scholarly journals Review of Methods for Assessing the Impact of WWTPs on the Natural Environment

2021 ◽  
Vol 3 (1) ◽  
pp. 98-122
Author(s):  
Joanna Bąk ◽  
Krzysztof Barbusiński ◽  
Maciej Thomas

Environmental management in facilities such as wastewater treatment plants (WWTPs) allows for the implementation of the Deming cycle, and thus the constant improvement of the mitigation of the environmental impact. The correct diagnosis of the current state of functioning of the WWTPs, the identification of aspects that may have a measurable impact on the environment, and their assessment are of key importance. The article discusses the possible causes of the impact of WWTPs on the natural environment. Among other problems, such issues as energy consumption, noise and the formation of bioaerosols and odor nuisances were taken into account. Different ways of assessing the impact of wastewater treatment plants on the environment were collated, taking into account the need to assess not only the technological process itself but also the buildings during their use. The results of methods for assessing the environmental impact of wastewater treatment plants in selected countries were also compared.

Energies ◽  
2020 ◽  
Vol 14 (1) ◽  
pp. 100
Author(s):  
Horia Andrei ◽  
Cristian Andrei Badea ◽  
Paul Andrei ◽  
Filippo Spertino

Wastewater treatment plants and power generation constitute inseparable parts of present society. So the growth of wastewater treatment plants is accompanied by an increase in the energy consumption, and a sustainable development implies the use of renewable energy sources on a large scale in the power generation. A case study of the synergy between wastewater treatment plants and photovoltaic systems, aiming to improve the energetic, environmental and economic impacts, is presented. Based on data acquisition, the energy consumption analysis of wastewater treatment plant reveals that the highest demand is during April, and the lowest is during November. The placement of photovoltaic modules is designed to maximize the use of free space on the technological area of wastewater treatment plant in order to obtain a power output as high as possible. The peak consumption of wastewater treatment plant occurs in April, however the peak production of the photovoltaic is in July, so electrochemical batteries can partly compensate for this mismatch. The impact of the photovoltaic system connectivity on power grid is assessed by means of the matching-index method and the storage battery significantly improves this parameter. Carbon credit and energy payback time are used to assess the environmental impact. The results prove that the photovoltaic system mitigates 12,118 tons of carbon and, respectively, the embedded energy is compensated by production in 8 ½ years. The economic impact of the photovoltaic system is analyzed by the levelized cost of energy, and the results show that the price of energy from the photovoltaic source is below the current market price of energy.


Energies ◽  
2021 ◽  
Vol 14 (18) ◽  
pp. 5826
Author(s):  
Mónica Vergara-Araya ◽  
Verena Hilgenfeldt ◽  
Di Peng ◽  
Heidrun Steinmetz ◽  
Jürgen Wiese

In the last decade, China has sharply tightened the monitoring values for wastewater treatment plants (WWTPs). In some regions with sensitive discharge water bodies, the values (24 h composite sample) must be 1.5 mg/L for NH4-N and 10 mg/L for total nitrogen since 2021. Even with the previously less strict monitoring values, around 50% of the wastewater treatment plants in China were permanently unable to comply with the nitrogen monitoring values. Due to the rapid changes on-site to meet the threshold values and the strong relation to energy-intensive aeration strategies to sufficiently remove nitrogen, WWTPs do not always work energy-efficiently. A Chinese WWTP (450,000 Population equivalents or PE) with upstream denitrification, a tertiary treatment stage for phosphorus removal and disinfection, and aerobic sludge stabilisation was modelled in order to test various concepts for operation optimisation to lower energy consumption while meeting and undercutting effluent requirements. Following a comprehensive analysis of operating data, the WWTP was modelled and calibrated. Based on the calibrated model, various approaches for optimising nitrogen elimination were tested, including operational and automation strategies for aeration control. After several tests, a combination of strategies (i.e., partial by-pass of primary clarifiers, NH4-N based control, increase in the denitrification capacity, intermittent denitrification) reduced the air demand by up to 24% and at the same time significantly improved compliance with the monitoring values (up to 80% less norm non-compliances). By incorporating the impact of the strategies on related processes, like the bypass of primary settling tanks, energy consumption could be reduced by almost 25%. Many of the elaborated strategies can be transferred to WWTPs with similar boundary conditions and strict effluent values worldwide.


Electronics ◽  
2021 ◽  
Vol 10 (10) ◽  
pp. 1149
Author(s):  
Pedro Oliveira ◽  
Bruno Fernandes ◽  
Cesar Analide ◽  
Paulo Novais

A major challenge of today’s society is to make large urban centres more sustainable. Improving the energy efficiency of the various infrastructures that make up cities is one aspect being considered when improving their sustainability, with Wastewater Treatment Plants (WWTPs) being one of them. Consequently, this study aims to conceive, tune, and evaluate a set of candidate deep learning models with the goal being to forecast the energy consumption of a WWTP, following a recursive multi-step approach. Three distinct types of models were experimented, in particular, Long Short-Term Memory networks (LSTMs), Gated Recurrent Units (GRUs), and uni-dimensional Convolutional Neural Networks (CNNs). Uni- and multi-variate settings were evaluated, as well as different methods for handling outliers. Promising forecasting results were obtained by CNN-based models, being this difference statistically significant when compared to LSTMs and GRUs, with the best model presenting an approximate overall error of 630 kWh when on a multi-variate setting. Finally, to overcome the problem of data scarcity in WWTPs, transfer learning processes were implemented, with promising results being achieved when using a pre-trained uni-variate CNN model, with the overall error reducing to 325 kWh.


