Category Archives: BIOMASS NOW — CULTIVATION AND UTILIZATION

Coupling the two observers

We consider now the coupling of observer (ll) with the estimation (a, в) provided by observer

(8) . This amounts to study the robustness of the second observer with respect to uncertainties of parameters a and в.

Proposition 5. Consider the observer (11) with (a, f) replaced by (a(-), в(:)) such that (a(t),f(t)) e [a-,a+] x [в-,в+], vt > 0,

then there exists positive numbers b>2, cT2, d2 such that for any є > 0 there exists 02 large enough to guarantee the inequalities

m(t) — m< є + b2e-c2t||£(0) — Z(0)|| (l2)

|x(t) — x(t) < є + d-2 ‘в(Є) — в + b2e-c21 ||t(0) — Z(0)|| (l3)

for any t > 0.

Proof. As for the proof of Proposition 3, we fix an initial condition of system (3) and consider the bounded set Oi = {yl (t) }t>Q. The dynamics of e = Z — Z is

e = (A + Ke2C)e + (ф(yl, Z, a, f,) — f (yl, Z, a, в))v

image074
Подпись: (15)

For 62 large enough, one has — 02/2 + /bL/ij < 0 and then, using again (18), obtains

from which we deduce the exponential convergence of the error vector e toward any arbitrary small neighbourhood of 0 provided that -2 is large enough.

The Lipschitz continuity of the map lm( ) w. r.t. Z uniformly iny Є O provides the inequality

(12) .

For the estimation of x(-), one has the inequality

x — x = m — eZ2 <e — в\Ы + в+ h — Z2

provided the estimation (13), the variable £2 being bounded. |

image076

Corollary 2. At any time t > 0, the coupled observer

f (yi, Z, a (s2), в&))/ 9l)

integrated for si Є [0, min(t, r(t))j and s2 Є [0, t],with

T(t)= yi(0) — yi (t)+ У2(0) — У2(t),

а (s2) = sat (a-, a+, la (yi (min(s2, r(t)))), jf(min(s2, r(t)))), e(s2) = sat (в-, , lp (yi (min(s2, r(t)))), £(min(s2, r(t)))),

provides the estimations

m(t) = l m(yi (t), £(t)) ^

(x(t), xd (t)) = (-в(t)^Z2(t), y2(t) + в (t)Z2 (t)) .

The convergence of the estimator is exponentially practical, provided 9i and 92 to be sufficiently large.

2. Numerical simulations

We have considered a Monod’s growth function (2) with the parameters pmax = 1 and Ks = 100 and the initial conditions s(0) = 50, x(0) = 1, xd(0) = 0. The parameters to be reconstructed have been chosen, along with a priory bounds, as follows:

parameter

к

m

value

0.2

0.2

0.1

bounds

[0.1,0.3]

[0.1,0.3]

[0.05,0.2]

Those values provide an effective growth that is reasonably fast (s(0) is about Ks/2), and a value T (see (6)) we find by numerical simulations is not too small. For the time interval 0 < t < tmax = 80, we found numerically the interval 0 < t < Tmax = T(tmax) ~ 37.22 (see Figure 1). For the first observer, we have chosen a gain parameter 9i = 3 that provides

image32,image33

a small error on the estimation of the parameters a and в at time Tmax (see Figures 2 and 3). These estimations have been used on-line by the second observer, with 82 = 2 as a choice

for the gain parameter. On Figures 4 and 5, one can see that the estimation error get small when the estimations provided by the first observer are already small. Simulations have been also conducted with additive noise on measurements y1 and y2 with a signal-to-noise

image36,image37,image38,image39,image40

ratio of 10 and a frequency of 0.1Hz (see Figures 6 and 7). In presence of a low frequency

noise (as it can be usually assumed in biological applications), one finds a good robustness of the estimations of parameters а, в and variables x and xd. Estimation of parameter m is more affected by noise. This can be explained by the structure of the equations (5): the estimation of m is related to the second derivative of both observations yi and y2, and consequently is more sensitive to noise on the observations.

