IMPACT OF CONCENTRATION OF URBAN ACTIVITIES ON TRANSPORT; COMPARATIVE ANALYSIS BETWEEN DUTCH AND JAPANESE CITIES

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1 IMPACT OF CONCENTRATION OF URBAN ACTIVITIES ON TRANSPORT; COMPARATIVE ANALYSIS BETWEEN DUTCH AND JAPANESE CITIES Cees D. van Goeverden Delft University of Technology, Transport and Planning Section Nobuaki Inoue and Kayoko Tsutsumi Fukuoka University, Civil Engineering 1. INTRODUCTION According to the principles of economic efficiency, the large Japanese cities developed an urban structure with a high concentration of economic activity and a relatively low residential density in the city centre. This development differs from that in many European cities, whose policy is to keep the cities compact for reasons of sustainability (Kaido, 2001). Moreover, in old cities with picturesque inner cities spatial development is strictly regulated, leading to higher dispersion of economic activities. The reason is to preserve city centres. An interesting question is whether the differences in urban structures bring about differences in travel behaviour and related environmental nuisance of traffic. The paper addresses this question. The relation between urban structure and travel behaviour has been extensively investigated in other studies. The general findings are that urban structure can have a significant but modest impact on travel behaviour (see for instance Maat, 2002, and Meurs et al., 2003). Some more specific findings are that compactness of the city reduces car use, mixed land use may have a slightly negative effect on car use, decentralization of work to suburban areas may decrease average trip length but increase share of the car, and a pedestrian-friendly design of the urban area as well as limited supply of car parking places reduce car use (Meurs, 2003). Partly based on these studies, two hypotheses are formulated regarding the influence of activity concentration. The first is: High concentration of activities leads to larger trip lengths. The rationale is that concentration of activities implies spatial separation between home and activity. The second hypothesis is: High concentration of activities supports use of space-efficient modes in general and public transport in particular. Space for vehicle storage is limited in concentration areas, so favouring space-efficient modes like public transport at the cost of space-consuming modes like the car. Besides, concentration of activities brings about concentration of traffic flows which makes public transport more competitive. The first hypothesis generally implies more pollution, the second less pollution. The investigation is done by comparing some Japanese and European cities regarding employment concentration, travel behaviour, and environmental impact of traffic. The latter is limited to the emission of CO 2. The selection of cities is explained in section 2. Section 3 describes the differences in urban structure of the selected cities in both countries. Section 4 deals with the differences in travel behaviour and traffic emissions. In section 5, the relation between concentration and travel behaviour is discussed. Finally, in section 6 the main findings are summarized.

2 2. SELECTION OF CITIES The selection of Japanese cities is limited to Kyushu, a group of islands in southern Japan including one main island where the largest cities are located. The selection of European cities is limited to the Netherlands. Kyushu and the Netherlands have about the same surface and the same number of inhabitants. Also the GDP is comparable. The main difference relates to the physical topography. Kyushu is very mountainous, while the Netherlands is almost flat. In Kyushu, the populated areas are limited to the coastal plains. In the Netherlands, the urbanized areas can be found everywhere in the country, though the population is relatively concentrated in the western and southern parts of the country. Figure 1 shows both the main island of Kyushu and the Netherlands on nearly the same scale. Fukuoka Kitakyushu Groningen Oita Nagasaki Kumamoto Miyazaki Amsterdam The Hague Utrecht Rotterdam Eindhoven Kagoshima Figure 1: The main island of Kyushu and The Netherlands The ranking of cities differs somewhat between Kyushu and the Netherlands. Based on municipality data, the largest cities of Kyushu are larger than those of the Netherlands. Kyushu has also more large cities but less medium-sized cities (Table 1).

