Green spaces are not all the same for the provision of air purification and climate regulation services: The case of urban parks

Does the morphology of residential greenspaces contribute to the development of a cardiovascular-healthy city?

BACKGROUNDS

Greenspaces are indispensable for the construction of a healthy city. Research has shown that greenspaces contribute to the reduction of cardiovascular risks. However, the role of greenspace morphology in the development of a healthy city is not well understood.

METHODS

Our study utilized data from a cardiovascular disease screening cohort comprising 106,238 residents in Anhui Province, China, aged between 35 and 75 years. We calculated landscape indices of each participant using high-resolution land cover data to measure the greenness, fragmentation, connectivity, aggregation, and shape of greenspaces. We used a multivariate linear regression model to assess the associations between these landscape indices and triglyceride risk, and employed a structural equation model to explore the potential contributions of heatwaves and fine particulate matter (PM2.5) to this association.

RESULTS

Overall, triglyceride was expected to increase by 0.046% (95% CI: 0.040%, 0.052%) with a 1% increase in the percentage of built-up area. Conversely, an increase in the percentage of greenspace was associated with a 0.270% (95% CI: 0.337%, -0.202%) decrease in triglyceride levels. Furthermore, when the total greenspace was held constant, the shape, connectedness, and aggregation of greenspace were inversely correlated with triglyceride levels, with effects of -0.605% (95% CI: 1.012%, -0.198%), -0.031% (95% CI: 0.039%, -0.022%), and -0.049% (95% CI: 0.058%, -0.039%), respectively. Likewise, the protective effect of the area-weighed mean shape index was higher than that of the total amount of greenspace. The stratification results showed that urban residents benefited more from greenspace exposure. Greenspace morphology can minimize triglyceride risk by reducing pollutant and heatwaves, with aggregation having the greatest effect on reducing pollutants whereas fragmentation is more efficient at reducing heatwaves.

CONCLUSION

Exposure to the greenspaces morphology is associated with a reduction in triglyceride risk. The study has important practical and policy implications for early health monitoring and the spatial layout of greenspace and will provide scientific information for healthy urban planning by reducing unfavorable health consequences.

Green space and its types can attenuate the associations of PM2.5 and its components with prediabetes and diabetes-- a multicenter cross-sectional study from eastern China

BACKGROUND

The effect of fine particulate matter (PM2.5) components on prediabetes and diabetes is of concern, but the evidence is limited and the specific role of different green space types remains unclear. This study aims to investigate the relationship of PM2.5 and its components with prediabetes and diabetes as well as the potential health benefits of different types and combinations of green spaces.

METHODS

A multicenter cross-sectional study was conducted in eastern China by using a multi-stage random sampling method. Health screening and questionnaires for 98,091 participants were performed during 2017-2020. PM2.5 and its five components were estimated by the inverse distance weighted method, and green space was reflected by the Normalized Difference Vegetation Index (NDVI), percentages of tree or grass cover. Multivariate logistic regression and quantile g-computing were used to explore the associations of PM2.5 and five components with prediabetes and diabetes and to elucidate the potential moderating role of green space and corresponding type combinations in these associations.

RESULTS

Each interquartile range (IQR) increment of PM2.5 was associated with both prediabetes (odds ratio [OR]: 1.15, 95%CI [confidence interval]: 1.10-1.20) and diabetes (OR: 1.18, 95% CI: 1.11-1.25), respectively. All five components of PM2.5 were related to prediabetes and diabetes. The ORs of PM2.5 on diabetes were 1.49 (1.35-1.63) in the low tree group and 0.90 (0.82-0.98) in the high tree group, respectively. In the high tree-high grass group, the harmful impacts of PM2.5 and five components were significantly lower than in the other groups.

CONCLUSION

Our study suggested that PM2.5 and its components were associated with the increased risk of prediabetes and diabetes, which could be diminished by green space. Furthermore, the coexistence of high levels of tree and grass cover provided greater benefits. These findings had critical implications for diabetes prevention and green space-based planning for healthy city.

Lichen - air quality association rule mining for urban environments in the tropics

There are significant gaps in air quality monitoring across many low- and middle-income countries, which can be filled by bioindicators like lichen. This study examined the links between lichen and air quality across urban environments in Nigeria. Lichen surveys and air quality monitoring were carried out across four major cities focusing on NO2, SO2, PM2.5, and PM10. Association rule mining was used to identify robust rules defining the association between lichen and air quality categories. For the maximal frequent set with Lichen in the antecedent, 9 and 5 rules were identified by A priori and Eclat, respectively. These indicated that three genera: Diorygma, Pyxine, and Physcia are the most commonly associated lichen with poor air quality particularly NO2 and SO2. This showed that these lichens are viable indicators of long-term air quality due to their consistent occurrence across the rules from different algorithms.

Urban green, blue spaces and their joint effect are associated with lower risk of emotional and behavior problem in children and adolescents, a large population-based study in Guangzhou, China

Extensive research has been conducted on the impact of urban Green and blue spaces (GBS) on mental health. However, there is a dearth of studies examining the potential influence of GBS on Emotion and behavior problems (EBP) in youth populations. This study seeks to address this research gap by examining the association between GBS exposure and EBP in youths, utilizing a large population-based survey. Exposure indicators were derived for each participant, taking into account the 1-m resolution land coverage percentage measurements at their residential and school locations, with buffer sizes of 500m and 800m. The study employed the parent-reported Strengths and Difficulties Questionnaire (SDQ) as a measurement to EBP. To investigate this relationship, a Poisson linear mixed-effects model with comprehensive adjustment was utilized. Stratified analyses were conducted, taking into account demographic variables, while sensitivity analyses were performed to evaluate the reliability of the findings. The primary analysis encompassed a sample of 172,490 individuals, with an average age of 10.2 (standard deviation = 2.99), of whom 55.8% were male. Among young individuals residing within a 500-m radius of residential green spaces (GS), those in the second and third tertiles experienced a 5.0% and 7.6% decrease in the risk of developing total difficulties respectively, compared to those in the first tertile. Exposure to blue spaces (BS) around the residence yielded comparable results, with an AOR of 0.896 (95% CI: 0.866, 0.928) for the second tertile and an AOR of 0.991 (95% CI: 0.879, 0.943) for the third tertile, compared to the first tertile. The decrease in EBPs may also be linked to the joint effect of GS and BS. Young individuals were exposed to GS or BS, as well as the higher level of GS in conjunction with comparable BS, exhibited an inverse correlation with self-reported EBPs.

When and where to exercise: An assessment of personal exposure to urban tropical ambient airborne pollutants in Singapore

BACKGROUND

Physical activity is associated with health benefits and has been shown to reduce mortality risk. However, exposure to high levels of ambient fine particulate matter (PM2.5) during exercise can potentially reduce the health benefits of physical activity. This study aims to assess and compare the PM2.5 concentrations of different exercise venues in Singapore by their location attributes and time of day.

METHODS

Personal PM2.5 exposures (μg/m3) at 24 common outdoor exercise venues in Singapore over 49 sampling days were collected using real-time personal sensors from September 2017 to January 2020. Wilcoxon rank-sum test and Kruskal-Wallis test were used to compare PM2.5 concentrations between different timings (peak (0700-0900; 1800-2000) vs. non-peak (0600-0700; 0900-1800; 2000-2300); weekend vs. weekday), and location attributes (near major roads (<50 m) vs. away from major roads (≥50 m)). Multivariable linear regression models were used to assess the associations between location attributes, timings and ambient PM2.5 with personal PM2.5 concentration, adjusting for potential confounders.

RESULTS

Compared with peak hours, exercising during non-peak hours was associated with a significantly lower PM2.5 exposure (median, 17.8 μg/m3 during peak vs. 14.5 μg/m3 during non-peak; P = 0.006). Exercise venues away from major roads have significantly lower PM2.5 concentrations as compared to those located next to major roads (median, 14.4 μg/m3 away from major roads vs. 18.5 μg/m3 next to major roads; P < 0.001). Individuals who exercised in parks experienced the highest PM2.5 exposure (median, 55.0 μg/m3) levels in the afternoon during 1400-1500. Furthermore, ambient PM2.5 concentration was significantly and positively associated with personal PM2.5 exposure (β = 0.85, P < 0.001).

