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Patent Searching and Data

Document Type and Number:
WIPO Patent Application WO/2012/109490
Kind Code:
A waste stream collection, processing and gasification system (700) obtains waste from a variety of sources (702). Waste from the various sources (702) is transported via carts (704) to a collection station. At the collection station, various measurements and observations (706) may be made on a cart-by-cart basis. These measurements and observations may be recorded on a processor (708). This information is used by the processor (708) to develop statistical information regarding the waste stream or a waste stream model (710).

Application Number:
Publication Date:
August 16, 2012
Filing Date:
February 09, 2012
Export Citation:
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International Classes:
B09B3/00; C10L3/00; F23G5/027
Foreign References:
Attorney, Agent or Firm:
MARSH FISCHMANN & BREYFOGLE LLP (8055 E. Tuffs Ave. Suite 45, Denver Colorado, US)
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What is claimed:

1 . A method for use in a system for converting waste from a content varying, heterogeneous waste stream into useable energy, said system involving processing of said waste stream to produce a fuel and processing of said feedstock fuel to generate energy said method comprising the steps of:

A) monitoring said waste stream over time to develop a model of a composition of the waste stream with respect to at least one of time and source locations of the waste stream; and

B) responsive to said step of monitoring, controlling one or more of the following to optimize production of said useable energy:

1 ) inputs into said waste stream;

2) a mixture of components of said waste stream used to produce said feedstock fuel; and

3) parameter values for processing said feedstock fuel to generate energy.

2. A method as set forth in Claim 1 , wherein said step of monitoring comprises receiving successive waste loads making up said waste stream and recording information on an load-by-load basis.

3. A method as set forth in Claim 2, wherein said information includes one of a source location, a time of arrival, a weight or volume, and a composition for each load.

4. A method as set forth in Claim 1 , wherein said step of monitoring comprises developing a model for variation of said waste stream as a function of time of day.

5. A method as set forth in Claim 1 , wherein said step of monitoring comprises developing a model for variation of said waste stream as a function of day or date.

6. A method as set forth in Claim 1 , wherein said waste stream is associated with one or more outlets for dispensing materials to consumers, and said step of controlling comprises selecting materials for dispensing at said outlets.

7. A method as set forth in Claim 1 , wherein said step of controlling comprises selectively importing waste from one or more outside sources for combination with a locally generated waste stream.

8. A method as set forth in Claim 1 , wherein said step of controlling comprises segregating portions of said waste stream have different compositions, into separate hoppers, and combining waste from said separate hoppers in selected proportions to form a mixture for processing to produce said feedstock fuel.

9. A method as set forth in Claim 8, wherein said step of controlling comprises supplementing said mixture with additional materials to improve a quality of said feedstock fuel.

10. A method as set forth in Claim 1 , wherein said step of controlling comprises varying a drying process for drying said feedstock fuel prior to introducing the feedstock fuel into a reactor.

1 1 . A method as set forth in Claim 10, wherein said step of controlling comprises selecting one of a temperature, an amount of air introduced and a drying time of said drying process.

12. A method as set forth in Claim 1 , wherein said step of controlling comprises selecting a type of reactor process for processing said feedstock fuel, said type being selected from a set of processing types including pryrolysis, pryrolysis followed by gasification, single stage gasification and multi-stage gasification.

13. A method as set forth in Claim 1 , wherein said step of controlling comprises tuning a reactor parameter including one of: a temperature of material entering the reactor; a number, location or direction of gas nozzles for introducing oxygen into the reactor; an air temperature of air used in the reactor; a pressure of the reactor; and a size of a reactor core or restriction therein.

14. A method as set forth in Claim 1 , wherein said step of controlling comprises tracking an output from said reactor and changing at least one of said parameter values based on said tracking.

15. A method as set forth in Claim 14, wherein the reduction zone inside of the reactor is controlled mechanically. The use of the controlled reduction zone could also be utilized to effectively reduce material clinking in reactor and assist in moving material within the reactor.

16. A method as set forth in Claim 14, wherein tracked output comprises one of: an amount or composition of syngas generated; an amount of effluent including volatiles or particulate matter; an amount or composition of ash generated; and a gas temperature on exit from the reactor.

17. A method as set forth in Claim 1 , wherein step of controlling comprises one of selectively compacting a portion of said waste stream, selectively reintroducing syngas back into the reactor; using exhaust or syngas to preheat material before introduction into the reactor, and tracking energy usage or production of the reactor.

18. A method as set forth in Claim 1 , further comprising providing a plurality of reactors for processing said waste stream wherein each reactor can be independently operated using selected processing parameters.

