Patent Application
20110015082
Biological nitrogen removal (BNR) is based on nitrification and denitrification and is a conventional way of removing nitrogen from sewage and municipal wastewater. Denitrification is the second step in the nitrification-denitrification process and is a microbially facilitated process of nitrate reduction that reduces oxidized forms of nitrogen in response to the oxidation of an electron donor such as domestic wastewater or other organic matter. BNR is generally performed by heterotrophic bacteria, but can be performed by autotrophic denitrifiers. Typically, denitrifiers in BNR processes include multiple species of bacteria.
Current processes for wastewater treatment typically include BNR processes with activated sludge. Processes including activated sludge are century-old, energy intensive, aerobic processes, which require pumping oxygen into a reactor. Such processes are costly with annual costs of treating U.S. wastewater alone are $25 billion and escalating. Known activated sludge processes are typically inefficient in that they do not include bacteria communities that are specifically targeted to the organic matter contained in the wastewater stream.
Bacterial communities are typically not tailored because of an inability to target denitrifiers in activated sludge using conventional techniques. A wide fraction of activated sludge bacteria denitrify. However, conventional techniques do not reveal what specific bacteria species are most effective at consuming particular specific carbonaceous chemical oxygen demand (COD) sources, such as methanol. Conventional techniques do not allow us to directly determine the fraction of activated sludge that consumes a specific COD source of interest. As a result, bacterial communities have not been developed that target specific COD sources, which are more prevalent in a particular wastewater stream, thereby decreasing the overall efficiency of the bacteria community and therefore of the wastewater treatment system.
Methods of evaluating the operating conditions in a biological nitrogen removal reactor using gene expression and abundance tracking are disclosed. In some embodiments, the methods include the following: obtaining a sample from the reactor during continuous reactor operation; expressing predetermined nitrification, denitrification, and structural genes for ammonia oxidizing bacteria contained in the sample to develop a sample genetic profile of the ammonia oxidizing bacteria; obtaining a genetic profile of a second bacteria substantially similar to the ammonia oxidizing bacteria, wherein the second bacteria was grown in a reactor having substantially optimum operating conditions; and comparing the sample genetic profile to the genetic profile of the second bacteria.
Systems for optimizing the operating conditions in a biological nitrogen removal reactor using gene expression and abundance tracking are disclosed. In some embodiments, the systems include the following: a diagnostic module for evaluating the operating conditions in a biological nitrogen removal reactor using gene expression and abundance tracking, the diagnostic module including mechanisms for obtaining a sample from the reactor, expressing predetermined nitrification, denitrification, and structural genes for ammonia oxidizing bacteria contained in the sample to develop a sample genetic profile of the predetermined ammonia oxidizing bacteria, and comparing the sample genetic profile to a genetic profile of a second bacteria; and a corrective module for identifying deficiencies in operating parameters of the biological nitrogen removal reactor and changing the operating parameters to correct the deficiencies.
Methods of evaluating the operating conditions in a biological nitrogen removal reactor using gene expression and abundance tracking are disclosed. In some embodiments, the methods include the following: obtaining a sample from the reactor; recording operating conditions data from the reactor at a time the sample is obtained; expressing predetermined nitrification, denitrification, and structural genes for ammonia oxidizing bacteria contained in the sample to develop a sample genetic profile of the predetermined ammonia oxidizing bacteria; selecting a genetic profile of a second bacteria substantially similar to the predetermined ammonia oxidizing bacteria from a library of genetic profiles including a plurality of predetermined denitrifying bacteria; comparing the sample genetic profile to the genetic profile of the second bacteria; and comparing the operating conditions data to optimum operating conditions data related to the second bacteria.
The drawings show embodiments of the disclosed subject matter for the purpose of illustrating the invention. However, it should be understood that the present application is not limited to the precise arrangements and instrumentalities shown in the drawings, wherein:
As discussed above, current BNR reactors are operated without knowledge of the active denitrification fraction taking place in the activated sludge. Presently, BNR reactors are operated without knowing whether the same bacteria degrade all COD sources or whether particular bacteria is more efficient over other bacteria at degrading a particular COD sources. Systems and methods according to the disclosed subject matter allow for the testing of BNR reactor environments and the determination of the active denitrification fraction of the activate sludge. Bacteria are analyzed on a genetic level to determine which specific bacteria are responsible for consuming specific COD sources. Systems and methods according to the disclosed subject matter provide a tool for optimizing conditions in bioreactors to sustain and promote the growth of the active denitrifying fraction.