CONCLUSIONS

Our findings suggest that exercising outdoors in the urban environment exposes individuals to differential levels of PM2.5 at different times of the day. Further research should investigate a wider variety of outdoor exercise venues, explore different types of air pollutants, and consider the varying activity patterns of individuals.

Assessing the effectiveness of artificial neural networks (ANN) and multiple linear regressions (MLR) in forcasting AQI and PM10 and evaluating health impacts through AirQ+ (case study: Tehran)

Air pollution is one of the major concerns for the population and the environment due to its hazardous effects. PM10 has affected significant scientific and regulatory interest because of its strong correlation with chronic health such as respiratory illnesses, lung cancer, and asthma. Forcasting air quality and assessing the health impacts of the air pollutants like particulate matter is crucial for protecting public health.This study incorporated weather, traffic, green space information, and time parameters, to forcst the AQI and PM10. Traffic data plays a critical role in predicting air pollution, as it significantly influences them. Therefore, including traffic data in the ANN model is necessary and valuable. Green spaces also affect air quality, and their inclusion in neural network models can improve predictive accuracy. The key factors influencing the AQI are the two-day lag time, the proximity of a park to the AQI monitoring station, the average distance between each park and AQI monitoring stations, and the air temperature. In addition, the average distance between each park, the number of parks, seasonal variations, and the total number of vehicles are the primary determinants affecting PM10.The straightforward effective Multilayer Perceptron Artificial Neural Network (MLP-ANN) demonstrated correlation coefficients (R) of 0.82 and 0.93 when forcasting AQI and PM10, respectively. This study also used the forcasted PM10 values from the ANN model to assess the health effects of elevated air pollution. The results indicate that elevated levels of PM10 can increase the likelihood of respiratory symptoms. Among children, there is a higher prevalence of bronchitis, while among adults, the incidence of chronic bronchitis is higher. It was estimated that the attributable proportions for children and adults were 6.87% and 9.72%, respectively. These results underscore the importance of monitoring air quality and taking action to reduce pollution to safeguard public health.

Vegetation growth enhancement modulated by urban development status

Cities are natural laboratories for studying the vegetation response to global change due to their own climatic, atmospheric, and biological conditions. However, whether the urban environment promoted vegetation growth is still uncertain. Using the Yangtze River Delta (YRD), an economic powerhouse of modern China, as a case study, this paper investigated the impact of urban environment on vegetation growth at three scales: cities, sub-cities (rural-urban gradient) -pixels. Based on the satellite observations of vegetation growth indicated during 2000-2020, we explored the direct (replacement of original land by impervious surfaces) and indirect impact (e.g., climatic environment) of urbanization on vegetation growth and their trends with urbanization level. We found that significant greening accounted for 43.18 %, and significant browning accounted for 3.60 % of the pixels in the YRD. Urban area was turning green faster than suburban area. Moreover, land use change intensity (D) was a representation of the direct impact ω_d of urbanization. The direct impact of urbanization on vegetation growth was positively correlated with the intensity of land use change. Furthermore, vegetation growth enhancement due to indirect impact ω_i occurred in 31.71 %, 43.90 % and 41.46 % of the YRD cities in 2000, 2010 and 2020. And vegetation enhancement occurred in 94.12 % of highly urbanized cities in 2020, while in medium and low urbanization cities, the averaged indirect impact was near zero or even negative, proving that vegetation growth enhancement was modulated by urban development status. Also, the growth offset (τ) was most pronounced in high urbanization cities (4.92 %), but there was no growth compensation in medium urbanization cities (-4.48 %) and low urbanization cities (-57.47 %). When urbanization intensity reached a threshold value of 50 % in highly urbanized cities, the growth offset (τ) tended to saturate and remained unchanged. Our findings have important implications for understanding the vegetation response to continuing urbanization process and future climate change.

Climatology and landscape determinants of AOD, SO2 and NO2 over Indo-Gangetic Plain

Indo-Gangetic Plains (IGP) experiences high loading of particulate and gaseous pollutants all year around and is considered to be the most polluted regions of India. Understanding the effect of landscape determinants on air pollution in IGP regions is crucial to make its environment sustainable. We examined satellite retrievals of OMI NO₂ and SO₂, and MODIS AOD to analyse the long-term trend, spatio-seasonal pattern and dynamics of aerosols, NO₂ and SO₂ over three IGP regions, namely Upper Indo-Gangetic plain (UIGP), Middle Indo-Gangetic plain (MIGP) and Lower Indo-Gangetic plain (LIGP) over the period 2005-2019. IGP experienced an overall increment in AOD (R² = 0.63) and SO₂ (R² = 0.67) values, with LIGP (AOD, R² = 0.8 & SO₂, R² = 0.8) experiencing the largest rate of enhancement. The levels of NO₂ (R² = 0.2) experienced a decrement after 2012 (owing to implementation of vehicle emission policy) except in MIGP, with UIGP (R² = 0.23) exhibiting the largest rate of decrement. Seasonal heterogeneity in the nature of sources was observed over IGP regions. AOD (0.61 ± 0.1) and NO₂ value (3.82 ± 0.98 × 10¹⁵ molecules/cm²) were found highest during post-monsoon in UIGP owing to crop residue burning activity. The value of NO₂ (3.8 ± 1.4 × 10¹⁵ molecules/cm²) in MIGP was found highest during pre-monsoon due to high consumption of coal in power plants for summer cooling demand. The highest SO₂ level (0.09 ± 0.06 DU) was observed during post-monsoon in UIGP, as a large number of brick kilns are fired during this period. Correlations among landscape determinants and pollutants revealed that topography is the dominant variable that affect the spatial pattern of AOD compared to vegetation and land use. Lower elevation tends to have high AOD values compared to higher elevation. Vegetation-AOD relationship showed an inverse association in IGP regions and is influenced by factors such as seasonal meteorology and size of the airborne particles. Vegetation possesses positive relationship with SO₂ and NO₂, implying no pollution abatement effect on SO₂ and NO₂ pollutants. Built-up change has deteriorating effect as well as quenching effect on pollutants. Increase in built terrain have deteriorated the air quality in UIGP whereas it favored in suppressing the aerosol level in LIGP.

Healthy City Community Space-Oriented Structural Planning and Management Optimization under COVID-19

This work studies ways of Healthy City Construction (HCC) and Urban Governance Optimization (UGO) during the COVID-19 pandemic. The specific urban community space planning structure is proposed following a literature review on the healthy city's theoretical basis and historical development. Then, the proposed HCC-oriented community space structure is tested by surveying residents' physical and mental health and infectious risk using a questionnaire survey and Particle Swarm Optimization (PSO). Specifically, the particle fitness is calculated according to the original data conditions, and the community space with the highest fitness is determined. Based on the calculation, the community space's neighbors are investigated from different aspects through a questionnaire survey on patients' daily activities and community health security coverage. The results showed that: (1) The score of daily activities of community patients with respiratory diseases was 2312 before the implementation of the proposed community structure and 2715 after the implementation. Therefore, the service quality of residents increases after implementation. (2) The proposed HCC-oriented community space structure improves the physical self-control ability of chronic patients and helps them reduce their pain. This work aims to create a people-oriented healthy city community space, improve the city's "immune system," and regenerate the energy and environmental sustainability of the urban living environment.

Investigating the Effects of Air Pollution on Plant Species Resistance in Urban Areas

Context: Air pollution is a serious concern for environmental and human health, especially due to increasing the risk of respiratory and cardiovascular diseases. The purpose of this study was to investigate the effects of air pollution on plant species resistance in urban areas. Evidence Acquisition: This narrative review was conducted by searching the databases of Web of Science, Science Direct, Scopus, PubMed, Google Scholar, and Springer. Sixty-five articles were screened by reading their abstracts and full texts. In the end, 12 relevant papers published from 1993 to 2021 were finally selected. Results: The literature review showed that the green spaces created by municipalities in different areas of the city included a set of trees and shrubs compatible by the climate, grass, soil, and water of the region, leading to a significant improvement in air quality. Based on the results, urban green space has the ability to reduce the amount of artificially produced pollutants, and the use of natural potential of trees can improve the quality of the environment depending on various factors such as the climatic condition of the region and the density and amount of vegetation cover. Conclusions: The most effective ways to reduce health and economic costs include reducing the emission of pollutants from cars and industries, extending urban green space, educating citizens, and organizational planning and cooperation. The findings of this study may have important implications for selecting plant species for vegetation traffic barriers.

