Biomass Energy Systems and

Resources in Tropical Tanzania

Lugano Wilson

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Licentiate Thesis in Furnace Technology

Stockholm, Sweden 2010

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Biomass Energy Systems and Resources in Tropical Tanzania

Lugano Wilson

Licentiate Thesis

Stockholm 2010 Royal Institute of Technology

School of Industrial Engineering and Management Department of Material Science and Engineering

Division of Energy and Furnace Technology SE-100 44 Stockholm

Sweden

Akademisk avhandling som med tillstånd av Kungliga Tekniska Högskolan I Stockholm framlägges för offentlig granskning för avläggande av teknologie

licentiatexamen fredagen den 17 September 2010, kl. 10 i sal B1, Brinellvägen 23, Kungliga Tekniska Högskolan, Stockholm.

ISRN KTH/MSE--10/44--SE+ENERGY/AVH

ISBN 978-91-7415-732-1

iii

Lugano Wilson. Biomass Energy Systems and Resources in Tropical Tanzania

Royal Institute of Technology School of Industrial Engineering and Management Department of Material Science and Engineering

Division of Energy and Furnace Technology SE-100 44 Stockholm

Sweden

ISRN KTH/MSE--10/44--SE+ENERGY/AVH

ISBN 978-91-7415-732-1

© The author

iv

ABSTRACT

Tanzania has a characteristic developing economy, which is dependent on

agricultural productivity. About 90% of the total primary energy consumption of

the country is from biomass. Since the biomass is mostly consumed at the

household level in form of wood fuel, it is marginally contributing to the

commercial energy supply. However, the country has abundant energy

resources from hydro, biomass, natural gas, coal, uranium, solar, wind and

geothermal. Due to reasons that include the limited technological capacity, most

of these resources have not received satisfactory harnessing. For instance: out

of the estimated 4.7GW macro hydro potential only 561MW have been

developed; and none of the 650MW geothermal potential is being harnessed.

Furthermore, besides the huge potential of biomass (12 million tons of oil

equivalent), natural gas (45 million cubic metres), coal (1,200 million tones), high

solar insolation (4.5 – 6.5 kWh/m2), 1,424km of coastal strip, and availability of

good wind regime (> 4 m/s wind speed), they are marginally contributing to the

production of commercial energy. Ongoing exploration work also reveals that the

country has an active system of petroleum and uranium. On the other hand, after

commissioning the 229km natural gas pipeline from SongoSongo Island to Dar

es Salaam, there are efforts to ensure a wider application in electricity

generation, households, automotive and industry.

Due to existing environmental concerns, biomass resource is an attractive future

energy for the world, Tanzania inclusive. This calls for putting in place

sustainable energy technologies, like gasification, for their harnessing. The high

temperature gasification (HTAG) of biomass is a candidate technology since it

has shown to produce improved syngas quality in terms of gas heating value that

has less tar.

This work was therefore initiated in order to contribute to efforts on realizing a

commercial application of biomass in Tanzania. Particularly, the work aimed at

establishing characteristic properties of selected biomass feedstock from

Tanzania. The characteristic properties are necessary input to thermochemical

v

process designers and researchers. Furthermore, since the properties are origin-

specific, this will provide baseline data for technology transfer from north to south.

The characteristic properties that were established were chemical composition,

and thermal degradation behaviour. Furthermore, laboratory scale high

temperature gasification of the biomasses was undertaken.

Chemical composition characteristics was established to palm waste, coffee

husks, cashew nut shells (CNS), rice husks and bran, bagasse, sisal waste,

jatropha seeds, and mango stem. Results showed that the oxygen content

ranged from 27.40 to 42.70% where as that of carbon and hydrogen ranged from

35.60 to 56.90% and 4.50 to 7.50% respectively. On the other hand, the

elemental composition of nitrogen, sulphur and chlorine was marginal. These

properties are comparable to findings from other researchers. Based on the

results of thermal degradation characteristics, it was evident that the cashew nut

shells (CNS) was the most reactive amongst the analyzed materials since during

the devolatilization stage the first derivative TG (DTG) peak due to hemicellulose

degradation reached (-5.52%/minute) compared palm stem whose first peak was

-4.81%/minute. DTG first peak for the remaining materials was indistinct.

Results from the laboratory gasification experiments that were done to the coffee

husks showed that gasification at higher temperature (900°C) had an overall

higher gasification rate. For instance, during the inert nitrogen condition, 7% of

coffee husk remained for the case of 900°C whereas the residue mass for the

gasification at 800 and 700°C was 10 and 17% respectively. Steam injection to

the biomass under high temperature gasification evolved the highest volumetric

concentration of carbon monoxide. The CO peak evolution at 900°C steam only

was 23.47 vol. % CO whereas that at 700°C was 21.25 vol. % CO.

Comparatively, the CO peaks for cases without steam at 900°C and 2, 3, and 4%

oxygen concentrations were 4.59, 5.93, and 5.63% respectively. The reaction

mechanism of coffee husks gasification was highly correlated to zero reaction

order exhibiting apparent activation energy and the frequency factor 161 kJ/mol

and 3.89x104/minute respectively.

vi

ACKNOWLEDGEMENT

The Swedish International Development Cooperation Agency (SIDA) through the

Department for Research Cooperation (SAREC) is acknowledged for the financial

support through the Capacity Building Project at the College of Engineering and

Technology (CoET) of the Universality of Dar es Salaam, Tanzania. Additional

financial support came from the Swedish Research Council (Vetenskapsrådet),

which is highly acknowledged.

My Supervisors at KTH, Prof. Weihong Yang and Wlodzimierz Blasiak, including

those at the University of Dar es Salaam, Prof. Geoffrey R. John and Cuthbert F.

Mhilu are acknowledged for their academic support throughout the study period.

Life at KTH and Stockholm in general was interesting through the social

interaction and academic challenges from my colleagues at the Division of

Energy and Furnace Technology: Aliaksandr Alevanau, Amit Kumar Biswas,

Xiaolei Zhang, Owden Robert Mwaikondela, Pawel Donaj, Lan Zhang, Efthymios

Kantarelis, and Qingli Zhang.

The continued moral support from my family and family members is highly

appreciated as it was the main foundation leading to this output. Unfortunately, it

is not possible to mention all those who contributed to this work, in one form or

another, I am taking this opportunity to thank all of you. May the blessing of our

Almighty God be extended to you, THANK YOU!

vii

To my Wife Grace (Mandiga) and our beloved children: Priscilla (Lahabu),

Maureen, and Joylyn

viii

Papers Included in the Thesis Supplement 1: Lugano Wilson, Geoffrey R. John, Cuthbert F. Mhilu,

Weihong Yang, and Wlodzimierz Blasiak, (2010) “Coffee

Husks Gasification Using High Temperature Air/Steam

Agent”, Fuel Processing Technology, Volume 91, Issue

10, pp. 1330 – 1337

Supplement 2: Lugano Wilson, Weihong Yang, Wlodzimierz Blasiak,

Geoffrey R. John, Cuthbert F. Mhilu, (2010), “Thermal

Characterization of Tropical Biomass Feedstocks”, Energy

Conversion and Management, doi:10.1016/

j.enconman.2010.06.058

Papers not Included in the Thesis

1. L. Wilson, G. R. John, C. F. Mhilu, W. Yang, and W.

Blasiak; (2009), “Combustion Characteristics of Cashew

Nut Shells and Coffee Husks by Thermogravimetry and

Calorimetry”, 17th European Biomass Conference &

Exhibition, 29th June – 3rd July, CCH - Congress Center

Hamburg, Germany

2. L. Wilson, G. R. John and C. F. Mhilu; (2008), “Thermal

Characteristics of Sugar Cane Bagasse with Storage”, The

9th Asia-Pacific International Symposium on Combustion

and Energy Utilization, 2nd – 6th November, Beijing, China

3. L. Wilson, W. Yang, W. Blasiak, G. R. John and C. F.

Mhilu; (2007), “Opportunities and Challenges of Biomass

Energy for Heat and Power Production in Tanzania”. 3rd

International Green Energy Conference, 18th – 20th June,

Västerås, Sweden

The author is the main contributor to the supplemented papers whereas co-

authors provided the necessary support in literature, experimental design, and

interpretation.

ix

TABLE OF CONTENTS

ABSTRACT .........................................................................................................IV

ACKNOWLEDGEMENT ......................................................................................VI

LIST OF TABLES ................................................................................................XI

LIST OF FIGURES ..............................................................................................XI

ABBREVIATIONS ..............................................................................................XII

SYMBOLS .........................................................................................................XIII

1 INTRODUCTION ............................................................................................ 1

1.1 ENERGY BALANCE ......................................................................... 1

1.2 POTENTIAL ENERGY RESOURCES .................................................... 3

1.2.1 Hydropower ................................................................................. 3

1.2.2 Natural Gas ................................................................................. 5

1.2.3 Biomass ....................................................................................... 5

1.2.4 Coal ............................................................................................. 9

1.2.5 Solar ............................................................................................ 9

1.2.6 Wind .......................................................................................... 10

1.2.7 Geothermal ................................................................................ 11

1.2.8 Tidal and Wave .......................................................................... 12

1.2.9 Petroleum Oil and Uranium Exploration .................................... 13

1.3 ELECTRICITY GENERATION MIX ..................................................... 15

1.4 BIOMASS COGENERATION ............................................................. 18

1.4.1 Kilombero Sugar Company........................................................ 18

1.4.2 Mtibwa Sugar Estate Limited ..................................................... 18

1.4.3 Tanganyika Planting Company Limited (TPC) ........................... 19

1.4.4 Kagera Sugar Limited (KASC) ................................................... 19

1.4.5 Saohill Sawmill .......................................................................... 19

1.4.6 Tanganyika Wattle Company (TANWAT) .................................. 20

1.5 ELECTRICITY DEMAND .................................................................. 21

1.6 ELECTRICITY DISTRIBUTION AND DISTRIBUTION NETWORK .............. 22

2. LITERATURE REVIEW ................................................................................ 23

x

2.1 BIOMASS GASIFICATION ................................................................ 23

2.2 HIGH TEMPERATURE AIR/STEAM GASIFICATION (HTAG) ................. 24

2.3 EFFECTS OF HEATING RATE AND TEMPERATURE ............................ 25

3. OBJECTIVES ............................................................................................... 26

4. METHODOLOGY ......................................................................................... 27

4.1 CHEMICAL COMPOSITION .............................................................. 27

4.2 THERMAL DEGRADATION CHARACTERISTICS .................................. 27

4.3 LABORATORY EXPERIMENTATION .................................................. 28

5. RESULTS AND DISCUSSION ..................................................................... 30

5.1 CHEMICAL COMPOSITION OF TROPICAL BIOMASSES........................ 30

5.2 THERMAL DEGRADATION OF TROPICAL BIOMASSES ........................ 34

5.2.1 Mass Loss Characteristics ......................................................... 34

5.2.2 Rate of Mass Loss Characteristics ............................................. 35

5.2.3 Burnout Temperature ................................................................. 37

5.3 LABORATORY GASIFICATION OF COFFEE HUSKS ............................ 38

5.3.1 Effects of Gasification Agent on Heating Rate ........................... 38

5.3.2 Gasification Rate ........................................................................ 39

5.3.3 Syngas Evolution ....................................................................... 43

5.3.4 Syngas Heating Value ............................................................... 49

5.3.5 Estimation of Coffee Husks Kinetic Parameters......................... 51

6. CONCLUSION .............................................................................................. 53

7 FUTURE WORK ........................................................................................... 54

REFERENCES .................................................................................................... 55

xi

LIST OF TABLES

Table 1: Petroleum fuels importation detail .......................................................... 2

