IMPROVING THE DESIGN OF A FULL SCALE … · Table 18: Summary of the compliance of the WWTP design...

POLITECNICO DI MILANO

Como Campus

M. Sc. in Environmental and Geomatic Engineering

IMPROVING THE DESIGN OF A FULL

SCALE

WASTEWATER TREATMENT PLANT

WITH THE USE OF THE COMPLEX

ACTIVATED SLUDGE MODEL

Academic Year 2015/2016

Supervisor: prof. Giorgio Guariso

Master Thesis by:

Vladimir Katić

Student ID 779548

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Table of Contents

Abstract ......................................................................................................................................... 5

LIST of abbreviations.................................................................................................................... 6

LIST of figures .............................................................................................................................. 7

LIST of tables ................................................................................................................................ 8

CHAPTER 1 - INTRODUCTION ................................................................................................ 9

1.1 Basics of biological wastewater treatment .................................................................. 10

1.2 Activated Sludge Process (ASP) ................................................................................. 11

1.2.1 General information ................................................................................................ 11

1.2.2 Activated Sludge Process variables......................................................................... 13

1.3 Membrane Bioreactor technology (MBR)................................................................... 15

1.3.1 General information ................................................................................................ 15

1.3.2 Efficiency and comparison with the conventional ASP ........................................... 17

1.4 Porec project background ............................................................................................ 20

1.4.1 Framework of the project ........................................................................................ 20

1.4.2 Description of the project ........................................................................................ 21

1.5 Scope of the Work ....................................................................................................... 24

CHAPTER 2 - MODELLING OF ACTIVATED SLUDGE PROCESSES ............................... 25

2.1 Overview ..................................................................................................................... 25

2.2 Activated sludge models ............................................................................................. 26

2.2.1 Activated sludge model development ...................................................................... 26

2.2.2 Activated sludge models assumptions and limitations ............................................ 29

2.3 Simulation environments ............................................................................................. 32

2.4 Model applications ...................................................................................................... 32

2.4.1 WWTP model simulation for learning ..................................................................... 33

2.4.2 WWTP model simulation for design ........................................................................ 33

2.4.3 WWTP model simulation for process optimization ................................................. 34

CHAPTER 3 - APPLICATION OF THE BIOWIN MODELLING TOOL ............................... 35

3.1 About BioWin 5.0 ....................................................................................................... 35

3.2 Implemented Biological/Chemical models ................................................................. 36

3.2.1 Activated sludge processes ...................................................................................... 37

3.2.2 Other important physical phenomena implemented ................................................ 41

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3.3 Model simulation for WWTP Porec South ................................................................. 42

3.3.1 Project design parameters....................................................................................... 42

3.3.2 Plant configuration ................................................................................................. 44

3.4 Performed simulations and results .............................................................................. 46

3.4.1 Input data ................................................................................................................ 47

3.4.2 Dynamic simulation, summer (variable inflow) ...................................................... 48

3.4.3 Dynamic simulation, winter (variable inflow)......................................................... 52

3.4.4 Yearly average SRT of the WWTP ........................................................................... 54

3.5 Comparison with ATV-DVWK rules and standards ................................................... 55

3.5.1 Required Sludge Age - winter .................................................................................. 56

3.5.2 Required Sludge Age - summer ............................................................................... 57

3.5.3 Determination of the proportion of the reactor volume for denitrification ............. 58

3.5.4 Phosphorous removal .............................................................................................. 59

3.5.5 Sludge production ................................................................................................... 60

3.5.6 Volume of the biological reactor ............................................................................. 63

3.5.7 Summary of obtained results ................................................................................... 64

3.6 Simulation of an extreme event ................................................................................... 65

3.6.1 Assumed scenario .................................................................................................... 65

3.6.2 Performed simulation and results ........................................................................... 65

CHAPTER 4 - CONCLUSIONS ................................................................................................ 69

BIBLIOGRAPHY ....................................................................................................................... 70

ANNEX - BIOWIN PARAMETERS (ASP) .............................................................................. 72

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Abstract

This thesis discusses the application of a complex activated sludge modelling tool which

was implemented to assure the predictability and improve the design and effectiveness

of a biological wastewater treatment for the full-scale Wastewater Treatment Plant

(WWTP) “Porec South”, situated in the touristic coastal town of Porec (Parenzo) -

Republic of Croatia.

The above mentioned plant represents a part of a larger project consisting of four

wastewater treatment plants, all designed with the Membrane Bioreactor Technology

(MBR). This project has been awarded to a consortium of companies SUEZ-STRABAG

in August 2015, for which the Design & Build process is still ongoing during the

development of this work.

The selected tool used for the simulation is BioWin 5.0 (EnviroSim Associates Ltd.).

Since the plant is characterized by a large seasonal difference in terms of its hydraulic

and mass loads, the model was applied for the period with the heaviest load (summer)

and then the simulation was repeated for the period with the lowest load (winter). The

obtained study and simulations describe and confirm the chosen configuration of the

WWTP Porec South and its design using a modelling tool which is widely used and

universally recognized in the scientific community.

The results will permit to check and validate the design and to confirm process tank

volumes (anaerobic, anoxic and aerated volumes), sludge concentration, excess sludge

extraction and sludge age, recirculation rates and most importantly, the compliance to

the discharge limits and the requirements of the project .

Furthermore, an additional simulation is performed to demonstrate the effect of an

extreme peak flow event (5-day storm event) on the plant and how it might affect the

performance of the wastewater treatment process. This would give further performance

indicators of the project, thus assuring the safety and operability of the plant.

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LIST of abbreviations

ASDM Activated Sludge/Digestion Model

ASM Activated Sludge Model

ASP Activated Sludge process

BOD Biological Oxygen Demand

BIO-P Biological Phosphorus Removal

COD Chemical Oxygen Demand

DO Dissolved Oxygen

F/M Food to Microorganism ratio

HRT Hydraulic Retention Time

IAWPRC International Association on Water Pollution Research and Control

IWA International Water Association

MBR Membrane Bioreactor

MBBR Moving Bed Biofilm Reactor

MLSS Mixed Liquor Suspended Solids

PAO Phosphorus Accumulating Organisms

PE Population Equivalent

RBC Rotating Biological Reactor

SBR Sequencing Batch Reactor

SRT Solids Residence Time

SS Suspended solids

TSS Total Suspended Solids

TUDP Metabolic model developed at the Delft University of Technology

VFA Volatile Fatty Acids

VSS Volatile Suspended Solids

WWTP Wastewater Treatment Plant

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LIST of figures

Figure 1: Generalized, schematic diagram of an activated sludge process

(complete mixing)

Figure 2: Example of a WWTP with a conventional ASP technology

(WWTP Milano San Rocco: 1.050.000 PE)

Figure 3: Submerged MBR with internal vacuum-driven membrane filtration

Figure 4: Side-stream MBR with external pressure driven membrane filtration

Figure 5: Overview of the filtration processes

Figure 6: Scope of the MBR process compared to the conventional activated

sludge process with extensions

Figure 7: Example of MBR technology with submerged membranes

(WWTP Rimini: 570.000 PE)

Figure 8: Project location

Figure 9: Substrate flows for autotrophic and heterotrophic biomass in ASM1

and ASM3 models

Figure 10: Substrate flows for storage and growth of PAOs in the ASM2 model

Figure 11: Substrate flows for storage and aerobic growth of PAOs in the

TUDP model

Figure 12: Example of a plant configuration in BioWin (WWTP Porec South)

Figure 13: Simplified scheme of WWTP Porec South biological section

Figure 14: BioWin main simulator window for WWTP Porec South (summer

period)

Figure 15: BioWin main simulator window for WWTP Porec South (winter

period)

Figure 16: Pattern of flow distribution employed for winter and summer

simulations, only the applied coefficients - that were not modified in the three

simulations - are reported (and not the flows)

Figure 17: Effluent Nitrogen fractions in summer

Figure 18: Total excess sludge production from dewatering in summer

Figure 19: Weekly operation of the centrifuge, where the 1 represent an hour of

duty of the equipment and the 0 an hour of standby

Figure 20: Total waste material produced from pretreatment in summer

Figure 21: Biomass concentrations

Figure 22: Effluent nitrogen fractions in winter

Figure 23: Total excess sludge production from dewatering in winter

Figure 24: Total waste material produced from pretreatment in winter

Figure 25: Effluent Nitrogen fractions (summer - extreme event)

Figure 26: Total waste material produced from pre-treatment (summer -

extreme event)

Figure 27: Total excess sludge production from dewatering (summer - extreme

event)

Figure 28: Air flow rate need to perform the aeration of biomass (summer -

extreme event)

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LIST of tables

Table 1: Comparison of the performance: membrane bioreactor process and

conventional activated sludge process (with and without extensions for

disinfection)

Table 2: Estimated pollution parameters for the project

Table 3: Estimated pollution and influent loads for the project

Table 4: Overview of activated sludge models

Table 5: Typical flow values of influent wastewater for WWTP Porec South

Table 6: Inhabitant-specific loads in g/(I·d)

Table 7: Design daily loads of influent wastewater for WWTP Porec South

Table 8: Limit values considered for water discharge from the WWTP Porec

South

Table 9: Influent characterization - Input values for BioWin simulation for

summer and winter period

Table 10: Summary of the biological tank volumes for WWTP Porec South

Table 11: Calculations to determine the yearly average SRT

Table 12: Dimensioning sludge age in days dependent on the treatment target

and the temperature as well as the plant size (intermediate values are to be

estimated)

Table 13: Standard values for the dimensioning of denitrification for dry

weather at temperatures from 10° to 12° C and common conditions (kg nitrate

nitrogen to be denitrified per kg influent BOD5)

Table 14: Values used in the calculation of the anaerobic HRT

Table 15: Parameters and calculations employed for the comparison on sludge

production

Table 16: Sludge production as a function of the different SRT obtained or

stated in the ATV-DVWK-A 131E

Table 17: Parameters for biological reactor volume determination

Table 18: Summary of the compliance of the WWTP design with ATV-DVWK-

A 131E/Wastewater Engineering: Treatment and Reuse

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CHAPTER 1 - INTRODUCTION

The progressive deterioration of water resources globally and the large amount of

polluted water generated in industrialized societies gives wastewater treatment

processes a fundamental importance in the water loss prevention. New guidelines and

regulations (i.e. Directive 91/271/CEE) enforce the adoption of specific quality indexes

for the treated wastewater. Taking into account current environmental problems, it is not

unrealistic to believe that this trend will continue. At the same time loads on existing

plants are expected to increase due to growth of urban areas. This situation demands

more efficient treatment procedures for wastewater.

Effluents from wastewater treatment plants has been reported as the main cause of

eutrophication in surface waters. Small amounts of nutrients can lead to eutrophication

and stimulate excessive production of chemical oxygen demand (COD) in the form of

algae, loss of oxygen resources, changes in aquatic population and subsequent

deterioration of water quality.

In the field of domestic wastewater treatment, there is an increasing requirement to

improve effluent quality for the benefit of receiving surface waters. Additionally, it is

required to minimise energy consumption and reduce the use of chemicals in the

treatment process.

Inside a biological wastewater treatment plant, the Activated Sludge Process (ASP) is

the most commonly used technology to remove organic pollutant from wastewater, even

if the process was developed in the early 20th century. This is because it is the most

cost-effective, it is very flexible (it can be adapted to any kind of wastewater), it is

reliable and has the capacity of producing high quality effluent (Mulas, 2006).

Further technological developments in recent years have led to the application of a

membrane bioreactor (MBR) technology for full-scale municipal wastewater treatment.

The MBR is a suspended growth-activated sludge system that utilizes microporous

membranes for solid/liquid separation instead of secondary clarifiers that are used in a

conventional ASP. It represents a decisive step forward concerning effluent quality by

delivering a hygienically pure effluent and by exhibiting a very high operational

reliability. Advanced MBR wastewater treatment technology is being successfully

applied at an ever-increasing number of locations around the world.

The design and operation of biological wastewater treatment plants that implement the

above mentioned technologies can be simplified through the use of mathematical

models. The activated sludge models elaborated in the last two decades have resulted in

several mathematical models comprehensively describing biological wastewater

treatment processes, especially with regard to activated sludge systems. A fundamental

meaning in this area had the formulation of the Activated Sludge Model no. 1 (ASM1)

by the International Association on Water Pollution Research and Control (IAWPRC,

formerly known as IAWQ and IWA). Although neither biological nor chemical

phosphorus removal was incorporated into ASM1, this model provided the matrix

notation system and the nomenclature used in further models (inter alia ASM2 and

ASM2d). The development of these initial models has allowed the prediction of the

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effluent composition including the content of carbon, nitrogen and phosphorus

compounds. They have proven to be very helpful in the optimization studies for the

existing wastewater treatment plants (WWTPs) and the design and development of

control strategies for the existing or new WWTPs (Liwarska-Bizukojc, 2013).

1.1 Basics of biological wastewater treatment

Biological treatment is an important and integral part of any wastewater treatment plant

that treats wastewater from either municipality or industry having soluble organic

impurities or a mix of the two types of wastewater sources. The obvious economic

advantage, both in terms of capital investment and operating costs, of biological

treatment over other treatment processes like chemical oxidation; thermal oxidation etc.

has cemented its place in any integrated wastewater treatment plant.

Biological treatment using aerobic activated sludge process has been in practice for well

over a century. Increasing pressure to meet more stringent discharge standards or not

being allowed to discharge treated effluent has led to implementation of a variety of

advanced biological treatment processes in recent years (e.g. Wastewater Engineering:

Treatment and Reuse, Metcalf & Eddy, 2002).

In principle, the biological wastewater treatment is based on metabolism of natural

microorganisms to eliminate pollution caused by dissolved substances and to achieve

the prescribed parameters for secure release into the environment. These

microorganisms eliminate dissolved contamination by assimilating it for the needs of

their own growth and reproduction, leading to an increase of biological sludge

(biomass) that has to be separated from treated water.

Development of microorganisms may be organized in the form of suspended growth or

as attached growth:

a) Suspended growth

In suspended growth systems, such as activated sludge (also aerated lagoons and

aerobic digestion) waste and microorganisms are combined while oxygen diffuse and

penetrate into the cell. The microorganisms develop freely in a liquid environment and

they naturally group in floccules. The settled flocs are retained in a clarifier while part

of the sludge is recycled to the aeration tank. The ratio of recycled sludge influences the

performance of biological treatment. In relation to activated sludge concentration, time

and volume needed for purification (in relation to natural purification in rivers) are

significantly reduced. Excess sludge is regularly extracted and conveyed to the sludge

treatment section.

b) Attached growth

Contrary to suspended solid systems, microorganisms can also develop on submerged or

fixed media, watered by water that needs treatment: it is an attached growth procedure.

Microorganisms as a biofilm are maintained and grown on the media and they get in

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contact with fresh wastewater. Trickling filters and rotating biological contactors

(RBCs) are two popular attached growth processes which are commonly used in

industrial wastewater treatment. The trickling filter consists of a fixed bed media of

rocks, plastic material, or textile media. In this process wastewater flows downward and

passes and creates a biofilm on the media, that becomes thick and falls off when the

thickness of biofilm increase considerably. This phenomenon is known as “sloughing”.

Also, RBCs consist of a series of circular disks rotating through the wastewater flow,

partially submerged. These rotating disks are usually plastic. Microorganisms as biofilm

are developed on exterior surface of the disks and eventually sloughs off if the film gets

thick.

Advantages of the attached growth are its compactness and reactivity. On the other

hand, it requires complex pre-treatment (primary straining or settling, depending on the

case) and the remaining sludge is very fermentable.

The suspended growth technique is more extensive than the attached growth technique,

but on the other hand it is characterized by greater culture stability. Combined systems

also exist: organisms from the fixed culture on mobile carriers are added and mixed in

the activated sludge mixture (e.g. Moving Bed Biofilm Reactors).

In the following chapters 1.2 and 1.3, we shall briefly discuss the fundamentals and the

differences between the conventional activated sludge process and the membrane

bioreactor process, given that the former represents the base for the implemented

modelling tool, while the latter represents the implemented technology of the project we

will examine (Case study).

In chapter 1.4 are represented all the basic information and parameters that make up the

considered application.

