Climate change and destination choices

CESAR WORKING DOCUMENT SERIES Project 1, working document no.1

Climate change effects on destination choices for daily activities in the Randstad Holland Second climate change analysis on Dutch National Travel Survey (MON) data

L. Böcker, J.Prillwitz and M.Dijst 19 March 2012

This working document series is a joint initiative of the University of Amsterdam, Utrecht University, Wageningen University and

Research centre and TNO

The research that is presented in this series is financed by the NWO program on Sustainable Accessibility of the Randstad: http://www.nwo.nl/nwohome.nsf/pages/nwoa_79vlym_eng

CESAR Project 1 working document series no.1 Climate change and destination choices

Page 2

TABLE OF CONTENT

1. INTRODUCTION................................................................................................................ 3

2. RESEARCH DESIGN ........................................................................................................... 3

3. ANALYSIS.......................................................................................................................... 5

4. REFERENCES................................................................................................................... 12


Page 3

1. INTRODUCTION

In the light of a growing societal interest for climate change adaptation, various recent studies have looked into the relationship between climate/weather and a variety of daily travel choices, such as choices for transport modes, departure times and routes (see for an overview of the literature Koetse and Rietveld, 2009 and Böcker, et al, submitted), as well as on long term preferences for tourism destinations (Nicholls and Amelung, 2008; Amelung and Viner, 2006; Hamilton et al., 2005; Bigano et al., 2006; Matzarakis and De Freitas 2001). However, the impact on daily destination choices has largely been neglected by these contributions. This is remarkable, since the role of changing weather patterns for daily destination choices is highly relevant from a geographical point of view. One can think of citizens escaping inner-‐city heat to recreational sites and shopping complexes outside cities, or a switch from active outdoor to inactive indoor activities with increasing periods of precipitation. Consequently, this study analyses the effects of projected climate change on the demand for different types of activity-‐destinations (like indoor/outdoor and recreational/maintenance) in different urban, suburban and rural residential environments in the Dutch Randstad. This working document presents the research design and preliminary analyses of seasonal climate change effects on destination choices in the Randstad Holland. First the research design will be outlined. Thereafter an analysis will be provided of the effects of climate change on: the balance between leisure and utilitarian activities; the participation into various activities; destination locations; and travelled distances in the Randstad Holland.

2. RESEARCH DESIGN

This research is located in the Randstad Holland. The densely populated region is located in the west of the Netherlands, spanning the area around the four largest cities Amsterdam, Rotterdam, The Hague and Utrecht. This region forms the study area of the CESAR-‐project (Climate and Environmental change and Sustainable Accessibility of the Randstad) on sustainable urbanisation and accessibility in which this study is embedded (http://www.nwo.nl/nwohome.nsf/pages/NWOP_7YUHV3_Eng).

This study’s research design is similar to an earlier research on climate change effects on mode choices and travelled distances (Böcker et al., submitted). Based on Randstad meteorological records (KNMI, 2011) and four regional climate change scenarios reflecting variations in global temperature rise (+1 to +2˚C) and prevailing wind patterns (KNMI, 2009), we estimate present as well as 2050 seasonal averages. In order to analyse climate change effects we select, from the last decade, seasons with average weather conditions for the climate at present as well as seasons with weather conditions projected to be average in 2050 (KNMI, 2009). Selected seasons represent precipitation and temperature patterns as accurately as possible. To address not only amounts but also distributions of precipitation, we include seasonal precipitation sums as well as numbers of wet days (≥0.1mm). With regard to temperature, seasons at the higher end of the projected 2050-‐bandwidth are preferred, as underlying climate scenarios for these are more likely to occur (KNMI, 2009). If necessary, precipitation is valued over temperature as a selection criterion, because of its higher significance for travel behaviour in the literature (e.g. Cools and other, 2010).

