international master of science in environmental ... · ! 1! master’s dissertation submitted in...
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Master’s dissertation submitted in partial fulfilment of the requirements for the joint degree of
International Master of Science in Environmental Technology and Engineering
an Erasmus+: Erasmus Mundus Master Course jointly organized by
Ghent University, Belgium University of Chemical Technology, Prague, Czech Republic
UNESCO-IHE Institute for Water Education, Delft, the Netherlands
Academic year 2014 – 2015
Autotrophic nitrogen removal from tanning wastewater in biofilm reactors
Host University:
Ghent University, Belgium
Veronica del Rosario Díaz Sosa Promotor: Prof. dr. ir. Eveline Volcke Co-promotor: Prof. dr. Nguyen Tan Phong
This thesis was elaborated at Ghent University, Belgium and defended at Ghent University, Belgium within the framework of the European Erasmus Mundus
Programme “Erasmus Mundus International Master of Science in Environmental Technology and Engineering" (Course N° 2011-0172)
© 2015, Ghent, Veronica del Rosario Díaz Sosa, Ghent University, all rights reserved.
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Acknowledgements
The current master thesis is product of the right mixture of commitment, discipline, guidance, perseverance, reinforcement and support. It is dedicated in an equal amount to the people that supported me in lesser or greater extent to study this master course and to be the person I am today. To begin with, I would like to express my gratitude to CONACYT for granting me the scholarship and the financial support that made this master course possible for me. I would also extend this gratitude to Duo-Belgium/Flanders fellowship 2014 for giving me the opportunity to have professional research experience and the experimental input for this study at Ho Chi Minh University of Technology in Vietnam. Gratitude and appreciation must be paid to Prof. dr. ir. Eveline Volcke, not only for being my promotor during this research work, but also for believing in me without further reference but my academic background and accepting my proposed research topic in collaboration with HCMUT in Vietnam. For supporting me through the research process, even from the distance and giving me the right insights to work with the available data in the best possible way. I am also very grateful to Prof. Volcke to have assigned me the best tutor I could have had during this master thesis journey. This thesis could not have been done without the tutorship of Thomas Vannecke, a person whose presence, guidance and support were the base for this master thesis to make sense and achieve meaningful results. During the time I worked under his tutorship I always felt comfortable, backed up and motivated even when the situations seemed very pessimistic. I would also like to thank Prof. Nguyen Tan Phong for supporting the possibility of the collaboration between UGent and HCMUT for this research to be done. Special mention must be made to Evelien Vandevelde, IMETE programme coordinator. Ever since she took over that position, she has not only made a terrific job but she has also become a supportive friend. She has been there and willing to help for academic and personal problems that have come up and it is very comforting knowing that despite the fact of being in a foreign country, you have someone that will offer you a helping hand. To my family and friends, who believed in me when I decided to quit my job and join this master course in Europe; who came to visit me and pamper me during these two years away from Mexico, and who are waiting for me back home full of pride for my achievements. To my IMETE family, to the precious friendships I have made here, for the amazing people that will remain in my life for many years and for the great synergy we developed during these two years of working side by side that made each other always feel supported. To the IMETE programme for giving me the opportunity to expand my horizons not only in academic knowledge matters but also in personal experiences. For giving me the opportunity to live in four different countries within two years and to meet such amazing people from all over the world who shared with me great moments I will never forget. And finally, to myself, for having the will to overcome fear and decide to change mi life to pursuit happiness while learning new things day by day and living life to the fullest. For not quitting despite the hard times, the stress and the anxiety, and for having the will to keep on learning in the future, now on a PhD level. Ghent, August 2015 Veronica del Rosario Díaz Sosa
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Table of Contents
List of abbreviations ................................................................................................................ 1
List of symbols .......................................................................................................................... 2
Abstract ..................................................................................................................................... 4
1. Introduction .......................................................................................................................... 6
2. Literature review ................................................................................................................. 8
2.1 Tannery industry ............................................................................................................................... 8
2.1.1 Overview of the tanning process ................................................................................................ 8
2.1.2 Tanning wastewater composition ............................................................................................ 10
2.1.3 Tanning wastewater treatment methods .................................................................................. 11
2.2 Nitrogen removal from wastewater ................................................................................................. 15
2.2.1 Nitrification .............................................................................................................................. 15
2.2.2 Denitrification .......................................................................................................................... 16
2.2.3 Anaerobic Ammonium Oxidation (Anammox) ......................................................................... 16
2.3 Landfill leachate versus tanning wastewater ................................................................................... 17
2.3.1 Landfill leachate composition .................................................................................................. 17
2.3.2 Comparison between landfill leachate and tanning wastewater treatment methods .............. 18
2.4 Concluding remarks ........................................................................................................................ 22
3. Materials and Methods ...................................................................................................... 23
3.1 Full-scale tanning facility ................................................................................................................ 23
3.1.1 Production process .................................................................................................................. 23
3.1.2 Wastewater treatment .............................................................................................................. 25
3.1.3 Available process data ............................................................................................................. 26
3.2 Lab-scale partial nitritation experiment .......................................................................................... 27
3.2.1 Reactor set-up .......................................................................................................................... 27
3.2.2 Operating conditions ............................................................................................................... 29
3.2.3 Available partial nitritation system data ................................................................................. 29
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3.3 Modelling and simulation study ...................................................................................................... 30
3.3.1 Partial nitritation model .......................................................................................................... 30
3.3.2 Simulation set-up ..................................................................................................................... 32
4. Results and discussion ....................................................................................................... 34
4.1 Experimental work .......................................................................................................................... 34
4.1.1 Reactor performance ............................................................................................................... 34
4.1.2 Nitrogen balance ...................................................................................................................... 35
4.1.3 Influence of operating variables .............................................................................................. 38
4.2 Simulation study .............................................................................................................................. 38
4.2.1 Reference case simulations ...................................................................................................... 38
4.2.2 Model adaptation for steady state simulations ........................................................................ 39
4.2.3 Steady state simulation of old landfill leachate ....................................................................... 43
4.2.4 Steady state simulation of tanning wastewater ........................................................................ 45
4.2.5 Dynamic simulation of old landfill leachate ............................................................................ 47
4.2.6 Dynamic simulation of tanning wastewater ............................................................................. 50
4.2.7 Conclusions .............................................................................................................................. 54
5. Conclusions and perspectives ........................................................................................... 56
References ............................................................................................................................... 59
Appendix ................................................................................................................................. 64
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List of abbreviations Anammox Anaerobic ammonium oxidation AOB Ammonium oxidizing bacteria AOPs Advanced oxidation processes BNR Biological nitrogen removal BOD Biological oxygen demand CASP Conventional activated sludge processes CF Coagulation-flocculation COD Chemical oxygen demand CWs Constructed wetlands DO Dissolved oxygen FA Free ammonia FNA Free nitrous acid HRT Hydraulic retention time MBBR Moving-bed biofilm reactors MBR Membrane Bioreactor MF Microfiltration MSW Municipal solid waste NF Nanofiltration NLR Nitrogen loading rate NOB Nitrite oxidizing bacteria PAC Poly aluminum chloride PAC Powdered activated carbon PAFC Poly aluminum ferric chloride PASiC Poly aluminum silicate PN Partial Nitritation PNA Partial Nitritation-Anammox RO Reverse osmosis SBR Sequencing Batch Reactor SRT Solid retention time SS Suspended solids TDS Total dissolved solids TKN Total Kjeldahl Nitrogen TNH Total ammonium TNO2 Total nitrite TOC Total organic carbon TSS Total suspended solids UASB Up-flow anaerobic sludge blanket UF Ultrafiltration UV Ultra Violet VFA Volatile fatty acids WWTP Wastewater treatment plant
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List of symbols Symbol Name / Process Unit
ρG,AOB Growth of AOB gCOD.m-3.d-1 ρG,NOB Growth of NOB gCOD.m-3.d-1 ρG,H Growth of aerobic heterotrophs gCOD.m-3.d-1 ρAG,H
NO2 Anoxic growth of heterotrophs (on NO2-) gCOD.m-3.d-1
ρAG,HNO3 Anoxic growth of heterotrophs (on NO3
-) gCOD.m-3.d-1 ρD,AOB Decay of AOB gCOD.m-3.d-1 ρD,NOB Decay of NOB gCOD.m-3.d-1
ρD,HA = Decay of heterotrophs gCOD.m-3.d-1
Soluble compounds
SS Concentration of organic substrate gCOD.m-3 SNH Ammonium concentration gN.m-3 SNO2 Nitrite concentration gN.m-3 SNO3 Nitrate concentration gN.m-3 SO2 Oxygen concentration gO2.m-3 SN2 Nitrogen concentration gN.m-3
Particulate compounds
XAOB Concentration of AOB gCOD.m-3 XNOB Concentration of NOB gCOD.m-3 XH Concentration of heterotrophs gCOD.m-3 XI Concentration of inert biomass gCOD.m-3
Stoichiometric parameters
YAOB Yield of AOB on ammonium gCOD.g-1COD YNOB Yield of NOB on nitrite gCOD.g-1COD YH Yield of heterotrophs gCOD.g-1COD fI Inert content in biomass gCOD.g-1COD iNXB Nitrogen content in active biomass gN.g-1COD iNXI Nitrogen content in inert biomass gN.g-1COD iNSS Nitrogen content in organic substrate gN.g-1COD
Kinetic parameters
Maximum growth rate of AOB d-1 Maximum growth rate of NOB d-1
Maximum growth rate of heterotrophs d-1 Ammonium half saturation constant for AOB g N.m-3 Nitrite half saturation constant for NOB g N.m-3
AOBmaxµNOBmaxµHmaxµAOBNHK
NOB2NOK
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Nitrite half saturation constant for heterotrophs g N.m-3 Nitrate half saturation constant for heterotrophs g N.m-3
Organic substrate half saturation constant for heterotrophs g COD.m-3
Oxygen half saturation constant for AOB g O2.m-3 Oxygen half saturation constant for NOB g O2.m-3
Oxygen half saturation constant for heterotrophs g O2.m-3
Ammonium half saturation constant for NOB and heterotrophs g N.m-3
bAOB Specific biomass decay rate for AOB d-1 bNOB Specific biomass decay rate for NOB d-1 bH Specific biomass decay rate for heterotrophs d-1 η Correction factor for µH under anoxic conditions -
Other parameters
DNH4 Diffusion coefficient of ammonium m2.d-1 DNO2 Diffusion coefficient of nitrite m2.d-1 DNO3 Diffusion coefficient of nitrate m2.d-1 DO2 Diffusion coefficient of oxygen m2.d-1 DN2 Diffusion coefficient of nitrogen gas m2.d-1 DS Diffusion coefficient of organic carbon compound m2.d-1 T Temperature K Tref Reference temperature K
Activation energy for AOB kJ.mol-1 Activation energy for NOB kJ.mol-1
R Ideal gas constant J.mol-1.K-1 Aij Stoichiometric coefficients gN.g-1COD or gCOD.g-1COD
HNOK 2HNOK 3
HSK
AOBOK 2NOBOK 2HOK 2
NOBHNHK
AOBaENOBaE
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Abstract
The current master dissertation deals with the treatment of tanning wastewater in an aerated biofilm reactor. The objective was partial nitritation for subsequent anammox-denitrification. The research was performed experimentally using a laboratory-scale partial nitritation (PN) reactor (Ho Chi Minh University of Technology, Vietnam). Furthermore, a simulation study on the partial nitritation process using a mathematical biofilm model developed in Aquasim was performed (Department of Biosystems Engineering, Ghent University, Belgium).
Tanning wastewater is typified by one of the highest toxic intensities per unit of effluent (Verheijen et al., 1996). It contains high concentrations of organic compounds, dissolved solids and nitrogen. Tanning effluent has low C/N ratio, hampering nitrogen removal through conventional biological nitrogen removal (BNR) methods based on autotrophic nitrification, followed by heterotrophic denitrification. This is the main reason why partial nitritation for subsequent anammox-denitrification is the focus of this study. The resulting insights are relevant for minimization of eutrophication and free ammonia availability caused by effluents of future tanning industry wastewater treatment plants (WWTPs).
The experimental study comprised a 0.012 m-3 partial nitritation reactor with biomass carriers allowing the growth of flat biofilms. Constant aeration was supplied with a manual air compressor valve and the DO concentration in the bulk liquid varied from 1.4 to 2.8 g.m-3. The pH value was maintained neutral (7-7.5) with a pH control system based on sodium bicarbonate addition. The average ammonium concentration in the influent was 500 gN.m-3. Available data on the experimental results comprised 40 days of experiment with 20 taken samples. The average nitrate-ammonium ratio was 0.52, when the ideal ratio according to anammox stoichiometry goes from 1.14 (Lotti et al., 2014) to 1.32 (Strous et al., 1999). The ideal nitrite-ammonium ratio was achieved when the DO concentration in the bulk liquid was between 2.2 to 2.8 g.m-3. Nitrate concentrations in the effluent were lower than 5 gN.m-3, meaning that the NOB were mostly inhibited. Ammonium conversion efficiency was 52% and nitrite accumulation was in average 34%. There was a gap in the nitrogen mass balance of 15% of nitrogen not acknowledged in the effluent, this is mostly attributed to heterotrophic denitrification being performed because of the theoretical COD load in the influent plus COD released from biomass decay; which means that nitrogen gas was probably escaping from the reactor without being measured.
The mathematical model considered the growth and decay of ammonium oxidizing bacteria (AOB), nitrite oxidizing bacteria (NOB) and heterotrophic denitrifiers in a flat biofilm. Parameter values were adapted according to the influent characteristics and free ammonia (FA) and nitrous acid (FNA) inhibition factors were added to the AOB and NOB kinetics.
The model was run for tanning wastewater as well as for old landfill leachate at fixed pH (8.1 for old landfill leachate and 7 for tanning wastewater) and temperature (30℃ for both influents). Although tanning wastewater is the main focus of this study, old landfill leachate was also considered because this effluent has similar characteristics to tanning wastewater. Data available on a similar study (Nguyen and Lan, 2014) using old landfill leachate, and performed on the same experimental facilities, was used for model validation and comparison of the simulation results of tanning wastewater and old landfill leachate.
A steady state simulation analysis was performed. Simulations were run with a constant ammonium load (1090 gN.m-3 for old landfill leachate and 500 gN.m-3 for tanning
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wastewater) until steady state (400 days for old landfill leachate and 250 days for tanning wastewater). The model was adapted to be able to simulate partial nitritation at steady state (nitrite-ammonium ratio of 1.07 for old landfill leachate and 1.23 for tanning wastewater). DO concentrations to achieve steady state were set at 2.5 gO2.m-3 for old landfill leachate and 2.2 gO2.m-3 for tanning wastewater. COD concentration were 0 gCOD.m-3 for old landfill leachate and 250 gCOD.m-3 for tanning wastewater.
Dynamic simulation was run subsequently to fit the simulation according to the experimental data (70 days for old landfill leachate and 40 days for tanning wastewater) on ammonium, nitrite and nitrate in the effluent, estimating influential parameter values. DO concentration is determining in the PN process performance, for the fitted simulation the oxygen levels were lower than for steady state, with concentrations of 1 gO2.m-3 for both influents. COD load were estimated at 99 gCOD.m-3 for old landfill leachate and 8.5 gCOD.m-3 for tanning wastewater. COD concentration was found to be very influential in the heterotrophic community, the higher the COD concentration in the effluent, the more heterotrophs were present in the biofilm and more nitrogen gas was produced in the effluent. FA and FNA inhibition constants had a major role suppressing NOB population and controlling the AOB density according to the ammonium load in the influent. The ammonium load in the influent clearly influenced the bacterial communities; species exposed to high nitrogen loads were acclimated to higher FA and FNA concentrations. The time to reach steady state was also influenced by the ammonium load, the higher it was, the longer the bacteria took to acclimate and the longer the simulation took to reach steady state.
Overall, this experimental and simulation study indicated the feasibility of partial nitritation process performed with tanning wastewater as influent under specific influent and operating conditions.
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1. Introduction
Nitrogen compounds present in wastewater lead to environmental disturbances when discharged in the environment at high concentrations. Eutrophication is one of the main problems caused by an excess of nutrients in water bodies, causing algae blooms in aquatic environments, leading to oxygen-depleting conditions. This results in an environmental issue that also affects public health, economical and recreational spheres. Furthermore, ammonia is toxic for aquatic life in its free or un-ionized form and can affect public health by impairing the ability to breathe and limiting visibility.
The tannery industry is responsible for leather production. Its wastewater effluent is characterized by one of the highest toxicity intensities per unit of effluent, including high concentrations of organic compounds, dissolved solids and also nitrogen concentrations. While tannery wastewater contains many different pollutants in high concentrations, this study focuses only on nitrogen removal. Tannery industry wastewater has a low C/N ratio, hampering nitrogen removal through conventional biological nitrogen removal (BNR) methods based on autotrophic nitrification, followed by heterotrophic denitrification.
The anaerobic ammonium oxidation process (anammox) offers an alternative method of nitrogen removal, combining NH4
+ and NO2- to produce N2 gas without the need of organic
carbon. In order to provide the anammox process with NH4+ and NO2
- concentrations in a suitable ratio, a preceding step of partial oxidation of NH4
+ to NO2- must be carried out by
ammonium oxidizing bacteria (AOB), while inhibiting the nitrite oxidizing bacteria (NOB), and thus preventing oxidation of nitrite to nitrate. One possibility is to perform BNR with bacteria growing in the form of biofilm on biomass carriers inside a bioreactor, as these systems allow slow growing bacterial species to survive due to the decoupling of the hydraulic retention time (HRT) and the solid retention time (SRT).
The concentration of NH4+ in the wastewater, along with variations of the bulk liquid oxygen
concentration (DO) and the pH, affect the microbial communities performing these processes and therefore their efficiency. These process conditions can be adjusted and monitored to find the optimal conditions for these bacterial communities to perform a highly efficient nitrogen removal.
Mathematical models have gained popularity due to the reliability of simulating different processes, the testing of different conditions inside a process and the benefit of being much more economical than building pilot plants to test process performance.
This master dissertation focuses on the experimental realization and mathematical modelling and simulation of biological nitrogen removal from tanning wastewater. More specifically, the partial nitritation process of tanning wastewater after physical-chemical pre-treatment, as a prerequisite for the nitrogen removal by anammox-bacteria, is studied.
To be able to compare the process performance and validate the mathematical model, available data of old landfill leachate used previously as influent for the same laboratory scale biofilm reactor was used as reference for this study.
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The present master thesis project has two main objectives:
1) To experimentally find the optimal parameters for nitrifying bacterial communities to perform partial nitritation in a laboratory-scale biofilm reactor, in order to prepare tanning wastewater for biological nitrogen removal by anammox bacteria;
2) To build a 1-dimensional biofilm model based on the experimental conditions and to simulate the partial nitritation process under different environmental conditions and/or for varying tannery wastewater composition.
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2. Literature review
The following information in this literature review aims to provide the basic knowledge about tanning wastewater composition and treatments, and how the partial nitritation process can be applied to it for biological nitrogen removal process.
Landfill leachate composition and treatment information is also given, aiming to compare the two types of effluents since in this thesis also data on the partial nitritation of old landfill leachate will be used.
