Air pollution has a direct impact to human health, and data-driven air quality models are useful for evaluating population exposure to air pollutants. In this paper, we propose a novel region-based Gaussian process model for estimating urban air pollution dispersion, and applied it to a large dataset of ultrafine particle (UFP) measurements collected from a network of sensors located on several...

Recently, kernel-based Machine Learning methods have gained great popularity in many data analysis and data mining fields: pattern recognition, biocomputing, speech and vision, engineering, remote sensing etc. The paper describes the use of kernel methods to approach the processing of datasets from environmental monitoring networks. Several typical problems of the environmental sciences and the...

We present an architecture of controlling a proposed spectrometer system for detecting pollution in water and gas. The system is based on LED sensors using a Michelson interferometer and stepper –motor for moving split mirrors. The system is designed so that changes in LED light intensity could allow to detect a wide spectrum of polluted substances. The architecture uses a special duty-cycle to...

The effects of abundant Mancozeb (Mn, Zn-bisdithiocarbamate) applications (2.5 kg ha⁻¹week⁻¹ for 10 years) on soil and surface-, subsurface- and groundwater pollution were monitored in a banana production region of tropical Mexico. In soils, severe manganese accumulation was observed, wheras the main metabolite ethylenethiourea was near the detection limit. Surface and subsurface water was high...

Results of radar monitoring of the sea surface in the Russian sector of the Black Sea coastal zone are presented. The attention was focused on the detection of oil pollution as well as biogenic and anthropogenic surfactant films. The basic data were high resolution radar images obtained by synthetic aperture radars (SAR) on board Envisat and ERS-2 satellites of the European Space Agency. Spatia...

Wireless sensor networks have been deployed for environmental monitoring over the last twenty years. However, this application is not frequently deployed to solve the environmental problems (e.g. air pollution detection) encountered by many African countries. This paper develops an architecture based on a Wireless Mesh Network of Sensors (WMNS) to measure air pollution in African cities. We are...

Environmental monitoring and assessment includes a wide spectrum of study that overlaps many disciplines, all of which are independent. This paper illustrates several broad subjects related to environmental constraints including water pollution, effects of atmospheric contamination, strip mining, and natural disasters. Remote sensing can provide complementary information to existing ground-base...

The use of protein electrophoretic data for determining the relationships among species or populations is widespread and generally accepted. However, there are many confounding factors that may alter the results of an electrophoretic study and may possibly allow erroneous conclusions to be drawn in taxonomic, systematic or population studies. Measured enzyme activities can also be affected sign...

Atmospheric contamination has deteriorated the health of plants and animals all over the globe. In particular, pollutants such as benzene(C6H6) has accelerated the rate of cancer among human beings. Therefore, accurate evaluation of the pollutant in the atmosphere is necessary by traffic supervision in urban areas. To reduce atmospheric contamination, an effective mobile strategy planning must ...

A novel sensing system has been designed for naphthalene detection based on the quenched fluorescence signal of CdS quantum dots. The fluorescence intensity of the system reduced significantly after adding CdS quantum dots to the water pollution model because of the fluorescent static quenching f mechanism. Herein, we have demonstrated the facile methodology can offer a convenient and low analy...