Progress 01/01/16 to 12/31/18
Outputs
Target Audience:During the three year project, we have shared our ideas, results and plans with several groups including local representatives of the National Park Servicea and CAFO managers, as well as with represenatives from one of our cooperator sites commercial dairy in northern Colorado. We have also shared information on the project with members of the academic community, primarily at Colorado State University, in the Departments of Mechanical Engineering, Soil and Crop Sciences, and Atmospheric Science. We have also shared results more broadly with academia via an invited talk by Professor Yalin at a meeting of the Optical Society of America. Changes/Problems:
Nothing Reported
What opportunities for training and professional development has the project provided?Graduate Student Training: -One graduate student (Soran Shadman) has been trained in the development of laser sensors and UAV usage for agricultural emissions measurements. -A second graduate student (Will Lassman) has been trained in numeric modeling of agricultural emissions, including how to use and invert the data to quantify deposition with our new tracer method. Undergraduate Student Training: -Two undergraduate students (Collin VanTilburg and Jared Ham) have been trained in scientific application of UAVs, including sensor integration, safe deployment and operations, and best practices to work with (non-technical) cooperator site peronnel. How have the results been disseminated to communities of interest?Repeated from Target Audience Section: During the three year project, we have shared our ideas, results and plans with several groups including local representatives of the National Park Servicea and CAFO managers, as well as with represenatives from one of our cooperator sites commercial dairy in northern Colorado. We have also shared information on the project with members of the academic community, primarily at Colorado State University, in the Departments of Mechanical Engineering, Soil and Crop Sciences, and Atmospheric Science. We have also shared results more broadly with academia via an invited talk by Professor Yalin at a meeting of the Optical Society of America. Further, we expect to have 2 journal publications (one focused on the UAV and sensors, one focused on the numeric modeling of the emissions) published in 2019 which will increase the reach of our research. What do you plan to do during the next reporting period to accomplish the goals?
Nothing Reported
Impacts
What was accomplished under these goals?
IMPACT: Animal feeding and agricultural activities are a major source of ammonia (NH3) emissions to the atmosphere. These emissions can lead to regional haze and health risks (from particle formation), and deposition of ammonia back to the ground can change ecosystems and cause soil acidification. Methane (CH4) is also emitted in significant quantities and impacts green house gas (GHG) inventories, ozone formation, and atmospheric oxidation. Currently, with reliance on ground based sensors, it is hard to quantify the emissions. Through the use of sensors deployed on small unammed aerial vehicles (UAVs), we have made substantial progress towards advancing the needed technologies and capabilitites towards ammonia and methane measurements from agricultural operations. We have developed highly sensitive laser sensors for both ammonia and methane, both in lightweight compact packages suitable for UAV deployment. The sensors have been successfully integrated and flown on a UAV, including at a cooperator dairy site, and have yielded emissions measurements. This sensor-UAV system represents a powerful capability towards future agricultural needs, including problems of ammonia deposition (that can inform new management practices to best address air quality and deposition to the ground, both nearby and far sites) as well as more general sensing capabilities relative to GHG emissions and other chemical species. ----- Below, we discuss specific progress under the 6 project objectives: 1. Develop lightweight open-path laser sensor for ammonia and methane and integrate to an sUAS. Both sensors have been developed. The ammonia sensor is based on wavelength modulation spectroscopy (WMS) in the mid-infrared at wavelength of ~10.3 microns and yields sensitivity of ~1 ppb in 1-s measurement time. The methane sensor is based on cavity ring-down spectoscopy (CRDS) in the near-infrared at wavelength of ~1.65 microns and yields sensitivity of ~10 ppb in 1-s measurement time. Both sensors use open-path configurations to obviate the need for bulky and power-hungry vacuum pumps. Both sensors, and their controlling electronics and data acquisition (DAQ) systems have been integrated to a UAV. 2. Obtain needed certification from the FAA to operate the sUAS at a cooperator site in eastern Colorado. Interestingly, FAA requirements have evolved over the course of the project. We have taken a series of steps towards integrating our UAV with the local Colorado air space while also contributing towards buildout of UAV infrastructure (for this and other related projects) at Colorado State University (CSU). Specific steps include: i) staying abreast of all FAA regulations, ii) insuring and registering our UAV (a 10' wing-span Senior Telemaster) with the Risk Management office at CSU, iii) training two undergraduate students on UAV operational and flight safety issues, including supporting one of the students in passing his FAA Part 107 exam (allowing him greater flexibility in UAV piloting inclkuding in cases where a commercial designation may be required), and iv) working with a local (dairy) cooperator site to establish a runway and safe flying operational protocols. 