2.1 Tannery industry
Leather is a commonly used material that is obtained from animal skin. In order to convert raw hide into the stable, imputrescible leather, several chemical and mechanical processes have to take place. These processes, further denoted as tannery, involve the use of chemicals such as acids, solvents, alkalis, chromium salts, tannings, oils, dyes, etc. Tannery is one of the oldest industries in the world; there are two methods to perform the tanning of the raw skin: vegetal tanning and chromium tanning. Although vegetal tanning agents exist, mostly chromium tanning salts are used in the global leather production (Durai & Rajasimman, 2011).
In average, for every kilogram of animal skin processed, 30 liters of effluent containing high loads of organic pollutants are generated (Lofrano et al., 2013). Furthermore, the tanning industry is typified by one of the highest toxic intensities per unit of effluent (Verheijen et al., 1996). The high generation of wastewater from tannery industry, the relatively low profit of leather production and the execution of 60% of the world’s leather production in developing countries, lead to a high impact of the wastewater treatment on the total cost of the leather production (Mousa et al., 2004) and limited treatment of the discharges in most cases.
2.1.1 Overview of the tanning process
The following information contains the process steps in making chromium tanned leather is made (Black et al., 2013), with special attention to the chemicals used and the link between the processes and the chemical composition of the wastewater. These steps are also summarized in Figure 1.
Sorting, soaking and liming
The fresh or salt-cured hides are soaked in water contained in big drums that turn very slowly, with the purpose of washing off the salt. After this, lime and sodium sulphide are added to remove the hair, unwanted proteins and to open the fiber structure of the skin.
Deliming, bathing, pickling and tanning
The hides are washed in drums with ammonium sulphide to remove the excess of lime. Water and sodium chloride are added to the drum along with sodium formate buffer and sulphuric acid. The salt prevents the acid from damaging the hides. The drum runs for about three hours and then the chromium tanning salts are added. Next, the drums are run for another three hours and magnesium oxide is added. Finally, the drum is run overnight at pH value of
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3.6 – 4.0 and temperature around 45 °C. The hides resulting from this process are the chromium-tanned leather with blue-like color, also known as “wet blue”.
The excess of moisture is drained from the hides for further splitting and shaving until the desired thickness is achieved.
Fig. 1. Main inputs and aqueous effluents of the leather production process (Black et al., 2013).
Neutralising, retanning, dyeing and fatliquoring
Since chromium tanning is an acidic process, the hides are neutralized adding sodium bicarbonate and sodium formate or acetate, and then it is retanned with syntans, which are synthetic tanning agents; resins and natural tannings are also used in this sub-process and finally the leather acquires the desired properties. From this point the leather gets
Sorting, soaking and liming
Deliming, bathing,
pickling and tanning
Neutralising, retanning, dyeing and fatliquoring
Drying, conditioning, staking and buffing
Finishing
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“fatliquored”, which means that it is processed with natural and synthetic oils to substitute the fat that has been removed and lubricate the fibers once the leather is dried.
Drying, conditioning, staking and buffing
In order to remove wrinkles and dry the leather, it can either be vacuum-dried or passed through a drying tunnel on a glass or metal bed.
After drying, the leather is softened and then buffed to correct surface defects. Before the finishing, it is inspected to make sure the wet blue look of the chromium-tanning has been corrected.
Finishing
In this final step, several pigments, resins, binders and dyes are applied to the leather to provide its final color, appearance and feel. It is milled in a drum for few hours, measured and packed for its next destination as final product.
2.1.2 Tanning wastewater composition
As shown in Table 1, the characteristics of tanning wastewaters vary largely from one industry to the other, depending on the amount of chemicals and water used in the processes and the characteristics of the final product (Durai & Rajasimman, 2011).
Table 1. Tanning wastewater characteristics (Lofrano et al., 2013). Conductivity is expressed in (µmho/cm), all other parameters in (g.m-3)
pH Conduc-tivity COD BOD5 TSS TS SS TDS Alkali-
nity Chloride Sulphate NH4-N Phosph. Chromium Iron
8.4 - 4947 - 2239 - - - 665 7601 - 95 4 - - 10.5 - 3114 1126 - 18884 1147 17737 - - 55 33 - 83 - 7.79 - 2155 - - - 915 - - - 35.8 168 - 50.9 -
7.5-9 - 5000-10000
1500-2000 - - - - - - - - - 100 -
8 - 1803 106 526 - - 9435 - 2251 - 70 - - - - - 8000 930 - - 2004 15152 - - 228 - - 11.2 -
7.4 - 2227 1800 578 - - - - 3430 - 137 - - - 8.2-8.5 - 5650 - - 19775 5025 14750 - - - - - - -
10.72 - 11153 2906 - - - 6810 - - 507 162 - 32.87 - 7.7 - 2200 - - - 5003 36800 - - - - - - - 7.7 - 2426 - - - - - - - 286 335 - 29.3 - 6.6 8600 6855 2700 2865 - - - 1010 2835 - 70.5 - 140 - 7.8 - - - - 10265 2820 - - - - 128 - 90-100 - 7.2 19950 2810 910 1520 - - - - 6400 89 130 - 62 0.62 8.3 - 3100 - 1195 - - - 1010 4150 - 54 - - -
7.08-8.7 - 4100-
6700 630-975 - - 600-
955 13300-19700 - - - - - 11.5-14.3 -
7.2 - 2102 - 576 - - - - 3260 860 118 - - - 7.9-9.2 20042 2533 977 1244 - - 21620 - 6528 440 118 62 258 2.56
7.4 - 3700 1470 - - 2690 - - - - 180 - - - COD: Chemical Oxygen Demand; BOD: Biochemical Oxygen Demand; TS: Total Solids; TSS: Total Suspended Solids; SS: Suspended Solids; TDS: Total Dissolved Solids; Phoph.: phosphorous.
An average of 30 -35 m3 of wastewater are produced per ton of raw hide, but it can vary from 10 to 100 m3 depending on the kind of animal skin that is being treated, the process and the final product. Therefore, it is very hard to generalize the main characteristics of this kind of industrial effluent but typically the biodegradable fraction of the chemical oxygen demand (COD), also named biological oxygen demand (BOD), is usually less than 20% even if it shows high concentration values as displayed in Table 1 (Lofrano et al., 2013). To evaluate
tannery industry wastewater, the main differentiation between one source and the other relays
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on the presence or absence of important parameters such as chromium and sulfide, over other like BOD, COD and suspended solids.
Although it is hard to generalize its characteristics, tanning raw wastewater, without either mechanical or chemical treatment, has average concentration of some parameters as displayed on Table 2. These concentrations are too high compared to most regulations and established standard limits worldwide. As an example, in the European Union, the standard limits for water bodies established in Fish Directives are suspended solids < 25 g.m-3 (tanning effluents concentrations are around 5300 g.m-3), BOD5 < 5 g.m-3 (tanning effluents are mostly over 800 g.m-3), ammonia (NH3
+) < 0.025 g.m-3 and Total Kjeldahl Nitrogen (TKN) < 0.78 g.m-3 (tanning effluents contain nitrogen concentrations mostly above 100 g.m-3). There are no limits set for COD as the substances and toxicity causing it cannot be specified (Bosnic et al., 1996).
Table 2. Average tanning raw wastewater characteristics.
Parameter Average value Unit Source
Chemical oxygen demand (COD) 6200 g.m-3 Durai and Rajasimman, 2011 Suspended solids (SS) 5300 g.m-3 Durai and Rajasimman, 2011 Total dissolved solids (TDS) 37000 g.m-3 Durai and Rajasimman, 2011 Total chromium >100 g.m-3 Lofrano et al., 2013 Cr+3 65-165 g.m-3 Lofrano et al., 2013 Chloride >6000 g.m-3 Lofrano et al., 2013 pH 8.1 - Lofrano et al., 2013 Total Kjeldahl Nitrogen (TKN) 214-358 g.m-3 Lofrano et al., 2013
2.1.3 Tanning wastewater treatment methods
As the tannery wastewater characteristics are different from tannery to tannery and they depend largely on the size of the facilities and production, a wide variety of treatment systems are described in literature.
Some tannery industries separate treatments for the different effluents coming from the individual sub-processes, however some others combine all the sub-processes effluents and treat it as a one single wastewater effluent from the whole production process.
Raw wastewater passes through mechanical treatments so it can be homogenized and settled, and then through chemical treatment of alum and/or iron salts to decrease the concentrations of chromium, sulphide, total nitrogen and COD. Plain settling constitutes a poor pretreatment because the effluent still contains COD levels higher than 2000 g.m3, 800 g.m3 of total suspended solids (TSS) and 40-50 g.m3 of chromium. These characteristics of the wastewater effluent after settling pretreatment would represent an inhibitor for bacteria to perform biological processes. Chemical treatment results in an effluent with ideal characteristics for further biological treatment such as concentrations around 1000 gCOD.m3, total nitrogen around 600 g.m3 and practically no suspended solids and chromium. From the COD in the chemical treatment effluent only around 20% of it is biodegradable, which requires consideration when defining further treatments, although in general it can be then treated with biological processes (Durai & Rajasimman, 2011).
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There are many different treatments that could apply for tannery wastewater, depending if the aim of the treatment is to remove the COD concentration or the removal of some nutrient such as nitrogen, heavy metals or other compounds. The most commonly used nowadays are summarized in Table 3 and briefly described below.
Chemical treatment: Coagulation and flocculation
Categorized as a pre-treatment, the first required step in tanning wastewater treatment is chemical coagulation and flocculation as it removes pollutants, particulate matter and chromium VI that inhibits bacterial growth in the following biological steps.
This method makes use of inorganic coagulants such as aluminum sulphate (AlSO4), ferric chloride (FeCl3) and ferrous sulphate (FeSO4). Coagulation/flocculation (CF) wastewater treatment of tannery effluent has been largely studied. The aim of the treatment is to reduce COD, suspended solids and toxic pollutants such as chromium. Each coagulant works ideally under a specific pH range, which is defined by the kind of coagulant, the dosage and the characteristics of the wastewater (Lofrano et al., 2013). Kabdasi et al. (1999) reported COD removal of 40 – 70% and chromium removal higher than 99% using the three of the coagulants mentioned above.
New types of coagulants have been developed to improve the efficiency and decrease the residual parts in the effluent; these are poly aluminum chloride (PAC), poly aluminum silicate (PASiC) and poly aluminum ferric chloride (PAFC), which have resulted in a removal of COD >70% and suspended solids of >95% (Lofrano et al., 2013). PAC was used for the chemical pre-treatment of the tanning wastewater used in this master thesis (see materials and methods, section 3.1.2).
Mechanical and physical treatments: Membrane processes.
In the past few years the application of membrane processes have been growing and their cost has been reduced. Several studies have shown how microfiltration (MF), ultrafiltration (UF), nanofiltration (NF), reverse osmosis (RO) and supported liquid membranes (SLMs) could be used for chromium recovery from tannery wastewater (Labanda et al., 2009). Reverse Osmosis permeate can even allow tannery treated effluent to be reused in the production cycle; this will decrease the use of groundwater resources (Lofrano et al., 2013).
Biological treatments
The use of microorganisms for removal of BOD concentrations is simple, reliable and cost-effective. Biological treatments are also implemented for removal of a specific pollutant; therefore they are widely used around the world. Under aerobic conditions, microorganisms degrade organic compounds to carbon dioxide or sludge, and under anaerobic conditions they produce biogas (Lema et al., 1988).
Aerobic treatments. Since tannery wastewater contains high concentrations of poorly biodegradable compounds or metals, like chromium in concentrations above 10 g.m-3, bacterial processes can be inhibited (Stasinakis et al., 2002).
Sequencing Batch Reactors (SBR) have shown a good performance for biological nitrification and denitrification when inhibiting substances are present in the bulk liquid because of the selection of specific bacterial strains (Farabegoli et al., 2004). As for the
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nitrification process, there can be adverse consequences when the bulk contains chloride, sulphide and chromium. Temperature fluctuations have very small effect on COD removal but high impact in nitrogen removal. Increasing or intermittently aeration flow improves nitrification performance and efficiency of nitrogen removal (Insel et al., 2009; Lofrano et al., 2013).
Table 3. Wastewater treatments most commonly applied to tannery effluents (Lofrano et al., 2013).
Treatments Examples Chemical
Coagulation and Flocculation
Common inorganic coagulants: AlSO4, FeCl3, FeSO4. New coagulants: poly aluminum chloride (PAC), poly aluminum silicate (PASiC) and poly aluminum ferric chloride (PAFC)
Mechanical and Physical
Membrane processes Microfiltration (MF), ultrafiltration (UF), nanofiltration (NF), reverse osmosis (RO) and supported liquid membranes (SLMs)
Biological
Aerobic processes Sequence batch reactors (SBR), conventional activated sludge process (CASP)
Anaerobic processes Anaerobic filters (AF), Up-flow Anaerobic Sludge Blanket (UASB)
Constructed wetlands (aerobic and anaerobic) Combination of advanced facultative pond (AFP), secondary facultative pond (SFP) and maturation pond (MP)
Innovative Membrane bioreactor (MBR) -
Advance oxidation processes (AOP) Oxidizing agents (O3, H2O2) and/or catalysts (Fe, Mn, TiO2)
Fenton based processes Reaction of H2O2 with ferric (Fe3+) and ferrous
(Fe2+) iron in acidic aqueous solutions
Photo-oxidation processes -
Ozone based processes Ozonation and ozonation catalyzed with H2O2, Fe2+,
UV light, and TiO2 Photocatalysis - Electrochemical treatment Electro Fenton (EF)
Anaerobic treatments. The interest in anaerobic processes has been growing despite the fact of the challenging disadvantages they represent, such as the need of technology for desorption treatment of H2S because of sulfide production due to the absence of alternative electron acceptors, like oxygen, by sulfate reduction. Another problem is that high protein components affect biomass, delay the kinetics and act as an inhibitor for granular sludge formation (Lofrano et al., 2013).
Wetlands and ponds. Tannery effluent can be treated with constructed wetlands (CWs), which support both aerobic and anaerobic processes. The choice of crops plays a very important role in the efficiency of the treatment, besides the dissolved oxygen concentration, pH and temperature. A serial arrangement of ponds can adequately treat raw combined tannery effluent, just preceded by simple pretreatment (Tadesse et al., 2004).
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Innovative treatment processes
In order to enhance the efficiency of the available treatments, combinations of treatment categories have been set into practice showing favorable results, although some still need improvements to be able to offer cost-effective or large scale applied solutions. Most of the innovative technologies to treat tannery wastewater have only been tried on a laboratory scale, and therefore their effects on a full scale are not ensured.
Some innovative processes aim to eliminate xenobiotics, which are micro pollutants like endocrine disruptors or pharmaceuticals, from tannery effluents but the cost of this is still very high. It is not possible to determinate which treatment is better than the others, but tannery wastewater treatment studies are increasing which will provide more data in the near future (Lofrano et al., 2013).
Membrane Bioreactors (MBR). MBRs combine membrane technology with bacterial communities and have shown advantages in their performance compared to the conventional activated sludge processes (CASP); on the other hand it also has disadvantages such as fouling caused by adsorption, clogging and cake formation in the membrane (Lofrano et al., 2013).
Advance oxidation processes (AOPs). Studies about AOPs application on tannery wastewater effluents are becoming more common in the last past years; these processes use catalyst agents such as Fe, Mn and TiO2, and/or strong oxidizing agents like O3 and H2O2. High-energy radiation is sometimes used as a support in the processes (Shrank et al., 2004).
Fenton based processes. To achieve Fenton’s oxidation, the use of ferric and ferrous iron (Fe3+, Fe2+) reaction with H2O2 in acidic aqueous conditions is needed. Effluents where chromium tanning process being performed twice or more times are good candidates for Fenton’s oxidation processes due to low pH, high amount of aromatic compounds and high temperature, fluctuating in a range of 43 – 45 °C (Lofrano et al., 2007).
Photo-oxidation processes. To be able to have an effect on the wastewater composition such as COD, TOC and toxicity, the photolysis process requires a strong UV light with a short wave length of < 400nm in combination with oxidants like H2O2 and O3 (Lofrano et al., 2013).
Ozone based processes. Before biological treatment of the tannery effluent, ozonation can be applied to remove high color and convert refractory organics into biodegradable organic compounds, increasing the wastewater biodegradability index from 0.18 to 0.49 (Preethi et al., 2009). This last process effect needs to be taken into account prior to its application because ozone can also oxidize the biodegradable faction of influent COD (Lofrano et al., 2013).
Photocatalysis. The greatest advantage of this process is the possibility to make use of solar light or near UV light, as irradiation force and this would result in economic savings. However, studies applying this technology on tannery wastewater have shown that despite the fact that COD removal is achieved; the toxicity is increased in the effluent (Shrank et al., 2004).
Electrochemical treatment. Some authors refer to this treatment as an expensive option because of its high capital costs but they also refer to the fact that it is compact and its effects
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are, in general, highly efficient. Nevertheless, it was proven that electrochemical treatment applied to tannery wastewater is not efficient because of the high energy requirements; but it does represent a competitive treatment according to cost and efficiency when it is applied as final polishing step or as a biological nitrification-denitrification process (Szpyrkowicz et al., 2001).
2.2 Nitrogen removal from wastewater
Nitrogen in tanning wastewater needs to be removed prior to discharge in the environment due to its toxicity for aquatic species in the form of unionized or free ammonia (NH3) and the eutrophicating effect as a plant nutrient on the receiving water bodies at high concentrations and the required nitrogen-control for water reuse applications (Tchobanoglous et al., 2003).
Nitrogen removal from tanning wastewater is here performed using an innovative biofilm reactor system based on partial nitritiation that oxidizes a fraction of the NH4 concentration into NO2 and prevents it from further oxidation to NO3, this is to prepare the ideal influent to complete the nitrogen removal process in a subsequent anammox reactor, which will fully oxidize the remnant NH4 and NO2 concentrations into N2 gas.
Nitrogen values and concentrations can be found in literature in different units, one of the most common for tanning wastewater are the Total Kjeldahl Nitrogen or the sum of ammonia, ammonium and organic nitrogen (TKN) and ammonium-nitrogen (NH4-N). The dominant form of ammonium will be in solution as ammonium ion (NH4
+) and un-ionized ammonia (NH3), which are in equilibrium depending on the pH and temperature of the solution. During nitrification, ammonium oxidizing bacteria (AOB) oxidize ammonium to nitrite (NO2
-) and nitrite oxidizing bacteria (NOB) oxidize nitrate to nitrate (NO3-). Hydrogen
ions are released as nitrite oxidation takes place, this makes the pH value to drop; nitrite will exist in equilibrium with un-ionized nitrous acid (HNO2). Also the fraction of free nitrous acid and nitrite are dependent on temperature and pH of the bulk liquid. Denitrification and anammox process further convert nitrite and nitrate into gaseous nitrogen species, mainly dinitrogen (N2) but also nitric oxide (NO) and nitrous oxide (N2O), although the latter two species in a lesser extent. These gas-phase nitrogen species are off-gassed to the atmosphere. Ammonia can also be volatilized when it is exposed to high aeration environments (Anthonisen et al., 1976; Seviour & Nielsen, 2010; Tchobanoglous et al., 2003).
The conventional way to perform nitrogen removal from wastewater is known as biological nitrogen removal (BNR), and is based on the nitrification-denitrification processes.
