How can vegetation protect us from air pollution? A critical review on green spaces' mitigation abilities for air-borne particles from a public health perspective - with implications for urban planning

Investigating the effects of the greenery increase on air temperature, ventilation and cooling energy demand in Melbourne with the Weather Research and Forecasting model and Local Climate Zones

Vegetation has a well-known potential for mitigating urban overheating. This work aims to explore the effects of enhancing urban greenery in Melbourne (Australia) through a configuration of the Weather Research and Forecasting (WRF) model including the Building Effect Parameterization and the Local Climate Zones and presents novelties in: i) covering two-months and ii) focusing on air circulation and buildings cooling energy demand through the ventilation coefficient (VC) and the cooling degree hours (CDHs). A control case and two "what-if" scenarios with a growing green coverage equal to 35 % (control case), 50 % (modest increase) and 60 % (robust increase) have been designed and then simulated for January and February 2019. Outcomes reveal a maximum drop in 2 m temperature of approximately 0.4 °C and 0.8 °C at 14:00 LT for the modest and robust green increase scenario, respectively. The urban-rural energy surplus for cooling buildings is reduced and even counterbalanced. Peak CDHs decrease from 143 °C·h of the control case to 135 °C·h (modest increase) and 126 °C·h (robust increase), while they measure 137 °C·h in the non-urban areas. Average wind speed increases by 0.8 m/s (equal to 22 % with respect to the control case). Furthermore, adding urban greenery has an unfavorable implication on VC (maximum reduction of 500 m2s-1) with a consequent deterioration of the transport and dispersion of pollutants. Middle- and high-density classes are touched more than low-density by the VC reduction. In addition, the benefits of enhancing urban greenery concern physiologically and psychologically the quality of life of the dwellers.

The urban air quality nexus: Assessing the interplay of land cover change and air pollution in emerging South Asian cities

Air quality degradation presents a significant public health challenge, particularly in rapidly urbanizing regions where changes in land use/land cover (LULC) can dramatically influence pollution levels. This study investigates the association between LULC changes and air pollution (AP) in the five fastest-growing cities of Bangladesh from 1998 to 2021. Leveraging satellite data from Landsat and Sentinel-5P, the analysis reveals a substantial increase in urban areas and sparse vegetation, with declines in dense vegetation and water bodies over this period. Urban expansion was most pronounced in Sylhet (22-254%), while Khulna experienced the largest increase in sparse vegetation (2-124%). Dense vegetation loss was highest in Dhaka (20-77%) and water bodies (9-59%) over this period. Concentrations of six major air pollutants (APTs) - aerosol index, CO, HCHO, NO2, O3, and SO2 - were quantified, showing alarmingly high levels in densely populated industrial and commercial zones. Pearson's correlation indicates strong positive associations between APTs and urban land indices (R > 0.8), while negative correlations exist with vegetation indices. Geographically weighted regression modeling identifies city centers with dense urban built-up as pollution hotspots, where APTs exhibited stronger impacts on land cover changes (R2 > 0.8) compared to other land classes. The highest daily emissions were observed for O3 (1031 tons) and CO (356 tons) at Chittagong in 2021. In contrast, areas with substantial green cover displayed weaker pollutant-land cover associations. These findings underscore how unplanned urbanization drives AP by replacing natural land cover with emission sources, providing crucial insights to guide sustainable urban planning strategies integrating pollution mitigation and environmental resilience.

Strategies to reduce air pollution emissions from urban residential buildings

As cities continue to grow, developing mitigation strategies is crucial to minimize the corresponding increase in air pollutants. One source of potentially controllable air pollution is the emissions from residential buildings. We conducted a literature review to systematically examine air pollution emissions from residential buildings in urban areas, identifying pollutants and their sources; investigated mitigation-aimed intervention types by field of application or study, and finally listed and discussed strategies to reduce the concentration of air pollutants in residential buildings. Our compilation shows that among the nature-based solutions, green walls offered the highest relative reduction of air pollution (-15 % NO2 and -23 % PM10). Of the construction-based solutions, already-available photocatalytic paint can achieve reductions of 25 % NO, 23 % NOx and 19 % NO2 as is. Industrial-based solutions promise high levels of reduction, but these must be adapted to residential buildings. The integration of various existing and potentially adapted mitigation solutions may achieve even higher pollution reduction rates in urban areas.

Association between prenatal air pollutant exposure and autism spectrum disorders in young children: A matched case-control study in Canada

The direction and magnitude of association between maternal exposure to ambient air pollutants across gestational windows and offspring risk of autism spectrum disorders (ASD) remains unclear. We sought to evaluate the time-varying effects of prenatal air pollutant exposure on ASD. We conducted a matched case-control study of singleton term children born in Ontario, Canada from 1-Apr-2012 to 31-Dec-2016. Provincial birth registry data were linked with applied behavioural analysis services and ambient air pollutant datasets to ascertain prenatal exposure to nitrogen dioxide (NO2), ground-level ozone (O3), fine particulate matter (PM2.5), and ASD diagnoses. Covariate balance between cases and controls was established using coarsened exact matching. Conditional logistic regression was used to assess the association between prenatal air pollutant exposure and ASD. Distributed lag non-linear models (DLNM) were used to examine the effects of single-pollutant exposure by prenatal week. Sensitivity analyses were conducted to assess the impact of exposure period on the observed findings. The final sample included 1589 ASD cases and 7563 controls. Compared to controls, cases were more likely to be born to mothers living in urban areas, delivered by Caesarean section, and assigned male sex at birth. NO2 was a consistent and significant contributor to ASD risk after accounting for co-exposure to O3, PM2.5 and covariates. The odds ratio per interquartile range increase was 2.1 (95%CI 1.8-2.3) pre-conception, 2.2 (2.0-2.5) for the 1st trimester, 2.2 (1.9-2.5) for the 2nd trimester, and 2.1 (1.9-2.4) for the 3rd trimester. In contrast, findings for O3 and PM2.5 with ASD were inconsistent. Findings from DLNM and sensitivity analyses were similar. Exposure to NO2 before and during pregnancy was significantly associated with ASD in offspring. The relationship between prenatal O3 and PM2.5 exposure and ASD remains unclear. Further investigation into the combined effects of multi-pollutant exposure on child neurodevelopment is warranted.

Short-term ozone exposure on stroke mortality and mitigation by greenness in rural and urban areas of Shandong Province, China

BACKGROUND

Short-term exposure to ozone (O3) has been associated with higher stroke mortality, but it is unclear whether this association differs between urban and rural areas. The study aimed to compare the association between short-term exposure to O3 and ischaemic and haemorrhagic stroke mortality across rural and urban areas and further investigate the potential impacts of modifiers, such as greenness, on this association.