3 Table 1: City ranking in Kyushu and the Netherlands Size of municipality Number of municipalities Name of the large (inhabitants) Kyushu The Netherlands municipalities (2000) (2001) Over 1 million 2 0 Fukuoka, Kitakyushu 500,000 to 1 million 2 2 Kumamoto, Kagoshima, Amsterdam, Rotterdam 250,000 to 500, Oita, Nagasaki, Miyazaki, The Hague, Utrecht 100,000 to 250, Less than 100, The following cities are selected for the comparative analysis: The two largest cities, Fukuoka and Amsterdam. Fukuoka is a good example of a strong centralized city, while Amsterdam is a good example of a city with a large old and picturesque inner city which development is limited by strict regulations. For instance, it is not allowed to build high buildings in the city centre. The two third largest cities, Kumamoto and The Hague. Kumamoto is again an example of a centralized city, but on a smaller scale than Fukuoka. The Hague is an old urban settlement that never got city charters and has not the urban layout of a typical Dutch city. A substantial part of the central area is rather new and the regulations for developments are less strict than in Amsterdam. The two second largest cities, Kitakyushu and Rotterdam, are left out of the analysis. They are less appropriate for the study for different reasons. Kitakyushu has an exceptional urban structure, because it is the amalgamation of five cities that have merged together. It has five nuclei instead of a single centre. Rotterdam lost its old centre in the Second World War. A completely new centre is build without serious restrictions regarding the height of buildings. Nowadays the centre of Rotterdam has the highest office buildings of the Netherlands and the city has the most centralized urban structure of the large Dutch cities. 3. DIFFERENCES IN URBAN STRUCTURE Next paragraphs discuss the differences in urban structures of the two defined city-pairs. The description of urban structures relates to three spatial levels: city centre, municipality and agglomeration. City centres are defined by joining adjacent districts or neighbourhoods in the inner city that have the highest employment density. Municipalities are administrative regions. Regarding agglomerations, both in Japan and in the Netherlands different definitions of agglomerations exist. In this study, agglomeration definitions are used that are based on functional relationships between the selected municipalities and the core city. The functional relationships are described by commuting and, in the Dutch cases, also by migration.

4 3.1. Fukuoka and Amsterdam Table 2 shows some general figures regarding city centres, municipalities and agglomerations of the largest cities, Fukuoka and Amsterdam. Table 2: Some general figures relating to Fukuoka and Amsterdam Fukuoka (1995) Amsterdam (2000) Centre Municip. Agglom. Centre Municip. Agglom. Area 1 (km 2 ) Population (*1000) Employees (652.8) 2 (*1000) Jobs (*1000) : excluding water 2: The number of employees is not available. The figure is estimated assuming that the ratio between employees and jobs in the municipality is also valid for the agglomeration. The figures indicate that the scale of the two cities is different. Fukuoka is larger than Amsterdam. It has a larger area and considerably more residents and employees. Only the areas of the defined centres are similar, while the number of residents in the centre of Amsterdam is even larger than that in the centre of Fukuoka. Employment is in Fukuoka centre considerably higher, however. Table 3 gives an overview of degree of centralization for the whole agglomerations. It shows residential and employment densities for the city centres, the remaining municipal areas and the remaining areas of the agglomerations. Table 3: Density figures for Fukuoka and Amsterdam (densities in ha) Fukuoka (1995) Amsterdam (2000) City centre municip. agglom. City centre municip. agglom. Residential density Employment density (3.8) 1 Employees/residents (0.41) 1 1: estimated figure The table shows that both residential densities and employment densities are highest in the city centres and lowest in the areas outside the city. The employees/residents rates are high in the city centres and have rather equal lower values in both other types of regions. Moreover, the table demonstrates the very high concentration of employment in the city centre of Fukuoka. The employment density in the centre is 30 times that of the remaining municipality. In Amsterdam this factor is only 7.4. The differences in urban structure between Fukuoka and Amsterdam are visualized in two ways. The first is Figure 2. The figure shows the area of the municipality of Amsterdam compared to a) the area of Fukuoka that has the same number of residents as Amsterdam and b) the area of Fukuoka that has

