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- Andersson-Sköld, Yvonne, et al.
(författare)
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An integrated method for assessing climate-related risks and adaptation alternatives in urban areas
- 2015
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Ingår i: Climate Risk Management. - : Elsevier BV. - 2212-0963. ; 7, s. 31-50
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Tidskriftsartikel (refereegranskat)abstract
- © 2015 The Authors. The urban environment is a complex structure with interlinked social, ecological and technical structures. Global warming is expected to have a broad variety of impacts, which will add to the complexity. Climate changes will force adaptation, to reduce climate-related risks. Adaptation measures can address one aspect at the time, or aim for a holistic approach to avoid maladaptation. This paper presents a systematic, integrated approach for assessing alternatives for reducing the risks of heat waves, flooding and air pollution in urban settings, with the aim of reducing the risk of maladaptation. The study includes strategies covering different spatial scales, and both the current climate situation and the climate predicted under climate change scenarios. The adaptation strategies investigated included increasing vegetation; selecting density, height and colour of buildings; and retreat or resist (defend) against sea-level rise. Their effectiveness was assessed with regard to not only flooding, heat stress and air quality but also with regard to resource use, emissions to air (incl. GHG), soil and water, and people's perceptions and vulnerability. The effectiveness of the strategies were ranked on a common scale (from -3 to 3) in an integrated assessment. Integrated assessments are recommended, as they help identify the most sustainable solutions, but to reduce the risk of maladaptation they require experts from a variety of disciplines. The most generally applicable recommendation, derived from the integrated assessment here, taking into account both expertise from different municipal departments, literature surveys, life cycle assessments and publics perceptions, is to increase the urban greenery, as it contributes to several positive aspects such as heat stress mitigation, air quality improvement, effective storm-water and flood-risk management, and it has several positive social impacts. The most favourable alternative was compact, mid-rise, light coloured building design with large parks/green areas and trees near buildings.
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| 3. |
- Börjesson, Maria, 1974-, et al.
(författare)
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An ex-post CBA for the Stockholm Metro
- 2014
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Ingår i: Transportation Research Part A. - : Elsevier BV. - 0965-8564 .- 1879-2375. ; 70, s. 135-148
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Tidskriftsartikel (refereegranskat)abstract
- This paper performs an ex-post cost-benefit analysis (CBA) of the Metro system in Stockholm built in the 1950s. We find that the Metro was socially beneficial and that the largest benefit of the Metro is its capacity, making it possible for many people to travel to and from the city center. We also assess the significance of the wider economic impacts due to labor market distortions and the land-use effects in the case of the Stockholm Metro. The wider economic impacts increase the consumer surplus with 48%, and the yearly income in the county with 1.5%. A land-use model is used to simulate how the land-use has been influenced by the Metro over the years 1956-2006. This simulation indicates that the historical centralized planning of housing along transit corridors has developed the region into a more dispersed region than if the market forces had ruled. The simulation also suggests that the land-use impact from the investment itself is small, but that the land-use impact from the planning accompanying the decision to build the Metro has been substantial.
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| 4. |
- Börjesson, Maria, 1974-, et al.
(författare)
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Land-use impacts in transport appraisal
- 2014
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Ingår i: Research in Transportation Economics. - : Elsevier BV. - 0739-8859 .- 1875-7979. ; 47, s. 82-91
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Tidskriftsartikel (refereegranskat)abstract
- Standard cost-benefit analysis (CBA) does not take into account induced demand due to relocation triggered by infrastructure investments. Using an integrated transport and land-use model calibrated for the Stockholm region, we explore whether this has any significant impact on the CBA outcome, and in particular on the relative ranking of rail and road investments. Our results indicate that induced demand has a larger impact on the benefit of rail investments than on the benefit of road investments. The effect on the relative ranking is still limited for two reasons. First, the number of houses that are built over 20 30 years is limited in comparison to the size of the existing housing stock. Second, the location of most of the new houses is not affected by any single infrastructure investment, since the latter has a marginal effect on total accessibility in a city with a mature transport system. A second aim of this paper is to investigate the robustness of the relative CBA ranking of rail and road investments, with respect to the planning policy in the region 25 years ahead. While the results suggest that this ranking is surprisingly robust, there is a tendency that the net benefit of rail investments is more sensitive to the future planning policy than road investments. Our results also underscore that the future land-use planning in the region in general has a considerably stronger impact on accessibility and car use than individual road or rail investments have.
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| 5. |
- Liu, Chengxi, 1987-, et al.