Table 2: Planned Macro hydropower plants ........................................................ 4

Table 3: Existing small-scale hydropower schemes ............................................ 4

Table 4: Waste generated (Tones) in Tanzania Cities ......................................... 8

Table 5: Wind stations with annual mean wind speeds ≥ 4.5 m/s ..................... 10

Table 6: Oil and gas exploration companies ..................................................... 14

Table 7: Installed generation capacity and source ............................................. 17

Table 8: Potential additional cogeneration capacity ........................................... 21

Table 9: Tropical biomasses chemical composition ............................................ 31

Table 10: Mass loss summary ............................................................................ 35

Table 11: Material’s characteristic properties summary ...................................... 36

Table 12: Residue mass summary for steam injected experiments .................... 41

Table 13: CO evolution characteristics summary ................................................ 48

Table 14: Syngas composition summary ............................................................ 51

LIST OF FIGURES

Figure 1: Geothermal potential sites in Tanzania ............................................... 12

Figure 2: Installed generation capacity and share (%) by source ....................... 16

Figure 3: Electricity generation and consumption, million kWh ......................... 22

Figure 4: Existing and proposed grid and isolated transmission system ........... 23

Figure 5: The high temperature gasification test rig ............................................ 29

Figure 6: Coalification diagram for the tropical biomasses .................................. 33

Figure 7: TG thermogram characteristics based on the coffee husks sample .... 34

Figure 8: Material‟s characteristic properties based on palm stem degradation . 37

Figure 9: Sample temperature profiles ................................................................ 40

Figure 10: Gasification rate under different experimental conditions .................. 42

Figure 11: Syngas (CO/CO2) evolution profiles ................................................... 47

Figure 12: Syngas evolution profiles ................................................................... 50

Figure 13: ln[g(α)/T2] versus 1/T for 900°C N2 condition experiment .................. 53

xii

ABBREVIATIONS

AVGAS Aviation Gasoline

CNG Compressed Natural Gas

CNS Cashew Nut Shells

DSC Differential Scanning Calorimetry

DTG Derivative TG

GC Gas Chromatograph

GDP Gross Domestic Product

GEF Global Environmental Fund

HHV Higher Heating Value (Gross Calorific Value)

HiTAC High Temperature Combustion

HTAG High Temperature Air/Steam Gasification

IEA International Energy Agency

IGCC Integrated Gasification Combined Cycle

IPTL Independent Power Tanzania Limited

KASC Kagera Sugar Limited

LHV Lower Heating Value (Net Calorific Value)

LPG Liquid Petroleum Gas

m.a.s.l Meters Above Sea Level

MEM Ministry of Energy and Minerals

MRP Mkuju River Project

NGOs Non-Government Organizations

OECD Organization for Economic Co-operation and Development

OTEC Ocean Thermal Energy Conversion

PSMP Power System Master Plan

PV Photovoltaic

SIDA Swedish International Development Authority

TANESCO Electric Supply Company Limited

TANWAT Tanganyika Wattle Company

TCH Tones of Cane Per Hour

TG Thermogravimetry

TOE Tons of Oil Equivalent

TPC Tanganyika Planting Company

TPDC Tanzania Petroleum Development Corporation

UNDP United Nations Development Program

xiii

SYMBOLS

Mass loss fraction

A Apparent frequency factor (Avogadro's constant) [/min]

Heating rate [K/min]

E Apparent activation energy [kJ/mole]

k Arrhenius constant

n Reaction order

R Universal gas constant [kJ/kmole K]

R2 Coefficient of Determination

T Absolute temperature [K]

1

1 INTRODUCTION

Tanzania has a characteristic developing economy of the world. The economy is

dependent on agricultural productivity. Information available from the National

Bureau of Statistics [1] shows that the agricultural sector contributes more than

44.70% of the total gross domestic product (GDP). It accounts for almost 56

percent of total merchandise exports and employs nearly 80% of the population.

Major agricultural exports are coffee, cotton, tea, tobacco, cashew nuts, and

sisal. The developing economy is reflected in inadequate infrastructure like roads

and electricity. On the other hand, the agricultural sector (in terms of agricultural

waste and dedicated energy crops), provides a potential energy source when

harnessed sustainably. This requires putting in place sustainable and innovative

biomass energy technologies that will contribute to the economic development.

1.1 ENERGY BALANCE

The Tanzania energy policy document [2] shows that over 90% of Tanzania‟s

primary energy consumption is accounted by biomass whereas petroleum and

electricity accounts for 8% and 1.2%, respectively. Other energy sources

including coal, solar, biogas and wind account for less than 1% of the total

primary energy consumption.

The distribution of the primary energy consumption by sector is such that

households consume 89.8%, agriculture 3.6%, transport 3.1%, industry 1.9%,

commerce 0.2% and other sectors 1.4%. The total final energy consumption

amounts to over 22 million tons of oil equivalent (TOE) or 0.7 TOE per capita.

The Commercial energy consumption pattern shows that the contribution by

individual end users is: transport sector 40.5%, industry 24.6%, household

18.6%, agriculture 8.2%, commerce 2.6% and others 5.5%. Imported petroleum,

whose importation per annum averages 850,000 metric tones, supplies over 90%

of the commercial energy needs. Its importation per annum consumes more than

30% of the foreign exchange earned by the country. Table 1 details the

petroleum fuels importation.

2

Table 1: Petroleum fuels importation detail [Tanzania Petroleum Development Corporation (TPDC) internal reports]

FUEL DESCRIPTION CONSUMPTION PER YEAR, „000 TONS

1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005

LPG (45% Household) 3.15 4.02 1.26 1.57 1.67 1.47 1.64 2.21 1.08 0.99 0.90

LPG (55% Industrial) 3.85 4.92 1.54 1.92 2.05 1.80 2.00 2.70 1.32 1.21 1.10

AVGAS (Civil Aviation) 4.19 3.94 1.58 4.76 4.82 1.46 2.7 2.5 2.2 2 1.8

PETROL (100% Road Transport) 103.61 107.05 108.56 106.74 83.72 120.80 142.98 163.89 150 156 165

DIESEL (2% Off road) 6.49 7.40 7.31 6.72 6.01 7.96 8.34 10.52 9.40 9.80 10.20

DIESEL (Rail Transport) 18.70 21.00 17.55 19.28 20.09 20.51 21.53 21.49 24.43 23.57 21.33

DIESEL (Waterborne Navigation) 0.69 0.80 0.76 0.79 0.83 0.71 0.81 0.93 0.85 0.87 1.18

DIESEL ( Balance -> Road Transport) 298.40 340.94 340.01 309.29 273.40 368.74 386.30 493.18 435.32 455.77 477.29

INDUSTRIAL DIESELa (Industrial) 38.63 33.25 23.89 18.56 37.65 20.99 25.73 14.82 16.5 14 12

FUEL OIL (Industrial) 116.97 114.12 105.67 114.38 109.57 114.28 99.97 100.77 100 97 96

JETFUEL – Civil Aviation 36.34 36.34 38.13 40.00 39.19 40.08 40.09 40.19 41.5 42.1 42.7

JETFUEL – International Bunkers (Aviation)

19.81 18.72 17.39 10.95 15.01 15.07 23.01 27.10 22 23 24

PARAFFIN (100% Domestic) 154.38 202.80 177.62 122.63 76.07 87.21 115.60 122.97 80 70 58

TOTAL 805.21 895.30 841.26 757.59 670.06 801.09 870.69 1,003.27 884.60 896.30 911.50

AVERAGE: 848.81

3

The high dependence on biomass is contributed by the fact that majority of

Tanzanians (75% of the population) live in rural areas that are far from modern

energy service infrastructure. As a result, the biomass energy is consumed at

the household level with a marginal contribution from commercial energy. A

sustainable harnessing of available potential energy resources is therefore

necessary to realize the commercial energy to the economy.

1.2 POTENTIAL ENERGY RESOURCES

Tanzania has abundant natural resources that can be harnessed into commercial

energy. These natural resources include hydro, biomass, natural gas, coal,

uranium, solar, wind and geothermal.

1.2.1 Hydropower

Tanzania‟s hydropower resource comprise of macro (large scale) and micro

(small scale) systems. The macro hydro potential is about 4.7GW out of which

only 561MW have been developed [3]. The micro hydropower potential is

estimated at more than 314MW out of which 1.5% has been developed [4].

The 561MW developed macro hydro-electricity power system comprises six

TANESCO owned and operated hydropower plants at Mtera (80MW), Kidatu

(204MW), Hale (21MW), Pangani Falls (68MW), Nyumba ya Mungu (8MW) and

Kihansi (180MW). As detailed in Table 2, other hydropower sites identified and

studied for further development include Rumakali (222MW), Ruhudji (358MW),

Mandera (21MW), Stigler‟s Gorge (1,200 to 1,400MW), Mpanga (200MW),

Masigira (250), and Upper Kihansi (120MW).

Tanzania has an estimated mini hydro potential of about 315MW, out of which

only 4.74MW is developed. A sustainable harnessing of this resource could

contribute significantly to the overall country‟s energy production and the overall

electrification. Details available in Table 3 show that religious missions have

installed most of the existing small-scale hydropower schemes the majority of

which are located in the southern highlands regions of Tanzania.

4

Table 2: Planned Macro hydropower plants [5, 6]

SITE CAPACITY

(MW) RIVER

LEVEL OF STUDY

Rumakali 222 Rumakali Feasibility

Ruhudji 358 Ruhudji Feasibility

Mandera 20 Pangani Feasibility

Stigler‟s Gorge – Phase I and II 1,200 Rufiji Prefeasibility

Mpanga 145 Mpanga Prefeasibility

Masigira 80 Ruhuhu Prefeasibility

Upper Kihansi 120 Kihansi Prefeasibility

TOTAL 2,145

Table 3: Existing small-scale hydropower schemes (TANESCO records)

LOCATION TURBINE

TYPE/MANUFACTURER INSTALLED CAPACITY

(kW)

TANESCO Owned

Tosamaganga (Iringa) Gilkes & Gordon/Francis 1220

Kikuletwa (Moshi) Boving & Voith Reaction 1160

Mbalizi (Mbeya) Gilkes & Gordon/Francis 340

Missions Owned

Kitai (Songea) Cross Flow/Ossberger 45

Nyagao (Lindi) Cross Flow/Ossberger 15.8

Isoko (Tukuyu) Cross Flow/Ossberger 15.5

Uwemba (Njombe) Cross Flow/Ossberger 800

Bulongwa (Njombe) Cross Flow/Ossberger 180.0

Kaengesa (Sumbawanga)

Cross Flow/Ossberger 44.0

Rungwe (Tukuyu) Cross Flow/Ossberger 21.2

Nyangao (Lindi) Cross Flow/Ossberger 38.8

Peramiho (Songea) Cross Flow/Ossberger 34.6

Isoko (Tukuyu) Cross Flow/Ossberger 7.3

Ndanda (Lindi) Gilbsk 14.4

Ngaresero (Arusha) Geiselbrecht 15.0

Sakare (Soni) Chinese 6.3

Mbarari (Mbeya) B. Maler 700.0

Ndolage (Bukoba) CMTIP 55.0

Ikonda (Njombe) Information not available 40.0

Tosamaganga (Iringa) Information not available Information not available

TOTAL: 4,737.9

5

1.2.2 Natural Gas

Ongoing petroleum exploration in Tanzania through the Tanzania Petroleum

Development Corporation has discovered natural gas along SongoSongo Island

and Mnazi Bay both of which are located in southeastern Tanzania. The

SongoSongo natural gas reserve is estimated at 30 million cubic metres whereas

the Mnazi Bay reserve is estimated to contain 15 million cubic metres.

