Preliminary investigations on nitrification coupled to photosynthetic oxygenation

Preliminary investigations on nitrification coupled to

photosynthetic oxygenation

Daniel de Deus Cunha

MSc Thesis ES 10.40 May 2010

UNESCO-IHE

INSTITUTE FOR WATER EDUCATION

NITRIFICATION

Preliminary investigations on nitrification coupled to

photosynthetic oxygenation

Master of Science Thesis by

Daniel de Deus Cunha

Supervisors C. M. Hooijmans, PhD (UNESCO-IHE) P. van der Steen, PhD (UNESCO-IHE) Prof. P. N. Lens, PhD (UNESCO-IHE)

Examination committee C. M. Hooijmans, PhD (UNESCO-IHE) Prof. P. N. Lens, PhD (UNESCO-IHE)

R. Bosma, PhD (Wageningen University)

This research is done for the partial fulfilment of requirements for the Master of Science degree at the

UNESCO-IHE Institute for Water Education, Delft, the Netherlands

Delft

May 2010

The findings, interpretations and conclusions expressed in this study do neither

necessarily reflect the views of the UNESCO-IHE Institute for Water Education, nor of

the individual members of the MSc committee, nor of their respective employers.

Here's the soap that will set you free, cleaning up your visions of reality. And all the

salesmen will agree: surround sound DVD is ecstasy. Life can be sweet with those

candy-bars. Increase your ego with that brand new car. Insure your safety, buy this lie,

and buy and buy and buy and buy. Turn the prism on its side. Through its faces shines

the light. Puncture what illusions hide. Don't be taken for a ride. Fast food burgers

slim your time. Send a present to your Valentine. Get your airmiles travel free. In

September start your Christmas shopping spree. It's in the stars, be a

millionaire. Conquer the world with new underwear. You're so free, you can buy the

lie, and lie and lie and lie and lie. Keep on track with the digital fun. Book in time for

the winter sun. Get a free cell-phone, call all day. The next great prey is on its

way. Turn the prism on its side. Through its faces shines the light. Puncture what

illusions hide. Don't be taken for a ride.

The Ex, Prism song

The ecological crisis in itself, in spite of its extreme gravity, is only a symptom. I hate

the word “environment”. Important things are not around us, but in us. We do not

destroy nature because we hate it: what would this mean? We destroy it because we

hate each other. In a duel, often third innocents, who were only passing by, are hit the

hardest. Destruction of nature and the intestine violence of men feed themselves

mutually (...). “Sustainable development” and “green growth” are slogans for those

who still believe they can solve the squaring of the circle.

Jean-Pierre Dupuy

Freedom can only consist in socialised man, the associated producers, rationally

regulating their interchange with Nature, bringing it under their common control,

instead of being ruled by blind forces; and achieving this with the least expenditure of

energy and under conditions most favourable to, and worthy of, their human nature.

Karl Marx, Das kapital

If the completion of the technological project involves a break with the prevailing

technological rationality, the break in turn depends on the continued existence of the

technical base itself. For it is this base which has rendered possible the satisfaction of

needs and the reduction of toil – it remains the very base of all forms of human freedom.

The qualitative change rather lies in the reconstruction of this base – that is, in its

development with a view of different ends. (...)This does not mean the revival of

“values”, spiritual or other, which are to supplement the scientific and technological

transformation of man and nature. On the contrary, the historical achievement of

science and technology has rendered possible the translation of values into technical

tasks – the materialization of values.

Herbert Marcuse, One-dimensional man

i

Abstract

Nutrient removal in wastewater treatment is dominated by activated sludge.

The activated sludge process needs intensive artificial aeration, what makes

it an energy intensive process in a world that is possibly facing an energy

crisis in the next years.

Photosynthetic oxygenation would be an alternative to achieve nitrification

without artificial aeration. Although research with photobioreactors is not

new, coming at least since the works of William J. Oswald in the 1950’s,

comprehensive analysis of the potentiality for photosynthetic oxygenation

for nitrification are scarce.

This work shows with experiments and mathematical modelling that

nitrification with photosynthetic oxygenation is a promising technology for

wastewater treatment. However, it is shown that nitrification in

photobioreactors is strongly dependent on operational conditions, as

incident irradiance and hydraulic retention time. This is because nitrification

in such systems is subject to stoichiometric and kinetic constraints. A

strategy is developed to overcome this constraints, in order to achieve

controlled nitrification with photosynthetic oxygenation.

This work also discusses conceptually the integration of photobioreactors

for nitrification in wastewater treatment plants, including the problem of

denitrification. Therefore, this thesis provides the first steps towards

wastewater treatment with nitrification coupled to photosynthetic

oxygenation followed by denitrification; more research is needed to confirm,

complement or correct the findings here presented.

Keywords: photobioreactors, nitrification, algae, nitrifiers, modelling

iii

Acknowledgements

Many thanks

to my family and Maria Alejandra Liendo, for understanding;

to my workmates at Ministério Público do Estado do Rio Grande do Sul, especially

Alencar Heidrich, for the support;

to my mentors and supervisor, Tineke Hooijmans, Peter van der Steen and Piet Lens, for

the discussions and advices;

to the laboratory staff (Fred Kruis, Frank Wiegman, Lyzette Robbemont, Peter Heerings,

Ferdi Battes, Don van Galen), for all the help with the laboratory work;

to Carlos Manuel López Vázquez, for kindly borrowing laboratory equipment;

to Mattheus Mimpen, for kindly providing an enriched culture of nitrifiers;

to classmates and friends from all over the world who made my stay in Holland a great

experience.

v

Table of Contents

Abstract .......................................................................................................................... i

Acknowledgements ..................................................................................................... iii

List of symbols ............................................................................................................ ix

1. Introduction .......................................................................................... 1

1.1 Objectives ......................................................................................................... 3

2 Literature review .................................................................................. 4

2.1 Algae-bacteria systems ..................................................................................... 4

2.2 Photobioreactors ............................................................................................... 5

2.3 Harvesting of algae ........................................................................................... 6

2.4 Factors affecting algae growth ......................................................................... 7

2.5 Selection and adaptation of algae and bacteria ................................................. 7

2.6 Nitrification ...................................................................................................... 7

2.7 Models .............................................................................................................. 8

2.8 Controlled nitrification in photobioreactors ..................................................... 8

2.9 Post-treatment of UASB effluents .................................................................... 9

2.10 Denitrification ................................................................................................... 9

3 Methodology ........................................................................................ 11

3.1 Experimental setup and analytical methods ................................................... 11

3.1.1 Experimental setup ................................................................................. 11

3.1.2 Physico-chemical analysis ...................................................................... 12

3.2 Modelling ....................................................................................................... 13

3.2.1 Overview ................................................................................................ 13

3.2.2 Processes and stoichiometry ................................................................... 14

3.2.3 Kinetics ................................................................................................... 15

3.2.4 Limitations of the model ........................................................................ 19

3.2.5 Input parameters and operational strategy .............................................. 21

4 Results .................................................................................................. 26

4.1 Experimental results ....................................................................................... 26

4.1.1 Phase 1: growth of nitrifiers ................................................................... 26

4.1.2 Phase 2: addition of algae and SRT control ........................................... 27

4.1.3 Phase 3: increased SRT .......................................................................... 28

4.1.4 Phase 4: uncontrolled SRT ..................................................................... 29

4.1.5 Phase 5: decreased influent ammonia concentration .............................. 29

4.1.6 Phase 6: increased settling time .............................................................. 30

4.1.7 General observations .............................................................................. 30

4.2 Model results .................................................................................................. 31

4.2.1 Input parameters and initial conditions .................................................. 31

4.2.2 Base results ............................................................................................. 33

4.2.3 Effect of irradiation ................................................................................ 37

4.2.4 Effect of hydraulic retention time (HRT) ............................................... 44

4.2.5 Control of nitrification coupling HRT to incident irradiance ................. 48

4.2.6 Control of nitrification manipulating hydraulic retention time, biomass

retention time and irradiation ................................................................................. 50

4.2.7 Effect of C/N ratio .................................................................................. 51

vi

4.2.8 Effect of reactor width ............................................................................ 53

4.2.9 The role of alkalinity .............................................................................. 54

4.2.10 Treatment of sewage with higher substrate content ............................... 56

4.2.11 Denitrification ......................................................................................... 57

5 Discussion ............................................................................................ 58

5.1 Experiments .................................................................................................... 58

5.2 Modelling ....................................................................................................... 58

5.3 Integration of experimental and model results ............................................... 61

5.4 Enclosed photobioreactors in wastewater treatment plants ............................ 61

6 Main conclusions and suggestions for further research ................. 66

References .................................................................................................. 67

7 Appendix: AQUASIM file ................................................................. 73

vii

List of tables

Table 1: medium composition ........................................................................................ 11

Table 2: trace element solution composition .................................................................. 11

Table 3: stoichiometry table of the model ...................................................................... 18

Table 4: rate equations of the model .............................................................................. 21

Table 5: kinetic comparison of microorganisms ............................................................ 22

Table 6: parameters of the model ................................................................................... 23

Table 7: Sewage as characterized in Nieuwe Waterweg, The Netherlands (Roeleveld

and van Loodsdrecht, 2002) ........................................................................................... 31

Table 8: Input parameters and initial conditions ............................................................ 32

Table 9: distribution of nitrogen in the effluent ............................................................. 37

Table 10: nitrogen in liquid phase .................................................................................. 37

Table 11: steps applied on irradiance (increasing irradiance) ........................................ 38

Table 12: steps applied on irradiance (decreasing irradiance) ....................................... 41

Table 13: steps applied on HRT (decreasing HRT) ....................................................... 44

Table 14: steps applied on HRT (increasing HRT) ........................................................ 46

Table 15: series of steps using optimal combinations of irradiance and HRT ............... 49

Table 16: series of steps using optimal combinations of irradiance, HRT and recycled

biomass ........................................................................................................................... 50

Table 17: ......................................................................................................................... 53

Table 18: Sewage as characterized in Nieuwgraaf, The Netherlands (Roeleveld and van

Loodsdrecht, 2002) ......................................................................................................... 56

Table 19: stoichiometric potential of sewage to denitrification, according to sewage

characterization by Roeleveld and van Loodsdrecht (2002) .......................................... 63

List of figures

Figure 1: algal bacterial symbiosis in sewage treatment (source: Oswald & Gotaas 1955)

.......................................................................................................................................... 1 Figure 2: algal bacterial symbiosis in sewage treatment (adapted from Oswald & Gotaas

1955) ................................................................................................................................. 2 Figure 3: simplified diagram of the model, showing main growth processes ................ 14 Figure 4: ammoium nitrogen concentration during in effluent in nitrifiers culture during

Phase 1 ............................................................................................................................ 26 Figure 5: concentration of nitrogen species in the medium during one cycle in Phase 1

........................................................................................................................................ 27

Figure 6: nitrate and ammonium nitrogen concentrations in the effluent during Phase 2

........................................................................................................................................ 28 Figure 7: dissolved oxygen in medium and transmitted light intensity through the

reactor during Phase 2 .................................................................................................... 28 Figure 8: nitrate and ammonia nitrogen in effluent and transmitted light intensity during

Phase 3 ............................................................................................................................ 29

Figure 9: nitrate nitrogen in effluent and transmitted light intensity during Phase 4 ..... 29 Figure 10: transmitted light intensity through the reactor during Phase 5 ..................... 30 Figure 11: nitrogen species in effluent and transmitted light intensity during Phase 6.. 30 Figure 12: layer of biomass that was on top of the magnetic stirrer fell upside down,

showing two distinct layers ............................................................................................ 31

viii

Figure 13: layer of biomass rolled over itself, showing two distinct layers (green on top,

brownish-grey on bottom). ............................................................................................. 31 Figure 14: biomass in the reactor ................................................................................... 34

Figure 15: nutritional limitation for algae ...................................................................... 34 Figure 16: nutritional limitation for heterotrophs ........................................................... 35 Figure 17: nutritional limitation for nitrifiers ................................................................. 35 Figure 18: growth rate of nitrifiers ................................................................................. 36 Figure 19: oxygen concentration in the reactor .............................................................. 36

Figure 20: main nitrogen forms in the effluent............................................................... 37 Figure 21: nitrate concentration in the effluent with a series of steps in irradiance ....... 39 Figure 22: carbon dioxide concentration in reactor ........................................................ 39 Figure 23: nutritional limitation for nitrifiers with a series of steps in irradiance.......... 40 Figure 24: nutritional limitation for algae with a series of steps in irradiance ............... 40