2.2.1 Nitrification
Nitrification is the process in which ammonia is fully oxidized to nitrate with nitrite as intermediate.
In reactors using activated sludge or biofilms, autotrophic bacteria are responsible for the nitrification process. This process has a two-step sub-processes performed by two different aerobic chemolithoautotrophic bacterial groups. The microorganisms performing nitrification are called nitrifiers and are divided by the sub-process they perform. Ammonia oxidation is also named nitritation and is performed by ammonia oxidizing bacteria (AOB) according to the following stoichiometric equation (Tchobanoglous et al., 2003; Seviour & Nielsen, 2010):
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NH4+ + 1.5 O2 →NO2
− + 2H++ H2 (1)
Nitratation is the next step performed by nitrite oxidizing bacteria (NOB), which oxidize nitrite into nitrate according to the following stoichiometric equation (Tchobanoglous et al., 2003; Seviour & Nielsen, 2010):
NO2− + 1.5 O2 → NO3
− (2)
Nitrification is highly dependent on pH, temperature, dissolved oxygen (DO) concentration and the composition of the wastewater (Tchobanoglous et al., 2003; Seviour & Nielsen, 2010), this is why in order to maintain a stable efficiency there is the need of control systems for these parameters.
Nitrfication remains a critical step in nitrogen removal process inside wastewater treatment, as no other available alternatives are known to perform the same process.
2.2.2 Denitrification
The second step of BNR is denitrification, which is mainly performed by facultatively anaerobic heterotrophic bacteria. These microorganisms, called denitrifiers, reduce nitrite and nitrate to the gaseous forms of nitrogen (Seviour & Nielsen, 2010). The stoichiometry followed for this process is expressed in equation 3 (Tchobanoglous et al., 2003):
5CH3OH + 6 NO3− → 3N2
+ 5CO2 + H2O + 6OH− (3)
The desired product of nitrification is N2 because it possesses an inert nature in the atmosphere, but the intermediates NO and N2O can be also released during nitrification, depending on the microbial community and the environmental characteristics, the two latter are greenhouse gases (Seviour & Nielsen, 2010; Kong et al., 2013).
2.2.3 Anaerobic Ammonium Oxidation (Anammox)
Anaerobic ammonium oxidizing bacteria, as the name implies, is an anaerobic process where ammonium is the electron donor, nitrite the electron acceptor and the final product is the desired dinitrogen gas. Anammox is an alternative method to perform nitrification-denitrification BNR. The stoichiometric equation for the process is described as follows (Strous et al., 1999):
NH4+ + 1.32 NO2
− + 0.066 HCO3− + 0.13 H+ →1.02 N2 + 0.26 NO3
− + 0.066 CH2O0.5N0.15 + 2.03 H2O (4)
However, recently a new stoichiometric equation for anammox has been proposed by Lotti et al. (2014):
1 NH4+ + 1.146 NO2
− + 0.071 HCO3− + 0.057 H+ → 0.986 N2 + 0.161 NO3
− + 0.071 CH1.74O0.31N0.20 + 2.002 H2O (5)
Anammox bacteria are obligate anaerobes, meaning they are highly sensitive to oxygen, and very slow growing chemolithoautotrophs, yielding relatively low biomass volume (Jetten et al., 2009; Seviour & Nielsen, 2010).
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2.3 Landfill leachate versus tanning wastewater
Due to the changing lifestyles and the growing industrial and commercial activities around the world, the solid waste production has also been increasing. Municipal solid waste (MSW) keeps on growing despite the fact that population grows at a slower rate. Sanitary landfills are the cheapest option of MSW disposal and that is one of the principal reasons it has a big acceptance around the world. Besides the low cost of landfilling, it also reduces environmental problems and allows the waste to decompose in controlled circumstances until its conversion to a sort of inert and stable material (Warah, 2001).
The main problem of landfill practice is its leachate production. Landfill leachate has gained attention because it constitutes a big source of contaminated wastewater and uncontrolled biogas release (Di Palma et al., 2012). Since sanitary landfills are the main MSW disposal treatment, they are part of the challenge because the produced leachate volume is increasing and needs to be properly treated (Renou et al., 2008).
2.3.1 Landfill leachate composition
The present project is based on the treatment of tannery wastewater; however, the reactor used for the experimental research was used previously for partial nitritation treatment research on old landfill leachate. Since data about this project was available, it was used for validation of the mathematical simulation model. The following information has as main objective to show the characteristics of landfill leachate in order to be able to compare it with tannery wastewater composition and treatment.
The definition of leachate refers to the aqueous effluent result of precipitation percolation through waste material, biochemical processes involved with waste or the water content of waste. Leachate characteristics include a large amount of organic matter, ammonia, nitrogen, heavy metals and chlorinated organic and inorganic salts (Clement et al., 1997).
There are two main factors that determine the characteristics of the landfill leachate: the volumetric flow rate and the composition. The amount of water coming from precipitation, run-off and infiltration percolating to the landfill play a major role, but also the nature of the waste and its compaction rate affect the final leachate characterization. Other parameters that affect leachate composition are the seasonal weather and mostly the landfill age because that determines the degree of solid waste stabilization (Lema et al., 1988). Since the age of the landfill influences the leachate quality, three types of leachate have been defined according to it: young, medium age and old (Table 4). Old landfill leachate contains the smallest concentrations of COD and its biodegradable fraction is also the smallest. Considering the organic content and the landfill age can be a robust criterion to select the appropriate treatment for the leachate (Renou et al., 2008).
Since landfill leachate characterization varies from landfill to landfill it is difficult to generalize information about it. The characteristics of landfill leachate are commonly presented in terms of COD, BOD, pH, suspended solids, heavy metals, ammonium nitrogen and total Kjeldahl nitrogen (TKN). Usually pH value ranges 5.8-8.5 and most of the TKN composition is ammonia but it can go from 0.2 to 13,000 g.m-3. As the landfill age increases, the biodegradable fraction of COD decreases and the ammonia concentration increases (Chian & De Walle, 1976).
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Table 4. Landfill leachate classification according to age. Old landfill leachate shows similar characteristics to tanning wastewater (Renou et al., 2008).
Young Medium Old
Age (years) < 5 5.0 - 10 >10
pH 6.50
6.5 -7.5
>7.5
COD (g.m-3) >10,000
4000 - 10000
<4000
BOD5/COD >0.3
0.1 - 0-3
<0.1
Organic compounds 80% VFA
5-30% VFA + humic and fulvic acids
Humic and fulvic acids
Heavy Metals Low-Medium
-
Low
Biodegradability Important Medium Low
Table 5 shows information from Renou et al. (2008), of a review about the composition of different landfill leachates classified as old that came from different parts of the world. It is clear that the biodegradable fraction of the chemical oxygen demand is very small, even smaller than the average value for tannery wastewater; however it shows a higher average total nitrogen and ammonium concentration than tannery effluent. For further information about characteristics of young and median age leachate Renout et al. (2008) can be referred.
Table 5. Old landfill leachate composition from different landfill sites (Renou et al., 2008). All concentrations are in (g.m-3) except for BOD/COD and pH.
Site COD BOD BOD/COD pH SS TKN NH3-N Brazil 3460 150 0.04 8.2 - - 800 Estonia 2170 800 0.37 11.5 - - - Finland 556 62 0.11 - - 192 159 Finland 340-920 84 0.09-0.25 7.1-7.6 - - 330-560 France 500 71 0.01 7.5 130 540 430 France 100 3 0.03 7.7 13-1480 5-960 0.2 France 1930 - - 7 - - 295 Malaysia 1533-2580 40-105 0.03-0.04 7.5-9.4 159-233 - - South Korea 1409 62 0.04 8.57 404 141 1522 Turkey 10000 - - 8.6 1600 1680 1590
2.3.2 Comparison between landfill leachate and tanning wastewater treatment methods
Similar challenges in relation to the treatment of tanning wastewater are dealt with for the treatment of landfill leachate, especially when the age of it is categorized as old and therefore the biological fraction of COD is in most cases even lower than 10%. The COD concentrations in old landfill leachate are in average lower than the average value in tanning wastewater, although in many cases they have shown the same levels. As for nitrogen content, old landfill leachate presents higher concentrations than the ones in tannery effluents in most of the cases shown in literature.
Just as tannery wastewater, landfill leachate composition varies from site to site depending on the type of waste and the weather where the landfill is located, therefore treatments applied to it are also very variable, not only depending on the composition but also on the technologies available and the cost of them.
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Typical landfill leachate treatments
Leachate transfer has been a common method that consists in combining landfill leachate with municipal sewage in the municipal wastewater treatment plant, but this practice has been criticized because the heavy metal and low biodegradability compounds content in the landfill leachate can decrease the efficiency of the treatment. One advantage of this practice is that landfill leachate provides nitrogen to the treatment and municipal sewage provides phosphorus, therefore these nutrients do not have to be added to the process anymore (Ceçen & Aktas, 2004).
Recycling is known as one of the cheapest option, recycling the leachate back to the tip of the landfill has been commonly used and it has proven benefits such as increasing the moisture content and distribution of nutrients and enzymes for the bacterial communities (Bae et al., 1998). The recirculation method, besides raising the quality of the leachate, also decreases the time period necessary to stabilize the solid waste from decades to two or three years (Reinhart & Al-Yousfi, 1996). However, the excessive recirculation or amount of leachate recirculating can bring adverse effects on the process, such as saturation or very acidic conditions that inhibit methanogens activity (Chang et al., 2002).
These two methods are not applicable to tanning wastewater due to the nature of its source; therefore they cannot be compared with tanning wastewater treatments.
Biological treatments
Just as in biological treatments for tanning wastewater, and in general in all biological treatments, microorganisms are also used for removal of BOD concentrations in landfill leachate. Biological treatments applied to landfill leachate have been proven to be more effective for young leachate, because the biodegradable faction of COD is larger than 0.5 (Lema et al., 1988). The effectiveness of biological treatments possesses a negative correlation with the landfill leachate age (Renou et al., 2008).
Aerobic treatments. This kind of biological treatment should partially abate biodegradable organic pollutants and also perform ammonium-nitrogen nitrification. Some of these treatments are based on suspended-growth biomass and have been used for long such as aerated lagoons, sequencing batch reactors (SBR) and activated sludge processes. These processes in general represent a good alternative because of low cost, high COD removal and heavy metals recovery (Hoilijoki et al., 2000). SBR in specific are suited for an effective nitrification-denitrification process (Diamadopolous et al., 1997). Attached-growth systems make use of biofilms, therefore there is no loss of active biomass, plus high nitrogen content and low temperatures have less effect on nitrification processes. Moving-bed biofilm reactors (MBBR) offer higher tolerance to toxic compounds because of higher biomass as it grows in a suspended porous polymer material, which is in constantly moving. Because of this feature, it has also shown to remove organics and high ammonia in one single process (Loukidou & Zouboulis, 2001).
Anaerobic treatment. Anaerobic treatments are ideal to treat young landfill leachate as it is characterized by high load of organic compounds (Pokhrel & Viraraghavan, 2004). Suspended-growth biomass processes have 80-90% of COD removal in a 35 °C laboratory scale, and 55% COD removal at ambient temperature (Lin, 1991). The anaerobic stage in sequencing batch reactors (SBR) can reduce significantly the organic content and higher nitrification performance can be achieved in the aerobic reactor and that is why anaerobic-
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aerobic systems are recommended to raise the removal efficiency of organic matter and nitrogen (Martienssen & Schops, 1997). Up-flow anaerobic sludge blanket (UASB) reactor offers high treatment efficiency with short hydraulic retention time. At 35 °C, the COD removal is 80% and between 20-23 °C it is around 70%. The principal drawback of this system is the high sensitivity to toxic substances (Kennedy & Lentz, 2000).
Attached-growth biomass processes include the anaerobic filter, which is a high rate filter where the biofilm is formed with the biomass retained on the support material; it has reported COD removal efficiency of 90% for different landfill leachate ages (Henry et al., 1987). The hybrid bed filter is another process in this sub-classification that consists of an anaerobic filter on top and an up-flow sludge blanket on the bottom; it works as a gas-solid separator and improves solid retention (Timur & Ozturk, 1997) but a disadvantage is the high cost of the support media. Finally, the fluidized bed reactor, which has proven higher effectiveness treating old landfill leachate when it is combined with biological activated carbon in the bed (Imai et al., 1993).
Constructed Wetlands. The effectiveness of the CWs treatment for landfill leachate is highly dependent on an effective pre-treatment before it is discharged to the CW and the CW type; surface flow leachate have shown better results than sub-surface horizontal flow leachate (Wojciechowska et al., 2010)
Mechanical and physical treatments
As the physical treatments applied for tannery effluents, the ones applied to landfill leachate also aim to reduce suspended solids concentrations, colloidal particles, colour and toxic substances. They are used as an additional process to the selected treatment, either as pre or post-treatment or to remove a specific contaminant (Renou et al., 2008).
Flotation is a common practice for removal of colloids, macromolecules and so on, but it has also been used as post-treatment to remove humic acids remaining from previous treatments with 60% effectiveness (Zouboulis et al., 2003).
Coagulation- flocculation has been used for old or stabilized leachate but it can also be used as a pre-treatment before biological processes or reverse osmosis, just as it is applied for tanning wastewater; also can serve as post-treatment to remove the non-biodegradable fraction of organic matter.
Adsorption of contaminants is also a known practice for landfill leachate treatment but there is not much literature available when it comes to tannery effluent applications; it can be done with activated carbon or powdered activated carbon (PAC) and it has a better performance on COD removal than chemical methods disregarding of the initial organic concentration. PAC can also be an auxiliary method to biological treatments to reduce non-biological organic matter (Ceçen & Aktas, 2004). The principal disadvantage of this material is the frequent regeneration needed for its proper performance. Other adsorption material is pre-treated peat, it is used for ammonia, COD and BOD removal and also to remove metals before further treatments (McLelland & Rock, 1988).
Membrane processes. Microfiltration (MF) is considered an effective treatment because it controls colloids and suspended matter, but it cannot be used alone and that is why is applied as pre-treatment for other membrane processes or in a joint treatment with chemical processes. Ultrafiltration (UF) process performance depends directly on the membrane
21
material (Renou et al., 2004). Membrane bioreactors are a mix of UF and bioreactors in a compact system that functions with high concentration of biomass and low sludge production, offering a high quality effluent (Van Dijk & Roncken, 1997). Nanofiltration (NF) uses a polymeric membrane that eliminates microbial, organic and inorganic pollutants (Peters, 1998). It has also been combined with physical methods with satisfactory results; however the disadvantage is the need of constant fouling control (Trebouret et al., 2002). Reverse osmosis (RO) regarding landfill leachate treatment, could be considered one of the most promising processes, although its disadvantages are the membrane fouling and the high volume concentrate generation (Rautenbach et al., 2000).
Chemical treatments
Chemical Oxidation is used for effluents that contain refractory compounds, which is the case of landfill leachate. There is growing interest nowadays in advanced oxidation processes (AOPs) such as ozonation, irradiation, ultrasound and catalyst among others. An advantage of these methods is that they make recalcitrant organic pollutants more biodegradable. Although they have proven to reduce COD concentrations as well (Haapea et al., 2002), they are mostly used as tertiary treatment before discharge to the environment (Silva et al., 2004).
Air stripping is still the most common method to remove ammonium from any kind of wastewater, and to do it requires high pH and the effluent gas that is contaminated must be treated with either H2SO4 or HCl (Marttinen et al., 2001).
Table 6. Removal efficiency for landfill leachate treatment methods (Renou et al., 2008).
Average removal (%) Process BOD COD TKN SS Turbidity Residuals Transfer
Combined treatment with domestic sewage Depending on the domestic water treatment plant Excess biomass
Recycling >90 60-80 - - - -
Lagooning 80 40-95 >80 30-40 30-40 Sludge
Physico/chemical
Coagulation/flocculation - 40-60 <30 >80 >80 Sludge
Chemical precipitation - <30 <30 30-40 >80 Sludge
Adsorption >80 70-90 - - 50-70 -
Oxidation - 30-90 - - >80 Residual O3
Stripping - <30 >80 - 30-40 Air -NH3 mixture
Biological
Aerobic processes >80 60-90 >80 60-80 - Excess biomass
Anaerobic processes >80 60-80 >80 60-80 - Excess biomass
Membrane Reactor >80 >85 >80 >99 40-60 Excess biomass
Membrane filtration
Ultrafiltration - 50 60-80 >99 >99 Concentrate
Nanofiltration 80 60-80 60-80 >99 >99 Concentrate
Reverse osmosis >90 >90 >90 >99 >99 Concentrate
From the previous information it can be concluded that there is no best method to treat landfill leachate as it was previously concluded for tannery wastewater. In Table 6 a summary of the landfill leachate removal efficiencies for parameters such as COD, BOD and TKN is shown. These parameters and the landfill leachate age are important in order to apply to most adequate treatment. Optimal treatment is still a challenge, however, the combination of treatment technologies has improved the effluent quality. More specifically RO offers the best solution for the water contamination problem.
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2.4 Concluding remarks
Tanning wastewater composition and concentrations cannot be characterized generically because the characterization varies depending on the facilities and processes applied in the industry, however it can be stated that water treatment needs to be applied to this effluent because ammonium and COD concentrations, among several other parameters, are too high compared with most water discharge regulations. An important remark for this master thesis is that the biodegradable fraction of the incoming COD tends to be small, meaning less than 20%.
Leachate characteristics include a large amount of organic matter, ammonia, nitrogen, heavy metals and chlorinated organic and inorganic salts (Clement et al., 1997). Old landfill leachate is comparable to tanning wastewater in the sense that its ammonium concentration is high (sometimes higher than tanning effluents) and the biodegradable fraction of COD is low. In fact, the biodegradable fraction of COD is smaller than 10%, which means it is even smaller than the one in tanning wastewater. Therefore, data on the partial nitritation of old landfill leachate can certainly be used to validate the mathematical model of the partial nitritation reactor used in this master dissertation to treat tanning wastewater
In the present study a partial nitritation process will be studied with tanning wastewater as influent; this means that ammonium concentration in it is partially oxidized to nitrite. The study covers the experimental use of a laboratory scale partial nitritation biofilm reactor and the mathematical model of same process for simulation.
During the study, environmental parameters, such as pH, DO concentration and temperature in the bulk liquid are monitored in order to allow the AOB community to partially oxidize the ammonium concentration in the influent, and at the same time prevent the NOB community from further oxidation of nitrite to nitrate. Due to this process conditions, the nitrogen effluent of the reactor should consist mainly of ammonium and nitrite in a ratio close to the stoichiometric equations of anaerobic ammonium oxidation process. Almost no conventional denitrification should be performed during the partial nitritation process, as the effluent is meant to be directed to an anaerobic ammonium oxidation reactor for an alternative denitrification process.
The partial nitritation experimental reactor was used for a previous study using old aged landfill leachate (Nguyen and Lan, 2014); since some characteristics of this effluent are also present in the tanning wastewater, available data from that study was used as reference for the current master thesis project in both experimental and simulation studies.
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3. Materials and Methods
This thesis deals with the experimental characterization of partial nitritiation in a biofilm reactor and the mathematical modelling of this process. The experimental work was performed in Vietnam in the period comprised between February and June 2015 and the mathematical modelling and simulation study to analyze the experimental data, was performed in Belgium in the period comprised between June and August.