Exploitation of the SongoSongo gas started in July 2004 after completion of the

229km gas pipeline from SongoSongo Island to Dar es Salaam. Todate, the

natural gas is utilized to generate 331MW of electricity through thermal power

plants located in Dar es Salaam City. Other uses of the gas include thermal

applications in factories, households, and automotive based within the City.

Natural gas application in automotive commenced following the commissioning of

the natural gas filling station project. The project has been implemented by the

Government of the United Republic of Tanzania in collaboration with the TPDC.

It has a capacity to benefit over 8,000 cars and some 30,000 households. Motor

vehicles conversion to run on compressed natural gas (CNG) from this project

commenced in mid 2009. Starting with the city of Dar es Salaam, two initial CNG

stations are designated at Ubungo and Mikocheni areas.

1.2.3 Biomass

Tanzania has about 33.5 million hectares of forest and woodlands, which is about

38% of total land area [7]. Out of this total area, almost two thirds are woodlands

on public lands that are under enormous pressure from human activities also

being an energy source. Besides wood fuel, the country has considerable

biomass resources in form of agricultural and forest residues and animal wastes

which, in combination with the woodlands, meet the majority of household energy

requirement.

Biomass potential can therefore be estimated from existing plantation forests and

agricultural waste. Currently, there are about 80,000 hectares of state owned

plantation forests that were mostly linked to state owned wood based panel

industry (veneer and plywood, hardboards, and chipboards) and the pulp and

6

paper industry. It is also estimated that there are 20,000 – 25,000 hectares of

private owned plantations, and in addition, there are up to 80,000 hectares of

plantations belonging to villagers, local Governments, non-Government

organizations (NGOs), civil societies, and religious organizations [8]. At 20%

residue factor from the harvested wood, it is estimated that the total biomass

potential from plantation forests residue is over 205,400 m3 [8, 9]. About 75% of

this potential is within the Saohill plantation forests followed by Buhindi plantation

that shares 4.67% of total potential.

On the other hand, evaluation of agricultural production data available from the

National Bureau of Statistics [1] shows that the total amount of waste that

originates from agricultural activities is over 12 million tones. With a share of

61.15% to total waste potential, corn stalks and cobs have the highest potential of

agricultural waste. Rice straw and husks follow in their contribution to the

potential stock, sharing 32.69% of total waste. Waste from sugarcane processing

(bagasse) is already being used for cogeneration in all four Tanzania‟s sugar

plants. The available bagasse shares 3.55% of total agro waste potential. It can

therefore be implied that agricultural wastes from corn, rice, and sugarcane have

the overall importance since they contribute 97.39% of the existing agricultural

waste potential.

From the available biomass resources in terms of 12 million tones of agricultural

waste; 205,400 tones of forestry waste; including planting the available 19 million

hectares with biomass forests, Wilson et al. [10] estimated that the total biomass

energy potential amounts to 12 million TOE. Currently, Tanzania imports a total

of 850,000 tones of petroleum oils per annum, the estimated biomass surpasses

the demand and, it suggests that Tanzania may become a net exporter of this

renewable energy.

A study by Kaseva and Mbuligwe [11] established that per capita waste

generation in the city of Dar es Salaam is 0.40kg/person/day. This shows that a

considerable solid waste is being generated in urban areas, and hence, the

potential energy and materials recovery. Shown in Table 4 is the municipal solid

waste data for 21 municipalities and major cities in Tanzania. Major Cities like

Dar es Salaam, Mwanza, Shinyanga, Kagera, Mbeya and Kigoma have relatively

7

higher potential energy from the waste. However, all over Tanzania urban waste

collection is marginal, at 32 percent of the total generated amount. Therefore for

this waste to be applied in energy generation there is a need to put in place

organized waste collection and management procedures and infrastructure.

8

Table 4: Waste generated (Tones) in Tanzania Cities [12]

NO. CITY/TOWN AMOUNT

GENERATED (TONES/DAY)

AMOUNT OPEN

DUMPED (TONES/DAY)

DUMPED/ GENERATED

RATIO

AMOUNT GENERATED

IN 2000 (TONES/DAY)

AMOUNT GENERATED

IN 2003 (TONES/DAY)

AMOUNT GENERATED

IN 2005 (TONES/DAY)

1 Dar es Salaam 2,200 2,000 2,848 3,100

2 Mwanza 210 80 38 751 977 1,036

3 Shinyanga 100 25 25 564 898 991

4 Kagera 24 8 31 64 242 714

5 Mbeya 145 66 46 442 662 712

6 Kigoma 60 15 25 274 537 620

7 Tabora 120 12 10 405 550 612

8 Morogoro 260 54 21 391 563 608

9 Dodoma 156 42 27 395 544 585

10 Tanga 400 190 48 519 657 554

11 Iringa 36 11 31 382 479 500

12 Mara 30 7 23 303 438 472

13 Kilimanjaro 92 45 49 354 442 464

14 Arusha 200 125 63 413 414 440

15 Rukwa 45 16 36 240 390 407

16 Lindi 206 253 385

17 Ruvuma 56 21 38 249 358 385

18 Mtwara 50 15 30 222 361 380

19 Singida 65 17 26 253 349 374

20 Manyara 193 332 373

21 Pwani 203 284 305

TOTAL 4,249 749 33 8,823 12,577 14,017

9

1.2.4 Coal

Coal reserves in Tanzania are estimated at about 1,200 million tones of which

304 million tones are proven. Coal sites include Kiwira, northwest of Lake Nyasa

and Mchuchuma/Katewaka on the southeast of the Lake. Generally, the

available coal is bituminous, with an average ash content of about 25% and

calorific value of between 22 and 28 MJ/kg. Some coal from Kiwira is generating

electricity (6 MW) and is also used for other thermal requirements in industries

like cement and textiles most of which are located in the neighbouring regions of

Mbeya, Iringa and Morogoro.

The coal has been analyzed to contain high content of sulphur (up to 9.2 wt.%),

which calls for the application of cleaner technologies [13, 14]. As indicated in

the National Power System Master Plan (PSMP) it is planned to utilize coal from

Mchuchuma and Kiwira to generate, respectively, 600 and 400MW of electricity.

While increasing the electrification level, such developments will also improve the

existing generation mix by relieving its strong bias to the hydropower.

1.2.5 Solar

Tanzania lies between 10 and 110 South of the Equator, with long sunshine

hours. The average daily insolation is about 4.5 – 6.5 kWh/m2 [15]. This

insolation provides an opportunity for installing solar photovoltaic (PV) and solar

thermal energy systems. However, todate there is a limited harnessing of the

solar resource as only about 1.2MWp of PV are installed countrywide as solar

home systems. The main PV applications in Tanzania include

telecommunications, lighting, vaccine refrigeration, water pumping, cathodic

protection of Tanzania Zambia oil pipeline and providing power backup systems.

Furthermore, solar thermal applications in Tanzania include solar water

heaters/pasteurizers, crop driers and solar cookers.

Some of the bottlenecks to the wider application of solar PV systems include:

high initial cost, limited market infrastructure, and lack of local technical capacity.

In its effort to bridge this, The Ministry of Energy and Minerals (MEM) initiated two

10

programs, respectively, supported by UNDP/GEF (2004 – 2009) and Sida (2005

– 2010). Besides putting in place PV systems demonstration facilities, the main

project output were: training to local technicians, development of PV standards,

and increased PV market infrastructure.

1.2.6 Wind

Preliminary wind pattern mapping for majority Tanzania regions show adequate

annual average wind speed for various applications (Table 5). Annual average

speeds suitable for stand alone and grid connected electricity generation

purposes (> 4 m/s) are strongly available along the Indian cost strip mainly

Tanga, Dar es Salaam, Zanzibar, and Mtwara regions. Other mainland regions

such as Mbeya, Iringa, Tabora, Mwanza and Dodoma have adequate wind

speeds.

Table 5: Wind stations with annual mean wind speeds ≥ 4.5 m/s [16]

NO STATION ANNUAL MEAN

WIND SPEED (m/s) RECORDING REFERENCE

TIME AT GMT

1 Amani – Tanga 4.97 1200

2 Dar es Salaam 5.31 1200

3 Dodoma 4.76 0600

4 Iringa 4.51 1200

5 Lindi 4.59 1200

6 Mbeya 5.36 1200

7 Mombo – Tanga 5.10 1200

8 Mtwara 4.68 0600

9 Mwanza 4.85 1200

10 Saohill – Iringa 5.11 0600

11 Songea 4.68 1200

12 Tabora 5.36 0600

13 Tanga 6.29 1200

14 Zanzibar 4.76 1200

15 Karatu 5.5 1500

16 Mkumbara 4.9 1500

17 Litembe 4.5 1500

A study by Nzali and Mushi [17] on the state of wind energy technologies in

Tanzania reported that there are no commercial electricity generation windmills.

Instead, there are over 106 windmills providing mechanical power for water

11

pumping in 11 regions of Tanzania. The study reported that 75.47% of the

installed windmills are owned by the local communities whereas church

organization owns 9.43% and 8.49% is owned by the Government. The

remaining 6.6% of the installations are owned by other organizations. With the

exception of two installations that used three-bladed horizontal axis and vertical

axis savonious rotor, respectively, the remaining installations utilized multi-bladed

horizontal axis technology, which is a proven technology for water pumping

purposes.

1.2.7 Geothermal

Preliminary reconnaissance activities on Tanzania geothermal potential

commenced in late 1970s. Between 1976-79 Messrs SWECO, a Swedish

consulting group, in collaboration with Virkir-Orkint, with the financial support of

the then Swedish International Development Authority (SIDA) conducted

reconnaissance survey of geothermal. The survey and surface exploration were

carried out in the north (near Arusha, Lake Natron, Lake Manyara and Maji Moto)

and in the south (Mbeya region). About 50 hot springs that are associated with

block faulting and recent volcanicity were mapped [18]. Information from the

MEM shows that existing geothermal potential is 650MW. However, these

geothermal resources are yet to be harnessed for energy generation due to the

lack of feasibility data. Figure 1 shows the geothermal energy potential sites in

Tanzania.

12

Figure 1: Geothermal potential sites in Tanzania (Documents available with

the MEM)

1.2.8 Tidal and Wave

Eastern Tanzania is a 1,424km coastal strip along the Indian Ocean. This strip

including those along the Zanzibar and Mafia Islands constitute a potential

energy source for tidal, wave, and ocean thermal energy conversion (OTEC)

technologies. However, the lack of full feasibility assessments and technological

capacity has led to the limited deployment.

13

1.2.9 Petroleum Oil and Uranium Exploration

Information available from the Tanzania Petroleum Development Corporation

shows that exploration activities over the past 50 years have led to natural gas

discovery at SongoSongo and Mnazi Bay. In this period a total of 35 exploration

and development wells have been drilled. Todate no oil has been produced

though available data and geological information reveal the existence of an active

petroleum system particularly in deep sea and along Lake Tanganyika. Table 6

details the existing oil and gas exploration companies that are operating in

Tanzania.