3. Perform flight campaigns to quantify local N deposition using the downwind change in NH3:CH4 ratio, and measure methane and ammonia emissions from the site, supported by ground (tower) measurements. Several initial flights with the combined methane and ammonia sensor system were performed, both at intial testing area as well as at the cooperating dairy site with ammonia (and methane) emissions. These latter flight data have been analyzed. We performed complementary ground-based measurements with the sensors at multiple locations and concurrent meteorological (wind) measurements. The observed concentrations correlated with position and wind in rough agreement with expectations, including showing decreasing ratio of ammonia:methane due to downwind deposition. These data have also been analyzed and have advanced our methodology to inferring deposition including initial estimates. 4. Perform additional measurements from the ground (tower) and mobile vehicles both during and between the UAS campaigns to provide better temporal coverage and determine if N deposition can be accurately measured without the need for sUAS. As discussed in resopnse to 3), complementary ground-based measurements have been performed. The measurements used a mobile platform (truck) and obtained methane and ammonia readings at a series of locations at different distances (and directions, relative to the wind) from the emitting dairy site. It has been shown that these data can provide information on the deposition; however, using the ground-based only measurements does require more assumptions on the nature of the vertical mixing layer. The results from this project set the stage for continued efforts to address this problem. 5. Use numeric models to infer sources and to quantify the ammonia deposition in the downwind shadow of the site. Signitcant progress has been made to advance the state-of-the-art in numeric models to analyze eth ammonia and methane spatiotemporal emission data to gain insight on downwind deposition. In short summary, we are using Large Eddy Simulation (LES) codies to explicitly simulate large turbulent eddies which are characteristic of the atmosphere on shorter timescales. Due to the chaotic nature of turbulence and the intensive computational resources required for LES, this type of simulation is not a good candidate for use in an inverse model. Instead, we use this to generate "pseudo-data" with which we can develop our inverse model. We use the System for Atmospheric Modelling (SAM) version 6.10.10 for our LES. We added two tracers to the model, one of which is inert (methane on these spatial scales) and one which undergoes dry deposition (ammonia). Our LES simulations show that under sunny unstable conditions in eastern CO, most of the vertical mixing is dominated by large eddies, rather than atmospheric diffusion. To produce realistic data that would be used in an inverse-model, we simulate making measurements on the LES output by sampling for two deployment cases - a mobile truck and UAV - and how they will sample the plume. Modeling shows that by measuring the ammonia:methane (excess above background) concentrations, down wind of the source, we can infer total deposition to the ground as well as making estimations of the ammonia deposition velocity. We find that for a surface only measurement (i.e., truck) the method produces and overestimate of ammonia deposition on the order of factor 1.5 due to sampling the air near the surface where concenrations are (already) depleted. However, via the UAV sampling, we can more accurately estimate the deposition (with fractional error <0.09 for cases considered). 6. Use these findings to infer how management of crops and vegetation downwind of beef feedlots could maximize N deposition and become part of a best management plan for mitigating impacts of emissions. The research successfully conducted in this project (objectives 1-5) provide previously unavailble sensor/UAV tecnhologies, numeric models, and system-level methodologies to gain insight into ammonia deposition. As such, we are now in a position to work together with cooperator sites (e.g. the dairy in nothern Colorado with whom we already partner) to conduct longer term studies to obtain the data and experience needed to advance management practices. Dissemination of our results (two journal publications in 2019) will allow other researchers to join us in addressing these problems.
