characterization of industrial volatile organic compounds...
TRANSCRIPT
FACULTY OF BIOSCIENCE ENGINEERING
CENTRE FOR ENVIRONMENTAL SCIENCE AND TECHNOLOGY
Academic year 2015-2016
CHARACTERIZATION OF INDUSTRIAL VOLATILE ORGANIC
COMPOUNDS EMISSION IN RWANDA AND BIOFILTRATION
OF ACETONE, DIMETHYL SULFIDE AND HEXANE
Juvenal MUKURARINDA
Promoter: Prof. dr. ir. Herman VAN LANGENHOVE
Tutors: Dr. ir. Christophe WALGRAEVE
Ir. Joren BRUNEEL
Master’s dissertation submitted in partial fulfillment of the requirements for the degree of
Master of Science in ENVIRONMENTAL SANITATION
i
COPYRIGHT
The author and promoter give permission to use this thesis for consultation and to copy parts of it
for personal use. Every other use is subject to the laws of copyright; more specifically the source
must be extensively specified when using results from this dissertation.
Gent, June 2016.
Juvenal MUKURARINDA (author)
Ir. Joren BRUNEEL (tutor)
Dr. ir. Christophe WALGRAEVE (tutor)
Prof. dr. ir. Herman VAN LANGENHOVE (promoter)
ii
ACKNOWLEDGEMENTS
First of all, I want to say thank you to God Almighty for his faithfulness, mercy, provision,
protection and support during my entire study period.
I would never have been able to finish my thesis without guidance from my tutors and professor.
My deepest gratitude goes to my promoter Prof. dr. ir. Herman Van LANGENHOVE for allowing
me to do research at the EnVOC lab. I am also particularly grateful to him for his scholastic
guidance, innovative suggestions, and supervision throughout the period of research work.
I gratefully thank my tutors, Dr. ir. Christophe WALGRAEVE and Ir. Joren BRUNEEL for their helpful
attitude, constant encouragement, providing information constructive comments and great
endurance throughout the research and manuscript writing. They consistently allowed this paper
to be my own work, but steered me in the right direction whenever they thought I needed it.
I also gratefully acknowledge the valuable comments and suggestions from
Prof. dr. ir. Kristof Demeestere during the EnVOC presentation seminars.
I wish to extend my gratitude to all members of the EnVOC family especially Lore and Patrick for
their kind assistance during the research time.
My sincere gratitude and cordial respect to Prof. dr.ir. Peter Goethals to have allowed me to join
the challenging but wonderful program (Master of Science in Environmental Sanitation). My
sincere thanks to the coordinators of the program: Sylvie, Veerle for their kind cooperation,
valuable advice and continuous encouragement during the entire study period.
I would like to like to thank the Flemish Interuniversity Council i.e. Vlaams Interuniversitaire Raad
(VLIR-OUS) for offering me a scholarship to pursue higher education at Ghent University, Belgium
as well as for their blessed aim of transferring knowledge towards developing countries such as
Rwanda.
Finally, I must express my very profound gratitude to my parents, sisters and brother for providing
me with unfailing support and continuous encouragement throughout my years of study.
iii
ABSTRACT
Rwanda’s economic transformation is based on the service delivery, mining sector and industrial
activities. Technologies to handle the emissions in industries from production processes especially
VOC are yet to be established. In addition to that, no studies have been conducted before to
check the status of emissions made in different local manufacturing industries in Rwanda. VOC
are organic compounds which have adverse effects on human health as well as the
environment when exposed to high concentrations for long time.
This study was divided into two parts: In the first part, samples by means of Tenax TA sorbent
tubes were collected indoor and outdoor in three different industries, Sulfo Rwanda industry,
AMEKI color and Inyange industries. Samples were analyzed by TD-GC-MS and a total new data
of 45 VOCs concentrations levels were monitored to both indoor and outdoor environment of
the three local manufacturing industries. In Sulfo, soap production unit, the TVOCs indoor and
outdoor were 3.38 103 and 3.51 103 μg.m-3 respectively. Still at Sulfo, cosmetic production unit,
the TVOCs was 0.13 103 μg.m-3 for indoor and 0.06 103 μg.m-3 for outdoor. In AMEKI color, the
indoor and outdoor was 39.2 103 and 0.02 103 μg.m-3 respectively. At Inyange, the TVOCs
encountered were 0.45 103 μg.m-3 indoor and 0.02 103 μg.m-3 outdoor. The second part of the
study investigated the performance of a biofilter contaminated by three compounds with
different physical chemical properties, acetone, DMS and hexane. By means of SIFT-MS, VOC
concentrations were measured at different position along the BF and perform dynamic
partitioning coefficient of BF packing materials. The performance assessment of the biofilter was
done by comparing inlet concentrations (IL), elimination capacity (EC) and removal efficiency
(RE). The maximum RE of the mixed target total VOC was 74 % to IL of 22.4 ± 4.80 mg C.m-3.min-1
and EC of 16.6 ± 4.07 mg C.m-3.min-1 at an EBRT of 57 s. The highest maximum RE for individual
contaminants was 99.9 % for acetone at an IL of 20.9 mg.m-3.min-1 and 20.9 mg.m-3.min-1 EC. The
maximum RE of DMS was 74 % at IL of 34.9 mg.m-3.min-1 and 25.72 mg.m-3.min-1 EC. The maximum
RE for hexane was 47 % at IL of 67.33 mg.m-3.min-1 and 31.68 mg.m-3.min-1 EC.
Based on this performance, biofiltration can be seen as an urgent technology for the treatment
of the target VOC in manufacturing and production industries where technology for VOC
treatment is yet to be implemented.
Keywords: VOC, thermal desorption, gas chromatography, mass spectroscopy, biofiltration,
selected ion flow tubes mass spectroscopy (SIFT-MS), Ion Chromatography.
iv
TABLE OF CONTENTS
COPYRIGHT ................................................................................................................................................... i
ACKNOWLEDGEMENTS................................................................................................................................ ii
ABSTRACT .................................................................................................................................................... iii
GENERAL INTRODUCTION ........................................................................................................................... 1
PROBLEM STATEMENT ................................................................................................................................... 1
CHAPTER 1 LITERATURE REVIEW ................................................................................................................... 2
1.1 Volatile organic compounds ..................................................................................................................... 2
1.2 Sources of Volatile organic compounds ................................................................................................ 2
1.2.1 Natural sources ....................................................................................................................................... 3
1.2.2 Anthropogenic sources ........................................................................................................................ 3
1.3 Hazards of VOCs ............................................................................................................................................ 4
1.3.1 Human health effect ............................................................................................................................ 4
1.3.2 Tropospheric photochemical ozone formation ............................................................................ 5
1.3.3 Stratospheric ozone depletion ........................................................................................................... 6
1.3.4 Global Greenhouse effect .................................................................................................................. 6
1.4 Air pollution control technologies for VOCs ........................................................................................... 7
1.4.1 Non-biological technology for VOCs ............................................................................................... 9
1.4.2 Biological treatment of VOCS ............................................................................................................ 9
1.4.2.1 Biotrickling filters ............................................................................................................................ 10
1.4.2.2 Bioscrubber .................................................................................................................................... 11
1.4.2.3 Biofilter ............................................................................................................................................. 12
1.4.3 The biodegradation of hydrophobic compounds ..................................................................... 15
1.4.4 Parameters used to check the performance of the biological systems .............................. 16
1.5 Scope and objectives ................................................................................................................................ 16
CHAPTER 2 MATERIALS AND METHODS .................................................................................................... 18
PART I: ANALYSIS OF INDUSTRIAL VOC CONCENTRATIONS IN RWANDA ............................................ 18
2.1 Tenax TA tubes ............................................................................................................................................. 18
2.2 Conditioning ................................................................................................................................................. 18
2.2.1 Loading with internal standards ...................................................................................................... 19
2.2.1.1 Chemicals ...................................................................................................................................... 19
2.2.1.2 Preparation of the closed two-phase system ...................................................................... 19
2.2.1.3 Calculation of the headspace concentration .................................................................... 20
v
2.2.1.4 Loading ........................................................................................................................................... 20
2.2.2 Pump Calibration ................................................................................................................................. 20
2.3 Sampling Campaigns ................................................................................................................................. 20
2.3.1 Description of the sampling locations............................................................................................ 22
2.3.1.1 Sulfo Rwanda Industries .............................................................................................................. 22
2.3.1.2 AMEKI Color ................................................................................................................................... 23
2.3.1.3 Inyange Industries ........................................................................................................................ 23
2.4 Analysis of Tenax TA sampling tubes ...................................................................................................... 24
2.4.1 TD-GC-MS ............................................................................................................................................... 24
2.4.2 Calibration of the TD-GC-MS ............................................................................................................ 25
2.5 Quantification .............................................................................................................................................. 26
2.5.1 Calculation of the analyte concentration ................................................................................... 26
PART II: ABATEMENT TECHNOLOGY ......................................................................................................... 28
2.6 BIOFILTRATION ............................................................................................................................................... 28
2.6.1 Physical chemical properties of the representative VOC compounds ............................... 28
2.6.2 Biofiltration process .............................................................................................................................. 28
2.6.2.1 Biofiltration design ........................................................................................................................ 28
2.6.2.2 Biofiltration setup .......................................................................................................................... 28
2.6.3 Characterization of the packing materials .................................................................................. 30
2.6.3.1 Bulk Density .................................................................................................................................... 31
2.6.3.2 Moisture content .......................................................................................................................... 31
2.6.3.3 Water holding capacity ............................................................................................................. 31
2.6.3.4 Porosity ............................................................................................................................................ 31
2.6.4 Environmental conditions of the filter bed .................................................................................... 34
2.6.4.1 Temperature .................................................................................................................................. 34
2.6.4.2 pH ..................................................................................................................................................... 34
2.6.4.3 Nutrients .......................................................................................................................................... 34
2.6.4.3 Pressure drop ................................................................................................................................. 34
2.6.5. Analytical instrumentation ............................................................................................................... 35
2.6.5.1 Analysis with SIFT-MS .................................................................................................................... 35
2.6.5.2 Analysis with Ion chromatography .......................................................................................... 35
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CHAPTER 3 RESULTS AND DISCUSSION ..................................................................................................... 36
PART I: INDUSTRIAL VOC ANALYSIS IN RWANDA .................................................................................... 36
3.1 Results ............................................................................................................................................................. 36
3.2 Discussion ....................................................................................................................................................... 41
3.2.1 General discussion ............................................................................................................................... 41
3.2.1 Indoor to outdoor concentrations of the sampling sites .......................................................... 44
Part II: BIOFILTRATION OF VOC ................................................................................................................ 46
3.3 Results and discussion ................................................................................................................................ 46
3.3.1 Partition coefficient of the pollutants to the packing materials ............................................. 46
3.3.2 Biological oxidation of pollutants. ................................................................................................... 48
3.3.3 Bioreactor bed ..................................................................................................................................... 49
3.3.4 The Carbon dioxide (CO2) and Elimination capacity (EC) ...................................................... 51
3.3.5 The effect of pH on the removal of target VOC ......................................................................... 52
3.3.6 Sulfate measurement ......................................................................................................................... 53
3.3.7 Effect of Silicon on the removal of hexane .................................................................................. 54
3.3.8 Inhibitory effect for hexane degradation ..................................................................................... 54
CHAPTER 4 CONCLUSION AND RECOMMENDATION ............................................................................. 56
4.1 CONCLUSION ............................................................................................................................................... 56
4.2 RECOMMENDATION.................................................................................................................................... 57
REFERENCES ................................................................................................................................................ 58
APPENDIX I ................................................................................................................................................. 69
APPENDIX II ................................................................................................................................................ 72
A. Breakthrough curves for dry silicon foam ............................................................................................... 72
B. Breakthrough curves for dry wood chips ................................................................................................ 72
C. Breakthrough curves for dry compost .................................................................................................... 73
D. Breakthrough curve of compost at normal and dry condition. ...................................................... 73
vii
LIST OF FIGURES
Figure 1: Industrial sector VOC emissions in EU-27 ....................................................................................... 4
Figure 2: A tree diagram of the VOC emissions abatement technology (Khan & Ghoshal, 2000). . 8
Figure 3: Application limit of flow rate vs VOC concentrations of different air pollution
technologies control. ..................................................................................................................... 8
Figure 4 : Biotrickling filter setup . .................................................................................................................. 11
Figure 5: Bioscrubber setup. ......................................................................................................................... 12
Figure 6: A typical setup of biofilter. ............................................................................................................ 12
Figure 7: Conditioning oven ......................................................................................................................... 19
Figure 8: Tol-d8 structure. ................................................................................................................................ 19
Figure 9 : Sampling locations on the map of Kigali city........................................................................... 21
Figure 10: Soap production unit. Figure 11: Cosmetics production unit. .......................... 22
Figure 12: Paint production. .......................................................................................................................... 23
Figure 13: Juice and milk production unit. ................................................................................................. 24
Figure 14 : The TD-GC-MS with (1) the TD (2) the transfer line from GC to MS, (3) GC and (4) MS. 24
Figure 15: Schematic diagram of the biofiltration setup. it. .................................................................... 29
Figure 16: Actual setup of the biofilter ........................................................................................................ 30
Figure 17: Packing materials used in biofiltration process. ...................................................................... 30
Figure 18: The peak injection experiment of acetone, DMS and hexane. .......................................... 32
Figure 19: The peak injection experiment using methane gas. ............................................................. 32
Figure 20: Breakthrough curve of the pollutant to the packing material and blank. ....................... 33
Figure 21: Pressure drop in the filter bed. .................................................................................................... 34
Figure 22: The total indoor and outdoor concentrations of four sampling sites. ................................ 41
Figure 23: The indoor total VOC concentrations of chemical groups in four sampling sites. .......... 42
Figure 24: The outdoor total VOC concentrations of chemical groups in four sampling sites. ....... 42
Figure 25: Indoor target groups’ abundances in four sampled sites. ................................................... 43
Figure 26: Outdoor target groups’ abundance in four sampled sites. ................................................. 43
Figure 27: Partitioning coefficient of acetone, DMS and Hexane ......................................................... 47
Figure 28: The normalized start up concentrations of acetone, DMS and hexane at EBRT of 57 s.49
Figure 29: The Total inlet concentrations ( ) and total removal efficiency ( ) of the three
pollutants at EBRT of 57 s. ............................................................................................................ 50
Figure 30: EC in function of IL of acetone, DMS and hexane at an EBRT of 57 s. ............................... 51
Figure 31: Produced CO2 in function of total EC at an EBRT of 57 s. ..................................................... 52
Figure 32: RE in function of pH of acetone, DMS and hexane at an EBRT of 57 s. ............................. 53
Figure 34: The EC in function of IL for hexane in mixture and hexane only at EBRT of 57 s. .............. 55
viii
LIST OF TABLES
Table 1: Related health effects to exposure of high VOC concentrations. .......................................... 4
Table 2: Classification of vapor phase biotechnology systems. ............................................................ 10
Table 3: Performance parameters used in biological treatment systems. .......................................... 16
Table 4: The overview information of the VOC sampling campaign collected at three local
industries in Rwanda. ....................................................................................................................... 22
Table 5: Physical chemical properties of acetone, dimethyl sulfide and hexane. ............................ 28
Table 6: Calculated physical chemical properties of the packing materials. .................................... 32
Table 7: The precursor and products ion used to measure concentrations in SIFT-MS. .................... 35
Table 8: Indoor VOC concentrations (μg.m-3) measured at four sampling sites, Kigali, Rwanda. . 37
Table 9: Outdoor VOC concentrations (μg.m-3) measured at four sampling sites, Kigali, Rwanda.
