Operating conditions for experiments at low oxygen concentration.
\r\n\tsandwiches, etc.
\r\n\r\n\tListeria monocytogenes causes one of the most serious and life-threatening diseases (listeriosis), usually caused by eating food contaminated with Listeria monocytogenes. An estimate of 1,600 people get sick (especially at risk-groups including pregnant women, newborns, old people (65 years old and above), people with weakened immune systems, etc.) and about 260 die (Listeria is the third leading cause of death from foodborne illness in the U.S.) each year, in the U.S. from Listeriosis.
\r\n\t
\r\n\tThe main goal of the book is to provide accurate and updated information on Listeria monocytogenes so governments (decision-makers), food industry, consumers, and other stakeholders can implement appropriate preventative measures to control Listeria monocytogenes. This book will cover several topics including the prevalence of Listeria monocytogenes in developed countries, the prevalence of Listeria monocytogenes in developing countries, the prevalence of Listeria monocytogenes in ready-to-eat food, detection of Listeria monocytogenes in Food, control of Listeria monocytogenes in food-processing facilities, etc.
Floods are common natural disasters throughout the world. Each year they cause considerable damage to people’s lives and properties. In the spring of 1973, the lower Saint John River in the Fredericton area (New Brunswick, Canada)
\n\t\t\tThe impact of flooding in Fredericton, New Brunswick in Spring, 2008
experienced its worst ever recorded flooding, resulting in economic losses of CAD 31,9 million, and the loss of one life (CIWD, 1974). At the peak of the flood, private houses and public churches were flooded, and roads and bridges were damaged.
\n\t\t\tFlooding of St. John River in 2008.
Since 1973 other floods have caused another three lives lost and more than CAD 68.9 million in damage.
\n\t\t\tOne house taken by the flood in 2008.
In May 2008, heavy rains combined with melted snow have overwhelmed the St. John River, which is 673 kilometres long, and brought water levels to a height that many regions have not seen in more than three decades. Homes have floated off their foundation and travelled downstream, while 600 families and individuals have been evacuated (see Figures 1, 2 and 3). The determination of the financial cost of damages caused by this flooding is still not finalized.
\n\t\t\tFlood forecasting has been proven to reduce the property damage and the loss of lives (Sanders et al., 2005). The recent advances in forecasting for flood warning (Moore et al., 2005) have shown that is possible to integrate rainfall modeling and forecasting with flood forecasting and warning. The research paper on World Wide Web based hydrological model for flood prediction using GIS (Al-Sabhan et al., 2003) gives an excellent overview of current research advances and a new on-line available prototype that combined hydrological modeling with Internet technology.
\n\t\t\tHowever, in this research we didn’t try to customize any of the existing flood forecasting models described in the literature as it is proven to be very difficult and very specific to the different modeling tools that are used (Al-Sabhan et al., 2003). Instead, we implemented the automatization of specific existing processes, workflows and modeling tools for flood forecasting and monitoring in the New Brunswick Department of Environment.
\n\t\t\tThe Saint John River Forecast System operated by the Department of Environment Hydrology Centre is monitoring and predicting flood events along the Saint John River. The Hydrology Centre team uses hydrologic modeling software to predict water levels for the next 24 and 48 hours along the lower Saint John River Valley by incorporating climate data, weather forecast data, snow data and flow data.
\n\t\t\tHowever, the predicted water levels provided by this system cannot satisfy the requirements of the decision support system for flood events. The system neither directly displays the areas affected by flooding, nor shows the difference between two flood events. Based on the water levels, it is hard for users to directly determine which houses, roads, and structures will be affected by the predicted flooding. To deal with this problem, it is necessary to visualize the output from hydrological modeling in a Geographic Information System (GIS). GISs have powerful tools that allow the predicted flood elevations to be displayed as a map showing the extent of the inundation. After the interfaces for the visualization of the impact of flood events are designed, a computerized system is developed that predicts the extent of floods and dynamically displays near-real-time flood information for decision makers and the general public.
\n\t\t\tTo improve flood prediction for Saint John River, we developed a Web GIS based decision support system for flood prediction and monitoring. In this paper, we present the methods for data integration, floodplain delineation, and online map interfaces. This paper is organized as follows: in Section 2, we briefly describe the Saint John River floodplain and in Section 3, we present hydrological modelling for flood forecasting. In section 4, we present the conceptual model of the flood prediction and monitoring system and in section 5, we explain the integration of hydrological modelling and GIS. Subsection 5.1 presents a Web-based interface for dynamic flood prediction monitoring and mapping that can dynamically display observed and predicted flood extents for decision makers and the general public. In section 6, we present our conclusions, and in section 7 our acknowledgments.
\n\t\tThe Saint John River lies in a broad arc across South-Eastern Quebec, northern Maine and western New Brunswick. Its Canadian portion extends from a point on the international boundary with the State of Maine in United States to the Bay of Fundy. It drains a total watershed area of 54.600 km2. The river is about 700 km long, and the total fall from its headwaters to the city of Saint John is about 482 m. The slope of the river gradually decreases from about 1,5 metres per kilometre in the headwaters to 0,4 metres per kilometre in the reach above Fredericton (see Figure 4).
\n\t\t\tThe study area of this research is the floodplain area along a 90 km long section of the river from Fredericton to Oak Point and the French, Grand, Indian and Maquapit lakes. Flooding has been a significant problem for this area for a long time. From the largest and best documented flood occurred between April and May 1973, the greatest flood damage areas are located within the proposed study area and include:
\n\t\t\tFredericton south of the former CNR Bridge,
Nashwaaksis Subdivision,
East Bank downstream of the Princess Margaret Bridge, and
the Lincoln area (ENB-MAL, 1979).
Overview of Saint John River watershed
Flood forecasting on the Saint John River is performed by the Hydrology Centre of the New Brunswick Department of Environment in co-operation from interprovincial and international agencies. Both hydrologic and hydraulic models are utilized in order to forecast water levels in the lower Saint John River. The basic component of the system is the U.S. Army Corps of Engineers’ Streamflow Synthesis and Reservoir Regulation (SSARR) model. The Simulated Open Channel Hydraulics (SOCH) model of the Tennessee Valley Authority and the Dynamic Wave Operational (DWOPER) model (Fread, 1992, Fread, 1993, Fread and Lewis, 1998) of the National Weather Service are also used.
\n\t\t\tThe map of existing water gauges in New Brunswick.
The operational model of flood forecasting in New Brunswick River Watch.
The Hydrology Centre monitors the water levels, stream flows and climate with partner agencies, and coordinates a co-operative snow survey with reports for the entire Saint John River Basin. There are networks of 25 stream-flow gauges, 16 water level gauges, and 43 climate stations throughout the Saint John River Basin (see Figure 5). The data are transmitted to the Hydrology Centre through a variety of telecommunication systems and protocols (see Figure 6). The data are processed and analyzed before being accepted as input data to the models.
\n\t\t\tComparisons of predicted and actual water level observations over the last 10 years have shown that these forecasted river water levels have a 95% confidence level of 0,2 m. Thus, the hydrological modelling has very good flood prediction capabilities (Fread, 1993). However, the water levels predicted by the hydrological model cannot satisfy the requirements of the decision support system for flood events. Indeed, it is hard for users to directly determine which houses, roads, and structures will be affected by the predicted flooding, because the model neither directly displays the areas affected by flooding, nor shows the difference between two flood events. In order to overcome this problem, it is necessary to interface the hydrological modelling software with a Geographic Information System (GIS).
\n\t\t\tIn the past decades, engineers have developed many methods for delineating floodplain boundaries. Most of these methods are manual, tedious, and labour-intensive. With the advent of robust computer tools (GIS) and high accuracy Digital Terrain Model (DTM), automated floodplain delineation is achievable. Recently, several management systems for floodplain delineation have been developed and applied in the flood risk areas. These include floodplain delineation using watershed Modeling System (WMS) (EMRL, 1998), Arc/Info MIKE11_GIS (DHI, 2004), and HEC-GeoRAS (Ackerman, 2005). In this project, we used all of the above systems with CARIS software in order to implement floodplain delineation. CARIS (Computer Aided Resource Information System) develops and supports rigorous, technologically advanced geomatics software for managing spatial and non-spatial data. CARIS software supports Triangulated Irregular Networks and offers advanced algorithms for Digital Terrain models, such as interpolating elevations for given coordinates. In the next sections, we will show how the integration of CARIS with hydrological modelling software allows us to generate floodplain maps.
\n\t\tIn order to improve the current flood prediction system for the Saint John River, a new research has been initiated. Several provincial organisations in New Brunswick (Emergency Measures Organisation, NB Department of Environment, River-Watch and the University of New Brunswick) have been actively involved in this new research project titled “Decision Support for Flood Event Prediction and Monitoring (FEPM)”.
\n\t\t\tThe main objective of this research project is to build up a decision support system to improve the prevention, mitigation, response, and recovery from flood events.
\n\t\t\tThe New Brunswick Department of Environment Hydrology Center monitors a wide range of information on factors affecting flooding such as snow conditions, temperatures, precipitation patterns, water levels and stream flow conditions by using a wide variety of telecommunication systems ranging from satellites to the telephone.
\n\t\t\tThe New Brunswick Department of Environment Hydrology Center team uses hydrologic modelling software (DWOPER[1] -) to predict water levels for the next 48 hours along the lower Saint John River Valley by processing climate data, weather forecast data, snow data, and flow data from approximately 60 water level gauges in New Brunswick.
\n\t\t\tThe design of the system allows near real-time imagery of actual flood conditions to be overlaid on the base mapping and existing imagery, as well as overlays indicating 100-year flood extents. Map layers of transportation networks, hydrographic features, property boundaries, municipal infrastructure (e.g. power lines, natural gas lines) and contour lines can also be visualized.
\n\t\t\tConceptual model of flood prediction and monitoring system.
The final software products are integrated together within CARIS software as shown conceptually on Figure 7. Several provincial and research organisations in New Brunswick (University of New Brunswick, Emergency Measures Organization, NB Department of Environment, etc.) have been actively involved in the project. In this project, CARIS GIS software was used to implement floodplain delineation and online mapping.
\n\t\tThe implementation that integrates hydrological modeling, Digital Terrain Modelling, and a GIS algorithm for floodplain delineation will be presented in the following section.
\n\t\t\tFloodplain delineation requires a high precision ground surface DTM. Analysis of available datasets shows that there are range and accuracy limitations among these datasets. It is therefore necessary to test and integrate these datasets in order to obtain a high accuracy Digital Elevation Model data. For this research, the accuracy of provincial elevation data and the city of Fredericton data were analyzed. High accuracy control points can be used to evaluate the accuracy of DTM data. This procedure is implemented by using CARIS GIS tools. Firstly, we generated a TIN model from elevation data (see Figure 8). Then using the CARIS GIS comparative surface analysis tool, the differences between the elevations of the control points and the interpolated elevation of the corresponding points were calculated. Finally, the statistical accuracy was computed using the methodology developed during previous floods in New Brunswick (CIWD, 1974) and (ENB-MAL, 1979).
\n\t\t\tDTM of the lower Saint John watershed.
The workflow of the calculation of predicted floodplain
To support near real-time flood modelling, we developed the procedures for transmitting real time water level data from the New Brunswick Department of Environment – River Watch to the end users (see Figure 13). The water level data from the output of flood modelling by the Hydrology Centre in the Department of Environment are transmitted via FTP. The timestamp of new data is checked every 30 minutes for upload in the database. Then, the water level data are transferred to the FEPM Web Page for generating and displaying gauge bar graphs.
\n\t\t\tAt the same time, the water level data are accessed by the software module for flood plain computations (Mioc et al., 2008). With the advent of robust GIS tools and high accuracy Digital Terrain Model (DTM), automated floodplain delineation is achievable (Noman et al., 2003). As shown on Figure 9, the most significant inputs for automated floodplain delineation[1] - are the DTM (see Figure 8) and the water levels on the sections shown on Figure 10. The process considers the DTM and water levels at different locations to determine the direction and extent of flow over a floodplain for a given hydrologic event.
\n\t\t\tModeling water level surface using cross sections
The floodplain depth dataset is the primary output of this process. It indicates the high water mark and the depth of water inside the floodplain polygon, and is generated by computing the height difference between the water surface TIN with the ground surface DTM data. Based on the obtained flood depth data, the floodplain extent and depth maps can be generated. The intermediate parts of the process involve geo-referencing the water levels, extending the water levels to the probable floodplain area, and creating a TIN of the water surface. CARIS GIS allows users to create an irregular TIN or regular grid DTM, to calculate the accurately differences between two TINs or regular grid DTMs, to interpolate contours using a DTM, and to display the DTM using the CARIS 3D Viewer program. These software functionalities were used for the development of the algorithm for floodplain delineation.
\n\t\t\tDetailed zoom of the DTM and the floodplain of the area with the cross sections around Fredericton
Floodplain delineation process – computation of water surface TIN (the thick edges are constrained Delaunay edges corresponding to cross sections while the thin edges are Delaunay edges that do not correspond to cross sections)
CARIS software provides an effective spatial analysis tool that calculates floodplain delineation and facilitates the mapping of flood events. As an example of floodplain delineation, Figure 11 shows the cross-sections used for the flooding event that took place in the Spring of 1973. Figure 12 shows the constrained Delaunay triangulation (see (Okabe et al., 2000) for an introduction to constrained Delaunay triangulations) used to compute the water surface. The flood plain is computed by interpolating linearly elevations and flood depths in the triangles. The cross sections are guaranteed to be present as edges of the triangulation, because they are the constrained edges. The cross sections are spaced in order to better evaluate the influence of confluents and effluents and their spacing decreases with the curvature of the river.
\n\t\t\tCARIS Spatial Fusion was used to develop software for integration of satellite imagery and dynamic flood maps. Web map Interfaces that dynamically display maps of current and predicted flood events were developed and implemented.
\n\t\t\t\tFlood data processing diagram.
New Brunswick River Watch Web site for flood warning in lower St. John River watershed.
The architecture of the flood data processing is shown on Figure 13. The Web GIS software that we developed, allows for a spatial query based on 6-digit postal code (see Figure 14), so the users will be able to easily locate their area of interest. The web site allows one to display historical flood maps for twenty and hundred years average as well as for the catastrophic flood of 1973 (see Figure 15).
\n\t\t\t\tExisting historical flood maps.
The Web-GIS interface is also designed to calculate the flood polygon of current and predicted flood plains and display them as prediction maps (next 24 hours and 48 hours - see Figure 16). Each layer of the web map is separate, allowing the overlay and visualization of transportation networks, hydrographical features, property boundaries, municipal infrastructure and contour lines.
\n\t\t\t\tPredicted flood maps.
Visualization of the flood in 1973 – Fredericton area.
Visualization of the flood in 1973 – rural area.
To better understand the spread and the impact of floods, the three-dimensional visualization of the flood of the Spring of 1973 was implemented (see Figures 17 and 18) using IVS3D[1] - software.
