Impact of particle formation on atmospheric ions and particle number concentrations in an urban environment

A measurement campaign was conducted from 3 to 19 December 2012 at an urban site of Brisbane, Australia. Size distribution of ions and particle number concentrations were measured to investigate the influence of particle formation and biomass burning on atmospheric ion and particle concentrations. Overall ion and particle number concentrations during the measurement period were found to be (-1.2 x 103 cm-3 | +1.6 x 103 cm-3) and 4.4 x 103, respectively. The results of correlation analysis between concentrations of ions and nitrogen oxides indicated that positive and negative ions originated from similar sources, and that vehicle exhaust emissions had a more significant influence on intermediate/large ions, while cluster ions rapidly attached to larger particles once emitted into the atmosphere. Diurnal variations in ion concentration suggested the enrichment of intermediate and large ions on new particle formation event days, indicating that they were involved in the particle formation processes. Elevated total ions, particularly larger ions, and particle number concentrations were found during biomass burning episodes. This could be due to the attachment of cluster ions onto accumulation mode particles or production of charged particles from biomass burning, which were in turn transported to the measurement site. The results of this work enhance scientific understanding of the sources of atmospheric ions in an urban environment, as well as their interactions with particles during particle formation processes.

A generalized estimating equations approach for analysis of the impact of new technology on a trawl fishery

The article describes a generalized estimating equations approach that was used to investigate the impact of technology on vessel performance in a trawl fishery during 1988-96, while accounting for spatial and temporal correlations in the catch-effort data. Robust estimation of parameters in the presence of several levels of clustering depended more on the choice of cluster definition than on the choice of correlation structure within the cluster. Models with smaller cluster sizes produced stable results, while models with larger cluster sizes, that may have had complex within-cluster correlation structures and that had within-cluster covariates, produced estimates sensitive to the correlation structure. The preferred model arising from this dataset assumed that catches from a vessel were correlated in the same years and the same areas, but independent in different years and areas. The model that assumed catches from a vessel were correlated in all years and areas, equivalent to a random effects term for vessel, produced spurious results. This was an unexpected finding that highlighted the need to adopt a systematic strategy for modelling. The article proposes a modelling strategy of selecting the best cluster definition first, and the working correlation structure (within clusters) second. The article discusses the selection and interpretation of the model in the light of background knowledge of the data and utility of the model, and the potential for this modelling approach to apply in similar statistical situations.

CAE-based prediction of projectile residual velocity for impact on single and multi-layered metallic armour plates

The present, paper deals with the CAE-based study Of impact of jacketed projectiles on single- and multi-layered metal armour plates using LS-DYNA. The validation of finite element modelling procedure is mainly based on the mesh convergence study using both shell and solid elements for representing single-layered mild steel target plates. It, is shown that the proper choice of mesh density and the strain rate-dependent material properties are essential for all accurate prediction of projectile residual velocity. The modelling requirements are initially arrived at by correlating against test residual velocities for single-layered mild steel plates of different depths at impact velocities in the ran.-c of approximately 800-870 m/s. The efficacy of correlation is adjudged, in terms of a 'correlation index', defined in the paper: for which values close to unity are desirable. The experience gained for single-layered plates is next; used in simulating projectile impacts on multi-layered mild steel target plates and once again a high degree of correlation with experimental residual velocities is observed. The study is repeated for single- and multi-layered aluminium target plates with a similar level of success in test residual velocity prediction. TO the authors' best knowledge, the present comprehensive study shows in particular for the first time that, with a. proper modelling approach, LS-DYNA can be used with a great degree of confidence in designing perforation-resistant single and multi-layered metallic armour plates.