Ongoing uranium exploration activities in Tanzania are being undertaken by an

Australian company, Mantra Resources Limited. The company owns the Mkuju

River Project (MRP), which is located in southern Tanzania, some 470km

southwest of Dar es Salaam City. The project at the MRP is aimed at advancing

the exploration and appraisal of the widespread „Karoo‟ sandstone-hosted

uranium mineral, which is identified within the Project area. Exploration and

drilling undertaken by the company todate has confirmed the presence of

widespread surface uranium mineralization and multiple stacked mineralized

horizons at shallow depths. Results of the pre-feasibility study that was

completed in March 2010 confirmed the technical and economic viability of the

project. The results show an average annual production of 3.7 million pounds of

uranium grade U3O8 at a minimum initial mine lifetime of twelve years [19]. Prior

to commencement of the mining operation, the company is in a process of

engaging a definitive feasibility study.

14

Table 6: Oil and gas exploration companies [20]

COMPANY NAME COUNTRY OF

ORIGIN EXPLORATION AREA

Antrim Resources Canada Zanzibar/Pemba

Artumas Group Canada Mnazi Bay

Dominion Oil & Gas United Kingdom Mandawa, Kisarawe, Selous &

deep sea block no 7

Dodsal Resources United Arab Emirates Ruvu block

Key Petroleum Australia West SongoSongo

Mauriel ET Prom France Bigwa and Mafia

Ndovu Resources/

Tullow Oil Australia Nyuni, Ruvuma

Ophir Energy United Kingdom Deep sea block no 1, 3 and 4

Pan African Energy United Kingdom SongoSongo

Petrobras Brazil Deep sea block no 5, 6 & 8

Petrodel Resources/

Heritage United Kingdom Tanga, Kimbiji and Latham

RAK-Gas company United Arab Emirates East Pande

SHELL International Holland Deep sea block no 9, 10, 11 &

12

Statoilhydro ASA Norway Deep sea block no 2

Hydrotanz United Kingdom North Mnazi Bay

Tullow Oil United Kingdom North Lake Tanganyika

Beach Petroleum Australia South Lake Tanganyika

15

1.3 ELECTRICITY GENERATION MIX

As detailed in Table 7 and shown in Figure 2, about 51.43% of the electricity is

generated from renewable sources comprising of 47.20% hydro and 4.23% from

biomass. The total country‟s installed electricity generation capacity is

1,190.37MW. Due to the availability of indigenous natural gas, it has acquired

the second in importance as 331MW is now being generated from the natural

gas. Electricity generated from natural gas will continue to increase so as to

diversify power generated and alleviate the current bias to hydro sources, which

are prone to climate change particularly the extended drought. Drought

experience was gained in year 2004 – 2007 when its effect led to extended

power shading countrywide. On 3rd December 2006 water level recorded at

Mtera reservoir was 686.92 meters above sea level (m.a.s.l), which is about 3.08

meters below the dead storage level of 690.0 m.a.s.l [21]. Future power

generation need also increase the share of coal from Kiwira and

Liganga/Mchuchuma from the current 0.50% as supplied by Kiwira only.

Currently, isolated and grid connected thermal power plants (from petroleum oils)

shares 20.26% of the installed generation capacity. With the exception of the

Independent Power Tanzania Limited (IPTL) plant, all petroleum-based power

plants are owned by the national utility company (TANESCO). Their operation is

intermittent as they are backup sources when the generation from hydro falls

below the demand. The general generation mode has been to run the

hydropower system at near full generating capacity during rainy season and to

reduce hydropower generation during dry season. During the dry season,

thermal generation is increased while suppressing part of the load demand to

ensure sufficient water is available to supply the power system throughout the

year. The closure of petroleum-based power plants will be mandatory when

future demand is met by natural gas, coal, and other potential resources.

Tanzania electricity grid is also fed by imported electricity from neighbouring

Zambia and Uganda. The importation, respectively, is currently at 5 and 8MW.

This trend is expected to reverse after a full capacity harnessing the indigenous

energy resources particularly natural gas, coal and uranium.

16

Figure 2: Installed generation capacity and share (%) by source

Hydro 47.20%

Natural gas27.81%

Petroleum oils20.26%

Coal0.50% Biomass

4.23%

17

Table 7: Installed generation capacity and source (TANESCO records, 2010)

SNO. DESCRIPTION INSTALLED

CAPACITY (MW) EFFECTIVE

(MW) %

SHARE

1

Hydro

47.20

Mtera

80.00

66.00

Kidatu

204.00

180.00

Hale

21.00

5.00

Pangani Falls

68.00

20.00

Nyumba ya Mungu

8.00

3.50

Lower Kihansi

180.00

75.00

Uwemba 0.843 0.71

Total hydro

561.84

350.21

2

Natural gas

Songas

182.00

180.50

27.81

TANESCO Ubungo

104.00

102.50

TANESCO Tegeta

45.00

45.00

Total natural gas

331.00

328.00

3

Petroleum oils

20.26

TANESCO grid diesel plants

85.70

35.30

TANESCO isolated diesel plants

55.50 35.3

IPTL plant

100.00

100.00

Total petroleum oils

241.20

170.60

4 Coal

6.00

2.00

0.50

5

Biomass

4.23

Bagasse cogeneration

46.80

Wood biomass cogeneration

3.53

3.53

Total biomass

50.33

Total generation

1,190.37

100.00

18

1.4 BIOMASS COGENERATION

Biomass cogeneration shares a marginal (3.03%) contribution to installed

electricity generation capacity of the country. There are three privately owned

biomass cogeneration facilities in Tanzania. They are being owned by sugar-

processing factories, a wattle processing plant, and by a forestry plant.

Tanganyika Wattle Company (TANWAT) operates a cogeneration plant which is

fueled by wood logs and spent wattle barks. On the other hand, Kilombero Sugar

Company located in Morogoro region, Mtibwa Sugar Estate Limited also located

in Morogoro region, Kagera Sugar Limited from Kagera region and Tanganyika

Planting Company (TPC) of Kilimanjaro are utilizing bagasse in their

cogeneration plants. Saw mill waste is the fuel for cogeneration plant owned by

Sao Hill Saw Mill located in Iringa region.

1.4.1 Kilombero Sugar Company

Sugar processing is through two processing plants known as Msolwa (Kilombero

K1) and Ruembe (Kilombero K2). The Msolwa plant has a cane crushing

capacity of 80 tones of cane per hour (TCH) with total sugarcane plantation

amounting to 2,960 hectares and average yield of 70 tones per hectare. Ruembe

plant has a cane crushing capacity of 100 TCH. About 3,400 hectares of

sugarcane are harvested annually.

Msolwa plant has two steam turbines rated 3MW where as Ruembe has one

steam turbine with a rating of 1.2MW and two other steam turbines rated 800kW

each. The installed generation capacity at Kilombero Sugar Company is

insufficient to export the power to the national grid.

1.4.2 Mtibwa Sugar Estate Limited

Mtibwa Sugar Estate Limited has a total sugarcane plantation of 4,200 hectares

with an average yield of 80 tones per hectare. The company has three steam

boilers that produce steam for running two sets of back-pressure turbo-

19

alternators of 2.5MW and 1.5MW respectively. In addition, there is a turbo

generator rated 9MW. Up to a total of 10GWh of electricity is generated during

production season. Since the locally produced power is insufficient, about

4.0GWh are imported annually from TANESCO. Imported power is mainly used

for irrigation and for domestic uses.

1.4.3 Tanganyika Planting Company Limited (TPC)

The TPC has a total of 16,000 ha of land out of which about 6,100 ha is under

cane cultivation. TPC has just commissioned a boiler to produce 90t/hr steam at

45 bar and 450C. The steam will be fed to a generator for producing 17.5MW of

electricity. At this capacity the plant will be able to sustain its power requirements

to factory, residential areas, irrigation, and export excess power to TANESCO.

1.4.4 Kagera Sugar Limited (KASC)

Kagera Sugar Limited owns 860 hectares of sugarcane plantation with plant cane

crushing capacity of 60 TCH. Cane yield is 70 tones per hectare. The

cogeneration at KSC is through two steam turbines rated 2.5MW. There is a

potential for the extra power to be used for electrifying nearby villages as the

national electricity grid is yet to be in Kagera region.

1.4.5 Saohill Sawmill

Saohill sawmill is an integrated wood establishment that operates sawmill,

impregnated treated wood poles, planer mill and joinery factory. The company

has leased plantation coverage of 35,000 hectares of both hard and soft wood

species. Saohill sawmill has installed 4 diesel generators each rated 250kW,

which is capable of meeting the installed load capacity of about 850kW. Further

to the diesel generators, there is a 1MW electrical generator being coupled to a

steam engine. Steam is generated through a water tube boiler, which is fueled

by wood chips, sawdust and wood shavings.

20

1.4.6 Tanganyika Wattle Company (TANWAT)

TANWAT is located at Njombe district in the southern highlands of Tanzania,

Iringa region. The company owns a 15,000 hectares site out of which 8,000

hectares are wattle plantations, 4,000 hectares pines and 1,000 hectares of

eucalyptus. Main activities being the production of tannin extract from the bark of

wattle trees. About 3,000 tones of timber are also produced per annum from the

pine trees.

Wattle barks are stripped in the fields and transported to the factory for

processing and manufacture of the tannin extract. The wood is a waste of the

process and resulting in excess of 60,000 tones of wood logs per annum. Once

the bark is extracted of the tannin, it is also a waste accumulating to over 10,000

tones of spent barks per annum. Further to these, at a 40% recovery rate there

is an added 4,500 tones of pines waste per annum in terms of off cuts and

sawdust. Additional volume of wood is available from the eucalyptus plantation.

TANWAT company information shows that its cogeneration plant has an installed

capacity of 2,500kW. There are 2 boilers rated 15 tones per hour of superheated

steam for generating electricity through a single stage condensing steam turbine.

TANWAT does not import power from TANESCO. Instead TANESCO shares

35% of total power generated at TANWAT.

A study by Mwihava and Wilson [22] showed that the immediate potential

expansion in cogeneration in these plants amounts to over 120MW (Table 8).

Increment of the cane crushing capacity and systems improvement is necessary

for realizing the potential.

21

Table 8: Potential additional cogeneration capacity [22]

S/N NAME OF COMPANY

EXISTING

COGENERATON

CAPACITY (MW)

POTENTIAL

ADDITIONAL

COGENERATION

CAPACITY (MW)

1 Mtibwa Sugar Estates

Limited 13 15

2 Kagera Sugar Limited 5 15

3 Tanganyika Planting

Company (TPC) 20 14 to 30

4 Kilombero Sugar Company 8.8 30

5 Pangani Sugar Limited 0 15

6 Tanganyika Wattle

Company 2.5 15

7 Sao Hill Saw Mill 1.025 3 to 4

Total 35.825 107 to 124

1.5 ELECTRICITY DEMAND

Figure 3 shows the trend of energy generation and consumption in Tanzania.

The current total annual electricity generation and consumption, respectively, is

4,800 and 3,600 million kWh. The difference between generation and

consumption is accounted by system loss, which averages 26%. Over the

analyzed period covering years 1999 to 2009 the consumption trend is growing at

7.49% per annum. The growth in power demand is attributed to population

growth and increasing economic activities. The peak demand is suppressed in

order to save the national grid from a total collapse, as the existing generation

and distribution capacity is far less than sufficient to meet peak demand.

22

Figure 3: Electricity generation and consumption, million kWh (TANESCO

records on generation, importation, and sales data, 2010)

1.6 ELECTRICITY DISTRIBUTION AND DISTRIBUTION NETWORK

Shown in Figure 4 is the electricity distribution network, which is solely (98%)

owned by the national utility (TANESCO). The distribution network is

concentrated in cities and urban areas leaving most of the rural areas uncovered.