METHODS

A multi-county time-series analysis was carried out in 19 counties of Shandong Province from 2013 to 2019. First, we employed generalized additive models (GAMs) to assess the effects of O3 on stroke mortality in each county. We performed random-effects meta-analyses to pool estimates to counties and compare differences in rural and urban areas. Furthermore, a meta-regression model was utilized to assess the moderating effects of county-level features.

RESULTS

Short-term O3 exposure was found to be associated with increased mortality for both stroke subtypes. For each 10-µg/m3 (lag0-3) rise in O3, ischaemic stroke mortality rose by 1.472% in rural areas and 1.279% in urban areas. For each 0.1-unit increase in the Enhanced Vegetation Index (EVI) per county, the ischaemic stroke mortality caused by a 10-µg/m3 rise in O3 decreased by 0.60% overall and 1.50% in urban areas.

CONCLUSIONS

Our findings add to the evidence that short-term O3 exposure increases ischaemic and haemorrhagic stroke mortality and has adverse effects in urban and rural areas. However, improving greenness levels may contribute to mitigating the detrimental effects of O3 on ischaemic stroke mortality.

Accumulation of airborne microplastics on leaves of different tree species in the urban environment

Microplastics (MPs) are omnipresent in the environment and they are linked to ecosystem and human health problems. The atmospheric transport of MPs and the role of tree leaves in MP atmospheric deposition has not been adequately studied. MP concentrations on the leaves of different tree species in urban regions of the Netherlands and Portugal, along with related MP deposition, were investigated in this study. We collected leaves from cedar, eucalyptus, oak, pine and willow trees, together with monthly deposition of particles under the trees and in the open space in Coimbra (Portugal). In Wageningen (the Netherlands), we collected leaves from a fir and a holly tree at different heights above the ground and with dry and wet weather conditions. MPs were extracted through density separation and quantified under a microscope. Polymer types were identified using μ-FTIR. The results showed a higher number of MP particles on the needle-shaped leaves from fir (2.52 ± 2.14 particles·cm-2) and pine (0.5 ± 0.13 particles·cm-2) and significantly lower numbers of MPs per cm2 of leaf area on the bigger leaves from eucalyptus (0.038 ± 0.003 particles·cm-2) and cedar (0.037 ± 0.002 particles·cm-2). All tree leaves seemed to filter airborne MPs, especially the smallest particles. A non-significantly higher number of particles on leaves was detected on lower tree branches and after dry periods. The deposition of MPs under trees was generally higher than in the open space. Our results indicated that part of the MPs retained by the tree leaves floats down to lower branches and to the soil surface. We also saw that different tree species had different capacities to retain particles on their leaves over time. To control the transport of MPs through the atmosphere, it is essential to consider the role of different vegetation types in filtering small particles, especially in cities.

Residential air pollution, greenspace, and adverse mental health outcomes in the U.S. Gulf Long-term Follow-up Study

Air pollution and greenness are environmental determinants of mental health, though existing evidence typically considers each exposure in isolation. We evaluated relationships between co-occurring air pollution and greenspace levels and depression and anxiety. We estimated cross-sectional associations among 9015 Gulf Long-term Follow-up Study participants living in the southeastern U.S. who completed the Patient Health Questionnaire-9 (depression: score ≥ 10) and Generalized Anxiety Disorder Questionnaire-7 (anxiety: score ≥ 10). Participant residential addresses were linked to annual average concentrations of particulate matter (1 km PM2.5) and nitrogen dioxide (1 km NO2), as well as satellite-based greenness (2 km Enhanced Vegetation Index (EVI)). We used adjusted log-binomial regression to estimate prevalence ratios (PR) and 95 % confidence intervals (CI) for associations between exposures (quartiles) and depression and anxiety. In mutually adjusted models (simultaneously modeling PM2.5, NO2, and EVI), the highest quartile of PM2.5 was associated with increased prevalence of depression (PR = 1.17, 95 % CI: 1.06-1.29), whereas the highest quartile of greenness was inversely associated with depression (PR = 0.89, 95 % CI: 0.80-0.99). Joint exposure to greenness mitigated the impact of PM2.5 on depression (PRPM only = 1.20, 95 % CI: 1.06-1.36; PRPM+green = 0.98, 95 % CI: 0.83-1.16) and anxiety (PRPM only = 1.10, 95 % CI: 1.00-1.22; PRPM+green = 0.95, 95 % CI: 0.83-1.09) overall and in subgroup analyses. Observed associations were stronger in urbanized areas and among nonwhite participants, and varied by neighborhood deprivation. NO2 exposure was not independently associated with depression or anxiety in this population. Relationships between PM2.5, greenness, and depression were strongest in the presence of characteristics that are highly correlated with lower socioeconomic status, underscoring the need to consider mental health as an environmental justice issue.

Impact of urban green spaces on air quality: A study of PM10 reduction across diverse climates

Urban areas face high particulate matter (PM10) levels, increasing the risk of respiratory and cardiovascular diseases. Green spaces can significantly reduce PM10 concentration, as shown at various scales, from boroughs to whole cities. However, long-term monitoring is needed to understand the specific mechanisms and cumulative impact of green spaces on air quality to changing pollution levels. We investigated the influence of neighbourhood green space percentage, climatic variables, and population density on PM10 deposition during the vegetation period across eight cities in contrasting climate zones over 20 years (2000-2020). We used a correlation matrix, generalized additive model, one-way ANOVA, and Tukey HSD test to analyze the impact of these factors on PM10 deposition rates, assess the role of green space percentage in reducing it, and identify significant differences in PM10 parameters at different proximities to emission sources. Cities with higher population density in warmer, drier climates had higher PM levels, since land surface temperature and wind pressure positively correlated with PM10 deposition, while relative humidity showed a negative correlation. The study found significantly higher PM10 concentrations in industrial areas (36.25 μg/m³) than in roadside areas (25.73 μg/m³) and parks (20.17 μg/m³) (p < 0.01). This highlights the need for targeted interventions in different zones. The study found a complex relationship between green space percentage and PM10 deposition rate onto plant surfaces. Our model suggests that at least 27% of green spaces as land cover can significantly reduce the particulate matter flux, although the minimum threshold can vary depending on the specific urban contexts. The study focused on the proportionate cover of green spaces; still, further investigation including quantitative aspects of urban surface forms, and traffic emissions can comprehend the climatic context and determine the optimal extent of green space required for strategic planning toward future urban sustainability initiatives.