Assessing the impact of occupant behaviour on the electricity consumption for lighting and small power in office buildings

Lighting and small power will typically account for more than half of the total electricity consumption in an office building. Significant variations in electricity used by different tenants suggest that occupants can have a significant impact on the electricity demand for these end-uses. Yet current modelling techniques fail to represent the interaction between occupant and the building environment in a realistic manner. Understanding the impact of such behaviours is crucial to improve the methodology behind current energy modelling techniques, aiming to minimise the significant gap between predicted and in-use performance of buildings. A better understanding of the impact of occupant behaviour on electricity consumption can also inform appropriate energy saving strategies focused on behavioural change. This paper reports on a study aiming to assess the intent of occupants to switch off lighting and appliances when not in use in office buildings. Based on the Theory of Planned Behaviour, the assessment takes the form of a questionnaire and investigates three predictors to behaviour individually: 1) behavioural attitude; 2) subjective norms; 3) perceived behavioural control. The paper details the development of the assessment procedure and discusses preliminary findings from the study. The questionnaire results are compared against electricity consumption data for individual zones within a multi-tenanted office building. Initial results demonstrate a statistically significant correlation between perceived behavioural control and energy consumption for lighting and small power

Impact of global warming on the interannual and interdecadal climate modes in a coupled GCM

In this study, we investigated the impact of global warming on the variabilities of large-scale interannual and interdecadal climate modes and teleconnection patterns with two long-term integrations of the coupled general circulation model of ECHAM4/OPYC3 at the Max-Planck-Institute for Meteorology, Hamburg. One is the control (CTRL) run with fixed present-day concentrations of greenhouse gases. The other experiment is a simulation of transient greenhouse warming, named GHG run. In the GHG run the averaged geopotential height at 500 hPa is increased significantly, and a negative phase of the Pacific/North American (PNA) teleconnection-like distribution pattern is intensified. The standard deviation over the tropics (high latitudes) is enhanced (reduced) on the interdecadal time scales and reduced (enhanced) on the interannual time scales in the GHG run. Except for an interdecadal mode related to the Southern Oscillation (SO) in the GHG run, the spatial variation patterns are similar for different (interannual + interdecadal, interannual, and interdecadal) time scales in the GHG and CTRL runs. Spatial distributions of the teleconnection patterns on the interannual and interdecadal time scales in the GHG run are also similar to those in the CTRL run. But some teleconnection patterns show linear trends and changes of variances and frequencies in the GHG run. Apart from the positive linear trend of the SO, the interdecadal modulation to the El Niño/SO cycle is enhanced during the GHG 2040 ∼ 2099. This is the result of an enhancement of the Walker circulation during that period. La Niña events intensify and El Niño events relatively weaken during the GHG 2070 ∼ 2090. It is interesting to note that with increasing greenhouse gas concentrations the relation between the SO and the PNA pattern is reversed significantly from a negative to a positive correlation on the interdecadal time scales and weakened on the interannual time scales. This suggests that the increase of the greenhouse gas concentrations will trigger the nonstationary correlation between the SO and the PNA pattern both on the interdecadal and interannual time scales.

Impact of skeletal maturation on bone metabolism biomarkers and bone mineral density in healthy Brazilian male adolescents

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

The impact of environmental enrichment on the outcome variability and scientific validity of laboratory animal studies.

It has been widely accepted for some time that species-appropriate environmental enrichment is important for the welfare of research animals, but its impact on research data initially received little attention. This has now changed, as the use of enrichment as one element of routine husbandry has expanded. In addition to its use in the care of larger research animals, such as nonhuman primates, it is now being used to improve the environments of small research animals, such as rodents, which are used in significantly greater numbers and in a wide variety of studies. Concern has been expressed that enrichment negatively affects both experimental validity and reproducibility. However, when a concise definition of enrichment is used, with a sound understanding of the biology and behaviour of the animal as well as the research constraints, it becomes clear that the welfare of research animals can be enhanced through environmental enrichment without compromising their purpose. Indeed, it is shown that the converse is true: the provision of suitable enrichment enhances the well-being of the animal, thereby refining the animal model and improving the research data. Thus, the argument is made that both the validity and reproducibility of the research are enhanced when proper consideration is given to the research animal's living environment and the animal's opportunities to express species-typical behaviours.

