Abstract
Benzene is a carcinogenic and genotoxic pollutant which mainly affects the people health through the inhalation. Nevertheless, this pollutant is not frequently measured by air-quality networks. To solve this problem, some models have been published to estimate benzene concentrations in the atmosphere. However, the lack of measures makes difficult the application of complex models in order to get a detailed spatio-temporal analysis, namely in urban areas. In this work was developed a simple semi-empirical model to predict benzene concentrations based on the ratio of benzene and carbon monoxide concentrations in order to predict the concentrations of this pollutant in large areas and periods with lack of benzene measurements but with higher impact in the human health. The model was applied to an urban area, the Metropolitan Area of Oporto, for a period of 12 years (1995-2006). Monthly correlations between benzene and carbon monoxide concentrations at Custias air-quality station are significant (p = 0.01) and higher in winter (r (s) > 0.7) than in summer (0.3 > r (s) > 0.7). Estimate of the monthly ratio of the concentration of these two pollutants range between 199 and 305. The methodology validation shows good results (r (s) = 0.81) which allow, assuming the availability of carbon monoxide data, the use of this tool for areas with low benzene recorded data. The application of this methodology in the study area shows an annual average trend decrease of benzene concentrations during the study period, which may be linked to a general trend decrease of benzene emissions in European urban areas, including the study domain.

Abstract
NNIGnets is a freeware computer program which can be used for teaching, research or business applications, of Artificial Neural Networks (ANNs). This software includes presently several tools for the application and analysis of Multilayer Perceptrons (MLPs) and Radial Basis Functions (RBEs), such as stratified Cross-Validation, Learning Curves, Adjusted Rand Index, novel cost functions, and Vapnik-Chervonenkis (VC) dimension estimation, which are not usually found in other ANN software packages. NNIGnets was built following a software engineering approach which decouples operative from GUI functions, allowing an easy growth of the package. NNIGnets was tested by a variety of users, with different backgrounds and skills, who found it to be intuitive, complete and easy to use.

Abstract
The main purpose of this paper is to present a preliminary study on the impact of stratospheric ozone on tropospheric ozone levels under specific atmospheric dynamical conditions. It is well accepted that stratospheric ozone can be the source of part of the tropospheric ozone. Previous studies indicate that the mechanism responsible for this ozone intrusion occurs generally in several steps or just in a single step, usually associated with strong upward motion. In the first part of this paper, the methodology used in order to identify particular short-term episodes, potentially associated to the abovementioned phenomenon, is presented. Several episodes have been studied occurring during 14 years of ozone data collection, recorded by the Portuguese ozone network. Then, an analysis of the dynamical atmospheric conditions associated to previously identified episodes have been developed in order to verify the possibility of stratospheric contribution for the observed ozone level in each episode. Two of these episodes show a relatively good relationship between synoptical patterns related to stratospheric intrusions and backward trajectories. For these cases, the possibility of stratospheric origin should not be discarded before further study is developed.

Abstract
We present new results on the performance of Minimum Error Entropy (MEE) decision trees, which use a novel node split criterion. The results were obtained in a comparive study with popular alternative algorithms, on 42 real world datasets. Carefull validation and statistical methods were used. The evidence gathered from this body of results show that the error performance of MEE trees compares well with alternative algorithms. An important aspect to emphasize is that MEE trees generalize better on average without sacrifing error performance.

Abstract
E-commerce growth is raising the demand for logistic activities, especially in the last-mile, which is considered the most ineffective part of the supply chain and a negative externalities source. Although various solutions aim to address these issues, selecting the best one is challenging due to multiple perspectives, conflicting criteria, trade-offs, and complex and sensitive urban contexts. This article proposes a 4-level hierarchical model based on the triple bottom line of sustainability that may assist decision-makers in selecting the most adequate last -mile solution for historic centers. The model was defined based on a systematic literature review; evaluated by interviewing a set of experts; and quantified according to an AHP-TOPSIS approach. This quantification focused on the historic center of Porto, Portugal. The experts considered all three sustainability dimensions similarly important. Air pollution was the most valued sub-criterion whereas Visual pollution was the least. 67 decision-maker profiles were defined, showing that environmentally oriented decision-makers prefer cargo bikes, while decision-makers who prioritize economic and social factors prefer parcel lockers. All last-mile solutions considered in the model yielded similar results, therefore suggesting a combined distribution strategy. Nevertheless, the use of parcel lockers is the most favorable solution for Porto's historic center.

Abstract
Globalisation, urbanisation and the recent COVID-19 pandemic has been raising the demand for logistic activities. This change is affecting the entire supply chain, especially the last-mile step. This step is considered the most expensive and ineffective part of the supply chain and a source of negative economic, environmental and social externalities. This article aims to characterise the sustainable urban last-mile logistics research field through a systematic literature review (N = 102). This wide and holistic review was organised into six thematic clusters that identified the main concepts addressed in the different areas of the last-mile research and the existence of 14 solutions, grouped into three types (vehicular, operational, and organisational solutions). The major findings are that there are no ideal last-mile solutions as their limitations should be further explored by considering the so-called triple bottom line of sustainability; the integration and combination of multiple last-mile alternative concepts; or by establishing collaboration schemes that minimise the stakeholders' conflicting interests.