\n\t\t\t\tIt allows users to visualize the major flood event that happened in the Spring of 1973 via “fly-through” animation. In this application the advanced software (from Interactive Visualization Systems) for dynamic visualization is used to interactively show the areas affected by the record high flooding in 1973.
\n\t\t\t\tThe basic map layers are integrated with orthophotos and flood areas to create this realistic visualisation tool using IVS3D.
\n\t\t\tThe Decision Support System for Flood Event Prediction and Monitoring implemented with web-mapping interfaces facilitates monitoring and prediction of flood events. It provides a basis for early warning and mapping of flood disasters. The general public can access the web site and browse the information in their area of interest. They can also visualize the impact of the flood events on the area where they live.
\n\t\t\tThis research paper presents the integration of the DWOPER hydraulic model with the CARIS GIS system to dynamically compute and display near-real-time flood warning in the lower Saint John River valley. The main phases of development and implementation of a web-based GIS software for flood monitoring and prediction are presented as well.
\n\t\t\tWith satellite imagery and a digital elevation model of the flood plain area, we can access a web-based prediction that models current flood events, and that can show how the water progresses based on the output from hydrological modelling for the next 24 and 48 hours along the lower Saint John River Valley.
\n\t\t\tThis research provides the foundation for a revised decision support system that can result in improvements in the prevention, mitigation, response, and recovery from flood events along the lower Saint John River.
\n\t\t\tFurther research is needed to improve the accuracy of digital terrain models by using LiDAR data, which will in turn improve the accuracy of hydrological modelling.
\n\t\tThe authors would like to acknowledge the generous contribution of time, materials and resources to this project by the New Brunswick Department of Transportation.This project was financially supported in part by the N.B. Emergency Measures Organization and the Canadian Department of Natural Resources Geoconnections program as well as the University of New Brunswick and the New Brunswick Innovation Foundation (NBIF). The IT Division of the City of Fredericton provided datasets available for this project. The New Brunswick Department of Environment has provided data and expertise related to hydrological modelling, and the NB Emergency Measures Organization helped with their expertise and additional funding for this project. CARIS provided the GIS software used in this project and contributed to the research project by providing the implementation of the web site and of all the related software components within CARIS Spatial Fusion. IVS provided the virtual reality software used in this project.
\n\t\tThe biological removal of nitrogen (N) comprises two processes: nitrification and denitrification. The nitrification is a strict aerobic process that involves the oxidation of ammonia (NH3) to nitrate (NO3−) by autotrophic bacteria. Firstly, ammonia is oxidized to nitrite (NO2−), by means of ammonia-oxidizing bacteria (AOB), and then nitrite is oxidized to nitrate by the nitrite-oxidizing bacteria (NOB) [1]. In the second step, named denitrification, nitrate is converted into a gaseous product, nitrous oxide (N2O) or molecular nitrogen (N2), which is finally eliminated into the atmosphere. Denitrification is an anoxic process performed by heterotrophic bacteria using nitrite and/or nitrate as the electron acceptor. In full denitrification, NO3− is reduced to NO2− and then to nitric oxide (NO), N2O, and finally to N2 [2].
\nNitrosomonas is the most common genus of autotrophic bacteria capable of oxidizing ammonium to nitrite; however, Nitrosococcus, Nitrosospira, Nitrosovibrio, and Nitrosolobus also have that ability. These ammonium oxidizers belong to the beta subdivision of the Proteobacteria [3]. Nitrobacter, Nitrospira, Nitrospina, Nitrococcus, and Nitrocystis are known to be involved in the nitrite oxidation [3]. Nitrite-oxidizing genera belong to the alpha, gamma, and delta subdivisions of the Proteobacteria [4]. Denitrification is carried out by several bacterial genera such as Achromobacter, Aerobacter, Alcaligenes, Bacillus, Brevibacterium, Lactobacillus, Micrococcus, Proteus, Pseudomonas, and Spirillum [5].
\nCarbon is not a difficult compound to eliminate by biological processes; on the contrary, one of the most common problems in wastewater treatment plants is the lack of organic carbon to carry out the denitrification process. Particularly, treatment plants with low chemical oxygen demand/nitrogen (COD/N) ratios exhibit difficulties for nitrogen removal due to a shortage of organic substrate [6, 7].
\nSeveral biological processes have been proposed for nitrogen removal. The modified Ludzack-Ettinger process is a widespread conventional technology for nitrogen biological removal. This process is a modification of a conventional activated sludge process where an anoxic reactor is located upstream of the aerobic reactor. This process with pre-anoxic configuration is commonly named anoxic/oxic (AN/OX) process. In the first reactor, denitrification is carried out using organic carbon from wastewater. For this, the process requires an internal recycle that carries nitrate, generated from ammonia by the nitrification process (aerobic reactor), to the anoxic reactor. The amount of nitrate removed in the anoxic reactor depends on both the recycle flow and availability of influent organic carbon. Several disadvantages are associated with this process: (a) high costs involved in the recirculation; (b) production of nitrogen oxides as end products, instead of N2, which is caused by microaerophilic conditions, generated by recirculation [8]; and (c) limitation of the carbon source in the anoxic tank, caused by the recirculation of the nitrate-rich mixed liquor, resulting in accumulation of intermediate products such as nitrites and nitrogen oxides [9].
\nSystems based on postanoxic denitrification have the anoxic tank located downstream of the aerobic tank. Nitrification and consumption of the organic carbon take place in the first reactor. Denitrification is carried out in the anoxic stage. Thus, mixed liquor recycle from the aerobic to the anoxic stage is not required. However, this oxic/anoxic (OX/AN) system leads usually to a total consumption of the organic carbon. This configuration was firstly proposed by Wuhrmann [10], where organic substrates required for denitrification were probably supplied from endogenous death and lysis of active biomass [11]. Then, Wuhrmann process was modified to improve denitrification by carbon addition [11]. However, additional operational costs are caused by the addition of exogenous carbon such as methanol or acetate [12]. Another disadvantage is attributed to the postanoxic denitrification process. Microaerophilic conditions generated from the transfer of oxygen by mixing in the anoxic reactor can exert an inhibitory effect on the denitrification rate [13]. This phenomenon can finally trigger the production of nitrogen oxides due to incomplete denitrification.
\nThree main routes for biological production of N2O have been proposed: hydroxylamine oxidation and nitrifier denitrification, both processes by AOB, and heterotrophic denitrification by heterotrophic denitrifiers [14]. N2O emissions from heterotrophic denitrification can occur under microaerophilic conditions, because oxygen could inhibit the activity of nitrous oxide reductase [15]. At low DOC, N removal takes place via partial nitrification, and formed nitrite is denitrified to N2/N2O by AOB [16].
\nSimultaneous nitrification and denitrification (SND) are an alternative process to the conventional configurations previously described. The SND process is carried out in a single reactor where partial nitrification, from ammonia to nitrite, coupled to denitrification, takes place. SND process is based on gradients of dissolved oxygen (DO) within the flocs. The nitrifying autotrophic bacteria are distributed on the periphery of the floc, where the dissolved oxygen concentration (DOC) is above 2 mg O2/L, while the denitrifying bacteria are located inside the floc, where the concentration of oxygen is very low [17, 18]. Large flocs (>125 μm) allow generating an oxygen gradient with anoxic conditions in the center of the floc [19, 20]. SND can be accomplished at low DOC [21]. However, at concentrations of about 0.4 mg O2/L, N2O instead of N2 may be the final product of denitrification [22]. In addition, nitrite accumulation above 1 mg/L triggers the production of N2O, and at higher nitrite levels, the denitrification process could be inhibited [21].
\nAnother alternative process to the conventional nitrification-denitrification is based on shortcut nitrification (nitritation) followed by denitritation. In this process, AOBs oxidize NH4+ to NO2−, and then, the formed NO2− is denitrified [23]. Nitrogen elimination via nitrite requires high ammonia concentration and low DOC (<0.4 mg O2/L) in order to prevent NOB growth [24]. In this process, oxygen consumption (aerobic phase) and organic carbon demand (anoxic stage) are reduced 25 and 40%, respectively, in comparison to the conventional nitrification-denitrification [25]. However, NO2− accumulated after nitritation is considered a key factor that triggers the N2O generation by means of the nitrifier denitrification in a low DO environment [26]. Partial nitritation/anammox was proposed 20 years ago as key strategy for achieving a more sustainable treatment of municipal wastewater. Partial nitritation/anammox is an autotrophic nitrogen removal process based on two successive processes: partial oxidation of ammonium to nitrite by AOBs followed by oxidation of the residual ammonium with the formed nitrite to nitrogen gas [27]. The last process named anammox is carried out by a group of Planctomycete bacteria, which grow with CO2 as the sole carbon source and use nitrite as the electron donor [3]. Partial nitrification, which occurs usually at low DO conditions (involving lower energy demands), can lead to NO2− accumulation. Nitrifier denitrification, in the presence of NO2− and low DO, has been considered the most likely pathway of production of N2O in both nitritation reactor and anammox reactor [23].
\nAdvanced N-removal processes such as partial nitrification-denitrification (shortcut nitrification, nitritation, followed by denitritation), SND, or partial nitritation-anammox are applied with the view to reducing the energy demands. However, N2O emissions still occur and can even be higher than the ones observed during conventional nitrification-denitrification [23].
\nAerobic denitrification is an alternative process to conventional anoxic denitrification, which can achieve complete denitrification at high oxygen concentrations. This process constitutes a good strategy to diminish N2O emissions [28]. A total of 37 species (14 genera) has been reported as potential aerobic denitrifiers, which belong mainly to α, β, and γ Proteobacteria [29]. Citrobacter diversus [30], Alcaligenes faecalis [31], Pseudomonas aeruginosa [32], Microvirgula aerodenitrificans [33], Paracoccus denitrificans [32], and Bacillus licheniformis [34], among others, have been reported to be able to carry out aerobic denitrification. Ji et al. [29] have proposed that nitrate and oxygen co-respiration is a microbial adaption that allows the degradation of toxic nitrate in an aerobic environment. Aerobic denitrification can be an auxiliary pathway next to aerobic respiration [35]. It has been suggested that the enzymatic system for aerobic and anaerobic denitrification is probably the same. Anaerobic denitrification is negatively affected by aerobic conditions, being widely accepted that nitrous oxide reductase is inhibited by oxygen. However, N2 generation as final product under high oxygen concentrations suggests the probable existence of different nitrous oxide reductases, which are insensitive to oxygen [35]. Denitrification via nitric oxide dismutation has been also proposed. In this process, denitrification of nitrate and nitrite to nitric oxide is followed by dismutation of nitric oxide into oxygen and N2, which did not require nitrous oxide reductase. However, it still needs to be investigated if nitric oxide dismutation is a common and widespread process between bacteria [35].
\nThe organic carbon required for denitrification has been considered the critical element in conventional nitrogen removal processes [36]. Therefore, it is crucial to achieve a nitrogen removal process using completely the organic carbon from wastewaters. Intracellular carbon such as PHA (polyhydroxyalkanoates) and/or glycogen is commonly stored in wastewater treatment systems. These carbon reserves could drive denitrification. Anaerobic/oxic (ANA/OX) configuration can enrich two kinds of organisms: polyphosphate-accumulating organisms (PAOs) and glycogen-accumulating organisms (GAOs) [37]. PAOs and GAOs are able to store PHA and glycogen. Denitrifying PAOs and denitrifying GAOs are able to denitrify using PHA and/or glycogen as carbon source.
\nThe sequential batch reactor (SBR) is one of the main technologies for the biological treatment of wastewaters, being successfully used in urban wastewater [38, 39], as in industrial wastewaters [40, 41]. A SBR with anaerobic/oxic/anoxic configuration (ANA/OX/AN SBR) has been used for the removal of carbon and nitrogen. Efficient nitrogen removal via nitrification followed by post-denitrification, without the addition of external organic carbon, was reported. For this, PHA and glycogen stored during the anaerobic phase were later used as electron donors during post-anoxic denitrification. Denitrification was attributed to denitrifying glycogen-accumulating organisms [36].
\nIn this chapter, a nitrogen removal process based on nitrification-aerobic denitrification was proposed. An anoxic/oxic (AN/OX) SBR with DOC higher than 1.5 mg O2/L during the aerobic period was utilized. In this system, two requirements must be met: (a) growth of denitrifying bacteria able to store internally sufficient carbon reserves (PHA and/or glycogen) in the anoxic phase and (b) ability of the denitrifying bacteria to denitrify during the aerobic phase by using the intracellular carbon reserves. The AN/OX SBR would avoid both mixed liquor recirculation and exogenous carbon addition, and additionally potential emissions of N2O could be minimized. Thus, the proposed system offers important advantages with respect to both conventional nitrification-denitrification and advanced N-removal processes.
\nA lab-scale SBR (1.2 L working volume) was operated for 10 months. The SBR was inoculated with sludge from a lab-scale activated sludge plant in Center of Research and Development in Food Cryotechnology (CIDCA, UNLP-CONICET-CIC, Argentina). The SBR was operated with cycles comprising the following phases: reaction (with anoxic and aerobic stages), biomass settling, and supernatant draw. The reactor was completely mixed at a stirring rate of 100 rpm, except during the settle and draw periods. The reactor was automatically controlled by a data acquisition and control system (DACS) developed in the electronic laboratory of CIDCA; pH was measured by a pH probe (Phoenix, Houston, TX, USA). Air was introduced through porous diffusers at the bottom of the reactor. Dissolved oxygen concentration was measured by a DO probe (Ingold Mettler Toledo, Urdorf, Switzerland) and expressed as percentage of the oxygen saturation level (OSL) by the DACS. The SBR scheme is shown in Figure 1.
\nScheme of the lab-scale sequencing batch reactor (from Alzate Marin et al. [42]).
Oxygen is known to increase the oxidative state of biological systems, which could negatively affect anaerobic and anoxic processes. Microaerophilic conditions can be caused by stirring. The volumetric oxygen transfer coefficient (kLa, h−1) is an important parameter in the aerobic wastewater treatment, particularly when anaerobic or anoxic conditions are required. In the present study, kLa was determined in order to evaluate the oxygen amount supplied to the reactor by agitation during the anoxic phase. kLa was measured by the clean water non-steady-state method [43] at 20°C, agitation rate of 100 rpm, and different aeration rates (vvm = 12–137 L/(L h)). Firstly, the SBR (1.2 L) was continuously aerated until the saturation concentration of oxygen (DOC*, mg O2/L) in water was reached. Then, DO is completely removed by the addition of sodium sulfite. Finally, the aeration was turned on to the oxygen saturation level. DOC was measured at several points during the aeration period. kLa in the reactor was measured by integration of the following equation:
\n\n
where DOC* is the saturation concentration of oxygen in water (mg O2/L) at the working temperature and DOC is the dissolved oxygen concentration (mg O2/L) at time (t). The driving force of the oxygen transfer process is given for the difference between DOC* and DOC.