1.2 Activated Sludge Process (ASP)

1.2.1 General information

The most common suspended growth process used for municipal wastewater treatment

is the activated sludge process as shown in figure:

Figure 1: Generalized, schematic diagram of an activated sludge process (complete mixing)

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In activated sludge process wastewater containing organic matter is aerated in an

aeration basin which promotes microorganisms to metabolize the suspended and soluble

organic matter. Part of organic matter is synthesized into new cells and part is oxidized

to CO2 and water to derive energy. In activated sludge systems the new cells formed in

the reaction are removed from the liquid stream in the form of a flocculent sludge in

settling tanks. A part of this settled biomass, described as activated sludge is returned to

the aeration tank and the remaining forms waste or excess sludge.

Activated sludge plant involves:

wastewater aeration in the presence of a microbial suspension;

solid-liquid separation following aeration;

discharge of clarified effluent;

wasting of excess biomass;

return of remaining biomass to the aeration tank.

Activated sludge is today the most common procedure for municipal wastewater

biological treatment, mainly because it has proved to be the most flexible and cost

effective. It enables treatment of primary municipal pollutants (carbon, nitrogen,

phosphorus, suspended solids) with production of relatively stable sludge.

Figure 2: Example of a WWTP with a conventional ASP technology

(WWTP Milano San Rocco: 1.050.000 PE)

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1.2.2 Activated Sludge Process variables

The main variables of activated sludge process are the mixing regime, loading rate, and

the flow scheme.

Mixing Regime

Generally two types of mixing regimes are of major interest in activated sludge process:

plug flow and complete mixing. In the first, the regime is characterized by orderly flow

of mixed liquor through the aeration tank with no element of mixed liquor overtaking or

mixing with any other element. There may be lateral mixing of mixed liquor but there

must be no mixing along the path of flow.

In complete mixing, the contents of aeration tank are well stirred and uniform

throughout. Thus, at steady state, the effluent from the aeration tank has the same

composition as the aeration tank contents.

The type of mixing regime is very important as it affects (1) oxygen transfer

requirements in the aeration tank, (2) susceptibility of biomass to shock loads, (3) local

environmental conditions in the aeration tank, and (4) the kinetics governing the

treatment process.

Loading Rate

A loading parameter that has been developed over the years is the hydraulic retention

time (HRT) θ defined as:

𝜃 =𝑉

𝑄

where V= volume of aeration tank, m3, and Q = sewage inflow, m3/d

Another empirical loading parameter is the volumetric organic loading which is

defined as the BOD applied per unit volume of aeration tank, per day.

A rational loading parameter which has found wider acceptance and is often preferred is

the specific substrate utilization rate, q, per day.

𝑞 =𝑄 ( 𝑆𝑜 − 𝑆𝑒)

𝑉 𝑋

where So and Se are influent and effluent organic matter concentration respectively,

measured as BOD5 (g/m3),

A similar loading parameter is the mean cell residence time or sludge retention time

(SRT) θc :

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𝜃𝑐 =𝑉 𝑋

𝑄𝑤𝑋𝑟 + (𝑄 − 𝑄𝑤𝑋𝑒)

where X, Xe and Xr are MLSS concentration in aeration tank, effluent and return sludge

respectively, and Qw = waste activated sludge rate.

Under steady state operation, the mass of waste activated sludge is given by:

𝑄𝑤𝑋𝑟 = 𝑌𝑄 (𝑆𝑜 − 𝑆𝑒) − 𝑘𝑑𝑋𝑉

where Y= maximum yield coefficient (microbial mass synthesized / mass of substrate

utilized) and kd = endogenous decay rate (d-1) .

From the above equation it is seen that 1/θc = Yq - kd

If the value of Se is small as compared So, q may also be expressed as Food to

Microorganism ratio, F/M

𝐹/𝑀 =𝑄(𝑆𝑜 − 𝑆𝑒)

𝑋𝑉= 𝑄𝑆𝑜/𝑋𝑉

The θc value adopted for design controls the effluent quality, and settleability and

drainability of biomass, oxygen requirement and quantity of waste activated sludge.

Flow Scheme

The flow scheme involves:

the pattern of sewage addition;

the pattern of sludge return to the aeration tank and;

the pattern of aeration.

Sewage addition may be at a single point at the inlet end or it may be at several points

along the aeration tank. The sludge return may be directly from the settling tank to the

aeration tank or through a sludge reaeration tank. Aeration may be at a uniform rate or it

may be varied from the head of the aeration tank to its end.

Conventional System and its Modifications

The conventional system maintains a plug flow hydraulic regime. Over the years,

several modifications to the conventional system have been developed to meet specific

treatment objectives. In step aeration settled sewage is introduced at several points

along the tank length which produces more uniform oxygen demand throughout.

Tapered aeration attempts to supply air to match oxygen demand along the length of

the tank. Contact stabilization provides for reaeration of return activated sludge from

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the final clarifier, which allows a smaller aeration or contact tank. Completely mixed

process aims at instantaneous mixing of the influent waste and return sludge with the

entire contents of the aeration tank. Extended aeration process operates at a low organic

load producing lesser quantity of well stabilized sludge.

1.3 Membrane Bioreactor technology (MBR)

1.3.1 General information

The combination of an activated sludge tank with a membrane filtration for the

separation of the activated sludge is called the membrane bioreactor process. The

membrane filtration takes over the separation of the activated sludge in place of the

conventional final clarification. While in secondary settling tanks only the part of the

activated sludge that is settleable is separated, i.e. forms settleable flocks. During

membrane filtration all parts of the activated sludge are separated which are larger than

the molecular separation size of the membrane. Thus, the separation of the activated

sludge from the treated waste water becomes independent of the settling characteristics

of the activated sludge and depends only on the membrane applied. In addition, a higher

solids content can be maintained in the bioreactor than in the conventional activated

sludge process so that less reactor space is needed (pg. 14, Merkblatt DWA-M 227

manual).

The two main MBR configurations for WWTPs are described below.

a) Internal/submerged membranes

The filtration element is installed in either the main bioreactor vessel or in a separate

tank. The membranes can be flat sheet or tubular or a combination of both, and can

incorporate an online backwash system which reduces membrane surface fouling by

pumping membrane permeate back through the membrane. In systems where the

membranes are in a separate tank to the bioreactor, individual trains of membranes can

be isolated to undertake cleaning regimes, however the biomass must be continuously

pumped back to the main reactor to limit TSS concentration increase. Additional

aeration is also required to provide air scouring to reduce fouling. Where the

membranes are installed in the main reactor, membrane modules are removed from the

vessel and transferred to an offline cleaning tank.

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Figure 3: Submerged MBR with internal vacuum-driven membrane filtration

(Image from http://www.atacsolution.com)

b) External/sidestream

The filtration elements are installed externally to the reactor, often in a plant room. The

biomass is either pumped directly through a number of membrane modules in series and

back to the bioreactor, or the biomass is pumped to a group of modules, from which a

second pump circulates the biomass through the modules in series. Cleaning and

soaking of the membranes can be undertaken in place with use of an installed cleaning

tank, pump and pipeline.

Figure 4: Side-stream MBR with external pressure driven membrane filtration

(Image from http://www.atacsolution.com)

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In the following figure an overview of the filtration process is given. To separate the

activated sludge with its microorganisms and particles from the treated waste water,

microfiltration membranes with a molecular separation size of maximally 0.5 µm are

used for the membrane bioreactor process.

Figure 5: Overview of the filtration processes

1.3.2 Efficiency and comparison with the conventional ASP

The membrane bioreactor process reaches performance values that are better than those

of a conventional activated sludge process with the same size (pg. 18, Merkblatt DWA-

M 227 manual). To achieve comparable values, a conventional activated sludge plant

should show process steps as shown in the following figure:

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Figure 6: Scope of the MBR process compared to the conventional activated sludge process with

extensions

The advantages of the membrane bioreactor process result from the possible higher

MLSS contents in the activated sludge tank and complete separation of all solid matter

by the membranes. Therefore, nitrogen, phosphorus and carbon in the effluent of

membrane bioreactors are reduced by the fraction which in conventional plants results

from solid matter in the effluent.

Table 1 shows the achievable performance values that can be expected under

conventional municipal supply conditions (pg. 18, Merkblatt DWA-M 227 manual).

Parameter Membrane bioreactor

plant

Conventional activated sludge

Without extensions With extensions

Solids mg/L 0 10 - 15 3 - 8

CCSB mg/L < 30 40 - 50 30 - 40

Microbiological

quality Bathing water quality 1) - Bathing water quality 1)

REMARK:

1) With regard to EC directive 76/160/ECC

Table 1: Comparison of the performance: membrane bioreactor process and conventional

activated sludge process (with and without extensions for disinfection)

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All the main advantages of MBR system over conventional activated sludge systems are

listed below (Arun Mittal, 2011):

Membrane filtration provides a positive barrier to suspended bio-solids that they

cannot escape the system. This contrasts gravity settling in activated sludge

process, where the bio-solids continuously escape the system along with

clarified effluent and sometimes a total loss of solids is also encountered due to

process upsets causing sludge-bulking in the clarifier. As a result, the bio-solids

concentration measured as MLSS/MLVSS can be maintained 3 to 4 times larger

in an MBR process (~ 10000 mg/L) in comparison to the activated sludge

process (~2500 mg/L).

Due to the above aspect of MBR, aeration tank size in the MBR system can be

one-third to one-fourth the size of the aeration tank in an activated sludge

system. Further, instead of gravity settling based clarifier, a much more compact

tank is needed to house the membrane cassettes in case of submerged MBR and

skid mounted membrane modules in case of non-submerged, external MBR

system.

Thus, MBR system requires only 40-60% of the space required for activated

sludge system, therefore significantly reducing the concrete work and overall

foot-print.

Due to membrane filtration (micro/ultrafiltration), the treated effluent quality in

case of MBR system is far superior compared to conventional activated sludge,

so the treated effluent can be directly reused as cooling tower make-up or for

gardening etc. Typical treated water quality from MBR system is:

o BOD5 < 5 mg/L

o Turbidity < 0.2 NTU

Figure 7: Example of MBR technology with submerged membranes

(WWTP Rimini: 570.000 PE)

20

In summary, membrane bioreactor technology has become more popular, abundant, and

accepted in recent years for the treatment of many types of wastewaters, whereas the

conventional ASP process cannot cope with either composition of wastewater or

fluctuations of wastewater flow rate. MBR technology is also used in cases where

demand on the quality of effluent exceeds the capability of conventional ASP. Although

MBR capital and operational costs exceed the costs of conventional process, it seems

that the upgrade of conventional process occurs even in cases when conventional

treatment works well.

Microorganisms are retained by membranes in a very high degree. Studies have shown

that the limit values and guide values for all microorganisms (total number of bacteria

coliforms, faecal coliforms and streptococci) in accordance with the EC Directive on the

quality of bathing water (76/160/EEC 1976) are independent of the weather conditions

(dry weather, storm, continuous rain) and were met in all cases.

Even viruses, the smallest pathogenic organisms which theoretically may pass through

the membrane pores, are retained by the membrane bioreactor process. The viruses

typically accumulate with particles and microorganisms so that they are removed from

the wastewater by the elimination of larger particles. During the studies mentioned

above (source: pg. 19, Merkblatt DWA-M 227 manual)., it was possible to significantly

reduce the concentrations of intestinal viruses.

Filtration units available in municipal wastewater treatment with membranes with a

nominal pore size below 0.5 µm do not differ with respect to the efficiency of particle

removal from each other.

For a long-term high performance it should be guaranteed that no short-circuits between

treated and non-treated wastewater exist and that membranes and connections are

always secure and a contamination of the permeate side is minimized.

1.4 Porec project background

1.4.1 Framework of the project

During the accession period towards the European Union (2013), the Republic of

Croatia had been obliged to transpose the Urban Waste Water Treatment Directive

(91/271/EEC) into the Croatian legal system. The adoption of the aforementioned

Directive demanded the implementation of extensive and financially “heavy”

investments for construction of integrated wastewater collection and treatment systems.

However, co-financing of such investments was made possible via means of the

Cohesion Fund and European Fund for Regional Development. The extensiveness of

investments, rules for EU co-financing and professional rules have sought a detailed and

careful preparation of the project documentation and attentive evaluation of submitted

tenders during the public procurement procedure of such projects.

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One such project, which was awarded to a consortium of companies STRABAG -

SUEZ, during August 2015, is the design and construction of four wastewater treatment

plants with Odvodnja LLC as the local public water authority for the town of Porec.

Figure 8: Project location

Located in Istria, a region on the Adriatic coast that is popular with tourists, the town of

Porec increases its population from 24.000 out of season to 115.000 residents during the

holiday season. The coastal waters in the area have been declared as a sensitive area.

With the backing of the European Union, the local authorities have launched a vast

programme to optimise the town's wastewater treatment infrastructures. The project

covers the design and construction of four wastewater treatment plants, equipped with

membrane bioreactors and with a total capacity of 137.500 population equivalent (PE),

as foreseen with the estimated horizon by the end of year 2045. The treated water will

be reused for agricultural irrigation and the sludge from the treatment of the wastewater

will be recovered by solar drying or by composting.

1.4.2 Description of the project

The sewage systems in the coastal areas are reasonably well developed. The sewage

currently only receives rudimentary treatment (mainly screening and, in some cases, grit

collection) and is disposed through submarine outfalls at various points along the coast

line. The sewage systems in settlements to the inland are not developed and wastewater

is disposed in septic tanks and cesspits.

According to the Urban Wastewater Treatment Directive the Porec area has a high

priority for compliance. Each of the existing four agglomerations generates more than

10.000 PE and discharges into a sensitive marine recipient and hence requires

appropriate treatment.

Tourist activity and growth rates

The annual tourist activity, measured in overnights and residing on campsites, in hotels

and apartment complexes is estimated to grow from the current 6,6 million annual

22

overnights to 7,5 million during a 30 year period. The peak is in July and August with

approximately 2 million overnights in each of these months and represents a tourist

inflow of between 70.000 and 75.000 people plus another 6.000 - 7.000 people in

weekend houses and in private rooms.

Demand analysis and seasonality

The water consumption and related waste water generation have an explicit seasonal

pattern. The minimum water consumption and waste water generation takes place in the

four winter months (November, December, January, February). The maximum water

consumption and hence wastewater generation takes place in the period from mid –

June to mid - September. Wastewater is generated by resident population, weekend

house users, tourists (camps, self-catering and hotels) and the ancillary tourist

infrastructure.

The total generated load in the summer months is estimated to be approx. 119.000 PE

for the predicted start of operation (2017) and will increase to approx. 137.500 PE at the

end of design horizon.

Climate and weather

The project area is in the border zone between sub-Mediterranean and mild continental

climate, but under strong maritime influence. The climate is mildly Mediterranean, with

dry and warm summers, frequent and intensive autumn and spring rains-showers, and

comparatively mild winters, mainly without snow.

According to Köppen classification, the climate of the City of Porec is moderately warm

and rainy sub-humid. The mean temperature in the coldest month of the year is higher

than 5°C, and lower than 22°C. There is no distinctive dry period and minimum rainfall

in summer, with mean temperature in the warmest month of the year higher than 25°C,

and with at least four consecutive months with mean temperature above 10°C, rainy

period in autumn, and in addition to the main rainfall minimum in winter, with a minor

dry period in summer.

The average annual rainfall ranges between 780 and 1.100 mm. The precipitation occurs

mainly in the form of rain, very rarely as hail or snow. The maximum average monthly

rainfall occurs in September, October and November and is over 100 mm per month.

The driest period is winter, in particular February and March with monthly average

rainfall not exceeding 40 mm per month.

Influent data

The flows and pollution loads on the WWTP Porec South have been estimated for the

years 2011 and 2045 taking into consideration the existing resident population, non-

household consumption and the tourist overnights. A slight growth is expected in

flows/loads up to the estimated horizon.

The estimated flows and the loads for the year 2045 are summarized in the following

table:

23

Table 2: Estimated pollution parameters for the project

For the estimation of the influent flows and pollution loads the following data were

used:

Influent and pollution loads

Months Population Tourist

Overnights

Average water consumption

2009-2011 (m3/month)

2011

Average

2009-2011 Households Non-Households

1 4.590 7.700 14.400 15.600

2 4.590 6.900 13.700 15.000

3 4.590 16.500 12.700 17.400

4 4.590 76.500 15.800 42.900

5 4.590 191.900 21.300 98.100

6 4.590 393.900 25.500 140.600

7 4.590 676.200 33.500 208.700

8 4.590 732.200 37.200 215.600

9 4.590 373.700 35.600 150.200

10 4.590 51.400 16.300 49.100

11 4.590 4.800 13.700 15.800

12 4.590 11.400 11.500 10.200

Estimated growth of tourist overnights from 2011 to 2045 15%

Permanent population for year 2045 5.578

Table 3: Estimated pollution and influent loads for the project

WWTP Porec South Estimated values

Flows/Loads M.U. Winter Summer

Pollution load PE = 60 g BOD 8.600 48.000

BOD load kg/d 516 2,880

Average daily flow m3/day 958 7,800

Peak factor = 16/24

Maximum dry weather flow m3/hour

60 490

Inflow/infiltration m3/day 487 487

Peak factor = 4/24

Maximum inflow/infiltration m3/hour

122 122

Peak daily flow m3/day 1.450 8.200

Peak hourly flow m3/hour 180 610

24

1.5 Scope of the Work

In the previous chapters, we have been briefly introduced to the importance of water

conservation and wastewater treatment considering the phenomena of climate change

and increase of urban populations globally. Also, we have been introduced to the basics

of biological wastewater treatment and all the information, which represents a

foundation for the development of this study.