Publications
- Type:
Journal Articles
Status:
Other
Year Published:
2019
Citation:
In preparation-
Soran Shadman, Laurie McHale, Jared Ham, Collin VanTilburg, Frederick Smith, Azer Yalin "Emissions Measurements with Ammonia and Methane Sensors Mounted on Unmanned Aerial Vehicles", in preparation for submission to journal Sensors in 2019
- Type:
Journal Articles
Status:
Other
Year Published:
2019
Citation:
In preparation-
William Lassman, Jeffrey L. Collett, Jay M. Ham, Azer Yalin, and Jeffrey R. Pierce "Methods of estimating deposition using atmospheric concentration measurements: a case study of ammonia downwind of a feedlot" in preparation for submission to journal Agriculture and Forest Meteorology in 2019
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Progress 01/01/17 to 12/31/17
Outputs
Target Audience:During the second year of the three year project, we have begun to share our ideas, results and plans with several groups including local representatives of the National Park Servicea and CAFO managers, as well as with represenatives from one of our cooperator sites commercial dairy in northern Colorado. We have also shared information on the project with members of the academic community, primarily at Colorado State University, in the Departments of Mechanical Engineering, Soil an Crop Sciences, and Atmospheric Science. We have also shared results more broadly with academia via an invited talk by Professor Yalin at a meeting of the Optical Society of America. As we move to the final year of the project, we will share our results with a broader group of stakeholders, i.e. CAFO managers, state and federal regulators, livestock commodity groups, EPA, the National Park Service, and members of academia. Changes/Problems:
Nothing Reported
What opportunities for training and professional development has the project provided?Two graduate students in Mechanical Engineering have received training and mentorship (from faculty) in development, integration and deployment of laser sensors for emission measurements from agricultural sources. One student focuses on the ammonia sensor, while the second focuses on the methane sensor (and their work includes also studies of oil and gas emissions, supported by other progjects). Two undergraduate students in Mechanical Engineering have received training and mentorship (from faculty) in analysis and operations of sUAS, including integration of sensors to the sUAS and practical flight considerations. A graduate student in Atmosperic Science has received training and mentorship (from faculty) in development and use of numeric models for plume dispersion including the specific appliction towards areal source emissions from CAFO operation, and deposition of ammonia to the ground. How have the results been disseminated to communities of interest?As reported in the products section, in the report period we have delivered one invited conference presentation that discussed the overall project. The talk was well attended by members of the optical sensing community. We plan on more extensive publication and dissemination in the final year of the project. What do you plan to do during the next reporting period to accomplish the goals?We will continue to work toward our objectives. We will continue work under objectives 3-6 in terms of performing flights with both the ammonia and methane sensors (so far we have only flown methane). We will also conduct additional ground-based measurements (usng the approaches demonstrated in this period) and continue applying the numeric models to measure the emissions and infer the ammonia deposition. These results will allow us to begin work on Objective 7 in terms of management practices.
Impacts
What was accomplished under these goals?
