As previously discussed in section 5.6, greenhouse gas emissions that are attributed to the Brighton municipality’s waste stream are a result of the de- composition of waste organic materials in landfill. In assessing the potential for Brighton Council to reduce its emission profile by means of a waste to energy facility, it is therefore important to analyse the flow of organic waste in Council’s waste transfer station. Moreover, it is important to quantify the organic waste that is separable or available for processing through a waste to energy facility. This fraction of the waste stream is primarily large green waste that could be sep- arated out prior to mixing with other, inorganic components, at the waste transfer station.
To this end, a survey was conducted by Council staff at the transfer station; refer to table K.1. Vehicles of different types carting green waste on to the site were recorded along with the percentage of green waste in their load. This survey was conducted over a period of 199 days between the fourteenth of August and the first of March, 2010. This period included a range of time over winter spring and summer, representing a good mix of non-growing and fast growing garden seasons. It can thus be assumed to be representative of an entire year.
well as the conversion factors of volume to mass. This enabled the flow rate of separable green waste through the site to be estimated, thus providing input into the model.
The following values were used:
Average volume UTE: 2 m3
Average volume TRAILER: 3 m3
Average volume CAR BOOT: 0.5 m3
Average bulk density: 240 kg/m3
Where the average bulk density is taken from Department of Climate Change [2008a]. In summary of the survey, the following results are obtained:
Total Tonnage: 678 tonnes
Aproximate Annual Tonnage: 1243 tonnes
Aproximate Monthly Tonnage: 104 tonnes
Period of Survey: 199 days
WTS hours open per month: 128 hrs
Average rate of green waste: 0.81 tonnes/hour (WTS open)
0.225 kg/sec
Therefore a value is given for the available flow rate of separable green waste from the waste transfer station (WTS) in terms of the opening hours of the waste transfer station. This is an appropriate unit since if Council was to pursue such an option, it would likely be operated at the waste transfer station and thus its operating hours would also be that of the site.
It is noted that there is a minor seasonal cycle evident in the green waste stream however there is space available for stockpiling the waste in order for the system to operate with an average flow rate, as discussed above.
Chapter 13
Technical Design
13.1
Pyrolysis Product Analysis
Accurate modeling of a biomass gasification system requires some under- standing of the chemical changes that occur to the biomass during the process. Therefore the methodology must go beyond the standard energy and mass balance approach.
Pyrolysation is the process that occurs as an organic material is heated in an environment void of oxygen. Under normal, oxygen rich conditions any type of organic material will eventually combust. However, with a lack of oxygen, combustion can not occur. Rather, the material is cracked to produce simpler compounds and elements that generally maintain their combustibility.
The composition of products that result from pyrolysation and gasification can be complex and extremely difficult to predict through analytic methods. It will be a result of a number of conditions including the precise composition, structure and homogeneity of the organic material prior to pyrolysation; the precise rate of temperature increase and final temperature that the biomass is held at; the pressure of the environment; the chemical composition of the environment and so on.
that has been diverted from landfill. It is thus extremely complex and unpre- dictable in terms of its composition. It is also likely to be inconsistent and non- uniform. Accurate prediction of its product following pyrolysation and gasification is therefore not achievable through theoretical means.
In order to overcome the issue outlined above, a review of the literature was undertaken and an approach identified that is applicable to the current work. Various studies have been conducted that employ the use of experimentation to determine the composition of products following pyrolysation and gasification of biomass. Results of these studies have been directly considered in the present model.
Olazar et al. [2001] analyse the composition of product states at different temperatures during the pyrolysation phase. The study considered only temper-
atures between 400◦C and 500◦C however for the purposes of this study; these
results have been extrapolated out to 600◦C in order to approximate the point at
which the pyrolysation phase transitions to pure gasification. This also allows us to assess the minimum temperature at which we are likely to see no liquids present in the product stream.
