Spatio-temporal surface soil heat flux estimates from satellite data: results for the AMMA experiment at the Fakara (Niger) supersite

This paper describes a method that employs Earth Observation (EO) data to calculate spatiotemporal estimates of soil heat flux, G, using a physically-based method (the Analytical Method). The method involves a harmonic analysis of land surface temperature (LST) data. It also requires an estimate of near-surface soil thermal inertia; this property depends on soil textural composition and varies as a function of soil moisture content. The EO data needed to drive the model equations, and the ground-based data required to provide verification of the method, were obtained over the Fakara domain within the African Monsoon Multidisciplinary Analysis (AMMA) program. LST estimates (3 km × 3 km, one image 15 min−1) were derived from MSG-SEVIRI data. Soil moisture estimates were obtained from ENVISAT-ASAR data, while estimates of leaf area index, LAI, (to calculate the effect of the canopy on G, largely due to radiation extinction) were obtained from SPOT-HRV images. The variation of these variables over the Fakara domain, and implications for values of G derived from them, were discussed. Results showed that this method provides reliable large-scale spatiotemporal estimates of G. Variations in G could largely be explained by the variability in the model input variables. Furthermore, it was shown that this method is relatively insensitive to model parameters related to the vegetation or soil texture. However, the strong sensitivity of thermal inertia to soil moisture content at low values of relative saturation (<0.2) means that in arid or semi-arid climates accurate estimates of surface soil moisture content are of utmost importance, if reliable estimates of G are to be obtained. This method has the potential to improve large-scale evaporation estimates, to aid land surface model prediction and to advance research that aims to explain failure in energy balance closure of meteorological field studies.

Investigating the origin of PM2.5 in Baltimore using highly time-resolved organic molecular markers measured during the Baltimore PM-supersite

The detailed organic composition of atmospheric fine particles with an aerodynamic diameter smaller than or equal to 2.5 micrometers (PM2.5) is an integral part of the knowledge needed in order to fully characterize its sources and transformation in the environment. For the study presented here, samples were collected at 3-hour intervals. This high time resolution allows gaining unique insights on the influence of short- and long-range transport phenomena, and dynamic atmospheric processes. A specially designed sequential sampler was deployed at the 2002-2003 Baltimore PM-Supersite to collect PM2.5 samples at a 3-hourly resolution for extended periods of consecutive days, during both summer and winter seasons. Established solvent-extraction and GC-MS techniques were used to extract and analyze the organic compounds in 119 samples from each season. Over 100 individual compounds were quantified in each sample. For primary organics, averaging the diurnal ambient concentrations over the sampled periods revealed ambient patterns that relate to diurnal emission patterns of major source classes. Several short-term releases of pollutants from local sources were detected, and local meteorological data was used to pinpoint possible source regions. Biogenic secondary organic compounds were detected as well, and possible mechanisms of formation were evaluated. The relationships between the observed continuous variations of the concentrations of selected organic markers and both the on-site meteorological measurements conducted parallel to the PM2.5 sampling, and the synoptic patterns of weather and wind conditions were also examined. Several one-to-two days episodes were identified from the sequential variation of the concentration observed for specific marker compounds and markers ratios. The influence of the meteorological events on the concentrations of the organic compounds during selected episodes was discussed. It was observed that during the summer, under conditions of pervasive influence of air masses originated from the west/northwest, some organic species displayed characteristics consistent with the measured PM2.5 being strongly influenced by the aged nature of these long-traveling background parcels. During the winter, intrusions from more regional air masses originating from the south and the southwest were more important.

Investigating the origin of PM2.5 in Baltimore using highly time-resolved organic molecular markers measured during the Baltimore PM-supersite

The detailed organic composition of atmospheric fine particles with an aerodynamic diameter smaller than or equal to 2.5 micrometers (PM 2.5) is an integral part of the knowledge needed in order to fully characterize its sources and transformation in the environment. For the study presented here, samples were collected at 3-hour intervals. This high time resolution allows gaining unique insights on the influence of short- and long-range transport phenomena, and dynamic atmospheric processes. A specially designed sequential sampler was deployed at the 2002-2003 Baltimore PM Supersite to collect PM2.5 samples at a 3-hourly resolution for extended periods of consecutive days, during both summer and winter seasons. Established solvent-extraction and GC-MS techniques were used to extract and analyze the organic compounds in 119 samples from each season. Over 100 individual compounds were quantified in each sample. For primary organics, averaging the diurnal ambient concentrations over the sampled periods revealed ambient patterns that relate to diurnal emission patterns of major source classes. Several short-term releases of pollutants from local sources were detected, and local meteorological data was used to pinpoint possible source regions. Biogenic secondary organic compounds were detected as well, and possible mechanisms of formation were evaluated. The relationships between the observed continuous variations of the concentrations of selected organic markers and both the on-site meteorological measurements conducted parallel to the PM2.5 sampling, and the synoptic patterns of weather and wind conditions were also examined. Several one-to-two days episodes were identified from the sequential variation of the concentration observed for specific marker compounds and markers ratios. The influence of the meteorological events on the concentrations of the organic compounds during selected episodes was discussed. It was observed that during the summer, under conditions of pervasive influence of air masses originated from the west/northwest, some organic species displayed characteristics consistent with the measured PM2.5 being strongly influenced by the aged nature of these long-traveling background parcels. During the winter, intrusions from more regional air masses originating from the south and the southwest were more important.

Structural analysis of dihydrofolate reductases enables rationalization of antifolate binding affinities and suggests repurposing possibilities

Antifolates are competitive inhibitors of dihydrofolate reductase ( DHFR), a conserved enzyme that is central to metabolism and widely targeted in pathogenic diseases, cancer and autoimmune disorders. Although most clinically used antifolates are known to be target specific, some display a fair degree of cross-reactivity with DHFRs from other species. A method that enables identification of determinants of affinity and specificity in target DHFRs from different species and provides guidelines for the design of antifolates is currently lacking. To address this, we first captured the potential druggable space of a DHFR in a substructure called the `supersite' and classified supersites of DHFRs from 56 species into 16 `site-types' based on pairwise structural similarity. Analysis of supersites across these site-types revealed that DHFRs exhibit varying extents of dissimilarity at structurally equivalent positions in and around the binding site. We were able to explain the pattern of affinities towards chemically diverse antifolates exhibited by DHFRs of different site-types based on these structural differences. We then generated an antifolate-DHFR network by mapping known high-affinity antifolates to their respective supersites and used this to identify antifolates that can be repurposed based on similarity between supersites or antifolates. Thus, we identified 177 human-specific and 458 pathogen-specific antifolates, a large number of which are supported by available experimental data. Thus, in the light of the clinical importance of DHFR, we present a novel approach to identifying differences in the druggable space of DHFRs that can be utilized for rational design of antifolates.