Table 1 presents shows the selected seasons. At present, the Randstad Holland is subjected to a maritime climate characterised by warm summers, mild winters with moderate but relatively stable year-‐round precipitation. For 2050, winters are projected to become much milder and wetter; springs warmer and wetter; summers hotter with at periods heavier precipitation as well as more intensive drought; and autumns will become warmer with also at periods intensified precipitation as well as drought, although less than in summer.


Page 4

Table 1: Overview of changing climate patterns present-2050 in the Netherlands, for the selected seasons Temperature Precipitation Selected season Average in ˚C Seasonal sum in mm # of days ≥0.1mm Present 2050 Present 2050 Present 2050 Present 2050 Winter 2004/05 2007/08 3.6 5.1 176 218 50 47 Spring 2005 2008 9.8 10.2 152 197 57 49 Summer 2009 2006 17.4 18.5 180 263 43 38 Autumn 2008 2005 10.2 12.0 267 241 50 43 Source: Böcker et al., forthcoming From 2004-‐2009 Dutch National Travel Survey data (Mobiliteitsonderzoek Nederland) we analyse activity data for the selected seasons. The total annual number of respondents varies from around 66,000 in 2004 to 40,000 in 2009. From a sub-‐sample of participants living in the Randstad region with the age of 18 years and older, we select heads of households and their partners only. For different activity destinations – work/study, maintenance (including shopping under 30 minutes), picking up persons, social visit, leisure-‐shopping (30 minutes or longer), leisure-‐touring and leisure-‐other – we analyse seasonal climate change effects on demand and location choice in terms of travelled distance and urbanization degree. Unfourtunately, an exact subdivision between indoors and outdoors leisure activities could not be made from the existing data. Generally, however, the leisure touring category comprises activities with a more outdoors character (recreational trips, including walking/cycling tours), whereas the leisure other category includes, in addition to some activities that could be either indoors or outdoors (hobby, sports), a lot of typically indoors activities (cultural activities, church, community center, etc). In the multivariate part we control for various independent individual/household attributes and spatio-‐temporal attributes in which trips are situated. As individual attributes we include age, gender, education level and workweek duration. We include the household attributes car availability, household income, and household type. The latter is a typology based on household size, presence of children under the age of 12, and the number of adults participating in the labour market. As spatial attributes we include address densities of the destination and the place of residence and as temporal attributes we include activity timing in view of day/night, peak/off-‐peak and weekday/weekend. Figure 1 summarizes all variables into a conceptual framework. Figure 1: Conceptual framework of variables used


Page 5

Activity demand is estimated in terms of the number of trips per person per day. Hereby use is made of negative binomial regression models, which, unlike Poisson regression, can deal with over-‐dispersed count-‐data with excess zeros generated by the large number of people not participating certain activities on a day. Travelled distance is estimated per trip by regression analyses. Activity location is estimated with binary logistic regressions in terms of whether or not people on the day of enquiry made a trip towards locations of varying urbanization degrees subdivided into five classes. For all analyses separate models are estimated for the different activity types. In order to address seasonal climate change effects, they are conducted for the full sample and thereafter repeated for the four separate seasons.

3. ANALYSIS

3.1 Recreational and utilitarian trip generation

In the literature we have encountered that on a daily level under dry and moderately warm weather conditions, people generally perform more, or cancel less, recreational trips, than under wet, cold or very hot weather conditions, whereas utilitarian trips remain more or less unaffected (Aaheim and Hauge, 2005; Sabir, 2011; Cools et al, 2010). Projected for the Randstad climate change generates warmer weather in all seasons in 2050. Especially in winter the temperature effect may have positive effects on recreational activities, whereas an extra increase in summer temperature will not, and may on the contrary at days have a negative effect. However in winter and spring also precipitation increases, which could counter the positive effect on recreational trips.

