Wastewater Treatment Plant System Research Articles

Reduced bioavailability of Au and isotopically enriched 109Ag nanoparticles transformed through a pilot wastewater treatment plant in Hyalella azteca under environmentally relevant exposure scenarios

Wastewater Treatment Plants (WWTP) are a major repository and entrance path of nanoparticles (NP) in the environment and hence play a major role in the final NP fate and toxicity. Studies on silver nanoparticles (AgNP) transport via the WWTP system and uptake by aquatic organisms have so far been carried out using unrealistically high AgNP concentrations, unlikely to be encountered in the aquatic environment. The use of high AgNP concentrations is necessitated by both the low sensitivity of the detection methods used and the need to distinguish background Ag from spiked AgNP.In this study, isotopically enriched 109AgNP were synthesized to overcome these shortcomings and characterized by a broad range of methods including transmission electron microscopy, dynamic and electrophoretic light scattering. 109AgNP and gold NP (AuNP) were spiked to a pilot wastewater treatment plant fed with municipal wastewater for up to 21 days. AuNP were used as chemically less reactive tracer. The uptake of the pristine and transformed NP present in the effluent was assessed using the benthic amphipod Hyalella azteca in fresh- and brackish water exposures at environmentally relevant concentrations of 30 to 500 ng Au/L and 39 to 260 ng Ag/L. The unique isotopic signature of the 109AgNP allowed to detect the material at environmentally relevant concentrations in the presence of a much higher natural Ag background. The results show that the transformations reduce the NP uptake at environmentally relevant exposure concentrations. For 109Ag, lower accumulation factors (AF) were obtained after exposure to transformed NP (250–350) compared to the AF values obtained for pristine 109AgNP (750–840). The reduced AF values observed for H. azteca exposed to effluent from the AuNP-spiked WWTP indicate that biological transformation processes (e.g. eco-corona formation) seem to be involved in addition to chemical transformation.

Pengaruh Penerapan Sistem IPAL terhadap Kulitas Air Buangan Rumah Pemotongan Hewan

PT X is a company engaged in animal slaughtering and produces liquid waste in the process of its activities. Located in Banyuwangi Regency, East Java Province, this study aims to determine the effect of the implementation of the Wastewater Treatment Plant (WWTP) system on the quality of PT X's wastewater. The effect of implementing the WWTP system can be measured through baseline data collection, evaluation of WWTP effectiveness, observation of WWTP operation and maintenance, and recommendations in accordance with the Regulation of the Minister of Environment and Forestry of the Republic of Indonesia Number 68 of 2016 concerning Domestic Wastewater Quality Standards. Pollutant parameters in wastewater include BOD, COD, TSS, and O&G (Oil & Grease) that exceed the quality standards. After the implementation of the WWTP system, the effluent results showed a decrease and no longer exceeded the quality standards, proving that the implemented WWTP system has a positive effect on the quality of the PT X abattoir discharge water.

Pengaruh Penerapan Sistem IPAL terhadap Kulitas Air Buangan Rumah Pemotongan Hewan

PT X is a company engaged in animal slaughtering and produces liquid waste in the process of its activities. Located in Banyuwangi Regency, East Java Province, this study aims to determine the effect of the implementation of the Wastewater Treatment Plant (WWTP) system on the quality of PT X's wastewater. The effect of implementing the WWTP system can be measured through baseline data collection, evaluation of WWTP effectiveness, observation of WWTP operation and maintenance, and recommendations in accordance with the Regulation of the Minister of Environment and Forestry of the Republic of Indonesia Number 68 of 2016 concerning Domestic Wastewater Quality Standards. Pollutant parameters in wastewater include BOD, COD, TSS, and O&G (Oil & Grease) that exceed the quality standards. After the implementation of the WWTP system, the effluent results showed a decrease and no longer exceeded the quality standards, proving that the implemented WWTP system has a positive effect on the quality of the PT X abattoir discharge water.

