Aglite lidar: a portable elastic lidar system for investigating aerosol and wind motions at or around agricultural production facilities

Marchant, Christian C.; Wilkerson, Thomas D.; Bingham, Gail E.; Zavyalov, Vladimir V.; Andersen, J.; Wright, Cordell B.; Cornelsen, Scott S.; Martin, Randal S.; Silva, Philip J.; Hatfield, Jerry L.

doi:10.1117/1.3097928

Cited by 29 publications

(26 citation statements)

References 4 publications

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“…The development of new eye-safe scanning lidar systems specifically designed for agricultural applications [25,26] is expected to contribute to agricultural air quality monitoring. Nevertheless, conventional lidar systems are unable to distinguish between different types of aerosols, which can lead to misinterpretation of the measurements.…”

Section: Introductionmentioning

confidence: 99%

Polarization Lidar Detection of Agricultural Aerosol Emissions

et al. 2018

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Agricultural aerosol emissions can significantly impact human and animal health as well as the environment. Therefore, it is essential to adopt new sensing techniques for real-time monitoring these emissions in high temporal and spatial resolution. In recent years, light detection and ranging (lidar) technology has been used for measuring the particulate matter emitted from agricultural operations. However, conventional nonpolarized lidar systems cannot discriminate between different types of aerosols, which can lead to misinterpretation of the results. To overcome this limitation, this study applies the polarization lidar technique to monitor agricultural aerosols. A 355 nm polarization lidar system was used to measure the emissions generated during pesticide spraying operations. The results showed that depolarization ratios due to field dust (0.220-0.268) and to road dust (0.385) are clearly higher than those caused by pesticide spray drift (0.028-0.043) or by diesel exhaust (0.099), which can be used to differentiate each type of aerosol. These results support the development of new polarization lidar systems specifically designed to study the impact of agricultural activities on air quality.

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Section: Introductionmentioning

confidence: 99%

Polarization Lidar Detection of Agricultural Aerosol Emissions

et al. 2018

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“…The first evidence of continuous mobile sun photometer measurements during vehicle's movement has been presented by Mortier (2012) during the DRAGON (Distributed Regional Aerosol Gridded Observation Networks; (Holben et al, unpublished) -USA campaign. For lidar, the term "mobile" refers mostly to scanning (Chiang et al, 2015;Marchant, 2009), transportable (Berkhout et al, 2016;Chazette et al, 2014;Freudenthaler et al, 2002) or scanning and transportable (Dou et al, 2014) systems, used for measurements in remote places, during field campaigns or simply outside laboratory rooms. To our knowledge, only a few studies presenting ground-based lidar profiling of aerosol properties by on-road mobile measurements have been conducted, over Paris agglomeration (Pal et al, 2012;Royer et al, 2011), on London's orbital motorway and from Paris to Siberia (Dieudonné et al, 2015).…”

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confidence: 99%

Description and applications of a mobile system performing on-road aerosol remote sensing and in situ measurements

et al. 2018

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Abstract. The majority of ground-based aerosols observations are limited to fixed locations, narrowing the knowledge on their spatial variability. In order to overcome this issue, a compact Mobile Aerosol Monitoring System (MAMS) was developed to explore the aerosol vertical and spatial variability. This mobile laboratory is equipped with a micropulse lidar, a sun photometer and an aerosol spectrometer. It is distinguished from other transportable platforms through its ability to perform on-road measurements and its unique feature lies in the sun photometer's capacity for tracking the sun during motion. The system presents a great flexibility, being able to respond quickly in case of sudden aerosol events such as pollution episodes, dust, fire or volcano outbreaks. Onroad mapping of aerosol physical parameters such as attenuated aerosol backscatter, aerosol optical depth, particle number and mass concentration and size distribution is achieved through the MAMS. The performance of remote sensing instruments on-board has been evaluated through intercomparison with instruments in reference networks (i.e. AERONET and EARLINET), showing that the system is capable of providing high quality data. This also illustrates the application of such a system for instrument intercomparison field campaigns. Applications of the mobile system have been exemplified through two case studies in northern France. MODIS AOD data was compared to ground-based mobile sun photometer data. A good correlation was observed with R 2 of 0.76, showing the usefulness of the mobile system for validation of satellite-derived products. The performance of BSCDREAM8b dust model has been tested by comparison of results from simulations for the lidar-sun-photometer derived extinction coefficient and mass concentration profiles. The comparison indicated that observations and the model are in good agreement in describing the vertical variability of dust layers. Moreover, on-road measurements of PM 10 were compared with modelled PM 10 concentrations and with ATMO Hauts-de-France and AIRPARIF air quality in situ measurements, presenting an excellent agreement in horizontal spatial representativity of PM 10 . This proves a possible application of mobile platforms for evaluating the chemistry-models performances.

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“…The effective range is 500 m to 15 km with each range bin approximately 6 m in length. 22 The LIDAR was placed in crosswind positions 550 m from the nearest tillage area border. It was at L1, as shown in Fig.…”

Section: Instrumentation and Sample Layoutmentioning

confidence: 99%

Particulate-matter emission estimates from agricultural spring-tillage operations using LIDAR and inverse modeling

Moore

Wojcik

Martin

et al. 2015

J. Appl. Remote Sens

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Abstract. Particulate-matter (PM) emissions from a typical spring agricultural tillage sequence and a strip-till conservation tillage sequence in California's San Joaquin Valley were estimated to calculate the emissions control efficiency (η) of the strip-till conservation management practice (CMP). Filter-based PM samplers, PM-calibrated optical particle counters (OPCs), and a PM-calibrated light detection and ranging (LIDAR) system were used to monitored upwind and downwind PM concentrations during May and June 2008. Emission rates were estimated through inverse modeling coupled with the filter and OPC measurements and through applying a mass balance to the PM concentrations derived from LIDAR data. Sampling irregularities and errors prevented the estimation of emissions from 42% of the sample periods based on filter samples. OPC and LIDAR datasets were sufficiently complete to estimate emissions and the strip-till CMP η, which were ∼90% for all size fractions in both datasets. Tillage time was also reduced by 84%. Calculated emissions for some operations were within the range of values found in published studies, while other estimates were significantly higher than literature values. The results demonstrate that both PM emissions and tillage time may be reduced by an order of magnitude through the use of a strip-till conservation tillage CMP when compared to spring tillage activities.

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Aglite lidar: a portable elastic lidar system for investigating aerosol and wind motions at or around agricultural production facilities

Cited by 29 publications

References 4 publications

Polarization Lidar Detection of Agricultural Aerosol Emissions

Polarization Lidar Detection of Agricultural Aerosol Emissions

Description and applications of a mobile system performing on-road aerosol remote sensing and in situ measurements

Particulate-matter emission estimates from agricultural spring-tillage operations using LIDAR and inverse modeling

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