\nA linear relationship between kLa and the aeration rate has been proposed by the following expression:
\n\n
where AER is the aeration rate (L/(L h)), m is the slope (L/L), and n (h−1) corresponds to the kLa produced by stirring without aeration (AER = 0). The parameters m and n were determined through linear regression analysis (Sigma Plot 10.0) resulting in 0.10 L/L and 2.34 h−1, respectively.
\nFor clean water, at working conditions of the SBR, 25°C, stirring rate of 100 rpm, and without aeration, a kLa value of 2.63 h−1 was estimated by using the following expression [43]:
\n\n
Based on this estimation, it was assumed that only stirring will cause oxygen penetration through liquid surface during the anoxic stage of the SBR operation.
\nSynthetic wastewater (SWW) contained sodium acetate (carbon and energy source), ammonium sulfate (nitrogen source), and potassium phosphate (phosphorus source). A micronutrient solution (1 ml) was added to the SWW (1 L) [44]; influent COD/N/P ratio was 100:10:5. SWW was fed to the reactor in the first 2 min of the anoxic period. Mixed liquor was withdrawn at the end of the aerobic phase, leading to a cellular residence time (CRT) of 10 days. Treated wastewater was removed from the SBR after settling period. A volumetric exchange ratio of about 27% was set. The effects of different operating parameters, such as DOC, organic load, cycle duration, and AN/OX ratio on the ability of nitrification and denitrification were studied.
\nThe SBR was monitored by determination of the following physical–chemical parameters: oxidation-reduction potential (ORP, mV), orthophosphate (PO43−-P, mg/L), ammonia nitrogen (NH3-N, mg/L), nitrate nitrogen (NO3−-N, mg/L), nitrite nitrogen (NO2−-N, mg/L), soluble COD (CODS, mg/L), and total COD (CODT, mg/L). The oxidation-reduction potential is a measure of the oxidative state in an aqueous system. ORP reflects the concentration of DO, organic substrate, activity of organisms, and some toxic compounds in the system, the DOC being the most important factor [45]. The ORP of the SBR was measured off-line using an ORP probe (Phoenix, Houston, TX, USA). The other physical-chemical parameters were determined by spectrophotometric methods using commercial reagents (Hach Company, Loveland, CO). CODS corresponded to the organic substrate. Biomass concentration was determined as COD (CODB, mg/L) from the difference between CODT and CODS. CODB was correlated with volatile suspended solids (VSS, mg/L). Intracellular poly-P and PHA granules were detected by Neisser and Sudan Black staining, respectively [46]. Total carbohydrate (TC) content was determined following a modified version of the anthrone method proposed by Jenkins et al. [47].
\nInorganic nitrogen (Ni) corresponded to the sum of ammonia, nitrite, and nitrate concentrations. The inorganic nitrogen removal (NiR) was measured throughout the operational cycle as follows:
\n\n
where NiO is the Ni concentration at the start of the anoxic phase (mg/L) given by the NH3-N from the wastewater and NiT corresponds to the Ni concentration (mg/L) at time t of the SBR operational cycle. Residual nitrate and nitrite (from of the previous cycle) were not considered in the determination of NiO.
\nSimultaneous nitrification and denitrification (SND) took place from the beginning of the aerobic phase until the moment when the ammonium was exhausted. Later, subsequent nitrogen removal occurred by denitrification (DN).
\nNitrogen removed via SND was determined in the aerobic phase from the difference between the amounts of oxidized ammonia nitrogen (NH3-Noxidized) and oxidized nitrogen (NOx−-N: NO3−-N + NO2−-N). For SND determination, NH3-Noxidized was calculated from the difference between the total NH3-N consumption and NH3-N assimilated into heterotrophic biomass (NH3-Nassimilated). Nitrogen assimilated by nitrifying bacteria was assumed to be negligible [48]. The total consumption of NH3-N was determined by spectrophotometry. NH3-N assimilated into heterotrophic biomass was estimated for the aerobic period in the presence of ammonium. For this, theoretical mass balances of carbon and nitrogen were carried out using typical values for stoichiometric coefficients of the studied biological process. In SBR with feast-famine regime, PHB (polyhydroxybutyrate) is synthetized from acetate under anaerobic or anoxic phase, and then biomass is produced during the aerobic phase from stored PHB. In our system, PHB production was estimated using a yield YPHB/Acetate of 0.52 C-mol PHB/C-mol Ac for anoxic condition [49]. Available acetate for PHB synthesis was estimated from difference between initial COD and COD required for anoxic denitrification using a stoichiometric coefficient of 3.8 mg CODAc/mg NO3−-N. Biomass production from PHB was estimated assuming a heterotrophic biomass yield YX/PHB of 0.5 C-mol X/C-mol PHB. Finally, NH3-Nassimilated by heterotrophs was determined assuming a biomass molecular formula of CH1.8O0.5N0.2, which is equivalent to 24.6 g VSS/C-mol X [48].
\nSND was calculated from the following equation [48]:
\n\n
where NOx−-N is the sum of the oxidized nitrogen species (nitrite and nitrate) at the moment when ammonia was exhausted and NH3-Noxidized corresponds to the ammonia nitrogen oxidized during the aerobic period.
\nNitrogen removed via denitrification (DN) was calculated from the difference between oxidized nitrogen at the end of nitrification (NOx−-NFN) and oxidized nitrogen at the end of the aerobic phase (NOx−-NFA) as follows:
\n\n
Experiments were carried out at low and high dissolved oxygen concentrations (oxygen saturation levels, OSL, of 20 and 60%, respectively) using in each case low and high organic loads (440 and 880 mg COD/L day). The following notation was used to describe and report the results of the experiments: low oxygen concentration and low organic load (LOLC), low oxygen concentration and high organic load (LOHC), high oxygen concentration and low organic load (HOLC), and high oxygen concentration and high organic load (HOHC).
\nIn these experiments, the effect of organic load on the nitrification process was evaluated at low DOC. An oxygen saturation level (OSL) of 20%, equivalent to a DOC of 1.6 mg O2/L, was set for the aerobic phase (Table 1). Experiments were carried out at two different organic volumetric loads. In experiment low oxygen concentration and low organic load (LOLC), 440 mg COD/(L day) was used, and in experiment low oxygen concentration and high organic load (LOHC), the value was 880 mg COD/(L day).
\nParameters | \nExperiment LOLC | \nExperiment LOHC | \n
---|---|---|
Anoxic phase (min) | \n150 | \n150 | \n
Aerobic phase (min) | \n150 | \n150 | \n
Settling phase (min) | \n50 | \n50 | \n
Draw phase (min) | \n10 | \n10 | \n
Total cycle length (h) | \n6 | \n6 | \n
Anoxic/aerobic ratio | \n1.0:1.0 | \n1.0:1.0 | \n
Temperature (°C) | \n25 ± 0.5 | \n25 ± 0.5 | \n
pH (anoxic and aerobic phases) | \n7.0 ± 0.1 | \n7.0 ± 0.1 | \n
Oxygen saturation level (%) | \n20 | \n20 | \n
Organic volumetric load (mg COD/(L day)) | \n440 | \n880 | \n
Nitrogen volumetric load (mg NH3-N/(L day)) | \n44 | \n88 | \n
Phosphorus volumetric load (mg P/(L day)) | \n22 | \n44 | \n
Operating conditions for experiments at low oxygen concentration.
Adapted from Alzate Marin et al. [42].
In the experiments LOLC, the SBR showed at steady state a good performance with a biomass concentration of 1220 ± 215 mg CODB/L. For organic carbon, a removal higher than 99% was reached in anoxic phase. Ammoniacal nitrogen removal was about 99%, mainly in the aerobic phase (Figure 2). In this phase, about 70% of the ammonium was nitrified up to nitrate as was determined by mass balance. According to these results, a redox potential of about +295 mV was measured during the aerobic phase, which involves a suitable oxidizing environment for autotrophic nitrification. It must be considered that ORP values between +100 and +350 mV are necessary for the nitrification process to take place [50]. A relatively low concentration of oxygen (<2.0 mg O2/L) was enough to achieve a good nitrifying activity without accumulation of nitrite. Volumetric and specific nitrification rates are shown in Table 2.
\nChanges of phosphorus and nitrogen concentrations during operational cycles of the steady-state SBR. Experiment with low oxygen concentration and low organic load (LOLC). (□) Orthophosphate (PO43−-P, mg P/L), (●) ammonia (NH3-N, mg N/L), (■) nitrate (NO3−-N, mg N/L), (▲) nitrite (NO2−-N, mg N/L), and (○) % inorganic nitrogen removal (% NiR).
Parameters | \nExperiment LOLC | \nExperiment HOLC | \nExperiment HOHC | \n|
---|---|---|---|---|
VNR (mg NH3-N/(L h)) | \n3.96 ± 0.10 | \n3.71 ± 0.45 | \n4.09 ± 0.08 | \n|
SNR (mg NH3-N/(g VSS h)) | \n4.22 ± 0.10 | \n4.14 ± 0.48 | \n1.33 ± 0.00 | \n|
VDNR (mg NO3−-N/(L h)) | \nND | \n2.53 ± 0.96 | \n2.57 ± 0.36 | \n|
SDNR (mg NO3−-N/(g VSS h)) | \nND | \n2.94 ± 1.10 | \n0.83 ± 0.10 | \n|
% NAS | \n— | \n10.0 ± 1.0 | \n28.7 ± 0.5 | \n|
% SND | \n11 ± 10 | \n0 ± 0 | \n9 ± 2 | \n|
% DN | \n5 ± 5 | \n55 ± 3 | \n57 ± 2 | \n|
% AR | \n99 ± 1 | \n99 ± 1 | \n99 ± 1 | \n|
% NiR | \n45 ± 2 | \n67 ± 2 | \n78 ± 1 | \n
Biological parameters of the SBR for the different experiments.
Adapted from Alzate Marin et al. [42].
ND, not determined.
PHA accumulation followed by degradation of the polymer took place in the anoxic and aerobic phases, respectively, as was detected by Sudan Black staining. Cocci-shaped cells arranged in tetrads (tetrad-forming organisms, TFOs) displayed that metabolic ability (Figure 3a and b). Some subgroups of Alphaproteobacteria and Gammaproteobacteria exhibit TFO morphology with GAO phenotype. These microorganisms are commonly associated with enhanced biological phosphorus removal (EBPR) deterioration [51]. In the present study, TFOs corresponded likely to some group of GAO commonly found in systems without EBPR.
\nMicrographs of activated sludge stained with Sudan black (a and b) and Neisser (c). (a) Tetrad-forming organisms (TFOs) showing positive PHA staining (final anoxic phase), (b) TFOs with negative PHA staining (final aerobic phase), and (c) negative Neisser staining.
PHA could be used as intracellular carbon source for denitrification. However, poor denitrification took place since at the end of the operational cycle, the final effluent exhibited a nitrate concentration of 4.75 ± 0.25 mg NO3−-N/L, equivalent to about 70–80% of the nitrified ammoniacal nitrogen. According to these results, nitrogen removal through the SND and DN processes represented 11 ± 10% and 5 ± 5%, respectively. The final effluent exhibited an inorganic nitrogen concentration of 4.84 ± 0.40 mg N/L, which resulted in a mean discharge of 5.80 mg N/day. These results involved an inorganic nitrogen removal of 45 ± 2% (Table 2). This poor nitrogen removal was associated with the low denitrification ability of the system. It must be considered that the residual nitrate, after the discharge of the final effluent, was completely removed by denitrification in the first 90 min of the following cycle (Figure 2).
\nPoly-P staining by Neisser method resulted negative (Figure 3c), and soluble phosphorus (orthophosphate) concentration did not show important changes (Figure 2). These results involve that PAO activity and hence the EBPR process did not take place. According to these findings, positive ORP values (+286 ± 8 mV) were recorded throughout the anoxic phase, which are not suitable for anaerobic PHA metabolism. It is well known that negative ORP values between −50 and − 200 mV are usually required for anaerobic polyphosphate breakdown [52]. In the anoxic phase, zero DOC was registered, and a kLa value of 2.63 h−1 was estimated by using Eq. (3). For these conditions, an oxygen transfer rate of 21.3 mg O2/(L h) was estimated at 25°C by using Eq. (1). The oxygen transfer by stirring increased the oxidative state (positive ORP) during the anoxic phase. It can be assumed that this phenomenon would lead to unfavorable ecological conditions for anaerobic metabolism of PAOs.
\nIn the experiments with low oxygen concentration and high organic load (LOHC), the organic volumetric load was increased from 440 to 880 mg COD/(L day) under identical operational conditions to those of the experiment LOLC (Figure 4). The nitrogen and phosphorus volumetric load were 88 mg NH3-N/(L day) and 44 mg P/(L day), respectively, in order to maintain the same COD/N/P ratio (100:10:5) (Table 1). The steady-state SBR reached a biomass concentration of 1850 ± 120 mg CODB/L. Ammoniacal nitrogen was removed only 15% throughout the operational cycle. Poor nitrification was observed as only 7% of ammonia from anoxic phase was nitrified, even though adequate oxidizing conditions were registered during the aerobic phase (ORP > +100 mV). Low nitrate concentrations were generated, and hence the denitrification process did not take place; nitrite was not accumulated. The final effluent showed a high inorganic nitrogen concentration (43.5 ± 0.20 mg N/L), resulting in a mean discharge of 57.42 mg N/day. Thus, a poor Ni removal of only 8% was achieved (Figure 4). It is important to highlight that even though the influent nitrogen load was only two times higher to that of the experiment LOLC, the daily nitrogen discharge was about ten times greater than that corresponding to the previous assay. EBPR activity was not observed; as was previously discussed for experiment LOLC, oxidizing conditions during the anoxic phase (positive ORP) were unfavorable for PAO growth.
\nChanges of phosphorus and nitrogen concentrations during operational cycles of the steady-state SBR. Experiment with low oxygen concentration and high organic load (LOHC). (□) Orthophosphate (PO43−-P, mg P/L), (●) ammonia (NH3-N, mg N/L), (■) nitrate (NO3−-N, mg N/L), (▲) nitrite (NO2−-N, mg N/L), and (○) % inorganic nitrogen removal (% NiR) (adapted from Alzate Marin et al. [42]).
In the tested system, a COD/N/P ratio of 100:10:5 was utilized in experiments LOLC and LOHC in order to ensure excess conditions of nitrogen and phosphorus. Nevertheless, a relatively low DO concentration was used, which can lead to competition between heterotrophic and nitrifying bacteria. In the experiment LOHC, the higher organic load led to a greater intracellular PHA production, in anoxic phase, in comparison to LOLC. Thus, a higher growth of heterotrophic bacteria from PHA took place in the aerobic phase, which would involve a greater oxygen uptake rate by heterotrophs. This observation was reported by Third et al. [48] working with an aerobic SBR fed with acetate. Nitrifying bacteria, with very low growth rate, were likely outcompeted by heterotroph overgrowth under low oxygen availability. This phenomenon could explain the poor nitrifying activity in experiment LOHC. In conclusion, the organic load stimulated strongly the competition by oxygen between heterotrophic and nitrifying bacteria at low DO concentrations.
