• Journal of Sensor Science and Technology
• /
• v.30 no.5
• /
• pp.320-325
• /
• 2021

Biochemical oxygen demand (BOD) and chemical oxygen demand (COD) methods are conventional analytical methods to analyze water quality. Both of these methods are technically indirect measurement methods, require complicated preconditions, and are time-consuming. On the other hand, the total organic carbon (TOC) method is a direct and fast measurement method which is more intuitive and accurate than the BOD and COD methods. However, general TOC analysis methods involve complicated processes and high power consumption owing to the process of phase transition from liquid to gas by a high-temperature heater. Furthermore, periodic consumables are also required for the removal of inorganic carbon (IC). Titanium dioxide (TiO₂) is one of the most suitable photocatalysts for simple processes. Its usage involves low power consumption because it only reacts with the organic carbon (OC) without the requirement of any other reagents and extra processes. We investigated a TiO₂ photocatalyst-based TOC analysis for simple and affordable products. TiO₂-coated fiber substrate maintained under carbon included water was exposed to ultraviolet (UV) radiation of wavelength 365 nm. This method is suitable for the real-time monitoring of water pollution because of its fast reaction time. Its linear property is also sufficient to match the real value.

• Journal of Korea Water Resources Association
• /
• v.52 no.3
• /
• pp.207-217
• /
• 2019

This study aims at development and application of a facility that is capable of reducing pollution in water quality by reducing nonpoint source pollutants (NPSP). NPSP originated from the initial rainfall caused not only large catchment of urban area pass a river but also small watershed pass a stream. For this purpose, the performance tests carried out with the field models from the facility based on the preceding study. And the tests induced reduction efficiency of biochemical oxygen demand (BOD), chemical oxygen demand (COD), total nitrogen (T-N) and suspended solid (SS), respectively. The average reduction efficiency obtained by time interval, and the result showed an excellent reduction performance. As a result, the facility satisfied reduction efficiency of NPSP of the proposed standard by the National Institute of Environmental Research, and thus it can be used in practical applications.

• Korean Journal of Agricultural Science
• /
• v.46 no.1
• /
• pp.67-78
• /
• 2019

The purpose of this study was to predict the water quality using the RNN (recurrent neutral network) and LSTM (long short-term memory). These are advanced forms of machine learning algorithms that are better suited for time series learning compared to artificial neural networks; however, they have not been investigated before for water quality prediction. Three water quality indexes, the BOD (biochemical oxygen demand), COD (chemical oxygen demand), and SS (suspended solids) are predicted by the RNN and LSTM. TensorFlow, an open source library developed by Google, was used to implement the machine learning algorithm. The Okcheon observation point in the Geum River basin in the Republic of Korea was selected as the target point for the prediction of the water quality. Ten years of daily observed meteorological (daily temperature and daily wind speed) and hydrological (water level and flow discharge) data were used as the inputs, and irregularly observed water quality (BOD, COD, and SS) data were used as the learning materials. The irregularly observed water quality data were converted into daily data with the linear interpolation method. The water quality after one day was predicted by the machine learning algorithm, and it was found that a water quality prediction is possible with high accuracy compared to existing physical modeling results in the prediction of the BOD, COD, and SS, which are very non-linear. The sequence length and iteration were changed to compare the performances of the algorithms.

• Journal of The Korean Society of Agricultural Engineers
• /
• v.61 no.3
• /
• pp.67-76
• /
• 2019

The objectives of this study were to analyze trends of water pollutants and to evaluate the achievement of water quality standards by subbasins in the Han River. The trends of 40 water pollutants at 232 water quality measurement points were analyzed. Chemical oxygen demand (COD), Total organic carbon (TOC), Total coliforms (TC), et cetera were found to be worsening trend. For evaluation of achievement, we evaluated water quality arithmetic mean with river environment standards and human health standards at representative points of the subbasin. Biochemical oxygen demand (BOD), TOC, Total phosphorus (T-P), Fecal coliforms (FC), TC exceeded water quality standards, and water quality of human health standards was all satisfied. So, we prioritized pollutants. If pollutants exceed water quality standards or were worse, they were classified first pollutants. Although BOD and T-P are first pollutants because of water quality standards excess, they are continuously improved. Also, it is better to maintain current status because water quality management system of BOD and T-P is well prepared. Meanwhile, TOC, TC, and FC exceed water quality standards. Furthermore, they were worse gradually, but there is a lack of management systems such as water quality standards of the effluence facilities. Therefore, it is necessary to supplement the system. The results of this study can be used as primary data for the establishment of water quality standards and selection of management pollutants.

