Low-power, open-path mobile sensing platform for high-resolution measurements of greenhouse gases and air pollutants
A low-power mobile sensing platform has been developed with multiple open-path gas sensors to measure the ambient concentrations of greenhouse gases and air pollutants with high temporal and spatial resolutions over extensive spatial domains. The sensing system consists of four trace gas sensors including two custom quantum cascade laser-based open-path sensors and two LICOR open-path sensors to measure CO2, CO, CH4, N2O, NH3, and H2O mixing ratios simultaneously at 10 Hz. In addition, sensors for meteorological and geolocation data are incorporated into the system. The system is powered by car batteries with a low total power consumption (~200 W) and is easily transportable due to its low total mass (35 kg). Multiple measures have been taken to ensure robust performance of the custom, open-path sensors located on top of the vehicle where the optics are exposed to the harsh on-road environment. The mobile sensing system has been integrated and installed on top of common passenger vehicles and participated in extensive field campaigns (>400 h on-road time with >18,000 km total distance) in both the USA and China. The simultaneous detection of multiple trace gas species makes the mobile sensing platform a unique and powerful tool to identify and quantify different emission sources through mobile mapping.
In recent years, vehicle-based mobile sensing laboratories have been developed and used extensively for the environmental studies [1, 2, 3, 4, 5, 6, 7, 8, 9]. The ground-based, mobile sensing platforms measure pollutants and greenhouse gases on local to regional scales at high spatiotemporal resolution [2, 3, 4, 5, 6, 7, 8, 9]. A mobile laboratory is advantageous in that it addresses the spatial undersampling problems common to traditional stationary monitoring stations. Mobile measurements provide comprehensive source attribution of greenhouse gases and air pollutants and information on their distribution, particularly for short-lived trace gas species that show high spatial variability.
Laser-based, trace gas detection is used in many mobile laboratories due to its high sensitivity, selectivity, and fast time response . Tunable diode laser absorption spectroscopy (TDLAS) is a general technique for the analytical instruments used in the environmental studies to monitor atmospheric trace gas species. In order to achieve high sensitivity and selectivity, TDLAS measurements are generally performed with long optical pathlengths in enclosed optical cells that are regulated at low pressures (~1–50 hPa). The selected optical absorption lines are narrow with little or no interferences from neighboring absorption lines of other trace gas species . A closed-path approach, however, poses sampling problems for the species such as water vapor (H2O) and ammonia (NH3) that readily adsorb and desorb from the instrument surfaces (e.g., inlets, tubing, and optical cells). To improve the response time, a high flow rate is needed to equilibrate the surfaces faster, but this requires large, heavy, and power hungry pumps. Even with a high pumping speed and sophisticated inlet design, sensor response is still a substantial challenge for the sticky gases like NH3. Furthermore, even gases without sampling issues such as N2O require large pumps to achieve fast time response (10 Hz). To meet the high power consumption of the onboard sensors and their support systems (e.g., pumps, instrument racks and air conditioning), existing mobile sensing platforms [3, 5, 6, 7, 8, 9] are typically deployed on heavily modified vans or trucks and are powered by portable generators or large battery units.
Open-path TDLAS techniques do not require a pressure-regulated closed cell nor their associated pumping systems. Ambient air passes freely through the optical cell, and thus, the sensors are capable of high time resolution, fast response time, and lower sampling artifacts than closed-path systems [11, 12, 13, 14]. However, there are many challenges to measure the trace gases directly under the ambient conditions including spectral interferences, pressure broadening of lineshapes, deterioration of any exposed optics, and a wide range of environmental conditions (e.g., precipitation, road spray, dust, insects, extreme temperatures).
Individual laser-based, open-path sensors have been previously developed to detect atmospheric carbon monoxide (CO, a tracer for fossil fuel combustion), nitrous oxide [N2O, an important greenhouse gas (GHG) and a major ozone depleting substance; 13], NH3 [a gas phase precursor for fine aerosol; 14], and CH4 [a potent greenhouse gas; 17]. The N2O, CO, and NH3 measurements take advantage of the gas molecules’ fundamental absorption bands in the mid-infrared at 4.54 µm (for N2O/CO) and 9.06 µm (for NH3) by using quantum cascade lasers (QCL) for high-sensitivity detection. The targeted absorption lines in the mid-infrared are specially selected to minimize spectral interferences from neighboring atmospheric species at ambient pressure while also to maintain relatively strong linestrengths (within a factor of two of the strongest ones in the fundamental bands). The most significant interferences are water vapor, though other trace gases need to be considered depending upon the wavelength of interest and precision, accuracy, and detection limit needed. Both of the QCL-based sensors in the mobile laboratory have been extensively tested in the field [15, 16].