Impact of environmental regulations on lead concentrations in Texas ambient air and water: 1970--1990

In the last two decades, the significance of lead has been addressed in a number of environmental regulations at the national and state levels. This project investigated the environmental regulations (Clean Air Act and Amendments, 1970-1990 and Clean Water Act of 1977) and their cumulative effects on lead in ambient air and water in the state of Texas. For this purpose, historical records from the Texas Water Development Board, Texas Natural Resources Conservation Commission, and the United States Geological Survey have been assembled and analyzed for temporal and spatial trends. These trends might correspond to the phase out of lead in gasoline and other regulations.^ This study concluded that there is a significant correlation (p $\leq$.001) between environmental regulations of lead in gasoline and the concentration of lead in ambient air. Lead concentrations in ambient air have been reduced by over 90 percent in the past twenty years. An overall significant difference (p $\leq$.001) was found in mean (94, 15 respectively) lead concentrations in surface water between two time periods, one at the beginning of the twenty year period and one at the end of the study period. There has been an overall reduction of lead concentrations in surface water in Texas of approximately 84 percent. However, this reduction cannot be statistically associated with any one regulation. Groundwater data could not be analyzed for lead concentrations because of limitations of reporting data as "less than". Approximately two percent of the groundwater data was analyzed by Oneway ANOVA and no significant difference was found between the means (18, 19 respectively) of two time periods, 1977-1979 and 1988-1990. This data is consistent with the regulations having a contributory affect on declining concentrations, but other factors cannot be ruled out as having added to these declines. This study can also serve as a starting point for a more in-depth study of environmental regulations and their impact on the environment. ^

Impact of thermal stress on evolutionary trajectories of pathogen resistance in three-spined stickleback (Gasterosteus aculeatus), supplementary material

Background: Pathogens are a major regulatory force for host populations, especially under stressful conditions. Elevated temperatures may enhance the development of pathogens, increase the number of transmission stages, and can negatively influence host susceptibility depending on host thermal tolerance. As a net result, this can lead to a higher prevalence of epidemics during summer months. These conditions also apply to marine ecosystems, where possible ecological impacts and the population-specific potential for evolutionary responses to changing environments and increasing disease prevalence are, however, less known. Therefore, we investigated the influence of thermal stress on the evolutionary trajectories of disease resistance in three marine populations of three-spined sticklebacks Gasterosteus aculeatus by combining the effects of elevated temperature and infection with a bacterial strain of Vibrio sp. using a common garden experiment. Results: We found that thermal stress had an impact on fish weight and especially on survival after infection after only short periods of thermal acclimation. Environmental stress reduced genetic differentiation (QST) between populations by releasing cryptic within-population variation. While life history traits displayed positive genetic correlations across environments with relatively weak genotype by environment interactions (GxE), environmental stress led to negative genetic correlations across environments in pathogen resistance. This reversal of genetic effects governing resistance is probably attributable to changing environment-dependent virulence mechanisms of the pathogen interacting differently with host genotypes, i.e. GPathogenxGHostxE or (GPathogenxE)x(GHostxE) interactions, rather than to pure host genetic effects, i.e. GHostxE interactions. Conclusion: To cope with climatic changes and the associated increase in pathogen virulence, host species require wide thermal tolerances and pathogen-resistant genotypes. The higher resistance we found for some families at elevated temperatures showed that there is evolutionary potential for resistance to Vibrio sp. in both thermal environments. The negative genetic correlation of pathogen resistance between thermal environments, on the other hand, indicates that adaptation to current conditions can be a weak predictor for performance in changing environments. The observed feedback on selective gradients exerted on life history traits may exacerbate this effect, as it can also modify the response to selection for other vital components of fitness.

Impact of dissolved inorganic carbon concentrations and pH on growth of the chemolithoautotrophic epsilonproteobacterium GD1

Epsilonproteobacteria have been found globally distributed in marine anoxic/sulfidic areas mediating relevant transformations within the sulfur and nitrogen cycles. In the Baltic Sea redox zones, chemoautotrophic epsilonproteobacteria mainly belong to the Sulfurimonas gotlandica GD17 cluster for which recently a representative strain, S. gotlandica GD1T, could be established as a model organism. In this study, the potential effects of changes in dissolved inorganic carbon (DIC) and pH on S. gotlandica GD1T were examined. Bacterial cell abundance within a broad range of DIC concentrations and pH values were monitored and substrate utilization was determined. The results showed that the DIC saturation concentration for achieving maximal cell numbers was already reached at 800 µmol/l, which is well below in situ DIC levels. The pH optimum was between 6.6 and 8.0. Within a pH range of 6.6-7.1 there was no significant difference in substrate utilization; however, at lower pH values maximum cell abundance decreased sharply and cell-specific substrate consumption increased.