• Journal of Korean Society on Water Environment
• /
• v.27 no.5
• /
• pp.625-633
• /
• 2011

A long-term water quality monitoring in the Han River Basin reveals a consistent increasing trend for the concentration of refractory organic matter (R-OM) in major monitoring sites of the watershed. Because the determination of R-OM concentrations typically requires a long time of microbial incubation, it is essential to present the estimation indices for R-OM for an efficient watershed management. In this study, a number of surface water samples were classified into three groups, each of which were collected from Lake Paldang, rivers at rain and non-rain events, respectively. The corresponding R-OM concentrations were correlated with biochemical oxygen demand (BOD), chemical oxygen demand (COD), and total organic carbon (TOC) concentrations as well as ultraviolet and fluorescence intensities of the filtered samples. Among the traditional organic matter parameters, TOC exhibited the highest correlation coefficient with the R-OM concentrations regardless of the types of the sample groups. The equations for conversing TOC into R-OM concentrations were finally suggested as $0.43{\times}TOC+1.12$, $0.44{\times}TOC+0.61$, $0.24{\times}TOC+1.28$ for river samples at rain and non-rain events, and lake samples, respectively. TOC-BOD(C), the values of the TOC concentrations subtracted by carbon-converted BOD concentrations, was a good index for estimating the absolute concentrations of R-OM. UV absorbance at 254 nm was well correlated with R-OM concentrations of river samples while fluorescence intensities at 350 nm showed an excellent relationship with R-OM concentration of the lake samples. Our results suggests that simple spectroscopic parameters could be applied for in-situ monitoring tool techniques in watersheds.

• Advances in environmental research
• /
• v.9 no.4
• /
• pp.233-249
• /
• 2020

To date, there is no central wastewater (WW) treatment plant in Erbil city, Kurdistan region, Iraq. Therefore, raw WW disposes to the environment and sometimes it used directly for irrigation in some areas of Erbil city. Disposal of the untreated WW to the natural environment and using for irrigation it causes problems for the people and the environment. The aims of the current work were to study the characteristics, design of primary and different secondary treatment units and reusing of produced WW. Raw WW samples from Ashty city-Erbil city were collected and analyzed for twenty three quality parameters such as Total Suspended Solids (TSS), total dissolved solids, total volatile and non-volatile solids, total acidity, total alkalinity, total hardness, five-day Biochemical Oxygen Demand (BOD5), Chemical Oxygen Demand (COD), biodegradability ratio (BOD5/COD), turbidity, etc. Results revealed that some parameters such as BOD5 and TSS were exceeded the standards for disposal of WW. Design and calculations for primary and secondary treatment (biological treatment) processes were presented. Primary treatment units such as screening, grit chamber, and flow equalization tank were designed and detailed calculation were illustrated. While, Conventional Activated Sludge (CAS), Sequencing Batch Reactor (SBR) and Moving Bed Biofilm Reactors (MBBR) were applied for the biological treatment of WW. Results revealed that MBBR was the best and economic technique for the biological treatment of WW. Treated WW is suitable for reusing and there is no restriction on use for irrigation of green areas inside Ashty city campus.

• Journal of the Korean Society of Environmental Restoration Technology
• /
• v.23 no.6
• /
• pp.137-149
• /
• 2020

This study was carried out to analyze the monthly runoff concentration on non rainfall days in order to prepare basic data to compare the runoff concentration on rainfall days in 7 forest watersheds in the Republic of Korea. Forest stream water has been collected through 15 times of sampling in each watershed and analyzed based on the changes in concentration of Biochemical Oxygen Demand(BOD), Chemical Oxygen Demand(COD), Total Organic Carbon(TOC), Total Nitrogen(TN), and Total Phosphorus(TP). The average concentration was 0.8 mg/L for BOD, 1.4 mg/L for COD, 0.8 mg/L for TOC, 1.85 mg/L for TN and 0.002 mg/L for TP during non rainfall days. Coniferous forested watersheds showed higher value of TN and TP concentration. Concentrations of BOD and TP in early March (p<0.01) were affected by melt water flow input in spring season. Significant differences (p<0.01) in concentrations were observed in BOD and TOC, indicating seasonal rainfall and vegetation growth impacts on forest stream quality. Concentration of TN and TP showed significant positive correlation, and weak negative correlation was found in the concentration of BOD and TOC. It is expected that result of forest stream water on non rainfall days could be basic information in managing non-point source from forest watersheds.

