Engineering design and assembly of a surface methane and carbon dioxide gas flux measurement chamber with a case study on the University of Utah Campus

Atmospheric methane and carbon dioxide have been deemed significant "greenhouse gases" (GHG) which are thought to be responsible for major climate changes. Wastewater treatment plants have seen quite a lot of attention with respect to methane release, but little study of sewer transport (pipeline) contribution has been reflected in recent literature. This lack of analysis on sewer systems could be because of the Intergovernmental Panel on Climate Change report stating that in most developed countries, sewers are closed and underground, and therefore would not make a large contribution to carbon emissions (especially CH4) emissions. Previous methods for quantifying sewer transport emissions have mainly utilized tracer gas coupled with measurement of flow or velocity rates within the sewer lines, or through lab studies. The purpose of this study was to develop a direct flux emissions measurement method based on existing technology, soil flux chambers, for CH4 and CO2 using lab calibration and field testing. Such chambers were designed for measuring diffuse soil fluxes exclusively, and decades of such measurements indicate the validity of the approach. In this thesis study, the soil chamber was used as a basis for designing a larger chamber capable of handling relatively larger magnitude point fluxes from sewer access covers. The University of Utah campus consists of a series of mixed gravity sewer designs and ages, spanning the past century. Assuming this system was representative of the range of urban gravity sewer infrastructure typical to U.S. cities, a case study was done as part of this thesis. For this work, 11 sewer access covers were analyzed using a specifically designed flux chamber to measure gas fluxes directly from the sewer access covers. Based on these surveys, a preliminary estimate of annual carbon emissions from these 11 access iv points was determined to be 1.066 Metric Tons CO2 equivalent per year (Mt CO2e). It is recommended that more calibration and continuous surveys of these, and all other sewer access points on campus, are done to facilitate the calculation and cumulative "carbon footprint" of the campus sewer system. Ultimately, the technology developed as part of this thesis work can form the basis of an effective methodology to measure CH4 and CO2 emissions from sewer lines and possibly other urban infrastructure, and quantify the relative major GHG emissions or "carbon footprint" of such emission sources.

ENGINEERING DESIGN AND ASSEMBLY OF A SURFACE METHANE AND CARBON DIOXIDE GAS FLUX MEASUREMENT CHAMBER WITH A CASE STUDY ON THE UNIVERSITY OF UTAH CAMPUS by Amanda K. Fenton A thesis submitted to the faculty of The University of Utah in partial fulfillment of the requirements for the degree of Master of Science Department of Civil and Environmental Engineering The University of Utah May 2017 Copyright © Amanda K. Fenton 2017 All Rights Reserved The University of Utah Graduate School STATEMENT OF THESIS APPROVAL Amanda K. Fenton The thesis of has been approved by the following supervisory committee members: Brian McPherson , Chair 05-20-2016 Date Approved Steven Burian , Member 06-02-2016 Date Approved Christine Pomeroy , Member 06-03-2016 Date Approved Thomas Rahn , Member 05-26-2016 Date Approved and by the Department/College/School of Michael Barber , Chair/Dean of Civil and Environmental Engineering and by David B. Kieda, Dean of The Graduate School. ABSTRACT Atmospheric methane and carbon dioxide have been deemed significant "greenhouse gases" (GHG) which are thought to be responsible for major climate changes. Wastewater treatment plants have seen quite a lot of attention with respect to methane release, but little study of sewer transport (pipeline) contribution has been reflected in recent literature. This lack of analysis on sewer systems could be because of the Intergovernmental Panel on Climate Change report stating that in most developed countries, sewers are closed and underground, and therefore would not make a large contribution to carbon emissions (especially CH4) emissions. Previous methods for quantifying sewer transport emissions have mainly utilized tracer gas coupled with measurement of flow or velocity rates within the sewer lines, or through lab studies. The purpose of this study was to develop a direct flux emissions measurement method based on existing technology, soil flux chambers, for CH4 and CO2 using lab calibration and field testing. Such chambers were designed for measuring diffuse soil fluxes exclusively, and decades of such measurements indicate the validity of the approach. In this thesis study, the soil chamber was used as a basis for designing a larger chamber capable of handling relatively larger magnitude point fluxes from sewer access covers. The University of Utah campus consists of a series of mixed gravity sewer designs and ages, spanning the past century. Assuming this system was representative of the range of urban gravity sewer infrastructure typical to U.S. cities, a case study was done as part of this thesis. For this work, 11 sewer access covers were analyzed using a specifically designed flux chamber to measure gas fluxes directly from the sewer access covers. Based on these surveys, a preliminary estimate of annual carbon emissions from these 11 access points was determined to be 1.066 Metric Tons CO2 equivalent per year (Mt CO2e). It is recommended that more calibration and continuous surveys of these, and all other sewer access points on campus, are done to facilitate the calculation and cumulative "carbon footprint" of the campus sewer system. Ultimately, the technology developed as part of this thesis work can form the basis of an effective methodology to measure CH4 and CO2 emissions from sewer lines and possibly other urban infrastructure, and quantify the relative major GHG emissions or "carbon footprint" of such emission sources. iv TABLE OF CONTENTS ABSTRACT...................................................................................................................................... iii LIST OF FIGURES .......................................................................................................................... vi LIST OF TABLES ........................................................................................................................... vii NOMENCLATURE......................................................................................................................... viii INTRODUCTION .............................................................................................................................. 1 Literature ................................................................................................................................... 2 Project Study ............................................................................................................................. 4 RESEARCH APPROACH: EQUIPMENT, MEASUREMENTS AND ANALYSIS ............................. 6 University of Utah Campus Case Study: Site Description ........................................................ 6 Equipment ................................................................................................................................. 7 CRDS Concentration Readings ................................................................................................ 8 Design and Development of a New Flux Chamber Technology ............................................... 9 Calibration Approach and Methods ......................................................................................... 12 Data Analysis: Algorithms for Processing and Interpreting Measured Concentration and Flux Data ......................................................................................................................................... 15 DISCUSSION OF ANALYSIS AND RESULTS ..............................................................................31 CRDS Concentration Measurements...................................................................................... 31 Calibration Results .................................................................................................................. 33 Flux Analysis Results .............................................................................................................. 35 CONCLUSIONS .............................................................................................................................49 Recommendations for Future Work ........................................................................................ 50 Appendices A: SOIL FLUX CALIBRATION ........................................................................................................52 B: MATLAB CODES .......................................................................................................................57 C: RAW CHAMBER FLUX DATA ...................................................................................................76 REFERENCES ...............................................................................................................................98 LIST OF FIGURES Figure Page 1 Aerial View of Study Site with Sewer Access Designations and Flow Regime ...................... 20 2 Laboratory Chamber Calibration Setup .................................................................................. 22 3 HMR Example of a Nonlinear Curve Fit .................................................................................. 23 4 HMR Example of a Linear Curve Fit ....................................................................................... 24 5 2012 Methane Concentration Summary ................................................................................. 25 6 2012 Carbon Dioxide Concentration Summary ...................................................................... 26 7 June 2013 Methane Concentration Summary ........................................................................ 27 8 June 2013 Carbon Dioxide Concentration Summary ............................................................. 28 9 July 2013 Methane Concentration Summary .......................................................................... 29 10 July 2013 Carbon Dioxide Concentration Summary ............................................................... 30 11 Concentration Measurements of CO2 (above) and CH4 (below) at Sewer Access Cover MH1 on June 21, 2013 ................................................................................................. 39 12 Concentration Measurements of CO2 (above) and CH4 (below) at Sewer Access Cover MH0 on June 26, 2013 ................................................................................................. 40 13 Concentration Measurements of CO2 (above) and CH4 (below) at Sewer Access Cover MH0 on June 27, 2013 ................................................................................................. 41 14 Concentration Measurements of CO2 (above) and CH4 (below) at Sewer Access Cover MHSU1 on July 3, 2013 ............................................................................................... 42 15 Chamber Laboratory Calibration Curves ................................................................................ 43 16 CRDS versus NDIR Analyzer Flux Data for MH4 ................................................................... 44 17 CRDS versus NDIR Analyzer Flux Data for MHSU3 .............................................................. 45 LIST OF TABLES Table Page 1 General Sewer Access Cover and Line Data ......................................................................... 21 2 Chamber Flux Calibration Results .......................................................................................... 44 3 Flux Gradient Data .................................................................................................................. 46 4 Sewer Access Cover Trends Based on Calculated Diffusive Flux Method versus Field Measured Flux ........................................................................................................................ 46 5 Sewer Access Cover Trends Based on Source Area versus Field Measured Flux ............... 47 6 Cover ID Flux Data.................................................................................................................. 48 7 Soil Flux Chamber and Method Comparison Summary ......................................................... 53 8 NDIR Analyzer with NDIR Chamber Soil Flux Measurements ............................................... 54 9 NDIR Analyzer with Built Chamber Soil Flux Measurements ................................................. 55 10 CRDS with Built Chamber Soil Flux Measurements ............................................................... 56 11 Raw CO2 Flux Chamber Data ................................................................................................. 77 12 Raw CH4 Flux Chamber Data ................................................................................................. 91 NOMENCLATURE CRDS Cavity Ring Down Spectrometer CH4 Methane CO2 Carbon dioxide GHG Greenhouse gases HRT Hydraulic retention time LLGHG Long-lived greenhouse gases NDIR Nondispersive infrared ppmv Parts per million volume ppbv Parts per billion volume STD Standard Deviation VOC Volatile organic compounds INTRODUCTION As population increases, the concentration of anthropogenic greenhouse gases (GHG) released into the atmosphere also increases. The top contributing long-lived greenhouse gases that occur naturally but are greatly increased by human activity are carbon dioxide, methane and nitrous oxide. According to the IPCC (1), long-lived greenhouse gases (LLGHG's) are classified as gases that are chemically stable and remain in the atmosphere up to decades or longer. These gases can have long term effects on climate change and become well mixed in the atmosphere much faster than they are removed (1). Over the years the ambient concentrations have continued to rise. CO2 is currently around 394 ppmv and CH4 is about 1.8 ppmv in 2012, on average according to the Environmental Protection Agency (2). CO2 has shown an approximate 100 ppmv increase in concentration since 1750 and has been attributed mainly to the burning of fossil fuels. CH4 has seen a concentration increase of about 1000 ppbv in the last two centuries, which can be accredited to many anthropogenic sources such as biomass burning and wastewater treatment (1). Locally, according to a report by Salt Lake City Energy and Carbon Advisory Committee and the Salt Lake City Division of Sustainability and Environment (3), the Salt Lake City community emission was 4.75 million Mt CO2e per year. It is hypothesized that increases in GHG emissions can lead to changes in global climate. Associated impacts can include higher sea levels, ocean acidification, animal extinctions, droughts in some areas or increased water availability, higher average global temperatures, and other potential factors that are yet to be foreseen (1). Within a local level, increasing droughts may 2 cause an increased demand on what can apparently be seen as an already strained water system. An escalation in wildfire frequency and less snow melt due to unusually longer periods of higher annual temperatures could also occur as well. This in addition can add to the overall bad air quality due to the local topology which traps pollutants effectively in the air through the inversions. It is known that emissions of CO2 and CH4 by anthropogenic sources are increasing; therefore, it is important to identify, quantify and mitigate or reduce the release of these gases within the earth's atmosphere. There are significant data to represent the portion of emissions coming from many of these sources, such as sewage treatment plants. However there is little information on the sewer transport system as a whole, particularly pertaining to CH4 and CO2. Volatile organic compounds (VOC's) and hydrogen sulfide have been studied within the sewer transport system due to these gases' detrimental effects on human life and the regulations for exposure limits in the workplace. These regulations have however created the need for studies on gas transport in the sewer transport system specifically regarding VOC's. (4) (5). Literature Current literature suggests that release of CO2 and CH4 associated with wastewater transport may be significant. Foley