Potential effects of the discharge of wastewater treatment plant (WWTP) effluents in benthic communities: evidence from three distinct WWTP systems

Wastewater treatment plant (WWTP) effluents can be sources of environmental contamination. In this study, we aimed to understand whether effluents of three different WWTPs may have ecological effects in riverine recipient ecosystems. To achieve this, we assessed benthic phytobenthos and macroinvertebrate communities at three different locations relative to the effluent discharge: immediately upstream, immediately downstream and 500-m downstream the effluent discharge. Two approaches were employed: the ecological status classification as defined in the Water Framework Directive (WFD) based on biological indicators; constrained multivariate analysis to disentangle the environmental drivers (physicochemical variables and contaminants, namely metals, polycyclic aromatic hydrocarbons, pharmaceuticals, and personal care products) of ecological changes across the study sites. The results showed inconsistencies between the WFD approach and the multivariate approach, as well as between the responses of macroinvertebrates and diatoms. The WWTP effluents impacted benthic communities in a single case: macroinvertebrates were negatively affected by one of the WWTP effluents, likely by the transported pharmaceuticals (other stressors are essentially homogeneous among sites). Given the findings and the scarcity of consistent evidence on ecological impacts that WWTP effluents may have in recipient ecosystems, further research is needed towards more sustainable regulation and linked environmental protection measures.

Machine learning assisted combined systems of wastewater treatment plants with constructed wetlands optimal decision-making

This study proposed an efficient framework for optimizing the design and operation of combined systems of wastewater treatment plants (WWTP) and constructed wetlands (CW). The framework coupled a WWTP model with a CW model and used a multi-objective evolutionary algorithm to identify trade-offs between energy consumption, effluent quality, and construction cost. Compared to traditional design and management approaches, the framework achieved a 27 % reduction in WWTP energy consumption or a 44 % reduction in CW cost while meeting strict effluent discharge limits for Chinese WWTP. The framework also identified feasible decision variable ranges and demonstrated the impact of different optimization strategies on system performance. Furthermore, the contributions of WWTP and CW in pollutant degradation were analyzed. Overall, the proposed framework offers a highly efficient and cost-effective solution for optimizing the design and operation of a combined WWTP and CW system.

Antibiotic-Resistant Bacteria across a Wastewater Treatment Plant

Antimicrobial resistance is presently one of the leading causes of death worldwide. The surveillance of different environments, namely, wastewater treatment plants (WWTPs), as hotspots of antibiotic-resistant bacteria, has become crucial under the One Health approach. This study aimed to characterize, phenotypically and genotypically, antibiotic-resistant bacteria along a WWTP receiving domestic and industrial sewage. Four sampling sites, representing distinct treatment points of the WWTP, were selected for sampling bacterial isolation in selective media supplemented, or not, with antibiotics, and subsequent antimicrobial susceptibility testing. Antibiotic resistance encoding genes were screened by molecular methods. A total of 50 bacterial isolates were obtained, 50% of which were affiliated with the genus Enterococcus. The antimicrobial susceptibility testing revealed antibiotic phenotypic resistance in isolates obtained from all the four treatment points of the wastewater samples, with resistance to tetracycline (32.5%) and ampicillin (25%) being the most common. Three isolates were found to be multidrug resistant and were affiliated with the genera Citrobacter, Shigella and Klebsiella. Molecular screening revealed the presence of tet(M), blaTEM, blaSHV and blaCTX-M, as well as class 1 integrons carrying dfrA25, ANT(3″)-IIa and aadA6 genes. This study highlights the relevance of bacterial isolation and their antimicrobial susceptibility evaluation in WWTP systems since antibiotic-resistant strains were found from the raw influent to the final effluent discharged into the environment, denoting the need for surveillance and containment measures.