.................................................................................................................................................................... 39
Table 10: Indoor to Outdoor ratio concentrations of the four sampling sites. .................................... 44
Table 11: Calculated partitioning coefficients of the dry packing material ....................................... 47
Table 12: Performance parameters of the biofilter. ................................................................................ 49
ix
LIST OF ABBREVIATION
AMEKI
Atelier des Meubles de Kigali
BF
Biofilter
Cin Inlet Concentration
Cout
Outlet concentration
CTS Closed two phase system
DMS
Dimethyl Sulfide
EBRT Empty Bed Residence Time
EC Elimination Capacity
EPA Environment Program Agency
GC Gas Chromatography
GWP Global Warming Potential
I/O Inlet to Outlet ratio
IL Inlet Load
IS Internal Standards
MINICOFIN
Ministry of Finance and Economic Planning, Rwanda
NIST National Institute of Standard and Technology
NOx Nitrogen Oxides
Q Flow
RF Response Factor
RSRF Relative Sample Response Factor
SIFT-MS Selected Ion Flow Tubes Mass Spectroscopy
TD Thermal Desorption
TVOCs Total Volatile Organic Compounds
V Volume
VOC Volatile Organic Compounds
1
GENERAL INTRODUCTION
PROBLEM STATEMENT
Air is an important free available commodity which defines life on earth but due to mostly
human activities the quality of air is changing and this reflect negative effects to human health
as well on environment.
The atmospheric emissions trends in developing countries are increasing mainly because of their
rapid economic transformation especially in urban places. In the last decade, emissions in
developed countries are reported to have decreased but some are still in higher concentrations
than the air quality standards for the protection of human health (Guerreiro et al., 2014). The
World Health Organizations (WHO) report that about seven million death globally attributed by
both indoor and outdoor air quality (WHO, 2014).
Atmospheric emissions are composed of (in) organic compounds and particulate matter.
Volatile organic compounds (VOCs) are part of organic compounds. They are harmful
pollutants with the ability to form the undesired photochemical tropospheric ozone smog and
potentially carcinogenic and mutagenic (Mohammed et al., 2013). Also VOCS participate in
destruction of stratospheric ozone which protects us from UV radiation (Mohammed et al., 2013).
Rwanda is an African developing country striving to transform its economy on average to 11.5 %
of Gross Domestic Products (GDP) growth by 2018 (MINECOFIN 2013). To attain that goal,
industries are increasing day to day in the country but know-how of handling emissions from
industrial activities is still lacking and there are no available air pollution control technologies. To
the best of our knowledge, so far in Rwanda no studies have been conducted to check the air
quality status in local manufacturing industries.
Therefore, to start bridging the gap, it is fortunate to characterize VOCs emitted from local
manufacturing industries in Rwanda and evaluate the performance of the cost effective
abatement technology which can be used to handle emission emitted during production
processes.
2
CHAPTER 1 LITERATURE REVIEW
1.1 Volatile organic compounds
Air is an essential component of life on earth. Therefore, air pollution is seen as a serious threat to
human being and the environment. Volatile organic compounds also commonly shorten as
VOCs, are organic compounds usually distinguished based on two groups definition; effect
definition and definition based on physical chemical properties (Demeestere et al., 2007).
Firstly, effect definition, US EPA define VOC as any compound containing at least one atom of
carbon, excluding carbon monoxide, carbon dioxide, carbonic acid, metallic carbides or
carbonates, and ammonium carbonates which participate in atmospheric photochemical
reactions (EPA, 2016). Secondly, based on physical and chemical properties, Solvent Emission
Directive (SED) defines VOC as any organic compound having at 20 °C a vapor pressure of
0.01 kPa (Directive 1999/13/EC).
Methane is often viewed separately due to non-absolute reactivity in the troposphere and
different concentrations range observed in different part of the atmosphere
(Demeestere et al. 2007). Therefore, it is imperative to take care of VOCs due to damage they
cause to both human health and as well as environment. They contribute to major
environmental problems to mention, global warming, stratospheric ozone depletion and
photochemical smog (Do et al., 2015). In presence of light, VOC react with nitrogen oxides to
form tropospheric ozone which in high concentrations cause human health problem
(Do et al., 2015). Many other VOCs like styrene and benzene are said to be responsible for
numerous adverse health effects, mainly respiratory, heart disorders and carcinogenic
(Stoji et al., 2015).
1.2 Sources of Volatile organic compounds
Sources of VOCs are divided into anthropogenic and natural sources. Anthropogenic sources
are the man-made VOCs while natural are emitted naturally mostly from vegetation. Often a
term biogenic is used to describe natural emissions of non-methane hydrocarbons (Evuti, 2013).
Emissions distribution depends on the industrial activities, climate and vegetation and varies
region to region (Evuti, 2013).
Globally, the biogenic VOCs, 1150 106 ton.yr-1 (Goldstein & Galbally, 2007), emissions in remote
areas are almost 10 times higher than the anthropogenic VOCs, 142.106 ton.yr-1 (Müller, 1992),
per carbon per year in the forms of VOCs. The inverse happen in urban places where
anthropogenic surpasses biogenic emissions concentrations (Burrows et al., 2007).
3
1.2.1 Natural sources
VOCs are naturally emitted from vegetation (Guenther et al., 2006). They account isoprenoids
(terpenes and monoterpenes) as well as alkanes, alkenes, carbonyls, alcohols, esters, ethers and
acids (Guenther et al., 2006) .
The concentrations of the emitted compounds reveal isoprenoids to be most prominent
compounds followed by alcohol and carbonyl compounds (Kesselmeier and Staudt, 1999).
The oxidation of the biogenic VOCs produce products with low volatility which participate in the
formation of Secondary Organic Aerosols (SOAs) (Kavouras et al., 1998; O’Dowd et al., 2002;
Kanakidou et al., 2005; Jimenez et al., 2009).
SOAs have an important impact on air quality and climate (Fiore et al., 2012; Scott et al., 2014).
To climate, SOA absorb and scatter solar radiation and they indirectly affect the cloud
condensation (Gouw, 2009).
Methane is not accounted in the oxidation process although it is produced naturally from
wetlands, rice field, livestock, landfills, biomass burning, forests, termites and oceans; it’s total
emissions is in between 145 to 260 106 ton.yr-1 (EPA, 2016).
1.2.2 Anthropogenic sources
Human made emissions encounter indoor and outdoor environment and they vary from various
sources (Bari et al., 2015). Indoor VOC concentrations are generally found in higher levels than
the ambient outdoor levels (Fellin et al., 1994; Spengler, 1995; Zhu et al., 2005; Heroux et al., 2008;
Stocco et al., 2008 ). Indoor VOCs are most emitted from building materials (e.g, floor and wall
coverings, carpet, insulation, paint), combustion processes (e.g, smoking, cooking, home
heating), consumer products (e.g, cleaners, solvents, air fresheners, and mothballs), attached
garages, dry-cleaned clothing, municipal tap water, or personal care products
(Wallace et al., 1987; Batterman et al., 2007; Stocco et al., 2008; wheeler et al.,2013;
Ye et al., 2014).
According to European Environment Agency, the main sectors involved in high VOC emissions
for the EU-27 are solvent and product use (41 %), the road and no road transportation
(18%), and commercial, institutional and household associated emissions (14 %)
(European environment Agency, 2010). Still in the EU-27 at the industry level, the most occurred
VOC sources are in; (1) energy (41 %), (2) chemical industry (22 %) and (3) coating and surface
treatment activities (18 %) (European Pollutant Release and Transfer Register, 2016) (Figure 1).
Ambient outdoor sources combine natural (e.g, vegetation and fires) and anthropogenic
sources (e.g, evaporation processes associated with industry and transportation, or paints and
solvents use) (Watson et al.,2001; Liu et al., 2008). In urban atmosphere, motor vehicles exhaust
4
and evaporative emissions are reported to have higher VOCs emissions concentrations than
other sources (Cetin et al.,2003; Lin et al., 2004).
Figure 1: Industrial sector VOC emissions in EU-27 (Adapted from European Pollutant
Release and Transfer Register, 2016).
1.3 Hazards of VOCs
1.3.1 Human health effect
The exposure to higher permissible limit of VOCs concentrations lead to acute or chronic health
effects (e.g, exposure to ceiling concentration for an 8 hours shift than 500 ppm of toluene
causes headache and dizziness (Jiang et al., 2005) (Table 1). But biochemical pathways and
physiological functions of most VOCs to human health are still uncertain (Rudnicka et al., 2014).
Table 1: Related health effects to exposure of high VOC concentrations.
Chemical compound Health effect
Benzene Carcinogenic
Ethers Producing peroxides, affecting the reproductive
system
Xylene Eye and respiratory tract irritation, narcotic effect,
nervous system depression and death
Chloroform Affect central nervous system causing depression,
dizziness, liver and kidney damages, skin infection
Acetone and Acetaldehyde Respiratory and eye irritation
Phenol Offensive odor and toxicity
Epoxides Toxic, carcinogenic, explosive
N-containing compounds
(Amines)
Bad Odor, carcinogenic (affecting urinary bladder)
Source: Viswanathan et al (2007).
41%
18%
8% 1%
22%
6% 1% 3%
Energy Sector
Coating & Surface treatment
activitiesProduction and processing of metals
Mineral Industry
Chemical Industry
Paper and wood production
Waste and Wastewater
management
5
1.3.2 Tropospheric photochemical ozone formation
Troposphere is the region of the Earth’s atmosphere where people reside and in which most
chemical compounds are emitted as a result of human activities (Atkinson 2000). Nitrogen
oxides (NOx= NO + NO2), VOCs and sulfur compounds lead the chemical and physical
transformation which results in the formation of tropospheric ozone globally (Logan, 1994), acid
deposition (Schwartz, 1989). The production of ozone in troposphere relies on the photolysis of
NO2 (Equation 1) and the subsequent association of the photoproducts O(3P) with O2 via
(Equation 2) through the molecular reaction with the third body (M being used to present any
third body co reactants, i.e N2) (Monks et al. 2015).
The mechanism reaction of tropospheric ozone formation is a complex branched chain reaction
between the VOCs and NOx in the presence of light (Evuti 2013). Equation 3 to 9 depicts the
mechanism reaction of tropospheric reaction. Ozone is first used as source of hydroxyl radicals
(OH) (Monks et al., 2015) through
O3 + ℎ𝑣 → O2 + O(1D) (Eq.3)
O(1D) + H2O → 2OH∙ (Eq.4)
Where O(1D) is the electronic excited state atomic oxygen formed through photolysis at
wavelengths <320 nm (Monks et al. 2015) . VOC, indicated here as R-H, molecules react with OH
to generate water vapor (H2O) and radical (R.) (Equation 5).
2OH∙ + R − H → R. + H2O (Eq.5)
The radical R. reacts directly with oxygen molecule yields peroxy radicals (RO2), which in turn
react with nitrogen monoxide (NO) to form nitrogen dioxide (NO2).
Under the influence of light, NO2 is decomposed into NO and oxygen atom (O). The reaction is
completed by oxygen atom and oxygen molecule to generate ozone (O3) (Monks et al., 2015).
NO2 + ℎ𝑣 → NO + O(3P) (Eq.1)
O(3P) + O2 + M → O3 + M (Eq.2)
R∙ + O2 → RO2 (Eq.6)
RO2 + NO → RO + NO2 (Eq.7)
NO2 + ℎ𝑣 → NO + O(3P) (Eq.8)
O(3P) + O2 + M → O3 + M (Eq.9)
6
The tropospheric O3 produced from hydrocarbon reactions as well as other sources is reportedly
to harm plants by reducing their growth due to limitation of carbon dioxide in stomata of
vegetation (Felzer et al., 2007).
1.3.3 Stratospheric ozone depletion
Stratospheric ozone layer is known to protect lower part of the earth’s atmosphere from high
frequency Ultraviolet (UV) light (Albritton, 1998). The ozone layer is reduced as a result of
imbalance between the formation and loss of ozone, where destruction is higher than
production (T et al., 2011).
Chlorine and Bromine released from man-made compounds such as chlorofluorocarbons
(CFCs) (example of CFC is dichlorodifluorocarbon [CCl2F2]) prone highly to the destruction of
stratospheric ozone (Angell et al., 2005). CFCs have long life time in the atmosphere (10 to 120
years) (Angell et al., 2005). As a matter of fact, CFCs are transported to the stratosphere where
they are eventually broken down by UV rays forming free chlorine (Equation 10) which reduce
ozone to oxygen molecule (equation 11 to 13).
CCl2F2 + ℎ𝑣 → Cl∙ + CF2Cl. (Eq. 10)
Cl. + O3 → ClO. + O2 (Eq. 11)
ClO. + O → Cl. + O2 (Eq. 12)
O3 + 0 → 2O2 (Eq. 13)
1.3.4 Global Greenhouse effect
Earth has the capacity to balance the absorption and emission of solar radiations (Evuti, 2013). It
absorbs the energy in the form of ultraviolet, visible light and infrared and emits the infrared to
outer space(Mohammed et al., 2012). Any process which interfere with this balance result in the
phenomenon of global warming also termed as climate change or greenhouse effect
(AEA group, 2007).
The Infrared (IR) absorption of atmospheric trace gases, water vapor and carbon dioxide
(Derwent, 1995; Mohammed et al., 2012) disturbs the radiative balance. Therefore, earth’s
surface and the atmosphere react to the disturbance by warming to restore the radiative
balance. This process is termed as radiative forcing and the warming is the greenhouse effect.
Halogenated compounds are also claimed to be powerful greenhouse gases and deplete
stratospheric ozone, they are ozone depleting substances (ODSs) especially compounds which
have chlorine and bromine attached on, hence, causing global warming (Myhre et al. 2013)
7
The effect of the compounds to cause global warming compared to carbon dioxide is
expressed in term of Global Warming Potentials (GWPs)(Evuti, 2013) (Table 2). The GWP is defined
as a ratio of the radiative forcing from a given mass emission of the trace gas compared to that
from the same mass emission of carbon dioxide, integrated over a given time horizon
(Mohammed et al., 2012).
Table 2: Global warming potential (GWP) of some VOCs in a 100-year time horizon.
Source: AEA group (2007).
1.4 Air pollution control technologies for VOCs
Many technologies have been introduced for VOC emission control. The available techniques
are basically classified into two different categories: (i) process and equipment modification and
(ii) add on control technique (Khan & Ghoshal, 2000) (Figure 2). In the first category, control of
VOC emissions are made by modifying the process equipment, raw material, and / or change
the process (Khan & Ghoshal, 2000).