In order to address whether people adjust their number of recreational and utilitarian trip to changing climate conditions, we descriptively analyse the number of recreational and utilitarian trips. Hereby recreational trips include trips made for social and leisure purposes including shopping trips longer than half an hour. Utilitarian trips include trips with the purpose of work/study, errands and the bringing or picking up of people. It appears that in winter, spring and summer, as well as year-‐round, people approximately make as many recreational trips as utilitarian trips, and that this ratio remains relatively stable when we compare 2050 to present seasons. In autumn a slight increase in the share of recreational over utilitarian trips can be observed from 44% at present to 47% in 2050. Although these figures do not point at clear climate change effects, we perform a multivariate analysis to see whether effects appear when controlled for various background variables.

The five binary logistic regressions – one for each season and one for the full year – presented in Table 1, show the effects for various independent background variables, including climate change, on whether a trip is recreational or utilitarian. The impacts of socio-‐demographic, household and temporal attributes are as could be expected, with for instance more recreational trips for elderly, couples and singles, especially those who work less, and for trips off-‐peak and in the weekend. Table 1: Determinants for the ratio between recreational and utilitarian trips

Binary logistic regression: Recreational trip generation (ref. = utilitarian trips) Winter Spring Summer Autumn All

B S.E. B S.E. B S.E. B S.E. B S.E.

Constant 1,461 *** ,160 1,521 *** ,160 1,394 *** ,168 ,791 *** ,160 1,289 *** ,080

Age (ref.=30-49) 18-29 -,110 ,086 ,068 ,090 ,060 ,090 ,028 ,090 ,007 ,044

50-64 ,107 * ,065 -,002 ,065 ,022 ,063 ,155 ** ,063 ,061 * ,032 65-75 ,442 *** ,105 ,055 ,104 ,053 ,103 ,539 *** ,108 ,255 *** ,052 75+ ,421 *** ,129 ,037 ,128 ,008 ,130 ,502 *** ,129 ,222 *** ,064


Page 6

Gender (ref.=female) male -,295 *** ,052 -,210 *** ,054 -,218 *** ,051 -,214 *** ,053 -,229 *** ,026

Education (ref.= higher) lower_education -,068 ,059 -,046 ,060 ,033 ,059 -,019 ,059 -,020 ,029

middle_education -,152 *** ,054 -,056 ,056 -,046 ,055 -,126 ** ,056 -,096 *** ,027

Work duration (ref. <12h/w) >30 hours/week -,621 *** ,082 -,520 *** ,082 -,564 *** ,082 -,565 *** ,081 -,556 *** ,040 12-30 hours/week -,630 *** ,084 -,416 *** ,087 -,307 *** ,088 -,313 *** ,084 -,410 *** ,043

Household type (ref.= family. 2 workers)

family 1 or no worker -,321 *** ,109 -,225 ** ,107 -,094 ,117 -,097 ,113 -,167 *** ,055 couple 1 worker ,250 ** ,109 ,414 *** ,115 ,409 *** ,115 ,510 *** ,113 ,407 *** ,056 couple 2 workers ,282 *** ,081 ,130 ,088 ,373 *** ,085 ,448 *** ,084 ,324 *** ,042 couple no worker ,436 *** ,122 ,685 *** ,125 ,559 *** ,125 ,527 *** ,126 ,574 *** ,062 single and worker ,111 ,104 ,254 ** ,104 ,340 *** ,103 ,389 *** ,108 ,303 *** ,052 single no worker ,433 *** ,141 ,601 *** ,145 ,561 *** ,143 ,528 *** ,142 ,553 *** ,071 other ,209 *** ,080 ,218 *** ,083 ,273 *** ,083 ,252 *** ,081 ,251 *** ,041

Household income (ref.<15K)

15,000 to 29,999 euros ,141 ,096 -,162 ,099 -,112 ,100 ,302 *** ,097 ,048 ,049 30,000 euros or more ,015 ,098 -,022 ,103 -,085 ,103 ,165 * ,098 ,033 ,050 unknown ,066 ,101 ,055 ,109 -,195 * ,107 ,052 ,103 ,006 ,052

Car ownership (ref.=no car) 2 cars or more ,062 ,093 -,034 ,090 ,096 ,092 ,049 ,095 ,036 ,046

