Evaluation and modelling of the spatial and temporal variability of particulate matter in urban areas

This thesis contains three subject areas concerning particulate matter in urban area air quality: 1) Analysis of the measured concentrations of particulate matter mass concentrations in the Helsinki Metropolitan Area (HMA) in different locations in relation to traffic sources, and at different times of year and day. 2) The evolution of traffic exhaust originated particulate matter number concentrations and sizes in local street scale are studied by a combination of a dispersion model and an aerosol process model. 3) Some situations of high particulate matter concentrations are analysed with regard to their meteorological origins, especially temperature inversion situations, in the HMA and three other European cities. The prediction of the occurrence of meteorological conditions conducive to elevated particulate matter concentrations in the studied cities is examined. The performance of current numerical weather forecasting models in the case of air pollution episode situations is considered. The study of the ambient measurements revealed clear diurnal variation of the PM10 concentrations in the HMA measurement sites, irrespective of the year and the season of the year. The diurnal variation of local vehicular traffic flows seemed to have no substantial correlation with the PM2.5 concentrations, indicating that the PM10 concentrations were originated mainly from local vehicular traffic (direct emissions and suspension), while the PM2.5 concentrations were mostly of regionally and long-range transported origin. The modelling study of traffic exhaust dispersion and transformation showed that the number concentrations of particles originating from street traffic exhaust undergo a substantial change during the first tens of seconds after being emitted from the vehicle tailpipe. The dilution process was shown to dominate total number concentrations. Minimal effect of both condensation and coagulation was seen in the Aitken mode number concentrations. The included air pollution episodes were chosen on the basis of occurrence in either winter or spring, and having at least partly local origin. In the HMA, air pollution episodes were shown to be linked to predominantly stable atmospheric conditions with high atmospheric pressure and low wind speeds in conjunction with relatively low ambient temperatures. For the other European cities studied, the best meteorological predictors for the elevated concentrations of PM10 were shown to be temporal (hourly) evolutions of temperature inversions, stable atmospheric stability and in some cases, wind speed. Concerning the weather prediction during particulate matter related air pollution episodes, the use of the studied models were found to overpredict pollutant dispersion, leading to underprediction of pollutant concentration levels.

Role of an RNA polymerase interacting protein, MsRbpA, from Mycobacterium smegmatis in phenotypic tolerance to rifampicin

Rifampicin and its derivatives are at the forefront of the current standard chemotherapeutic regimen for active tuberculosis; they act by inhibiting the transcription activity of prokaryotic RNA polymerase. Rifampicin is believed to interact with the beta subunit of RNA polymerase. However, it has been observed that protein-protein interactions with RNA polymerase core enzyme lead to its reduced susceptibility to rifampicin. This mechanism became more diversified with the discovery of RbpA, a novel RNA polymerase-binding protein, in Streptomyces coelicolor that could mitigate the effect of rifampicin on RNA polymerase activity. MsRbpA is a homologue of RbpA in Mycobacterium smegmatis. On deciphering the role of MsRbpA in M. smegmatis we found that it interacts with RNA polymerase and increases the rifampicin tolerance levels, both in vitro and in vivo. It interacts with the beta subunit of RNA polymerase. However, it was found to be incapable of rescuing rifampicin-resistant RNA polymerases in the presence of rifampicin at the respective IC50.

Dynamics of ''internal'' interannual variability of the Indian summer monsoon in a GCM

1] The poor predictability of the Indian summer monsoon ( ISM) appears to be due to the fact that a large fraction of interannual variability (IAV) is governed by unpredictable "internal'' low frequency variations. Mechanisms responsible for the internal IAV of the monsoon have not been clearly identified. Here, an attempt has been made to gain insight regarding the origin of internal IAV of the seasonal ( June - September, JJAS) mean rainfall from "internal'' IAV of the ISM simulated by an atmospheric general circulation model (AGCM) driven by fixed annual cycle of sea surface temperature (SST). The underlying hypothesis that monsoon ISOs are responsible for internal IAV of the ISM is tested. The spatial and temporal characteristics of simulated summer intraseasonal oscillations ( ISOs) are found to be in good agreement with those observed. A long integration with the AGCM forced with observed SST, shows that ISO activity over the Asian monsoon region is not modulated by the observed SST variations. The internal IAV of ISM, therefore, appears to be decoupled from external IAV. Hence, insight gained from this study may be useful in understanding the observed internal IAV of ISM. The spatial structure of the ISOs has a significant projection on the spatial structure of the seasonal mean and a common spatial mode governs both intraseasonal and interannual variability. Statistical average of ISO anomalies over the season ( seasonal ISO bias) strengthens or weakens the seasonal mean. It is shown that interannual anomalies of seasonal mean are closely related to the seasonal mean of intraseasonal anomalies and explain about 50% of the IAV of the seasonal mean. The seasonal mean ISO bias arises partly due to the broad-band nature of the ISO spectrum allowing the time series to be aperiodic over the season and partly due to a non-linear process where the amplitude of ISO activity is proportional to the seasonal bias of ISO anomalies. The later relation is a manifestation of the binomial character of rainfall time series. The remaining 50% of the IAV may arise due to land-surface processes, interaction between high frequency variability and ISOs, etc.

