INVESTIGADORES
PANEBIANCO Juan Esteban
artículos
Título:
Meteorological conditions during dust (PM10) emission from a tilled loam soil: Identifying variables and thresholds
Autor/es:
AVECILLA, FERNANDO; JUAN E. PANEBIANCO; BUSCHIAZZO D.E
Revista:
AGRICULTURAL AND FOREST METEOROLOGY
Editorial:
ELSEVIER SCIENCE BV
Referencias:
Lugar: Amsterdam; Año: 2017
ISSN:
0168-1923
Resumen:
Soil wind erosion and consequent PM10 emission is a complex process that has been related to surface propertiesand meteorological conditions. Most of the studies have emphasized on the relationship between the surfaceconditions and the dust emission, in general on deserts and dry lakes or playas. Little is known about theinfluence of meteorological variables on PM10 emission from agricultural soils. The objective of this study was toidentify the most important meteorological variables involved in the emission of PM10, identify their thresholdvalues, and to analyze their interaction with the soil surface conditions. Measurements were made on a loam soil(Entic Haplustoll) in the semiarid Argentinian Pampa. Horizontal mass transport (Q) and PM10 emission weremeasured during two years on a bare and flat surface that was tilled periodically. The meteorological variablesmeasured were: average and maximum wind speed, wind direction, air temperature, relative humidity and soiltemperature. In 30% of the events, the PM10 concentration at 1.8 m height exceeded the average values allowedby the World Health Organization (50 μg m−3 for a 24 h period). Maximum values exceeded 1000 μg m−3. Theslope of the PM10 concentration gradient changed between spring − summer and autumn − winter periods.Threshold values of the studied variables were set when PM10 concentration values at 1.8 m height wereconsistently above the 50 μg m−3 limit. The highest PM10 emission rates were observed when relative humidityvalues were below 20% and the air temperature was higher than 30 °C. In addition when the wind speedexceeded 8 m s−1, dust emission increased significantly. From a multiple regression analysis, results indicatedthat PM10 emission was well correlated (p< 0.001) with maximum wind speed, relative humidity, and airtemperature. Maximum wind speed and relative humidity conditioned the PM10 emission in a synergistic way.However, the regression explained only 32% of the variability. Although higher average PM10 emission valueswere measured during events with a crusted surface, lower average values of Q were measured during eventswith a crust. Field observations indicated that the complex interaction between the weather conditions and soilsurface properties such as soil crusts, aggregate size distribution, soil moisture and even the soil condition whenthe tilling is done,