5 the same number of employees. The areas of Fukuoka are defined by starting at the city hall in the centre and then increasing the area in all directions, summing the residents and employees until they are equal to those of Amsterdam. Figure 2: Illustration of the high employment concentration in Fukuoka The area in central Fukuoka that harbours the number of employees that equals the number in the whole municipality of Amsterdam is only a fraction of the area of Amsterdam (a little bit more than 10%). The area in Fukuoka that accommodates the same number of residents as Amsterdam is also smaller than the area of Amsterdam. This is remarkable, because the residential density in Amsterdam is higher, both in the centre and in the remaining municipality (see Table 3). One may conclude from this, that the residential density in Fukuoka municipality is higher near the centre than in the outskirts of the town. The second way to visualize the differences in urban structure is by drawing distribution curves that show the differences in employees and employed residents as a function of the distance to the centre. Figure 3 shows the cumulative distributions of these differences if one moves outwards from the centre. The curves may be illustrated by an example. The point on the Fukuoka curve from 1975 belonging to 5 km from downtown is valued 519. This means, that, if you draw a circle of 5 kilometres from the city centre, this circle encloses an area where the number of employees exceeds the number of employed residents by 519,000. Figure 3: Cumulative distribution curves for Fukuoka and Amsterdam

6 The rather flat curve of Amsterdam illustrates the relatively equal distribution of residents and employees over the city Kumamoto and The Hague Next the cities of Kumamoto and The Hague will be compared. Table 4 shows some general figures. Table 4: Some general figures relating to Kumamoto and The Hague (2000) Kumamoto The Hague Centre Municip. Agglom. Centre Municip. Agglom. Area 1 (km 2 ) Population (*1000) Employees (370.3) 2 (*1000) Jobs (*1000) : excluding water 2: estimated figure Kumamoto is larger than The Hague. This is in particular true for the size of the area. The area of the municipality of Kumamoto is 3 to 4 times that of The Hague, while population and employment are 1.15 to 1.3 times larger. On the other hand, the size of the city centre of Kumamoto, as defined in the paper, is smaller than that of The Hague. It houses less residents and about the same number of employees. Again, in the city centre residential densities are higher in the Dutch city, while employment densities are higher in the Japanese city. This is also indicated by Table 5. Table 5: Density figures for Kumamoto and The Hague (densities in ha) Kumamoto (2000) The Hague (2000) City centre municip. agglom. City centre municip. agglom. Residential density Employment density (6.7) 1 Employees/residents (0.40) 1 1: estimated figure However, the employment densities in the city centres are much more close to each other than those of Fukuoka and Amsterdam. The case is that employment density in the centre of Kumamoto is considerably smaller than that of Fukuoka, while employment density of The Hague equals that of Amsterdam. The degree of concentration seems to fall down with decreasing scale of the town in Japan, while there may be no clear relation between concentration and town scale in the Netherlands. Of course, the number of observed cities is too small for a strong support for this kind of general statements. The residential and employment densities in both the remaining municipality and the agglomeration outside the municipality are much lower in Kumamoto

7 than in The Hague. One may conclude that both the concentration of employment and that of residents are higher in Kumamoto than in The Hague. 4. DIFFERENCES IN TRAVEL BEHAVIOUR AND TRAFFIC EMISSIONS In section 1 influences of concentration on both trip distance and modal split are hypothesized. Next trip distances and modal shares in the selected cities are described. The description of trip distances includes both the average trip distance and kilometres travelled per person per day. The latter are relevant for calculating the environmental impact. The analysis is based on travel survey data. In Japan, every 10 years a survey is performed in the large urbanized areas. The consulted surveys are the surveys of the Greater North Kyushu area (1993) and the Greater Kumamoto area (1997). In the Netherlands, an annual survey is performed for the whole country. Because the number of observations is relatively low on the level of a single agglomeration, the databases of three successive years are used, 1999 to One should keep in mind that travel characteristics as far as they are registered in travel surveys depend on the set-up of the survey. It has been proved in the Netherlands that changes in the set-up of the national survey may have a substantial impact on, for instance, the number of trips per person per day. Therefore, observed differences in the next sections can be attributed (partly) to differences in the set-up of the Japanese and Dutch surveys Trip distance The analysis of trip distances is complicated by the fact, that in Japanese surveys the respondents are not asked for their trip distances. In the Dutch surveys, the respondents are asked to fill in the distance of each trip, but it has been proved that they generally overestimate the actual distances. Both surveys register travel time. The problem of missing distances in the Japanese surveys is solved by estimating the distances under the assumption that the average speed by mode in the Japanese cities equals the speed in the Dutch cities. For the Dutch cities, the average speed for the complete trips is calculated by main mode. Using the same speed for the Japanese cities, trip distances can be estimated. Assuming, that the registration of the travel times is correct in both the Dutch and the Japanese cities, or that they have the same bias, the resulting distances are in principle overestimated just like the Dutch distances. For comparing the Japanese and Dutch distances this is no problem. Table 6 shows average trip lengths, number of trips per person per day and trip distances per person per day. The figures relate to all trips that start or end in the agglomeration and that are made by the residents of the agglomeration. Trips of persons younger than 5 years old (Japan) or 6 years old (the Netherlands) are excluded.

