Pretreatment processes for the recycling and reuse of sewage sludge

2000 ◽  
Vol 42 (9) ◽  
pp. 167-174 ◽  
Author(s):  
J. A. Müller
Keyword(s):  
Energy Consumption ◽  
Sewage Sludge ◽  
Low Cost ◽  
Great Influence ◽  
Electrical Energy ◽  
Ozone Treatment ◽  
Nitrogen And Phosphorus ◽  
Mechanical Disintegration ◽  
Mechanical Methods ◽  
Reuse Options

This paper focuses on mechanical disintegration and will compare its results to thermal and ozone treatment. Several mechanical methods can be used for disintegration of sewage sludge. The methods differ in energy consumption and suitability of the machines for practical application, which is of great influence on the selection of the method. Thermal disintegration processes have a higher energy consumption than mechanical methods, but they can use low cost thermal energy instead of electrical energy. The highest solution of organic components is achieved using ozone treatment. Several reuse options of disintegrated sludge in aerobic and anaerobic processes are explained. An acceleration and enhancement of the anaerobic stabilisation process is observed, especially if excess sludge is used. Mechanical disintegration leads to better results than thermal treatment in the range of 60 to 130°C. For the aerobic process the substitution of external proton donors is of special interest. High denitrification rates can be achieved, if the sludge is adapted to the substrate. Increasing the concentration of nitrogen and phosphorus in the supernatant, in order to recycle these valuable compounds, mechanical disintegration and ozone treatment seem to be more suitable than thermal disintegration.

VERMICOMPOSTING TECHNOLOGY FOR STABILIZING THE SEWAGE SLUDGE FROM RURAL WASTE WATER TREATMENT PLANTS

2008 ◽  
Vol 3 (1) ◽  
Author(s):  
V. Lina Cardoso ◽  
C. Esperanza Ramírez ◽  
E. Violeta Escalante
Keyword(s):  
Rural Communities ◽  
Sewage Sludge ◽  
Low Cost ◽  
Waste Water Treatment ◽  
Treatment Plant ◽  
Microbiological Quality ◽  
Fecal Coliforms ◽  
Nitrogen And Phosphorus ◽  
Sludge Management

There are problems associated with sludge management in small treatment plants (<10 L/s) located in rural communities, due to costly conventional technology for sludge stabilization. Many of these plants have only sludge drying beds. Mexican Institute of Water Technology has proposed developing suitable low-cost technologies, one of which is vermicomposting a biodegradation system using earthworms of the species Eisenia foetida (earthworm) which stabilize sludge and reduce its pathogenicity. The objective of this work is to present two case studies where vermicomposting technology has been applied in Mexico. The first study corresponds to a plant where 4.8 m3/month of sludge are produced; for these wastes, a vermicomposting system was built and installed. The second study is a treatment plant where 9 m3/month of sludge are produced; experimental tests were conducted with sludge and water hyacinth and a vermicomposting system was designed. The vermicomposts were analyzed using parameters defined by Mexican standards. In regards to stabilization, TVS was reduced by 38% and the microbiological quality of the vermicompost was Class A and B, with a reduction in fecal coliforms and Helminth eggs according to NOM-004-SEMARNAT-2002. A CRETI (Corrosivity, Reactivity, Explosivity, Toxicity and Ignitability) analysis (NOM-052-SEMARNAT-2005) was used to show that the process reduced the concentration of releasable sulfides. The agronomic quality of the vermicompost exhibited a high content of organic matter comparable to many organic manures and high content of nutrients such as nitrogen and phosphorus. It is concluded that it is possible to improve the conditions of sewage sludge management in small plants of rural communities with a minimum investment (less than $10,000.00 USD) and with a requirement of a minimum area of 60 to 70 m2 for a production of less than 9 m3/month of dehydrated sludge (80% humidity).

scholarly journals Normative Aspects of Nudging in the International Sphere

AJIL Unbound ◽  
2021 ◽  
Vol 115 ◽  
pp. 263-267
Author(s):  
Doron Teichman ◽  
Eyal Zamir
Keyword(s):  
Energy Consumption ◽  
Organ Donation ◽  
Low Cost ◽  
National Level ◽  
The Past ◽  
The People ◽  
Posthumous Organ Donation ◽  
Regulatory Problems

The use of nudges—“low-cost, choice-preserving, behaviorally informed approaches to regulatory problems”—has become quite popular at the national level in the past decade or so. Examples include changing the default concerning employees’ saving for retirement in a bid to encourage such saving; altering the default about consent to posthumous organ donation to increase the supply of organs for transplantation; and informing people about other people's energy consumption to spur them to reduce theirs. Nudges are therefore used to promote the welfare of the people being nudged, and of society at large. However, the use of nudges has sparked a lively normative debate. When turning to the international arena, new arguments for and against nudges can be raised. This essay focuses on the normative aspects of using nudges in the international arena.