In the scope of the project, pollution loads are calculated for each month according to

Table 3 and ATV specific pollution load per inhabitant (pg. 19, table 1, ATV-DVWK-A

131E manual). However, for the design of the plant, it was considered the month of

August, given that it is a month with the highest pollution loads (worst case scenario to

assure the proper design of the plant). Additionally, the month of January is a period of

highest load with respect to other winter months. With this in mind and given that for

the assumed winter temperature (12°C) the biomass growth rate is much slower, this

month was selected for the simulation of the winter period.

It is also important to note that in the design of the WWTP Porec South, it was taken

into consideration the fact that due to changes in holiday periods and weather

conditions, the number of tourists can vary significantly and hence the flows and loads

in the transition months between low season (winter) and high season (summer) can

substantially deviate from the above mentioned estimated values.

With this in mind, this study is essentially split into the following parts: Chapter 2

which discusses the theory behind the activated sludge process modelling and

simulation, while the Chapter 3 deals with actual implementation of the BioWin

modelling tool for the expected summer and winter loads of the WWTP Porec South,

along with an additional simulation for an “extreme peak inflow” event as a further step

of assuring the behaviour of the plant during unusual weather circumstances and inflow

patterns.

The goal is not only to have a plant designed according to the specifications set out by

the project and the applied regulations with the respect to the set limits (ATV

standards), but also to go “above the needs” and to perform additional simulation(s) that

could give further performance indicators of the plant.

25

CHAPTER 2 - MODELLING OF ACTIVATED

SLUDGE PROCESSES

2.1 Overview

The purpose of Chapter 2 is to demonstrate how the model selection, the data

collection and the WWTP model calibration all relate to the modelling purpose. Note

that there is an essential difference between an activated sludge model and a WWTP

model. A WWTP usually consists of a set of activated sludge tanks, combined with a

sedimentation tank, with a range of electron acceptor conditions occurring in the tanks.

Depending on the concentrations of dissolved oxygen (DO) and nitrate present in the

tanks, aerobic (oxygen present), anoxic (nitrate present, no oxygen) or anaerobic (no

oxygen, no nitrate) tanks can be distinguished. The term WWTP model is used to

indicate the ensemble of activated sludge model, hydraulic model, oxygen transfer

model and sedimentation tank model needed to describe an actual WWTP. The term

activated sludge model is used to indicate a set of differential equations that represent

the biological (and chemical) reactions taking place in one activated sludge tank.

Activated sludge model will thus refer exclusively to white-box models, i.e. models

based on first engineering principles. The hydraulic model describes tank volumes,

hydraulic tank behaviour (e.g. perfectly mixed versus plug flow behaviour, constant

versus variable volume, etc.) and the liquid flow rates in between tanks, such as return

sludge flow rate and internal recycle flow rate. The sedimentation tank models are

available in varying degrees of complexity. Dedicated WWTP simulators allow

construction of WWTP models based on libraries of activated sludge models,

sedimentation tank models, etc. (Gernaey V.K. et al., 2004).

A number of factors are to be considered with regard to activated sludge modelling and

model applications, and a step-wise approach is needed to evolve from the model

purpose definition to the point where a WWTP model is available for simulations. The

following main steps can be distinguished in this process:

Definition of the WWTP model purpose or the objectives of the model application

(control, design, simulation);

26

Model selection: choice of the models needed to

describe the different WWTP units to be considered in

the simulation, i.e. selection of the activated sludge

model, the sedimentation model, etc.;

Hydraulics, i.e. determination of the hydraulic

models for the WWTP or WWTP tanks;

Wastewater and biomass characterisation,

including biomass sedimentation characteristics;

Data reconciliation to a steady-state model;

Calibration of the activated sludge model

parameters;

Model unfalsification. In this task it is

determined whether or not the model is sufficiently

accurate for its intended purpose. If this is the case, the

model is said to be unfalsified with respect to the

available data. If this is not the case, a number of the

preceding steps needs to be repeated until the model is

unfalsified;

Scenario evaluations.

The following paragraph will provide a number of key

references as guidance through some of the

abovementioned steps. The activated sludge models that

are most frequently used today will be summarized.

Available WWTP simulators will be described just

briefly.

2.2 Activated sludge models

The most frequently used activated sludge models will

be considered in an attempt to support the modeller in

the model selection phase.

2.2.1 Activated sludge model development

The focus will be on the recent developments of

activated sludge models, mainly the family of activated

sludge models developed by the International Water

Association (IWA) and the metabolic model developed

at the Delft University of Technology (TUDP model).

Table 4 summarises essential features of these and

several other activated sludge models.

The Activated Sludge Model No. 1 (ASM1; Henze et al.,

1987) can be considered as the reference model, since

this model triggered the general acceptance of WWTP

Ta

ble

4:

Ov

erv

iew

of

act

iva

ted

slu

dg

e m

od

els

27

modelling, first in the research community and later on also in industry. This evolution

was undoubtedly supported by the availability of more powerful computers. Many of

the basic concepts of ASM1 were adapted from the activated sludge model defined by

Dold et al. (1980).

Even today, the ASM1 model is in many cases still the state of the art for modelling

activated sludge systems. ASM1 has become a reference for many scientific and

practical projects (Roeleveld and van Loosdrecht, 2002), and has been implemented (in

some cases with modifications) in most of the commercial software available for

modelling and simulation of WWTPs for N removal (Copp, 2002).

ASM1 was primarily developed for municipal activated sludge WWTPs to describe the

removal of organic carbon compounds and N, with simultaneous consumption of

oxygen and nitrate as electron acceptors. The model furthermore aims at yielding a good

description of the sludge production. Chemical oxygen demand (COD) was adopted as

the measure of the concentration of organic matter. In the model, the wide variety of

organic carbon compounds and nitrogenous compounds are subdivided into a limited

number of fractions based on biodegradability and solubility considerations.

Figure 9: Substrate flows for autotrophic and heterotrophic biomass in ASM1 and ASM3 models

The ASM3 model (Gujer et al. 1999) was also developed for biological N removal

WWTPs, with basically the same goals as ASM1. The ASM3 model is intended to

become the new standard model, correcting for a number of defects that have appeared

during the usage of the ASM1 model (Gujer et al. 1999). The major difference between

28

the ASM1 and ASM3 models is that the latter recognises the importance of storage

polymers in the heterotrophic activated sludge conversions. In the ASM3 model, it is

assumed that all readily biodegradable substrate (SS) is first taken up and stored into an

internal cell component (XSTO) prior to growth (see Figure 9). The heterotrophic

biomass is thus modelled with an internal cell structure, similar to the phosphorus

accumulating organisms (PAOs) in the biological phosphorus removal (Bio-P) models.

The internal component XSTO is subsequently used for biomass growth in the ASM3

model. Biomass growth directly on external substrate as described in ASM1 is not

considered in ASM3. A second difference between ASM1 and ASM3 is that the ASM3

model should be easier to calibrate than the ASM1 model. This is mainly achieved by

converting the circular growth–decay–growth model, often called death–regeneration

concept, into a growth-endogenous respiration model (Figure 9). Whereas in ASM1

effectively all state variables are directly influenced by a change in a parameter value, in

ASM3 the direct influence is considerably lower thus ensuring a better parameter

identifiability. Koch et al. (2000)concluded that ASM1 and ASM3 are both capable of

describing the dynamic behaviour in common municipal WWTPs, whereas ASM3

performs better in situations where the storage of readily biodegradable substrate is

significant (industrial wastewater) or for WWTPs with substantial non-aerated zones.

The ASM3 model can be extended with a Bio-P removal module (Ky et al., 2001;

Rieger et al., 2001).

Figure 10: Substrate flows for storage and growth of PAOs in the ASM2 model

The overview of models including Bio-P will start with the ASM2 model (Henze et al.

1995), which extends the capabilities of ASM1 to the description of Bio-P. Chemical P

removal via precipitation was also included. The ASM2 publication mentions explicitly

that this model allows the description of bio-P processes, but does not yet include all

observed phenomena. For example, the ASM2d model (Henze et al., 1999) builds on

the ASM2 model, adding the denitrifying activity of PAOs which should allow a better

description of the dynamics of phosphate and nitrate. Bio-P modelling in ASM2 is

illustrated in Figure 10: the PAOs are modelled with cell internal structure, where all

29

organic storage products are lumped into one model component (XPHA). PAOs can only

grow on cell internal organic storage material; storage is not depending on the electron

acceptor conditions, but is only possible when fermentation products such as acetate are

available. In practice, it means that storage will usually only be observed in the

anaerobic activated sludge tanks.

The TUDP model (van Veldhuizen et al. 1999; Brdjanovic et al., 2000) combines the

metabolic model for denitrifying and non-denitrifying Bio-P of Murnleitner et al. (1997)

with the ASM1 model (autotrophic and heterotrophic reactions). Contrary to

ASM2/ASM2d, the TUDP model fully considers the metabolism of PAOs, modelling

all organic storage components explicitly (XPHA and XGLY), as shown in Figure 11. The

TUDP model was validated in enriched Bio-P sequencing batch reactor (SBR)

laboratory systems over a range of sludge retention time (SRT) values (Smolders et al.,

1995) for different anaerobic and aerobic phase lengths and for oxygen and nitrate as

electron acceptor (Murnleitner et al., 1997).

Figure 11: Substrate flows for storage and aerobic growth of PAOs in the TUDP model

In some cases, such as high pH (>7.5) and high Ca2+ concentrations, it can be necessary

to add biologically induced P precipitation to the Bio-P model (Maurer et al., 1999;

Maurer and Boller, 1999). Indeed, under certain conditions the Bio-P reactions coincide

with a natural precipitation that can account for an important P removal effect that is not

related to the Bio-P reactions included in the models described thus far. The formation

of these precipitates, mostly consisting of calcium phosphates, is promoted by the high

P concentration and increased ionic strength during the anaerobic P release of the PAOs.

2.2.2 Activated sludge models assumptions and limitations

Influence of environmental effects

Temperature: Kinetic model parameters are temperature dependent, and consequently

one has either to estimate the model parameters when calibrating the model for a

specific temperature, or to develop appropriate temperature correction factors to include

30

the temperature dependency of the reaction kinetics in the simulations. Henze et al.

(1987) provide two sets of typical parameters for 10 and 20 °C, respectively. Later

models, such as ASM2 and the TUDP model, use an Arrhenius type temperature

dependence. Different reactions have different temperature dependencies, where

nitrification is generally most sensitive. Hellinga et al. (1999) provide a detailed

explanation of the influence of temperature on nitrification kinetics. Finally, Henze et

al. (1995) warn that the ASM2 temperature coefficients are only valid between 10 and

25 °C.

pH: In ASM1, it is assumed that the pH is constant and near neutrality. Including

alkalinity as one of the state variables in the model allows detection of possible pH

problems. For some reactions, specific functions can be added to the model to describe

inhibitory pH effects, as illustrated by Helinga et al. (1999) for the nitrification reaction.

Toxic components: Nitrification is especially sensitive to inhibition by toxic

components. In ASM1, the nitrification parameters are assumed to be constant. This

means that any inhibitory effect of the wastewater on the nitrification kinetics is

assumed to be included in the calibrated nitrification parameters. It is thus only possible

to represent an “average inhibitory effect” of the wastewater. Alternatively, the

nitrification rate equation can be extended to represent sudden acute inhibition by

specific chemicals (Nowak et al., 1995). It is then up to the modeller to select the best

inhibition kinetics model for the actual inhibition problem.

Wastewater composition: The models in Table 4 were developed for simulation of

municipal WWTPs. Model modifications are typically needed for WWTP systems

where industrial contributions dominate the wastewater characteristics. Acute

nitrification inhibition by toxic components related to industrial activity is one of the

model modifications that are often necessary. Ky et al. (2001) combined the ASM3

model with the bio-P reactions of the TUDP model. In their modelling study, the

simulation of a SBR treating the wastewater of a cheese industry, Mg2+ Monod

switching functions were added to specific Bio-P model reactions to account for Mg2+

limited kinetics. Coen et al. (1998) proposed a modified ASM1 model extended to three

different soluble biodegradable organic substrates to describe a WWTP in the

pharmaceutical industry.

Biodegradation kinetics

Cell growth limitations due to low nutrient concentrations (e.g. N and P) are not

considered in ASM1. Later models have included these limitations, e.g. the ASM3

model includes N and alkalinity limitations (Gujer et al., 1999). The Bio-P models

usually include P limitations too.

Biomass decay in ASM1 is modelled according to the death–regeneration concept

(Dold et al., 1980). In the ASM3 model this was replaced by the endogenous

respiration or maintenance concept (see Table 4). As a result, the conversion

reactions of both autotrophs and heterotrophs are clearly separated in ASM3,

whereas the decay product regeneration cycles of the autotrophs and heterotrophs

are strongly interrelated in ASM1 (see Figure 9). Moreover, the use of the

endogenous respiration concept in the ASM3 model should allow easier

comparisons between the results of kinetic parameters derived from respirometric

31

batch experiments with activated sludge of the plant to be modelled (Vanrolleghem

et al. 1999) and the activated sludge model used to describe the phenomena in the

full-scale plant. Note that the TUDP model uses the death regeneration concept for

the autotrophic and heterotrophic (non-PAO) reactions, whereas the maintenance

concept is used for the PAOs. Effectively you want to describe maintenance,

viruses, decay, protozoa, rotifers, nematodes, etc., in the model, since all these

processes lead to a decreased sludge production or oxygen consumption in the

absence of external substrate in the full-scale WWTP (van Loosdrecht and Henze,

1999). It has been shown that all these processes can conveniently be lumped in

one activated sludge model reaction.

The hydrolysis of organic matter and organic nitrogen are coupled and occur

simultaneously with equal rates. In the Bio-P models this was extended to include

also organic phosphate.

ASM1 cannot deal with elevated nitrite concentrations, i.e. nitrification is modelled

as a one-step process thereby ignoring the possible appearance of nitrite, a

nitrification intermediate, in full-scale WWTPs. Typically, the assumption of one-

step nitrification is acceptable. However, when modelling a WWTP where

considerable nitrite concentrations occur, or where the temperature is above 20°C,

a two-step nitrification model with nitrite as intermediate might be useful.

Nitrogen gas, a denitrification product, is not included in the ASM1 model. As a

consequence, the model does not allow checking the N balances. Most of the later

models included nitrogen gas as a model component (Henze et al., 1995, 1999;

Gujer et al., 1999; Brdjanovic et al., 2000). Clearly, the modeller can easily add

nitrogen gas to the model as an extra component. The P-balances in the Bio-P

models are always closed.

In ASM1, the type of electron acceptor present does not affect the biomass decay

rate. In contrast, ASM3 allows differentiation between aerobic and anoxic

heterotrophic biomass, storage product (XSTO) and autotrophic biomass decay rates.

According to the experimental result reported in Siegrist et al. (1999), this

differentiation between aerobic, anoxic, and, if necessary, anaerobic autotrophic

biomass decay rates seems to be justified.

In ASM1, the type of electron acceptor does not affect the heterotrophic biomass

yield coefficient, whereas the ASM3 model (Gujer et al., 1999) and the model of

Barker and Dold (1997) allow inclusion of different aerobic and anoxic

heterotrophic biomass yield coefficients in the model. It has been theoretically

proven, based on metabolic process energetics, that anoxic yields are consistently

lower than aerobic ones (Orhon et al., 1996). Indeed similar differences between

aerobic and anoxic yield were obtained experimentally with activated sludge

(McClintock et al., 1988; Sperandio et al., 1999). A metabolic model takes this

explicitly into account because a different energetic efficiency for the different

electron acceptors is included.

