Accurately identifying and quantifying particulate matter (PM) in the atmosphere is key to determining air quality. Researchers are particularly interested in PM that have a diameter of less than 2.5 micrometers because they are believed to contribute to heart and lung disease in humans and animals. These tiny particles are invisible to the naked eye and originate from power plants, fires, and volcanic eruptions. High levels of PM that have a diameter of less than 10 micrometers, such as dust, mold and pollen, are also dangerous and can lead to asthma and other health problems if inhaled.
Measuring particles in the atmosphere that we can’t see is a challenge; however, by using an integrated approach, researchers are gaining access to more accurate, detailed information. Rather than relying on just one type of sensor, data are collected from multiple complementary instruments and combined to obtain a comprehensive understanding of the composition and movement of the atmosphere.
For example, an in-depth study in north Beijing deployed multiple instruments, including horizontal scanning LiDAR sensors, vertical profiling LiDAR sensors — Mini Micro Pulse LiDAR (MiniMPL), weather cameras, weather stations, radiometers and other in situ instruments, to observe how haze is transported across the city and how it mixes with the local atmosphere repeatedly throughout the day.
The timing of successive waves of haze and alternating mixing events was closely tracked while radiometers recorded vertical temperature and relative humidity profiles, both direct driving factors of aerosol transportation. Simultaneously MiniMPL units measured and identified types of particulate and noted the vertical distribution of layers in the atmosphere. Densely deployed ground-based PM2.5 instruments, along with weather cameras and weather stations, provided horizontal coverage.
The results of this study clearly show a wave phenomenon occurring within the city limits that is caused by haze transport from other locations. The combined data detected several waves of haze as thick as a dust storm and successfully differentiated between dry/cool waves and wet/warm waves. It was found wet/warm waves impact air quality more than dry/cool waves. The wet/warm waves were observed staying in the local atmosphere longer, greatly reducing visibility and forming a heavy pollution layer about 400m thick for several days!
Micro Pulse LiDAR technology plays a key role in such data synergy because its vertical aerosol profiling capability uses highly efficient and sensitive photon-counting detectors that produce information not provided by traditional sensors, such as dual polarization backscatter measurements. Also, as compared to other aerosol LiDARs, Micro Pulse LiDAR instruments offer stability against environmental factors, and strict and reliable calibration based on over ten years of development. These advantages are particularly valuable when moving from qualitative observations to quantitative measurements. It also ensures reliable data synergy between different types of sensors.
By integrating vertical and horizontal aerosol LiDAR data with temperature, relative humidity, wind speed and direction, etc., correlations can be developed that explain why a certain type of atmospheric distribution exists and predict how it is going to develop, based on a set of conditions. This comprehensive data set forms a complete 3D model of the atmosphere to support further research.