Not in their genes: phenotypic flexibility, behavioural traditions and cultural evolution in wild bonnet macaques

Phenotypic flexibility, or the within-genotype, context-dependent, variation in behaviour expressed by single reproductively mature individuals during their lifetimes, often impart a selective advantage to organisms and profoundly influence their survival and reproduction. Another phenomenon apparently not under direct genetic control is behavioural inheritance whereby higher animals are able to acquire information from the behaviour of others by social learning, and, through their own modified behaviour, transmit such information between individuals and across generations. Behavioural information transfer of this nature thus represents another form of inheritance that operates in many animals in tandem with the more basic genetic system. This paper examines the impact that phenotypic flexibility, behavioural inheritance and socially transmitted cultural traditions may have in shaping the structure and dynamics of a primate society--that of the bonnet macaque (Macaca radiata), a primate species endemic to peninsular India. Three principal issues are considered: the role of phenotypic flexibility in shaping social behaviour, the occurrence of individual behavioural traits leading to the establishment of social traditions, and the appearance of cultural evolution amidst such social traditions. Although more prolonged observations are required, these initial findings suggest that phenotypic plasticity, behavioural inheritance and cultural traditions may be much more widespread among primates than have previously been assumed but may have escaped attention due to a preoccupation with genetic inheritance in zoological thinking.

Applicability of Statistical Learning Algorithms for Spatial Variability of Rock Depth

Two algorithms are outlined, each of which has interesting features for modeling of spatial variability of rock depth. In this paper, reduced level of rock at Bangalore, India, is arrived from the 652 boreholes data in the area covering 220 sqa <.km. Support vector machine (SVM) and relevance vector machine (RVM) have been utilized to predict the reduced level of rock in the subsurface of Bangalore and to study the spatial variability of the rock depth. The support vector machine (SVM) that is firmly based on the theory of statistical learning theory uses regression technique by introducing epsilon-insensitive loss function has been adopted. RVM is a probabilistic model similar to the widespread SVM, but where the training takes place in a Bayesian framework. Prediction results show the ability of learning machine to build accurate models for spatial variability of rock depth with strong predictive capabilities. The paper also highlights the capability ofRVM over the SVM model.

Using IRAP markers for analysis of genetic variability in populations of resource and rare species of plants

Species specific LTR retrotransposons were first cloned in five rare relic species of drug plants located in the Perm’ region. Sequences of LTR retrotransposons were used for PCR analysis based on amplification of repeated sequences from LTR or other sites of retrotransposons (IRAP). Genetic diversity was studied in six populations of rare relic species of plants Adonis vernalis L. by means of the IRAP method; 125 polymorphic IRAP markers were analyzed. Parameters for DNA polymorphism and genetic diversity of A. vernalis populations were determined.

Using IRAP markers for analysis of genetic variability in populations of resource and rare species of plants

Species specific LTR retrotransposons were first cloned in five rare relic species of drug plants located in the Perm’ region. Sequences of LTR retrotransposons were used for PCR analysis based on amplification of repeated sequences from LTR or other sites of retrotransposons (IRAP). Genetic diversity was studied in six populations of rare relic species of plants Adonis vernalis L. by means of the IRAP method; 125 polymorphic IRAP markers were analyzed. Parameters for DNA polymorphism and genetic diversity of A. vernalis populations were determined.

