Dataset Information

Gauging the happiness benefit of US urban parks through Twitter.

ABSTRACT: The relationship between nature contact and mental well-being has received increasing attention in recent years. While a body of evidence has accumulated demonstrating a positive relationship between time in nature and mental well-being, there have been few studies comparing this relationship in different locations over long periods of time. In this study, we analyze over 1.5 million tweets to estimate a happiness benefit, the difference in expressed happiness between in- and out-of-park tweets, for the 25 largest cities in the US by population. People write happier words during park visits when compared with non-park user tweets collected around the same time. While the words people write are happier in parks on average and in most cities, we find considerable variation across cities. Tweets are happier in parks at all times of the day, week, and year, not just during the weekend or summer vacation. Across all cities, we find that the happiness benefit is highest in parks larger than 100 acres. Overall, our study suggests the happiness benefit associated with park visitation is on par with US holidays such as Thanksgiving and New Year's Day.

SUBMITTER: Schwartz AJ

PROVIDER: S-EPMC8967001 | biostudies-literature | 2022

REPOSITORIES: biostudies-literature

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Gauging the happiness benefit of US urban parks through Twitter.

Schwartz Aaron J AJ Dodds Peter Sheridan PS O'Neil-Dunne Jarlath P M JPM Ricketts Taylor H TH Danforth Christopher M CM

PloS one 20220330 3

The relationship between nature contact and mental well-being has received increasing attention in recent years. While a body of evidence has accumulated demonstrating a positive relationship between time in nature and mental well-being, there have been few studies comparing this relationship in different locations over long periods of time. In this study, we analyze over 1.5 million tweets to estimate a happiness benefit, the difference in expressed happiness between in- and out-of-park tweets, ...[more]

PMID: 35353831

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Project description:This work presents a portable framework to estimate potential park demand and park exposure through bipartite weighted networks. We use mobility information and open spatial information. Mobility information comes in the form of daily activities sampled from a model based on Call Detail Records (CDR). Spatial information comprise parks represented through OpenStreetMaps polygons and census tracts from the 2010 decennial US Census. The framework summarizes each city's information into one bipartite weighted network with the link weights representing the number of potential visits to a park from each census tract on an average weekday. We compare park exposure and park demand in Greater Los Angeles and Greater Boston in a pre-pandemic scenario. The park exposure of a census tract is calculated as the number of parks surrounding the daily activities of its inhabitants. The demand of a park is calculated as the number of daily activities surrounding it. We find that both cities' distribution of park exposure have similar shape with Boston having a higher average. On the other hand, the distribution of park demand is very similar in both cities, although their park spatial distributions are different. We include racial/ethnic information from the Census to explore how the park exposure connects tracts of different racial/ethnic groups. We associate parks to racial/ethnic groups based on the number of visitors from each group. Parks within minorities' tracts are mostly used by majority groups. Finally, through detecting communities in the network, we find that park exposure connects the cities locally, linking parks to their tracts nearby. Furthermore, we find a significant spatial correlation between network communities and different racial/ethnic composition in Los Angeles. This way, patterns of park exposure reproduce the separation among demographic groups of the city.Supplementary informationThe online version contains supplementary material available at 10.1140/epjds/s13688-022-00351-9.

Project description:Ambient air pollution is the most important environmental factor impacting human health. Urban landscapes present unique air quality challenges, which are compounded by climate change adaptation challenges, as air pollutants can also be affected by the urban heat island effect, amplifying the deleterious effects on health. Nature-based solutions have shown potential for alleviating environmental stressors, including air pollution and heat wave abatement. However, such solutions must be designed in order to maximize mitigation and not inadvertently increase pollutant exposure. This study aims to demonstrate potential applications of nature-based solutions in urban environments for climate stressors and air pollution mitigation by analyzing two distinct scenarios with and without green infrastructure. Utilizing low-cost sensors, we examine the relationship between green infrastructure and a series of environmental parameters. While previous studies have investigated green infrastructure and air quality mitigation, our study employs low-cost sensors in tropical urban environments. Through this novel approach, we are able to obtain highly localized data that demonstrates this mitigating relationship. In this study, as a part of the NERC-FAPESP-funded GreenCities project, four low-cost sensors were validated through laboratory testing and then deployed in two locations in São Paulo, Brazil: one large, heavily forested park (CIENTEC) and one small park surrounded by densely built areas (FSP). At each site, one sensor was located in a vegetated area (Park sensor) and one near the roadside (Road sensor). The locations selected allow for a comparison of built versus green and blue areas. Lidar data were used to characterize the profile of each site based on surrounding vegetation and building area. Distance and class of the closest roadways were also measured for each sensor location. These profiles are analyzed against the data obtained through the low-cost sensors, considering both meteorological (temperature, humidity and pressure) and particulate matter (PM1, PM2.5 and PM10) parameters. Particulate matter concentrations were lower for the sensors located within the forest site. At both sites, the road sensors showed higher concentrations during the daytime period. These results further reinforce the capabilities of green-blue-gray infrastructure (GBGI) tools to reduce exposure to air pollution and climate stressors, while also showing the importance of their design to ensure maximum benefits. The findings can inform decision-makers in designing more resilient cities, especially in low-and middle-income settings.

Project description:IntroductionUrban neighborhood parks are designed to provide easy access to recreation and physical activity. We analyzed data from the first National Study of Neighborhood Parks, which assessed the characteristics and use of a representative sample of U.S. urban neighborhood parks. This article compares factors associated with active commuting (e.g., walking) to parks among men and women and park characteristics associated with observed moderate-to-vigorous physical activity (MVPA) within neighborhood parks.MethodsWe used systematic direct observation to quantify parks visitors of all ages in 162 U.S. neighborhood parks in 25 cities in 2016 and surveyed a sample of adult visitors (877 women and 793 men). We used descriptive statistics to identify park facilities, amenities, and park management practices associated with park use. We also conducted multivariate regressions to identify factors most closely associated with observed park-based MVPA among all age groups and with self-reported levels of active commuting to parks among adults.ResultsReasons to visit parks varied by gender, with women more likely than men to bring children (59% vs 42% for men; p < .001), and men more likely than women to go to parks to relax (38% vs 29%; p = .01). Bringing children to parks was associated with more motorized transport among women, but not among men. Active commuting to parks was associated with living closer to parks (β = -0.92; p < .0001), a greater frequency of park use (β = 0.99; p < .0001), and the park having a working drinking fountain (β = 0.62; p = .01), with no significant differences between men and women. Men and boys used park facilities very differently than women and girls. Men and boys engaged in the most MVPA in soccer fields, gyms, and skate parks, whereas for women and girls the top three sites were pools, playgrounds, and walking paths.ConclusionsSignificant gender differences in why men and women visit parks and how parks are used likely reflect cultural determinants of gender roles. Our findings suggest that park management practices should be adjusted to mitigate the lower use of parks and lower levels of park-based MVPA among women and girls compared with men and boys.

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Gauging the happiness benefit of US urban parks through Twitter.

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Gauging the happiness benefit of US urban parks through Twitter.

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