Figure 25: biomass in reactor with a series of steps in irradiance .................................. 41

Figure 26: nitrate concentration in the effluent with a series of steps in irradiance ....... 42 Figure 27: oxygen concentratio in reactor ...................................................................... 42

Figure 28: nutritional limitation for nitrifiers with a series of steps in irradiance.......... 43 Figure 29: nutritional limitation for heterotrophs with a series of steps in irradiance ... 43 Figure 30: biomass in reactor with a series of steps in irradiance .................................. 44

Figure 31: nitrate concentration in the effluent with a series of steps applied on HRT . 45 Figure 32: nutritional limitation for nitrifiers with a series of steps on HRT ................. 45 Figure 33: nutritional limitation for heterotrophs with a series of steps on HRT .......... 46

Figure 34: biomass in reactor with a series of steps on HRT ......................................... 46 Figure 35: nitrate concentration in the effluent with a series of steps applied on HRT . 47

Figure 36: nutritional limitation for nitrifiers with a series of steps on HRT ................. 47 Figure 37: nutritional limitation for algae with a series of steps on HRT ...................... 48 Figure 38: biomass in reactor with a series of steps on HRT ......................................... 48

Figure 39: nitrate in effluent with a series of steps in irradiance and HRT .................... 49

Figure 40: nutritional limitation for nitrifiers with a series of steps in irradiance and

HRT ................................................................................................................................ 50 Figure 41: control of nitrification with different combinations of irradiance, HRT and

SRT ................................................................................................................................. 51

Figure 42 ......................................................................................................................... 52 Figure 43: nitrogen in the effluent with high organic content wastewater ..................... 52 Figure 44: nutrient limitation for nitrifiers with high organic content wastewater ........ 53 Figure 45 ......................................................................................................................... 54 Figure 46: ........................................................................................................................ 55

Figure 47: ........................................................................................................................ 55 Figure 48: ........................................................................................................................ 56 Figure 49: nitrogen forms in the effluent with wastewater with high organic content .. 57

Figure 50: optimized hydraulic and sludge retention time for photobioreactor

(nitrification of around 60% of influent NH3-N) with 10 cm of width and other

parameters described in tables 6 and 7 ........................................................................... 59 Figure 51: optimized hydraulic and sludge retention time for photobioreactor

(nitrification of around 65% of influent NH3-N, slightly decreasing as HRT decreases)

with data based on tables 6, 7 and 14 ............................................................................. 60 Figure 52: photobioreactor for sewage treatment ........................................................... 62 Figure 53: photobioreactor for post-treatment of UASB effluents ................................ 64

ix

List of symbols

Daniel de Deus Cunha 1

1. Introduction

Activated sludge is a well established method of wastewater treatment especially in case

of nutrient removal. It is a mature technology, with numerous and reliable models

available. How efficient it may be, it might not be up to the challenges of our times: it is

an energy intensive process in an energy scarce world.

William J. Oswald and his co-workers (Oswald et al 1953) proposed the concept of

“photosynthetic oxygenation”, that is, the use of algae to provide the oxygen needed for

natural biodegradation of organic matter, in an algal-bacterial symbiosis, so that

artificial aeration and the related energy consumption would be unnecessary (Fig. 1).

Oswald later expanded his concept to close the nutrient cycle: algae grown in

wastewater treatment plants should be harvested and used as animal feed (Oswald 1995).

The result would be a basically solar-driven technology that in one system treats

wastewaters and recovers nutrients.

Figure 1: algal bacterial symbiosis in sewage treatment (source: Oswald & Gotaas 1955)

Quite surprisingly, the system was already proposed in 1953, during the hey-days of

fordism, mass production and unconcerned energy and natural resources consumption.

Maybe it was ahead of its time, and activated sludge overwhelmingly dominated the

scene of wastewater nutrient removal during the whole of the 20th century (Wanner

1994).

The first attempts of photosynthetic oxygenation were carried out in open

photobioreactors, or high-rate algal ponds. Today there are relatively few of these in

operation. Oswald himself tried unsuccessfully to develop an enclosed photobioreactor

– called “symbiocon” (Oswald et al 1953). Nowadays they are a reality not only in

laboratory, but also in full scale. These reactors, however, are designed for the mass

production of algae in itself (not related to wastewater treatment). A renovated interest

in photosynthetic oxygenation in enclosed photobioreactors for wastewater treatment

arouse recently, but always focusing on algae mass production, harvesting and recycling.

2 MSc thesis

Although assimilation by algae is certainly the most sustainable approach, considering

that synthetic nitrogen fertilizers are derived from fossil fuels, using the Haber-Bosch

process (Pierzinsky et al 2005), there are some reasons for a different approach, namely,

to nitrify the nitrogen, instead of let it be assimilated by algae (although a certain extent

of assimilation is unavoidable). Harvesting of algae is still costly and might become an

operational burden; the application of biomass far away from where it is harvested

could cause more environmental impacts than the environmental benefits brought by

nutrients recycling (due to transportation emissions, etc.); and the large scale application

of the integrated approach requires an also integrated community planning which,

unfortunately, is not yet a reality.

In between the main line of nutrient removal from wastewater – activated sludge – and

the alternative proposed by Oswald – photosynthetic oxygenation with massive algae

harvesting – opens up a field of research to a great extent unexplored: the use of

photosynthetic oxygenation for nitrification (Fig. 2).

Figure 2: algal bacterial symbiosis in sewage treatment (adapted from Oswald & Gotaas 1955)

Artificial aeration accounts for 45 to 75% of the energy consumption in wastewater

treatment plants (Stenstrom and Rosso 2008). Considering that we are possibly facing

an energy crisis in the next years due to the depletion of oil reserves (Tsoskounoglou et

al 2008, Hall et al 2008, Kjärstad and Johnsson 2009), the development of alternative

technologies that save energy have an important social role. The potentiality of

technology reconfiguration as means and end of social change cannot be overestimated.

Illich argues that above a certain threshold of per capita energy consumption it is

impossible to have an egalitarian society (Illich 1974); Marcuse claims that technology

embeds values, and that an effective social change is dependent on the "materialization

of values", i. e., the "translation of values into technical tasks", (Marcuse 1964). This

work deals with the technical task of investigating the feasibility of nitrification with

photosynthetic oxygenation.

NITRIFICATION


1.1 Objectives

The goal of this research is to carry out preliminary investigations on the feasibility of

nitrification coupled to algae photosynthetic oxygenation in wastewater treatment. To

achieve this goal, the following resources will be used:

a) experiments: experimental work will be carried out trying to demonstrate the

possibility of coexistence of algae, heterotrophs and nitrifiers in a stirred reactor,

in steady state;

b) modelling: a mathematical model will be developed, trying to demonstrate the

feasibility, key factors and best operational conditions for nitrification in

enclosed photobioreactors;

c) conceptual process analysis: making use of characteristics of wastewaters,

different treatment systems and simple stoichiometric calculations, the use of

enclosed photobioreactors for nitrification will be contextualized, in order to

explore its potential uses, including denitrification and post-treatment of UASB

effluents.

4 MSc thesis

2 Literature review

This literature review will outline the main subjects covered in this work, covering

general aspects on algae-bacteria systems, photobioreactors and nitrification as well as

modelling and specific issues that should be considered when planning the potential role

of enclosed photobioreactors in wastewater treatment plants, i. e., denitrification, post-

treatment of UASB effluents and harvesting of algae.

2.1 Algae-bacteria systems

“Photosynthetic oxygenation” was proposed in the fifties by Oswald et al (1953). It was

realized that two phases were identifiable in an oxidation pond treating sewage: a first

bacterial phase where bacteria decompose organic matter, depleting dissolved oxygen

and generating, among other species, ammonia and carbon dioxide, part of it escaping to

the atmosphere; and a second phase where algae promote photosynthetic oxygenation,

taking up, among other species, carbon dioxide and nitrogen, possibly resulting in

supersaturation of dissolved oxygen and consequent emission to the atmosphere. The

two phases are subsequent in time and space, occurring in different sections in the pond.

The authors point out that the efficiency of this system is very low; both oxygen and

carbon are wasted. They propose then the “integration of bacterial and algal phases”,

that is an “algal bacterial symbiosis”, where algae uses the products of bacterial activity

as nutrients (carbon dioxide, nitrogen) and bacteria uses the products of algal activity

(oxygen). These authors performed experiments in closed and open continuous systems

with algal-bacterial symbiosis (Oswald et al 1953). Closed systems – called

“symbiocon” – were found extremely difficult to obtain a dynamic equilibrium. In open

systems, equilibrium was readily obtained, and the authors identified as main variables

affecting the symbiosis the retention period, sewage strength, light intensity and

periodicity, temperature and the bacterial and algae species and activity. The same

authors (Oswald et al 1953b) also studied the growth of Chlorella in sewage and found

that in continuous cultures, with varying retention time, there is a maximum in yield

(productivity) that correspond to a relatively low cell density. It was also found that

varying retention times, i.e., varying the age of cells, their morphology and physiology

changes. Based on these previous studies, the basic design parameters of high-rate algal

ponds were established (Oswald & Gotaas 1955).

It has been proposed that algae ponds could be used to close the nutrient cycle, i.e., that

algae should be harvested and used either as fertilizer or animal food. That would

configure a solar-driven sustainable system of “controlled photosynthesis”, integrating

wastewater treatment and nutrient recovery, suitable for times facing superpopulation

and food insecurity; under this paradigm the goal would be to produce as much algae as

possible under the given conditions (Oswald & Gotaas 1955; Oswald 1962; Oswald

1995; Oswald 2003). Another alternative is the use of algae biomass for anaerobic

energy production (Muñoz & Guieysse 2006).

McGriff Jr. and McKinney (1972) describe an open system of algal-bacterial symbiosis

in which the MLSS (mixed-liquor suspended solids) could be controlled, that, in

analogy with the activated sludge process, is called “activated algae”. These authors


showed that removal efficiencies of a system like this could reach 97% of BOD, 87%

COD, 92% nitrogen and 74% phosphorous. Nitrification was detected, but in very low

levels; it should be noted then that most of the nitrogen removal was represented by

algal uptake. More recently the interest in photobioreactors as a means of algae

production has increased. Many configurations of enclosed photobioreactors have been

proposed and or developed. Concerning the biomass physical distribution, three basic

configurations can be identified: suspended growth (Muñoz and Guieysse 2006),

immobilized microalgae (Moreno-Garrido 2008; Mallick 2008) and biofilm systems

(Muñoz et al 2009).

2.2 Photobioreactors

Several recent studies show the applicability of photobioreactors for wastewater

treatment, and specifically for nitrogen removal, under their specific configurations and

operating conditions. Nitrogen removal by Chlorella pyreneidosa and Scenedesmus sp.

in consortia with heterotrophs was shown by Tam & Young (1989). Aziz & Ng (1992)

showed removals above 60% of ammonium nitrogen in activated algae systems treating

domestic sewage, and pretreated piggery and oil mill wastewater; Muñoz et al (2003)

were able to promote the degradation of sodium salycilate using a consortium of

Chlorella sorokiniana and Ralstonia brasiliensis, and established the dependence of

biodegradation on microalgal concentration, light intensity and temperature. Gutzeit et

al (2005) showed that in a sequencing batch reactor it is possible to develop a

bioflocculent algal-bacterial biomass and were able to use the system to treat synthetic

wastewater. Muñoz et al (2005) successfully used an algal-bacterial consortium for

combined carbon and nitrogen removal from acetonitrile, and reported nitrification of

12% of the theoretically produced ammonium nitrogen. Muñoz et al (2005) achieved

33% of nitrogen removal in a pilot scale symbiotic consortium degrading acetonitrile.

Essam et al (2006) used an experimental design having as parameters the presence of

algae, bacteria, light and carbon source (phenol) to show the effectiveness of the algal-

bacterial symbiosis, which was able to degrade phenol from coke factory wastewater

after detoxification. Using a tubular biofilm photobioreactor, González et al (2008)

showed an efficient nutrient removal from swine manure using an algae-bacteria

consortium. The consortia consisted of Chlorella sorokiniana and a mixed bacterial

culture from an activated sludge process. The authors report 82% of ammonium-

nitrogen assimilated and 13% nitrified. Godos et al (2009a) again showed simultaneous

nutrients and carbon removal from pretreated slurry in a tubular biofilm photobioreactor.