The impact of green low-carbon development on public health: a quasi-natural experimental study of low-carbon pilot cities in China

Background

In recent years, climate change and environmental pollution have posed significant threats to public health. As environmental policies such as low-carbon city initiatives are progressively implemented, their role in enhancing public health has become a topic of growing interest. This study aimed to investigate the relationship between green low-carbon development and public health and to analyze the underlying mechanisms.

Methods

We utilized data from 271 prefecture-level cities in China spanning from 2007 to 2020, focusing on green low-carbon development, climate change, environmental pollution, and public health. Employing the quasi-natural experimental framework of China's low-carbon city pilot projects, we constructed a multi-site difference-in-differences (DID) model for empirical analysis. Various robustness checks, including parallel trend tests, placebo tests, sample selection bias checks, and adjustments to the temporal and spatial scope of the samples, were conducted to ensure the reliability of the results. Additionally, we explored the positive effects of green low-carbon development on public health through dual mediation pathways involving climate change mitigation and pollution reduction. Finally, we examined the heterogeneity of the results across different city tiers, economic growth rates, levels of technological investment, and green finance development.

Results

The findings indicate that green low-carbon development significantly enhances public health, a conclusion supported by robustness tests. Mechanism analysis reveals that the benefits of green low-carbon development on public health are realized through mitigating climate change and reducing environmental pollution. Further analysis reveals that the positive impact on public health is more pronounced in first-and second-tier cities, as well as in cities with faster economic growth, greater technological investment, and more developed green finance sectors.

Discussion

This study highlights the crucial role of urban green low-carbon development in improving environmental quality and public health. In addition to providing empirical evidence that supports the promotion of green low-carbon development in cities, the results point to policy recommendations for enhancing public health. Moreover, the findings contribute to the development of environmental policies and the implementation of the "Healthy China" strategy.

Exploring the pathways linking prenatal and early childhood greenness exposure to attention-deficit/hyperactivity disorder symptoms during childhood: An approach based on robust causal inference

BACKGROUND

Epidemiological studies suggest that exposure to greenness during childhood may protect children from developing attention-deficit hyperactivity disorder (ADHD).

OBJECTIVE

We analyzed the effect of both prenatal (pregnancy) and early childhood (4-5-year follow-up) residential greenness exposure and green space availability on ADHD symptoms during childhood (up to the age of 12 years) and further explored the potential mediating role of PM2.5 and physical activity in the association.

METHODS

The study population included participants from the INfancia y Medio Ambiente (INMA) prospective birth cohort (Gipuzkoa, Sabadell, and Valencia). Average Normalized Difference Vegetation Index (NDVI) in buffers of 100-, 300- and 500-m around the residential addresses was used as an indicator of greenness, while green space availability was determined based on the presence of a major green space within 150-m from the residence. Childhood ADHD symptoms were assessed at the 6-8- and 10-12-year follow-ups using Conners Parents Rating Scale-Revised: Short Form.

RESULTS

Although no association was found for the prenatal exposure period, increased early childhood NDVI inversely associated with the OR of clinically significant ADHD symptoms during the 6-8-year follow-up at the 100-m (OR 0.03, 95% CI: 0.003 to 0.44), 300-m (OR 0.04, 95% CI: 0.003 to 0.42) and 500-m (OR 0.08, 95% CI: 0.01 to 0.76) buffers, but exclusively in the context of direct effects. Additionally, the 10-12-year follow-up analysis found moderate to weak evidence of potential total and direct effects of NDVI at both 100- and 300-m buffers on inattention scores, as well as for NDVI at the 300-m buffer on ADHD index scores. The analysis did not reveal evidence of mediation through PM2.5 or physical activity.

CONCLUSIONS

The evidence suggests that early childhood greenness exposure may reduce the risk of developing ADHD symptoms later in childhood, and that this association is not mediated through PM2.5 and physical activity.

Variation in insect herbivory across an urbanization gradient: The role of abiotic factors and leaf secondary metabolites

Urbanization impacts plant-herbivore interactions, which are crucial for ecosystem functions such as carbon sequestration and nutrient cycling. While some studies have reported reductions in insect herbivory in urban areas (relative to rural or natural forests), this trend is not consistent and the underlying causes for such variation remain unclear. We conducted a continental-scale study on insect herbivory along urbanization gradients for three European tree species: Quercus robur, Tilia cordata, and Fraxinus excelsior, and further investigated their biotic and abiotic correlates to get at mechanisms. To this end, we quantified insect leaf herbivory and foliar secondary metabolites (phenolics, terpenoids, alkaloids) for 176 trees across eight European cities. Additionally, we collected data on microclimate (air temperature) and soil characteristics (pH, carbon, nutrients) to test for abiotic correlates of urbanization effects directly or indirectly (through changes in plant secondary chemistry) linked to herbivory. Our results showed that urbanization was negatively associated with herbivory for Q. robur and F. excelsior, but not for T. cordata. In addition, urbanization was positively associated with secondary metabolite concentrations, but only for Q. robur. Urbanization was positively associated with air temperature for Q. robur and F. excelsior, and negatively with soil nutrients (magnesium) in the case of F. excelsior, but these abiotic variables were not associated with herbivory. Contrary to expectations, we found no evidence for indirect effects of abiotic factors via plant defences on herbivory for either Q. robur or F. excelsior. Additional biotic or abiotic drivers must therefore be accounted for to explain observed urbanization gradients in herbivory and their interspecific variation.

Association of residential air pollution and green space with all-cause and cause-specific mortality in individuals with diabetes: an 11-year prospective cohort study

BACKGROUND

To assess the long-term impact of residential air pollution and green space exposure on cause-specific mortality in individuals with type 2 diabetes mellitus (T2DM).

METHODS

This study includes 174,063 participants newly diagnosed with T2DM from a prospective cohort in Shanghai, China, enrolled between 2011 and 2013. Residential annual levels of air pollutants, including fine (PM2.5) and coarse (PM2.5-10) particulate matter, nitrogen dioxide (NO2), along with the normalized difference vegetation index (NDVI), were derived from satellite-based exposure models.

FINDINGS

During a median follow-up of 7.9 years (equivalent to 1,333,343 person-years), this study recorded 22,205 deaths. Higher exposure to PM2.5 was significantly associated with increased risks for all mortality outcomes, whilst PM2.5-10 showed no significant impacts. The strongest associations of PM2.5 were observed for diabetes with peripheral vascular diseases [hazard ratio (HR): 2.70; per 10 μg/m3 increase] and gastrointestinal cancer (2.44). Effects of NO2 became significant at concentrations exceeding approximately 45 μg/m³, with the highest associations for lung cancer (1.20) and gastrointestinal cancer (1.19). Conversely, each interquartile range increase in NDVI (0.10) was linked to reduced mortality risks across different causes, with HRs ranging from 0.76 to 1.00. The association between greenness and mortality was partly and significantly mediated by reduced PM2.5 (23.80%) and NO2 (26.60%). There was a significant and negative interaction between NO2 and greenness, but no interaction was found between PM2.5 and greenness.