As a result only 2% of rural population has access to electricity whereas the

portion of urban population with access to electricity is 37% [23, 24].

Electrification is one of key catalysts of development, and consequently, low

electrification levels have negative consequences leading to low economic

activities, poor access to clean water, low literacy levels, and inferior health

services. Increasing the electrification levels has the potential to contribute in

accelerating development of the country.

-

1,000

2,000

3,000

4,000

5,000

6,000

1998

2000

2002

2004

2006

2008

2010

YEAR

VA

LU

E, M

ill. k

Wh

Total (Generated + Imported)

Consumption (Sold)

23

Figure 4: Existing and proposed grid and isolated transmission system [25]

2. LITERATURE REVIEW

2.1 BIOMASS GASIFICATION

In terms of energy supply and environmental conservation, biomass energy is the

most important renewable energy. Studies establishing the technical biomass

energy potential of biomass show that the annually available biomass is over

seven times the current consumption of petroleum oil, coal and natural gas [26,

27]. In year 2000 biomass energy supplied 7% of total renewable energy in the

OECD countries being second to hydro, which supplied 87% of total renewables

[28]. However, the importance of biomass energy in environmental conservation

is from the tendency to recycle the greenhouse gas carbon dioxide in the growing

feedstock [29, 30].

24

Biomass gasification is an efficient biomass-to-energy conversion technology.

Through integrated gasification combined cycles (IGCC), it is possible to increase

the conventional Rankine cycle power generation‟s efficiency from 30% to 50%

[31]. Besides the syngas energy from biomass gasification, various other energy

streams can be generated. These energy steams are conventionally used for

electricity generation and for thermal applications. However, it is foreseeable that

the transport sector is the most important end use sector due to its poor

environmental performance [32-34]. In this respect renewable hydrogen and

second generation bio-automotive fuels are expected to decarbonize the

transport sector. The renewable hydrogen can be produced by upgrading the

producer gas from biomass gasification [35, 36], whereas the two main biomass

syngas components, H2 and CO, are widely recognized as an important platform

in the production of second generation bio-automotive fuels like methanol,

ethanol, dimethyl-ether (DME), Fischer-Tropsch (FT)-diesel, synthetic natural gas

(SNG), and hydrogen [37].

2.2 HIGH TEMPERATURE AIR/STEAM GASIFICATION (HTAG)

The high temperature air/steam gasification (HTAG) of biomass technology

stems from an advanced combustion technology, the high temperature

combustion (HiTAC). Tshuji et al. [38] have shown that the key sustainability

criterion of the HiTAC technology is from its energy savings, which is a key

feature of sustainable energy technologies. Further studies by Rafidi & Blasiak

[39] and Tiwari et al. [40] revealed the low NOx emission characteristic of the

HiTAC technology. From Le Chatelier's Principle, the high operating temperature

of the HTAG process favours achieving a dynamic equilibrium of the endothermic

primary water gas reaction (Eq. 1), which becomes significant from 1000C.

Studies by Lucas [41] reported that the formation of H2 increased by about 14%

with an increase of HTAG feed gas temperature from 350C to 830C.

C + H2O CO + H2 (1)

25

2.3 EFFECTS OF HEATING RATE AND TEMPERATURE

Pyrolysis is an important initial stage during thermal degradation of biomass the

control of which determines the final product and product distribution [42, 43].

Yield of the main syngas components of CO, H2, CH4, and CO2 is enhanced by

increasing temperature and heating rate with longer residence time [44, 45].

However, the tendency of the CO2 and CH4 yield is to increase with temperature

to an asymptotic value. The high temperature, high heating rate and longer

residence time is sufficient to allow for secondary thermocracking reactions that

lead to more syngas yield [46].

2.3 CO/CO2 Ratio of Product Gas

Different fire indices have been traditionally used in characterization of the extent

and progression of fires. Such indices as the C/H ratio, CO/O2 deficiency % and

the CO/CO2% are commonly used [47]. During gasification, high concentration of

CO will be produced in the oxygen deficient atmosphere and at a proper

temperature. CO is produced mainly from devolatilization stages and through the

partial oxidation (Eq. 2), Boudouard (Eq. 3) and primary water gas reaction (Eq.

1). Various studies have shown that higher CO/CO2 ratios are favoured by higher

gasification temperatures [48, 49].

C + ½ O2 CO (2)

C + CO2 2CO (3)

26

3. OBJECTIVES

Studies that established the potential renewable energy from biomass show the

existence of enormous potential. However, biomass is a complex material having

varied characteristic properties that poses challenges while harnessing the

energy potential. Variations in the characteristics and volume of the biomass

components and differences in cellular structure make woods heavy or light, stiff

or flexible, and hard or soft. This also implies to the differences in moisture

content, volatile matter, heating value, elemental composition, and the inclusion

of inorganic materials. Further, the differences in the growing location and

condition will influence the biomass properties.

While the characteristic properties of biomass feedstock in the developed world

are well-studied, those in the developing counterpart are partially studied. It is

therefore the objective of this work to establish the characteristic properties of

selected biomass feedstock from Tanzania. The characteristic properties to be

established will provide the necessary input to thermochemical process designers

and researchers. Furthermore, since the properties are origin-specific, they

provide baseline data for technology transfer from north to south.

27

4. METHODOLOGY

4.1 CHEMICAL COMPOSITION

In order to correlate the chemical composition to the respective thermal

behaviour of the biomass materials under characterization, standard test

methods namely proximate and ultimate analysis were done. The proximate

analysis (ASTM D3172-5) reports volatile matter and ash content, fixed carbon,

and higher heating value. On the other hand, the elemental composition of the

biomass is determined by the ultimate analysis (ASTM D3176).

4.2 THERMAL DEGRADATION CHARACTERISTICS

A thermal gravimetric analyzer type NETZSCH STA 409 PC Luxx was utilized to

establish the thermal degradation characteristics of the biomasses under the

study. The STA 409 PC Luxx is a dynamic thermal analyzer that combines both

the heat flux Differential Scanning Calorimetry (DSC) and Thermogravimetry

(TG). The experiments were carried out under controlled inert nitrogen condition

with nitrogen flow rate kept at 60 ml/min while heating the sample at 10 K/min.

The TG data acquisition, storage and analysis were done using the “Proteus”

software. Prior to testing, the biomasses were dried in oven overnight. This was

necessary for removing the naturally absorbed moisture.

28

4.3 LABORATORY EXPERIMENTATION

Besides establishing the chemical composition and thermal degradation

characteristic of the biomasses under study, a laboratory scale high temperature

gasification of biomass was undertaken. The gasification experiments were done

for the purpose of investigating the influence of steam and oxygen oxidizers while

varying temperature in three different ranges of 900, 800, and 700°C. During the

laboratory gasification experiments, the oxygen level was maintained at three

concentrations of 2, 3, and 4%. Coffee husk, which is a tropical agricultural

waste, was the material utilized for the laboratory investigation. Fifteen grams of

the coffee husk sample was taken for each gasification experimental run. Steam

flow to the gasification was set at 0.469 kg/min.

The schematic diagram of the high temperature gasification rig is shown in Figure

5. The rig is batch type, which is preheated to predetermined temperature using

a methane burner (7). Honeycomb (9) stores heat energy from primary

combustion chamber (8). The heat stored in the honeycomb is then released to

heat the secondary combustion chamber (10) to a constant desired experimental

temperature. A thermocouple (15) records the secondary chamber temperature,

when it reaches the desired level the burner is switched off. Oxygen

concentration (%) is achieved by setting oxygen and nitrogen flow through

respective inlets (3) and (4) that are controlled by Bronkhorst EL-Flow mass flow

meters and controllers (6). Steam is injected through inlet pipe (1) whereas inlet

pipes (2) and (5) are available for more oxidants. The sample (18) is inserted

into the furnace through inlet flange (13) where it is also cooled through the

chamber (11). Nitrogen (12) is used to purge air infiltrated while inserting the

sample and it is also used to cool down the sample before exiting the furnace.

Sample temperature is monitored at the cooling chamber and during the

experiments through thermocouples (17) and (16) respectively. The behaviour of

the sample during the experiment can be observed through glass window (14).

The syngas exits through pipe (20) where the sampling probe (21) collects gas

for analysis. Prior to composition analysis, the sampled syngas is cleaned by

passing through sampling train (22). The syngas enters the first flat bottomed

29

flask which is in ice bath that allows the collection of syngas condensates that

includes water vapour. Further condensation is enhanced by a condenser. On

exiting the condenser the syngas enters a series of three bottles that are

contained in a second ice bath. Further syngas condensates and particulates are

collected in the first bottle that contains water. The second bottle and third bottle

contains iso-butanol (Isobutyl alcohol), which allows absorption of all tars

remaining in the syngas after exiting the first bottle. A clean syngas exits the

third bottle and enters the fourth dry bottle that contains a dry cotton wool. The

cotton wool allows further cleaning of the gas and traps all the escaping

particulates.

Online carbon monoxide and carbon dioxide analyzer type Maihak Multor 610

was utilized to monitor flue gas composition whereas mass loss data was

measured by a digital online balance (19) type Radwag model WPX 1500.

Furthermore, a micro GC monitored the syngas composition with respect to CO,

CO2, CH4, C2H4, C2H6, and C2H2 species. All data generated by the

thermocouples, gas analyzer, micro GC, and digital balance were collected in a

laptop computer via TCP/IP multiplexer type Keithley 2710.

F

F

F

1

4 2

7

38

9

1213

1615

11

20

21

6

14

22

5

O2

N2

10

18

1719

To data acquisition

system

To gas

analyzers

Figure 5: The high temperature gasification test rig

30

5. RESULTS AND DISCUSSION

5.1 CHEMICAL COMPOSITION OF TROPICAL BIOMASSES

A total of 15 tropical biomasses were analyzed for their chemical composition.

The analyzed materials were palm waste, coffee husks, cashew nut shells (CNS),

rice husks and bran, bagasse, sisal waste, jatropha seeds, and mango stem.

Results of their chemical properties as established by undertaking proximate and

ultimate analysis are detailed in Table 9. With respect to biomass materials

analysis done by Jenkins et al. [50], the analyzed tropical biomasses have

comparable heating value and contents of volatiles, carbon, hydrogen and

oxygen. Furthermore, the relative content of nitrogen, sulphur, and chlorine is

marginal.

The relatively higher presence of chlorine (Cl) and sulphur (S) in biomass as

exhibited in the palm branch and jatropha seeds are not desirable combustion

properties. Chlorine and sulphur are the major contributing factor to ash formation

as they facilitate the mobility of inorganic compounds from the fuel to surfaces

where they form the corrosive compounds [51, 52].