19. An apparatus for use in converting waste from a content varying, heterogeneous waste stream into useable energy, said converting involving processing of said waste stream to produce a fuel and processing of said feedstock fuel to generate energy said apparatus comprising:

A) waste stream model storage for storing information regarding a model of a composition of the waste stream with respect to at least one of time and source locations of the waste stream; and

B) a controller for using said waste stream model information for controlling one or more of the following to optimize production of said useable energy:

1 ) inputs into said waste stream;

2) a mixture of components of said waste stream used to produce said feedstock fuel; and 3) parameter values for processing said feedstock fuel to generate energy.

20. An apparatus as set forth in Claim 19, wherein said information includes one of a source location, a time of arrival, a weight or volume, and a composition for each of successive loads making up said waste stream.

21 . An apparatus as set forth in Claim 19, wherein said controller is operative for providing information for varying a drying process for drying said feedstock fuel prior to introducing the feedstock fuel into a reactor.

22. An apparatus as set forth in Claim 19, wherein said controller is operative for providing information regarding one of a temperature, an amount of air introduced and a drying time of said drying process.

23. An apparatus as set forth in Claim 19, wherein said step of controlling comprises tuning a reactor parameter including one of: a temperature of material entering the reactor; a number, location or direction of gas nozzles for introducing oxygen into the reactor; an air temperature of air used in the reactor; a pressure of the reactor; and an adjustable size of a reactor core or restriction therein.

Systems and Methods for Waste Collection, Processing, and Optimization, Biomass Fuel Generation, and Gasification

Cross-Referenced To Related Application

This application which claims priority to U.S. Provisional Application No. 061/441 , 198, entitled, "Systems and Methods for Waste Collection, Processing, and Optimization, Biomass Fuel Generation, and Gasification," filed on February 9, 201 1 , the contents of which are incorporated herein as if set forth in full.

Field of the Invention

The present invention relates generally to generating energy from biomass feedstocks and, in particular, to optimizing the processes for engineering fuel and generating syngas from a waste stream. The invention has particular advantages for effectively and fully processing waste streams that vary in content and volume over time.


Sources of fossil fuels are becoming increasingly scarce and costly, causing the energy and petrochemical industries to actively search for cost effective engineered fuel feedstock alternatives to fossil fuels. Today, engineered biomass feedstocks are increasingly supplementing and/or replacing fossil fuels for use in combustion processes for the production of energy and gasification processes for generating syngas used in the downstream production of chemicals and liquid fuels. Syngas generation has been quite successful in environments where the feedstock is highly consistent in volume and composition, e.g., woodchips or sewage processing. However, many challenges remain with respect to environments where the feedstock is highly variable in composition (e.g., a heterogeneous waste stream) and where volumes and compositions vary with respect to time of day or seasonally. Summary

The present invention involves a system and methodology (a "utility") that may be used to convert waste to energy. More specifically, the inventors have recognized the need for a utility for analyzing heterogeneous waste streams in a manner that informs the production of a predictable and stable biomass feedstock for use in a number of downstream processes such as, for example, a gasification process. In this regard, the inventors have developed tools for use in examining, optimizing, and controlling inputs to waste streams so as to engineer fully or substantially utilizable waste streams that may be blended to generate a feedstock having desired material properties (e.g., composition, thermodynamic properties, moisture content, density, etc.). These tools allow a viable feedstock to be produced on a year-round basis despite a number of fluctuating variables relevant to the waste streams themselves (e.g., the amount of waste collected, the types of waste collected) as well as environmental variables that impact the downstream gasification of the feedstock (e.g., temperature, humidity).

Beyond producing an optimized feedstock from varying and heterogeneous waste streams, the inventors have identified a number of design parameters that are relevant to one or more gasification reactors and/or technologies that combine gasification with fast pyrolysis for use in generating syngas from the engineered feedstock. These parameters are key to the development of waste-to-energy systems that can meet the needs of both large and small institutions/facilities in consistently producing energy from on-site waste on a year-round basis.

Notably, while the disclosure below describes several implementations of the waste-to-energy utility described above in the context of a zoo, animal management, or animal containment environment, it should be understood that the contemplated waste-to-energy utility is not limited to zoological or animal management environments and may be used to convert waste to energy within any appropriate environment, including any facility that generates waste and collects it in multiple locations, communities in which homes develop independent and unique waste streams, facilities in which waste is managed by staff/contractors, facilities interested in minimizing waste handling costs, and/or facilities with waste collection, disposal, and/or energy operational concerns. For instance, embodiments of the waste-to- energy utility described below may be implemented within or in relation to theme or amusement parks, convention centers, outdoor arenas used for sporting and other events, concert venues, and much larger environments such as municipalities/communities.

