5 resultados para atmospheric sampling

em Instituto Politécnico do Porto, Portugal


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A methodology based on microwave-assisted extraction (MAE) and LC with fluorescence detection (FLD) was investigated for the efficient determination of 15 polycyclic aromatic hydrocarbons (PAHs) regarded as priority pollutants by the US Environmental Protection Agency and dibenzo(a,l)pyrene in atmospheric particulate samples. PAHs were successfully extracted from real outdoor particulate matter (PM) samples with recoveries ranging from 81.4±8.8 to 112.0±1.1%, for all the compounds except for naphthalene (62.3±18.0%) and anthracene (67.3±5.7%), under the optimum MAE conditions (30.0 mL of ACN for 20 min at 110ºC). No clean-up steps were necessary prior to LC analysis. LOQs ranging from 0.0054 ng/m3 for benzo( a)anthracene to 0.089 ng/m3 for naphthalene were reached. The validated MAE methodology was applied to the determination of PAHs from a set of real world PM samples collected in Oporto (north of Portugal). The sum of particulate-bound PAHs in outdoor PM ranged from 2.5 and 28 ng/m3.

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One of the most important measures to prevent wild forest fires is the use of prescribed and controlled burning actions as it reduce the fuel mass availability. The impact of these management activities on soil physical and chemical properties varies according to the type of both soil and vegetation. Decisions in forest management plans are often based on the results obtained from soil-monitoring campaigns. Those campaigns are often man-labor intensive and expensive. In this paper we have successfully used the multivariate statistical technique Robust Principal Analysis Compounds (ROBPCA) to investigate on the sampling procedure effectiveness for two different methodologies, in order to reflect on the possibility of simplifying and reduce the sampling collection process and its auxiliary laboratory analysis work towards a cost-effective and competent forest soil characterization.

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Coal contains trace quantities of natural radionuclides such as Th-232, U-235, U-238, as well as their radioactive decay products and 40K. These radionuclides can be released as fly ash in atmospheric emissions from coal-fired power plants, dispersed into the environment and deposited on the surrounding top soils. Therefore, the natural radiation background level is enhanced and consequently increase the total dose for the nearby population. A radiation monitoring programme was used to assess the external dose contribution to the natural radiation background, potentially resulting from the dispersion of coal ash in past atmospheric emissions. Radiation measurements were carried out by gamma spectrometry in the vicinity of a Portuguese coal-fired power plant. The radiation monitoring was achieved both on and off site, being the boundary delimited by a 20 km circle centered in the stacks of the coal plant. The measured radionuclides concentrations for the uranium and thorium series ranged from 7.7 to 41.3 Bq/kg for Ra-226 and from 4.7 to 71.6 Bq/kg for Th-232, while K-40 concentrations ranged from 62.3 to 795.1 Bq/kg. The highest values were registered near the power plant and at distances between 6 and 20 km from the stacks, mainly in the prevailing wind direction. The absorbed dose rates were calculated for each sampling location: 13.97-84.00 ηGy/h, while measurements from previous studies carried out in 1993 registered values in the range of 16.6-77.6 ηGy/h. The highest values were registered at locations in the prevailing wind direction (NW-SE). This study has been primarily done to assess the radiation dose rates and exposure to the nearby population in the surroundings of a coal-fired power plant. The results suggest an enhancement or at least an influence in the background radiation due to the coal plant past activities.

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Mathematical models and statistical analysis are key instruments in soil science scientific research as they can describe and/or predict the current state of a soil system. These tools allow us to explore the behavior of soil related processes and properties as well as to generate new hypotheses for future experimentation. A good model and analysis of soil properties variations, that permit us to extract suitable conclusions and estimating spatially correlated variables at unsampled locations, is clearly dependent on the amount and quality of data and of the robustness techniques and estimators. On the other hand, the quality of data is obviously dependent from a competent data collection procedure and from a capable laboratory analytical work. Following the standard soil sampling protocols available, soil samples should be collected according to key points such as a convenient spatial scale, landscape homogeneity (or non-homogeneity), land color, soil texture, land slope, land solar exposition. Obtaining good quality data from forest soils is predictably expensive as it is labor intensive and demands many manpower and equipment both in field work and in laboratory analysis. Also, the sampling collection scheme that should be used on a data collection procedure in forest field is not simple to design as the sampling strategies chosen are strongly dependent on soil taxonomy. In fact, a sampling grid will not be able to be followed if rocks at the predicted collecting depth are found, or no soil at all is found, or large trees bar the soil collection. Considering this, a proficient design of a soil data sampling campaign in forest field is not always a simple process and sometimes represents a truly huge challenge. In this work, we present some difficulties that have occurred during two experiments on forest soil that were conducted in order to study the spatial variation of some soil physical-chemical properties. Two different sampling protocols were considered for monitoring two types of forest soils located in NW Portugal: umbric regosol and lithosol. Two different equipments for sampling collection were also used: a manual auger and a shovel. Both scenarios were analyzed and the results achieved have allowed us to consider that monitoring forest soil in order to do some mathematical and statistical investigations needs a sampling procedure to data collection compatible to established protocols but a pre-defined grid assumption often fail when the variability of the soil property is not uniform in space. In this case, sampling grid should be conveniently adapted from one part of the landscape to another and this fact should be taken into consideration of a mathematical procedure.

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A set of radiation measurements were carried out in several public and private institutions. These were selected with basis on the people affluence and passage to these sites. These measurements were registration formed either indoor, outdoor or underground and were compiled in three Case Studies. Radiation doses measurements were also made, surface and underground locations, and compiled in other two Case Studies. There were sampled, at the same time, humidity, temperature, atmospheric pressure and relevant construction materials at sampling locations. They were collected and registration formed to analyse if there is any relation or contribution for the measured value in each specific place. Geostatistical models were used to elaborate maps of the results both for radiation values and for doses. Preliminary relations were established among the measured parameters.