Impact of elevated pCO2 on acid-base regulation of the sea urchin Echinometra mathaei and its relation to resistance to ocean acidification: A study in mesocosms

Due to their low metabolism and apparent poor ion regulation ability, sea urchins could be particularly sensitive to ocean acidification resulting from increased dissolution of atmospheric carbon dioxide. Therefore, we evaluated the acid-base regulation ability of the coral reef sea urchin Echinometra mathaei and the impact of decreased pH on its growth and respiration activity. The study was conducted in two identical artificial reef mesocosms during seven weeks. Experimental tanks were maintained respectively at mean pHT 7.7 and 8.05 (with field-like night and day variations). The major physico-chemical parameters were identical, only pCO2 and pHT differed. Results indicate that E. mathaei can regulate the pH of its coelomic fluid in the considered range of pH, allowing a sustainable growth and ensuring an unaffected respiratory metabolism, at least at short term.

Impact of elevated pCO2 on paralytic shellfish poisoning toxin content and composition in Alexandrium tamarense

Ocean acidification is considered a major threat to marine ecosystems and may particularly affect primary producers. Here we investigated the impact of elevated pCO2 on paralytic shellfish poisoning toxin (PST) content and composition in two strains of Alexandrium tamarense, Alex5 and Alex2. Experiments were carried out as dilute batch to keep carbonate chemistry unaltered over time. We observed only minor changes with respect to growth and elemental composition in response to elevated pCO2. For both strains, the cellular PST content, and in particular the associated cellular toxicity, was lower in the high CO2 treatments. In addition, Alex5 showed a shift in its PST composition from a nonsulfated analogue towards less toxic sulfated analogues with increasing pCO2. Transcriptomic analyses suggest that the ability of A. tamarense to maintain cellular homeostasis is predominantly regulated on the post-translational level rather than on the transcriptomic level. Furthermore, genes associated to secondary metabolite and amino acid metabolism in Alex5 were down-regulated in the high CO2 treatment, which may explain the lower PST content. Elevated pCO2 also induced up-regulation of a putative sulfotransferase sxtN homologue and a substantial down-regulation of several sulfatases. Such changes in sulfur metabolism may explain the shift in PST composition towards more sulfated analogues. All in all, our results indicate that elevated pCO2 will have minor consequences for growth and elemental composition, but may potentially reduce the cellular toxicity of A. tamarense.

Impact of changing carbonate chemistry, temperature, and salinity on growth and test degradation of the benthic foraminifer Ammonia aomoriensis

The present study investigated the combined effects of ocean acidification, temperature, and salinity on growth and test degradation of Ammonia aomoriensis. This species is one of the dominant benthic foraminifera in near-coastal habitats of the southwestern Baltic Sea that can be particularly sensitive to changes in seawater carbonate chemistry. To assess potential responses to ocean acidification and climate change, we performed a fully crossed experiment involving three temperatures (8, 13, and 18°C), three salinities (15, 20, and 25) and four pCO2 levels (566, 1195, 2108, and 3843 µatm) for six weeks. Our results highlight a sensitive response of A. aomoriensis to undersaturated seawater with respect to calcite. The specimens continued to grow and increase their test diameter in treatments with pCO2 <1200 µatm, when Omega calc >1. Growth rates declined when pCO2 exceeded 1200 µatm (Omega calc <1). A significant reduction in test diameter and number of tests due to dissolution was observed below a critical Omega calc of 0.5. Elevated temperature (18°C) led to increased Omega calc, larger test diameter, and lower test degradation. Maximal growth was observed at 18°C. No significant relationship was observed between salinity and test growth. Lowered and undersaturated Omega calc, which results from increasing pCO2 in bottom waters, may cause a significant future decline of the population density of A. aomoriensis in its natural environment. At the same time, this effect might be partially compensated by temperature rise due to global warming.