INTERPRETATION

Our findings highlight the vulnerability of individuals with T2DM to the adverse health effects of air pollution and emphasise the potential protective effects of greenness infrastructure.

FUNDING

The 6th Three-year Action Program of Shanghai Municipality for Strengthening the Construction of Public Health System (GWVI-11.1-22), the National Key Research and Development Program (2022YFC3702701), and the National Natural Science Foundation of China (82030103, 82373532).

Modifying effects of green space on the relationships between air pollution and ischemic cerebrovascular event recurrence in Tianjin, China

This study aimed to explore how air pollution and green space influence ICE recurrence and whether they might interact with each other. A case-cross design was used in this study, which was carried out in Tianjin, China. A total of 8306 patients with recurrent ICE were collected from 2019 to 2020. The maximum effects of PM2.5, PM10, SO2, NO2, CO were 1.012 (95%CI: 1.004, 1.019), 1.010 (95%CI: 1.004, 1.016), 1.035 (95%CI: 0.982, 1.091), 1.067 (95%CI: 1.043, 1.091) and 1.012 (95%CI: 1.004, 1.021)  , respectively, and the risk was higher in males and in the 50-60 age group. In the stratification of greening, it was found that air pollution except O3 had the highest risk of ICE recurrence for those with lower green space. Our study found that air pollution (except O3) can increase the risk of ICE recurrence, and this risk can be reduced by increasing green space.

Factors influencing the coupled and coordinated development of cities in the Yangtze River Economic Belt: A focus on carbon reduction, pollution control, greening, and growth

Atmospheric pollutants PM2.5 and CO2 share similar sources and impact mechanisms. Green innovations and urban greening significantly reduce these pollutants while promoting economic growth. However, the synergies and trade-offs between carbon reduction, pollution control, green expansion, and economic growth remain understudied. This paper examines 110 cities in the Yangtze River Economic Belt (YREB), China's premier green development site, as a unified system. Using fractional-order synthesis analysis, this paper constructs an assessment indicator system and measures synergy with a coupled coordination degree model. The driving factors are explored using a system-generalized method of moments estimation. The findings indicate that most cities in the YREB are at an intermediate coordination stage. The coupling of greening with carbon reduction, pollution control, and growth has a low degree, highlighting an urgent need to strengthen greening efforts. Key drivers include the digital economy, advanced industrial structure, innovative talent aggregation, infrastructure construction, financial investment, and marketization. The digital economy significantly influences all regions of the Yangtze River. Notable heterogeneity exists in the impact of other drivers across different regions. These results offer valuable policy insights for managing carbon emissions and pollutants, contributing to sustainable urban development.

Effect modification of air pollution on the association between heat and mortality in five European countries

BACKGROUND

Evidence suggests that air pollution modifies the association between heat and mortality. However, most studies have been conducted in cities without rural data. This time-series study examined potential effect modification of particulate matter (PM) and ozone (O3) on heat-related mortality using small-area data from five European countries, and explored the influence of area characteristics.

METHODS

We obtained daily non-accidental death counts from both urban and rural areas in Norway, England and Wales, Germany, Italy, and the Attica region of Greece during the warm season (2000-2018). Daily mean temperatures and air pollutant concentrations were estimated by spatial-temporal models. Heat effect modification by air pollution was assessed in each small area by over-dispersed Poisson regression models with a tensor smoother between temperature and air pollution. We extracted temperature-mortality relationships at the 5th (low), 50th (medium), and 95th (high) percentiles of pollutant distributions. At each air pollution level, we estimated heat-related mortality for a temperature increase from the 75th to the 99th percentile. We applied random-effects meta-analysis to derive the country-specific and overall associations, and mixed-effects meta-regression to examine the influence of urban-rural and coastal typologies and greenness on the heat effect modification by air pollution.

RESULTS

Heat-related mortality risks increased with higher PM levels, rising by 6.4% (95% CI: -2.0%-15.7%), 10.7% (2.6%-19.5%), and 14.1% (4.4%-24.6%) at low, medium, and high PM levels, respectively. This effect modification was consistent in urban and rural regions but more pronounced in non-coastal regions. In addition, heat-mortality associations were slightly stronger at high O3 levels, particularly in regions with low greenness.

CONCLUSION

Our analyses of both urban and rural data indicate that air pollution may intensify heat-related mortality, particularly in non-coastal and less green regions. The synergistic effect of heat and air pollution implies a potential pathway of reducing heat-related health impacts by improving air quality.

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.

Urban green spaces, self-rated air pollution and health: A sensitivity analysis of green space characteristics and proximity in four European cities

Exploring the influence of green space characteristics and proximity on health via air pollution mitigation, our study analysed data from 1,365 participants across Porto, Nantes, Sofia, and Høje-Taastrup. Utilizing OpenStreetMap and the AID-PRIGSHARE tool, we generated nine green space indicators around residential addresses at 15 distances, ranging from 100m to 1500m. We performed a mediation analysis for these 135 green space variables and revealed significant associations between self-rated air pollution and self-rated health for specific green space characteristics. In our study, indirect positive effects on health via air pollution were mainly associated with green corridors in intermediate Euclidean distances (800-1,000m) and the amount of accessible green spaces in larger network distances (1,400-1,500m). Our results suggest that the amount of connected green spaces measured in intermediate surroundings seems to be a prime green space characteristic that could drive the air pollution mitigation pathway to health.

Personal exposure to ultrafine particles in multiple microenvironments among adolescents

BACKGROUND

Experimental studies suggest ultrafine particles (UFPs), the smallest size fraction of particulate matter, may be more toxic than larger particles, however personal sampling studies in children are lacking.

OBJECTIVE

The objective of this analysis was to examine individual, housing, and neighborhood characteristics associated with personal UFP concentrations as well as the differences in exposures that occur within varying microenvironments.

METHODS

We measured weekly personal UFP concentrations and GPS coordinates in 117 adolescents ages 13-17 to describe exposures across multiple microenvironments. Individual, home, and neighborhood characteristics were collected by caregiver completed questionnaires.

RESULTS

Participants regularly exposed to secondhand tobacco smoke had significantly higher indoor concentrations of UFPs compared to participants who were not. We observed that the 'home' microenvironment dominated the relative contribution of overall UFP concentrations and sampling time, however, relative proportion of integrated UFP exposure were higher in 'other' environments.

