With 276,526 residents in 2014, Graz is Austria’s second largest city.2For more than a decade, Graz has been Austria’s most rapidly growing residential urban area, and it has increased by 14 % between 2002 and 2013. The growing city size today poses a number of challenges to urban planners. Since the permanent settlement area has stayed almost constant since 1995 (being equal to approximately 97 km2out of a total available area of 127 km2), these challenges come in the form of limited land resources, but also in the form of increasing environmental pressure. Specifically, air pollution is a serious problem in Graz, which strongly affects the well-being
1The dominant modelling approach for UED management problems has focused on the spatial distribution of population and economic activity between the centre and the surroundings of a city (as e.g. in the New Economic Geography, cf. Fujita et al.1999; Brakman et al.2001). For a New Economic Geography based model of urban settlement structure, commuting and local environmental quality see Koland (2010) and Bednar-Friedl et al. (2011). We abstain here from the regional aspect in favour of understanding the intertemporal evolution of urban economic development and investigate the associated problem as one that progresses over time (but not in space).
2Data source: Prọsidialabteilung of the City of Graz.
of its residents, i.e. Graz suffers from high concentrations of particulate matter (PM10) which, especially in winter during stagnating weather conditions, multiply in excess of the European Union (EU) pollution limits. This situation is exacerbated by its geographical location south of the Alpine bow and the associated frequent weather inversions. While targeted policy measures have helped to substantially reduce emissions over the last two decades, air pollution is likely to remain an issue in the future, due to increasing traffic volumes and growing population numbers.3
A city like Graz clearly pools the advantages of proximity, such as the supply of a variety of goods and services (e.g. healthcare and education) and a sound public transport infrastructure, and it offers economic opportunities such as jobs, consumers and suppliers. Yet, along with the benefits of urbanisation come envi- ronmental, social and health problems. The quality of living in Graz results from a combination of centripetal and centrifugal forces which co-determine, in conjunc- tion with institutional and political conditions, residential location choice. When a city comes closer to its carrying capacity, the negative effects of overpopulation tend to outweigh the benefits of urban life, and maintaining urban areas as liveable places becomes a substantial challenge for local planners. The following variables may be used to describe the UED problem for Graz and similar cities:
Residential densityis regarded to be a key driver of UED dynamics. It can, however, be described by a spectrum of empirical measurements; apart from obvious ones such as population density, land use measurements may also be used to quantify residential density. To cover most of the spectrum, for the study focus of Graz, the following groups of time series data were collected and/or calculated: (1) urban population and population density (population per unit area), (2) construction of dwellings, building surface and building density (share of building surface in total permanent settlement area) and (3) sealed area and sealing ratio (share of sealed area in settlement area).4For Graz, we find a high positive and significant correlation of the urban population data for the period 2002 to 2013 with all other residential density indicators (see Table1, left column) and infer that the measurements for the number of residents can be used as a satisfactory proxy for residential density.
Quality of livingis perceived to be the second key driver for UED. This broad qualitative conceptinter aliaincludes environmental conditions (e.g. air pollution, noise, accessibility of parks), security conditions and the traffic situation (cf.
Magistrat2009,2013) alongside the supply of goods and services (e.g. healthcare, education, childcare) and the cost of living (e.g. housing prices). To capture the quality of living and its development over time for the city of Graz, the following data were collected: (1) air pollution (particulate matter concentration as averages per day, month and year as well as the number of exceedance days with respect
3Traffic volume causes half of the particulate matter emissions in Graz (39 % in winter season), followed by the emissions from industry and commerce (27 %; 22 % in winter) and domestic heating (23 %; 39 % in winter) (Heiden et al.2008).
4Data sources: own calculations based on data supplied by Statistics Austria, the Federal Office for Metrology and Surveying (BEV) and the Environment Agency Austria (UBA). See Table4in the Appendix for more details.
Table 1 Correlation (Spearman-Rho) of various indicators for Graz Urban population
(measured on 31st Dec of each year)
PM10 concentration (yearly average) Building surface 0.988** PM10 exceedance days (per
year)
0.963**
Building density 0.970** Green space (recreational area and gardens)
0.731*
Sealed area 1.000** Price of owner-occupied flats 0.782**
Sealing ratio 1.000** Property price 0.763**
Data sources: Statistics Austria; Regional Statistics Styria; Federal Office for Metrology and Surveying; Regional Government of Styria, Department of Air Monitoring; Austrian Federal Economic Chamber, Association of Real Estate and Asset Trustees; 1995–2013 own calculations Significance levels of correlations: ** 0.01, * 0.05
to EU-limits), (2) green space (parks and recreational areas), (3) wage income and (4) housing prices (prices of owner-occupied flats, of property, and of single-family houses).5We acknowledge that environmental quality is an important ingredient for the quality of living and a key determining factor in people’s settlement decisions.
Since a region’s environmental quality suffers from the emission and the re- circulation of air pollutants, and since it is affected by the level of sealed soil surface (buildings, road infrastructure), reducing exposure to particulate matter in urban areas is important for assure public health. A large number of epidemiological studies find that the exposure to nanoparticles such as PM10 leads to adverse health effects (e.g. Murr and Garza2009; McConnell et al.2006; Samet2007; Samal et al.
2008). In this regard, daily peaks and exceedance days, which mark EU limits for critical PM10 thresholds, matter the most, because PM10 concentration is harmful to the residents as soon as the threshold is reached.
Part of Graz’s permanent local air quality monitoring network is theGraz Don Bosco station that was already implemented in 2001. For example, in 2001 it counted 158 exceedance days of PM10 emissions while the number declined to 46 in 2013 (see Fig.1).6Looking at the Graz data, the yearly PM10 averages follow the same dynamics as the number of exceedance days per year, as can be seen in Fig.1(there is a significant correlation ofC0.963 between the two time series, see Table1). Therefore, we regard the yearly PM10 concentration as reasonable proxy for local air pollution, and we epitomise ‘quality of living’ by ‘air pollution’ (i.e.
5Data sources: Regional Government of Styria, Department of Air Monitoring; the Austrian Federal Economic Chamber, Association of Real Estate and Asset Trustees; Statistics Austria;
Regional Statistics Styria; own calculations based on data supplied by the Federal Office for Metrology and Surveying (BEV) and the Environment Agency Austria (UBA). See also Table5in the Appendix for more details.
6For PM10, the EU’s clean air policy imposes a limit of 50g/m3of air for the daily average value.
This limit may be exceeded by up to 35 days per year (25 days according to IG-L, the Pollution Protection Act/Air for Austria).
0 25 50 75 100 125 150 175
0 10 20 30 40 50 60
2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013
# exceedance days
PM10
yearly average (PM10 àg/m³) exceedance days (#) EU limit
value PM10
EU limit value exceedance days
Fig. 1 Yearly PM10 averages and number of exceedance days for the period 2001–2013 in Graz Don Bosco including limit values (dashed lines) for PM10 (40g/m3yearly limit) and exceedance days (35 days per year). Data source: Regional Government of Styria, Division 15 of Energy, Housing & Technology, Department of Air Monitoring, own illustration
inverse environmental quality). Furthermore, there are also strong and significant correlations of PM10 concentration with the other indicators for quality of living such as housing prices (Table 1, right column). On the one hand, the positive correlation between green space and PM10 concentration indicates that more green space leads to less PM10. On the other hand, the negative correlation between PM10 and, for example, property prices indicates that housing prices reflect environmental attributes and that environmental quality is a non-market good that people value.
Figure 2 illustrates the relationship of the key variables in the UED system:
residential density (measured by urban population) and quality of living (measured by local air pollution).