Cooling effect of the pocket park in the built-up block of a city: a case study in Xi'an, China

Pocket parks, the green infrastructures with small sizes and flexible layouts, are suitable for thermal environment improvement in the urban built-up block with limited green space. To quantify the relationship between pocket parks and the thermal environment in western China, two parks in the built-up block of Xi'an were selected. By field measurement, the cooling effect could be extended 100 m from the park boundary, connecting two parks. Furthermore, the road and greening within the block demonstrate significant influence on the cooling diffusion by regression analysis. Based on ENVI-met simulation, the ratio of the tree and the grass, the layout of the tree and the grass, and the layout of the paving were analyzed at different proportions of greening and paving of the park. Finally, a combination of the daytime physiological equivalent temperature (PET) and nighttime air temperature (AT) was proposed to choose the optimum layouts: the trees concentrated in the center and the pavement with more roads. Results can provide insights for designing pocket parks based on the thermal environment improvement.

Mining association rules between lichens and air quality to support urban air quality monitoring in Nigeria

Urban environments represent the most intense human-environment interaction. This interaction can result in negative outcomes like air pollution and its health implications. There is a significant data deficit in air quality monitoring across many developing nations, which prevents effective policies and measures from being taken to promote the accomplishment of sustainable development. Around the world, lichens have been used to track environmental changes due to their sensitivity to changes and concentration of atmospheric pollutants. This study investigated the relationships between lichen and air quality across some Nigerian cities. Lichen surveys were conducted in four cities. At various periods during the day, NO₂, SO₂, PM_2.5, and PM₁₀ levels were measured. Association rule mining was carried out to investigate the relationship between lichen found and air quality categories. Results showed that the most prevalent lichen Genera are Pyxine in Abuja and Kano, Diorygma in Lagos, and Dirinaria in Port Harcourt. Out of the 40 rules found from the rule mining, 17 are important (lift values ≥ 1.1), capturing six of the fourteen lichen genera identified in the field. The findings indicated that there are important relationships between lichens and air quality indices, suggesting that some lichen species in Nigeria may serve as indicators of long-term air quality. To develop a network of urban environmental quality bioindicators across Nigerian cities, surveying and transplanting are advised. The use of lichen for air quality monitoring can provide information for sustainable management of air quality and environmental quality in Nigeria.

Analysis of Land Use Change Drivers and Simulation of Different Future Scenarios: Taking Shanxi Province of China as an Example

This study analyzed change and spatial patterns of land use in Shanxi from 2000 to 2020. The drivers of land use and cover change (LUCC) in cultivated lands, forest lands, grasslands, and rural construction areas were explored from four dimensions, including population, natural environment, location traffic, and economic development. The CA-Markov model was used to simulate the scenarios of natural growth (NG), ecological protection (EP), economic development (ED), food security (FS), ecological protection-economic development (EP-ED), and ecological protection-food security (EP-FS) in 2030. The results indicated that: (1) The conversion to built-up areas primarily dominated the LUCC processes, and their expansion was mainly to the detriment of the cultivated lands and grasslands during 2000-2020. (2) From 2000 to 2020, population, economy, and land productivity were the main factors of LUCC; the interaction of drivers for the increase of cultivated lands, forest lands, grasslands, and rural construction areas showed enhancement. (3) Under the NG, ED, and EP-ED scenarios, the rural construction areas would have increased significantly, while under the FS and EP-FS scenarios, the cultivated lands would only just have increased. These future land use scenarios can inform decision-makers to make sound decisions that balance socio-economic, ecological, and food security benefits.

Residential greenness and dyslipidemia risk: Dose-response relations and mediation through BMI and air pollution

BACKGROUND

Evidence on associations of residential greenness with dyslipidemia is limited, particularly regarding dose-response relations and mediation.

OBJECTIVES

To investigate associations between greenness and dyslipidemia, non-linear dose-response relationships and mediators.

METHODS

This cross-sectional study draws on the 2018 Fujian Behavior and Disease Surveillance (FBDS) cohort that used multi-stage stratified random sampling from the general population of Fujian Province, China. Participants with one or more abnormities in total cholesterol (TC), triglycerides (TG), high-density lipoprotein cholesterol (HDL-C), or low-density lipoprotein cholesterol (LDL-C) were classified as having dyslipidemia. Residential greenness was operationalized as 3-year average of the normalized difference vegetation index (NDVI_500m) and enhanced vegetation index (EVI_500m). A doubly robust approach was used for effect quantification. Dose-response relations were studied with natural cubic splines. Mediation via physical activity (PA), body mass index (BMI), PM_2.5, PM₁₀, SO₂, and NO₂ was also examined.

RESULTS

Data from 43,183 participants were analyzed. Increases in NDVI_500m and EVI_500m residential greenness were associated with decreased dyslipidemia risk and improved blood lipids. Non-linear dose response relationships were discovered. Significant reduction of dyslipidemia risk was observed at levels of EVI_500m > 0.48 and NDVI_500m > 0.65. Joint mediation effects of PA, BMI, PM_2.5, PM₁₀, NO₂, and SO₂ on the associations of NDVI_500m and EVI_500m with dyslipidemia risk were 49.74% and 44.64%, respectively.

CONCLUSIONS

Increased residential exposure to greenness was associated with decreased risk of dyslipidemia. A non-linear dose-response relationship between greenness and dyslipidemia suggests that specific thresholds of greenness need to be reached in order to achieve effects. BMI, PM_2.5, and PM₁₀ partially mediated the association.

A trait-based typification of urban forests as nature-based solutions

Urban forests as nature-based solutions (UF-NBS) are important tools for climate change adaptation and sustainable development. However, achieving both effective and sustainable UF-NBS solutions requires diverse knowledge. This includes knowledge on UF-NBS implementation, on the assessment of their environmental impacts in diverse spatial contexts, and on their management for the long-term safeguarding of delivered benefits. A successful integration of such bodies of knowledge demands a systematic understanding of UF-NBS. To achieve such an understanding, this paper presents a conceptual UF-NBS model obtained through a semantic, trait-based modelling approach. This conceptual model is subsequently implemented as an extendible, re-usable and interoperable ontology. In so doing, a formal, trait-based vocabulary on UF-NBS is created, that allows expressing spatial, morphological, physical, functional, and institutional UF-NBS properties for their typification and a subsequent integration of further knowledge and data. Thereby, ways forward are opened for a more systematic UF-NBS impact assessment, management, and decision-making.

Associations and pathways between residential greenness and hyperuricemia among adults in rural and urban China

BACKGROUND

Residential greenness may decrease the risk for hyperuricemia in rural areas, but the urban-rural disparities in this association and underlying pathways have not been studied.

OBJECTIVES

To investigate the associations and potential pathways between residential greenness and hyperuricemia in urban and rural areas.

METHODS

The baseline survey of the China Multi-Ethnic Cohort (CMEC) was used. Hyperuricemia was defined as serum uric acid (SUA) > 417 μmol/L for men and >357 μmol/L for women. The satellite-based normalized difference vegetation index (NDVI) and enhanced vegetation index (EVI) were used to capture residential greenness. A propensity score inverse-probability weighting method was used to assess urban-rural differences in the associations between residential greenness and hyperuricemia, with possible mediation effects of physical activity (PA), body mass index (BMI), PM_2.5, and NO₂ examined by causal mediation analyses.

RESULTS

A total of 72,372 participants were included. The increases in the EVI_500m and NDVI_500m residential greenness were associated with a decreased risk for hyperuricemia and the SUA level in both urban and rural areas. For example, each 0.1-unit increase in EVI_500m was associated with a decreased hyperuricemia risk of 7% (OR = 0.93 [0.91, 0.96]) and a decreased SUA level of -1.77 μmol/L [-2.60, -0.93], respectively; such associations were stronger in urban areas for both the risk for hyperuricemia (OR = 0.84 [0.83, 0.86]) and SUA level (-7.18 μmol/L [-7.91, -6.46]). The subgroup analysis showed that the greenness-hyperuricemia/SUA association varied by age, sex, and annual household income. The percentage of the joint mediation effect of PA, BMI, PM_2.5, and NO₂ on the association between EVI_500m and the risk for hyperuricemia was higher in urban (34.92%) than rural areas (15.40%). BMI, PM_2.5, and PA showed significantly independently mediation effects for the greenness-hyperuricemia association in both rural and urban areas.