Depending on the wastewater load, nitrifications of 7, 23 and 8% were reported.

Additionally, denitrification was reported with a high wastewater load.

Nitrification was also reported in open photobioreactors, or high-rate algal ponds

(HRAP) (Evans et al 2005; Godos et al 2009; Barthel et al 2008; Ip et al 1982, Cromar

et al 1997). The percentage of nitrogen converted to nitrate in HRAP was independent

of the loading rate and improved with retention time, and it was suggested that it is due

to the low growth rate of nitrifying bacteria, especially Nitrosomonas sp; nitrification

was also favored by lower C:N:P ratios (Cromar & Fallowfield 1997). In HRAP’s

treating piggery wastewater with varying dilutions, up to 86% of TKN was removed via

nitrification, and denitrification was also reported (Godos et al 2009b). In experiments

with HRAP’s specifically designed to evaluate nitrification and denitrification, it was

shown that the percentage of nitrification presents a maximum as COD loading rate

6 MSc thesis

varies, and that at high COD loading rates nitrification may be limited by lack of

oxygen; varying retention time and depth also influenced results (Evans et al 2005).

However, nitrification in open photobioreactors is not a rule (Craggs 2005; El Hafiane

et al 2003); it has been observed in the treatment of high strength wastewaters (Craggs

2005) and appears to occur seasonally in temperate climates, especially in the winter,

when due to decreased algal productivity there is less ammonia nitrogen assimilation by

algae and reduced ammonia volatilization because of lower pH (Pearson 2005). Higher

light intensity in the summer may also be a factor, as nitrifying bacteria are sensible to

sunlight (Pearson 2005). It is important to realize that open photobioreactors such as

HRAP’s have important differences when compared to closed photobioreactors (that is,

closed to the atmosphere and possibly with pure algal cultures), such as the occurrence

of ammonia volatilization (Craggs 2005) or changing composition of algae population

(Godos et al 2009b).

2.3 Harvesting of algae

In the suspended growth activated algae configuration, special attention should be given

to harvesting, as it is necessary to ensure good effluent quality and prevent cell washout

(Muñoz & Guieysse 2006). Common industrial approaches of filtration, centrifugation,

microstraining, etc. are not economical and therefore not suitable for large-scale

microalgae removal (Muñoz & Guieysse 2006). Flocculation followed by gravity

sedimentation is the most common harvesting technique, but this approach is not always

efficient, especially in the case of small and rapidly growing Chlorella or Scenedesmus

sp. (Muñoz & Guieysse 2006). Multicellular cyanobacteria of the genus Spirulina or the

self-aggregating Phormidium have been applied (Muñoz & Guieysse 2006), and in

high-rate algal ponds (HRAP’s) mixing promotes the growth of non-motile colonial

microalgal species such as Scenedesmus and Micractinium, which unlike free

swimming algae like Chlorella produce extracellular polymers and flocculate and

therefore are more easily settled (Craggs 2005; Pearson 2005). The selection of settling

algae-bacteria aggregates of Chlorella and wastewater bacteria was achieved making

use of an SBR reactor with continuous discharge of the supernatant, resulting in

bioflocs with good settling characteristics after four weeks of operation (Gutzeit et al

2005). The addition of chemical flocculants (alum, lime or polyferric sulfate) is efficient

and reliable but still expensive (Muñoz & Guieysse 2006). Some commercial

flocculants as Zetag 63 and CF 400 may also be efficient (Buelna et al 1990); on the

other hand, anionic and non-ionic polymer seems to be ineffective for algal-bacterial

flocculation (Tilton et al 1972). Chitosan, on the other hand, is biodegradable and cheap

and can be used for algae harvesting (Muñoz & Guieysse 2006, Divakaran 2002,

Lertsutthiwong et al 2009, Morales et al 1985, Lubián 1989, Buelna et al 1990), but the

flocculation efficiency is highly dependent on pH (Divakaran 2002, Lertsutthiwong et al

2009, Morales et al 1985, Lubián 1989). A method involving pH adjustment between

10 and 10.6 plus addition of flocculant was also proposed for marine algae (Knuckey et

al 2006). Other methods of harvesting have been proposed, as those making use of

ultrasound (Bosma et al 2003), which has the advantage of, being a physical process, to

not interfere in chemical and biological properties of the cultivated media, and

electrolytic flocculation (Poelman et al 1997; Alfafara et al 2002), the latter with

production of oxygen in the process of electrolysis.


2.4 Factors affecting algae growth

Several factors affect algae growth. In high-rate oxidation ponds (open photobioreactors)

they can be classified in abiotic, biotic and operational (Borowitzka 1998). Abiotic

factors are light (quality and quantity), temperature, nutrient concentration (especially

nitrogen, phosphorous and organic carbon), oxygen and carbon dioxide, pH, salinity,

toxic chemical. Biotic factors are pathogens (bacteria, fungi, viruses), predation by

zooplankton, competition. Operational factors are mixing, dilution rate, depth, addition

of bicarbonate and harvest frequency (Borowitzka 1998). Cell concentration also plays a

prominent role (Richmond 2004). In both open and enclosed photobioreactors algae

productivity reaches a maximum in a specific population density, above or below

which productivity decreases (Borowitzka 1998; Richmond 2004); this is valid also for

algae grown in sewage (Oswald et al 1953b). It was reported that salicylate

decomposition by an algal-bacterial consortium in an enclosed photobioreactor

increased 44% when biomass concentration increased from 0.4 to 0.6 gL-1, but

decreased 15% when biomass increased further from 0.6 to 1.3 gL-1. This phenomena

might be caused by self-shading and dark-respiration by algae (Muñoz et al 2006), but

algae aging may also be an explanation (Oswald et al 1953b). Algae have to capacity to

adjust its chlorophyll content according to the irradiance, a process called

photoadaptation. The process encompasses a fast (seconds) and a slow (hours)

dynamics (Kmet et al 1993). Photoadaptation (or photoacclimation) can manifest itself

through changes in cell morphology, changes in pigment content and changes in the PI

(photosynthesis-irradiance) curve (Zonneveld 1998).

2.5 Selection and adaptation of algae and bacteria

The microbial selection for the photobioreactors is determined by several parameters.

Microalgae have to be tolerant to the pollutant to be treated (Muñoz & Guieysse 2006).

It has been reported that algae are sensitive to a high ammonia concentration

(reference!). Microbial interactions have to evaluated, as algae-bacterial relationship

may not only be one of symbiosis but also of competition (Muñoz & Guieysse 2006).

Microbial growth rates can influence in the final performance of the photobioreactor, as

microalgae generally grow at slower rates than heterotrophic bacteria; therefore, in these

systems pollutant removal is often limited by oxygen production by algae (Muñoz &

Guieysse 2006); however, carbon limitation was also reported. Microalgae

predominance in principle should not be a problem in enclosed photobioreactors

(Muñoz & Guieysse 2006). Inoculation can be done with raw sewage or activated

sludge, allowing co-selection and compatibility of bacteria and algae; isolation with

specific strains is also possible (for easier harvesting, for example), but in this case

interaction effects and stability should be carefully investigated (Muñoz & Guieysse

2006).

2.6 Nitrification

Nitrification is the process whereby free and saline ammonia is oxidized to nitrite and

nitrate. Nitrifying bacteria are chemoautotrophic, using carbon dioxide as carbon source

and the oxidation of ammonium nitrogen as energy source (Ekama and Wentzel, 2008).

8 MSc thesis

Stoichiometrically, 4.6 miligrams of oxygen are necessary per miligram of ammonia

nitrogen oxidized (Ekama & Wentzel, 2008; Bitton 2005), or 4.3 miligrams of oxygen if

ammonia used for cell synthesis is considered (Ekama & Wentzel, 2008). The

nitrification process is influenced by several factors: the magnitude of the specific

growth rate of nitrifiers, as it is dependent on the wastewater; temperature; unaerated

zones in the reaction media, because nitrifiers are obligate aerobes; dissolved oxygen

concentration; cyclic flow and load conditions; pH, because the maximum specific

growth rate of nitrifiers is strongly suppressed when pH is outside the 7 to 8 range

(Ekama & Wentzel, 2008); ammonia and nitrite concentration, as growth of nitrifiers

follow Monod’s kinetics; and BOD5/TKN ratio, as the fraction of nitrifiers decreases

when the BOD5/TKN ratio increases (Bitton 2005). According to the present literature

review, experimental works focused on nitrification in enclosed photobioreactors have

never been published.

2.7 Models

Models for photobioreactors are not abundant. A dynamic mechanistic model for HRAP

was proposed, but it does not account for light limitation and neither nitrification (Buhr

& Miller). Another model for HRAP was proposed based on River Water Quality

Model 1 (RWQM1), this time accounting for nitrifiers growth. For biofilm

photobioreactor the dynamic mechanistic PHOBIA model was developed which

includes nitrification (Wanner & Reichert 1995; Wolf et al 2007). A mechanistic

stationary model was developed in the case of decomposition of toxic pollutant in an

enclosed photobioreactor, not taking nitrification into account (Bordel et al 2009). Other

models aim at predicting algal productivity based on optical parameters (Eilers &

Peeters 1988; Kroon et al 1989). Artificial neural networks were also used to model a

continuous stirred tank photobioreactor (Arranz et al 2008). For nitrification, the most

widely accepted model is the activated sludge model (ASM), in its several versions

(Henze et al, 2000), on which the previously cited PHOBIA model was based for

nitrifiers and heterotrophs stoichiometry and kinetics.

2.8 Controlled nitrification in photobioreactors

Several authors reported the occurrence of nitrification in photobioreactors (section 2.2).

However, works on the best conditions for nitrification are scarce. Abeliovitch (1985),

using an irradiated chemostat inoculated with oxidation pond effluent, showed

experimentally that nitrification varies with the hydraulic retention time. Evans et al

(2005) showed that in pilot high-rate algal ponds (open photobioreactors) hydraulic

retention time, depth of the pond, loading rate and oxygen availability influenced the

extent of nitrification. Finally, using the PHOBIA model for biofilm photobioreactors,

Wolf et al (2007) found that nitrifiers growth was insignificant due to competition for

inorganic carbon with algae (CO2 limitation).


2.9 Post-treatment of UASB effluents

UASB reactor is an efficient process for the removal of organic material and suspended

solids from sewage, depending on the temperature. However, it has little effect on the

concentration of macronutrients (nitrogen and phosphorous) and pathogens (van

Haandel and Lettinga, 1994). Therefore, post-treatment of UASB effluents is necessary.

Among the post-treatment methods used are stabilisation ponds, activated sludge,

rotating biological contactors, submerged aerated filters, trickling filters, wetlands,

dissolved air flotation (van Haandel and Lettinga 1994, Foresti et al 2006).

2.10 Denitrification

Denitrification is normally done with readily biodegradable organic substrate as electron

donor (Ekama and Wentzel 2008). More recently, it has been proposed that methane can

be used for denitrification (Modin et al 2007; Raghoebarsing et al 2006; Thalasso et al

1997; Islas-Lima et al 2004; Costa et al 2000). Denitrification using methane could be

anaerobic or aerobic. In the aerobic process, methanotrophs oxidise methane, producing

organic substrate as by-product, that in its turn is assimilated by heterotrophs for

denitrification. In anaerobic denitrification with methane, methane is used directly as

electron donor (Modin et al 2007). A microbial consortium culture that couples

anaerobic methane oxidation to denitrification was recently enriched (Raghoebarsing et

al 2006). However, the growth rate of this microbial consortium is very slow (Modin et

al 2007). Denitrification using methane could be useful in the case of post-treatment of

anaerobic reactors (Foresti et al 2006). It has been reported that oxidation of methane

occurs preferentially over ammonium oxidation in an aerobic environment (Hatamoto et

al 2010).