1. Develop lightweight open-path laser sensor for ammonia and methane and integrate to an sUAS. Objective complete. The methane sensor employs cavity ring-down spectroscopy (CRSD) with a near-infrared telecom sytle distributed feedback (DFB) diode laser at 1.65 microns, while the ammonia sensors employs wavelength modulation spectroscopy (WMS) with a 10.3 micron quantum cascade laser (QCL) source. Each sensor has total mass of ~7 pounds and power draw of ~30 W, as can be supported on our sUAS. The methanse sensor has a detection limit of ~10 ppb in 1s, while ammonia is ~1 ppb in 1s. The sensors have been mechanically and electrically integrated to the sUAS and shown to operate while the sUAS is stationary or taxiing on the ground. The ammonia sensor has been flown on the sUAS and successfully collected data (with a dummy sensor also on board to accound for needed mass of methane sensor). Both sensors will be flown together in early 2018. 2. Obtain needed certification from the FAA to operate the sUAS at a cooperator site in eastern Colorado. Complete / Non-Applicable. [Interestingly, the FAA rules on universirt operation of sUAS have changed between the time of proposal preparation and the present. Given that we meet the standard rules for sUAS (i.e., below 55 pounds, flights below 400' and within line of sight) we do not need a Certificate of Approval (COA) from the FAA. We have obtained all needed permissions including registering our drone and plans under our internal university approval process and insurance.] 3. Perform flight campaigns to quantify local N deposition using the downwind change in NH3:CH4 ratio, and measure methane and ammonia emissions from the site, supported by ground (tower) measurements. In progress. As mentioned above, the ammonia sensor has been flown on the sUAS and yielded ammonia concentration data. Wind speed and direction was also measured and we are curretnly reducing the data. Combined methane and ammonia measurements to be conducted in early 2018. We have also tested our deposition algorithms, and sensor robustness for this application, by performing ground-based measurements (at different distances downwind of a dairy) and showed ability to infer deposition velocity results. 4. Perform additional measurements from the ground (tower) and mobile vehicles both during and between the UAS campaigns to provide better temporal coverage and determine if N deposition can be accurately measured without the need for sUAS. In progress. See Objective 3. We have performed complementary measurements, on a mobile vehicle on the ground, with both the methane and ammonia sensors and used results to infer ammonia deposition. More of these measurements will be performed in 2018. 5. Use numeric models to infer sources and to quantify the ammonia deposition in the downwind shadow of the site. In progress. We have made good progress on development of the numeric models to quantify near-field dry deposition downwind of the CAFO. To do this, we need to develop an inverse model which determines best-fit dispersion and deposition parameters from measurements from the sUAS-based instruments. To develop a sampling strategy with the UAV, we are using Large Eddy Simulation (LES) output. LES explicitly simulates large turbulent eddies which are characteristic of the atmosphere on shorter timescales. We use the System for Atmospheric Modelling (SAM) version 6.10.10 for our LES. Per Objectives 3) and 4) we have used the the model to interpret and analyze the ground-based measurements, and will apply to sUAS in 2018. 7. Use these findings to infer how management of crops and vegetation downwind of beef feedlots could maximize N deposition and become part of a best management plan for mitigating impacts of emissions. This is upcoming in the next period.
Publications
- Type:
Conference Papers and Presentations
Status:
Published
Year Published:
2017
Citation:
Invited talk:
A.P. Yalin, L.E. McHale, S. Shadman Measurement Of Agricultural Emissions Using Laser Sensors On Unmanned Aerial Systems OSA Optics and Photonics for Energy and the Environment, NCAR, Boulder, CO, November 2017
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Progress 01/01/16 to 12/31/16
Outputs
Target Audience:During the first year of this two year project, we have begun to share our ideas, results and plans with several groups including local representatives of the National Park Servicea and CAFO managers (including our cooperator site - a commercial beef feedlot in northern Colorado). We have also shared information on the project with members of the academic community, primarily at Colorado State University, in the Departments of Mechanical Engineering, Soil an Crop Sciences, and Atmospheric Science. We have also shared results more broadly with academia via an invited talk by Professor Yalin at a meeting of the Optical Society of America. In later stages of the project, we will actively share our results with a broader group of stakeholders, i.e. CAFO managers, state and federal regulators, livestock commodity groups, EPA, the National Park Service, and members of academia. Changes/Problems:
Nothing Reported
What opportunities for training and professional development has the project provided?A graduate student in Mechanical Engineering has received training and mentorship (from faculty) in development, integration and deployment of laser sensors for emission measurements from agricultural sources. An undergraduate student in Mechanical Engineering has received training and mentorship (from faculty) in analysis and operations of sUAS, including integration of sensors to the sUAS. A graduate student in Atmosperic Science has received training and mentorship (from faculty) in development and use of numeric models for plume dispersion including the specific appliction towards areal source emissions from CAFO operation, and deposition of ammonia to the ground. How have the results been disseminated to communities of interest?As reported in the products section, so far we have one journal publication on the ammonia sensor and one invited conference presentation that discussed the overall project. We have also informally communicated results to stakeholders including the CSU academic community, National Park Service, and management at our cooperator site. We plan on more extensive publicaton and dissemination of results in later stages of the project. What do you plan to do during the next reporting period to accomplish the goals?We will continue to work toward our objectives. We will continue work under objectives 3-6 in terms of performing flights with the sensors, and supporting ground based measurements, and use of the numeric models to measure the emissions and infer the ammonia deposition. These results will allow us to begin work on Objective 7 in terms of management practices.