Machine learning modeling for the prediction of phosphorus and nitrogen removal efficiency and screening of crucial microorganisms in wastewater treatment plants

The effectiveness of wastewater treatment plants (WWTPs) is largely determined by the microbial community structure in their activated sludge (AS). Interactions among microbial communities in AS systems and their indirect effects on water quality changes are crucial for WWTP performance. However, there is currently no quantitative method to evaluate the contribution of microorganisms to the operating efficiency of WWTPs. Traditional assessments of WWTP performance are limited by experimental conditions, methods, and other factors, resulting in increased costs and experimental pollutants. Therefore, an effective method is needed to predict WWTP efficiency based on AS community structure and quantitatively evaluate the contribution of microorganisms in the AS system. This study evaluated and compared microbial communities and water quality changes from WWTPs worldwide by meta-analysis of published high-throughput sequencing data. Six machine learning (ML) models were utilized to predict the efficiency of phosphorus and nitrogen removal in WWTPs; among them, XGBoost showed the highest prediction accuracy. Cross-entropy was used to screen the crucial microorganisms related to phosphorus and nitrogen removal efficiency, and the modeling confirmed the reasonableness of the results. Thirteen genera with nitrogen and phosphorus cycling pathways obtained from the screening were considered highly appropriate for the simultaneous removal of phosphorus and nitrogen. The results showed that the microbes Haliangium, Vicinamibacteraceae, Tolumonas, and SWB02 are potentially crucial for phosphorus and nitrogen removal, as they may be involved in the process of phosphorus and nitrogen removal in sewage treatment plants. Overall, these findings have deepened our understanding of the relationship between microbial community structure and performance of WWTPs, indicating that microbial data should play a critical role in the future design of sewage treatment plants. The ML model of this study can efficiently screen crucial microbes associated with WWTP system performance, and it is promising for the discovery of potential microbial metabolic pathways.

Optimizing city-level centralized wastewater management system using machine learning and spatial network analysis

Access to proper sanitation is a basic human right and a crucial component of public health. Wastewater treatment plants (WWTP) play a critical role in ensuring sanitation access by preventing water pollution. However, in Bandung, one of Indonesia’s strategic cities, only 63% of the population has access to proper sanitation. Therefore, this study aims to identify priority areas for developing a centralized WWTP system using models that consider wastewater production and the availability of sanitation access on a building scale. The novelty of this study lies in integrating wastewater production models and sanitation access availability to prioritize developing WWTP systems at the building level and developing a pipeline model to connect WWTP candidate points with priority building targets. We also analyzed the suitability of optimal WWTP locations to support the development of wastewater treatment systems and determine wastewater pipeline routes using the optimal path method in priority areas. To model wastewater production, we used the number of residents per building and building area as the basis. The availability of sanitation access was modeled by considering the percentage of access per district, identifying urban slums, and analyzing proximity to existing wastewater pipes and rivers. After the modeling process, we classified nine development priority classes. Our results revealed that there is approximately 7.38 km2 of priority area for developing a wastewater treatment system in Bandung which comprises 67,135 priority buildings and 178 potential sites for WWTP. These priority areas are mostly located in the districts of Bojongloa Kaler, Astanaanyar, Batununggal, Kiaracondong, Cibeunying Kidul, Coblong, and Sukajadi. This study’s findings provide valuable insights for policymakers and urban planners to prioritize developing WWTP systems in areas that need them most. It also highlights the importance of considering sanitation access availability and wastewater production models when planning and developing WWTP systems.

Metagenomic Evidence for Cobamide Producers Driving Prokaryotic Co-occurrence Associations and Potential Function in Wastewater Treatment Plants.

Cobamides are required by most organisms but are only produced by specific prokaryotic taxa. These commonly shared cofactors play significant roles in shaping the microbial community and ecosystem function. Wastewater treatment plants (WWTPs) are the world's most common biotechnological systems; knowledge about sharing of cobamides among microorganisms is predicted to be important to decipher the complex microbial relationships in these systems. Herein, we explored prokaryotic potential cobamide producers in global WWTP systems based on metagenomic analyses. A set of 8253 metagenome-assembled genomes (MAGs) were recovered and 1276 (15.5%) of them were identified as cobamide producers, which could potentially be used for the practical biological manipulation of WWTP systems. Moreover, 8090 of the total recovered MAGs (98.0%) contained at least one enzyme family dependent on cobamides, indicating the sharing of cobamides among microbial members in WWTP systems. Importantly, our results showed that the relative abundance and number of cobamide producers improved the complexity of microbial co-occurrence networks and most nitrogen, sulfur, and phosphorus cycling gene abundances, indicating the significance of cobamides in microbial ecology and their potential function in WWTP systems. These findings enhance the knowledge of cobamide producers and their functions in WWTP systems, which has important implications for improving the efficiency of microbial wastewater treatment processes.