1 car and main driver ,019 ,081 ,044 ,078 ,044 ,080 -,028 ,083 ,018 ,040 1 car. not main driver ,011 ,095 ,111 ,092 ,207 ** ,093 ,146 ,097 ,121 ** ,047

Geographical context address density residence ,006 ,016 -,023 ,017 -,015 ,017 ,000 ,017 -,009 ,008 address density destination -,014 ,013 -,015 ,014 -,020 ,014 ,006 ,014 -,011 ,007

Temporal context

weekend (ref. = weekday) -1,440 *** ,054 -1,286 *** ,055 -1,284 *** ,055 -1,336 *** ,056 -1,329 *** ,027 night (ref. = day) ,545 *** ,054 ,224 *** ,085 ,165 ,129 ,416 *** ,061 ,318 *** ,032 peak (ref. = off-peak) -2,570 *** ,094 -2,118 *** ,087 -1,917 *** ,082 -2,099 *** ,084 -2,143 *** ,043

2050 Climate change ,019 ,044 -,097 ** ,047 ,047 ,047 ,131 *** ,047 ,012 ,022

Goodness of fit Pseudo R2 (Nagelkerke) .342 .302 .271 .314 .304

*p<0.10; **p<0.05; ***p<0.01 When tested multivariately, in spring a significant decrease in recreational trips can be observed, which may have to do with the fact that in spring 2050 weather conditions not only got warmer but also wetter. In line with the descriptives a positive effect can be observed in autumn, which could be explained by the combination of warmer weather with an increasing number of dry days in the 2050 autumn season: conditions under which we expected people to participate more in recreational


Page 7

trips. During the other seasons, temperature also increases but this is accompanied by an increase in (heavy) precipitation. As with the descriptives, no significant climate change effects have been found on the ratio between utilitarian and recreational trips in winter and summer as well as year-‐round. Overall, therefore, seasonal climate change effects on the ratio between recreational and utilitarian trips may seem quite marginal. When put in perspective, this is however not entirely surprising, as it may be questioned whether substitution between leisure and utilitarian activities, as observed in the literature on a daily level, may actually take place on a seasonal level.

3.2 Trip generation and travelled distances for different activity types

In section 4.1 we observed a relative decrease in leisure over utilitarian activities in spring and a relative increase in autumn. However from this ratio we cannot conclude which changes in absolute terms take place. Neither, it becomes clear exactly which different types of utilitarian and recreational trips are affected by climate change. In this section we will therefore subdivide within recreational as well as utilitarian trips between different activity types. Based on the literature we expect that the participation in different types of recreational activities is more subjected to changing weather conditions than that in utilitarian activities (e.g. Cools et al., 2010; Brandenburg et al., 2004). In the literature we have also encountered that physical activities (e.g. Chan and Ryan, 2009) outdoor leisure activities (Spinney and Millward, 2010) and walking/cycling trips (e.g. Keay, 1992; Aultman-‐Hall, 2010) are positively affected by warm and dry weather conditions and negatively by wet, cold or very hot weather conditions. Hence our expectation is to observe within the recreational sphere an increase in leisure-‐touring activities in the slightly wetter but much milder 2050-‐winters, and an opposed effect in the hot 2050-‐summers with increased heavy precipitation and drought. For the generally more indoor and less active leisure-‐other and leisure shopping categories, which are competing within the same leisure time budget as leisure-‐touring and partially satisfy the same needs (Nijland et al., 2011), we expect reversed effects due to potential substitution.