On the other hand the latter category, require an additional control method to regulate the
VOC emissions. It has two subgroups dubbed destruction and recovery of VOCs
(Khan & Ghoshal, 2000; Delhoménie & Heitz, 2005).
VOC GWP VOC GWP
Carbon dioxide 1 Dimethylether 1
Bromomethane 5 propylene 4.9
Propane 6.3 ethylene 6.8
Butane 7 1,1- Difluoroethane 122
Ethane 8.4 Difluoromethane 670
Dichloromethane 10 1,1,1,3,3,-Pentafluorobutane 782
Chloromethane 16 1,1,1,3,3-Pentafluoropropane 1020
Dichlorotrifluoroethane 76 1,1,1,2-Tetrafluoethane 1410
Dichloropentafluoropropane 120 1,1,1,2,3,4,4,5,5,5-Decafluoropentane 1610
1,1,1-Trichloroethane 144 1,1,1,2,3,3,3 Heptafluoropropane 3140
Dichlorotetrafluoroethane 599 Pentanfluoromethane 3450
Dichlorodifluoroethane 713 1,1,1-Trifluoroethane 4400
Chlorodifluoromethane 1780 1,1,1,3,3,3- Hexafluoropropane 9500
Chlorodifluoroethane 2270 Trifluoromethane 14310
8
*RFR: Reverse Flow Reactor
Figure 2: A tree diagram of the VOC emissions abatement technology (Khan & Ghoshal, 2000).
The adaptation or choice of technology lies on the operating conditions (flow rate,
temperature, humidity and VOC concentrations) and the pollutants physico-chemical
characteristics (solubility, vapor pressure, biodegradability level and inflammability)
(Crocker & Schnelle, 1998). An illustration is given in Figure 3, of the application limit for flow rate
in function of VOC concentrations of destruction and recovery technologies.
Figure 3: Application limit of flow rate vs VOC concentrations of different air pollution
technologies control (Delhoménie and Heitz 2005).
VOC removal technique
Process and equipment
modification
Condensation Oxidation
Add on control techniques
Destruction Recovery
Absorption Adsorption Biofiltration Membrane
separation
Thermal
oxidatio
n
RFR*
8
Catalytic
oxidation
Activated carbon based adsorption Zeolite based adsorption
9
Biofiltration is the only biological VOC treatment technology found in recovery technologies. The
remaining ones found in recovery and all destruction control techniques are non-biological
treatment technologies.
1.4.1 Non-biological technology for VOCs
As indicated in Figure 3, the non- biological technologies are physical chemical technologies
generally applied to reduce off-gas with high VOC emission concentrations. The lower VOC
concentrations in the flue gases the higher energy input will be required to get rid of the VOC
especially in the oxidation processes (incinerations)(Khan and Ghoshal, 2000). In terms of cost,
physical chemical treatment technologies for VOCs emission involve higher cost than biological
treatments (Font and Artola 2011).
1.4.2 Biological treatment of VOCS
The biological treatment technology (biotechnology) for VOCs emissions was introduced first by
the European countries (Germany followed by The Netherlands), in 1960 (Leson & Winer, 1991;
Cloirec et al, 2005). The fundamental purpose of that biological treatment technology was to
handle odor and VOC emission at the industrial scale (Álvarez-hornos et al., 2011).
In 2003, the European IPPC reported that vapor-phase biotechnologies, including biofilters,
biotrickling filters and bioscrubbers, have proven to be more environmental friendly and chosen
as best available technologies for the reduction of the VOC emissions in chemical sector
(European commission, 2003).
Hence, biological gas treatment (biotechnologies) are seen as potential alternative to the
conventional physico-chemical processes for removal of VOCs with high flow rate emission
streams with relative low VOC concentrations; conditions observed more particular in painting,
coating and printing processes (Álvarez-hornos et al., 2011).
Biotechnologies or biological VOC treatment technologies rely on the capacity of
microorganisms of using their metabolisms to translate the organic pollutants to less harmful
compounds. Since the pollutants are in gas phase, they have to be transferred in aqueous
phase to be ready and used by microorganism (Álvarez-hornos et al. 2004).
The overall degradation process of the biofiltration is presented in Equation 14
( Álvarez-hornos et al., 2011; Font & Artola, 2011).
Organic pollutant + O2 CO2 + H2O + heat + biomass + other byproduct (Eq. 14)
microbes
10
The main types of biological treatment of VOC emissions include biofilters, biotrickling filters and
bioscrubbers (Delhoménie and Heitz 2005). The basic idea for the removal of VOCs mechanism
for these three biological technologies is similar but there notable differences with regards to the
aqueous phase and microorganism growth (Álvarez-hornos et al., 2011) (table 2).
Table 2: Classification of vapor phase biotechnology systems.
Biotechnology system Microorganism growth Aqueous phase
Biofiltration Attached growth Stationary
Biotrickling filter Attached growth Flowing
Bioscrubber Suspended growth Flowing
Source: Álvarez-hornos et al (2011).
1.4.2.1 Biotrickling filters
In biotrickling filters, biodegrdation happen when the gas is first transferred to the biofilm which
grow to the packing materials. The packing materials are made from chemical inert materials
such as plastic rings (Waweru et al,. 2000), resins, ceramics, celite, polyurethane foam
(Yamashima and Kitagawa, 1998), and no nutrients are available in such materials for
microorganism to grow. Nutrients are continuously supplied from the top to bottom in
countercurrent with the flue gas, the leachate is collected at the bottom and recycled back up
(Berenjian et al., 2012)( Figure 4). This feeding process facilitates control of biological operating
parameters like nutrients and pH (Muñoz et al., 2015). Soluble VOC are reported to be highly
removed by biotrickling flters (Berenjian et al., 2012).
The major bottleneck of this system is the clogging of excess biomass in the filter bed and
research has developed three major solutions, mechanical, chemical and biological
(Delhoménie and Heitz 2005). Mechanical by bed stirring (Wübker et al., 1997;
Laurenzis et al., 1998) or bed backwashing with water which allows drainage of the excess
accumulated biomass (Smith et al., 1996).
Chemical treatment to breakdown the chemical bindings between biomass and bed particle
by using disinfecting reagents (Diks et al.,1994; Schönduve et al., 1996; Cox and Deshusses, 1999;
Armon et al., 2000; Chen and Stewart, 2000). Biological use biomass predators such as protozoa
(Cox and Deshusses, 1997). Amongst all these solutions mechanical treatment using water for
backwashing is claimed to be most efficient and at least friendly to the ecosystem
(Cai et al., 2004).
11
Figure 4 : Biotrickling filter setup (Delhoménie and Heitz, 2005).
1.4.2.2 Bioscrubber
The bioscrubber contains two reactors, the absorption tower and bioreactor. In the absorption
tower, the gas is absorbed or diffused into aqueous solution via the countercurrent gas-liquid
flow through the inert packing materials. Packing material within the absorption tower provides
a better surface transfer between VOC and aqueous phase (Kellner and Flauger, 1998)
(Figure 5). The washed off or clean gas flow to the top and the contaminated liquid is pumped
in the bioreactor (Berenjian, Chan, and Malmiri 2012). The bioreactor is inoculated with
degrading constrains in aqueous phase and contains nutrients essential for their growth and
maintenance
(Delhoménie and Heitz 2005). The major limitation of bioscrubbing system is that they are applied
to only soluble contaminants with low Henry’s constant (<0.01) and low concentrations
(<5 mg.m-3)(Berenjian, Chan, and Malmiri 2012).
Continuous trickling Treated air
Polluted air
Bed made
from inert
materials,
inoculated
Nutrient solution
Waste solutions possible recycling
12
Figure 5: Bioscrubber setup (Delhoménie and Heitz, 2005).
1.4.2.3 Biofilter
This is the most basic biological treatment process that uses organic packing materials in which
culture of microorganisms are developed to degrade pollutants into less harmful compounds.
The contaminated air pass through a biofilter packed with organic carrier materials where
biofilm are fixed (Figure 6). Before the inlet gas stream enters the filter bed, it is pre-humidified to
avoid clogging in filter bed (Waweru et al., 2000). Biodegradation happen when the pollutant is
first transferred from gas to liquid phase. In the liquid phase, the pollutant is either absorbed in
water or adsorbed on the packing material. The unavailable pollutants for biofilm diffuse through
the filter bed.
Figure 6: A typical setup of biofilter (Delhoménie and Heitz 2005).
Aqueous solution Clean air
Bioreactor
Waste solutions containing pollutants
Polluted air
Activated sludge, suspended in
nutrient solution
Absorption
column
Treated air
Nutrient solution
Occasional irrigation
Waste solutions possible recycling Polluted air
Bed packed
with organic
materials
13
The successfulness of microorganisms to degrade pollutants depends on a good follow up of
physical, chemical and biological parameters of the biological system:
(I) Filter bed, is an important part of the biological treatment process because they support the
growth of microorganism communities responsible for pollutants degradation and increase the
contact between the gas and biofilm (Iranpour et al., 2005; Kennes et al., 2009).
A good packing material should have a high specific area favorable for microbial activity, good
water retention to avoid dehydration, high porosity to provide a homogeneous gas distribution
entirely into bed, availability of intrinsic for nutrients and diverse microflora
(Delhoménie & Heitz, 2005; Berenjian et al., 2012).
The most used organic packing media are compost, peat, soil, and at smaller scale woodchips
and bark(Easter et al., 2005; Delhoménie & Heitz, 2005; Gabriel et al., 2007). Studies made on
woodchips or bark found that these packing materials are less satisfactory as compared to peat
and compost because of their low pH buffering capacity, low specific area and nutrient
availability (Smet et al., 1996a; Smet et al., 1999; Hong & Park, 2004).
(II) Moisture content is a crucial parameter for effective filter bed as microorganisms need water
to carry their metabolic activity (Shareefdeen et al., 2005). Less bed moisture content lead to
dehydration and gas channeling which affect particularly the microflora
(Delhoménie and Heitz 2005). On the contrary too much water in the filter bed cause flooding
which leads to compaction and anaerobic conditions (Delhoménie and Heitz 2005). The
moisture content of the overall carrier materials must have a value between 40 and 60 (w/w)
(Ottengraf 1986; Waweru et al., 2000).
(III) Temperature, microbial activity also depends on the biofilter operating temperature. The
microbial growth in biological systems works at a temperature between 10 and 40oC
(Cloirec et al., 2005). Most of microorganisms grow in the biofilter are mesophilic
(Kennes & Thalasso, 1998) at a temperature ranging between 20 and 40 oC. And this
temperature ranges define the optimum temperature in biofilters (Delhoménie and Heitz 2005).
(IV) pH, to support the microbial growth a pH range from 5 to 9 is normally used and the stability
of this parameter in the biofilter increase the microbial activity (Cloirec et al. 2005). The optimum
pH is around neutrality, pH≈7 (Delhoménie and Heitz 2005). Compounds containing heteroatoms
(sulfur, chlorine and nitrogen) are oxidized to acid by-products which in turn lower the pH of the
biofilter (Devinny and Hodge, 1995; Christen et al., 2002). The effect of pH on biofiltration
efficiency depends on types of microorganisms (Clark et al., 2004). Fungi has the ability to grow
14
at both neutral as well as acidic medium conditions and they are metabolically active at pH
approximately between 2 and 7 (Delhoménie and Heitz 2005). On the other hand, bacteria are
very sensitive to pH, they are less tolerant to pH below 7 (Kumar et al., 2011). Two methods used
by authors to maintain pH to neutrality are either to irrigate the biofilter by nutrients solution
which have buffer capacity or insert the buffer materials in biofilters
(Delhoménie and Heitz 2005). Nevertheless, the ideal pH of the biofilter medium depends on the
pollutant being treated and the characteristics of the microbial ecosystem (Kumar et al., 2011) .
(V)Nutrient requirement, aerobic microorganisms’ performance in biofilter depends on the
availability of nutrients. The most elements needed for the growth of the biomass are nitrogen,
phosphorous, potassium, sulfur and trace elements in additional to oxygen and carbon
(Álvarez-hornos et al., 2011). For the long term performance of the biofilter an additional of
nutrients is required (Yang et al., 2002). Due to the importance of nitrogen towards biomass
growth, an additional of nitrogen to the biofitler media is reported to enhance the performance
of the biofilter (Morales et al., 1998).
(VI) Bed porosity, this is an essential parameter which maintains even air flow rate and decrease
the pressure drop across biofilter (Álvarez-hornos et al., 2011). The filter bed which used only
compost as packing material report to be 44.4 % for dry compost and 39.6 % for wet compost
(Douglas & Devinny, 1997). To increase the porosity and decrease degree of compaction in the
bed filter, a mixture of packing materials are used (Bohn, 1992).
(VII) Inlet pollutant concentration, obviously biofilter perform best for treating pollutant which are
in concentration less than 1000 ppm. High inlet VOC concentration in the biofilter lead to
inhibition of microbial activity (Álvarez-hornos et al., 2011). Also, high inlet concentrations lead to
insufficient oxygen availability in biofilter (Ottengraf, 1987). Studies have found that 30 ppm of
toluene had 99% removal efficiency but when doubled its concentration, the removal get down
to 82% removal efficiency (Álvarez-hornos et al., 2011).
(VIII) Microorganisms and acclimation time, the natural organic packing material used in bed
media parent microorganism in biofiltration. Microorganism such bacteria and fungi are used for
the degradation of VOCs (Kumar et al., 2011). The degradation of the pollutant depend on the
nature of the filtering materials and the biodegradability level of VOC to be treated
(Kumar et al., 2011). A single type of microorganism is enough to degrade certain pollutants and
for certain group of pollutants or even a culture of microorganism is used (Nanda et al., 2012).
15
Compost has been reported to use bacteria belonging to a group of Proteobacteria,
Actinobacteria, Bacteroidetes and Firmicutes (Chung, 2007).
An acclimation, time required obtaining stable high removal efficiency over a long time, for
microorganism to handle new substrate environment may take 10 days to 10 weeks
(Ralebitso et al., 2012). Introduction of inoculum to the bed media can shorten the lag phase
(Álvarez-hornos et al., 2011). A typical biofilter usually contains 106-1010 cfu of bacteria and
actinomycetes per gram of bed and fungi in the range of 103-106 cfu per gram of bed
(Ottengraf, 1987). Degrading species in a biofilter are normally between 1 and 15 % of the total
microbial population (Pedersen et al., 1997; Delhomenie et al., 2001).
(IX) Empty bed residence time (EBRT), both air flow rate and EBRT are important parameters with
reasonable impact on the biodegradation performance of the biofilter (Elmrini et al., 2004).
Increasing EBRT will produce high removal efficiency. EBRT can be relied on to increase the
biofiltration performance and should be greater the time needed for diffusion processes for low
operating flow rate (Álvarez-hornos et al., 2011).