Dynamic Failure Risk Assessment of Wastewater Treatment and Reclamation Plant: An Industrial Case Study

Due to the growing scarcity of water resources, wastewater reuse has become one of the most effective solutions for industrial consumption. However, various factors can detrimentally affect the performance of a wastewater treatment plant (WWTP), which is considered a risk of not fulfilling the effluent requirements. Thus, to ensure the quality of treated wastewater, it is essential to analyze system failure causes and their potential outcomes and mitigation measures through a systematic dynamic risk assessment approach. This work shows how a dynamic Bayesian network (DBN) can be effectively used in this context. Like the conventional Bayesian network (BN), the DBN can capture complex interactions between failure contributory factors. Additionally, it can forecast the upcoming failure likelihood using a prediction inference. This proposed methodology was applied to a WWTP of the Moorchekhort Industrial Complex (MIC), located in the center of Iran. A total of 15 years’ time frame (2016–2030) has been considered in this work. The first six years’ data have been used to develop the DBN model and to identify the crucial risk factors that are further used to reduce the risk in the remaining nine years. The risk increased from 21% to 42% in 2016–2021. Applying the proposed risk mitigation measures can decrease the failure risk from 33% to 9% in 2022–2030. The proposed model showed the capability of the DBN in risk management of a WWTP system which can help WWTPs’ managers and operators achieve better performance for higher reclaimed water quality.

Implementasi Green Economy pada Sistem Instalasi Pengolahan Air Limbah Tahu dan Sensor Terintegrasi di Kediri

Every industry has special attention to environmental preservation; however, it has become an unresolved problem in the industrial center of tofu village. Based on the analysis, there were problems related to liquid waste produced by tofu craftsmen that doesn’t meet the Quality Standards for liquid waste of the Food Products Industry, limited costs, land, and space thus that it didn’t meet the adequacy of space for Wastewater Treatment Plants (WWTP). The PKM (Community Service Program) activity aimed to implement Green Economy Concept on Integrated WWTP Systems and Sensors for the Kediri Tofu Industry as an effort to solve the waste problem in the tofu industry. This activity began with field observations, compatibility and requirements analysis, construction design and designing WWTP systems and sensors, small-scale trials, analysis, and evaluation. The WWTP system used involves components of pre-treatment, neutralization, coagulation and flotation, sedimentation, and filtration. The designed sensors included Arduino Nano-based pH meter and TDS meter sensors that were connected to computers and smartphones by Arduino IDE and Blynk software. It was hoped that this activity might spur business actors to actively participate in solving waste problems and reducing environmental impact pollution with all the space and cost limitations.

Resource-oriented sanitation: Identifying appropriate technologies and environmental gains by coupling Santiago software and life cycle assessment in a Brazilian case study.

Implementation of resource recovery technologies is becoming increasingly important, as humans are exhausting the world's natural resources. Recovering nutrients and water from wastewater treatment systems will play an important role in changing the current trends towards a circular economy. However, guidance is still needed to determine the most appropriate way to do this. In this study two decision-support tools, sanitation planning software (Santiago) and life cycle assessment (LCA), were applied to identify appropriate technologies and their environmental impacts. As a case study, current and alternative scenarios for a wastewater treatment plant (WWTP) in Campo Grande, west-central Brazil, were used. Among 12 scenarios provided by Santiago for efficient nutrient recovery, eight were selected for further assessment. The current WWTP system (UASB reactors) resulted in the highest negative impacts in two of nine assessment categories (freshwater and marine eutrophication), due to nutrient discharge to water. A source separation scenario with urine stored in a urine bank and co-composting of feces showed best overall performance. Electricity consumption played a crucial role for impacts in several categories, while water consumption was not significantly affected by choice of toilet. One Santiago scenario matched the most appropriate scenario with the best environmental performance, but the other seven scenarios were not as beneficial, indicating a need for some adjustments in the software. These results highlight the importance of performing LCA to compare alternative scenarios, even when using a tool designed to identify locally appropriate technologies. The results also indicate that the current wastewater treatment system has reasonable environmental performance, but could be improved if measures were taken to recover energy and reuse water.

