DEVELOPING AN INTEGRATED AGRO-INDUSTRIAL MODEL FOR THE SUSTAINABLE PRODUCTION AND CONVERSION OF BIOMASS INTO BIOFUELS AND ADDED VALUE PRODUCTS

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1 Energy Use of Biomass: a Challenge for Machinery Manufacturers DEVELOPING AN INTEGRATED AGRO-INDUSTRIAL MODEL FOR THE SUSTAINABLE PRODUCTION AND CONVERSION OF BIOMASS INTO BIOFUELS AND ADDED VALUE PRODUCTS Paulo Seleghim Jr. University of São Paulo Brazil seleghim@sc.usp.br

2 Energy use by humankind

3 Energy use by humankind Energy and quality of life HDI IDH 1,000 0,900 saturation China Noruega EUA Canadá Islândia target 0,800 Emirados Árabes India 0,700 0,600 Brasil 41 % increase in world energy consumption 0,500 0,400 Moçambique China, India Indonesia, Brazil 0, kw kw kw kw kw power/capta/year kgoe/capita/year

4 Bioenergies will play an important role in meeting these expectations!

5 But how renewable energies will displace fossil energies?

6 Modern bioenergies constitute a disruptive technology

7 Disruptive and incremental evolution of technology Fuel for Otto cycle engines performance energy balance ecological footprint etc. 1G bioethanol 2G bioethanol gasoline robustness we are here CO 2 sequestration technologies time energy security cost competitiveness impact on food prices worldwide applicability etc. time

8 Fuel for Otto Cycle engines 2 nd generation ethanol: promising energy vector Produced from ligno-cellulosic fibers Abundant feedstock (crops or wastes) Can coexist without impacting on food prices Strategic importance for Brazil Sugarcane Oversupply of electricity from biomass residues in SP Need for automotive fuel ( ) Sugarcane sector already mature

pasture 172.3 Mha available 105.8 Mha cultivated 76.

9 Environmental planning Agricultural and livestock land occupation non-arable 492,6 Mha arable 354,8 Mha pasture Mha available Mha cultivated 76.7 Mha soya 26.6 Mha corn 14.0 Mha orange 0.9 Mha sugar cane 7.8 Mha

10 Sugarcane sector in Brazil Characteristic numbers Cultivated area: Industrial processing units: Sugarcane production: Sugar production: Ethanol production: 7.8 Mha (0.9 % territory) 432 plants nationwide 562 million tons / year 31.2 Mt/year 27 Mm 3 /year Energy matrix share: 16.4% (hydroelectricity = 13%) Electricity generation: 2.1 GW Electricity potential: 7 GW (Itaipu = 14 GW)

11 Sugarcane sector in Brazil Typical sugarcane industrial processing plant An AIBPM is a set of mathematical equations enforcing mass, energy, exergy and monetary balances governing the overall process of biomass production and transformation into added value products.

Sugarcane sector in Brazil Typical sugarcane industrial processing plant sunlight water CO 2 CO 2 2 t/h 20 40 kha

12 Sugarcane sector in Brazil Typical sugarcane industrial processing plant sunlight water CO 2 CO 2 2 t/h kha Processing 500 t/h sugar (65 t/h) ethanol (42 m 3 /h) feedstok electricity (50 MW) nutrients solids 1-10 t/h vinasse 500 m 3 /h

16 1000 t/h sugar cane diffuser

23 Typical sugarcane mill Agriculture / Industry equilibrium Plantation area Industrial equip. Economies of scale Feedstock usage Therm. efficiencies Turnover + Efficiency ~ area ~ r 2 Plantation area Field operations Soil manipulation Crop Harvesting Transportation Field ops. costs ~ area distance ~ r 3

24 Typical sugarcane mill Agriculture / Industry equilibrium $ f.o. cost ~ r 3 turnover ~r 2 viability limit frequency (%) state of São Paulo area (kha) plantation external limit (r)

25 Evolution of the current sugarcane agroindustrial model Evolving towards a full scale biorefinery Biomass depolymerization Low vol. / high value chemical products High vol. / low value liquid transportation fuels Enhancing sustainability Energy balance (currently ~9:1) Water balance (currently negative) Soil nutrients recycling (currently uneconomical)

26 An integrated agro-industrial model for the sustainable production and conversion of biomass into biofuels and added value products