Impact of long-term moderate hypercapnia and elevated temperature on the energy budget of isolated gills and branchial in vivo and in vitro enzyme capacities of Atlantic cod (Gadus morhua)

Effects of severe hypercapnia have been extensively studied in marine fishes, while knowledge on the impacts of moderately elevated CO2 levels and their combination with warming is scarce. Here we investigate ion regulation mechanisms and energy budget in gills from Atlantic cod acclimated long-term to elevated PCO2 levels (2500 µatm) and temperature (18 °C). Isolated perfused gill preparations established to determine gill thermal plasticity during acute exposures (10-22 °C) and in vivo costs of Na+/K+-ATPase activity, protein and RNA synthesis. Maximum enzyme capacities of F1Fo-ATPase, H+-ATPase and Na+/K+-ATPase were measured in vitro in crude gill homogenates. After whole animal acclimation to elevated PCO2 and/or warming, branchial oxygen consumption responded more strongly to acute temperature change. The fractions of gill respiration allocated to protein and RNA synthesis remained unchanged. In gills of fish CO2-exposed at both temperatures, energy turnover associated with Na+/K+-ATPase activity was reduced by 30% below rates of control fish. This contrasted in vitro capacities of Na+/K+-ATPase, which remained unchanged under elevated CO2 at 10 °C, and earlier studies which had found a strong upregulation under severe hypercapnia. F1Fo-ATPase capacities increased in hypercapnic gills at both temperatures, whereas Na+/K+ATPase and H+-ATPase capacities only increased in response to elevated CO2 and warming indicating the absence of thermal compensation under CO2. We conclude that in vivo ion regulatory energy demand is lowered under moderately elevated CO2 levels despite the stronger thermal response of total gill respiration and the upregulation of F1Fo-ATPase. This effect is maintained at elevated temperature.

Modelling the Impact of Built Environment, Geographical Scales and Latent Constructs On Individual Travel Behaviour