The following information describes the materials and methods applied for both parts of the research work, the experimental laboratory-scale biofilm reactor study and for the mathematical modeling and simulation study.
3.1 Full-scale tanning facility
The experimental part of the study was performed at the Faculty of Environment and Natural Resources of the Ho Chi Minh City University of Technology in Ho Chi Minh City, Vietnam. The wastewater used for the experiments was taken from Dang Tu Ky Leather Co., located inside the Industrial zone Nhon Trach 1 in the Nhon Trach District, Dong Nai Province, Vietnam, from April to July 2015.
3.1.1 Production process
As mentioned in section 2.1.2, tanning effluent has different characteristics according to the processes and the chemicals used in them. Inside the facilities of Dang Tu Ky Leather Company (Figure 2 and Figure 3) the tanning process is performed. The production process of this company is illustrated in Figure 4, along with the input of raw materials and chemicals and wastes of each step. The nature of the input in each step influences the pH value and COD, BOD, suspended solids and heavy metals content in the effluent (e.g. during picking and tanning steps, sulfuric acid is added resulting in a wastewater with low).
Fig. 2. Exterior and interior facilities of the Dang Tu Ky Leather Company.
Fig. 3. Tanning tanks in the interior of the Dang Tu Ky Leather Company.
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Fig. 4. Production process in the Dang Tu Ky Leather Company (Adapted from Steinert, 2014).
25
The steps described in Figure 4 are not exactly the same as in the literature review and showed in Figure 1, this is due to the fact that tanning process is different from facility to facility and it is important to have an overview of the specific facility that produced the wastewater used in the current study.
3.1.2 Wastewater treatment
After the production process, all wastewater is combined and directed to a wastewater treatment plant (WWTP) inside the factory facilities. After the mechanical steps of the WWTP (Figure 5), the water is chemically treated in a batch process with Fe(II)SO4 and PAC (poly aluminum chlorine) for precipitation of S2
- and Cr with aeration steering system. Flocs containing Cr and Fe are formed, settled, and subsequently removed as sludge (Figure 6). Also H2SO4 is added for neutralization of the effluent and to make it suitable for further biological treatment. The effluent of the chemical stage of the WWTP has a negligible concentration of chromium in it, making the effluent suitable as input for biological systems of nitrogen removal.
Fig. 5. Mechanical WWT steps (A) sedimentation (B) screening.
Fig. 6. Chemical WWT tanks. The effluent of the chemical stage of WWTP is then pumped to an experimental unit sponsored by the Federal Ministry of Education and Research of Germany, where research on biological nitrogen removal using a membrane bioreactor is performed (subproject 8 of EWATEC COAST research Project and TU Braunschweig). In the experimental unit, the effluent of the chemical treatment is pumped from a sedimentation tank of the WWTP to a buffering tank. Subsequently, the water passes through various tanks and reactors (Figure 7):
1) From the buffering tank the water goes to a microflotation unit for suspended solids removal.
2) Next, it goes to another buffering tank of 2 m3 and then to the membrane bioreactor (2 membranes for microfiltration).
26
3) Finally, the bulk liquid passes to the anoxic zone with continuous stirring. The facilities for the subproject 8 of EWATEC COAST research Project and TU Braunschweig are shown in Figure 8.
Fig. 7. Schematic representation of the experimental unit sponsored by the Federal Ministry of Education and Research of Germany. The influent is the same influent used in the current study.
Fig. 8. Experimental unit sponsored by the Federal Ministry of Education and Research of Germany: (A) Laboratory (B) Exterior of the laboratory (C) MBR reactor (D) First buffering tank.
3.1.3 Available process data
Tests on NO2-, NO3
-, NH4+, Cr, SO4
2-, COD, DO, pH are performed on a weekly basis to the
influent and effluent of the mentioned experimental unit. The influent in this process is also the influent for the Partial Nitrification (PN) bioreactor used for the present master thesis project. Data from these tests were shared to be used as reference for the current study (Appendix 1).
27
3.2 Lab-scale partial nitritation experiment
3.2.1 Reactor set-up
In the laboratory of Advanced Waste Treatment Technology, Ho Chi Minh City University of Technology there is an experimental set-up of a partial nitritation process and a subsequent anammox process for biological nitrogen removal from the tanning wastewater obtained from Dang Tu Ky Leather Co. after mechanical and chemical treatment. Figure 9 shows the schematic representation of the complete laboratory set-up. Qin1 represents the influent for the partial nitritation process. The effluent of the PN reactor was stored in an exchange vessel from where the volume is divided to feed two anammox reactors, one with 8 liter capacity and operated under completely anaerobic conditions and the other with a capacity of 4 liters operated with anaerobic, anoxic and aerobic stages. This master thesis research focuses on the partial nitritation reactor. The PN reactor is made out of acrylic plastic (Figure 10), with two separate compartments: a reaction tank and a sedimentation tank. Partial nitritation takes place in the reaction tank. The volume of the reaction tank is 12 liters. Biomass carriers and air diffuser stone were fixed in the reaction tank. The air diffuser stone supplied aeration in small bubbles to enhance the dissolved oxygen concentration and to help the bulk water circulation inside the tank. The sedimentation tank, located on the right ride of the reaction tank, has a volume of 3 liters and its purpose is to separate the sludge coming from the reaction tank. Sludge recirculates from the sedimentation tank to the reaction tank. An air compressor connected to the air diffuser stone inside the tank supplied the air needed to perform partial nitritation. The airflow could be adjusted by means of a valve. The pH of the process was maintained constant between 7 - 7.5 using a pH controller that supplies NaHCO3 through a chemical pump to provide alkalinity. The temperature of the process was kept ambient, between 28 and 33oC.
Fig. 9. Experimental set-up of partial nitritation and anammox reactors.
28
A
Figure 10. Scheme of the partial nitritation reactor: (A) Flow scheme (adapted from Lam and Nguyen, 2014) (B) Picture of laboratory set-up: a) partial nitritation reactor b) anammox reactor.
The biomass carrier inside the PN reactor consisted of polyester fibers manufactured by Vilene Company (Japan) (Figure 11). The sponge-like material was shaped into a prismatic star of eight edges. Each edge has a width of 4.5 cm, length 41 cm and thickness of 0.5 cm. The total specific area of the substrate is 14.76 m2/m3 (Lam and Nguyen, 2014) and the total surface of the biomass carrier is 0.6304 m2.
Fig. 11. Polyester non-woven biomass carrier (Lam and Nguyen, 2014).
B
a) b)
29
3.2.2 Operating conditions
In order to acclimate AOB community to the high total dissolved solids (TDS) concentration in the influent, the influent was diluted with water before it was fed to the PN reactor, resulting in a decrease of the influent TDS concentration. NH4Cl was added at the same time to get the influent ammonium concentrations back at the original level (average concentration of 500 gNH4.m-3). The experimental operation included five stages (Table 7) starting on April 20th 2015 (day 1) and finishing on July 31st 2015 (day 100). The dilution rate was gradually decreased. DO concentration was modified and monitored along with pH and temperature, to assess its impact on the partial nitritation process in terms of ammonium conversion efficiency, nitrite accumulation and nitrite-ammonium ratio in the effluent. Table. 7. Operation stages of partial nitritation reactor.
Time (days)
Dilution 1:n pH NH4
+-N (g/m3)
TDS (g/m3)
1 - 30 4 7 - 7.5 500 3375 30 - 50 4 7 - 7.5 500 3375 51 - 60 3 7 - 7.5 500 4333 60 - 80 2 7 - 7.5 500 6250 80-100 1 7 - 7.5 500 12000
Analytical methods The measurements of the influent and effluent concentrations of ammonium, nitrite and nitrate and the bulk liquid concentrations of dissolved oxygen, pH and temperature were measured three times per week during the 100 of days the experiment. Ammonium-nitrogen (NH!!-N), nitrite-nitrogen (NO!!-N), nitrate-nitrogen (NO!!-N) and solids concentrations in the influent and effluent of the PN reactor model were determined according to the Standard Methods for the Examination of Water and Wastewater (APHA AWWA, 1999). The pH was controlled by the BL-981411-Hanna automatic systems manufactured in England and DO and temperature were measured using a DO-meter EXTECH 407510 made in Taiwan.
3.2.3 Available partial nitritation system data
Since the laboratory scale partial nitritation reactor was previously used to run a study with an influent of old landfill leachate (Nguyen and Lan, 2014), data about the operation conditions and influent and effluent nitrogen concentrations were available (Appendix 2). The study was conducted during 70 days in total: 25 days of start-up and 45 days in which the nitrogen loading rate (NLR) was increased. These data were used for analysis and comparison of the reactor performance.
30
3.3 Modelling and simulation study
In this study, nitrogen removal from tanning wastewater using a biofilm reactor for partial nitritation will be simulated. Mathematical modelling has gained popularity in the past few decades because it allows replicability of processes under changing parameters with no need of experimental facilities. Biological processes can be simulated using models that describe the kinetic rates and parameters involved in them. Autotrophic nitrogen removal in biofilm reactors was previously modelled in several studies such as the ones from Volcke et al. (2010) and Mozumder et al. (2013); the latter studies concern granular reactors with a nitrifying, denitrifiying and anammox bacterial communities (Volcke et al. 2010), besides heterotrophic bacteria (Mozumder et al. 2013).
In this study a mathematical biofilm model will be developed for the simulation of the partial nitritation reactor used during the experiments. The model will be validated using old landfill leachate data from a previous partial nitritation experimental study (Nguyen and Lan, 2014) that made use of the same experimental reactor set-up considered as in the current study.
3.3.1 Partial nitritation model
A one-dimensional biofilm model was set up in order to describe the interactions between the autotrophic and heterotrophic microbial communities. The model was implemented in the Aquasim simulation software (Reichert, 1994) to simulate the biological PN process. The model created by Volcke et al. (2010) and modified by Mozumder et al. (2013) was taken as base for this study and modified to describe the experimental set-up under study.
Growth and decay of the ammonium oxidizing bacteria (XAOB), nitrite oxidizing bacteria (XNOB) and heterotrophic bacteria (XH) were considered in the biofilm model. Ammonium oxidation to nitrite occurs in the nitritation process by XAOB, followed by nitrite oxidation to nitrate by XNOB. Free ammonia (FA) and free nitrous acid (FNA) inhibition were included in the model for this study, following Jubany et al. (2009). Heterotrophic bacteria can grow under both aerobic and anoxic (in presence of NO2
- and/or NO3-) conditions, their growth
relies on organic carbon, which is either present in the reactor influent or as the result of biomass decay. The stoichiometric matrix for the different bacterial groups and the kinetic rate expressions are given in Tables 8 and 9 respectively. Stoichiometric and kinetic parameters are listed in Appendix 3.
The model considered a total reactor volume of 0.012 m3 (bulk liquid, biomass carrier and biofilm). The model used by Mozumder et al. (2013) was adapted to work with a flat biofilm instead of granules. The flat biofilm in the experiments was calculated to represent a biofilm surface area of 0.63 m2. The biofilm initial and steady state thickness were set at 0.5mm, which is a rather high value, nevertheless still possible in BNR reactors (Eldyasti et al., 2014). Furthermore, as it was visually observed in the experimental reactor, the biofilm was rather thick. The dissolved oxygen in the bulk liquid was controlled at around 2.2 g.m-3 and the temperature was set at a value of 30oC. The model assumed that the bulk liquid was well mixed and the concentrations were equal throughout the bulk liquid. The number of grid points inside the biofilm for the simulation was set at 50.
31
Table. 8. Stoichiometric matrix of the used model Aij (adapted from Mozumder et al., 2013).
Aij i
component →
SS SNH SNO2 SNO3 SO2 SN2 XAOB XNOB XH XI [gCOD.m-3] [gN.m-3] [gN.m-3] [gN.m-3] [gO2.m-3] [gN.m-3] [gCOD. m-3] [gCOD. m-3] [gCOD. m-3] [gCOD. m-3]
j process ↓ Growth
Growth of XAOB -1/YAOB -
iNXB 1/YAOB 1-3.43/YAOB 1
Growth of XNOB -iNXB -1/YNOB 1/YNOB 1-
1.14/YNOB 1
Aerobic growth of heterotrophs -1/YH -iNXB+1/
YH. iNSS 1-1/YH 1
Anoxic (on NO2
-) growth of heterotrophs
-iNXB+1/ YH. iNSS
1
Anoxic (on NO3
-) growth of heterotrophs
-iNXB+1/ YH. iNSS
1
Decay
Decay of XAOB 1-fI iNXB - fI iNXI – (1-fI) iNSS -1 fI
Decay of XNOB 1-fI iNXB - fI iNXI – (1-fI) iNSS -1 fI
Decay of XAN 1-fI iNXB - fI iNXI – (1-fI) iNSS fI
Ddecay of XH 1-fI iNXB - fI iNXI – (1-fI) iNSS -1 fI
Composition matrix
gCOD/unit comp 1 0 -3.43 -4.57 -1 -1.71 1 1 1 1
gN/unit comp iNSS 1 1 1 0 1 iNXB iNXB iNXB iNXI
32
Table. 9. Kinetic rate expressions of the used model (adapted from Mozumder et al., 2013).
j process ↓
Growth of AOB
ρG,AOB = 𝜇!"#!"# ∙ !!!!!!!"#! !!!
∙ !!"
!!"!"#! !!"!
!!"!
!"!"!"#
∙ !"!"!!"#
!"!"!!"#!!!"!
∙ 𝑋!"#
Growth of NOB
ρG,NOB = 𝜇!"#!"# ∙ !!!!!!!"#! !!!
∙ !!"!!"!"#$! !!"
∙ !!"!
!!"!!"#! !!"!!
!!"!!
!"!"!!"#
∙ !"!"!"#
!"!"!"#!!!"
∙ 𝑋!"#
Growth of aerobic heterotrophs
ρG,H =
Anoxic growth (on NO2) of heterotrophs
ρAG,HNO2
=
Anoxic growth (on NO3
-) of heterotrophs
ρAG,HNO3
=
Decay of AOB
ρD,AOB =
Decay of NOB
ρD,NOB =
Decay of heterotrophs
ρD,HA =
3.3.2 Simulation set-up
Two different kinds of influent were accounted for the simulation study. Aiming for validation of the model, old landfill leachate data from Nguyen and Lan (2014) study was simulated. In parallel, available results on partial nitritation of tanning wastewater were also introduced in the model for simulation. For both influents, a reference case was set-up, and to achieve successful partial nitritation process at steady state with a fixed ammonium concentration in the influent, specific parameters were included and/or adapted in the model. After steady state analysis, the adapted models were used to simulate the available dynamic data. For both tanning and leachate wastewater, the model needed to be adapted further to reflect the dynamic PN reactor behaviour.
Reference case
The model of Mozumder et al. (2013) was used with some adaptation in the parameters. The pH was set at 8.1 and temperature at 30℃. Affinity constants for AOB and NOB were
HNH
NOBHNH
NH
OHO
O
SHS
SH XSK
SSK
SSK
S⋅
++⋅
+⋅ .
22
2maxµ
HNH
NOBHNH
NH
SHS
S
NONO
NO
NOHNO
NO
OHO
HO
NOH X
SKS
SKS
SSS
SKS
SKK
⋅++
⋅+
⋅+
⋅+
⋅ .η32
2
22
2
22
22maxµ
HNH
NOBHNH
NH
SHS
S
NONO
NO
NOHNO
NO
OHO
HO
NOH X
SKS
SKS
SSS
SKS
SKK
⋅++
⋅+
⋅+
⋅+
⋅ .η32
3
33
3
22
23maxµ
AOBAOB Xb
NOBNOB Xb
HHXb
33
calculated accordingly. The COD concentration in the influent (considering that COD in the model represents the biodegradable part of the total COD) was set at 100 g.m-3 and the ammonium concentration in the influent was set at the highest value of the experimental data available (1200 gN.m-3 for landfill leachate and 500 gN.m-3 for tanning wastewater). The DO concentration was set at 2.5 g.m-3. No inhibition terms were considered in the reference case 𝐾𝑖!"!"# = 𝐾𝑖!"!!"# = 𝐾𝑖!"!"# = 𝐾𝑖!"!!"# = ∞ . The simulation was run until it reached steady
state (2000 days).
Adaption for steady state simulation
Simulations with the reference case model were run for both influent types, just modifying the influent ammonium concentration representative for each one. As partial nitritation at steady state was not achieved, some parameters in the model were adjusted and inhibition was added to the growth rates for the AOB and NOB bacterial communities to achieve partial nitritation results at steady state according to Jubany et al. (2009). These parameters were pH, DO concentrations and the inhibition constants besides nitrogen and carbon loading rate; the two latter were modified from the reference case values because the NLR for landfill leachate was increasing in the experiment and there were no strict measurements of COD concentrations for neither of the two influent types.
Parameters adapted for dynamic simulation
The simulation set-ups for steady state were taken as a starting point for the dynamic simulation. For each of the influent types, two simulations were run according to the following steps:
1. The available ammonium concentrations in the influent were introduced in the model as a dynamic variable in time. All other parameters maintained their values set for the steady state simulations. The simulation was run for as many days as the influent data was available.
2. A parameter estimation was performed to find the most suitable values of bulk DO and influent COD concentrations for tanning wastewater, the same parameters beside the FA and FNA inhibition constants for old landfill leachate, to fit the effluent simulation results to the experimental effluent data in terms of ammonium, nitrite and nitrate.
34
4. Results and discussion 4.1 Experimental work
4.1.1 Reactor performance
During the experimental work in Ho Chi Minh University of Technology, the ammonium, nitrite and nitrate concentrations in the influent and effluent, and the oxygen concentration in the bulk liquid, were recorded. Data of the first 40 days of the process were available at the time this master thesis was written.
The recorded data are expressed in Figure 12 and show that both ammonium and nitrite were present in the effluent during the first 40 days of the experiment, however at different concentrations. Nitrite and nitrate concentrations in the influent were not taken into account in the figure because both showed measured concentrations of less than 1gN.m-3, therefore the total nitrogen concentration in the influent is equal to the ammonium concentration in the influent. There was a lack of measurements from day 8 until day 18.
Fig. 12. Concentration of ammonium in the influent (expressed as total influent of nitrogen) and ammonium, nitrite, nitrate and total nitrogen in the effluent of the partial nitritation reactor fed with tanning wastewater during the first 40 days of experiment.
Ammonium is being converted on an average efficiency of 52% ± 12% (20 samples) compared to the ammonium concentration in the influent. Nitrite accumulation was performed with an average efficiency of 34% ± 17% (Figure 13), which means that nitrite concentrations increased to 161.5 ± 86.5 gN.m-3. Nitrate concentrations remained low at an average value of 4.5 ± 3.1 gN.m-3 which can prove that the NOB were inhibited in the biofilm and the AOB were performing the partial nitritation of the ammonium concentration in the influent. The average nitrite-ammonium ratio in the effluent was 0.52 meaning a PN efficiency of 46% compared to 1.14 ideal ratio (Lotti et al., 2004).
The nitritation process achieved, meaning nitrite production without nitrate, can be explained with the relatively high temperature of the bulk liquid (around 31℃) and pH value around 7
0
100
200
300
400
500
600
0 5 10 15 20 25 30 35 40
Con
cent
ratio
n (g
.m-3
)
Time (days)
Total N influent
Ammonium effluent
Nitrate effluent
Nitrite effluent
Total N effluent
35
that prevent nitrite oxidation. At temperatures above 30℃ and pH value of 7 the AOB grow faster than the NOB (Hellinga et al., 1998).