et al. (6) measured the dissolved methane concentrations along a single rising main off the Gold Coast area in Queensland, Australia. Four major locations were measured: a pump station wet well, a pressurized sampling point 500 m downstream, a pressurized sampling point 1,100 m downstream, and a pressurized sampling point 1,900 m downstream of the pump station. The measured data were correlated with the sewer pipeline geometry (area and volume) and the hydraulic retention time (HRT) to determine a release rate. Assuming that all dissolved methane was assimilated as gas into the atmosphere, it was concluded 3 that based on the measurements there was substantial methane release potential of 230 Mt CO2e per year. A case study by Willis et al. (7) measured methane concentration released from wet wells in DeKalb County, GA and then used the monthly average flow rates to calculate the approximate emissions from 60 low flow (<700 gpm) gravity lift stations and 4 high flow (>2000 gpm) lift stations. The calculated methane emissions from these lift stations came to roughly 940 Mt CO 2e per year. Guisasola et al. (8) made simulated measurements in a lab experiment as well as field measurements at two pressurized rising mains of the Gold Coast area in Australia. This method used dissolved methane concentration and HRT to calculate the field methane flux. The lab scale measurements were done using a reactor based system and assumed all the dissolved methane from the sewage discharged was assimilated into the atmosphere. The methane released was approximated to be within the range of 900-5300 Mt CO2e per year. Transportation of gases through sewer systems was studied in reference to ventilation and horizontal gas transport. Madsen et al. (9) analyzed the horizontal gas transport process in an intercepting gravity sewer by measuring the velocity and dispersion of the gas in the sewer atmosphere in Denmark. Transport of sewer gas was determined by pulse injecting molecular oxygen at an injection station to change the composition of the sewer atmosphere. The oxygen concentration was measured downstream of the injection zone. This allowed the gas velocity, coefficient of dispersion and ventilation rate to be calculated. It was observed that gas transport was non-uniform. Dispersion was present in 71% of experiments and not present in 29%. Their system showed little to no ventilation or re-aeration. They concluded this could have been due to fewer openings and no side connections. When covers were opened there was an increase in ventilation but it was still considered low. The study concluded that the sewer gas transport was caused by an inflow of gas to the upstream part of the gravity sewer, followed by horizontal 4 transport along the sewer line and outflow of gas at the end of the sewer. It was also concluded that variations in climatic conditions did not influence gas velocity or the coefficient of dispersion. Using carbon monoxide as a tracer gas, Parker et al. (10) injected the tracer gas into a fullscale collector sewer and the concentration was monitored along the upstream and downstream. Temperature, wind speed, and barometric pressure were also obtained and compared to the data. The data showed that the velocities and flow rates varied with distance and time along the sewer. Lower velocities resulted in higher tracer gas loss through the system, which was assumed to be lost through the sewer access cover. Higher velocities tended to show a smaller loss in tracer gas. Gas phase flows from the headspace were estimated and there was an increase in flow farther downstream. There was a lack of repeatability with the gas flow, suggesting that it was dependent upon a time-varying mechanism such as wind draft from the sewer access cover but was inconclusive. In general, the literature provides little to no information on the release of CO2 (into the atmosphere) from the sewers. Methane emissions described were mostly based on the potential of dissolved methane released or on lab scale testing, which was said to be an overestimate by the Guisasola et al. (8) experiment as mentioned previously. These studies do not directly measure flux out of the sewer access covers or other specific points in the sewer transport system. A better estimation of emissions from a given wastewater transport system could be determined by directly reading and quantifying the release from a direct source. Project Study The current studies present limited data on the contribution of CO2 and CH4 to the atmosphere and all vary in the methods and approach. In this thesis a new method was presented to measure directly from the source, the sewer access covers, which could reasonably measure 5 the gas release and accumulation rates. By studying the release of CO2 and CH4, the implementation of a direct, portable chamber method was systematically created for point emission sources enabling a simultaneous measurement CO2 and CH4 concentration and gas flux. This thesis describes the study site, equipment, instrument design and assembly followed by the algorithms necessary for flux calculation. Surveys (field measurements) of CO2 and CH4 concentration and gas flux at the study site, the University of Utah campus, are presented and discussed. Efforts were made to verify and calibrate the on-site survey measurements through field and laboratory calibration with a summarization of how the measurements are used to determine an estimate of the annual emissions release from the 11 sewer access covers is provided. While 11 sewer access covers only represent a small sample of the overall system, the results could lead to understanding the release and behavior of the system on a larger scale. RESEARCH APPROACH: EQUIPMENT, MEASUREMENTS AND ANALYSIS University of Utah Campus Case Study: Site Description All data were collected on the University of Utah campus located in Salt Lake City, Utah. The study area focused on the gravity sewer lines around the Student Union, the Civil and Materials Engineering Building, HEDCO, Frederick Albert Sutton Building, William Browning Building, Orson Spencer Hall, Languages and Communications Building, Sterling Sill Center and the Experimental Studies Building. James Staples with the University of Utah Plumbing Shop provided general sewer line data as seen in Figure 1 and Table 1. The Student Union lines were completed in 1955; lines with the designation MHSU in Figure 1. The lines around the HEDCO were also completed in the 50s; lines designated with an MH in Figure 1. Therefore the sewer lines within the study area were around 59-64 years old. Salt Lake City's climate is subhumid, with dry summers and wet winters. The concentration measurements discussed in this study were taken in late September 2012 and then sporadically, weather permitting, through July 2013. Flux measurements were taken from September 2013 through January 2014, again intermittently due to weather limitations. For the flux measurements 11 sewer access holes were studied along two separate sewer lines. Figure 1 shows the sewer access cover locations along the sewer lines, the flow regime and each access cover designation. More access covers were studied but many were outside of the scope of this study and some were found to be linked to inactive or abandoned lines and were not studied in great detail. 7 Equipment A chamber method was designed around a viable and accepted method; a soil flux chamber. CO2 and CH4 soil flux chambers are separately, readily available from various suppliers of such technologies; however custom chambers would presumably need to be ordered for this project and would require two separate instruments. Due to limited resources and the availability of only two gas analyzers through the University of Utah, the design and construction of a custom chamber was done in house. The two gas analyzers used for these measurements utilize two different processes to determine gas concentration. The Picarro G2311-F uses a laser-based cavity ring down spectroscopy (CRDS) method, which measures continuous streams of water vapor, CO2 and CH4 concentrations through an inlet tube that feeds directly to the instrument. The CRDS is highly sensitive, measuring absolute optical extinction by samples that scatter and absorb light at specific wavelengths. The CRDS unit measures the CO2 concentration to one standard deviation precision of 200 parts per billion volume (ppbv), CH4 to a precision of 2 ppbv, and water vapor to 20 parts per million volume (ppmv) precision (11). The CRDS on its own is only able to measure the concentration at a point or along a line; however it can also be fit to a chamber or a flux tower to measure concentration over a point source or area. The CRDS requires a 2000 watt inverter generator to accommodate the approximate 1000 watts necessary for the complete CRDS system to run. The generator allows for around 6-8 hours of run time with the CRDS system. For field measurements two heavy-duty wagons were used to tow the CRDS system, pump, generator, the CRDS GPS unit, battery and monitor. The system is more accurate when there is little to no wind to disrupt the concentration values. The Li-COR 8100 is a nondispersive infrared (NDIR) gas analyzer that measures CO2 soil flux. This technique uses energy absorption characteristics of a particular gas, CO2, in the infrared 8 region to determine concentration. The flux is measured by observing the rate of CO2 increase within a chamber to estimate the rate at which CO2 diffuses into free air outside of a specified chamber. The Li-COR 8100 has an accuracy of 1.5% of the reading for both CO2 and H2O with a measurement range of 0-3000 ppm for CO2 and 0-80 mmol/mol for H2O. The NDIR analyzer can be fitted to various chambers developed by Li-COR Biosciences or can be fitted to a customary chamber measuring the concentration or flux over the chambers specified area. The Li-COR 8100 system has multiple components that were utilized in this study. The analyzer control unit houses the electronics, infrared gas analyzer, internal and external memory, and wireless communications compatible with a palm pilot with loaded software or with any apple ipod, iphone or ipad. The NDIR analyzer also has a 20 cm survey chamber that is utilized for calibration. The system has rechargeable batteries for easy use during field surveys as well as a 110V wall connector for lab experiments or use with a generator (12). CRDS Concentration Readings Using just the CRDS analyzer concentration readings were done primarily in the fall of 2012 and the summer of 2013. Most measurements were done along specific sewer lines, maintaining a measurement at the access holes for a few minutes at a time. The measurements focused on the area above the sewer lines and any sewer access covers. A few specific sites were chosen for long term measurements; defined as greater than 4-hour time increments. Measurements taken in the fall of 2012 were mostly done between 12:00 pm and 3:00 pm. During the summer of 2013, measurements were done on an almost daily basis running approximately the same route two to three times weekly. At least four 5 to 8-hour measurements were completed on an individual access cover that showed potential for larger concentrations. This was done to help determine the diurnal variations and to show any possible trends in the data. Over 9 35 days of readings were taken over the 10-month period, of which many of the measurements focused on other sewer access covers outside of the scope of this study. Limitations on the quantity of measurements able to be taken were incurred during this time due to weather and equipment related issues. The issues encountered were typically due to valve leaks, debris in the tube and a several month period where the equipment was sent back to the distributor to get the power board replaced. Design and Development of a New Flux Chamber Technology To determine the accumulation rates released from the sewer lines, two chambers were designed and built to determine the CH4 and CO2 flux simultaneously. A design was implemented to accommodate concentration measurements using the CRDS and the NDIR analyzer. Two 55gallon plastic garbage cans were acquired for the chambers. The 55-gallon size fits completely around the sewer access covers 26 ½" diameter. A comparison study done by Pihlatie et al. (13) tested 15 chambers currently used in the biological community to compare each design for advantages and disadvantages. The study discussed how using a larger chamber reduces the negative effects of a chamber and minimizes the underestimation of the flux. These chamber sizes were significantly smaller than that of the 55-gallon chamber we experimented with, but it is hypothesized that the larger chamber size will hold to these conclusions. Parkin et al. (14) presented a study through the National Laboratory of Agriculture and the Environment with their USDA-ARS GRACnet Project that put out a protocol for creating a flux chamber that measures trace gases. The project focused on N2O, CO2 and CH4 measurements from soil. The chapter they presented goes through each issue presumably faced when creating a chamber and ways to mitigate these issues. Some issues do not directly apply to this study, mainly soil diffusion. Nevertheless their suggestions were helpful for current and future 10 deployment for site-specific uses. Parkin et al. (14) also suggested that using a larger chamber height as well as shorter deployment times would both decrease the negative chamber effects. Utilizing the CRDS ring down spectrometer allowed for shorter deployment times due to the ability to take accurate readings multiple times per second, instead of using a syringe at various times during the measurement as in the Parkin (14) study. Another relevant suggestion in the study is to use a manifold to pull gas from multiple areas of the chamber instead of mixing the inside of the chamber with a fan, which can cause pressure perturbations. The Parkin (14) study highly suggested that diurnal variation should be taken into account and can be done by measuring the fluxes at various times during the day. It was also recommended that flux is measured directly after a perturbation-induced event and properly venting the chamber to allow for natural movement of the gas (14). Xu et al. (15) presented research On Maintaining Pressure Equilibrium Between a Soil CO2 Flux Chamber and the Ambient Air. The research presented concern with the flux chamber regarding whether the equilibrium between the inside of the chamber and the surrounding air outside will be maintained during measurements. Having small pressure changes from the surrounding ambient pressure can cause anomalous mass flow, which can lead to over or underestimations of the flux. There has been research showing that using a vent tube connected to the chamber helps in maintaining the pressure. This method however presents the concern the vent tube will cause a significant loss. However if considerations were given to the internal diameter and length of the vent tube, the loss is not likely to be significant. The main issue with having a vent tube would be during windy conditions where negative pressure excursions will occur as wind blows over the vent tube's opening. There has been research on types of vent designs that would lessen this Venturi effect that could easily be used. The chamber measurements should also be made on a steady impermeable collar, for this study was 11 substituted for the manhole casing, which was both steady and impermeable. These chamber reports were based on a soil flux chamber and results and conclusions may vary based upon the different source and subsurface conditions. However the theory is assumed to be similar enough for relative accuracy. The assumption is also made that the large chamber and the CRDS unit vacuum suction would help to simulate natural flow. This assumption was not tested for accuracy. To achieve a seal around the opening of the garbage can 1-inch diameter pipe insulation was used with a silicon caulking, along with a removable weight. The chamber's intent is to be used with the CRDS and the NDIR analyzer, so push lock fittings were obtained for easy transition and seal; the CRDS requires a 1/8" connection and a 1/4" for the NDIR analyzer. All tubing was high density, nonreactive polyethelene, used for its low permeability rate for the project's tested gases. The garbage can is gray, so to achieve a more reflective surface it was painted white using spray paint that was adhesive to plastic. This created a reflective, nonreactive surface which