In the particular implementation described below, the processing can be optimized with respect to variations in the waste stream so as to provide a holistically optimized solution. This may involve analyzing the waste stream, influencing the materials that are introduced into the waste stream, supplementing the waste stream with outside waste or additives, mixing waste stream components to generate a desirable fuel stock, optimizing processing of waste materials to generate the fuel stock, optimizing reactor design and operation for generating syngas, utilizing multiple reactors to address fuel stock variation and scalability, and reconfiguring reactors and processing to optimize performance, efficiency and effluent/ash control. In this manner, a highly flexible process is enabled for handling varying volumes (including smaller facilities) and compositions including, for example, combinations of refuse derived solid (RDF) waste and animal waste.

Brief Description Of The Drawings

For a more complete understanding of the present invention and further advantages thereof reference is now made to the following Detailed Description, taken in conjunction with the drawings in which:

FIG. 1 is a chart showing data and methodology for tracking and identifying peak waste delivery times;

FIG. 2 is a chart showing standard deviation of carts within a timeframe;

FIG. 3 is a graph showing a delivery time distribution;

FIG. 4 is a graph showing the different types of waste generated by a facility;

FIG. 5 shows an exemplary screenshot of a waste analysis data table;

FIG. 6 is a chart showing a simulation of a gasification process in accordance with the present invention; and

FIG. 7 illustrates a waste stream collection, processing and gasification system in accordance with the present invention. Detailed Description

In the following description, the invention is set forth in the exemplary environment of processing all or substantially all of the waste from a zoo. This is a particularly challenging environment and serves to illustrate important aspects of the invention. However, it will be understood that the invention is not limited to this environment, but rather extends to the full scope of the claims set forth below.

A zoo generates a waste stream that is highly variable in volume and in composition. The waste stream includes, among other things, concessions solid waste, office waste and animal waste. The concessions waste and office waste may include plastic, paper, metals, and a wide variety of other materials. The animal waste also varies in important ways. For example, the waste from herbivores may contain a more consistent and readily know biomass for downstream processing. The waste stream arrives from multiple sources, typically in transportable carts, and varies depending on source location, time of day, season, attendance, special events, and other factors. This environment is thus very different from many conventional syngas environments, but much like many other waste management environments (though perhaps an extreme example) where gasification has generally not been attempted.

A fundamental recognition of the present invention is that the system is best optimized not by reference to static assumptions but, rather, based on understanding of variations of the waste stream over time and through rigorous data collection and analyses. Through this understanding of existing processes fuel can be generated from the waste stream, and produce syngas that can be optimized with respect to such variations. This involves 1 ) monitoring and modeling the waste stream volume and composition over time, 2) selective waste processing/assessments to obtain stock from which to produce fuel 3) selective processing of the stock, including drying and pelletizing, to produce an engineered fuel, and 4) controlling gasification and generator operation for optimal results. Each of these aspects is discussed in turn below. It will be appreciated that the utility of the invention lies largely in defining an approach that allows for optimizing processing for a variety of waste stream volumes and compositions, not in identifying the optimal parameter values for any specific, momentary waste stream volume and composition. Waste Data Collection:

A methodology has been developed to track the zoo's waste stream. Key features of this are:

• Every building/exhibit/area has a waste collection bin that is labeled and the waste identified as being from that location.

• Weight is tracked daily from each building/exhibit/area.

• Time of delivery is tracked to identify statistical time of day.

• Weights of most typical materials are stored in a database and are used in a combination of visual assessments of waste containers to approximate weights.

• Data is stored and sorted in a database to develop a statistical assessment of year's worth of data.

Using this data and the developed methodology for tracking, we can provide graphically the disposal time and weight variance. FIG. 1 is a graph of total material delivery during each month. This data provides information about how the material weights delivered vary over time during each month to assist in assessing the consistency of material quantities delivered yearly. This chart identifies peak delivery times during the day for materials and shows that the majority of materials are delivered in the morning and that the morning also contains the most inconsistency. Further evaluation shows seasonal shifting due to weather events.

Evaluating this data further on a waste cart location basis can define a delivery schedule and weight value associated with a cart to statistically develop a model for waste carts based upon historical data. In other words, developing theoretical delivery times and weights for carts moving forward. FIG. 2 is a chart showing that a concession cart will most likely show up at 7:30 am, but can show up between 7am and 8am.

Expanding upon the delivery time further, we may view every waste cart delivery vs. time and see which carts can vary and which ones are easily determined. The standard deviation of these carts within a timeframe (maximum, minimum, and average) can be seen in the graph of FIG. 3. This data is then used to define the statistical delivery parameters for the simulation model.

It can be seen from this graph that the 100 numbered cart (concessions, carnivore, and operations) waste is typically delivered before 1 1 am, which assisted us in developing a run rule for the simulation whereby material in the morning will be stored or mixed separately/selectively from the 200 carts, which are the herbivores and contain a more consistent biomass material for downstream processing.

Because an institution's waste generation profile/weight may fluctuate with attendance, an evaluation of the effects of attendance on waste generated and the types of waste generated is helpful. By expressing large data sets into a graph, it can be shown how types of waste may fluctuate and to what degree they are expressed in the waste stream.

