Modelling spatio-temporal air pollution data from a mobile monitoring station

ABSTRACT

Environmental data is typically indexed in space and time. This work deals with modelling spatio-temporal air quality data, when multiple measurements are available for each space-time point. Typically this situation arises when different measurements referring to several response variables are observed in each space-time point, for example, different pollutants or size resolved data on particular matter. Nonetheless, such a kind of data also arises when using a mobile monitoring station moving along a path for a certain period of time. In this case, each spatio-temporal point has a number of measurements referring to the response variable observed several times over different locations in a close neighbourhood of the space-time point. We deal with this type of data within a hierarchical Bayesian framework, in which observed measurements are modelled in the first stage of the hierarchy, while the unobserved spatio-temporal process is considered in the following stages. The final model is very flexible and includes autoregressive terms in time, different structures for the variance-covariance matrix of the errors, and can manage covariates available at different space-time resolutions. This approach is motivated by the availability of data on urban pollution dynamics: fast measures of gases and size resolved particulate matter have been collected using an Optical Particle Counter located on a cabin of a public conveyance that moves on a monorail on a line transect of a town. Urban microclimate information is also available and included in the model. Simulation studies are conducted to evaluate the performance of the proposed model over existing alternatives that do not model data over the first stage of the hierarchy.     

Performance of distance sampling estimators: a simulation study for designs based on footpaths

ABSTRACT

Recently, distance sampling emerged as an advantageous technique to estimate the abundance of many animal populations, including ungulates. Its basic design involves the random selection of several samplers (transects or points) within the population range, and a Horvitz–Thompson-like estimator is then applied to estimate the population abundance while correcting for animal detectability. Ensuring even coverage probability is essential for subsequent inference on the population size, but it may not be achievable because of limited access to parts of the population range. Moreover, in several environmental conditions, a random selection of samplers may induce very high survey costs because it does not minimize the displacement time of the observer(s) between successive samplers. We thus tested whether two-stage designs – based on the random selection of points and then of nearby samplers – could be more cost-effective, for a given population size and when even area coverage cannot be guaranteed. Here, we further extend our analyses to assess the performance of two-stage designs under varying animal densities.     

Initial agronomic performances of Mediterranean xerophytes in simulated dry green roofs

The growing desire to make the urban environment more sustainable from an ecological point of view has stimulated research on the architectural and agronomic aspects of green roofs. The practical realisation of green roofs, is however limited by economic and ecological issues. More specifically, water availability is the most limiting factor, and is likely to be ever more so in the future in the light of climate change. For this reason, we evaluated the agronomic performance of several xerophytes in a simulated dry green roof. Seeds of 20 species were collected in typically dry habitats (abandoned quarries, rocky soils, dunes, etc.) and studied in the laboratory for germination ecology. In cases of strong dormancy, methods were tested to stimulate germination and their germination ecology was studied. The resulting seedlings were transplanted in spring 2008 in two green roof types that differ in substrate depth (150 and 200 mm) made up of lapil, pumice, zeolites and peat, resting on a drainage layer of hydroperlite. Temperature and humidity in the substrate and drainage layer were measured during the whole test period. Survival of the seedlings in both substrate depths was almost 100%, favoured by a rainy spring. Most of the tested species showed an excellent performance during the hot and dry summer months in terms of survival rates, growth, and vegetation cover dynamics, notwithstanding the difficult ecological conditions (temperatures around 50°C; hydric potential Ψ -15 bars). Furthermore, most of the species had a long flowering stage in the first year of growth. Plants in the green roof with the deeper substrate depth produced, for most of the tested taxa, a significantly higher vegetation cover and growth compared to when they were placed in the 150 mm substrate. The results of this study show that some Mediterranean xerophytes have biological characteristics suitable for their use in dry green roofs, although an irrigation system for emergency use seems advisable. To conclude, further research should focus on long term evaluation of green roof vegetation in terms of plant survival and flowering dynamics.     

A mind in a disk: the attribution of mental states to technological systems

This paper reports a study about the role of different variables in the process of attributing mental states to technological systems, variables such as the number of figural elements displayed in the system and the personality traits of the subjects interacting with the systems. In an experiment, participants were interacting with a computer on whose screen several disks of various sizes and colours were blinking at different rates. Each time a disk reappeared on the screen its position was randomly varied. As in a videogame, participants had to click on the disks to increase their score. The results showed that, even in the case of such a simple system, subjects believed that the figural elements they were interacting with had some form of mental states, although their confidence in these beliefs varied in the different experimental conditions. The confidence level of the attributions, in fact, was not the same for all the different mental states considered, and it varied also both with the number of elements being displayed as well as with some personality traits of the subjects.     

A mortality model based on a mixture distribution function

A new mortality model based on a mixture distribution function is proposed. We mix a half-normal distribution with a generalization of the skew-normal distribution. As a result, we get a six-parameter distribution function that has a good fit with a wide variety of mortality patterns. This mixture model is fitted to several mortality data schedules and compared with the Siler (five-parameter) and Heligman–Pollard (eight-parameter) models. Our proposal serves as a convenient compromise between the Heligman–Pollard model (which ensures a good fit with data but is often overparameterized) and the Siler model (which is more compact but fails to capture ‘accident humps’).     

