Empirics of the international inequality in CO2 emissions intensity: explanatory factors according to complementary decomposition methodologies

This paper analyses the international inequalities in CO2 emissions intensity for the period 1971–2009 and assesses explanatory factors. Multiplicative, group and additive methodologies of inequality decomposition are employed. The first allows us to clarify the separated role of the carbonisation index and the energy intensity in the pattern observed for inequalities in CO2 intensities; the second allows us to understand the role of regional groups; and the third allows us to investigate the role of different fossil energy sources (coal, oil and gas). The results show that, first, the reduction in global emissions intensity has coincided with a significant reduction in international inequality. Second, the bulk of this inequality and its reduction are attributed to differences between the groups of countries considered. Third, coal is the main energy source explaining these inequalities, although the growth in the relative contribution of gas is also remarkable. Fourth, the bulk of inequalities between countries and its decline are explained by differences in energy intensities, although there are significant differences in the patterns demonstrated by different groups of countries. JEL codes: D39; Q43; Q56. Key words: CO2 international distribution, inequality decomposition, CO2 emissions intensity

Proposal of three thermodynamic variables to discriminate between storms associated with hail and storms with intense rainfall in Catalonia (Proposta de tres variables termodinàmiques per discriminar entre tempestes amb pedregades i tempestes amb pluges intenses)

Between late spring and early fall, the development of storms is common in Catalonia. Despite the fact that they usually produce heavy showers of short duration, they can also involve severe weather with ice pellets or hail. While the latter usually affect inland regions, and there are numerous publications on these cases; the analysis of events affecting the coast and causing damage to public and private properties is not so well developed. The aim of this study is to provide additional thermodynamic indicators that help differentiate storms with hail from storms without hail, considering cases that have affected various regions of Catalonia, mainly coastal areas. The aim is to give more information to improve prognosis and the ability to detail information in these situations. The procedure developed involved the study of several episodes of heavy rainfall and hail that hit Catalonia during the 2003-2009 period, mainly in the province of Girona, and validated the proposal during the campaign of late summer and fall of 2009, as well as 2012. For each case, several variables related to temperature, humidity and wind were analyzed at different levels of the atmosphere, while the information provided by the radio sounding in Barcelona was also taken into account. From this study, it can be concluded that the temperature difference between 500 hPa and 850 hPa, the humidity in the lower layers of the atmosphere and the LI index are good indicators for the detection of storms with associated hail.

Scale effect in hazard assessment - application to daily rainfall

Daily precipitation is recorded as the total amount of water collected by a rain-gauge in 24h. Events are modelled as a Poisson process and the 24h precipitation by a Generalized Pareto Distribution (GPD) of excesses. Hazard assessment is complete when estimates of the Poisson rate and the distribution parameters, together with a measure of their uncertainty, are obtained. The shape parameter of the GPD determines the support of the variable: Weibull domain of attraction (DA) corresponds to finite support variables, as should be for natural phenomena. However, Fréchet DA has been reported for daily precipitation, which implies an infinite support and a heavy-tailed distribution. We use the fact that a log-scale is better suited to the type of variable analyzed to overcome this inconsistency, thus showing that using the appropriate natural scale can be extremely important for proper hazard assessment. The approach is illustrated with precipitation data from the Eastern coast of the Iberian Peninsula affected by severe convective precipitation. The estimation is carried out by using Bayesian techniques

Rainfall is a risk factor for sporadic cases of Legionella pneumophila Pneumonia

It is not known whether rainfall increases the risk of sporadic cases of Legionella pneumonia. We sought to test this hypothesis in a prospective observational cohort study of non-immunosuppressed adults hospitalized for community-acquired pneumonia (1995-2011). Cases with Legionella pneumonia were compared with those with non-Legionella pneumonia. Using daily rainfall data obtained from the regional meteorological service we examined patterns of rainfall over the days prior to admission in each study group. Of 4168 patients, 231 (5.5%) had Legionella pneumonia. The diagnosis was based on one or more of the following: sputum (41 cases), antigenuria (206) and serology (98). Daily rainfall average was 0.556 liters/m2 in the Legionella pneumonia group vs. 0.328 liters/m2 for non-Legionella pneumonia cases (p = 0.04). A ROC curve was plotted to compare the incidence of Legionella pneumonia and the weighted median rainfall. The cut-off point was 0.42 (AUC 0.54). Patients who were admitted to hospital with a prior weighted median rainfall higher than 0.42 were more likely to have Legionella pneumonia (OR 1.35; 95% CI 1.02-1.78; p = .03). Spearman Rho correlations revealed a relationship between Legionella pneumonia and rainfall average during each two-week reporting period (0.14; p = 0.003). No relationship was found between rainfall average and non-Legionella pneumonia cases (−0.06; p = 0.24). As a conclusion, rainfall is a significant risk factor for sporadic Legionella pneumonia. Physicians should carefully consider Legionella pneumonia when selecting diagnostic tests and antimicrobial therapy for patients presenting with CAP after periods of rainfall.

