Simulating the impact of urban sprawl on air quality and population exposure in the German Ruhr area. Part I: Reproducing the reference state / Part II: Development and evaluation of an urban growth scenario

Université Louis Pasteur (ULP), Strasbourg, France
Atmospheric Environment (Impact Factor: 3.28). 09/2008; 42(30):7070-7077. DOI: 10.1016/j.atmosenv.2008.06.044

ABSTRACT The impact of uncontrolled urban growth (‘sprawl’) on air pollution and associated population exposure is investigated. This is done for the Ruhr area in Germany, by means of a coupled modelling system dealing with land use changes, traffic, meteorology, and atmospheric dispersion and chemistry. In a companion paper [De Ridder, K., Lefebre F., Adriaensen S., Arnold U., Beckroege W., Bronner C., Damsgaard O., Dostal I., Dufek J., Hirsch J., Int Panis L., Kotek Z., Ramadier T., Thierry A., Vermoote S., Wania A., Weber C., 2008. Simulating the impact of urban sprawl on air quality and population exposure in the German Ruhr area. Part I: reproducing the base state.], a description was given of the coupling of these models and of the validation of simulation results. In the present paper, a land use change scenario was implemented to mimic urban sprawl, relocating 12% of the urban population in the study domain to the green periphery. The resulting updated land use, population and employment density patterns were then used as input for traffic simulations, yielding an increase of total traffic volume by almost 17%. As a consequence, the domain-average simulated pollutant concentrations of ozone and particulate matter increased, though by a smaller amount, of approximately 4%. In a final step, population exposure to air pollution was calculated, both for the base case and the scenario simulations. A very slight domain-average exposure increase was found, of the order of a half percent. A compensating mechanism was identified, explaining this small figure. However, when stratifying the population into groups of individuals that were relocated to the urban periphery and those that were not, much larger exposure changes following urban sprawl emerged. Indeed, it was found that the relatively small proportion of relocated individuals benefited of a decrease of exposure to particulate matter by almost 13%, mainly because of their moving out of the most polluted areas; and that this came at the expense of an increase of exposure of 1.2% by the individuals not having moved.

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Available from: Filip Lefebre, Sep 26, 2015
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    • "Simulations to date have been used as a basis for supporting environmental health studies and assessments (Eubank et al., 2004) and for informing policy and planning strategies (Cuvelier et al., 2007; Lefebvre et al., 2013). Simulations are particularly powerful when analysing very complex phenomena such as the spread of infectious diseases (Ferguson et al., 2006), to assess activity-based vehicle emissions (Beckx et al., 2009) or to explore the effects of dynamic exposures (De Ridder et al., 2008). This is done mostly using data from real-world urban areas to answer questions specific to a town or city. "
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    ABSTRACT: This paper introduces an urban simulation model for environmental health analysis (SIENA). SIENA is a novel tool to explore urban interactions and processes with regard to exposure assessments. It is based on urban structures and relationships observed in real-world cities making it a realistic representation of a functioning city. The development of SIENA involved identifying and quantifying fundamental processes and similarities in urban areas in Great Britain and using those to guide the building of SIENA within a GIS. An internal validation confirmed SIENA's realism. Its generality, achieved through the pooling of information from different real-world cities, makes it particularly useful for developing and testing spatial epidemiological concepts and models; simulating processes and interactions relating to environmental exposure; and exploring theoretical and methodological problems in the spatial analysis of environmental health. SIENA ultimately provides a much needed tool in the form of a controlled, simplified urban simulation model.
    Environmental Modelling and Software 08/2014; 58:1–11. DOI:10.1016/j.envsoft.2014.03.013 · 4.42 Impact Factor
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    • "These spatially and temporally distributed emissions are then used in the bi-Gaussian IFDM model (Lefebvre et al., 2011b). The results are coupled to output of the Eulerian model AURORA (De Ridder et al., 2008) which was calibrated using the land-use regression model RIO (Janssen et al., 2008). The coupling between AURORA and IFDM is done using a method (Lefebvre et al., 2011b) to avoid the double counting of the local emissions. "
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    ABSTRACT: Increasing the spatial resolution of air quality assessments in urban environments is designated as a priority area within current research. Biomagnetic monitoring and air quality modelling are both methodologies able to provide information about the spatial variation of particulate pollutant levels within urban environments. This study evaluates both methods by comparing results of a biomagnetic monitoring campaign at 110 locations throughout Antwerp, Belgium, with modelled pollutant concentrations of PM10 and NO2. Due to the relation of biomagnetic monitoring with railway traffic, analyses were conducted for both all locations (n = 110) and railway traffic excluded locations (n = 67). While the general spatial variation, land use comparison and the relation with traffic intensity were comparable between the two applied methodologies, an overall bad agreement is obtained when the methodologies are correlated to each other. While no correlation was found between SIRM and PM10 results (p = 0.75 for n = 110 and p = 0.68 for n = 67), a significant but low (r ≤ 0.33) correlation was found between SIRM and NO2 (p < 0.01 for n = 110 and p = 0.04 for n = 67). While biomagnetic monitoring and air quality modelling are both able to provide high spatial resolution information about urban pollutant levels, we need to take into account some considerations. While uncertainty in the biomagnetic monitoring approach might arise from the processes that determine leaf particulate deposition and the incorporation of multiple emission sources with diverging magnetic composition, air quality modelling remains an approximation of reality which implies its dependency on accurate emission factors, implication of atmospheric processes and representation of the urban morphology. Therefore, continuous evaluation of model performance against measured data is essential to produce reliable model results. Nevertheless, this study demonstrates that in addition to telemetric monitoring networks, the combination of both air quality modelling and biomagnetic monitoring is a valuable approach to provide insights into the variation of atmospheric pollutants in heterogeneous urban environments.
    Atmospheric Environment 07/2014; 92:130-140. DOI:10.1016/j.atmosenv.2014.04.013 · 3.28 Impact Factor
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    • "Indicators on Framework Conditions for a Sustainable Ecological Development Spatial analyses in Munich on drivers of urban soil sealing between 1998 and 2011 showed that the main drivers of sealing were transport areas, which increased especially at the urban fringes (Artmann 2013a). In general, urban sprawl increases the distances between working and living and therefore the need for roads, which leads to an increase in the use of cars, energy consumption, and traffic emissions (de Ridder et al. 2008). Therefore, reducing private motorized traffic can support a reduction in sealing and at a larger scale also in energy consumption and air pollution (Artmann 2013a). "
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    ABSTRACT: Soil sealing has negative impacts on ecosystem services since urban green and soil get lost. Although there is political commitment to stop further sealing, no reversal of this trend can be observed in Europe. This paper raises the questions (1) which strategies can be regarded as being efficient toward ecologically sustainable management of urban soil sealing and (2) who has competences and should take responsibility to steer soil sealing? The analyses are conducted in Germany. The assessment of strategies is carried out using indicators as part of a content analysis. Legal-planning, informal-planning, economic-fiscal, co-operative, and informational strategies are analyzed. Results show that there is a sufficient basis of strategies to secure urban ecosystem services by protecting urban green and reducing urban gray where microclimate regulation is a main target. However, soil sealing management lacks a spatial strategically overview as well as the consideration of services provided by fertile soils.
    AMBIO A Journal of the Human Environment 05/2014; 43(4):530-41. DOI:10.1007/s13280-014-0511-1 · 2.29 Impact Factor
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