A simulation-assessment-optimization approach towards energy self-sufficiency and carbon reduction in regional-scale sewage systems

Utilizing renewable energy is a practical pathway for realizing energy self-sufficiency and offsetting carbon emissions in wastewater treatment plants (WWTPs). The holistic optimization of hybrid renewable energy of multiple WWTPs overweighs individual WWTPs studies by providing global optimal solutions and cost-effective resources management schemes with expended spatial scales. Few studies have focused on the overall optimal utilization and management of hybrid renewable energy from WWTPs on a regional scale. This study aims to explore how to optimize the configuration of renewable energy facilities for multiple WWTPs to achieve the cost-effective use of renewable energy for the overall system. Uncertainty associated with PV power generation and the size effects of WWTPs were considered in the general framework to enhance the reliability and cost effectiveness of the utilization of renewable energy. The developed approach was then applied to the hybrid renewable energy management of a city-scale WWTP system comprising 31 plants in Guangzhou, China. Results indicated that the energy self-sufficiency of sewage systems can be realized by recovering renewable energy. The levelized cost of energy generation in the overall system was approximately 0.19 CNY/kW·h, and the overall reduction in greenhouse gas (GHG) emissions was approximately 129.5 t CO2-eq/d. The overall optimization reduced the total cost by approximately 3% than did the traditional individual WWTP studies. The thermal energy recovered from wastewater could further reduce the operational costs of WWTPs through carbon credit trading. The developed approach can also be applied to other areas of the world to promote sustainable wastewater treatment and strengthen the utilization of renewable energy.

Chemical characterization of riverine sediments affected by wastewater treatment plant effluent discharge

This study was aimed at assessing the contribution of wastewater treatment effluents to the contamination profile of the sediments of receiving waterways. Three wastewater treatment plants (WWTP) were addressed, encompassing different population equivalent sizes, urbanization degrees and treatment methods translating differences in expected contamination patterns. Within each WWTP system, the assessment targeted the effluent and sediment samples collected upstream and downstream the effluent discharge point; contaminants belonging to several concerning chemical classes (metals and metalloids; pesticides; pharmaceuticals and personal care products, PPCPs; and polycyclic aromatic hydrocarbons, PAHs) were quantified both in effluent and sediment samples. Clear associations between contaminants present in the effluent and corresponding sediment samples were not always verified. In fact, a noticeable difference between the number or abundance of contaminants detected in effluents and in sediments, suggesting that effluents are not always the most likely source (e.g. PAHs). However, sediment contaminants that were likely sourced by the effluents were also identified (e.g. PPCPs). Sediment analysis offers an important historical view of contamination, especially in flowing recipient ecosystems where any characterization over the water matrix is ephemeral and linking exclusively to the moment of sampling. Hence, sediments should be considered for the establishment of WWTP operational benchmarks regulating the emission of contaminants, which is currently focused mostly on effluent composition thus potentially over/underestimating the longer-term impact of effluent discharge in the recipient waterways.

Effectiveness of Wastewater Treatment Installation and Liquid Waste Quality in Dr. Soetomo General Hospital, Surabaya