CONCLUSIONS

Exposure to residential greenness was associated with a decreased risk for hyperuricemia, partially through the pathways of PA, BMI, PM_2.5, and NO₂, which varied in urban and rural areas.

Exploring the association between neighbourhood streetscape vegetation and subjective well-being in a high-density built environment: Evidence from Beijing, China

Many studies have disentangled the perceived benefits of vegetation on subjective well-being (SWB). Yet, scant attention has been paid to the joint effect of vegetation and building density on SWB. This study explores the relationship between streetscape vegetation (SV), building density and SWB in Beijing, China. Our analysis relies on rich measures of street view data to assess SV exposure at the neighbourhood level. Notably, we distinguish between trees (SV-tree) and grasses (SV-grass) when evaluating SV metrics. The results suggest that streetscape trees and grasses are positively associated with SWB, though estimated effects are dependent upon tree and grass density exposures. We also find that the effects of streetscape trees and grass are moderated by building density in the neighbourhood. Additional decomposition analysis provides the insight that the well-being implications of street vegetation and building density are varied significantly by individual sociodemographic characteristics such as sex, age and income. The findings of this study suggest the importance of considering density in SV planning and land use policies to enhance people's quality of life.

Contribution of Home Gardens to Sustainable Development: Perspectives from A Supported Opinion Essay

Home gardening has a long history that started when humans became sedentary, being traditionally considered an accessible source of food and medicinal plants to treat common illnesses. With trends towards urbanization and industrialization, particularly in the post-World War II period, the importance of home gardens as important spaces for growing food and medicinal plants reduced and they began to be increasingly seen as decorative and leisure spaces. However, the growing awareness of the negative impacts of agricultural intensification and urbanization for human health, food quality, ecosystem resilience, and biodiversity conservation motivated the emergence of new approaches concerning home gardens. Societies began to question the potential of nearby green infrastructures to human wellbeing, food provisioning, and the conservation of traditional varieties, as well as providers of important services, such as ecological corridors for wild species and carbon sinks. In this context. and to foster adaptive and resilient social-ecological systems, our supported viewpoint intends to be more than an exhaustive set of perceptions, but a reflection of ideas about the important contribution of home gardens to sustainable development. We envision these humble spaces strengthening social and ecological components, by providing a set of diversified and intermingled goods and services for an increasingly urban population.

Classifying and Mapping Cultural Ecosystem Services Using Artificial Intelligence and Social Media Data

Quantifying and mapping cultural ecosystem services are complex because of their intangibility. Data from social media, such as geo-tagged photographs, has been proposed for mapping cultural use or appreciation of ecosystems. However, manual content analysis and classification of large numbers of photographs is time-consuming. The potential of deep learning for automating the analysis of crowdsourced social media content is still being explored in CES research. Here, we use a new deep learning model for automating the classification of natural and human elements relevant to CES from Flickr images. This approach applies a convolutional neural network architecture to analyze over 29,000 photographs from the Lithuanian coast and uses hierarchical clustering to group these photographs. The accuracy of the classification was assessed by comparison with manual classification. Over 37% of the photographs were taken for the landscape appreciation class, and 28% of the photographs were taken of nature, of animals or plants, which represent the nature appreciation class. The main clusters were identified in urban areas, more precisely in the main coastal cities of Lithuania. The distribution of the nature photographs was concentrated around particular natural attractions, and they were more likely to occur in parks and natural reserves with high levels of vegetation and animal cover. This approach that was developed for clustering the photographs was accurate and saved approximately 100 km of manual work. The method demonstrates how analyzing large numbers of digital photographs expands the analytical toolbox available to researchers and allows the quantification and mapping of CES at large geographical scales. Automated assessment and mapping of cultural ecosystem services could be used to inform urban planning and improve nature reserve management.

Macro-Morphological Traits of Leaves for Urban Tree Selection for Air Pollution Biomonitoring: A Review

Urban trees provide different ecosystem benefits, such as improving air quality due to the retention of atmospheric particulate matter (PM) on their leaves. The main objective of this paper was to study, through a systematic literature review, the leaf macro-morphological traits (LMTs) most used for the selection of urban trees as air pollution biomonitors. A citation frequency index was used in scientific databases, where the importance associated with each variable was organized by quartiles (Q). The results suggest that the most biomonitored air pollutants by the LMTs of urban trees were PM between 1-100 µm (Q1 = 0.760), followed by O₃ (Q2 = 0.586), PM_2.5 (Q2 = 0.504), and PM₁₀ (Q3 = 0.423). PM was probably the most effective air pollutant for studying and evaluating urban air quality in the context of tree LMTs. PM_2.5 was the fraction most used in these studies. The LMTs most used for PM monitoring were leaf area (Q1) and specific leaf area (Q4). These LMTs were frequently used for their easy measurement and quantification. In urban areas, it was suggested that leaf area was directly related to the amount of PM retained on tree leaves. The PM retained on tree leaves was also used to study other f associated urban air pollutants associated (e.g., heavy metals and hydrocarbons).

Exposure to greenspace and cancer incidence, prevalence, and mortality: A systematic review and meta-analyses

We conducted a systematic review and meta-analysis of the available literature on the association between greenspace exposure and all-sites and site-specific cancer incidence, prevalence, and mortality in adults. We searched PubMed, Scopus, and Web of Science for original articles published, without language restriction until September 2021. We assessed the risk of bias in each study and the overall quality of evidence for exposure-outcome pairs that were reported in two or more studies. Out of the 18 included studies, cross-sectional studies were the most common study design (n = 8), and most of the studies were conducted in Europe (n = 8). In terms of risk of bias, the majority of cohorts (four out of six) and case-control studies (three out of four) were of good or very good quality, and cross-sectional studies were mostly (five out of eight) of poor quality. Outcomes (incidence, prevalence, mortality) on different cancer sites were reported: lung cancer (n = 9), prostate cancer (n = 4), breast cancer (n = 4), skin cancer (n = 3), colorectal cancer (n = 2), all-sites cancer (n = 2), brain cancer (n = 1), mouth and throat cancer (n = 1), and esophageal cancer (n = 1). The meta-analyses for the breast, lung, and prostate cancer incidence did not show statistically significant associations (for example for breast cancer: hazard ratio = 0.83; 95% confidence interval: 0.47-1.48). For skin cancer, the available evidence suggests that greenspace could be a potential risk factor. For the other cancers, the evidence was non-conclusive. The overall quality of evidence of all of the exposure-outcome pairs was very low. Given the wide confidence interval of the pooled estimates and very low quality of evidence, the findings should be interpreted with caution. Future large and longitudinal studies are needed to assess the potential association of greenspace exposure with cancers, considering types and quality of greenspace, evaluation of cancer sub-types, and adjustment for a sufficient set of covariates.

Do We Need More Urban Green Space to Alleviate PM2.5 Pollution? A Case Study in Wuhan, China

Urban green space can help to reduce PM2.5 concentration by absorption and deposition processes. However, few studies have focused on the historical influence of green space on PM2.5 at a fine grid scale. Taking the central city of Wuhan as an example, this study has analyzed the spatiotemporal trend and the relationship between green space and PM2.5 in the last two decades. The results have shown that: (1) PM2.5 concentration reached a maximum value (139 μg/m3) in 2010 and decreased thereafter. Moran’s I index values of PM2.5 were in a downward trend, which indicates a sparser distribution; (2) from 2000 to 2019, the total area of green space decreased by 25.83%. The reduction in larger patches, increment in land cover diversity, and less connectivity led to fragmented spatial patterns of green space; and (3) the regression results showed that large patches of green space significantly correlated with PM2.5 concentration. The land use/cover diversity negatively correlated with the PM2.5 concentration in the ordinary linear regression. In conclusion, preserving large native natural habitats can be a supplemental measure to enlarge the air purification function of the green space. For cities in the process of PM2.5 reduction, enhancing the landscape patterns of green space provides a win-win solution to handle air pollution and raise human well-being.