• Journal of Korean Society on Water Environment
• /
• v.37 no.6
• /
• pp.520-530
• /
• 2021

Multivariate statistical analysis and an environmental hydrological model were applied for investigating the causes of water pollution and providing best management practices for water quality improvement in urban and agricultural watersheds. Principal component analysis (PCA) and cluster analysis (CA) for water quality time series data show that chemical oxygen demand (COD), total organic carbon (TOC), suspended solids (SS) and total phosphorus (T-P) are classified as non-point source pollutants that are highly correlated with river discharge. Total nitrogen (T-N), which has no correlation with river discharge and inverse relationship with water temperature, behaves like a point source with slow and consistent release. Biochemical oxygen demand (BOD) shows intermediate characteristics between point and non-point source pollutants. The results of the PCA and CA for the spatial water quality data indicate that the cluster 1 of the watersheds was characterized as upstream watersheds with good water quality and high proportion of forest. The cluster 3 shows however indicates the most polluted watersheds with substantial discharge of BOD and nutrients from urban sewage, agricultural and industrial activities. The cluster 2 shows intermediate characteristics between the clusters 1 and 3. The results of hydrological simulation program-Fortran (HSPF) model simulation indicated that the seasonal patterns of BOD, T-N and T-P are affected substantially by agricultural and livestock farming activities, untreated wastewater, and environmental flow. The spatial analysis on the model results indicates that the highly-populated watersheds are the prior contributors to the water quality degradation of the river.

• Journal of Sensor Science and Technology
• /
• v.32 no.3
• /
• pp.140-146
• /
• 2023

Water quality is crucial for human health and the environment. Accurate measurement of the quantity of organic carbon in water is essential for water quality evaluation, identification of water pollution sources, and appropriate implementation of water treatment measures. Total organic carbon (TOC) analysis is an important tool for this purpose. Although other methods, such as chemical oxygen demand (COD) and biochemical oxygen demand (BOD) are also used to measure organic carbon in water, they have limitations that make TOC analysis a more favorable option in certain situations. For example, COD requires the use of toxic chemicals, and BOD is time-consuming and can produce inconsistent and unreliable results. In contrast, TOC analysis is rapid and reliable, providing accurate measurements of organic carbon content in water. However, common methods for TOC analysis can be complex and energy-intensive because of the use of high-temperature heaters for liquid-to-gas phase transitions and the use of acid, which present safety risks. This study focuses on a TOC analysis method using TiO₂ photocatalysis, which has several advantages over conventional TOC analysis methods, including its low cost and easy maintenance. For TiO₂, rutile and anatase powders are mixed with an inorganic binder and spray-coated onto a glass fiber substrate. The TiO₂ powder and inorganic binder solutions are adjusted to optimize the photocatalytic reaction performance. The TiO₂ photocatalysis method is a simple and low-power approach to TOC analysis, making it a promising alternative to commonly used TOC analysis methods. This study aims to contribute to the development of more efficient and cost-effective approaches for water quality analysis and management by exploring the effectiveness and reliability of the developed equipment.

• Proceedings of the Korea Water Resources Association Conference
• /
• 2021.06a
• /
• pp.241-241
• /
• 2021

Recent developments recommend the use of SSS to prevent combined sewer overflows and reduce excessive pollutant deposition in the receiving waters; however, other studies also suggest that SSS have minimal or no advantage over CSS in terms of reducing the pollutant loads being discharged in natural waterways. This study was conducted to evaluate the effectiveness of employing SSS in improving the water quality of the rivers in Okcheon-gun, South Korea. The former combined sewer outfalls (CSOs) were monitored to determine the presence of illicit connections or leaks in the newly-established SSS. Dry and wet-day monitoring was conducted alongside the collection of water samples on 14 points along the reach of the rivers and four former CSOs to determine water quality changes and patterns of pollutant loading. Among the 34 former CSOs in the study area, eight former CSOs exhibited dry-day discharges, implying the possibility of having illicit connections, leaks, or illegal wastewater discharge in the system. Moreover, relatively high biochemical oxygen demand (BOD) chemical oxygen demand (COD) concentrations, ranging from 4.8 mg/L to 24.9 mg/L and 6.4 mg/L to 10.1 mg/L, respectively were observed on three out of the four monitored CSOs. Fluctuations in the pollutant concentrations in the different monitored points along the river was also observed due to the presence of pipes discharging polluted water. Ultimately, further studies are necessary to identify the sources of dry-day discharges in the CSOs to successfully improve the water quality of the rivers in the area.