FIG. 4 is a graph of waste generated: for reference the different types of waste are separately shown as segments of each bar: bottom= concessions waste; middle = Animal, Concessions, and Operations; top = Herbivore/Compost. It has been discovered that attendance did affect the type of waste generated, but because of material residence time in waste containers, only when attendance was high consistently (8000+) for more than three days would it affect the waste profile significantly. This is somewhat predictable because only after two days of high attendance would the material mixture have to be evaluated closely or adjusted.

By statistically sampling the data moving forward into a simulation, continuous seasonal profiling can be predictive and assist with making future adjustments to material processing and energy conversion.

The use of this data collection methodology may be placed anywhere that has any of the following:

• A facility that generates waste and collects it in multiple locations.

• Community waste streams where homes develop independent unique waste streams.

• Waste that is managed by staff or outside contractors.

• An interest in tracking their waste stream more closely. • A site that currently has waste collection, disposal, or energy operational concerns/issues.

• A facility who would like to minimize waste handling costs.

• An environmental leader who wants to tackle waste sorting/handling/disposal effectiveness.

Waste data collection may be expanded to collect:

• More detailed information per each waste container including weight of material, moisture content, and % weight of each constituent making up each individual waste container.

• Combining any waste collection with the existing statistical model, approximations may be derived for future operations for many facilities.

• Specific known heavy use Products (such as event based cups, containers, etc.) may be tracked based upon sales to assist in balancing out the waste stream from facility "cradle" to "fuel source".

o This may also be used to test how reusable products are treated by guests/visitors/members.

• Waste containers may each be fabricated with a built-in means to collect material weight and even photograph contents to remotely communicate data to a "hub" for statistical modeling.

o This may be expanded to allow for staff to identify items of interest, such as: batteries, electronic waste, metals, large quantities of glass, etc.

o This may also relay information to waste management crew to pickup containers that may be filling quickly do to demand.

o This data may also be used to "test" the best areas, signage, designs, sorting, etc. for proper waste handling and to eliminate contamination and pollution.

o Data may be used to accurately create a facility waste-stream environmental footprint.

o Informative signage may be developed that have statements like:

"Most (88.5%) of our guests have chosen to recycle cans" and "detailed data collected from each waste container to reduce OUR impact", etc...

• Pick-up routes may be modeled for fuel, energy, and time to provide waste management - some modeling has been done for this already.

• Re-evaluation of current methodology for delivery of waste to a secondary location (typical of offices, buildings with floors, etc.) may be performed and data used to compare alternative or more efficient or appropriate options.

Waste Processing:

Upon the arrival of material, we have developed a simulation model that is capable of tracking this material as it changes state/form in processing equipment and mixes. Data tracked/collected may include the following:

• Calculations for mixing and development of formula for mixing based upon stratification scientific journals and stated equipment operations from manufacturer.

• Separation and storage of waste streams through tracking material as it is processed and storing material in one of three feed hoppers.

• Using dumpster surveys previously performed to track and appropriately mix materials throughout the processing. Source component materials are tracked and may include: office paper, paperboard, cardboard, HDPE/LDPE, PETE, and PLA plastics, woodchips, yard trimmings, animal waste, rice straw, alfalfa stems, glass, aluminum, metals, and potential heavy metals. Additional components can be added/removed when necessary for different waste streams. In addition, fill of dumpsters and moisture content approximations may be made. FIG. 5 shows an exemplary screenshot of the resulting data table after data is collected, sorted and a max, min, and mode are identified:

• Each one of the source materials has specific laboratory data associated with it including but not limited to: btu/lb (LHV or HHV), ash analyses, chemical make-up (typically ultimate and/or proximate analysis performed) which allows for the capability to "dial" in the simulation to ANY waste stream containing these or other available component data as well as any laboratory data that we have collected.

• Changing material properties during processing: density, volume, moisture content, BTU value, chemical constituents that could cause problems like: heavy metals, materials containing chlorides, and materials that give off VOC's at lower temperatures.

• Tracking the separation of liquids or particulate matter for materials during processing. This can be valuable to assign liquid properties to incoming materials and how material type affects losses/filtration/particulates generated/volatiles created at temperatures/key liquid properties such as: BOD, COD, TSS, Alkalinity, and PH.

• Track all energy use based upon duration of operation, kW load from equipment, federates, and/or difficulty to process materials.

• Material is tracked per cubic foot (or whatever the user denotes as being necessary) and the simulation model may track each "chunk" of material even as it is split and shared between multiple chunks along the way.

• Using an AutoCAD file as a background, two-dimensional equipment may be displayed with theoretical material in final locations and even transport the material proper: distances, heights, depths, etc.

• A process flow chart is the backbone of this operation and the simulation may be run in this form to see the logic behind what is going on in the actual material: mixing, delivery, errors, machine failures, etc.