IMPACT STATEMENT

In this study, we employed a novel panel study design, involving real-time measurement of UFP exposure within the multiple microenvironments of adolescents. We found a combination of personal sampling and detailed activity patterns should be used in future studies to accurately describe exposure-behavior relationships.

Confounding associations between green space and outdoor artificial light at night: Systematic investigations and implications for urban health

Excessive urbanization leads to considerable nature deficiency and abundant artificial infrastructure in urban areas, which triggered intensive discussions on people's exposure to green space and outdoor artificial light at night (ALAN). Recent academic progress highlights that people's exposure to green space and outdoor ALAN may be confounders of each other but lacks systematic investigations. This study investigates the associations between people's exposure to green space and outdoor ALAN by adopting the three most used research paradigms: population-level residence-based, individual-level residence-based, and individual-level mobility-oriented paradigms. We employed the green space and outdoor ALAN data of 291 Tertiary Planning Units in Hong Kong for population-level analysis. We also used data from 940 participants in six representative communities for individual-level analyses. Hong Kong green space and outdoor ALAN were derived from high-resolution remote sensing data. The total exposures were derived using the spatiotemporally weighted approaches. Our results confirm that the negative associations between people's exposure to green space and outdoor ALAN are universal across different research paradigms, spatially non-stationary, and consistent among different socio-demographic groups. We also observed that mobility-oriented measures may lead to stronger negative associations than residence-based measures by mitigating the contextual errors of residence-based measures. Our results highlight the potential confounding associations between people's exposure to green space and outdoor ALAN, and we strongly recommend relevant studies to consider both of them in modeling people's health outcomes, especially for those health outcomes impacted by the co-exposure to them.

Spatial analysis of the impact of urban built environment on cardiovascular diseases: a case study in Xixiangtang, China

BACKGROUND

The built environment, as a critical factor influencing residents' cardiovascular health, has a significant potential impact on the incidence of cardiovascular diseases (CVDs).

METHODS

Taking Xixiangtang District in Nanning City, Guangxi Zhuang Autonomous Region of China as a case study, we utilized the geographic location information of CVD patients, detailed road network data, and urban points of interest (POI) data. Kernel density estimation (KDE) and spatial autocorrelation analysis were specifically employed to identify the spatial distribution patterns, spatial clustering, and spatial correlations of built environment elements and diseases. The GeoDetector method (GDM) was used to assess the impact of environmental factors on diseases, and geographically weighted regression (GWR) analysis was adopted to reveal the spatial heterogeneity effect of environmental factors on CVD risk.

RESULTS

The results indicate that the built environment elements and CVDs samples exhibit significant clustering characteristics in their spatial distribution, with a positive correlation between the distribution density of environmental elements and the incidence of CVDs (Moran's I > 0, p < 0.01). Further factor detection revealed that the distribution of healthcare facilities had the most significant impact on CVDs (q = 0.532, p < 0.01), followed by shopping and consumption (q = 0.493, p < 0.01), dining (q = 0.433, p < 0.01), and transportation facilities (q = 0.423, p < 0.01), while the impact of parks and squares (q = 0.174, p < 0.01) and road networks (q = 0.159, p < 0.01) was relatively smaller. Additionally, the interaction between different built environment elements exhibited a bi-factor enhancement effect on CVDs. In the local analysis, the spatial heterogeneity of different built environment elements on CVDs further revealed the regional differences and complexities.

CONCLUSIONS

The spatial distribution of built environment elements is significantly correlated with CVDs to varying degrees and impacts differently across regions, underscoring the importance of the built environment on cardiovascular health. When planning and improving urban environments, elements and areas that have a more significant impact on CVDs should be given priority consideration.

Relationship between urban green space and mental health in older adults: mediating role of relative deprivation, physical activity, and social trust

Introduction

The importance of improving older adults' mental health is increasing worldwide with the rapid development of the aging process. Green space is an important part of the urban built environment, demonstrates a deep connection with the mental health of older adults, and its internal mechanisms have been widely studied. This study analyzed the influence of urban green spaces on the mental health of older adults via three factors: relative deprivation, physical activity, and social trust.

Methods

Based on the 2018 China Labor Dynamics Survey, a multi-level structural equation model was used to explore the mediating roles of relative deprivation, physical activity, social trust in urban green spaces, and the mental health of older adults.

Results

Urban green space was positively correlated with the mental health of older adults. Relative deprivation and physical activities played a mediating role between urban green space and the mental health of older adults.

Discussion

An increase in urban green spaces can help increase the number of older adults obtaining green space resources, and help them maintain good mental health. Secondly, older adults with a relatively homogeneous environment have more equal opportunities to obtain urban green space resources, which helps to reduce the comparison of older adults in access to green space resources and reduce the adverse impact of relative deprivation on their mental health. Additionally, increasing urban green spaces can encourage older adults to engage in physical activities and improve their mental health. Finally, we suggest improving the accessibility, fairness, and quality of green spaces, paying attention to the psychological needs of older adults, encouraging older adults to engage in physical activities in green spaces, and taking various measures to enhance the positive role of green space on the mental health of older adults.

Utilizing spiders for biomonitoring air pollution from road traffic: a novel approach and preliminary findings

Polycyclic aromatic hydrocarbons (PAHs) are air pollutants generated mainly by fuel combustion, industry, and other anthropogenic sources. The level of these pollutants can be assessed by employing biomonitors, a cost-effective and less contaminating alternative than conventional methods. In the present study, we aimed to investigate whether spiders inhabiting areas around a major city like Córdoba, Argentina, adsorb and retain PAHs in their exoskeletons. Additionally, we aimed to determine if spiders' life traits influence their capacity to accumulate PAHs and explore potential relationships between PAH levels and the types of roads where they were collected. Specimens of a funnel-shaped web spider (Aglaoctenus lagotis) and an orb-weaver (Metepeira spp.) were collected from roadsides. Roads were classified into four categories based on their traffic intensity. Using high-performance liquid chromatography (HPLC), we identified 15 different PAHs. Both species exhibited varying concentrations of PAHs, although Metepeira spp. showed 15-18 times higher PAH levels compared to A. lagotis. Moreover, A. lagotis individuals living alongside highways accumulated up to six times more PAHs compared to those along other road types. These findings suggest that spiders' life traits may influence pollutant concentrations. Our study demonstrates that spiders near roads are exposed to and accumulate PAHs on their exoskeletons, likely sourced from petrogenic vehicular emissions, highlighting their value as biomonitors and emphasizing the need for mitigation measures to address air pollutants emitted from mobile sources.

