Publications by authors named "Dimitris G Kaskaoutis"

Article Synopsis
  • - This research presents a new method using deep learning and active learning to create accurate global maps of land susceptibility to wind erosion, employing models like RNN and GRU alongside various interpretation techniques.
  • - Thirteen environmental factors were analyzed, and through optimization, eight significant factors (such as wind speed and soil moisture) were selected to predict wind erosion risk.
  • - The findings show that the GRU-AL model was the most effective, categorizing global land into different levels of susceptibility, with significant insights into how factors like soil carbon and precipitation interact with erosion risk predictions.
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Total suspended particulates (TSP), as a key pollutant, is a serious threat for air quality, climate, ecosystems and human health. Therefore, measurements, prediction and forecasting of TSP concentrations are necessary to mitigate their negative effects. This study applies the gated recurrent unit (GRU) deep learning model to predict TSP concentrations in Zabol, Iran, during the dust period of the 120-day wind (3 June - 4 October 2014).

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Assessment of indoor air quality is especially important, since people spend substantial amounts of time indoors, either at home or at work. This study analyzes concentrations of selected heavy metals in 40 indoor dust samples obtained from houses in the highly-industrialized Asaluyeh city, south Iran in spring and summer seasons (20 samples each). Furthermore, the health risk due to exposure to indoor air pollution is investigated for both children and adults, in a city with several oil refineries and petrochemical industries.

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Since its first appearance in Wuhan, China at the end of 2019, the new coronavirus (COVID-19) has evolved a global pandemic within three months, with more than 4.3 million confirmed cases worldwide until mid-May 2020. As many countries around the world, Malaysia and other southeast Asian (SEA) countries have also enforced lockdown at different degrees to contain the spread of the disease, which has brought some positive effects on natural environment.

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Urban areas in developing countries are major sources of carbonaceous aerosols and air pollutants, pointing out the need for a detailed assessment of their levels and origin close to the source. A multi-instrument research campaign was performed in Delhi during December 2015-February 2016 aimed at exploring the pollution levels and the contribution of various sources to particulate matter (PM) concentrations, black carbon (BC) aerosols, and trace gases. The weak winds (< 5-6 m s) along with the shallow boundary layer favoured the formation of thick and persistent fog conditions, which along with the high BC (24.

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