3.

image41,image42

Conclusion

The extension of the Monod’s model with an additional compartment of dead cells and substrate recycling terms is no longer identifiable, considering the observations of the substrate concentration and the total biomass. Nevertheless, we have shown that the model can be written in a particular cascade form, considering two time scales. This decomposition allows to design separately two observers, and then to interconnect them in cascade. The first one works on a bounded time scale, explaining why the system is not identifiable at steady state, while the second one works on unbounded time scale. Finally, this construction provides a practical convergence of the coupled observers. Each observer has been built considering the variable high-gain technique proposed in [10] with an explicit construction of Lipschitz extensions of the dynamics, similarly to the work presented in [19]. Other choices of observers techniques could have been made and applied to this particular structure. We believe that such a decomposition might be applied to other systems of interest, that are not identifiable or observable at steady state.

Total Trucks Required — 24-h Hauling

To achieve 24-h hauling, the truck drivers will work 8-h shifts and the trucks will run continuously from 0600 Monday to 0600 Sunday, a total of 144 h/wk. The total racks processed each week are 630, equal to 315 truckloads. If a uniform delivery is assumed, the average truck unload time is,

315 trucks / 144 h = 2.2 trucks / h = 1 truck /27 min.

This productivity is well within the Rack System design goal of a 10 min unload time. As previously stated, the 24-h hauling concept envisions that the SSL crew will leave a supply of loaded racks on trailers at the SSL when they finish their 10-h workday. These racks will be hauled during the night. The next morning, the loading crew will load empty racks delivered during the night and load them during their workday.

The key variable in hauling is the truck cycle time. To calculate cycle time, for example, an average haul distance is needed. An actual database was developed for a proposed bioenergy plant location at Gretna, Virginia, USA to calculate the average haul distance.

An analysis was done for a 30-mi (48 km) radius around Gretna to identify potential production fields based on current land use determined from current aerial photography and GIS methods. It is conservatively assumed that 5% of the total land was assigned into switchgrass production. SSLs were established at 199 locations (Figure 5), and the existing road network was used to determine the travel distance from each SSL to the proposed plant location at Gretna. Some loads were hauled 2 miles (3.2 km) and some were hauled over 40 miles (64 km). A weighted ton-mi parameter was computed and found to be 25.4 miles (40.6 km). This means that, across all 199 SSLs, each ton travels an average of 25.4 miles (40.6 km) to get to the plant.

Truck cycle time is calculated using the 25.4-mile average haul distance, a 45 mph average speed, 10-min to hook/unhook trailers a SSL, and 10-min to lift full and empty racks from the trailers. Theoretical cycle time is 1.46 h. In 24 hours of operation, one truck can haul:

24 h/ (1.46 h/ load) = 16.4 loads per truck per day

Assuming that a truck fleet can average 70% of the theoretical capacity, then (0.7*16.4 =11.5 loads per truck per day can be achieved. Remember, since the trucks run continuously, a decimal number of loads can be used as the average achieved per-day of productivity.

It is not practical to use the each-haul contractor-runs-their-own-trucks assumption for 24-h hauling. The way to maximize truck fleet productivity is to have the Feedstock Manager have the control to send any truck to any SSL where a trailer with full racks is available. This greatly facilitates the hauling at both day-haul and night-haul SSLs.

Total trucks being controlled by the Feedstock Manager is:

53 loads / day required at the plant /11.5 loads per truck = 4.6 trucks (5 trucks’)

Since five SSL crews, one per SSL, are loading trailers/racks. More realistic is that eight to ten trucks will be available and some would also have responsible for bring other supplies to the biorefinery or hauling waste and other value-added products from the biorefinery.