Evaluating the impact of evolving green and grey urban infrastructure on local particulate pollution around city square parks

The relationship between green and grey urban infrastructure, local meteorological conditions, and traffic-related air pollution is complex and dynamic. This case study examined the effect of evolving morphologies around a city square park in Dublin and explores the twin impacts of local urban development (grey) and maturing parks (green) on particulate matter (PM) pollution. A fixed air quality monitoring campaign and computational fluid dynamic modelling (ENVI-met) were used to assess current (baseline) and future scenarios. The baseline results presented the distribution of PM in the study area, with bimodal (PM2.5) and unimodal (PM10) diurnal profiles. The optimal vegetation height for air quality within the park also differed by wind direction with 21 m vegetation optimal for parallel winds (10.45% reduction) and 7 m vegetation optimal for perpendicular winds (30.36% reduction). Increased building heights led to higher PM2.5 concentrations on both footpaths ranging from 25.3 to 37.0% under perpendicular winds, whilst increasing the height of leeward buildings increased PM2.5 concentrations by up to 30.9% under parallel winds. The findings from this study provide evidence of the importance of more in-depth analysis of green and grey urban infrastructure in the urban planning decision-making process to avoid deteriorating air quality conditions around city square parks.

Public health impacts of air pollution from the spatiotemporal heterogeneity perspective: 31 provinces and municipalities in China from 2013 to 2020

Air pollution has long been a significant environmental health issue. Previous studies have employed diverse methodologies to investigate the impacts of air pollution on public health, yet few have thoroughly examined its spatiotemporal heterogeneity. Based on this, this study investigated the spatiotemporal heterogeneity of the impacts of air pollution on public health in 31 provinces in China from 2013 to 2020 based on the theoretical framework of multifactorial health decision-making and combined with the spatial durbin model and the geographically and temporally weighted regression model. The findings indicate that: (1) Air pollution and public health as measured by the incidence of respiratory diseases (IRD) in China exhibit significant spatial positive correlation and local spatial aggregation. (2) Air pollution demonstrates noteworthy spatial spillover effects. After controlling for economic development and living environment factors, including disposable income, population density, and urbanization rate, the direct and indirect spatial impacts of air pollution on IRD are measured at 3.552 and 2.848, correspondingly. (3) China's IRD is primarily influenced by various factors such as air pollution, economic development, living conditions, and healthcare, and the degree of its influence demonstrates an uneven spatiotemporal distribution trend. The findings of this study hold considerable practical significance for mitigating air pollution and safeguarding public health.

Towards a Green Equal City: Measuring and matching the supply-demand of green exposure in urban center

Exposure to green environments is crucial for human health. However, urbanization has reduced the contact of urban residents with natural environments, causing a mismatch between the supply and demand for green exposure. Research in this field is hindered by the lack of long-term, reliable data sources and methodologies, leading to insufficient consideration of temporal variations in green exposure. This study presented a comprehensive methodology for assessing green exposure at a fine scale utilizing satellite images for urban tree canopy identification. We conducted a case study in the core area of Beijing from 2010 to 2020 and examined the effects of urban renewal and alleviation efforts. The results revealed a slight decrease in green exposure for the elderly over the decade, with minimal changes in equity. In contrast, green exposure for children has increased, with increasing inequality. Moreover, urban renewal has improved green exposure for nearly half of the low-supply blocks. However, a significant mismatch was observed between supply and demand for blocks with increased demand but limited supply. This study enhances the assessment of green exposure and provides guidance for planning and constructing a "Green Equal City".

Seasonal variation of arsenic in PM10 and PMx in an urban park: The influence of vegetation-related biomethylation on the distribution of its organic species and air quality

Arsenic (As) levels in particulate matter (PM) are routinely monitored in cities of developed countries. Despite advances in the knowledge of its inorganic species in PM in urban areas, organic species are often overlooked with no information on their behaviour in urban parks - areas with increased potential for As biomethylation. Therefore, the aim of this study was to characterize As distribution, bioaccessibility, seasonal variation and speciation (AsIII, AsV, MMA, DMA and TMAO) in PMx-PM10 of an urban park. Two sites with different distance from the road were selected for winter and summer sampling. From the PM samples, we gravimetrically determined PM10 concentrations in the air and via ICP-MS the total As content there. To assess the portion of bioaccessible As, water extractable As content was analysed. Simultaneously, the As species in PM10 water extracts were analysed via coupling of HPLC with ICP-MS method. There was no seasonal difference in PM10 concentration in the park, probably due to the increased summer PM load related to recreational activities in the park and park design. Spatial distribution of total As in PM10 and As fractional distribution in PMx suggested that As mostly didn't originate from traffic although highest As content was observed in the fine fraction (PM2.5) related to combustion processes. However, significant winter increase of As (determined by AsIII and AsV) despite the unchanged concentration of PM10 indicated a decisive influence of household heating-related combustion and possibly influence of reduced vegetation density. As present in the PM10 was mostly in bioaccessible form. Seasonal influence of As biomethylation was clearly demonstrated on the TMAO specie during the summer campaign. Except the significant summer TMAO increase, the results also indicated the biomethylation influence on DMA. Therefore, an increased risk of exposure to organic As species in urban parks can be expected during summer.

Contemporary Concise Review 2023: Environmental and occupational lung diseases

Air pollutants have various effects on human health in environmental and occupational settings. Air pollutants can be a risk factor for incidence, exacerbation/aggravation and death due to various lung diseases, including asthma, chronic obstructive pulmonary disease (COPD), hypersensitivity pneumonitis or pneumonia (HP), pulmonary fibrosis such as pneumoconiosis and malignant respiratory diseases such as lung cancer and malignant pleural mesothelioma. Environmental and occupational respiratory diseases are crucial clinical and social issues worldwide, although the burden of respiratory disease due to environmental and occupational causes varies depending on country/region, demographic variables, geographical location, industrial structure and socioeconomic situation. The correct recognition of environmental and occupational lung diseases and taking appropriate measures are essential to their effective prevention.