Figure 2 presents the relative impact of seasonal climate change effects on various activity types expressed in per cent changes. The activities are ordered, based on the size (not direction) of climate change impact summed up for the different seasons, with maintenance activities on the left resembling the smallest impact and leisure touring activities showing the highest impact. In line with the literature and our expectations Figure 2 clearly demonstrates that the participation into recreational activities, such as the leisure other and leisure touring categories, is much more sensitive to climate change than the participation into utilitarian activities such as work/study and maintenance. Figure 2: Seasonal climate change effects on per cent changes in number of trips per person per day for different activity types


Page 8

Two exceptions here are the relatively higher climate change impact on more or less utilitarian category of bringing and picking up persons, and the relatively lower climate change impact on the more or less recreational category of social visits. An explanation for the first could be that bringing or picking up persons may, in some cases, be a more voluntary or even recreational event. Explanations for the latter could be that social visits cannot easily be substituted for by other activities (regardless of the weather in a season one wants/needs to meet friends and family), that social visits may need to be planned far in advance, and that social home visits may often be flexibly located indoors or outdoors (as they may be situated inside, in the garden or on the terrace), and for all these potential reasons are less subjected to the weather. Again we will first turn to the multivariate part before discussing into detail the results in the context of seasonal climate change.

In order to analyse trip generation multivariately, we estimated 35 negative binomial regression models: for each activity type one model per season and one for the full year. In these models, climate change effects are analysed along with the effects of various individual and household background predictors. Table 2 summarizes only the effects for climate change; we will not go into detail into the effects of the other predictors, but upon checking their respective effects seemed logical. Table 2: Climate change effects on frequencies for various activities

Negative binomial models: Climate change effects on # trips/person/day Winter Spring Summer Autumn All seasons

B B B B B Work/study -,045 -.019 .085 -,056 -,012 Maintenance -.091 -..099 -.019 .000 -.036 Picking up .294 *** .220 ** -.142 ,190 ** ,071 * Social visit .089 -.019 -.076 .127 * .061 ** Leisure shopping -.032 -.171 *** .188 *** .024 -.018 Leisure touring .475 *** .277 *** -.327 *** -.129 * .097 *** Leisure other -.321 *** -.243 *** .210 *** .207 *** -.088 *** All trips .012 -.025 .020 .008 .005 Goodness of fit: Unscaled deviance/df lies between .43 and .63 and unscaled Pearson Chi2/df between .71 and 1.66. All full models are significant improvement over intercept-only models (Omnibus-test). In most models the majority of predictors is significant.

*p<0.10; **p<0.05; ***p<0.01 In line with the descriptives utilitarian trips remain largely unaffected by climate change. Work trips, remain largely unaffected by climate change, and so do errands trips. Climate change does seem to strongly increase trip for bringing and picking up persons in winter. Additional analysis (not included in this paper) shows that this is mostly an increase of trips by active transport modes, indicating that it may often involve people (parents) who, with the milder 2050-‐winter weather, more often bring or pick up others (their children) by foot or bicycle. Also in spring and autumn this category increases significantly, whereas in summer a non-‐significant decrease is observed.

Under recreational trips more significant climate change effects can be found. In line with the decriptives social visits are an exception. For social visits we observe non-‐significant effects for all seasons except for autumn and full year, when significant positive effect can be identified. In line with the decriptives and our expectations, leisure touring trips increase highly significantly in the warmer and wetter 2050-‐winter and –spring, whereas highly significant declines are observed in the hotter/warmer 2050-‐summer and -‐autumn with intensified precipitation and drought. These effects on leisure-‐touring coincide with the higher use of active open-‐air transport modes in the Randstad-‐Holland in 2050-‐winter and spring seasons in contrast to the lower use of these in summer and autumn, found in an earlier publication (Böcker et al., submitted). As expected, leisure-‐shopping and leisure-‐other trips are subjected to seasonal climate change in the exact


Page 9

opposite directions. Both decrease in winter (although shopping insignificantly) and spring, while increasing significantly in summer. In autumn, shopping non-‐significantly decreases and leisure-‐other significantly increases. Although comparison between the activities should be made carefully (as of the separate models) and substitution effects cannot directly be derived, there seems a strong indication that people substitute between on the one hand the more active and outdoors leisure-‐touring activities and on the other hand the leisure-‐shopping and leisure-‐other activities with a more mixed/indoors character.