1.4.3 The biodegradation of hydrophobic compounds
Hydrophobic compounds have high Henry’s constant as compared to hydrophilic compounds.
That said, they are less soluble in water than hydrophilic compounds a factor which make them
often hard to reach the biofilm layer in biofilter thus providing low removal efficiency.
The composition of the filter materials is a critical parameter for effective biofilter toward the
removal efficiency of the hydrophobic and less soluble compounds. Studies conducted on
biofiltration of hydrophobic compounds proposed that improved adsorbing materials such as
granular activated carbon (GAC) may have characteristics that may promote higher
elimination capacity particularly for compounds with low solubility that emitted in variable loads
(Tonekaboni, 1998). Also, a way suggested by researchers to reduce solubility and transport of
hydrophobic compounds into filter bed was the use of Fungi (Woertz et al., 2001;
García-Peña et al., 2001). García-Peña et al (2001) described elimination capacity for toluene
up to six times higher than usually reported for bacteria using Paecilomyces variotii. Again for
hexane, which is around 100 times less soluble than toluene, EC between 100 and 150g.m-3.h-1
were obtained by Aspergillus níger (Spigno et al., 2003), while only between 10 and 60g.m-3.h-1
have been reported with bacterial consortia (Budwill and Coleman, 1999; Paca et al., 2001;
Kibazohi et al., 2004).
16
1.4.4 Parameters used to check the performance of the biological systems
The most common parameters used to check and compare the performance of biological
systems are summarized below (table 3)
Table 3: Performance parameters used in biological treatment systems.
Parameter Formula [unit] Description
EBRT EBRT =
V
Q[𝑠]
EBRT is the time taken by a gas in the biofilter.
Where V= Volume of the reactor (m3)and Q =
the flow of the gas (m3.h-1)
Inlet Load (IL) IL =
Q
Vx Cin[g. m−3. h−1]
This is the amount of the pollutant introduced in
biofilter per unit volume per time. Where Cin is
concentration of pollutants in the inlet gas
stream (g.m-3)
Elimination
capacity
(EC)
EC
=Q
V (Cin − Cout)[g. m−3 . h−1]
This is the amount of the pollutant removed per
volume of a filter bed per unit time
Removal
efficiency
(RE)
RE =(Cin−cout)
Cin x 100 [ %] This is the amount of the pollutant removed in
fraction converted in percentage.
Source: Waweru et al (2000).
1.5 Scope and objectives
Rwanda is a landlocked country whose economy has shown to be increasing since the tragedy
of the 1994 Tutsi’s Genocide (MINECOFIN 2013). Despite the tragedy of Tutsi’s Genocide,
population density (people per km2) is increasing year to year (449 in 2010 and 460 in 2015)
(World Bank, 2016). The basic country’s economic transformation is helped by the industrial,
service delivery and mining sector (Rwanda national institute of statistics, 2011). Industrial
activities and traffic are believed to be the main contributors of high atmospheric emissions in
the country especially in the capital city, Kigali.
Prior to industrial emissions, there are no available abatement technologies for the already
implemented industries. In addition to that, no studies have been conducted before to check
the status of emissions made in different local manufacturing industries. This is a common
problem shared by almost all African countries where data on the concern of air quality status
are hardly or not even found (Do et al. 2013).
17
To start bridging the gaps, a VOC study was conducted to make a new qualitative and
quantitative data in three different local industries namely Sulfo Rwanda industries producing
soap and cosmetic, Atelier Des Meubles de Kigali (AMEKI) making paints and Inyange industries
producing milk and juices by means of active sampling using Tenax TA tubes and TD-GC-MS
analysis.
This study is divided into two main objectives:
1. To characterize the VOC emitted in three local manufacturing industries, Sulfo Rwanda
Industries, AMEKI color and Inyange industries. Specific objectives on this first part are:
To characterize VOCs emitted in three industries
To identify and comparing the most occurring compounds from Indoor to outdoor in all
industries.
2. To evaluate biofiltration for the cost effective treatment of the waste gases containing
important pollutants, focus given to acetone, dimethyl sulfide and hexane.
Specific objectives on are:
To compare removal efficiencies of the three compounds (acetone, dimethyl sulfide and
hexane) in a biofilter packed with compost, silicon foam and wood chips.
To check the effect of using adsorbing materials, silicon foam, for the removal of
hydrophobic organic, hexane and assess inhibitory effects.
To check the partition coefficient of target VOC to the packing materials.
18
CHAPTER 2 MATERIALS AND METHODS
This chapter is split into two parts; Part (I) is the analysis of the industrial VOC concentrations
sampled in Rwanda. Samples were taken at three different local manufacturing industries by
means of active sampling using Tenax TA sorbent tubes. After sampling, they were transported
to the environment organic chemistry and technology lab for analysis. Part (II) is the Technology
based part, where biofiltration a cost effective abatement technology was used to evaluate the
removal efficiency of VOC where focus was given to acetone, dimethyl sulfide (DMS) and
hexane as representative VOC.
PART I: ANALYSIS OF INDUSTRIAL VOC CONCENTRATIONS IN RWANDA
2.1 Tenax TA tubes
Tenax TA tubes are tubes filled with sorbent resin (2, 6 diphenylene oxide) to capture VOCs and
semi-VOCs. They have standard dimensions of 1/4 inch (6.4 mm outer diameter x 5 mm internal
diameter), the length of 3.5 inch( 89 mm) and are filled with 200 mg of Tenax TA) (Anon, 2011).
Tenax TA tube can be heated up to 350 °c, has low affinity for water and has a specific surface
area of 35 m2.g-1 and average pore size of 200 nm based on Scientific Instrument Services
(SIS, 2016). The tubes are closed with 1/4 inch brass closure caps (Anon, 2011). The cap has a
white Teflon ferrule (Alltech SF-400T) that creates a better airtight seal. Each tube has an external
groove which indicates the sampling side (Do et al, 2009). The tube can be used more than 100
and after that period the resin should be replaced out of precaution (SIS, 2016).
2.2 Conditioning
Prior to sampling, the Tenax TA tubes should be conditioned to make sure that no residual
components remain on sorbents. Stainless steels, Tenax TA tubes, were put in an oven at 300 oc
for an hour under the flow of 10-50 ml.min-1 helium, to remove all residual components. During
heating oxygen should be avoided to enter since it is detrimental to the adsorbent resin. The
Tenax TA tubes in the oven are positioned with the sampling side mounted out. The oven
(Carlo Erba Instruments, MFC 500) is capable of heating nine tubes all at once.
19
Figure 7: Conditioning oven
2.2.1 Loading with internal standards
2.2.1.1 Chemicals
Deuterated Toluene (Tol-d8; 99.5%; Acros organics, Geel, Belgium) was used as an internal
standard (IS) (Figure 8).
Figure 8: Tol-d8 structure.
The solvent used for IS is methanol (LC-MS grade, 99.5%, Biosolve, Valkenswaard, Netherlands).
Tenax TA sorbet tubes have low affinity for methanol that’s why methanol was used as a solvent.
The stock solution of 223.7 µg.ml-1 was prepared by putting 24 µL of Tol-d8 in 100 mL of methanol
then kept in total darkness at -18 oC.
2.2.1.2 Preparation of the closed two-phase system
To prepare a gaseous Tol-d8, 20 μL of stock solution was added to 20 ml of deionized water
present in 119.8 mL of a glass bottle. Then, the bottle containing a mixture of stock solution and
deionized water was gas tightly sealed with a mininert valve (Alltech, Lokeren, Belgium) and
incubated in a thermostatic water bath at 25 ± 0.2 oC for 12 hours to assure the equilibrium
between gas and the liquid phase is reached.
D
CD3
D
D
D
D
20
2.2.1.3 Calculation of the headspace concentration
A given gas and water volumes at a specific temperature with known total mass and Henry’s
law constant of Tol-d8 (Dewulf et al., 1996), the headspace concentration of IS can be
calculated from the mass balance equilibrium. First, the total mass of Tol-d8 (m total) added to
the CTS was equal to 4474 ng. Based on the mass balance and Henry constant of Tol-d 8 at
25 oc (H= 0.183), we can derive,
Equation 15 can be rewritten into Equation. 17
4474 ng =Cair
0.183∗ Vwater + Cair ∗ Vair
(Eq. 17)
Then with Vwater= 20 mL; Vair =99.8 mL, the concentration of Tol-d8 in the headspace can be
calculated as 21.4 (ng.mL-1). This means that 0.5 mL air in the CTS contains 10.7 ng of Tol-d8.
2.2.1.4 Loading
In CTS, 0.5 mL of headspace was taken by 0.5 ml gastight pressure lock VICI precision analytical
syringe (Series A, Alltech). The desired volume was loaded onto the sorbent tubes through an
injection system flushed with helium (He) (flow rate of 100 mL.min-1). And finally, the He stream
was held on for 3 min before the tubes were sealed with ¼ inch brass long term storage
endcaps, equipped with ¼ inch one-piece PTFE ferrules.
2.2.2 Pump Calibration
A Gil Air sampling pump was calibrated before use by Gilibrator to make sure the targeted flow
rate is at least repeatedly obtained, and it was regulated on an average flow rate of 100 ± 0.5 %
mL.min-1 (n = 8).
2.3 Sampling Campaigns
The sampling campaign of VOCs in Rwanda was held at three different local industries namely
Sulfo Rwanda industries, AMEKI color and Inyange industries producing cosmetics, paints and
beverages respectively (Figure 9).
mtotal = mair + mwater=cair × Vair+cwater × Vwater ( Eq. 15)
H =Cair
CWater=0.183 mol.L−1 mol.L−1⁄ ( Eq. 16)
21
The sampling campaign was performed by means of active sampling using Tenax TA sorbent
tubes (n = 1) at indoor and outdoor of the three local manufacturing industries on 16th July and
30th July 2015 (Table 4). Two samples (one for three minutes and another for 30 minutes) were
sampled indoor and outdoor at each sampling site and two blanks were among sampling Tenax
tubes which remained closed entirely the whole campaign. The three minutes samples are the
one which were analyzed as they were found to be loaded with enough VOC concentrations
for measurements.
(1) Sulfo soap production unit (2) Sulfo cosmetics production unit, (3) AMEKI color for paints (4) Inyange for
juice and milk processing (beverages)
Figure 9 : Sampling locations on the map of Kigali city.
2
1
3
4
1
2
3
4
40 km
22
Table 4: The overview information of the VOC sampling campaign collected at three local
industries in Rwanda.
Indoor Outdoor Date Time Sample
size
Sampling times
1. Sulfo Rwanda Industries
16-07-2015
11:00-13:50
8 I. Soap production 30 30
3 3
II. Cosmetics 30 30
3 3
2. AMEKI color 30 30 16-07-2015 14:30-16:00 4
3 3
3. Inyange Industries 30 30 30-07-2015 16:00-17:45 4
3 3
2.3.1 Description of the sampling locations
2.3.1.1 Sulfo Rwanda Industries
Sulfo Rwanda Industries is a local manufacturing industry producing drinking water, hard and soft
soap, and cosmetics (body lotion, glycerin and toilet soap). The industry has four production
units. Samples were taken in late morning between 11:00 and 13:50 on 16th July, 2015 at two
manufacturing units, hard soap production and cosmetics unit.
The two production units are built in the middle of a busy place downtown in the capital city; on
the street of soap production unit there is a lot of traffic, big public parking lot at the back and
like in 300 m there is also a big city market hall and other many retailing business around it. The
cosmetic production unit is close to a national museum and prison (Figure 10) and (Figure 11).
Figure 10: Soap production unit. Figure 11: Cosmetics production unit.
23
2.3.1.2 AMEKI Color
AMEKI color is a paint production company located at the industrial park; it neighbors different
industries and is no far away from a polyclinic and petro station. Samples were taken in
afternoon between 14:30 and 16:00 on 16th July, 2015.
AMEKI color is the leading paint local manufacturing industry in Rwanda. Paints produced are;
(1) latex matt, based on styrene acrylic emulsion, suitable for ceilings and walls internally or
externally whether new or previously painted and (2) Silk Vinyl emulsion, water-based emulsion,
noted to be environmental friendly (Figure 12).
The company is mostly manual based paints production and permanent employees are in
direct contact with the raw products for paint making. Diesel is entirely used for cleaning all used
materials in the process.
Figure 12: Paint production.
2.3.1.3 Inyange Industries
The Inyange industry is located outside the capital, there is no high traffic as compared to the
city center and it is built in the lowland close to marchland. There is little habitation across the
industry. Inyange is the first ranked industry for the production of beverages in the country. Their
daily production is drinking water, juices, milk packaging and milk processing. All production
units are combined in the same site. After the production and packaging, caustic soda is
passed in the tanks for cleaning purposes. Samples were collected in the afternoon from 16:00 to
17:45 on 30th July, 2015 in the milk and juice production units (Figure 13).
24
Figure 13: Juice and milk production unit.
2.4 Analysis of Tenax TA sampling tubes
2.4.1 TD-GC-MS
Tenax TA tubes used in three sampling campaign location in Rwanda were transported to
laboratory and analyzed by TD-GC-MS in a method described by Do et al (2009) (Figure 14).
Figure 14 : The TD-GC-MS with (1) the TD (2) the transfer line from GC to MS,
(3) GC and (4) MS.
The desorption of analytes pre-concentrated on the Tenax TA sorbent tubes was performed by
a unity 2 thermal Desorption system (Markes, Llantrisant, UK) at 260 oC with 20 mL.min-1 helium
flow for 10 minutes. Each Tenax TA tube was put in the TD system equipped with two special
diffusion caps.
Desorption process was first pre-purged at 34 oC for two minutes to make sure that water vapor is
eliminated inside Tenax TA tubes and then a temperature of 260 oC for 10 min was set to tube
desorption. Next, analytes were refocused on a microtrap 100 % Tenax TA (noC-TNXTA)
(Markes, Llantrisant, UK) cooled at -10 oC. The Tenax TA tubes were heated up sharply from
-10 oC to 280 oC within three minutes.
2
4
3
1
25
Analytes were carried by a helium flow and injected onto a 30 m factor four VF-1 ms low bleed
bounded phase capillary GC column (Varian, Sint-Katelijne-Waver, Belgium;
100 % polydimethylsiloxane, internal diameter 0.25 mm, film thickness 1µm), after splitting helium
flow at 5 ml.min-1. The column head pressure was set at 50 kPa, resulting into a flow of
1.0 mL.min-1 (at 130 oC) through the GC column.
The GC (Focus GC, Thermo Scientific, Italy) oven temperature was initially set at 35 oC for
10 minutes. Next, the temperature in the GC was increased gradually up to 240 oC into four
stages (1) from 35 to 60 oC (2 oC.min-1), (2) from 60 to 170 oC (8 oC.min-1), (3) from 170 to 240 oC
(15 oC. min-1) and (4) (240 oC) was held for 10 minutes before cooling down to 35 oC. Even
though GC was cooled down, the transfer line from GC to MS was kept at 240 oC.
Mass from m/z 29 to 300 were recorded in full scan mode (200 ms per scan) on a DSQ II.