31

Table 9: Tropical biomasses chemical composition

MATERIAL AND PROPERTY PALM

STEM

PALM

BRANCH

PALM

FIBRE

PALM

SHELLS

COFFEE

HUSKS

MASASI

CNS

OLAM

CNS

RICE

HUSKS

Proximate analysis (%), dry basis

Moisture 9.10 8.10 4.98 8.40 10.10 6.70 6.10 8.80

Volatile matter 81.20 79.60 79.00 75.40 83.20 84.10 84.80 59.20

Fixed carbon 15.30 12.60 9.30 20.00 14.30 14.00 13.10 14.60

Ash 3.50 7.80 11.80 4.60 2.50 1.90 2.00 26.20

Ultimate analysis (%), dry basis

C 47.50 45.60 52.20 51.50 49.40 56.00 56.90 35.60

H 5.90 5.60 7.10 5.70 6.10 6.90 7.00 4.50

N 0.28 0.19 0.70 0.36 0.81 0.44 0.45 0.19

O (by difference) 42.50 39.30 28.00 37.70 41.20 34.70 33.60 33.40

Cl 0.18 1.33 0.06 0.05 0.03 0.03 0.03 0.08

S 0.13 0.16 0.07 0.03 0.07 0.05 0.04 0.02

Higher heating value (MJ/kg) 17.38 16.24 21.98 19.29 18.34 22.38 22.83 13.24

"H:C" Ratio 0.12 0.12 0.14 0.11 0.12 0.12 0.12 0.13

"O:C" Ratio 0.89 0.86 0.54 0.73 0.83 0.62 0.59 0.94

32

MATERIAL AND PROPERTY RICE

BRAN

TPC MILL

BAGASSE

SISAL

BOLES

SISAL

POLE

SISAL

LEAF

JATROPHA

SEEDS

MANGO

STEM

Proximate analysis (%), dry basis

Moisture 7.80 9.00 7.50 10.10 8.50 6.60 7.50

Volatile matter 64.60 80.50 84.10 79.30 80.20 80.30 83.50

Fixed carbon 14.20 16.20 12.80 14.60 12.60 14.70 12.00

Ash 21.10 3.30 3.10 6.10 7.20 5.00 4.50

Ultimate analysis (%), dry basis

C 37.80 48.10 48.00 47.00 47.00 56.60 48.00

H 5.00 5.90 6.00 6.00 5.70 7.50 5.80

N 0.55 0.15 0.10 1.66 0.14 3.16 0.13

O (by difference) 35.40 42.40 42.70 39.10 39.90 27.40 41.50

Cl 0.09 0.07 0.06 0.05 0.04 0.12 0.03

S 0.05 0.02 0.03 0.13 0.03 0.17 <0.012

Higher heating value (MJ/kg) 13.93 17.33 17.20 17.35 17.23 21.90 16.90

"H:C" Ratio 0.13 0.12 0.13 0.13 0.12 0.13 0.12

"O:C" Ratio 0.94 0.88 0.89 0.83 0.85 0.48 0.86

33

A detailed analysis of the materials‟ properties was done by investigating their

"H:C" and "O:C" ratios whose findings is shown in the coalification diagram,

Figure 6. The materials that exhibit higher H:C ratio with relatively low O:C ratio

(located on top left corner of the plot) like Jatropha seeds, palm fibre and cashew

nut shells have better energy value compared to the rest. This is due to the high

correlation of hydrogen and carbon to the higher heating value (HHV) of biomass

materials as indicated in Equation 4 [53]. From equation 5.1, K1, K2, K3, and K4

are correlation coefficients characteristic of the individual biomasses. For the

purpose of correlating the heating value of any biomass material, the authors

approximated the value of K1, K2, K3, and K4 to be -0.763, 0.301, 0.525 and 0.064

respectively.

)(%*)(%*)(%*/4321

OKHKCKKkgMJHHV (4)

Further analysis to the biomass chemical composition as done by Jenkins et al.

(1998) showed that the atomic oxygen-to-carbon (O:C) ratio for biomass

materials ranges from 0.38 to 0.86 whereas the respective ratio for coals ranges

between 0 and 0.36. The high O:C ratio for biomass is detrimental to their

energy content since materials rich in oxygen are associated with poor high

heating value [54]. This is due to increased process irreversibility, which is

inversely proportional to the biomass oxygen content [55].

Figure 6: Coalification diagram for the tropical biomasses

34

5.2 THERMAL DEGRADATION OF TROPICAL BIOMASSES

5.2.1 Mass Loss Characteristics

The mass loss characteristics of five selected tropical biomasses as derived from

thermogravimetry analysis are represented by Figure 7. All TG thermograms

clearly showed three regions of moisture release, devolatilization, and char

degradation. The TG profiles are typical for biomasses as observed by other

researchers [54, 56].

Figure 7: TG thermogram characteristics based on the coffee husks sample

The study findings on the mass loss during the moisture release stage shows that

the cashew nut shells suffered the most mass loss of 12.27% compared to the

rest whose mass loss was below 8%. Coffee husks and bagasse suffered a

relatively high mass loss of 7.16% and 6.33% respectively. The least mass loss

due to moisture release was observed from the palm stem, which experienced a

mass loss of 3.55% (Table 10). The apparently higher moisture released from the

CNS is due to a simultaneous moisture and low temperature volatiles release.

The presence of low temperature volatiles in the cashew nut shell liquid was also

mentioned by Das and Ganesh [57]. While extracting bio-oil from the CNS, the

authors found that a larger portion of the bio-oil oozed out from the CNS up to a

temperature of 150°C. Analysis of the resulting bio-oil depicted a moisture

content of 3.5%. Further analysis of the DTG profile for the CNS shows two

35

peaks in the moisture region. The two moisture peaks have same value of -

1.1%/min but appears at higher temperature (133°C and 161°C) compared to the

remaining materials whose moisture peaks occurred at about 80°C. This shows

that the moisture in the CNS material is entrained in its cell walls and for this

particular structure its evaporation requires more energy and this occurs at higher

temperatures [58].

Table 10: Mass loss summary

SNO MATERIAL

MASS LOSS, % BURNOUT TEMPERATURE,

C MOISTURE

VOLATILES RELEASE

CHAR

1 Bagasse 6.33 63.81 15.88 377.00

2 Palm stem 3.55 52.25 12.84 365.00

3 Cashew nut shells (CNS)

12.27 44.80 20.94 364.01

4 Coffee husks 7.16 46.77 17.39 378.00

5 Sisal bole 4.67 57.47 18.41 382.00

AVERAGE 6.80 53.02 17.09 373.20

Volatiles release stage is the most important region of the thermogram shown in

Figure 7 since on the average over 53% of the materials´ mass loss was

experienced in this region. Details presented in Table 10 show that the bagasse

and sisal bole had the highest mass loss of 63.81% and 57.47% respectively.

Mass loss to the palm stem was the average at the value of 52.25% whereas the

least mass loss were from coffee husks and cashew nut shells whose values

were 46.77% and 44.8% respectively.

5.2.2 Rate of Mass Loss Characteristics

Rate of mass loss as expressed by the derivative TG (DTG) is an indication of

reactivity of the material under investigation [59, 60]. From the DTG

thermograms, the reactivity is indicated by the respective peaks due to

hemicellulose and cellulose degradation. Table 11 summarizes the characteristic

properties of the analyzed materials as extracted from their respective DTG

thermograms as defined by Jeguirim and Trouvé [61] and represented in Figure 8.

36

Besides indicating the material‟s reactivity, these characteristics are also important

in the establishment of the material‟s kinetic parameters.

Table 11: Material‟s characteristic properties summary

MATERIAL AND CHARACTERISTIC PROPERTY

Tonset [°C]

Hemicellulose peak

Cellulose peak Toffset [°C] (-dX/dt)sh

[%/Min.] Tsh [°C]

(-dX/dt)peak [%/Min.]

Tpeak [°C]

Bagasse 234.57 -9.02 346.63 397.61

Palm stem 180.55 -4.77 284.76 -8.19 334.17 370.64

Cashew nut shells (CNS)

203.13 -5.52 291.03 -4.35 343.02 371.97

Coffee husks 218.75 -6.33 352.74 381.75

Sisal bole 122.83 -8.10 353.18 406.70

Where,

Tonset Is the extrapolated onset temperature calculated from the

partial peak that results from the decomposition of the

hemicellulose component

(-dX/dt)sh Is the overall maximum of the hemicellulose decomposition

rate

Tsh Is the temperature corresponding the overall maximum of the

hemicellulose decomposition rate

(-dX/dt)peak Is the overall maximum of the cellulose decomposition rate

Tpeak Is the temperature corresponding the overall maximum of the

cellulose decomposition rate

Toffset Is the extrapolated offset temperature of the (-dX/dt) curves.

This value describes the end of the cellulose decomposition.

37

Figure 8: Material‟s characteristic properties based on palm stem

degradation

Based on the characteristic properties presented in Table 11, the CNS is the

most reactive amongst the analyzed materials since during the devolatilization

stage the first peak reached (-5.52%/minute) of hemicellulose degradation after

25 minutes. Compared to the CNS, DTG peaks for palm stem exhibited lower

value of -4.77%/minute whereas the bagasse, coffee husks, and sisal bole had

their two peaks merged into one.

5.2.3 Burnout Temperature

Burnout temperature has been widely used by researchers to characterize

combustion properties of solid fuels [62-64]. Burnout temperature is defined as

the temperature where the rate of weight loss consistently decreases to less than

1%/minute. In this respect, burnout temperature was investigated for the biomass

samples under this study. Low burnout temperature was exhibited by CNS

(364.01°C) and palm stem (365°C). The remaining materials, namely bagasse,

coffee husks, and sisal bole showed relatively higher burnout temperature of 377,

378, and 382°C respectively. In this respect, the CNSL and palm stem biomasses

are relatively more readily combustible compared to the bagasse, coffee husks,

and sisal bole [65, 66].

38

5.3 LABORATORY GASIFICATION OF COFFEE HUSKS

By utilizing the laboratory test rig shown in Figure 5, experiments on high

temperature gasification of coffee husks were done for the purpose of

investigating the influence of steam and oxygen oxidizers while varying

temperature in three different ranges of 900, 800, and 700°C. During these

gasification experiments, the oxygen level was maintained at three

concentrations of 2, 3, and 4%.

5.3.1 Effects of Gasification Agent on Heating Rate

The sample centre temperature profiles resulting from this study are shown in

Figure 9 (a) to (c). It can be generalized that in all gasification experiments that

were carried using both oxygen and steam oxidizers achieved relatively higher

sample centre temperature compared to the experiments that were carried using

individual oxidizers including those under inert nitrogen condition. A detailed

analysis of the profiles shows that this effect was more remarkable in all

experimental cases that were carried at 800°C including all the experimental

cases that were carried with 4% oxygen concentration. Maintaining the reactor

temperature at 800°C is beneficial since this temperature is thermodynamically

favourable for higher yield of hydrogen [67].

The high sample centre temperature is partly induced by the highly preheated

steam oxidizer, which provides the extra reaction enthalpy. Furthermore, the

effect of exothermic character of the water-gas shift reaction (Eq. 5) and the

carbon oxidation reaction (Eq. 6) are responsible for liberating a sensible heat at

elevated oxygen concentrations as for the cases of 4% oxygen concentration

experiments.

222 HCOOHCO (5)

22 COOC (6)

39

5.3.2 Gasification Rate

The coffee husk gasification rate profiles as indicated by the mass loss to the

respective experimental runs are shown in Figure 10 (a) to (c). From Figure 10

(a) on the effect of varying temperature on gasification rate, it can be seen that

gasification at 900°C had an overall higher gasification as exhibited by less

materials left at the end of the experiment. For instance, during the inert nitrogen

condition, 7% of coffee husk remained for the case of 900°C whereas the residue

mass for the gasification at 800 and 700°C was 10 and 17% respectively.

Furthermore, the higher temperature (900°C) had the effect of accelerating

gasification rate in the initial stages, which is mainly for devolatilization of the

biomass material.

40

Figure 9 (a): Sample temperature at 700°C with varied oxygen concentration

Figure 9 (b): Sample temperature at 800°C with varied oxygen concentration

Figure 9 (c): Sample temperature at 900°C with varied oxygen concentration

Figure 9: Sample temperature profiles

SAMPLE TEMPERATURE AT 700 C; O2 = 2%

0

200

400

600

800

010

020

030

040

050

060

0

TIME, S.

