Reducing Urban Pollution Exposure from Road Transport(RUPERT)

This paper presents the preliminary results of a two-year study on reducing urban pollution exposure from road transport (RUPERT). The main aim of this project is to develop a new modelling framework for nitrogen dioxide, carbon monoxide and particulate matter to simulate exposures of different population groups across a city, and to assess the impact of roadside concentrations on these exposures. This will be achieved by modelling the frequency distribution of personal exposures (PEFDs) as a function of urban background and roadside concentrations, under different traffic conditions. The modelling approach combines new and existing models relating traffic and air pollution data, with particular emphasis of the impact of congestion, and the probabilistic modelling framework of personal exposure. Modelling of roadside concentrations consists of two main elements, namely the analysis of concentrations patterns at different roadside sites and of the relationship between traffic conditions and added roadside pollution. Roadside concentrations are predicted using empirically derived relationships; statistical models, novel statistics and artificial neural networks namely feed forward neural network and radial basis neural network. The exposure modelling is carried out by linking two models: the INDAIR model, which is designed to simulate probabilistically diurnal profiles of air pollutant concentrations in a range of microenvironments, and the EXPAIR model, which is designed to simulate population exposure patterns based on population time-activity patterns and a library of micro-environmental concentrations derived from the INDAIR model

Renormalization-Group Improvement of Effective Actions Beyond Summation of Leading Logarithms

Invariance of the effective action under changes of the renormalization scale $\mu$ leads to relations between those (presumably calculated) terms independent of $\mu$ at a given order of perturbation theory and those higher order terms dependent on logarithms of $\mu$. This relationship leads to differential equations for a sequence of functions, the solutions of which give closed form expressions for the sum of all leading logs, next to leading logs and subsequent subleading logarithmic contributions to the effective action. The renormalization group is thus shown to provide information about a model beyond the scale dependence of the model's couplings and masses. This procedure is illustrated using the $\phi_6^3$ model and Yang-Mills theory. In the latter instance, it is also shown by using a modified summation procedure that the $\mu$ dependence of the effective action resides solely in a multiplicative factor of $g^2 (\mu)$ (the running coupling). This approach is also shown to lead to a novel expansion for the running coupling in terms of the one-loop coupling that does not require an order-by-order redefinition of the scale factor $\Lambda_{QCD}$. Finally, logarithmic contributions of the instanton size to the effective action of an SU(2) gauge theory are summed, allowing a determination of the asymptotic dependence on the instanton size $\rho$ as $\rho$ goes to infinity to all orders in the SU(2) coupling constant.Comment: latex2e, 30 pages, 2 eps figures embedded in mansucript. v2 corrects several minor errors in equation

Comparison of different stomatal conductance algorithms for ozone flux modelling

A multiplicative and a semi-mechanistic, BWB-type [Ball, J.T., Woodrow, I.E., Berry, J.A., 1987. A model predicting stomatalconductance and its contribution to the control of photosynthesis under different environmental conditions. In: Biggens, J. (Ed.), Progress in Photosynthesis Research, vol. IV. Martinus Nijhoff, Dordrecht, pp. 221–224.] algorithm for calculating stomatalconductance (gs) at the leaf level have been parameterised for two crop and two tree species to test their use in regional scale ozone deposition modelling. The algorithms were tested against measured, site-specific data for durum wheat, grapevine, beech and birch of different European provenances. A direct comparison of both algorithms showed a similar performance in predicting hourly means and daily time-courses of gs, whereas the multiplicative algorithm outperformed the BWB-type algorithm in modelling seasonal time-courses due to the inclusion of a phenology function. The re-parameterisation of the algorithms for local conditions in order to validate ozone deposition modelling on a European scale reveals the higher input requirements of the BWB-type algorithm as compared to the multiplicative algorithm because of the need of the former to model net photosynthesis (An

Plântulas de soja 'Tracajá' expostas ao ozônio sob condições controladas

The objective of this work was to assess initial growth, biomass production, gas exchange and antioxidative defenses of soybean 'Tracajá' seedlings, cultivated in the Amazonian region, exposed to ozone under controlled conditions. Seeds germinated in pots were placed in two chambers, one with filtered air (AF) and other with filtered air plus 30 ppb of ozone (AF + O 3). At 10 and 20 days after sowing, gas exchange, growth and biomass were measured; at 20 days after sowing, antioxidative defenses (ascorbic acid and superoxide dismutase) were analyzed. Net photosynthesis, stomatal conductance, transpiration rate, height, leaf area and biomass were 16, 27, 11, 22, 29 and 18% smaller, respectively, in AF + O3 at 10 days after sowing. At 20 days after sowing, besides this parameters, root length, stem diameter and root:shoot ratio were 10, 15 and 12% smaller, respectively, although ascorbic acid concentrations and superoxide dismutase activity increased. Soybean 'Tracajá' seedlings have low tolerance to concentration of 30 ppb of ozone

Scaling ozone responses of forest trees to the ecosystem level in a changing climate

Many uncertainties remain regarding how climate change will alter the structure and function of forest ecosystems. At the Aspen FACE experiment in northern Wisconsin, we are attempting to understand how an aspen/birch/maple forest ecosystem responds to long-term exposure to elevated carbon dioxide (CO 2 ) and ozone (O 3 ), alone and in combination, from establishment onward. We examine how O 3 affects the flow of carbon through the ecosystem from the leaf level through to the roots and into the soil micro-organisms in present and future atmospheric CO 2 conditions. We provide evidence of adverse effects of O 3 , with or without co-occurring elevated CO 2 , that cascade through the entire ecosystem impacting complex trophic interactions and food webs on all three species in the study: trembling aspen ( Populus tremuloides Michx . ), paper birch ( Betula papyrifera Marsh), and sugar maple ( Acer saccharum Marsh). Interestingly, the negative effect of O 3 on the growth of sugar maple did not become evident until 3 years into the study. The negative effect of O 3 effect was most noticeable on paper birch trees growing under elevated CO 2 . Our results demonstrate the importance of long-term studies to detect subtle effects of atmospheric change and of the need for studies of interacting stresses whose responses could not be predicted by studies of single factors. In biologically complex forest ecosystems, effects at one scale can be very different from those at another scale. For scaling purposes, then, linking process with canopy level models is essential if O 3 impacts are to be accurately predicted. Finally, we describe how outputs from our long-term multispecies Aspen FACE experiment are being used to develop simple, coupled models to estimate productivity gain/loss from changing O 3 .Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/72464/1/j.1365-3040.2005.01362.x.pd

Plant Species Sensitivity Distributions for ozone exposure

Contains fulltext : 111393.pdf (preprint version ) (Open Access