Effect of radar rainfall time resolution on the predictive capability of a distributed hydrologic model

The performance of a hydrologic model depends on the rainfall input data, both spatially and temporally. As the spatial distribution of rainfall exerts a great influence on both runoff volumes and peak flows, the use of a distributed hydrologic model can improve the results in the case of convective rainfall in a basin where the storm area is smaller than the basin area. The aim of this study was to perform a sensitivity analysis of the rainfall time resolution on the results of a distributed hydrologic model in a flash-flood prone basin. Within such a catchment, floods are produced by heavy rainfall events with a large convective component. A second objective of the current paper is the proposal of a methodology that improves the radar rainfall estimation at a higher spatial and temporal resolution. Composite radar data from a network of three C-band radars with 6-min temporal and 2 × 2 km2 spatial resolution were used to feed the RIBS distributed hydrological model. A modification of the Window Probability Matching Method (gauge-adjustment method) was applied to four cases of heavy rainfall to improve the observed rainfall sub-estimation by computing new Z/R relationships for both convective and stratiform reflectivities. An advection correction technique based on the cross-correlation between two consecutive images was introduced to obtain several time resolutions from 1 min to 30 min. The RIBS hydrologic model was calibrated using a probabilistic approach based on a multiobjective methodology for each time resolution. A sensitivity analysis of rainfall time resolution was conducted to find the resolution that best represents the hydrological basin behaviour.

Sidelobe elimination for generalized synthetic discriminant functions by a two-filter correlation and subsequent postprocessing of the intensity distributions

One of the most important problems in optical pattern recognition by correlation is the appearance of sidelobes in the correlation plane, which causes false alarms. We present a method that eliminate sidelobes of up to a given height if certain conditions are satisfied. The method can be applied to any generalized synthetic discriminant function filter and is capable of rejecting lateral peaks that are even higher than the central correlation. Satisfactory results were obtained in both computer simulations and optical implementation.

Torrential rainfall in northeast of the Iberian Peninsula: synoptic patterns and WeMO influence

This study presents a catalogue of synoptic patterns of torrential rainfall in northeast of the Iberian Peninsula (IP). These circulation patterns were obtained by applying a T-mode Principal Component Analysis (PCA) to a daily data grid (NCEP/NCAR reanalysis) at sea level pressure (SLP). The analysis made use of 304 days which recorded >100 mm in one or more stations in provinces of Barcelona, Girona and Tarragona (coastland area of Catalonia) throughout the 1950-2005 period. The catalogue comprises 7 circulation patterns showing a great variety of atmospheric conditions and seasonal or monthly distribution. Likewise, we computed the mean index value of the Western Mediterranean Oscillation index (WeMOi) for the synoptic patterns obtained by averaging all days grouped in each pattern. The results showed a clear association between the negative values of this teleconnection index and torrential rainfall in northeast of the IP. We therefore put forward the WeMO as an essential tool for forecasting heavy rainfall in northeast of Spain

Empirics of the international inequality in CO2 emissions intensity: explanatory factors according to complementary decomposition methodologies

This paper analyses the international inequalities in CO2 emissions intensity for the period 1971- 2009 and assesses explanatory factors. Multiplicative, group and additive methodologies of inequality decomposition are employed. The first allows us to clarify the separated role of the carbonisation index and the energy intensity in the pattern observed for inequalities in CO2 intensities; the second allows us to understand the role of regional groups; and the third allows us to investigate the role of different fossil energy sources (coal, oil and gas). The results show that, first, the reduction in global emissions intensity has coincided with a significant reduction in international inequality. Second, the bulk of this inequality and its reduction are attributed to differences between the groups of countries considered. Third, coal is the main energy source explaining these inequalities, although the growth in the relative contribution of gas is also remarkable. Fourth, the bulk of inequalities between countries and its decline are explained by differences in energy intensities, although there are significant differences in the patterns demonstrated by different groups of countries.

Energy intensity in road freight transport of heavy goods vehicles in Spain

This paper examines the factors that have influenced the energy intensity of the Spanish road freight transport of heavy goods vehicles over the period 1996–2012. This article aims to contribute to a better understanding of the factors behind the energy intensity change of road freight and also to inform the design of measures to improve energy efficiency in road freight transport. The paper uses both annual single-period and chained multi-period multiplicative LMDI-II decomposition analysis. The results suggest that the decrease in the energy intensity of Spanish road freight in the period is explained by the change in the real energy intensity index (lower energy consumption per tonne-kilometre transported), which is partially offset by the behaviour of the structural index (greater share in freight transport of those commodities the transportation of which is more energy intensive). The change in energy intensity is analysed in more depth by quantifying the contribution of each commodity through the attribution of changes in Divisia indices.

The determinants of capital intensity in Japan and the U.S

We estimate the determinants of capital intensity in Japan and the US, characterized by striking different paths. We augment an otherwise standard Constant Elasticity of Substitution (CES) model with demand-side considerations, which we find especially relevant in the US. In this augmented setting, the elasticity of substitution between capital and labor is placed around 0.85 in Japan, and 0.30 in the US. We also find evidence of biased technical change, which is capital-saving in Japan but labor-saving in the US. These differences help us explain the diverse experience in the capital deepening process of these economies, and lead us to conclude that demand-side drivers may also be relevant to account for different growth experiences. A close look at the nature of technological change is also needed before designing one-size-fits-all industrial, economic growth, and/or labor market policies.