Prediction of the abiotic degradability of organic compounds in the troposphere

A statistically relevant correlation between the reaction rate coefficient, k _OH, for the OH radical reaction with 161 organic compounds in the gas phase at 300 K, and the corresponding vertical ionisation energies E _i,v, reveals two classes of compounds: aromatics where –log(k _OH/cm³s^-1)3/2E _i,v(eV)–2 and aliphatics where –log(k _OH/cm³s^-1)4/5E _i,v(eV)+3. The prediction of the rate coefficient, k _OH, for the reaction of OH with organic molecules from the above equations has a probability of about 90%. Assuming a global diurnal mean of the OH radical concentration of 5×10⁵ cm³, the upper limit of the tropospheric half-life of organic compounds and their persistence can be estimated.     

Eddy energy dissipation rate and puff diffusion during calms

The paper considers a puff diffusion in its inertial stage when particle separation obeys the laws of the inertial subrange and depends only on eddy energy dissipation rate . The can be determined in the surface layer by the turbulent kinetic energy equation. Similarity equations connect with diffusion measure .A simple analytical model has been deduced to estimate pollutants diffusion during calms.     

Numerical Modeling of the Ston-Slano (Croatia) Aftershock Sequence

The rate of aftershock occurrence after the M6 Ston-Slano (Croatia) earthquake is modeled as the Epidemic Type Aftershock Sequence (ETAS). Increase of the modeled cumulative number of aftershocks with time was fitted to observations by the least-squares criterion using the combined grid-search and Monte-Carlo approach. This enabled not only the estimation of the most probable ETAS parameters, but also the determination of their confidence limits, as well as the estimation of the bias between them. It has been found that the bias is significant for some of the parameter pairs, regardless of the threshold magnitude assumed. Residual analyses revealed that all strong aftershocks (M _L 4.5) occurred during the periods of normal to high aftershock activity. There were two periods of quiescence in the sequence, both of which were followed by a strong aftershock.     

Lysosomal membrane stability and metallothioneins in digestive gland of Mussels (Mytilus galloprovincialis Lam.) as biomarkers in a field study

The lysosomal membrane destabilization and the metallothionein content in the digestive gland cells of mussels (Mytilus galloprovincialis Lam.), collected along the east coast of the North Adriatic (Istrian and Kvarnerine coast, Croatia), were examined over a period of four years (1996–1999). The lysosomal membrane stability, as a biomarker of general stress, showed that the membrane labilization period in mussels from polluted, urban- and industrial-related areas was significantly decreased (p<0.05) when compared to mussels from control, clean sea water sites. In the harbour of Rijeka, the most contaminated site, the lysosomal membrane stability was reduced by more than 70% compared to the control. This method also proved to be a useful biomarker for detection of additional stress caused by short-term hypoxia that occurred once during this study inside the polluted and periodically quite eutrophic Pula Harbour. The concentration of metallothioneins in the mussel digestive gland, as a specific biomarker of exposure to heavy metals, did not reveal significant differences (p<0.05) between sites covered by this study.     

N–PLS regression as empirical downscaling tool in climate change studies

Summary An N–PLS regression technique was tested as an empirical downscaling method. Average monthly near-ground air temperature (t), specific humidity (q), and sea-level pressure (p) fields across Central and Western Europe were used as predictors for average monthly air temperature (T), dew temperature (D), and precipitation amount (P) at 4 locations in Slovenia. The empirical downscaling models (EM) were developed by means of available predictand data from the ARSO archive and predictor data from the NCEP/NCAR reanalysis project, for the period 1951–2002, separately for single months. Using the combination of t and p as predictors, the EM for T explained from 73% to 95% of predictand variability, for D from 74% to 97% of predictand variability, and for P from 31% to 76% of predictand variability. The use of q as an additional predictor did not improve the quality of the EM considerably. Developed EM using p and t as predictors were applied to the results of 5 general circulation models (GCM): CSIRO/Mk2, CCC/CGCM2, UKMO/HadCM3, DOE-NCAR/PCM, and MPI-DMI/ECHAM4-OPYC3. Only the simulations based on SRES A2 and B2 emission scenarios were considered in our calculations. Available mean monthly values of predictors for the period 1951–2100 were used. All the projections of GCM results indicate an increase in T and D and decrease in P in the 21^st century at all 4 locations. The expected range of changes in T, D, and P is wide due to the different response of GCM to identical changes in the atmospheric composition, and represents a source of uncertainty in empirical downscaling results. Another important source of uncertainty in empirical downscaling studies, especially when temperature dependent predictors are used, is the problem of extrapolation. By using the proper mathematical approach for EM development we only reduce a part of the uncertainty related to the quality of empirical models that also strongly depend on the quality of input data and predictor selection. The N–PLS regression seems to be a suitable choice of mathematical method, as the feature selection from a large number of predictor time series is not predictand independent. Finally, any climate change and impact studies for the future are affected by many other uncertainties that we have to be fully aware of, while interpreting their results.