8 Table 6: Trip distances in the four agglomerations Average trip length (km) Trips pppd Trip kilometres pppd Fukuoka Kumamoto Amsterdam The Hague : estimated figure The table suggests that trip length is larger in Japanese agglomerations. However, one should keep in mind that the margins of the estimated distances are substantial. Given the rather small differences between trip lengths, there is no hard evidence about the differences. An interesting observation is the substantial difference between the number of trips per person per day between the Japanese and Dutch cities. Do increasing distances to activities decrease the number of trips? This seems not to be the case, because there is no clear difference between trip numbers in Fukuoka and Kumamoto, despite a large difference in employment concentration. Maybe Japanese people make generally less trips than Dutch people. Another possible explanation is that the set-up of the Japanese surveys results in lower trip numbers than the set-up of the Dutch surveys. Multiplying the larger trip lengths and smaller trip numbers of the Japanese cities produces slightly more trip kilometres. Of course, also for these figures large margins apply, making the observed differences doubtful Modal split Table 7 shows the modal split in the four agglomerations. Multimodal trips are represented by the defined main mode. The definition is based on an assumed hierarchy between the modes. Table 7: Modal split in the four agglomerations Fukuoka Kumamoto Amsterdam The Hague Walk 23.9% 17.6% 20.3% 20.8% Bicycle 11.4% 12.4% 24.2% 23.5% Moped 2.5% 3.8% 0.8% 1.0% Motorcycle 0.8% 0.9% 0.3% 0.3% Car 1 driver 35.7% 48.9% 28.0% 30.5% Car 1 passenger 7.9% 10.5% 12.5% 13.3% Bus 6.2% 4.1% 3.4% 2.5% Tram - 0.7% 6.3% 4.4% 2 Underground % Train 1.1% 3.6% 3.2% Other 0.0% 0.1% 0.5% 0.4% 1: including taxi 2: nearly all tram, being no underground network in The Hague, but includes also some trips by underground in other cities

9 Remarkable findings from the table are: The share of the bicycle is high in Dutch cities. Since the Netherlands is famous for its high bicycle use, a comparison between Dutch cities and most of the other European cities would also display a higher bicycle share for the former. The share of motorized cycles is much higher in Japanese cities. The share of car drivers, that represent the number of cars, is higher in the Japanese cities, especially in Kumamoto. On the other hand, the share of car passengers is lower in the Japanese cities. Therefore, car occupation is substantially lower (1.22 versus 1.44 persons per car in the Japanese and Dutch cities respectively). The share of public transport is high in Fukuoka, but low in Kumamoto. Within public transport, in the Japanese cities the share of the bus is relatively high, while in the Dutch cities the rail modes are dominant. Generally, the shares of car and public transport seem to increase and decrease respectively when the city size decreases. It is likely that employment concentration affects mainly commuting trips, rather than trips for other purposes. Table 8 shows modal split figures for commuting trips. Table 8: Modal split in commuting trips in the four agglomerations Fukuoka Kumamoto Amsterdam The Hague Walk 9.8% 5.3% 4.2% 5.2% Bicycle 10.1% 10.1% 23.8% 26.1% Moped 3.8% 5.3% 1.7% 2.2% Motorcycle 1.4% 1.5% 1.0% 0.6% Car 1 driver 36.6% 64.5% 39.7% 41.3% Car 1 passenger 4.4% 4.4% 5.1% 5.3% Bus 14.7% 6.4% 4.8% 3.7% Tram - 1.1% 11.2% 7.2% Underground % Train 1.3% 8.2% 8.0% Other 0.0% 0.1% 0.4% 0.4% 1: including taxi Comparing shares for commuting trips to those for all trips, one can see that the share of walking is much lower and the shares of the motorized cycles and public transport are much higher. Except for Fukuoka, also the shares of the car are higher. The car occupancies are lower, especially for the Dutch cities and Kumamoto. Car occupancy in Fukuoka is now comparable to that of the Dutch cities Environmental impact The analysis of environmental impacts is limited to the emissions of CO 2. The emissions are calculated by multiplying a mode specific emission factor with the distance that residents of an agglomeration travel with the relating mode on an average day. The emission factors indicate the emissions by travelling