• The simulation model may easily accept outside materials from additional vendors and describe quantities and delivery schedules with them.

• Simulation may replace any piece of equipment at anytime via a description/set-up and place it anywhere in the line and easily process material to test the following:

o Throughput.

o Reduction.

o Moisture removal.

o Maintenance schedule.

o Particulate matter generation.

o Electrical usage. o Thermal usage,

o Feedrate.

o Holding time.

This simulation is a powerful tool that when used in conjunction with operational data can provide a means to test equipment operation, performance, energy balances, mixing, breakdowns, schedule maintenance, etc to any facility. Examples of how this simulation may assist plant operations include:

• Data tracking and comparing equipment stated parameters (energy usage, throughput, mixing, moisture reduction, material make-up) with actual operational parameters.

• Predicting equipment performance prior to material being processed.

• Developing "run-time" rules for unanticipated breakdowns, jams, bridging, etc. that provide the operator with a procedure to follow to get the system operational more rapidly.

• Modeling equipment for other facilities to provide them with a cost, mixing, and operational assessment for a potential future facility.

• Adding more detailed information that may pertain to emissions, waste, etc. parameters to be able to provide real-time along with future anticipated solid, air, and water emissions to environmental agencies.

• Use simulation to test potential replacement/new equipment prior to installation to verify how it could affect future operations.

• Use simulation in conjunction with feedback from equipment controls system and actual performance data to predict and improve future performance.

Simulation of Drying:

We have realized many options that are available to remove moisture from material for further processing. The downstream technology that thermally converts the solid biomass defines the moisture content necessary for efficient and effective conversion of the biomass. Using existing drying curves based upon basic temperature, air introduced, moisture removed, fluid used, etc., we have recognized that different component materials will respond differently. Approximating material response is important to understand associated energy balances and includes the following:

• Capability to develop drying curves and collect data based upon many materials for a complex mixture.

• Ability to adjust incoming and outgoing moisture content and see the estimated energy usage response.

• Ability to add/adjust energy introduced to test moisture change over drying time.

• Use of specific heat of materials and water to approximate energy usage and create multi-material curves.

• Capability to attach the dryer VBA module to the simulation model and feed data into the dryer material components as received. This allows for a more realistic operation for the dryer.

• Ability to provide drying constants in model using moisture content and time in dryer to adapt curves for actual performance data.

• Ability to tune the dryer performance (throughput, feed-rate, moisture content etc.) to improve downstream equipment processes such as a specific pelletizing technology.

1 . Additional areas that may be optimized include:

• Ability to more accurately predict Volatile, Particulate Matter, and other problematic emissions (both liquid and air).

• Modeling mechanical and thermal drying technologies at the same time.

• Improve the quality of gases leaving dryer.

Simulation of Gasification:

The inventive system was a software platform constructed in VBA language so that it may be tested and adjusted via spreadsheets and data can be manipulated in a material properties program language file. This model may be used to approximate the following thermal conversions in a reactor (FIG. 6 is a screenshot of the spreadsheet side of the model):

Gasifier Model (performs pyrolysis and gasification reactions together). • Material Properties are entered into a .txt file. These properties include:

o Proximate and Ultimate Analysis information (HHV, btu/lb, Carbon,

Nitrogen, etc., wt %/lb, ash wt %).

o Ash analysis (components such as: Si02, K20, CaO, etc.).

o Specific heat, moisture content, drying constants.

• Input Parameters.

o Temperature of material entering reactor - This could also allow for multiple thermo chemical biomass conversion units to be set in front of one another (given a new input material -(example - pyrolyzed waste paper)).

o Quantity of inlet air per lb of material entering. The amount of oxygen will depend on elevation and is described below:

Amount of oxygen (%) introduced into the gasifier (this will define the level of thermal conversion/combustion in the reactor) - a specific amount is necessary to retain the temperatures in the reactor.

Quantities, types, densities, and wt% for moisture. These parameters can be added for an unlimited number of materials, but the current data set is 16.

Material Molar representative wt% elemental analysis for each individual material based upon elemental analyses.

Product Gas temperatures on exit.

Ratio of inlet air to pounds of dry biomass.

• Using the material properties and the underlying Molar base conversions that are based upon the mole fraction of an air based gasifier and the oxygen equivalence ratio graphs, an output is calculated.

• Output - o Combustible Gasses.

Carbon Monoxide (CO).

Hydrogen gas (H2).

Methane (CH4).

Other hydrocarbons (such as C2H6, C3H8...etc.).

o Nitrogen Gases. Ammonia (NH3).

Nitric oxide (NO).

Nitrous oxide (N20).

Nitrous (HN02).

o Sulfur Gasses.

Hydrogen sulfide (H2S).

Sulfur dioxide (S02).

Sulfer trioxide (S03).

o Chloride Gasses.

o Ash including the following examples:



Titanium oxide.