The influence of early-life residential exposure to different vegetation types and paved surfaces on early childhood development: A population-based birth cohort study

BACKGROUND

Growing evidence suggests that exposure to green space is associated with improved childhood health and development, but the influence of different green space types remains relatively unexplored. In the present study, we investigated the association between early-life residential exposure to vegetation and early childhood development and evaluated whether associations differed according to land cover types, including paved land.

METHODS

Early childhood development was assessed via kindergarten teacher-ratings on the Early Development Instrument (EDI) in a large population-based birth cohort (n = 27,539) in Metro Vancouver, Canada. The residential surrounding environment was characterized using a high spatial resolution land cover map that was linked to children by six-digit residential postal codes. Early-life residential exposure (from birth to time of EDI assessment, mean age = 5.6 years) was calculated as the mean of annual percentage values of different land cover classes (i.e., total vegetation, tree cover, grass cover, paved surfaces) within a 250 m buffer zone of postal code centroids. Multilevel models were used to analyze associations between respective land cover classes and early childhood development.

RESULTS

In adjusted models, one interquartile range increase in total vegetation percentage was associated with a 0.33 increase in total EDI score (95% CI: 0.21, 0.45). Similar positive associations were observed for tree cover (β-coefficient: 0.26, 95% CI: 0.15, 0.37) and grass cover (β-coefficient: 0.12, 95% CI: 0.02, 0.22), while negative associations were observed for paved surfaces (β-coefficient: -0.35, 95% CI: -0.47, -0.23).

CONCLUSIONS

Our findings indicate that increased early-life residential exposure to vegetation is positively associated with early childhood developmental outcomes, and that associations may be stronger for residential exposure to tree cover relative to grass cover. Our results further indicate that childhood development may be negatively associated with residential exposure to paved surfaces. These findings can inform urban planning to support early childhood developmental health.

A process approach to the open green space system planning

Open green spaces have significant contributions to the city, urban residents and ecosystem. However, these contributions could not be fully reflected on the urban space due to rapid urbanization. Furthermore, studies on this reflection have focused only on a specific function of open green spaces without a holistic approach. Also, there is no common framework for the definition, classification and standardization of open green spaces or a comprehensive analysis of these domains. The present study aimed to propose a guideline that included five criteria to serve as a baseline to plan open green space systems. In the study, open green spaces and the city were considered as a subsystem of the landscape. Thus, open green space objectives and strategies were proposed based on the landscape functions, urban character and urbanization level (urban density). Furthermore, the study reconsidered the definition and classification of open green spaces and recommended standards. These standards were categorized in two groups based on recreational standards and natural disasters. Thus, the open green spaces were analyzed based on qualitative, quantitative, connectivity and location selection criteria with a holistic approach and a multi-dimensional framework was developed based on ecological, recreational and disaster criteria.

Change of nutrients, microorganisms, and physical properties of exposed extensive green roof substrate

Green roofs (GR) can be used as a nature-based solution to tackle eco-environmental problems caused by climate change and rapid urbanization. The substrate in the GRs is the growing medium for vegetation, and its properties directly affect the ecosystem services of GRs. To investigate the characteristic changes of an exposed substrate after the removal of vegetation, a one-year field experiment was conducted. Substrate properties were comprehensively compared for areas in GR that were planted with Sedum lineare and those with bare substrate. Results show that vegetation cover not only prevented substrate loss by 5.14% (p < 0.05) but also protected the chemical, microbial, and physical properties of the substrate. Moreover, the structure of the substrate changed, as evidenced by a significant increase in fine sand (p < 0.05). The results highlight that attention should be paid to maintaining vegetation cover during GR management. In addition, extensive GRs may not be suitable for fallowing. Once a GR has been established, it needs regular maintenance. Otherwise, the ecological and economic benefits of the GR may be reduced. The findings of the present study can be used to determine the life-cycle costs. Further research should focus on differences in the substrate loss rates, runoff, and temperatures of the substrates under exposure and vegetation cover. The microbial changes after revegetation should also be studied to clarify the role of vegetation in GR ecosystems. The present study provides a reference for improving GR management and ensuring their sustainability.

The Impact of Urban Public Transport on Residential Transaction Prices: A Case Study of Poznań, Poland

This study aims to determine the magnitude and nature of the impact of public urban transport accessibility on the value of residential properties in Poznań. The study was based on 2561 residential transactions completed within the study area in 2020. The input data obtained from the Board of Geodesy and Municipal Cadastre “GEOPOZ” were analysed statistically and spatially. The main part of both the spatial and the statistical analysis was performed using the hedonic pricing method (HPM)-OLS (ordinary least squares) and WLS (weighted least squares). The use of statistical tools enabled the finding of evidence to prove that the convenient accessibility of trams is positively related to housing prices. This has also been confirmed by previous research works conducted in other parts of the world. However, the collected data did not enable the identification of statistically significant relationships between housing prices and the distance from bus stops. The study also attempts to use spatial choropleth maps to clearly illustrate the mechanisms within the local housing market.

Influence of soil moisture level on metabolism of non-structural carbohydrates in Quercus robur leaves

The long-term increases in average temperature and intensification of droughts which characterise the current state of the Earth’s climate system have a negative impact on forest ecosystems and can lead to a decrease in their area and deterioration of the living conditions of their components. In the conditions of the Ukrainian Steppe an important environmental, antierosion, water-protective and soil-protective role belongs to the ravine forests. The most valuable component of the ravine forests is presented by natural populations of common oak (Quercus robur L.), which are able to tolerate the arid climate typical of the steppe region. But with global warming, the endurance of this species is changing. It is believed that a significant role in plant adaptation to drought and high temperatures may belong to non-structural carbohydrates. Therefore, it is important to study changes in the concentration of these substances in the leaves of this leading species under the action of adverse hydrothermal conditions. The article analyzes the content and dynamics of soluble sugars (glucose, fructose, sucrose) and starch in the leaves of Quercus robur L. under different forest growth conditions of the ravine forest (hygromesophilic (CL2–3), mesoxerophilic (CL1) and xerophilic (CL0)). The research was conducted in the forest in the Viyskove area (steppe zone of Ukraine) in the thalweg and at different levels of slope of southern exposure. Content of glucose, fructose, sugar and starch in Quercus robur leaves was determined. It was found that when exposed to high temperatures and increasing water stress during the vegetation period in xerophilic (CL0–1) and mesoxerophilic (CL1) forest growth conditions, the concentration of both glucose and sucrose in the leaves of Q. robur increases and it becomes much higher than in conditions of more optimal water supply. At the same time, the disaccharide content increases more significantly than that of monosaccharide. The greatest amount of these sugars is observed in the driest months (July, August), when conditions for providing plants with water are the most stressful. When water stress grows the increase in concentration of glucose and sucrose is correlated with reduction of starch content. It has been found that the concentration of fructose in Q. robur leaves in droughty conditions of growing was comparable to more favourable conditions of moisture. In September, there is a decline in the content of all forms of non-structural carbohydrates in the leaves of plants of all variants compared to the previous month, especially in conditions of adverse water supply. Therefore, forest growth conditions do not affect the nature of the dynamics of soluble sugars and starch in the leaves of Q. robur, although they change their quantitative indicators. Based on the protective function of sugars under the action of stressors on plants, we can assume that in conditions of significant lack of moisture in the soil their accumulation in the leaves in areas with mesoxerophilic and xerophilic hygrotopes plays an important role in increasing Q. robur drought resistance.

Can parkland mitigate mental health burden imposed by the COVID-19? A national study in China

The worldwide coronavirus disease 2019 (COVID-19) pandemic has seriously affected not only physical health but also mental wellbeing (i.e mental stress and suicide intention) of numerous urban inhabitants across the globe. While many studies have elucidated urban parkland enhances and mental wellbeing of urban residents, the potential for parkland to mitigate mental health burden imposed by the COVID-19 has received no attention. This nationwide study systematically explored the association between parkland, the COVID-19 pandemic situation and mental wellbeing from 296 cities in China. The study innovatively used big data from Baidu Search Engine to assess city-level mental wellbeing, thereby enabling comparisons among cities. The results show that the provision of parkland is positively associated with mental wellbeing during the COVID-19 epidemic. For COVID-19-related indicators, the geographical distance to Wuhan city, work resumption rate, and travel intensity within the city are also positively associated with mental wellbeing, while the number of COVID-19 infections and the proportion of migrants from Hubei Province for each city are negatively associated with mental wellbeing. Last, the most important finding is that parkland reduces the negative effect of COVID-19 on mental wellbeing during the COVID-19 epidemic. To achieve the goal of promoting mental wellbeing through urban planning and design during the future pandemics, policymakers and planners are advised to provide more well-maintained and accessible parkland and encourage residents to use them with proper precautions.