TE

MP

., C

.

O2=2%

N2

(O2-Steam)

(Steam)

SAMPLE TEMPERATURE AT 700 C; O2 = 3%

0

200

400

600

800

010

020

030

040

050

060

0

TIME, S.

TE

MP

., C

.

O2=3%

N2

(O2-Steam)

(Steam)

SAMPLE TEMPERATURE AT 700 C; O2 = 4%

0

200

400

600

800

010

020

030

040

050

060

0

TIME, S.

TE

MP

., C

.

O2=4%

N2

(O2-Steam)

(Steam)

SAMPLE TEMPERATURE AT 800 C; O2 = 2%

0

200

400

600

800

010

020

030

040

050

060

0

TIME, S.

TE

MP

., C

.

N2

O2=2%

(O2-Steam)

(Steam)

SAMPLE TEMPERATURE AT 800 C; O2 = 3%

0

200

400

600

800

010

020

030

040

050

060

0

TIME, S.

TE

MP

., C

.

N2

O2=3%

(O2-Steam)

(Steam)

SAMPLE TEMPERATURE AT 800 C; O2 = 4%

0

200

400

600

800

010

020

030

040

050

060

0

TIME, S.

TE

MP

., C

.

N2

O2=4%

(O2-Steam)

(Steam)

SAMPLE TEMPERATURE AT 900 C; O2 = 2%

0

200

400

600

800

1000

0 50 100

150

200

250

300

350

400

450

TIME, S.

TE

MP

., C

N2

O2=2%

(O2-Steam)

(Steam)

SAMPLE TEMPERATURE AT 900 C; O2 = 3%

0

200

400

600

800

1000

0 50 100

150

200

250

300

350

400

450

TIME, S.

TE

MP

., C

N2

O2 = 3%

(O2-Steam)

(Steam)

SAMPLE TEMPERATURE AT 900 C; O2 = 4%

0

200

400

600

800

1000

0 50 100

150

200

250

300

350

400

450

TIME, S.

TE

MP

., C

N2

O2 = 4%

(O2-Steam)

(Steam)

41

Figure 10 (b) and (c) shows that steam injection, generally, had no positive

effects on enhancing the mass loss of the material under gasification. Figure 10

(b), which represents the variation of temperature at fixed oxygen concentration

of 2%, shows that in all cases the residue mass for steam injected experiments

was higher than the without cases. Similarly, in Figure 10 (c), with exception of

the case of 3% oxygen concentration the remaining cases showed no

enhancement in mass loss due to steam injection. Steam oxidizer supports gas

phase reactions namely water gas shift (Eq. 5) and steam reforming of methane

(Eq. 7), which at higher temperature result in more hydrogen and CO formation.

Steam and carbon reaction under the endothermic primary water gas shift

reaction (Eq. 8) requires higher temperatures above 1000°C. Table 12

summarizes the residue masses for Figure 10 (b) and (c).

224 3HCOOHCH (7)

22 HCOOHC (8)

Table 12: Residue mass summary for steam injected experiments

RESIDUE MASS AT 2% OXYGEN CONCENTRATION

TEMPERATURE 700°C 800°C 900°C

Without steam 4.74 2.93 1.76

With steam 18.42 9.76 13.53

RESIDUE MASS AT 900°C

OXYGEN CONCENTRATION 2% 3% 4%

Without steam 2.93 27.27 8.18

With steam 13.17 13.64 23.64

Figure 10 (a): Effects of temperature and agent on gasification rate

N2 condition

Steam injected

42

Figure 10 (b): Effects of steam injection on gasification rate (oxygen

concentration fixed at 2%)

Figure 10 (c): Effects of steam injection on gasification rate (varied oxygen

concentration, temperature fixed at 900°C)

Figure 10: Gasification rate under different experimental conditions

43

5.3.3 Syngas Evolution

The gasification experiments under the study generated data on carbon

monoxide and carbon dioxide evolution. The two gases are major components of

the syngas though each has a different role on the syngas quality and heating

value. Being combustible, the carbon monoxide is desired component of the

syngas whereas carbon dioxide is not desired as it plays a negative role on

syngas heating value.

44

Figure 11 (a) to (f) summarizes the CO and CO2 gases evolution during the

gasification experiment. Under this figure, the graphs are arranged horizontally in

increasing oxygen concentration from 2 to 3 and 4% while temperature remains

constant. In each case, gas evolution comparison is made to inert nitrogen only,

oxygen and steam oxidizers mixture, and steam oxidizer only. Moving vertically

from Figure 11 (a) to Figure 11 (f) the comparison is made under fixed oxygen

concentration while temperature is increased from 700 to 900°C.

From the summary provided in Table 13, it is evident that the steam only injection

to biomass under gasification evolved the highest volumetric concentration of

carbon monoxide. Two evolution characteristic features are observed from these

graphs. The first being the fact that at higher temperature the peaks of CO are

relatively higher compared to low temperature peaks. Thus it can be seen that

the peak at 900°C steam only was 23.47 vol. % CO whereas that at 700°C was

21.25 vol. % CO. Comparatively, the CO peaks for cases without steam at 900°C

and 2, 3, and 4% oxygen concentrations were 4.59, 5.93, and 5.63%

respectively. The second characteristic is the early onset of the CO peaks in the

low temperature regimes. At 700C, the CO peak due to steam gasification was

the first to emerge while at 900°C it was the third after peaks due to oxygen, and

oxygen and steam mixture.

Next in importance to steam in evolving high volumetric levels of CO was a

mixture of steam and oxygen oxidizers. Generally, more CO evolved at higher

temperature (900°C) compared to 800 and 700°C counterparts. Thus it can be

extrapolated from the graphs that at 900°C the CO peaks for oxygen

concentration of 2, 3, and 4% were respectively 26.45, 17.66, and 18.09%. The

respective CO peaks at 800C were 20.77, 17.43, and 11.53% whereas the

peaks at 700°C were 21.23, 12.14, and 15.50%. It is also evident that the

experiments at 2% oxygen concentration had overall highest CO peaks.

The CO/CO2 index showed the same trend as that for the CO evolution. The

index was therefore generally higher for cases at higher temperature. With the

analysis details shown in Table 13 it shows the benefits of steam gasification as it

has a multiplier factor on CO evolution compared to the without scenario.

45

Figure 11 (a): Influence of oxidizer agent on CO evolution at temperature 700°C

Figure 11 (b): CO/CO2 index as a function of oxidizer agent at temperature 700°C

CO EVOLUTION - TEMPERATURE 700 C; O2 = 2%

0

5

10

15

20

25

0 100 200 300 400 500 600

TIME, S.

CO

, V

OL

. %

N2

O2=2%

(O2-Steam)

(Steam)

CO EVOLUTION - TEMPERATURE 700 C; O2 = 3%

0

5

10

15

20

25

0 100 200 300 400 500 600

TIME, S.

CO

, V

OL

. %

N2

O2=3%

(O2-Steam)

(Steam)

CO EVOLUTION - TEMPERATURE 700 C; O2 = 4%

0

5

10

15

20

25

0 100 200 300 400 500 600

TIME, S.

CO

, V

OL

. %

N2

O2=4%

(O2-Steam)

(Steam)

CO/CO2 INDEX - TEMPERATURE 700 C; O2 = 2%

0,0

0,5

1,0

1,5

2,0

2,5

3,0

0 100 200 300 400 500 600

TIME, S.

IND

EX

N2

O2=2%

(O2-Steam)

(Steam)

CO/CO2 INDEX - TEMPERATURE 700 C; O2 = 3%

0,0

0,5

1,0

1,5

2,0

2,5

3,0

0 100 200 300 400 500 600

TIME, S.

IND

EX

N2

O2=3%

(O2-Steam)

(Steam)

CO/CO2 INDEX - TEMPERATURE 700 C; O2 = 4%

0,0

0,5

1,0

1,5

2,0

2,5

3,0

0 100 200 300 400 500 600

TIME, S.

IND

EX

N2

O2=4%

(O2-Steam)

(Steam)

46

Figure 11 (c): Influence of oxidizer agent on CO evolution at temperature 800°C

Figure 11 (d): CO/CO2 index as a function of oxidizer agent at temperature 800°C

Figure 11 (e): Influence of oxidizer agent on CO evolution at temperature 900°C

CO EVOLUTION - TEMPERATURE 800C; O2 = 2%

0

5

10

15

20

25

0 100 200 300 400 500 600

TIME, S.

CO

, V

OL

. %

N2

O2=2%

(O2-Steam)

CO EVOLUTION - TEMPERATURE 800C; O2 = 3%

0

2

4

6

8

10

12

14

16

18

20

0 100 200 300 400 500 600

TIME, S.

CO

, V

OL

. %

N2

O2=3%

(O2-Steam)

CO EVOLUTION - TEMPERATURE 800C; O2 = 4%

0

2

4

6

8

10

12

14

0 100 200 300 400 500 600

TIME, S.

CO

, V

OL

. %

N2

O2=4%

(O2-Steam)

CO/CO2 INDEX - TEMPERATURE 800 C; O2 = 2%

0,0

0,5

1,0

1,5

2,0

2,5

3,0

0 100 200 300 400 500 600

TIME, S.

IND

EX

N2

O2=2%

(O2-Steam)

CO/CO2 INDEX - TEMPERATURE 800C; O2 = 3%

0,0

0,5

1,0

1,5

2,0

2,5

0 100 200 300 400 500 600

TIME, S.

IND

EX

N2

O2=3%

(O2-Steam)

CO/CO2 INDEX - TEMPERATURE 800C; O2 = 4%

0,0

0,5

1,0

1,5

2,0

2,5

0 100 200 300 400 500 600

TIME, S.

IND

EX

N2

O2=4%

(O2-Steam)

CO EVOLUTION - TEMPERATURE 900 C; O2 = 2%

0

5

10

15

20

25

30

0 100 200 300 400 500 600

TIME, S.

CO

, V

OL

. %

N2

O2=2%

(O2-Steam)

(Steam)

CO EVOLUTION - TEMPERATURE 900 C; O2 = 3%

0

5

10

15

20

25

0 100 200 300 400 500 600

TIME, S.

CO

, V

OL

. %

N2

O2=3%

(O2-Steam)

(Steam)

CO EVOLUTION - TEMPERATURE 900 C; O2 = 4%

0

5

10

15

20

25

0 100 200 300 400 500 600

TIME, S.

CO

, V

OL

. %

N2

O2=4%

(O2-Steam)

(Steam)

47

Figure 11 (f): CO/CO2 index as a function of oxidizer agent at temperature 900°C

Figure 11: Syngas (CO/CO2) evolution profiles

CO/CO2 INDEX - TEMPERATURE 900 C; O2 = 2%

0,0

0,5

1,0

1,5

2,0

2,5

3,0

3,5

0 100 200 300 400 500 600

TIME, S.

IND

EX N2

O2=2%

(O2-Steam)

(Steam)

CO/CO2 INDEX - TEMPERATURE 900 C; O2 = 3%

0,0

0,5

1,0

1,5

2,0

2,5

3,0

3,5

0 100 200 300 400 500 600

TIME, S.IN

DE

X

EXP. 33

O2=3%

(O2-Steam)

(Steam)

CO/CO2 INDEX - TEMPERATURE 900 C; O2 = 4%

0,0

0,5

1,0

1,5

2,0

2,5

3,0

3,5

0 100 200 300 400 500 600

TIME, S.