Water ◽  
2020 ◽  
Vol 12 (4) ◽  
pp. 1143
Author(s):  
Ana Belén Lozano Avilés ◽  
Francisco Del Cerro Velázquez ◽  
Mercedes Llorens Pascual Del Riquelme

Phase I of the proposed energy optimization methodology showed how the selection of best management criteria for the biological aeration process, and the guarantee of its control at the wastewater treatment plant (WWTP) in San Pedro del Pinatar (Murcia, Spain) produced reductions of around 20% in energy consumption by considerably reducing the oxygen needs of the microorganisms in the biological system. This manuscript focused on phase II of this methodology, which describes the tools that can be used to detect and correct deviations in the optimal operating points of the aeration equipment and the intrinsic deficiencies in the installation, in order to achieve optimization of the oxygen needs by the microorganisms and improve the efficiency of their transfer from the gas phase to the liquid phase. The objectives pursued were: (i) to minimize the need for aeration, (ii) to reduce the pressure losses in the installation, (iii) to optimize the air supply pressures to avoid excessive energy consumption for the same airflow, and (iv) to optimize the control strategy for the actual working conditions. The use of flow modeling and simulation techniques, the measurement and calculation of air transfer efficiency through the use of off-gas hoods, and the redesign of the aeration facility at the San Pedro del Pinatar WWTP were crucial, and allowed for reductions in energy consumption in Phase II of more than 20%.


Energies ◽  
2022 ◽  
Vol 15 (2) ◽  
pp. 580
Author(s):  
Michał Gołębiewski ◽  
Marta Galant-Gołębiewska ◽  
Remigiusz Jasiński

Protection of the natural environment is a key activity driving development in the transport discipline today. The use of simulators to train civil aviation pilots provides an excellent opportunity to maintain the balance between efficiency and limit the negative impact of transport on the environment. Therefore, we decided to determine the impact of selected simulations of air operations on energy consumption. The aim of the research was to determine the energy consumption of the flight simulator depending on the type of flight operation and configuration used. We also decided to compare the obtained result with the energy consumption of an aircraft of a similar class, performing a similar aviation operation and other means of transport. In order to obtain the results, a research plan was proposed consisting of 12 scenarios differing in the simulated aircraft model, weather conditions and the use of the simulator motion platform. In each of the scenarios, energy consumption was measured, taking into account the individual components of the simulator. The research showed that the use of a flight simulator has a much smaller negative impact on the natural environment than flying in a traditional plane. Use of a motion platform indicated a change in energy consumption of approximately 40% (in general, flight simulator configuration can change energy consumption by up to 50%). The deterioration of weather conditions during the simulation caused an increase in energy consumption of 14% when motion was disabled and 18% when motion was enabled. Energy consumption in the initial stages of pilot training can be reduced by 97% by using flight simulators compared to aircraft training.


2021 ◽  
Vol 894 (1) ◽  
pp. 012004
Author(s):  
S Hartini ◽  
B S Ramadan ◽  
R Purwaningsih ◽  
S Sumiyati ◽  
M A A Kesuma

Abstract Tofu contains various substances that are very good when consumed to improve people’s nutrition. In addition, tofu also has good taste. The problem is that the tofu production process produces products and non-product outputs in the form of waste that is very dangerous if directly disposed of in the environment. The BOD5 content of tofu small and medium-sized enterprises (SMEs) in Sugihmanik Village ranged from 3,667-4,933 mg/L and COD 7,668-9,736 mg/L. At the same time, the TSS values ranged from 701-1,189 mg/L. The BOD5 value in the river water content is 367 mg/L. It greatly exceeds the set Threshold Value. This study aims to measure the environmental impact using Life Cycle Assessment (LCA). LCA can identify the impact of each activity based on the impact category to identify the processes that contribute significantly to damaging the environment. This study found that the cooking and frying process had the highest impact, where the climate change category was the largest. Wastewater treatment plants, biogas from the biodigester as a substitute for electricity for water pumps, rice husks, and corn cobs are expected to reduce environmental impacts. The first section in your paper


2009 ◽  
Vol 21 ◽  
pp. 49-55 ◽  
Author(s):  
Q. D. Lam ◽  
B. Schmalz ◽  
N. Fohrer

Abstract. The aims of this study are to identify the capacities of applying an ecohydrological model for simulating flow and to assess the impact of point and non-point source pollution on nitrate loads in a complex lowland catchment, which has special hydrological characteristics in comparison with those of other catchments. The study area Kielstau catchment has a size of approximately 50 km2 and is located in the North German lowlands. The water quality is not only influenced by the predominating agricultural land use in the catchment as cropland and pasture, but also by six municipal wastewater treatment plants. Ecohydrological models like the SWAT model (Soil and Water Assessment Tool) are useful tools for simulating nutrient loads in river catchments. Diffuse entries from the agriculture resulting from fertilizers as well as punctual entries from the wastewater treatment plants are implemented in the model set-up. The results of this study show good agreement between simulated and measured daily discharges with a Nash-Sutcliffe efficiency and a correlation coefficient of 0.76 and 0.88 for the calibration period (November 1998 to October 2004); 0.75 and 0.92 for the validation period (November 2004 to December 2007). The model efficiency for daily nitrate loads is 0.64 and 0.5 for the calibration period (June 2005 to May 2007) and the validation period (June 2007 to December 2007), respectively. The study revealed that SWAT performed satisfactorily in simulating daily flow and nitrate loads at the lowland catchment in Northern Germany.


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