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3 Methodology

3.1 Experimental setup and analytical methods

3.1.1 Experimental setup

A reactor, cylindrical in shape, with transparent glass walls and open to the atmosphere,

with a volume of 1 liter, was operated as a sequencing batch reactor (SBR), with 50%

dilution and cycle time of 24 hours. The cycle was comprised of 1.5 hours of settling

time (except for the last experiment, when settling time was increased to 5 hours), 20

minutes for effluent withdrawal and 5 minutes for reactor filling, and the remaining

time for reaction. pH was controlled and kept between 7.0 and 8.0, and temperature was

kept at 30oC +/-2. The composition of the medium was according to tables 1 and 2,

except for Phase 6 of the experiment, when ammonium nitrate was reduced from 400 to

50 mg/L, all other species reduced proportionally. The liquid phase was constantly

aerated and stirred. When reactor contained algae, it was continuously illuminated (no

light-dark cycles) with a lamp Philips E27 ES, positioned 0.5 cm from the reactor wall.

The light intesity at this distance was measured as 700 μEm-2s-1. Samples were filtered

with GF/C filters and, when necessary, stored on the fridge (maximum 4 ºC) prior to

analysis. When biomass retention time was controlled, a fixed fraction of the media was

withdrawn in suspension (stirrer turned on). Here the biomass was settled and the

remaining medium volume was withdrawn, up to 50% of the total reactor volume.

Table 1: medium composition

Species Medium concentration

(mg/L)

(NH4)2SO4 1891.7

KH2PO4 33.3

MgSO4.7H2O 33.3

CaCl2.2H2O 50

FeSO4.7H2O 4.17

Trace element sol. 0.33 (mL/L)

Yeast extract 0.33

Table 2: trace element solution composition

Species Concentration

(mg/L)

EDTA 15

ZnSO4.7H2O 0.43

CoCl2.6H2O 0.24

MnCl2.4H2O 1

CuSO4.5H2O 0.25

(NH4)6Mo7O24.4H2O 0.22

NiCl2.6H2O 0.2

H3BO3 0.15

KI 0.18

12 MSc thesis

The biomass inoculated consisted in an enriched culture of nitrifiers provided by

Kluyver Laboratory at TU Delft and the algae used was Scenedesmus sp., cultured at

UNESCO-IHE laboratory.

3.1.2 Physico-chemical analysis

3.1.2.1 Ammonia nitrogen

The ammonia nitrogen analysis was performed following the spectroscopic method

according to NEN 6472. Salicylate and dichloroisocyanurate reagents were previously

prepared. Salicylate reagent was prepared dissolving 130 g of sodiumsalicylate and 130

g sodiumcitrateehydrat and 0.970 g disodiumpentacyano in 1,000 L deminralyzed water.

Dichloroisocyanurate reagent was prepared dissolving 32.0 g of NaOH in 500 ml of

demineralized water. After cooling down to room temperature, 2.00 g of

sodiumdichloroisocyanurete was added, and volume was completed to 1000 mL.

Standard NH4 was prepared with 10 gN per mL. A calibration curve was built with

several volumes of standard solution added to 4 mL of each reagent, in flasks of 50 mL

completed with demineralized water. Absorbance was measured in spectrophotometer at

655 nm beween 1 and 3 hours after preparation of solutions.

3.1.2.2 Nitrate nitrogen

Nitrate nitrogen was determined via ion cromatography. The equipment used was a

Dionex ICS-1000.

3.1.2.3 Chlorophyll-a

Chlorophyll-a was determined according to NEN 6520. Samples were filtered with GF6

filter. The filter was transferred to Schott GL 18 COD tubes with 25 mL of 80% ethanol.

Chlorophyll was extracted in water at 75oC for 5 minutes with agitation. Tubes were

then cooled in ice and centrifuged for 10 minutes at 3000 rpm. Absorbance was

measured at 750 nm (E0) and 665 nm (Ex) against 80% ethanol. 0.10 mL HCl was added

to 10.0 mL extract and after 30 minutes absorption was measured again at 750 nm (E0a)

and 665 nm (Exa). The chlorophyll-a content was determined according to the

expressions:

pV

EEVaChl

EEE

EEE

an

axaa

xn

0

1

0

0

296

where the number 296 is a correction factor based on specific absorption coefficient of

Chl-a, V1 is the volume of 80% ethanol added to the filter with algae (in mL), V0 is the

sample volume which is filtered (in L) and p is the path length of the cuvette (in mm).


3.1.2.4 Light intensity

Light intensity was used as indirect fast measurement of biomass. With light source and

stirrer turned on, a photometer LI-COR model LI-250A was positioned directly pointing

to the light source, on the opposite side of the reactor, touching its wall, so that it detects

the photosynthetically active radiation (PAR) that is transmitted through the reactor

(including light reflected on its walls). Therefore, an increased light intensity

measurement means that a decreased biomass is present inside the reactor.

3.1.2.5 Dissolved oxygen

A sensor WTW Oxi 340 was positioned inside of the stirred medium in the reactor.

3.2 Modelling

3.2.1 Overview

The model presented here is not meant to represent the experimental setup previously

described, as it has a different hydraulic regime, different geometry of the reactor and

different influent characteristics. It was based on three existing models: ASM1, for

nitrifiers and heterotrophs kinetics and stoichiometry, PHOBIA for algae stoichiometry

and kinetics (except light limitation) and the algae light limitation model proposed by

Molina Grima et al (1999). The main assumptions of the model are:

Reactor is continously stirred, with ideal mixing.

Reactor is enclosed (no gaseous exchange with atmosphere).

Reactor is constantly irradiated (no light-dark cycles).

Reactor can be considered either as a flat plate with orthogonally oriented

spatially uniform irradiation, or cylindrically shaped, in which an external

cylinder containing the reaction medium and an internal cylinder containing a

linear light source. Both configurations allow for the same mathematical

modelling of light intensity in the reactor.

Constant temperature (25oC).

Constant pH (neutral).

No accumulation of nitrite.

Light is considered to be qualitatively uniform and adequate to algae growth (no

spectral variability in space or time).

The model was implemented in AQUASIM software. A simplified diagram of the main

growth processes involved is presented in Fig. 3.

14 MSc thesis

Figure 3: simplified diagram of the model, showing main growth processes

3.2.2 Processes and stoichiometry

The model includes the following processes:

Algae growth on carbon dioxide and ammonia

Algae growth on carbon dioxide and nitrate

Heterotrophs growth

Nitrifiers growth

Algae decay

Heterotrophs decay

Nitrifiers decay

Denitrification (heterotrophs anoxic growth on nitrate)

Carbon dioxide/bicarbonate equilibrium

The stoichiometry used was adapted from PHOBIA model (Wolf et al 2007), which in

its turn, for heterotrophs and nitrifers processes, is based on ASM1, and is shown in

Table 3. From the PHOBIA stoichiometry table the processes of algae growth on

bicarbonate and nitrate, algae growth on bicarbonate and ammonia, algae respiration,

and extra-cellular polymeric substances hydrolysis were removed, as they were not

considered relevant in a suspended growth model; and, for algae growth processes, the

mass of internal polyglucose and extra-cellular polymeric substances were considered to

be zero, as in this model dark respiration and biofilm formation are not considered.


3.2.3 Kinetics

An overview of kinetic expressions is given on Table 4. The following sections clarify

some relevant aspects of the kinetic modelling.

3.2.3.1 Growth rates

Growth rates of microorganisms assume the form described by Wolf et al (2007):

ji ffff ,...,,,min 321max,

where max,i is the maximum growth rate, i are the species (algae, heterotrophs, nitrifiers)

and f are the limitation terms for the nutrients. As stated in the equation, the growth rate

will be determined by and only by the most limiting nutrient. Limitation terms, with the

exception of light, assume a Monod type:

jij

j

jKS

Sf

where Kji is the half-saturation constant for a given nutrient and microorganism.

The uptake (or release) of chemical species (oxygen, ammonia, carbon dioxide, nitrate)

by microorganisms is thus expressed as

iijiij XYUptake

where Yij is the stoichiometric yield of microorganism i for the chemical species j in a

given biological process and Xi is the biomass of species i.

3.2.3.2 Light limitation

The modelling of light limitation is dependent on the shape of the reactor. Unlike

chemical species, light cannot be “mixed”, so that there is a gradient of irradiance along

the irradiation path through the cells, with a certain light extinction coefficient. The

approach of the model is the following:

choose a specific shape for the reactor

calculate light gradient using the Beer-Lambert expression, considering

unidimensional light flux (no scattering, etc.)

calculate the average irradiance on the reactor and consider this average as the

“well mixed irradiance”, i. e., that the whole reactor is irradiated uniformly by

this irradiance

The shape of the reactor was chosen considering simplification of the mathematical

formulation: a flat-plate. Alternatively, it can be considered as an internally illuminated

photobioreactor, with an internal cylinder where a linear light source is located and an

external cylinder where the biomass and medium flow (the reactor itself). Both

16 MSc thesis

configurations allow the calculation of light extinction and average irradiance using the

following expressions:

zXkII Tt exp0

where I0 is the incident irradiance on the face of the plate (or on the internal face of the

external cylinder) of the photobioreactor, kt is the light extinction coefficient, XT is the

total particulates concentration and z is the distance from the surface of the reactor.

The average irradiance on the reactor (Iavg) can be calculated integrating the previous

equation over the width (or the diameter), which results in:

LXkLXk

II Tt

Tt

avg

exp10

where L is either the total width of the flat-plate or the external minus internal diameter

in the cylindrical reactor.

As in the case of the photobioreactor not only algae biomass is present, but also

heterotrophs and nitrifiers, as well as organic and inert particulates, we consider XT as

the total particulates concentration. However, we consider that algae light extinction is

much higher (as their cellular machinery is especially adapted for light absorption), so

that XT is assumed as:

ISNHAT XXXXXX 1.01.01.01.0

Where XA is the algae biomass, XH is the heterotrophs biomass, XN is the nitrifiers

biomass, XS is the slowly degradable substrate and XI represents the particulate inerts.

The other particulates were assumed to have one tenth of the light extinction than that of

algae, considering that the last has a cellular machinery specifically adapted for light

absorption.

The mathematical expression used for light limitation was that proposed by Molina

Grima et al (1999), which accounts for both light saturation and inhibition:

0

0

0

0

max

1 I

cb

avg

I

cb

a

i

k

I

cb

avg

IK

II

I

where Ik is the light affinity of the algae, Ki is the photoinhibition constant and a, b and

c are adjustment parameters. This equation was considered suitable for this model, as it

accounts for light extinction without the need of using profiles (average irradiance) and

a set of the parameters is available for an outdoor culture of P. tricornutum (Molina

Grima et al 1999).

18 MSc thesis

Table 3: stoichiometry table of the model Particulates Solubles Rates

Process

XA

kg

(COD)

/m3

XH

kg

(COD)

/m3

XN

kg

(COD)

/m3

XS

kg

(COD)

/m3

XI

kg

(COD)/

m3

SNH3

kmol/m3

SO2

kmol/m3

SCO2

kmol/ m3

SS

kg

(COD

)/m3

SI

kg

(COD)/

m3

SNO3

kmol/ m3

SHC

O3

kmo

l/ m3

Algae growth on

ammonia

1 -0.111 1.5864 -2.18 r1

Algae growth on

nitrate

r2

Heterotrophs

growth

1 6.33

2.0

03125.0

32

1

HY

02976.0

32

1

HY

HY

1

r3

Heterotrophs

anoxic growth

(denitrification)

1 02976.032

1

HY

HY

1

02857.032

8.0

HY

r4

Nitrifiers growth 1

NY14

1000593.0

32

1

7

1

NY

6.33

1

NY14

1

r5

Algae decay

-1 r6

Heterotrophs

decay

-1 XIf1 XIf

14

1083.0 ,, XIXINXIXSN fifi

r7

Nitrifiers decay

-1 XIf1 XIf

14

1083.0 ,, XIXINXIXSN fifi

r8

Hydrolysis

-1 14

,, SISINXSN fii SIf1

SIf r9

Alkalinity

equilibrium

-1 1 r10


3.2.3.3 Decay

Decay of biomass is modeled as a first-order process. The equations take the form:

idii Xkdecay

iijdiij XYkrelease

Where kdi is the decay rate for microorganism i.

3.2.3.4 Bicarbonate/carbon dioxide equilibrium

As effluent from anaerobic treatment have high levels of alkalinity and carbon dioxide

bill be both produced (by heterotrophs) and consumed (by algae) in the system, it is

important to model the bicarbonate/carbon dioxide equilibrium. We use the same

expressions as Wolf et al (2007):

1

.. 3

2

2

K

SSSk

dt

dS HHCO

COAB

CO

where kAB is the rate constant for the equilibrium and K1 the dissociation constant.