Quadrupole MS (Thermo Scientific, Austin, TX, USA), hyphenated to the GC, and operating at an
electron impact energy of 70 eV. Chromatograms and mass spectra were processed using
Xcalibur software (Thermo Finnigan, version 2.2)
Compound identifications were predicted based on (i) their fragmentation patterns and by
comparison of their mass spectra with the US National Institute of Science and Technology (NIST,
Gaithersburg, MD, USA) 2.0 database [NIST/US Environmental Protection Agency (EPA)/US
National Institute of Health (NIH) Mass Spectra Library], and (ii) comparison of retention time with
the standards.
2.4.2 Calibration of the TD-GC-MS
To have the correct concentration values, calibration was performed. A total set of 78 LC-MS
grade standard VOCs were used for the calibration.
These VOCs were purchased at the Acros Organics (Geel, Belgium) and/or at Sigma-Aldrich
(Bornen, Belgium) and all had a purity of at least 99.8 %. Methanol (LC-MC grade, 99.95 %,
Biosolve, Valkenswaard, Netherlands) served as a solvent for all standard compounds.
The 78 standards compounds were prepared and divided into three stock solutions (A, B and C)
(in methanol) together with a known mass of Tol-d8. A known volume 1µL of the stock solution
was loaded on two Tenax TA sampling tubes corresponding with a loaded mass between 31.3
and 81.2 ng. For each calibration of the TD-GC-MS, there were six calibration files corresponding
with 2x3 sampling tubes. The six tubes were then analyzed in the TD-GC-MS in full scan mode.
The quantification, data were processed by an extracted ion chromatogram.
26
The sample response factor (SRFi) in the chromatography is defined as the signal output per unit
mass of the substance injected. Therefore, SRFi can be calculated based on the Equation 18.
Where, Ai is the peak area and mi the mass (ng) of the substance i on the sorbent tube. Based on
the concept of SRF, the RSRF (Relative Sample Response Factor) is defined as the ratio of sample
response factor of the analyte (SRFa) and Tol-d8 (SRFst).
It is worth noting that RSRF is dimensionless. During the calibration of the TD-GC-MS, both
analyses and Tol-d8 were loaded from the liquid phase.
Demeestere et al. (2008) have found RSRF L,L (both loaded from liquid phase) and RSRF G,G (both
loaded from air phase) are the same.
2.5 Quantification
2.5.1 Calculation of the analyte concentration
Since we know (i) the mass of the IS (mst = 10.7 ng as calculated in section 2.2.1.3 from CTS (ii) the
peak areas of the analyte and the IS and (iii) RSRFL,L from the calibration of TD-GC-MS we can
depict the mass of the target compound (ma) on the sorbent in active sampling.
The Volume of the sampled air can be obtained from Eq.23.
SRFi =Ai
mi
(Eq.18)
RSRF =SRFa
SRFst
(Eq.19)
RSRFL,L =SRFa
SRFst
(Eq.20)
RSRFL,L ≈ RSRFG,G =SRFa
SRFst
(Eq.21)
ma =mast × Aa
Ast × SRFL,L
(Eq.22)
27
And Qsample is the flow rate of the sampling pump and tsample is the sampling residence time. And
the concentration can be calculated as:
All components’ peaks were determined from respective extracted ion chromatographs and
the RSRFL, L was determined from the calibration of the TD-GC-MS. A blank correction was also
performed during the concentration calculations.
V = QSample × tsample (Eq.23)
Ca =ma
V (Eq.24)
28
PART II: ABATEMENT TECHNOLOGY
2.6 BIOFILTRATION
Given state of the art cost effective abatement technology, biofiltration was used to evaluate
the removal efficiency of VOCs where focus was given to three compounds, acetone, dimethyl
sulfide and hexane.
2.6.1 Physical chemical properties of the representative VOC compounds
The most important physical chemical properties describing acetone, dimethyl sulfide and
hexane are summarized in Table 5.
Table 5: Physical chemical properties of acetone, dimethyl sulfide and hexane.
Parameters Acetone DMS Hexane
Functional group Ketone Sulfur compound Alkane
Molecular weight (g.mol-1) 58.08 62.13 84.17
Odor threshold(ppmv)2 42 0.003 1.5
Boiling point (0C)2 46.5 29.5 68.5
Vapor pressure at 25 0C (mmHg)3 231 502 153
Solubility in H2O at 25 oC( g.L-1)2 94 45 0.016
Henry’s law constant (-) (Cg/CL)1 0.012 0.048 44
1Calculated using the solubility and vapor pressure
2 (Nagata, 2003); 3 (SciFinder, 2016); (Daubert, 1989)
2.6.2 Biofiltration process
2.6.2.1 Biofiltration design
The biofiltrer was built using six identical cylindrical modules of Plexiglas and the total height of
the setup was 1.2 m with internal diameter of 10 cm. The packing materials in the biofilter
occupied only 1 m height and the remained 0.2 m at the bottom was occupied by glassbits
purposed to homogenize gas flow streams before enter the filter bed.
2.6.2.2 Biofiltration setup
The biofiltration setup used in the experiment was divided into three major parts: (A) generation
of the flow air controlled by mass flow controllers (B) the filter bed equally packed by compost,
woodchips and silicon foam and (C) analysis of VOC concentrations and CO2 produced by
29
SIFT-MS (Syft technology, the Voice 200®, Christchurch, New Zealand) and Vaisala CARBOCAP®
hand held carbon dioxide analyzer (GM70 model, vaisala, Finland) respectively (Figure 15).
Figure 15: Schematic diagram of the biofiltration setup. (1) pressure regulator (PR), (2) mass flow
controllers (MFC1; Q1 = 5 L.mim-1, MFC2 ; Q2 = 2.5 L.min-1, MCF3; Q5 = 0.2 L.min-1 and
Q3= Q1+Q2) (3) acetone bottle, (4) DMS bottle, (5) hexane bottle, (6) pressure control valve, (7)
humidifier column, (8) filter bed, (L1) leachate collection port, (P1) inlet port, (P2), (P3), (P4) and
(P5) are intermediate ports, (P6) outlet port, (9) flow monitoring valve, (10) rotameter, (11) clean
gas exit.
The aim of the setup was to measure the overall performance of the filter bed polluted with
acetone, DMS and hexane. The polluted air flow streams were generated by passing streams of
air into capillaries attached to liquid bottles filled with acetone, DMS and Hexane
(Acros Organics) controlled by mass flow controllers (Brooks Instruments, Mass flow controllers®,
Hartfield, USA). The capillary used for acetone and hexane was 5 cm long and 1/8 inch
diameter, and DMS was 10 cm long and 1/8 inch diameter. They were connected to ¼ inch
white Teflon PFTE tubing which connected the streams in the entire system. The main
Q4
Q3
Q5
Q3
Q1
Q2
2
11
9
1
1
2
2
6
3 4 5
7
L1
1
P1
10
P6
P2
P3
P4
P5
MFC 1
SIFT-MS
CO2
8
A B
b
C
MFC 2
MFC 3
30
contaminated stream flow (Q3) was pre-humidified in humidifier filled with water before getting
in the filter bed packed equally in volume by compost, woodchips and silicon foam.
The stream (Q3) flows upward in the filter bed which had six measuring ports (i.e. inlet, outlet and
four intermediate measuring ports). The leachate collection port was at the bottom of the filter
bed. Valve on measuring port was manually switched to start a small flow (Q4) that was
analyzed from the big stream (Q3) in the BF. This stream flow (Q4) controlled by valves and
measured with rotameter was diluted with a stream flow (Q5) of nitrogen before reaching
measuring instruments to avoid high concentration in the SIFT-MS. Figure 16 represent the actual
experimental set up for the study
Figure 16: Actual setup of the biofilter (1) PR, (2) polluted bottles, (3) humidifier column,
(4) biofilter, (5) SIFT-MS.
2.6.3 Characterization of the packing materials
The packing materials used for the experiments were compost (port grand, Belgium), woodchips
and silicon foam (sponge cord®, Netherlands). They were mixed and put in a filter bed at equal
volume fractions (1/3 v/v) (Figure 17). The physical chemical properties conducted for the
packing materials were density, moisture content, water holding capacity and porosity.
Figure 17: Packing materials used in biofiltration process. (1) Compost, (2) woodchips and
(3) Silicon foam.
5
2 3
4
1
1
2
3
31
2.6.3.1 Bulk Density
The apparent density of the three packing materials was measured by weighting packing
materials at ambient conditions into a known volume dimension. The Equation (25) was used to
calculate the bulk density, where mP and VB are weight of the packing material and volume of
used column respectively.
Bulk density =mP
VB
(Eq.25)
2.6.3.2 Moisture content
The moisture content of the packing materials was calculated based on Equation (26) with mP
and mDP the mass of the packing material at ambient conditions and the mass of the dry
packing material after 72 h at 358 K in oven.
Moisture content =mP − mDP
mp
x100 (Eq.26)
2.6.3.3 Water holding capacity
The water holding capacity of the packing materials was calculated by applying Equation (27)
with mw and mWP the amount water poured on the dried packing material and the mass of the
packing material 15 min after pouring water.
2.6.3.4 Porosity
The porosity of the mixed packing materials (1/1/1 volume ratio) was calculated based on an
online method using SIFT-MS. It was calculated as the ratio of net residence time (NRT) over
empty bed residence time (EBRT) (Equation 28). Compounds with high Henry’s law constants
behave as inert compound into biofilter and no degradation and absorption might happen to
such compounds (Volckaert, 2014). Dynamic experiment to calculate the porosity in a first
attempt was done by injecting 10 μL of hexane liquid into the biofilter. No peaks were found at
the outlet port for acetone, DMS and hexane. This can be cause by the interaction of the
packing materials with the contaminants (Figure 18). The second experiment, a 15 ml of
methane (± 35000 ppm) gas was injected and the peaks were recorded by the SIFT-MS to both
Water holding capacity =mWP − mDP
mW
x100 (Eq.27)
32
inlet and outlet (Figure 19). The net residence time was calculated by subtracting the time of
injection to the top of the peak.
Figure 18: The peak injection experiment of acetone, DMS and hexane.
Figure 19: The peak injection experiment using methane gas.
Table 6 represents the summary of the calculated physical chemical properties.
Table 6: Calculated physical chemical properties of the packing materials.
Packing material
Property (unit) Compost Woodchips Silicon foam
Moisture content (w/w %) 79 23 16
Water holding capacity (w/w %) 76 61 5
Bulky density (g.mL-1) 0.28 0.33 0.13
Porosity of the mixed packing materials (%) 37 ± 1.27
Porosity =
NRT
EBRT
( Eq. 28)
33
2.6.3.5 Partitioning coefficient determination procedure
Walgraeve et al (2015) developed a new easy and fast online method to calculate the
partitioning coefficient using SIFT-MS. The same method was used to calculate the partitioning
coefficient of acetone, DMS and hexane to the packing materials (compost, woodchips and
silicon foam). Pollutants with constant concentrations were bubbled through a solid phase
(packing material). At this positon, there was phase transfer from gas to solid phase which were
monitored by SIFT-MS.
A small flow F1 (31.92 ml.min-1) of acetone, DMS and hexane leaving the BF controlled by valve
system and measured by rotameter was connected to a four way valve switching system
(SS-43YFS2 Swagelok, Belgian fluid system technologies BVBA, Groot-Bijgaarden, Belgium). Air
stream F2 controlled by mass flow controller was also flowed into a four way valve aimed to
clean the system and blank measurements.
From four way valve, polluted air was fed to a bubble column filled with known weight of
packing material. The concentrations leaving the bubble column was continually measured by
SIFT-MS until the outlet concentrations (cout) becomes equal to the inlet concentration (cin).
The resulted breakthrough curves (see an example on Figure 20) was used to calculate the
dimensionless partitioning coefficient of the packing materials to the pollutants (KPM/air) (mg
[VOC].m-3 [packing material]).(mg [VOC].m-3) [air])-1 (Equation 29) where A is the surface of the
packed material breakthrough curve based on the normalized concentration (outlet over inlet
concentration), B the surface of obtained breakthrough curve of empty bubble column,
Q (m3.min-1) is the flow of the sample concentrations and V (m3) the volume of the packing
material in bubble column.
Partition coefficient =
(A − B) x Q
V
(Eq. 29)
Figure 20: Breakthrough curve of the pollutant to the packing material and blank.
34
2.6.4 Environmental conditions of the filter bed
2.6.4.1 Temperature
The temperature of the filter bed was simulated based on the room temperature where the
biofilter was placed. The average bioreactor temperature was 18 ± 2 oC.
2.6.4.2 pH
The pH of the system was investigated by analyzing the leachate collected weekly after pouring
nutrients and deionized water in equal volumes at the top of the biofilter using a pH meter
(3310 Jenway, pH meter).
2.6.4.3 Nutrients
To enhance the performance and lifetime of the filter bed a weekly supply of nutrients was used
based on the C: N: P ratio of 100:5:1. A 200ml of nutrients and 200ml of deionized water were the
volumes poured at the top of the filter bed each week. The chemical compounds served as
nutrients to the biofilter were: KH2PO4 (8 g), K2HPO4 (8 g), KNO3 (53.6 g), Vitamin (A, B1, B2, B3, B5,
B8, B9, and D3) (10 mL) and MgSO4 (0.5 g).
2.6.4.3 Pressure drop
The pressure drop measurement of the biofilter bed was made by using a homemade
instrument. It was measured from inlet to outlet port connected to the filter bed. The dimension
of the filter bed influences the pressure drop in the filter bed (Delhoménie & Heitz, 2005;
Álvarez-hornos et al., 2011).
Figure 21: Pressure drop in the filter bed.
The maximum pressure drop difference from inlet to outlet was 137 Pa for the mixed packing
materials. According to literature, to pressure difference obtained using only the compost was
10 mm H2O.m-1 (98 Pa) (Chou and Li, 2009).
35
2.6.5. Analytical instrumentation
2.6.5.1 Analysis with SIFT-MS
SIFT-MS was used entirely to investigate the performance of the biofilter. It is a real time
quantification technique used to analyze trace VOCs in air and breath related disease (Spesyvyi
2012). It can be used in medicine to diagnose breath diseases, security for the detection of
explosive and toxic substances and in environmental monitoring and food control (Smith et al.,
2005; Španěl et al., 2012).
SIFT-MS use chemical ionization of product ions obtained from the reaction of the sample VOCs
and the injected precursor ions. The formed products ions flow in the mass spectroscopy where
ions are separated by their mass to charge ratios (m/z) and measure count rate in the wanted
m/z (Španěl & Smith, 2001). The unknown concentration of sample can be calculated by using a
library of the rate of coefficient of ion molecular reactions (Spesyvyi 2012). The most frequent
precursors used are H3O+, NO+ and O2+. Table 7 represents the precursor ions used in the method
to measure concentrations in the SIFT-MS.
Table 7: The precursor and products ion used to measure concentrations in SIFT-MS.