Twenty-Five Years of Materialism: Do the US and Europe Diverge?

Using data from the World Values Survey and the European Values Study, we compare the trends of materialism over the last quarter of century among the US and six major European countries: France, Spain, Italy, Germany, Great Britain and Sweden. We use the definition of materialism adopted by positive psychologists. We find that the trends in Europe and in the US diverged. In the US materialism increased, while in Europe it decreased. However, some mixed patterns arise. In particular, Great Britain, Spain and Sweden showed some symptoms of an increase of materialistic values, although they were far less pronounced compared to the American ones. As far as the levels of materialism are concerned, it is interesting that, according to most of our measures, Americans were relatively less materialistic at the beginning of our period of observation. Yet, towards the end of the period they scored very high in the ranking of materialism in our sample of countries.     

Bayesian non-parametric inference for species variety with a two-parameter Poisson–Dirichlet process prior

Summary.  A Bayesian non-parametric methodology has been recently proposed to deal with the issue of prediction within species sampling problems. Such problems concern the evaluation, conditional on a sample of size n , of the species variety featured by an additional sample of size m . Genomic applications pose the additional challenge of having to deal with large values of both n and m . In such a case the computation of the Bayesian non-parametric estimators is cumbersome and prevents their implementation. We focus on the two-parameter Poisson–Dirichlet model and provide completely explicit expressions for the corresponding estimators, which can be easily evaluated for any sizes of n and m . We also study the asymptotic behaviour of the number of new species conditionally on the observed sample: such an asymptotic result, combined with a suitable simulation scheme, allows us to derive asymptotic highest posterior density intervals for the estimates of interest. Finally, we illustrate the implementation of the proposed methodology by the analysis of five expressed sequence tags data sets.     

Fragile scenes,fractured communities: Tunisian Metal and sceneness

The paper proposes a reshaping of musical and cultural scene as a framework for the study of youth cultures. Developed in the ambit of post-subcultural theories, scene well represents the forces and flaws of such a category: high dynamism and ethnographic richness on one side; vagueness on the other. In order to reduce such vagueness, I conceptualise sceneness, intended as the substance of scenes, their density in networking and infrastructures. I use Arjun Appadurai’s concepts of locality and neighbourhoods to signify, respectively, sceneness and the actual scenes: in this way I redefine scene as a fragile construct that needs to be ritually revived, and that can work as a context for the development of new meanings and social groups. This implies conflict as a central element of scenes, one which can lead them to disequilibrium and disappearance. Such a redefinition is helpful for analysing fragile scenes which struggle to exist in troubled contexts, such as poor and hostile social environments. I provide, as an example, my ethnographic research on Metal in Tunisia. Caught between idealised images of community and an actual community which was conflictual and ‘fractured’, the Tunisian Metal scene lives a precarious existence threatened by material constraints and cultural marginality.     

Leaving your mamma: why so late in Italy?

In Italy, young adults tend to postpone their transition to adulthood and live with their parents until very late compared with other countries. A dynamic discrete choice model is proposed in which agents choose residential arrangements, together with labor supply and marital status, conditional on the economic and institutional framework and on other agents’ choices. The model is structurally estimated with the Simulated Method of Moments for non-student high-school graduate males and then used to assess, through a variety of counterfactual experiments, the relative importance of factors that are claimed to influence the choice to leave home in the existing literature: labor market conditions, parental resources, housing market conditions and social interaction. Results suggest that Italians choose to remain with their parents due to a combination of poor labor market conditions and high housing costs. The relatively high income of parents could contribute to the patterns observed by acting as an insurance against unemployment. Finally, estimates indicate that individuals tend to conform to a social norm, especially in the South of the country were family ties and the costs in terms of utility from not complying with expected behaviors appear to be stronger.

     

Estimates of Household Consumption Expenditure at Provincial Level in Italy by Using Small Area Estimation Methods: “Real” Comparisons Using Purchasing Power Parities

Household consumption expenditure represents a crucial measure to be used for assessing individuals’ material living conditions and well-being. Indeed, the analysis of household conditions can provide policy makers with a clear picture of the economic and social situation of the area in which they are operating. However, official sample surveys which are generally used for this purpose, such as the Household Budget Survey in Italy carried out by the National Institute of Statistics, do not allow for reliable disaggregated estimates thus hindering appropriate and effective planning and evaluation of political interventions at local level. By referring to the 2012 Italian Household Budget Survey, this paper aims at obtaining reliable provincial estimates of household consumption expenditure in Italy. We use Small Area Estimation methods and we adjust the estimates for spatial differences in price levels by computing and using sub-national Purchasing Power Parities, thus obtaining “real” estimates of consumption expenditure to be used for intra-national comparisons.