\nIn these assays, at high dissolved oxygen concentration, a value of OSL (60%), equivalent to a DOC of 4.8 mg O2/L, was set for the aerobic phase (Table 3). As in the previous experiments, two organic volumetric loads were evaluated: 440 and 880 (mg COD/(L day)) (Table 3). The effects of cycle duration, anoxic/aerobic ratio, and organic load on the denitrification process were evaluated. The purpose of these experiments was to determine optimal experimental conditions to attain a good denitrifying activity and hence an acceptable process of nitrogen removal. Therefore, in addition to achieving efficient nitrification, sufficient organic carbon must be supplied for the denitrification process to take place. High oxygen availability permitted to minimize competition by oxygen between heterotrophic and nitrifying bacteria. In these experiments, the extension of the operating cycle was increased from 6 h to 12 h, and the anoxic/aerobic ratio was decreased from 1.0:1.0 to 0.5:1.0. These conditions were set in order to provide a longer aerobic period to favor the denitrification process.
\nParameters | \nExperiment HOLC | \nExperiment HOHC | \n
---|---|---|
Anoxic phase (min) | \n220 | \n220 | \n
Aerobic phase (min) | \n440 | \n440 | \n
Settling phase (min) | \n51 | \n51 | \n
Draw phase (min) | \n9 | \n9 | \n
Total cycle length (h) | \n12 | \n12 | \n
Anoxic/aerobic ratio | \n0.5:1.0 | \n0.5:1.0 | \n
Temperature (°C) | \n25 ± 0.5 | \n25 ± 0.5 | \n
pH (anoxic and aerobic phases) | \n7.5 ± 0.1 | \n7.5 ± 0.1 | \n
Oxygen saturation level (%) | \n60 | \n60 | \n
Organic volumetric load (mg COD/(L day)) | \n440 | \n880 | \n
Nitrogen volumetric load (mg NH3-N/(L day)) | \n44 | \n44 | \n
Phosphorous volumetric load (mg P/(L day)) | \n22 | \n44 | \n
Operational conditions for experiments at high dissolved oxygen concentration with different organic loads.
In the experiment HOLC, the volumetric loads of organic carbon, nitrogen, and phosphorus were the same as those used in the experiment LOLC. All the operating conditions are shown in Table 3.
\nThe COD/N/P ratio (100:10:5) and oxygen saturation level (60%) used in this assay would minimize competition between heterotrophs and nitrifiers. Oxidizing conditions were registered in the anoxic phase (ORP = +187 ± 13), being unfavorable for the EBPR process to occur. Ammonium was almost completely removed (99%). About 80% was eliminated in the aerobic phase. Nitrification produced nitrate concentrations of about 10–12 mg NO3−-N/L in the first 2 h of the aerobic period. ORP values higher than +190 mV favored the nitrifying activity. Then, the nitrate concentration gradually decreased, which was attributed to the activity of denitrifying bacteria (Figure 5). The mean discharge of nitrate was 3.2 mg N/day. This concentration was about 32% lower than the one obtained in experiment LOLC for a same nitrogen volumetric load.
\nChanges of the phosphorus and nitrogen concentrations during an operational cycle of the steady-state SBR (experiment HOLC). (□) orthophosphate (PO43−-P, mg P/L), (●) ammonia (NH3-N, mg N/L), (■) nitrate (NO3−-N, mg N/L), (▲) nitrite (NO2−-N, mg N/L), and (○) % inorganic nitrogen removal (% NiR) (adapted from Alzate Marin et al. [42]).
Residual nitrate was denitrified at the beginning of the following cycle (anoxic phase). Nitrite was not accumulated in the SBR, as was also observed in the previous experiments. The mean discharge of inorganic nitrogen was 3.2 mg N/day (corresponding totally to nitrate), being about 45% lower than the results obtained in experiment LOLC. According to the nitrogen mass balance, about 85% of the incoming ammonia in aerobic period was nitrified; nitrogen assimilation by heterotrophic bacteria corresponded to 15%. Nitrogen assimilated by heterotrophs represented 10% of the total ammonia load applied to the SBR. Volumetric and specific nitrification rates were not significantly different to those determined in the experiment LOLC. SND did not take place; denitrification began once the nitrification process was completed; 55 ± 3% of the generated nitrate was removed (Table 2).
\nNitrification followed by denitrification was the most important process for nitrogen removal. The elimination of Ni was about 50% higher than that achieved in experiment LOLC (Table 2). The greater efficiency for nitrogen removal was attributed to a higher denitrifying activity in the experiment HOLC. In addition, the improved denitrification process of this assay can be attributed to a greater extension of the aerobic phase. However, the denitrification was probably limited by a low availability of intracellular organic carbon during the aerobic phase. In the experiment HOHC, the organic volumetric load was increased from 440 to 880 mg COD/(L day), while the ammoniacal nitrogen load was the same as that corresponding to the HOLC (44 mg NH3-N/(L day)). This led to an increase in the COD/N ratio from 100:10 to 100:5. The volumetric load of phosphorus was 29 mg P/(L day). The other operating conditions were identical to those used in the experiment HOLC (Table 3).
\nOrganic substrate was completely removed in anoxic phase. Ammonium was almost depleted during the process; about 80–85% was eliminated in the aerobic phase (Figure 6). Nitrogen assimilated by heterotrophs represented almost 30% of the incoming ammonia to the SBR (Table 2). Oxidizing conditions were similar to those corresponding to previous assays, with positive ORP values. The specific nitrification rate was significantly lower than that corresponding to the assay HOLC (Table 2). This result was attributed to the enrichment of the biomass in heterotrophic bacteria because of the higher organic load applied in experiment HOHC. Biomass concentration was twice the value reached in the HOLC assay.
\nChanges of the phosphorus and nitrogen concentrations during an operational cycle of the steady-state SBR (experiment HOHC). (□) orthophosphate (PO43−-P, mg P/L), (●) ammonia (NH3-N, mg N/L), (■) nitrate (NO3−-N, mg N/L), (▲) nitrite (NO2−-N, mg N/L), and (○) % inorganic nitrogen removal (% NiR).
The SND process showed little improvement. The denitrification was similar to that obtained in experiment HOLC, and the specific denitrification rate was significantly lower than that observed in the previous experiment. The mean discharge of inorganic nitrogen was 2.2 mg N/day. The inorganic nitrogen removal was 78 ± 1%, being significantly higher than that observed in the previous assay (Table 2). In the experiments HOHC, the higher organic load generated a greater PHA production, as was estimated by material balance, in comparison with HOLC assay. Thus, a higher content of endogenous carbon and energy reserve for the denitrification process was available. However, the higher efficiency of inorganic nitrogen removal attained in experiment HOHC was attributed mainly to a greater assimilation of nitrogen by heterotrophic bacteria, which was about three times larger than that observed at low organic load (Table 2).
\nAs was mentioned, the highest inorganic nitrogen removal was attained in the experiments HOHC; however, the specific denitrification rate was significantly lower than that corresponding to the assay HOLC. It must be considered that a high organic load led to an excessive growth of heterotrophs, which probably involved an intense competition by different growth factors among heterotrophic bacteria. Under these conditions, it can be inferred that denitrifying bacteria would preferably use oxygen as the final acceptor of electrons instead of nitrate, which represents a competitive advantage in terms of energy efficiency. This would explain the low specific denitrification rate obtained in the HOHC experiment.
\nIn all the experiments, the denitrification process at aerobic phase took place without external organic carbon. Denitrification occurred from intracellular carbon and energy reserves; the specific denitrification rates obtained were higher than those corresponding to endogenous decay (0.2–0.6 mg NO3−-N/(g VSS h) [53]). Under steady-state conditions, the total carbohydrate (TC) concentration of the biomass was determined by the anthrone method throughout the operational cycle of the reactor. TC increased slightly during the anoxic phase and initial period of the aerobic phase, and then it decreased slightly at the end of the aerobic phase. These TC changes could not be attributed to cyclic changes of intracellular glycogen, which are typical of reactors with anaerobic/aerobic regime. In these systems, the microbial community is commonly enriched with GAOs and/or PAOs, which are responsible for the degradation and synthesis of glycogen during the anaerobic and aerobic stages, respectively. In the case of GAOs, glycogen constitutes the primary source of energy for both uptake of exogenous organic carbon and PHA storage during the initial anaerobic stage [51, 54]. Then, glycogen is replenished aerobically from PHA. In the anoxic/oxic SBR of the present study, GAOs as tetrad-arranged cocci and positive PHA staining were microscopically detected. However, typical GAO metabolism regarding glycogen cycling was not observed. TC increase was mainly attributed to microbial growth instead of glycogen accumulation, even though a light glycogen increase during the anoxic phase of the operational cycle cannot be discarded. Slight decay of TC at final aerobic phase could be attributed to the glycogen component. Anyway, GAO was not a representative microbial phenotype in the anoxic-oxic SBR. This result could be explained considering that oxidative conditions were prevalent in the anoxic period generated by the high oxygen transfer during the agitation.
\nBased on this analysis, it can be argued that the denitrification achieved in the SBR took place from the intracellular reserves of PHA during the aerobic phase. Denitrification process could also be driven from intracellular glycogen but to a lesser extent. PAOs and GAOs are able to denitrify using intracellular carbon source. In the present study, PAO activity was not observed. The absence of EBPR activity was associated to high oxidative conditions not favorable to PAOs during anoxic phase more than to the GAO-PAO competition. GAOs with tetrad-type morphology were probably responsible of the denitrification process; however, the denitrifying activity of other microbial groups should not be discarded.
\nThe specific denitrification rates obtained in the present study were similar (experiment HOHC) or higher (experiment HOLC) than those reported in literature for anoxic denitrification carried out by PAOs; intracellular glycogen was the carbon source used for anoxic denitrification [9, 55]. Vocks et al. [56] reported a similar SDNR to that obtained in the experiment HOLC, using a membrane bioreactor (ANA/OX/AN); denitrifying GAOs were considered as responsible for the denitrification using stored glycogen as internal carbon source [56]. Li et al. [36] reported SDNRs of 0.5 and 1.24 mg NO3−-N/(g VSS h) using glycogen and PHA, respectively, at anoxic conditions. These SDNRs were similar to that obtained in the experiment HOHC and 2–6 times lower than that corresponding to experiment HOLC.
\nAnoxic denitrification rates are commonly higher than those obtained under aerobic conditions [57]. In contrast, the specific denitrification rates (SDNR) obtained in the present study, at bulk DO concentration higher than 4.0 mg O2/L, were similar or higher to those reported for anoxic conditions.
\nA lab-scale sequencing batch reactor (SBR) operated with two phases, anoxic and aerobic, achieved complete COD removal. At low DO concentration, the nitrification process depended on the organic load. Low DO concentration and relatively high organic load (LOHC) led to significant growth of heterotrophic bacteria and poor nitrification. At low DO concentration and low organic load (LOLC), a good nitrifying activity led to an inorganic nitrogen removal of about 45%. It is known that in activated sludge systems, competition by growth factors (macro- and micronutrients and DO) between heterotrophic and nitrifying bacteria can occur. In both experiments, LOLC and LOHC, a COD/N/P ratio of 100:10:5 assured excess conditions of nitrogen and phosphorus. Nevertheless, competition by oxygen between both groups of microorganisms took place at high organic load.
\nWith reference to the experiments carried out at high oxygen concentration (HOLC and HOHC), a high DOC minimized competition by oxygen between heterotrophs and nitrifiers. Higher inorganic nitrogen removal (67–78%) was achieved at the following conditions: pH = 7.5, higher dissolved oxygen concentration, and prolonged aerobic phase. Nitrification followed by denitrification during the aerobic phase was the most important process for nitrogen removal. The elimination of Ni was 50–70% higher than that achieved in experiment LOLC. The greater efficiency for nitrogen removal was attributed to a higher denitrifying activity, due to a greater extension of the aerobic phase. From the results obtained using high dissolved oxygen concentrations (HOLC and HOHC), it can be concluded that there was no shortage of intracellular carbon and energy reserve. Thus, organic carbon was not the limiting substrate for the denitrification process under aerobic conditions. Denitrification took place mainly from the intracellular reserves of PHA during the aerobic phase. Aerobic denitrification could be attributed to glycogen-accumulating organism (GAOs) with tetrad-type morphology; activity of polyphosphate-accumulating organisms (PAOs) was not observed. Other microbial groups have probably contributed to the denitrifying activity. The nitrification followed by denitrification, under aerobic conditions, analyzed in the present chapter, is an alternative process to the conventional configurations. The specific denitrification rates, at bulk DO concentration higher than 4.0 mg O2/L, were similar or higher to those reported for anoxic conditions. It is widely accepted that in an aerobic environment, denitrifying bacteria can survive in the anaerobic/anoxic center of the microbial flocs. If not, denitrifiers could tolerate oxygen so that the denitrification process is not affected. Aerobic denitrifiers can use alternatively nitrate or oxygen as final electron acceptor. In the present study, denitrifying activity was attributed to the aerobic denitrification process.
\nThe proposed AN/OX system constitutes a simple and potentially eco-friendly process for biological nitrogen removal, providing N2 as the end product and decreasing the formation of N2O, a greenhouse gas that has an important influence on atmosphere warming.
\nThe authors gratefully acknowledge the financial support given by the Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET), Universidad Nacional de La Plata, and Agencia Nacional de Promoción Científica y Tecnológica, Argentina.
\n\n aeration rate (L/(L h) anoxic ammonia removal anaerobic ammonia-oxidizing bacteria chemical oxygen demand biomass concentration as COD (mg CODB/L) soluble COD (mg/L) total COD (mg/L) cellular residence time (days) data acquisition and control system denitrification dissolved oxygen concentration (mg O2/L) saturation concentration of oxygen (mg O2/L) glycogen-accumulating organisms volumetric oxygen transfer coefficient (h−1) low oxygen concentration and high organic load low oxygen concentration and low organic load high oxygen concentration and high organic load high oxygen concentration and low organic load molecular nitrogen nitrous oxide nitrogen assimilated by heterotrophic bacteria ammonia ammonia nitrogen (mg/L) ammonia nitrogen assimilated by heterotrophs (mg/L) oxidized ammonia nitrogen (mg/L) inorganic nitrogen (mg/L) Ni concentration at the start of the anoxic phase (mg/L) Ni concentration at time t (mg/L) inorganic nitrogen removal nitric oxide nitrite nitrite nitrogen (mg/L) nitrate nitrate nitrogen (mg/L) oxidized nitrogen (mg/L) oxidized nitrogen at the end of the aerobic phase (mg/L) oxidized nitrogen at the end of nitrification (mg/L) nitrite-oxidizing bacteria oxygen saturation level oxic polyhydroxyalkanoates polyphosphate-accumulating organisms orthophosphate (mg/L) sequencing batch reactor specific denitrification rate (mg NO3−-N/(g VSS h) simultaneous nitrification and denitrification specific nitrification rate (mg NH3-N/(g VSS h) synthetic wastewater tetrad-forming organisms total carbohydrates volumetric denitrification rate (mg NO3−-N/(L h)) volumetric nitrification rate (mg NH3-N/(L h)) volatile suspended solids (mg VSS/L) yield coefficient for PHB from acetate (C-mol PHB/C-mol Ac) yield coefficient for heterotrophic biomass from PHB (C-mol X/C-mol PHB)
License
\n\nBook Chapters published in edited volumes are distributed under the Creative Commons Attribution 3.0 Unported License (CC BY 3.0). IntechOpen maintains a very flexible Copyright Policy that ensures that there is no copyright transfer to the publisher. Therefore, Authors retain exclusive copyright to their work. All Monographs are distributed under the Creative Commons Attribution-NonCommercial 4.0 International (CC BY-NC 4.0).