helped to prevent any drastic temperature changes within the chamber during deployment. The deployment method was approximately 10 minutes with at least 2-3 back-to-back measurements. The chamber was evacuated after every reading to prevent issues with high headspace concentrations, which can affect the measured rates. Measurements were done repeatedly throughout different time periods to show the diurnal changes. Most sewer access cover measurements were only taken a few times per cover. However on a few occasions there were more long term readings, including two 24-hour sittings. Over 250 flux measurements were taken between September 2013 and January 2014 with the NDIR analyzer and CRDS over the 11 sewer access holes specified in the project area (Figure 1). Most measurements were taken with the CRDS as it measures CH4 and CO2 simultaneously, but the NDIR analyzer was useful for verification of CO2 measurements and trends. Laboratory and field calibration efforts were made to verify the data using the NDIR and 12 CRDS. The laboratory calibration involves a comparison of chamber measurements to artificial (controlled) fluxes, whereas the field calibration compared flux chamber measurements to natural (uncontrolled) fluxes. Both calibration efforts use both gas analyzers and the two built chambers for comparison; the lab calibration also incorporated the NDIR analyzer's custom 20 cm chamber. The NDIR measurements along with laboratory measurements used for calibration were discussed in the subsequent sections. Calibration Approach and Methods For the laboratory-based calibration, a CO2 gas mixture required a concentration greater than ambient conditions, but not too high for equipment accuracy. The most reasonable range is between 800 and 2000 ppmv as it would adequately mimic the average elevated values seen in the field. Using a K sized partially filled nitrogen tank, pure CO2 was added until reaching a value of CO2 approximately equal to 1300 ppmv. Using the CRDS and NDIR analyzers, the built chambers were calibrated against the NDIR analyzer's original custom-built 20 cm survey chamber. The known CO2 gas concentration cylinder was used to create a consistent flux using a pressure gauge and flow meter. The laboratory setup for the built chamber using either the NDIR analyzer or CRDS is shown in Figure 2. A platform large enough to accommodate the chambers' diameter was created allowing for a point source leak using the gas from the cylinder with the known CO2 concentration. Three separate flow rates were used to determine the relationship between the chambers and create a best-fit curve. This allowed for the creation of correction ratio curves which were used to determine a correction factor that was applied to each chamber measurement based on method and chamber type. The NDIR analyzer's chamber and built chambers were each used multiple times during the laboratory session to measure the flux from the lab generated point source in 13 order to generate a valid average and standard deviation. The CRDS analyzer was used right after the NDIR sensor and measured under the same conditions using the built chambers. The measurements were done one after another for 10-minute intervals with a 5-minute resting period in between to allow for gas evacuation from the chambers. In the field the NDIR analyzer was used in conjunction with the CRDS as an additional way to calibrate the measurements. The NDIR analyzer was not used at the same time as the CRDS due to the system constraints. Each method was used on the same point source (sewer access) cover for 10 minutes with a 5-minute resting period for chamber gas evacuation and then following with the opposing analyzer method. This created a 10 to 20-minute gap between the data using the same chamber, due to swapping each analyzer method in between measurements. It was assumed that the short interval with which the chambers were switched would allow for an accurate calibration of the two analyzer methods, assuming the system did not change during this time. Only the built chambers were used for the point source due to the NDIR analyzer's chamber not being conducive to the large diameter of the sewer access cover. These back to back measurements were done for a 24-hour period on October the 25th - 26th and a few hours on October the 28th. A soil flux measurement was also done using both analyzers. The NDIR analyzer was run using its original chamber for 10 measurements directly on the soil. Then the NDIR analyzer was set on the same soil area with the built chamber right next to the CSDR analyzer with the twin built chamber. The analyzers ran coincidentally for the same amount of time. These measurements analyzed whether the CRDS coupled with a built chamber would be valid for soil flux measurements; this information is presented in Appendix A. The correction factors determined were assumed to be valid for both CO 2 and CH4. This may cause an over- or underestimation for CH4 flux considering the gas properties vary 14 significantly when compared to CO2. This assumption was made based upon the inability to measure CH4 with an accurate alternative method due to financial and time constraints. The correction ratio curves were developed in terms of flux and were curbed to the NDIR analyzer as it is an accepted method and used widely in the biological industry. The range of flux rates used in the lab experiments were assumed to validate the field data relatively based on similar gas concentrations seen in the field. When analyzing the flux data potential, outliers were investigated and assumptions were made on the concentration versus time plots (used for calculating flux) shown to have sporadic data. The assumption was made that these inaccuracies were based on human error such as improper seal at the leak sight. It was also assumed that if the concentration versus time plots had high initial values contradictory to what should be seen with proper evacuation and then coincidentally had a lower concentration over time, indicating a negative flux, then these values were assumed to be errors from improper evacuation. Concentration versus time plots having less than a ~2 ppmv change for CO2 and less than ~0.3 ppmv change for CH4 were assumed to be a zero or no flux reading. Lab experiments were done to verify these assumptions; similar trends were seen when initiating a controlled leak and improper seal. Therefore the assumptions were assumed to be valid. There was an issue with respect to the type of method each analyzer uses. It was unclear the effects using two different methods would have on the measurements and the limitation that only CO2 could be compared and not CH4. Some issues when using the NDIR analyzer in conjunction with the CRDS are the equations the NDIR analyzer use are more in depth and have more correction coefficients that are not necessarily readily available or relevant to this specific study site, considering the NDIR was specifically created for soil flux. This issue was bypassed by locating and directly reading the concentration data within the NDIR analyzer and using a more 15 generalized or site specific equation when determining the flux that corresponds well with the site specific built chamber. The equations and algorithms for data processing and interpretation of the measured field and laboratory data are discussed next section. Data Analysis: Algorithms for Processing and Interpreting Measured Concentration and Flux Data The data are logged internally in the CRDS unit. The unit outputs the date, time, water vapor, CH4, and CO2 concentration for both dry concentration and in air. A GPS unit was fitted and gave the spatial location in latitude and longitude. Due to the excess of data from the CRDS unit, the data were queried to focus the information for better analysis. The CRDS creates large .dat files that are difficult for a word processing program; therefore a script in Matlab was created called pcut found in Appendix B. This script was used to import the data files, reformat the data and then cut both the CO2 and CH4 at a specific threshold value that eliminates ambient conditions and any outlying data determined by observation or user input. The observation value took into account the ambient concentrations for CO2 (~290 ppmv) and CH4 (~1.87 ppmv) as well as the typical concentrations that were created from outside sources, such as passing vehicles. The cut data were exported into a comma delineated format that is acceptable for importation into the ArcGIS program, a mapping and spatial visualization software. The data have the date, time, CH4 and CO2 concentrations, as well as spatial information from the GPS and any other user depicted values. The code was created for use in future analysis and allows for any delimited formatting. Details can be found in Appendix B. Once the concentration data from the CRDS were reformatted, it could either import into ArcGIS or be used for flux calculation. The concentration measurements (no chamber readings) were imported in ArcGIS where the XY data were defined in latitude and longitude for spatial referencing. Shapefiles (a geospatial vector data format) of the sewer utility lines and 16 maintenance cover locations were acquired from the University of Utah Facilities Management and were overlayed on a tagged image file format (TIFF) map of the University of Utah. The TIFF file was obtained from gis.utah.gov. Both the campus map and the utility shapefiles originated in UTM coordinates. Therefore the CRDS data were projected from the WGS 1983 geographical projection to UTM 1987 zone 12 projected coordinates. After the data were modified into a feature class (a classification format of geographic features and supporting data in a coverage) with the correct projection, the data were visually quantified by graduated symbols. The symbol values represent the CO2 and CH4 concentrations values in a range from low to high. The sewer line feature class was copied and modified to encompass only the area of analysis as shown in Figure 5 through Figure 10. These data were then used to create a flow regime, which was developed from observations of the campus topography and the sewer lines (Figure 1). The CRDS spectrometer was also used to gather headspace concentrations at each of the 11 sewer access holes. The covers were removed and the depth, headspace concentration and surface concentrations were measured using only the CRDS. These data were used with Fick's Law, Eq. 1, to calculate the diffusive flux gradient. This equation was used under the assumption that the sewer access covers were under a steady state and exhibit an ideal mixture relationship during the measurement time (<2-minutes). The diffusion coefficients for methane (CH4) and carbon dioxide (CO2) in air were found from the USDA Forest Service website. These values were determined with the understanding that this applies only for near standard temperature and pressure values. This assumption should be valid for this study because the analyzed sewer lines are no more than 11-feet below the surface. This method was used to determine any diffusional relationship in gas transport within the sewer. 𝐽𝐽 = −𝐷𝐷 𝜕𝜕𝜕𝜕 𝜕𝜕𝜕𝜕 (Eq. 1) 17 𝐽𝐽 = 𝐷𝐷𝐷𝐷𝐷𝐷𝐷𝐷𝐷𝐷𝐷𝐷𝐷𝐷𝐷𝐷𝐷𝐷 𝐹𝐹𝐹𝐹𝐹𝐹𝐹𝐹 ( 𝑎𝑎𝑎𝑎𝑎𝑎𝑎𝑎𝑎𝑎𝑎𝑎 𝑜𝑜𝑜𝑜 𝑠𝑠𝑠𝑠𝑠𝑠𝑠𝑠𝑠𝑠𝑠𝑠𝑠𝑠𝑠𝑠𝑠𝑠/𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉/𝑇𝑇𝑇𝑇𝑇𝑇𝑇𝑇) 𝜑𝜑 = 𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶 (𝑎𝑎𝑎𝑎𝑎𝑎𝑎𝑎𝑎𝑎𝑎𝑎 𝑜𝑜𝑜𝑜 𝑠𝑠𝑠𝑠𝑠𝑠𝑠𝑠𝑠𝑠𝑠𝑠𝑠𝑠𝑠𝑠𝑠𝑠/𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉) 𝑥𝑥 = 𝑃𝑃𝑃𝑃𝑃𝑃𝑃𝑃𝑡𝑡𝑖𝑖𝑖𝑖𝑖𝑖 (𝑙𝑙𝑙𝑙𝑙𝑙𝑙𝑙𝑙𝑙ℎ) 𝐷𝐷 = 𝐷𝐷𝐷𝐷𝐷𝐷𝐷𝐷𝐷𝐷𝐷𝐷𝐷𝐷𝐷𝐷𝐷𝐷 𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐 𝑜𝑜𝑜𝑜 𝐷𝐷𝐷𝐷𝐷𝐷𝐷𝐷𝐷𝐷𝐷𝐷𝐷𝐷𝐷𝐷𝐷𝐷𝐷𝐷𝐷𝐷 (𝑎𝑎𝑎𝑎𝑎𝑎𝑎𝑎/𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡) In order to calculate the chamber flux, the data files from each analyzer required reformatting for compatibility into R, a statistical analysis program, and combined with the HMR package function. HMR is an R package found to calculate the flux for a static closed chamber. R is a free statistical analysis package created by Robert Gentleman and Ross Ihaka from the University of Auckland in New Zealand. The HMR package within R was created by Asger R. Pedersen to estimate flux within a static chamber using nonlinear regression or linear regression analysis. In most practices, a linear best fit curve is used on the data but according to a study by Pihlatie et al. (13), using an exponential fit when determining the flux rate, better captures the concentration development within the chamber when compared to a linear regression fit. This HMR program package requires separated columns for the series name, chamber volume, chamber cross sectional area, time elapsed and the concentration in a comma separated value format (.csv). The series name in our case was the sewer access cover name (e.g., MH4). The Matlab scripts calculated the elapsed time from initiation to the end of deployment in minutes; the script for the CRDS analyzer is called Rflux and NDIR analyzer uses the Lflux script; both scripts are found in Appendix B. It should be noted that the CRDS records data in milliseconds, but the deployment time was taken manually to the nearest minute. Therefore these data were inspected manually within the said minute of recorded data and approximated to the nearest second. The volume remains constant and is based on the chamber used; for this study there were 2x55 gallon (208,198 cm3) garbage cans or the 20 cm NDIR analyzer survey chamber (4,843 cm3). The cross sectional area is dependent upon the source. For the purposes of this study the area was unitized, giving flux in µL/min or grams/day. The concentrations were taken from the start and end time of deployment for either CH4 or CO2. The start and end time 18 are important as the flux is defined as the change in concentration over a corresponding change in time according to the chamber volume and the source cross sectional area as shown in Eq. 2. 𝐹𝐹 = 𝑑𝑑𝑑𝑑 𝑉𝑉 𝑑𝑑𝑑𝑑 𝐴𝐴 (Eq. 2) 𝐹𝐹 = 𝐹𝐹𝐹𝐹𝐹𝐹𝐹𝐹 ( 𝜇𝜇𝜇𝜇/𝑚𝑚2 /𝑚𝑚𝑚𝑚𝑚𝑚) 𝑑𝑑𝑑𝑑 = 𝐶𝐶ℎ𝑎𝑎𝑎𝑎𝑎𝑎𝑎𝑎 𝑖𝑖𝑖𝑖 𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐 (𝑝𝑝𝑝𝑝𝑝𝑝𝑝𝑝 𝑜𝑜𝑜𝑜 𝜇𝜇𝜇𝜇/𝐿𝐿) 𝑑𝑑𝑑𝑑 = 𝐶𝐶ℎ𝑎𝑎𝑎𝑎𝑎𝑎𝑎𝑎 𝑖𝑖𝑖𝑖 𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡 (𝑚𝑚𝑚𝑚𝑚𝑚) 𝑉𝑉 = 𝐶𝐶ℎ𝑎𝑎𝑎𝑎𝑎𝑎𝑎𝑎𝑎𝑎 𝑣𝑣𝑣𝑣𝑣𝑣𝑣𝑣𝑣𝑣𝑣𝑣 (𝐿𝐿) 𝐴𝐴 = 𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆 𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴 (𝑚𝑚2 ) HMR uses a nonlinear function by Hutchinson and Moiser (Eq. 3) using a single parameter (k) criterion or simple linear regression to determine the best fit for the flux data. The program will then recommend the best fit for the data. Criterion plots were shown along with the data plot and its various fit curves as seen in Figure 3 and Figure 4. In the figures it shows an MSE criterion vs. log (k) on the upper left hand side. This was the mean squared error (MSE) for the feasible values of k and the upper right hand plot was the close up for the recommended value for k shown in blue. The actual data plot and curve fits were shown in the lower left corner along with the recommendation. The recommendation will show as nonlinear (HMR) as in Figure 3 or linear (LR) as shown in Figure 4. The buttons shown in the lower right hand corner were the choices for which fit you would like to calculate the flux. 𝐶𝐶𝑡𝑡 = 𝜑𝜑 + 𝑓𝑓0 𝑒𝑒 −𝑘𝑘𝑘𝑘 (Eq. 3) 𝐶𝐶𝑡𝑡 = 𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶 𝑎𝑎𝑎𝑎 𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡 𝑡𝑡 𝜑𝜑 = 𝑁𝑁𝑁𝑁𝑁𝑁 𝑐𝑐ℎ𝑎𝑎𝑎𝑎𝑎𝑎𝑎𝑎𝑎𝑎 𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒 𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐 𝑓𝑓0 = 𝐼𝐼𝐼𝐼𝐼𝐼𝐼𝐼𝐼𝐼𝐼𝐼𝐼𝐼 𝑓𝑓𝑓𝑓𝑓𝑓𝑓𝑓 𝑘𝑘 = 𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴 𝑟𝑟𝑟𝑟𝑟𝑟𝑟𝑟 𝑑𝑑𝑑𝑑𝑑𝑑𝑑𝑑𝑑𝑑𝑑𝑑𝑑𝑑𝑑𝑑𝑑𝑑 𝑜𝑜𝑜𝑜 𝑡𝑡ℎ𝑒𝑒 𝑠𝑠𝑠𝑠𝑠𝑠𝑠𝑠, 𝑔𝑔𝑔𝑔𝑔𝑔 𝑎𝑎𝑎𝑎𝑎𝑎 𝑐𝑐ℎ𝑎𝑎𝑎𝑎𝑎𝑎𝑎𝑎𝑎𝑎 𝑐𝑐ℎ𝑎𝑎𝑎𝑎𝑎𝑎𝑎𝑎𝑎𝑎𝑎𝑎𝑎𝑎𝑎𝑎𝑎𝑎𝑎𝑎𝑎𝑎𝑎𝑎𝑎𝑎, 𝑘𝑘 > 0 𝑡𝑡 = 𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡 After a fit was chosen by the user, values were determined for the estimated flux, standard deviation, p-value for the null hypothesis of zero flux, the lower end point of the 95% confidence interval, and the upper end point of the 95% confidence interval for the flux. The flux units were determined by user input parameters and in this case the concentration was in ppmv 19 so the volume is in liters, area is in m2, and time is in minutes. This will give us a flux in µL/m2/min, but since the area is unitized the flux becomes µL/min. Along with imputing the flux data information for each chamber flux reading, the temperature and pressure during the reading time was recorded using the wunderground weather data. This information was then used to determine the density for CH4 and CO2 using their individual equations of state from the peace software website developed by the programmer Berndt Wischnewski from the Max Plank Institute for Human Development. The densities are used to convert the flux units of µL/m2/min to g/m2/day and µMole/m2/sec. These values can all be found in relation to their correlating flux measurement in Appendix C. All flux calculations were quantified by converting the CH4 and CO2 into Metric Tons CO2 equivalent (Mt CO2e). This was done using Eq. 4. The time was expressed in 1 year for easy comparison. The Global Warming Potential (GWP) from US Environmental Protection Agency (EPA) for methane is 21, meaning methane has 21 times more potential for trapping heat in the atmosphere when compared to CO2. 