The Alkaline Hydrolysis of Sulfonate Esters: Challenges in Interpreting Experimental and Theoretical Data

Sulfonate ester hydrolysis has been the subject of recent debate, with experimental evidence interpreted in terms of both stepwise and concerted mechanisms. In particular, a recent study of the alkaline hydrolysis of a series of benzene arylsulfonates (Babtie et al., Org. Biomol. Chem. 10, 2012, 8095) presented a nonlinear Brønsted plot, which was explained in terms of a change from a stepwise mechanism involving a pentavalent intermediate for poorer leaving groups to a fully concerted mechanism for good leaving groups and supported by a theoretical study. In the present work, we have performed a detailed computational study of the hydrolysis of these compounds and find no computational evidence for a thermodynamically stable intermediate for any of these compounds. Additionally, we have extended the experimental data to include pyridine-3-yl benzene sulfonate and its N-oxide and N-methylpyridinium derivatives. Inclusion of these compounds converts the Brønsted plot to a moderately scattered but linear correlation and gives a very good Hammett correlation. These data suggest a concerted pathway for this reaction that proceeds via an early transition state with little bond cleavage to the leaving group, highlighting the care that needs to be taken with the interpretation of experimental and especially theoretical data

Evapotranspiration monitoring in the Mediterranean saltmarsh scrubs of the Rhône River Delta, (south-eastern France).

International audienc

Estimation of evapotranspiration in the Mediterranean saltmarsh scrubs of the Rhône River Delta, (south-eastern France).

International audienc

Albedo and LAI estimates from FORMOSAT-2 data for crop monitoring

This paper aimed at estimating albedo and Leaf Area Index (LAI) from FORMOSAT-2 satellite that offers a unique source of high spatial resolution (eight meters) images with a high revisit frequency (one to three days). It mainly consisted of assessing the FORMOSAT-2 spectral and directional configurations that are unusual, with a single off nadir viewing angle over four visible-near infra red wavebands. Images were collected over an agricultural region located in South Eastern France, with a three day frequency from the growing season to post-harvest. Simultaneously, numerous ground based measurements were performed over various crops such as wheat, meadow, rice and maize. Albedo and LAI were estimated using empirical approaches that have been widely used for usual directional and spectral configurations (i.e. multidirectional or single nadir viewing angle over visible-near infrared wavebands). Two methods devoted to albedo estimation were assessed. based on stepwise multiple regression and neural network (NNT). Although both methods gave satisfactory results, the NNT performed better (relative RMSE=3.5% versus 7.3%), especially for low vegetation covers over dark or wet soils that corresponded to albedo values lower than 0.20. Four approaches for LAI estimation were assessed. The first approach based on a stepwise multiple regression over reflectances had the worst performance (relative RMSE=65%), when compared to the equally performing NDVI based heuristic relationship and reflectance based NNT approach (relative RMSE=34%).The NDVI based neural network approach had the best performance (relative RMSE=27.5%), due to the combination of NDVI efficient normalization properties and NNT flexibility. The high FORMOSAT-2 revisit frequency allowed next replicating the dynamics of albedo and LAI, and detecting to some extents cultural practices like vegetation cuts. It also allowed investigating possible relationships between albedo and LAI. The latter depicted specific trends according to vegetation types, and were very similar when derived from ground based data, remotely sensed observations or radiative transfer simulations. These relationships also depicted large albedo variabilities for low LAI values, which confirmed that estimating one variable from the other would yield poor performances for low vegetation cover with varying soil backgrounds. Finally, this empirical study demonstrated, in the context of exhaustively describing the spatiotemporal variability of surface properties, the potential synergy between 1) ground based web-sensors that continuously monitor specific biophysical variables over few locations, and 2) high spatial resolution satellite with high revisit frequencies

Reconstruction of temporal variations of evapotranspiration using instantaneous estimates at the time of satellite overpass

Evapotranspiration estimates can be derived from remote sensing data and ancillary, mostly meterorological, information. For this purpose, two types of methods are classically used: the first type estimates a potential evapotranspiration rate from vegetation indices, and adjusts this rate according to water availability derived from either a surface temperature index or a first guess obtained from a rough estimate of the water budget, while the second family of methods relies on the link between the surface temperature and the latent heat flux through the surface energy budget. The latter provides an instantaneous estimate at the time of satellite overpass. In order to compute daily evapotranspiration, one needs an extrapolation algorithm. Since no image is acquired during cloudy conditions, these methods can only be applied during clear sky days. In order to derive seasonal evapotranspiration, one needs an interpolation method. Two combined interpolation/extrapolation methods based on the self preservation of evaporative fraction and the stress factor are compared to reconstruct seasonal evapotranspiration from instantaneous measurements acquired in clear sky conditions. Those measurements are taken from instantaneous latent heat flux from 11 datasets in Southern France and Morocco. Results show that both methods have comparable performances with a clear advantage for the evaporative fraction for datasets with several water stress events. Both interpolation algorithms tend to underestimate evapotranspiration due to the energy limiting conditions that prevail during cloudy days. Taking into account the diurnal variations of the evaporative fraction according to an empirical relationship derived from a previous study improved the performance of the extrapolation algorithm and therefore the retrieval of the seasonal evapotranspiration for all but one datasets

EVASPA (EVApotranspiration Assessment from SPAce) tool: An overview. Procedia

International audienc

Influence of agricultural practices on micrometerological spatial variations at local and regional scales

International audienceSoil-vegetation-atmosphere transfers significantly influence interactions and feedbacks between vegetation and boundary layer, in relation with plant phenology and water status. The current study focused on linking micrometeorological conditions to cultural practices at the local and regional scales (lower than 100km2), over an agricultural region in South Western France. This was achieved considering observation and modelling tools designed for characterising spatial variabilities over land surfaces. These tools were the ASTER high spatial resolution optical remote sensing data, and the SEBAL spatialised surface energy balance model. Surface bidirectional reflectance and brightness temperature were first derived from ASTER data through solar and thermal atmospheric radiative transfer codes, and next used to infer surface radiative properties required for model simulations. Assessing model consistency in terms of air temperature simulations gave satisfactory results when intercomparing against weather station data, although basic model assumptions were not systematically verified in terms of spatial variability. Next, spatialised simulations of evapotranspiration and air temperature were analysed at the regional and local scales, in relation with pedology, land use, and cultural practices. It was shown model estimates were consistent with the considered crops and the related cultural practices. Irrigation appeared as the main factor amongst others (soil, landuse, sowing date) explaining the micrometeorological variability. Although interesting and promising in terms of linking micrometeorological conditions to cultural practices, the results reported here emphasised several difficulties, specially about capturing subfield scale variability and monitoring the considered processes at an appropriate temporal sampling

Monitoring evapotranspiration from remote sensing data for groundwater resources evaluation

International audienc

Monitoring evapotranspiration from remote sensing data for groundwater resources evaluation

International audienc