10 one km with a certain mode. The calculated emissions are the emissions per person per day. Then they are comparable for the different cities. Table 9 presents the emission factors and the calculated emissions by mode. Table 9: Emissions of CO 2 per person per day in the four agglomerations Emission Emissions (g/pppd) (g/person km) Fukuoka Kumamoto Amsterdam The Hague Soft modes Moped Motorcycle Car + taxi Bus Rail Other Total : emission per car kilometre The emission factors of the private modes are estimated by Geurs et al. (1998) and apply to the Netherlands. The emission factors for the public modes are provided by the Japanese government (Ministry of Land, Infrastructure and Transport, 2000) and concern the Japanese average. Dutch studies indicate that the bus figure in the Netherlands is lower while the rail figure is higher. The differences may be due to different vehicle occupancies. However, we use for each mode the same emission factor for both countries in order just to eliminate possible differences in total emissions that must be ascribed to different emission factors. The table shows that the car is responsible for by far the largest part of total traffic emissions. Therefore, the differences in emissions between cities are mainly caused by differences in car use. It is not surprising that the emissions are highest in the Japanese cities, because they have the highest car use (Table 7). In Kumamoto the emissions are yet substantially higher than in Fukuoka, while those in The Hague are lower than in Amsterdam. Only the latter finding is not suggested by the share of car drivers in Table 7, because this share is a little higher in The Hague. However, Table 7 displays the shares in the number of trips. Car emissions are not related to the number of car trips but to car kilometres. The latter are lower in The Hague, because the average length of car trips is considerably shorter. 5. IMPACT OF EMPLOYMENT CONCENTRATION Regarding the hypothesized impact of employment concentration on travel behaviour two questions have to be answered. First, are the observed differences between the Japanese and Dutch cities in line with the hypotheses? Second, can the observed differences be attributed to a causal relation between concentration and travel? The outcomes of the former analysis are that a) Japanese cities have by far the highest employment concentration, b) trip lengths seem to be highest in the Japanese cities, though there is no hard evidence about differences in trip lengths,