Assessing the role of urban green spaces for human well-being: a systematic review

Human has been evolving in a natural environment over a long time; thus, he is habitual to adapt it. Green spaces are obligatory landscapes in an urban structure that provide a natural environment and accelerate other life events. In contrast, unplanned urbanization, and conversion from green to grey structures have damaged natural environmental resources. Studies through different angles have highlighted the importance of urban green spaces for human well-being but now need to identify their role according to the potential. The demands of urban green spaces may differ with the change of population size, types of grey structure, urban expansion, the altitude of the place, and geographical location. Therefore, this systematic review aims to analyse the significance of urban green spaces for human well-being. The study opted for a systematic process during the selection and organization of studies for this review. After analysing, 46 studies were finalized with the consensus of three review authors. Accordingly, literature was analysed under the central theme of "Urban Green Spaces for Human Well-being." Human Well-being was assessed under six sub-themes; physical, psychological, mental, social, subjective, and environmental well-being. The review concluded that urban green spaces are the primary pillar for a sustainable urban place and human well-being due to highly positive and positive correlations. Moreover, the study did not find any demarcation line between green spaces and grey structures according to any specific need. Therefore, the study suggested that the role of urban green spaces for human well-being should be analysed according to their potential and required optimal ratio under different communities' urban specific environments and social behaviour.

Are greenspace quantity and quality associated with mental health through different mechanisms in Guangzhou, China: A comparison study using street view data

Residential greenspace quality may be more important for people's mental health than the quantity of greenspace. Existing literature mainly focuses on greenspace quantity and is limited to exposure metrics based on an over-head perspective (i.e., remote sensing data). Thus, whether greenspace quantity and quality influence mental health through different mechanisms remains unclear. To compare the mechanisms through which greenspace quantity and quality influence mental health, we used both remote sensing and street view data. Questionnaire data from 1003 participants in Guangzhou, China were analysed cross-sectionally. Mental health was assessed through the World Health Organization Well-Being Index (WHO-5). Greenspace quantity was measured by both remote sensing-based Normalized Difference Vegetation Index (NDVI) and Street View Greenness-quantity (SVG-quantity). Greenspace quality was measured by both Street View Greenness-quality (SVG-quality) and questionnaire-based self-reported greenspace quality. Structural equation models were used to assess mechanisms through which neighbourhood greenspace exposure has an influence on mental health. Stress, social cohesion, physical activity and life satisfaction were found to mediate both SVG-quality - WHO-5 scores and self-reported greenspace quality - WHO-5 scores associations. However, only NO₂ (nitrogen dioxide) mediated the association between NDVI and WHO-5 scores, while NO₂, perceived pollution and social cohesion mediated the association between SVG-quantity and WHO-5 scores. The mechanisms through which neighbourhood greenspace exposure influences mental health may vary across different exposure assessment strategies. Greenspace quantity influences mental health through reducing harm from pollution, while greenspace quality influences mental health through restoring and building capacities.

Cooling strategies for thermal comfort in cities: a review of key methods in landscape design

Under the climate change scenario, the negative impacts of urban heat island (UHI) will exacerbate due to unsustainable urban planning and human activities. Thermal comfort has close relationships with UHI in urban areas. This paper is based on the studies of urban heat island, thermal comfort, microclimate, and urban planning in cities in the recent decade, combined with a method of research into design. The key topics include vegetation and water conditions, the albedo of materials, and urban morphology. By the comparative case studies in landscape projects, the results further reveal that the density of tree canopies, the natural structure and density of ground cover, the form of water features, the color and texture of materials, and the scale of shading structures have different cooling effect and performance in outdoor thermal comfort improvement with specific features in the landscape design. It is also found that there are some external conditions that can influence design determinations in real practices. The purpose of this study is to provide theoretical research methods and evaluation of thermal comfort landscape design elements and to provide guidance for future sustainable city research and landscape design.

Green Space Quality and Health: A Systematic Review

(1) Background: As cities densify, researcher and policy focus is intensifying on which green space types and qualities are important for health. We conducted a systematic review to examine whether particular green space types and qualities have been shown to provide health benefits and if so, which specific types and qualities, and which health outcomes. (2) Methods: We searched five databases from inception up to June 30, 2021. We included all studies examining a wide range of green space characteristics on various health outcomes. (3) Results: 68 articles from 59 studies were found, with a high degree of heterogeneity in study designs, definitions of quality and outcomes. Most studies were cross-sectional, ecological or cohort studies. Environment types, vegetation types, and the size and connectivity of green spaces were associated with improved health outcomes, though with contingencies by age and gender. Health benefits were more consistently observed in areas with greater tree canopy, but not grassland. The main outcomes with evidence of health benefits included allergic respiratory conditions, cardiovascular conditions and psychological wellbeing. Both objectively and subjectively measured qualities demonstrated associations with health outcomes. (4) Conclusion: Experimental studies and longitudinal cohort studies will strengthen current evidence. Evidence was lacking for needs-specific or culturally-appropriate amenities and soundscape characteristics. Qualities that need more in-depth investigation include indices that account for forms, patterns, and networks of objectively and subjectively measured green space qualities.

PM2.5 Pollutant Concentrations in Greenspaces of Nanjing Are High but Can Be Lowered with Environmental Planning

Small-scale greenspaces in high-density central urban districts serve as important outdoor activity spaces for the surrounding residents, especially the elderly. This study selects six small-scale, popular greenspaces with distinct characteristics that are jointly situated along the same main urban artery in a high-density central urban district. Field investigations and questionnaires are conducted and combined with statistical analyses, to explore the spatial-temporal distribution and influencing factors of PM2.5 concentrations in these greenspaces. The study finds that the air quality conditions in the sites are non-ideal, and this has potential negative impacts on the health of the elderly visitors. Moreover, the difference values of PM2.5 concentrations' spatial-temporal distributions are significantly affected by vehicle-related emissions, which have significant temporal characteristics. PM2.5 concentration is strongly correlated with percentage of green coverage (R = 0.82, p < 0.05), degree of airflow (R = -0.83, p < 0.05), humidity and comfort level (R = 0.54, p < 0.01 and R = -0.40, p < 0.01 respectively). Meanwhile, the sites' "sky view factor" is strongly correlated with degree of airflow (R = 0.82, p < 0.05), and the comfort level plays an indirect role in the process of PM2.5 affecting crowd activities. Based on this analysis, an optimal set of index ranges for greenspace elements which are correlated with the best reduction in PM2.5 concentrations is derived. As such, this research reveals the technical methods to best reduce their concentrations and provides a basis and reference for improving the quality of small-scale greenspaces in high-density urban districts for the benefit of healthy aging.

Using machine learning to examine street green space types at a high spatial resolution: Application in Los Angeles County on socioeconomic disparities in exposure

BACKGROUND

Compared to commonly-used green space indicators from downward-facing satellite imagery, street view-based green space may capture different types of green space and represent how environments are perceived and experienced by people on the ground, which is important to elucidate the underlying mechanisms linking green space and health.

OBJECTIVES

This study aimed to evaluate machine learning models that can classify the type of vegetation (i.e., tree, low-lying vegetation, grass) from street view images; and to investigate the associations between street green space and socioeconomic (SES) factors, in Los Angeles County, California.

METHODS

SES variables were obtained from the CalEnviroScreen3.0 dataset. Microsoft Bing Maps images in conjunction with deep learning were used to measure total and types of street view green space, which were compared to normalized difference vegetation index (NDVI) as commonly-used satellite-based green space measure. Generalized linear mixed model was used to examine associations between green space and census tract SES, adjusting for population density and rural/urban status.

