A Bibliometric Analysis on Designing Urban Green and Blue Spaces Related to Environmental and Public Health Benefits
Abstract
:1. Introduction
2. Theoretical Framework
2.1. Air Pollution: A Problem for Health and the Environment
2.2. The Carbon-Neutral Cities Challenge
2.3. Nature as a Solution in Air Phytoremediation
2.4. Effectiveness of NBSs in Improving Health and Well-Being
3. Data and Methodology
4. Results
4.1. General Characteristics of the Body of Research
4.2. Citation Analysis
4.3. Keywords
4.4. The Focus of the Articles
4.4.1. Impact of UGBSs on Air Quality and Carbon Neutrality
4.4.2. Impact of UGBSs on Health and Well-Being
5. Discussion
6. Conclusions
Supplementary Materials
Author Contributions
Funding
Informed Consent Statement
Data Availability Statement
Conflicts of Interest
Abbreviations
NBSs | Nature-Based Solutions |
UGBSs | Urban Green and Blue Spaces |
UGBI | Urban Green and Blue Infrastructure |
PM10 | Particulate Matter with Diameter ≤ 10 μm |
PM2.5 | Particulate Matter with Diameter ≤ 2.5 μm |
SO2 | Sulphur Dioxide |
NO2 | Nitrogen Dioxide |
CO | Carbon Monoxide |
O3 | Ozone |
CO2 | Carbon Dioxide |
WoS | Web of Science |
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Topic | Sub-Topic | Aim |
---|---|---|
| Types of UGBSs that positively influence air quality | Analyse different types of green space and their benefits in terms of air purification (green corridors, urban parks, urban forest, etc.) |
Climate zones | Focus on studying the benefits of UGBSs for air quality in specific climate zones | |
Carbon sequestration by UGBSs and mobility and lifestyle | Analyse the impact of vegetation and soil on carbon sequestration and mobility and lifestyle modes that influence carbon neutrality in cities | |
Urban planning solutions to mitigate air pollution | Focus on urban planning solutions to mitigate air pollution | |
| Designing for health | Focus on urban planning and targeted design solutions to enhance the health of certain social groups (e.g., elderly people, children) |
Non-communicable diseases | Focus on the benefits of UGBSs for non-communicable diseases (cancer, cardiovascular diseases, dementia, obesity, and respiratory disease) | |
Child development | Focus on the benefits of interaction with UGBSs for child development (birthweight, cognitive and motor development) | |
Well-being indicators | Reviews the indicators of well-being (health status, self-rated health, self-rated well-being, happiness and mood, personal security, social connectedness, and social cohesion) | |
Mental health conditions | Focus on the benefits of interaction with UGBSs for pathologies associated with mental health (depression, anxiety, and stress) | |
Typologies of UGBSs that positively influence mental health and well-being | Analyse different types of green space and their benefits for health and well-being (green corridors, urban parks, urban forest, etc.) | |
Environment comparison | Focus on comparison between indoor and outdoor environment and urban versus natural environment |
Authors | Aim | Geographic Location | Findings | Limitations |
---|---|---|---|---|
Alcock et al. [94] | To study the association between emergency hospitalisations for asthma in urban residential areas and the presence of green spaces at different levels of air pollutant exposure. | England, Europe | Green spaces and gardens are associated with reductions in asthma hospitalisation when pollutant exposures are lower. Tree density is associated with reduced asthma hospitalisation when pollutant exposures are higher. | It is not possible to interpret the results at a different spatial scale. Do not consider exposer to pollutants from indoor sources. Do not allow to see any seasonal or secular trends in how asthma emergencies relate to interaction effects between the natural environment and air pollutant exposures. |
Engemann et al. [95] | To study the associations between growing up surrounded by different environments and psychiatric disorders. | Denmark, Europe | Growing up surrounded by a range of natural environments may lower rates of psychiatric disorders. | It was not possible to infer causality. Certain socioeconomic factors, social disadvantages in deprived neighbourhoods or crime rates, were not considered. Estimating land cover and vegetation density from satellite images contains no information about how people use or perceive their local environment. |
Sanchez et al. [82] | To evaluate the pathways and effects of green spaces on air pollution and the mortality of respiratory diseases. | Tehran, Asia | Green spaces have a significant mitigating effect on air pollution and the mortality of respiratory diseases. Air pollution has an increasing effect on mortality due to respiratory diseases. | Temperature was not included in the model as an influential factor in air pollution. |