\n\n',metaTitle:"Open Access Statement",metaDescription:"Book chapters published in edited volumes are distributed under the Creative Commons Attribution 3.0 Unported License (CC BY 3.0)",metaKeywords:null,canonicalURL:"/page/open-access-statement/",contentRaw:'[{"type":"htmlEditorComponent","content":"Formats
\\n\\nBased on your preferences and the stage of your scientific projects, you have multiple options for publishing your scientific research with IntechOpen:
\\n\\nPeer Review Policies
\\n\\nAll scientific Works are subject to Peer Review prior to publishing.
\\n\\n\\n\\nCosts
\\n\\nThe Open Access publishing model followed by IntechOpen eliminates subscription charges and pay-per-view fees, thus enabling readers to access research at no cost to themselves. In order to sustain these operations, and keep our publications freely accessible, we levy an Open Access Publishing Fee on all manuscripts accepted for publication to help cover the costs of editorial work and the production of books.
\\n\\n\\n\\nDigital Archiving Policy
\\n\\nIntechOpen is dedicated to ensuring the long-term preservation and availability of the scholarly research it publishes.
\\n"}]'},components:[{type:"htmlEditorComponent",content:'Formats
\n\nBased on your preferences and the stage of your scientific projects, you have multiple options for publishing your scientific research with IntechOpen:
\n\nPeer Review Policies
\n\nAll scientific Works are subject to Peer Review prior to publishing.
\n\n\n\nCosts
\n\nThe Open Access publishing model followed by IntechOpen eliminates subscription charges and pay-per-view fees, thus enabling readers to access research at no cost to themselves. In order to sustain these operations, and keep our publications freely accessible, we levy an Open Access Publishing Fee on all manuscripts accepted for publication to help cover the costs of editorial work and the production of books.
\n\n\n\nDigital Archiving Policy
\n\nIntechOpen is dedicated to ensuring the long-term preservation and availability of the scholarly research it publishes.
\n'}]},successStories:{items:[]},authorsAndEditors:{filterParams:{sort:"featured,name"},profiles:[{id:"6700",title:"Dr.",name:"Abbass A.",middleName:null,surname:"Hashim",slug:"abbass-a.-hashim",fullName:"Abbass A. Hashim",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/6700/images/1864_n.jpg",biography:"Currently I am carrying out research in several areas of interest, mainly covering work on chemical and bio-sensors, semiconductor thin film device fabrication and characterisation.\nAt the moment I have very strong interest in radiation environmental pollution and bacteriology treatment. The teams of researchers are working very hard to bring novel results in this field. I am also a member of the team in charge for the supervision of Ph.D. students in the fields of development of silicon based planar waveguide sensor devices, study of inelastic electron tunnelling in planar tunnelling nanostructures for sensing applications and development of organotellurium(IV) compounds for semiconductor applications. I am a specialist in data analysis techniques and nanosurface structure. I have served as the editor for many books, been a member of the editorial board in science journals, have published many papers and hold many patents.",institutionString:null,institution:{name:"Sheffield Hallam University",country:{name:"United Kingdom"}}},{id:"54525",title:"Prof.",name:"Abdul Latif",middleName:null,surname:"Ahmad",slug:"abdul-latif-ahmad",fullName:"Abdul Latif Ahmad",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:null},{id:"20567",title:"Prof.",name:"Ado",middleName:null,surname:"Jorio",slug:"ado-jorio",fullName:"Ado Jorio",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"Universidade Federal de Minas Gerais",country:{name:"Brazil"}}},{id:"47940",title:"Dr.",name:"Alberto",middleName:null,surname:"Mantovani",slug:"alberto-mantovani",fullName:"Alberto Mantovani",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:null},{id:"12392",title:"Mr.",name:"Alex",middleName:null,surname:"Lazinica",slug:"alex-lazinica",fullName:"Alex Lazinica",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/12392/images/7282_n.png",biography:"Alex Lazinica is the founder and CEO of IntechOpen. After obtaining a Master's degree in Mechanical Engineering, he continued his PhD studies in Robotics at the Vienna University of Technology. Here he worked as a robotic researcher with the university's Intelligent Manufacturing Systems Group as well as a guest researcher at various European universities, including the Swiss Federal Institute of Technology Lausanne (EPFL). During this time he published more than 20 scientific papers, gave presentations, served as a reviewer for major robotic journals and conferences and most importantly he co-founded and built the International Journal of Advanced Robotic Systems- world's first Open Access journal in the field of robotics. Starting this journal was a pivotal point in his career, since it was a pathway to founding IntechOpen - Open Access publisher focused on addressing academic researchers needs. Alex is a personification of IntechOpen key values being trusted, open and entrepreneurial. Today his focus is on defining the growth and development strategy for the company.",institutionString:null,institution:{name:"TU Wien",country:{name:"Austria"}}},{id:"19816",title:"Prof.",name:"Alexander",middleName:null,surname:"Kokorin",slug:"alexander-kokorin",fullName:"Alexander Kokorin",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/19816/images/1607_n.jpg",biography:"Alexander I. Kokorin: born: 1947, Moscow; DSc., PhD; Principal Research Fellow (Research Professor) of Department of Kinetics and Catalysis, N. Semenov Institute of Chemical Physics, Russian Academy of Sciences, Moscow.\r\nArea of research interests: physical chemistry of complex-organized molecular and nanosized systems, including polymer-metal complexes; the surface of doped oxide semiconductors. He is an expert in structural, absorptive, catalytic and photocatalytic properties, in structural organization and dynamic features of ionic liquids, in magnetic interactions between paramagnetic centers. The author or co-author of 3 books, over 200 articles and reviews in scientific journals and books. He is an actual member of the International EPR/ESR Society, European Society on Quantum Solar Energy Conversion, Moscow House of Scientists, of the Board of Moscow Physical Society.",institutionString:null,institution:{name:"Semenov Institute of Chemical Physics",country:{name:"Russia"}}},{id:"62389",title:"PhD.",name:"Ali Demir",middleName:null,surname:"Sezer",slug:"ali-demir-sezer",fullName:"Ali Demir Sezer",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/62389/images/3413_n.jpg",biography:"Dr. Ali Demir Sezer has a Ph.D. from Pharmaceutical Biotechnology at the Faculty of Pharmacy, University of Marmara (Turkey). He is the member of many Pharmaceutical Associations and acts as a reviewer of scientific journals and European projects under different research areas such as: drug delivery systems, nanotechnology and pharmaceutical biotechnology. Dr. Sezer is the author of many scientific publications in peer-reviewed journals and poster communications. Focus of his research activity is drug delivery, physico-chemical characterization and biological evaluation of biopolymers micro and nanoparticles as modified drug delivery system, and colloidal drug carriers (liposomes, nanoparticles etc.).",institutionString:null,institution:{name:"Marmara University",country:{name:"Turkey"}}},{id:"61051",title:"Prof.",name:"Andrea",middleName:null,surname:"Natale",slug:"andrea-natale",fullName:"Andrea Natale",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:null},{id:"100762",title:"Prof.",name:"Andrea",middleName:null,surname:"Natale",slug:"andrea-natale",fullName:"Andrea Natale",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"St David's Medical Center",country:{name:"United States of America"}}},{id:"107416",title:"Dr.",name:"Andrea",middleName:null,surname:"Natale",slug:"andrea-natale",fullName:"Andrea Natale",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"Texas Cardiac Arrhythmia",country:{name:"United States of America"}}},{id:"64434",title:"Dr.",name:"Angkoon",middleName:null,surname:"Phinyomark",slug:"angkoon-phinyomark",fullName:"Angkoon Phinyomark",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/64434/images/2619_n.jpg",biography:"My name is Angkoon Phinyomark. I received a B.Eng. degree in Computer Engineering with First Class Honors in 2008 from Prince of Songkla University, Songkhla, Thailand, where I received a Ph.D. degree in Electrical Engineering. My research interests are primarily in the area of biomedical signal processing and classification notably EMG (electromyography signal), EOG (electrooculography signal), and EEG (electroencephalography signal), image analysis notably breast cancer analysis and optical coherence tomography, and rehabilitation engineering. I became a student member of IEEE in 2008. During October 2011-March 2012, I had worked at School of Computer Science and Electronic Engineering, University of Essex, Colchester, Essex, United Kingdom. In addition, during a B.Eng. I had been a visiting research student at Faculty of Computer Science, University of Murcia, Murcia, Spain for three months.\n\nI have published over 40 papers during 5 years in refereed journals, books, and conference proceedings in the areas of electro-physiological signals processing and classification, notably EMG and EOG signals, fractal analysis, wavelet analysis, texture analysis, feature extraction and machine learning algorithms, and assistive and rehabilitative devices. I have several computer programming language certificates, i.e. Sun Certified Programmer for the Java 2 Platform 1.4 (SCJP), Microsoft Certified Professional Developer, Web Developer (MCPD), Microsoft Certified Technology Specialist, .NET Framework 2.0 Web (MCTS). I am a Reviewer for several refereed journals and international conferences, such as IEEE Transactions on Biomedical Engineering, IEEE Transactions on Industrial Electronics, Optic Letters, Measurement Science Review, and also a member of the International Advisory Committee for 2012 IEEE Business Engineering and Industrial Applications and 2012 IEEE Symposium on Business, Engineering and Industrial Applications.",institutionString:null,institution:{name:"Joseph Fourier University",country:{name:"France"}}},{id:"55578",title:"Dr.",name:"Antonio",middleName:null,surname:"Jurado-Navas",slug:"antonio-jurado-navas",fullName:"Antonio Jurado-Navas",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/55578/images/4574_n.png",biography:"Antonio Jurado-Navas received the M.S. degree (2002) and the Ph.D. degree (2009) in Telecommunication Engineering, both from the University of Málaga (Spain). He first worked as a consultant at Vodafone-Spain. From 2004 to 2011, he was a Research Assistant with the Communications Engineering Department at the University of Málaga. In 2011, he became an Assistant Professor in the same department. From 2012 to 2015, he was with Ericsson Spain, where he was working on geo-location\ntools for third generation mobile networks. Since 2015, he is a Marie-Curie fellow at the Denmark Technical University. His current research interests include the areas of mobile communication systems and channel modeling in addition to atmospheric optical communications, adaptive optics and statistics",institutionString:null,institution:{name:"University of Malaga",country:{name:"Spain"}}}],filtersByRegion:[{group:"region",caption:"North America",value:1,count:5766},{group:"region",caption:"Middle and South America",value:2,count:5227},{group:"region",caption:"Africa",value:3,count:1717},{group:"region",caption:"Asia",value:4,count:10367},{group:"region",caption:"Australia and Oceania",value:5,count:897},{group:"region",caption:"Europe",value:6,count:15789}],offset:12,limit:12,total:118188},chapterEmbeded:{data:{}},editorApplication:{success:null,errors:{}},ofsBooks:{filterParams:{sort:"dateEndThirdStepPublish"},books:[{type:"book",id:"10231",title:"Proton Therapy",subtitle:null,isOpenForSubmission:!0,hash:"f4a9009287953c8d1d89f0fa9b7597b0",slug:null,bookSignature:"",coverURL:"https://cdn.intechopen.com/books/images_new/10231.jpg",editedByType:null,editors:null,productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}},{type:"book",id:"10652",title:"Visual Object Tracking",subtitle:null,isOpenForSubmission:!0,hash:"96f3ee634a7ba49fa195e50475412af4",slug:null,bookSignature:"",coverURL:"https://cdn.intechopen.com/books/images_new/10652.jpg",editedByType:null,editors:null,productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}},{type:"book",id:"10653",title:"Optimization Algorithms",subtitle:null,isOpenForSubmission:!0,hash:"753812dbb9a6f6b57645431063114f6c",slug:null,bookSignature:"",coverURL:"https://cdn.intechopen.com/books/images_new/10653.jpg",editedByType:null,editors:null,productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}},{type:"book",id:"10655",title:"Motion