An efficient reduction algorithm for computation of interconnect delay variability for statistical timing analysis in clock tree planning

In this paper, we propose a novel and efficient algorithm for modelling sub-65 nm clock interconnect-networks in the presence of process variation. We develop a method for delay analysis of interconnects considering the impact of Gaussian metal process variations. The resistance and capacitance of a distributed RC line are expressed as correlated Gaussian random variables which are then used to compute the standard deviation of delay Probability Distribution Function (PDF) at all nodes in the interconnect network. Main objective is to find delay PDF at a cheaper cost. Convergence of this approach is in probability distribution but not in mean of delay. We validate our approach against SPICE based Monte Carlo simulations while the current method entails significantly lower computational cost.

Intraspecific variation in brain size and architecture : population divergence and phenotypic plasticity

Brain size and architecture exhibit great evolutionary and ontogenetic variation. Yet, studies on population variation (within a single species) in brain size and architecture, or in brain plasticity induced by ecologically relevant biotic factors have been largely overlooked. Here, I address the following questions: (i) do locally adapted populations differ in brain size and architecture, (ii) can the biotic environment induce brain plasticity, and (iii) do locally adapted populations differ in levels of brain plasticity? In the first two chapters I report large variation in both absolute and relative brain size, as well as in the relative sizes of brain parts, among divergent nine-spined stickleback (Pungitius pungitius) populations. Some traits show habitat-dependent divergence, implying natural selection being responsible for the observed patterns. Namely, marine sticklebacks have relatively larger bulbi olfactorii (chemosensory centre) and telencephala (involved in learning) than pond sticklebacks. Further, I demonstrate the importance of common garden studies in drawing firm evolutionary conclusions. In the following three chapters I show how the social environment and perceived predation risk shapes brain development. In common frog (Rana temporaria) tadpoles, I demonstrate that under the highest per capita predation risk, tadpoles develop smaller brains than in less risky situations, while high tadpole density results in enlarged tectum opticum (visual brain centre). Visual contact with conspecifics induces enlarged tecta optica in nine-spined sticklebacks, whereas when only olfactory cues from conspecifics are available, bulbus olfactorius become enlarged.Perceived predation risk results in smaller hypothalami (complex function) in sticklebacks. Further, group-living has a negative effect on relative brain size in the competition-adapted pond sticklebacks, but not in the predation-adapted marine sticklebacks. Perceived predation risk induces enlargement of bulbus olfactorius in pond sticklebacks, but not in marine sticklebacks who have larger bulbi olfactorii than pond fish regardless of predation. In sum, my studies demonstrate how applying a microevolutionary approach can help us to understand the enormous variation observed in the brains of wild animals a point-of-view which I high-light in the closing review chapter of my thesis.

Local variability and base sequence effects in DNA crystal structures.

The importance and usefulness of local doublet parameters in understanding sequence dependent effects has been described for A- and B-DNA oligonucleotide crystal structures. Each of the two sets of local parameters described by us in the NUPARM algorithm, namely the local doublet parameters, calculated with reference to the mean z-axis, and the local helical parameters, calculated with reference to the local helix axis, is sufficient to describe the oligonucleotide structures, with the local helical parameters giving a slightly magnified picture of the variations in the structures. The values of local doublet parameters calculated by NUPARM algorithm are similar to those calculated by NEWHELIX90 program, only if the oligonucleotide fragment is not too distorted. The mean values obtained using all the available data for B-DNA crystals are not significantly different from those obtained when a limited data set is used, consisting only of structures with a data resolution of better than 2.4 A and without any bound drug molecule. Thus the variation observed in the oligonucleotide crystals appears to be independent of the quality of their crystallinity. No strong correlation is seen between any pair of local doublet parameters but the local helical parameters are interrelated by geometric relationships. An interesting feature that emerges from this analysis is that the local rise along the z-axis is highly correlated with the difference in the buckle values of the two basepairs in the doublet, as suggested earlier for the dodecamer structures (Bansal and Bhattacharyya, in Structure & Methods: DNA & RNA, Vol. 3 (Eds., R.H. Sarma and M.H. Sarma), pp. 139-153 (1990)). In fact the local rise values become almost constant for both A- and B-forms, if a correction is applied for the buckling of the basepairs. In B-DNA the AA, AT, TA and GA basepair sequences generally have a smaller local rise (3.25 A) compared to the other sequences (3.4 A) and this seems to be an intrinsic feature of basepair stacking interaction and not related to any other local doublet parameter. The roll angles in B-DNA oligonucleotides have small values (less than +/- 8 degrees), while mean local twist varies from 24 degrees to 45 degrees. The CA/TG doublet sequences show two types of preferred geometries, one with positive roll, small positive slide and reduced twist and another with negative roll, large positive slide and increased twist.(ABSTRACT TRUNCATED AT 400 WORDS)