𝑀𝑀𝑀𝑀 𝐶𝐶𝑂𝑂2 𝑒𝑒 𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡 𝑔𝑔 𝐶𝐶𝑂𝑂 1 𝑀𝑀𝑀𝑀 𝐶𝐶𝑂𝑂 = 𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡2 × 1000000 𝑔𝑔 2𝐶𝐶𝑂𝑂 × 𝐺𝐺𝐺𝐺𝐺𝐺 𝐺𝐺𝐺𝐺𝐺𝐺 = 𝐺𝐺𝐺𝐺𝐺𝐺𝐺𝐺𝐺𝐺𝐺𝐺 𝑤𝑤𝑤𝑤𝑤𝑤𝑤𝑤𝑤𝑤𝑤𝑤𝑤𝑤 𝑝𝑝𝑝𝑝𝑝𝑝𝑝𝑝𝑝𝑝𝑝𝑝𝑝𝑝𝑝𝑝𝑝𝑝 2 (Eq. 4) 20 Figure 1: Aerial View of Study Site with Sewer Access Designations and Flow Regime 21 Table 1: General Sewer Access Cover and Line Data Location Length (m) Depth (m) % Slope Source Area (m2) MH00 1.8 60.5 MH0 3 MH1 MH2 0.007 3 MH3 0.003 2.7 MH4 MHSU6 0.002 3 3.4 MHSU5 0.005 0.005 3 MHSU4 0.004 1.5 MHSU3 0.005 2.6 Concrete 0.1524 [6] 0.004 4.58 1.8 Concrete 0.1016 [4] 1.95 113.7 Concrete Concrete 0.1016 [4] 5.85 107.9 Concrete 0.1524 [6] 3.02 42.8 Concrete 0.1524 [6] 2.28 53.0 Concrete 0.1524 [6] 3.85 100.9 Concrete 0.1524 [6] 7.03 70.2 Concrete 0.003 1.8 Type 0.1524 [6] 5.77 59.9 MHSU1 0.003 0.33 31.3 Pipe Diameter (m)[in] Concrete 0.2032 [8] 0.002 Concrete 22 Figure 2: Laboratory Chamber Calibration Setup 23 Figure 3: HMR Example of a Nonlinear Curve Fit 24 Figure 4: HMR Example of a Linear Curve Fit 25 Figure 5: 2012 Methane Concentration Summary 26 Figure 6: 2012 Carbon Dioxide Concentration Summary 27 Figure 7: June 2013 Methane Concentration Summary 28 Figure 8: June 2013 Carbon Dioxide Concentration Summary 29 Figure 9: July 2013 Methane Concentration Summary 30 Figure 10: July 2013 Carbon Dioxide Concentration Summary DISCUSSION OF ANALYSIS AND RESULTS CRDS Concentration Measurements Figure 5 through Figure 10 show symbolized values of the CO2 and CH4 measurements in concentration from low to high. The figures symbolize values relative to the sewer access covers but not necessarily directly over them. This was due to a proximity error with the equipment and GPS location accuracy at the time of measurement. The GPS was at times positioned as far as 2 meters away from the actual measurement location. This was done to mitigate the effects of the generator exhaust on the concentrations and close proximity of a body to the GPS creates interference with the accuracy. The 2012 measurements have been summarized for the 2 months of viable data collected. The methane concentration values taken from the sewer access covers showed highs of up to 130 ppmv. The highest values were seen at MHSU1 and MHSU3 for methane. Carbon dioxide was seen in the 18,000 ppmv range, with the highest activity seen at MHSU1 and MHSU3 on the southern line located next to the Student Union and MH4, MH3 and MH0 having the highest readings on the northern line. June 2013 focused on the northern line and had highs in the 60 ppmv for methane and 13,650 ppmv for CO2. The highest readings for methane were seen at MH4 and MH1 and MH4, MH2 and MH1 for CO2. July 2013 had high methane concentrations of 133 ppmv and in the high 4000 ppmv for carbon dioxide. This is 74 times greater than the ambient conditions for CH4 and 1000 times greater for CO2. Again the highest readings for methane were seen at MHSU1 and MHSU3. All of 32 these values can be relatively deduced by the data shown in Figure 5 through Figure 10. A basic range was set for the CH4 and CO2 concentrations to create consistent symbology sizing. This worked well in relating the values except during the July 2013 carbon dioxide readings that only showed the same circle sized based on the measured concentrations. Therefore this month's summary did not adequately show which sewer access cover had the highest concentration readings for that time period. During the fall of 2012 there were higher concentration measurements than the summer of 2013. This could be due to the less activity on campus. Figure 11 through Figure 14 show 5 to 8-hour concentration measurements of sewer access covers MH1, MH0 and MHSU1. MH1 shows a series of small spikes in concentration before noon for both CH4 and CO2, then large more sporadic spikes in the afternoon (Figure 11). MH0 for June 26th stays at a fairly, consistently elevated concentration before 1:00 pm and then there was a gradual increase until 5:00 pm with sporadic downwards spikes in concentration. This was the observed trend for both CH4 and CO2 as shown in Figure 12. MH0 for the 27th of June shows a similar trend as June 26th for CO2, but CH4 stays fairly consistent throughout the whole time period, with more sporadic downtrend spikes after about 1:00 pm (Figure 13). MHSU 1 shows more elevated and inconsistent spikes prior to 1:00 pm and more consistent higher concentrations after 1:00 pm for both CH4 and CO2 (Figure 14). Carbon dioxide and methane seem to show a proportional relationship during the same time of measurement as visually shown by the concentration measurements in Figure 11 through Figure 14. This could be due to formation from the same chemical reaction. Anaerobic conditions, the absence of oxygen, can occur within the sewer lines. These conditions could lead to methanogenesis. Methanogenesis can be formed from the biodegradation of organic matter, which will go through a 4 stage process to form CH4 but also CO2 as a byproduct; the four stages are hydrolysis, acidogenesis, acetogenesis and methangogenesis. There are many reactions 33 involved in generating methane but the main reactions involved which form both CO2 and CH4 are shown in the reactions in Eq. 5 through Eq. 10 ( (16)). This assessment could be verified through testing the sewage for acetic acid and pH. Hydrolysis is the process of turning the soluble organics (waste) to soluble monomers (e.g. simple sugars). Hydrolysis: 𝐶𝐶6 𝐻𝐻10 𝑂𝑂4 + 2𝐻𝐻2 𝑂𝑂 → 𝐶𝐶6 𝐻𝐻12 𝑂𝑂6 + 2𝐻𝐻2 (Organic waste) (Glucose) (Eq. 5) Acidogenesis turns the insoluble organics into volatile fatty acids, ketones and alcohols. Acidogenesis: 𝐶𝐶6 𝐻𝐻12 𝑂𝑂6 ↔ 2𝐶𝐶𝐻𝐻3 𝐶𝐶𝐻𝐻2 𝑂𝑂𝐻𝐻 + 2𝐶𝐶𝑂𝑂2 (Glucose) (Ketone: ethanol) 𝐶𝐶6 𝐻𝐻12 𝑂𝑂6 + 2𝐻𝐻2 ↔ 2𝐶𝐶𝐻𝐻3 𝐶𝐶𝐻𝐻2 𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶 + 2𝐻𝐻2 𝑂𝑂 (Glucose) (Volatile fatty acid: propionate) (Eq. 6) (Eq. 7) Acetogenesis turns the volatile fatty acids, ketones and alcohols into acetate, acetic acid CO2 and H2. Acetogenesis: 𝐶𝐶𝐶𝐶3 𝐶𝐶𝐶𝐶2 𝐶𝐶𝐶𝐶𝐶𝐶− + 3𝐻𝐻2 𝑂𝑂 ↔ 𝐶𝐶𝐻𝐻3 𝐶𝐶𝐶𝐶𝑂𝑂− + 𝐻𝐻 + + 2𝐻𝐻𝐻𝐻𝑂𝑂3 + 3𝐻𝐻2 (Volatile fatty acid) (Acetate) 𝐶𝐶6 𝐻𝐻12 𝑂𝑂6 + 2𝐻𝐻2 𝑂𝑂 ↔ 2𝐶𝐶𝐻𝐻3 𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶 + 2𝐶𝐶𝐶𝐶2 + 4𝐻𝐻2 (Glucose) (Acetic acid) (Eq. 8) (Eq. 9) Methanogenesis turns acetate and acetic acid into methane and/or carbon dioxide Methanogenesis: 𝐶𝐶𝐶𝐶3 𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶 ↔ 𝐶𝐶𝐻𝐻4 + 𝐶𝐶𝑂𝑂2 (Acetic acid) (Eq. 10) Calibration Results The results for the chamber laboratory calibration are shown in Table 2 and Figure 15. The calibration results show the flux for all chambers have a relatively logarithmic relationship depending on the flow rate. The ratio best fit curve is shown as exponential when using the NDIR analyzer with the built chamber, but had a more linear trend when using the CRDS with the built 34 chamber. It was observed that the greater the flux, the larger the discrepancy between curves when coupling the NDIR analyzer and built chamber. Most of the data measured fit within the allotted flux rates found in the lab, giving some confidence in using the correction values curve on the data. Eq. 11 and Eq. 12 were found to best represent the correction curves based on the laboratory calibration data. These equations were used to determine the correction ratio applied to each calculated flux value from the measurements made with either the CRDS or NDIR analyzer. Figure 16 and Figure 17 show the NDIR and CRDS flux data measured back to back over a certain time period. Figure 16 encompasses an approximate 24-hour flux trend for the access cover MH4 on October 25th through the 26th. Figure 17 shows a few hours of back to back NDIR and CRDS flux measurements for the MHSU3 access cover on October the 28th. The figures show differences in measured flux values based on the analyzer. 𝑦𝑦𝐿𝐿 = 0.7745𝑒𝑒 −0.152𝑥𝑥𝐿𝐿 (Eq. 11) 𝑦𝑦𝑃𝑃 = 0.0695𝑥𝑥𝑃𝑃 + 0.7583 (Eq. 12) 𝑦𝑦𝐿𝐿 = 𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶 𝑟𝑟𝑟𝑟𝑟𝑟𝑟𝑟𝑟𝑟 𝑓𝑓𝑓𝑓𝑓𝑓 𝑁𝑁𝑁𝑁𝑁𝑁𝑁𝑁 𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚 𝑥𝑥𝐿𝐿 = 𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶 𝐹𝐹𝐹𝐹𝐹𝐹𝐹𝐹 𝑓𝑓𝑓𝑓𝑓𝑓𝑓𝑓 𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚 𝑁𝑁𝑁𝑁𝑁𝑁𝑁𝑁 𝑣𝑣𝑎𝑎𝑙𝑙𝑙𝑙𝑙𝑙𝑙𝑙 (𝑔𝑔𝑔𝑔𝑔𝑔𝑔𝑔𝑔𝑔/𝑑𝑑𝑑𝑑𝑑𝑑) 𝑦𝑦𝑃𝑃 = 𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶 𝑟𝑟𝑟𝑟𝑟𝑟𝑟𝑟𝑟𝑟 𝑓𝑓𝑓𝑓𝑓𝑓 𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶 𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚 𝑥𝑥𝑃𝑃 = 𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶 𝐹𝐹𝐹𝐹𝐹𝐹𝐹𝐹 𝑓𝑓𝑓𝑓𝑓𝑓𝑓𝑓 𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚 𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶 𝑣𝑣𝑣𝑣𝑣𝑣𝑣𝑣𝑣𝑣𝑣𝑣 (𝑔𝑔𝑔𝑔𝑔𝑔𝑔𝑔𝑔𝑔/𝑑𝑑𝑑𝑑𝑑𝑑) The chamber calibration indicated the built chambers, when using the NDIR analyzer system, were underestimating the flux results at smaller measured values and overestimating the flux results for higher calculated values. This could have been due to the large volume change or the chambers' area and volume ratio (A/V), which changes depending on the source cross sectional area. The built chambers have a smaller A/V ratio when compared to the NDIR analyzer, but the proportionality will remain the same when comparing the same source. The CRDS calibration in relation to the NDIR analyzer with NDIR analyzer chamber seemed to have a more 35 linear trend for the correction factor. This may have more to do with the system being designed specifically for use with the CRDS, the A/V ratio, and/or the analyzer's precision and accuracy. Methane is lighter than air which means there could be more dispersion within the system than what was actually measured due to the inability to calibrate CH4 for the built chamber as was done for CO2. More calibration is recommended for all methods to get a better understanding of the discrepancy in readings, based on method and chamber type. The analyzers were also not calibrated to measure concentrations at these extremes, which would add question to the integrity of the data as the concentrations get into the tens of thousands range. The NDIR analyzer and CRDS seem to have somewhat relative trends when looking at the flux plots versus time. Some of the discrepancy could be from the type of curve fit used to calculate the flux from one device to another. When using a nonlinear or linear fit to calculate the predicted or approximate flux there can be large differences, but all flux data were determined using the best fit curve. The morning and late evening measurements seem to follow a very similar trend. During the afternoon there were high variabilities in the readings, which were consistently shown in all the data and have shown large disparities within a short period of time. The inconsistencies could also be from the measurements not being done at the exact same time, at the same cover, and/or due to the limited predictability of the system. It may be reasonable to allow for a high degree of uncertainty when comparing actual values. Flux Analysis Results The results shown in Table 3 give the field measured concentration values and calculated flux gradient data for the 11 access covers assessed for diffusion calculated by Eq. 1. The flux gradient values are shown as negative only because they go from a high concentration to low concentration. Table 4 shows the theoretical trend for the flux release of the sewer access covers 36 based on the flux gradient (diffusion) and compares it to the actual measured values for flux. Specifically the table shows the sewer access covers that would theoretically have the highest values (left) to the lowest values (right) if the flux was primarily controlled by diffusion for both CH4 and CO2. This was done for both carbon dioxide and methane as they behave differently from one access cover to the next. No obvious trends were seen for the theoretical and actual in either CO2 or CH4. It should be noted that not all the sewer access covers had the same amount of measurements and were done at sporadic times throughout the week. This coupled with the inconsistencies observed from the sewer may have an impact on the averaging, quantification and trend correlations. Table 5 shows the theoretical values for high flux rates according to the ventilation out of the sewer access covers according to the approximated potential area of release, meaning if the flux was controlled primarily by the source area (area of release potential) then theoretically the sewer access cover with the highest flux should be MH1 and sewer access cover MHSU1 should show the lowest flux for both gases. There were no obvious trends or connections between either the theoretical or actual values. The actual values for CO2 and CH4 when compared are also variable and have limited connections in terms of source area. The flux data for each access cover were averaged over morning and afternoon. This was done because the trend in the concentration and flux data showed there were either higher values in the afternoon when compared to the morning or vice versa depending on the sewer access cover observed. Table 6 shows these averaged data as well as the total values expressed in g/day and the Mt CO2e/yr. The fluxes for CH4 were between 0.00002-35 g CH4/day and CO2 had fluxes around 0.04-32,000 g CO2/day and an overall average of 62 g CO2/day and 0.412 g CH4/day. These data encompass all real data that were not deemed outliers or caused by human or mechanical errors, including all data measured using the NDIR analyzer. The total measured emissions from 37 the 11 sewer access covers were calculated to be 1.066 Mt CO2e. All raw flux data are shown in Appendix C. The average value of emissions of 1.066 Mt CO2e per year for the 11 sewer access covers can be compared to the total estimated emissions for the University of Utah campus. There are 459 sewer access covers on campus making this sample set approximately 2% of the entire system. According to the University of Utah's Sustainability Resource Center (17) the total University of Utah campus emissions was 283,077 Mt of CO2e; making this sample source accountable for 0.016% of the total campus wide emissions. The source is located at the further most upstream section of the system and therefore could be a very limited emissions contributor when compared to the main trunk lines in the system. As these lines would have higher flows and more continuous activity. The trunk lines may also have more flow data and a higher level of predictability. Barometric temperature and pressure versus concentration plots were created for each access cover to see if there were any relations. Unfortunately no obvious trends were seen. Plots showing the methane and carbon dioxide seem to show a reasonable proportionality for each observation day. This was only true for the access covers that were active; this was not true for the abandoned lines which had a small but consistent flux of CO2 but relatively no or negligible flux for CH4. The dates determined to have zero or no flux were days when the University of Utah campus had fall break. This could indicate for those specific sites that the lack of sewer use had no or very little flow, possibly creating no flux and possibly lowering concentrations. This could support the assumption that flow is one of the main driving forces for gas transport to the surface. This also supports the assumption that the sewer gas flux could be affected by the sewer's activity. After observing all the data, it was determined that many of the higher concentrations and flux 38 measurements tend to be more prevalent on sewer maintenance covers that are located at junction points. This could be due to the combining flows and subsequent turbulence. This however did not seem to correlate to the source area for the access covers. The theoretical and actual flux comparisons from high to low were generally not accurate for both diffusion and source area ventilation. For diffusive flux this could have been