Generally, the disclosed subject matter relates to a system 100 for optimizing the operating conditions in a biological nitrogen removal reactor 102 using gene expression and abundance tracking. As represented schematically in
Diagnostic module 104 includes mechanisms for evaluating the operating conditions in a biological nitrogen removal reactor using gene expression and abundance tracking. Diagnostic module 104 includes a sampling apparatus 110, a testing apparatus 112, and an analysis apparatus 114.
Sampling apparatus 110 are used for obtaining a sample 116 from reactor 102 during batch growth of bacteria. Typically, operating conditions data from reactor 102 are recorded when sample 116 is obtained. Testing apparatus 112 are used for expressing predetermined nitrification, denitrification, and structural genes for ammonia oxidizing bacteria 118 contained in sample 116 to develop a sample genetic profile 120 of the predetermined ammonia oxidizing bacteria. In analysis apparatus 114, a genetic profile 122 for a second bacteria substantially similar to the predetermined ammonia oxidizing bacteria, but grown in a biological nitrogen removal reactor (not shown) having substantially optimum operating conditions is obtained and compared to sample genetic profile 120. Genetic profile 122 is typically obtained by selecting the genetic profile from a library 124 of genetic profiles of a plurality of predetermined nitrifying bacteria including a plurality of predetermined ammonia oxidizing bacteria grown in a biological nitrogen removal reactor and under substantially optimum operating conditions. The plurality of predetermined ammonia oxidizing bacteria included in library 124 are grown in a biological nitrogen removal reactor (not shown), are grown under substantially optimum operating conditions, and have an optimum maximum specific growth rate for specific chemical oxygen demand (COD) sources of interest. The COD sources typically include one of methanol, other organic compounds, and combinations thereof.
Corrective module 106 includes mechanisms for identifying whether deficiencies exist in operating parameters of biological nitrogen removal reactor 102 based on data from analysis apparatus 114 and comparing the operating conditions data in reactor 102 to optimum operating conditions data from the biological nitrogen removal reactor (not shown). If deficiencies are identified, corrective module 106 includes mechanisms for changing the operating parameters to correct the deficiencies.
Tracking module 108 includes mechanisms for scheduling operation of diagnostic module 104 and corrective module 106 and for storing data generated by both diagnostic module 104 and corrective module 106. For example, tracking module 108 can include a software program for scheduling sampling, testing, and corrective action on a regular basis. It is contemplated system 100 will be configured to be operated automatically and in real time. For example, certain operating parameters will be continuously evaluated by diagnostic module 104. If certain predetermined levels for those operating parameters are achieved, corrective module 106 will be automatically activated to correct the operating parameters so that they are within predetermined ranges.
Referring now to
Referring now to
Methods according to the disclosed subject matter provide advantages and benefits over known methods because they allow for direct determination of the activated sludge fraction that consumes any given COD source. From there, the concentrations of XCOD1, COD2, CODn over time can be determined. This information can be used to develop targeted bacteria communities for specific COD sources, which are more prevalent in a particular wastewater stream, thereby increasing the overall efficiency of the bacteria community and wastewater treatment system.
Although the disclosed subject matter has been described and illustrated with respect to embodiments thereof, it should be understood by those skilled in the art that features of the disclosed embodiments can be combined, rearranged, etc., to produce additional embodiments within the scope of the invention, and that various other changes, omissions, and additions may be made therein and thereto, without parting from the spirit and scope of the present invention.
This application claims the benefit of U.S. Provisional Application No. 60/977,415, filed Oct. 4, 2007, which is incorporated by reference as if disclosed herein in its entirety.
| Filing Document | Filing Date | Country | Kind | 371c Date |
|---|---|---|---|---|
| PCT/US08/78921 | 10/6/2008 | WO | 00 | 9/13/2010 |
| Number | Date | Country | |
|---|---|---|---|
| 60977415 | Oct 2007 | US |