The production of the appropriate nitrite-ammonium mixture depends on the alkalinity-ammonium ratio in the influent. For oxidation of ammonium to nitrite, two proton equivalents are produced per mol of ammonium converted (Fux et al., 2002). Half of these protons are neutralized by CO2-stripping. As result, for influents with bicarbonate and ammonium in the same molar amounts and without pH control in the reactor, typically half of the ammonium would be converted before significant pH decrease occurs. To obtain higher ammonium conversion, the pH value would need to be corrected (Volcke, 2006). The experimental reactor for the partial nitritation process had an automatic pH control system that maintained the pH at a neutral value (7-7.5) by addition of sodium bicarbonate. According to this, a higher ammonium conversion would have been taking place and more than half of the available ammonium would have been converted to nitrite. The experimental results on Figure 13 prove otherwise by showing that on average, 52% of ammonium was converted. This could be explained by miscalibration in the pH control, possibly keeping the process at a higher pH value (some measurements showed pH value around 8), therefore the free ammonia concentration raised and the AOB could have been inhibited, limiting the ammonium oxidation efficiency.
Fig. 13. Ammonium conversion efficiency and nitrite accumulation in the bulk liquid of the partial nitritation reactor fed with tanning wastewater during the first 40 days of the experiment (20 samples). (Ammonium conversion efficiency = NH4
+ effluent/ NH4+ influent.
Nitrite accumulation = NO2- effluent/ NH4
+ influent).
4.1.2 Nitrogen balance
The total nitrogen concentration in the influent had an average value of 473 ± 39.2 g.m-3 but in the effluent it was an average of 392 ± 74.5 g.m-3. The nitrogen gap represents an average of 13% ± 18% of the nitrogen concentration in the influent. This gap in the nitrogen balance was further investigated. First, it was taken into account that the bulk liquid was diluted by the amount of NaHCO3 solution that is introduced to the system by the automatic pH regulator. The corresponding mass balance is as follows (Equation 6):
𝑸𝒊𝒏 .𝑺𝑵𝑯𝟒𝒊𝒏 = 𝑸𝒐𝒖𝒕 𝑺𝑵𝑯𝟒
𝒐𝒖𝒕 + 𝑺𝑵𝑶𝟐𝒐𝒖𝒕 + 𝑺𝑵𝑶𝟑
𝒐𝒖𝒕 (6)
0% 10% 20% 30% 40% 50% 60% 70% 80% 90%
1 2 5 7 19 21 22 23 26 27 28 29 30 33 34 35 36 37 39 40
Eff
icie
ncy
(%)
Time (days)
Ammonium conversion
Nitrite accumulation
36
With 𝑸𝒐𝒖𝒕 calculated as (Equation 7):
𝑸𝒐𝒖𝒕 = 𝑸𝒊𝒏 + NaHCO3 influent = 12.36 m3.day-1 (7)
On average 473 gN.m-3 (20 samples) were introduced in the system, while 392 gN.m-3 exited the system in the effluent.
0.012 m3.day-1 * 473 g.m-3 = 0.01236 m3.day-1 * 392 g.m-3
5.676 g.day-1 = 4.845 g.day-1
Around 15% of the nitrogen content in the effluent is not being acknowledged in the measurements of the effluent. Also when the same experimental set-up was used to treat landfill leachate (Nguyen and Lan, 2014), an average of 9 ± 17% of the nitrogen measured in the influent was missing from the effluent, Nguyen and Lan (2014) do not discuss nor give any possible reasons why the total amount of nitrogen is not maintained during the process. A missing fraction of nitrogen in the mass balance of an aerated partial nitritation reactor can be attributed to several reasons:
• Nitrogen is incorporated in the biomass during growth • Denitrification • Ammonia volatilization • Nitrous oxide formation • Measurement errors
Nitrogen is incorporated in the biomass during growth, as all living organisms need nitrogen to survive. The nitrogen content of the biomass in the reactor was calculated according to the model of Mozumder et al. (2013). For the current model, the biofilm surface area (0.6304m2) and the biofilm thickness (0.0005m) were used to calculate the biofilm volume (0.0003152m3). The bacterial density is given by the expression 60,000/0.75/0.2 gCOD.m-3, corresponding to 80,000 gVSS.m-3 for a typical conversion factor of 0.75 gVSS.g-
1COD (Henze et al., 2000; van Benthum et al., 1995) and the total biomass fraction is assumed to be 0.2 (Mozumder et al., 2013). Also, Mozumder et al. (2013) takes as an assumption that the nitrogen content in the biomass is 0.07 gN.g-1COD, therefore we can calculate that the amount of biomass in the biofilm volume was around 126.08 gCOD and the nitrogen content in this biomass was around 8.82 gN. This amount of nitrogen represents 1.8% of the total nitrogen in the influent and can, thus in a small extent, explain the missing nitrogen in the effluent.
Denitrification can also take place in the reactor although it is not the aim of the system. Since the reactor can develop zones with low oxygen concentration, some anoxic bacteria can be growing in them and performing oxidation of NO3 to N2, which escapes from the reactor to the atmosphere. It is difficult to estimate the amount of nitrogen escaping via this route in this case, as no feature to trap and measure the gaseous effluent was installed. Furthermore, possible nitrogen bubbles could not be distinguished from the bubbles created in the bulk liquid by the aeration system. According to the stoichiometry of denitrification process (Equation 3), a theoretical example can be explained, although COD in the influent is partially biodegradable and partially not biodegradable, and no methanol was added to the influent. Denitrification according to equation 3 uses methanol as carbon source. For each 5g of methanol and 6g of nitrate, 3g of nitrogen gas will be produced (Tchobanoglous et al., 2003). If the 15% of the nitrogen that is missing from the mass balance is escaping in the
37
form of nitrogen gas as result of denitrification process, that means that 70 gN would have to undergo this process daily. Taking into account that 1g of methanol equals 1.5g of COD and assuming that all COD is biologically degradable, 175 gCOD had to be used only by heterotrophs just for the denitrification process. According to literature conclusions on the biodegradable fraction of the influent COD in tanning water being likely to be <20%. Taking into account the total COD concentrations in the influent that were measured in the tanning wastewater by subproject 8 of EWATEC COAST research Project and TU Braunschweig, Germany (an average of 1755 gCOD.m-3), there is possibly around 351gCOD.m-3 available for the heterotrophs. This means that the amount of COD required for 70g of N2 production is certainly available and therefore if the conditions for denitrifying bacterial communities to develop are also available, it could be possible that the missing nitrogen amount in the mass balance has escaped the reactor as nitrogen gas. However, these hypothetical calculations are neglecting that COD will also, or even in the first place, be converted by heterotrophs under aerobic conditions.
Furthermore, biomass decay can also provide the heterotrophs with readily biodegradable COD. However, the nitrogen denitrified based on COD set free during biomass decay is assumed to be negligible based on simulation results of Mozumder et al. (2013).
Nitrous oxide can be formed during nitrification and denitrification processes. The AOB are one of the bacterial groups responsible for N2O formation during nitrification (Beumont et al., 2002). Heterotrophic denitrifiers are also able to produce N2O since this compound is an obligate intermediate during denitrification. N2O emissions are related to the presence of oxygen or nitrite accumulation during heterotrophic denitrification (Lu and Chandran, 2010; von Schulthess et al., 1994; Wunderlin et al., 2012). Since denitrification is very likely to be taking place, nitrous oxide emissions are accompanying this process. Since the aeration system was working continuously inside the reactor, according to Castro-Barros et al. (2015) formation of N2O was likely to occur in an average of 2% of the incoming nitrogen load, escaping as off-gas and even accumulating in the liquid phase.
Ammonia volatilization can be taking place since the reactor is open and the ambient temperature tends to be high because of the tropical weather that characterizes Ho Chi Minh City (an average of 31℃). Ammonia content could be stripped out of the bulk liquid into the atmosphere as result of the high dependence of the percentage of free ammonia in the total ammonium-nitrogen content as shown in Figure 15 (Anthonisen et al., 1976). This could also be the reason why there is a strong smell in the facilities of the faculty where the experiment is being conducted. It is important to consider that the influent concentrations of the different nitrogen components are measured from an 80 liters container that is not hermetically sealed, therefore ammonia can also be volatilized from it before the influent entered the reactor. Since the influent measurements are not taken from the actual influent volume, but from the container, even not proper homogenization of the influent container before taking the measurement could represent a threat for the measurement accuracy. It could be recommended to provide the reactor in the experimental set-up of the Ho Chi Minh University of Technology with cover lids or floating material preventing evaporation to avoid ammonia stripping. Sealing the container with the wastewater that will be used as influent will also prevent ammonia stripping. A further addition could be a gas trap and measurement device for the out-coming flow of gas produced during the process to quantify the nitrogen concentration and have a more accurate mass balance.
38
Errors in the measurements can always be possible. In Figure 12 few measurements of the total nitrogen in the effluent are higher than the nitrogen content in the influent, which raises the concern on the accuracy of the measurements. Errors can be attributed to human error or to equipment miscalibration or malfunctioning.
4.1.3 Influence of operating variables
The pH value for the whole process was controlled, therefore the influence of this parameter in the process performance variation cannot be considered. On the other hand, DO concentrations were changing with time according to the manual adjustment of the aeration valve. In Figure 14 the influence of DO concentrations on the nitrite-ammonium ratio is shown, as well as on the ammonium removal efficiency of the process. The variations of DO concentrations in the bulk liquid do not seem to be crucial for the ammonium removal efficiency of the process because the values do not vary more than 10% in the DO range from 1.4 to 2.8 g.m3; however for the nitrite-ammonium ratio it is highly influential. The ideal ratio according to the stoichiometric parameters of the anammox process is 1.32 (Strous et al., 1999) although Lotti et al. (2014) has recently discovered a new stoichiometry for anammox yield in which there is a need of a nitrite-ammonium ratio of 1.14. To obtain either one of the ideal ratio values, it would be necessary to first achieve a DO concentration between 2.2 and 2.8 g.m3 according to the experimental measurements available in the 20 samples. It is important to mention that in order to achieve the newly discovered ratio by Lotti et al. (2014), the DO concentration would have to be lower than the one necessary to achieve the ratio in the stoichiometry discovered by Strous et al. (1999).
Fig. 14. Effect of DO concentration in the partial nitrification reactor fed with tanning wastewater during the first 40 days of the experiment on (A) NO2
-/NH4+ ratio (B) ammonium
conversion efficiency.
4.2 Simulation study
4.2.1 Reference case simulations
The nitrifying biofilm model described in section 3.3.1 was first applied to simulate partial nitritation of landfill leachate and tanning wastewater with slight value adaptation described as reference case (section 3.3.2). Figure 15 shows the nitrogen components in the effluent for the simulation of the reference case setting the ammonium concentration in the influent at 1200 gN.m-3 for old landfill leachate and 500 gN.m-3 for tanning wastewater. There was no ammonium present in either of the simulations and the NOB were not inhibited as nitrate was present in the effluent, therefore there was no partial nitritation process being performed. Next, as partial nitritation process was not possible to simulate, some parameters were
0
1
2
3
1.4 2 2.1 2.2 2.8
NO
2 - :NH
4+ ra
tio
DO concentration (g.m-3)
A
0
50
100
1.4 2 2.1 2.2 2.8 NH
4+ c
onve
rsio
n (%
)
DO concentration (g.m-3)
B
39
adjusted and/or added for this purpose. Subsequently, simulations were run using the available dynamic data from the experimental studies. The results were analyzed considering the effluent composition and the substrates and biomass concentration in the biofilm.
Fig. 15. Concentration of nitrogen components in the effluent of reference case simulation during 2000 days with (A) old landfill leachate as influent (B) tanning wastewater as influent.
4.2.2 Model adaptation for steady state simulations
To run the model to actually perform partial nitritation the following parameters were adjusted and inhibition by FA and FNA were added in the model kinetic expressions for the AOB and the NOB bacterial communities.
DO concentrations
The concentration of DO for old landfill leachate was set at 2.5 g.m-3, like the average value from Nguyen and Lan (2014) study and at 2.2 g.m-3 for tanning wastewater, where the oxygen concentration varied in a lower range.
0
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N2
NH
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NO3
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40
Influent concentrations of ammonium and COD
The influent COD and NH concentrations were defined based on information from literature and on the available experimental data. For old landfill leachate, the ammonium value was set at 1090 gNH.m-3. Ammonium concentration was chosen to be constant around the average of the observed influent concentrations range (800 - 1200 gNH.m-3) from the study by Nguyen and Lan (2014). The total COD in the influent was set at 0 gCOD.m-3 even though there was no available data concerning the biodegradable COD concentration in the bulk liquid in the study by Nguyen and Lan (2014). Renou et al. (2008) and Chian and De Walle (1976) emphasize that the biodegradable fraction of COD in old landfill leachate is very minimal and close to zero.
For tanning wastewater the ammonium value was set at 500 gNH.m-3 based on the experimental set-up (section 3.2.2). The COD concentration was set at 250 gCOD.m-3 based on the literature value of biodegradable fraction of total COD, which is an average of 20% in tannery effluents. The total COD in the influent was on average 1300 gCOD.m-3, based on the information provided by the experimental unit sponsored by the Federal Ministry of Education and Research of German (Appendix 1).
Affinity constants at a certain pH
The model was kept at a constant temperature of 30℃. The pH selected for the simulations with landfill leachate was set at 8.1, as the average pH value described by Nguyen and Lan (2014). This pH value has corresponding affinity constant values of 𝐾!"!"# at 0.3 gN.m-3 and 𝐾!"!!"# at 2.04 gN.m-3. For tanning wastewater the pH was set at a value of 7 according to the experimental set-up (see section 3.2.2), and corresponding affinity constant values at 𝐾!"!"# at 3.46 gN.m-3 and 𝐾!"!!"# at 0.162 gN.m-3.
The affinity constants for AOB (𝐾!"!"# ) and NOB (𝐾!"!!"# ) are dependent on pH and temperature. Figure 16 shows the dependency of the affinity constants of AOB and NOB for ammonium and nitrite on to the different pH values at a temperature of 30℃. The pH value in the reactor is an important factor to determine the amount of free ammonia (FA) and free nitrous acid (FNA) in the system, at increasing pH, FA concentration increases and FNA concentration decreases. It is visible that AOB and NOB affinities behave in an inverse way depending on the pH changes.
Fig. 16. Affinity constants for AOB and NOB bacterial communities at different pH values and temperature of 30℃.
0
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7 7.5 8 8.5
k (g
N.m
-3)
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K_AOB_NH K_NOB_NO2
41
FA and FNA inhibition
As explained by Anthonisen et al. (1976), high concentrations of free nitrous acid (FNA) and free ammonia (FA) can act as an inhibitor for AOB and/or NOB communities affecting or even suppressing their development. The PN process requires AOB to oxidize ammonium and at the same time to inhibit NOB to prevent further nitrite oxidation to nitrate. To set inhibition constants based on FA and FNA concentrations is another way to approach the simulation study to the factual process conditions that are maintaining these bacterial communities from growing more than the right concentrations, and perform PN efficiently.
The inhibition of AOB and NOB by FA and FNA was added to the model and included as a factor of AOB 𝐾𝑖!"!"# ,𝐾𝑖!"!!"# and NOB 𝐾𝑖!"!"# ,𝐾𝑖!"!!"# growth rate expressions originally described in the model adapted by Mozumder et al. (2013) (Equation 8 and 9). The inhibition constants followed the growth rate expressions as described in Jubany et al. (2009).
ρG,AOB = 𝜇!"#!"# ∙ !!!!!!!"#! !!!
∙ !!"
!!"!"#! !!"!
!!"!
!"!"!"#
∙ !"!"!!"#
!"!"!!"#!!!"!
∙ 𝑋!!" (8)
ρG,NOB = 𝜇!"#!"# ∙ !!!!!!!"#! !!!
∙ !!"!!"!"#$! !!"
∙ !!"!
!!"!!"#! !!"!!
!!"!!
!"!"!!"#
∙ !"!"!"#
!"!"!"#!!!"
∙ 𝑋!"# (9)
Concentrations of FA and FNA were expressed in terms of the model state variables as total ammonium (TNH) and total nitrite (TNO2) according to the corresponding temperature set in the model and the pH value for each kind of influent. The amount of FA and FNA are highly dependent on the temperature and the pH value, as shown in Figure 17. At fixed pH value of 7.5, as temperature increases the FA fraction of the total ammonium increases and the FNA concentration decreases. At a fixed temperature of 30℃, the FA concentration increases at pH above 7.5 and the FNA concentration increases at a pH value below 6.
Fig. 17. Percentage of FA of TNH and FNA of TNO2 depending on the temperature and pH values: (A) Percentage of FA in TNH at different temperatures and at pH value of 7.5, (B) Percentage of FNA in TNO2 at different temperatures and at pH value of 7.5, (C) Percentage of FA in TNH at different pH values at 30℃ (D) Percentage of FNA in TNO2 at different pH values at 30℃ (adapted from Anthonisen et al., 1976).
42
The values to inhibit NOB were chosen to be very low; therefore the inhibition was higher because this bacterial community had to be inhibited completely in order to achieve partial nitritation. For AOB inhibition the values were chosen to be a little higher according to some studies (Table 10), because this bacterial community needs to be present to perform the partial nitritation process, therefore its inhibition has to be lower.
Table 10. Inhibition constants of FA and FNA, expressed in terms of TNH and TNO2 respectively, for AOB and NOB bacterial communities (8.1 pH value and temperature of 30℃ for old landfill leachate and at 7 pH value and temperature of 30℃ for tanning wastewater).
Old landfill leachate and Tanning wastewater
Old landfill leachate (30oC, pH 8.1)
Tanning wastewater (30oC, pH 7)
Ki_AOB Ki_NOB Ki_AOB Ki_NOB Ki_AOB Ki_NOB Source (g.m-3) (g.m-3) (g.m-3) (g.m-3) (g.m-3) (g.m-3)
FA FNA FA FNA TNH TNO2 TNH TNO2 TNH TNO2 TNH TNO2
48.09 - - - 516 - - - 5943 - - - Carrera et al. (2004) - 0.053 - - - 3382 - - - 268 - - Panbrun et al. (2006) - - 0.43 - - - 4 - - - 53 - Baquerizo et al. (2005) - - - 0.018 - - - 1148 - - - 91 Jubany et al. (2008)
For both influents, the concentrations of FA and FNA to inhibit the AOB and the NOB were chosen to be the same. However, since old landfill leachate has a pH of 8.1 and tanning wastewater a pH of 7, the corresponding fractions of these two inhibiting compounds had different concentrations in terms of TNH and TNO2.
For old landfill leachate the inhibition constant value for AOB by FA (516 gTNH-N.m-3) was chosen to be a higher value than the corresponding ones for NOB inhibition by FA and FNA in revised literature. Otherwise they would have been inhibited the AOB growth too much and no partial nitritation would have been performed. For inhibition of the AOB by FNA, again the lower value was chosen (3382 gTNO2-N.m-3) and it was was still too high to inhibit this bacterial community because even if all ammonium influent was converted to nitrite, the maximum nitrite concentration in the bulk would be around 1200 gN.m-3. To achieve partial nitritation results, the inhibition constants of both FA and FNA for the NOB were set at low concentration values, so higher inhibition, since this bacterial community needed to be suppressed.