27 sugar cane 500 tc/h mechanical processing straw water juice extraction bagasse 130 t/h juice cooking crystallization bagasse pre-treatment lignin boiler and turbines electricity 0-50MW sugar centrifugation molasses sugar cellulose hydrolization glycerin juice fermentation wine distillation CO 2 2 t/h vinasse 500 m 3 /h photobioreactor broth conversion transest. extraction separation biodiesel / chemicals nutrients water ethanol m 3 /h sugar 0-65 t/h

28 These propositions are not viable in current technology status

29 2 nd generation ethanol from sugarcane bagasse: A two stages process Rupture of macro structures (Pre-treatment) Cellulose and hemicellulose fermentable Lignin biochemicals or energy Depolymerization of fermentable sugars Hydrolysis cellulose lignin hemicellulose

30 2 nd generation ethanol from sugarcane bagasse: Technological alternatives Pre-treatment Ammonia or CO 2 explosion Steam explosion or hydrothermal scale? Supercritical fluids, microwave and ozone PHWS followed by explosive depressurization Cellulose and hemicellulose hydrolysis Acid or alkaline efficiency? Enzymatic

31 Pre-Treatment

32 2 nd generation ethanol from sugarcane bagasse: Pre-Treatment PHWS followed by explosive depressurization 1. Absorption of liquid water within the macroscopic structures of ligno-cellulose material 2. Solubilisation of lignin 3. Explosive expansion inducing in loco vaporization to foam the ligno-cellulosic material

33 PHWS followed by explosive depressurization A continuous pre-treatment system for 150 tsc/h pre-soaking bin pressure vessel feeding system expansion device cyclone separator

states time 100 o C 1 bar 25 o C 1 bar 100 o C

34 PHWS followed by explosive depressurization Bentch top batch reactor for operating parameter optimization studies pressure (bar) 20 bar 210 o C 210 o C temperature metastable states time 100 o C 1 bar 25 o C 1 bar 100 o C enthalpy (kj/kg) metastability even more rapid expansion

35 Hydrolysis

36 2 nd generation ethanol from sugarcane bagasse: Enzymatic hydrolysis Development of a high productivity bioreactor for enzyme production 1. Dispersion of residence times / flow management 2. Cell death / shear stress management 3. Temperature homogeneity / heat management 4. Solids deposition / stagnation zones 5. Etc conflicting objectives multiobjective optimization

37 2 nd generation ethanol from sugarcane bagasse: Enzymatic hydrolysis Design strategy X 1 X 1 geometry parameters X 2 X 4 X 3 X 2 mesh generator parameter corrections X 4 X 3 CFD solver optimization method disp. res. time optimization parameters Pareto frontier shear stress

38 Sustainability

39 Nutrients recycling: The problem Typical sugarcane industrial processing plant sunlight water CO 2 CO 2 2 t/h kha Processing 500 t/h sugar (65 t/h) ethanol (42 m 3 /h) feedstok electricity (50 MW) nutrients 1 ton NPK / 499 ton water solids 1-10 t/h vinasse 500 m 3 /h 975 kg/h of NPK

40 Nutrients recycling: The problem Chemical composition of vinasse molasses molasses molasse and sc juice sc juice

41 Nutrients recycling: The problem

42 Nutrients recycling: The problem Problems related to vinasse application 1. Highly uneconomical operation 2. Can strongly impact soil, groundwater, or nearby watercourses or lakes 3. It is necessary to correct vinasse acidity 4. Biodigest organic matter to reduce impacts on soil microorganisms 5. Modify soil mechanical properties, particularly permeability, favoring soil compaction.

ethanol Prospective configuration: Chlorella vulgaris

43 Nutrients recycling: The solution (?) Cultivation of microalgae from CO 2 and vinasse juice ethanol Prospective configuration: Chlorella vulgaris (high photosynthetic efficiency ~ 8%) Open raceway pond (cheap and simple operation) 43

44 Nutrients recycling: The solution (?) Preliminary design parameters (C.vulgaris): Oh-Hama, T.; Miyachi, S. In Microalgal Biotechnology; Borowitzka, M. A.; Borowitzka, L. J., Eds.; Cambridge University Press: Cambridge, 1988.