For travelled distances our expectations are less clear. Based on one earlier Norwegian study (Aaheim and Hauge, 2005), an increase in leisure trip distance may be expected when weather conditions get warmer and dryer, whereas decreases may be expected when weather conditions get colder and wetter. This supports the intuitive way of reasoning that climate change effects on trip frequencies would be more or less in line with the effects on trip generation. However, climate change effects could also work their way through on travelled distances indirectly via the choice for transport modes – a problem recognised but not accounted for by the earlier Norwegian study (Aaheim and Hauge, 2005) – rising uncertainty in our expectations about its net effects. In order to analyse the seasonal climate change effects on travelled distance, for each season and the full year we run separate regression models for each of the activity types and all trips combined. A summary of these models with regard to the effects of climate change is given in table 3 and will be compared to the results on trip generation in table 2. Table 3: Summary of seasonal climate change effects on trip distance for different leisure activities

OLS regression: Climate change effects on travelled distance (in 0.1 km) per trip Winter Spring Summer Autumn All

B Beta B Beta B Beta B Beta B Beta

Work/study .004 .003 -.030 -.023 .039 .030 .030 .024 .012 .010

Maintenance -.042 -.036 .005 .004 -.049 * -.041 .026 .022 -.021 -.018 Picking up -.001 -.001 -.090 ** -.072 -.029 -.022 .009 .007 -.007 -.006 Social visit .018 .013 -.084 ** -.057 -.033 -.022 .035 .024 -.011 -.007 Leisure shopping -.037 -.035 -.111 *** -.096 .029 .026 .071 *** .065 -.02 -.01 Leisure Touring -.059 * -.049 .112 *** .087 -.058 -.045 -.011 -.008 .012 .010 Leisure Other -.043 -.034 -.067 ** -.052 -.003 -.002 .076 ** .061 -.015 -.013

All trips -.022 * -.016 -.033 ** -.023 -.001 -.001 .049 *** .035 -.001 -.001

Goodness of fit: R2 values lie between .05 and .15 Notes: For travelled distances the log is taken. *p<0.10; **p<0.05; ***p<0.01 In line with the effects on trip generation, travel distances for recreational trips are more strongly influenced by seasonal climate change those for utilitarian trips. When looked at the shoulder seasons Tables 2 and 3 show many similarities. Trip distances seem to be mostly influenced in the warmer and wetter 2050 spring season. Trip distances significantly increase for touring and significantly decrease for shopping and leisure other, as well as for some of the other activity types and the average for all trips combined. It seems that with the increase in the participation into the active and outdoors oriented leisure-‐touring activities (Table 2), people are also willing to travel further for these (Table 3). For autumn we observe, also in line with climate change effects on trip generation, a decrease in leisure-‐touring trips (although non-‐significant) and highly significant increases in distances for shopping and leisure-‐other, as well as in the average distance for all trips combined.

However, when looked at winter and summer, a comparison between Table 2 and 3 reveals much dissimilarity. In contrast to the number of trips, trip distances in warmer 2050-‐winters significantly decrease for touring trips. At the same time we do not observe a significant decrease in distances travelled in summer. Above all, climate change effects on travelled distance in winter and summer seem to be rather limited, rising our expectation of the interference of second process: mode choice. In a previous study on mode choice in the Randstad Holland, we found that the


Page 10

choices for active transport modes increase slightly in spring and largely in winter conditions whereas they decrease slightly in autumn and largely in 2050-‐summer weather conditions (Böcker et al., submitted). Consequently, for instance warmer winter weather may on the one hand enhance further travelling for leisure touring, but on the other hand increase the use of active transport modes – typically used for shorter distances –counteracting the former effect. Interference of the indirect effect via mode choices could explain why in contrast to the clear climate change effects on trip generation, its effects on trip distance are less clear, especially in winter and summer when climate change effects on mode choice are strongest (Böcker et al., submitted).