Compound Precursor
ions
Mass (m/z) Products
ions
Branching
ratio
Hexane NO+ 85 C6H13+ 100 %
Acetone O2+ 58 C3H6O+ 60 %
DMS O2+ 46 CH2S+ 15 %
2.6.5.2 Analysis with Ion chromatography
Ion chromatography (IC) was used to analyze the major anions in the leachate collected each
week after adding nutrient to the biofilter. Ion chromatography is a form of liquid
chromatography used to measure the concentrations of the ionic species by separating them
based on their interactions with the resin (ion chromatography, 2016). Samples solutions pass
through a pressured chromatographic column where ions are absorbed by column constituents
(ion chromatography, 2016). The eluent runs through the column and the absorbed ions begin
separating from the column and the resulted retention time of different species determines the
ionic concentrations in the samples via conduction (ion chromatography, 2016). IC was
equipped with the cationic resin which made possible to measure the anions content in the
leachate. It is connected to software (chromeleon 7.0) that detects and monitor the amount of
anions found in samples. The anions measured were chloride (CL-), phosphate (PO43-), sulfate
(SO42-) and nitrate (NO3-). For cations ions like Mg2+ and K+ it was not possible to measure them
since the resin was positive.
36
CHAPTER 3 RESULTS AND DISCUSSION
PART I: INDUSTRIAL VOC ANALYSIS IN RWANDA
Volatile organic compounds were monitored in three different manufacturing industries at the
capital city, Kigali, Rwanda. Samples without replications (n=1) in three manufacturing industries
were collected on July, 16th and 31st July, 2015. After sampling, the analysis of VOC
concentrations was performed by TD-GC-MS (see chapter 2 part I). From the 78 target VOCs, 45
were identified from nearly all samples collected indoor and outdoor of the four different
sampling sites.
3.1 Results
The target 45 VOCs concentrations (μg.m-3), indoor and outdoor, of the four sampling sites are
illustrated in table 8 and 9. Out of 78 target VOC compounds, 33 were not detected in the
sampling campaign. They are 1-pentene, 1-hexene, 1-bromo-4-fluorobenzene,
isobutylaldehyde, 3-methylbutylaldehyde, 1-octanol, 3-methyl-1-butanol, 2-octanone,
5-nonanone, 5-methyl-3-heptanone, n-propylacetate, methylbenzoate, furan, 2-methylfuran,
tetrahydrofuran, chloroform, carbon tetrachloride, 1,3-dichlorobenzene,1,2,4-trimethylbenzene,
1,3,5-triisopropylbenzene, 1,2,-chloropropane, 1,1,2-trichlorotrifluoroethane, trichloroethylene,
tetrachloroethylene, 1,24-trichlorobenzene, 1,1,1,2-tetrachloroethane, dimethylsulfide,
dimethyl disulfide, carbon disulfide, acetonitrile, hexamethyl disiloxane and trimethoxymethyl
silane.
37
Table 8: Indoor VOC concentrations (μg.m-3) measured at four sampling sites, Kigali, Rwanda
(2015) (ND = Not detected, ∑VOC = Total volatile organic compounds).
Industry name Sulfo AMEKI color Inyange
Product manufactured Soap Cosmetics Paints Beverage
Sampling date 16/07 16/07 16/07 31/07
Sampling time 11:00-12:20 12:30-13:50 14:30-16:00 16:00-17:45
Average temperature(0C) 29 30 29 26
Average relative humidity (%) 33 35 36 38
Alkane
Pentane 297 ND 1214 ND
2-methylpentane 547 ND ND ND
Hexane 27 0.06 46 0.3
Heptane 135 1 1934 3
Octane 51 1 2764 3
Nonane 21 2 3129 3
Decane 8 2 2357 4
Undecane 4 1 1216 3
Dodecane 2 2 718 2
Total 1093 9 13376 17
Cycloalkane
cyclohexane 54 ND 692 ND
Methylcyclopentane 146 ND 423 ND
Total 200 1114
Alcohol
Isopropanol 4 ND 222 9
2-methyl -1-propanol ND ND 79 ND
1-butanol ND ND 578 ND
1-pentanol 10 ND ND ND
2-Ethyl-1-hexanol ND ND 1766 25
Total 14 0 2645 34
Aromatic compounds
Benzene 177 2 303 11
Toluene 540 21 3448 18
Ethylbenzene 132 1 1379 3
o-xylene 201 ND 1968 4
m-xylene 440 2 4480 8
p-xylene 210 1 1999 92
Styrene 5 0 44 1
Phenol 2 1 26 3
38
Industry name Sulfo AMEKI color Inyange
Product manufactured Soap Cosmetics Paints Beverages
Sampling date 16/07 16/07 16/07 31/07
Sampling time 11:00-12:20 12:30-13:50 14:30-16:00 16:00-17:45
Average temperature(0C) 29 30 29 26
Average relative humidity (%) 33 35 36 38
Propylbenzene 40 0.2 278 0.5
1,2,4 Trimethylbenzene 233 1 1170 4
Total 1980 29 15095 145
Aldehydes
Butylaldehyde ND 33 12 ND
Hexanal 6 ND 15 1
Heptaldehyde 1 ND ND 1
Benzaldehyde 10 3 27 13
Total 17 36 53 15
Ketones
2-Butanone 7 51 370 222
2-Hexanone 37 ND 859 ND
2-heptanone 3 0.02 254 0.41
Acetophenone 21 1 230 6
Total 68 52 1713 228
Esters
Methyl acetate ND ND 486 ND
Ethylacetate 1 1 3838 4
Total 1 1 4325 4
Halogenated compounds
Dichloromethane ND 1 11 ND
1,2 dichloroethane ND ND 2 ND
1,1,2Trichloroethane ND ND 7 ND
1,2 dichloropentane ND ND 1 ND
Chlorobenzene 1 ND 93 ND
Total 1 1 114 0
Nitrogen containing compounds
Benzonitrile 4 1 16 1
Total 4 1 16 1
Terpenes
α-Pinene 1 0.17 ND 0.47
Limonene 2 4 ND 1
Linalool 2 1 750 1
Total 5 5 750 3
∑VOCs 3383 132 39203 446
39
Table 9: Outdoor VOC concentrations (μg.m-3) measured at four sampling sites, Kigali, Rwanda
(2015) (ND=Not detected, TVOC= Total volatile organic compounds).
Industry name Sulfo AMEKI color Inyange
Product manufactured Soap Cosmetics Paints Beverage
Sampling date 16/07 16/07 16/07 31/07
Sampling time 11:00-12:20 12:30-13:50 14:30-16:00 16:00-17:45
Average temperature(0C) 26 27 29 26
Average relative humidity (%) 42 41 39 40
Alkane
Pentane 2436 ND ND ND
2-methylpentane 214 ND ND ND
Hexane 8 ND 0.0 ND
Heptane 64 1.0 0.4 0.1
Octane 57 0.6 0.3 0.3
Nonane 5 0.9 0.3 1
Decane 4 0.8 0.3 1
Undecane 6 0.7 0.3 1
Dodecane 4 0.3 ND 0.2
Total 2797 4.3 2 4
Cycloalkane
cyclohexane ND ND ND ND
Methylcyclopentane 50 ND ND ND
Total 50 0 0 0
Alcohol
Isopropanol 6 ND 8 ND
2-methyl -1-propanol ND ND ND ND
1-butanol ND ND ND ND
1-pentanol 26 ND ND ND
2-Ethyl-1-hexanol ND ND ND ND
Total 32 0.0 8 0.0
Aromatic compounds
Benzene 48 3.2 0.1 1.3
Toluene 113 16 0.5 1.2
Ethylbenzene 20 1.0 0.1 0.1
O-xylene 24 4 0.2 0.3
m-xylene 58 3 0.2 1
p-xylene 25 3 0.1 0.2
Styrene 1 0.3 ND 0.1
Phenol 1 2 1 1
40
Industry name Sulfo
AMEKI
color Inyange
Product manufactured Soap Cosmetics Paints Beverage
Sampling date 16/07 16/07 16/07 31/07
Sampling time 11:00-12:20 12:30-13:50 14:30-16:00 16:00-17:45
Average temperature(0C) 26 27 29 26
Average relative humidity (%) 42 41 39 40
Propylbenzene 5 3 0.02 0.03
1,2,4 Trimethylbenzene 28 1.3 0.11 0.3
Total 324 37 2 5
Aldehydes
Butyraldehyde 30 ND ND ND
Hexanal 5 1.4 0.4 1
Heptaldehyde 1 ND ND 0.03
Benzaldehyde 5 7 3 3
Total 41 8 3 4
Ketones
2-Butanone 43 ND ND ND
2-Hexanone 5 ND ND ND
2-heptanone 29 ND 0.11 0.1
Acetophenone 5 3 1 3
Total 82 3 1 3
Esters
Methyl acetate 139 ND ND ND
Ethylacetate 2 3 2 3
Total 141 3 2 3
Halogenated compounds
Dichloromethane ND ND ND ND
1,2 dichloroethane ND ND ND ND
1,1,2 trichloroethane ND ND ND ND
1,2 dichloropentane ND ND ND ND
Chlorobenzene ND ND ND ND
Total 0 0 0 0
Nitrogen containing compounds
Benzonitrile 0.5 1 0.4 0.3
Total 0.5 1 0.4 0.3
Terpenes
α-Pinene 8 ND ND 0.14
Limonene 29 2 ND ND
Linalool 7 0.4 0.2 0.3
Total 44 2.3 0.2 0.5
∑VOCs 3512 58 18 17
41
3.2 Discussion
3.2.1 General discussion
Today, the sum of all target VOC compounds (∑VOC) value is widely accepted as an important
screening parameter for the overall air quality (Salthammer, 2011). The evaluated target VOCs
concentrations for both indoor and outdoor in four industries were all classified in ten target
chemical groups (alkanes, cycloalkanes, alcohols, aromatics compounds, aldehydes, ketones,
esters, halogenated compounds, nitrogen containing compounds and terpenes). In the indoor,
AMEKI color presented the highest ∑VOC concentrations (39.2 103 µg.m-3), 12 times higher than
Sulfo making soap (3.38 103 µg.m-3) and 298 times for cosmetics (0.132 103 µg.m-3), and 88 times
higher than Inyange which makes beverage (juices and milk) (0.45 103 µg.m-3).
On the other hand, the ∑VOC outdoor concentrations measured around the premises of Sulfo
industry making Soap (3.51 103 µg.m-3) was the highest among the other sampling sites. The
concentrations in Sulfo, cosmetics production unit was (0.58 102 µg.m-3), AMEKI color for paintings
(0.18 102 µg.m-3) and (0.17 102 µg.m-3) for Inyange producing beverages (juices and milk). It can
be seen that there was a big variation of ∑VOC measured concentrations indoor and outdoor
of the four sampling sites. To avoid the skewness of the measured total concentrations for both
indoor and outdoor concentrations, a logarithmic scale was used to present the total VOC
concentrations of indoor and outdoor concentrations of the sampling sites (Figure 22).
Figure 22: The total indoor and outdoor concentrations of four sampling sites.
42
The concentrations of the ten targets chemical groups for both indoor and outdoor in the four
sampling locations were presented in stacked column (Figure 23 and Figure 24).
Figure 23: The indoor total VOC concentrations of chemical groups in four sampling sites.
Figure 24: The outdoor total VOC concentrations of chemical groups in the four sampling sites.
All the target compounds in the aromatic group were present and measured for both indoor
and outdoor of the four sampling sites. This has made aromatics to be more abundantly in both
indoor and outdoor sampling sites, followed by alkanes and ketone. In the indoor sites, the most
groups contributing to the higher VOC concentrations than the others were aromatics 59 % for
soap production unit, ketone 39 % for cosmetics, aromatics 39 % for paints production and 51 %
ketones in juice and milk production (beverage)(Figure 25).
1 2
1 2 3
3
1 2 3
1 2 3
43
The previous sampling campaign conducted not in industry but in house and urban places in
Vietnam, Bangladesh and Ethiopia also confirmed that the aromatics compounds were
abundantly occurring as compared to other target VOC (Do et al. 2013).
Figure 25: Indoor target groups’ abundances in four sampled sites.
However, in the outdoor sites the highest contributing chemical VOC groups were alkanes with
79 % outdoor of soap production unit, 63 % of aromatics for cosmetics, 44 % alcohols for paints
making and 28 % again aromatics in the beverage production unit. Halogenated compounds
were not found outdoor in all sampling locations. Cycloalkanes were only present at the soap
production units (Figure 26).
Figure 26: Outdoor target groups’ abundance in four sampled sites.
44
Benzene is mostly viewed as an indicator for the human health effects (Stranger et al., 2007).
According to World Health Organization (WHO), the concentrations of airborne benzene that
are associated with an excess life-time risk of leukemia of 1/10000, 1/100000, 1/1000000 are 17,
1.7 and 0.17 μg.m-3 respectively (WHO Regional Office for Europe, 2010). The monitored indoor
benzene concentrations exceeded the WHO guideline; in Sulfo (for soap production unit was
117 μg.m-3 and 2 μg.m-3 for cosmetics production unit), 303 μg.m-3 for AMEKI color (paints
production) and 11 μg.m-3 for Inyange industry (juice and milk processing). For the outdoor
concentrations levels, in Europe it is restricted to just 5 μg.m-3 on annual average
(Do et al., 2013). This value was exceeded in Sulfo for soap production unit, 48 μg.m-3.
Nevertheless, it should be point out that, the analysis of the results was temporally restricted
based on the monitored concentrations made at selected local industries in Rwanda for a
defined period of time with limited number of measurements while the guideline often sets
concentrations for long time exposure (e.g. the ambient EU limit for benzene is
for 1 year).
3.2.1 Indoor to outdoor concentrations of the sampling sites
The ratio of indoor and outdoor concentrations is very important for VOC sources identification.
The indoor to outdoor concentrations ratio are often found to be higher than one
(Beak et al., 1997; Jia et al., 2008) and can reach up to 100 times (Caselli et al., 2009). The indoor
to outdoor concentrations ratio of the four industrial sites are illustrated in Table 10.
Table 10: Indoor to Outdoor ratio concentrations of the four sampling sites.
Measured concentrations
(µg/m3)
I/O ratio Sampling Location-products Total Indoor (I) Total outdoor (O)
Sulfo-soap 3.38 103 3.51 103 0.96
Sulfo-cosmetics 0.13 103 0.06 103 2
AMEKI-paints 39.2 103 0.02 103 2161
Inyange-beverages 0.45 103 0.02 103 26
The observation from Table 10 indicates that the I/O ratio of Sulfo, soap production unit, is less
than one which implies that there is a strong outdoor VOC sources compared to the indoor
sources. This is true because of the location of this production unit. It is located in a busy place
downtown of the capital city, with a lot of traffic, close to public transportation parking lot,
market (see chapter two). Usually, vehicles used in Rwanda are old and they do not have
exhaust controlling device (catalyst) which implies that there is high VOC concentrations
45
emitted by cars. Also same industry side of cosmetics production unit, the I/O ratio is 2, shows
main sources to be from the indoor concentrations but there could be slight contributions from
the outdoor concentrations since the unit production is also situated few meters from the road.