Biomasses characterization

The organic biomasses, not-processed and processed, were supplied by the anaerobic digestion plant of the "Research Centre for Animal Production — Foundation Centre for Studies and Research" (C. R.P. A. — F. C.S. R. S. p.A., Reggio Emilia, Italy). Their main chemical characteristics of solid fractions of swine livestock manure are below reported:

Подпись: digested = 8.0 digested = 0.39% digested = 3.0% digested = 35,9%pH: not-digested = 7.0

N content (as received): not-digested = 0.47% N content (dry matter) not-digested = 2.9% C organic (dry matter): not-digested = 43,5%

In order to evaluate the organic matter stability of the two biomasses, both the digested and not-digested solid fractions of swine manure were previously analyzed by isoelectrofocusing (IEF) technique. organic matter extraction was carried out on 2 g of each biomass with 100 mL of a solution NaOH/Na4P2O7 0.1N for 48 hours at 65°C. After centrifugation and filtration, the extracts were stored at 4°C under nitrogen atmosphere. Ten millilitres of NaOH/Na4P2O7 extracts were dialysed in 6,000-8,000 Dalton membranes, lyophilised and then electrofocused in a pH range 3.5-8.0, on a polyacrylamide (acrylamide/bis-acrylamide: 37.5/1) slab gel, using 1 mL of a mixture of carrier ampholytes (Pharmacia Biotech) constituted by: 25 units of Ampholine pH 3.5-5.0; 10 units of Ampholine pH 5.0-7.0; 5 units of Ampholine pH 6.0-8.0. A prerun (2h 30′; 1200V; 21mA; 8W; 1°C) was performed and the pH gradient formed in the slab gel was checked by a specific surface electrode. The electrophoretic run (2h; 1200V; 21mA; 8W; 1°C) was carried out loading the same C amount of water-resolubilised extracts (1 mg Cx50 L-1 x sample-1). The bands obtained were stained with an aqueous solution of Basic Blue 3 (30%) for 18 h and then scanned by an Ultrascan-XL Densitometer (Amersham — Pharmacia) [10].

Decarbonylation

In general, bio-oil contains significant amounts of aldehydes and ketones c. a. 10.9% and 36.6% respectively. The presence of carbonyl groups in the structure reduces the heating value and stability of bio-oil. Therefore, selective removal of carbonyl group as carbon monoxide as given in eq. (6) is another route to make bio-oil a more favorable fuel intermediate. However, the level of understanding of decarbonylation as a route for the upgrading bio-oil is still quite limited.

RCOH ^ RH + CO (6)

According to literature, decarbonylation and decarboxylation are integral reactions in the deoxygenation of carboxylic acids and esters. At times, instead of removing CO2, removal of CO and H2O can take place in the deoxygenation step and is considered as decarbonylation. Moreover, product(s) derived by decarbonylation / decarboxylation are not significantly different from those obtained from hydrogenolysis [47].

Decarbonylation usually takes place over supported noble metal catalysts such as Pd/C at elevated temperatures [47]. A study on decarbonylation reaction has been carried out to understand the effect of the presence of Cs on zeolyte-X for the deoxygenation of methyl octanoate (MO) as well as the effect of methanol co-feeding with MO [60]. The results indicated that the decarbonylation of MO occurs at a higher rate and for extended periods over CsNaX when co-fed with methanol. The surface analysis revealed that MO strongly adsorbed on basic sites of CsNaX and Cs improved the basicity of the catalyst. It was concluded that not only the basicity of the catalyst but also the polar nature of the zeolite catalyst assisted the decarbonylation process [60].

Deoxygenation of aldehyde, ketone and carboxylic acid containing bio-oil constituents has been studied using model compounds such as acetaldehyde, acetone, butanone, and acetic
acid [61]. In this study, HZSM-5 was used as the catalyst. Acetone was considered to undergo a reaction via a mechanism as depicted in figure (12). The results indicated that acetone is less reactive than alcohols and that a higher space velocity was needed to achieve higher conversion into aromatics. A significant increase in coke formation had been observed for both aldehyde and carboxylic acids compared to alcohol.

Подпись: Aromatic parafins r. Figure 12. The reaction scheme for acetone decarbonylation on HZSM-5 (In formation was extracted from Gayubo et al. [61].)

