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New copy - Usually dispatched within 2 working days. The UAV repeated this procedure moving in a zig-zag fashion within the plume, stopping when it reached the source. Finally, the pseudo-gradient algorithm included a new measuring strategy to deal with the strong disturbances induced by the rotors of a rotary-wing UAV, since measuring a local concentration gradient with spatially separated sensors as part of the gradient algorithm was not feasible in this case.

The pseudo gradient algorithm also considered wind information in order to overcome the limitations of older gradient ascent methods that are unable to determine whether they are following a plume towards or away from the source. A fan was used to blow the gas towards the UAV, which was placed 1. Data collection behind the gas source would have also been advantageous to obtain a more accurate and reliable gas source location estimate. The study showed that it was difficult to locate gas sources in a dynamic environment where changes in wind speed and direction, together with high turbulence, were present.

Bennetts et al. When using UAVs, and in particular rotary-wing platforms, the location of air sampler or air sensor intakes is crucial for accurate sampling [ ]. Significant differences were found between the different gas sampling approaches, however, none of them were capable of measuring the reference gas concentration 0.

The average measured concentration was 0. Although the active gas transport approach was most effective at reducing the propeller dilution effect, the additional weight 76 g of the long carbon fiber tube, the position of the tube inlet which strongly dictates the measurement results and the enlarged drone size which makes it more susceptible to wind conditions were found to be significant drawbacks.

Gerhardt et al. Nathan et al. The sensing payload consisted in a custom made laser-based open path methane sensor with a precision of 0. Data was collected from 22 flights around a natural compressor station to monitor CH 4 leakage. To understand if the reason was due to real changes in the emission rates, atmospheric variability or flight sampling issues, Nathan et al.

During the campaign, two additional and independent research groups measured the methane concentrations on the ground. This is likely due to the impossibility of measuring the lofted emissions by the ground stations. Statistically, the interpolated methane downwind concentration was the main reason for the flux error analysis. In order to quantify this error, an interpolated map of areas where the flight did not sample is needed. The temporal distribution of fugitive CH 4 emission rates from compressor stations needs further study, but the study highlighted that UAVs can be a valuable approach to quantify emission from point sources.

The UK Environment agency recently issued a report based on Allen et al. Allen et al. An alternative could be to obtain CH 4 measurements from a tethered rotary platform which involves vertical sampling profiling from a series of locations along a downwind transect.

List of unmanned aerial vehicles

Using portable equipment i. Using a tethered UAS platform the size of the methane instrument would not be a constraint. UAV systems have been demonstrated to be an appropriate platform for in-situ inspection systems to sample closer to the source. However, bias can be introduced in a number of ways, including sampling a region with significantly few pollutants and assuming a uniform distribution.

Quantifying emissions on a UAV is inherently challenging.

Unmanned Aircraft Systems: UAVS Design, Development and Deployment

A Gaussian single plume model is not ideal to create estimates of airborne data collection when there is more than one central plume. In fact, all basic Gaussian plumes would assume that constant and continuous emissions create a steady-state system. Therefore, the largest and most problematic assumption for these in-flight data sets would be to have one central plume. Although the point source approximation might be appropriate for most point source studies, the emissions from other locations around the investigated source could significantly be affected by the single-plume-model approach.

To overcome this issue, researchers have investigated other approaches and the Kriging interpolation seems to be a better methodology to analyze UAV-acquired measurements from a point source [ ]. Future studies need to optimize a more refined model that considers either a segmented Gaussian plume or a Gaussian puff. Currently, mechanical design limitations affect UAV applications. This is because the majority of commercially available UAVs are not designed to facilitate operations like quantification of CH 4 emissions from compressor stations.

These constraints can be addressed through UAV design, construction, and careful flight and sampling design [ ]. Since most operations take place on controlled access sites, developing procedures that allow UAV use across the entire site during normal operational hours is required. Finally, payload and endurance limits, system network integration and aerospace legislation will affect UAV applications.

Air quality research is moving towards the more wide-spread use of UAVs to: measure gases at different altitudes; compare ground based data; and autonomously track plumes emitted by combustion sources, revealing the origin of pollutants [ ]. New miniaturized instruments have been, and are still being developed, such as ultra-portable 10 kg weight and 21, cm 3 volume and low powered 24V mass spectrometer MS , for the study and visualization of gaseous volcanic emissions [ ]. Similarly, research into UAV navigation is empowering more efficient bio-inspired algorithms [ ] to enable aircraft to autonomously locate, and fly into or out of, an existing plume [ ].

UAVs can complement existing wireless stationary networks WSN to improve the accuracy of data assimilation [ 90 , ] by providing data comparable to that obtained using the stationary network, but with more than 30 sensors [ ].