Conformational Variability in Modified Nucleosides. Crystal and Molecular Structure of 2',3'-O-Isopropylidene Inosine

The crystal structure of 2',3'-O-isopropylidene inosine shows a number of interesting features. The four independent molecules in the asymmetric unit exhibit significant conformational variations. Ribose puckers fall in the O(4')-exo region, unfavourable in unsubstituted nucleosides. Hypoxanthine bases show base-pairing (I.I) in a manner analogous to the guanine self pairs (G.G) in 2',3'-O-isopropylidene guanosine but with a C(2)-H…O(6) hydrogen bond instead of N(2)-H…O(6).

Aperiodic Variability in the Cane-Zebiak Model: A Diagnostic Study

The finite predictability of the coupled ocean-atmosphere system is determined by its aperiodic variability. To gain insight regarding the predictability of such a system, a series of diagnostic studies has been carried out to investigate the role of convergence feedback in producing the aperiodic behavior of the standard version of the Cane-Zebiak model. In this model, an increase in sea surface temperature (SST) increases atmospheric heating by enhancing local evaporation (SST anomaly feedback) and low-level convergence (convergence feedback). The convergence feedback is a nonlinear function of the background mean convergence field. For the set of standard parameters used in the model, it is shown that the convergence feedback contributes importantly to the aperiodic behaviour of the model. As the strength of the convergence feedback is increased from zero to its standard value, the model variability goes from a periodic regime to an aperiodic regime through a broadening of the frequency spectrum around the basic periodicity of about 4 years. Examination of the forcing associated with the convergence feedback reveals that it is intermittent, with relatively large amplitude only during 2 or 3 months in the early part of the calendar year. This seasonality in the efficiency of the convergence feedback is related to the strong seasonality of the mean convergence over the eastern Pacific. It is shown that if the mean convergence field is fixed at its March value, aperiodic behavior is produced even in the absence of annual cycles in the other mean fields. On the, other hand, if the mean convergence field is fixed at its September value, the coupled model evolution remains close to periodic, even in the presence of the annual cycle in the other fields. The role of convergence feedback on the aperiodic variability of the model for other parameter regimes is also examined. It is shown that a range exists in the strength of the SST anomaly feedback for which the model variability is aperiodic even without the convergence feedback. It appears that in the absence of convergence feedback, enhancement of the strength of the air-sea coupling in the model through other physical processes also results in aperiodicity in the model.

Mechanisms of variability and predictability of the tropical coupled ocean-atmosphere system

A conceptual model is proposed to explain the observed aperiodicity in the short term climate fluctuations of the tropical coupled ocean-atmosphere system. This is based on the evidence presented here that the tropical coupled ocean-atmosphere system sustains a low frequency inter-annual mode and a host of higher frequency intra-seasonal unstable modes. At long wavelengths, the low frequency mode is dominant while at short wavelengths, the high frequency modes are dominant resulting in the co-existence of a long wave low frequency mode with some short wave intra-seasonal modes in the tropical coupled system. It is argued that due to its long wavelength, the low frequency mode would behave like a linear oscillator while the higher frequency short wave modes would be nonlinear. The conceptual model envisages that an interaction between the low frequency linear oscillator and the high frequency nonlinear oscillations results in the observed aperiodicity of the tropical coupled system. This is illustrated by representing the higher frequency intra-seasonal oscillations by a nonlinear low order model which is then coupled to a linear oscillator with a periodicity of four years. The physical mechanism resulting in the aperiodicity in the low frequency oscillations and implications of these results on the predictability of the coupled system are discussed.

Low-frequency variability and the galactic distribution of electron-density fluctuation

A sample of 96 compact flat-spectrum extragalactic sources, spread evenly over all galactic latitudes, has been studied at 327 MHz for variability over a time interval of about 15 yr. The variability shows a dependence on galactic latitude being less both at low and high latitudes and peaking around absolute value of b approximately 15-degrees. The latitude dependence is surprisingly similar in both the galactic centre and anticentre directions. Assuming various single and multi-component distributions for the ionized, irregular interstellar plasma, we have tried to generate the observed dependence using a semi-qualitative treatment of refractive interstellar scintillations. We find that it is difficult to fit our data with any single or double component cylindrical distribution. Our data suggests that the observed variability could be influenced by the spiral structure of our Galaxy.