Introduction

During the last centuries, a process of urbanisation has been taking place all over the world. Today, more than half of the global population live in urban areas with an increase in high-density cities. This share of urban residence is expected to increase (Ritchie & Roser, 2019). Urbanisation is part of a wider process of societal modernisation, which also involves industrialisation, institutional specialisation and mental individualisation.

Qualms about urban life

Social developments are typically attended with traditionalist counter-currents, and urbanisation is no exception to that. There have always been misgivings about urban life, in the past primarily about its moral climate, such as in the biblical case of Sodom and Gomorra, and today especially about the liveability of urban environments. Illustrative topics in the current discourse about urban living are pollution, crime, loneliness and mental disorder. These reservations have instigated efforts to incorporate rural elements in urban environments, such as when new-build city quarters were modelled architecturally as urban villages. The furthering of urban green is part of that movement and involved the building of public parks and planting trees in streets.

Biophilia theory

The call for urban green was recently strengthened by the theory that humans have an innate need for contact with nature and in particular with other forms of life (Wilson, 1984). A variant of this theory holds that we feel better in the vegetated environments in which the human species developed (Rogers, 2019). This theory has inspired a movement in biophilic urban design, a recent overview of which is found in Beatley (2017). An indication for the innate nature of this preference is seen in the existence of biophobic tendencies in humans, such as an aversion for spiders and snakes, which is likely to have involved better survival chances for our early forefathers.

This innate need does not necessarily give rise to a conscious preference for green environments. Cultural influences may make us sniff at nature but cannot prevent that we feel less well without it. Hence the theory legitimates biophilic policies for the sake of the public good, even if not demanded. Fostering urban green is one of these policies. Theoretically, the biophilia theory goes against the view that the evolution of humankind involved the vanishing of instinctual stimulus-response reactions, since we specialised in adaptation to different environments using the more flexible cognition enabled biologically by the development of the neocortex (Wentholt, 1989). In that view, we can live as well in a brick-and-concrete city, though the newly developed cognitive capacities may set their own demands for visual stimulation (Wentholt, 1969). Empirical evidence for the biophilia theory is mixed as yet. Confirmation is seen in a study that found faster recovery of patients situated in a hospital room with an outlook on a park than in rooms with an outlook on a car park (Ulrich, 1984). Although widely cited, this study has not been replicated to our knowledge. Beneficial effects of pet ownership on health (Anderson et al., 1992) have also been mentioned as proof for the biophilia theory, but can also be explained otherwise. Likewise, the self-reported gain in happiness and health of voluntary participants in organised walks in the wild (Richardson et al., 2016) can be due to other causes than meeting of an innate need for contact with nature. Similarly, the observation by Chang et al. (2020) that users of social media share more pictures of nature in relation to leisure and vacation activities does not prove the biophilia theory. A more detailed critical review of the biophilia theory is given in Joyce and DeBlock (2011).

Implied and other possible effects of urban green on happiness

Urban green provides another opportunity to test the biophilia theory. If true, citizens living in green areas will be happier than citizens living in brick-and-concrete environments, other conditions being equal. This effect on happiness is implied in the tenet that we have an innate need for contact with greenery; gratification of needs will foster happiness, its affective component in particular (to be discussed below), while frustration of that need will lower happiness.

Next to this direct effect, urban green can add to happiness in other ways. For instance, urban green will improve air quality and reduce the effects of hot summers, which is likely to add to happiness through effects on health. Likewise, urban parks provide opportunities for outdoor leisure. Urban green may further attract richer residents and as such add to local amenities. However, urban green can also affect happiness negatively. Urban green is costly and its price is paid in local tax and housing prices. Urban green can also attract unwelcome animals, such as snakes, and create unsafe places.

Why focus on happiness?

There is much research on the effect of urban green on various aspects of ‘well-being’, such as outdoor recreation (Chapter 22 of this book). It is difficult to strike the balance of these effects; happiness captures the total effect. Notions of ‘well-being’ are often based on assumptions of what is good for people, e.g. that they take walks and have contact with neighbours. Happiness is free of such presumptions and measures ‘apparent quality of life’ (Veenhoven, 2005).

Research questions

In this chapter we seek answers to the following questions:

1. Does urban greenery typically add to happiness? If so, how much?
2. Is the effect of urban green on happiness similar for everybody? If not, what kind of people benefit from urban green and what kind of people do not?
3. What kind of greenery will add most to happiness?
4. Does urban greenery add more to the affective component of happiness (how well one feels most of the time) than to the cognitive component (perception of getting what one wants)?

Social relevance

Answers to questions 1, 2 and 3 will be relevant for urban policymakers who are faced with demands for more parks and trees in the streets and wonder whether this will really add to the happiness of citizens, what kind of greenery will add most, and whether investing in greenery is worth the cost. The information is also useful for individual citizens who consider buying a house and wonder whether buying a more expensive house in a green environment will make them happier, or whether they will be equally happy in a cheaper brick-and-concrete environment. Though people are typically aware of what they want, they are often unaware of what they need. Observed effects of urban green on happiness denote a link with general human needs.