11 c) there is no unambiguous result regarding shares of public transport; the largest Japanese city, Fukuoka, has a higher share than the Dutch cities, the smaller city, Kumamoto, has a considerably lower share, d) car shares are higher in the Japanese cities (especially in Kumamoto), e) the estimated environmental impacts are highest in the Japanese cities, mainly due to higher car shares combined with lower car occupation. Hypothesis 1, presuming a positive contribution of concentration to trip length, is supported by the findings, though the support is not strong because of uncertainties. Hypothesis 2, presuming that concentration affects use of public transport positively and car use negatively, is only supported regarding public transport use in Fukuoka. Findings regarding public transport use in Kumamoto and car use in the two Japanese cities are contradictory to the hypothesis. Can be said anything about the causal relation between employment concentration and travel behaviour as well as environmental impacts? Of course, concentration will be not the only influencing factor. Also other factors, not included in the analysis, play a role. These may weaken observed support for the hypotheses, but could likewise explain why a true hypothesis still is not supported. One possible additional factor explaining trip length could be the area of the agglomeration. Table 6 shows that in both countries trip length is shorter in the agglomeration with the smallest area. Because the areas of the two Japanese cities are larger than those of the Dutch cities, this factor may partly explain the higher trip lengths in Japan, so weakening the still rather weak support for hypothesis 1. On the other hand, the contradictory results regarding modal split in Kumamoto could be explained by the low residential densities in the Kumamoto area. Low densities are in favour of the car and disadvantageous for public transport. These effects may overrule the effects of employment concentration. Another possible factor explaining the relatively low car use in the Dutch cities is the Dutch cycling culture, assuming that higher bicycle use is partly at the expense of car use. German figures support this assumption. Lower bicycle shares in German cities are compensated by higher shares of walking, car driver, and public transport (Socialdata, 2006). If the Dutch were less bicycleminded, the shares of car driver in cities like Amsterdam and The Hague might have been between 30 and 40% and could have exceeded the share in Fukuoka. However, also shares of public transport would have been higher (presumably 15-20%, according to the German figures), which may eliminate the difference between Amsterdam and Fukuoka, the only initial support for the modal split hypothesis. The Dutch cycling culture could also be the main explaining factor for the relatively small traffic pollution in the Dutch cities, rather than low employment concentration. Though there is some weak support for the trip distance hypothesis while also validity of the modal split hypothesis can be motivated, a clear causal relation between employment concentration on the one hand and trip distance, modal split and environmental impact of traffic on the other hand cannot be proved. Inclusion of more cities into the analysis might give more evidence about this relation.

12 6. CONCLUSION In the two selected Japanese cities, Fukuoka and Kumamoto, employment is more concentrated in the city centre than in the two selected Dutch cities, Amsterdam and The Hague. In particular in Fukuoka, the largest of the four cities, the employment concentration is very high. There is a large difference in concentration between the two Japanese cities, while in both Dutch cities the degree of concentration is rather equal. The analysis of the influence of employment concentration on travel behaviour does not prove any relation between the two factors. The assumed influences on travel distance and modal split could not be clearly confirmed, though there is some evidence that concentration enlarges the average trip length. The analysis is complicated by data problems that enlarge the margins of the outcomes as well by lack of knowledge about the influence of other explanatory variables. The emissions of CO 2 are almost fully determined by car emissions. The Japanese cities, that have the highest car use, have also the highest emissions. This is in particular true for Kumamoto. Two significant differences between Japanese and Dutch cities that lead to higher emissions in the former are car occupation and bicycle use. Both are substantially lower in Japanese cities. If one aims to reduce pollution, a policy to reduce car use and increase car occupancies is advisable. But still the question remains whether car use can be influenced by affecting employment concentration. ACKNOWLEDGEMENT The research is supported by the Obayashi foundation. The authors are grateful for that. BIBLIOGRAPHY Geurs, K.T., Brink, R.M.M. van den, Annema, J.A., Wee, G.P. van (1998) Verkeer en vervoer in de Nationale Milieuverkenning 4, Rijksinstituut voor Volksgezondheid en Milieu, Bilthoven, The Netherlands Kaido, K. (2001) Compact City, Gakugei-shuppan, Kyoto Maat, K. (2002) The compact city: Conflict of interest between housing and mobility aims in the Netherlands. In: Stern, E., Salomon, I. and Bovy, P.H.L. (Eds.), Travel Behaviour, Spatial Patterns, Congestion and Modelling, Edward Elgar, Cheltenham UK and Northampton USA, pp Meurs, H. (2003) Special issue: Land Use and Sustainable Mobility, editorial summary of The European Journal of Transport and Infrastructure Research 3 (2)

13 Meurs, H., Wee, G.P. van (2003) Land Use and Mobility: a Synthesis of Findings and Policy Implications, European Journal of Transport and Infrastructure Research 3 (2) Ministry of Land, Infrastructure and Transport of Japan (2000) The Economic White Paper 2000 Socialdata (2006) Mobilität und Verkehrsmittelwahl, Erhebungen mit dem KONTIV-Design, figures provided at the website Survey of the Greater North Kyushu area, 1993 Survey of Greater Kumamoto area, 1997 Dutch Central Bureau of Statistics (CBS), Dutch National Travel Survey (OVG), databases of 1999, 2000 and 2001