In the ASM1 model, hydrolysis reaction rates depend on the electron acceptor

present (aerobic or anoxic conditions). In the ASM3 model, hydrolysis is

independent of the available electron acceptor (Gujer et al., 1999). ASM2

32

acknowledges that hydrolysis reaction rates may depend on the available electron

acceptor, also under anaerobic conditions (Henze et al., 1995).

The Bio-P models cannot handle two extreme situations (van Veldhuizen et al.,

1999): (1) full depletion of the organic storage product pool XPHA in the PAOs; (2)

simultaneous presence of volatile fatty acids (= substrate for storage reactions) and

electron acceptors. Model extensions are needed to handle these two situations.

Storage of substrate by non-PAOs is not accounted for in ASM2/ASM2d and

TUDP.

The models are not able to describe filamentous biomass growth and sludge

bulking.

2.3 Simulation environments

A WWTP simulation environment can be described as software that allows the modeller

to simulate a WWTP configuration. General-purpose simulation environments can be

distinguished from specific WWTP simulators. General-purpose simulation

environments normally have a high flexibility, but the modeller has to supply the

models that are to be used to model a specific WWTP configuration. The latter task can

be very time consuming. However, it is better to spend time on the model

implementation and debugging, to avoid running lots of simulations with a model that

afterwards turns out to be erroneous for the specific application task. As a consequence,

general-purpose simulation environments require a skilled user that fully understands

the implications of each line of code in the models. A popular example of a general-

purpose simulator environment is MATLAB/Simulink (http://www.mathworks.com).

Specific WWTP simulation environments usually contain an extended library of

predefined process unit models, for example a perfectly mixed ASM1 or ASM2d

bioreactor, and a one-dimensional 10-layer settler model. The process configuration to

be simulated can easily be constructed by connecting process unit blocks. Pop-up

windows allow modifying the model parameters. Examples of specific commercial

WWTP simulator environments are (in alphabetic order): AQUASIM

(http://www.aquasim.eawag.ch), BioWin (http://www.envirosim.com), EFOR

(http://www.dhisoftware.com/efor), GPS-X (http://www.hydromantis.com), SIMBA

(http://www.ifak-system.com), STOAT (http://www.wrcplc.co.uk/software), and WEST

(http://www.hemmis.com).

2.4 Model applications

A model may be applied in the following roles (Russel et al., 2002): (1) a service role,

where the model, when solved, provides the needed numerical values for further

analysis; (2) an advice role, where the model provides insights that help to understand

and solve related sub-problems contributing to the solution of an overall problem; (3) an

analysis role, where simulations with the model indicate how to use models to solve a

specific task. The purpose for WWTP model studies can be (Hulsbeek et al., 2002;

33

Petersen et al., 2002): (1) learning, i.e. use of simulations to increase process

understanding, and to develop people’s conception of the system; (2) design, i.e.

evaluate several design alternatives for new WWTP installations via simulation; (3)

process optimisation and control, i.e. evaluate several scenarios that might lead to

improved operation of existing WWTPs. The latter two are applications of the model in

a service role. An application of the model in an analysis role can for example be a

study where the suitability to describe a particular process is evaluated for several

modelling concepts enclosed in different activated sludge models.

2.4.1 WWTP model simulation for learning

Simulations with WWTP models can be applied in different ways to increase the

process understanding of the user. For the WWTP operator, simulations might for

example be useful to indicate the consequences of process operation modifications on

the activated sludge composition and the WWTP effluent quality. Similarly, simulations

with e.g. the ASM1 benchmark plant (Coop, 2002) for different weather disturbance

scenarios are very informative to get an idea of the behaviour of a WWTP under

variable weather conditions.

From a research perspective, Brdjanovic et al. (2000) used the TUDP model to increase

the understanding of a full-scale Bio-P process. Siegrist et al. (1999) noticed in the

experimental work that the decay rate of autotrophic bacteria is lower under anaerobic

and anoxic conditions, compared to aerobic conditions. Simulations with a WWTP

model incorporating this hypothesis showed that avoiding excess aeration in the

activated sludge tanks, for example via intermittent aeration, not only saves aeration

energy but also improves the nitrification capacity of the plant.

2.4.2 WWTP model simulation for design

During the design phase, process alternatives can be evaluated via simulation. Such a

model study was presented e.g. by Salem et al. (2002), where different alternatives for

the upgrade of a biological N removal plant were evaluated with focus on appropriate

treatment of sludge reject water. The WWTP model simulations provided the

knowledge basis that was needed to decide on full-scale implementation of one of the

proposed alternatives. In this context, modelling can substantially reduce the scale-up

time, because different options can be evaluated before a pilot plant is built. The model

thus contributes significantly in bridging the gap between lab and full-scale application

(Hellinga et al, 1999). A WWTP model thus transforms data obtained from lab scale

experiments into quantitative knowledge, which helps in decision-making processes.

Yuan et al. (1998) evaluated a sludge storage concept via ASM1 simulations, based on

the reduced decay of autotrophic bacteria under anaerobic conditions. The concept

provides spare nitrification capacity for nitrogen shock load situations by storing the

waste activated sludge temporarily in an anaerobic tank with a retention time of a few

days, whereas the SRT in the activated sludge plant is reduced considerably. The

concept thus results in a WWTP with less sludge but a similar nitrification capacity

compared to traditional reactor design, and was successfully evaluated in pilot plant

34

studies (Yuan et al., 2000). Savings on reactor volume were evaluated to be around

20%, but increased sludge production could be a problem with respect to operational

costs.

2.4.3 WWTP model simulation for process optimization

Process optimization can be used in different contexts. Off-line process optimisation

refers to applications where off-line simulations with the calibrated model are used to

determine how to optimally run the process, whereas the result is later implemented and

tested on the full-scale plant. In on-line process optimization, simulations with the

calibrated model are applied in an on-line optimization scheme.

Off-line process optimization is often needed because new stricter demands are imposed

to existing WWTPs, or considerable changes in the plant load have occurred, or

deficiencies have appeared during WWTP operation such that the initially required

effluent quality cannot any longer be obtained. In this context, simulations are often

used to evaluate whether the pollutant removal efficiencies can be improved within the

existing plant lay-out, e.g. via improved process control. The ASM1- based benchmark

WWTP (Copp, 2002) was specifically developed for simulation-based objective

evaluation of different control strategies on a N removal WWTP, and includes several

criteria to evaluate the WWTP performance.

Scenario evaluations with ASM1/ASM3 usually aim at upgrading a WWTP for

biological N removal (Coen et al., 1996), evaluating the possibilities for improved

biological N removal within an existing WWTP configuration (Ladiges et al., 1999), or

predicting the effect of a change in load on the WWTP performance. During scenario

evaluations with Bio-P models, evaluation of different process alternatives often results

in a trade-off between Bio-P capacity and nitrification, where increased DO

concentrations will promote nitrification but negatively influence the Bio-P process due

to increased aerobic decay of PAO storage products (Cinar et al., 1998). Gernaey et al.

(2002) illustrate the implementation of chemical P precipitation on an existing N

removal WWTP.

35

CHAPTER 3 - APPLICATION OF THE BIOWIN

MODELLING TOOL

3.1 About BioWin 5.0

Biowin is a computer simulation package that is able to dynamically simulate the

wastewater treatment process. It combines various published models, such as the

activated sludge models, anaerobic digestion model, and solids settling model, into a

single simulation platform (EnviroSim Associates Ltd). It is a flexible platform that

allows investigations into changes in configurations or operations without having to

alter conditions in the actual treatment plant.

The user can define and analyse behaviour of complex treatment plant configurations

with single or multiple wastewater inputs. An example of a plant configuration window

is shown (where in the background is the graphical representation of WWTP Porec

South):

Figure 12: Example of a plant configuration in BioWin (WWTP Porec South)

Most types of wastewater treatment systems can be configured in BioWin using the

many process modules. These include:

A range of activated sludge bioreactor modules – suspended growth reactors

(diffused air or surface aeration), various SBRs, media reactors for IFAS and

MBBR systems, variable volume reactors;

Anaerobic and aerobic digesters;

Various settling tank modules – primary, ideal and 1-D model settlers;

36

Different input elements – wastewater influent (COD- or BOD-based), user-

defined (state variable concentrations), metal addition for chemical phosphorus

precipitation (ferric or alum), methanol for denitrification;

Other process modules – holding tanks, equalization tanks, dewatering units,

flow splitters and combiners.

A crucial component of BioWin is the biological process model. The BioWin model is

unique in that it merges both activated sludge and anaerobic biological processes.

Additionally, the model integrates pH and chemical phosphorus precipitation processes.

The BioWin simulator suite presently includes two modules:

A steady state module for analysing systems based on constant influent loading

and/or flow weighted averages of time-varying inputs. This unit is also very

useful for mass balancing over complex plant configurations.

An interactive dynamic simulator where the user can operate and manipulate the

treatment system "on the fly". This module is ideal for training and for analysing

system response when subjected to time-varying inputs or changes in operating

strategy.

BioWin is a very powerful analysis tool. The program has been evaluated against an

extensive data set and has been demonstrated to provide accurate simulation results for

a range of systems. Nevertheless, it is still merely a tool.

BioWin incorporates a number of models. These necessarily are a simplification of

reality and have limited ranges of applicability. It is the responsibility of the user to

carefully assess results generated by the program.

3.2 Implemented Biological/Chemical models

BioWin uses a general Activated Sludge/Anaerobic Digestion (ASDM) model which is

referred to as the BioWin ASDM. The BioWin ASDM has more than fifty state

variables and over eighty process expressions. These expressions are used to describe

the biological processes typically occurring in wastewater treatment plants. This

complete model approach frees the user from having to map one model’s output to

another model’s input which significantly reduces the complexity of building full plant

models, particularly those incorporating many different process units.

In the following chapter 3.2.1 an overview of the parameters included in the model

(kinetic, stoichiometric and chemical constants) with a brief description of the model

process.

In the performed simulations, only the default BioWin ASDM was used.

37

3.2.1 Activated sludge processes

The process employed in the simulation were:

a. Growth and Decay of Ordinary Heterotrophic Organisms;

b. Hydrolysis, Adsorption, Ammonification and Assimilative denitrification;

c. Growth and Decay of Ammonia Oxidizing Biomass;

d. Growth and Decay of Nitrite Oxidizing Biomass;

e. Growth and Decay of Phosphorus Accumulating Organisms.

A brief description of each is provided in the following text.

(a) Growth and Decay of Ordinary Heterotrophic Organisms (OHO)

Number of sub-processes: 24

Engineering objective: BOD removal, denitrification

Implementation: Always active in the BioWin model

Module description:

This group of processes describes the growth and decay of ordinary heterotrophic

organisms under all conditions. The activated sludge model allows for direct ordinary

heterotrophic aerobic growth on acetate, propionate, readily biodegradable complex

substrate and methanol.

The base rate expression for each of the growth processes is the product of a maximum

specific growth rate, the heterotrophic biomass concentration and a Monod expression

for the substrates. This base rate is modified to account for environmental conditions

(dissolved oxygen, nitrate and nitrite), nutrient limitations (ammonia, phosphate, other

cations and anions) and pH inhibition. BioWin uses ammonia as a nitrogen source for

cell synthesis with all of the substrates under aerobic, anoxic and anaerobic conditions.

At low ammonia concentrations BioWin allows for assimilative ammonia production

from either nitrate or nitrite in order to satisfy synthesis demands.

Although the maximum specific growth rate under aerobic and anoxic conditions is the

same, under anoxic conditions the base rate is also multiplied by an anoxic growth

factor. This allows for anoxic growth at a different rate or for only a fraction of the

OHOs being able to perform any kind of denitrification (or both of these). Of the OHOs

that can perform denitrification, a fraction can use either nitrate or nitrite (with nitrogen

gas as an end product), and the remainder of the denitrifying OHOs can only use nitrate

(with nitrite as an end product).

There are two pathways for ordinary heterotrophic growth through fermentation of

readily biodegradable (complex) substrate to acetate, propionate, carbon dioxide and

hydrogen. The dominant pathway is governed by the dissolved hydrogen concentration.

In activated sludge vessels there is also an anaerobic growth factor applied to all growth

through fermentation.

38

There are decay processes appropriate for each environment (aerobic, anoxic and

anaerobic).

(b) Hydrolysis, Adsorption, Ammonification and Assimilative denitrification


Engineering objective: Conversion of organic, nitrogen and phosphorous fractions


Module description:

These processes are discussed here separately for each different organism groupings

because they involve more than one organism type (in general both the ordinary

heterotrophic organisms and the phosphate accumulating organisms).

Hydrolysis of biodegradable particulate organic substrate to readily biodegradable

complex substrate: The base rate is the product of the hydrolysis rate constant, the sum

of the ordinary heterotrophs and the phosphate accumulating organisms, and a Monod

expression for the ratio of particulate substrate to organism COD. There is an efficiency

factor applied for anoxic conditions and another for anaerobic conditions.

Hydrolysis of biodegradable particulate organic nitrogen and phosphorus: The

hydrolysis of biodegradable particulate nitrogen (phosphorus) is assumed to proceed at

the same rate as the biodegradable particulate organics but is adjusted by the ratio of

biodegradable particulate organic nitrogen (phosphorus) to biodegradable particulate

organic.

Adsorption or flocculation of colloidal organic material to particulate organic

material (occurring spontaneously as opposed to chemically facilitated flocculation

with metal (ferric or alum) addition: The rate is the product of the adsorption rate

constant, the colloidal substrate concentration and the sum of the ordinary heterotrophs

and the phosphate accumulating organism concentrations. The rate is decreased as the

ratio of particulate substrate to organism COD approaches the maximum adsorption

ratio constant.

Ammonification of soluble organic nitrogen to ammonia: The rate is the product of

the ammonification rate constant, the soluble organic nitrogen concentration and the

sum of the ordinary heterotrophic and the phosphate accumulating organisms

concentrations.

Assimilative denitrification of nitrate or nitrite to ammonia for synthesis: BioWin

allows for the production of ammonia for synthesis by OHOs, PAOs and methylotrophs

under low ammonia conditions (as ammonia becomes limiting for growth). The

assimilative process will use nitrite if it is available otherwise it will use nitrate. The

base rate is the product of the assimilation rate constant and the organism COD. This

base rate is modified to account for environmental conditions (off with ammonia, and

selecting between nitrate and nitrite).

Slow decay of endogenous products to particulate substrate: BioWin allows for the

conversion of endogenous decay products to particulate substrate. The rate is the

product of the specified rate constant and the endogenous products concentration.

39

(c) Growth and Decay of Ammonia Oxidizing Biomass (AOB)


Engineering objective: Nitrification


Module description:

This biomass grows by oxidizing ammonia to nitrite and using the energy to synthesize

organic material from inorganic carbon (fixing CO2). Nitrogen source for cell synthesis

is ammonia.

The base rate expression for the growth process is the product of the maximum specific

growth rate, the ammonia oxidizing biomass concentration and a Monod expression for

ammonia. This base rate is modified to account for environmental conditions (off at low

dissolved oxygen), nutrient limitations (phosphate, inorganic carbon, other cations and

anions) and pH inhibition.

The decay rate varies between an aerobic value and an anoxic/anaerobic value

depending on the dissolved oxygen concentration.

(d) Growth and Decay of Nitrite Oxidizing Biomass (NOB)


Engineering objective: Conversion of organic, nitrogen and phosphorous fractions


Module description:

This biomass grows by oxidizing nitrite to nitrate and using the energy to synthesize

organic material from inorganic carbon (fixing CO2). Nitrogen source for cell synthesis

is ammonia.

The base rate expression for the growth process is the product of the maximum specific

growth rate, the nitrite oxidizing biomass concentration and a Monod expression for

nitrite. This base rate is modified to account for environmental conditions (off at low

dissolved oxygen and inhibited by ammonia), nutrient limitations (ammonia, phosphate,

inorganic carbon, other cations and anions) and pH inhibition.

The decay rate varies between an aerobic value and an anoxic/anaerobic value

depending on the dissolved oxygen concentration.

(e) Growth and Decay of Phosphorus Accumulating Organisms (PAOs)


Engineering objective: Biological phosphorous removal


Module description:

40

This group of processes describes the growth and decay of polyphosphate accumulating

organisms (PAOs) under all conditions. This includes descriptions of aerobic and anoxic

growth, volatile fatty acid (VFA) sequestration and polyphosphate lysis.