Other alkalinity related equilibria are not included in the model because they are not

significant in neutral pH (e. g., formation of carbonate).

3.2.3.5 Recirculation

In simulations, both chemostat and “activated algae” configurations were used.

“Activated algae” means that part of the biomass is recirculated, in analogy with the

activated algae process. When biomass recirculation is used the settler is modelled as an

“ideal settler”, i. e., only biomass and biodegradable and inert particulates are

recirculated (no liquid stream) at a specified fraction of the total biomass outflow.

Recirculation is considered to be in the same fraction for all particulates (algae,

heterotrophs, nitrifiers, slowly biodegradable substrate and inert particulates).

3.2.4 Limitations of the model

Several processes are not considered in the model. The most important of them are:

Ammonia/ammonium equilibrium: as the system was considered to have a

constant controlled pH, it was not considered to be relevant; therefore, in this

work “ammonia nitrogen” and “ammonium nitrogen” can be used

interchangeably;

Temperature variation

pH variation

20 MSc thesis

Algae growth on bicarbonate, considered less important as carbon

dioxide/bicarbonate equilibrium is very fast and there are no diffusion

constraints (stirred reactor).

Dark respiration of algae, not modelled considering that nitrification does not

take place in this system the absence of photosynthesis.

Photoadaptation of algae

Nitrite accumulation and toxicity: as in ASM1, the kinetics of nitrification is

lumped in one single rate constant. It might, however, be important in this

system, especially in case nitrite is toxic to algae.

Toxicity of high dissolved oxygen content.


Table 4: rate equations of the model

Rates r1 Algae growth on ammonia

AAI

NHASNH

NH

COASCO

CO

A XfKS

S

KS

S.,,min. ,

3,,3

3

2,,2

2

max,

r2 Algae growth on nitrate

AAI

NHAinhNH

NHAinh

NHASNH

NO

COASCO

CO

A XfKS

K

KS

S

KS

S.,,,min. ,

3,,3

3,,

3,,3

3

2,,2

2

max,

r3 Heterotrophs growth

H

SHSS

S

NHHSNH

NH

OHSO

O

H XKS

S

KS

S

KS

S.,,min.

,,3,,3

3

2,,2

2

max,

r4 Heterotrophs anoxic growth

H

CODHSS

S

NHHSNH

NH

NOHSNO

NO

OHinhO

OHinh

DNH XKS

S

KS

S

KS

S

KS

K.,,,min.

,,3,,3

3

3,,3

3

2,,2

2,,

,max,

r5

Nitrifiers growth

N

CONSCO

CO

NHNSNH

NH

ONSO

O

N XKS

S

KS

S

KS

S.,,min.

2,,2

2

3,,3

3

2,,2

2

max,

r6

Algae decay AAd Xk .,

r7

Heterotrophs decay

HHd Xk .,

r8

Nitrifiers decay

NNd Xk .,

r9

Hydrolysis

H

HSXhS

HS

h XXXK

XXk

,,

.

R10

Alkalinity equilibrium

1

.. 3

2K

SSSk HHCO

COAB

3.2.5 Input parameters and operational strategy

A strategy for optimization of nitrification coupled with photosynthetic oxygenation can

be figured out from the stoichiometric and kinetic parameters of the model. It can be

noticed that nitrification in the modelled system presents several constraints, both of

stoichiometric as well as of kinetic nature. The stoichiometric constraint is due to the

fact that the oxygen consumed in nitrification comes exclusively from algae

photosynthesis, but this photosynthesis also requires nitrogen assimilation by algae;

therefore, there is a theoretical maximum stoichiometric nitrification, that can be

calculated from Table 3. For each 1 mol of ammonia nitrified, 0.31 mol of ammonia is

assimilated by algae for the production of the required oxygen, what gives a theoretical

maximum of 76% of nitrification, not considering the uptake of oxygen and ammonia

by heterotrophs. Kinetic constraints are those arising from the different growth rates and

22 MSc thesis

efficiencies of nutrient assimilation of the organisms, which regulate the outcome of

competition for nutrients. The parameters that define these competitions are

summarized in Table 5.

Table 5: kinetic comparison of microorganisms

Nitrifiers

max = 1 d-1

Algae

max = 1.512 d-1

NH3 KNH3,N = 7.14 x 10-5 mol/L

KNH3,A = 1.2 x 10-6 mol/L

CO2 KCO2,N = 1 x 10-4 mol/L

KCO2,A = 1 x 10-4 mol/L

Heterotrophs

max = 5.5 d-1

NH3 KNH3,N = 7.14 x 10-5 mol/L

KNH3,H = 1 x 10-10 mol/L

O2 KO2,N = 1.56 x 10-5 mol/L

KO2,H = 6.25 x 10-6 mol/L

As can be seen in Table 5, in every possible competition for nutrients nitrifiers tend to

be outcompeted, as its maximum growth rate is lower and its half-saturation coefficients

are higher in all cases, with the exception of the half-saturation constant for carbon

dioxide, which is the same as that of algae. That means that the competitors grow

potentially faster and are more efficient in nutrient assimilation, i. e., if grown in the

same medium (same concentration of nutrient), nitrifiers will always be outcompeted by

either algae or heterotrophs. It implies that the operational strategy for nitrification

optimization should ensure that nitrifiers are not directly competing for nutrients with

either algae or heterotrophs. Considering this, the operational strategy comes out

straightfowardly:

algae should be light-limited, so that they produce enough oxygen for

nitrification, but do not uptake most of the ammonia-nitrogen;

heterotrophs should be substrate (COD) limited, so that they do not uptake most

of the oxygen necessary for nitrification;

to ensure an adequate supply of inorganic carbon for algae, even though

heterotrophs might not produce enough due to substrate limitation, the influent

should have a high alkalinity;

the influent that best suits the desired characteristics – a high ammonia content

for nitrification, a low COD content and high alkalinity content is the one

coming from anaerobic treatment of sewage, that needs a post-treatment for

nutrients removal; however, effluent from anaerobic treatment contains

dissolved methane that could be a constraint for nitrification; therefore,

treatment of sewage will also be investigated.

The influent composition to be used will be according to Roeleveld and van

Loodsdrecht (2002), who presented data for Dutch wastewater treatment plants

according to the ASM1 model, i. e., in terms of SS, SI, XS and XI. As ammonium

nitrogen concentration is not mentioned in this compilation, it will be assumed to be

equal to 40 mg/L NH4-N.

As the alkalinity of sewage is not mentioned in Roeleveld and van Loodsdrecht (2002),

it will be assumed that it is equal to 5 meq/L, both for sewage and anaerobically treated


sewage. According to van Haandel and Lettinga (1994) the alkalinity of sewage varies

between 5 and 10 meq/L, and tends to increase with anaerobic treatment, so that the

assumption is conservative.

Table 6: parameters of the model

Model parameter Symbol Value Unit Reference

Maximum

specific growth

rate algae

μmax,A 1.512 d-1 Molina-

Grima et al

(1999)

Maximum

specific growth

rate heterotrophs

μmax,H 5.5 d-1 Wolf et al

(2007)

Maximum

specific anoxic

growth rate

heterotrophs

μmax,H,DN 1.6 d-1 Wolf et al

(2007)

Maximum

specific growth

rate nitrifiers

μmax,N 1 d-1 Wolf et al

(2007)

CO2 half-

saturation

constant algae

KS,A,CO2 10-4 kmol (CO2) m-3 Wolf et al

(2007)

NH3 half-

saturation

constant algae

KS,A,NH3 1.2 x 10-6 kmol (NH3) m-3 Wolf et al

(2007)

O2 half-saturation

constant

heterotrophs

KS,H,O2 6.25 x 10-6 kmol (O2) m-3 Wolf et al

(2007)

NH3 half-

saturation

constant

heterotrophs

KS,H,NH3 10-10 kmol (NH3) m-3 Wolf et al

(2007)

Readily

degradable

organic substrate

half-saturation

constant

heterotrophs

KS,H,S 0.004 kg (COD) m-3 Wolf et al

(2007)

O2 half-saturation

constant nitrifiers

KS,N,O2 1.56 x 10-5 kmol (O2) m-3 Wolf et al

(2007)

CO2 half-

saturation

constant nitrifiers

KS,N,CO2 10-4 kmol (CO2) m-3 Wolf et al

(2007)

NH3 half-

saturation

constant nitrifiers

KS,N,NH3 7.14 x 10-5 kmol (NH3) m-3 Wolf et al

(2007)

NO3 half-

saturation

constant

heterotrophs

KS,H,NO3 3.6 x 10-5 kmol (NO3) m-3 Wolf et al

(2007)

Particulate COD KS,h,X 0.1 kg (COD) / kg Wolf et al

24 MSc thesis

half-saturation

constant

(COD) (2007)

NH3 inhibition

coefficient for

algae growth on

nitrate

Kinh,A,NH3 1.2 x 10-6 kmol (NH3) m-3 Wolf et al

(2007)

O2 inhibition

coefficient for

heterotrophs

growth on nitrate

Kinh,H,O2 6.25 x 10-6 kmol (O2) m-3 Wolf et al

(2007)

Algae decay rate

constant

kd,A 0.09 d-1 Wolf et al

(2007)

Heterotrophs

decay rate

constant

kd,H 0.4 d-1 Wolf et al

(2007)

Nitrifiers decay

rate constant

kd,N 0.15 d-1 Wolf et al

(2007)

Dissociation

constant CO2

hydrolysis

K1 10-6.36 Wolf et al

(2007)

Rate constant CO2

hydrolysis

kAB 2221 d-1 Wolf et al

(2007)

Microalgal

affinity for light

Ik 94.3 μEm-2s-1 Molina-

Grima et al

(1999)

Photoinhibition

constant

Ki 3426 μEm-2s-1 Molina-

Grima et al

(1999)

Parameter in light

limitation

equation

a 3.04 Molina-

Grima et al

(1999)

Parameter in light

limitation

equation

b 1.209 Molina-

Grima et al

(1999)

Parameter in light

limitation

equation

c 514.6 Molina-

Grima et al

(1999)

Yield of

heterotrophs on Ss

YH 0.630 kg COD (XH) / kg

COD

Wolf et al

(2007)

Yield of nitrifiers

on NO3

YN 0.240 kg COD (XN) / kg

NO3-N

Wolf et al

(2007)

Fraction of

particulate inert

COD in biomass

fXI 0.100 kg COD (XI) / kg

COD (XA, XH, XN)

Wolf et al

(2007)

Fraction of

soluble inert COD

in particulate

substrate

fSI 0.190 kg COD (SI) / kg

COD (XS)

Wolf et al

(2007)

Fraction of

soluble inert COD

in algae biomass

fSI,A 0.001 kg COD (SI) / kg

COD (XA)

Wolf et al

(2007)


Fraction of N in

slowly degradable

particulate organic

matter

iN,XS 0.043 kg N / kg COD (XS) Wolf et al

(2007)

Fraction of N in

particulate inert

organic matter

iN,XI 0.040 kg N / kg COD (XI) Wolf et al

(2007)

Fraction of N in

soluble inert

organic matter

iN,SI 0.010 kg N / kg COD (SI)

or kg N / kg COD

(SI,A)

Wolf et al

(2007)

26 MSc thesis

4 Results

4.1 Experimental results

Experimental results will be presented according to its five different phases,

schematically presented below along with its main defining characteristic in relation

with the others:

Phase 1: growth of nitrifiers

Phase 2: addition of algae and SRT control

Phase 3: increased SRT

Phase 4: uncontrolled SRT

Phase 5: decreased influent ammonia concentration

Phase 6: increased settling time

4.1.1 Phase 1: growth of nitrifiers

In this phase nitrifiers were cultured alone in the media, without SRT control. Nitrifers

were able to nitrify 400 mg/L of ammonia nitrogen after approximately 3 weeks.

Results for ammonia concetration in the effluent can be seen in Fig. 4. In the first days

ammonia nitrogen concentration in the effluent was higher than in the influent. Due to

an unintentional pH shock on December 18th, most of the biomass died, but was able to

recovered without additional inoculation. Analysis during one cycle indicated that there

is nitrite accumulation in the media..

