
The Earth Systems Observation Group at Los Alamos National Laboratory (LANL) leveraged LI-COR’s drone-mountable TriSonica® Mini Wind and Weather Sensor to study aerosol effects on cloud chemistry and formation dynamics in Houston, Texas.
The Earth Systems Observation Group conducts field campaigns focused on identifying methane leaks from oil and gas infrastructure. These campaigns also address methane emissions from dairy farms and other natural sources using sensor arrays equipped with trace gas analyzers, sonic anemometers, and additional meteorological instruments.
Data gathered by these instruments allows the team to apply physics-based models to enhance field sampling techniques, and vice versa. This dual approach aids in understanding the behavior and interactions of emissions in the atmosphere and their potential environmental impacts.
To achieve this, the team utilized a sensor array housed in a shipping container, along with a TriSonica Mini Wind and Weather Sensor mounted on the container. These tools measured gases in the air, wind direction, wind speed, air temperature, pressure, and relative humidity.
The resulting data, which included real-time aerosol and trace gas measurements, was integrated with information from the TriSonica Wind and Weather Sensor to trace the origins of the gases. In addition to stationary measurements from the container, the team equipped a vehicle with sensors and drove through Houston to detect aerosol and greenhouse gas emissions from refineries and other sources.
Aaron G. Meyer, a trace gas specialist with the Earth Systems Observation Group, pointed out, “In characterizing methane and other hydrocarbon emissions from oil and gas infrastructure, trace gas analyzers can give us continuous volumetric concentrations in the air of methane and ethane and other hydrocarbon species.
“However, to go from a concentration that you may be measuring in a plume downwind of a source to an actual quantifiable emission flux, the wind data is as important as the trace gas concentration data because of the atmospheric dynamics that are at play.”
The researchers observed that characterizing emission sources downwind can vary significantly based on wind conditions. A day with optimal wind conditions for downwind measurements will yield different concentration results compared to days with varying wind speeds. For accurate calculations of target gas concentrations—whether through basic atmospheric dispersion equations or advanced modeling and turbulence profiling—wind speed and direction are indispensable factors.
The team emphasizes that wind data encompasses more than just wind direction and speed; it includes temperature and pressure as well. Meteorological characteristics are integral to obtaining accurate results. Meyer clarified, “In the absence of wind data, any kind of quantification of wind and atmospheric flux with just a trace gas analyzer would be basically impossible. So, when we’re doing research on something like how much methane is coming out of a coal vent shaft in the San Juan Basin, having accurate wind measurements from multiple points is critical.
“Any situation where one of your goals is to characterize the location of where a source is coming from is inherently tied to wind direction because of atmospheric transport, since the dispersion of gas or aerosol sources are directly tied to the characteristics of the wind. While a smoke plume from a wildfire behaves differently from a methane plume from a wellhead, the underlying dynamics are the same and require accurate measurement of the wind.
“Our field campaigns always come back to wind characterization. It is such an important factor in finding where potential sources are coming from and being able to quantify their size. All of that is contingent upon having accurate wind data.”