Scientific relevance

An affirmative answer to question 4 would support the biophilia theory. According to Veenhoven (2009), gratification of innate needs will manifest primarily in affective experience, mood level in particular, while realising culture-specific wants will rather result in cognitive contentment. This theoretical question is also of practical relevance for policymakers, who prefer to invest in enduring sources of happiness over putting money in time-bound cultural preference.

Approach

We answer these questions by taking stock of the available empirical research findings on happiness and urban green. To that end, we will first define these concepts and select acceptable operationalisations on that basis. We next describe how findings were selected and entered in an online finding archive, the World Database of Happiness (Veenhoven, 2020a). On that basis we will then consider the research questions one by one.

Concepts and measures

Components and measures of happiness

In classic philosophy, the word happiness is used to denote a ‘good life’ and as such is synonymous with the contemporary terms of ‘well-being’ and ‘quality of life’. In contemporary social sciences, the word is mostly used in the more limited sense of ‘satisfaction with life’ and also denoted as ‘subjective well-being’. In this chapter we follow this latter meaning and define happiness as the degree to which individuals judge the overall quality of their life as a whole favourably, or in other words, how much one likes the life one leads (Veenhoven, 1984). Another term for happiness is ‘life satisfaction’.

The overall evaluation of life draws on two different sources of information, regarded as ‘components’ of happiness. The affective component is how well one feels most of the time and is called the ‘hedonic level of affect’. The cognitive component is the extent to which one perceives getting from life what one wants from it and is called ‘contentment’. Veenhoven’s (2009) theory of how we assess how happy we are holds that the affective component reflects the degree to which universal human needs are met, while the cognitive component reflects the meeting of culturally relative aspirations (Kainulainen et al., 2018). If so, the biophilia theory would predict a stronger correlation with the affective component of happiness than with the cognitive component and less variability in correlation across cultures.

Since happiness is defined as a mental state of which we are aware, it can be measured by asking people. Some illustrative questions are:

• Question on overall happiness:
  • Taking all together, how satisfied or dissatisfied are you with your life as a whole these days?
• Questions on hedonic level of affect:
  • Would you say that you are usually cheerful or dejected?
  • How is your mood today? (Repeated over several days)
• Question on contentment:
  • Here is a picture of a ladder. Suppose we say that the top of the ladder represents the best possible life for you and the bottom represents the worst possible life for you. Where on the ladder do you feel you personally stand at the present time?

A review of strengths and weaknesses of measures of happiness and their applicability in different contexts is available in Veenhoven (2017).

Urban green

Urban greenspaces are ‘areas with vegetation within or partly embraced by urban fabric …, which usually has recreational or ornamental character and is usually accessible for the public’ (European Environment Agency, 2019). There is green within the built urban environment, such as parks, and green outside urban boundaries, such as woods, which are easily accessible for urbanites. Within the built environment there is further a difference between outside green, such as trees in streets and inside green, such as plants in homes and workplaces. A further difference is between kinds of vegetation, such as grass fields and bushes, and landscapes, such as hills or water courses The occurrence of urban green is assessed in the investigated studies in objective and subjective ways. An objective way is assessment by satellites; a subjective way is the respondent’s perception of their access to greenspaces. A question of this kind reads:

Method: research synthesis from a finding archive

As noted above, we seek answers to our research questions by taking stock of the available research findings. This is called ‘research synthesis’. For this purpose, we use an existing finding archive, the World Database of Happiness (Veenhoven 2020b). This database is a collection of research findings on happiness in the sense of life satisfaction. It contains both distributional findings on how happy people are in different times and places, and correlational findings on things that go together with more or less happiness. These findings are described on electronic finding pages in a standard format and terminology, each with a unique Internet address. An example of a finding page is presented in Figure 23.1. Finding pages are sorted by subject in collections. For this study we use the collections of correlational findings on happiness and local nature and time spent in nature. This technique is described in more detail in Veenhoven et al. (2022).

Figure 23.1 Example of a finding page.

At 1 June 2020, the World Database of Happiness held seventeen empirical studies in which a relation between happiness and urban green was assessed. These studies are listed in Table 23.1. Together, these studies yielded thirty-eight correlational findings which are presented in Table 23.2. These studies were published between 2004 and 2018. Data was gathered in the following countries: New Zealand, Austria, the United Kingdom, Japan, the Netherlands, Uruguay, Germany, Finland, Hungary, Italy and China. Together, the seventeen studies cover the responses of 126,321 people.

Presentation of findings

The use of an online finding archive allows for a new way of presenting research findings in a review paper. Since this presentation will be unusual for most readers, the following explanation will be helpful. Each of the thirty-eight research findings is described in detail in the World Database of Happiness on a finding page with a unique Internet address. In our presentation of these findings in Table 23.2 we simply use a sign that denotes the observed direction of correlation (-/0/+), with each sign hyperlinked to an online finding page. This allows a condensed presentation of the main trend in the findings, while providing the reader with access to the full details. Unlike traditional review papers, we need not describe all the findings in this text and bypass the problem that page limitation typically does not allow them to be provided in sufficient detail. This technique works only for electronic texts. In Table 23.2 we coloured findings obtained with an objective measure of urban happiness red and finding obtained with a subjective measure blue. In Table 23.2, we present the observed direction of correlation using (+) and (–) signs. Statistical significance is indicated in bold. In Table 23.3 we present the twenty-one findings that were expressed with a comparable effect size, in this case a standardised regression coefficient with a theoretical range between –1 and +1.