Figure 4: ammoium nitrogen concentration during in effluent in nitrifiers culture during Phase 1


Figure 5: concentration of nitrogen species in the medium during one cycle in Phase 1

4.1.2 Phase 2: addition of algae and SRT control

In phase 2 (Fig. 6), after ammonia nitrogen concentration in the effluent came to zero,

algae was inoculated in the reactor. Due to unintentional operational problems with pH

control, reactor flooded and most of biomass was lost. After that, algae grew and reactor

presented a dark green color. During this period light transmission through the reactor

was very low (below 0.5 mol μEm-2s-1). After about ten days nitrifiers started to grow

exponentially, as shown by nitrate concentration, and a decreased in algae biomass was

detected with a decrease in chlorophyll-a and an increase in light trasmission. On

February 8th SRT started to be controlled, subtracting 10% of biomass in each cycle,

intending to have an SRT of 10 days. After that, algae was washed out from the reactor,

as detected both visually (absence of green color) and with light transmission

measurements that indicated a sharp increase (Fig. 7). Nitrifiers biomass decreased

sharply, as indicated by nitrate concentration, that dropped to 25 mg/L.

28 MSc thesis

Figure 6: nitrate and ammonium nitrogen concentrations in the effluent during Phase 2

Figure 7: dissolved oxygen in medium and transmitted light intensity through the reactor during Phase 2

4.1.3 Phase 3: increased SRT

In phase 3 (Fig. 8) the intended SRT was increased to 20 days, i. e, 5% of reactor media

was removed with the stirrer switched on in each cycle. Once more, algae tended to be

washed out from the reactor. Nitrifiers activity was decreasing. Analysis of chlorophyll-

a content in the effluent and in the media withdrawn for SRT control o March 12th

indicated 0.074 and 0.37 mg/L, respectively. As the corresponding volumes were of 50

mL and 450 mL, it indicated that, due to inefficient settling, at this moment SRT was

actually half of the intended. This phase of the experiment was then interrupted.


Figure 8: nitrate and ammonia nitrogen in effluent and transmitted light intensity during Phase 3

4.1.4 Phase 4: uncontrolled SRT

In this phase SRT was left uncontrolled, so that it would be the outcome of growth rates

and withdrawal with the effluent (as settling was inefficient). Once more, algae was

visually washed out from the reactor (Fig. 9). Nitrifiers were growing steadily.

Figure 9: nitrate nitrogen in effluent and transmitted light intensity during Phase 4

4.1.5 Phase 5: decreased influent ammonia concentration

To evaluate a possible effect of nitrite toxicity on algae, influent ammonia nitrogen

concentration was decreased to 50 mg/L, all other nutrient concentrations decreased

proportionally. Algae tended to be washed out (Fig. 10).

30 MSc thesis

Figure 10: transmitted light intensity through the reactor during Phase 5

4.1.6 Phase 6: increased settling time

In phase 6 settling time was increased to 5 hours. Fresh algae were added (not previouly

stored on the fridge), cultivated in BG-11 medium, but in such a volume that do not

changed significantly the composition of the reactor medium (1% of the reactor volume).

Results shown in figure 11 indicate that both algae and nitrifiers tended to stabilize after

two weeks. However, ammonia was present in significant quantity in the effluent,

indicating that there might have been another limitation for the growth of nitrifiers.

Figure 11: nitrogen species in effluent and transmitted light intensity during Phase 6

4.1.7 General observations

During all phases of the experiment nitrifiers activity caused a continuous decrease in

pH, so that base addition was necessary. Algae tended to adhere to the walls of the

reactor, and were manually removed daily. It was observed that the biomass formed

after settling was made up of two layers, the bottom layer with a brownish-grey color


and the upper layer with a green color. In fig. X and Y it is possible to see photos taken

when this layer was disturbed during the filling phase of the reactor, so that part of the

layer turned upside down. In figure X the biomass layer that was on top of the magnetic

stirrer dropped upside down, and in fig Y the biomass layer rolled over itself.

Figure 12: layer of biomass that was on top of the

magnetic stirrer fell upside down, showing two

distinct layers

Figure 13: layer of biomass rolled over itself,

showing two distinct layers (green on top,

brownish-grey on bottom).

4.2 Model results

4.2.1 Input parameters and initial conditions

The initial input parameters and initial conditions are listed in Table 6 (sewage

parameters according to ASM1) and 7 (other parameters). The sewage chosen was that

with the lowest organic matter content in the list presented by Roeleveld and van

Loodsdrecht (2002). Whenever one or more parameter is modified in the simulations it

will be explicitly mentioned.

Table 7: Sewage as characterized in Nieuwe Waterweg, The Netherlands (Roeleveld and van

Loodsdrecht, 2002)

Symbol Parameter Value Unit

SS,IN Influent readily degradable COD

concentration

0.086 kg (COD)/m3

SI,IN Influent soluble inert COD

concentration

0.027 kg (COD)/m3

XS,IN Influent slowly degradable COD

concentration

0.108 kg (COD)/m3

XI,IN Influent particulate inert COD

concentration

0.209 kg (COD)/m3

32 MSc thesis

Table 8: Input parameters and initial conditions

Symbol Parameter Value Unit

SNH3-N,IN Influent ammonia-nitrogen

concentration

0.002857 kmol/m3

SHCO3,IN Influent bicarbonate concentration 0.005 kmol/m3

SCO2,IN Influent dissolved carbon dioxide

concentration

0.0009 kmol/m3

SO2,IN Influent dissolved oxygen concentration 0 kmol/m3

SNO3,IN Influent nitrate concentration 0 kmol/m3

SN2,IN Influent dissolved dinitrogen

concentration

0 kmol/m3

XA,ini Initial algae biomass in reactor 0.01 kg (COD)/m3

XH,ini Initial heterotrophs biomass in reactor 0.01 kg (COD)/m3

XN,ini Initial nitrifiers biomass in reactor 0.01 kg (COD)/m3

I0 Irradiance on surface of reactor 500 Em-2s-1

HRT Hydraulic retention time 6.67 d

r Fraction of recycled biomass 0 adimensional

L Width of the reactor 0.3 m

In the presentation of results, "limitation factor" or "nutrient limitation" is here

understood as the outcome of the Monod-type expression with the form

ijj

j

ijKS

Sf

Where fij is the limitation factor for microorganism i in relation to species j, Sj is the

concentration of the species j in the medium and Kij is the half-saturation constant for

assimilation of species i by microorganism j. In the case of light limitation, the

expression developed by Molina Grima is used (Molina Grima et al 1999):

0

0

0

0

,

1 I

cb

avg

I

cb

a

i

k

I

cb

avg

lightA

IK

II

If

“Nitrification” in the results is defined as the ratio of effluent nitrate nitrogen and

influent ammonia nitrogen, i. e:


nitrification = SNO3 / SNH3,IN

4.2.2 Base results

Results obtained with inputs from tables 6 and 7 are shown in figures 14-20. In Figure

14 it is shown that the biomass of the three microorganisms grows. Initially, algae and

heterotrophs grow together, strongly coupled (Fig. 14), and oxygen concentration is

close to zero (Fig. 19). Heterotrophs are thus assimilating most of the oxygen produced

by algae, and nitrifiers growth is limited to around 10% of their maximum growth rate

(Fig. 17). Heterotrophs biomass in the reactor suddenly stops growing after around 5

days, while algae biomass keeps growing (Fig. 14); this is due to the fact that

heterotrophs became COD-limited (Fig. 16). Soon after that, oxygen concentration

sharply increases (Fig. 19), followed by nitrate concentration (Fig. 20), as now

nitrification is feasible due to the available oxygen that was previously missing. With

nitrification taking place, oxygen comes again close to zero around day 10 (Fig. 19).

Nitrifiers growth is limited by oxygen and subsequently by ammonium, and then

stabilizes (Fig. 17). Between days 10 and 20 oxygen is depleted (Fig. 19) and nitrate is

available in the system (Fig. 20), so that denitrification starts to take place, as seen by

the growing concentration of dinitrogen (Fig. 20). However, with the depletion of

ammonium (Fig. 20) algae starts growing partially on nitrate (Fig. 18; an inflection in

algae biomass curve can be seen on Fig. 14 around day 20 due to this switch to growth

on nitrate) and denitrification decreases (Fig. 20). During the whole process algae

growth was limited by light (Fig. 15).

In Fig. 20 and Table 8 it can be seen that 54% of the nitrogen in the effluent is in the

nitrate form, followed by nitrogen assimilated by algae (29%) and heterotrophs (16%).

In the liquid phase, around 98% of nitrogen is in the nitrate form. Nitrification, as

defined here, was of 65%.

34 MSc thesis

Figure 14: biomass in the reactor

Figure 15: nutritional limitation for algae


Figure 16: nutritional limitation for heterotrophs

Figure 17: nutritional limitation for nitrifiers

36 MSc thesis

Figure 18: growth rate of nitrifiers

Figure 19: oxygen concentration in the reactor


Figure 20: main nitrogen forms in the effluent

Table 9: distribution of nitrogen in the effluent

Fraction %N in effluent

NO3-N 54

Algae assimilation 29

Heterotrophs assimilation 16

Table 10: nitrogen in liquid phase

Fraction Conc [mg/L]

Influent NH3-N 40

Effluent NH3-N 0.45

Effluent NO3-N 25.9

4.2.3 Effect of irradiation

In order to show the effect of incident irradiation on nitrification, a series of steps in this

input was applied, according to tables 10 (increasing irradiance intensity) and 11

(decreasing irradiance intensity), with all other parameters constant. In Fig. 10 it can be

seen that incident irradiance has a strong effect on the level of nitrification in the system,

coming from a maximum until no nitrification when irradiance deviates considerably

from an optimum irradiation intensity. When irradiation is too high (650 Em-2s-1) or

too low (300 Em-2s-1), nitrifiers are washed out. In-between this two levels of

irradiance, nitrification takes place with varying degrees, presenting a maximum with an

incident irradiance of around 500 Em-2s-1.

In the case high irradiance, nitrifiers are washed out due to competition for carbon

dioxide with algae, as can be seen in Fig. 21-24. As the inicident irradiance increases

stepwise, algae biomass increases also stepwise (Fig. 24), and, as a consequence, carbon

38 MSc thesis

dioxide decreases stepwise (Fig. 22), up to the point that it becomes the limiting nutrient

for nitrifiers (Fig. 21). When carbon dioxide becomes the limiting nutrient for nitrifiers

and algae simultaneously (Fig. 23 and Fig. 24, from day 250 on), nitrification stops

completely (Fig. 21, from day 250 on).

It can be seen that when nitrifiers are oxygen limited (Fig. 28, between days 0 and 100)

increasing incident irradiation causes an increase in nitrification (Table 10, Fig. 20

between days 0 and 100). That is because increasing light intensity causes increase in

biomass of algae (Fig. 23) and consequently in oxygen production. When nitrifiers

became ammonia-limited (Fig. 21, between days 100 and 200), increasing light

intensity caused a decrease in nitrification (Table 10, Fig. 20 between days 100 and

200). That happens because, as already mentioned, increasing irradiance causes and

increase in algae biomass. In this case, however, the dominant effect is not the extra

production of oxygen, but the extra ammonia assimilation, as now nitrifiers are

ammonia-limited. When nitrifiers are limited by carbon dioxide (Fig. 21, between days

200 and 250) but algae are limited by light (Fig. 22, between days 200 and 250),

nitrification still takes place (Fig. 20, between days 200 and 250). However, when both

nitrifiers and algae are simultaneously limited by inorganic carbon (Fig. 21 and 22,

between days 250 and 300), nitrifiers are washed out but algae remains on the system

(Fig. 23), showing that algae outcompetes nitrifiers when competing for this nutrient. In

the last two steps on incident irradiance, however, algae biomass does not grow, as it is

already considerably light limited (due to higher biomass and consequently higher light

extinction) and thereafter becomes limited by inorganic carbon (Fig. 25, days 200-300).

Table 11: steps applied on irradiance (increasing irradiance)

Time (d) Irradiation (E/m2/s)

0-50 400

50-100 450

100-150 500

150-200 550

200-250 600

300-350 650


Figure 21: nitrate concentration in the effluent with a series of steps in irradiance

Figure 22: carbon dioxide concentration in reactor

40 MSc thesis

Figure 23: nutritional limitation for nitrifiers with a series of steps in irradiance

Figure 24: nutritional limitation for algae with a series of steps in irradiance


Figure 25: biomass in reactor with a series of steps in irradiance

In the case low incident irradiance, nitrifiers are washed out due to competition for

oxygen with heterotrophs, as can be seen in Fig. 25-29. As the inicident irradiance

decreases stepwise, algae biomass decreases also stepwise (Fig. 28), and, as a

consequence, oxygen concentration also decreases stepwise (Fig. 29), up to the point

that it becomes the limiting nutrient for nitrifiers (Fig. 27, from day 100). When oxygen

becomes the limiting nutrient for nitrifiers and heterotrophs simultaneously (Fig. 27 and

Fig. 28, from day 250 on), nitrification stops completely (Fig. 26, from day 250 on).