There are two maximum specific growth rates for PAOs under aerobic conditions. The

lower growth rate constant is used under P limited conditions and has a different

stoichiometry (no polyphosphate storage). There are also two anoxic growth processes,

one uses nitrate and the other nitrite. Growth processes under phosphate rich conditions

result in uptake of phosphate, as well as balancing calcium ions magnesium ions and

other cations. A lack of these ions will stop the growth processes by appropriate Monod

switches. For all of these growth processes, the base growth rate is the product of the

maximum specific rate constant, the PAO concentration and a Monod switch on the

ratio PHA to PAO. This base rate is modified to account for environmental conditions

(dissolved oxygen, nitrate and nitrite), nutrient limitations (ammonia, anions, cations,

for polyphosphate storage magnesium, and calcium are also required) and pH inhibition.

BioWin uses ammonia as a nitrogen source for cell synthesis under aerobic, anoxic and

anaerobic conditions. At low ammonia concentrations BioWin allows for assimilative

ammonia production from either nitrate or nitrite in order to satisfy synthesis demands.

Although the maximum specific growth rate under aerobic and anoxic conditions is the

same, under anoxic conditions the base rate is also multiplied by an anoxic growth

factor. This allows for anoxic growth at a different rate or for only a fraction of the

PAOs being able to perform any kind of denitrification (or both of these). Of the PAOs

that can perform denitrification, a fraction can use either nitrate or nitrite (with nitrogen

gas as an end product), and the remainder of the denitrifying PAOs can only use nitrate

(with nitrite as an end product).

The PAOs use polyphosphate as an energy source to sequester VFAs under anaerobic

conditions. The sequestered VFAs are stored internally as polyhydroxy alkanoates

(PHA). In the BioWin model the PAOs can use both acetate and propionate for this

process. The base sequestration rate is the product of the sequestration rate constant, the

PAO concentration and a Monod switch on the appropriate substrate (acetate or

propionate). The rate is also dependent on the availability of the stored polyphosphate

(poly-P).

There are two decay processes (aerobic/anoxic and anaerobic). Associated with each

decay process is a lysis process for PHA, low and high molecular weight

polyphosphate. The lysis rates are directly proportional to the decay rate itself.

There is a polyphosphate cleavage process for anaerobic maintenance that releases

phosphate if no oxygen is present (default off).

There is also an aerobic/anoxic maintenance process that releases organism COD as

well as synthesis nitrogen and phosphorus but no polyphosphate or PHA (default off).

41

3.2.2 Other important physical phenomena implemented

pH

It has been recognized from the early stages of wastewater process modelling that pH is

an important factor in simulating the performance of biological wastewater treatment

processes.

The pH impacts the species distribution of the weak acid systems (carbonate, ammonia,

phosphate, acetate, propionate, etc.) present in the process. This in turn dictates the rate

of many of the biological and physico-chemical phenomena occurring in these systems.

For example, biological activity, that can be severely limited outside an optimal pH

range. It is difficult to model pH because the underlying components and reactions are

so fast and complex.

BioWin uses a mixed kinetic/equilibrium based approach to minimize the negative

impact on simulations speed. This approach is applicable across a wide range of

biological treatment process models (i.e. activated sludge and anaerobic digestion, etc.).

Alkalinity

The model determines alkalinity by noting that at the H2CO3 equivalence point [H+] =

[HCO3- ]. This additional equation can then be used to solve the carbonate equilibrium

explicitly to determine the [HCO3- ] concentration at the equivalence point (and

consequently the pH).

Gas Transfer and Aeration Models

There are seven gas-liquid mass transfer processes implemented in BioWin to allow

interphase transfer of oxygen, carbon-dioxide, methane, nitrogen, ammonia, hydrogen

and nitrous oxide.

The main parameters related to mass transfer are the Liquid phase mass transfer and the

Henry’s law constants coefficient for the above mentioned compounds. Other important

parameters are the ones for aeration (for example, % in the off-gas of the compounds)

and for diffuser system.

Supply of oxygen constitutes a major operating cost for biological wastewater treatment

systems. Emphasis on energy conservation has highlighted the need to develop effective

methods for design and operation of aeration systems.

Oxygen demand in activated sludge reactors varies with time, necessitating a varying

oxygen supply rate to maintain the desired dissolved oxygen (DO) concentration.

In diffused air systems bubbles are distributed from diffusers at the base of the reactor.

Mass transfer occurs between the rising bubbles and the mixed liquor. The transfer of

oxygen from the gas to the liquid is required to supply the oxygen requirements for the

biological process. A number of equipment and operational parameters interact to

influence the efficiency and rate of transfer of oxygen; inter alia, diffuser pore size and

density, and air flow rate. These parameters determine factors such as bubble size, the

rate of bubble rise, the bubble residence time in the reactor, the fractional gas hold-up,

the interfacial surface area available for mass transfer, the change in oxygen partial

pressure in the rising bubbles and the degree of turbulence. Conditions in the mixed

liquor also impact on the transfer; for example, temperature, ionic strength, presence of

42

surface-active compounds, and solids concentration. Quantifying the impact of all these

factors on the overall mass transfer behaviour is very difficult.

3.3 Model simulation for WWTP Porec South

3.3.1 Project design parameters

Design flows and loads

As it was already mentioned, the modelling simulation has been applied to WWTP

Porec South for summer and winter conditions.

The plant will receive wastewater originating from different locations. Both municipal

and industrial wastewaters (suitable for biological treatment) will be delivered to the

plant by various pumping stations and networks.

The sewage collection network is a separate system except from a small part of the old

city of Porec. Certain number of connections of roofs drains and the drainage of storm

water from fixed surfaces are existing and this results in some stormwater inflow into

the drainage system.

The flows and pollution loads on WWTP Porec South have been estimated for the years

2011 and 2045 taking into consideration the existing resident population, non-household

consumption and the tourist overnights.

Hydraulic load

Design flow values of influent wastewater are summarized in Table 5. The values refer

to typical conditions considering both summer and winter seasons.

Parameter M.U.

WWTP Porec South

Winter Summer

Average daily flow m³/day 958 7.800

Maximum dry weather flow

Peak factor 16/24 m³/h 60 490

Infiltration m³/day 487 487

Infiltration

Peak factor 4/24 m³/h 122 122

Peak daily flow m³/day 1.450 8.200

Peak hourly flow m³/h 180 610

Table 5: Typical flow values of influent wastewater for WWTP Porec South

43

Pollution load

Design daily loads values are derived from ATV-DVWK-A 131E (pg. 19, ATV-

DVWK-A 131E manual), and are shown in Table 6. The considered values for the

influent wastewater are summarized in Table 7.

Parameter Raw wastewater

BOD5 60

COD 120

SS 70

TKN 11

P 1,8

Table 6: Inhabitant-specific loads in g/(I·d)

Parameter M.U.

WWTP Porec South

Winter Summer

Capacity PE 8600 48000

BOD5 1 kg/day 516 2880

COD kg/day 1032 5760

TSS kg/day 602 3360

VSS/TSS % 70 70

N-NTK kg/day 94,6 528,0

Pt kg/day 15 86

Table 7: Design daily loads of influent wastewater for WWTP Porec South

The results obtained in the following simulation are strictly dependent on the

characteristics of the influent, for example the fraction of volatile suspended solids over

the total suspended solids in the influent that affects the amount of volatile matter in the

wasted sludge.

Wastewater design temperature

Design wastewater temperature has been considered equal to 12°C for winter conditions

and 20°C for summer ones.

1 The Inlet BOD5 is an important parameter for ATV that will be used later in the calculations at pg. 56

44

Effluent quality requirement and guarantees

Given the sensitivity of the recipient, effluent limits are aligned with the requirements

for discharge from the treatment of urban wastewater into sensitive areas which are

subject to eutrophication, as defined in Annex IIA of the Directive of the European

Council 91/271/EEC concerning urban wastewater purification and the amendment

98/15/EEC for WWTP of a capacity of 10.000 – 100.000 PE.

The effluent requirements set out by the Republic of Croatia are defined by the

ordinance on the limitation of emissions of wastewater (Official Gazette 80/13). The

limit values taken into account for the discharge of water from the plant into the

Adriatic sea are shown in Table 8.

Parameter Limit value

Suspended Solids < 5 mg/l

BOD5 (20°C) < 10 mgO2/l

CODCr < 125 mgO2/l

Total Phosphorus < 2 mgP/l

Total Nitrogen * (organic N + NH4-N + NO2-N + NO3-N) < 15 mgN/l

Turbidity < 1 NTU

Coliforms < 2.000 CFU/100 ml

Coliforms of faecal origin < 500 CFU/100 ml

Streptococcus of faecal origin < 200 CFU/100 ml

Escherichia Coli < 10 CFU/100 ml

Intestinal enterococci < 200 CFU/100 ml

pH 6 - 9

* Limit value for the total nitrogen is applied when the wastewater temperature at the effluent of the

aeration tank is equal or greater than 12°C .

Table 8: Limit values considered for water discharge from the WWTP Porec South

3.3.2 Plant configuration

In the modelling of WWTP Porec South, the whole mechanical pretreatment section of

the plant (fine screen, aerated grit-grease removal and microscreen) is represented as a

single unit, whose output is grit and screened material.

After the pretreatment section, the plant is designed with four identical biological

treatment lines in order to guarantee a high flexibility in the operation according to the

variable influent flowrate and load (seasonal variations).

Each biological line is designed in three different zones (environments) where different

processes happen: an anaerobic zone, and anoxic zone, an aerated zone (with a final

45

volume that can be switched on and off to guarantee a complete

nitrification/denitrification, according to process needs). To reproduce the real

behaviour of the plant, the aerated zone has been represented with two different

reactors: one aerated and one switch zone (aerobic/anoxic) that can be dynamically

controlled in order to mimic optimized SUEZ’s aeration system (Greenbass™2).

Figure 13: Simplified scheme of WWTP Porec South biological section

Three recirculation flows have been implemented, according to the WWTP design: from

anoxic volume to anaerobic volume, from aerobic volume to anoxic volume and from

membrane trains to aerobic volume.

After the biological section, there is the membrane compartment for solid-liquid

separation. This section is foreseen with three treatment lines. However, when

modelling the WWTP, just one reactor is used to represent the behaviour of the process

because the simulation does not cover the membrane train operational modes.

As shown below, the MLSS form dewatering is also taken into account.

Figure 12 shows the BioWin simulator applied to WWTP Porec South.

Figure 14: BioWin main simulator window for WWTP Porec South (summer period)

2 https://www.suezwaterhandbook.com/degremont-R-technologies/wastewater-treatment/biological-

processes/regulation-of-sequenced-aeration-for-activated-sludge-Greenbass

Inlet

Effluent

Sludge

Membrane Tank

Anaerobic_1

Anaerobic_2

Anaerobic_3

Anaerobic_4

Anox_1

Anox_2

Anox_3

Anox_4

Sidestream Mixer20

General Mixer22 Ox_1.1

Ox_2.1

Ox_3.1

Ox_4.1

Ox_1.2

Ox_2.2

Ox_3.2

Ox_4.2

General Mixer28

grit and screened material

46

To simulate the plant in the winter period, due to the lower load and flowrate, only two

of the four lines are considered in operation (see Figure 13 below).

Figure 15: BioWin main simulator window for WWTP Porec South (winter period)

3.4 Performed simulations and results

Two simulations are carried out:

Dynamic simulation with variable inflow, summer conditions;

Dynamic simulation with variable inflow, winter conditions.

The objective of a dynamic simulation with variable inflow is to mimic the behaviour

of the system in real conditions, thus meaning that the inputs of the system are time-

varying, as in real operation. This type of simulation really allows to check and verify

the design of the WWTP and its performance.

The dynamic simulation is carried out with a variable inflow, daily trend of the flow is

presented in Figure 16. It is used the same distribution of the flow for summer and

winter conditions, supposing that the pattern of water consumption is constant during

the year.

The average and the peak values are the ones required by the project while assumed

distribution is based on SUEZ’s experience and know-how 3.

Two peaks of three and four hours are considered.

3 http://www.youbuyfrance.com/medias/press/degremont_1_4_2013_19_43.pdf

in

out

Sludge

Membrane Tank

Anaerobic_1

Anaerobic_2

Anox_1

Anox_2

Sidestream Mixer20

General Mixer22 Ox_1.1

Ox_2.1

Ox_1.2

Ox_2.2

General Mixer28

grit and screened material

47

Figure 16: Pattern of flow distribution employed for winter and summer simulations, only the

applied coefficients – that were not modified in the three simulations - are reported (and not the

flows)

3.4.1 Input data

Starting from the influent values as estimated by the project, a list of chemical

parameters has been defined as input of the BioWin model.

The characterization of the COD, Nitrogen, suspended solid and phosphorous

components, that is also necessary as in input for BioWin model, is detailed according

to the typical fractionation of municipal wastewaters.

Parameter M.U.

WWTP Porec South

Winter Summer

Capacity PE 8600 48000

BOD5 kg/day 516 2880

COD kg/day 1032 5.760

TSS kg/day 602 3360

VSS/TSS % 70 70

N-NTK kg/day 94,6 528,0

Pt kg/day 15 86

Table 9: Influent characterization - Input values for BioWin simulation for summer and winter

period

0

0,2

0,4

0,6

0,8

1

1,2

1,4

1,6

1,8

0 4 8 12 16 20 24

48

Other input data that are necessary to set the model are the volume of the tanks as

detailed below in Table 10.

Please note that the considered tank volumes in BioWin simulations are conservative

because they are calculated with the minimum water height.

Biological treatment step Volume per tank Total volume

Anaerobic 200 m3 800 m3

Anoxic 175 m3 700 m3

Aerobic 360 m3 1440 m3

Aerated membrane 75 m3 225 m3

Table 10: Summary of the biological tank volumes for WWTP Porec South

The results obtained by the simulation of the plant of both summer and winter period

are shown in the following text.

3.4.2 Dynamic simulation, summer (variable inflow)

For the summer period, the equilibrium sludge retention time is 6.48 days. The obtained

value is compliant with ATV-DVWK-A 131E, and the effluent quality respects the

project requirements.

It should be noted that all the values provided in the following paragraphs are expected

values, while guaranteed values are higher and equal to the one presented in Table 8.

As to say, COD concentration < 125 mgO2/L and TN concentration < 15 mgN/L.

Expected TN outlet value, presented in Figure 17 is less than 15 mgN/l according to the

limit and a complete nitrification is achieved (N-NH4 and N-NO2 below 1 mgN/l); the

Figure 17 also shows the guaranteed TN value (orange line).

The annual average of the samples for each parameter shall conform to the relevant

parametric values, according to the Directive 91/271/EEC.

Aeration system is controlled and optimized in order to achieve complete nitrification.

Controls implemented in BioWin mimic the behaviour of SUEZ’s patented

Greenbass™ that adjusts the air supply to completely oxidize inflow ammonium to the

aerated tank.

The equilibrium concentrations of pollutants in the effluent that are shown in Figure 17

(and the following for winter simulations) are a consequence of the implemented

controller that allows for keeping outlet concentrations constant.

49

Figure 17: Effluent Nitrogen fractions in summer

The concentration in the membrane tanks is around 10 gTSS/L with a volatile fraction

close to 60%.

The production of excess sludge is estimated to be around 2440 kgTSS/d4 from the

sludge line to the centrifuge that were assumed with a solid retention efficiency of the

95%5, corresponding to a production of sludge to disposal of about 2320 kgTSS/d (see

Figure 19). Please note that sludge dewaterability depends on the ratio of VSS over TSS

headed to the centrifuge.

4 The results from the dynamic simulation are, by definition, not constant in time. Therefore a slight variation from

values is a part of the intrinsic nature of the simulation. 5 The considered efficiency is conservative because this equipment, already installed in many WWTPs can achieve

higher performances

50

Figure 18: Total excess sludge production from dewatering in summer

The graph in Figure 18 reports the weekly average summer sludge production.

However, actual operation of the centrifuges will be for six days a week and ten hours

per day. The realistic pattern of centrifuge duty (and therefore sludge production to

disposal) is given in Figure 19.

Figure 19: Weekly operation of the centrifuge, where the 1 represent an hour of duty of the

equipment and the 0 an hour of standby

A production of grit and screened material is also been simulated, resulting in about

660 kg/d on average the value is reported in the following Figure 20.

T=20°C

Dewatering unit Total suspended solids (U) Average dewatered sludge

20-0818-0816-0814-0812-0810-0808-0806-0804-0802-08

Slu

dg

e p

rod

uc

tio

n (

kg

TS

S/d

)

2.800

2.700

2.600

2.500

2.400

2.300

2.200

2.100

2.000

51

Figure 20: Total waste material produced from pretreatment in summer

In normal operation membrane tanks are working with TSS concentrations of 10 g/L.

