"Biophilic Cities": Quantifying the Impact of Google Street View-Derived Greenspace Exposures on Socioeconomic Factors and Self-Reported Health

Urban greenspace under a changing climate: Benefit or harm for allergies and respiratory health?

An increasing proportion of the world's population lives in urban settings that have limited greenspace. Urbanization puts pressure on existing greenspace and reduces its access. Climate impacts, including increased temperature and extreme weather events, challenge the maintenance of urban vegetation, reducing its ecosystem services and benefits for human health. Although urban greenspace has been positively associated with numerous health indicators, the evidence for allergies and respiratory health is much less clear and mixed. To address these uncertainties, a workshop with 20 global participants was held in Munich, Germany, in May 2024, focusing on the impact of greenspace-related co-exposures on allergies and respiratory health. This narrative review captures key insights from the workshop, including the roles of urban greenspace in (1) climate change mitigation, (2) interactions with pollen, and (3) emissions of biogenic volatile organic compounds and their byproducts, such as ozone. Additionally, it presents research and stakeholder recommendations from the workshop. Future studies that integrate advanced greenspace exposure assessments and consider the interplay of greenspace with pollen and biogenic volatile organic compounds, along with their relevant byproducts are needed. Increased public awareness and policy actions will also be essential for developing urban greenspace that maximizes health benefits, minimizes risks, and ensures resilience amid a changing climate and rapid urbanization.

Systems thinking-informed and data-driven urban decarbonisation framework for individual, community and urban scale climate action

There is an urgent need to rapidly reduce greenhouse gas (GHG) emissions and, although human activity is a primary driver of emissions, a knowledge gap remains in terms of the key individual and collective drivers of emissions, and on how to harmonise citizen-led climate action with top-down emissions mitigation policy. In response to this, an urban decarbonisation framework which was informed by systems thinking was developed to support multi-level climate action and decision making. Another aim was to demonstrate the integration of a data-driven and activity-based GHG emissions model for individuals into the framework to enable decarbonisation. This model was populated using individual activity and lifestyle data which were collected for 172 people using a smartphone application. The resulting emissions drivers were identified as well as their interaction with the overarching urban decarbonisation framework. The research will have important implications in terms of informing emissions mitigation efforts at individual, community and urban scales. By applying the framework, individual data and GHG emissions modelled at scale can inform citizen and population-level actions and high-level emissions mitigation policy for accelerating the sustainability transition that our societies and cities must urgently undergo.

Exposure to greenspaces sourced soils improves mice gut microbiota

Greenspaces are important components of our living environment and have been linked to various human health. However, the mechanisms underlying the linkages remain unclear. Enriching microbiota has emerged as a novel mechanism, but the corresponding evidence is still limited. We collected soil samples from forest land, grassland, and barren land in Zunyi City, southwestern China and prepared soil solutions. A total of 40 BALB/c mice were evenly divided into normal control group, model control group, forest soil group, grassland soil group, and barren land soil group. After establishing the pseudo germ-free mouse model, different soil solutions were administered through gavage, lasting for seven weeks. Fecal samples were collected and a 16S rRNA high-throughput sequencing analysis was performed. Then, alpha- and beta-diversity were calculated and employed to estimate the effects of soil exposures on mice gut microbial diversity and composition. Further, Linear Discriminant Analysis Effect Size (LEfSe) analysis was carried out to evaluate the effects of soil exposures on gut microbiota specific genera abundances and functional pathways. Compared to mice exposed to barren land soils, those exposed to soils sourced from forest land showed an increase of 0.43 and 70.63 units in the Shannon index and the Observed ASVs, respectively. In addition, exposure to soils sourced from forest land and grassland resulted in healthier changes (i.e., more short-chain fatty acids (SCFAs)-producing bacteria) in gut microbiota than those from barren land. Furthermore, mice exposed to forest soil and grassland soil showed enrichment in 5 and 3 pathways (e.g., butanoate metabolism) compared to those exposed to barren land soil, respectively. In conclusion, exposure to various greenspaces soils may modify the gut microbial communities of mice, potentially fostering a more beneficial microbiota profile. Further better-designed studies are needed to validate the current findings and to explore the effects of greenspace related gut microbiota on human health.

Closing the loop between environment, brain and mental health: how far we might go in real-life assessments?

PURPOSE OF REVIEW

Environmental factors such as climate, urbanicity, and exposure to nature are becoming increasingly important influencers of mental health. Incorporating data gathered from real-life contexts holds promise to substantially enhance laboratory experiments by providing a more comprehensive understanding of everyday behaviors in natural environments. We provide an up-to-date review of current technological and methodological developments in mental health assessments, neuroimaging and environmental sensing.