Introduction: Hospitals are institutions that produce liquid waste that may pollute the environment and have a dangerous impact on health. Hospital waste has the potential to contain hazardous chemicals, pharmaceutical waste, radioactivity and microbiological pathogens in liquid waste that can pollute the environment and disrupt the balance of the ecosystem. This study aims to determine the effectiveness of the Wastewater Treatment Plant (WWTP) and the quality of the liquid waste at the Dr. Soetomo General Hospital. Methods: This research was a quantitative descriptive study using secondary data from laboratory analysis of wastewater inlet and outlet of The Central Wastewater Treatment Plant (WWTP) of Dr. Soetomo General Hospital for the January-December 2020 period. Effectiveness was obtained by calculating the difference between the inlet and outlet values of each parameter divided by the inlet value multiplied by 100%. Results and Discussion: WWTP in Dr. Soetomo General Hospital Surabaya used a central WWTP which had 3 (three) units, namely WWTP Sequence Batch Reactor (SBR), WWTP Membrane Biostrain Reactor (MBR) and WWTP Aerobic Biofilter which aims to improve the quality of liquid waste. Based on the results of the research analysis, it has been found that hospital wastewater treatment using a central WWTP system is effective for reducing the levels of parameters, namely Total Suspended Solid (TSS) by 60.55%, Biological Oxygen Demand (BOD) by 72.52%, Chemical Oxygen Demand (COD) by 54.02%, Ammoniacal Nitrogen (NH3N) by 90.91%, Phospate (PO4) by 71.43%, bacteria group E. Coli by 99.93%. The temperature and Potential of Hydrogen (pH) parameters recorded at the outlet are in accordance with the established quality standards. Conclusion: The three WWTP units used in Dr. Soetomo General Hospital are able to treat liquid waste effectively. Liquid waste at each outlet parameter is in accordance with East Java Governor Regulation No. 72 of 2013 concerning quality standards for health facilities waste water, so that the effects of contamination on the environment can be minimized.

The Analysis of Decision-making Items for Operation Management of Digital Twin Simulators for Sewage and Water Treatment Facilities

This paper addresses the derivation of decision-making factors for the operation and management of the Cyber Physical systems (CPS)-linked wastewater treatment plants (WWTPs) and drinking water treatment plants (DWTPs) simulator. The analytical hierarchy process (AHP) method was applied to evaluate the importance of each influencing factor on the operational elements targeting experts. Here, the experts were 37 people working for WWTPs and 30 people working for DWTPs, respectively. The analysis factors for decision-making were influent load, reactor capacity, treatment process, occurrence of high turbidity influent, risk, urgency, response, and recovery, and their relative importance was analyzed. Among the operational elements of WWTPs, influent fluctuations have been shown as the most important factor. Conversely, the possibility of occurrence was found to be the most important influencing factor. In the case of DWTPs, the inflow of high turbidity was found to be the main operating factor, and the influencing factors were the probability of occurrence and the degree of risk. Based upon the results obtained, this study is expected to contribute to the establishment of a stable system of both WWTPs and DWTPS by identifying influent fluctuations, which are a major influencing factor, and by controlling operation factors connected with the establishment of a digital twin simulation.

An assessment of resistome and mobilome in wastewater treatment plants through temporal and spatial metagenomic analysis

Wastewater treatment plants (WWTPs) are regarded as critical points in disseminating antibiotic resistance genes (ARGs). In particular, the discharging effluents from WWTPs generally bring downstream catchment areas exogenous ARGs and resistant bacteria. However, there lacks a sufficient assessment of the resistome and mobilome in effluents. In this study, a consecutive monthly sampling was conducted over 13 months in three Hong Kong (HK) WWTPs for metagenomic sequencing. Prevalence information of ARGs and mobile genetic elements (MGEs) was compared with counterparts in effluents from cities of North America, South America, Europe, and Asia. Moreover, a publicly accessible platform integrating the exposure ranking scheme, which was based on the global archive of ARG abundance, and a readily implementable online pipeline was developed to benefit communication in academia and government consultancy. Results demonstrated HK WWTPs were featured high ARG removal efficiency of 2.34–2.43 log reduction rate, and effluents were ranked in moderate levels of Level 2 and Level 3 in the exposure prioritizing scheme based on total ARG abundance. Moreover, absolute quantification of temporal variations of effluent resistome disclosed distinct changes over time among varied ARG types which were associated with prevalently used antibiotics, including quinolone and sulfonamide. This reinforces the need for real-time management of WWTP systems. Notably, ARGs of anthropogenic prevalence, high mobility, and potential pathogenicity were found to be present in HK effluents, drawing attention to the necessity for improved risk management. In addition, source tracking of effluent resistome and structural equation model analysis was conducted to explore the disparity in ARG abundance and diversity in different samples. The discovery of this study and the recommendation of a comprehensive exposure assessment will facilitate decision-making in resistome management in WWTPs to reduce the ARG and antibiotic resistant bacteria (ARB) contamination in the receiving environments.

