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Autonomous Unmanned Aerial Vehicles for Pollution Monitoring

V. Ramanathan, chief scientist of the Maldives Campaign, and AUAVs. Photo: Scripps Institution of Oceanography/UCSD

A research consortium funded by the National Science Foundation (NSF) and led by the Scripps Institution of Oceanography at the University of California, San Diego, has successfully sent a fleet of aerial drones through the pollution-filled skies over the Indian Ocean, thereby achieving an important milestone in the tracking of pollutants responsible for dimming Earth’s atmosphere.

The instrument-bearing autonomous unmanned aerial vehicles (AUAVs) completed 18 successful stacked flight data-gathering missions in the vicinity of the Maldives, an island chain nation south of India, said Scripps scientist V. Ramanathan.

During the Maldives AUAV Campaign (MAC), groupings of three aircraft were flown in a vertical formation that allowed their onboard instruments to observe conditions below, inside and above clouds simultaneously (stacked flight).

Researchers hope the data produced during the flights will reveal in unprecedented detail how pollution particles cause dimming and contribute to the formation of clouds which amplify the dimming caused by the pollution.

MAC has demonstrated that lightweight AUAVs and their miniaturized instruments are an effective and inexpensive means of simultaneously sampling clouds in polluted environments from within and from all sides. They will serve as critically important additions to our atmospheric measurement capability for one of the major issues in climate change science: How does pollution affect cloud microphysical and radiative processes in the context of weather and climate?

—Jay Fein, NSF Division of Atmospheric Sciences

Stacked flights with manned aircraft have been attempted, but rarely. The difficulty and cost of assembling and coordinating three similar aircraft have prevented the sort of repeated measurements required to sample clouds adequately.

Based on MAC’s success it is possible that in five years, hundreds of lightweight AUAVs will be documenting how human beings are polluting the planet and hopefully provide an early warning system for potential environmental disasters in the future.

—V. Ramanathan

The skies over the Indian Ocean visibly bear the imprint of human activities in South Asia, frequently in what are termed atmospheric brown clouds, particulate-laden haze and cumulus clouds that frequently blanket the region. The role that dust and aerosols from industrial, urban and agricultural emissions play in creating this brown haze is an important variable to researchers who study climate change, especially how human activities could be changing the planet’s albedo, or reflectivity.

Cloud cover cools Earth’s surface by reflecting solar radiation back into space. In recent years, researchers have realized that pollution in the atmosphere, and the dimming and cooling it causes, could be leading scientists to underestimate the true magnitude of global-warming trends observed in recent decades.

Ramanathan has led a consortium of academic and industrial partners in the development of aircraft and integrating them with miniaturized instruments that can obtain aerosol-cloud-solar radiation data in remote regions once considered unobtainable: multi-dimensional portraits of clouds created in polluted environments over periods of several hours.

Each AUAV, constructed by Advanced Ceramics Research (ACR) bears an instrument package that weighs less than five kilograms (11 pounds). The packages developed by the team include sensors for measuring solar radiation, cloud-drop size and concentrations, particle size and concentrations, turbulence, humidities and temperatures.

Flights took place between March 6 and March 31, 2006, taking off from an airport on the island of Hanimaadhoo in the Maldives. Each AUAV tracked a separate component of brown cloud formation. The lowest, flying beneath the cloud, quantified the input of pollution particles and measured quantities of light that penetrated the clouds.

The aircraft flying through the cloud measured the cloud’s response to the introduction of particles. The aircraft flying above the cloud measured the amount of sunlight reflected by the clouds into space and the export of particles out of the clouds.

In addition to NSF, the research was funded by the National Oceanic and Atmospheric Administration (NOAA), the National Aeronautics and Space Administration (NASA), the G. Unger Vetlesen Foundation and the Alderson Foundation. The research was also supported by the United Nations Environmental Program and the Republic of Maldives.


allen zheng

A step in the right direction. More needs tobe done to understand the effects of global dimming on the planet's atmosphere. As more countries industrialise/revamp economic growth after hiatus of the 90's (eg Asia, Eastern Europe, FSU, possibly Africa in the next few decades, and the emerging Latin American economies) theres bound tobe more polution before theres less. In the end, elimination of particulates without reduction of GHGs will ensure double wammy in a rapid rise in global temperatures. Another thing to look into further is the solar cycle. Much more needs tobe done to account for the Sun's output. At just over 1kw per square meter, even a 0.1% rise or dip in the solar output could result in a marked rise or dip in the records of global temperatures. Factored into the quadruple wammy of deforestation, GHG emmisions, solar output/dimming, and thermal pollution/output due to human activities, we have our hands full.
My 2 cents, gargantuan solar farms (concentrator dish type) in our world's deserts, Mojave, Saharan, Takla Makan, Kalahari, Austrailian (various), and Atacama, along with rootop units. Plus, push efficiency and productivity.
use of reflector-concentrators to make efficient use of cosly advanced photovotaic cells.
Maybe not on the scale shown, due to higher efficiencies and local/regional market demands, but you get the idea.


regarding solar output changes, that is a major goal of the SoHo project:

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