This paper reports the development and the field deployment of the first open-path, multiple trace gas mobile sensing platform. By integrating individual open-path sensors, this platform detects the four most important greenhouse gases (CO2, CH4, N2O, and H2O) and two key air pollutants (NH3, CO) simultaneously at 10 Hz. It provides a lightweight, compact and low-power alternative to the closed-path sensors and also allows for unprecedented time response for the sticky gas such as NH3. The simultaneous detection of the six different gases provides a powerful tool to fingerprint different emission sources and quantify their emissions. The mobile platform has been field deployed for 18,000 km of on-road measurements in five different field experiments in the USA and China. This study describes additional modifications to incorporate the sensors into the mobile system and demonstrates its field performance and measurement results for distinguishing and characterizing trace gas sources in urban areas.
2 Material and methods
2.1 Onboard sensors
Specifications of four sensors
Sensitivity at 10 Hz
Sensor head mass
9.06 µm QCL
150 pptv NH3
4.54 µm QCL
3 ppbv CO
0.2 ppbv N2O
0.11 ppmv CO2
0.0047 ppmv H2O
1.65 µm VCSEL
5 ppbv CH4
2.2 Mobile platform
The optical sensor heads in the mobile platform were mounted close to each other in parallel on two slim (90 cm in length, 20 cm in width and 1.27 cm in thickness, Thorlabs, Inc., USA) aluminum optical breadboards, which in turn were mounted onto a commercial roof rack (Thule 400) of a passenger car as shown in Fig. 1. Vibration damping rubber mounts were placed between the breadboard and roof rack to isolate vibrations from the road. The control units for the sensors were placed in the backseat or the trunk of the vehicle with the cables running through either the windows or sunroof. The base of the optical sensing system was able to be mounted on different common passenger vehicles using commercially available standard luggage or ski racks, allowing great flexibility to use rental vehicles for different field campaigns. Chevy Impalas (2013, 2014 models) and Honda CRVs (2013, 2014 models) have been used to host the sensor system. The maximum load for the roof rack was 75 kg. The total mass mounted on top of the vehicle was 35 kg. The compact size and modular structure of the system allowed it to be packed conveniently in checked airline luggage for the overseas deployment and also minimized customs/shipping issues compared to the international freight shipments.
The entire mobile sensor system—computers and sensors—consumed ~200 W. The computer I and the cameras were powered directly from common 12 VDC car outlets. The rest of the components were powered by two 12 V car batteries (90 A h) placed in the back of the vehicle. The system operated for as long as 14 h without recharging the batteries, and this duration of time is typically longer than 1 day’s worth of sampling. The mobile system was deployed at speeds as high as the legal speed limit (33.5 m s−1) with no noticeable change in performance, thereby providing large spatial coverage in addition to high-resolution measurements.
2.3 Optomechanical optimization
A major challenge for the open-path, mobile sensing system was to maintain the integrity of the optomechanical design for robust on-road performance. The two QCL sensors and LI-7700 all used open-path, multiple pass optical cells to achieve long optical pathlengths in a relatively short mirror separation. The structural robustness of the optical cell and its associated components were critical for maintaining the optical alignment in the high airspeeds and vibrations of a vehicle. A standard Herriott cell formed by two spherical mirrors  was used in the LI-7700 to achieve a 30 m pathlength with 47 cm mirror separation . For the QCL sensors, an astigmatic open-path multipass cell consisting of two cylindrical mirrors  was originally tested in the field. However, sufficiently tight tolerances on mirror separation, rotational angle, and input laser beam angle  were not successfully maintained in the field. Significant changes in alignment were observed over the course of a diurnal temperature cycle (13 °C). Instead, a standard Herriott cell design was used in both QCL sensors that allowed for more tolerance in the optical alignment. The NH3 sensor had an optical cell with two 76-mm-diameter mirrors separated by ~52 cm to get a 46 m pathlength. The N2O/CO sensor uses two 51-mm-diameter mirrors with a ~28 cm separation for a 15.8 m pathlength. With the structural reinforcement of the carbon fiber rods, the Herriott optical cells maintained the optical alignment and the structural rigidity in the field conditions on the rooftop of a moving vehicle.
To address the mirror durability problem, polished uncoated molybdenum (Mo) mirrors were ultimately used instead of protected silver-coated mirrors for the Herriott cells of the mid-infrared sensors. Mo mirrors have been used for guiding high-power mid-IR lasers in harsh industrial environments. With advanced polishing techniques, a high-quality (scratch/dig of 60–40, front surface flatness of λ/4 at 632 nm) uncoated Mo mirror (Rocky Mountain Instrument Co., USA) was able to achieve a high natural broadband reflectivity of >98 % from 4 to 12 µm. The Mo mirror surface withstood frequent cleaning and resisted organic solvents and detergents. The Mo mirrors have shown great performance with almost no deterioration in the reflectivity and the surface quality. The detector light intensity of the NH3 sensor equipped with Mo mirrors has remained within 10 % of the original level after more than 10,000 km of on-road measurements.
2.4 Power consumption and thermal management
The power consumption of a mobile platform directly influences its design and the performance of the system. Generally, a mobile platform with a high power consumption requires a bulky and complicated system for the power and thermal management (such as custom batteries, generators, or an air conditioning system) and limits the range and the payload of the vehicle. Thus, a low-power system simplifies the design and field operation.
