Forest Fires Can Cause Global Warming More Than Before

Forest Fires Can Cause Global Warming More Than BeforebismillahiRR: Forest fires produce wizard drinks containing carbon particles, as people fighting the wind direction from forest fires can prove. Various fine carbon particles rise high into the air significantly decreases air quality, damages human health and wildlife, and interacts with sunlight to influence climate. But measurements made during the 2011 Las Conchas fire near Los Alamos National Laboratory show that carbon-containing particles actually emitted by fires are very different from those used in current computer models, providing potential for imprecision in current climate modeling results.

"We've found that substances that resemble tar balls dominate, and even soot coated by organic sunlight-focused," said senior laboratory scientist Manvendra Dubey, "The two components could potentially improve climate warming with increased light absorption."

The Las Conchas fire emission findings underscore the need to provide a framework for incorporating a realistic representation of carbon aerosols in climate models, the researchers say. They suggested that emissions from fires could contribute more to the observed climate warming than current estimates indicate.

"The fact that we are experiencing more fires and that climate change can increase the frequency of fires underscores the need to include special particles in computer models, and our results show how this can be done," Dubey said.

Aerosol samples reveal "tar balls" in the sky

Conventional wisdom is that fire-driven particles contain carbon black or soot that absorbs sunlight to warm the climate, and organic carbon or smoke that reflects sunlight to cool the climate. But in a paper just published in Nature Communications scientists from Los Alamos and Michigan Technological University analyzed the morphology and a certain aerosol composition emitted by Las Conchas fire.

Las Conchas, which began June 26, 2011, was the largest fire in NM history at the time, burning 245 square miles. As soon as Los Alamos National Laboratory was reopened for scientists and staff, the team established an extensive aerosol sampling system to monitor smoke from a smoldering fire for more than 10 days.

High-tech tools allow smoke sample analysis

Dubey, along with fellow postdoctoral Allison Aiken and post-graduate student Kyle Gorkowski, coordinated with Michigan Tech professor Claudio Mazzoleni (a fellow former Los Alamos Director) and a Chinese Swarup graduate student to undertake the study.

The team used emission field scanning electron microscopy and dispersive energy X-ray spectroscopy to analyze aerosol samples and determined that a spherical carbon ball particle called a tar ball 10 times more than carbon black.

Furthermore, bare soot particles, the composite porous fractal structures are made of tiny spherical carbon, which is significantly modified by the organic emitted by the flame. About 96 percent of soot from fire is covered by other organic substances, with 50 percent being completely coated. In addition, the complexity of soot can be categorized into 4 morphological structures as "embedded," "partially coated," "by inclusion" and "naked."What's missing from modeling and why is it important

Why is this important for the climate? Dubey notes that, "Most climate assessment models treat fire emissions as a mixture of pure carbon black and organic aerosols that compensate for their respective warming and cooling effects from each other on climates.However, Las Conchas The results show that the tar ball exceeds carbon black by a factor of 10 and soot will be coated by organic fire emissions, each producing more of a warming effect than currently assumed. "

"The Tar ball can absorb sunlight at short blue and ultraviolet wavelengths (also called brown carbon due to color) and can cause considerable warming," he said. "In addition, the organic layer on soot action such as a lens that focuses sunlight, strengthens the absorption and heating by soot by a factor of 2 or more.This has a big impact on how they should be treated in computer models."

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