RESULTS

The accuracy of the deep learning model was high with 92.5% mean intersection over union. NDVI were moderately correlated with total street view-based green space and tree, and weakly correlated with low-lying vegetation and grass. Total and three types of green space showed significant negative associations with neighborhood SES. The percentage of total green space decreased by 2.62 [95% confidence interval (CI): -3.02, -2.21, p < 0.001] with each interquartile range increase in CalEnviroScreen3.0 score. Disadvantaged communities contained approximately 5% less average street green space than other communities.

CONCLUSION

Street view imagery coupled with deep learning approach can accurately and efficiently measure eye-level street green space and distinguish vegetation types. In Los Angeles County, disadvantaged communities had substantively less street green space. Governments and urban planners need to consider the type and visibility of street green space from pedestrian's perspective.

Using machine learning to examine street green space types at a high spatial resolution: Application in Los Angeles County on socioeconomic disparities in exposure

BACKGROUND

Compared to commonly-used green space indicators from downward-facing satellite imagery, street view-based green space may capture different types of green space and represent how environments are perceived and experienced by people on the ground, which is important to elucidate the underlying mechanisms linking green space and health.

OBJECTIVES

This study aimed to evaluate machine learning models that can classify the type of vegetation (i.e., tree, low-lying vegetation, grass) from street view images; and to investigate the associations between street green space and socioeconomic (SES) factors, in Los Angeles County, California.

METHODS

SES variables were obtained from the CalEnviroScreen3.0 dataset. Microsoft Bing Maps images in conjunction with deep learning were used to measure total and types of street view green space, which were compared to normalized difference vegetation index (NDVI) as commonly-used satellite-based green space measure. Generalized linear mixed model was used to examine associations between green space and census tract SES, adjusting for population density and rural/urban status.

RESULTS

The accuracy of the deep learning model was high with 92.5% mean intersection over union. NDVI were moderately correlated with total street view-based green space and tree, and weakly correlated with low-lying vegetation and grass. Total and three types of green space showed significant negative associations with neighborhood SES. The percentage of total green space decreased by 2.62 [95% confidence interval (CI): -3.02, -2.21, p < 0.001] with each interquartile range increase in CalEnviroScreen3.0 score. Disadvantaged communities contained approximately 5% less average street green space than other communities.

CONCLUSION

Street view imagery coupled with deep learning approach can accurately and efficiently measure eye-level street green space and distinguish vegetation types. In Los Angeles County, disadvantaged communities had substantively less street green space. Governments and urban planners need to consider the type and visibility of street green space from pedestrian's perspective.

Microbial degradation of pyrene in holm oak (Quercus ilex) phyllosphere: Role of particulate matter in regulating bioaccessibility

In this study we first measured the mineralization of pyrene on leaves of urban holm oak (Quercus ilex) by autochthonous microorganisms and an inoculated PAH degrading bacterium (i.e., Mycobacterium gilvum), selected as a model phyllosphere species, as well as the leaf-water (K_LW) and leaf-air (K_LA) partition coefficients for this chemical. Mineralization was investigated in two different experimental systems in terms of leaf and microorganism environment. Additionally, the influence on pyrene partitioning and mineralization when particulate matter (PM) was present on the leaf surface or removed was studied. Mineralization of ¹⁴C-labeled pyrene by autochthonous microorganisms was lower than 1% after approximately two weeks, while M. gilvum mineralized 5% to 17% of pyrene. These extents corresponded to mineralization half-lives that ranged between ~30 to ~200 days. We proposed that PM present at the leaf surface reduced the accumulation of pyrene by inner compartments (cuticle) distantly located from microbial cells and enhanced the bioaccessibility of pyrene, speeding up microbial activity and therefore mineralization. These results highlight that plant-phyllosphere microorganism interaction is more complex than currently established and deserves additional studies to further comprehend the air purification ecosystem service of phyllosphere microorganisms.

The Impact of Indoor Living Wall System on Air Quality: A Comparative Monitoring Test in Building Corridors

Living wall systems have been widely recognized as one of the promising approaches for building applications due to their aesthetic value and ecological benefits. Compared with outdoor living wall systems, indoor living wall systems (ILWS) play a more vital role in indoor air quality. The aim of this study is to investigate the effects of ILWS on indoor air quality. In an office building, two parallel corridors were selected as comparative groups. A 10.6 m2 ILWS was installed on the sidewall of the west corridor while the east corridor was empty. Some important parameters, including indoor air temperature, relative humidity, concentrations of carbon dioxide (CO2), and particulate matter (PM) were obtained based on the actual environment monitoring. According to the statistical analysis of the data, there were significant differences in the concentrations of CO2 and PMs in the corridors with and without ILWS, which indicated that CO2 and PM2.5 removal rate ranged from 12% to 17% and 8% to 14%, respectively. The temperature difference is quite small (0.13 °C on average), while relative humidity slightly increased by 3.1–6.4% with the presence of the ILWS.

Residential greenness associated with lower serum uric acid levels and hyperuricemia prevalence in a large Chinese rural population

BACKGROUND

The association between residential greenness and hyperuricemia remains unclear, especially in developing countries. The current study aimed to explore the associations between residential greenness and both serum uric acid (SUA) levels and hyperuricemia in a Chinese rural population and to examine potential pathways of these associations.

METHODS

In this cross-sectional study, 38,721 rural residents were recruited from the baseline survey of the Henan Rural Cohort study in 2015-2017. Two satellite-derived vegetation indices, i.e., the normalized difference vegetation index (NDVI) and the enhanced vegetation index (EVI), were used to estimate residential greenness. Air pollution was determined by two proxies: particulate matter with aerodynamic diameter ≤ 2.5 μm (PM_2.5) and nitrogen dioxide (NO₂). Hyperuricemia was defined as SUA levels of >417 μmol/L and > 357 μmol/L for men and women, respectively. Multivariable-adjusted linear regression and logistic regression models were applied to investigate the associations of greenness with SUA and hyperuricemia, and mediation analyses were used to explore possible mechanisms underlying the associations.

RESULTS

An interquartile range (IQR) increase in both EVI and NDVI in the 500 m buffer was significantly associated with reductions in SUA levels of -7.23 μmol/L (95% confidence interval (CI): -8.96, -5.50) and -4.38 μmol/L (95% CI: -5.93, -2.83), respectively. The same increases in EVI_500-m and NDVI_500-m were associated with 13.8% (95% CI: 5.8%, 21.2%) and 13.0% (95% CI: 5.6%, 19.8%) lower hyperuricemia prevalence, respectively. These associations were stronger in older people (age ≥ 65), men or participants with higher averaged monthly income. The associations were partly mediated by physical activity and BMI, while no mediation effect was observed for air pollution.

CONCLUSIONS

Higher levels of residential greenness were significantly associated with lower SUA levels and hyperuricemia prevalence in the Chinese rural population. BMI and physical activity may play important mediating roles in the associations.

Temporal variability of noise pollution attenuation by vegetation in urban parks

The present study proposed a novel approach to investigate variability in the acoustic behavior of a number of deciduous tree-dominated narrow and long urban parks in Isfahan city, central Iran, between winter leaf fall and summer foliage. Noise levels (Lq30 in dB) were measured along two adjacent sides of the parks: along the road-adjacent side (Ro transect) and the relatively calmer river-adjacent side of the parks (Ri transect) during 4-17 January 2018 and 7-14 August 2019. Using Sentinel-2 images, two NDVI maps were also produced for these two periods to determine how changes in green biomass were associated with changes in noise levels. Using ANOVA, a significant difference was found in Ri-Lq30 and NDVI maps between winter and summer (p = 0.0), while the difference was insignificant for Ri-Lq30 (p = 0.1). We also developed two multiple linear regressions, one for each season, to assess the dependency of Ri-Lq30 to the intensity of vegetation and Ro-Lq30 and compare the two seasons by performing a t test analysis on the intercept and slope of the models, with results suggesting there is a significant difference in the association of green biomass and noise levels measured inside the parks between leaf fall and foliage time (p = 0.04). Our results indicated the temporal variability of park characteristics in providing calmer urban landscapes throughout the year.