The ongoing interest in understanding decarbonylation mechanism(s) under the umbrella of organometalic chemistry has resulted in some useful insights. For example, a theoretical and an isotope labeled experimental study of decarbonylation of benzaldehyde and phenyl acetaldehyde on rhodium surface in the presence of bidentate phosphine ligand indicate that decarbonylation mechanism consists of oxidative addition, migratory extrusion, and reductive elimination with migratory extrusion as the rate-determining step [62].

Using DFT calculations, it has been deduced that decarbonylation of acetaldehyde is assisted by Co+ as the representative transition metal ion. The study concludes that decarbonylation of acetaldehyde follows four steps, i. e., complexation, C-C activation, aldehyde H-shift and nonreactive dissociation [63].

Furan, C4H4O is one of the common oxygenated compounds in the biomass derived bio-oils that has been used to study decarbonylation. Adsorption and desorption steps of furan on pure metal surfaces during the deoxygenation reaction can be found in many publications [64-66]. Some studies on furan decarbonylation has been conducted on different single crystal metal surfaces such as Cu (110), Ag (110) and Pd(111). It was observed that furan absorbs on Cu, Ag and, under mild temperatures, on Pd. Under mild conditions, it was observed that furan desorbs on the metal surface without disrupting the molecule, but, at elevated temperatures, undergoes a deoxygenation reaction [67].

Agronomy

The beneficial effects of integrated agronomic practices like reduced tillage operations, balanced fertilization; organic recycling of mill by-products (filter mud and boiler ash); intercropping with legumes; green manuring with sunn hemp; crop residue recycling through cane trash blanketing in ratoons by green cane harvesting to sustain soil fertility and cane productivity in monoculture sugarcane based cropping system are presented and discussed. Partitioning of dry matter between plant and ratoon crops of cane grown on the estate and Outgrowers fields were quantified and also presented in this chapter.

3.1.1. Influence of agronomic practices on cane yield and cane productivity

3.1.1.1. Green manuring

There was considerable increase in cane yield (7.92 tc/ha) and cane productivity (0.62 tc/ha/m) in plant and ratoon crops due to green manuring as compared to blocks without green manuring (Table 1).

Crop cycle

Green manuring

No green manuring

Variance

Yield

tc/ha

Productivity

tc/ha/m

Yield

tc/ha

Productivity

tc/ha/m

Yield

tc/ha

Productivity

tc/ha/m

Plant

125.3

5.9

112.2

5.2

13.1

0.8

Ratoon 1

95.3

5.8

92.4

5.0

2.8

0.8

Ratoon 2

92.4

5.0

84.6

4.7

7.8

0.3

# average

104.3

5.6

96.4

5.0

7.9

0.6

Table 1. Cane yield and cane productivity variance due to green manuring

Growing sunn hemp (Crotolaria juncia) during fallow period for in-situ cultivation has been a common practice to improve soil health on the estate since 2004. Sunn hemp at 50% flowering on average produces 27.4 t/ha and 5.9 t/ha of fresh and dry weights respectively. It contains 2.5% N on oven dry basis and adds about 147kg N/ha to the soil. Of this amount, 30% (44kg N/ha) is presumed to be available to the succeeding sugarcane plant crop. "[11]" reported that N available to sugarcane ranges between 30 — 60% of total N added to soils in South Africa.

3.1.1.2. Balanced fertilization

The results indicated that application of N to plant crop at 100kg /ha, phosphorus at 160kg P2O5 /ha, potassium at 100 K2O /ha and sulphur at 40kg /ha significantly increased the cane yields by 23.3 tc/ha; 22.25 tc/ha; 12.07 tc/ha and 8.71 tc/ha respectively over no application of

N, P, K and S. Sugar yields were also improved due to N, P, K and S application by 2.91 ts/ha; 2.17 ts/ha; 2.88 ts/ha and 0.44 ts/ha respectively as compared to no application (Table 2).