Impacts
What was accomplished under these goals?
IMPACT: US agriculture emits 3.5 Tg of ammonia per year through fertilizer application and livestock waste. These ammonia emissions have important impacts on air quality and ecosystems downwind of the sources. Ammonia may contribute to airborne fine particulate matter, which can adversely affect health, visibility and climate, while deposition of ammonia and ammonium to soils can change plant growth charateristics. The current project uses laser sensors deployed on small unmanned aerial systems (sUAS) to measure ammonia and methane emissions from concentrated animal feeding operations (CAFOs) and to quantify ammonia deposition downwind of CAFOs. Key innovations of the emissions monitoring system include: 1) simultaneous ammonia (NH3) and methane (CH4) detection using open-path sensors, 2) sUAS flight capabilities that are more nimble, safer and more cost effective to operate than manned aircraft, and 3) inversion and flux modeling to infer sources, fluxes, and ammonia deposition. In addition to providing an improved means to quantify amonia emissions and deposition, we are seeking to identify new best practices to mitigate their negative effects, for example, planting crops downwind of sites to increase local ammonia deposition and reduce deposition at further locations. The methane measurements provide source fluxes to quantify the carbon footprint of CAFOs. More broadly, the projectl also demonstrates the possibility of certifying and flying sUAS at agricultural sites which can also be useful for crop, soil, and canopy imaging, as well as animal health monitoring and other applications. DISCUSSION ON OBJECTIVES: 1. Develop lightweight open-path laser sensor for ammonia and methane and integrate to an sUAS. Substantial progress has been made on sensor development and integration. As a first step, we developed and tested both the methane and ammonia sensors on the "benchtop" in our laboratory. Both sensors are in open-path configurations, meaning they do not use flow cells or vacuum pumps, which allows for lightweight and low power designs. The methane sensor employs cavity ring-down spectroscopy (CRSD) with a near-infrared telecom sytle distributed feedback (DFB) diode laser at 1.65 microns, while the ammonia sensors employs wavelength modulation spectroscopy (WMS) with a 10.3 micron quantum cascade laser (QCL) source. The benchtop setups performed successfully and we then advanced to designing and building more compact versions of these sensors for use on the sUAS. Those designs are complete and in the manufacturing phase. Each sensor comprises a sensor head and an electronics enclosure. Each sensor has total mass of ~7 pounds and power draw of ~30 W, as can be supported on our sUAS. The methanse sensor has a detection limit of ~10 ppb in 1s, while ammonia is ~1 ppb in 1s. We have also made substantial progress on integration of the sensors to the sUAS. The mounting concept is to hang each sensor below the fuselage with the laser optical axis aligned with the flight direction. 2. Obtain needed certification from the FAA to operate the sUAS at a cooperator site in eastern Colorado. Interestingly, the FAA rules on universirt operation of sUAS have changed between the time of proposal preparation and the present. Given that we meet the standard rules for sUAS (i.e., below 55 pounds, flights below 400' and within line of sight) we do not need a Certificate of Approval (COA) from the FAA. We have obtained all needed permissions including registering our drone and plans under our internal university approval process. (Our university, to manage drone operations and liability, has developed a form and process for all drone flights by university personnel.) 