This concentration allows the correct functioning of the plant without any particular

membrane cleaning needs, since the biomass growth is well controlled and membrane

fibres are not overstressed. During periods of peak conditions, the concentration in a

membrane tank can be increased up to 12 g/L (for a short period). By observing the

following Figure 21, we can see that even in the peak period (month August) the

average TSS concentration in the MBR tanks is just slightly larger than 10 g/L.

Therefore the design of the plant is conservative, there is no additional clogging (with

the potential need of additional membrane cleaning).

According to the project, the membranes are to be cleaned for a period of 1 hour per

week. This short timeframe does not affect the model simulation especially given that

the flow of wastewater coming from one of the lines under cleaning regime is

distributed towards the lines in operation, therefore the total mass balance remains

equal.

T=20°C

Total suspended solids Mass rate from pre-treatmentAverage solids from pretreatment production

20-0818-0816-0814-0812-0810-0808-0806-0804-0802-08So

lid

s f

rom

pre

-tre

atm

en

t (k

g T

SS

/d)

1.000

950

900

850

800

750

700

650

600

550

52

Figure 21: Biomass concentrations

3.4.3 Dynamic simulation, winter (variable inflow)

For the winter period design, the resulting sludge retention time is of 20.39 days. The

obtained value is compliant with ATV-DVWK-A 131E, and the effluent quality

respects the project requirements.

Due to slower biological reactions in winter period, expected TN outlet is close to 14

mgN/L according to the limit and complete nitrification is achieved (N-NH4 and N-NO2

below 1 mgN/L). The limit value for the total nitrogen is applied when the wastewater

temperature at the effluent of the aeration tank is equal or greater than 12°C.

Results are presented in the following Figure 22 that also shows the guaranteed TN

value (orange line).

T=20°C

WWTP POREC JUG

Anaerobic TSS Anoxic TSS Aerated TSSMBR TSS Anaerobic TSS (flow weighted) Anoxic TSS (flow weighted)Aerated TSS (flow weighted) MBR TSS (flow weighted)

22/0820/0818/0816/0814/0812/0810/0808/0806/0804/0802/08

CO

NC

. (m

gT

SS

/L)

10.500

10.000

9.500

9.000

8.500

8.000

7.500

7.000

6.500

6.000

5.500

5.000

4.500

4.000

3.500

3.000

2.500

2.939,154 2.935,66 2.935,871

5.618,89 5.612,031 5.612,584

8.467,163 8.464,491 8.465,408

10.176,134 10.172,096 10.173,202

53

Figure 22: Effluent nitrogen fractions in winter

The concentration in the membrane tank is around 10 gTSS/L with a volatile fraction

close to 60%. The production of excess sludge is estimated to be around 420 kgTSS/d

on average from the sludge line to the centrifuge that were assumed with a solid

retention efficiency of the 95%, corresponding to a production of sludge to disposal of

about 400 kgTSS/d (see Figure 23).

Also in winter the same considerations on the pattern of centrifuges duty can be done.

Figure 23: Total excess sludge production from dewatering in winter

A production of grit and screened material is also been simulated, resulting in about 60

kg TSS/d, as reported in the following Figure 24.

T=12°C

Dewatering unit Total suspended solids (U) Average sludge production

19-0117-0115-0113-0111-0109-0107-0105-0103-0101-01

Slu

dg

e p

rod

uc

tio

n (

kg

TS

S/d

)

500

480

460

440

420

400

380

360

340

320

300

54

Figure 24: Total waste material produced from pretreatment in winter

3.4.4 Yearly average SRT of the WWTP

With the performed simulations, taking into account the global SRT of the plant (also

therefore considering anaerobic tank, membrane volumes and recirculation channels),

the weighted annual average sludge retention time is higher than 17 days, and it is 22.63

days. The calculation takes into account a summer period of 122 days at 8.32 days and

the rest of the year at 29.81 days. The performed simulation is therefore compliant with

project requirements of a global SRT of the WWTP higher than 17 days. Volumes and

concentrations taken into account are shown in Table 11.

T=12°C

Solids from pre-treatment Total suspended solids Mass rateAverage solids production from pre-treatment

19-0117-0115-0113-0111-0109-0107-0105-0103-0101-01So

lid

s f

rom

pre

-tre

atm

en

t (k

g T

SS

/d)

100

80

60

40

20

0

55

Parameter Winter Summer M.U.

Volume anaerobic 200 m3

Anaerobic concentration 4 g/l

Volume anoxic 175 m3

Anoxic concentration 6 g/l

Aerated volume 360 m3

Aerated concentration 8 g/l

Sludge Production 400 2320 kg/day

Biological lines in operation 2 4

Membrane concentration 10 g/l

Operating membrane volume 50 m3

MBR tank volume 75 m3

Biomass volume 25 m3

MBR line in operation 1 3

Total 25 75 m3

Volume aeration outlet common channel 258 m3

Volume sludge recirculation channel 19 m3

Volume tube + pit recirculation 46 m3

SRT (aerated) 20,39 6,48 days

Total SRT WWTP 29,81 8,32 days

Duration 243 122 days

Annual average 22,63 days

Table 11: Calculations to determine the yearly average SRT

3.5 Comparison with ATV-DVWK rules and standards

What is the ATV standard?

Since no European-wide design standards have been drafted so far (Benedetti L., 2006)

for wastewater treatment plant design, most of the Member States have their own

standards or guidelines providing advice for good design practice, but they are usually

just suggesting broad ranges of design parameters (e.g. ANPA, 2001). However, one of

the most adopted guideline all over Europe is the German “Standard ATV-DVWK-A

131E, Dimensioning of Single-Stage Activated Sludge Plants” (ATV, 2000).

The standard ATV-DVWK-A-131E and its guidelines along with the design approach

of Wastewater Engineering: Treatment and Reuse (Metcalf & Eddy, 2002) are widely

used for the design of wastewater treatment plants. These approaches are both based on

more or less simplified steady-state assumptions and have been proven in practice since

decades. ATV-A-131 is tailored to the boundary conditions of temperate climates in

Europe, whereas the Metcalf & Eddy approach is widely used especially in Anglo-

American and Asian regions. The main design parameters of these guidelines are the

solids retention time (SRT), the mixed liquor suspended solids (MLSS) concentration

and the related excess sludge production of the activated sludge system. All three

56

parameters are connected to each other, basically as a result of the incoming load

(characteristics) and the growth rate of the heterotrophic and autotrophic

microorganisms under the present operational conditions.

Scope

The standard applies for wastewater which essentially originates from households or

from plants which serve commercial or agricultural purposes, insofar as the harmfulness

of this wastewater can be reduced by means of biological processes with the same

success as with wastewater from households.

In accordance with the project requirements, all process calculations were to be

performed according to the ATV-DVWK-A 131E standard. Since for this case study it

was opted the use of BioWin in order to estimate the output data, in the following sub-

chapter a comparison between the simulated results and ATV-DVWK-A 131E standard

is presented.

3.5.1 Required Sludge Age - winter

When referring to the required aerated sludge age (SRT or 𝑡𝑆𝑆,), the biological volumes

taken into account are the aerobic and anoxic. According to the scope of the project, the

yearly average SRT of the WWTP and the aerated sludge age have two different

values.

The required sludge age for ATV standards can be derived from the following Table 12

(pg. 21, ATV-DVWK-A 131E manual). The design temperature was considered of

12°C.

To read the table, the row and the column of Porec should be determined. The row, in

case of WWTP Porec South is the one with Nitrogen Removal (paragraph 5.2.1.3 of the

ATV-DVWK-A 131E: Plants with Nitrification and Denitrification). The ratio between

VD and VAT is determined as follows:

𝑉𝐷𝑉𝐴𝑇

⁄ = 200 𝑚3

(200 𝑚3 + 360 𝑚3) = 0.357 ⁄

Where:

𝑉𝐷= volume of the biological reactor used for denitrification (200 m3)

𝑉𝐴𝑇= volume of the biological reactor (aerated tank + denitrification tank: 360 m3)

Moreover, the BOD5 inlet parameter should be used and during winter conditions this

value is 516 kgBOD/d (see Table 7). Indeed, the value for the ratio between 𝑉𝐷

𝑉𝐴𝑇⁄ is

between the two provided in the tables, of 0.3 and 0.4. In Table 13 it is therefore

highlighted the two SRT values that were interpolated to get the final result: 11.7 days

and 13.7. The value for the SRT is therefore 12.24 days, during winter period.

This value is smaller than the one obtained with the performed simulation (20.39 days).

It is therefore compliant with ATV-DVWK-A 131E requirements.

57

Table 12: Dimensioning sludge age in days dependent on the treatment target and the temperature

as well as the plant size (intermediate values are to be estimated)

3.5.2 Required Sludge Age - summer

The calculation of the aerated SRT in summer is to be determined through the equation

provided since no tables are given at 20°C.

The required sludge age for nitrification and denitrification, according to ATV-DVWK-

A 131E standards (pg. 23, ATV-DVWK-A 131E manual) is calculated as follows:

𝑡𝑆𝑆,𝑑𝑖𝑚 = 𝑆𝐹 ∗ 3.4 ∗ 1,103(15−𝑇) ∗1

1− 𝑉𝐷

𝑉𝐴𝑇⁄

[𝑑𝑎𝑦𝑠]

Where:

SF = it is determined from the capacity of the plant, below 1200 kgBOD/d is 1.8 while

above 6000 kgBOD/d is 1.45

3.4 = empirical coefficient derived from the net growth rate of Nitrosomonas at 15°C.

T = the design temperature (20°C)

VDVAT

⁄ = the ratio calculated in the previous paragraph

In the WWTP Porec South case, the SF was interpolated for the design BOD load (2880

kg BOD/d), as for ATV-DVWK-A 131E prescriptions. The obtained SF is 1.68. The

calculation of the aerated SRT is therefore:

𝑡𝑆𝑆, = 1,7 ∗ 3.4 ∗ 1,103(15−20) ∗1

1 − 0.33= 5.19 𝑑𝑎𝑦𝑠

58

The required sludge age during summer period is therefore 5.19 days.

Hence, also for summer conditions the equilibrium tSS (SRT) of the system (6,48 days)

is compliant with ATV-DVWK-A 131E standards.

3.5.3 Determination of the proportion of the reactor volume for

denitrification

The empirical values listed in Table 12 (pg. 25, ATV-DVWK-A 131E manual) should

be used to determine the ratio between denitrification and aerated tank. For a check, the

ratio between the concentration of nitrogen to be denitrified and of influent BOD were

determined.

According to ATV-DVWK-A 131E standards:

𝑆𝑁𝑂3,𝐷 = 𝐶𝑁,𝐼𝐴𝑇 − 𝑆𝑜𝑟𝑔𝑁,𝐸𝑆𝑇 − 𝑆𝑁𝐻4,𝐸𝑆𝑇 − 𝑆𝑁𝑂3,𝐸𝑆𝑇 − 𝑋𝑜𝑟𝑔𝑁,𝐵𝑀 [𝑚𝑔/𝐿]

Where:

SNO3,D = daily average nitrate concentration to be denitrified

CN,IAT = influent nitrogen concentration

SorgN,EST = organic nitrogen in the effluent (default value is 2 mg/l)

SNH4,EST = ammonium content in the effluent (as a safety factor it was considered zero)

SNO3,EST = nitrate concentration in the influent (considered zero)

XorgN,BM = amount of nitrogen incorporated in the biomass, it can be considered the

0.05 ∗ CBOD,IAT

Therefore:

𝑆𝑁𝑂3,𝐷 = 99 − 2 − 0.05 ∗ 539 = 70.05 𝑚𝑔/𝐿

This value should be divided for the BOD concentration in the inlet, thus making:

𝑆𝑁𝑂3,𝐷𝐶𝐵𝑂𝐷,𝐼𝐴𝑇

⁄ =70.05 𝑚𝑔/𝑙

539 𝑚𝑔/𝑙⁄ = 0.13

The obtained value is the same as the one reported in Table 12 for the ratio between the

denitrification tank and the total biological volume.

59

Table 13: Standard values for the dimensioning of denitrification for dry weather at temperatures

from 10° to 12° C and common conditions

(kg nitrate nitrogen to be denitrified per kg influent BOD5)

3.5.4 Phosphorous removal

According to ATV-DVWK-A 131E standards, biological phosphorous removal can take

place if the retention time in the anaerobic tank is at least 0.5 ÷ 0.75 hours, referred to

the maximum dry weather inflow and return sludge flow (pg. 26, ATV-DVWK-A 131E

manual). Note that the return from the centrifuge is not taken into account because its

contribution to the HRT would have been very small (less than 3% of the total flow to

be considered in calculations).

The calculation is therefore:

𝑉𝑎𝑛𝑎𝑒𝑟𝑜𝑏𝑖𝑐 ∗ #𝑙𝑖𝑛𝑒𝑠 𝑖𝑛 𝑜𝑝𝑒𝑟𝑎𝑡𝑖𝑜𝑛𝑄𝐷𝑊,ℎ + 𝑄𝑅𝑆

⁄ ≥ 0.5 ÷ 0.75

Results are shown in Table 14.


QDW

60

490

[m3/h]

QRS

40 325 [m3/h]

Lines in operation 2 4 -

HRT 4 0.98 h

Table 14: Values used in the calculation of the anaerobic HRT

60

As it can be seen from the table, the hydraulic retention time is above the upper limit

provided by the ATV-DVWK-A 131E.

The foreseen anaerobic volume is therefore compliant with ATV-DVWK-A 131E

suggested values.

The high value of HRT obtained during winter condition takes into account the

difficulties in performing biological phosphorous removal at low temperature.

3.5.5 Sludge production

Comparison with Wastewater engineering: Treatment and reuse (Metcalf & Eddy,

2002)

Due to the lack of guidelines on the biological sludge production in a MBR WWTP, the

results from the dynamic model are compared with the sludge production that is

expected from Wastewater Engineering: Treatment and Reuse (Metcalf & Eddy, 2002).

The following equation was used (Ch. 7: “Fundamentals of Biological Treatment”, pg.

594):

𝑃𝑋,𝑉𝑆𝑆 = 𝑄 ∗ 𝑌 ∗ (𝑆0 − 𝑆)

1 + 𝑘𝑑 ∗ 𝑆𝑅𝑇+

𝑓𝑑 ∗ 𝑘𝑑 ∗ 𝑄 ∗ 𝑌 ∗ (𝑆0 − 𝑆) ∗ 𝑆𝑅𝑇

1 + 𝑘𝑑 ∗ 𝑆𝑅𝑇+ 𝑄 ∗ 𝑋0,𝑖

𝑃𝑋,𝑉𝑆𝑆 = (𝐴) + (𝐵) + (𝐶)

Where:

Q = inflow (m3/d)

Y = biomass yield (mg VSS/mg bs COD)

S0 = influent substrate concentration, as mg bsCOD/l

This value is calculated as S0 = Fbs ∗ CODin with Fbs being the rb soluble COD

fraction in the inlet (assumed of 0.2)

S = effluent substrate concentration, as mg bsCOD/l, assumed as 5 mg bsCOD/l

Kd = endogenous decay rate coefficient (d-1)

fd = fraction of biomass that remains as cell debris (gVSS/gVSS)

X0,i = amount of non-biodegradable VSS in the influent (mg VSS/l)

This value is given from X0,i = Fup ∗ CODin where Fup is the nobiodegradable

particulate COD. A value of 0.13 is assumed (taken from the fractioning employed in

the simulations).

The letters A, B and C respectively indicate heterotrophic biomass growth, cell debris

and the amount of non-biodegradable VSS in the influent.

61

Once found, the daily production of VSS, this must be corrected for the amount of TSS

as follows:

𝑃𝑋,𝑇𝑆𝑆 =(𝐴)

𝑉𝑆𝑆𝑇𝑆𝑆⁄

+(𝐵)

𝑉𝑆𝑆𝑇𝑆𝑆⁄

+ (𝐶) + 𝑄 ∗ (𝑇𝑆𝑆0 − 𝑉𝑆𝑆0)

Where:

TSS = total suspended solids in the effluent (mg /l)

VSS = volatile suspended solids in the effluent (mg /l)

In the following Table 15 the calculations are shown:


SRT (𝑡𝑆𝑆) 20.39 6.48 d

Q 958 7800 m3/d

Y 0.4 0.4 mg VSS/mg bs COD

Fbs 0.2 0.2 -

COD0 1077 738 mg COD/L

S0 215 147 mg bs COD/L

S 5 5 mg bs COD/L

kd 0.15 0.15 d-1

fd 0.1 0.1 -

Fup 0.13 0.13 -

X0i 140 96 g nbVSS/m3

VSS/COD 1.2 1.2 g COD/ g nbTSS

PVSS 187 1145 kg VSS/d

VSS/TSSin 0.7 0.7 -

TSS0 628 431 g/m3

62

VSS0 440 302 g/m3

ISS0 188 129 g/m3

VSS/TSSout 0.6 0.6 -

PTSS 385 2319 kg TSS/d

Sludge production 400 2320 kg TSS/d

Difference +15 +1 kg TSS/d

Table 15: Parameters and calculations employed for the comparison on sludge production

Therefore, the results obtained from the simulations are in line with the expected sludge

production from Wastewater Engineering: Treatment and Reuse (Metcalf & Eddy,

2002).