RECENT FINDINGS

Mental health research progressed in recent years towards integrating tools, such as smartphone based mental health assessments or mobile neuroimaging, allowing just-in-time daily assessments. Moreover, they are increasingly enriched by dynamic measurements of the environment, which are already being integrated with mental health assessments. To ensure ecological validity and accuracy it is crucial to capture environmental data with a high spatio-temporal granularity. Simultaneously, as a supplement to experimentally controlled conditions, there is a need for a better understanding of cognition in daily life, particularly regarding our brain's responses in natural settings.

SUMMARY

The presented overview on the developments and feasibility of "real-life" approaches for mental health and brain research and their potential to identify relationships along the mental health-environment-brain axis informs strategies for real-life individual and dynamic assessments.

Modelling & Spatial Mapping of Residential-Sector Emissions for Sub-National & Urban Areas

The residential sector accounts for 33% of energy-related Greenhouse Gas (GHG) emissions globally and must undergo rapid emissions reductions in order to support broader society-wide sustainability and net-zero transitions. Additionally, urban areas account for approximately 70% of global GHG emissions. To provide a baseline for urban climate action plans and mitigation strategies, sub-national municipalities must quantify their sectoral baseline emissions in detail and develop strategies for reducing emissions relative to these baselines. Therefore, it is important to establish clear methodologies for computing these baselines in accordance with the best available science. This paper establishes a novel methodology for developing a residential sector emissions model using a data-driven and spatial mapping approach. This would form an important component of future multi-sectoral baseline emissions inventories. •The residential sector emissions model combines publicly available census and building energy performance datasets in order to model and visualize the distribution of energy demand and resultant emissions across an urban study domain in Ireland.•The methodology presented was developed in line with the approaches and requirements of the Global Covenant of Mayors and the Intergovernmental Panel on Climate Change.•It is envisioned that this residential sector emissions model methodology could be applied in any urban area worldwide.

Greenspaces And Cardiovascular Health

Accumulating evidence suggests that living in areas of high surrounding greenness or even brief exposures to areas of high greenery is conducive to cardiovascular health, which may be related to the environmental, social, psychological, and physiological benefits of greenspaces. Recent data from multiple cross-sectional, longitudinal, and cohort studies suggest that living in areas of high surrounding greenness is associated with a lower risk of all-cause and cardiovascular mortality. High levels of neighborhood greenery have been linked also to a decrease in the burden of cardiovascular disease risk factors as reflected by lower rates of hypertension, dyslipidemia, and diabetes. Those who live in greener environments report better mental health and more frequent social interactions, which can benefit cardiovascular health as well. In this narrative review, we discuss evidence linking greenspaces to cardiovascular health as well as the potential mechanisms underlying the beneficial effects of greenspaces, including the impact of vegetation on air, noise and light pollution, ambient temperature, physical activity, mental health, and biodiversity. We review literature on the beneficial effects of acute and chronic exposure to nature on cardiovascular disease risk factors, inflammation and immune function, and we highlight the potential cardiovascular effects of biogenic volatile organic compounds that are emitted by trees and shrubs. We identify current knowledge gaps in this area and underscore the need for additional population studies to understand more clearly and precisely the link between greenness and health. Such understanding is urgently needed to fully redeem the promise of greenspaces in preventing adverse environmental exposures, mitigating the effects of climate change, and creating healthier living environments.

Unlocking ground-based imagery for habitat mapping

Fine-grained environmental data across large extents are needed to resolve the processes that impact species communities from local to global scales. Ground-based images (GBIs) have the potential to capture habitat complexity at biologically relevant spatial and temporal resolutions. Moving beyond existing applications of GBIs for species identification and monitoring ecological change from repeat photography, we describe promising approaches to habitat mapping, leveraging multimodal data and computer vision. We illustrate empirically how GBIs can be applied to predict distributions of species at fine scales along Street View routes, or to automatically classify and quantify habitat features. Further, we outline future research avenues using GBIs that can bring a leap forward in analyses for ecology and conservation with this underused resource.

Data Insights for Sustainable Cities: Associations between Google Street View-Derived Urban Greenspace and Google Air View-Derived Pollution Levels

Unprecedented levels of urbanization have escalated urban environmental health issues, including increased air pollution in cities globally. Strategies for mitigating air pollution, including green urban planning, are essential for sustainable and healthy cities. State-of-the-art research investigating urban greenspace and pollution metrics has accelerated through the use of vast digital data sets and new analytical tools. In this study, we examined associations between Google Street View-derived urban greenspace levels and Google Air View-derived air quality, where both have been resolved in extremely high resolution, accuracy, and scale along the entire road network of Dublin City. Particulate matter of size fraction less than 2.5 μm (PM2.5), nitrogen dioxide, nitric oxide, carbon monoxide, and carbon dioxide were quantified using 5,030,143 Google Air View measurements, and greenspace was quantified using 403,409 Google Street View images. Significant (p < 0.001) negative associations between urban greenspace and pollution were observed. For example, an interquartile range increase in the Green View Index was associated with a 7.4% [95% confidence interval: -13.1%, -1.3%] decrease in NO2 at the point location spatial resolution. We provide insights into how large-scale digital data can be harnessed to elucidate urban environmental interactions that will have important planning and policy implications for sustainable future cities.