La relación entre la estructura urbana y la movilidad ha sido estudiada desde hace más de 70 años. El entorno urbano incluye múltiples dimensiones como por ejemplo: la estructura urbana, los usos de suelo, la distribución de instalaciones diversas (comercios, escuelas y zonas de restauración, parking, etc.). Al realizar una revisión de la literatura existente en este contexto, se encuentran distintos análisis, metodologías, escalas geográficas y dimensiones, tanto de la movilidad como de la estructura urbana. En este sentido, se trata de una relación muy estudiada pero muy compleja, sobre la que no existe hasta el momento un consenso sobre qué dimensión del entorno urbano influye sobre qué dimensión de la movilidad, y cuál es la manera apropiada de representar esta relación. Con el propósito de contestar estas preguntas investigación, la presente tesis tiene los siguientes objetivos generales: (1) Contribuir al mejor entendimiento de la compleja relación estructura urbana y movilidad. y (2) Entender el rol de los atributos latentes en la relación entorno urbano y movilidad. El objetivo específico de la tesis es analizar la influencia del entorno urbano sobre dos dimensiones de la movilidad: número de viajes y tipo de tour. Vista la complejidad de la relación entorno urbano y movilidad, se pretende contribuir al mejor entendimiento de la relación a través de la utilización de 3 escalas geográficas de las variables y del análisis de la influencia de efectos inobservados en la movilidad. Para el análisis se utiliza una base de datos conformada por tres tipos de datos: (1) Una encuesta de movilidad realizada durante los años 2006 y 2007. Se obtuvo un total de 943 encuestas, en 3 barrios de Madrid: Chamberí, Pozuelo y Algete. (2) Información municipal del Instituto Nacional de Estadística: dicha información se encuentra enlazada con los orígenes y destinos de los viajes recogidos en la encuesta. Y (3) Información georeferenciada en Arc-GIS de los hogares participantes en la encuesta: la base de datos contiene información respecto a la estructura de las calles, localización de escuelas, parking, centros médicos y lugares de restauración. Se analizó la correlación entre e intra-grupos y se modelizaron 4 casos de atributos bajo la estructura ordinal logit. Posteriormente se evalúa la auto-selección a través de la estimación conjunta de las elecciones de tipo de barrio y número de viajes. La elección del tipo de barrio consta de 3 alternativas: CBD, Urban y Suburban, según la zona de residencia recogida en las encuestas. Mientras que la elección del número de viajes consta de 4 categorías ordinales: 0 viajes, 1-2 viajes, 3-4 viajes y 5 o más viajes. A partir de la mejor especificación del modelo ordinal logit. Se desarrolló un modelo joint mixed-ordinal conjunto. Los resultados indican que las variables exógenas requieren un análisis exhaustivo de correlaciones con el fin de evitar resultados sesgados. ha determinado que es importante medir los atributos del BE donde se realiza el viaje, pero también la información municipal es muy explicativa de la movilidad individual. Por tanto, la percepción de las zonas de destino a nivel municipal es considerada importante. En el contexto de la Auto-selección (self-selection) es importante modelizar conjuntamente las decisiones. La Auto-selección existe, puesto que los parámetros estimados conjuntamente son significativos. Sin embargo, sólo ciertos atributos del entorno urbano son igualmente importantes sobre la elección de la zona de residencia y frecuencia de viajes. Para analizar la Propensión al Viaje, se desarrolló un modelo híbrido, formado por: una variable latente, un indicador y un modelo de elección discreta. La variable latente se denomina “Propensión al Viaje”, cuyo indicador en ecuación de medida es el número de viajes; la elección discreta es el tipo de tour. El modelo de elección consiste en 5 alternativas, según la jerarquía de actividades establecida en la tesis: HOME, no realiza viajes durante el día de estudio, HWH tour cuya actividad principal es el trabajo o estudios, y no se realizan paradas intermedias; HWHs tour si el individuo reaiza paradas intermedias; HOH tour cuya actividad principal es distinta a trabajo y estudios, y no se realizan paradas intermedias; HOHs donde se realizan paradas intermedias. Para llegar a la mejor especificación del modelo, se realizó un trabajo importante considerando diferentes estructuras de modelos y tres tipos de estimaciones. De tal manera, se obtuvieron parámetros consistentes y eficientes. Los resultados muestran que la modelización de los tours, representa una ventaja sobre la modelización de los viajes, puesto que supera las limitaciones de espacio y tiempo, enlazando los viajes realizados por la misma persona en el día de estudio. La propensión al viaje (PT) existe y es específica para cada tipo de tour. Los parámetros estimados en el modelo híbrido resultaron significativos y distintos para cada alternativa de tipo de tour. Por último, en la tesis se verifica que los modelos híbridos representan una mejora sobre los modelos tradicionales de elección discreta, dando como resultado parámetros consistentes y más robustos. En cuanto a políticas de transporte, se ha demostrado que los atributos del entorno urbano son más importantes que los LOS (Level of Service) en la generación de tours multi-etapas. la presente tesis representa el primer análisis empírico de la relación entre los tipos de tours y la propensión al viaje. El concepto Propensity to Travel ha sido desarrollado exclusivamente para la tesis. Igualmente, el desarrollo de un modelo conjunto RC-Number of trips basado en tres escalas de medida representa innovación en cuanto a la comparación de las escalas geográficas, que no había sido hecha en la modelización de la self-selection. The relationship between built environment (BE) and travel behaviour (TB) has been studied in a number of cases, using several methods - aggregate and disaggregate approaches - and different focuses – trip frequency, automobile use, and vehicle miles travelled and so on. Definitely, travel is generated by the need to undertake