samples tested. The colour, turbidity, total hardness and total dissolved oxygen of the samples were within the WHO guideline. The pH samples of the two wells did not conform to WHO specification from 6.5 to 8.5. Both pH were acidic. Conductivity is temperature dependent. Higher conductivities recorded in samples 1, 2, 4 and 5 signified presences of contaminations. Total solids gave an idea of both suspended solids and total dissolved solids. Samples with more than 500mg/l TDS usually have disagreeably strong taste. In the bacteriological loading, only sample 2 showed the presence of Escherichia coli (E. coli). The presence of E. coli in the stream sample indicates feacal coliform contamination which is a potential health risk for individuals exposed to this water. In conclusion, the proximity of wells and the exposure of surface steam to the dumpsite promote groundwater pollution due to leachate migration. This study recommended that wells should be cited at distance recharge area rather than the closed discharge side of the dumpsite. Sinking of borehole was recommended in the area rather than shallow well. The risks of leachate generation can be mitigated by properly designed and engineered landfill sites, such as sites that are constructed on geologically impermeable materials or sites that use impermeable liners made of geo membranes or engineered clay. This will prevent by gravity infiltration and percolation of leachate to the underground water thereby causing contamination. Periodic physicochemical and microbiological treatment of water is of essence.