Chlorophyll fluorescence parameters, leaf traits and foliar chemistry of white oak and red maple trees in urban forest patches

The provisioning of critical ecosystem services to cities of the eastern USA depends on the health and physiological function of trees in urban areas. Although we know that the urban environment may be stressful for trees planted in highly developed areas, it is not clear that trees in urban forest patches experience the same stressful environmental impacts. In this study, we examine chlorophyll fluorescence parameters, leaf traits, foliar nutrients and stable isotope signatures of urban forest patch trees compared with trees growing at reference forest sites, in order to characterize physiological response of these native tree species to the urban environment of three major cities arranged along a latitudinal gradient (New York, NY; Philadelphia, PA; Baltimore, MD). Overall, white oaks (Quercus alba L.) show more differences in chlorophyll fluorescence parameters and leaf traits by city and site type (urban vs reference) than red maples (Acer rubrum L.). The exceptions were δ13C and δ15N, which did not vary in white oak foliage but were significantly depleted (δ13C) and enriched (δ15N) in urban red maple foliage. Across all sites, red maples had higher thermal tolerance of photosynthesis (Tcrit) than white oaks, suggesting a greater ability to withstand temperature stress from the urban heat island effect and climate change. However, the highest average values of Tcrit were found in the Baltimore urban white oaks, suggesting that species suitability and response to the urban environment varies across a latitudinal gradient. Stomatal pore index (SPI) showed inter-specific differences, with red maple SPI being higher in urban trees, whereas white oak SPI was lower in urban trees. These results demonstrate that differences in native tree physiology occur between urban and reference forest patches, but they are site- and species-specific. Data on local site characteristics and tree species performance over time remain necessary to gain insight about urban woodland ecosystem function.

Associations between land cover categories, gaseous PAH levels in ambient air and endocrine signaling predicted from gut bacterial metagenome of the elderly

There is evidence that polycyclic aromatic hydrocarbons (PAHs) and human gut microbiota are associated with the modulation of endocrine signaling pathways. Independently, studies have found associations between air pollution, land cover and commensal microbiota. We are the first to estimate the interaction between land cover categories associated with air pollution or purification, PAH levels and endocrine signaling predicted from gut metagenome among urban and rural populations. The study participants were elderly people (65-79 years); 30 lived in rural and 32 in urban areas. Semi-Permeable Membrane devices were utilized to measure air PAH concentrations as they simulate the process of bioconcentration in the fatty tissues. Land cover categories were estimated using CORINE database and geographic information system. Functional orthologues for peroxisome proliferator-activated receptor (PPAR) pathway in endocrine system were analyzed from gut bacterial metagenome with Kyoto Encyclopaedia of Genes and Genomes. High coverage of broad-leaved and mixed forests around the homes were associated with decreased PAH levels in ambient air, while gut functional orthologues for PPAR pathway increased along with these forest types. The difference between urban and rural PAH concentrations was not notable. However, some rural measurements were higher than the urban average, which was due to the use of heavy equipment on active farms. The provision of air purification by forests might be an important determining factor in the context of endocrine disruption potential of PAHs. Particularly broad-leaved forests around homes may reduce PAH levels in ambient air and balance pollution-induced disturbances within commensal gut microbiota.

Monitoring the Spatial Variation of Aerosol Optical Depth and Its Correlation with Land Use/Land Cover in Wuhan, China: A Perspective of Urban Planning

Aerosols significantly affect environmental conditions, air quality, and public health locally, regionally, and globally. Examining the impact of land use/land cover (LULC) on aerosol optical depth (AOD) helps to understand how human activities influence air quality and develop suitable solutions. The Landsat 8 image and Moderate Resolution Imaging Spectroradiometer (MODIS) aerosol products in summer in 2018 were used in LULC classification and AOD retrieval in this study. Spatial statistics and correlation analysis about the relationship between LULC and AOD were performed to examine the impact of LULC on AOD in summer in Wuhan, China. Results indicate that the AOD distribution expressed an obvious “basin effect” in urban development areas: higher AOD values concentrated in water bodies with lower terrain, which were surrounded by the high buildings or mountains with lower AOD values. The AOD values were negatively correlated with the vegetated areas while positively correlated to water bodies and construction lands. The impact of LULC on AOD varied with different contexts in all cases, showing a “context effect”. The regression correlations among the normalized difference vegetation index (NDVI), normalized difference built-up index (NDBI), normalized difference water index (NDWI), and AOD in given landscape contexts were much stronger than those throughout the whole study area. These findings provide sound evidence for urban planning, land use management and air quality improvement.

Assessing and Predicting the Impact of Multi-Scenario Land Use Changes on the Ecosystem Service Value: A Case Study in the Upstream of Xiong’an New Area, China

The evaluation of ecosystem service value has become the basis of ecological protection, ecological regionalization, and ecological compensations. Land use changes have taken place due to several natural and anthropogenic reasons, significantly influencing the ecosystem services value (ESV). In this study, we used an interactive coupling model that simulates future land use changes and the equivalent coefficient table method to predict and evaluate the ecosystem service value in the upstream of Xiong’an New Area in 2035, and we quantitatively calculated the impact of land use changes on the ecosystem service value under four future scenarios. The results indicate that from 2015 to 2035, the ecosystem service value in the production scenario and life scenario decreased significantly by CNY 1635.39 million and 561.95 million, respectively, and the areas where the ESV decreased mainly appeared in river banks and surrounding areas of towns. The conversion of forest land to cultivated land and the conversion of grassland to construction land are the main reasons for the reduction of the ecosystem service value in the production scenario and life scenario, respectively. The ecosystem service value in the ecological scenario increased significantly by CNY 2550.59 million, and the conversion of grassland to waters is the main reason for the increase in ecosystem service value, with a contribution rate of 73.89%. Moreover, due to the trade-off between ecosystem services, the overall change of ecosystem service value in the current scenario is not obvious. In conclusion, strictly controlling the scale of construction land, strengthening the management and protection of water resources, and expanding the afforestation scale may improve the ecosystem service value of the upstream Xiong’an New Area in the future.

Determination of the most effective control methods of SO2 Pollution in Tehran based on adaptive neuro-fuzzy inference system

Air pollution in metropolises is one of the serious problems of human life. Tehran is one of the cities facing air pollution problem. Urban managers concern about choosing different management methods to control air pollution. In this study, a combination of fuzzy systems and neural networks has been used to select the most suitable scenario for controlling SO₂ pollution. According to the method presented in this paper, 8 input data categories such as wind speed, precipitation, temperature, pressure, humidity, gas oil consumption, gasoline consumption and urban green space levels have been used as independent parameters and SO₂ pollutant concentration has been considered as the dependent parameter. The contribution of each meteorological station to the meteorological data was determined by Thiessen Polygon Method. Then, using adaptive neural fuzzy inference systems, modeling was done in Sugeno Method and the least root mean square error (3.19) was determined for the model. Then, by changing each of the independent parameters, the effect of each of these independent parameters on SO₂ pollutant was measured. The results showed that the parameters of pressure, urban green space, gasoline consumption, gas oil consumption, temperature, wind speed and humidity, respectively, had the greatest effect on reducing the SO₂ concentration. Since the parameters of gasoline and gas oil consumption as well as the area of green space are changeable by different policies and by human decisions, the concentration of SO₂ pollutant can be controlled by reducing the consumption of gasoline and gas oil and increasing the green space in Tehran.

Green Space Exposure Association with Type 2 Diabetes Mellitus, Physical Activity, and Obesity: A Systematic Review

Type 2 diabetes mellitus (T2DM) is a public health challenge that must be addressed considering the large number of risk factors involved in its appearance. Some environmental risk factors are currently described as predictors of diabetes, with access to green spaces being an element to consider in urban settings. This review aims to study the association between exposure to green spaces and outcomes such as diabetes, obesity, and physical activity in the general population. A systematic review was carried out using the PubMed, Embase, and LILACS databases and other sources. The search strategy was carried out from October 2019 to October 2020. Cross-sectional and cohort studies were included. The article selection was made by a pair of reviewers, and data extraction was carried out using a data extraction sheet. The quality assessment of the included studies was carried out using a validated tool. Finally, 19 scientific articles were included in this review. Evidence supports that people and communities exposed to green spaces, especially in their neighborhood, reduce the risk of T2DM and reduce the risk of being obese and increase the likelihood of physical activity. The onset of T2DM can be moderated by using green spaces, improving physical activity levels, and reducing the risk of being overweight and obese.