Both QCL sensors consume much more power than the laser-based LI-7700 as shown in Table 1. The LI-7700 used custom electronics/microprocessor inherent to the instrument to control the sensor and reduce the power consumption, whereas the two QCL sensors used a general data acquisition board (National Instruments, NI-DAQ USB 6251) with a separate, dedicated computer. Another important difference was the higher power consumption of QCLs compared to vertical cavity surface emitting lasers (VCSELs). The LI-7700 used a 1.65 µm VCSEL that consumed ~10 mW of electrical power to produce ~1 mW of optical power (plus an additional W of power for laser thermal control). In contrast, the QCLs needed much higher electrical power (4–8 W) to produce 10–100 s mW optical power. Several more watts of the electrical power were also needed for laser temperature control by a thermoelectric cooler (TEC). In addition, the MCT (mercury cadmium telluride) detectors (Intelligent Material Solutions Inc. and Teledyne Judson Technologies) for the mid-IR detection in two QCL sensors operated at −50 °C for optimal sensitivity, which added another few watts (1–3 W) of the electrical power for the active cooling.
For all of the open-path sensors, calibrations were performed by enclosing the sensor and flowing a gas standard (or some diluted amount of it) into the enclosure. However, it was too difficult to perform such calibrations on-road with the sensors mounted on top of the vehicle. Therefore, it was necessary to take the sensor off the vehicle to perform the calibrations before and after on-road measurements to ensure the consistency of the calibrations. CO2, CH4, N2O, and CO were calibrated with a NOAA ESRL gas standard (393.444 ± 0.003 ppmv CO2; 1871.3 ± 0.1 ppbv CH4; 138.5 ± 1 ppbv CO; and 325.81 ± 0.15 ppbv N2O). Note that for mixing ratios approximately greater than twice the ambient background, certified gas standards of accuracies of ±5 % were used. H2O was calibrated with a dew point generator (LI-610 from LI-COR). The calibration of NH3 was challenging due to its ability to adsorb on and desorb off calibration surfaces and gas handling lines. To calibrate the open-path NH3 sensor in the laboratory, a large hermetically sealed aluminum enclosure (1.5 × 0.3 × 0.4 m) was placed over the entire sensor. The large surface area of the enclosure created sampling bias from surface effects. Indeed, readings on average were 68 % lower than those predicted from dilutions of a 5 ppmv NH3 standard (Air Liquide).
2.6 Impact of self-emission and sensor separations
3 Field measurements and results
3.1 On-road sensor response and stability
3.2 Spatial and temporal mapping of gas concentrations
3.3 Identify and characterize emission sources
4 Conclusions and future outlook
In this paper, the development of a mobile sensing platform formed with multiple open-path sensors has been demonstrated. The advantage for using an open-path design for sensors is low power consumption, low mass, fewer sampling artifacts, and fast sampling response. The mobile system can also be easily installed on common passenger vehicles for field studies. The mobile sensor system consumes only 200 W with a mass of 35 kg—a significant improvement for portable, long-term mobile sensing compared with large closed-path mobile laboratory vans. It measures six different gas molecules including all major greenhouse gases and two important air pollutants. The mobile sensing platform has been installed on top of the common passenger vehicles for multiple field campaigns in both the USA and China. The field observations with this mobile sensing platform have shown its advantages in quickly mapping a large spatial area with the capability to identify and quantify the different emission sources.
For future system development, a shared optical cell would reduce the overall size and mass of the platform and provide a common measurement length scale (optical base path) among all species. More experiments are needed to verify sensor precision and calibration while driving. Waterproofing the sensors is also needed. New sensors to measure gases such as ethane (C2H6) and nitric oxide (NO) are being developed to expand the measurement capabilities. Finally, while the mobile sensing platform is a low power and highly flexible unit, there remain challenges in optimizing the sampling strategy for mobile-based measurements in order to quantify local emissions accurately.
The authors acknowledge the following people associated with the mobile platform development and deployment including James Smith, Claire Gmachl, Elie Bou-Zeid, and Denise Mauzerall at Princeton University, Tong Zhu at Peking University, Barry Lefer at University of Houston, Robert Griffin at Rice University, Jim Crawford at NASA Langley Research Center, the NASA DISCOVER-AQ science team, Andrew Neuman and Thomas Ryerson at NOAA ESRL Chemical Sciences Division for calibrations with their NH3 permeation source, Dayle McDermitt from LICOR Biosceiences, and Yan Zhang from Scinovation. The research is supported by Princeton University, the National Geographic Air and Water Conservation Fund, NSF Center for Mid-Infrared Technologies for Health and the Environment (MIRTHE, NSF-ERC) under Grant No. EEC-0540832. Special thanks to the support and helpful discussions with LI-COR Environmental division and for providing a set of LICOR sensors for the mobile laboratory. K. Sun acknowledges support by NASA Earth and Space Science Fellowship (NN12AN64H). D. J. Miller acknowledges support by the National Science Foundation Graduate Research Fellowship (DGE-0646086). We thank two anonymous reviewers for very helpful feedback and comments on the manuscript.
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