Planning",subtitle:null,isOpenForSubmission:!0,hash:"809b5e290cf2dade9e7e0a5ae0ef3df0",slug:null,bookSignature:"",coverURL:"https://cdn.intechopen.com/books/images_new/10655.jpg",editedByType:null,editors:null,productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}},{type:"book",id:"10657",title:"Service Robots",subtitle:null,isOpenForSubmission:!0,hash:"5f81b9eea6eb3f9af984031b7af35588",slug:null,bookSignature:"",coverURL:"https://cdn.intechopen.com/books/images_new/10657.jpg",editedByType:null,editors:null,productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}},{type:"book",id:"10662",title:"Pedagogy",subtitle:null,isOpenForSubmission:!0,hash:"c858e1c6fb878d3b895acbacec624576",slug:null,bookSignature:"",coverURL:"https://cdn.intechopen.com/books/images_new/10662.jpg",editedByType:null,editors:null,productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}},{type:"book",id:"10673",title:"The Psychology of Trust",subtitle:null,isOpenForSubmission:!0,hash:"1f6cac41fd145f718ac0866264499cc8",slug:null,bookSignature:"",coverURL:"https://cdn.intechopen.com/books/images_new/10673.jpg",editedByType:null,editors:null,productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}},{type:"book",id:"10675",title:"Hydrostatics",subtitle:null,isOpenForSubmission:!0,hash:"c86c2fa9f835d4ad5e7efd8b01921866",slug:null,bookSignature:"",coverURL:"https://cdn.intechopen.com/books/images_new/10675.jpg",editedByType:null,editors:null,productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}},{type:"book",id:"10677",title:"Topology",subtitle:null,isOpenForSubmission:!0,hash:"85eac84b173d785f989522397616124e",slug:null,bookSignature:"",coverURL:"https://cdn.intechopen.com/books/images_new/10677.jpg",editedByType:null,editors:null,productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}},{type:"book",id:"10678",title:"Biostatistics",subtitle:null,isOpenForSubmission:!0,hash:"f63db439474a574454a66894db8b394c",slug:null,bookSignature:"",coverURL:"https://cdn.intechopen.com/books/images_new/10678.jpg",editedByType:null,editors:null,productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}},{type:"book",id:"10679",title:"Mass Production",subtitle:null,isOpenForSubmission:!0,hash:"2dae91102099b1a07be1a36a68852829",slug:null,bookSignature:"",coverURL:"https://cdn.intechopen.com/books/images_new/10679.jpg",editedByType:null,editors:null,productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}},{type:"book",id:"10684",title:"Biorefineries",subtitle:null,isOpenForSubmission:!0,hash:"23962c6b77348bcbf247c673d34562f6",slug:null,bookSignature:"",coverURL:"https://cdn.intechopen.com/books/images_new/10684.jpg",editedByType:null,editors:null,productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}}],filtersByTopic:[{group:"topic",caption:"Agricultural and Biological Sciences",value:5,count:14},{group:"topic",caption:"Biochemistry, Genetics and Molecular Biology",value:6,count:3},{group:"topic",caption:"Business, Management and Economics",value:7,count:1},{group:"topic",caption:"Chemistry",value:8,count:7},{group:"topic",caption:"Computer and Information Science",value:9,count:6},{group:"topic",caption:"Earth and Planetary Sciences",value:10,count:7},{group:"topic",caption:"Engineering",value:11,count:15},{group:"topic",caption:"Environmental Sciences",value:12,count:2},{group:"topic",caption:"Immunology and Microbiology",value:13,count:3},{group:"topic",caption:"Materials Science",value:14,count:5},{group:"topic",caption:"Mathematics",value:15,count:1},{group:"topic",caption:"Medicine",value:16,count:24},{group:"topic",caption:"Neuroscience",value:18,count:1},{group:"topic",caption:"Pharmacology, Toxicology and Pharmaceutical Science",value:19,count:2},{group:"topic",caption:"Physics",value:20,count:2},{group:"topic",caption:"Psychology",value:21,count:4},{group:"topic",caption:"Social Sciences",value:23,count:2},{group:"topic",caption:"Technology",value:24,count:1},{group:"topic",caption:"Veterinary Medicine and Science",value:25,count:1}],offset:12,limit:12,total:187},popularBooks:{featuredBooks:[{type:"book",id:"9385",title:"Renewable Energy",subtitle:"Technologies and Applications",isOpenForSubmission:!1,hash:"a6b446d19166f17f313008e6c056f3d8",slug:"renewable-energy-technologies-and-applications",bookSignature:"Tolga Taner, Archana Tiwari and Taha Selim Ustun",coverURL:"https://cdn.intechopen.com/books/images_new/9385.jpg",editors:[{id:"197240",title:"Associate Prof.",name:"Tolga",middleName:null,surname:"Taner",slug:"tolga-taner",fullName:"Tolga Taner"}],equalEditorOne:{id:"186791",title:"Dr.",name:"Archana",middleName:null,surname:"Tiwari",slug:"archana-tiwari",fullName:"Archana Tiwari",profilePictureURL:"https://mts.intechopen.com/storage/users/186791/images/system/186791.jpg",biography:"Dr. Archana Tiwari is Associate Professor at Amity University, India. Her research interests include renewable sources of energy from microalgae and further utilizing the residual biomass for the generation of value-added products, bioremediation through microalgae and microbial consortium, antioxidative enzymes and stress, and nutraceuticals from microalgae. She has been working on algal biotechnology for the last two decades. She has published her research in many international journals and has authored many books and chapters with renowned publishing houses. She has also delivered talks as an invited speaker at many national and international conferences. Dr. Tiwari is the recipient of several awards including Researcher of the Year and Distinguished Scientist.",institutionString:"Amity University",position:null,outsideEditionCount:0,totalCites:0,totalAuthoredChapters:"3",totalChapterViews:"0",totalEditedBooks:"1",institution:{name:"Amity University",institutionURL:null,country:{name:"India"}}},equalEditorTwo:{id:"197609",title:"Prof.",name:"Taha Selim",middleName:null,surname:"Ustun",slug:"taha-selim-ustun",fullName:"Taha Selim Ustun",profilePictureURL:"https://mts.intechopen.com/storage/users/197609/images/system/197609.jpeg",biography:"Dr. Taha Selim Ustun received a Ph.D. in Electrical Engineering from Victoria University, Melbourne, Australia. He is a researcher with the Fukushima Renewable Energy Institute, AIST (FREA), where he leads the Smart Grid Cybersecurity Laboratory. Prior to that, he was a faculty member with the School of Electrical and Computer Engineering, Carnegie Mellon University, Pittsburgh, PA, USA. His current research interests include power systems protection, communication in power networks, distributed generation, microgrids, electric vehicle integration, and cybersecurity in smart grids. He serves on the editorial boards of IEEE Access, IEEE Transactions on Industrial Informatics, Energies, Electronics, Electricity, World Electric Vehicle and Information journals. Dr. Ustun is a member of the IEEE 2004 and 2800, IEC Renewable Energy Management WG 8, and IEC TC 57 WG17. He has been invited to run specialist courses in Africa, India, and China. He has delivered talks for the Qatar Foundation, the World Energy Council, the Waterloo Global Science Initiative, and the European Union Energy Initiative (EUEI). His research has attracted funding from prestigious programs in Japan, Australia, the European Union, and North America.",institutionString:"Fukushima Renewable Energy Institute, AIST (FREA)",position:null,outsideEditionCount:0,totalCites:0,totalAuthoredChapters:"1",totalChapterViews:"0",totalEditedBooks:"0",institution:{name:"National Institute of Advanced Industrial Science and Technology",institutionURL:null,country:{name:"Japan"}}},equalEditorThree:null,productType:{id:"1",chapterContentType:"chapter"}},{type:"book",id:"8985",title:"Natural Resources Management and Biological Sciences",subtitle:null,isOpenForSubmission:!1,hash:"5c2e219a6c021a40b5a20c041dea88c4",slug:"natural-resources-management-and-biological-sciences",bookSignature:"Edward R. Rhodes and Humood Naser",coverURL:"https://cdn.intechopen.com/books/images_new/8985.jpg",editors:[{id:"280886",title:"Prof.",name:"Edward R",middleName:null,surname:"Rhodes",slug:"edward-r-rhodes",fullName:"Edward R Rhodes"}],equalEditorOne:null,equalEditorTwo:null,equalEditorThree:null,productType:{id:"1",chapterContentType:"chapter"}},{type:"book",id:"9027",title:"Human Blood Group Systems and Haemoglobinopathies",subtitle:null,isOpenForSubmission:!1,hash:"d00d8e40b11cfb2547d1122866531c7e",slug:"human-blood-group-systems-and-haemoglobinopathies",bookSignature:"Osaro Erhabor and Anjana Munshi",coverURL:"https://cdn.intechopen.com/books/images_new/9027.jpg",editors:[{id:"35140",title:null,name:"Osaro",middleName:null,surname:"Erhabor",slug:"osaro-erhabor",fullName:"Osaro Erhabor"}],equalEditorOne:null,equalEditorTwo:null,equalEditorThree:null,productType:{id:"1",chapterContentType:"chapter"}},{type:"book",id:"7841",title:"New Insights Into Metabolic Syndrome",subtitle:null,isOpenForSubmission:!1,hash:"ef5accfac9772b9e2c9eff884f085510",slug:"new-insights-into-metabolic-syndrome",bookSignature:"Akikazu Takada",coverURL:"https://cdn.intechopen.com/books/images_new/7841.jpg",editors:[{id:"248459",title:"Dr.",name:"Akikazu",middleName:null,surname:"Takada",slug:"akikazu-takada",fullName:"Akikazu Takada"}],equalEditorOne:null,equalEditorTwo:null,equalEditorThree:null,productType:{id:"1",chapterContentType:"chapter"}},{type:"book",id:"8558",title:"Aerodynamics",subtitle:null,isOpenForSubmission:!1,hash:"db7263fc198dfb539073ba0260a7f1aa",slug:"aerodynamics",bookSignature:"Mofid Gorji-Bandpy and Aly-Mousaad Aly",coverURL:"https://cdn.intechopen.com/books/images_new/8558.jpg",editors:[{id:"35542",title:"Prof.",name:"Mofid",middleName:null,surname:"Gorji-Bandpy",slug:"mofid-gorji-bandpy",fullName:"Mofid Gorji-Bandpy"}],equalEditorOne:null,equalEditorTwo:null,equalEditorThree:null,productType:{id:"1",chapterContentType:"chapter"}},{type:"book",id:"9668",title:"Chemistry and Biochemistry of Winemaking, Wine Stabilization and Aging",subtitle:null,isOpenForSubmission:!1,hash:"c5484276a314628acf21ec1bdc3a86b9",slug:"chemistry-and-biochemistry-of-winemaking-wine-stabilization-and-aging",bookSignature:"Fernanda Cosme, Fernando M. Nunes and Luís Filipe-Ribeiro",coverURL:"https://cdn.intechopen.com/books/images_new/9668.jpg",editors:[{id:"186819",title:"Prof.",name:"Fernanda",middleName:null,surname:"Cosme",slug:"fernanda-cosme",fullName:"Fernanda Cosme"}],equalEditorOne:null,equalEditorTwo:null,equalEditorThree:null,productType:{id:"1",chapterContentType:"chapter"}},{type:"book",id:"7847",title:"Medical Toxicology",subtitle:null,isOpenForSubmission:!1,hash:"db9b65bea093de17a0855a1b27046247",slug:"medical-toxicology",bookSignature:"Pınar Erkekoglu and Tomohisa Ogawa",coverURL:"https://cdn.intechopen.com/books/images_new/7847.jpg",editors:[{id:"109978",title:"Prof.",name:"Pınar",middleName:null,surname:"Erkekoglu",slug:"pinar-erkekoglu",fullName:"Pınar Erkekoglu"}],equalEditorOne:null,equalEditorTwo:null,equalEditorThree:null,productType:{id:"1",chapterContentType:"chapter"}},{type:"book",id:"8620",title:"Mining Techniques",subtitle:"Past, Present and Future",isOpenForSubmission:!1,hash:"b65658f81d14e9e57e49377869d3a575",slug:"mining-techniques-past-present-and-future",bookSignature:"Abhay Soni",coverURL:"https://cdn.intechopen.com/books/images_new/8620.jpg",editors:[{id:"271093",title:"Dr.",name:"Abhay",middleName:null,surname:"Soni",slug:"abhay-soni",fullName:"Abhay Soni"}],equalEditorOne:null,equalEditorTwo:null,equalEditorThree:null,productType:{id:"1",chapterContentType:"chapter"}},{type:"book",id:"9660",title:"Inland Waters",subtitle:"Dynamics and Ecology",isOpenForSubmission:!1,hash:"975c26819ceb11a926793bc2adc62bd6",slug:"inland-waters-dynamics-and-ecology",bookSignature:"Adam Devlin, Jiayi Pan and Mohammad Manjur Shah",coverURL:"https://cdn.intechopen.com/books/images_new/9660.jpg",editors:[{id:"280757",title:"Dr.",name:"Adam",middleName:"Thomas",surname:"Devlin",slug:"adam-devlin",fullName:"Adam Devlin"}],equalEditorOne:null,equalEditorTwo:null,equalEditorThree:null,productType:{id:"1",chapterContentType:"chapter"}},{type:"book",id:"9122",title:"Cosmetic Surgery",subtitle:null,isOpenForSubmission:!1,hash:"207026ca4a4125e17038e770d00ee152",slug:"cosmetic-surgery",bookSignature:"Yueh-Bih Tang",coverURL:"https://cdn.intechopen.com/books/images_new/9122.jpg",editors:[{id:"202122",title:"Prof.",name:"Yueh-Bih",middleName:null,surname:"Tang",slug:"yueh-bih-tang",fullName:"Yueh-Bih Tang"}],equalEditorOne:null,equalEditorTwo:null,equalEditorThree:null,productType:{id:"1",chapterContentType:"chapter"}},{type:"book",id:"9043",title:"Parenting",subtitle:"Studies by an Ecocultural and Transactional Perspective",isOpenForSubmission:!1,hash:"6d21066c7438e459e4c6fb13217a5c8c",slug:"parenting-studies-by-an-ecocultural-and-transactional-perspective",bookSignature:"Loredana Benedetto and Massimo Ingrassia",coverURL:"https://cdn.intechopen.com/books/images_new/9043.jpg",editors:[{id:"193200",title:"Prof.",name:"Loredana",middleName:null,surname:"Benedetto",slug:"loredana-benedetto",fullName:"Loredana Benedetto"}],equalEditorOne:null,equalEditorTwo:null,equalEditorThree:null,productType:{id:"1",chapterContentType:"chapter"}},{type:"book",id:"9731",title:"Oxidoreductase",subtitle:null,isOpenForSubmission:!1,hash:"852e6f862c85fc3adecdbaf822e64e6e",slug:"oxidoreductase",bookSignature:"Mahmoud Ahmed