3.3 Degree of urbanization of selected destinations for leisure activities

For our analysis of activity destination locations in terms of urbanization degree, we will focus our analysis on the recreational activities shopping, leisure-‐touring and leisure-‐other (excluding social visits) for two reasons. First, in contrast to the other activities, these leisure activities are generally more voluntary, flexible and occassional, and as such are expected to be less fixed in time and space and more strongly subjected to weather conditions, for which evidence has been found throughout the literature (e.g. Cools et al., 2010; Brandenburg et al., 2004) and which we have seen in section 4.2. Second these leisure activities are directly competing with each other within the same leisure time budget as found in the literature (Nijland et al 2011) and encountered in section 4.2. Based on the literature (e.g. Nikopoulou and Lykoudis, 2007) and intuitive reasoning, our expectation is that people stick to more sheltered inner-‐city locations for leisure activities when the weather conditions are colder or wetter, to benefit from the urban heat island (against cold) or to be less exposed to precipitation or heavy wind. In contrast, with warmer and dryer weather conditions we may expect people to enjoy more weather-‐exposed destinations outside the city. During very hot weather conditions, such as in the selected 2050-‐summer, we may – as a result of an escape of inner-‐city heat – also expect people to select destinations outside cities, although we doubt whether this effect will show on the aggregated seasonal level. A descriptive overview of the seasonal climate change effects on selected destination locations of various degrees of urbanization for the different leisure activities is presented in figure 3. Figure 3: Seasonal climate change effects on attendances of destinations of different density for leisure activities, in per cent changes of the number of trips per person per day.


Page 11

Figure 3 in broad lines echoes the climate change effects on activity participation found earlier in Figure 2, with clear increases in touring destinations in winter/spring and decreases in summer and to a lesser extent autumn, against opposed effects for leisure-‐other and shopping. But when looked into more detail it appears that for these different leisure activities under changing weather conditions different locations are preferred. For instance in winter, very clearly it appears that the increases in touring (found earlier in Figure 2) are mostly taking place in the more rural/ suburban locations and not in inner-‐city areas. Before discussing these effects on leisure destination locations in the context of seasonal climate change, we will first turn to the multivariate analysis. For all seasons, we modelled the effects of climate change, along with various individual and household background predictors, on the number of trips per person per day for the different leisure activities’ destinations of varying address density. Table 4 presents a summary of the effects of seasonal climate change. Table 4: Summary of seasonal climate change effects on location in terms of urbanization degree

Binary logistic regression: Climate change effects on #trips/person/day towards different densities Winter Spring Summer Autumn All

B Bet

a B Bet

a B Beta B Bet

a B Bet

a

Leisure shopping <700 -0,277 0,209 -0,731 *** 0,223 0,028 0,216 0,504 ** 0,222 -0,105 0,097 700-1400 0,057 0,131 -0,146 0,139 0,343 ** 0,143 -0,080 0,149 0,022 0,066 1400-2000 -0,079 0,108 -0,054 0,129 0,000 0,127 0,132 0,135 -0,037 0,059 2000-3500 -0,102 0,094 -0,068 0,104 0,367 *** 0,112 -0,151 0,103 -0,028 0,049

>3500 -0,176 0,125 -0,402 *** 0,150 0,263 * 0,149 0,250 * 0,144 -0,040 0,065

Leisure touring <700 0,346 ** 0,164 0,052 0,173 -0,401 *** 0,140 -0,281 0,174 -0,049 0,078 700-1400 0,640 *** 0,168 0,239 0,173 -0,411 *** 0,142 0,145 0,171 0,170 ** 0,079 1400-2000 0,541 *** 0,174 0,417 ** 0,166 -0,278 * 0,163 0,046 0,189 0,165 * 0,084 2000-3500 -0,029 0,172 0,131 0,164 -0,269 * 0,153 0,156 0,164 0,053 0,078 >3500 -0,047 0,224 0,493 ** 0,206 -0,888 *** 0,192 -0,534 ** 0,211 -0,162 0,101

Leisure other

<700 -0,279 * 0,168 -0,400 ** 0,164 0,397 ** 0,182 0,188 0,174 -0,069 0,079 700-1400 -0,607 *** 0,149 -0,051 0,132 0,295 * 0,164 -0,033 0,144 -0,171 ** 0,068 1400-2000 -0,022 0,142 -0,138 0,150 0,342 ** 0,171 0,061 0,148 0,032 0,072