It can be seen that when nitrifiers are limited by ammonia (Fig. 28, between days 0 and

100) decreasing incident irradiation causes an increase in nitrification (Table 11, Fig. 26

between days 0 and 100). That is because decreasing light intensity causes a decrease in

biomass of algae (Fig. 30) and consequently a decrease in oxygen production. When

nitrifiers became limited by oxygen (Fig. 28, between days 100 and 200), decreasing

light intensity caused a decrease in nitrification (Table 11, Fig. 28 between days 100

and 300). That happens because, as already mentioned, decreasing irradiance causes a

decrease in algae biomass. As nitrifiers became limited by oxygen, this effects

dominates over the decreased ammonia assimilation by algae. When nitrifiers are

limited by oxygen (Fig. 28, between days 100 and 250) but heterotrophs are limited by

COD (Fig. 29, between days 100 and 250), nitrification still takes place (Fig. 26,

between days 100 and 250). However, when both nitrifiers and heterotrophs are

simultaneously limited by oxygen (Fig. 28 and 29, between days 250 and 300), nitrifiers

are washed out but heterotrophs remains on the system (Fig. 30), showing that

heterotrophs outcompete nitrifiers when competing for this nutrient.

Table 12: steps applied on irradiance (decreasing irradiance)

Time (d) Irradiation (E/m2/s)

0-50 550

50-100 500

100-150 450

42 MSc thesis

150-200 400

200-250 350

300-350 300

Figure 26: nitrate concentration in the effluent with a series of steps in irradiance

Figure 27: oxygen concentratio in reactor


Figure 28: nutritional limitation for nitrifiers with a series of steps in irradiance

Figure 29: nutritional limitation for heterotrophs with a series of steps in irradiance

44 MSc thesis

Figure 30: biomass in reactor with a series of steps in irradiance

4.2.4 Effect of hydraulic retention time (HRT)

In order to show the effect of hydraulic retention time (HRT) on nitrification, a series of

steps in this input was applied, according to tables 12 (increasing HRT) and 13

(decreasing HRT). In Fig. 31-38 it can again be seen that HRT a strong effect on the

level of nitrification in the system. The effect is analogous to that of incident irradiance,

coming from a maximum until no nitrification when HRT deviates considerably from

an optimum HRT; increasing HRT, algae biomass increases. When HRT is too low

(around 1.67 days), nitrifiers are washed out due to competition for oxygen with

heterotrophs (figures 32 and 33). When HRT is too high (around 20 days), nitrifiers are

washed out due to competition for inorganic carbon with algae. Near the optimum HRT,

once more algae are limited by light, heterotrophs are limited by organic substrate and

nitrifiers are limited by ammonium. The dynamics of nutrient limitations for

microorganisms are analogous to that found varying incident irradiation intensity.

Table 13: steps applied on HRT (decreasing HRT)

Time (d) HRT (d)

0-50 10

50-100 5

100-150 3.33

150-200 2.5

200-250 2

300-350 1.67


Figure 31: nitrate concentration in the effluent with a series of steps applied on HRT

Figure 32: nutritional limitation for nitrifiers with a series of steps on HRT

46 MSc thesis

Figure 33: nutritional limitation for heterotrophs with a series of steps on HRT

Figure 34: biomass in reactor with a series of steps on HRT

Table 14: steps applied on HRT (increasing HRT)

Time (d) HRT (d)

0-50 5

50-100 6.67

100-150 10

150-250 20


Figure 35: nitrate concentration in the effluent with a series of steps applied on HRT

Figure 36: nutritional limitation for nitrifiers with a series of steps on HRT

48 MSc thesis

Figure 37: nutritional limitation for algae with a series of steps on HRT

Figure 38: biomass in reactor with a series of steps on HRT

4.2.5 Control of nitrification coupling HRT to incident irradiance

As incident irradiance and HRT have analogous effects on nitrification, it is possible to

manipulate one of this variables when the other changes, so that the same (high) level of

nitrification can be maintained. The adequate combination of incident irradiance and

HRT, therefore, allows controlled nitrification. A series of steps is applied with pairs of

incident irradiance and HRT that optimize nitrification, as listed in Table 15, and the

output of nitrate, ammonia and dinitrogen concentration is shown in Fig. 39; in this


figure it is possible to see that nitrification is kept in high levels, although operational

changes were applied, since incident irradiance and hydraulic retention time were

optimally coupled. At lower HRT's, however, nitrate concentration tends to decrease

and more ammonia tends to remain in the effluent, indicating that nitrifiers start to be

washed out.

There is a limit to the HRT-incident irradiance applied that keeps nitrification, as when

irradiance is higher than 1200 Em-2s-1 (and the correspondent HRT is lower than 1.53

days) inorganic carbon limitation inhibits the increase in growth rate of nitrifiers that

would be necessary to keep them in a system with a lower HRT (Fig. 40).

Table 15: series of steps using optimal combinations of irradiance and HRT

Time (d) I0 HRT (d)

0-50 500 6.67

50-100 600 4

100-150 700 2.85

150-200 800 2.22

200-250 900 2

250-300 1000 1.73

300-350 1100 1.57

350-400 1200 1.53

Figure 39: nitrate in effluent with a series of steps in irradiance and HRT

50 MSc thesis

Figure 40: nutritional limitation for nitrifiers with a series of steps in irradiance and HRT

4.2.6 Control of nitrification manipulating hydraulic retention time, biomass

retention time and irradiation

Recycling of biomass makes possible the use of lower HRT’s (and correspondingly

higher incident irradiances) and avoids the increase of ammonium in the effluent with

low HRT’s. A series of steps was applied according to Table 16, and the resulting

nitrogen compounds concentrations in the liquid phase is shown in Fig. 41, showing that

nitrification is kept at high levels, without decreasing at higher HRT’s.

Table 16: series of steps using optimal combinations of irradiance, HRT and recycled biomass

Time (d) I0 (Em-2s-1) HRT (d) Fraction of recycled

biomass

0-50 500 6.67 0

50-100 1000 1.73 0.15

100-150 1500 1.53 0.70

150-200 2000 1.53 0.90

200-250 2500 1.18 0.90

250-300 3000 0.91 0.70


Figure 41: control of nitrification with different combinations of irradiance, HRT and SRT

4.2.7 Effect of C/N ratio

With the parameters defined in tables 6 and 7, changing the ammonia concentration

while keeping organic substrate constant will change the results for nitrification. With

an influent with 60 mg NH3-N and additional oxygen production with an incident

irradiance of 580 Em-2s-1, nitrification improves to 67% (Fig. 42). However, with NH3-

N of 80 mg/L the extra oxygen production by algae cannot be achieved due to carbon

limitation, so that nitrification is poorer and about one fourth of ammonia nitrogen is

neither nitrified nor assimilated by algae (Fig. 43-44). In this case the maximum

nitrification achieved is of 51%, plus 5% denitrification.

52 MSc thesis

Figure 42

Figure 43: nitrogen in the effluent with high organic content wastewater


Figure 44: nutrient limitation for nitrifiers with high organic content wastewater

4.2.8 Effect of reactor width

Decrasing reactor width from 30 to 10 cm reduces efficiency of nitrification (around 5%

less efficient), but allows considerably lower hydraulic retention times. A series of steps

was applied according to Table 17. Results are shown in Fig. 46, which shows that

nitrification is kept at the same level.

Table 17:

Time (d) I0 (Em-2s-1) HRT (d) Fraction of recycled biomass

0-50 500 1.43 0.50

50-100 1000 0.59 0.70

100-150 1500 0.43 0.85

150-200 2000 0.33 0.85

200-250 2500 0.31 0.90

250-300 3000 0.30 0.90

54 MSc thesis

Figure 45

4.2.9 The role of alkalinity

The model shows that alkalinity works as a “buffer” of inorganic carbon in the system.

In the absence of alkalinity, nitrification might not take place due to limitation either of

inorganic carbon (with higher algae biomass) or of oxygen (with lower algae biomass);

in this case, strong coupling of algae and heterotrophs inhibit nitrifiers growth.

Alkalinity might be regarded as an additional degree of freedom in this system, as it

substitutes the role of heterotrophs (production of inorganic carbon) without consuming

oxygen.

To illustrate this, in Fig. 47 it is shown the step response in day 50 of the system as

described in Tables 6 and 7, when the concentration of bicarbonate is divided by 2.

Nitrification stops completely. That happens due to inorganic carbon limitation and

competition with algae, as can be seen in figures 48 and 49. Increasing organic substrate

in the influent in order increase inorganic carbon production by heterotrophs would

probably not compensate for alkalinity, as then algae must assimilate more ammonia.

This will be shown in the next section.


Figure 46:

Figure 47:

56 MSc thesis

Figure 48:

4.2.10 Treatment of sewage with higher substrate content

Using as wastewater the concentrations indicated by Roeleveld and van Loodsdrecht

(2002) for Nieuwgraaf (Table 18), with higher organic load, and fixing HRT as 6.67

days, it is found that maximum nitrification occurs with an incident irradiance of 560

Em-2s-1. It is observed that nitrification is less efficient than that for Nieuwe Waterweg

(compare Fig. 50 with figure 20). Nitrification was of 65% with wastewater from

Nieuwe Waterweg, while it is of 43% with wastewater from Nieuwgraaf. In Fig. 50 it

can be seen that this is due to higher ammonia assimilation by algae, which has to

produce additional oxygen for the degradation of the increased organic matter by

heterotrophs, that assilate oxygen before (i. e. more efficiently than) nitrifiers.

Table 18: Sewage as characterized in Nieuwgraaf, The Netherlands (Roeleveld and van Loodsdrecht,

2002)

Input Parameter Value Unit

SS,in 0.258 kg COD/m3

SI,in 0.039 kg COD/m3

XS,in 0.086 kg COD/m3

XI,in 0.230 kg COD/m3


Figure 49: nitrogen forms in the effluent with wastewater with high organic content

4.2.11 Denitrification

When there is nitrification in the system limited by oxygen (and not by ammonia),

oxygen concentration is depleted and denitrification takes place. However,

denitrification is not significant, accounting for a maximum of around 5% of nitrogen in

the effluent.

58 MSc thesis

5 Discussion

5.1 Experiments

Some difficulties in the experiments showed that the operation of photobioreactors are

complex and subject to several constraints and limitations. It seems that in an SBR,

besides stoichiometric and kinetic constraints (discussed in next section), settling of

algae as well as nitrite accumulation might play important roles. However, settling

alone might not be the only reason for the washing out of algae in phases 2-5, as in the

beginning of phase 2, when nitrifiers were still not growing, algae could grow well. This

two factors should be carefully investigated. It is possible that chlorophyll sampling

during phase 2 (50 and 20 mL) contributed to washing out algae. In case nitrite

accumulation significantly limits algae growth due to toxicity, as suggested by the fact

that algae were washed out after nitrifiers grew during phase 2, it might be that an SBR

is not the best configuration for this system, as nitrite concentration would always have

a cyclic behaviour, depending on the phase of the cycle and on the temperature; a

chemostat or a biofilm reactor would be more indicated. However, a biofilm reactor

might limit controllability, as the hydraulic retention time of algae could not be

controlled.

In Phase 6 of the experiments it seems that it was possible to keep stable populations of

nitrifiers, algae and heterotrophs (although the influent did not contain organic substrate,

decay products are a source of nutrients for heterotrophs). This confirmed what has

already been published in the literature. The fact that in this phase ammonia was

available in significant levels in the effluent without being nitrified seems to indicate

that there was another limitation for nitrifiers. One possible explanation is that there was

inorganic carbon limitation, taking into consideration that it came exclusively from

aeration and that nitrifiers competed with algae for this nutrient. Otherwise, there might

be a limitation of another micronutrient.

The conditions of the last phase of the experiment might be a good starting point for

further studies, e. g., adding organic substrate and bicarbonate in the media, and trying

to experimentally confirm the effect of light intensity on nitrification.