A persuasive multi-agent simulator to improve electrical energy consumption

2021 ◽  
pp. 1-15
Author(s):  
Fernanda P. Mota ◽  
Cristiano R. Steffens ◽  
Diana F. Adamatti ◽  
Silvia S. Da C Botelho ◽  
Vagner Rosa
Keyword(s):  
Energy Consumption ◽  
Electrical Energy ◽  
Electrical Energy Consumption ◽  
Multi Agent

scholarly journals Computation offloading through mobile vehicles in IoT-edge-cloud network

2020 ◽  
Vol 2020 (1) ◽  
Author(s):  
Jun Long ◽  
Yueyi Luo ◽  
Xiaoyu Zhu ◽  
Entao Luo ◽  
Mingfeng Huang
Keyword(s):  
Reinforcement Learning ◽  
Energy Consumption ◽  
Low Cost ◽  
Computation Offloading ◽  
Mobile Edge Computing ◽  
Challenging Problem ◽  
Learning Technique ◽  
Cloud Network ◽  
The City ◽  
Task Offloading

AbstractWith the developing of Internet of Things (IoT) and mobile edge computing (MEC), more and more sensing devices are widely deployed in the smart city. These sensing devices generate various kinds of tasks, which need to be sent to cloud to process. Usually, the sensing devices do not equip with wireless modules, because it is neither economical nor energy saving. Thus, it is a challenging problem to find a way to offload tasks for sensing devices. However, many vehicles are moving around the city, which can communicate with sensing devices in an effective and low-cost way. In this paper, we propose a computation offloading scheme through mobile vehicles in IoT-edge-cloud network. The sensing devices generate tasks and transmit the tasks to vehicles, then the vehicles decide to compute the tasks in the local vehicle, MEC server or cloud center. The computation offloading decision is made based on the utility function of the energy consumption and transmission delay, and the deep reinforcement learning technique is adopted to make decisions. Our proposed method can make full use of the existing infrastructures to implement the task offloading of sensing devices, the experimental results show that our proposed solution can achieve the maximum reward and decrease delay.

scholarly journals Research on Task-Oriented Computation Offloading Decision in Space-Air-Ground Integrated Network

2021 ◽  
Vol 13 (5) ◽  
pp. 128
Author(s):  
Jun Liu ◽  
Xiaohui Lian ◽  
Chang Liu
Keyword(s):  
Energy Consumption ◽  
Decision Process ◽  
Learning Algorithm ◽  
Low Cost ◽  
Transition Process ◽  
Computation Offloading ◽  
Processing Efficiency ◽  
Integrated Network ◽  
Decision Scheme ◽  
Task Offloading

In Space–Air–Ground Integrated Networks (SAGIN), computation offloading technology is a new way to improve the processing efficiency of node tasks and improve the limitation of computing storage resources. To solve the problem of large delay and energy consumption cost of task computation offloading, which caused by the complex and variable network offloading environment and a large amount of offloading tasks, a computation offloading decision scheme based on Markov and Deep Q Networks (DQN) is proposed. First, we select the optimal offloading network based on the characteristics of the movement of the task offloading process in the network. Then, the task offloading process is transformed into a Markov state transition process to build a model of the computational offloading decision process. Finally, the delay and energy consumption weights are introduced into the DQN algorithm to update the computation offloading decision process, and the optimal offloading decision under the low cost is achieved according to the task attributes. The simulation results show that compared with the traditional Lyapunov-based offloading decision scheme and the classical Q-learning algorithm, the delay and energy consumption are respectively reduced by 68.33% and 11.21%, under equal weights when the offloading task volume exceeds 500 Mbit. Moreover, compared with offloading to edge nodes or backbone nodes of the network alone, the proposed mixed offloading model can satisfy more than 100 task requests with low energy consumption and low delay. It can be seen that the computation offloading decision proposed in this paper can effectively reduce the delay and energy consumption during the task computation offloading in the Space–Air–Ground Integrated Network environment, and can select the optimal offloading sites to execute the tasks according to the characteristics of the task itself.

scholarly journals BIM and IoT Sensors Integration: A Framework for Consumption and Indoor Conditions Data Monitoring of Existing Buildings

2021 ◽  
Vol 13 (8) ◽  
pp. 4496
Author(s):  
Giuseppe Desogus ◽  
Emanuela Quaquero ◽  
Giulia Rubiu ◽  
Gianluca Gatto ◽  
Cristian Perra
Keyword(s):  
Energy Consumption ◽  
Low Cost ◽  
Application Programming Interface ◽  
Visual Programming ◽  
Information Modeling ◽  
Sensor Data ◽  
Time Data ◽  
Existing Building ◽  
Building Maintenance ◽  
Indoor Conditions