In Tables 23.2 and 23.3, we present the observed correlations by research method used. We distinguish between (a) cross-sectional studies which assess same-time correlation, (b) longitudinal studies which assess over-time correlation and (c) experimental studies which assess over-time change in happiness after induced change in contact with urban green. For each of these research methods, we distinguish between (1) ‘raw’ zero-order correlations and (2) partial correlations, in which the effect of possible intervening variables is filtered away. Such control procedures are meant to weed out spurious correlation but can also remove mediating effects and as such throw the baby away with the bathwater.

Results

We will now answer the research questions mentioned earlier. Does urban greenery add to happiness? In Table 23.2, we see mainly + signs, which means that more contact with urban green tends to go with greater happiness. This holds for ‘greenspace’, ‘access to green’, ‘proximity to green’, ‘closeness to green’, ‘parks’, ‘time spent in green’. Note that about half (seventeen) of the thirty-eight correlations are statistically significant. All the significant correlations are obtained with objective measures of urban green and are marked red. If so, how much? Of the thirty-eight studies in Table 23.2, only twenty-one express this correlation in a comparable effect size, mostly standardised regression coefficients. These effect sizes are reported in Table 23.3. The correlations with objective measures of contact with urban green are quite small. The only sizeable correlation is with self-reported time spent in nature and may say more about leisure preference than about benefits of contact with urban green.

Is the effect of urban green on happiness similar for everybody? If not, what kind of people benefit from urban green and what kind of people do not? As yet, only two differentiating personal characteristics have been considered. The studies by Ambrey et al. (2014) and Fleming et al. (2016) in Australia and New Zealand observed a negative correlation with closeness to urban green among urbanites who fear crime and therefore see parks as unsafe places. The study by Tsurumi and Managi (2015) in Japan found that people with a greater ‘affection for greenery’ benefit more from greenspaces than those without such preference. What sort of greenery will add most to happiness? In Table 23.2 we can see that three kinds of urban green have been considered, of which only one (parks) correlated significantly with happiness. Table 23.3 provides no further information about relative addition to happiness. There is more data on closeness to urban green. The coefficients in Table 23.3 do not support the intuition that the effect of urban green will be greater the smaller the distance from one’s home, but reveal a slightly stronger correlation with urban green at distances of 100m to 1,000m from home.

The discussion so far has been about outdoor green. At the bottom of Table 23.2 the reader can also see a study on the relation between indoor green and happiness. This experimental study is strong in design but met several practical problems which resulted in the loss of most participants and consequently in statistical insignificance of observed changes in happiness. Does urban greenery relate more to the affective component of happiness than to the cognitive component? The study on distance to urban green by Tsurumi et al. (2018) used three measures of happiness, covering overall happiness and its two components. The affective component was measured using a balance score of positive and negative affects experienced the previous day. The cognitive component was measured using the Cantril (1965) Ladder of Life question on which people rate their present life on a ladder scale ranging from the ‘best possible’ to the ‘worst possible’ life (Glatzer & Gulyas, 2014). In Table 23.3 we can see that closeness to urban green correlates significantly with how well one feels affectively (coloured red), but not with how close to the ideal life one thinks they are (coloured blue). This difference is in line with the biophilia theory.

Discussion and conclusion

The available research shows small positive correlations between greenery in urban areas and the happiness of people who live there. It is not clear to what extent this correlation results from an effect of contact with green on happiness or from an effect of happiness on choice for a greener environment. The observed support for the biophilia theory implies that there is at least some effect of greenery on happiness. Possibly, the real-life effects of urban green are stronger than the observed correlation coefficients suggest. Correlations are diluted in several ways, such as by measurement error. It is a task for future research to consider that problem.

A possible objection to the observed correlations could be that they stem from a tendency of happy people to see more greenery in their environment, while unhappy people perceive less green in the same environment, especially when seeking external causes for their misery. In this context it is worth noting that most of the correlations are obtained with objective measures of urban green, such as the percent of green surface in the respondent’s neighbourhood. Anyway, the few subjective measures of urban green show no relation with happiness.

The available data provides little answer to the question of what kind of people benefit more or less from urban green happiness-wise: e.g. children or elderly? As yet, we also do not know what kind of outdoor urban green adds most to happiness, for instance private gardens, public parks, concentrated green in parks or dispersed in streets, trees or grasslands etc. Answers to these questions are essential for effective greening policy.

The evidence base is small as yet and smaller than one might expect given the political prominence of the issue and the interest of the greenery sector. Most of the thirteen studies reviewed in this chapter are from recent dates and that promises more studies in the near future. The format used in this chapter can then be used for periodic updates. To date (June 2021) there is not much empirical research on the relationship between urban green and the happiness of urbanites. The few available findings suggest a small positive effect but leave us largely in the blind about causality, mediators and moderators.