5.2 Modelling

The model shows that there are several constraints in an enclosed photobioreactor for

nitrification process. These constraints are both stoichiometric and kinetic.

Stoichiometrically, nitrification is limited to a maximum theoretical threshold, due to

the fact that algae also assimilate ammonium nitrogen to produce oxygen. Kinetic

constraints arise because both algae and heterotrophs grow faster and are more efficient

to assimilate nutrients than nitrifiers, and therefore outcompete them when these

nutrients are limited. However, the model showed that with a proper strategy, that

involves keeping algae light-limited and heterotrophs substrate-limited, nitrification can

indeed take place.


The model also shows that nitrification can be controlled with the manipulation of

incident irradiance, hydraulic retention time and/or biomass retention time, in such a

way that nitrification is kept near the theoretical stiochiometric maximum. This

behaviour qualifies nitrification in enclosed photobioreactors as an optimisation

problem.

The choice of reactor width can influence the range of operability of the reactor, in

terms of stability and range of light intensity and hydraulic retention time. Reactor

width could be used as a design parameter according to local irradiation characteristics.

For example, in a location where natural irradiances between 2000 and 3000 μEm-2s-1

are common, a reactor with 10 cm of width would provide good controllability, as in

this range of irradiance nitrification is not very sensitive to changes in light intensity

(Fig 46, using data from Table 16). When natural light intensity falls below these values,

complementary artificial illumination could be used. Another location where the usual

irradiance falls between 900 and 1200 μEm-2s-1 would rather operate as depicted in Fig.

47.

Figure 50: optimized hydraulic and sludge retention time for photobioreactor (nitrification of around 60%

of influent NH3-N) with 10 cm of width and other parameters described in tables 6 and 7

60 MSc thesis

Figure 51: optimized hydraulic and sludge retention time for photobioreactor (nitrification of around 65%

of influent NH3-N, slightly decreasing as HRT decreases) with data based on tables 6, 7 and 14

Differently than the PHOBIA model, developed for biofilm photobioreactors, this

model shows that significant nitrification can take place in suspended stirred

photobioreactors. Two reasons might be the cause for this difference: as said by the

developers of PHOBIA, the biofilm photobioreactor imposes diffusion limitations

(Wolf et al 2007) that are absent in the suspended biomass configuration; another

possible reason might be that the alkalinity used in simulations with PHOBIA was

significantly lower than the ones used in this work, based on typical sewage alkalinity.

As Abeliovitch (1985) showed experimentally, nitrification is dependent on hydraulic

retention time; however, the model does not show two peaks of nitrification as in his

experimental work, but only one. The finding of Evans et al (2005) that nitrification on

HRAP's is dependent on pond depth might perhaps be better explained as a dependancy

on average light intensity, as increased depth means increased light extinction,

considering constant concentrations in the water column.

The model developed does not account for some processes that might play a role in the

system. One of them is nitrite accumulation, but in a chemostat configuration it should

be only a transitory state. Dark respiration could be important in systems without

artificial irradiation. One phenomena that might make nitrification more difficult is

photoadaptation. If algae can significantly change the chlorophyll content according to

the irradiance they receive, that could be a difficulty for the effective control as

discussed in this work. However, this photoadaptation is very likely bounded to limits;

on the other hand, it would require a stable condition, so that, in case it is a problem,

intentional oscillations of the operating conditions could avoid it. Temperature effects

might also modify the optimal operating conditions in case microorganisms increase or

decrease their growth rates in different proportions.

A sensitivity analysis of the model was not yet carried out. However, it is conceptually

possible to identify some critical parameters in the model. One of these is the inhibition

constant for algae growth on nitrate. If there is not a strong preference of algae for

growth on ammonia instead of nitrate, results of the model could change significantly,

as growth on nitrate could considerably decrease the efficiency of nitrification, even

though the process of nitrification itself is taking place. Another issue is the light


extinction coefficients of other particulates besides algae. Should algae cells have a light

extinction not so much higher than other particulates as modelled here (as 10% of algae

light extinction), higher light intensities should be necessary to achieve the same results,

due to increased extinction.

Finally, it must be said that some inconsistencies might arise in the model due to the

fact that the kinetic parameters used were derived for algae species P. tricornutum,

while the stoichiometric parameters were derived for algae species xxxx. However,

considering that different species of algae have similar functional properties, so that

biofilm development is reproducible with different species (Wolf et al 2007), one might

perhaps assume that the same is valid for algae cultured in suspension.

5.3 Integration of experimental and model results

The model was developed for a different situation than the experimental setup presented

here, so direct inferences cannot be made. However, one important finding was that

biomass seems to grow separately, as two layers were formed in the bottom of the

reactor after settling. That is an indication that the kinetic parameters of ASM1 are valid

in this system. If phenomena such as adsorption took place, it might be that those

parameters changed, due to e. g. diffusional limitations. The model also indicates that it

might be that a better experimental strategy might be adding bicarbonate to the medium,

instead of using aeration; in this case nitrifiers growth would be more clearly coupled to

photosynthetic oxygenation, and bicarbonate would simulated the role of alkalinity (e. g.

of sewage).

5.4 Enclosed photobioreactors in wastewater treatment plants

Enclosed photobioreactors would not be used alone in a wastewater treatment plant. The

effluent should certainly be previously treated for the removal of course solids, for

example. Another issue is the removal of nitrate. Denitrification seems to be possible in

a pre-anoxic tank, as suggested by the composition of sewage reported by Roeveled and

van Loodsdrecht (2002). The readily biodegradable substrate is stoichiometrically

sufficient for denitrifying nitrate, as shown in table 18. However, in this case, to ensure

anoxic conditions, either algae should be removed in the recycling stream, or the reactor

should be "dark", so that photosynthsis does not take place. Therefore, one can imagine

a system as qualitatively outlined in Fig. 46, with pretreatment, pre-anoxic tank for

denitrification and a photobioreactor.

62 MSc thesis

Figure 52: photobioreactor for sewage treatment

According to the stoichiometry table for denitrification (Table 3), with the appropriate

unit conversions, one finds that for each mol of NO3-N denitrified a stoichiometric

amount of 1.66 mg of readily degradable substrate is necessary. In Table 18 are listed

the concentrations of readily degradable substrate of wastewater in Dutch wastewater

treatment plants (Roeleveld and van Loodsdrecht 2002), together with the

stoichiometric potential for denitrification. As it can be seen, the readily degradable

substrate concentration seems to be enough for the denitrification. Besides, this pre-

anoxic tank would improve nitrification in the photobioreactor, as algae would not have

to produce extra oxygen for de oxydation of organic substrate and therefore would

assimilate less ammonia, and heterotrophs would also assimilate less ammonia, and

nitrification of high organic load wastewater would be more efficient.

NO3-

Algae

Algae

N2

Pre-treatment Anoxic

tank

NO3-

Effluent

Algae

harvesting

COD

NH3

TKN


Table 19: stoichiometric potential of sewage to denitrification, according to sewage characterization by

Roeleveld and van Loodsdrecht (2002)

WWTP Ss (mg /L) NO3-N potentially

denitrified (mg/L)

Geestmarambacht 105 63.2

Niedorpen 115 69.3

Stolpen 170 102.4

Ursem 202 121.7

Wieringermeer 104 62.6

Wieringen 203 122.3

Deventer 97 58.4

Nijmegen 129 77.7

Franeker 65 39.1

Gouda 149 89.7

Venlo 204 122.9

Appeldoorn 165 99.4

Boxtel 140 84.3

Nieuwgraaf 258 155.4

Groote Lucht 129 77.7

Nieuwe Waterweg 86 51.8

Haarlem-WP 97 58.4

Alphen KenZ 118 71.1

Groesbeek 153 92.2

Hardenberg 185 111.4

Papendrecht 102 61.4

Photobioreactors could also be used in post-treatment of effluent from anaerobic

reactors (e. g. UASB reactors), that have low organic substrate but high ammonium

nitrogen content. One difficulty to treat effluent coming from this system in an enclosed

photobioreactor for nitrification is that the effluent coming from the anaerobic reactor

would contain dissolved methane - up to 16 mg/L, the methane solubility at 300 K (van

Haandel and Lettinga 1994), and methanotrophs might outcompete nitrifiers (Hatamoto

et al 2010), reducing the efficiency of nitrification. Another difficulty is that UASB

effluent has low organic substrate content, so that external electron donor should be

added. However, it might be that this system also offers the solution to this problem,

that would be using methane as electron donor in a pre-anoxic tank for denitrification.

This way, the pre-anoxic tank would have the double funcion of removing nitrate and

methane previously to feeding the wastewater in the photobioreactor. According to

Modin et al (2007), for each mol of NO3-N denitrified, the correspondent

stoichiometric ammount of methane is 0.625 mol, or a requirement of 0.71 mg CH4/mg

NO3-N. It means that with 16 mg/L of CH4 a total of 22.5 mg of NO3-N could be

stoichiometrically denitrified. This seems to be enough for denitrification with a

wastewater with 40 mg/L NH4-N and 60-70% of nitrification, admitting that 10 mg/L

NO3-N is allowed in the effluent. In case it is not enough due to stoichiometric or

kinetic reasons, gaseous methane from the anaerobic reactor could be added to the

reactor; alternatively, a fraction of the wastewater could be partly bypassed directly to

the anoxic tank (addition of readily degradable substrate).

64 MSc thesis

Biogas from the anaerobic reactor could be used for electricity production to provide

artificial (complementary) illumination to the photobioreactor. In a treatment plant for a

population of 200 000, 300 kW of useful power could be generated (van Haandel and

Lettinga 1994) and the excess algae harvested in the effluent could be fed back into the

anaerobic reactor. A system like this is outlined in Fig. 47. The artificial illumination

would make the process more controllable, and besides would allow the operation

during the night or during periods when solar irradiation is less intense. The main

difficulties for such a system seem to be algae harvesting and the denitrification process

with methane as electron donor. This last process was found recently, and it seems that

anaerobic denitrification with methane has a very slow growth rate (Modin et al 2007).

Algae harvesting might be still more difficult than in reported in the literature, because

it should be carried out selectively (not together with nitrifiers). Different settling or

other physical properties of the microorganism might be used for this goal.

Figure 53: photobioreactor for post-treatment of UASB effluents

The two process configurations qualitatively outlined above would encompass

nitrification and denitrification without any artificial aeration. Some of the ammonia

nitrogen would be assimilated by the algae, but this would be used as energy source to

provide (complementary) artificial illumination. Nevertheless, more quantitative

analysis is necessary in order to assess the feasibility of these systems, including the

removal of other pollutants such as phosphorous, as well as basic research, e. g. in the

fields of algae harvesting and denitrification with methane as electron donor. To the best

of the author's knowledge, this is the first time that a controllable nitrification-

denitrification system coupled to photosynthetic oxygenation and without any artificial

aeration and/or external electron donor addition is proposed.

NO3-

Algae

COD

TKN

NH3

CH4

UASB

NO3-

Algae

NH3

Biogas

Turbine

N2

Pre-treatment Anoxic

tank

Effluent

Algae

harvesting

66 MSc thesis

6 Main conclusions and suggestions for further research

Based on the model and experiments, the main conclusions of this work are:

1. Enclosed photobioreactors are a promising alternative for wastewater treatment

with nitrification coupled to photosynthetic oxygenation.

2. Nitrification in enclosed photobioreactors is strongly dependent on the operating

conditions, and can be characterized as an optimization problem.

3. Enclosed photobioreactors might be integrated in wastewater treatment plants in

such a way that nitrification and denitrification could be carried out without

artificial aeration, i. e., exclusevely based on photosynthetic oxygenation.

To achieve this, however, more research is needed. It is suggested that the following

studies are carried out:

1. Sensitivity analysis, calibration and validation of the model.

2. Demonstrate experimentally the dependence of nitrification on irradiance.

3. Investigate nitrite toxicity to algae.

4. Experimentally determine the light extinction coefficient for nitrifiers,

heterotrophs and other particulates present in wastewater.

5. Consider the use of a method to improve algae settling, e. g., chitosan as

flocculant or ultrasound.

6. Modelling of photoadaptation and dark respiration

7. Modelling temperature effects

8. In-depth quantitative research and modelling of complete wastewater treatment

plants with nitrification and denitrification coupled to photosynthetic

oxygenation.


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