Potassium oxide.

Heavy metals.


Additional areas that may be optimized include: Updating cost/design analysis portion to sizing a reactor.

Expand upon the fast pyroloysis reactions that can occur (no oxygen with external heat) and the "staged" approach for the gasifier. This would allow for more detailed chemical equations and the ability to monitor temperature and pressure locations. This would allow for more detailed analysis/assessment of future reactor and allow for better tracking of temperatures and how they affect the system.

Integrate data collection system with model, allowing model to better approximate actual operation.

Energy balance equations for reactor

Graphics added for reference

Detailed model related specifically toward technology that is chosen. Basically, a standard gasification "model" and a technology specific model that is adapted toward the chosen vendor technology/custom design. • A model that may operate within the PLC for the reactor to show a direct comparison of expectations vs. actual operation to approximate gasses through historical material data collection combined with temperatures, pressures, and flow characteristic variables.

• Model that may be easily scaled and integrated to future PLC's for gasification/pyrolysis units for KNOWN materials being processed. Once adequate material processing development occurs and then material testing performed, the Programmable Logic Controller (PLC) will have a model for syngas prediction and "run-rules" to operate continuously without the need of expensive gas monitoring equipment.

Downdraft Gasification Ideation Design Parameters:

From our research, we are implementing a downdraft gasifier that may perform with the following parameters:

• Preheat material using exhaust from engine and/or exiting syngas from the reactor.

• Penetrate the reactor bed from center and tube outward on or using:

o Multiple planes.

o Feeding air/gases multiple directions.

o A designed manifold to distribute gases evenly through reactor bed. o A mechanism that spins around the center access to both stir and deliver gas evenly.

• Tar recycling

o Using/pulling syngas back through the reactor could be used to heat and also openings in the bed could be used to reticulate syngas through the bed an further "crack" or process tars in the outgoing gas. This would eliminate waste in the form of tars that occur within the gasification process. This is similar to a cyclonic action that separates heavier particulate/tar matter.

• Pressurize reactor o The reactor will be capable of being pressurized, which may be used as a control mechanism to maintain syngas quality and quantity given small material characteristic Auctions,

o Two reactors may be operating at different pressures and temperatures to produce a mixed syngas that captures a larger variation of hydrocarbon gasses.

• Multiple reactors acting simultaneously

o Multiple reactors would be designed similarly and could be tuned differently while being fed identical fuel to best describe how minor adjustments in: temperature profile, air temperature, pressure, nozzle: angle, height, or zone, restriction cone size, ash collection/filtration, densified material size, moisture content, etc. affect the outgoing gas quality.

o Be operated on different fuel streams depending upon fluctuation in feed material.

o Allow for waste processing system to remain "active" while adjustments/maintenance is performed on another unit.

o Allow for real-time comparisons of the operation of multiple.

o Allow for one reactor to be utilized to test feedstock from another future client without affecting operations significantly.

o Allow for growth to larger output by just "adding" a reactor to the line for processing more fuel "power-plant built for growth".

• Steam injection in multiple zones and in ash.

o It is known that a water-gas shift reaction can occur with the char leftover after gasification, experimentation with this may be important to control gas quality.

o Adding steam in zones may be a control mechanism for zones in reactor by controlling temperature and minimizing bed temperature fluctuations.

o This may also be used to increase hydrogen production in bursts to control syngas combustion value "flame temperatures and flash points". • Mechanically or easily accessible/adjusted and rotating reduction zone in reactor.

o Adjusting the restriction zone shape, size, height, and texture are all important aspects to the reduction zone.

o This adjustment could also reduce known "clinker" issues associated with the gasification of difficult solid fuels by dropping out any solids that may be impeding the flow and operation of the reactor. o The rotation of the reduction zone keeps the flow of the producer/syngas inside the reactor consistent by moving any obstructive materials around and grinding them against the sides or against and added purposeful scraping blade.

o The vertical movement of the reduction zone may be pulsed on a programmed time duration to replace the "shaking" devices used to assist in moving materials downward and reduce known bridging issues with materials as they are pyrolyzed and may adhere to each other.

o The reduction zone may also be attached to a grate that will rotate and assist with the moving of ash downward, which is a known build-up issue that can affect the performance of the reactor. The use of scrapper blades may assist in eliminating this blockage as well.

• Temperature controlled reduction zone.

o Coiled high temperature heater added to ensure that temperatures are being met for sufficient gasification even during feedstock fluctuations, o Temperature coil could be used for start-up of reactor.

• Reintroduction of ash into the feedstock.

o would reduce moisture content.

o allow for ash to be more fully processed.

o increase steam introduction variable for testing.

o potential greater hydrogen production and reduced carbon monoxide.