Nutrient levels (kg/ha)

Attributes

Cane yield (tc/ha)

Sugar yield (ts/ha)

N levels: 0

112.68

15.69

50

124.38

17.08

100

135.98

18.60

P2O5 levels: 0

108.70

14.51

80

120.40

16.34

160

130.95

18.01

K2O levels: 0

108.06

15.58

50

124.86

17.32

100

134.13

18.46

Sulphur levels: 0

113.90

11.92

40

122.61

12.36

CD at 5%: N

10.69

1.20

P2O5

9.80

1.18

K2O

9.06

1.06

S

6.94

0.32

Table 2. Influence of N, P, K and S nutrition on cane and sugar yields

Balanced fertilizer application is very vital for crop growth. Adequate amounts of especially the major nutrients need to be supplied for proper crop growth. Excessive application of N in cane plant crop has been shown to inhibit the activity of free living N-fixing bacteria and chloride ions from Muriate of potash adversely affecting soil microbial populations "in [14]".

Appropriate species for biofuel crops

1.1. Ideal biomass crop for biofuels

There are mainly three goals to develop biomass crop for biofuels: (1) maximizing total biomass yield per year; (2) maintaining sustainability while minimizing inputs; (3) maximizing the fuel production per unit of biomass. To achieve the above goals, an ideal biomass crops should have some attributes as followings: high photosynthesis efficiency (e. g., C4 plants), long canopy (green leaf) duration, low inputs, high water-use efficiency, winter hardiness, no known pests and disease, noninvasive, and uses of existing farm equipment [2]. Based on above criteria, perennial forage crops would be ideal candidates for biofuel crops. The primary purpose for growing perennial crops for biomass production is reducing input and maintenance costs. Economically, using perennial species is more cost effective than annual ones, given the current high costs of fertilizers, pesticides (mainly herbicides) and operation fuels, and low values of lands for growing biomass crops.

Computer model of biomass logistics systems

When a series of operations are linked into a long chain of events, it is often difficult to see which operation is having the most impact on cost-effectiveness. Computer-assisted decision making tools are useful to select the most cost-effective logistics system. Recent studies [30-33] compared a number of different scenarios to determine the best unit operation options and identify bottlenecks. Mathematical programming approaches have been used to develop optimization models that are applicable to a variety of cases studies [34-37]. More recently, focus has shifted to simulation models using object-oriented programming [38] or discrete event simulation [39, 40]. The object-oriented approach [22, 41-43] simplifies scenario building, particularly related to various equipment options available for the same operation, since data pertaining to different options are stored in a standard object-oriented format.

The biomass logistics subject area can be divided into two types of modeling approaches depending on the environment encountered: stochastic or deterministic, and integer or continuous. In the areas of stochastic and deterministic environment, ISBAL and BioFeed capture the stochastic biomass logistics issues such as variability in processing as a result of weather, time, equipment breakdowns, etc. Additional work in this area can be found in [34; 40; 44-45]. In the deterministic environment, most work utilizes a geographic information system (GIS) interactively with optimization. This allows the GIS framework to work as a data management tool, which may call the optimization software directly. Most of the deterministic models are mixed-integer programs [37, 46-49]. One of the principles of designing an effective logistics system is starting with the feedstock resources distribution, and the simplest method is to utilize a GIS framework for data management.

Continuous models assume that all the land within a region is utilized for biomass production [50-52]. This approach uses average haul distances and cost. Hence, the solution obtained is difficult to implement due to lack of detail, as opposed to the solution obtained using an integer model formulation, where each production field is considered as a specific entity with specific costs, thereby resulting in precise decisions for implementation.

Characteristics of microorganisms and mechanisms of pollutants degradation in BAC filtration

2.2. Immobilization of microorganisms on the carriers

At present, most of the BAC process is based on ordinary BAC which is naturally formed during the long-term operation. Due to the complexity of biofacies on its surface, the greatest deficiency of conventional BAC is that dominant microflora are hard to be formed, which has been improved by the rapid development of modern biology technology and the technology known as immobilization biological activated carbon (IBAC). The basic principle of IBAC is screening and acclimation dominant biocommunity from nature, followed by immobilizing the community on activated carbon, to enhance the efficiency and rate of degradation. Meanwhile, dominant biocommunity should be nonpathogenic and has strong antioxidant capacity and enzyme activity which enable the growing and reproducing under poor nutrition environment. Therefore, the effect of biodegradation after activated carbon adsorption saturation is highly improved by IBAC[31-32].