Mansour",coverURL:"https://cdn.intechopen.com/books/images_new/9731.jpg",editors:[{id:"224662",title:"Prof.",name:"Mahmoud Ahmed",middleName:null,surname:"Mansour",slug:"mahmoud-ahmed-mansour",fullName:"Mahmoud Ahmed Mansour"}],equalEditorOne:null,equalEditorTwo:null,equalEditorThree:null,productType:{id:"1",chapterContentType:"chapter"}}],offset:12,limit:12,total:5229},hotBookTopics:{hotBooks:[],offset:0,limit:12,total:null},publish:{},publishingProposal:{success:null,errors:{}},books:{featuredBooks:[{type:"book",id:"10065",title:"Wavelet Theory",subtitle:null,isOpenForSubmission:!1,hash:"d8868e332169597ba2182d9b004d60de",slug:"wavelet-theory",bookSignature:"Somayeh Mohammady",coverURL:"https://cdn.intechopen.com/books/images_new/10065.jpg",editors:[{id:"109280",title:"Dr.",name:"Somayeh",middleName:null,surname:"Mohammady",slug:"somayeh-mohammady",fullName:"Somayeh Mohammady"}],equalEditorOne:null,equalEditorTwo:null,equalEditorThree:null,productType:{id:"1",chapterContentType:"chapter"}},{type:"book",id:"9644",title:"Glaciers and the Polar Environment",subtitle:null,isOpenForSubmission:!1,hash:"e8cfdc161794e3753ced54e6ff30873b",slug:"glaciers-and-the-polar-environment",bookSignature:"Masaki Kanao, Danilo Godone and Niccolò Dematteis",coverURL:"https://cdn.intechopen.com/books/images_new/9644.jpg",editors:[{id:"51959",title:"Dr.",name:"Masaki",middleName:null,surname:"Kanao",slug:"masaki-kanao",fullName:"Masaki Kanao"}],equalEditorOne:null,equalEditorTwo:null,equalEditorThree:null,productType:{id:"1",chapterContentType:"chapter"}},{type:"book",id:"9385",title:"Renewable Energy",subtitle:"Technologies and Applications",isOpenForSubmission:!1,hash:"a6b446d19166f17f313008e6c056f3d8",slug:"renewable-energy-technologies-and-applications",bookSignature:"Tolga Taner, Archana Tiwari and Taha Selim Ustun",coverURL:"https://cdn.intechopen.com/books/images_new/9385.jpg",editors:[{id:"197240",title:"Associate Prof.",name:"Tolga",middleName:null,surname:"Taner",slug:"tolga-taner",fullName:"Tolga Taner"}],equalEditorOne:{id:"186791",title:"Dr.",name:"Archana",middleName:null,surname:"Tiwari",slug:"archana-tiwari",fullName:"Archana Tiwari",profilePictureURL:"https://mts.intechopen.com/storage/users/186791/images/system/186791.jpg",biography:"Dr. Archana Tiwari is Associate Professor at Amity University, India. Her research interests include renewable sources of energy from microalgae and further utilizing the residual biomass for the generation of value-added products, bioremediation through microalgae and microbial consortium, antioxidative enzymes and stress, and nutraceuticals from microalgae. She has been working on algal biotechnology for the last two decades. She has published her research in many international journals and has authored many books and chapters with renowned publishing houses. She has also delivered talks as an invited speaker at many national and international conferences. Dr. Tiwari is the recipient of several awards including Researcher of the Year and Distinguished Scientist.",institutionString:"Amity University",position:null,outsideEditionCount:0,totalCites:0,totalAuthoredChapters:"3",totalChapterViews:"0",totalEditedBooks:"1",institution:{name:"Amity University",institutionURL:null,country:{name:"India"}}},equalEditorTwo:{id:"197609",title:"Prof.",name:"Taha Selim",middleName:null,surname:"Ustun",slug:"taha-selim-ustun",fullName:"Taha Selim Ustun",profilePictureURL:"https://mts.intechopen.com/storage/users/197609/images/system/197609.jpeg",biography:"Dr. Taha Selim Ustun received a Ph.D. in Electrical Engineering from Victoria University, Melbourne, Australia. He is a researcher with the Fukushima Renewable Energy Institute, AIST (FREA), where he leads the Smart Grid Cybersecurity Laboratory. Prior to that, he was a faculty member with the School of Electrical and Computer Engineering, Carnegie Mellon University, Pittsburgh, PA, USA. His current research interests include power systems protection, communication in power networks, distributed generation, microgrids, electric vehicle integration, and cybersecurity in smart grids. He serves on the editorial boards of IEEE Access, IEEE Transactions on Industrial Informatics, Energies, Electronics, Electricity, World Electric Vehicle and Information journals. Dr. Ustun is a member of the IEEE 2004 and 2800, IEC Renewable Energy Management WG 8, and IEC TC 57 WG17. He has been invited to run specialist courses in Africa, India, and China. He has delivered talks for the Qatar Foundation, the World Energy Council, the Waterloo Global Science Initiative, and the European Union Energy Initiative (EUEI). His research has attracted funding from prestigious programs in Japan, Australia, the European Union, and North America.",institutionString:"Fukushima Renewable Energy Institute, AIST (FREA)",position:null,outsideEditionCount:0,totalCites:0,totalAuthoredChapters:"1",totalChapterViews:"0",totalEditedBooks:"0",institution:{name:"National Institute of Advanced Industrial Science and Technology",institutionURL:null,country:{name:"Japan"}}},equalEditorThree:null,productType:{id:"1",chapterContentType:"chapter"}},{type:"book",id:"8985",title:"Natural Resources Management and Biological Sciences",subtitle:null,isOpenForSubmission:!1,hash:"5c2e219a6c021a40b5a20c041dea88c4",slug:"natural-resources-management-and-biological-sciences",bookSignature:"Edward R. Rhodes and Humood Naser",coverURL:"https://cdn.intechopen.com/books/images_new/8985.jpg",editors:[{id:"280886",title:"Prof.",name:"Edward R",middleName:null,surname:"Rhodes",slug:"edward-r-rhodes",fullName:"Edward R Rhodes"}],equalEditorOne:null,equalEditorTwo:null,equalEditorThree:null,productType:{id:"1",chapterContentType:"chapter"}},{type:"book",id:"9671",title:"Macrophages",subtitle:null,isOpenForSubmission:!1,hash:"03b00fdc5f24b71d1ecdfd75076bfde6",slug:"macrophages",bookSignature:"Hridayesh Prakash",coverURL:"https://cdn.intechopen.com/books/images_new/9671.jpg",editors:[{id:"287184",title:"Dr.",name:"Hridayesh",middleName:null,surname:"Prakash",slug:"hridayesh-prakash",fullName:"Hridayesh Prakash"}],equalEditorOne:null,equalEditorTwo:null,equalEditorThree:null,productType:{id:"1",chapterContentType:"chapter"}},{type:"book",id:"9313",title:"Clay Science and Technology",subtitle:null,isOpenForSubmission:!1,hash:"6fa7e70396ff10620e032bb6cfa6fb72",slug:"clay-science-and-technology",bookSignature:"Gustavo Morari Do Nascimento",coverURL:"https://cdn.intechopen.com/books/images_new/9313.jpg",editors:[{id:"7153",title:"Prof.",name:"Gustavo",middleName:null,surname:"Morari Do Nascimento",slug:"gustavo-morari-do-nascimento",fullName:"Gustavo Morari Do Nascimento"}],equalEditorOne:null,equalEditorTwo:null,equalEditorThree:null,productType:{id:"1",chapterContentType:"chapter"}},{type:"book",id:"9888",title:"Nuclear Power Plants",subtitle:"The Processes from the Cradle to the Grave",isOpenForSubmission:!1,hash:"c2c8773e586f62155ab8221ebb72a849",slug:"nuclear-power-plants-the-processes-from-the-cradle-to-the-grave",bookSignature:"Nasser Awwad",coverURL:"https://cdn.intechopen.com/books/images_new/9888.jpg",editors:[{id:"145209",title:"Prof.",name:"Nasser",middleName:"S",surname:"Awwad",slug:"nasser-awwad",fullName:"Nasser Awwad"}],equalEditorOne:null,equalEditorTwo:null,equalEditorThree:null,productType:{id:"1",chapterContentType:"chapter"}},{type:"book",id:"9027",title:"Human Blood Group Systems and Haemoglobinopathies",subtitle:null,isOpenForSubmission:!1,hash:"d00d8e40b11cfb2547d1122866531c7e",slug:"human-blood-group-systems-and-haemoglobinopathies",bookSignature:"Osaro Erhabor and Anjana Munshi",coverURL:"https://cdn.intechopen.com/books/images_new/9027.jpg",editors:[{id:"35140",title:null,name:"Osaro",middleName:null,surname:"Erhabor",slug:"osaro-erhabor",fullName:"Osaro Erhabor"}],equalEditorOne:null,equalEditorTwo:null,equalEditorThree:null,productType:{id:"1",chapterContentType:"chapter"}},{type:"book",id:"10432",title:"Casting Processes and Modelling of Metallic Materials",subtitle:null,isOpenForSubmission:!1,hash:"2c5c9df938666bf5d1797727db203a6d",slug:"casting-processes-and-modelling-of-metallic-materials",bookSignature:"Zakaria Abdallah and Nada Aldoumani",coverURL:"https://cdn.intechopen.com/books/images_new/10432.jpg",editors:[{id:"201670",title:"Dr.",name:"Zak",middleName:null,surname:"Abdallah",slug:"zak-abdallah",fullName:"Zak Abdallah"}],equalEditorOne:null,equalEditorTwo:null,equalEditorThree:null,productType:{id:"1",chapterContentType:"chapter"}},{type:"book",id:"7841",title:"New Insights Into Metabolic Syndrome",subtitle:null,isOpenForSubmission:!1,hash:"ef5accfac9772b9e2c9eff884f085510",slug:"new-insights-into-metabolic-syndrome",bookSignature:"Akikazu Takada",coverURL:"https://cdn.intechopen.com/books/images_new/7841.jpg",editors:[{id:"248459",title:"Dr.",name:"Akikazu",middleName:null,surname:"Takada",slug:"akikazu-takada",fullName:"Akikazu Takada"}],equalEditorOne:null,equalEditorTwo:null,equalEditorThree:null,productType:{id:"1",chapterContentType:"chapter"}}],latestBooks:[{type:"book",id:"9550",title:"Entrepreneurship",subtitle:"Contemporary Issues",isOpenForSubmission:!1,hash:"9b4ac1ee5b743abf6f88495452b1e5e7",slug:"entrepreneurship-contemporary-issues",bookSignature:"Mladen Turuk",coverURL:"https://cdn.intechopen.com/books/images_new/9550.jpg",editedByType:"Edited by",editors:[{id:"319755",title:"Prof.",name:"Mladen",middleName:null,surname:"Turuk",slug:"mladen-turuk",fullName:"Mladen Turuk"}],equalEditorOne:null,equalEditorTwo:null,equalEditorThree:null,productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}},{type:"book",id:"10065",title:"Wavelet Theory",subtitle:null,isOpenForSubmission:!1,hash:"d8868e332169597ba2182d9b004d60de",slug:"wavelet-theory",bookSignature:"Somayeh Mohammady",coverURL:"https://cdn.intechopen.com/books/images_new/10065.jpg",editedByType:"Edited by",editors:[{id:"109280",title:"Dr.",name:"Somayeh",middleName:null,surname:"Mohammady",slug:"somayeh-mohammady",fullName:"Somayeh Mohammady"}],equalEditorOne:null,equalEditorTwo:null,equalEditorThree:null,productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}},{type:"book",id:"9313",title:"Clay Science and Technology",subtitle:null,isOpenForSubmission:!1,hash:"6fa7e70396ff10620e032bb6cfa6fb72",slug:"clay-science-and-technology",bookSignature:"Gustavo Morari Do Nascimento",coverURL:"https://cdn.intechopen.com/books/images_new/9313.jpg",editedByType:"Edited by",editors:[{id:"7153",title:"Prof.",name:"Gustavo",middleName:null,surname:"Morari Do Nascimento",slug:"gustavo-morari-do-nascimento",fullName:"Gustavo Morari Do Nascimento"}],equalEditorOne:null,equalEditorTwo:null,equalEditorThree:null,productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}},{type:"book",id:"9888",title:"Nuclear Power Plants",subtitle:"The Processes from the Cradle to the Grave",isOpenForSubmission:!1,hash:"c2c8773e586f62155ab8221ebb72a849",slug:"nuclear-power-plants-the-processes-from-the-cradle-to-the-grave",bookSignature:"Nasser Awwad",coverURL:"https://cdn.intechopen.com/books/images_new/9888.jpg",editedByType:"Edited by",editors:[{id:"145209",title:"Prof.",name:"Nasser",middleName:"S",surname:"Awwad",slug:"nasser-awwad",fullName:"Nasser Awwad"}],equalEditorOne:null,equalEditorTwo:null,equalEditorThree:null,productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}},{type:"book",id:"8098",title:"Resources of Water",subtitle:null,isOpenForSubmission:!1,hash:"d251652996624d932ef7b8ed62cf7cfc",slug:"resources-of-water",bookSignature:"Prathna Thanjavur Chandrasekaran, Muhammad Salik Javaid, Aftab Sadiq",coverURL:"https://cdn.intechopen.com/books/images_new/8098.jpg",editedByType:"Edited by",editors:[{id:"167917",title:"Dr.",name:"Prathna",middleName:null,surname:"Thanjavur Chandrasekaran",slug:"prathna-thanjavur-chandrasekaran",fullName:"Prathna Thanjavur Chandrasekaran"}],equalEditorOne:null,equalEditorTwo:null,equalEditorThree:null,productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}},{type:"book",id:"9644",title:"Glaciers and the Polar Environment",subtitle:null,isOpenForSubmission:!1,hash:"e8cfdc161794e3753ced54e6ff30873b",slug:"glaciers-and-the-polar-environment",bookSignature:"Masaki Kanao, Danilo Godone and Niccolò Dematteis",coverURL:"https://cdn.intechopen.com/books/images_new/9644.jpg",editedByType:"Edited by",editors:[{id:"51959",title:"Dr.",name:"Masaki",middleName:null,surname:"Kanao",slug:"masaki-kanao",fullName:"Masaki Kanao"}],equalEditorOne:null,equalEditorTwo:null,equalEditorThree:null,productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}},{type:"book",id:"10432",title:"Casting Processes and Modelling of Metallic Materials",subtitle:null,isOpenForSubmission:!1,hash:"2c5c9df938666bf5d1797727db203a6d",slug:"casting-processes-and-modelling-of-metallic-materials",bookSignature:"Zakaria Abdallah and Nada Aldoumani",coverURL:"https://cdn.intechopen.com/books/images_new/10432.jpg",editedByType:"Edited by",editors:[{id:"201670",title:"Dr.",name:"Zak",middleName:null,surname:"Abdallah",slug:"zak-abdallah",fullName:"Zak Abdallah"}],equalEditorOne:null,equalEditorTwo:null,equalEditorThree:null,productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}},{type:"book",id:"9671",title:"Macrophages",subtitle:null,isOpenForSubmission:!1,hash:"03b00fdc5f24b71d1ecdfd75076bfde6",slug:"macrophages",bookSignature:"Hridayesh