Effect Modifications of Overhead-View and Eye-Level Urban Greenery on Heat-Mortality Associations: Small-Area Analyses Using Case Time Series Design and Different Greenery Measurements

BACKGROUND

The protective effect of urban greenery from adverse heat impacts remains inconclusive. Existing inconsistent findings could be attributed to the different estimation techniques used.

OBJECTIVES

We investigated how effect modifications of urban greenery on heat-mortality associations vary when using different greenery measurements reflecting overhead-view and eye-level urban greenery.

METHODS

We collected meteorological and daily mortality data for 286 territory planning units between 2005 and 2018 in Hong Kong. Three greenery measurements were extracted for each unit: a) the normalized difference vegetation index (NDVI) from Landsat remote sensing images, b) the percentage of greenspace based on land use data, and c) eye-level street greenery from street view images via a deep learning technique. Time-series analyses were performed using the case time series design with a linear interaction between the temperature term and each of the three greenery measurements. Effect modifications were also estimated for different age groups, sex categories, and cause-specific diseases.

RESULTS

Higher mortality risks were associated with both moderate and extreme heat, with relative risks (RRs) of 1.022 (95% CI: 1.000, 1.044) and 1.045 (95% CI: 1.013, 1.079) at the 90th and 99th percentiles of temperatures relative to the minimum mortality temperature (MMT). Lower RRs were observed in greener areas whichever of the three greenery measurements was used, but the disparity of RRs between areas with low and high levels of urban greenery was more apparent when using eye-level street greenery as the index at high temperatures (99th percentile relative to MMT), with RRs for low and high levels of greenery, respectively, of 1.096 (95% CI: 1.035, 1.161) and 0.985 (95% CI: 0.920, 1.055) for NDVI (p = 0.0193 ), 1.068 (95% CI: 1.021, 1.117) and 0.990 (95% CI: 0.906, 1.081) for the percentage of greenspace (p = 0.1338 ), and 1.103 (95% CI: 1.034, 1.177) and 0.943 (95% CI: 0.841, 1.057) for eye-level street greenery (p = 0.0186 ). Health discrepancies remained for nonaccidental mortality and cardiorespiratory diseases and were more apparent for older adults (≥ 65 years of age) and females.

DISCUSSION

This study provides new evidence that eye-level street greenery shows stronger associations with reduced heat-mortality risks compared with overhead-view greenery based on NDVI and percentage of greenspace. The effect modification of urban greenery tends to be amplified as temperatures rise and are more apparent in older adults and females. Heat mitigation strategies and health interventions, in particular with regard to accessible and visible greenery, are needed for helping heat-sensitive subpopulation groups in coping with extreme heat. https://doi.org/10.1289/EHP12589.

Towards sustainable and net-zero cities: A review of environmental modelling and monitoring tools for optimizing emissions reduction strategies for improved air quality in urban areas

Climate change is a defining challenge for today's society and its consequences pose a great threat to humanity. Cities are major contributors to climate change, accounting for over 70% of global greenhouse gas emissions. With urbanization occurring at a rapid rate worldwide, cities will play a key role in mitigating emissions and addressing climate change. Greenhouse gas emissions are strongly interlinked with air quality as they share emission sources. Consequently, there is a great opportunity to develop policies which maximize the co-benefits of emissions reductions on air quality and health. As such, a narrative meta-review is conducted to highlight state-of-the-art monitoring and modelling tools which can inform and monitor progress towards greenhouse gas emission and air pollution reduction targets. Urban greenspace will play an important role in the transition to net-zero as it promotes sustainable and active transport modes. Therefore, we explore advancements in urban greenspace quantification methods which can aid strategic developments. There is great potential to harness technological advancements to better understand the impact of greenhouse gas reduction strategies on air quality and subsequently inform the optimal design of these strategies going forward. An integrated approach to greenhouse gas emission and air pollution reduction will create sustainable, net-zero and healthy future cities.