Lai & Kontokosta [96] | To study the impact of street trees on air quality and the prevalence of acute respiratory illness. | NYC, North America | A greater concentration of trees contributes to better local air quality. Some species, including Quercus palustis, Quercus rubra, Quercus bicolor, and Fraxinus pennsylvanica, with severe allergenicity can increase local asthma hospitalisation rates. | The available data were not widely available at the intended scale. Limited analysis due to a lack of individual tree data within urban parks. |
Nowak et al. [39] | To estimate the amount of PM2.5 removal and resuspension by trees and its effect on PM2.5 concentrations, including the associated values and impact on human health. | NYC, North America | Trees improve general air quality by intercepting PM2.5. PM2.5 resuspension can lead to short-term increases in pollutant concentrations. Urban trees area was responsible for substantial health improvements and values. | The premise is that all particles are removed from leaves by precipitation events that cover the complete leaf area. Do not consider the interaction with water on leaves after precipitation events. Do not consider precipitation events in the form of snow. It uses the average for the particle distribution in the atmosphere and the average wind speed in the city. Do not consider tree volatile organic compound emissions and their potential contribution to PM2.5 concentrations. Vd is assumed to be equal for all leaves within a tree canopy. Rainfall intensity is not considered. Use of 24 h average concentration data to estimate the hourly concentrations during the day. |
Sun et al. [97] | To study whether residential neighbourhood greenness modifies the short-term association between air pollution and respiratory mortality among the elderly. | Hong Kong, Asia | Elders living in higher greenness areas are less susceptible to pneumonia mortality associated with air pollution. | Some measurement errors may exist due to the use of the average pollution over the whole territory and residential greenness to represent the participants’ exposure. The sample only includes Chinese older adults, so the results cannot be generalised. It measured only greenness quantity instead of the quality of greenness space. |
Wang et al. [98] | To examine the biopsychosocial pathways linking residential green space quantity and quality to mental health. | Guangzhou, Asia | Green space quantity influences mental health mainly by reducing harm. Greenspace quality influences mental health mainly by restoring capacities and building capacities. | The several mediators used were based on self-reported questions. The actual use or visual exposure to green spaces respondents’ information was impossible to consider. The street view data and survey data were from different periods of time. Imprecision in the exposure assessment for some environmental variables. Do not consider exposure to indoor greenspace or window views. |
Zock et al. [99] | To assess a range of potentially relevant physical and social environmental characteristics to study their mutual correlations and explore associations with residents’ morbidity. | Netherlands, Europe | Social cohesion and collective efficacy tended to be higher in less urbanised municipalities. The degree of urbanisation was associated with higher morbidity in all disease groupings. A higher social cohesion coincided with a lower prevalence of depression and migraine/severe headache. | The aggregation of the social capital variables to the neighbourhood level had limited reliability. It analyses only a few potential confounders at individual levels. Do not consider data on social cohesion and collective efficacy for surrounding neighbourhoods. Do not apply strict statistical criteria to identify significant associations. |
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de Sousa Silva, C.; Bell, S.; Lackóová, L.; Panagopoulos, T. A Bibliometric Analysis on Designing Urban Green and Blue Spaces Related to Environmental and Public Health Benefits. Land 2025, 14, 1230. https://doi.org/10.3390/land14061230
de Sousa Silva C, Bell S, Lackóová L, Panagopoulos T. A Bibliometric Analysis on Designing Urban Green and Blue Spaces Related to Environmental and Public Health Benefits. Land. 2025; 14(6):1230. https://doi.org/10.3390/land14061230
Chicago/Turabian Stylede Sousa Silva, Catarina, Simon Bell, Lenka Lackóová, and Thomas Panagopoulos. 2025. "A Bibliometric Analysis on Designing Urban Green and Blue Spaces Related to Environmental and Public Health Benefits" Land 14, no. 6: 1230. https://doi.org/10.3390/land14061230
APA Stylede Sousa Silva, C., Bell, S., Lackóová, L., & Panagopoulos, T. (2025). A Bibliometric Analysis on Designing Urban Green and Blue Spaces Related to Environmental and Public Health Benefits. Land, 14(6), 1230. https://doi.org/10.3390/land14061230