due to limiting the flux gradient measurements for one day and there may be more accuracy in doing an average. This could also indicate the diffusion and/or ventilation area is not the main method of gas transport. This supports the Parker et al. (10) results indicating the release to the atmosphere of the tracer gas was dominated by advective processes and that diffusion could be neglected for gas transport in the sewer system. Figure 11: Concentration Measurements of CO2 (above) and CH4 (below) at Sewer Access Cover MH1 on June 21, 2013 39 Figure 12: Concentration Measurements of CO2 (above) and CH4 (below) at Sewer Access Cover MH0 on June 26, 2013 40 Figure 13: Concentration Measurements of CO2 (above) and CH4 (below) at Sewer Access Cover MH0 on June 27, 2013 41 Figure 14: Concentration Measurements of CO2 (above) and CH4 (below) at Sewer Access Cover MHSU1 on July 3, 2013 42 Figure 15: Chamber Laboratory Calibration Curves 43 Flow Meter Head (mm) 30 90 155 Table 2: Chamber Flux Calibration Results Average Flux (g/day) Standard Deviation of Flux (g/day) Built Built NDIR Built Built NDIR Chamber Chamber Chamber Chamber Chamber Chamber with NDIR with CRDS with NDIR with NDIR with CRDS with NDIR 0.420 0.395 0.312 0.075 0.006 0.020 1.41 1.05 0.861 0.253 0.233 0.072 6.07 2.08 1.88 0.544 0.135 0.340 Correction Ratio NDIR CRDS 0.74 0.61 0.31 0.79 0.82 0.91 Figure 16: CRDS versus NDIR Analyzer Flux Data for MH4 44 Figure 17: CRDS versus NDIR Analyzer Flux Data for MHSU3 45 COVER ID MH4 MH3 MH2 MH1 MH0 MH00 MHSU6 MHSU5 MHSU4 MHSU3 MHSU1 ∂x (ft) ∂x (m) 9.8 9.0 9.8 6.0 10.0 6.0 11.0 9.8 5.0 8.5 6.0 3.0 2.7 3.0 1.8 3.0 1.8 3.4 3.0 1.5 2.6 1.8 φ1,CO2 (ppmv) 397 460 630 480 690 430 440 512 390 485 400 Table 3: Flux Gradient Data φ2,CO2 ∂φCO2 JCO2 (ppmv) (ppmv) (g/day) 387 10 -4.29 410 50 -23.4 480 150 -64.3 430 50 -35.2 630 60 -25.3 415 15 -10.5 420 20 -7.66 505 7 -3.01 387 3 -2.53 440 45 -22.3 395 5 -3.51 φ1,CH4 (ppmv) 1.91 3.50 3.10 2.60 8.80 2.10 1.93 1.96 1.83 2.90 1.95 φ2,CH4 (ppmv) 1.75 2.40 2.20 2.30 7.80 1.98 1.82 1.95 1.78 2.30 1.75 ∂φCH4 (ppmv) 0.16 1.10 0.90 0.30 1.00 0.12 0.11 0.01 0.05 0.60 0.20 JCH4 (g/day) -0.117 -0.176 -0.148 -0.253 -0.514 -0.218 -0.109 -0.111 -0.234 -0.178 -0.192 Table 4: Sewer Access Cover Trends Based on Calculated Diffusive Flux Method versus Field Measured Flux Flux Calculation Method CH4 Diffusion Field CO2 Diffusion Field Sewer Access Cover ID High Flux −−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−˃ Low Flux MH0 MHSU3 MH1 MH0 MHSU4 MHSU1 MH00 MHSU5 MHSU1 MH1 MHSU3 MH4 MH3 MHSU6 MH2 MH2 MHSU5 MH3 MH4 MHSU4 MHSU6 MH00 High Flux −−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−˃ Low Flux MH2 MHSU3 MH1 MH0 MH0 MH1 MH3 MHSU1 MHSU3 MHSU5 MH00 MH4 MHSU6 MH2 MH4 MH3 MHSU1 MHSU6 MHSU5 MH00 MHSU4 MHSU4 46 Flux Calculation Method Source Area Field CH4 Field CO2 Table 5: Sewer Access Cover Trends Based on Source Area versus Field Measured Flux Sewer Access Cover ID High Flux −−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−˃ Low Flux MH1 MH4, MHSU6, MHSU4 MHSU3 MHSU5 MH0 MH2 MH00 MH3 MHSU1 MHSU3 MH0 MHSU1 MHSU5 MH1 MH4 MHSU6 MH2 MH3 MHSU4 MH00 MHSU3 MH0 MH1 MHSU1 MHSU5 MH4 MH2 MH3 MHSU6 MH00 MHSU4 47 48 Table 6: Cover ID Flux Data Cover ID MH0 Average of CO2 Flux Average of CH4 Flux MH00 Average of CO2 Flux Average of CH4 Flux MH1 Average of CO2 Flux Average of CH4 Flux MH2 Average of CO2 Flux Average of CH4 Flux MH3 Average of CO2 Flux Average of CH4 Flux MH4 Average of CO2 Flux Average of CH4 Flux MHSU1 Average of CO2 Flux Average of CH4 Flux MHSU3 Average of CO2 Flux Average of CH4 Flux MHSU4 Average of CO2 Flux Average of CH4 Flux MHSU5 Average of CO2 Flux Average of CH4 Flux MHSU6 Average of CO2 Flux Average of CH4 Flux TOTAL Morning Afternoon Morning Afternoon (g/day) (g/day) (Mt CO2e) (Mt CO2e) Sum of All Measurem ents (Mt CO2e) 983.1 1,886 18.69 0.0818 0.3588 0.05 0.0068 0.0006 0.3656 0.0501 - 1.63 0.003 - 0.0006 2.63E-05 0.0006 2.63E-05 185.4 19.39 15.74 0.0366 0.0677 0.0010 0.0057 0.0003 0.0734 0.0013 6.906 0.009 12.73 0.0199 0.0025 0.0001 0.0046 0.0002 0.0072 0.0002 2.484 0.003 11.93 0.0254 0.0009 0.00002 0.0044 0.0002 0.0053 0.0002 3.630 0.0356 22.99 0.0915 0.0013 0.0003 0.0084 0.0007 0.0097 0.0010 18.26 0.2101 30.41 0.2464 0.0067 0.0016 0.0111 0.0019 0.0178 0.0035 7.347 0.2147 1340 1.875 0.0027 0.0016 0.4891 0.0144 0.4918 0.0160 - 1.196 0.0162 - 0.0004 0.00012 0.0004 0.0001 39.31 1.513 5.702 0.4057 0.0143 0.0000 0.0021 0.0031 0.0164 0.0032 - 4.392 0.0311 - 0.5090 0.0016 0.0002 0.5566 0.0016 0.0002 1.066 CONCLUSIONS A chamber method was developed to measure the CO2 and CH4 gas emissions from 11 sewer access covers upstream of the Salt Lake City sewer network. This method was developed based on a soil flux chamber design and modified to adapt to the study's site specific conditions. It is reasonable to assume this method is effective in measuring the gas release from point sources throughout the sewer. This chamber based method could also be a better solution when making assumptions on the overall sewer network CO2 and CH4 emissions contribution, as it measures the release directly. This method is versatile and can be retrofit to most any spectroscopy equipment, which allows for various gas types to be measured. The spectroscopy equipment used for concentration and flux measurements are both widely used in the biological community for soil and atmospheric sciences. However the concentration and flux range typically seen in this field of study are on order of magnitudes greater than what they are traditionally used for. The equipment can handle these higher values, but they do tend to lose accuracy unless calibrated using higher concentrations, which was not done for this study. Therefore it is more prudent to look at the trends the data show rather than the actual values. The data show there are high concentrations for both CO2 and CH4 over the sewer access covers when compared to ambient conditions; i.e., 394 ppmv ambient CO2 to a high of 18,000 ppmv CO2 and 1.8 ppmv ambient CH4 compared to a high of 130 ppmv CH4. CO2 and CH4 concentration readings show a proportional relationship in measured field readings, i.e., they had 50 coincident peaks. This could indicate the gas creation for CO2 and CH4 concentrations are made or driven by the same reaction, such as methanogenesis. The sewer access covers showed a positive accumulation of concentration (flux) within the chambers, indicating there is a release of methane and carbon dioxide into the atmosphere. The average values for both CO2 and CH4 flux show minor emission rates in terms of Mt CO2e and were shown to be a significantly lower contribution than estimated in the previously discussed studies. The calculated values do not necessarily indicate the sewer system as a whole is not a significant contributor, but that the small data set and study site conditions are most likely insufficient to make any assumptions on the entire system without further study. More analysis should be done on the chamber assessment and design to get more realistic values for the emissions. It is unclear whether the age of the sewer lines have an impact on the formation or emissions of CO2 or CH4 as this factor was not discussed in any of the emission studies cited. However it may be worth studying. No flow data were available for the sewer lines studied; therefore no definite conclusions can be made based on the flow or activity of the sewer. It should be noted that the sewer pipe line size, line depth, slope, age, pH, corrosion and actual sewer flow values were not a factor in determining any conclusions made from the data. It is recommended that in future research these components be used to make a more complete analysis. Recommendations for Future Work Recommendations for future work would include more frequent data during each seasonal change, more in depth analysis on the effects of temperature and pressure effects upon the system and determining the driving forces of transport. Other potential sewer gases could be assessed to determine interference within the system and how these may have an effect on the 51 measurements, such as gas displacement. For the flux gradient it may be prudent to make measurements at incremental depths to prove or disprove steady state assumption. The built chamber is currently very user intensive and other designs and volumes should be considered to inhibit potential user error and for maximum efficiency. Obtaining another way to verify the chamber calibration for methane would also be beneficial in verifying or creating a more accurate correction curve for the methane flux data. It may also be valuable to do a more in depth study on the sewer concentration and any relationships or correlations it may have in determining the flux. For future this chamber based method could be proposed for assessing general emissions. Recommendations for measuring gas quantification emissions could be made more accurate by defining the number of access covers using junctions, nonjunctions and depth relationships, determining where the highest potential contributors are within the system and what factors define them. This would allow for defining key areas that have the maximum release potential and making estimates for the system as a whole based on similar terrain and pipe properties throughout the sewer network. Methane and carbon dioxide have been shown to be released by sewer access covers. Therefore research should be considered on any possible mitigation or harnessing procedures. APPENDIX A SOIL FLUX CALIBRATION 53 Table 7: Soil Flux Chamber and Method Comparison Summary Method & Chamber Type Licor w/ Licor chamber Licor w/ built chamber Picarro w/ built chamber CO2 Flux STD 2 (g/m /day) 2 (g/m /day) 8.41 5.36 10.57 1.00 0.64 0.80 Difference compared Difference compared to Licor chamber to Picarro method 1.00 0.64 1.26 1.26 0.80 1.00 Table 8: NDIR Analyzer with NDIR Chamber Soil Flux Measurements Cover ID Date Start Time End Time Grass Grass Grass Grass Grass Grass Grass Grass Grass Grass Average 2/17/2014 2/17/2014 2/17/2014 2/17/2014 2/17/2014 2/17/2014 2/17/2014 2/17/2014 2/17/2014 2/17/2014 Morning Morning Morning Morning Morning Morning Morning Morning Morning Morning 2 minute measurement 2 minute measurement 2 minute measurement 2 minute measurement 2 minute measurement 2 minute measurement 2 minute measurement 2 minute measurement 2 minute measurement 2 minute measurement CO2 Flux 2 CO2 Flux CO2 Flux 2 2 (microL/m /min) (g/m /day) (μmol/m /s) 2339 3297 3110 2511 2523 3938 4412 2695 3354 2551 3073 6.40 9.03 8.52 6.88 6.91 10.78 12.08 7.38 9.18 6.98 8.41 1.68 2.37 2.24 1.81 1.82 2.84 3.18 1.94 2.42 1.84 2.21 STD Lower 95% Confidence Upper 95% Confidence 46.1 33.4 74.0 71.9 39.8 67.5 43.1 29.5 43.2 38.1 48.7 2248 3231 2963 2368 2444 3805 4326 2637 3268 2475 2977 2430 3363 3257 2653 2602 4072 4497 2754 3440 2626 3169 54 Table 9: NDIR Analyzer with Built Chamber Soil Flux Measurements Cover ID Date Start Time End Time Grass Grass Grass Grass Grass Grass Grass Grass Grass Grass Average 2/17/2014 2/17/2014 2/17/2014 2/17/2014 2/17/2014 2/17/2014 2/17/2014 2/17/2014 2/17/2014 2/17/2014 11:32 AM 11:45 AM 11:58 AM 12:11 PM 12:24 PM 12:38 PM 12:52 PM 1:06 PM 1:18 PM 1:32 PM 11:42 AM 11:55 AM 12:08 PM 12:21 PM 12:34 PM 12:48 PM 1:02 PM 1:16 PM 1:28 PM 1:42 PM CO2 Flux 2 CO2 Flux CO2 Flux (microL/m /min) (g/m /day) (μmol/m2/s) 804 2540 788 1938 1797 2953 2344 2944 1187 2597 1989 2 2.18 6.88 2.13 5.23 4.85 7.97 6.31 7.90 3.19 6.97 5.36 0.57 1.81 0.56 1.38 1.27 2.10 1.66 2.08 0.84 1.83 1.41 STD Lower 95% Confidence Upper 95% Confidence 6.5 28.9 6.1 11.1 9.4 13.0 21.3 32.0 14.3 26.0 16.9 791 2483 776 1916 1779 2928 2302 2881 1159 2546 1956 816 2597 800 1960 1816 2979 2386 3006 1215 2648 2022 55 Table 10: CRDS with Built Chamber Soil Flux Measurements Cover ID Date Start Time End Time Grass Grass Grass Grass Grass Grass Grass Grass Grass Average 2/17/2014 2/17/2014 2/17/2014 2/17/2014 2/17/2014 2/17/2014 2/17/2014 2/17/2014 2/17/2014 11:32:00 AM 11:45:00 AM 11:58:00 AM 12:11:00 PM 12:24:00 PM 12:38:00 PM 1:06:00 PM 1:18:00 PM 1:32:00 PM 11:42:00 AM 11:55:00 AM 12:08:00 PM 12:21:00 PM 12:34:00 PM 12:48:00 PM 1:16:00 PM 1:28:00 PM 1:42:00 PM CO2 Flux 2 CO2 Flux CO2 Flux 2 2 (microL/m /min) (g/m /day) (μmol/m /s) 5078 3900 2791 2783 3035 5742 5740 2962 3222 3917 13.79 10.56 7.55 7.51 8.18 15.50 15.41 7.95 8.64 10.57 3.63 2.78 1.98 1.98 2.15 4.08 4.05 2.09 2.27 2.78 STD Lower 95% Confidence Upper 95% Confidence 20.6 20.1 23.4 19.8 19.9 63.6 45.0 16.5 18.6 27.5 5038 3860 2745 2744 2996 5617 5652 2929 3185 3863 5119 3939 2837 2821 3074 5867 5828 2994 3258 3971 56 APPENDIX B MATLAB CODES 58 function [text_data, data] = importfile1(filename, anem, gps, startRow, endRow) % % THIS FILE was GENERATED USING THE MATLAB CODE GENERATION AND THEN % was MODIFIEDBY AMANDA VARLAND FOR SPECIFIC FILE IMPORTATION % % IMPORTFILE Imports data from a text file as a matrix. % EXDAT = IMPORTFILE(FILENAME) Reads data from text file FILENAME % for the default selection. % % EXDAT = IMPORTFILE(FILENAME, STARTROW, ENDROW) Reads data from % rows STARTROW through ENDROW of text file FILENAME. % % anem was a string input that defines whether or not the imported % data has anemometer data present in the file. Expressed as 'Y' 'y' % for yes there was anemometer data present or 'N' 'n' for not % present % % gps was a string input that defines whether or not the imported % data has GPS data present in the file. Expressed as 'Y' 'y' for % yes there was GPS data present or 'N' 'n' for not present % % Example: % exdat = importfile('CFHADS2005-20121001-124123Z-DataLog_User. % dat','n','n' 1, 1325); % %% Initialize variables. delimiter = ' '; if nargin <= 4 startRow = 1; endRow = inf; end %% Read columns of data as strings: % For more information, see the TEXTSCAN documentation. formatSpec = '%s%s%s%s%s%s%s%s%s%s%s%s%s%s%s%s%s%s%s%s%s%s%s%s%s%s%s%s%s%s%s%s%s%s%[ ^\n\r]'; %% Open the text file. % fileID = fopen(filename); %% Read columns of data according to format string. % This call was based on the structure of the file used to generate 59 % this code. If an error occurs for a different file, try % regenerating the code from the Import Tool. dataArray = textscan(fileID, formatSpec, endRow(1)-startRow(1)+1,... 