Grantee Research Project Results
2024 Progress Report: Analysis of Continuous Monitoring Data with Inverse Atmospheric Models to Improve Landfill Gas Emissions Data and Elucidate Drivers of Emissions
EPA Grant Number: R840624Title: Analysis of Continuous Monitoring Data with Inverse Atmospheric Models to Improve Landfill Gas Emissions Data and Elucidate Drivers of Emissions
Investigators: Schauer, James J. , deFoy, Benjamin , Tinjum, James M , Aydin, Orhun , Edwards, Ross
Institution: University of Wisconsin - Madison , Saint Louis University - Main Campus
EPA Project Officer: Davey, Elisa
Project Period: September 1, 2023 through May 8, 2025
Project Period Covered by this Report: September 1, 2023 through August 31,2024
Project Amount: $998,049
RFA: Understanding and Control of Municipal Solid Waste Landfill Air Emissions Request for Applications (RFA) (2023) RFA Text | Recipients Lists
Research Category: Landfill Emissions , Air Toxics , Watersheds , Endocrine Disruptors , Environmental Engineering , Air Quality and Air Toxics , Waste Reduction and Pollution Prevention , Air , Land and Waste Management
Objective:
The overall goal of the project is to demonstrate and standardize existing inverse modeling and spatial mapping methods for quantifying emissions of methane and other health impacting gases released from landfills. The project will demonstrate these methods at four landfills in the USA by quantifying the impact landfill design and operation have on gaseous emissions. The project will demonstrate the practicality of routinely using these low-cost methods to provide continuous emissions measurements from landfills.
Progress Summary:
The selection of monitoring station locations was completed in Year 1, with four landfills located in four different states across the U.S. that have unique geographic characteristics. The partner landfills include a mix of private and public ownership, with two being privately operated and two publicly owned and operated. These landfills process annual tonnages ranging from approximately 200,000 tons to 800,000 tons of solid waste. The landfills generate renewable energy from landfill gas, three produce high-BTU pipeline-grade natural gas, while one primarily uses the gas to generate electricity. Each landfill has a collaborative relationship with the project team and employs state-of-the-art techniques for landfill gas management, control, and beneficial recovery, with a focus on sustainability and advancing the science of landfill gas design. After fabrication, prototyping, and testing, monitors were installed at two of the landfills in Year 1 of the project, and the remaining monitors are planned to be installed in the early part of Year 2 of the Project.
During Year 1 of the project, the stationary monitors for CH4, H2S, odor, NH3 and CO2 were fabricated and field tested. The monitors consist of an OEM tunable laser diode (TLDAS) CH4 spectrometer housed in a portable waterproof case and an external passive sensor system for H2S, odor, NH3 and CO2. The spectrometer requires that the gas cell and incoming air are at the same temperature. We developed a temperature-controlled enclosure for the spectrometer, which incorporates an inline air heating system and flexible heater around the gas cell. In addition to heating the incoming air and the spectrometer gas cell, a temperature-controlled fan is used to regulate the air temperature within the spectrometer enclosure. We fabricated inline thermocouples to control the air heating system and to record the temperature of air exiting the gas cell. Air is pulled through the cell using a long-life vibrating armature pump (can run continuously for ~ 5 years) an inline pressure sensor was located after the TLDAS gas cell and prior to the gas pump to test for leaks and to monitor the air filtration system, which was located on the inlet line outside the waterproof case. A robust external sensor module was developed for H2S, odor, NH3 and CO2 and connected to the waterproof case using a RJ45 cable. The H2S, odor, and NH3 measurements are based on solid-polymer catalytic electrochemical sensors. The solid-polymer sensors have sub-ppm detection limits, minimal drift, a wide temperature, and humidity range (-40 to 55 C), fast response times (~ 3 s T90 < 30 s), anti-poisoning and lifetimes > 5 years. The solid polymer sensors include dual NH3 / odor sensor (https://ecsense.com, 04-DGM10-SMELL-NH3-5-10-01) with a range of NH3 of 0 - 10 ppm, and a resolution of 10 ppb. The odor sensor has a range of 0 - 5 ppm and a resolution of 10 ppb with a good response to VOCs, H2S / sulfides, hydrocarbons, and ketones. To deploy the monitors in the field, we have used pole-mounted, heated/vented NEMA enclosures.
The Generalized Additive Model (GAM) has been developed in previous projects for the simulation of PM2.5. In the first year of this project, we have adapted the modeling approach for the methane measurements taken near landfill sites. Meteorological data was obtained from the closest airport as well as from the ERA5 reanalysis model. We developed R programs to generate diagnostic plots using preliminary data and to test that the process was working smoothly. Preliminary data from Year 1 of the project was used as preliminary data to test the GAM simulations and to develop appropriate ways of interpreting and displaying the results and the results using the relatively small data set demonstrated the power of the overall project strategy.
The UAV team led by Co-PI Aydin successfully integrated the procured methane sensor, Aeris Strato MIRO, onto the NDDA-compliant hexacopter UAV. The hexacopter and sensor system is tested for its endurance on various UAV flights and the team has been operating the system for 45-min non-stop mapping missions. The team has developed a safety checklist that expands the regular FAA operating procedures to include landfill operating safety. In addition, the team has developed battery hot-swap procedures to swap batteries for the drone and the sensor to continue data collection for up to 90 min. The UAV system has been tested on landfill methane missions where both automated grid patterns over large areas of the landfill and facility-scanning flights for mapping methane emissions over methane treatment facility are conducted.
Future Activities:
In Year 2 of the project, the project team will complete the deployment of the landfill gas monitors and closely monitor the monitoring data to assure high-quality long-term data. In addition, the project team will work with a subset of the landfills to collect landfill operations data that will be used with the monitoring data in the GAM model to better elucidate the meteorological parameters and landfill operational parameters that are drivers of emissions. Once sufficient results are generated, a transport model will be used to quantify emissions using an inverse modeling approach.
In Year 2 of the project, we will continue testing the model and developing it to handle the specific questions raised by methane transport. We expect the model to distinguish between predictable signals and sporadic events. Analyzing the statistics of infrequent peaks in concentrations is of particular interest for this project, for example by identifying meteorological conditions and temporal factors (time of day, day of the week) associated with unusually high concentrations.
Supplemental Keywords:
HAPS, greenhouse gases, waste, fugitive emissionsProgress and Final Reports:
Original AbstractThe perspectives, information and conclusions conveyed in research project abstracts, progress reports, final reports, journal abstracts and journal publications convey the viewpoints of the principal investigator and may not represent the views and policies of ORD and EPA. Conclusions drawn by the principal investigators have not been reviewed by the Agency.