Parsimonious Random-Forest-Based Land-Use Regression Model Using Particulate Matter Sensors in Berlin, Germany

Machine learning (ML) methods are widely used in particulate matter prediction modelling, especially through use of air quality sensor data. Despite their advantages, these methods' black-box nature obscures the understanding of how a prediction has been made. Major issues with these types of models include the data quality and computational intensity. In this study, we employed feature selection methods using recursive feature elimination and global sensitivity analysis for a random-forest (RF)-based land-use regression model developed for the city of Berlin, Germany. Land-use-based predictors, including local climate zones, leaf area index, daily traffic volume, population density, building types, building heights, and street types were used to create a baseline RF model. Five additional models, three using recursive feature elimination method and two using a Sobol-based global sensitivity analysis (GSA), were implemented, and their performance was compared against that of the baseline RF model. The predictors that had a large effect on the prediction as determined using both the methods are discussed. Through feature elimination, the number of predictors were reduced from 220 in the baseline model to eight in the parsimonious models without sacrificing model performance. The model metrics were compared, which showed that the parsimonious_GSA-based model performs better than does the baseline model and reduces the mean absolute error (MAE) from 8.69 µg/m3 to 3.6 µg/m3 and the root mean squared error (RMSE) from 9.86 µg/m3 to 4.23 µg/m3 when applying the trained model to reference station data. The better performance of the GSA_parsimonious model is made possible by the curtailment of the uncertainties propagated through the model via the reduction of multicollinear and redundant predictors. The parsimonious model validated against reference stations was able to predict the PM2.5 concentrations with an MAE of less than 5 µg/m3 for 10 out of 12 locations. The GSA_parsimonious performed best in all model metrics and improved the R2 from 3% in the baseline model to 17%. However, the predictions exhibited a degree of uncertainty, making it unreliable for regional scale modelling. The GSA_parsimonious model can nevertheless be adapted to local scales to highlight the land-use parameters that are indicative of PM2.5 concentrations in Berlin. Overall, population density, leaf area index, and traffic volume are the major predictors of PM2.5, while building type and local climate zones are the less significant predictors. Feature selection based on sensitivity analysis has a large impact on the model performance. Optimising models through sensitivity analysis can enhance the interpretability of the model dynamics and potentially reduce computational costs and time when modelling is performed for larger areas.

Greenness mitigate cause-specific mortality associated with air pollutants in ischemic and hemorrhagic stroke patients: An ecological health cohort study

BACKGROUND

Air pollution is one of the most serious environmental risks to mortality of stroke. However, there exists a noteworthy knowledge gap concerning the different stroke subtypes, causes of death, the susceptibility of stroke patient, and the role of greenness in this context.

METHODS

We analyzed data from an ecological health cohort, which included 334,261 patients aged ≥40 years with stroke (comprising 288,490 ischemic stroke and 45,771 hemorrhagic stroke) during the period 2013-2019. We used Cox proportional hazards models with time-varying exposure to estimate hazard ratios (HRs) and 95% confidence intervals (CIs) to assess the associations of annual average fine particulate matter (PM2.5), nitrogen dioxide (NO2), and ozone (O3) with both all-cause and cause-specific mortality. Additionally, we conducted analyses to examine the effect modification by greenness and identify potential susceptibility factors through subgroup analyses.

RESULT

In multivariable-adjusted models, long-term exposure to PM2.5 and NO2 was associated with increased risk of all-cause mortality (HR: 1.038, 95% CI: 1.029-1.047 for PM2.5; HR: 1.055, 95% CI: 1.026-1.085 for NO2, per 10 μg/m3, for ischemic stroke patients; similar for hemorrhagic stroke patients). Gradually increasing effect sizes were shown for CVD mortality and stroke mortality. The HRs of mortality were slightly weaker with high versus low vegetation exposure. Cumulative exposures increased the HRs of pollutant-related mortality, and greater greenness decreased this risk. Two subtypes of stroke patients exhibited diverse patterns of benefit.

CONCLUSION

Increasing residential greenness attenuates the increased risk of mortality with different patterns due to chronic air pollutants for ischemic and hemorrhagic stroke, offering valuable insights for precise tertiary stroke prevention strategies.

PM2.5, vegetation density, and childhood cancer: a case-control registry-based study from Texas 1995-2011

BACKGROUND

Air pollution is positively associated with some childhood cancers, whereas greenness is inversely associated with some adult cancers. The interplay between air pollution and greenness in childhood cancer etiology is unclear. We estimated the association between early-life air pollution and greenness exposure and childhood cancer in Texas (1995 to 2011).

METHODS

We included 6101 cancer cases and 109 762 controls (aged 0 to 16 years). We linked residential birth address to census tract annual average fine particulate matter <2.5 µg/m³ (PM2.5) and Normalized Difference Vegetation Index (NDVI). We estimated odds ratios (ORs) and 95% confidence intervals (CIs) between PM2.5/NDVI interquartile range increases and cancer. We assessed statistical interaction between PM2.5 and NDVI (likelihood ratio tests).

RESULTS

Increasing residential early-life PM2.5 exposure was associated with all childhood cancers (OR = 1.10, 95% CI = 1.06 to 1.15), lymphoid leukemias (OR = 1.15, 95% CI = 1.07 to 1.23), Hodgkin lymphomas (OR = 1.27, 95% CI = 1.02 to 1.58), non-Hodgkin lymphomas (OR = 1.24, 95% CI = 1.02 to 1.51), ependymoma (OR = 1.27, 95% CI = 1.01 to 1.60), and others. Increasing NDVI exposure was inversely associated with ependymoma (0- to 4-year-old OR = 0.75, 95% CI = 0.58 to 0.97) and medulloblastoma (OR = 0.75, 95% CI = 0.62 to 0.91) but positively associated with malignant melanoma (OR = 1.75, 95% CI = 1.23 to 2.47) and Langerhans cell histiocytosis (OR = 1.56, 95% CI = 1.07 to 2.28). There was evidence of statistical interaction between NDVI and PM2.5 (P < .04) for all cancers.

CONCLUSION

Increasing early-life exposure to PM2.5 increased the risk of childhood cancers. NDVI decreased the risk of 2 cancers yet increased the risk of others. These findings highlight the complexity between PM2.5 and NDVI in cancer etiology.

Advances in amelioration of air pollution using plants and associated microbes: An outlook on phytoremediation and other plant-based technologies

Globally, air pollution is an unfortunate aftermath of rapid industrialization and urbanization. Although the best strategy is to prevent air pollution, it is not always feasible. This makes it imperative to devise and implement techniques that can clean the air continuously. Plants and microbes have a natural potential to transform or degrade pollutants. Hence, strategies that use this potential of living biomass to remediate air pollution seem to be promising. The simplest future trend can be planting suitable plant-microbe species capable of removing air pollutants like SO2, CO2, CO, NOX and particulate matter (PM) along roadsides and inside the buildings. Established wastewater treatment strategies such as microbial fuel cells (MFC) and constructed wetlands (CW) can be suitably modified to ameliorate air pollution. Green architecture involving green walls and green roofs is facile and aesthetic, providing urban ecosystem services. Certain microbe-based bioreactors such as bioscrubbers and biofilters may be useful in small confined spaces. Several generative models have been developed to assist with planning and managing green spaces in urban locales. The physiological limitations of using living organisms can be circumvent by applying biotechnology and transgenics to improve their potential. This review provides a comprehensive update on not just the plants and associated microbes for the mitigation of air pollution, but also lists the technologies that are available and/or can be modified and used for air pollution control. The article also gives a detailed analysis of this topic in the form of strengths-weaknesses-opportunities-challenges (SWOC). The strategies mentioned in this review would help to attain corporate Environmental Social and Governance (ESG) and Sustainable Development Goals (SDGs), while reducing carbon footprint in the urban scenario. The review aims to emphasise that urbanization is possible while tackling air pollution using facile, green techniques involving plants and associated microbes.