Comparison with ATV-DVWK-A 131E

Sludge production depends on the sludge age through the following (pg. 27, ATV-

DVWK-A 131E manual):

𝑆𝑃𝑑 = 𝐵𝑑.𝐵𝑂𝐷 ∗ (0.75 + 0.6 ∗ 𝑋𝑆𝑆.𝐼 𝐴𝑇

𝐶𝐵𝑂𝐷.𝐼 𝐴𝑇−

(1 − 0.2) ∗ 0.17 ∗ 0.75 ∗ 𝑡𝑆𝑆 ∗ 𝐹𝑇

1 + 0.17 ∗ 𝑡𝑆𝑆 ∗ 𝐹𝑇 [

𝑘𝑔𝑑

⁄ ]

Where:

XSS,I AT = influent solids concentration to the aeration tank, respectively 583 mg/l and

350 mg/L for winter and summer conditions (data taken from BioWin simulations).

CBOD,I AT = influent BOD concentration to the aeration tank. For the sake of simplicity

this value was considered to be equal to the one in the influent. The values are 539 and

369 mg /L for winter and summer respectively.

The role of temperature is taken into account with the coefficient FT, whose value is

determined as follows:

𝐹𝑇 = 1.072(𝑇−15)

Thus resulting, in 0.81 and 1.42 respectively for winter and summer period.

The following Table 16 sums up the obtained results:

63


𝑡𝑆𝑆 considered in calculation 20.39 6.48 d

Specific Sludge Production 0.96 0.95 kg/kg BOD

Daily Sludge Production 493 2746 kg/d

Actual sludge production 400 2320 kg/d

Table 16: Sludge production as a function of the different SRT obtained or stated in the ATV-

DVWK-A 131E

The ATV-DVWK-A 131E guidelines have led to a calculated sludge production that is

higher than what obtained with BioWin simulations. However, ATV-DVWK-A 131E

guideline do not regulate sludge production in WWTPs with membrane technologies,

since they only refer to conventional ASP plants.

It must be noted that standards of Merkblatt DWA-M 227 on membrane system design

do not mention biological sludge production. Therefore, for biological sludge

production, reference values are taken from ATV-DVWK-A 131E.

3.5.6 Volume of the biological reactor

The mass of suspended solid in system is given by (pg. 30, ATV-DVWK-A 131E

manual):

𝑀𝑆𝑆,𝐴𝑇 = 𝑡𝑆𝑆 ∗ 𝑆𝑃𝑑 [𝑘𝑔]

Where the meaning of tSS and SPd has already being explained in the previous text.

The volume of the biological reactor is derived from:

𝑉𝐴𝑇 =𝑀𝑆𝑆,𝐴𝑇

𝑆𝑆𝐴𝑇 [𝑚3]

Where:

VAT = volume of the biological reactor

64

SSAT = biomass concentration in the aerated and anoxic tank, weighted average

In the following Table 17, the obtained results are presented:


𝑡𝑆𝑆 considered in calculation 20.39 6.48 d

𝑆𝑃𝑑 400 2320 kg/day

𝑀𝑆𝑆,𝐴𝑇 8156 15034 kg

𝑉𝐴𝑇 1110 2047 m3

𝑉𝐴𝑇,𝑑𝑒𝑠𝑖𝑔𝑛 𝑣𝑎𝑙𝑢𝑒6 1070 2140 m3

Excess volume with comparison to the ATV-DVWK-A 131E -4% +5% -

Table 17: Parameters for biological reactor volume determination

As it can be seen from the table, the design volume is compliant with what is required

from the ATV-DVWK-A 131E .

3.5.7 Summary of obtained results

In the following Table 18, a final summary of the comparison between the design of the

WWTP and the ATV-DVWK-A 131E/Wastewater Engineering: Treatment and Reuse

(Metcalf & Eddy, 2002) is shown:

6 Only the volumes of the anoxic and aerobic tanks were considered in the calculation, as required by ATV-DVWK-

A 131E

65

Design parameter

Design values ATV-DVWK-A

131E values Compliance

Winter Summer Winter Summer Winter Summer

𝑡𝑆𝑆 20.39 6.48 12.24 5.19 Yes Yes

Proportion of reactor volume

for Denitrification 0.33 0.33 0.33 0.33 Yes Yes

𝐻𝑅𝑇 for Phosphorous

removal 4.0 0.98

≥ 0.5

÷ 0.75

≥ 0.5

÷ 0.75 Yes Yes

𝑆𝑃𝑑 400 2320 495 2728 Yes7 Yes

Volume of the aerated tank 1070 2140 1110 2047 Yes Yes

Table 18: Summary of the compliance of the WWTP design with ATV-DVWK-A 131E/

Wastewater engineering: Treatment and reuse

3.6 Simulation of an extreme event

3.6.1 Assumed scenario

In order to perform this simulation, a scenario of a 5-day storm event during the month

of August (month with the highest flows to the plant) was simulated. The goal is to

simulate the performance of the plant under “above peak flow” conditions and to see if

the plant could still maintain its normal operation and at the same time respect the

effluent requirements. To do this, the following assumptions were taken:

Three hours of peak inflow (between the night time hours 01:00 - 04:00, when

under normal conditions the lowest flow values are present);

Peak flow: 610 m3/h;

SRT: 6.28 days;

Temperature: 20°C;

Duration: 5 days (Aug 21th - Aug 26th).

3.6.2 Performed simulation and results

After the performed simulation and by observing the results, it can be concluded that

even under these unfavourable inflow conditions, the plant remains operable.

7 The compliance on sludge production has already been discussed. The lack of regulation in the ATV-DVWK-A

131E has led to the comparison with Wastewater Engineering: Treatment and Reuse (Metcalf & Eddy, 2002)

66

By looking at Figure 25, it can be observed that the effluent Ammonia is somewhat

elevated under these conditions; however a complete nitrification is still achieved (N-

NH4 and N-NO2 are still below 1 mgN/L).

The only cause for concern would be the period of Aug 25th - Aug 26th, in which the

value of TN is above the 15 mg/L limit set for the project. However, after this short

period the TN value drops and equilibrium is achieved just at the given limit.

Figure 25: Effluent Nitrogen fractions (summer - extreme event)

In the Figure 26 and Figure 27, it can be seen, as expect, the increase in the excess

sludge production and biomass production, which as a consequences requires higher

aeration rate (higher oxygen demand of the biomass) as shown in Figure 28.

T=20°C

Effluent Nitrate N Effluent Nitrite NEffluent Total N Effluent Ammonia NAverage Effluent Nitrate Average Ammonia EffluentAverage Effluent Total P Average Effluent NitriteEffluent Total Kjeldahl Nitrogen Average Effluent TKNEffluent Composite Ammonia N (flow weighted) Effluent Composite Total N (flow weighted)

30/0828/0826/0824/0822/0820/0818/0816/0814/0812/0810/0808/0806/0804/0802/08

CO

NC

. (m

gN

/L)

20

19

18

17

16

15

14

13

12

11

10

9

8

7

6

5

4

3

2

1

0

67

Figure 26: Total waste material produced from pre-treatment (summer - extreme event)

Figure 27: Total excess sludge production from dewatering (summer - extreme event)

T=20°C

Total suspended solids Mass rate from pre-treatmentAverage solids from pretreatment production

30-0828-0826-0824-0822-0820-0818-0816-0814-0812-0810-0808-0806-0804-0802-08So

lid

s f

rom

pre

-tre

atm

en

t (k

g T

SS

/d)

1.200

1.150

1.100

1.050

1.000

950

900

850

800

750

700

650

600

550

T=20°C

Dewatering unit Total suspended solids (U) Average dewatered sludge

30-0828-0826-0824-0822-0820-0818-0816-0814-0812-0810-0808-0806-0804-0802-08

Slu

dg

e p

rod

uc

tio

n (

kg

TS

S/d

)

2.800

2.700

2.600

2.500

2.400

2.300

2.200

2.100

2.000

2.355,451 2.354,072 2.354,155 2.354,364 2.354,547

2.543,988

68

Figure 28: Air flow rate needed to perform the aeration of biomass (summer - extreme event)

T=20°C

WWTP POREC JUG

1st zone air flow rate 2nd zone air flow rate Total Air Flow Rate

30/0828/0826/0824/0822/0820/0818/0816/0814/0812/0810/0808/0806/0804/0802/08

AIR

FL

OW

RA

TE

(m

3/h

r (2

0C

, 1

01

.32

5 k

Pa

))

1.500

1.450

1.400

1.350

1.300

1.250

1.200

1.150

1.100

1.050

1.000

950

900

850

800

750

700

650

600

550

500

450

400

350

300

250

200

150

100

50

0

69

CHAPTER 4 - CONCLUSIONS

Activated sludge modelling and simulation are widely applied. Learning, design and

process optimization are the main application areas of WWTP models. The introduction

of the ASM model family by the IWA task group was of great importance in this field,

providing researchers and practitioners with a standardised set of basic models. These

basic models are mainly applicable to municipal wastewater systems, but can be

adapted easily to specific situations such as the presence of industrial wastewater.

Further developments in computer technology have led to the development of more

complex models as well as simulation environments such as BioWin that incorporate

many wastewater processes into a modelling tool along with an ease of use.

The availability of models and software applications such as these has allowed

engineers to explore, through simulation, a very broad range of system configurations,

inputs and operational strategies. By doing so, the base of experience is greatly

expanded and their intuitive decision making ability is increased.

In this work, we have established that:

With the aid of a modelling tool we were able to verify the design and a chosen

configuration of a wastewater treatment plant;

By given inputs of the Project and with the simulation for both summer and

winter conditions we were able to verify that the set effluent limits are respected

at all times;

By modifying the input parameters and based on the initial WWTP design we

can essentially create many different scenarios and simulate their effects on the

plant and its processes.

All of this research can prove to be of great benefit during the design of a WWTP, since

the results allow to check and validate process tank volumes (anaerobic, anoxic and

aerated volumes), sludge concentrations, excess sludge extraction and sludge age,

recirculation rates and the compliance to the discharge limits. Any extreme event that

can have a detrimental effect on the activated sludge processes, aeration needs (biggest

source of energy consumption of most WWTPs) can be easily simulated and

anticipated.

Finally, through continued application of the models during the plant’s design phase, it

will be possible to define the feasible space better, thereby reducing the alternatives

which must be considered by a designer. Engineering design has always depended upon

heuristic rules founded upon experience. By increasing their experimental base, the

validity of those rules will be strengthened and the engineer’s ability will be improved.

70

BIBLIOGRAPHY

o ATV-DVWK-A 131E – Dimensioning of Single-Stage Activated Sludge Plants

(May 2000)

o Barker P.S., Dold P.L. (1997). General model for biological nutrient removal

activated-sludge systems: model presentation, Water Environ. Res.69 (5), 969 o Dold P. L., Wentzel M. C., Billing A. E., Ekama G. A. and Marais G. v. R. (1991)

Activated Sludge System Simulation Programs. Water Research Commission,

Pretoria, North Africa. o EnviroSim Associates Ltd. (2012). User Manual for BioWin v.4.0, EnviroSim

Associates Ltd., Hamilton, Canada. o Gernaey K. V., Loosdrecht M. C. M., Henze M., Lind M., Jorgensen S. B. (2004).

Activated sludge wastewater treatment plant modelling and simulation: state of

the art. Environ. Modell. Softw., 19(9): 763–783. o Henze M.; Grady C.P.L.; Gujer W.; Marais G.v.R.; Matsuo T. (1987a). Activated

Sludge Model No. 1, IAWPRC Scientific and Technical Report No. 1. London, UK:

International Water Association. o Henze M, Gujer W, Mino T, Matsuo T, Loosdrech M V. (2002). Activated sludge

models ASM1, ASM2, ASM2d and ASM3. IWA Scientific and Technical Report

No.9, London, UK. p.45–102. o Liwarska-Bizukojc E., Biernacki R., Gendaszewska D., Ledakowicz S., (2013),

Improving the operation of the full scale wastewater treatment plant. Lodz

University of Technology. o Meijer S.C.F. (2004). Theoretical and practical aspects of modelling activated

sludge processes. Delft University of Technology, The Netherlands. o Melcer H., Dold P.L., Jones R.M., Bye C.M., Takacs I., Stensel H.D., Wilson A.W.,

Sun P., Bury S. (2004). Methods for wastewater characterization in activated

sludge modeling. 99-WWF-3, Water Environment Research Foundation (WERF),

Alexandria, VA, USA. o Merkblatt DWA-M 227, Membran-Bioreaktor Verfahren (October 2014). o Mittal A., (2011), Wastewater Applications Engineering Department, Aquatech. o Mulas M., (2006), Modelling and Control of Activated Sludge Processes.

Università degli Studi di Cagliari, Italy. o Odvodnja Porec LLC, Tender documents, Book 3: Collection system with

Wastewater Treatment Plants of the city of Porec (2013). o Radjenovic J., Matosic M., Mijatovic I., Petrovic M., Barcelò D. (2008)

Membrane Bioreactor (MBR) as an Advanced Wastewater Treatment Technology. o Metcalf & Eddy, Inc. (2002). Wastewater engineering: Treatment and reuse

(Fourth Edition) revised by Tchobanoglous, G., Burton, F. L., Stensel, H. D.,

McGraw-Hill.

71

o Wentel M.C., Dold P.L, Ekama G.A., Marais G.V.R. (1989) Enhanced

polyphosphate organism cultures in activated sludge systems. Part II.

Experimental behaviour, Water SA, 15, 71. o Wentzel M.C., Dold P.L., Ekama, G.A., Marais G.V.R., (1989) Enhanced

polyphosphate organism cultures in activated sludge systems. Part III: Kinetic

model, Water SA, 15, 89. o Wiesmann U., Choi I. S., Dombrowski E., (2007) Fundamentals of Biological

Wastewater Treatment: WILEY-VCH.

72

ANNEX - BIOWIN PARAMETERS (ASP)

Growth and Decay of Ordinary Heterotrophic Organisms (OHO):

Table A1: Kinetic parameters assumed in the growth and decay of OHOs

Name Default Unit Explanation

Maximum specific

growth rate 3.2 d-1

Determines the maximum specific growth rate of

ordinary heterotrophs. Substrate and nutrient

limitations will decrease the growth rate. This

parameter is sensitive only in very high loaded

plants (short SRT), and determines maximum BOD

removal capacity.

Substrate half

saturation 5.0 mgCOD/L

This parameter impacts the residual soluble

substrate concentration in the effluent. The value is

usually low in normal municipal plants.

Anoxic growth

factor 0.5 -

This parameter represents the fraction of organisms

that are able to grow under anoxic conditions

and/or a reduction in the growth rate under anoxic

conditions. Substrate and nutrient limitations may

further reduce the growth rate.

Denitrification N2

producers (NO3 or

NO2)

0.5 -


which are able to reduce either nitrate or nitrite to

nitrogen gas. [The remaining organisms being those

only capable of reducing nitrate to nitrite.]

Aerobic decay rate 0.62 d-1

Decay rate constant under aerobic conditions. This

parameter impacts the endogenous respiration rate

and VSS destruction during aerobic stabilization.

Anoxic decay rate 0.233 d-1 Decay rate constant when there is no oxygen, but

either nitrate or nitrite is available.

Anaerobic decay

rate 0.131 d-1

Decay rate constant when there is no oxygen,

nitrate or nitrite available.

Fermentation rate 1.6 d-1 Maximum specific growth rate of ordinary

heterotrophs under anaerobic conditions.

