Meteorological conditions during dust (PM10) emission from a tilled loam soil: Identifying variables and thresholds

Abstract

Soil wind erosion and consequent PM10 emission is a complex process that has been related to surface properties and meteorological conditions. Most of the studies have emphasized on the relationship between the surface conditions and the dust emission, in general on deserts and dry lakes or playas. Little is known about the influence of meteorological variables on PM10 emission from agricultural soils. The objective of this study was to identify the most important meteorological variables involved in the emission of PM10, identify their threshold values, 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 were measured during two years on a bare and flat surface that was tilled periodically. The meteorological variables measured were: average and maximum wind speed, wind direction, air temperature, relative humidity and soil temperature. In 30% of the events, the PM10 concentration at 1.8m height exceeded the average values allowed by the World Health Organization (50μgm−3 for a 24h period). Maximum values exceeded 1000μgm−3. The slope 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 1.8m height were consistently above the 50μgm−3 limit. The highest PM10 emission rates were observed when relative humidity values were below 20% and the air temperature was higher than 30°C. In addition when the wind speed exceeded 8ms−1, dust emission increased significantly. From a multiple regression analysis, results indicated that PM10 emission was well correlated (p <0.001) with maximum wind speed, relative humidity, and air temperature. 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 values were measured during events with a crusted surface, lower average values of Q were measured during events with a crust. Field observations indicated that the complex interaction between the weather conditions and soil surface properties such as soil crusts, aggregate size distribution, soil moisture and even the soil condition when the tilling is done, can produce a high variability and unpredictability, of the PM10 emission from bare agricultural soils.