(författare)
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Development of a large-scale transport model with focus on cycling
- 2020
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Ingår i: Transportation Research Part A. - : Elsevier. - 0965-8564 .- 1879-2375. ; 134, s. 164-183
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Tidskriftsartikel (refereegranskat)abstract
- This study presents a transport model to better model cycling demand. The model improves modelling of cycling in several ways compared to a conventional transport model. First, it uses a detailed bicycle network containing information about existing bicycle infrastructure. Second, generalised cost measures based on different bicycle route choice models are calculated and compared to evaluate how to best represent the impact of bicycle infrastructure in the model. Third, the model utilizes a refined zone system with smaller zones of size 250 m × 250 m. Using these smaller zones, more short-distance tours are included in the model, and these are predominantly walking and cycling trips. Fourth, the model considers cycling also as an access mode choice to public transport. Therefore, the model treats cycling and public transport as both competing and complementary modes. Results show that the model captures detailed individual heterogeneity in cycling demand for different trip purposes. Impacts of bicycle infrastructure, land use characteristics and individual/household socio-demographics are investigated. Detailed individual level travel time and generalised cost are derived for cyclists of different socio-demographics. The result highlights the importance of choosing a good measure of generalised cost, given that different bicycle route choice models result in different effects of bicycle infrastructure. In future applications, the model can be used to evaluate proposed bicycle investments regarding their impact on link flow, bicycle route choice, modal shift and generation of completely new tours. The model can also be a powerful tool in a cost-benefit analysis of bicycle investments.
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| 6. |
- Lorenzo Varela, Juan Manuel, 1987-
(författare)
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Learning about the unobservable : The role of attitudes, measurement errors, norms and perceptions in user behaviour.
- 2019
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Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- Unobservable factors are important to understand user behaviour. Moreover, they contain information to help design services that willsolve today’s challenges. Yet, we have barely scratched the surface ofthe underlying mechanisms ruling user behaviour. For decades, userbehaviour analysis has focused on the capabilities of observable variables,as well as assumptions of regular preferences and rational behaviourto explain user choices; and amalgamated unobservable factorsinto ”black-box” variables. As a response, the field of behaviouraleconomics has produced an array of so-called choice anomalies, wherepeople seem not to be fully rational. Furthermore, as a consequence of the ”digital revolution”, nowwe harvest data on an unprecedented scale -both in quantity andresolution- that is nurturing the golden age of analytics. This explosionof analytics contributes to reveal fascinating patterns of humanbehaviour and shows that when users face difficult choices, predictionsbased only on observable variables result in wider gaps between observedand predicted behaviour, than predictions including observableand unobservable factors. Impacts of the ”digital revolution” are not limited to data and analyticsbut they have filtered through the whole tissue of society. Forinstance, telecommunications allow users to telework, and telework allowsusers to change their travel patterns, which in turn contributes toincrease the overall system complexity. In addition to the new worlddynamics facilitated by Information and Communications Technology,megatrends such as hyper-urbanization or increase demand of personalisedtransport services are imposing pressures on transport networksat a furious pace, which also contributes to increase the complexity ofthe choices needed in order to navigate the networks efficiently. In an effort to alleviate these pressures, new mobility services suchas electric and autonomous vehicles; bicycle and car sharing schemes;mobility as a service; vacuum rail systems or even flying cars are evolving. Each of these services entails a different set of observable variableslike travel time and cost, but also a completely different set of unobservableones such as expectations, normative beliefs or perceptionsthat will impact user behaviour. Hence, a good understanding of theimpact of underlying, unobservable, factors -especially when servicesare radically different from what users know and have experienced inthe past- will help us to predict user behaviour in uncharted scenarios. Unobservable factors are elusive by nature, hence to incorporatethem into our models is an arduous task. Furthermore, there is evidence showing that the importance of these factors might differ across time and space, as user preferences, perceptions, normative beliefs, etc.are influenced by local conditions and cultures. As a consequence, we have witnessed a surge of interest in behavioural economics over the past two decades, due to its ability to increase the explanatory and predictive power of models based on economic theory by adding a more psychologically plausible foundation. This thesis contributes to the existing body of literature in TransportScience in the areas of user perceptions, measurement errors, and the influence of attitudes and social norms in the adoption of new mobility solutions. The work builds on the behavioural economics theoretical framework, underpinned by economic theory, discrete choice analysis -rational behaviour and random utility maximization-, as well as social and cognitive psychology. Methodological contributions include a framework to systematically test differences in user preferences for a set of public transport modes, relating to observed and unobserved attributes; and a framework to assess the magnitude of unobservable measurement errors in the input variables of large-scale travel demand models. On an empirical dimension, findings support the existence of a ”rail factor”, the impact of modelling assumptions on parameter estimates of hybrid choice models, the presence of larger measurement errors in the cost variables than in the time variables, -which in turn translates into diluted parameters that under-estimate the response to pricing interventions-, and that the model with the best fit does not guarantee better parameter estimates. Therefore, I expect this thesis to be of interest not only to modellers, but also to decision makers; and that its findings will contribute to the design of the mobility solutions that users need and desire, but also that will benefit society as a whole.
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