For tanning wastewater, the inhibition constant values for AOB, FA value converted to TNH terms was very high despite the fact of being one of the lower values available in revised literature (5943 gTNO2-N.m-3). Nevertheless, this did not affect the performance because AOB did not need to be inhibited. For AOB inhibition by FNA, the inhibition value was 268 gTNO2-N.m-3, which is above 50% of the nitrogen in the influent. That percentage matches the amount of ammonium required to be converted to nitrite for a proper nitrite-ammonium ratio. For NOB, both values of FA and FNA were low, which allows NOB inhibition as required for PN process.
With the new parameters values and the inhibition constants added to the model, the simulations were run for 2000 days to determine at what point in time the process reached steady state. This was performed parallely using old landfill leachate and tanning wastewater as influent.
43
4.2.3 Steady state simulation of old landfill leachate
Old landfill leachate as influent achieved steady state on the day 400 of the simulation. DO concentration was 2.5 g.m-3 and pH value of 8.1 as described in the study by Nguyen and Lan (2014); however, ammonium concentration in the influent was set at 1090 gN.m-3
and COD concentration to zero.
Fig. 18. Concentration of nitrogen components in the effluent of partial nitritation process simulation at steady state with old landfill leachate as influent. Macroscopic reactor behaviour
Figure 18 shows the results of the old landfill leachate partial nitritation simulation, achieving steady state at 400 days with a nitrate-ammonium ratio in the effluent of 1.07, which is close to the ideal ratio described by Lotti et al. (2014). Nitrate concentrations in the effluent are close to zero, which indicates that the NOB were successfully inhibited. Nitrogen gas is also being produced, although at a very low rate. The average N2 concentration in the effluent at steady state of 5.5 gN.m-3
For AOB, the inhibition by FA is playing a major role in this simulation because steady state is only achieved when the ammonia concentration in the effluent is below 516.37. Since the ammonium concentration in the influent is set at 1090 gN.m-3, this means that the inhibition factor is allowing the AOB to grow without any inhibition up to the limit concentration value. The nitrite production of AOB with the ammonium concentration below the inhibition value provides an ideal ratio of nitrite-ammonium at steady state in the system.
The N2 in the effluent means that denitrification is taking place. The available concentration of nitrogen gas only represents 0.5% of the total nitrogen in the influent. The amount of not acknowledged nitrogen in the experimental study was 9% (section 4.1.2). Therefore only a small part of the nitrogen missing in the effluent can be attributed to heterotrophic denitrification taking place in the system. The low percentage of nitrogen gas can be attributed to the concentration of COD in the influent set at 0 gCOD.m-3 because old landfill leachate is characterized for the very low concentration of biodegradable COD, which leaves heterotrophs with no more substrate than the COD available from biomass decay.
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44
There was also a dependency between the ammonium and the COD loads in the influent. When the ammonium concentration in the influent was set above 1050 gN.m-3 and the COD load was very low, close to zero, the partial nitritation process showed better nitrite-ammonium ratio. If any of these last two parameters was changed, the simulation did not show high efficiency partial nitritation process being performed. Therefore it can be concluded that partial nitritation performance is highly dependent on COD and ammonium concentrations when the pH, temperature and DO concentration values are fixed at 8.1, 30oC and 2.5 g.m-3 respectively.
During the first 70 days of the simulation, only an efficiency of 38% in partial nitritation process was achieved, unlike the experimental results found by Nguyen and Lan (2014) with 70.6% average efficiency within 70 days. According to the simulation it is necessary to reach 400 days of process to achieve the experimental efficiency.
Biofilm distribution
The bacterial community distribution in the biofilm is the reason of the nitrogen components concentration in the effluent. Figure 19 displays bacterial distribution and the oxygen concentration through the biofilm at steady state on day 400. It is shown that in the closest part to the biomass carrier only inerts were found to be forming the base of the biofilm. Oxygen concentration in the bulk liquid was available in the biofilm in the last 100 𝜇m close to the biofilm surface and was there where the AOB community showed its highest density. NOB growth was successfully inhibited in the whole biofilm. Heterotrophs showed a little growth close to the biofilm surface.
Nitrite was the main substrate in the biofilm with a concentration of 560 gN.m-3, although ammonium had concentration of 522 gN.m-3. Both ammonium and nitrite were available through the whole biofilm without showing a strong concentration gradient.
Fig. 19. Biofilm distribution for partial nitritation process simulation at steady state with old landfill leachate as influent (day 400): (A) Biomass (B) Oxygen concentration.
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cent
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45
The inerts in the base of the biofilm mean that all the decayed biomass was forming the base of the biofilm. AOB was the dominant community in the last 100 𝜇m close to the biofilm surface because the oxygen availability and the high concentration of ammonium in the influent allowed this bacterial community to grow at high concentrations. NOB growth was inhibited in the whole biofilm and that is the reason why no nitrate concentration was present in the effluent. Heterotrophs grew close to the biofilm surface and then their density decreased since the COD concentration in the influent was set at a value of zero; therefore they did not have the substrate to grow properly and the amount of COD from biomass decay is known to be nearly negligible (Mozumder et al., 2013). This is why the nitrogen gas concentration in the effluent was so low.
4.2.4 Steady state simulation of tanning wastewater
Tanning wastewater as influent achieved steady state on the day 250 of the simulation. DO concentration was 2.2 g.m-3, ammonium influent concentration of 500 gN.m-3 and pH value of 7, based on the values described in the experimental set up (section 3.2.2); however, the COD concentration was set at 250 gCOD.m-3.
Macroscopic reactor behavior
Figure 20 shows the results of the nitrogen components in the effluent of the partial nitritation simulation on tanning wastewater achieving steady state at 250 days. The achieved nitrate-ammonium ratio in the effluent is 1.23. Nitrate concentration in the effluent was almost zero. Nitrogen gas in the effluent had an average concentration of 40 gN.m-3.
Fig. 20. Concentration of nitrogen components in the effluent of partial nitritation process simulation at steady state with tanning wastewater as influent.
The absent concentration of NO3 in the effluent is explained by the successful inhibition of
the NOB, who were present in the beginning of the simulation but died within a week. The achieved nitrite-ammonium ratio achieved (1.23) describes a 92% efficiency of the partial nitiritation process according to the 1.14 ideal ratio described by Lotti et al. (2014) and
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46
95% efficiency if 1.32 is taken as ideal ratio, as described by Strous et al. (1999). The 40 gN.m-3 of nitrogen gas produced indicate that heterotrophic denitrification is taking place using the COD in the influent as substrate. The N2 concentration in the effluent represents 8% of the nitrogen in the influent, compared to the 15% that was not being acknowledged in the mass balance based on the experimental results, the nitrogen gas production in this simulation could justify more than half of the experimental nitrogen gap.
The FNA inhibition for the AOB played a major role in this simulation by maintaining the balance for steady state to be achieved for PN process. When the NO2 concentration in the effluent was higher than 268.76 gTNO2-N.m-3, the AOB were inhibited and their growth got limited, therefore the ammonium oxidation efficiency decreased and the nitrite production had to be maintained below the inhibition factor value. Since the inhibition factor value is close to 50% of the ammonium concentration in the influent, this allowed the AOB to have enough substrate to maintain a stable NO2 production in the desired nitrite-ammonium ratio to achieve steady state.
At day 100 in the simulation, partial nitritation with a nitrite-ammonium ratio above 1.0 is starting to be performed; however it only reached steady state after 250 days. For proper comparison of the simulation performance with the experimental results, it must be mentioned that during the experimental period there was no previous acclimation period for bacteria to stabilize. The bacterial acclimation and growth were taking place during the experiment itself. Comparing the available experimental data of 40 days and the simulation within the same amount of days, the experimental nitrite-ammonium ratio achieved was 0.36 and the simulated one was 0.52. The experimental efficiency of the partial nitritation process is 31% and the simulation shows 46% efficiency. These simulation results approximate to the experimental ones, but it cannot be stated that the simulation accurately describes the experimental process due to lack of experimental data for the following 210 days.
Biofilm distribution
The biomass distribution and the oxygen concentration through the biofilm are displayed in Figure 21. Inerts occupied the biofilm base and the active communities were available in the last 150 𝜇m. NOB concentration was zero through the biofilm. AOB were present but were not the dominant bacterial community. Heterotrophs were the dominant population at the surface of the biofilm.
The oxygen concentration in the biofilm behaved as expected, no oxygen was available in the closest 400 𝜇m to the biomass carrier, and it started being available in the closest 100 𝜇m to the biofilm surface, allowing aerobic autotrophs to grow (Figure 21). There was no concentration gradient for ammonium and nitrite, which remained though the biofilm thickness at a value of 212 gN.m-3 and 264 gN.m-3 respectively.
The AOB were present in a lesser extent than in the leachate steady state simulation due to the decrease in the influent nitrogen load of more than 50%. The dominancy of heterotrophs can be attributed to the 250 gCOD.m-3 in the influent that provided substrate for them to grow. Heterotrophs grew both aerobically (in the top 100 µm in the biofilm) and anoxically (in the region of 320 to 400 µm from the substratum/carrier). In the part where they grew anoxically, they produced nitrogen gas, which is the reason why the nitrogen gas production was higher. The amount of missing nitrogen in the mass balance was higher for the experimental process using tanning wastewater as influent than the one from Nguyen and Lan
47
(2014) with old landfill leachate, but both could be partially attributed to denitrification process taking place.
Fig. 21. Biofilm distribution for partial nitritation process simulation at steady state with tanning wastewater as influent (day 250): (A) Biomass (B) Oxygen concentration.
4.2.5 Dynamic simulation of old landfill leachate
Using the same model and parameter values as the steady state, the concentration of ammonium in the influent was set dynamic according to the study results of Nguyen and Lan (2014) (Appendix 2). The simulation was run for 70 days according to the available data and the simulation results did not fit the experimental ones according to the nitrite and ammonium concentrations in time (Figure 22). Nitrogen gas in the effluent represented an average of 5.7±2.2% of the nitrogen contained in the dynamic influent concentration, which indicates that heterotrophic community has a stable behaviour.
In the simulation results, the NOB were present during the first 10 days as nitrate was formed. Around day 15, NOB are inhibited and AOB became dominant, oxidizing all ammonium in the influent to nitrite. At day 60 there was a switch in the performance and ammonium oxidation rate decreased drastically because the increasing ammonium concentration in the influent exceeded the value set as inhibition factor of FA for AOB (516.73 g.m-3 of TNH) and AOB could not grow any further so the bacterial density decreased and consequently the nitrite production droped.
Parameter estimation was run to fit the ammonium and nitrate concentrations in simulation to the experimental results. DO and COD concentrations along with inhibition constants of FA for both AOB and NOB were calculated (at pH 8.1 and 30℃). The changes were reflected in the effluent composition (Figure 23).
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.m-3
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48
Fig. 22. Concentration of nitrogen components in the effluent of dynamic simulation of partial nitritation process with old landfill leachate as influent using steady state parameter values. Lines represent simulation results and markers represent experimental results.
Macroscopic reactor behavior The parameter estimation changed the COD concentration from 0 to 98.98 gCOD.m-3 and DO concentration from 2.5 g.m-3 to 0.92 g.m-3. Inhibition constants of FNA were not included in the parameter estimation because they did not play a significant role in the steady state simulation, unlike FA inhibition constants. Inhibition constant value of FA for the NOB went from one of the lowest values found in literature (0.43 gFA.m-3) to 20 gFA.m-3 (equivalent to 214.75 gTNH-N.m-3 at pH 8.1 and 30℃), which is a much higher value that matches the one in the study by Wett and Rauch (2003). Inhibition constant of FA for AOB was estimated to be an extremely high value (31521.67 gTNH-N.m-3) close to the one also given by Wett and Rauch (2003) (3000 gFA.m-3, equivalent to 32212.79 gTNH-N.m-3 at pH 8.1 and 30℃), which represents around 30 times the nitrogen concentration in the influent. The estimated COD concentration of 98.98 gCOD.m-3 is a possible value according to literature (Renou et al., 2008), but since there is no available data from the experimental study by Nguyen and Lan (2014), it is not possible to validate this value. The nitrogen gas in the effluent had an average concentration of 66.7 ± 9.2 gN.m-3 during the total length of the simulation. The increased N2 production is caused by the amount of COD in the influent that was set at 98.98 gCOD.m-3 compared to steady state simulation set at a value of zero. The average missing nitrogen in the experimental study by Nguyen and Lan (2014) was 9% ± 17% of the nitrogen in the influent, for this fitted dynamic simulation, nitrogen gas produced represents in average 10 ± 4% of the available nitrogen in the influent. Meaning that the missing nitrogen in the effluent of the experimental results could be probably completely attributed to nitrogen gas escaping from the reactor.
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NH NO2 NO3 N2 NH_exp NO2_exp
49
Fig. 23. Concentration of nitrogen components in the effluent of the fitted dynamic simulation of partial nitritation process with old landfill leachate as influent using estimated parameters according to experimental data. Lines represent simulation results and markers represent experimental results. The parameter that changed the information obtained from the experimental set-up is DO concentration, because in Nguyen and Lan (2014) study used a range of 2.2 – 2.8 g.m-3 but the parameter estimation set a DO concentration of 0.92 g.m-3 which is a rather low value compared to the one used by Nguyen and Lan (2014). This low value is not unrealistic, as there is literature (Isanta et al., 2015) that explains that partial nitritation reactors show better performance with low DO concentrations (around 1 g.m-3) to prevent nitrite oxidation in the bulk liquid. It should be mentioned that in the experimental lab-scale PN reactor, the DO measurements were taken from the surface of the bulk liquid, therefore is possible that much lower oxygen concentrations were present in deeper areas of the reactor but were not measured. Inhibition constants of FA and for AOB and NOB were not expected to change, however if they remained at the steady state values, the simulation did not achieved a proper fitting to the experimental data. Inhibition constant of FA for NOB was estimated to a much higher value equivalent to 214.75 gTNH-N.m-3. This change was not expected since the NOB are desired to be inhibited, so the lower the constant value is, the more inhibited the nitrite oxidizers will be. However NOB are being inhibited and the NO3 concentration drops to zero from day 10 (Figure 23). The inhibition constant of FA for AOB was estimated to a extremely high value 31521.67 gTNH-N.m-3, which indicates that AOB will never be inhibited by FA concentrations because the limiting value will never be reached with the defined ammonium concentration set in the influent. This means that the AOB probably adapted to the increasing ammonium load in the influent and the FA available in the bulk liquid. Turk and Mavinic (1989) explained that AOB were capable of tolerating increasing levels of FA.
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cent
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NH NO2 NO3 N2 NH_exp NO2_exp
50
Biofilm distribution
The biomass distribution and the oxygen concentration through the biofilm are displayed in Figure 24. The biofilm base was formed of inerts and a small fraction of NOB community from the initial concentration that were decaying. As oxygen became available in the last 50 𝜇m of the biofilm, AOB community grew exponentially. Heterotrophic denitrifiers were more active when the parameters were fitted for the experimental results. The ammonium and nitrite concentrations in the biofilm did not show a substantial concentration gradient and their concentrations remained stable at 633 gN.m-3 for ammonium and 532 gN.m-3 for nitrite.
Fig. 24. Biofilm distribution for fitted dynamic simulation of partial nitritation process with old landfill leachate as influent (day 70): (A) Biomass (B) Oxygen concentration.
The AOB community maintained a high concentration in the biofilm surface due to the high substrate of ammonium concentration in the influent. Heterotrophs high concentration was due to the COD in the influent, which was substrate for their growth. The higher nitrogen gas production was consequence of heterotrophic activity because they grew even in the anoxic areas in the biofilm, since oxygen was only available in the 50𝜇m closest to the biofilm surface.
4.2.6 Dynamic simulation of tanning wastewater
Experimental data for partial nitritation with tanning wastewater included nitrate concentrations in the effluent, aside from the ammonium and nitrite concentrations. Data available included 40 days of experiment length (Appendix 4).
The first dynamic simulation was run for 40 days with the model used for steady state simulation of partial nitritation of tanning wastewater and the values of ammonium
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cent
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.m-3
)
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B O2
51
concentrations in the influent according to experimental data. The results showed partial nitritation being performed with an average nitrite-ammonium ratio of 0.35, which represents 31% efficiency in the process (Figure 25). The average ratio achieved during the experiment was 0.52; therefore the model parameters still needed to be adjusted for the simulation results to fit the experimental data.
Fig. 25. Concentration of nitrogen components in the effluent of dynamic simulation of partial nitritation process with tanning wastewater as influent using steady state parameter values. Lines represent simulation results and markers represent experimental results.
In order to fit simulation results of ammonium, nitrite and nitrate with experimental data, parameter estimation was run to calculate the best-suited values for DO and COD concentrations. All other parameters were maintained as the ones in the model for steady state. This time inhibition constant values were not estimated because the previous simulation already showed partial nitritation being performed, so the bacterial parameters remained unchanged. Macroscopic reactor behavior The parameter estimation changed the COD concentration from 250 gCOD.m-3 to 8.43 gCOD.m-3 and DO concentration from 2.2 to 0.95 g.m-3. The changed value of COD concentration was very low, and although is a possible value according to literature, it is likely improbable. Biodegradable fraction of COD is usually lower than 20% and this percentage represents around 250 g.m-3 according to the information shared by the experimental research unit sponsored by the Federal Ministry of Education and Research of Germany (Appendix 1). The value estimated was very low compared to the theoretical one, but it could be possible that heterotrophs could have used the available biodegradable COD in the wastewater before it was used as influent for the PN reactor, leaving just a little COD available for the process.
0
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0 5 10 15 20 25 30 35 40
Con
cent
ratio
n (g
N.m
-3)
Time (days)
NH NO2 NO3 N2 NH_exp NO2_exp NO3_exp
52
Fig. 26. Concentration of nitrogen components in the effluent of the fitted dynamic simulation of partial nitritation process with tanning wastewater as influent using estimated parameters according to experimental data. Lines represent simulation results and markers represent experimental results. The estimated DO concentration was very low compared to range of oxygen concentration (1.4 – 2.8 gO2.m-3) recorded during the experiment. An average value of 0.95 gO2.m-3 could be possible if the overall oxygen concentration was much lower than the measured one. Indeed, the DO concentration tests were taken from the upper part of the bulk liquid, and assumed to be the same in all parts of the reactor; possibly the DO concentrations in deeper parts of the reactor were much lower than in the shallow one. Furthermore, as it is assumed that denitrification was taken place and escaped nitrogen gas could have accounted for about 15% of the incoming nitrogen balance, also substantial regions with very low oxygen concentrations had to be present in the reactor.
Denitrification was observed during the simulation (Figure 26) and the average concentration of nitrogen gas in the effluent was 36.48 gN.m-3, which justifies more than half of the 70 gN.m-3 missing from the effluent in the experimental results. Since the COD concentration in the influent was low, N2 production could be mainly attributed to the substrate provided by biomass decay.
