Project Title

LiDAR for Air Quality Measurement

Collaborating Universities

Old Dominion University
1 Old Dominion University
Norfolk, VA 23529

Virginia Tech
1424 S Main St.
Blacksburg, VA 24061

Principal Investigator(s)

Khan Iftekharuddin (ODU) Email:
Mecit Cetin (ODU) Email:
Hesham Rakha (VT) Email:

Funding Source(s) and Amounts Provided (by each agency or organization)

US DOT $150,000 (Federal)
ODU $100,000 (Match)
VT $ 50,000 (Match)

Total Project Costs

$150,000 Federal/ $150,000 Match

Agency ID or Contract Number


Start Date


Completion Date



We propose to investigate a unique light detection and ranging (LiDAR) technology for ambient air quality measurement of particulate matter (PM).

The ODU team has recently received a state-of-the-art elastic LiDAR from NASA Langley Research Center that has been developed to measure aerosol vertical profiles.  The system offers a measurement for every 30 meters vertically from ground level to the altitude of the aircraft to create a profile, or distribution, of aerosols.  This special LiDAR system can also be operated from ground to obtain either horizontal or vertical measurements in the atmosphere over a wide area with a range of 12 km.  With appropriate modifications, this LiDAR system can measure depolarization ratio, which enables measurement of PM in the atmosphere at very high spatial resolution.  This unique advantage of obtaining continuous measurements of PM in the atmosphere and at a long range simultaneously is not available today with the alternative PM measurement technologies.

By adopting this NASA LiDAR system, large datasets of PM measurements will be collected very cost-effectively for an urban area or a given corridor (e.g hot-spot chokepoints such as port, tunnel entrance etc. in the Hampton Roads area), which will then allow investigation of both temporal and spatial relationships between air quality and traffic flow patterns.  For example, the LiDAR system will be set up at an appropriate elevation (e.g. rooftop) and data will be collected over an area with high truck traffic or congestion to analyze the variation in PM distribution over time and space, and in relation to the variation in traffic levels.

Simultaneously, we will operate the LiDAR system at the selected hot-spots (e.g. port with high volume of diesel truck traffic) and acquire large number of localized measurements that will be processed to extract the distributions of the PM in those hot spots.  We will perform similarity analysis between the different measurements acquired during different day and different weather conditions.  We will develop sophisticated feature extraction and learning algorithms to analyze and classify collected global and localized LIDAR measurement data to extract the percentage of the PM particles that are related to diesel engines exhaust and to derive their distributions during various environmental and traffic conditions.  When combined with land use and traffic flow activity over the geographic are covered, significant results about sustainable land usage practice can also be obtained.  Finally, we plan to obtain the variation in pollution levels in relation to traffic patterns at different locations in Hampton Roads area.



The LiDAR system will be deployed in the field at locations in Hampton Roads to collect air quality data.  The LIDAR system allows measurement of air quality over large areas and can potentially reduce the data collection costs.  The collected air quality data will be correlated with traffic flows and congestion on the roadways to estimate emissions that can be attributed to traffic.  Once the accuracy of the LiDAR system is validated, the team plan to contact various state and federal agencies (e.g. FHWA, EPA, FAA) to demonstrate the potential application of the LiDAR system in improving air quality data collection.  Since the proposed LiDAR system will be invaluable to validate the results from plume dispersion models, which are utilized by EPA and other agencies to assess the impacts of tailpipe emissions on air quality.

Furthermore, novel LiDAR system enhancement and data analysis techniques discussion in our proposal are expected to yield new hardware-software algorithms and methods that will have potential intellectual property possibilities.


The expected benefits of this project include the ability to:

  1. Perform hot-spot analysis of selected choke points in Hampton Roads are for both long range global and local measurements of smoke and soot emitted from the vehicle emissions that are related to particulate material (PM) using a sophisticated LiDAR system,
  2. Investigate correlation between measured PM concentration over a large area and traffic flow patterns, and
  3. Incorporate measured air quality data from LiDAR into GIS and accurately identify the locations of high pollution areas adversely affected due to operation of diesel engines (e.g. ports and other chokepoints).

These capabilities will then enable the research team at MATS UTC to reach out to DOTs, FHWA, FAA and EPA for further testing and evaluation, since the government agencies routinely strive to obtain accurate assessments of the impacts of various infrastructure projects on the air quality and, consequently, on public health.

Web Links to Reports and to the Project website