'Delimiter', delimiter, 'MultipleDelimsAsOne', true, 'HeaderLines',... startRow(1)-1, 'ReturnOnError', false); for block=2:length(startRow) frewind(fileID); dataArrayBlock = textscan(fileID, formatSpec, endRow(block)-startRow(block)+1, 'Delimiter', delimiter, 'MultipleDelimsAsOne', true, 'HeaderLines', startRow(block)-1, 'ReturnOnError', false); for col=1:length(dataArray) dataArray{col} = [dataArray{col};dataArrayBlock{col}]; end end %% Close the text file. % fclose(fileID); %% Convert the contents of columns containing numeric strings to % numbers. Replace non-numeric strings with NaN. % numericData = NaN(size(dataArray{1},1),size(dataArray,2)); %% Split data into numeric and cell columns. % b = length(dataArray); new = cell(1,b); for num = 1:b if(~strcmp('',dataArray{num}(1,1))) new{num} = dataArray{num}; end end new = new(~cellfun('isempty',new)); c = length(new{end}); raw = cell(c,length(new)); 60 for i = 1:length(new) raw(1:c,i) = new{i}(1:c); end %% Create output variables with columns based upon the users input % values % [a,b] = size(raw); if(strcmp(anem, 'y') && strcmp(gps,'y') || strcmp(anem,'Y') && strcmp(gps,'Y')) CH4 = find(ismember(raw(1,:),'CH4')); CO2 = find(ismember(raw(1,:),'CO2')); DCH4 = find(ismember(raw(1,:),'CH4_dry')); DCO2 = find(ismember(raw(1,:),'CO2_dry')); H2O = find(ismember(raw(1,:),'H2O')); ANC = find(ismember(raw(1,:),'ANEMOMETER_C')); ANUX = find(ismember(raw(1,:),'ANEMOMETER_UX')); ANUY = find(ismember(raw(1,:),'ANEMOMETER_UY')); ANUZ = find(ismember(raw(1,:),'ANEMOMETER_UZ')); GPSLat = find(ismember(raw(1,:),'GPS_ABS_LAT')); GPSLong = find(ismember(raw(1,:),'GPS_ABS_LONG')); data = zeros(a-1,11); if (nargin < 4) data = raw(2:end,[CH4 DCH4 CO2 DCO2 H2O ANC ANUX ANUY ANUZ GPSLat GPSLong]); data = str2double(data); text_data = cell(a,13); text_data(startRow,:) = raw(startRow,[1:2 CH4 DCH4 CO2 DCO2 H2O ANC ANUX ANUY ANUZ GPSLat GPSLong]); text_data(startRow + 1:end,1:2) = raw(startRow + 1:end,1:2); elseif (nargin >= 4) data = raw(2:end,[CH4 DCH4 CO2 DCO2 H2O ANC ANUX ANUY ANUZ GPSLat GPSLong]); data = str2double(data); text_data = cell(a,13); text_data(2:end,1:2) = raw(2:end,1:2); end 61 elseif(strcmp(anem, 'y') || strcmp(anem,'Y') && strcmp(gps,'n') ||strcmp(gps,'N')) CH4 = find(ismember(raw(1,:),'CH4')); CO2 = find(ismember(raw(1,:),'CO2')); DCH4 = find(ismember(raw(1,:),'CH4_dry')); DCO2 = find(ismember(raw(1,:),'CO2_dry')); H2O = find(ismember(raw(1,:),'H2O')); ANC = find(ismember(raw(1,:),'ANEMOMETER_C')); ANUX = find(ismember(raw(1,:),'ANEMOMETER_UX')); ANUY = find(ismember(raw(1,:),'ANEMOMETER_UY')); ANUZ = find(ismember(raw(1,:),'ANEMOMETER_UZ')); data = zeros(a-1,9); if (nargin < 4) data = raw(2:end,[CH4 DCH4 CO2 DCO2 H2O ANC ANUX ANUY ANUZ]); data = str2double(data); text_data = cell(a,11); text_data(startRow,:) = raw(startRow,[1:2 CH4 DCH4 CO2 DCO2 H2O ANC ANUX ANUY ANUZ]); text_data(startRow + 1:end,1:2) = raw(startRow + 1:end,1:2); elseif (nargin >= 4) data = raw(2:end,[CH4 DCH4 CO2 DCO2 H2O ANC ANUX ANUY ANUZ]); data = str2double(data); text_data = cell(a,11); text_data(2:end,1:2) = raw(2:end,1:2); end elseif(strcmp(anem, 'n') && strcmp(gps,'y') || strcmp(anem,'N') && strcmp(gps,'Y')) CH4 = find(ismember(raw(1,:),'CH4')); CO2 = find(ismember(raw(1,:),'CO2')); DCH4 = find(ismember(raw(1,:),'CH4_dry')); DCO2 = find(ismember(raw(1,:),'CO2_dry')); H2O = find(ismember(raw(1,:),'H2O')); GPSLat = find(ismember(raw(1,:),'GPS_ABS_LAT')); GPSLong = find(ismember(raw(1,:),'GPS_ABS_LONG')); data = zeros(a-1,7); if (nargin < 4) data = raw(2:end,[CH4 DCH4 CO2 DCO2 H2O GPSLat GPSLong]); 62 data = str2double(data); text_data = cell(a,9); text_data(startRow,:) = raw(startRow,[1:2 CH4 DCH4 CO2 DCO2 H2O GPSLat GPSLong]); text_data(startRow + 1:end,1:2) = raw(startRow + 1:end,1:2); elseif (nargin >= 4) data = raw(2:end,[CH4 DCH4 CO2 DCO2 H2O GPSLat GPSLong]); data = str2double(data); text_data = cell(a,9); text_data(2:end,1:2) = raw(2:end,1:2); end elseif(strcmp(anem, 'n') && strcmp(gps,'n') || strcmp(anem,'N') && strcmp(gps,'N')) CO2 = find(ismember(raw(1,:),'CO2')); CH4 = find(ismember(raw(1,:),'CH4')); CH4_dry = find(ismember(raw(1,:),'CH4_dry')); CO2_dry = find(ismember(raw(1,:),'CO2_dry')); H2O = find(ismember(raw(1,:),'H2O')); data = zeros(a-1,5); if (nargin < 4) data = raw(2:end,[CH4 CH4_dry CO2 CO2_dry H2O]); data = str2double(data); text_data = cell(a,7); text_data(startRow,:) = raw(startRow,[1:2 CH4 CH4_dry CO2 CO2_dry H2O]); text_data(startRow + 1:end,1:2) = raw(startRow + 1:end,1:2); else data = raw(2:end,[CH4 CH4_dry CO2 CO2_dry H2O]); data = str2double(data); text_data = cell(a,7); text_data(2:end,1:2) = raw(2:end,1:2); end end end ******************************************************************** function pcut(dat_files,CO2_file,CH4_file, CO2_threshold, CH4_threshold) % % THIS FUNCTION was FOR QUERYING THE CRDS DATA MEASURED ON CAMPUS. % THIS QUERY WILL FIRST IMPORT ALL THE .DAT FILES THE CRDS 63 % INSTRUMENT CREATES, THEN IT WILL REMOVE OR CUT OUT ALL THE DATA % THAT was AROUND AMBIENT CONDITIONS OR AT A USER SPECIFIED THRESHOLD % VALUE. THE CUT DATA WILL THEN BE OUTPUT INTO A .TXT FILE THAT CAN % BE DIRECTLY IMPORTED INTO GIS. % % AUTHOR: AMANDA VARLAND % % FUNCTION CALL: pcut % % INPUT VALUES: % NAME: DESCRIPTION: EXAMPLE: % dat_files A .DAT FILE OR CELL ARRAY OF '/Volumes/ % .DAT FILES WITH THE NAME AND CarbonData/ % LOCATION Geographical/GIS % /Northern Utah % /University of Utah % Campus/Data/2012 % /10/Raw Data/09-Raw % Data/CFHADS2005% 20121009-082949Z- % DataLog_User.dat' % % CO2_file THE LOCATION AND NEW NAME OF '/Volumes/ % THE CO2 DATA IN .TXT FORMAT CarbonData % /Geographical/GIS/ % Northern Utah % /University of Utah % Campus/Data/2012/ % 10/CP09122012.txt' % % CH4_file THE LOCATION AND NEW NAME OF '/Volumes/ % THE CH4 DATA IN .TXT FORMAT CarbonData/ % Geographical/GIS/ % NortheRn Utah % /University of Utah % Campus/Data/2012/ % 10/HP09122012.txt' % % CO2_threshold THE THRESHOLD LIMIT AT WHICH 800 % CO2 DATA WILL BE CUT IN PPMV % % CH4_threshold THE THRESHOLD LIMIT AT WHICH 3 % CH4 DATA WILL BE CUT IN PPMV % % % % IF THERE were MULTIPLE FILES THEN IT WILL CONCATINATE THEM OR % COMBINE THEM INTO ONE FILE WITH HEADERS 64 % %% ASKS THE USER WHAT INFORMATION THEY WILL REQUIRE BASED ON THE % CRDS ATTACHMENTS anem = input('Is there Anemometer data (y/n)? ','s'); gps = input('Is there GPS data y/n? ','s'); %% DETERMINES HOW MANY .DAT FILES were WITHIN dat_files. % l = length(dat_files); if l == 1 [text_data, data] = importfile1(dat_files,anem,gps); else [text_data, data] = importfile1(dat_files{1},anem,gps); for i = 2:l [text_data2, data2] = importfile1(dat_files{i},anem,gps,1,inf); text_data = [text_data;text_data2]; data = [data;data2]; end end %% PREDEFINES THE SIZE OF THE .TXT FILES FOR FASTER COMPUTING % format longG [u,v] = size(text_data); H1 = data(data(:,1) >= CH4_threshold); C1 = data(data(:,3) >= CO2_threshold); H2 = length(H1); C2 = length(C1); cut_data = zeros(C2,v-2); cut_data2 = zeros(H2,v-2); Ccut = cell(C2,v); Hcut = cell(H2,v); 65 Ccut(1,:) = text_data(1,:); Hcut(1,:) = text_data(1,:); %% CUTS THE DATA ACCORDING TO THE PREDEFINED THRESHOLD VALUES % [row,col] = size(data); n1 = 0; n2 = 0; for r = 1:row if(data(r,3) > CO2_threshold) n1 = n1 + 1; cut_data(n1,:) = data(r,:); Ccut(n1 + 1,:) = text_data(r + 1,:); end if(data(r,1) > CH4_threshold) n2 = n2 + 1; cut_data2(n2,:) = data(r,:); Hcut(n2 + 1,:) = text_data(r + 1,:); end end %% COMBINES THE THE TEXT AND NUMERICAL DATA INTO ONE MATRIX % cut_data = num2cell(cut_data); cut_data2 = num2cell(cut_data2); [m,n] = size(Ccut); [o,p] = size(Hcut); for im = 2:m for in = 3:n Ccut{im,in} = cut_data{im - 1,in - 2}; end end 66 if(CO2_threshold == CH4_threshold) Hcut = Ccut; else for io = 2:o for ip = 3:p Hcut{io,ip} = cut_data2{io - 1,ip - 2}; end end end %% This removes any rows that have empty cells % Ccut(any(cellfun(@isempty,Ccut)'),:) = []; Hcut(any(cellfun(@isempty,Hcut)'),:) = []; %% TAKES THE DATA AND FORMATS IT INTO A GIS READABLE .TXT FILE % dlmcell(CO2_file, Ccut); dlmcell(CH4_file, Hcut); end ******************************************************************** function timeplot(date,time,CO2,timecorrection,heading,CH4) % % THIS FUNCTION was FOR PLOTTING ALL THE DATA FROM A TXT FILE WHEN % IMPORTED AS COLUMN VECTORS. PARTICULARLY ALL DAY CONCENTRATION % MEASUREMENTS DONE AT A SEWER ACCESS HOLE. % % AUTHOR: AMANDA VARLAND % % FUNCTION CALL: timeplot % % INPUT VALUES: % NAME: DESCRIPTION: EXAMPLE: % date DATE COLUMN VECTOR OF STRINGS '2013-12-01' % GIVEN FROM BY CRDS IN THE '2013-12-01' % FORMAT 'YYYY-MM-DD' '2013-12-01' % % 67 % % % % % % % % % % % % % % % % % % % % time TIME COLUMN VECTOR OF STRINGS '13:45:01.123' GIVEN FROM BY CRDS IN THE '13:45:01.223' FORMAT 'HH:MM:SS.FFF' IN 24 '13:45:01.323' HOUR FORMATTING '13:45:01.423' CO2 THE CO2 CONCENTRATION GIVEN '395' BY THE CRDS IN PPMV AND '400' COLUMN VECTOR FORMAT '405' timecorrection THE CRDS was MEASURED IN 0.25 MEAN GREENWICH TIME. THIS was THE CORRECTION VALUE FOR WHATEVER TIME ZONE was CHOSEN IN HOURS. NOTE THE VALUE was SUBTRACTED FROM THE TIME. heading THE PLOT TITLE 'JULY 21, 2013 -% MH0' % % % CH4 % % % % THE CH4 CONCENTRATION GIVEN '10' BY THE CRDS IN PPMV AND '11' COLUMN VECTOR FORMAT '12' %% COMBINES THE DATE AND TIME INFORMATION AND CORRECTS THE VALUE % ts = datenum(strcat(date,time),'yyyy-mm-ddHH:MM:SS'); ts = ts - timecorrection; %% PLOTS BOTH THE CO2 AND CH4 CONCENTRATIONS OVER TIME WITH SPECIFIC % PROPERTIES % subplot(2,1,1); plot(ts,CO2,'Color',[0 0 0],'LineWidth',0.25) t = title(heading); set(t, 'FontWeight', 'bold','FontSize', 20,'FontName','Calibri') ylabel('CO_2 Concentration (ppmv)') h = get(gca, 'xlabel'); set(h, 'FontName', 'Calibri','FontSize',12) 68 g = get(gca, 'ylabel'); set(g, 'FontName', 'Calibri','FontSize',12) grid on axis tight set(gca,'XTickLabelMode','auto') datetick('x','HH:MMPM'); axis tight subplot(2,1,2) plot(ts, CH4,'Color',[1 0 0],'LineWidth',0.25) ylabel('CH_4Concentration (ppmv)') h = get(gca, 'xlabel'); set(h, 'FontName', 'Calibri','FontSize',12) g = get(gca, 'ylabel'); set(g, 'FontName', 'Calibri','FontSize',12) grid on axis tight set(gca,'XTickLabelMode','auto') datetick('x','HH:MMPM'); axis tight end ******************************************************************** function timeplot1(date,time,st,et,ydata,timecorrection,heading) % % THIS FUNCTION was FOR PLOTTING DATA FROM A TXT FILE WHEN IMPORTED % AS COLUMN VECTORS. PARTICULARLY CHAMBER FLUX MEASUREMENTS DONE AT % A SEWER ACCESS COVER. % % AUTHOR: AMANDA VARLAND % % FUNCTION CALL: timeplot1 % % INPUT VALUES: % NAME: DESCRIPTION: EXAMPLE: % date DATE COLUMN VECTOR OF STRINGS '2013-12-01' % GIVEN FROM BY CRDS IN THE '2013-12-01' % FORMAT 'YYYY-MM-DD' '2013-12-01' % % % time TIME COLUMN VECTOR OF STRINGS '13:45:01.123' 69 % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % GIVEN BY CRDS IN THE '13:45:01.223' FORMAT 'HH:MM:SS.FFF' IN 24 '13:45:01.323' HOUR FORMATTING '13:45:01.423' st THE START TIME OF CHAMBER '2013-06-12 MEASUREMENT GIVEN BY CRDS 13:45:01.123' IN THE FORMAT 'YYYY-MM-DD HH:MM:SS.FFF' IN 24 HOUR FORMATTING et THE END TIME OF CHAMBER '2013-06-12 MEASUREMENT GIVEN BY CRDS 13:45:01.123' IN THE FORMAT 'YYYY-MM-DD HH:MM:SS.FFF' IN 24 HOUR FORMATTING ydata THE CO2 OR CH4 CONCENTRATION '395' DATA GIVEN BY THE CRDS IN '400' PPMV AND COLUMN VECTOR FORMAT '405' timecorrection THE CRDS was MEASURED IN 0.25 MEAN GREENWICH TIME. THIS was THE CORRECTION VALUE FOR WHATEVER TIME ZONE was CHOSEN IN HOURS. NOTE THE VALUE was SUBTRACTED FROM THE TIME. heading THE PLOT TITLE 'JULY 21, 2013 MH0' %% COMBINES THE DATE AND TIME INFORMATION AND CORRECTS THE VALUE % ts = datenum(strcat(date,time),'yyyy-mm-ddHH:MM:SS'); ts = ts - timecorrection; stime = datenum(st,'yyyy-mm-ddHH:MM:SS'); etime = datenum(et,'yyyy-mm-ddHH:MM:SS'); a = length(ts); new = zeros(a,2); 70 %% CALCULATES THE ELAPSED TIME % b = 0; for i = 1:a if(ts(i) >= stime && ts(i) <= etime) b = b + 1; new(b,1) = ts(i); new(b,2) = ydata(i); end end new(all(new==0,2),:) = []; %% PLOTS THE CONCENTRATION OVER TIME FROM START OF CHAMBER % MEASUREMENT TO THE END. % plot(new(:,1),new(:,2)) t = title(heading); set(t, 'FontWeight', 'bold','FontSize', 15,'FontName','Comic Sans MS') ylabel('Concentration (ppmv)') h = get(gca, 'xlabel'); set(h, 'FontName', 'Calibri','FontSize',12) g = get(gca, 'ylabel'); set(g, 'FontName', 'Calibri','FontSize',12) axis tight set(gca,'XTickLabelMode','auto') datetick('x','HH:MMPM'); axis tight end ******************************************************************** function Rflux(DATE, TIME, DATA, start, endtime, timecorr, Volume, Area, series) % % THIS FUNCTION was FOR CUTTING OUT THE FLUX CHAMBER DATA TAKEN FROM % THE CRDS INTO INDIVIDUAL RUNS AND INTO A FORMAT ACCEPTABLE FOR % THE R STATISTICAL ANALYSIS PROGRAMS BUILT IN PACKAGE R TO 71 % CALCULATE FLUX. IT was NECESSARY TO IMPORT THE CRDS DATA OR TEXT % FILE AS COLUMN VECTORS. % % AUTHOR: AMANDA VARLAND % % FUNCTION CALL: Rflux % % INPUT VALUES: % NAME: DESCRIPTION: EXAMPLE: % DATE DATE COLUMN VECTOR OF STRINGS '2013-12-01' % GIVEN FROM BY CRDS IN THE '2013-12-01' % FORMAT 'YYYY-MM-DD' '2013-12-01' % % % TIME TIME COLUMN VECTOR OF STRINGS '13:45:01.123' % GIVEN FROM BY CRDS IN THE '13:45:01.223' % FORMAT 'HH:MM:SS.FFF' IN 24 '13:45:01.323' % HOUR FORMATTING '13:45:01.423' % % % DATA THE CO2 OR CH4 CONCENTRATION '395' % GIVEN BY THE CRDS IN PPMV '400' % AND COLUMN VECTOR FORMAT '405' % % % timecorr THE CRDS was MEASURED IN 0.25 % MEAN GREENWICH TIME THIS % was THE CORRECTION VALUE FOR % WHATEVER TIME ZONE was CHOSEN % IN HOURS NOTE THE VALUE was % SUBTRACTED FROM THE TIME. % % % Volume THE VOLUME OF THE FLUX 208.1976 % CHAMBER IN LITERS % % % AREA THE CROSS SECTIONAL AREA OF 0.0015 % THE SOURCE AREA IN M^2 % % % series THE NAME DESIGNATION FOR EACH 'MH4' % POINT OR THE SEWER ACCESS % COVER NAME %% COMBINES THE DATE AND TIME COLUMN VECTORS INTO A NEW COLUMN % VECTOR % 72 format longG ts = zeros(length(DATA),1); ts = datenum(strcat(DATE,TIME),'yyyy-mm-ddHH:MM:SS.FFF'); ts = ts - timecorr; stime = datenum(start,'yyyy-mm-ddHH:MM:SS'); etime = datenum(endtime,'yyyy-mm-ddHH:MM:SS'); %% PREDEFINES THE NEW .TXT FILE FOR FASTER COMPUTING % a = length(ts); new = zeros(a,5); %% CALCULATES THEH ELASPED TIME SINCE START OF MEASUREMENT % b = 0; for i = 1:a if(ts(i) >= stime && ts(i) <= etime) b = b + 1; new(b,1) = ts(i); new(b,5) = DATA(i); end end %% REMOVES EMPTY CELLS/ROWS % new(all(new==0,2),:) = []; %% INPUTS THE REQUIRED VALUES INTO THE NEW MATRIX % for n = 1:(b - 1) new(n + 1,4) = new(n + 1,1) - new(n,1) + new(n,4); end 73 new(:,2) = Volume; new(:,3) = Area; new(:,4) = new(:,4) .* 1440; %minutes %% REMOVES DUPLICATES AND CHANGES TO CELL MATRIX, ENABLING IMPORTATION OF % STRINGS % [~,ia,~] = unique(new(:,1),'rows','stable'); new = new(ia,:); new = num2cell(new); [a,b] = size(new); for row = 1:a new{row,1} = series; end %% ADDS THE HEADER ROW % head = {'series','V','A','Time','Concentration'}; new = [head;new]; %% CREATES THE .TXT FILE file = input('Input the output file name: ','s'); dlmcell(file, new,'; '); end ******************************************************************** function Lflux(ETIME, DATA, Volume, Area, series) % % THIS FUNCTION was FOR CORRECTLY FORMATTING Li-COR 8100 RAW % CONCENTRATION DATA INTO A FORMAT ACCEPTABLE FOR THE R STATISTICAL % ANALYSIS PROGRAMS BUILT IN PACKAGE R TO CALCULATE FLUX. IT was % NECESSARY TO IMPORT THE NDIR ANALYZER DATA OR TEXT FILE AS COLUMN % VECTORS. % % AUTHOR: AMANDA VARLAND % 74 % FUNCTION CALL: Lflux % % INPUT VALUES: % NAME: DESCRIPTION: EXAMPLE: % ETIME THE ELAPSED TIME COLUMN VECTOR '0' % GIVEN FROM THE NDIR ANALYZER DATA '1' % '2' % % % DATA THE CO2 CONCENTRATION GIVEN '395' % BY THE NDIR ANALYZER IN PPMV AND '400' % COLUMN VECTOR FORMAT '405' % % % Volume THE VOLUME OF THE FLUX 208.1976 % CHAMBER IN LITERS % % % AREA THE CROSS SECTIONAL AREA OF 0.0015 % THE SOURCE AREA IN M^2 % % % series THE NAME DESIGNATION FOR EACH 'MH4' % POINT OR THE SEWER ACCESS % COVER NAME %% PREDEFINES THE SIZE OF THE NEW .TXT FILES FOR FASTER COMPUTING % AND MAKES SURE THE ELAPSED TIME STARTS AT 0 % format longG a = length(ETIME); new = zeros(a,5); b = 0; for i = 1:a if(ETIME(i) >= 0) b = b + 1; new(b,4) = ETIME(i); new(b,5) = DATA(i); end end 75 %% REMOVES EMPTY CELLS/ROWS % new(all(new==0,2),:) = []; %% INPUTS THE VOLUME, AREA AND ELAPSED TIME IN MINUTES AND SERIES % INTO THE APPROPRIATE COLUMNS IN THE NEW FILE % new(:,2) = Volume; new(:,3) = Area; new(:,4) = new(:,4) ./ 60; %minutes [~,ia,~] = unique(new(:,4),'rows','stable'); new = new(ia,:); new = num2cell(new); [a,b] = size(new); for row = 1:a new{row,1} = series; end %% INSERTS A HEADER ROW % head = {'series','V','A','Time','Concentration'}; new = [head;new]; %% PROMPTS THE USER FOR THE FILE NAME AND CREATES THE FILE % file = input('Input the output file name: ','s'); dlmcell(file, new,'; '); end APPENDIX C RAW CHAMBER FLUX DATA Table 11: Raw CO2 Flux Chamber Data Cover ID Date MH0 10/16/2013 MH0 MH0 MH0 MH0 MH0 MH0 MH0 MH0 MH00 MH00 MH00 10/16/2013 10/15/2013 10/15/2013 9/16/2013 9/16/2013 10/3/2013 9/16/2013 10/3/2013 10/16/2013 10/15/2013 10/14/2013 MH1 10/16/2013 MH1 10/16/2013 MH1 MH1 MH1 MH1 MH1 MH1 10/2/2013 10/15/2013 10/2/2013 10/15/2013 10/2/2013 9/16/2013 Start Time 12:52:37 PM 1:09:35 PM 2:07:57 PM 2:28:13 PM 2:48:02 PM 3:03:10 PM 3:05:20 PM 3:20:08 PM 3:21:54 PM 1:44:21 PM 1:46:00 PM 4:09:08 PM 12:16:21 PM 12:34:02 PM 2:40:25 PM 2:47:07 PM 2:54:22 PM 3:02:29 PM 3:11:57 PM 3:36:11 PM End Time CO2 Flux (µL/min) CO2 Flux (g/day) CO2 Flux (μmol/s) STD Lower 95% Confidenc e Upper 95% Confidenc e Spectromete r 1:03:02 PM 3908 10.74 2.83 32.9 14024 14152 CRDS 1:19:30 PM 2:20:18 PM 2:38:46 PM 2:58:01 PM 3:13:02 PM 3:15:46 PM 3:31:00 PM 3:32:12 PM 1:54:16 PM 1:58:41 PM 4:13:00 PM 5763 3632 3719 9868 21213 760 15325 531 392 115 1282 15.85 9.98 10.21 25.07 53.89 2.07 38.93 1.45 1.07 0.32 3.51 4.17 2.62 2.69 6.59 14.17 0.54 10.24 0.38 0.28 0.08 0.92 34.0 22.2 13.2 74.1 110.9 3.3 56.9 1.3 3.3 0.8 40.6 20455 13075 13401 34257 69490 2794 51751 1956 1441 426 4612 20588 13162 13452 34547 69925 2807 51974 1961 1454 429 4771 CRDS CRDS CRDS CRDS CRDS CRDS CRDS CRDS CRDS CRDS CRDS 12:26:46 PM 1453 4.00 1.05 5.7 5346 5369 CRDS 12:44:31 PM 3426 9.44 2.48 5.5 12527 12549 CRDS 2:50:11 PM 2:56:43 PM 3:04:48 PM 3:12:53 PM 3:22:33 PM 3:46:00 PM 7934 3333 18198 7789 17518 3403 20.58 9.15 47.21 21.39 45.45 8.63 5.41 2.41 12.42 5.62 11.95 2.27 39.3 5.4 21.1 32.6 33.4 11.0 28545 12191 63538 28005 61564 12444 28699 12213 63621 28133 61395 12487 CRDS CRDS CRDS CRDS CRDS CRDS 77 Table 11: Continued CO2 Flux (µL/min) CO2 Flux (g/day) CO2 Flux (μmol/s) STD Lower 95% Confidenc e Upper 95% Confidenc e Spectromete r 3:47:04 PM 4:03:45 PM 4:04:35 PM 4:20:00 PM 11:49:00 AM 758 4238 1232 2675 2.10 10.74 3.42 6.78 0.55 2.82 0.90 1.78 0.8 20.8 1.6 17.6 2799 15441 4543 9790 2803 15522 4549 9859 CRDS CRDS CRDS CRDS 2501 6.91 1.82 14.8 9051 9109 CRDS 12:04:37 PM 5175 14.29 3.76 19.6 18365 18442 CRDS 1:13:00 PM 1:23:00 PM 1179 3.30 0.87 4212 4444 CRDS 1:27:18 PM 1:40:39 PM 3:16:00 PM 3:35:17 PM 3:50:12 PM 3:52:13 PM 4:08:01 PM 4:06:47 PM 4:22:14 PM 4:34:54 PM 4:35:28 PM 4:50:15 PM 5:06:01 PM 1:37:41 PM 1:50:59 PM 3:26:00 PM 3:45:52 PM 4:00:56 PM 4:02:07 PM 4:17:01 PM 4:17:57 PM 4:32:02 PM 4:45:00 PM 4:45:00 PM 5:01:01 PM 5:16:00 PM 225 160 14 11575 9155 9340 4300 6936 5801 4905 4273 4867 4064 0.63 0.45 0.04 30.05 23.80 25.14 11.57 18.03 15.66 12.94 11.57 12.83 10.72 0.17 0.12 0.01 7.90 6.26 6.61 3.04 4.74 4.12 3.40 3.04 3.38 2.82 828 586 52 39505 31732 32255 15376 24401 20539 17390 15299 17355 14567 836 597 53 39566 31780 32320 15436 24440 20571 17629 15323 17402 14627 CRDS CRDS CRDS CRDS CRDS CRDS CRDS CRDS CRDS CRDS CRDS CRDS CRDS Cover ID Date Start Time End Time MH1 MH1 MH1 MH1 10/3/2013 9/16/2013 10/3/2013 9/16/2013 MH2 10/16/2013 MH2 10/16/2013 3:37:31 PM 3:53:00 PM 3:53:47 PM 4:10:04 PM 11:39:17 AM 11:54:00 AM MH2 10/4/2013 MH2 MH2 MH2 MH2 MH2 MH2 MH2 MH2 MH2 MH2 MH2 MH2 MH2 10/4/2013 10/4/2013 9/17/2013 10/2/2013 10/2/2013 9/26/2013 9/26/2013 10/2/2013 9/26/2013 9/19/2013 9/26/2013 9/19/2013 9/19/2013 5930. 