Carbon and nitrogen compounds removal efficiency in continuous and sequencing flow MBBR reactors

The oxygen accessibility play a very important role in bioreactor performance. Four aeration/nonaeration time intervals were tested: 75/45, 45/45, 30/30 and 15/15 minutes. The most effective was the last interval in which oxygen deficit lasted 10 min was observed in nonaeration phase and maximum for SND process oxygen concentration (0.8 mg O2/dm3) was achieved. In these conditions for continuous flow, the maximum removal efficiencies for carbon and nitrogen compounds were equal to 98% and 85% respectively [16,11]. The optimal hydraulic retention time was equal to 12 hours.

The outflow pollutants concentrations were related mainly to biomass loading: the higher loading — the lower the removal efficiency, especially for medium and high loaded reactors (the most evident for sequencing batch reactor). This relationship was more evident for nitrogen compounds removal (figure 6) excepting total nitrogen removal in SBR.

image110

Figure 6. Relationship between pollutants’ concentration in purified sewage and biomass loading

The increase in loading up to 2.5 g COD/gdmd caused the rise of contaminants removal rate (figure 7), although it was partly related to biomass concentration decrease as a result of lading rise. The removal efficiency in SBR was related to the volumetric exchange ratio (0.2­0.5 range); the higher ratio — the lower removal efficiency.

image111

Figure 7. Relationship between pollution removal rate and biomass loading

Some authors stated the higher resistance for hydraulic overloading and more stable nitrification in hybrid reactors than in conventional activated sludge reactors [12]. These research showed that suspended/attached biomass ratio was related to the biomass organic compounds loading (figure 8). The higher biomass loading — the higher attached biomass concentration (the same — lower suspended biomass concentration). This phenomenon was

image112

So the conclusion can be drown that highly loaded reactors (especially SBR) do not need excess sludge removal, although biomass growth yield can reach values in range 0.31 — 0.50

gdm/gsub rem.

Aquaponics

Aquaponics is a sustainable food production system that combines a traditional aquaculture with hydroponics in a symbiotic environment. The water is efficiently recirculated and reused for maximum benefits through natural biological filtration and recirculation. The waste that is excreted by aquatic species or uneaten feed is naturally converted into nitrate and other beneficial nutrients in the water. Those nutrients are then absorbed by the vegetables and fruits in a "natural fertilization way".

Aquaculture species including fish, crayfish, freshwater prawns or shrimp are usually reared in tanks and the water directed into separated race-ways of hydroponics vegetables. A worldwide well-known aquaponics system was successfully developed by University of Virgin Islands (Fig 6). Typical plants raised in aquaponics include lettuce, chard, tomato, fruits such as passion fruit, strawberry, water melon, etc.; and a large variety of spices. Size of aquaculture tanks varies according aquatic species/vegetables demand and usual shapes includes round, square or rectangular tanks.

image145

(Source: UVI website www. uvi. edu )

Figure 6. Aquaponics system at University of Virgin Islands

Nowadays, BFT have been successfully applied in aquaponics. The presence of rich-biota (microorganisms of biofloc) and a variety of nutrients such as micro and macronutrients originated from un-eaten or non-digested feed seems to contribute in plant nutrition. A well — known example of biofloc and aquaponics interaction was also developed by UVI. However, the application of BFT in aquaponics needs particular attention, mainly on management of solid levels in water (for review, see [28]). High concentration of solids may cause excessive adhesion of microorganism on plants roots (biofilm), causing its damage, lowering oxygenation and poor growth. Filtering and settling devices are often needed (Fig 7).

image146

(Source: UVI website www. uvi. edu )

Figure 7. Scheme of worldwide well-known UVI Aquaponics System