The other two industries show strong indoor sources as compared to the outdoor. The total
indoor VOC concentrations could not be only from the VOC emitted from the production
process but also from leaks of the solvent storage tanks.
46
Part II: BIOFILTRATION OF VOC
3.3 Results and discussion
The traditional biological treatments of VOC are cost effective abatement technologies as
compared to physical chemical technologies. Biofiltration is an easy and affordable biological
abatement technology for VOC. This part of study was aimed at evaluating the performance of
biofilter when polluted with VOC where focus was given to acetone, dimethyl sulfide and
hexane. The main parts discussed were: (i) partition coefficient of pollutant to the packing
materials (ii) general biodegradation reaction of acetone, DMS and hexane, (iii) concentration
profile and removal efficiency, (iv) elimination capacity in function of Inlet load of each
pollutant, (v) the produced carbon dioxide in function of elimination capacity of the mixed
compound, (vi) sulfate collected in function of inlet concentration of DMS,(vii) effect of pH on
removal efficiency, (viii) effect of silicon foam on the removal of hexane and (ix) Check the
inhibitory effects.
3.3.1 Partition coefficient of the pollutants to the packing materials
The transfer of the pollutants from air phase to liquid and or solid phase is important for the
success of the vapor phase biotechnologies. Partitioning coefficient is the ratio of a
contaminant concentration in the solids/water phase to contaminant concentration in the air
phase of the biofilter at equilibrium (Hodge & Devinny, 2010). Determining the constants under
realistic conditions is difficult since the transfer and biodegradation happen simultaneously in
active biofilters (Hodge &Devinny, 2010). With a new method developed by Walgraeve et al
(2015) to calculate the partitioning coefficient using SIFT-MS, it was possible to investigate the
phase transfer of the pollutants, acetone, DMS and hexane in gas phase to solid phase of the
packing materials. The breakthrough curve of the compounds depends on the mass of the
packing material, humidity, temperature and the flow rate (Walgraeve et al., 2015). The resulted
breakthrough curves were concentrations of target VOC (acetone, DMS and hexane) from
bubble column packed one at time with compost, silicon and woodchips monitored by SIFT-MS.
The experiment was carried out for dry packing materials (compost, silicon and woodchips) and
ambient condition of the packing material (used compost only). For dry packing materials, the
flow, relative humidity (RH) and temperature of the mixed VOC leaving packed bubble column
was 390 mL.min-1 for the silicon foam (RH = 25.8 % at 20.8 oc), 390 mL.min-1 (RH = 7.55 % at 20.7 oc)
for the compost and 400 mL.min-1 (RH = 5.73 % at 20.9 oc) for the woodchips experiment (see
example of the breakthrough curves in the appendix II section).
47
The relative humidity and temperature were measured by humidity meter (Humidity meter
testo® 625, USA). The experiment was also conducted on the compost at ambient condition
(taken from the bag as it is); the flow of stream leaving the bubble column packed with
compost was 395 ml.min-1 (RH = 98.8 % and 21 oc). It should be noted that, the blank experiment
(empty bubble column) was carried out for the correction of the determined partitioning
coefficient. The blank bubble column was at 29 % of relative humidity and 20.9 oc (see an
example in the appendix II section). Table 11 represents the calculated partitioning coefficient
of acetone, DMS and hexane to dry parking materials.
Table 11: Calculated partitioning coefficients of the dry packing material
(mg [VOC].m-3[packing]).(mg[VOC].m-3)[air])-1.
Partition coefficient (KPM/air)
(mg [VOC].m-3[packing]).(mg[VOC].m-3)[air])-1,(RSD)
Bulk density = 0. 13 g/mL Bulk density = 0.33 g/mL Bulk density = 0.28 g/mL
Silicon foam n Woodchips n Compost n
Acetone 3.77 102 (12 %) 3 2.69 101 (8 % ) 2 0.89 103* 1
DMS 1.23 102 (24 %) 3 0.24 101 1 0.12 103 (22 %) 2
Hexane 2.12 102 (14%) 3 0.16 101 1 0.59 103 1
(*) This is an indicative partitioning coefficient value because the concentration did not reach the
equilibrium.
The results in table 11 based on the bulk density indicate acetone to have a high partitioning
coefficient in all dry packing materials than DMS and hexane. That said, acetone is highly
adsorbed to the packing materials than DMS and hexane. If partitioning coefficient was applied
to the packing materials with their real density silicon form would expect to have higher
partitioning coefficient than other packing materials. Figure 27 represents partitioning coefficient
of acetone, DMS and hexane to the dry compost, woodchips and silicon foam.
Figure 27: Partitioning coefficient of acetone, DMS and Hexane
(mg [VOC].m-3[packing]). (mg [VOC].m-3)[Air])-1.
48
For compost at ambient conditions, the calculated partitioning coefficient (KPM/air) of acetone
was (1.48 102mg.m-3/mg.m-3), DMS (0.05 102mg.m-3/mg.m-3) and hexane (0.02 102mg.m-3/mg.m-3)
which found to be lower than the partitioning coefficient calculated for dry packing materials
(Table 11). At 600 minutes no equilibrium of acetone were reached for dry compost while 90 % of
breakthrough curve was reached to the compost at ambient conditions, this can be explained
by the water vapor molecules which were bound to the packing material that has reduced the
surface of the compost which resulted in faster breakthrough curve. For DMS, the time needed
to obtain equilibrium was 80 minutes for compost at ambient condition and 100 minutes for the
dry one. The equilibrium for hexane was obtained after 10 for compost at ambient conditions
and 40 minutes for dry compost.
According to Hodge and Devinny (2010) in a mathematical model they developed to calculate
the partitioning coefficient of the packing materials, they have indicated that when the
partitioning coefficient is low, the contaminant is more less not adsorbed by the water or
packing material, moves at the same speed as the air and on the contrary when it’s partitioning
coefficient is high the contaminant is retained for a long time and the breakthrough is delayed
(Hodge &Devinny, 2010). The delay for the equilibrium for the dry packing materials were also
observed in the online method used to calculate the partitioning coefficient of the packing
materials using SIFT-MS.
3.3.2 Biological oxidation of pollutants.
A stream of contaminated pollutants was fed into the filter bed upward packed with compost,
woodchips and silicon foam. At this point in the filter bed, there is phase transfer where by
pollutant in gas phase is changed into liquid and or solid phase. Therefore, the pollutant in l iquid
and or solid phase is ready to be used by microorganism. Microorganism populations use
pollutant(s) as carbon and energy source for their maintenance and growth (Kumar et al., 2011).
At favorable conditions (temperature, humidity, pH, etc.) they break down pollutants into less
harmful compounds, carbon dioxide, water, new biomass and other by products e.g. SO42-.
Acetone and hexane were transformed in carbon dioxide and water (Equation 20 and 32). DMS
was transformed into carbon dioxide, sulfuric acid and water (Equation 31).
CH3COCH3 + 4O2 3 CO2+ 3 H2O (Eq. 30)
CH3SCH3+ 5O2 H2SO4 + 2CO2+ 2H2O (Eq. 31)
CH3CH2CH2CH2CH2CH3 + 9.5 O2 6CO2+ 7H2O (Eq. 32)
49
3.3.3 Bioreactor bed
The setup has been in operation for six months. The filter bed had a volume of 7.85 L, gas flow
rate of 8.21 L.min-1 and operated by this means at an EBRT of 57 s. The average temperature of
the bioreactor was 18 ± 2 oc. The biofilter started up without inoculation and the evolution of the
microbial activity degrading acetone, DMS and hexane at all position of the filter bed for the first
three weeks (taking 1 day at end of each week) is indicated in Figure 28. At day 8, acetone at
the outlet port was already degraded at 99.9 %. DMS was removed at 20, 50 and 91 % for day 8,
15 and 22 respectively. Hexane was degraded at 18 % (day 8), 47 % (day 15), and 45 % (day 22).
Figure 28: The normalized start up concentrations of acetone, DMS and hexane at EBRT of 57 s.
The overall performance parameters of the biofilter (average concentrations and standard
deviation) are summarized in Table 12. The removal efficiency was calculated based on the
ratio of the total elimination capacity over total inlet load concentrations of the three
compounds.
Table 12: Performance parameters of the biofilter.
Phase Days pH IL (mg C.m-3.min-1) EC(mg C.m-3.min-1) RE (%)
I 0 - 23 6.08 ± 0.03 49 ± 16 20 ± 14 20 ± 12
Starvation period
II 40 - 50 5.68 ± 0.19 25 ± 3 12 ± 2 49 ± 9
III 51 - 76 4.57 ± 0.08 16 ± 2 7 ± 2 41 ± 10
IV 77 - 108 5.52 ± 0.53 16 ± 4 8 ± 4 73 ± 12
V 109 - 138 7.09 ± 0.09 22 ± 5 17 ± 4 74 ± 5
VI 139 - 151 7.20 ± 0.03 24 ± 3 17 ± 2 71± 2
VII 152 - 170 6.87 ± 0.04 15 ± 6 11 ± 4 73 ± 7
Hexane measurement only
VIII 171-181 6.20 ± 0.14 6 ± 1 4 ± 3 64 ± 3
50
The results from the Table 12 indicates that the highest removal efficiency of the target VOC
mixture was at 74 % for IL of 22.36 ± 4.80 mg C.m-3.min-1 and EC of 16.63 ± 4.07 mg C.m-3.min-1 at
an empty bed residence time of 57 s. The evolution of total inlet flow concentrations and total
removal efficiency of the mixed three pollutants (acetone, DMS and hexane) in biofilter for the
entire time in operation is plotted in Figure 29. Different phases were presented; phase I, shows
the startup of the biofilter which was fed with nutrients and the inlet concentrations were
increasing. Phase II, nutrients concentrations were fed into the system again after starvation
period. Phase III, indicated a period of low pH even though biofilter kept fed by nutrients. Phase
IV showed the pH recovery by using 0.1 M potassium phosphate buffer solution (KH2PO4 and
KHPO4 at pH 7.5). From phase V to VII, pH was maintained at optimum by feeding, buffer solution
and deionized water and recycled of leachate in absence of buffer solution using only nutrients
solution at pH 6.78. Phase VIII indicated the period of hexane measurement only.
Figure 29: The Total inlet concentrations ( ) and total removal efficiency ( ) of the
three pollutants at EBRT of 57 s.
Inlet load concentration and maximum elimination capacity are two crucial parameters
characterizing the success of biofilters (Gracy et al., 2006). The individual elimination capacity in
function of the inlet concentration of acetone, DMS and hexane capacity of each pollutant is
given in Figure 30. The black dots explain stable inlet concentrations in the biofilter, the red ones
(B) show an increase of inlet concentrations, which takes sometimes for microorganism to adapt
to such concentrations. The blue dots (A) indicate the highest maximum EC reached for each
compound. The maximum EC of acetone was 20.93 mg.m-3.min-1 at IL of 20.93 mg.m-3.min-1
51
(99.9 % removal), DMS was 25.82 mg.m-3.min-1 at IL of 34.85 mg.m-3.min-1 (74 % removal) and
31.68 mg.m-3.min-1 at inlet concentration of 67.33 mg.m-3.min-1 (47 % removal efficiency) for
hexane.
Figure 30: EC in function of IL of acetone, DMS and hexane at an EBRT of 57 s.
3.3.4 The Carbon dioxide (CO2) and Elimination capacity (EC)
Vaisala was an instrument behind the measurement of CO2 produced in the biofilter. The CO2
monitored at all ports in function of the days followed the degradation profile of acetone, DMS
and hexane measured by SIFT-MS. Figure 31, represent CO2 produced (PCO2)at the outlet port of
the biofilter in function of total elimination capacity of the three compounds for the stable inlet
concentrations in the biofilter. The PCO2 plotted data ranged from 5.75 to13.54 mg C.m-3.min-1.
52
Figure 31: Produced CO2 in function of total EC at an EBRT of 57 s.
Figure 31 depicts the proportion ratio between total EC and CO2 produced (PCO2) indicating
that 0.873 mg PCO2.m-3.min-1 was formed for each 1 mg of the target VOCs.m-3.min-1 reduced.
To simplify, it means that 87 % of the total EC in mixture is transformed into CO2 and the
remaining 13 % is possibly shared either to biomass or rinsed away into leachate.
3.3.5 The effect of pH on the removal of target VOC
Biofiltration of target VOCs which produce acids overtime lowers pH that result in decline of
microorganism populations and activity (Shekher et al., 2014). DMS is a sulfur containing
contaminants that is oxidized to sulfuric acid (see section 3.3.2) which was mainly responsible for
acidifying the BF packing materials. The supply of 0.1 M potassium phosphate buffer solution at
25 oc (mixture of KH2PO4 and KHPO4 at pH=7.5) proved to overcome the acidity in the filter bed.
Pollutants removal efficiency in function of pH for the entire setup in operation is given in
Figure 32. The removal efficiency of acetone remained to be 99.9 % for pH = 6.9 and pH = 4.51.
DMS dropped from 99.6 to 39 % at pH = 6.9 to pH = 4.51 and hexane dropped from 57 % to
21 % at pH = 6.9 to pH = 4.51 respectively. The pH was maintained at optimum value and the
removal efficiency kept decreasing which can be possibly explained by the die off
microorganism. The arrows in the figure indicate the increase of the removal efficiency after
adding nutrients to the BF. That effect was seen to the DMS and hexane degradation not to
acetone.
53
Figure 32: RE in function of pH of acetone, DMS and hexane at an EBRT of 57 s. Arrows indicate
increase of RE after supply of nutrients to the biofilter kept at the optimum pH.
3.3.6 Sulfate measurement
Sulfate ions in the leachate resulted from the oxidation of DMS and magnesium sulfate (Mg SO4)
the nutrient ingredients. They were measured in leachate using ion chromatography. Because of
the influence of the DMS inlet concentrations and additional of nutrients in the BF, it is difficult to
account which one participated in increase or decrease of sulfate anions into leachate. There
are two metabolism pathways of DMS, one is sulfuric acid collected in leachate and another
sulfur is assimilated by microorganism for the cell material (Shekher et al., 2014).
A sulfur balance was conducted to the incoming sulfur concentrations going to the biofilter
(from DMS and Mg SO4) and SO4 leaving the biofilter through leachate. The concentrations of
sulfate in leachate used to be collected once a week and the in between days’ concentrations
54
were assumed to be constant for days where measurements were not taken for calculation.
It was found out that for a period of 110 days, the total amount of sulfur (from DMS and Mg SO4)
given to the biofilter was 6 g and 11 g of sulfur (from sulfate) were collected in the leachate.
These are indicative values because of the expectation that change of inlet concentrations
might balance with the amount of sulfur in the leachate.
3.3.7 Effect of Silicon on the removal of hexane
The biofiltration of the hydrophobic pollutants is often limited by the gas transfer to liquid and or
solid phase (see section 1.5.3). Silicon foams are used in aerospace, aviation, electronics and
chemicals (IKSonic, 2016). Because of possible sorption capacity of VOC, it was mixed with
compost and woodchips in biofilter to see how target VOC will be degraded especially hexane.