The low accessibility to the information regarding buildings current performances causes deep difficulties in planning appropriate interventions. Internet of Things (IoT) sensors make available a high quantity of data on energy consumptions and indoor conditions of an existing building that can drive the choice of energy retrofit interventions. Moreover, the current developments in the topic of the digital twin are leading the diffusion of Building Information Modeling (BIM) methods and tools that can provide valid support to manage all data and information for the retrofit process. This paper shows the aim and the findings of research focused on testing the integrated use of BIM methodology and IoT systems. A common data platform for the visualization of building indoor conditions (e.g., temperature, luminance etc.) and of energy consumption parameters was carried out. This platform, tested on a case study located in Italy, is developed with the integration of low-cost IoT sensors and the Revit model. To obtain a dynamic and automated exchange of data between the sensors and the BIM model, the Revit software was integrated with the Dynamo visual programming platform and with a specific Application Programming Interface (API). It is an easy and straightforward tool that can provide building managers with real-time data and information about the energy consumption and the indoor conditions of buildings, but also allows for viewing of the historical sensor data table and creating graphical historical sensor data. Furthermore, the BIM model allows the management of other useful information about the building, such as dimensional data, functions, characteristics of the components of the building, maintenance status etc., which are essential for a much more conscious, effective and accurate management of the building and for defining the most suitable retrofit scenarios.

scholarly journals AUDIT ENERGI PADA SEBUAH HOTEL

2012 ◽  
Vol 16 (3) ◽  
pp. 131
Author(s):  
Didik Ariwibowo
Keyword(s):  
Energy Consumption ◽  
Air Conditioning ◽  
Energy Savings ◽  
Electric Energy ◽  
Electrical Energy ◽  
Hot Water ◽  
Electrical Energy Consumption ◽  
Energy Audit ◽  
Electric Energy Consumption ◽  
Pumping System

Didik Ariwibowo, in this paper explain that energy audit activities conducted through several phases, namely: the initial audit, detailed audit, analysis of energy savings opportunities, and the proposed energy savings. Total energy consumed consists of electrical energy, fuel, and materials in this case is water. Electrical energy consumption data obtained from payment of electricity accounts for a year while consumption of fuel and water obtained from the payment of material procurement. From the calculation data, IKE hotels accounted for 420.867 kWh/m2.tahun, while the IKE standards for the hotel is 300 kWh/m2.tahun. Thus, IKE hotel included categorized wasteful in energy usage. The largest energy consumption on electric energy consumption. Largest electric energy consumption is on the air conditioning (AC-air conditioning) that is equal to 71.3%, and lighting and electrical equipment at 27.28%, and hot water supply system by 4.44%. Electrical energy consumption in AC looks very big. Ministry of Energy and Mineral Resources of the statutes, the profile of energy use by air conditioning at the hotel by 48.5%. With these considerations in the AC target for audit detail as the next phase of activity. The results of a detailed audit analysis to find an air conditioning system energy savings opportunities in pumping systems. Recommendations on these savings is the integration of automation on the pumping system and fan coil units (FCU). The principle of energy conservation in the pumping system is by installing variable speed drives (VSD) pump drive motor to adjust speed according to load on the FCU. Load variations FCU provide input on the VSD pumps to match. Adaptation is predicted pump can save electricity consumption up to 65.7%. Keywords: energy audit, IKE, AC

scholarly journals Specific Electrical Energy Consumption and CO2 Emissions Assessment of Agrifood Industries in the Central Region of Portugal

2014 ◽  
Vol 675-677 ◽  
pp. 1880-1886 ◽  
Author(s):  
Pedro D. Silva ◽  
Pedro Dinis Gaspar ◽  
J. Nunes ◽  
L.P.A Andrade
Keyword(s):  
Energy Efficiency ◽  
Energy Consumption ◽  
Food Safety ◽  
Central Region ◽  
Electrical Energy ◽  
Electrical Energy Consumption ◽  
Reference Levels ◽  
Energy Characteristics ◽  
Result Analysis

This paper provides a characterization of the electrical energy consumption of agrifood industries located in the central region of Portugal that use refrigeration systems to ensure the food safety. The study is based on the result analysis of survey data and energy characteristics of the participating companies belonging to the following agrifood sectors: meat, dairy, horticultural, distribution and wine. Through the quantification of energy consumption of companies is possible to determine the amount of greenhouse gases (GHGs) emissions indexed to its manufacturing process. Comparing the energy and GHGs emissions indexes of companies of a sector and between sectors is possible to create reference levels. With the results of this work is possible to rating the companies in relation to reference levels of energy and GHGs emissions and thus promote the rational use of energy by the application of practice measures for the improvement of the energy efficiency and the reduction of GHGs emissions.

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