activities and obtain services, and there is a general consensus that urban components affect TB. However researches are still needed to better understand which components of the travel behaviour are affected most and by which of the urban components. In order to fill the gap in the research, the present dissertation faced two main objectives: (1) To contribute to the better understanding of the relationship between travel demand and urban environment. And (2) To develop an econometric model for estimating travel demand with urban environment attributes. With this purpose, the present thesis faced an exhaustive research and computation of land-use variables in order to find the best representation of BE for modelling trip frequency. In particular two empirical analyses are carried out: 1. Estimation of three dimensions of travel demand using dimensions of urban environment. We compare different travel dimensions and geographical scales, and we measure self-selection contribution following the joint models. 2. Develop a hybrid model, integrated latent variable and discrete choice model. The implementation of hybrid models is new in the analysis of land-use and travel behaviour. BE and TB explicitly interact and allow richness information about a specific individual decision process For all empirical analysis is used a data-base from a survey conducted in 2006 and 2007 in Madrid. Spatial attributes describing neighbourhood environment are derived from different data sources: National Institute of Statistics-INE (Administrative: municipality and district) and GIS (circular units). INE provides raw data for such spatial units as: municipality and district. The construction of census units is trivial as the census bureau provides tables that readily define districts and municipalities. The construction of circular units requires us to determine the radius and associate the spatial information to our households. The first empirical part analyzes trip frequency by applying an ordered logit model. In this part is studied the effect of socio-economic, transport and land use characteristics on two travel dimensions: trip frequency and type of tour. In particular the land use is defined in terms of type of neighbourhoods and types of dwellers. Three neighbourhood representations are explored, and described three for constructing neighbourhood attributes. In particular administrative units are examined to represent neighbourhood and circular – unit representation. Ordered logit models are applied, while ordinal logit models are well-known, an intensive work for constructing a spatial attributes was carried out. On the other hand, the second empirical analysis consists of the development of an innovative econometric model that considers a latent variable called “propensity to travel”, and choice model is the choice of type of tour. The first two specifications of ordinal models help to estimate this latent variable. The latent variable is unobserved but the manifestation is called “indicators”, then the probability of choosing an alternative of tour is conditional to the probability of latent variable and type of tour. Since latent variable is unknown we fit the integral over its distribution. Four “sets of best variables” are specified, following the specification obtained from the correlation analysis. The results evidence that the relative importance of SE variables versus BE variables depends on how BE variables are measured. We found that each of these three spatial scales has its intangible qualities and drawbacks. Spatial scales play an important role on predicting travel demand due to the variability in measures at trip origin/destinations within the same administrative unit (municipality, district and so on). Larger units will produce less variation in data; but it does not affect certain variables, such as public transport supply, that are more significant at municipality level. By contrast, land-use measures are more efficient at district level. Self-selection in this context, is weak. Thus, the influence of BE attributes is true. The results of the hybrid model show that unobserved factors affect the choice of tour complexity. The latent variable used in this model is propensity to travel that is explained by socioeconomic aspects and neighbourhood attributes. The results show that neighbourhood attributes have indeed a significant impact on the choice of the type of tours either directly and through the propensity to travel. The propensity to travel has a different impact depending on the structure of each tour and increases the probability of choosing more complex tours, such as tours with many intermediate stops. The integration of choice and latent variable model shows that omitting important perception and attitudes leads to inconsistent estimates. The results also indicate that goodness of fit improves by adding the latent variable in both sequential and simultaneous estimation. There are significant differences in the sensitivity to the latent variable across alternatives. In general, as expected, the hybrid models show a major improvement into the goodness of fit of the model, compared to a classical discrete choice model that does not incorporate latent effects. The integrated model leads to a more detailed analysis of the behavioural process. Summarizing, the effect that built environment characteristics on trip frequency studied is deeply analyzed. In particular we tried to better understand how land use characteristics can be defined and measured and which of these measures do have really an impact on trip frequency. We also tried to test the superiority of HCM on this field. We can concluded that HCM shows a major improvement into the goodness of fit of the model, compared to classical discrete choice model that does not incorporate latent effects. And consequently, the application of HCM shows the importance of LV on the decision of tour complexity. People are more elastic to built environment attributes than level of services. Thus, policy implications must take place to develop more mixed areas, work-places in combination with commercial retails.