5 2.0 2.8 0.2 15.4 12.3 16.4 15.5 10.0 8.3 61.0 6.1 12.0 15.3 78 Table 11: Continued Cover ID Date MH3 10/16/2013 MH3 10/16/2013 MH3 MH3 MH3 MH3 MH3 MH3 MH3 10/15/2013 10/15/2013 9/12/2013 9/12/2013 9/19/2013 9/19/2013 9/19/2013 MH4 10/26/2013 MH4 MH4 MH4 MH4 MH4 MH4 MH4 10/26/2013 10/26/2013 10/26/2013 10/26/2013 10/26/2013 10/25/2013 10/25/2013 MH4 10/25/2013 MH4 10/16/2013 Start Time End Time 11:06:02 AM 11:23:22 AM 3:27:00 PM 3:40:52 PM 3:25:06 PM 4:49:03 PM 5:23:04 PM 5:35:53 PM 5:50:02 PM 12:02:00 AM 1:03:29 AM 2:02:54 AM 4:03:00 AM 5:04:50 AM 7:03:42 AM 9:09:22 AM 9:41:40 AM 10:10:17 AM 10:32:51 AM 11:15:33 AM 11:33:11 AM 3:36:04 PM 3:52:03 PM 3:55:00 PM 5:19:27 PM 5:33:31 PM 5:46:18 PM 6:00:49 PM 12:13:42 AM 1:14:24 AM 2:12:46 AM 4:13:01 AM 5:15:52 AM 7:14:29 AM 9:19:25 AM 9:52:52 AM 10:20:31 AM 10:42:15 AM CO2 Flux (µL/min) CO2 Flux (g/day) CO2 Flux (μmol/s) STD Lower 95% Confidenc e Upper 95% Confidenc e Spectromete r 456 1.26 0.33 6.5 1670 1695 CRDS 305 0.84 0.22 2.7 1122 1132 CRDS 1757 8715 8843 3204 595 407 1027 4.82 23.93 23.04 8.28 1.57 1.08 2.71 1.27 6.29 6.06 2.18 0.41 0.28 0.71 21.3 19.1 10.2 10.8 3.3 2.0 7.6 6357 29828 30360 11511 2186 1498 3756 6440 29903 30400 11553 2199 1506 3785 CRDS CRDS CRDS CRDS CRDS CRDS CRDS 2113 5.91 1.55 3.2 7739 7752 CRDS 2957 763 886 1612 2883 285 197 8.27 2.14 2.48 4.54 8.14 0.79 0.54 2.18 0.56 0.65 1.19 2.14 0.21 0.14 3.3 1.6 1.9 6.8 4.4 1.1 2.9 10789 2814 3265 5910 10519 1053 723 10801 2820 3273 5937 10536 1057 735 CRDS CRDS CRDS CRDS CRDS CRDS CRDS 1003 2.76 0.73 4.8 3690 3709 CRDS 603 1.68 0.44 1.2 2226 2231 CRDS 79 Table 11: Continued Cover ID Date MH4 10/25/2013 MH4 10/16/2013 MH4 10/21/2013 MH4 9/30/2013 MH4 10/25/2013 MH4 9/30/2013 MH4 9/30/2013 MH4 10/25/2013 MH4 9/30/2013 MH4 9/30/2013 MH4 10/25/2013 MH4 MH4 MH4 10/25/2013 10/25/2013 10/25/2013 CO2 Flux (µL/min) CO2 Flux (g/day) CO2 Flux (μmol/s) STD Lower 95% Confidenc e Upper 95% Confidenc e Spectromete r 61 0.17 0.04 1.8 221 228 CRDS 1253 3.48 0.91 4.3 4607 4624 CRDS 2994 8.23 2.16 98.0 10740 11124 CRDS 1199 3.10 0.82 9.9 4401 4439 CRDS 948 2.59 0.68 11.0 3476 3519 CRDS 1369 3.54 0.93 8.4 5024 5057 CRDS 887 2.28 0.60 13.0 3247 3298 CRDS 12:02:28 PM 1772 4.82 1.27 12.0 6487 6534 CRDS 12:05:18 PM 2211 5.72 1.51 22.8 8065 8154 CRDS 12:18:28 PM 4720 12.22 3.21 46.7 17023 17206 CRDS 12:41:54 PM 5062 13.72 3.61 66.8 18175 18437 CRDS 1:23:27 PM 1:58:08 PM 3:08:45 PM 4555 3184 51984 12.29 8.53 139.03 3.23 2.24 36.56 69.9 109.9 364.6 16374 11402 158130 16648 11833 159550 CRDS CRDS CRDS Start Time End Time 10:44:45 AM 10:46:42 AM 10:59:35 AM 11:10:04 AM 11:20:10 AM 11:26:00 AM 11:41:42 AM 11:52:11 AM 11:55:55 AM 12:08:28 PM 12:32:37 PM 1:11:38 PM 1:48:43 PM 2:59:12 PM 10:55:29 AM 10:56:50 AM 11:10:01 AM 11:19:57 AM 11:32:00 AM 11:35:10 AM 11:51:16 AM 80 Table 11: Continued Cover ID Date Start Time End Time CO2 Flux (µL/min) CO2 Flux (g/day) CO2 Flux (μmol/s) STD Lower 95% Confidenc e Upper 95% Confidenc e Spectromete r MH4 MH4 MH4 MH4 MH4 MH4 MH4 MH4 MH4 MH4 MH4 MH4 MH4 10/25/2013 10/25/2013 10/15/2013 10/15/2013 10/25/2013 10/25/2013 10/25/2013 10/25/2013 10/25/2013 10/25/2013 10/25/2013 10/25/2013 10/25/2013 3:37:16 PM 4:03:17 PM 4:11:21 PM 4:25:21 PM 4:31:32 PM 5:00:55 PM 5:28:18 PM 5:56:09 PM 6:28:22 PM 6:57:53 PM 7:58:09 PM 8:36:12 PM 9:07:37 PM 258 22417 8083 13473 30517 22639 13881 16947 8375 13555 5086 4170 2609 0.69 59.81 22.19 36.91 81.67 60.79 37.34 45.69 22.70 37.73 13.95 11.45 7.17 0.18 15.73 5.84 9.71 21.48 15.99 9.82 12.02 5.97 9.92 3.67 3.01 1.89 2.1 114.1 57.0 44.8 170.2 150.0 81.4 61.1 102.7 22.0 10.2 5.1 10.0 951 75240 28701 46821 99420 75813 48138 58106 29629 47092 18364 15128 9525 960 75687 28925 46997 100090 76401 48457 58346 30031 47178 18404 15148 9565 CRDS CRDS CRDS CRDS CRDS CRDS CRDS CRDS CRDS CRDS CRDS CRDS CRDS MH4 10/25/2013 10:21:34 PM 723 2.00 0.53 1.9 2665 2673 CRDS MH4 10/25/2013 3:26:21 PM 3:53:51 PM 4:01:20 PM 4:16:33 PM 4:20:22 PM 4:48:58 PM 5:16:16 PM 5:45:13 PM 6:17:52 PM 6:46:55 PM 7:46:24 PM 8:25:24 PM 8:56:50 PM 10:11:17 PM 11:02:51 PM 11:12:00 PM 306 0.85 0.22 5.6 1122 1144 CRDS 9:48:29 AM 9:56:52 AM 31167 86.36 22.71 460.1 85058 86861 CRDS 10:01:01 AM 10:15:28 AM 10:10:41 AM 10:25:32 AM 1632 4.52 1.19 8.1 5894 5926 CRDS 1923 5.31 1.40 37.8 6861 7010 CRDS MHSU 1 MHSU 1 MHSU 1 10/14/2013 10/14/2013 10/14/2013 81 Table 11: Continued Cover ID MHSU 1 MHSU 1 MHSU 1 MHSU 1 MHSU 1 MHSU 1 MHSU 1 MHSU 1 MHSU 1 MHSU 1 MHSU 1 MHSU 1 MHSU 1 Date 10/7/2013 10/9/2013 9/23/2013 10/7/2013 10/9/2013 9/23/2013 10/7/2013 10/9/2013 9/23/2013 10/7/2013 10/21/2013 10/15/2013 10/21/2013 Start Time End Time 10:23:26 AM 10:24:27 AM 10:28:08 AM 10:38:56 AM 10:39:53 AM 10:44:07 AM 10:54:58 AM 10:59:34 AM 11:02:20 AM 11:10:54 AM 11:31:19 AM 11:48:23 AM 11:48:10 AM 10:34:00 AM 10:35:06 AM 10:38:21 AM 10:49:00 AM 10:50:41 AM 10:53:13 AM 11:05:45 AM 11:10:52 AM 11:12:53 AM 11:20:16 AM 11:42:00 AM 11:57:16 AM 12:00:49 PM CO2 Flux (µL/min) CO2 Flux (g/day) CO2 Flux (μmol/s) STD Lower 95% Confidenc e Upper 95% Confidenc e Spectromete r 5221 14.08 3.70 22.5 18035 18123 CRDS 9926 26.70 7.02 55.4 32539 32756 CRDS 3738 10.01 2.63 10.0 13160 13200 CRDS 4133 11.09 2.92 18.7 14465 14538 CRDS 14904 39.94 10.50 49.0 46677 46869 CRDS 4847 12.97 3.41 13.3 16839 16891 CRDS 6150 16.51 4.34 12.9 21047 21098 CRDS 5899 15.81 4.16 9.7 20252 20290 CRDS 2611 6.99 1.84 10.1 9319 9359 CRDS 5646 15.09 3.97 14.7 19435 19492 CRDS 2883 7.89 2.08 13.0 10244 10295 CRDS 209 0.58 0.15 1.0 770 773 CRDS 2171 5.92 1.56 8.9 7788 7823 CRDS 82 Table 11: Continued Cover ID MHSU 1 MHSU 1 MHSU 1 MHSU 1 MHSU 1 MHSU 1 MHSU 1 MHSU 1 MHSU 3 MHSU 3 MHSU 3 MHSU 3 MHSU 3 Date 10/15/2013 10/21/2013 9/20/2013 9/20/2013 Start Time 12:01:06 PM 12:08:18 PM 12:35:53 PM 12:49:08 PM End Time CO2 Flux (µL/min) CO2 Flux (g/day) CO2 Flux (μmol/s) STD Lower 95% Confidenc e Upper 95% Confidenc e Spectromete r 12:10:00 PM 1157 3.19 0.84 5.6 4206 4228 CRDS 12:18:18 PM 2527 6.89 1.81 7.3 9030 9059 CRDS 12:45:00 PM 16107 42.16 11.09 78.2 50027 50334 CRDS 12:58:52 PM 38900 101.83 26.78 120.3 103380 103850 CRDS 9/20/2013 1:06:13 PM 1:16:00 PM 25867 67.41 17.73 104.5 74609 75018 CRDS 10/22/2013 3:01:24 PM 3:11:47 PM 5310 14.20 3.73 24.7 18328 18424 CRDS 10/22/2013 3:15:11 PM 3:25:57 PM 6301 16.85 4.43 13.5 21533 21586 CRDS 10/22/2013 3:28:25 PM 3:37:39 PM 5698 15.24 4.01 36.1 19559 19700 CRDS 10:43:23 AM 10:56:00 AM 10:57:17 AM 11:28:10 AM 11:41:43 AM 10:53:15 AM 11:06:11 AM 11:07:22 AM 11:38:57 AM 11:49:20 AM 1145 3.17 0.83 5.6 4206 4228 CRDS 8582 22.61 5.95 130.7 30178 30690 CRDS 1707 4.73 1.24 5.3 6256 6277 CRDS 1775 4.66 1.23 6.0 6505 6529 CRDS 2546 6.78 1.78 10.2 9284 9325 CRDS 10/15/2013 10/28/2013 10/15/2013 10/28/2013 9/23/2013 83 Table 11: Continued Cover ID MHSU 3 MHSU 3 MHSU 3 MHSU 3 MHSU 3 MHSU 3 MHSU 3 MHSU 3 MHSU 3 MHSU 3 MHSU 3 MHSU 3 MHSU 3 Date 10/7/2013 9/23/2013 10/28/2013 10/7/2013 9/23/2013 10/7/2013 10/28/2013 Start Time End Time CO2 Flux (µL/min) CO2 Flux (g/day) CO2 Flux (μmol/s) STD Lower 95% Confidenc e Upper 95% Confidenc e Spectromete r 11:49:14 AM 11:58:59 AM 12:00:00 PM 12:05:29 PM 12:14:01 PM 12:19:19 PM 12:33:42 PM 11:59:57 AM 2756 7.33 1.93 12.7 10039 10089 CRDS 12:08:47 PM 2486 6.62 1.74 8.7 9072 9106 CRDS 12:12:04 PM 11629 30.40 7.99 217.3 40242 41094 CRDS 12:15:16 PM 3656 9.73 2.56 17.9 13249 13319 CRDS 12:24:14 PM 4216 11.21 2.95 18.2 15240 15312 CRDS 12:25:54 PM 6750 17.84 4.69 39.7 24074 24229 CRDS 12:43:49 PM 10011 26.17 6.88 137.2 35004 35542 CRDS 10/28/2013 1:06:38 PM 1:16:44 PM 1955 5.11 1.34 17.2 7135 7202 CRDS 10/21/2013 1:24:27 PM 1:35:05 PM 1183236 5 31961.0 2 8405.34 33799 .0 4989800 5122300 CRDS 9/20/2013 1:31:27 PM 1:41:18 PM 1740 4.53 1.19 6.3 6377 6402 CRDS 10/28/2013 1:38:57 PM 1:49:43 PM 2264 5.92 1.56 26.8 8237 8342 CRDS 10/21/2013 1:40:46 PM 1:51:05 PM 576 1.55 0.41 2.5 2123 2133 CRDS 9/20/2013 1:44:30 PM 1:54:45 PM 1600 4.15 1.09 8.0 5862 5894 CRDS 84 Table 11: Continued Cover ID MHSU 3 MHSU 3 MHSU 3 MHSU 3 MHSU 3 MHSU 3 MHSU 3 MHSU 3 MHSU 4 MHSU 4 MHSU 5 MHSU 5 MHSU 5 Date Start Time End Time CO2 Flux (µL/min) CO2 Flux (g/day) CO2 Flux (μmol/s) STD Lower 95% Confidenc e Upper 95% Confidenc e Spectromete r 10/21/2013 1:56:17 PM 2:07:07 PM 1458 3.93 1.03 10.1 5342 5381 CRDS 9/20/2013 1:58:40 AM 2:08:42 PM 2054 5.33 1.40 21.7 7486 7571 CRDS 10/24/2013 3:30:09 PM 3:40:31 PM 783 2.09 0.55 2.8 2885 2896 CRDS 10/24/2013 3:44:03 PM 3:54:34 PM 847 2.26 0.60 3.8 3117 3131 CRDS 10/24/2013 4:03:26 PM 4:13:49 PM 3181 8.51 2.24 9.5 11569 11606 CRDS 10/16/2013 4:04:29 PM 4:15:08 PM 357 0.97 0.26 4.6 1312 1330 CRDS 10/24/2013 4:16:00 PM 4:27:55 PM 3476 9.30 2.45 12.6 12618 12668 CRDS 10/16/2013 4:20:34 PM 4:31:00 PM 1671 4.55 1.20 9.4 6116 6153 CRDS 12:43:00 PM 156 0.41 0.11 3.5 570 583 CRDS 12:58:00 PM 745 1.98 0.52 11.0 2730 2773 CRDS 9/23/2013 9/23/2013 12:33:11 PM 12:48:40 PM 10/14/2013 2:17:01 PM 2:27:28 PM 3515 9.61 2.53 21.6 12702 12787 CRDS 10/14/2013 2:30:55 PM 2:41:18 PM 2108 5.76 1.52 21.5 7666 7750 CRDS 10/14/2013 2:45:52 PM 2:56:23 PM 1089 2.98 0.78 4.3 3999 4016 CRDS 85 Table 11: Continued Cover ID MHSU 5 MHSU 5 MHSU 6 MHSU 6 MHSU 6 MHSU 6 MHSU 6 MH4 MH4 MH4 MH4 MH4 MH4 MH4 MH4 MH4 MH4 Date Start Time End Time CO2 Flux (µL/min) CO2 Flux (g/day) CO2 Flux (μmol/s) STD Lower 95% Confidenc e Upper 95% Confidenc e Spectromete r 10/16/2013 2:47:15 PM 2:56:51 PM 1355 3.69 0.97 9.8 4960 4998 CRDS 10/16/2013 3:03:49 PM 3:15:01 PM 2374 6.47 1.70 4.5 8659 8676 CRDS 10/16/2013 2:16:58 PM 2:26:59 PM 435 1.19 0.31 2.9 1603 1615 CRDS 10/16/2013 2:32:19 PM 2:42:50 PM 761 2.07 0.55 3.8 2803 2818 CRDS 10/14/2013 3:05:59 PM 3:16:39 PM 638 1.74 0.46 9.9 2339 2378 CRDS 10/14/2013 3:24:42 PM 3:35:51 PM 86 0.24 0.06 1.9 315 323 CRDS 10/14/2013 3:43:00 PM 3:54:20 PM 6107 16.72 4.40 196.1 21585 22354 CRDS 8:52:00 AM 9:24:00 AM 9:56:00 AM 12:13:00 PM 12:57:00 PM 1:28:00 PM 2:03:00 PM 2:58:00 PM 3:25:00 PM 3:52:00 PM 78 416 703 561 3372 2018 3167 6561 4511 9739 0.22 1.15 1.94 1.53 9.17 5.43 8.49 17.55 12.05 25.99 0.06 0.30 0.51 0.40 2.41 1.43 2.23 4.61 3.17 6.83 3.1 14.9 31.7 20.7 106.2 60.2 87.2 68.2 824.7 920.9 278 1488 2505 2007 12431 7346 11671 25259 15475 37201 290 1546 2630 2088 12848 7583 12013 25527 18714 40819 NDIR NDIR NDIR NDIR NDIR NDIR NDIR NDIR NDIR NDIR 10/25/2013 10/25/2013 10/25/2013 10/25/2013 10/25/2013 10/25/2013 10/25/2013 10/25/2013 10/25/2013 10/25/2013 86 Table 11: Continued Cover ID Date MH4 MH4 MH4 MH4 MH4 MH4 MH4 MH4 MH4 MH4 MH4 10/25/2013 10/25/2013 10/25/2013 10/25/2013 10/25/2013 10/25/2013 10/25/2013 10/25/2013 10/25/2013 10/25/2013 10/25/2013 MH4 10/26/2013 MH4 MH4 MH4 MH4 10/26/2013 10/26/2013 10/26/2013 10/26/2013 MH3 10/18/2013 MH3 10/18/2013 MH3 10/18/2013 Start Time End Time 10:19:48 AM 10:52:55 AM 11:11:52 AM 4:20:00 PM 4:48:00 PM 5:16:00 PM 5:44:00 PM 6:46:00 PM 7:15:00 PM 7:46:00 PM 8:25:00 PM 8:56:00 PM 10:27:00 PM 11:20:00 PM 12:17:00 AM 1:16:00 AM 2:16:00 AM 3:16:00 AM 7:16:00 AM 10:29:49 AM 11:02:55 AM 11:21:51 AM CO2 Flux (µL/min) CO2 Flux (g/day) CO2 Flux (μmol/s) STD Lower 95% Confidenc e Upper 95% Confidenc e Spectromete r 10151 17361 3310 15933 11067 6971 2037 2437 3569 1568 196 27.17 46.62 8.91 42.96 30.17 19.06 5.71 6.69 9.81 4.35 0.55 7.14 12.26 2.34 11.30 7.93 5.01 1.50 1.76 2.58 1.14 0.14 440.9 403.9 334.5 838.1 135.4 74.7 53.7 42.4 59.7 17.1 9.8 39999 75795 11739 67339 44871 26994 7435 8971 13295 5743 695 41730 77381 13053 70631 45403 27288 7646 9138 13530 5810 733 NDIR NDIR NDIR NDIR NDIR NDIR NDIR NDIR NDIR NDIR NDIR 2129 5.93 1.56 37.2 7815 7961 NDIR 3669 3126 389 270 10.27 8.75 1.09 0.76 2.70 2.30 0.29 0.20 47.0 86.9 6.8 10.2 13720 11529 1402 962 13905 11870 1429 1002 NDIR NDIR NDIR NDIR 82 0.22 0.06 3.8 290 305 NDIR 395 1.08 0.28 10.2 1425 1465 NDIR 609 1.66 0.44 12.0 2212 2259 NDIR 87 Table 11: Continued Cover ID Date MH3 10/18/2013 MH3 10/18/2013 MH3 10/18/2013 MH3 MH3 MH3 CO2 Flux (µL/min) CO2 Flux (g/day) CO2 Flux (μmol/s) STD Lower 95% Confidenc e Upper 95% Confidenc e Spectromete r 995 2.71 0.71 13.6 3653 3706 NDIR 972 2.64 0.69 16.2 3560 3624 NDIR 12:49:42 PM 3321 8.84 2.33 60.8 12732 12971 NDIR 1:12:14 PM 1:38:11 PM 2:00:57 PM 5078 15248 8664 13.56 40.72 23.13 3.57 10.71 6.08 18873 83779 37491 21968 85752 38659 NDIR NDIR NDIR 2:08:02 PM 2:18:02 PM 9927 26.50 6.97 42969 47481 NDIR 2:39:26 PM 3:01:00 PM 3:25:33 PM 4:13:59 PM 5:02:18 PM 5:22:18 PM 5:39:03 PM 5:55:31 PM 6:11:58 PM 6:29:05 PM 8:09:09 PM 8:39:11 PM 2:49:26 PM 3:11:00 PM 3:35:32 PM 4:23:59 PM 5:12:18 PM 5:32:18 PM 5:49:03 PM 6:05:31 PM 6:21:58 PM 6:39:05 PM 8:19:09 PM 8:49:11 PM 16791 13162 13130 19990 361 549 1548 3631 3563 2497 574 1371 44.79 35.09 35.03 53.37 0.97 1.47 4.15 9.75 9.58 6.74 1.57 3.74 11.78 9.23 9.21 14.04 0.25 0.39 1.09 2.56 2.52 1.77 0.41 0.98 788.0 502.2 297.5 1148. 6 516.1 211.6 243.7 691.4 68.5 40.9 51.3 65.4 115.9 52.1 17.8 29.2 100440 66394 66111 173240 1186 1931 5683 14025 13640 9409 2069 5050 102470 67226 67068 175950 1455 2092 5884 14282 14095 9613 2139 5165 NDIR NDIR NDIR NDIR NDIR NDIR NDIR NDIR NDIR NDIR NDIR NDIR Start Time End Time 11:42:17 AM 11:58:38 AM 10/18/2013 10/18/2013 10/18/2013 11:32:17 AM 11:48:38 AM 12:39:43 PM 1:02:14 PM 1:28:11 PM 1:50:57 PM MH3 10/18/2013 MH3 MH3 MH3 MH3 MH3 MH3 MH3 MH3 MH3 MH3 MH3 MH3 10/18/2013 10/18/2013 10/18/2013 10/18/2013 10/18/2013 10/18/2013 10/18/2013 10/18/2013 10/18/2013 10/18/2013 10/18/2013 10/18/2013 88 Table 11: Continued Cover ID Date Start Time End Time CO2 Flux (µL/min) CO2 Flux (g/day) CO2 Flux (μmol/s) STD Lower 95% Confidenc e Upper 95% Confidenc e Spectromete r MH3 MH3 MH3 MH3 MH3 10/18/2013 10/18/2013 10/18/2013 10/18/2013 10/18/2013 9:03:12 PM 9:18:05 PM 9:33:29 PM 9:48:07 PM 10:03:18 PM 180 2652 1194 545 1114 0.49 7.23 3.26 1.49 3.04 0.13 1.90 0.86 0.39 0.80 10.7 93.0 23.9 21.0 29.4 634 9956 4386 1957 4070 676 10321 4480 2039 4185 NDIR NDIR NDIR NDIR NDIR MH3 10/18/2013 10:18:16 PM 1407 3.84 1.01 14.9 5214 5273 NDIR MH3 10/18/2013 10:33:44 PM 380 1.04 0.27 7.9 1373 1404 NDIR MH3 10/18/2013 10:57:53 PM 2105 5.75 1.51 16.8 7924 7991 NDIR MH3 10/18/2013 11:15:36 PM 3450 9.43 2.48 22.8 13371 13461 NDIR MH3 10/18/2013 11:36:28 PM 2437 6.66 1.75 34.3 9209 9343 NDIR MH3 10/18/2013 3460 9.45 2.49 30.0 13396 13514 NDIR MH3 MH3 MH3 MH3 MH3 MH3 MH3 10/19/2013 10/19/2013 10/19/2013 10/19/2013 10/19/2013 10/19/2013 10/19/2013 8:53:12 PM 9:08:05 PM 9:23:29 PM 9:38:07 PM 9:53:18 PM 10:08:16 PM 10:23:44 PM 10:47:53 PM 11:05:36 PM 11:26:28 PM 11:52:29 PM 4:44:47 PM 5:02:42 PM 5:22:38 PM 5:38:05 PM 5:53:57 PM 6:15:33 PM 6:32:39 PM 3655 1056 3157 3450 2507 1458 5417 9.60 2.78 8.33 9.12 6.64 3.87 14.45 2.53 0.73 2.19 2.40 1.75 1.02 3.80 322.2 76.8 76.1 78.3 149.6 29.4 73.1 13596 3754 12022 13229 9245 5379 21808 14862 4056 12321 13537 9832 5494 22094 NDIR NDIR NDIR NDIR NDIR NDIR NDIR 12:02:29 AM 4:54:47 PM 5:12:42 PM 5:32:38 PM 5:48:05 PM 6:03:57 PM 6:25:33 PM 6:42:39 PM 89 Table 11: Continued Cover ID CO2 Flux (µL/min) CO2 Flux (g/day) CO2 Flux (μmol/s) STD Lower 95% Confidenc e Upper 95% Confidenc e Spectromete r 7:02:03 PM 7:23:53 PM 7:47:28 PM 11:12:00 AM 11:44:00 AM 4998 6045 5199 13.36 16.21 13.96 3.51 4.26 3.67 48.8 77.8 73.9 19970 24720 20832 20161 25025 21123 NDIR NDIR NDIR 389 1.02 0.27 38.7 1341 1493 NDIR 3239 8.47 2.23 103.1 11956 12361 NDIR 10/28/2013 12:17:00 PM 1657 4.33 1.14 26.3 6065 6168 NDIR 10/28/2013 12:47:00 PM 10684 27.92 7.34 1070. 2 41690 45894 NDIR 10/28/2013 1:22:00 PM 1363 3.56 0.94 72.8 4871 5157 NDIR 10/28/2013 1:52:00 PM 1933 5.05 1.33 110.3 6938 7371 NDIR 14068 39.31 10.34 440188 1221.91 321.35 268472 744.21 195.72 58775 162.79 75083 207.91 Date Start Time End Time MH3 MH3 MH3 MHSU 3 MHSU 3 MHSU 3 MHSU 3 MHSU 3 MHSU 3 MHSU 5 10/19/2013 10/19/2013 10/19/2013 6:52:03 PM 7:13:53 PM 7:37:28 PM MH0 1/25/2014 MH0 1/25/2014 MH1 1/25/2014 MH1 1/25/2014 10/28/2013 10/28/2013 1/25/2014 10:07:00 AM 10:59:07 AM 11:13:23 AM 11:27:27 AM 11:48:00 AM 10:17:32 AM 11:09:37 AM 11:23:29 AM 11:37:57 AM 11:58:36 AM 6066. 