• Feed syngas through long ash auger system for further tar clean-up.

o This would eliminate the need for some additional packed bed filtration and keep the cyclone in the system from getting filled with particulate matter. o Ash would then collect the tars for further use/introduction into waste stream

• Introduction of a medium that could better control the federate of ash out of the bottom of the reactor.

o This may be multiple layers of perforated plate rotating together to only allow smaller particulate matter and gasses to pass through. o May introduce a media of lava rock, ceramic material, or high temp alloys that hold the ash bed height and prevent "drop-out" of material in the reduction zone, which causes temperature and gas issues.

o Spacing of rotating cylinders that hold the bed height and loosely "grind" ash to a fine powder at a specific height below the reduction zone.

o Added char-bed that is held at a higher temperature and will thermally decompose/transition, but does allow for added syngas clean-up - could be used and replaced when needed.

• Exterior of reactor is vacuum that is monitored to ensure no leaks in reactor and used for insulation.

Other Technology Parameters:

We have also identified and evaluated technologies that combine gasification with fast pyrolysis. The major difference between these technologies is the amount of air/oxygen introduced and the source of attaining high temperatures to thermo chemically alter the material to a combustible gas In this regard, pyrolysis can be implemented as an option for gasification and stand-alone. The associated design options include:

• Using a pyrloysis auger prior to gasification to bring the feedstock to a charred state and dry it simultaneously to homogenize the fuel, improve efficiency, and crack hydrocarbons and volatiles contained in the gas stream.

• Cooling the syngas by passing it through the feedstock/pyrolysis unit to transfer heat to incoming material. Using waste exhaust heat from the combustion technology to heat feedstock material and assist with pyrolysis to improve efficiency of entire system.

Using pyrolysis to improve the gas quality of syngas and then controlling the air addition downstream in a gasification zone to crack tars and volatiles still left after pyrolysis.

Feed system for either gasification or pyrolysis is difficult and having an air lock and/or a means of extracting air via vacuum will affect the performance. There is believed to be a way to do this by just compacting (improving the density of material) either hydraulically or mechanically and minimizing air introduction in the process.

Another means of controlling air being introduced with material is to accommodate and calculate quantities it in a feed hopper above the reactor and just ensure that the feed hopper is always full and the feed system to that hopper could then be a batch airlock feed mechanism.

The introduction of a thermally conductive media such as: high temperature metallic alloy or ceramic may be introduced with the feedstock to assist in applying a more evenly distributed thermal profile in the reactor or pyrolysis unit.

o This would mean that these conductive materials will be separated from the ash stream and reintroduced into the process with or without the ash.

A grate system may allow ash to fall through, but not allow these conductive materials to pass and then they could be collected a redistributed into the feedstock in some percentage as to not affect the overall performance.

Keeping these conductive materials at a high temperature may improve the overall efficiency of the gasification/pyrolysis system.

Allowing these conductive materials to cool with the ash could improve the gas clean-up that is occurring when syngas is passing through the ash by holding a tar cracking temperatures in the ash for a longer duration and thus influence end gas. • Introducing or recirculation syngas through the feedstock in a pyrolysis unit may assist in balancing pressures in the reactor out while at the same time allowing for heat transfer to occur between the syngas and the feedstock and maybe improve efficiency. Many scientific journals have identified the potential of reintroducing syngas into a gasifier or pyrolysis unit.

• Heat source - Most companies use external burners as a source of heat for pyrolysis to occur. This would require propane or natural gas for start-up and shut-down of the unit which may be problematic for a utility provider who does not view any use of fossil fuels to violate the "sustainable", "green", or "renewable" energy provider status. This may be avoided by:

o Storing syngas from previous runs and using the stored syngas to start-up system (which would mean continuing to run reactor without generation/combustion for some time to collect and store gas).

o Use an external renewable/sustainable electrical or heat providing energy source such as (but not limited to): Solar Photovoltaics to provide the boost necessary to start the system (with the use of local power source (batteries) of course).

o Using gasification/introduction of air/steam/oxygen to get pyrolysis unit up to temperature and then switching over to gas when system temperatures meet operational parameters.

System Architecture

FIG. 7 illustrates a waste stream collection, processing and gasification system 700 in accordance with the present invention. The illustrated system obtains waste from a variety of sources 702. For example, these sources may include concession waste bins, office waste bins, public waste receptacles, and various animal waste collection tanks. Waste from the various sources 702 is transported via carts 704 to a collection station thereby defining a waste stream 712.

At the collection station, various measurements and observations may be made on a cart-by-cart basis, as generally indicated at box 706. For example, these measurements and observations may include a weight of the waste, a moisture content of the waste, a density of the waste, and a composition of the waste. These measurements and observations may be recorded on a processor 708 such as one or more computers. This information may be entered into the processor 708 by one or more users or automatically transferred to the processor 708 by measurement instruments. In some cases, previously obtained information may be used in analyzing waste from a cart. For example, statistical information may be available based on cart number, source location or categories of waste. Thus, for example, a technician may estimate the proportions of different waste components in a load based on visual inspection or otherwise, and use statistically derived information to determine information regarding weight, density, moisture content, fuel BTU value, ash content, and the like.