45 vinasse 500 m 3 /h kg/h 43.7 kg/h kg/h 46.0x10-3 kg N/kg µa 9.9x10-3 kg P/kg µa 8.2 x10-3 kg K/kg µa 3043 kg µa/h 4414 kg µa/h kg µa/h 24.75x10-3 kg µa/m 2 /24h 24.75x10-3 kg µa/m 2 /24h 24.75x10-3 kg µa/m 2 /24h ~300 ha ~400 ha ~7400 ha Not cost effective in general Prohibitive earthmoving costs Critical contamination control Critical temperature control Etc.

46 Nutrients recycling: The solution! Obtain at least a ten-fold increase in algal productivity (kg/m 2 /day) Factors afecting algal production Inadequate irradiance levels and cycles Deficient photossynthetic O 2 removal Depletion of CO 2 Bad temperature control Contamination All these factors are interdependent and must be optimized simultaneously!

47 The coupled Bio-Photo-Fluidynamic problem

48 Bio / photo / Fluidynamic coupled problem Cell photosynthesis rate x irradiance µ= K 1 µ max I + I+ K 2 I 2 µ = Growth rate (g/s) I = Irradiance (W/m 2 ) K = Species constants µ 1+2 max k 1 K 2 Photoinhibition Activation k1/ K 2

49 Bio / photo / Fluidynamic coupled problem Light attenuation in function of phase fractions γ = attenuation coefficient (m -1 ) di = γ I dx I = Irradiance (W/m 2 x = distance from light source (m) Constant γ in single phase flow I(x) = I e 0 γx Variable γ in three phase flow I(x) = I 0 e γ ww x e ( γ bw γ ww )K bw (x) e ( γ pw γ ww )K pw (x)

50 Bio / photo / Fluidynamic coupled problem Light attenuation in function of phase fractions α ww +αbw+αpw = 1 α ww = water phase fraction α bw = CO 2 void fraction α pw = microalgae phase fraction γ eq = 1 αbw αpw) Equivalent attenuation model ( γ +α γ +α γ ww bw bw pw pw γ ww = attenuation of water γ bw = attenuation of CO 2 (bubbly flow) γ pw = attenuation of microalgae (turbidity)

51 Bio / photo / Fluidynamic coupled problem Light attenuation in function of phase fractions K []w(x) α []wdx = x 0 K pw (x) = CO 2 cumulative void fraction K bw (x) = microalgae cumulative phase fraction Example: phase fractions distributions known a priori normalized values α bw (x) =α bw,0 x α + x 0 bw e x 1 x 0 α pw (x) =α pw,0 x α + x 0 pw e x 1 x 0 I(x)

52 Bio / photo / Fluidynamic coupled problem Resulting productivity distribution µ (x) = K 1 µ max I(x) + I(x) + K 2 I(x) normalized values 0.1 µ ( x) excessive illumination adequate illumination insufficient illumination x 1

53 Bio / photo / Fluidynamic coupled problem Illumination/darkness cycles I light source excessive illumination adequate illumination insufficient illumination Recirculation caused by CO 2 injection Irradiance in function of the distance from light source x

54 Thank You All! Paulo Seleghim Jr.

55 Typical sugarcane mill Impact of field related technologies $ f.o. cost ~ r 3 turnover ~r 2 increased turnover productivity, mechanization harvesting, logistics soil preparation, fertilizers, irrigation increased plantation area r

56 Typical sugarcane mill Impact of industrial processing technologies $ f.o. cost ~ r 3 turnover ~r 2 increased turnover new conversion routes, enhanced thermodynamic efficiencies, feedstock usage, economies of scale, biochemical conversion increased plantation area r

Energy use by humankind Power to sustain

57 Energy use by humankind Power to sustain our life processes 2500 cal/day 120 W 2000 W 90 W Power to support our lifestyle 500 EJ/year 7 billion people 2300 W industry + agriculture (28% = ) transportation sector (27% ) services + residences (36% )

58 Energy use by humankind With 120W we survive, but we live with 2300W

59 Disruptive and incremental evolution of technology Digital storage media performance storage capacity dimensions freq. band etc. Disruptive technology time robustness durability cost interchangeability etc. New technology is subjected to experimentation, refinement, and increasingly realistic testing Evolutive optimization time

The Brazilian Biofuels Experience. Flavio Castelar Executive Director APLA Brasil. GBEP Bioenergy Week Mozambique

The Brazilian Biofuels Experience Flavio Castelar Executive Director APLA Brasil GBEP Bioenergy Week Mozambique The future of fuel? Henry Ford - 1906 Henry Ford blend and Gasoline to start up the first