4 4209. 6 4509. 6 40182 64000 CRDS 1574800 1590000 CRDS 967780 985000 CRDS 42.81 911.0 215140 219000 CRDS 54.68 1635. 4 273580 280000 CRDS 90 Table 12: Raw CH4 Flux Chamber Data Cover ID Date Start Time End Time CH4 Flux (µL/min) MH0 MH0 MH0 MH0 MH0 MH0 MH0 MH0 MH0 MH00 MH00 MH00 MH1 MH1 MH1 MH1 MH1 MH1 MH1 MH1 MH1 MH1 10/16/2013 10/16/2013 10/15/2013 10/15/2013 9/16/2013 9/16/2013 10/3/2013 9/16/2013 10/3/2013 10/16/2013 10/15/2013 10/14/2013 10/16/2013 10/16/2013 10/2/2013 10/15/2013 10/2/2013 10/15/2013 10/2/2013 9/16/2013 10/3/2013 9/16/2013 12:52:37 PM 1:09:35 PM 2:07:57 PM 2:28:13 PM 2:48:02 PM 3:03:10 PM 3:05:20 PM 3:20:08 PM 3:21:54 PM 1:44:21 PM 1:46:00 PM 4:09:08 PM 12:16:21 PM 12:34:02 PM 2:40:25 PM 2:47:07 PM 2:54:22 PM 3:02:29 PM 3:11:57 PM 3:36:11 PM 3:37:31 PM 3:53:00 PM 1:03:02 PM 1:19:30 PM 2:20:18 PM 2:38:46 PM 2:58:01 PM 3:13:02 PM 3:15:46 PM 3:31:00 PM 3:32:12 PM 1:54:16 PM 1:58:41 PM 4:13:00 PM 12:26:46 PM 12:44:31 PM 2:50:11 PM 2:56:43 PM 3:04:48 PM 3:12:53 PM 3:22:33 PM 3:46:00 PM 3:47:04 PM 4:03:45 PM 25.5 21.0 58.4 52.0 116.1 228.8 36.6 165.4 72.7 5.1 0.8 4.5 5.3 10.7 18.4 38.8 27.9 89.0 22.1 6.5 89.2 7.4 CH4 CH4 Flux Flux (μmol/s) (g/day) 0.026 0.021 0.058 0.052 0.107 0.211 0.036 0.153 0.072 0.005 0.001 0.004 0.005 0.011 0.017 0.039 0.026 0.089 0.021 0.006 0.090 0.007 0.018 0.015 0.042 0.037 0.077 0.152 0.026 0.110 0.052 0.004 0.001 0.003 0.004 0.008 0.013 0.028 0.019 0.064 0.015 0.004 0.065 0.005 STD 0.133 0.135 0.358 0.196 0.859 1.309 0.353 0.660 0.168 0.048 0.005 0.633 0.018 0.018 0.078 0.066 0.034 0.398 0.051 0.027 0.111 0.036 Lower 95% Upper 95% Spectrometer Confidence3 Confidence4 94.4 77.6 215.6 192.3 428.1 844.2 135.0 611.1 268.9 18.9 2.9 15.3 19.5 39.6 68.1 143.6 103.4 329.1 81.7 24.1 330.3 27.5 94.9 78.1 217.0 193.1 315.1 849.3 136.4 613.7 265.6 19.1 2.9 17.8 19.6 39.7 68.4 143.9 103.5 330.6 81.9 24.2 330.7 27.7 CRDS CRDS CRDS CRDS CRDS CRDS CRDS CRDS CRDS CRDS CRDS CRDS CRDS CRDS CRDS CRDS CRDS CRDS CRDS CRDS CRDS CRDS 91 Table 12: Continued Cover ID Date MH1 MH1 MH2 MH2 MH2 MH2 MH2 MH2 MH2 MH2 MH2 MH2 MH2 MH2 MH2 MH2 MH2 MH2 MH3 MH3 MH3 MH3 MH3 10/3/2013 9/16/2013 10/16/2013 10/16/2013 10/4/2013 10/4/2013 10/4/2013 9/17/2013 10/2/2013 10/2/2013 9/26/2013 9/26/2013 10/2/2013 9/26/2013 9/19/2013 9/26/2013 9/19/2013 9/19/2013 10/16/2013 10/16/2013 10/15/2013 10/15/2013 9/12/2013 Start Time End Time 3:53:47 PM 4:04:35 PM 4:10:04 PM 4:20:00 PM 11:39:17 AM 11:49:00 AM 11:54:00 AM 12:04:37 PM 1:13:00 PM 1:23:00 PM 1:27:18 PM 1:37:41 PM 1:40:39 PM 1:50:59 PM 3:16:00 PM 3:26:00 PM 3:35:17 PM 3:45:52 PM 3:50:12 PM 4:00:56 PM 3:52:13 PM 4:02:07 PM 4:08:01 PM 4:17:01 PM 4:06:47 PM 4:17:57 PM 4:22:14 PM 4:32:02 PM 4:34:54 PM 4:45:00 PM 4:35:28 PM 4:45:00 PM 4:50:15 PM 5:01:01 PM 5:06:01 PM 5:16:00 PM 11:06:02 AM 11:15:33 AM 11:23:22 AM 11:33:11 AM 3:27:00 PM 3:36:04 PM 3:40:52 PM 3:52:03 PM 3:25:06 PM 3:55:00 PM CH4 Flux (µL/min) 123.7 4.2 9.2 18.2 0.7 27.1 21.6 0.0 14.6 13.5 50.1 29.6 6.7 39.4 6.6 44.5 12.5 19.2 3.6 2.7 26.6 100.8 25.2 CH4 CH4 Flux Flux (μmol/s) (g/day) 0.124 0.004 0.009 0.018 0.001 0.028 0.022 0.000 0.014 0.013 0.049 0.029 0.006 0.039 0.006 0.044 0.012 0.018 0.004 0.003 0.027 0.100 0.024 0.090 0.003 0.007 0.013 0.001 0.020 0.016 0.000 0.010 0.009 0.035 0.021 0.005 0.028 0.005 0.032 0.009 0.013 0.003 0.002 0.019 0.073 0.017 STD 0.117 0.031 0.061 0.069 0.026 0.060 0.118 0.001 0.020 0.019 0.088 0.113 0.010 0.063 0.028 0.058 0.060 0.091 0.056 0.023 0.284 0.239 0.036 Lower 95% Upper 95% Spectrometer Confidence3 Confidence4 457.9 15.7 34.1 67.4 2.6 100.5 79.6 0.1 53.9 50.0 185.5 109.3 24.6 145.7 24.5 164.6 46.4 70.9 13.1 9.9 98.2 372.8 93.3 458.4 15.8 34.3 67.7 2.7 100.7 80.1 0.1 54.0 50.1 185.9 109.8 34.7 145.9 24.6 164.8 46.6 71.3 13.3 10.0 99.3 373.7 93.5 CRDS CRDS CRDS CRDS CRDS CRDS CRDS CRDS CRDS CRDS CRDS CRDS CRDS CRDS CRDS CRDS CRDS CRDS CRDS CRDS CRDS CRDS CRDS 92 Table 12: Continued Cover ID Date Start Time End Time CH4 Flux (µL/min) MH3 MH3 MH3 MH3 MH4 MH4 MH4 MH4 MH4 MH4 MH4 MH4 MH4 MH4 MH4 MH4 MH4 MH4 MH4 MH4 MH4 MH4 MH4 9/12/2013 9/19/2013 9/19/2013 9/19/2013 10/26/2013 10/26/2013 10/26/2013 10/26/2013 10/26/2013 10/26/2013 10/25/2013 10/25/2013 10/25/2013 10/16/2013 10/25/2013 10/16/2013 10/21/2013 9/30/2013 10/25/2013 9/30/2013 9/30/2013 10/25/2013 9/30/2013 4:49:03 PM 5:23:04 PM 5:35:53 PM 5:50:02 PM 12:02:00 AM 1:03:29 AM 2:02:54 AM 4:03:00 AM 5:04:50 AM 7:03:42 AM 9:09:22 AM 9:41:40 AM 10:10:17 AM 10:32:51 AM 10:44:45 AM 10:46:42 AM 10:59:35 AM 11:10:04 AM 11:20:10 AM 11:26:00 AM 11:41:42 AM 11:52:11 AM 11:55:55 AM 5:19:27 PM 5:33:31 PM 5:46:18 PM 6:00:49 PM 12:13:42 AM 1:14:24 AM 2:12:46 AM 4:13:01 AM 5:15:52 AM 7:14:29 AM 9:19:25 AM 9:52:52 AM 10:20:31 AM 10:42:15 AM 10:55:29 AM 10:56:50 AM 11:10:01 AM 11:19:57 AM 11:32:00 AM 11:35:10 AM 11:51:16 AM 12:02:28 PM 12:05:18 PM 11.8 3.7 3.4 9.0 11.1 17.2 8.0 5.2 34.8 171.1 20.2 31.0 124.0 10.4 9.4 17.6 6.7 32.5 48.9 36.8 20.2 112.0 42.9 CH4 CH4 Flux Flux (μmol/s) (g/day) 0.011 0.004 0.003 0.009 0.011 0.017 0.008 0.005 0.035 0.175 0.020 0.031 0.124 0.011 0.009 0.018 0.007 0.031 0.048 0.035 0.019 0.111 0.040 0.008 0.003 0.002 0.006 0.008 0.013 0.006 0.004 0.026 0.126 0.015 0.022 0.089 0.008 0.007 0.013 0.005 0.022 0.035 0.025 0.014 0.080 0.029 STD 0.052 0.015 0.012 0.061 0.012 0.039 0.021 0.011 0.168 0.251 0.064 0.462 0.438 0.019 0.137 0.061 0.041 0.258 0.387 0.232 0.295 0.756 0.405 Lower 95% Upper 95% Spectrometer Confidence3 Confidence4 43.7 13.8 12.6 33.3 41.0 63.6 29.5 19.4 128.5 633.1 74.8 114.0 458.3 38.6 34.4 65.0 24.7 119.8 180.6 135.9 74.3 413.2 158.0 43.9 13.9 12.6 33.6 41.1 63.8 29.6 19.5 129.1 634.0 75.0 115.8 460.0 38.6 35.0 65.2 24.8 120.8 182.1 136.8 75.5 416.2 159.6 CRDS CRDS CRDS CRDS CRDS CRDS CRDS CRDS CRDS CRDS CRDS CRDS CRDS CRDS CRDS CRDS CRDS CRDS CRDS CRDS CRDS CRDS CRDS 93 Table 12: Continued Cover ID MH4 MH4 MH4 MH4 MH4 MH4 MH4 MH4 MH4 MH4 MH4 MH4 MH4 MH4 MH4 MH4 MH4 MH4 MH4 MH4 MHSU1 MHSU1 MHSU1 Date Start Time End Time 9/30/2013 12:08:28 PM 12:18:28 PM 10/25/2013 12:32:37 PM 12:41:54 PM 10/25/2013 1:11:38 PM 1:23:27 PM 10/25/2013 1:48:43 PM 1:58:08 PM 10/25/2013 2:59:12 PM 3:08:45 PM 10/25/2013 3:26:21 PM 3:37:16 PM 10/25/2013 3:53:51 PM 4:03:17 PM 10/15/2013 4:01:20 PM 4:11:21 PM 10/15/2013 4:16:33 PM 4:25:21 PM 10/25/2013 4:20:22 PM 4:31:32 PM 10/25/2013 4:48:58 PM 5:00:55 PM 10/25/2013 5:16:16 PM 5:28:18 PM 10/25/2013 5:45:13 PM 5:56:09 PM 10/25/2013 6:17:52 PM 6:28:22 PM 10/25/2013 6:46:55 PM 6:57:53 PM 10/25/2013 7:46:24 PM 7:58:09 PM 10/25/2013 8:25:24 PM 8:36:12 PM 10/25/2013 8:56:50 PM 9:07:37 PM 10/25/2013 10:11:17 PM 10:21:34 PM 10/25/2013 11:02:51 PM 11:12:00 PM 10/14/2013 9:48:29 AM 9:56:52 AM 10/14/2013 10:01:01 AM 10:10:41 AM 10/14/2013 10:15:28 AM 10:25:32 AM CH4 Flux (µL/min) 83.8 95.8 46.7 18.0 258.1 90.2 87.3 99.7 127.6 114.8 95.4 78.8 95.1 60.4 101.8 46.5 42.7 37.3 6.7 306.2 715.5 56.3 66.1 CH4 CH4 Flux Flux (μmol/s) (g/day) 0.079 0.094 0.046 0.017 0.251 0.087 0.085 0.099 0.127 0.112 0.093 0.077 0.093 0.059 0.101 0.046 0.043 0.037 0.007 0.309 0.720 0.057 0.066 0.057 0.068 0.033 0.013 0.181 0.063 0.061 0.072 0.092 0.081 0.067 0.056 0.067 0.043 0.073 0.033 0.031 0.027 0.005 0.223 0.519 0.041 0.048 STD 0.795 1.092 0.705 0.628 2.150 1.000 0.422 0.754 0.422 0.694 0.554 0.456 0.341 0.887 0.177 0.076 0.054 0.163 0.014 5.551 13.536 0.284 1.552 Lower 95% Upper 95% Spectrometer Confidence3 Confidence4 308.7 352.8 171.7 65.3 951.2 332.1 322.5 367.9 471.9 423.8 352.2 291.1 351.5 222.2 376.6 172.2 158.0 137.9 25.0 1122.0 2597.6 207.9 241.6 311.8 357.0 174.5 67.8 959.7 336.0 324.2 370.9 473.6 426.6 354.3 292.8 352.9 225.7 377.3 172.5 158.2 138.5 25.0 1143.8 2650.6 209.0 247.7 CRDS CRDS CRDS CRDS CRDS CRDS CRDS CRDS CRDS CRDS CRDS CRDS CRDS CRDS CRDS CRDS CRDS CRDS CRDS CRDS CRDS CRDS CRDS 94 Table 12: Continued Cover ID Date Start Time End Time CH4 Flux (µL/min) MHSU1 MHSU1 MHSU1 MHSU1 MHSU1 MHSU1 MHSU1 MHSU1 MHSU1 MHSU1 MHSU1 MHSU1 MHSU1 MHSU1 MHSU1 MHSU1 MHSU1 MHSU1 MHSU1 MHSU1 MHSU1 MHSU3 MHSU3 10/7/2013 10/9/2013 9/23/2013 10/7/2013 10/9/2013 9/23/2013 10/7/2013 10/9/2013 9/23/2013 10/7/2013 10/21/2013 10/15/2013 10/21/2013 10/15/2013 10/21/2013 9/20/2013 9/20/2013 9/20/2013 10/22/2013 10/22/2013 10/22/2013 10/15/2013 10/28/2013 10:23:26 AM 10:24:27 AM 10:28:08 AM 10:38:56 AM 10:39:53 AM 10:44:07 AM 10:54:58 AM 10:59:34 AM 11:02:20 AM 11:10:54 AM 11:31:19 AM 11:48:23 AM 11:48:10 AM 12:01:06 PM 12:08:18 PM 12:35:53 PM 12:49:08 PM 1:06:13 PM 3:01:24 PM 3:15:11 PM 3:28:25 PM 10:43:23 AM 10:56:00 AM 10:34:00 AM 10:35:06 AM 10:38:21 AM 10:49:00 AM 10:50:41 AM 10:53:13 AM 11:05:45 AM 11:10:52 AM 11:12:53 AM 11:20:16 AM 11:42:00 AM 11:57:16 AM 12:00:49 PM 12:10:00 PM 12:18:18 PM 12:45:00 PM 12:58:52 PM 1:16:00 PM 3:11:47 PM 3:25:57 PM 3:37:39 PM 10:53:15 AM 11:06:11 AM 266.5 424.3 118.4 134.6 536.1 200.6 155.1 201.2 100.2 84.1 142.5 2.3 83.9 2.7 79.8 321.1 642.1 469.7 215.0 281.2 216.3 1145.4 54.0 CH4 CH4 Flux Flux (μmol/s) (g/day) 0.261 0.415 0.115 0.131 0.522 0.195 0.151 0.196 0.097 0.082 0.142 0.002 0.083 0.003 0.079 0.305 0.611 0.445 0.209 0.273 0.210 1.152 0.051 0.188 0.299 0.083 0.095 0.376 0.141 0.109 0.141 0.070 0.059 0.102 0.002 0.060 0.002 0.057 0.220 0.441 0.321 0.151 0.197 0.152 0.832 0.037 STD 1.211 1.672 0.371 0.678 1.925 0.706 0.342 0.339 0.438 0.237 0.564 0.037 0.209 0.012 0.256 1.646 2.774 2.112 1.043 0.656 1.608 5.578 0.765 Lower 95% Upper 95% Spectrometer Confidence3 Confidence4 981.6 1560.0 437.2 496.6 1968.3 740.0 573.0 742.7 370.1 311.0 525.9 8.5 310.3 10.0 294.8 1181.3 2353.3 1725.4 792.4 1036.7 795.9 4206.4 198.6 986.3 1566.5 438.7 499.3 1975.8 742.8 574.4 744.1 371.8 311.9 528.2 8.6 311.1 10.0 295.8 1187.8 2364.2 1733.7 796.5 1039.3 802.2 4228.2 201.6 CRDS CRDS CRDS CRDS CRDS CRDS CRDS CRDS CRDS CRDS CRDS CRDS CRDS CRDS CRDS CRDS CRDS CRDS CRDS CRDS CRDS CRDS CRDS 95 Table 12: Continued Cover ID Date Start Time End Time CH4 Flux (µL/min) CH4 CH4 Flux Flux (μmol/s) (g/day) MHSU3 MHSU3 MHSU3 MHSU3 MHSU3 MHSU3 MHSU3 MHSU3 MHSU3 MHSU3 MHSU3 MHSU3 MHSU3 MHSU3 MHSU3 MHSU3 MHSU3 MHSU3 MHSU3 MHSU3 MHSU3 MHSU3 MHSU3 10/15/2013 10/28/2013 9/23/2013 10/7/2013 9/23/2013 10/28/2013 10/7/2013 9/23/2013 10/7/2013 10/28/2013 10/28/2013 10/21/2013 9/20/2013 10/28/2013 10/21/2013 9/20/2013 10/21/2013 9/20/2013 10/24/2013 10/24/2013 10/24/2013 10/16/2013 10/24/2013 10:57:17 AM 11:28:10 AM 11:41:43 AM 11:49:14 AM 11:58:59 AM 12:00:00 PM 12:05:29 PM 12:14:01 PM 12:19:19 PM 12:33:42 PM 1:06:38 PM 1:24:27 PM 1:31:27 PM 1:38:57 PM 1:40:46 PM 1:44:30 PM 1:56:17 PM 1:58:40 AM 3:30:09 PM 3:44:03 PM 4:03:26 PM 4:04:29 PM 4:16:00 PM 11:07:22 AM 11:38:57 AM 11:49:20 AM 11:59:57 AM 12:08:47 PM 12:12:04 PM 12:15:16 PM 12:24:14 PM 12:25:54 PM 12:43:49 PM 1:16:44 PM 1:35:05 PM 1:41:18 PM 1:49:43 PM 1:51:05 PM 1:54:45 PM 2:07:07 PM 2:08:42 PM 3:40:31 PM 3:54:34 PM 4:13:49 PM 4:15:08 PM 4:27:55 PM 4.7 6.3 38.7 37.7 37.2 60.1 25.9 32.4 31.4 24.5 8.2 35716.5 11.3 7.5 8.3 12.9 15.6 17.7 4.8 4.7 150.6 1933.1 130.7 0.005 0.006 0.037 0.036 0.036 0.057 0.025 0.031 0.030 0.023 0.008 35.020 0.011 0.007 0.008 0.012 0.015 0.017 0.005 0.005 0.146 1.911 0.127 0.003 0.004 0.027 0.026 0.026 0.041 0.018 0.023 0.022 0.017 0.006 25.269 0.008 0.005 0.006 0.009 0.011 0.012 0.003 0.003 0.106 1.379 0.092 STD 0.015 0.022 0.139 0.160 0.119 1.193 0.102 0.113 0.162 0.351 0.067 780.350 0.040 0.088 0.020 0.065 0.084 0.158 0.014 0.020 0.439 36.726 0.529 Lower 95% Upper 95% Spectrometer Confidence3 Confidence4 17.5 23.2 143.2 139.5 137.4 220.5 95.7 119.9 116.1 89.9 30.4 111520.0 41.9 27.6 30.7 47.6 57.5 65.3 17.9 17.5 556.8 7015.6 482.9 17.5 23.3 143.7 140.2 137.9 225.2 96.1 120.3 116.7 91.3 30.6 114580.0 42.0 27.9 30.8 47.8 57.8 65.9 17.9 17.6 558.5 7159.6 485.0 CRDS CRDS CRDS CRDS CRDS CRDS CRDS CRDS CRDS CRDS CRDS CRDS CRDS CRDS CRDS CRDS CRDS CRDS CRDS CRDS CRDS CRDS CRDS 96 Table 12: Continued Cover ID Date Start Time End Time CH4 Flux (µL/min) MHSU3 MHSU4 MHSU4 MHSU5 MHSU5 MHSU5 MHSU5 MHSU5 MHSU6 MHSU6 MHSU6 MHSU6 MHSU6 MHSU5 MH0 MH0 MH1 MH1 10/16/2013 9/23/2013 9/23/2013 10/14/2013 10/14/2013 10/14/2013 10/16/2013 10/16/2013 10/16/2013 10/16/2013 10/14/2013 10/14/2013 10/14/2013 1/25/2014 1/25/2014 1/25/2014 1/25/2014 1/25/2014 4:20:34 PM 12:33:11 PM 12:48:40 PM 2:17:01 PM 2:30:55 PM 2:45:52 PM 2:47:15 PM 3:03:49 PM 2:16:58 PM 2:32:19 PM 3:05:59 PM 3:24:42 PM 3:43:00 PM 10:07:00 AM 10:59:07 AM 11:13:23 AM 11:27:27 AM 11:48:00 AM 4:31:00 PM 12:43:00 PM 12:58:00 PM 2:27:28 PM 2:41:18 PM 2:56:23 PM 2:56:51 PM 3:15:01 PM 2:26:59 PM 2:42:50 PM 3:16:39 PM 3:35:51 PM 3:54:20 PM 10:17:32 AM 11:09:37 AM 11:23:29 AM 11:37:57 AM 11:58:36 AM 3.4 1.0 32.6 16.2 36.7 3.9 1993.3 0.9 0.9 25.5 1.8 3.2 125.3 6.8 10016.7 5047.4 134.1 170.0 CH4 CH4 Flux Flux (μmol/s) (g/day) 0.003 0.001 0.031 0.016 0.036 0.004 1.971 0.001 0.001 0.025 0.002 0.003 0.125 0.006 8.582 4.318 0.115 0.145 0.002 0.001 0.023 0.012 0.026 0.003 1.422 0.001 0.001 0.018 0.001 0.002 0.090 0.004 6.193 3.116 0.083 0.105 STD 0.017 0.028 0.466 0.103 0.351 0.163 71.873 0.013 0.008 0.568 0.043 0.029 5.265 0.450 91.230 77.870 1.960 3.500 Lower 95% Upper 95% Spectrometer Confidence3 Confidence4 12.6 3.8 119.9 59.8 135.4 14.2 7154.8 3.4 3.2 93.5 6.8 11.8 453.9 24.4 36900.0 18500.0 493.0 623.0 12.6 3.9 121.8 60.2 136.7 14.3 7436.6 3.4 3.3 95.7 6.9 12.0 474.5 26.1 37300.0 18800.0 501.0 637.0 CRDS CRDS CRDS CRDS CRDS CRDS CRDS CRDS CRDS CRDS CRDS CRDS CRDS CRDS CRDS CRDS CRDS CRDS 97 REFERENCES 1. Intergovernmental Panel on Climate Change. Climate Change 2007 Synthesis Report; Intergovernmental Panel on Climate Change, 2008. 2. Environmental Protection Agency. Atmospheric Concentrations of Greenhouse Gases; 2013. 3. Salt Lake City Energy and Carbon Advisory Committee and Salt Lake City Division of Sustainability and Environment. Salt Lake City Community Carbon Footprint; United States Department of Energy, 2010. 4. Quigley, C. J.; Corsi, R. L. Emissions of VOC's from a Municipal Sewer. Air and Waste Management Association 1995, 45 (5), 395-403. 5. Olson, D. A.; Varma, S.; Corsi, R. L. A New Approach for Estimating Volatile Organic Compound Emissions from Sewers: Methodology and Associated Errors. Water Environmental Research 1998, 70 (3), 276-282. 6. Foley, J.; Yuan, Z.; Lant, P. Dissolved Methane in Rising Main Sewer Systems: Field Measurements and Simple Model Developement for Estimation Greenhouse Gas Emissions. Water Science and Technology 2009, 60 (11), 2963-2971. 7. Willis, J.; Barnes, R.; Fillmore, L.; Shah, A. Quantifying Methane Evolution from Sewers: Phase 1 Results of the WERF/DeKalb County, Georgia, Case Study. Proceedings of the Water Environment Federation, 2010; pp 5411-5419. 8. Guisasola, A.; de Haas, D.; Keller, J.; Yuan, Z. Methan Formation in Sewer Systems. Water Systems 2008, 42 (6-7), 1421-1430. 9. Madsen, H. I.; Hvitved-Jacobsen, T.; Vollertsen, J. Gas Phase Transport in Gravity Sewers: A Methodology for Determination of Horizontal Gas Transport and Ventilation. Water Environmental Research 2006, 78 (11), 2203-2209. 10. Parker, W. J.; Ryan, H. A Tracer Study of Headspace Ventilation in a Collector Sewer. Air and Waste Management Association 2001, 51 (4), 582-592. 11. Picarro Inc. Picarro G2311-f 10Hz CO2, CH4, and H2O Analyzer for Eddy Covariance Flux; Picarro Inc: Santa Clara, CA, USA, 2012. 99 12. LI-COR. LI-8100A Automated Soil CO2 Flux System and LI-8150 Multiplexer Instruction Manual; LI-COR: Lincoln, NE, USA, 2010. 13. Pihlatie , M. K.; Christiansen , J. R.; Aaltonen , H.; Korhonen, J. F. J.; Nordbo, A.; Rasilo, T.; Benanti, G.; Giebels, M.; Helmy, M.; Sheehy, J.; Jones, S.; Juszczak, R.; Klefoth, R.; Lobo-doVale , R.; Schreiber, P.; Serça, D.; Vicca, S.; Wolf, B.; Pumpanen, J. Comparison of Static Chambers to Measure CH4 Emissions from Soils. Agricultural and Forest Meterology 2012, 171-172, 124-136. 14. Parkin, T. B.; Venterea, R. T. Chapter 3. Chamber Based Trace Gas Flux Measurements; Aricultural Research Service, 2010. 15. Xu, L.; Furtaw, M. D.; Madsen, R. A.; Garcia, R. L.; Anderson, D. J.; McDermitt, D. K. On Maintaining Pressure Equillibrium Between a Soil CO2 Flux Chamber and the Ambient Air. Journal of Geophysical Research: Atmospheres 2006, 111 (2156-2202). 16. Ostrem, K. Greening Waste: Anaerobic Digestion for Treating the Organic Fraction of Municipal Solid Wastes; Thesis; Earth Engineering Center Columia University, 2004. 17. The Office of Sustainability; The President's Sustainability Advisory Board; The CAP Planning Team. Energy and Environmental Stewardship Initiative: 2010 Climate Action Plan; University of Utah: Salt Lake City, 2010.