The simulation fitted to the experimental results showed on Figure 26 did not show a proper partial nitritation performance, as ammonium concentrations were always higher than the nitrite ones. Better partial nitritation results were achieved (around 85% efficiency) if the simulation was run with the estimated parameter for COD concentration (8.43 gCOD.m-3) but changing DO concentration from the estimated value (0.95 gO2.m-3) to 2.5 gO2.m-3. Although partial nitritation performance was more efficient, results of this simulation are not shown, as they did not fit to the target experimental data.
0
50
100
150
200
250
300
350
400
0 5 10 15 20 25 30 35 40
Con
cent
ratio
n (g
.m-3
)
Time (days)
NH NO2 NO3 N2 NH_exp NO2_exp NO3_exp
53
Biofilm distribution
The biomass distribution and the oxygen concentration through the biofilm for the fitted simulation are displayed in Figure 27. Biomass density in the biofilm thickness did not reach the 500 𝜇m set as biofilm thickness in the model. In the bottom of the biofilm NOB were present along with AOB. The closer to the biofilm surface, the less NOB density and more AOB density could be found. AOB was the dominant bacterial community and the only one present on the biofilm surface. Heterotrophs were present in the anoxic part of the biofilm and their density decreased as oxygen got available.
Substrate concentration of ammonium and nitrate did not show any concentration gradient, remaining constant at 260 gN.m-3 and 185 gN.m-3 respectively. Oxygen concentration in the bulk liquid (0.95 gO2.m-3) was only available in the last 25 𝜇m previous to reach the biofilm surface.
Fig. 27. Biofilm distribution for fitted dynamic simulation of partial nitritation process with tanning wastewater as influent (day 40): (A) Biomass (B) Oxygen concentration.
The fact that the bacterial density did not reach the specified model thickness shows that the process simulation did not reach steady state and the bacterial communities were not developed enough to fill the volume established for the biofilm. The NOB present in the bottom of the biofilm were inhibited and decaying. The biomass from decay was generating biodegradable COD and the influent also had 8.43 gCOD.m-3, which was being used as substrate by the heterotrophs to perform denitrification. AOB were dominant on the biofilm surface in a quite large concentration and the nitrite production reflected in the effluent can be attributed to this bacterial community.
0
20000
40000
60000
80000
100000
0 1 2 3 4 5
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cent
ratio
n (g
CO
D.m
-3)
Biofilm thickness (10-4 m)
A AOB
NOB
Heterotrophs
Inerts
0
0.5
1
0 1 2 3 4 5
Con
cent
ratio
n (g
.m-3
)
Biofilm thickness (10-4 m)
B O2
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4.2.7 Conclusions
In order to achieve partial nitritation process with high efficiency rate at a fixed pH and temperature, some parameters need to be taken into account according to the ammonium and concentration in the influent. Old landfill leachate has a higher ammonium concentration than tanning wastewater, therefore it is possible that the nitrifying community treating leachate was acclimated to a higher nitrogen load and was thus able to withstand higher concentrations of FA and FNA. Therefore, the inhibition constant values can possibly vary according to the microbial community they are representing.
For tanning wastewater and old landfill leachate, the reactor pH also differed (7 for tanning wastewater and 8.1 for old landfill leachate). As the fraction of FA:TNH and FNA:TNO2 changed according to pH, this pH difference could also have resulted in different inhibition constant values for each type of influent.
Steady state partial nitritation simulation and fitting the model to the available dynamic experimental data was achieved with the parameters displayed in Table 11. Each simulation showed an approximation of the ideal behavior of partial nitritation process, meaning nitrite-ammonium ratio around 1.32 as described by Strous et al. (1999) or 1.14 as recently described by Lotti et al. (2014), however with different parameter values.
Table 11. Parameters value for partial nitritation process with old landfill leachate and tanning wastewater during steady state and dynamic simulation. NLR for dynamic simulation refers to experimental data from the corresponding studies. FA and FNA inhibition constants for AOB and NOB are in terms of TNH-N and TNO2-N.
Simulation Influent type Temp. pH NLR COD DO Ki AOB NH
Ki AOB NO2
Ki NOB NH
Ki NOB NO2
Time (
oC) - (gN.m
-3) (g.m
-3) (g.m
-3) (gN.m
-3) (gN.m
-3) (gN.m
-3) (gN.m
-3) (days)
Steady state Landfill leachate 30 8.1 1090 0 2.5 516 3382 4 1148 400
Tanning wastewater 30 7 500 250 2.2 5943 268 53 91 250
Dynamic (fitting to data)
Landfill leachate 30 8.1 data 98.98 0.92 31521 3382 214 1148 70 Tanning
wastewater 30 7 data 8.43 0.95 5943 268 53 91 40
The NOB were successfully inhibited in all simulations, partly due to the high temperature that allows AOB to grow faster than the NOB, but also the FA inhibition constants limited the NOB growth. In contrast to the NOB, the AOB growth got inhibited according to the pH value of the bulk liquid. Since old landfill leachate has a high pH value (8.1), FA tends to have a higher concentration; therefore FA inhibition factor plays a determinant role for the AOB performance. For tanning wastewater the determinant role for AOB inhibition is played by FNA due to the lower pH of this effluent.
The change in the FA inhibition constant values for AOB and NOB in the leachate dynamic simulation was not expected but needed to be done in order to get a proper simulation fitting to the experimental data. The change could be explained because of the change in the nitrogen loading rate. During the steady state simulation, the bacteria were fitted to be acclimated to a constant high nitrogen load (1090 gN.m-3), while in the dynamic simulation they were still adapting to an increasing nitrogen load in time (Turk and Mavinic, 1989). In
55
the dynamic simulations the overall community was different from the one in the steady state simulations because the bacteria in the beginning (day 0) and at the end (day 70) were actually different. The values of the parameters are giving a lumped value for the different communities that followed each other in time during the process performance.
COD concentration in the influent also affects the system performance as it provides substrate for heterotrophs to grow. A high COD load could lead to inhibition of the AOB by overtaking the biofilm density, aside from performing denitrification and affecting the nitrogen mass balance of the process.
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5. Conclusions and perspectives
Partial nitritation is a necessary pre-process to achieve the proper influent for subsequent anammox denitrification. In order to get a high efficiency in the PN process, the effluent must have a nitrite-ammonium ratio of 1.14 (Lotti et al., 2014) - 1.32 (Strous et al., 1999).
During experimental PN process with tanning wastewater as influent, an efficiency of 46% was achieved with a nitrite-ammonium ratio of 0.52 based on 40 days data (20 samples). The NOB were successfully inhibited and the nitrate concentration in the effluent was less than 1% of the total nitrogen in the influent; however, the nitrogen mass balance reflected a 15% of nitrogen missing in the effluent. The nitrogen not acknowledged in the experimental effluent could be attributed to nitrogen incorporated in the biomass, but this only justifies up to 1.8% of the nitrogen gap. Nitrous oxide emissions could also justify another 2% of the gap. Denitrification process is most likely the responsible of the remaining amount of nitrogen that has not been acknowledged, because it has escaped the system as nitrogen gas. The COD concentration in the influent plus the COD incorporated by biomass decay, allowed heterotrophs to perform denitrification. Another possible reason for nitrogen losses was ammonia stripping caused by the high ambient temperatures where the lab-scale reactor is located and because there were no covers on the reactor or the influent wastewater containers that could prevent ammonia from volatilizing. Measurement errors by equipment miscalibration could also be considered. DO concentrations in the bulk liquid were very influential in the nitrate-ammonium ratio. According to the data, the ideal ratio would be achieved with a DO concentration between 2.2 and 2.8 g.m-3; however, there is a possibility of equipment miscalibration error in these measurements due to technical problems during the experiment. Tanning effluents need to undertake physicochemical treatment prior to go through autotrophic partial nitritation for subsequent anammox-denitrification.
As perspectives for future experimental studies of partial nitritation process, it is recommended to update the reactor design adding coverlids to avoid ammonia stripping and gas traps to measure the nitrogen gas emissions for an accurate nitrogen mass balance. The length of the experiment is also a crucial factor in the results because bacterial communities need to stabilize to perform PN process and short data collection can lead to inaccurate conclusions. Special attention needs to be paid to the accuracy and proper functioning of the measuring devices in order to achieve reliable data for PN research. It is advised for experimental studies to run an acclimation period with increasing nitrogen loading rate previous to the constant one or to include the increasing nitrogen loading rate in the experiment but extend the length of the study to achieve reliable results that approach to an stable process performance. Relatively constant ammonium concentrations in the influent lead to better results as the bacterial communities stabilize to the provided environmental conditions easier, this could be achieved by controlling the inflow rate accordingly.
During mathematical modelling and simulation studies, partial nitritation was highly dependent on the amount of ammonium being introduced in the system. COD concentration in the influent was influential as well and it had to be low, otherwise the COD load plus the COD coming from biomass decay provided heterotrophs with substrate to grow and perform denitrification in a higher rate. If heterotrophic bacteria growth is not controlled by substrate limitations, it can outcompete the AOB in biomass density and no proper partial nitritation would be achieved. However in the simulation, the major role for partial nitritation to be reached belongs to inhibition by FA and FNA, especially for the AOB. The AOB are inhibited according to the pH value. For high pH values (such as old landfill leachate, pH
57
8.1), FA inhibition factor plays a determinant role for the AOB performance because FA has higher concentrations in higher pH. For neutral pH values (such as tanning wastewater, pH 7) the determinant role for AOB inhibition is played by FNA. The FA and FNA inhibition constants for the NOB are likely to have low values because this bacterial community needs to be completely inhibited in order to prevent NOB from oxidizing the produced nitrite into nitrate and achieve a partial nitritation effluent with the desired characteristics for subsequent anammox-denitrification.
The simulation study proved that in all cases, denitrification process is taking place inside the reactor and nitrogen gas is escaping the system. This does not affect the partial nitritation process if the heterotrophs density is not outcompeting the AOB, but does affect the nitrogen mass balance as there will never be the same amount of nitrogen in the liquid effluent as in the influent if the gas escaping is not measured. The rate of nitrogen gas production highly depends on the amount of biodegradable COD entering the system. The simulation study for tanning wastewater reveals that more than 50% of the nitrogen missing in the experimental mass balance is in the form of N2 gas in the effluent for the fitted dynamic simulation.
Simulation at steady state used the same DO concentration as the experimental results of tanning wastewater, but the same DO concentration was too high for the parameters estimated to fit the nitrogen compounds concentrations experimentally found in the effluent. This can be explained because of DO measurement errors, since the measurements were always taken from the surface of the bulk liquid and considered to be extensive to all the reactor, when deeper parts could have had much lower DO concentrations. Limited available data is another important factor. In order to achieve proper and reliable results, the system needs to reach stable performance. According to the simulation it was reached after 250 days, therefore 40 days data do not predict accurately the efficiency the system could reach at stable performance. Old landfill leachate experimental data was used for validation, as there was a bigger data collection available of this previous study and because this kind of effluent has a similar composition compared to tanning wastewater. Partial nitritation on both experimental and simulation studies, showed better efficiency rates with old landfill leachate than with tanning wastewater as influent, but the length of the experiment was not sufficient either to make extensive conclusions about the stable performance results.
As a future perspective for partial nitritation modelling and simulation, growth and decay of the anammox bacterial community could be added to the model to see how it influences the partial nitritation performance. Even if the reactor is aerated, the biofilm is tick enough to have more than half of its thickness in anoxic conditions, which opens the possibility of hosting anammox. For the fitted simulations, oxygen concentrations were lower than 1 g.m-3, which provides a more suitable environment for anammox growth in the biofilm anoxic zone. Furthermore, the growth of anammox could be another reason why nitrogen in the form of nitrogen gas escapes from the reactor. However, in the current contribution, anammox was not included in the aerated partial nitritiation biofilm reactor model as it was based on the experimental set up, which included constant aeration and relatively high oxygen concentrations. Also, the length of the experiment was not long. Anammox are known to have a slow growing rate and are easily outcompeted by fast growers as the heterotrophs. Therefore the bacterial community was not likely to be active during the experiment duration. It could also be possible that constant aeration would create shear stress on the biofilm, washing out the biomass on the surface and making oxygen available in deeper layers of the biofilm; therefore anammox would not be able to grow either.
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To conclude, partial nitritation process is feasible for tanning wastewater but since the composition of this effluent is highly variable according to the tanning process, attention must be paid to the pH values of the wastewater and the ammonium and COD content in the influent. DO concentrations in the bulk liquid must be lower than 2.5 g.m-3 and proper monitoring should guard the performance efficiency of the process in order to find the best parameter values to achieve efficient and stable process performance.
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References Alpkvist E., Picioreanu C., van Loosdrecht M.C.M. & Heyden A. (2006). Three-dimensional
biofilm model with individual cells and continuum EPS matrix, Biotechnology Bioengineering, 94, 962-979.
Anthonisen, A. C., Loehr, R. C., Prakasam, T. B. S., & Srinath, E. G. (1976). Inhibition of nitrification by ammonia and nitrous acid. Water Pollution Control Federation, 835-852.
APHA AWWA, WEF. (1999), Standard Methods for the Examination of Water and Wastewater, American Public Health Association, Washington DC, USA.
Aziz, H. A., Yussff, M. S., Adlan, M. N., Adnan, N. H. & Alias, S. (2004). Physico-chemical removal of iron from semi-aerobic leachate by limestone filter. Waste Management, 24, 353–358.
Bae, J. H., Cho, K.W., Bum, B.S., Lee, S.J. & Yoon, B.H. (1998). Effects of leachate recycle and anaerobic digester sludge recycle on the methane production from solid waste. Water Science and Technology, 38, 159–168.
Baquerizo, G., Mestre, J. P., Sakuma, T., Deshusses, M. A., Gamisans, X., Gabriel, D. & Lafuente, J. (2005). A detailed model of a biofilter for ammonia removal: model parameters analysis and model validation. Chemical Engineering Journal, 113(2), 205-214.
Barth, E. F., Richard, C. B. & Ronald, F. L. (1968). Chemical-biological control of nitrogen and phosphorus in wastewater effluent. Journal (Water Pollution Control Federation, 2040-2054.
Beaumont, H.J.E., Hommes, N.G., Sayavedra-Soto, L.A., Arp, D.J., Arciero, D.M., Hooper, A.B., Westerhoff, H.V. & van Spanning, R.J.M. (2002). Nitrite reductase of Nitrosomonas europaea is not essential for production of gaseous nitrogen oxides and confers tolerance to nitrite. Bacteriology, 184 (9), 2557.
Black, M., Canova, M., Rydin, S., Scalet, B. M., Roudier, S., & Sancho, L. D. (2013). Best Available Techniques (BAT) Reference Document for the Tanning of Hides and Skins.
Bosnic, M., Buljan, J., & Daniels, R. P. (1996). Pollutants in tannery effluents: definitions and environmental impact, limits for discharge into water bodies and sewers. Pollutants in tannery effluents: definitions and environmental impact, limits for discharge into water bodies and sewers. ONUDI.
Carrera, J., Jubany, I., Carvallo, L., Chamy, R. & Lafuente, J. (2004). Kinetic models for nitrification inhibition by ammonium and nitrate in a suspended and an immobilized biomass systems. Process Biochemistry, 39(9), 1159-1165.
Castro-Barros, C. M., Daelman, M. R. J., Mampaey, K. E., van Loosdrecht, M. C. M., & Volcke, E. I. P. (2015). Effect of aeration regime on N 2 O emission from partial nitritation-anammox in a full-scale granular sludge reactor. Water Research, 68, 793 -803.
Ceçen, F. & Aktas, O. (2004). Aerobic co-treatment of landfill leachate with domestic wastewater. Environmental Engineering Science, 21, 303–312.
Chan, G. Y. S., Chu, L. M. & Wong, M. H. (2002). Effects of leachate recirculation on biogas production from landfill co-disposal of municipal solid waste, sewage sludge and marine sediment. Environmental Pollution, 118, 393– 399.
Chian, E. S. K. & DeWalle, F.B. (1976). Sanitary landfill leachates and their treatment. Environmental Engineering Division, 411–431.
Clément, B., Janssen, R.C. & Le Duˆ-Delepierre, A. (1997). Estimation of the hazard of landfills through toxicity testing of leachates. Chemosphere, 35, 2783–2796.
60
Di Palma, L., Ferrantelli, P., Merli, C. & Petrucci, E. (2002). Treatment of industrial landfill leachate by means of evaporation and reverse osmosis. Waste Management, 22, 951–955.
Diamadopoulos, E., Samaras, P., Dabou, X. & Sakellaropoulos, G. P. (1997). Combined treatment of leachate and domestic sewage in a sequencing batch reactor. Water Science and Technology, 36, 61–68.
Durai, G. & Rajasimman, M. (2011) Biological treatment of tannery wastewater – a review. Environmental Science and Technology, 4(1), 1-17.
Eldyasti, A., Nakhla, G. & Zhu, J. (2014). Influence of biofilm thickness on nitrous oxide (N2O) emissions from denitrifying fluidized bed bioreactors (DFBBRs). Biotechnoloy, 192, 281-290
Farabegoli, G., Carucci, A., Majone, M. & Rolle, E. (2004). Biological treatment of tannery wastewater in the presence of chromium. Environmental Management, 71, 345–9.
Fux, C., Boehler, M., Huber, P., Brunner, I., & Siegrist, H. (2002). Biological treatment of ammonium-rich wastewater by partial nitritation and subsequent anaerobic ammonium oxidation (anammox) in a pilot plant. Biotechnology, 99(3), 295-306.
Haapea, P., Korhonen, S. & Tuhkanen, T. (2002). Treatment of industrial landfill leachates by chemical and biological methods: ozonation, ozonation + hydrogen peroxide, hydrogen peroxide and biological post-treatment for ozonated water. Ozone Science Engineering, 24.
Hao, X.D. & van Loosdrecht, M. C. M. (2004). Model-based evaluation of COD influence on a partial nitrification-Anammox biofilm (CANON) process. Water Science and Technology, 49, 83-90.
Hellinga C., van Loosdrecht M. C. M. & Heijnen J. J. (1999). Model based design of a novel process for nitrogen removal from concentrated flows. Mathematical and Computer Modelling of Dynamical Systems, 5, 351-371.
Henry, J. G., Prasad, D. & Young, H. (1987). Removal of organics from leachates by anaerobic filter. Water Research, 21, 1395–1399.
Henze M., Gujer W., Mino T. & van Loosdrecht M. C. M. (2000). Activated Sludge Models ASM1, ASM2, ASM2d and ASM3 in IWA scientific and technical report no 9. IWA Publishing, London, 130.
Hoilijoki, T. H., Kettunen, R.H. & Rintala, J.A. (2000). Nitrification of anaerobically pretreated municipal landfill leachate at low temperature. Water Research, 34, 1435–1446.
Imai, Iwami, N., Matsushige, K., Inamori, Y. & Sudo, R. (1993). Removal of refractory organics and nitrogen from landfill leachate by the microorganism-attached activated carbon fluidized bed process. Water Resources, 27, 143–145.
Insel, G. H., Görgün, E., Artan, N. & Orhon, D. (2009). Model based optimization of nitrogen removal in a full scale activated sludge plant. Environmental Engineering Science, 26, 471–80.
Isanta, E., Reino, C., Carrera, J., & Pérez, J. (2015). Stable partial nitritation for low-strength wastewater at low temperature in an aerobic granular reactor. Water research, 80, 149-158.