Page 12

2000-3500 -0,511 *** 0,138 -0,306 ** 0,147 -0,145 0,158 0,581 *** 0,152 -0,105 0,067 >3500 -0,332 ** 0,157 -0,375 ** 0,177 0,153 0,206 0,263 0,186 -0,158 * 0,082

Goodness of fit: Pseudo R2 (Nagelkerke) range from .015 to .232 and average .085

*p<0.10; **p<0.05; ***p<0.01 In the slightly wetter but much milder 2050-‐winters leisure touring trips increase highly significantly towards locations with lower address densities, whereas towards higher-‐density destinations this is not the case (non-‐significant decreases). According to our expectations and the descriptives it seems that the milder 2050 weather conditions favour the visiting of more-‐exposed lower density areas, which are less attractive in colder present-‐day winters. At the same time the more indoors leisure-‐other trips towards all urbanization degrees decrease significantly, with the exception of medium density locations, which remain unaffected. Also shopping trips are not significantly impacted.

According to the descriptives, in the warmer and wetter 2050 spring seasons we can see significant increases in touring trips, towards medium density locations (including many of the cities’ fringes), as well as in inner-‐city environments (including urban parks). Touring in rural areas seems to be less affected. Leisure-‐other and shopping trips are negatively affected, but decreases are only significant for the higher density locations and the very rural locations. In hotter 2050-‐summers with increased heavy precipitation and drought, leisure touring activities significantly decrease for all degrees of urbanization. As in the descriptives, the decrease in general seems to be stronger for lower density areas, which could be related lack of shelter in these areas to heavy rain. But the decrease in touring is also exceptionally high, and highly significant, for the highest density areas, which could be a result of the unattractiveness of these areas for physical activity during heat. With regard to the more indoors/mixed recreational alternatives, leisure-‐other activities increase mostly in lower density areas whereas leisure shopping increases mostly in higher density areas. Of all seasons, in autumn location in terms of urbanization degree seems to be least clearly affected. Leisure touring seems to decrease for the most rural (near-‐to-‐significant) and urban areas (significant), whereas towards locations of more medium density non-‐significant increases can be observed. Leisure shopping significantly increases in very urban and very rural areas, whereas leisure-‐other increases only significantly in moderately urban areas. As of opposite seasonal climate change effects, over the whole year the net climate change effect on destination location for leisure activities is mostly marginal: shopping remains entirely unaffected; touring seems to increase significantly only for medium density destinations; and leisure other decreases in moderately rural and very urban areas. In this section it became clear that climate change highly affects the choices for recreational activities on the seasonal level, but that in addition to what we have seen in section 4.2, considerable differences exist between the generation of trips in different geographical contexts. References Amelung, B. and Viner, D. (2006) Mediterranean tourism: explaining the future with the tourism

climatic index, Journal of Sustainable Tourism 14, pp. 349–366. Bigano, A., Hamilton, J.M. and Tol, R.S.J. (2006) The impact of climate change on holiday destination

choice, Climatic Change 76, 389–406. Hamilton, J.M., Maddison, D.J. and Tol, R.S.J. (2005) Climate change and international tourism: a

simulation study, Global Environmental Change, 15, pp. 253–266. Koetse, M.J. and Rietveld, P. (2009) The impact of climate change and weather on transport: An

overview of empirical findings, Transportation Research Part D, 14, pp. 205-‐221.


Page 13

Matzarakis, A. and De Vreitas, C. (2001) Proceedings of the First International Workshop on Climate, Tourism, and Recreation. International Society of Biometeorology, Commision on Climate Tourism and Recreation.

Nicholls, S. and Amelung, B. (2008) Climate change and tourism in Northwestern Europe: impacts and adaptation, Tourism Analysis, 13, pp. 21-‐31.

Technology

Climate change and destination choices