Prakash",coverURL:"https://cdn.intechopen.com/books/images_new/9671.jpg",editedByType:"Edited by",editors:[{id:"287184",title:"Dr.",name:"Hridayesh",middleName:null,surname:"Prakash",slug:"hridayesh-prakash",fullName:"Hridayesh Prakash"}],equalEditorOne:null,equalEditorTwo:null,equalEditorThree:null,productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}},{type:"book",id:"8415",title:"Extremophilic Microbes and Metabolites",subtitle:"Diversity, Bioprospecting and Biotechnological Applications",isOpenForSubmission:!1,hash:"93e0321bc93b89ff73730157738f8f97",slug:"extremophilic-microbes-and-metabolites-diversity-bioprospecting-and-biotechnological-applications",bookSignature:"Afef Najjari, Ameur Cherif, Haïtham Sghaier and Hadda Imene Ouzari",coverURL:"https://cdn.intechopen.com/books/images_new/8415.jpg",editedByType:"Edited by",editors:[{id:"196823",title:"Dr.",name:"Afef",middleName:null,surname:"Najjari",slug:"afef-najjari",fullName:"Afef Najjari"}],equalEditorOne:null,equalEditorTwo:null,equalEditorThree:null,productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}},{type:"book",id:"9731",title:"Oxidoreductase",subtitle:null,isOpenForSubmission:!1,hash:"852e6f862c85fc3adecdbaf822e64e6e",slug:"oxidoreductase",bookSignature:"Mahmoud Ahmed Mansour",coverURL:"https://cdn.intechopen.com/books/images_new/9731.jpg",editedByType:"Edited by",editors:[{id:"224662",title:"Prof.",name:"Mahmoud Ahmed",middleName:null,surname:"Mansour",slug:"mahmoud-ahmed-mansour",fullName:"Mahmoud Ahmed Mansour"}],equalEditorOne:null,equalEditorTwo:null,equalEditorThree:null,productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}}]},subject:{topic:{id:"221",title:"Astrophysics",slug:"astrophysics",parent:{title:"Physics",slug:"physics"},numberOfBooks:3,numberOfAuthorsAndEditors:42,numberOfWosCitations:9,numberOfCrossrefCitations:12,numberOfDimensionsCitations:14,videoUrl:null,fallbackUrl:null,description:null},booksByTopicFilter:{topicSlug:"astrophysics",sort:"-publishedDate",limit:12,offset:0},booksByTopicCollection:[{type:"book",id:"7357",title:"New Ideas Concerning Black Holes and the Universe",subtitle:null,isOpenForSubmission:!1,hash:"0c081ffdc6173f4c7d7d2d47231f61b9",slug:"new-ideas-concerning-black-holes-and-the-universe",bookSignature:"Eugene Tatum",coverURL:"https://cdn.intechopen.com/books/images_new/7357.jpg",editedByType:"Edited by",editors:[{id:"261441",title:"Dr.",name:"Eugene",middleName:"Terry",surname:"Tatum",slug:"eugene-tatum",fullName:"Eugene Tatum"}],equalEditorOne:null,equalEditorTwo:null,equalEditorThree:null,productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}},{type:"book",id:"6768",title:"Cosmic Rays",subtitle:null,isOpenForSubmission:!1,hash:"1578350f18d0bc3abfbcf62278630739",slug:"cosmic-rays",bookSignature:"Zbigniew Szadkowski",coverURL:"https://cdn.intechopen.com/books/images_new/6768.jpg",editedByType:"Edited by",editors:[{id:"67836",title:"Prof.",name:"Zbigniew Piotr",middleName:null,surname:"Szadkowski",slug:"zbigniew-piotr-szadkowski",fullName:"Zbigniew Piotr Szadkowski"}],equalEditorOne:null,equalEditorTwo:null,equalEditorThree:null,productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}},{type:"book",id:"5918",title:"Trends in Modern Cosmology",subtitle:null,isOpenForSubmission:!1,hash:"6fbfd7e2f33ac06d54517d3b52005231",slug:"trends-in-modern-cosmology",bookSignature:"Abraao Jesse Capistrano de Souza",coverURL:"https://cdn.intechopen.com/books/images_new/5918.jpg",editedByType:"Edited by",editors:[{id:"52362",title:"Dr.",name:"Abraao",middleName:"Jesse",surname:"Capistrano",slug:"abraao-capistrano",fullName:"Abraao Capistrano"}],equalEditorOne:null,equalEditorTwo:null,equalEditorThree:null,productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}}],booksByTopicTotal:3,mostCitedChapters:[{id:"54849",doi:"10.5772/68113",title:"Superfluid Quantum Space and Evolution of the Universe",slug:"superfluid-quantum-space-and-evolution-of-the-universe",totalDownloads:1231,totalCrossrefCites:4,totalDimensionsCites:5,book:{slug:"trends-in-modern-cosmology",title:"Trends in Modern Cosmology",fullTitle:"Trends in Modern Cosmology"},signatures:"Valeriy I. Sbitnev and Marco Fedi",authors:[{id:"93881",title:"Dr.",name:"Valeriy",middleName:null,surname:"Sbitnev",slug:"valeriy-sbitnev",fullName:"Valeriy Sbitnev"},{id:"200600",title:"Dr.",name:"Marco",middleName:null,surname:"Fedi",slug:"marco-fedi",fullName:"Marco Fedi"}]},{id:"60002",doi:"10.5772/intechopen.75426",title:"Cosmic Ray Muons as Penetrating Probes to Explore the World around Us",slug:"cosmic-ray-muons-as-penetrating-probes-to-explore-the-world-around-us",totalDownloads:735,totalCrossrefCites:3,totalDimensionsCites:4,book:{slug:"cosmic-rays",title:"Cosmic Rays",fullTitle:"Cosmic Rays"},signatures:"Paola La Rocca, Domenico Lo Presti and Francesco Riggi",authors:[{id:"18197",title:"Dr.",name:"Francesco",middleName:null,surname:"Riggi",slug:"francesco-riggi",fullName:"Francesco Riggi"},{id:"18200",title:"Dr.",name:"Paola",middleName:null,surname:"La Rocca",slug:"paola-la-rocca",fullName:"Paola La Rocca"},{id:"243971",title:"Dr.",name:"Domenico",middleName:null,surname:"Lo Presti",slug:"domenico-lo-presti",fullName:"Domenico Lo Presti"}]},{id:"54705",doi:"10.5772/68116",title:"The Impact of Baryons on the Large-Scale Structure of the Universe",slug:"the-impact-of-baryons-on-the-large-scale-structure-of-the-universe",totalDownloads:1147,totalCrossrefCites:2,totalDimensionsCites:2,book:{slug:"trends-in-modern-cosmology",title:"Trends in Modern Cosmology",fullTitle:"Trends in Modern Cosmology"},signatures:"Weiguang Cui and Youcai Zhang",authors:[{id:"199688",title:"Dr.",name:"Weiguang",middleName:null,surname:"Cui",slug:"weiguang-cui",fullName:"Weiguang Cui"},{id:"205491",title:"Dr.",name:"Youcai",middleName:null,surname:"Zhang",slug:"youcai-zhang",fullName:"Youcai Zhang"}]}],mostDownloadedChaptersLast30Days:[{id:"60002",title:"Cosmic Ray Muons as Penetrating Probes to Explore the World around Us",slug:"cosmic-ray-muons-as-penetrating-probes-to-explore-the-world-around-us",totalDownloads:734,totalCrossrefCites:3,totalDimensionsCites:4,book:{slug:"cosmic-rays",title:"Cosmic Rays",fullTitle:"Cosmic Rays"},signatures:"Paola La Rocca, Domenico Lo Presti and Francesco Riggi",authors:[{id:"18197",title:"Dr.",name:"Francesco",middleName:null,surname:"Riggi",slug:"francesco-riggi",fullName:"Francesco Riggi"},{id:"18200",title:"Dr.",name:"Paola",middleName:null,surname:"La Rocca",slug:"paola-la-rocca",fullName:"Paola La Rocca"},{id:"243971",title:"Dr.",name:"Domenico",middleName:null,surname:"Lo Presti",slug:"domenico-lo-presti",fullName:"Domenico Lo Presti"}]},{id:"60664",title:"Galactic Cosmic Rays from 1 MeV to 1 GeV as Measured by Voyager beyond the Heliopause",slug:"galactic-cosmic-rays-from-1-mev-to-1-gev-as-measured-by-voyager-beyond-the-heliopause",totalDownloads:613,totalCrossrefCites:1,totalDimensionsCites:0,book:{slug:"cosmic-rays",title:"Cosmic Rays",fullTitle:"Cosmic Rays"},signatures:"William R. Webber",authors:[{id:"114311",title:"Prof.",name:"William R",middleName:null,surname:"Webber",slug:"william-r-webber",fullName:"William R Webber"}]},{id:"60125",title:"Galactic Cosmic Rays and Low Clouds: Possible Reasons for Correlation Reversal",slug:"galactic-cosmic-rays-and-low-clouds-possible-reasons-for-correlation-reversal",totalDownloads:817,totalCrossrefCites:0,totalDimensionsCites:0,book:{slug:"cosmic-rays",title:"Cosmic Rays",fullTitle:"Cosmic Rays"},signatures:"Svetlana Veretenenko, Maxim Ogurtsov, Markus Lindholm and\nRisto Jalkanen",authors:[{id:"83636",title:"Dr.",name:"Maxim",middleName:null,surname:"Ogurtsov",slug:"maxim-ogurtsov",fullName:"Maxim Ogurtsov"},{id:"239574",title:"D.Sc.",name:"Svetlana",middleName:null,surname:"Veretenenko",slug:"svetlana-veretenenko",fullName:"Svetlana Veretenenko"},{id:"245213",title:"Dr.",name:"Markus",middleName:null,surname:"Lindholm",slug:"markus-lindholm",fullName:"Markus Lindholm"},{id:"245214",title:"Dr.",name:"Risto",middleName:null,surname:"Jalkanen",slug:"risto-jalkanen",fullName:"Risto Jalkanen"}]},{id:"54849",title:"Superfluid Quantum Space and Evolution of the Universe",slug:"superfluid-quantum-space-and-evolution-of-the-universe",totalDownloads:1226,totalCrossrefCites:4,totalDimensionsCites:5,book:{slug:"trends-in-modern-cosmology",title:"Trends in Modern Cosmology",fullTitle:"Trends in Modern Cosmology"},signatures:"Valeriy I. Sbitnev and Marco Fedi",authors:[{id:"93881",title:"Dr.",name:"Valeriy",middleName:null,surname:"Sbitnev",slug:"valeriy-sbitnev",fullName:"Valeriy Sbitnev"},{id:"200600",title:"Dr.",name:"Marco",middleName:null,surname:"Fedi",slug:"marco-fedi",fullName:"Marco Fedi"}]},{id:"54580",title:"The Importance of Cosmology in Culture: Contexts and Consequences",slug:"the-importance-of-cosmology-in-culture-contexts-and-consequences",totalDownloads:2572,totalCrossrefCites:0,totalDimensionsCites:0,book:{slug:"trends-in-modern-cosmology",title:"Trends in Modern Cosmology",fullTitle:"Trends in Modern Cosmology"},signatures:"Nicholas Campion",authors:[{id:"200410",title:"Dr.",name:"Nicholas",middleName:null,surname:"Campion",slug:"nicholas-campion",fullName:"Nicholas Campion"}]},{id:"54784",title:"Neutrino Interactions with Nuclei and Dark Matter",slug:"neutrino-interactions-with-nuclei-and-dark-matter",totalDownloads:1044,totalCrossrefCites:0,totalDimensionsCites:0,book:{slug:"trends-in-modern-cosmology",title:"Trends in Modern Cosmology",fullTitle:"Trends in Modern Cosmology"},signatures:"Paraskevi C. Divari",authors:[{id:"200618",title:"Prof.",name:"Paraskevi",middleName:null,surname:"Divari",slug:"paraskevi-divari",fullName:"Paraskevi Divari"}]},{id:"67823",title:"A Heuristic Model of the Evolving Universe Inspired by Hawking and Penrose",slug:"a-heuristic-model-of-the-evolving-universe-inspired-by-hawking-and-penrose",totalDownloads:428,totalCrossrefCites:0,totalDimensionsCites:0,book:{slug:"new-ideas-concerning-black-holes-and-the-universe",title:"New Ideas Concerning Black Holes and the Universe",fullTitle:"New Ideas Concerning Black Holes and the Universe"},signatures:"Eugene Terry Tatum",authors:[{id:"261441",title:"Dr.",name:"Eugene",middleName:"Terry",surname:"Tatum",slug:"eugene-tatum",fullName:"Eugene Tatum"}]},{id:"61639",title:"Exploration of Solar Cosmic Ray Sources by Means of Particle Energy Spectra",slug:"exploration-of-solar-cosmic-ray-sources-by-means-of-particle-energy-spectra",totalDownloads:526,totalCrossrefCites:0,totalDimensionsCites:1,book:{slug:"cosmic-rays",title:"Cosmic Rays",fullTitle:"Cosmic Rays"},signatures:"Jorge Perez-Peraza and Juan C. Márquez-Adame",authors:[{id:"92548",title:"Dr.",name:"Jorge",middleName:null,surname:"Perez-Peraza",slug:"jorge-perez-peraza",fullName:"Jorge Perez-Peraza"},{id:"248825",title:"Dr.",name:"Juan Carlos",middleName:null,surname:"Marquez Adame",slug:"juan-carlos-marquez-adame",fullName:"Juan Carlos Marquez Adame"}]},{id:"55093",title:"Relativistic Celestial Metrology: Dark Matter as an Inertial Gauge Effect",slug:"relativistic-celestial-metrology-dark-matter-as-an-inertial-gauge-effect",totalDownloads:875,totalCrossrefCites:0,totalDimensionsCites:0,book:{slug:"trends-in-modern-cosmology",title:"Trends in Modern Cosmology",fullTitle:"Trends in Modern Cosmology"},signatures:"Luca Lusanna and Ruggero Stanga",authors:[{id:"113030",title:"Dr.",name:"Luca",middleName:null,surname:"Lusanna",slug:"luca-lusanna",fullName:"Luca Lusanna"},{id:"201395",title:"Dr.",name:"Ruggero",middleName:null,surname:"Stanga",slug:"ruggero-stanga",fullName:"Ruggero Stanga"}]},{id:"54917",title:"Deformed Phase Space in Cosmology and Black Holes",slug:"deformed-phase-space-in-cosmology-and-black-holes",totalDownloads:1023,totalCrossrefCites:0,totalDimensionsCites:0,book:{slug:"trends-in-modern-cosmology",title:"Trends in Modern Cosmology",fullTitle:"Trends in Modern Cosmology"},signatures:"E.A. Mena-Barboza, L.F. Escamilla-Herrera, J.C. López-Domínguez\nand J. Torres-Arenas",authors:[{id:"58258",title:"Dr.",name:"Eri",middleName:"Atahualpa",surname:"Mena",slug:"eri-mena",fullName:"Eri Mena"}]}],onlineFirstChaptersFilter:{topicSlug:"astrophysics",limit:3,offset:0},onlineFirstChaptersCollection:[],onlineFirstChaptersTotal:0},preDownload:{success:null,errors:{}},aboutIntechopen:{},privacyPolicy:{},peerReviewing:{},howOpenAccessPublishingWithIntechopenWorks:{},sponsorshipBooks:{sponsorshipBooks:[{type:"book",id:"10176",title:"Microgrids and Local Energy Systems",subtitle:null,isOpenForSubmission:!0,hash:"c32b4a5351a88f263074b0d0ca813a9c",slug:null,bookSignature:"Prof. Nick Jenkins",coverURL:"https://cdn.intechopen.com/books/images_new/10176.jpg",editedByType:null,editors:[{id:"55219",title:"Prof.",name:"Nick",middleName:null,surname:"Jenkins",slug:"nick-jenkins",fullName:"Nick Jenkins"}],equalEditorOne:null,equalEditorTwo:null,equalEditorThree:null,productType:{id:"1",chapterContentType:"chapter"}}],offset:8,limit:8,total:1},route:{name:"profile.detail",path:"/profiles/334733/viorel-paleu",hash:"",query:{},params:{id:"334733",slug:"viorel-paleu"},fullPath:"/profiles/334733/viorel-paleu",meta:{},from:{name:null,path:"/",hash:"",query:{},params:{},fullPath:"/",meta:{}}}},function(){var e;(e=document.currentScript||document.scripts[document.scripts.length-1]).parentNode.removeChild(e)}()