Jetten, M. S. M., Niftrik, L. Van, Strous, M., Kartal, B., Keltjens, J. T., & Op den Camp, H. J. M. (2009). Biochemistry and molecular biology of anammox bacteria. Critical Reviews in Biochemistry and Molecular Biology, 44(2-3), 65–84.
Jubany, I., Carrera, J., Lafuente, J. & Baeza, J. A. (2008). Start-up of a nitrification system with automatic control to treat highly concentrated ammonium wastewater: Experimental results and modeling. Chemical Engineering Journal, 144(3), 407-419.
61
Jubany, I., Lafuente, J., Baeza, J. A. & Carrera, J. (2009). Total and stable washout of nitrite oxidizing bacteria from nitrifying continuous activated sludge system using automatic control based on Oxygen Uptake Rate measurements. Water Research, 43, 2761-2772.
Kabdasli, I., Tunay, O. & Orhon, D. (1999). Wastewater control and management in a leather tanning district. Water Science and Technology, 40, 261–7.
Kennedy, K. J. & Lentz, E. M. (2000). Treatment of landfill leachate using sequencing batch and continuous flow upflow anaerobic sludge blanket (UASB) reactors. Water Research, 34, 3640–3656.
Knox, K. (1985). Leachate treatment with nitrification of ammonia, Water Research 19, 895–904.
Kong, Q., Liang, S., Zhang, J., Xie, H., Miao, M. & Tian, L. (2013). N2O emission in a partial nitrification system: dynamic emission characteristics and the ammonium-oxidizing bacteria community. Bioresource Technology, 127, 400–6.
Labanda, J., Khaidar, M. S. & Llorens, J. (2009). Feasibility study on the recovery of chromium (III) by polymer enhanced ultrafiltration. Desalination, 249, 577–81.
Lam, H. V. & Nguyen, T. P. (2014). Studying the Partial Nitritation for High Ammonium of Old Landfill Leachate Treatment. Science and Technology.
Lema, J. M., Mendez, R. & Blazquez, R. (1988). Characteristics of landfill leachates and alternatives for their treatment: a review. Water, Air and Soil Pollution, 40, 223–250.
Leta, S., Assefa, F., Gumaelius, L. & Dalhammar, G. (2004). Biological nitrogen and organic matter removal from tannery wastewater in pilot plant operations in Ethiopia. Applied Microbiology Biotechnology, 66, 333-339.
Li, X. Z., Zhao, Q. L. & Hao, X. D. (1999). Ammonium removal from landfill leachate by chemical precipitation. Waste Management, 19, 409–415.
Lin C.Y. (1991). Anaerobic digestion of landfill leachate. Water SA, 17, 301–306. Lofrano, G., Meric, S., Belgiorno, V. & Napoli, R. M. A. (2007) Fenton's oxidation of
various based synthetic tannins (syntans). Desalination, 21, 10–21. Lofrano, G., Meric, S., Zengin, G. M. & Orhon, D. (2013). Chemical and biological
treatment technologies for leather tannery chemicals and wastewaters: a review. Science of the Total Environment, 461– 462, 265–281.
Loizidou, M., Vithoulkas, N. & Kapetanios, E. (1992). Physical chemical treatment of landfill leachate from landfill. Environmental Science and Health, A27, 1059–1073.
Loukidou, M. X. & Zouboulis, A.I. (2011). Comparison of two biological treatment process using attached-growth biomass for sanitary landfill leachate treatment. Environmental Pollution, 111, 273–281.
Lu, H.J. & Chandran, K. (2010). Factors promoting emissions of nitrous oxide and nitric oxide from denitrifying sequencing batch reactors operated with methanol and ethanol as electron donors. Biotechnology and Bioengineering, 106 (3), 390 - 398.
Martienssen, M. & Schops R. (1997). Biological treatment of leachate from solid waste landfill sites—alterations in the bacterial community during the denitrification process. Water Research, 31, 1164–1170.
Marttinen, S. K., Kettunen, R. H., Sormunen, K. M., Soimasuo, R. M. & Rintala, J. A. (2002). Screening of physical–chemical methods for removal of organic material, nitrogen and toxicity from low strength landfill leachates. Chemosphere 46, 851–858.
McLellan J. K. & Rock C. A. (1988). Pretreating landfill leachate with peat to remove metals. Water, Air, and Soil Pollution, 37(1-2), 203-215.
Moussa, M. S., Rojas, A. R., Hooijmans, C. M., Gijzen, H. J. & van Loosdrecht, M. C. M. (2004). Model-base evaluation of nitrogen removal in a tannery wastewater treatment plant. Water Science and Technology, 50(6), 251-260
62
Mozumder, S. I. (2011). Effect of heterotrophic growth on autotrophic nitrogen removal in a granular sludge reactor. Faculty of Bioscience Engineering. Ghent University, Belgium.
Mozumder, S. I., Picioreanu, C., van Loosdrecht, M. C. M. & Volcke, E. I. P. (2013). Effect of heterotrophic growth on autotrophic nitrogen removal in a granular sludge reactor. Environmental Technology, 35(8), 1027 – 1037.
Muller A., Wentzel M. C., Loewenthal R. E. & Ekama G. A. (2003). Heterotroph anoxic yield in anoxic aerobic activated sludge systems treating municipal wastewater. Water Research, 37, 2435-2441.
Pambrun, V., Paul , E. & Sperandio, M. (2006). Modeling the partial nitrification in a sequence batch reactor for biomass adapted to high ammonia concentrations. Biotechnology Bioengineering, 95(1), 120–131.
Peters, T. A. (1998). Purification of landfill leachate with membrane filtration. Filtration and Separation, 35, 33–36.
Picioreanu, C., van Loosdrecht, M. C. M. & Heijnen J. J. (1997). Modelling the effect of oxygen concentration on nitrite accumulation in a biofilm airlift suspension reactor, Water Science and Technology, 36, 147-156.
Pirbazari, M., Ravindran, V., Badriyha, B. N. & Kim, S. (1996). Hybrid membrane filtration process for leachate treatment. Water Research, 30, 2691– 2706.
Preethi, V., Parama Kalyani, K.S., Iyappan, K., Srinivasakannan, C., Balasubramaniam, N. N. & Vedaraman, N. (2009). Ozonation of tannery effluent for removal of cod and color. Hazard Materials, 166, 150–4.
Rautenbach, R., Linn & T., Eilers, L. (2000). Treatment of severely contaminated wastewater by a combination of RO and NF—potential and limits of the process. Membrane Science, 174, 231–241.
Reichert P. (1994). Aquasim – a tool simulation and data-analysis of aquatic system. . Water Science and Technology, 30, 21–30.
Reinhart, D. R. & Al-Yousfi A. B. (1996). The impact of leachate recirculation on municipal solid waste landfill operating characteristics. Waste Management & Research, 14, 337–346.
Renou, S., Givaudan, J. G., Poulain, S., Dirassouyan, F. & Moulin, P. (2008). Landfill leachate treatment: review and opportunity. Hazardous Materials, 150, 468-493.
Schrank, S. G., José, H. J., Moreira, R. F. P. M. & Schroder, H. Fr. (2005). Applicability of Fenton and H2O2/UV reactions in the treatment of tannery wastewaters. Chemosphere, 60, 644–55.
Schrank, S. G., José, H. J., Moreira, R. F. P. M. & Schroder, H. Fr. (2004). Elucidation of the behaviour of tannery wastewater under advanced oxidation conditions. Chemosphere, 56, 411–23.
Seviour, R. & Nielsen, P. H. (2010). Microbial Ecology of Activated Sludge, London, UK: IWA Publishing.
Silva, A. C., Dezotti, M. & Sant’Anna Jr., G. L. (2004). Treatment and detoxication of a sanitary landfill leachate. Chemosphere, 55, 207–214.
Stasinakis, A. S., Mamais, D., Thomaidis, N. S. & Lekkas, T. D. (2002). Effect of chromium (VI) on bacterial kinetics of heterotrophic biomass of activated sludge. Water Research, 36, 3342–50.
Steinert, T. (2014). Studies of the treatment of tannery wastewater in Vietnam with a membrane bioreactor. University of applied science. Ostwestfalen Lippe, Germany.
Strous, M., Kuenen, J. G., & Jetten, M. S. (1999). Key physiology of anaerobic ammonium oxidation. Applied and environmental microbiology, 65(7), 3248-3250.
63
Szpyrkowicz, L., Kelsall, G. H., Kaoul, S. N. & De Faveri, M. (2001). Performance of electrochemical reactor for treatment of tannery wastewaters. Chemical Engineering Science, (56)15, 79–86.
Tadesse, I., Green, F.B. & Puhakka, J.A. (2004). Seasonal and diurnal variations of temperature, pH and dissolved oxygen in advanced integrated wastewater pond system® treating tannery effluent. Water Research, 38, 645–5.
Tchobanoglous, G., Burton, F.L. & Stensel D.H. (2003) Wastewater Engineering: Treatment and Reuse. (4th ed.) Mc Graw Hill.
Timur, H. & Ozturk, I. (1997). Anaerobic treatment of leachate using sequencing batch reactor and hybrid bed filter. Water Science and Technology, 36, 501–508.
Trebouet, D., Schlumpf, J. P., Jaouen, P., Quemeneur, F. (2001). Stabilized landfill leachate treatment by combined physicochemical–nanofiltration process. Water Research, 35, 2935–2942.
Turk, O., & Mavinic, D. S. (1989). Maintaining nitrite build-up in a system acclimated to free ammonia. Water Research, 23(11), 1383-1388.
van Benthum, W. A. J., van Loosdrecht, M. C. M., Tijhuis, L. & Heijnen, J. J. (1995). Solids retention time in heterotrophic and nitrifying biofilms in a biofilm airlift suspension reactor. Water Science and Technology, 32, 53–60.
van Dijk, L. & Roncken, G. C. G. (1997). Membrane bioreactors for wastewater treatment: the state of the art and new developments. Water Science and Technology, 35, 35–41.
Verheijen, L. A. H. M., Weirsema, D., Hwshoffpol, L.W. & Dewit, L.W. (1996). Live Stock and the Environment: Finding a Balance Management of Waste from Animal Product Processing. International Agriculture Centre, Wageningen, The Netherlands.
Volcke E.I.P. (2006). Modelling, analysis and control of partial nitritation in a SHARON reactor. PhD thesis, Ghent University, Belgium, pp. 11. ISBN 90-5989-108-2
Volcke, E. I. P., Picioreanu, C., de Baets, B. & van Loosdrecht, M. C. M. (2013). Effect of granule size on autotrophic nitrogen removal in a granular sludge reactor. Environmental Technology, 31, 1271–1280.
von Schulthess, R., Wild & D., Gujer, W. (1994). Nitric and nitrous oxides from denitrifying activated-sludge at low-oxygen concentration. Water Science and Technology, 30 (6), 123 - 132.
Warah, R. (2001). The state of the World’s cities—UrbanWaste, 70–71. Wett, B. & Rauch, W. (2003). The role of inorganic carbon limitation in biological nitrogen
removal of extremely ammonia concentrated wastewater. Water Research, 37 (5), 1100-1110.
Wiesmann U. (1994). Biological nitrogen removal from wastewater, Advances in Biochemical Engineering Biotechnology 51, 113-154.
Williamson K. & McCarty, P. L. (1976). Verification Studies of the Biofilm Model for Bacterial Substrate Utilization. Water Pollution Control, 48, 281-296.
Wojciechowska, E., Gajewska, M. & Obarska-Pempkowiak, H. (2010). Treatment of Landfill Leachate by Constructed Wetlands: Three Case Studies. Polish Environmental Studies, 19 (3), 643-650.
Wunderlin, P., Mohn, J., Joss, A., Emmenegger, L. & Siegrist, H. (2012). Mechanisms of N2O production in biological wastewater treatment under nitrifying and denitrifying conditions. Water Research, 46 (4), 1027 - 1037.
Zouboulis, I., Jun, W. & Katsoyiannis, A. (2003). Removal of humic acids by flotation. Colloids and Surfaces A: Physicochemical and Engineering Aspects, 231, 181–193.
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Appendix Table 1. Results of analytical test applied to the influent of the experimental research unit sponsored by the Federal Ministry of Education and Research of Germany (Tilman Steinert, personal communication, April 6, 2015).
Date Temp. pH Conducti-vity COD NH4-N
filtrated NO3-N filtrated Ntotal SO4
2- S2-
(DD:MM:YY) (°C) ( - ) (µS/cm) (mg/l) (mg/l) (mg/l) (mg/l) (mg/l) (mg/l) 3/2/15 34.1 7.54 27830 1890 580 0 580
3/10/15 30.2 7.1 27900 1015 740 10 900 3/13/15 29.3 7.5 27800 1845 750 0 >750 3/16/15 3/17/15 28.7 7.6 27500 1275 1170 1100 3/19/15 30 7.7 27400 1125 1010 0 1200 370 93.5 3/27/15 30.8 7.9 27100 1035 730 0 >750 260 25
65
Table 2. Experimental results of partial nitritation process with to old landfill leachate as influent (Nguyen and Lan, 2014).
Influent Effluent
Influent Effluent
Time NH4 NH4 NO2
Time NH4 NH4 NO2
(days) (g/m3) (g/m3) (g/m3)
(days) (g/m3) (g/m3) (g/m3)
Star
t up
1 358 291 108
Incr
ease
d N
LR
26 545 196 165 2 392 297 119
27 539 374 100
3 358 291 95
28 550 423 104 4 336 269 70
29 560 357 165
5 347 197 174
30 547 318 191 6 426 134 223
31 509 291 184
7 414 180 225
32 513 294 130 8 403 210 159
33 572 312 125
9 493 192 198
34 525 282 128 10 479 192 207
35 545 237 139
11 479 286 235
36 556 498 54 12 472 210 245
37 534 480 62
13 465 291 244
38 553 394 105 14 457 271 201
39 534 421 217
15 467 218 216
40 834 421 117 16 488 167 191
41 812 389 157
17 465 211 213
42 854 385 109 18 543 278 205
43 836 371 397
19 515 291 221
44 815 401 412 20 505 205 293
45 809 451 348
21 513 289 261
46 809 390 463 22 501 248 254
47 854 411 478
23 525 269 287
48 853 478 171 24 539 286 262
49 834 402 432
25 527 222 251
50 829 411 449
51 819 424 435
52 812 468 412
53 815 462 410
54 802 410 398
55 810 398 345
56 1231 386 498
57 1228 492 501
58 1203 519 468
59 1184 551 575
60 1234 573 514
61 1298 618 512
62 1277 618 501
63 1267 654 605
64 1252 622 582
65 1221 610 551
66 1243 567 598
67 1251 689 557
68 1209 623 638
69 1220 678 621
70 1218 612 609
66
Table 3. Stoichiometric and kinetic parameters values of the used model (Mozumder et al., 2013).
Parameter Value Unit Reference Stoichiometric parameters YAOB 0.2 g COD.g-1 N Weismann (1994) (1) YNOB 0.057 g COD.g-1 N Weismann (1994) (1) YH 0.67 g COD.g-1 COD Henze et al. (2000) YH,NO2 0.53 g COD.g-1 COD Muller et al. (2003) YH,NO3 0.53 g COD.g-1 COD Muller et al. (2003) iNXB 0.07 g N.g-1 COD Assumed in this study iNXI 0.07 g N.g-1 COD Assumed same as iNXB iNSS 0.03 g N.g-1 COD Henze et al. (2000) fI 0.08 g COD.g-1 COD Henze et al. (2000) Kinetic parameters (at 30°C, pH 7.5) 1.36 d-1 Hellinga et al. (1999) (2)
0.79 d-1 Hellinga et al. (1999) (2)
12 d-1 Henze et al. (2000) (3)
1.1 g N.m-3 Weismann (1994) (4)
0.51 g N.m-3 Weismann (1994) (4)
0.3 g N.m-3 Alpkvist et al. (2006)
0.3 g N.m-3 Alpkvist et al. (2006)
20 g COD.m-3 Henze et al. (2000)
0.3 g O2.m-3 Weismann (1994)
1.1 g O2.m-3 Weismann (1994)
0.2 g O2.m-3 Henze et al. (2000)
0.02 g N.m-3 Assumed in this study
bAOB 0.068 d-1 Assumed, set such that bAOB: = bH:
bNOB 0.04 d-1 Assumed, set such that bNOB: = bH:
bH 0.6 d-1 Assumed / 20 for this study
ηNO2=ηNO3 0.8 - Henze et al., (2000)
AOBmaxµ
NOBmaxµ
Hmaxµ
AOBNHK
NOB2NOK
HNOK 2
HNOK 3
KSH
AOBOK 2
NOBOK 2
HOK 2
NOBHNHK
AOBmaxµ H
maxµ
NOBmaxµ H
maxµ
Hmaxµ
67
Mass transfer
DNH4 1.5x10-4 m2.d-1 Williamson and McCarty (1976)
DNO2 1.4x10-4 m2.d-1 Williamson and McCarty (1976)
DNO3 1.4x10-4 m2.d-1 Williamson and McCarty (1976)
DO2 2.2x10-4 m2.d-1 Picioreanu et al., (1997)
DN2 2.2x10-4 m2.d-1 Williamson and McCarty (1976)
DS 1x10-4 m2.d-1 Hao and van Loosdrecht (2004)
(1) After unit conversion, using a typical biomass composition of CH1.8O0.5N0.2, corresponding with 1.3659 g COD.g-1
(2) Conversion of values given by Hellinga et al. at 35°C (written for XAOB, analogous for XNOB)
with =68 kJ.mole-1 ; =44 kJ.mole-1; R=8.31 J.mole-1.K-1. (3) Conversion of ASM1-values given by Henze et al. at 10°C and 20°C to 30°C using
temperature relationship proposed by these authors (ASM3). Calculated value at T=30°C and pH=7 from = 0.028 g NH3-N.m-3 and from = 3.2x10-5 g HNO2-N.m-3 considering the T and pH dependency of the chemical equilibrium
and
( )⎟⎟⎠
⎞⎜⎜⎝
⎛
⋅⋅
−⋅⋅=
ref
refAOBa
refAOBAOB
TTRTTE
TT exp)()( 1max
1max µµ
AOBaE
NOBaE
AOB3NHK NOB
2HNOK
++ +↔ HNHNH 34+− +↔ HNOHNO 22
68
Table 4. Available experimental results of partial nitritation process with tanning wastewater as influent.
Influent Effluent Time NH4 NH4 NO2 NO3 (days) (g/m3) (g/m3) (g/m3) (g/m3)
1 418.9 189.3 90.0 0.8 2 510.7 224.0 242.5 1.7 5 510.7 224.0 242.5 1.7 7 510.7 215.0 85.7 2.9
19 500.0 220.0 100.0 1.9 21 504.0 200.0 90.0 2.9 22 480.0 201.6 84.6 4.3 23 414.4 220.0 156.9 10.8 26 488.3 241.9 144.2 6.0 27 480.0 230.0 140.0 5.0 28 504.0 190.4 300.1 4.3 29 495.0 180.0 357.0 5.0 30 490.0 170.0 346.5 6.5 33 504.0 246.4 138.3 10.0 34 414.4 224.0 132.0 12.4 35 459.2 224.0 142.4 5.3 36 392.0 280.0 80.9 3.1 37 403.2 336.0 63.9 0.9 39 490.0 210.0 160.0 2.4 40 481.0 291.0 134.0 3.3