This information is used by the processor 708, executing appropriate logic attached to the stream processing equipment 714, to develop statistical information regarding the waste stream and how the waste stream affected the operation of the stream processing 714 or a waste stream model 710. The processor will also receive information from the Stream Processing 714 equipment that will describe how material is flowing through the system and the utilization properties of the equipment. This will allow the processor 708 to define operating rules that may relate to scheduled and unscheduled maintenance occurrences as well as allow for communication between components contained with the Stream Processing 714 and also from 718,720, and 726. This may be conceptualized as involving a start-up phase and an operating phase, though the functionality of these phases will largely overlap. In the start-up phase, which may be conducted at least in-part prior to operation of the gasification process, waste materials may be analyzed over time to develop a model, as described above, defining characteristics of the waste stream as a function of location, time of day, season of the year, and the like. It may be useful to develop this model over a substantial length of time prior to implementing the gasification process. The use of the stream data/model collection 710 will be compared with the actual equipment operation and the simulation model will be updated with actual operational data to better improve performance of equipment. However, it will typically be useful to continue to develop and modify the waste stream model even after the gasification process has been implemented.

As noted above, it may be useful to compile separate waste stream components and to separately process waste stream components using multiple reactors. For example, this may be useful in order to tune processing parameters for different waste stream components, to allow for scalability of the process, and/or to provide redundancy to accommodate repairs, maintenance and experimentation. Such parallel processing is generally indicated in FIG. 7 by schematic replication of elements 712, 714, 716, 718, 720 and 726. This is dependent upon material types and necessary processing and modification of the feedstock throughout this process and not all processing may need to be considered parallel for all elements 712, 714,716,718,726.

The waste from the carts 704 defines a waste stream 712. The waste stream 712 may be physically separated into separate components or processed in an orderly fashion using statistical arrival data to establish an order, for example, including one or more animal waste components, one or more concession waste components, and one or more paper stock components processed in that order or separated then processed. These components are then processed (714) to provide one or more fuel stocks (716). For example, such processing may involve mixing waste stream components in desired portions, drying the resulting fuel stock, compressing the fuel stock, shredding and/or pulverizing the material and forming the fuel stock into desired sizes, shapes or textures of fuel.

The fuel may then be further processed (718) and introduced into one or more reactors (720). For example, the fuel processing may involve further compressing or dimensioning texturing of the fuel, treating the fuel with additive agents or the like, heating the fuel, etc. The fuel may then be processed at one or more reactors. For example, a hydrolysis reactor and/or a multi-stage downdraft gasification reactor may be employed individually or in series. The processor 708 may control a number of processing parameters depending, for example, on the characteristics of the waste stream or resulting fuel. For example, the processor may control: a pre-heat temperature of the fuel; the amount of air/oxygen introduced into the reactor per pound of fuel; or the location, number, direction, and output of air injection nozzles 722, and the operating parameters of any other reactor components 724 such as reactor bed agitation components. The processor may also control the timing and operation of motors that control the reduction zone and the speed at which the ash is processed/moved through the reactor. The processor may also control the height of the material inside of the gasifier feed the reactor to retain the material height that best retains temperature, pressure, and throughput for the reactor. The processor 708 may also receive feedback regarding any output properties (726) of the reactor 720, the Fuel Processing 718, and Stream Processing 714. For example, the processor 708 may receive information regarding: any volatiles or particulates in an output stream; the volume, composition, temperature or the like of syngas produced; the amount and composition ash remaining; the energy produced by the process or efficiency in relation to energy required; or any other useful feedback. The Stream Processing 714 may receive information related to motor amp loads, material fill sensors, motor speeds (thus conveyor speeds), temperatures, and pressure drops for filtration components, The Fuel Processing 718 portion may relay information related to motor speeds, particulate and material fill sensors, temperatures of equipment. The gasifier 708 may communicate information related to fill to Fuel Processing 718 conveyances that may determine where and the quantities of fuel necessary to be delivered to continue operation. This information may be used to analyze and optimize the overall process over time. The foregoing description of the present invention has been presented for purposes of illustration and description. Furthermore, the description is not intended to limit the invention to the form disclosed herein. Consequently, variations and modifications commensurate with the above teachings, and skill and knowledge of the relevant art, are within the scope of the present invention. The embodiments described hereinabove are further intended to explain best modes known of practicing the invention and to enable others skilled in the art to utilize the invention in such or other embodiments and with various modifications required by the particular application(s) or use(s) of the present invention. It is intended that the appended claims be construed to include alternative embodiments to the extent permitted by the prior art.