The study from Olazar et al. [2001] was based on a similar experimental setup to that proposed in the present model however the fluidizing atmosphere was nitrogen as opposed to steam and thus results must be considered a first approximation only. Further to this, Olazar et al. [2001] used a sawdust biomass which maybe significantly finer than the green waste feed stock considered in this design. Importantly however, it is likely to be of similar composition.
Table 13.1 and Figure 13.1 present findings from Olazar et al. [2001] and the extrapolated results.
In terms of the present study, the key learning from Olazar et al. [2001] was
that temperatures above 600◦C are likely to yield only gas. This then becomes
the critical temperature since it is important for the system to entirely avoid tar
Liquid Gas Char Total
T(◦C) Yield(wt%) Yield(wt%) Yield(wt%) Yield(wt%)
Study Results 400 61.5 15 22.5 99.0 420 64 15 20.5 99.5 440 66 17 17.5 100.5 460 66.5 19 14 99.5 480 60 28.5 11 99.5 500 56 35 9 100.0 Extrapolated 520 47.3 45.7 7.8 100.8 540 36.7 57.7 6.5 100.9 560 23.7 71.3 5.3 100.4 580 8.4 86.3 4.4 99.1 600 0.0 102.8 3.6 106.4
Table 13.1: Composition with Temperature Variation [Olazar et al., 2001]
90 100
Liquid Gas Char
80 90
Liquid Gas Char
60 70 40 50 y ie ld ( % w e ig h t) 20 30 y ie ld ( % w e ig h t) 0 10 20 0 400 450 500 550 600 Temperature (degC)
the time of residence varied in order to vary the output of ungasified char and gas. Based on this concept, the model may be balanced such that the ungasified char stream is sufficient but no more than is required by the combustion bed for use as a heating fuel. In this way the gas stream maybe maximized and thus, the system optimised.
Further to this, Fox [1988] notes that under wood combustion conditions,
volatiles evolve from the wood at between 250◦C and 600◦C. Beyond 600◦C all of
the volatiles burn off. Therefore it follows that if combustion bed temperatures
are maintained above 600◦C, exhaust smoke will be minimised and fouling of the
equipment due to tar build up will be prevented.
Ahmed and Gupta [2009] discusses the characteristics of gaseous yield from steam gasification, also based on experimental results. Data is provided in terms of the energy content of the gas when produced under steam gasification conditions,
at temperatures between 600◦C and 1000◦C. This also is directly applicable to the
present study and provides input into the model in its assessment of the quality of syngas under different temperature conditions.
Table 13.2 and Figure 13.2 present findings from Ahmed and Gupta [2009].
Temperature Energy (◦C) (KJ/kg Syngas) 600 1550 700 6500 800 9118 900 10777 1000 11180
Table 13.2: Energy Content of Gaseous Yield from Steam Gasification [Ahmed and Gupta, 2009]
4000 6000 8000 10000 12000 Ener gy (kJ/kg ) 0 2000 500 600 700 800 900 1000 1100 Temp (°C)
Figure 13.2: Syngas Energy Yield with Temperature Variation [Ahmed and Gupta, 2009]
ature, to a limiting value near 1000◦C. This apparent increase in energy density is
a result of a varied composition and proportion of gas type. That is, under gasifi- cation conditions, the biomass is cracked to produce some combination of carbon monoxide, hydrogen and other constituents. The energy density of each of these constituents is different and thus by varying the proportions, the combined energy density is changed. Ahmed and Gupta [2009] show that this change in proportions occurs relative to the temperature in which the biomass is cracked. Intuitively, this leads to the conclusion that the model will be optimised by maximising the temperature and thus producing the best quality syngas. Given the design of the overall system however, the drawback to this thinking is that greater amounts of combustion fuel will be required to produce the higher temperatures, and thus less syngas is produced. There is therefore a trade off between quantity and quality of the syngas that maybe produced. A later section of this chapter discusses the optimisation of the system based on results from Ahmed and Gupta [2009], thus
providing clarity to this tradeoff.
For reference, Basu [2010] suggests that the optimal temperature range for
fluidized bed gasification of biomass is 700◦C and 900◦C.