IND

EX

N2

O2=4%

(O2-Steam)

(Steam)

48

Table 13: CO evolution characteristics summary

EXPERIMENT CONDITION AND SYNGAS COMPONENT

PEAK GAS EVOLUTION, VOL. % (WITH/WITHOUT STEAM, AND N2/STEAM ONLY)

N2 O2=2% O2=3% O2=4%

Steam Only Without With Without With Without With

900 °C

CO 5.49 4.59 26.45 5.93 17.66 5.63 18.09 23.47

CO/CO2 Ratio 1.82 1.68 3.19 1.36 2.10 1.61 1.58 2.92

800 °C

CO 3.96 2.45 20.77 4.45 17.43 4.10 11.53

CO/CO2 Ratio 1.95 0.98 2.41 2.11 2.24 2.17 1.42

700 °C

CO 2.17 0.78 21.23 3.28 12.14 3.25 15.5 21.25

CO/CO2 Ratio 1.85 1.02 2.80 1.22 1.79 2.03 0.88 2.79

CO gas ratios

RATIO N2 O2=2% O2=3% O2=4%

STEAM ONLY Without With Without With Without With

CO (900°C/800°C) 1.39 1.87 1.27 1.33 1.01 1.37 1.57

CO (900°C/700°C) 2.53 5.91 1.25 1.81 1.45 1.73 1.17 1.10

CO (With)/(Without) at 900°C 5.76 2.98 3.21

CO (With)/(Without) at 800°C

8.47 3.92 2.81

CO (With)/(Without) at 700 C 27.32 3.7 1.14

CO in Nitrogen (900°C/800°C)

1.39

CO in Nitrogen (900°C/700°C)

2.53

49

5.3.4 Syngas Heating Value

The syngas higher heating value (HHV) was obtained from the micro gas

chromatograph (GC) data, which was collected during the experimentation. The

micro GC data was collected to selected experiments that were carried at 900 °C

using oxygen, steam and, a mixture of oxygen and steam oxidizers. From the

syngas evolution profiles presented in Figure 12 (a) and (b), it can be seen that

steam gasification consistently evolved more combustible gas components of H2,

CO, and CH4. Higher hydrocarbons profile had the same characteristics. The

syngas heating value is calculated based on these combustible gas components

[68, 69]. The summary shown in Table 14 reveals that the HHV of syngas from

3% oxygen oxidizer was 14,21 MJ/nm3 while the HHV from steam, and oxygen

and steam oxidizer mixtures gasification was 11,95 MJ/nm3 and 11,18 MJ/nm3

respectively. The results of steam gasification is plausible though due to

problems of merging peaks associated with early onset of syngas components

from steam gasification, the micro GC could not capture all the peaks of H2, CO,

and CH4.

50

Figure 12 (a): Syngas composition with respect to H2, CO, and CH4 components at 900°C

Figure 12 (b): Syngas composition with respect to higher hydrocarbons components at 900°C

Figure 12: Syngas evolution profiles

H2 GAS EVOLUTION, VOL. %

0

2

4

6

8

10

0 100 200 300 400 500 600

TIME, S.

EV

OL

UT

ION

, V

OL

. %

O2=3%

Steam

O2-Steam

CO GAS EVOLUTION, VOL. %

0

5

10

15

20

0 100 200 300 400 500 600

TIME, S.

EV

OL

UT

ION

, V

OL

. %

O2=3%

Steam

O2-Steam

CH4 GAS EVOLUTION, VOL. %

0

1

2

3

4

5

6

7

8

0 100 200 300 400 500 600

TIME, S.

EV

OL

UT

ION

, V

OL

. %

O2=3%

Steam

O2-Steam

C2H4 EVOLUTION, VOL. %

0,00

0,50

1,00

1,50

2,00

0 100 200 300 400 500 600 700 800

TIME, S.

EV

OL

UT

ION

, V

OL

. %

O2=3%

Steam

O2-Steam

C2H6 EVOLUTION, VOL. %

0,00

0,05

0,10

0,15

0,20

0,25

0,30

0,35

0,40

0 100 200 300 400 500 600 700 800

TIME, S.

EV

OL

UT

ION

, V

OL

. % O2=3%

Steam

O2-Steam

C2H2 GAS EVOLUTION, VOL. %

0,00

0,10

0,20

0,30

0,40

0,50

0,60

0,70

0 100 200 300 400 500 600 700 800

TIME, S.

EV

OL

UT

ION

, V

OL

. %

O2=3%

Steam

O2-Steam

51

Table 14: Syngas composition summary

GAS AND OXIDIZER

H2 CO CH4 C2H4 C2H6 C2H2 HHV,

MJ/nm3

O2=3% 1.60 3.65 1.29 0.44 0.08 0.04 14.21

Steam 5.23 18.45 3.64 0.74 0.12 0.30 11.95

O2-Steam 5.05 15.07 4.63 1.19 0.21 0.05 11.18

5.3.5 Estimation of Coffee Husks Kinetic Parameters

Generally, the thermal decomposition of biomass is expressed by the following

relation:

)()(

kfdt

d (9)

Where is the mass loss fraction; k is a constant that obeys the Arrhenius

correlation:

)exp(RT

EAk (10)

In this Arrhenius correlation, A [/min] is the apparent frequency factor; E [kJ/mole]

is the apparent activation energy, R [kJ/kmole K] is the universal gas constant;

and T [K] is the absolute temperature.

By introducing the Arrhenius correlation, equation (9) becomes:

)()exp(

f

RT

EA

dT

d (11)

Where, [K/min] is the heating rate. The specific form of f() represents the

hypothetical model of the reaction mechanism or “model function”, which may be

represented in the form of an nth order reaction:

52

nf )1()( (12)

Following Coats and Redfern [70] the approximation to the integral form of (11)

is:

RT

E

E

RT

E

AR

T

g ]

21[ln]

)(ln[

2

(13)

and,

11

)1(1

1)1ln(

)( 1

nn

n

g n

(14)

By adopting the Coats and Redfern method, the kinetic parameters (A and E) of

the material under study can be derived from the thermo balance data. A plot of

2/)(ln[ Tg versus 1/T results in a straight line whose slope is equivalent to –E/R.

The frequency factor (A) is derived from the intercept of this line.

Integral and differential kinetic methods that bases on single heating rate

experiments are bound to errors for material involving complex reactions [71-73].

However, their adoption finds useful application in materials analysis [74-75].

Mass loss and rate of mass loss data for the experiment conducted at 900°C

nitrogen condition were adopted for estimating kinetic parameters as per the

Coats and Redfern algorithm. Figure 13 shows a plot of 2/)(ln[ Tg versus 1/T

with each line representing, respectively, results for reaction order (n) of 0, 1, 2,

and 3. From this figure it is evident that the reaction mechanism was highly

correlated to zero reaction order (R2 = 0.962). The apparent activation energy

and the frequency factor are therefore established to be 161 kJ/mol and

3.89x104/minute respectively.

53

Figure 13: ln[g(α)/T2] versus 1/T for 900°C N2 condition experiment

6. CONCLUSION

Chemical composition characteristics was established to palm waste, coffee

husks, cashew nut shells (CNS), rice husks and bran, bagasse, sisal waste,

jatropha seeds, and mango stem. Results showed that the oxygen content

ranged from 27.40 to 42.70% where as that of carbon and hydrogen ranged from

35.60 to 56.90% and 4.50 to 7.50% respectively. On the other hand, the

elemental composition of nitrogen, sulphur and chlorine was marginal. These

properties are comparable to findings from other researchers. Based on the

results of thermal degradation characteristics, it was evident that the cashew nut

shells (CNS) was the most reactive amongst the analyzed materials since during

the devolatilization stage the first derivative TG (DTG) peak due to hemicellulose

degradation reached (-5.52%/minute) compared palm stem whose first peak was

-4.81%/minute. DTG first peak for the remaining materials was indistinct.

Results from the laboratory gasification experiments that were done to the coffee

husks showed that gasification at higher temperature, 900°C, had an overall

higher gasification rate as during the inert nitrogen condition, 7% of coffee husk

remained for the case of 900°C whereas the residue mass for the gasification at

LN(g( )/T2) Vs. 1/T (900 C)

y = -0,0296x - 9,9612

R2 = 0,8976

n=3y = -0,0185x - 11,065

R2 = 0,9267

n=2

y = -0,0193x - 12,499

R2 = 0,962

n=0

y = -0,0242x - 11,996

R2 = 0,952

n=1-15,00

-14,00

-13,00

-12,00

-11,00

-10,00

-9,00

-8,00

0,0

0231

0,0

0219

0,0

0210

0,0

0202

0,0

0195

0,0

0188

0,0

0182

0,0

0176

1/T

LN

(g(

)/T

2)

54

800 and 700°C was 10 and 17% respectively. Steam injection to the biomass

under high temperature gasification evolved the highest volumetric concentration

of carbon monoxide. The CO peak evolution at 900°C steam only was 23.47 vol.

% CO whereas that at 700°C was 21.25 vol. % CO. Comparatively, the CO

peaks for cases without steam at 900°C and 2, 3, and 4% oxygen concentrations

were 4.59, 5.93, and 5.63% respectively. Syngas heating value as calculated

from its composition as captured by the micro GC reveals that the HHV of syngas

from 3% oxygen oxidizer was 14,21 MJ/nm3 while the HHV from steam, and

oxygen and steam oxidizer mixtures gasification was 11,95 MJ/nm3 and 11,18

MJ/nm3 respectively.

The reaction mechanism of coffee husks gasification was established using the

mass loss and rate of mass loss data for the experiment conducted at 900°C

nitrogen condition. The results showed that its reaction mechanism was highly

correlated to zero reaction order. The respective apparent activation energy and

the frequency factor were established to be 161 kJ/mol and 3.89x104/minute.

7 FUTURE WORK

The biomass materials under this study were successfully characterized with

respect to chemical composition, and thermal degradation. Laboratory scale

gasification also showed promising results. For the purpose of process design

prior to putting in place real gasification plants there are more detailed work to be

done. This will involve undertaking detailed simulation work for the purpose of

investigating various parameters such as moisture and inorganic materials, which

are influential in the syngas quality and performance of the HTAG process of

biomass. Parametric studies on the effect of moisture and inorganic materials

with respect to syngas gas composition, gas heating value, and cold gas

efficiency of the process need therefore be undertaken. The simulation work

need be validated by laboratory scale gasification.

55

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Supplement I

Supplement I

Coffee Husks Gasification Using High Temperature Air/Steam Agent

Lugano Wilson, Geoffrey R. John, Cuthbert F. Mhilu, Weihong Yang, and

Wlodzimierz Blasiak

Published in the Fuel Processing Technology Journal, Volume 91, Issue 10,

(2010), pp. 1330 – 1337

Royal Institute of Technology

School of Industrial Engineering and Management

Department of Material Science and Engineering

Division of Energy and Furnace Technology

SE-100 44 Stockholm

Sweden

Supplement II

Supplement II

Thermal Characterization of Tropical Biomass Feedstocks,

Lugano Wilson, Weihong Yang, Wlodzimierz Blasiak, Geoffrey R. John,

Cuthbert F. Mhilu,

Article in press with the Energy Conversion and Management Journal, (2010),

doi:10.1016/j.enconman.2010.06.058

Royal Institute of Technology

School of Industrial Engineering and Management

Department of Material Science and Engineering

Division of Energy and Furnace Technology

SE-100 44 Stockholm

Sweden