EVALUATION OF WASTEWATER TREATMENT IN NUSA DUA TOURISM AREA AND THEIR CHALLENGES TO ALGAE BLOOM

<p>The wastewater treatment plant (WWTP) in the Nusa Dua area has implemented a stabilization pond to reduce organic matter and nutrients. Because it has been operating since 1980, it is necessary to evaluate the existing conditions. The aim of this study was to determine the percentage of organic and nutrient reduction from the WWTP system. Organic removal in the form of BOD and COD parameters were 71.84% and 75.11%, respectively. Meanwhile, nutrient parameters in the form of NH3-N, TN, and TP have a percentage of 83.64%; 59.41%, and -375.81%, respectively. TP is the only parameter that has increased, causing a problem which is caused by the explosion of algae population in the reservoir. TP allowance should be a concern in choosing advanced treatment.<em></em></p>

Analisis Kebijakan Sistem Pengolahan Air Limbah Rumah Tangga Kota Depok

Study on domestic wastewater management policies is still minimal. Previous research was based on law. This research was conducted to discuss according hierarchy of regulations, then policy analysis under the stakeholders’ understanding. Wastewater management is important because it involves human health and the availability of clean water. The problem in Depok City is untreated domestic wastewater polluting rivers. This condition is caused by the communal Waste Water Treatment Plant (WWTP) that has not been able to reach all settlements and housing. The study aims to conduct a policy analysis of domestic wastewater management to reduce household pollution in Depok. The study was conducted in 2018. Primary data were consisting of perceptions of domestic waste policy makers at regional to national level. Secondary data were previous studies and policy products of Depok City. Qualitative research is determined by the results of content analysis and stakeholder analysis. Primary data obtained through interviews and focus group discussion. The finding is domestic wastewater pollution comes from settlements established before 2012 and settlements that are not served by integrated communal WWTP in Depok City. These conditions can be overcome by building inexpensive and easy to operate domestic wastewater treatment system. The research recommendation is the application of a constructed wetland. The policy implication is adoption of WWTP system in Depok City regulations.

Development of an H2S emission model for wastewater treatment plants

ABSTRACT Modeling and prediction of H2S emission from wastewater are important since gaseous H2S will induce significant corrosion and odor problems. Most previous studies focused on H2S emission of wastewater in pipeline systems, which may not be fit for H2S emission in wastewater treatment plants (WWTPs). This study provided a two-phase mass transfer model for prediction of H2S emission concentrations. The model is based on the mass transfer rate equation of the mass transfer impetus, expressed by the concentration difference. The main parameters of the model are the mass transfer coefficient, the carrier gas flow rate and the concentration of H2S in liquid phase. The results showed that the model can simulate and predict H2S emission concentrations of various processes in WWTPs. Moreover, the model can analyze and predict the influences of different pH values, mass transfer coefficients and carrier gas flow rates on H2S emission concentrations and loads. Therefore, the model provides theoretical guidance for design of WWTPs regarding H2S emissions. Implications: Modeling and prediction of H2S emission from wastewater are quite important since gaseous H2S will induce significant corrosion and odor problems. Most of previous studies are focused on H2S emission from wastewater in pipeline system, which may not be fit for H2S emission in wastewater treatment plants (WWTPs). Thus in this study, a model for predicting H2S emission from typical units of WWTPs is established and verified. Moreover, the influences of pH values, mass transfer coefficients and carrier gas flow rates on H2S emission are analyzed. The model can be a useful tool to predict the H2S concentration in odor gas collection system of WWTP and understand the behaviors of H2S emission under different WWTPs operating conditions.