Chemists at the US Fish and Wildlife Service (USFWS) have been developing a method to identify trafficked wood on the spot using chemical fingerprinting.
According to Chemical and Engineering News, the estimated annual value of illegal wood trade as of 2017 was $50 billion to $150 billion, and the USFWS has been instrumental in developing a technique for wood identification and sharing it with law enforcement labs around the world. The technique is called direct analysis in real time mass spectrometry, or DART-MS for short. Today, the suite of molecules it measures can be used to rapidly identify the species, and sometimes even the region, a piece of wood came from.
Mass spectrometry gets information about the molecules in a sample by ionizing them and then measuring their mass-to-charge ratio when they hit a detector. While typical mass spectrometers do this within a vacuum, DART-MS ionizes samples in the open air in a process known as ambient ionization. A blue barrel capped at one end with a steel nozzle heats helium to about 400 °C and blows it across the sample held in an open-air gap and into the mass spectrometer. The helium stream ionizes molecules blown off the sample and directs them into the mass spectrometer for analysis.
Wood is more complex than most materials, and that makes it even harder to analyze than typical mixtures of drugs and adulterants. To simplify DART-MS data analysis, chemist Edward Sisco of the National Institute of Standards and Technology (NIST), and NIST colleague Arun Moorthy recently created a software program to make it easier to analyze wood.
According to the report, while DART-MS-based analysis is one technique used internationally for tree identification, other techniques are available. Several US ports of entry have installed sophisticated imaging systems that capture magnified multispectral photos that wood anatomists can later investigate. Other labs conduct genetic analysis.
To read the entire study on DART-MS and other methods to identify illegally trafficked wood, click here.
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