Associations of residential greenness with unhealthy consumption behaviors: Evidence from high-density Hong Kong using street-view and conventional exposure metrics

AIM

Residential greenness was theoretically associated with health-related consumption behaviors concerning the socio-ecological model and restoration environment theory, but empirical studies were limited, especially in high-density cities. We examined the associations of residential greenness with unhealthy consumption behaviors (infrequent breakfast consumption, infrequent fruit consumption, infrequent vegetable consumption, alcohol drinking, binge drinking, cigarette smoking, moderate-to-heavy smoking, and heavy smoking) using street-view and conventional greenness metrics in high-density Hong Kong.

METHODS

This cross-sectional study employed survey data from 1,977 adults and residence-based objective environmental data in Hong Kong. Street-view greenness (SVG) was extracted from Google Street View images using an object-based image classification algorithm. Two conventional greenness metrics were used, including normalized difference vegetation index (NDVI) derived from Landsat 8 remote-sensing images and park density derived from a geographic information system database. In the main analyses, logistic regression analyses together with interaction and stratified models were performed with environmental metrics measured within a 1000-m buffer of residence.

RESULTS

A standard deviation higher SVG and NDVI were significantly associated with fewer odds of infrequent breakfast consumption (OR = 0.81, 95% CI 0.71-0.94 for SVG; OR = 0.83, 95% CI 0.73-0.95 for NDVI), infrequent fruit consumption (OR = 0.85, 95% CI 0.77-0.94 for SVG; OR = 0.85, 95% CI 0.77-0.94 for NDVI), and infrequent vegetable consumption (OR = 0.78, 95% CI 0.66-0.92 for SVG; OR = 0.81, 95% CI 0.69-0.94 for NDVI). The higher SVG was significantly associated with less binge drinking and the higher SVG at a 400-m buffer and a 600-m buffer were significantly associated with less heavy smoking. Park density was not significantly associated with any unhealthy consumption behaviors. Some of the above significant associations were moderated by moderate physical activity, mental and physical health, age, monthly income, and marital status.

CONCLUSIONS

This study highlights the potential beneficial impact of residential greenness, especially in terms of street greenery, on healthier eating habits, less binge drinking, and less heavy smoking.

Neighborhood greenspace and cognition: The cardiovascular health study

OBJECTIVES

We examined whether greenspace measures (overall percent greenspace and forest, and number of greenspace types) were associated with clinically adjudicated dementia status.

METHODS

In a sample of non-demented older adults (n = 2141, average age = 75.3 years) from the Cardiovascular Health and Cognition Study, Cox proportional hazard and logistic regression analyses were used to estimate associations of baseline greenspace with risks of incident dementia and MCI, respectively, while adjusting for demographics, co-morbidities, and other neighborhood factors. We derived quartiles of percent greenness (greenspace), forest (percent tree canopy cover), and tertiles of greenspace diversity (number of greenspace types) for 5-km radial buffers around participant's residences at study entry (1989-1990) from the 1992 National Land Cover Dataset. Dementia status and mild cognitive impairment (MCI) over 10 years was clinically adjudicated.

RESULTS

We observed no significant association between overall percent greenspace and risk of mild cognitive impairment or dementia and mostly null results for forest and greenspace diversity. Forest greenspace was associated with lower odds of MCI (OR quartile 4 versus 1: 0.54, 95% CI: 0.29-0.98) and greenspace diversity was associated with lower hazard of incident dementia (HR tertile 2 versus 1: 0.70, 95% CI = 0.50-0.99).

DISCUSSION

We found divergent results for different types of greenspace and mild cognitive impairment or dementia. Improved greenspace type and diversity measurement could better characterize the association between greenspace and cognition.

Exploring the impacts of street-level greenspace on stroke and cardiovascular diseases in Chinese adults

In recent years, cardiovascular diseases (CVDs) have become the primary cause of death in the world. Existing studies have found that greenspace is important for the prevention of CVDs and stroke. However, since they only focus on large green infrastructure (e.g., urban parks) or the general greenspace (usually being evaluated through normalized difference vegetation index), little information exists regarding the association between street-level greenspace and CVDs (stroke). In this study, the CVDs and stroke data of participants were retrieved from the 33 Chinese Community Health Study. We measured participants' exposure to street-level greenspace exposure using street view images and machine learning technique. Multilevel logistic regressions were applied. While controlling for confounders, we found that higher level of street-level greenspace exposure was associated with lower CVDs prevalence. However, street-level greenspace exposure was associated with stroke prevalence only for females. The associations were stronger among females, younger adults, participants with educational attainment above high school, physically active participants and participants who were not overweight. None of the mediators (air pollution, physical exercise, and BMI) can explain the associations between street-level greenspace exposure and CVDs (stroke) prevalence. Our findings suggest that street-level vegetation should be increased to cope with the rapid growth of the CVDs burdens. Also, the differences between the effect of street-level trees and grasses should be noted before formulating specific urban planning policies.