3. Perform flight campaigns to quantify local N deposition using the downwind change in NH3:CH4 ratio, and measure methane and ammonia emissions from the site, supported by ground (tower) measurements. We are progressing towards flights with the sensors using our Senior Telemaster aircraft. First, the Telemaster power system selection was verified through three different forms of power and airframe calculations; a Hardware-in-the-Loop (HIL) simulation developed at CSU, power system spreasheet calculations developed at CSU, and Ecalc, a commercial electric motor calculator. We performed calculations on the thrust, lift force, drag force and related aerodnymic parameters. The simulation tools also allow us to examine mock flight profiles allowing us to determine the endurance and range for different flight paths. We expect flights of >30 minute duration with typical spees of about 40 knots. In terms of experimental work, we have performed a static test where the motor and propeller was operated on the ground, and the thrust was measured. At full throttle we found a thrust of 18 pounds which is in good agreement (better than 10%) with simulated values. More recenlty, we have made our first flights with the sUAS. These flights have verified the basic air worthiness of the air frame and it's ability to carry the sensor mass. In the upcoming period we will perform flights with the sensors. 4. Perform additional measurements from the ground (tower) and mobile vehicles both during and between the UAS campaigns to provide better temporal coverage and determine if N deposition can be accurately measured without the need for sUAS. We have developed a ground measurement capability to complement and augment the sUAS mesaurements. Ammonia concentrations were sampled by two different ground based instruments for comparison purposes. Both sensors were placed on the west side of the feedlot, which provided a downwind fenceline measurement when winds were easterly. Instrumentation included a long-path laser (Boreal Laser Inc.) and a cavity ring down analyzer (Picarro Inc.). Results show a wide range of concentration at the fenceline. The average concentration when the winds were from the direction of the cattle was around 1000 ppb, but spikes over 2000-3000 ppb were common when wind speed were low. These measurements will continue in the next period with the sUAS measurements. 5. Use numeric models to infer sources and to quantify the ammonia deposition in the downwind shadow of the site. We have made good progress on development of the numeric models to quantify near-field dry deposition downwind of the CAFO. To do this, we need to develop an inverse model which determines best-fit dispersion and deposition parameters from measurements from the sUAS-based instruments. To develop a sampling strategy with the UAV, we are using Large Eddy Simulation (LES) output. LES explicitly simulates large turbulent eddies which are characteristic of the atmosphere on shorter timescales. We use the System for Atmospheric Modelling (SAM) version 6.10.10 for our LES. We added two tracers to the model, one of which is inert (methane on these spatial scales) and one which undergoes dry deposition (ammonia). Model results show that temporal averaging of our LES output converges to a smooth, Gaussian-like plume. In order to build a robust inverse model, we need acomputationally efficient forward model to estimate concentrations. We are investigating analytical solutions, based ona steady state model that uses Green's Functions, rather than a numerical solution to the atmospheric diffusion equations which govern this system. By superpositioning many point sources on the same domain, we can approximate an area source as we would expect for a CAFO. So far, we have done rough tuning of the dispersion and deposition parameters in the steady state model to match the simulated SAM measurements. This "optimization" will be done systematically in our inverse model, in upcoming work. 7. Use these findings to infer how management of crops and vegetation downwind of beef feedlots could maximize N deposition and become part of a best management plan for mitigating impacts of emissions. This is upcoming in the next period.
Publications
- Type:
Journal Articles
Status:
Published
Year Published:
2016
Citation:
S. Shadman, C. Rose and A.P Yalin, 2016 Open path cavity ring down spectroscopy sensor for atmospheric ammonia Appl. Phys. B 122 (7)
- Type:
Conference Papers and Presentations
Status:
Published
Year Published:
2016
Citation:
Azer P. Yalin, Laura E. McHale, Soran Shadman, Charles Rose Open-Path Cavity Ring-Down Spectroscopy Sensors for Atmospheric Measurements Invited Talk, Paper ATh3J.1, Conference on Lasers and Electro-Optics (CLEO), Optical Society of America, San Jose, CA, 2016
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