Table S2 in the Supplementary Materials summarizes the on-board UAV technologies which have been used for air quality data collection to date. A recent literature review [ ] suggested the use of UAVs to measure VOCs emitted from healthy plants and those under environmental stress. While this might enable researchers to detect plant stress and disease in its early stages, difficulties arise in terms of sampling methodologies and the chemical species to be sampled.

Therefore, ground-based robots would be better suited for such an application, however, they could work in co-ordination with UAVs, to sample the broader area using optical sensors and relay information regarding site-specific points of interest. Alternatively, the sensor could be suspended from the UAV and a slow hover-like flight path would allow for the sensor to move through the field and obtain reliable measurements.

An analysis of the literature presented in this paper has highlighted potential applications for the use of small lightweight UAVs in the atmospheric research domain. However, there are a number of challenges that may prevent the science community from moving towards a widespread use of UAVs for air quality measurements [ 88 , , ]. The most significant of them relates to aviation policy and regulations that cover using unmanned aircraft to investigate atmospheric composition and phenomena in the ABL within national airspace systems [ ].

In addition, limitations such as flight time, sensor integration and limited autonomy are driving research into the use of small UAVs. Table 2 shows the overall benefits and limitations and other challenges to the use of these small robotic platforms for air quality research.

Overall benefits and limitations for the use of small lightweight UAVs in the atmospheric research domain. Another potential research area is plume tracking using UAVs, but a system capable of such a task under real world conditions, including changing wind speed and direction, has not yet been developed. To date, experimental tests have shown that it is possible to track plumes where the airflow is more stable, like those emitted by industrial chimneys in a higher atmospheric layer, or on wide open landfill sites, geo-dynamically active regions or waste disposal sites [ 90 ].

Small instrument technology is developing quickly, with promising methods for both gas measurements, including tunable diode lasers, cascade quantum lasers and fiber chemical sensing [ ], and PM measurements [ ]. Future instruments for GHG analysis should also be equipped with on-board calibration cylinders for real time and in-flight instrument calibration [ ], and autopilot improvements will enable more precise flight paths, as well as optimized sampling procedures [ ].

Future methane instruments may also be suitable for rotary UAS platforms. The flight control and flight management software for multi-rotors is more mature than the equivalent software for fixed wing UAVs. The reason comes from both the requirement for sophisticated software to control multi-rotors and the current dominance of photography in the market for small multi-rotors UAVs.

Application of advanced control and optimization techniques to flight control system for UAVs

The result is that, for some applications, multi-rotors are the preferred solution; however, their lower endurance would preclude them from use on larger sites [ , ]. Established ground-based methods for air quality sampling, such as the sorbent tube or solid phase micro extraction SPME sampling techniques for VOCs, could be re-designed for use on-board UAVs, as well as integration with real-time display and data logging.

Algorithm developments using multiple UAVs for plume tracking is possible where one UAV is flying upwind while the other tracks the plume downwind, in order to predict the path of the plume and provide early warning for areas of contamination.

Introduction To The UAV Special Edition

Genetics algorithms could also be used to obtain faster and more efficient reactions. UAVs can offer high resolution spatiotemporal sampling, which is not possible or feasible with manned aircraft. The future of UAVs for use in air quality applications is promising, thanks to the capability and flexibility of these robotic platforms.

At the same time, new technologies in fields such as chemistry, physics and information technology are also developing very fast, resulting in smaller and lighter devices, with higher sensitivity and the ability to work remotely. Questions still need to be addressed regarding the miniaturization of sensors, which seems to be the main issue when working with lightweight UAVs. In fact, the diverse range of UAV payload capacity is primarily made by the difference between rotary and fixed wing UAVs.

The key limiting factors in new sensor development include: power, mass, and size, because these are intimately connected to the type of platform rotary instead of fixed wings , engine electrically or gas powered and the type of mission speed, longer distances with low altitude, rather than flight stability and low speed for a higher spatial resolution.

Strict civil aviation regulations mean UAVs are commonly deployed for weather forecasting, atmospheric monitoring or as a tool for volcanology research. The authors like to thank John Paul Cunningham, Queensland University of Technology QUT , for the collaboration and helpful discussion during the preparation of the manuscript. Tommaso Francesco Villa conducted the literature search following the research plan developed with the other authors and drafted the entire manuscript. Felipe Gonzalez contributed to the sections: 3.

Branka Miljievic contributed to the literature search and reviewed the entire manuscript.

Zoran D. Ristovski contributed to the literature search and reviewed the entire manuscript. Lidia Morawska directed the research project, contributed to the revision of the entire manuscript and to the discussion of UAV systems for air quality studies. National Center for Biotechnology Information , U. Journal List Sensors Basel v. Sensors Basel. Published online Jul Find articles by Tommaso Francesco Villa. Find articles by Branka Miljievic.

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