The observed maximum removal efficiency of hexane resulted in biofilter packed with compost,
woodchips and silicon foam was 57 % at IL of 8.46 mg.m-3.min-1 and EC of 4.05 mg.m-3.min-1 to an
EBRT of 57 s. The research made on the degradation of hexane using two types of packing
material, peat (50 % w/w) and perlite (50% w/w) showed a removal concentration of 40 % at a
flow 20 g.m-3.h-1(333 mg.m-3.min-1) (Kibazohi et al., 2004). For biofilter which started up without
inoculation, evidence is needed to prove that the silicon foam has an effect on the removal
efficiency of hexane.
3.3.8 Inhibitory effect for hexane degradation
Among the three compounds used to investigate the performance of the biofilter acetone was
an easiest compounds accessible source for microorganism(s) which could cause the inhibition
of the biodegradation of the hexane. In study conducted by Bruneel (2013) showed that the
presence of acetone proved to inhibit the removal of hexane while removal DMS followed the
same trend with hexane (Bruneel, 2013).
In this study, the last phase of the biofilter in operation (phase VIII) was used to investigate the
removal efficiency of hexane by removing streams of acetone and DMS into the system. For 10
days run of hexane only in the BF indicated a higher removal efficiency than it was in the mixture
(Figure 35). On average for hexane only in BF, the EC was 4.15 ± 2.96 mg.m-3.min-1 at IL of
6.45 ± 0.54 mg.m-3.min-1 which corresponds to 64 ± 3 % RE on average. The total RE of hexane in a
mixture on average for the entire period of biofilter was 33 ± 10 % at IL of 18 ± 15 mg.m-3.min-1
and EC of 6 ± 6 mg.m-3.min-1.
55
Figure 33: The EC in function of IL for hexane in mixture and hexane only at EBRT of 57 s.
0
10
20
30
40
50
0 10 20 30 40 50
EC H
exan
e (m
g.m
-3. m
in-1
)
IL Hexane (mg.m-3.min-1)
Hexane in mixture Hexane only
56
CHAPTER 4 CONCLUSION AND RECOMMENDATION
4.1 CONCLUSION
Rwanda is an interesting African country reporting a remarkable economic transformation for
the last decade. Industrial activity is one of the mostly income generating for the country. Local
manufacturing industries are increasing day to day where a lot of emissions are encountered
and technologies to handle such emissions especially the volatile organic compounds in the
country are yet to be established.
In the first part of this work, VOC were monitored at three local manufacturing industries in
Rwanda through one time sampling campaign indoor and outdoor without replication on 16th
July, 2015 to Sulfo Rwanda industry producing soap and cosmetic and AMEKI color which makes
paints and on 30th July, 2015 at Inyange producing beverages (juices and milk processing).
Samples were taken by means of active sampling using Tenax TA sorbent tubes. After sampling,
they were transported to the environment organic chemistry and technology (EnVOC) lab for
analysis. The analysis was made by TD-GC-MS. In the second part of the work, technology part,
biofiltration was used to evaluate the removal efficiency of VOC where focus was given to
acetone, dimethyl sulfide (DMS) and hexane as representative VOC. These compounds where
chosen because of the wide range of physical chemical properties.
This research has brought forward new data on 45 VOCs concentrations levels to both indoor
and outdoor environment of the three local manufacturing industries. By making use of ∑VOCs
and chemical groups, a direct comparison for the VOCs concentrations monitored in three local
manufacturing industries was made. In sulfo, soap production unit, the ∑VOCs indoor and
outdoor were 3.38 103 and 3.51 103 μg.m-3 respectively. Still at sulfo, cosmetic production unit, the
∑VOCs was 0.13 103 μg.m-3 for indoor and 0.06 103 μg.m-3 for outdoor. For paints making industry,
the indoor and outdoor was 39.2 103 and 0.02 103 μg.m-3 respectively. At Inyange, the ∑VOCs
encountered indoor and outdoor were 0.45 103 and 0.02 103 μg.m-3 respectively. Aromatics
compounds where found to be the most contributing chemical group to the ∑VOCs monitored
in all industries followed by the alkanes and ketones groups.
As expected the indoor concentrations levels were higher than the outdoor concentrations
which simply means that most VOC contributing to indoor sources are within the production
area. The only exception was to Sulfo, soap production unit, where indoor concentrations were
less than outdoor concentrations and at this condition it is hard to identify the source of VOC
since the contribution is from both indoor and outdoor concentrations. Soap production unit is
located downtown where a lot of activities are happening and this could define the raison why
57
the outdoor source is high as compared to the indoor. The benzene level was higher than the
guidelines of the WHO indoor concentrations for Sulfo (117 μg.m-3 for soap production unit and
2 μg.m-3 for cosmetics production unit), 303 μg.m-3 for AMEKI color (paints production) and 11
μg.m-3 for Inyange industry (juice and milk production). The outdoor at Sulfo part of soap
production unit, the concentrations (48 μg.m-3) was found to be higher than the EU directive on
the outdoor benzene limit (5 µg.m-3).
The second part of this research, the technology part, biofilter equally packed (1/3 w/w) with
compost, woodchips and silicon foam was used to investigate the removal efficiency of the
representative target VOC, acetone, DMS and hexane. SIFT-MS (for IL and EC) and Vaisala
(CO2) were two major instruments used to record concentrations of the microorganism
degradation behavior.
The performance assessment of the biofilter was done by comparing inlet concentrations,
elimination capacity and removal efficiency of the target compounds mixed altogether. The
maximum removal efficiency of the mixed compounds was 74 ± 5 % at IL of
22.4 ± 4.80 mg C.m-3.min-1 and EC of 17 ± 4 mg C.m-3.min-1 at EBRT of 57 s. Based on the
partitioning coefficient experiment, acetone was found to be highly adsorbed to all packing
materials followed by DMS and hexane. Based on the removal of individual compound, the
maximum EC of acetone was 20.93 mg.m-3.min-1 at IL of 20.93 mg.m-3.min-1
(99.9 % removal), DMS the maximum EC was 25.82 mg.m-3.min-1 at IL of 34.85 mg.m-3.min-1 (74 %
removal) and for hexane the maximum EC was 31.68 mg.m-3.min-1 at inlet concentration of
67.33 mg.m-3.min-1 (47 % removal efficiency).
The experiment of hexane as contaminants only in the biofilter showed to be higher than when
mixed with acetone and DMS. The high removal of hexane was also contributed by the silicon
foam used in the mixture of packing material. To conclude, based on this performance,
biofiltration can be seen as an urgent technology for the treatment of the target VOC in
manufacturing and production industries.
4.2 RECOMMENDATION
The samples taken in three local manufacturing industries gave us an insight on the level of VOC
emissions in three manufacturing industries, a further study can be also conducted to the same
industries by taking more sample replications at different times to see when and how VOC
variate. Another recommendation, for the biofiltration setup, further studies can be conducted
to check the responsible microorganism(s) for the degradation of acetone, DMS and hexane.
58
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APPENDIX I
78 standard VOCs used for calibration of the TD-GC-MS are shown together with their
characterizing ions, the load mass, the retention time, relative peak area and RSRF toluene d8.
Compound Ion Mass Retention time RSRF RPA
(ng) (min)
Alkanes
hexane 41,71,86 32.95 5.88 1.27 0.87
heptane 70,71,100 34.20 12.64 0.26 0.19
octane 71,85,114 35.15 22.33 0.26 0.19
nonane 57,85,128 35.90 28.28 0.43 0.33
decane 75,85,142 36.50 31.71 0.12 0.10
undecane 57,85,156 37.00 34.36 0.51 0.40
dodecane 57,85,170 37.65 36.61 0.53 0.42
2-methyl pentane 43,57,71 32.65 4.74 0.14 0.10
cycloalkanes
methylcyclopentane 55,56,69,84 37.45 7.23 0.04 0.03
cyclohexanes 41,55,56,69,84 38.95 9.32 0.08 0.07
Alkenes
1-pentene 55,70 32.00
1-hexene 84,15 39.90 5.43 0.02 0.02
Aromatic hydrocarbons
Benzene 52,63,77,78 43.70 8.73 0.59 0.54
Toluene 65,91,92 43.30 17.89 0.99 0.91
Ethylbenzene 91,106 43.35 25.91 0.90 0.84
p-xylene 91,105,106 43.30 26.44 0.99 0.92
m-xylene 91,105,106 43.40 26.39 0.93 0.85
o-xylene 91,105,106 43.90 27.52 0.99 0.92
styrene 51,78,104 45.45 27.32 0.92 0.86
propylbenzene 9,192,120 43.10 30.02 1.07 0.98
1,2,4-trimethylbenzene 105,120 44.00 31.37 1.09 1.02
Phenol 65,66,94 53.50 30.68 0.45 0.51
1-bromo-4-fluorobenzene 75,95,174,176 79.65 28.59 0.69 1.20
Aldehydes
hexanal 44,56,72,82 40.75 20.26 0.25 0.22
heptanal 44,70,96 41.00 27.48 0.26 0.23
benzaldehyde 77,105,106 52.50 29.7 0.48 0.56
butanal 41,44,45,72 40.85 4.9 0.19 0.16
isobutylaldehyde 41,43,73 39.50 4.01 0.33 0.30
3-methylbutylaldehyde 41,42,43,58,71,86 39.80 7.75 0.23 0.20
Alcohols
70
1-butanol 28,31,33,56 40.50 8.9 0.17 0.14
1-pentanol 29,31,55,57,70 40.55 20.65 0.15 0.13
2-ethyl-1-hexanol 31,56,70,83,112 41.55 32.23 0.23 0.21
1-octanol 68,69,70,83,84,112 41.35 33.31 0.30 0.27
3-methyl-1-butanol 29,31,42,70 40.00 15.00 0.21 0.18
isopropanol 29,31,45,59 39.25 2.93 0.41 0.34
2-methyl-1-propanol 31,33,43,74 40.15 6.77 0.19 0.16
Ketone
2-butanone 71,72,73 40.30 5.04 0.38 0.32
2-hexanone 43,71,85,100 40.60 19.35 0.35 0.30
2-heptanone 58,71,114 41.00 26.99 0.38 0.33
2-octanone 58,113,128 40.95 30.88 0.36 0.31
5-nonanone 85,100,142 41.00 33.31 0.36 0.32
5-methyl-3-heptanone 71,99,128 41.15 29.3 1.01 0.90
acetophenone 51,77,105,120 51.50 33.05 0.59 64
Esters
Ethylacetate 61,70,88 45.10 5.96 0.12 0.11
n-propylacetate 61,73 44.00 12.74 0.17 0.16
methylbenzoate 77,105,136 54.00 33.93 0.85 0.97
methylacetate 29,43,59,74 46.50 3.46 0.28 0.28
other oxyganated compounds
furan 39,68,69 46.80 3.04 0.20 0.20
2-methylfuran 53,81,82 45.50 5.7 0.26 0.25
tetrahydrofuran 41,71,72 44.45 6.69 0.27 0.25
Halogated compounds
Chloroform 47,83,85 74.60 6.11 0.23 0.37
carbon tetrachloride 117,119,121 79.70 9.11 0.13 0.22
dichloromethane 49,84,86 66.25 3.52 2.06 2.90
chlorobenzene 77,112,114 55.38 24.77 0.62 0.73
1,3-dichlorobenzene 75,111,146,148 64.40 31.64 0.82 1.12
1,2,4 trimethylbenzene 105,120 44.00 31.37 1.09 0.99
1,3,5 Triisopropylbenzene 161,189,204 42.70 38.82 1.03 0.94
1,1,2 trichloroethane 61,97,99,132 71.75 17.00 0.34 0.51
1,2-dichloroethane 62,64,98 62.65 7.32 0.11 0.15
1,2- dichloropropane 62,63,76 57.80 10.91 0.25 0.30
1,1,2-trichlorotrifluoroethane 101,103,151,153 78.50 3.70 0.12 0.07
trichloroethylene 95,97,130,132 73.00 11.66 0.53 0.83
tetrachloroethylene 131,164,166,168 81.15 22.37 0.48 0.83
1,2,4-trichlorobenzene 145,180,182,184 72.70 36.25 0.74 1.15
1,1,1,2-tetrachloroethane 95,117,119,161,133 79.90 24.80 0.46 0.78
Sulfur compounds
dimethyldisulfide 945,79,94 53.13 15.2 0.004 0.004
carbondisulfide 44,76 63.00 3.79 0.04 0.06
71
dimethylsulfide 61,62 42.00 3.36 0.02 0.02
Nitrogen containing compounds
acetonitrile 39,40,41 39.30 2.59 0.41 0.35
benzonitrile 76,103 50.50 30.32 0.88 0.95
Silicon containing compounds
hexamethyldisiloxane 73,147,148,149 38.20 11.63 0.97 0.79
trimethoxymethylsilane 91,105,121 48.00 13.97 0.11 0.10
Terpene
α-pinene 92,93,121,136 42.90 29.66 0.69 0.64
limonene 68,93,107,121,136 43.50 34.11 0.75 0.67
linalool 71,93,121,136 43.50 34.11 0.44 0.40
Internal Standard
Toluene-d8 98,100 47.00 17.52 - -
72
APPENDIX II
A. Breakthrough curves for dry silicon foam
Acetone DMS Hexane
B. Breakthrough curves for dry wood chips
Acetone DMS Hexane
0
0.2
0.4
0.6
0.8
1
1.2
0 50
No
rmal
ize
d c
on
cen
trat
ion
s (-
)
time( min)
Acetone
0
0.2
0.4
0.6
0.8
1
1.2
0 50
No
rmal
ise
d c
on
cen
trat
ion
(-)
Time (min)
0
0.2
0.4
0.6
0.8
1
1.2
0 50
No
rmal
ize
d c
on
cen
trat
ion
s (-
)
Time (min)
0
0.2
0.4
0.6
0.8
1
1.2
0 50
no
rmal
ize
d c
on
cen
trat
ion
s (-
)
Time(min)
0
0.2
0.4
0.6
0.8
1
1.2
0 20
no
rmal
ize
d c
on
cen
trat
ion
s (-
)
Time(min)
0
0.2
0.4
0.6
0.8
1
1.2
0 20
no
rmal
ize
d c
on
cen
trat
ion
s (-
)
Time(min)
73
C. Breakthrough curves for dry compost
Acetone* DMS Hexane
* Equilibrium not obtained
D. Breakthrough curve of compost at normal and dry condition.
0
0.2
0.4
0.6
0.8
1
1.2
0 100 200
no
rmal
ize
d c
on
cen
trat
ion
s (-
)
Time (min)
0
0.2
0.4
0.6
0.8
1
1.2
0 200 400No
rmal
ize
d c
on
cen
trat
ion
s (-
) Time (min)
0
0.2
0.4
0.6
0.8
1
1.2
0 200 400
No
rmal
ize
d c
on
cen
trat
ion
s (-
)
Time (min)