Fermentation half


Half saturation of complex substrate under

anaerobic conditions

Fermentation

growth factor (AS) 0. 25 -

Growth rate reduction under anaerobic conditions

in activated sludge

73

Table A2: Stoichiometric parameters assumed in the growth and decay of OHOs


Yield

(Aerobic) 0.666 mgCOD/mgCOD

Amount of biomass COD produced using one

unit of readily biodegradable complex substrate

COD. The remaining COD is oxidized. This

parameter is very stable in municipal plants and

seldom needs adjustment. In case there is a

mismatch between measured and simulated

sludge production and OUR.

N in Biomass 0.07 mgN/mgCOD

N content of heterotrophs. This parameter

impacts the nitrogen available for nitrification

and therefore oxygen demand.

P in Biomass 0.022 mgP/mgCOD

P content of heterotrophs. This parameter

influences the P removal in non Bio-P systems,

and the P content of the sludge.

Endogenous

fraction -

aerobic

0.08 - Fraction of biomass that becomes inert upon

aerobic decay.

Endogenous

fraction -

anoxic


anoxic decay.

Endogenous

fraction -

anaerobic


anaerobic decay.

Yield (anoxic) 0.54 mgCOD/mgCOD Biomass yield on readily biodegradable complex

substrate COD under anoxic conditions.

74

Table A3: Stoichiometric parameters assumed, common to all the processes


Biomass volatile

fraction (VSS/TSS) 0.92 mgVSS/ mgTSS

Volatile fraction of active biomass.

Internal ISS 8 generated (uptake of

minerals and micronutrients) by biomass

growth.

Endogenous residue

volatile fraction

(VSS/TSS)

0.92 mgVSS/ mgTSS Volatile fraction of endogenous residue.

N in endogenous

residue 0.07 mgN/ mgCOD

N content of endogenous residue from

organism decay.

P in endogenous

residue 0.022 mgP/ mgCOD

P content of endogenous residue from

organism decay.

Endogenous residue

COD:VSS Ratio 1.42 mgCOD/mgVSS

Conversion factor between endogenous

residue measured as COD and its VSS

content.

Particulate substrate


Conversion factor between particulate

substrate measured as COD and its VSS

content.

Particulate inert


Conversion factor between particulate

inert measured as COD and its VSS

content.

Table A4: pH inhibition for OHOs


OHO low pH

limit 4.0

pH

units

At a pH equal to this value the growth rate of ordinary

heterotrophic biomass will be reduced by 50%.

Heterotrophs exhibit tolerance for pH changes – hence the

wide pH range.

OHO high pH

limit 10.0

pH

units


heterotrophic biomass will be reduced by 50%.

OHO low pH

limit (anaerobic) 5.5

pH

units


heterotrophic biomass under anaerobic conditions will be

reduced by 50%.

OHO high pH

limit (anaerobic) 8.5

pH

units


heterotrophic biomass under anaerobic conditions will be

reduced by 50%.

8 ISS= inorganic suspended solid

75

Table A5: Switching functions for OHOs


OHO DO half

saturation 0.05 mgO2/L

This constant is used to switch off aerobic OHO

activity under low DO conditions (that is in

anaerobic and anoxic reactors). Anoxic or

anaerobic processes will become active as

environmentally appropriate.

Anoxic/anaerobic

NOx half saturation 0.15 mgN/L

This constant is used to turn off anoxic growth,

decay and hydrolysis processes on under

conditions of low nitrate and nitrite.

Anoxic NO3

(→NO2) half

saturation

0.1 mgN/L

This constant is used to switch off anoxic growth

processes producing nitrite under low nitrate

conditions.

Anoxic NO3 (→N2)

half saturation 0.05 mgN/L


processes using nitrate under low nitrate

conditions.

Anoxic NO2 (→N2)



processes using nitrite under low nitrite

conditions.

NH3 nutrient half

saturation 0.005 mgN/L

This constant is used to slow all biomass growth

processes at low ammonia-N concentrations (N

nutrient limiting conditions.

P nutrient half

saturation 0.001 mgP/L

This constant is used to slow the growth of

biomass when there is no phosphorus available

as nutrient.

H2 low/high half


This constant switches between two fermentation

pathways, generating acetate and propionate in

various ratios, depending on available H2

concentration.

Synthesis

anion/cation half

saturation

0.01 meq/L Half saturation concentration for anions and

cations.

76

Hydrolysis, Adsorption, Ammonification and Assimilative denitrification:

Table A6: Kinetic parameters (common to all the above mentioned processes)


Hydrolysis rate 2.1 d-1 Rate constant for hydrolysis of slowly degradable organics

into readily degradable substrate.

Hydrolysis half

saturation 0.06 -

Monod half saturation constant for the regulation of

hydrolysis rate, expressed in terms of particulate substrate to

heterotrophic biomass ratio.

Anoxic

hydrolysis

factor

0.28 - Rate reduction factor for hydrolysis under anoxic conditions.

Anaerobic

hydrolysis

factor (AS)

0.04 - Rate reduction factor for hydrolysis under anaerobic

conditions in activated sludge.

Anaerobic

hydrolysis

factor (AD)

0.5 - Rate reduction factor for hydrolysis under anaerobic

conditions in anaerobic digestion.

Adsorption rate

of colloids 0.15 d-1 Conversion rate of colloidal material to particulate.

Ammonification

rate 0.08 d-1

Conversion rate of soluble organic nitrogen compounds to

ammonia

Assimilative

nitrate/nitrite

reduction rate

0.5 d-1 Conversion rate of nitrite and/or nitrate to ammonia under

ammonia limited conditions

Endogenous

products decay

rate

0 d-1 Conversion rate of endogenous products to particulate

substrate.

Table A7: Threshold value of absorbed slowly biodegradable substrate from OHO


Adsorption

Max. 1.0 mgCOD/mgCOD

Threshold ratio of adsorbed slowly biodegradable

substrate to heterotrophic organisms. Above this

threshold ratio colloidal adsorption ceases.

77

Table A8: Switching functions for all the above mentioned processes


OHO DO half


This constant is used to switch off aerobic

activity under low DO conditions (that is in

anaerobic and anoxic reactors).

Anoxic/anaerobic NOx


This constant is used to turn off anoxic growth,

decay and hydrolysis processes under conditions

of low nitrate and nitrite.

NH3 nutrient half





Growth and Decay of Ammonia Oxidizing Biomass (AOB):

Table A9: Kinetic parameters for AOB


Max. spec. growth

rate 0.9 d-1


ammonia oxidizing biomass. Substrate and nutrient

limitations will decrease the growth rate. This

parameter has a direct impact on the nitrification

capacity.

Substrate (NH4) half


This parameter impacts the residual ammonia

concentration in the effluent. The value is usually low

in normal municipal plants.

AOB denite DO

half saturation 0.10 mg/L-

DO half saturation concentration for AOB

denitrification. Note: This parameter is only used if

the Nitrous oxide model option is turned on.

Aerobic decay rate 0.17 d-1 Decay rate constant under aerobic conditions for

ammonia oxidizing biomass.

Anoxic/anaerobic

decay rate 0.08 d-1

Decay rate constant under non-aerobic conditions for

ammonia oxidizing biomass.

KiHNO2 0.005 mmol/L Nitrous acid inhibition concentration.

78

Table A10: Stoichiometric parameters for AOB


Yield 0.15 mgCOD/mgN AOB COD produced by oxidizing 1 mg of

ammonia to nitrite.

N in biomass 0.07 mgN/ mgCOD N content of AOB.

P in biomass 0.022 mgP/ mgCOD P content of AOB.

Fraction going to

endogenous

residue


decay.

COD:VSS ratio 1.42 mgCOD/mgVSS

Conversion factor between biomass as

measured in COD and its VSS content. This

value is relatively stable for biomass. (Actually

this value was already shown in Table A3)

Table A11: pH inhibition for autotrophic biomass (and therefore for AOB).


Autotrophs low

pH limit 5.5

pH

units

At a pH equal to this value the growth rate of AOB,

NOB and AAO organisms will be reduced by 50%.

Autotrophs high

pH limit 9.5

pH

units

At a pH equal to this value the growth rate of AOB,

NOB and AAO organisms will be reduced by 50%.

79

Table A12: Switching functions for AOB (autotrophic biomass)


AOB DO half

saturation

0.25

mgO2/L

This parameter is used to switch off ammonia

oxidation by AOB organisms under low DO

conditions.

P nutrient half

saturation

0.001

mgP/L

This parameter is used to switch off the growth of

biomass when there is no phosphorus available as

nutrient.

Autotroph CO2 half

saturation

0.1

mmol/L


AOB and NOB organisms when there is little

inorganic carbon available.

Synthesis

anion/cation half

saturation


cations.

Growth and Decay of Nitrite Oxidizing Biomass (NOB):

Table A13: Kinetic parameters for NOB. Please note that those values differ to the ones presented

for AOB bacteria only for the maximum specific growth rate (that is slightly lower for NOB) with

all other values being the same as the ones presented in Table 9


Max. spec. growth

rate 0.7 d-1


nitrite oxidizing biomass. Substrate, nutrient

limitations and environmental conditions will

decrease the growth rate. This parameter has a direct

impact on the nitrification capacity.

Substrate (NO2)


This parameter impacts the residual nitrite

concentration in the effluent. The value is usually

very low in normal municipal plants.

Aerobic decay rate 0.17 d-1 Decay rate constant under aerobic conditions for

nitrite oxidizing biomass.

Anoxic/anaerobic

decay rate 0.08 d-1

Decay rate constant under non-aerobic conditions for

nitrite oxidizing biomass.

KiHNH3 0.075 mmol/L Ammonia inhibition concentration.

80

Table A14: Stoichiometric parameters for NOB


Yield 0.09 mgCOD/mgN NOB COD produced by oxidizing 1 mg of

nitrite N.

N in biomass 0.07 mgN/ mgCOD N content of NOB.

P in biomass 0.022 mgP/ mgCOD P content of NOB.

Fraction going to

endogenous residue 0.08 -

Fraction of biomass that becomes inert upon

decay.

COD:VSS ratio 1.42 mgCOD/mgVSS



value is relatively stable for biomass.

Table A15: Switching functions for NOB (autotrophic biomass)


NOB DO half


This parameter is used to switch off nitrite oxidation

by NOB under low DO conditions.

NH3 nutrient half





P nutrient half



biomass when there is no phosphorus available as

nutrient.

Autotroph CO2 half

saturation 0.1 mmol/L


AOB, NOB and AAO organisms when there is little

inorganic carbon available.

Synthesis

anion/cation half

saturation

0.01 meq/L Half saturation concentration for anions and cations.

81

Growth and Decay of Phosphorus Accumulating Organisms (PAOs):

Table A16: Kinetic parameters for PAO


Max. spec.

growth rate 0.95 d-1

Determines the maximum attainable growth rate of

phosphorus accumulating heterotrophic organisms if

no substrate, DO or P limitation occurs.

Max. spec.

growth rate, P-

limited

0.42 d-1

Determines the maximum attainable growth rate of

phosphorus accumulating heterotrophic organisms

under phosphorus limiting conditions.

Substrate half

saturation 0.1

mg

CODPHB

/ mg

CODPAO

Half saturation constant for PHA, used as substrate

by phosphorus accumulating organisms.

Substrate half

saturation, P-

limited

0.05

mg

CODPHB

/ mg CODPAO

Half saturation constant for PHA, under phosphorus

limiting conditions.

Magnesium half

saturation 0.1 mgMg / L

Half saturation constant for Magnesium storage

during poly-P synthesis.

Cation half

saturation 0.1 meq / L

Half saturation constant for cation (primarily

potassium) storage during poly-P synthesis.

Calcium half

saturation 0.1 mgCa / L

Half saturation constant for Calcium storage during

poly-P synthesis.

Aerobic/anoxic

decay rate 0.1 d-1

Decay rate constant under aerobic or anoxic

conditions.

Aerobic/anoxic

maintenance rate 0 d-1

Maintenance rate constant under aerobic or anoxic

conditions. [Default off]

Anaerobic decay

rate 0.04 d-1 Decay rate constant under anaerobic conditions.

Anaerobic

maintenance rate 0 d-1

Maintenance/polyphosphate cleavage rate constant

under anaerobic conditions. [Default off]

Sequestration

rate 4.5 d-1

Rate constant for VFA sequestration to form PHA

(stored substrate).

Anoxic growth

factor 0.33 -


that are able to grow under anoxic conditions and/or

a reduction in the growth rate under anoxic

conditions. Substrate and nutrient limitations may

further reduce the growth rate.

82

Table A17: Stochiometric parameters for PAOs


Yield (aerobic) 0.63

9 mgCOD/mgCOD

Amount of biomass produced using one unit

of substrate under aerobic conditions. The

rest of the substrate will be oxidized.

Yield (anoxic) 0.52 mgCOD/mgCOD Amount of biomass produced using one unit

of substrate under anoxic conditions.

Aerobic P/PHA

uptake 0.93 mgP/mgCOD

Amount of P stored per unit of PHA oxidized

in aerobic conditions

Anoxic P/PHA

uptake 0.35 mgP/mgCOD

Amount of P stored per unit of PHA in

anoxic conditions.

Yield of PHA on

sequestration

0.88

9 mgCOD/mgCOD

Amount of PHA stored when 1 mg of acetate

or propionate is sequestered.

N in biomass 0.07 mgN/ mgCOD

N content of phosphorus accumulating

organisms. Has a significant effect on

nitrogen availability for nitrification and

therefore oxygen demand.

N in sol. inert 0.07 mgN/ mgCOD

N content of soluble inert organics

originating from phosphorus accumulating

organism decay.

P in biomass 0.02

2 mgP/ mgCOD

P content of phosphorus accumulating

organisms, not including P stored in the form

of Poly-P

Fraction to

endogenous part. 0.25 -

Fraction of biomass that becomes particulate

inert upon decay.

Inert fraction of

endogenous sol. 0.2 -

Fraction of biomass that becomes soluble

inert upon decay.

P/Ac release ratio 0.51 mgP/mgCOD Amount of P released for one mg of acetate

sequestered in the form of PHA




value is relatively stable for biomass.

(Actually this value was already shown in

Table A3)

83

Yield of low PP 0.94 mgP/mgP

Fraction of P stored in releasable poly-P form

(rest of P is stored in high molecular weight,

non-releasable poly-P)

Mg to P mole ratio

in polyphosphate 0.3 molMg/molP

Mole ratio of magnesium to phosphorus in

stored polyphosphate. This magnesium is

released when polyphosphate is used

(together with the phosphate release).

Cation to P mole

ratio in

polyphosphate

0.15 meq/mmolP

Mole ratio of other cations (primarily

potassium) to phosphorus in stored

polyphosphate. These cations are released

when polyphosphate is used (together with

the phosphate release).

Ca to P mole ratio

in polyphosphate 0.05 molCa/molP

Mole ratio of calcium to phosphorus in stored

polyphosphate. This calcium is released

when polyphosphate is used (together with

the phosphate release).

Table A18: pH inhibition for PAOs


PAO low

pH limit 4.0

pH

units

At a pH equal to this value the growth rate of polyphosphate

accumulating biomass will be reduced by 50%.

PAO high

pH limit 10.0

pH

units

At a pH equal to this value the growth rate of polyphosphate

accumulating biomass will be reduced by 50%.

84

Table A19: Switching functions for PAOs


PAO DO half


This constant is used to switch off aerobic

PAO activity under low DO conditions (that is

in anaerobic and anoxic reactors).

Anoxic/anaerobic

NOx half saturation 0.15 mgN/L

This constant is used to turn off anoxic

growth, decay and hydrolysis processes under

conditions of low nitrate and nitrite.

Anoxic NO3

(→NO2) half

saturation

0.1 mgN/L

This constant is used to switch off anoxic

growth processes producing nitrite under low

nitrate conditions.

Anoxic NO3 (→N2)



growth processes using nitrate under low

nitrate conditions.

Anoxic NO2 (→N2)



growth processes using nitrite under low

nitrite conditions.

NH3 nutrient half


This constant is used to slow all biomass

growth processes at low ammonia-N

concentrations (N nutrient limiting conditions)

PolyP half saturation 0.01 mgP/mgCOD

This constant stops sequestration of VFA and

P release as the ratio of low molecular weight

polyphosphate to PAO falls.

VFA sequestration

half saturation 5.0 mgCOD/L

This is the half saturation concentration for

the sequestration of acetate and propionate.

P uptake half


This constant stops growth with

polyphosphate storage at low soluble

phosphate concentrations. This constant will

have an impact on the effluent soluble P

concentration in a bio-P system.

P nutrient half


This constant is used to slow the growth of

biomass when there is no phosphorus

available as nutrient.

Synthesis

anion/cation half

saturation


cations.

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