Pesticide Avoidance: Results From a Sri Lankan Study with Health and Environmental Policy Implications

In this paper the contingent valuation method (CVM) is used to elicit bids/values to avoid direct exposure to pesticides and the resulting illnesses among subsistence farmers in a developing country, namely Sri Lanka. Farmers using pesticides on their farms suffer from short-term as well as long-term illnesses. Deaths from direct exposure to pesticides are not uncommon. The CVM is used to determine the yearly value to an average farmer of avoiding the costs of direct exposure to pesticides and to calculate the pesticide cost scenarios for the entire country. The last section of the paper examines the factors that influence the willingness to pay (WTP) to avoid direct exposure to pesticides and the resulting illnesses and discuss the health and environmental policy implications stemming from the regression analysis.

A WTP Model Showing the Relationships Between Three Approaches For Pollution

In this paper, a simple willingness to pay (WTP) model that shows the theoretical relationships among three valuation approaches that can be used to measure changes in health resulting from pollution is developed. The three valuation approaches considered are the contingent valuation (CV), cost of illness (COI) and the defensive behaviour approaches. After showing the relationships between the three valuation approaches, the model demonstrates that the CV approach exceeds the COI and the defensive behaviour approaches. The theoretical results are supported by field survey data. The pollution referred to in this paper is direct exposure to pesticides by farmers during handling and spraying on their farms.

Acoustic suppression of the coffee-ring effect

We study the influence of acoustic fields on the evaporative self-assembly of solute particles suspended inside sessile droplets of complex fluids. The self-assembly process often results in an undesirable ring-like heterogeneous residue, a phenomenon known as the coffee-ring effect. Here we show that this ring-like self-assembly can be controlled acoustically to form homogeneous disc-like or concentrated spot-like residues. The principle of our method lies in the formation of dynamic patterns of particles in acoustically excited droplets, which inhibits the evaporation-driven convective transport of particles towards the contact line. We elucidate the mechanisms of this pattern formation and also obtain conditions for the suppression of the coffee-ring effect. Our results provide a more general solution to suppress the coffee-ring effect without any physiochemical modification of the fluids, the particles or the surface, thus potentially useful in a broad range of industrial and analytical applications that require homogenous solute depositions

Estimation of subsurface porosities and thermal conductivities of polygonal tundra by coupled inversion of electrical resistivity, temperature, and moisture content data

Studies indicate greenhouse gas emissions following permafrost thaw will amplify current rates of atmospheric warming, a process referred to as the permafrost carbon feedback. However, large uncertainties exist regarding the timing and magnitude of the permafrost carbon feedback, in part due to uncertainties associated with subsurface permafrost parameterization and structure. Development of robust parameter estimation methods for permafrost-rich soils is becoming urgent under accelerated warming of the Arctic. Improved parameterization of the subsurface properties in land system models would lead to improved predictions and a reduction of modeling uncertainty. In this work we set the groundwork for future parameter estimation (PE) studies by developing and evaluating a joint PE algorithm that estimates soil porosities and thermal conductivities from time series of soil temperature and moisture measurements and discrete in-time electrical resistivity measurements. The algorithm utilizes the Model-Independent Parameter Estimation and Uncertainty Analysis toolbox and coupled hydrological-thermal-geophysical modeling. We test the PE algorithm against synthetic data, providing a proof of concept for the approach. We use specified subsurface porosities and thermal conductivities and coupled models to set up a synthetic state, perturb the parameters, and then verify that our PE method is able to recover the parameters and synthetic state. To evaluate the accuracy and robustness of the approach we perform multiple tests for a perturbed set of initial starting parameter combinations. In addition, we varied types and quantities of data to better understand the optimal dataset needed to improve the PE method. The results of the PE tests suggest that using multiple types of data improve the overall robustness of the method. Our numerical experiments indicate that special care needs to be taken during the field experiment setup so that (1) the vertical distance between adjacent measurement sensors allows the signal variability in space to be resolved and (2) the longer time interval between resistivity snapshots allows signal variability in time to be resolved

Short-scale turbulent fluctuations driven by the electron-temperature gradient in the national spherical torus experiment

Measurements with coherent scattering of electromagnetic waves in plasmas of the National Spherical Torus Experiment indicate the existence of turbulent fluctuations in the range of wave numbers k(perpendicular to)rho(e)=0.1-0.4, corresponding to a turbulence scale length nearly equal to the collisionless skin depth. Experimental observations and agreement with numerical results from a linear gyrokinetic stability code support the conjecture that the observed turbulence is driven by the electron-temperature gradient.X1155sciescopu