Geospatial artificial intelligence for estimating daytime and nighttime nitrogen dioxide concentration variations in Taiwan: A spatial prediction model

Nitrogen dioxide (NO2) is a major air pollutant primarily emitted from traffic and industrial activities, posing health risks. However, current air pollution models often underestimate exposure risks by neglecting the bimodal pattern of NO2 levels throughout the day. This study aimed to address this gap by developing ensemble mixed spatial models (EMSM) using geo-artificial intelligence (Geo-AI) to examine the spatial and temporal variations of NO2 concentrations at a high resolution of 50m. These EMSMs integrated spatial modelling methods, including kriging, land use regression, machine learning, and ensemble learning. The models utilized 26 years of observed NO2 measurements, meteorological parameters, geospatial layers, and social and season-dependent variables as representative of emission sources. Separate models were developed for daytime and nighttime periods, which achieved high reliability with adjusted R2 values of 0.92 and 0.93, respectively. The study revealed that mean NO2 concentrations were significantly higher at nighttime (9.60 ppb) compared to daytime (5.61 ppb). Additionally, winter exhibited the highest NO2 levels regardless of time period. The developed EMSMs were utilized to generate maps illustrating NO2 levels pre and during COVID restrictions in Taiwan. These findings could aid epidemiological research on exposure risks and support policy-making and environmental planning initiatives.

Residential greenness and chronic obstructive pulmonary disease in a large cohort in southern China: Potential causal links, risk trajectories, and mediation pathways

INTRODUCTION

Residential greenness may influence COPD mortality, but the causal links, risk trajectories, and mediation pathways between them remain poorly understood.

OBJECTIVES

We aim to comprehensively identify the potential causal links, characterize the dynamic progression of hospitalization or posthospital risk, and quantify mediation effects between greenness and COPD.

METHODS

This study was conducted using a community-based cohort enrolling individuals aged ≥ 18 years in southern China from January 1, 2009 to December 31, 2015. Greenness was characterized by normalized difference vegetation index (NDVI) around participants' residential addresses. We applied doubly robust Cox proportional hazards model, multi-state model, and multiple mediation method, to investigate the potential causal links, risk trajectories among baseline, COPD hospitalization, first readmission due to COPD or COPD-related complications, and all-cause death, as well as the multiple mediation pathways (particulate matter [PM], temperature, body mass index [BMI] and physical activity) connecting greenness exposure to COPD mortality.

RESULTS

Our final analysis included 581,785 participants (52.52% female; average age: 48.36 [Standard Deviation (SD): 17.56]). Each interquartile range (IQR: 0.06) increase in NDVI was associated with a reduced COPD mortality risk, yielding a hazard ratio (HR) of 0.88 (95 % CI: 0.81, 0.96). Furthermore, we observed per IQR (0.04) increase in NDVI was inversely associated with the risk of multiple transitions (baseline - COPD hospitalization, baseline - death, and readmission - death risks), especially a declined risk of all-cause death after readmission (HR = 0.66 [95 %CI: 0.44, 0.99]). Within the observed association between greenness and COPD mortality, three mediators were identified, namely PM, temperature, and BMI (HR for the total indirect effect: 0.773 [95 % CI: 0.703, 0.851]), with PM showing the highest mediating effect.

CONCLUSIONS

Our findings revealed greenness may be a beneficial factor for COPD morbidity, prognosis, and mortality. This protective effect is primarily attributed to the reduction in PM concentration.

Long-term exposure to PM2.5 and mortality in a national cohort in South Korea: effect modification by community deprivation, medical infrastructure, and greenness

BACKGROUND

Long-term exposure to PM2.5 has been linked to increased mortality risk. However, limited studies have examined the potential modifying effect of community-level characteristics on this association, particularly in Asian contexts. This study aimed to estimate the effects of long-term exposure to PM2.5 on mortality in South Korea and to examine whether community-level deprivation, medical infrastructure, and greenness modify these associations.

METHODS

We conducted a nationwide cohort study using the National Health Insurance Service-National Sample Cohort. A total of 394,701 participants aged 30 years or older in 2006 were followed until 2019. Based on modelled PM2.5 concentrations, 1 to 3-year and 5-year moving averages of PM2.5 concentrations were assigned to each participant at the district level. Time-varying Cox proportional-hazards models were used to estimate the association between PM2.5 and non-accidental, circulatory, and respiratory mortality. We further conducted stratified analysis by community-level deprivation index, medical index, and normalized difference vegetation index to represent greenness.

RESULTS

PM2.5 exposure, based on 5-year moving averages, was positively associated with non-accidental (Hazard ratio, HR: 1.10, 95% Confidence Interval, CI: 1.01, 1.20, per 10 µg/m3 increase) and circulatory mortality (HR: 1.22, 95% CI: 1.01, 1.47). The 1-year moving average of PM2.5 was associated with respiratory mortality (HR: 1.33, 95% CI: 1.05, 1.67). We observed higher associations between PM2.5 and mortality in communities with higher deprivation and limited medical infrastructure. Communities with higher greenness showed lower risk for circulatory mortality but higher risk for respiratory mortality in association with PM2.5.

CONCLUSIONS

Our study found mortality effects of long-term PM2.5 exposure and underlined the role of community-level factors in modifying these association. These findings highlight the importance of considering socio-environmental contexts in the design of air quality policies to reduce health disparities and enhance overall public health outcomes.

Impact of green space and built environment on metabolic syndrome: A systematic review with meta-analysis

Metabolic Syndrome presents a significant public health challenge associated with an increased risk of noncommunicable diseases such as cardiovascular conditions. Evidence shows that green spaces and the built environment may influence metabolic syndrome. We conducted a systematic review and meta-analysis of observational studies published through August 30, 2023, examining the association of green space and built environment with metabolic syndrome. A quality assessment of the included studies was conducted using the Office of Health Assessment and Translation (OHAT) tool. The Grading of Recommendations, Assessment, Development, and Evaluations (GRADE) assessment was used to evaluate the overall quality of evidence. Our search retrieved 18 studies that met the inclusion criteria and were included in our review. Most were from China (n = 5) and the USA (n = 5), and most used a cross-sectional study design (n = 8). Nine studies (50 %) reported only green space exposures, seven (39 %) reported only built environment exposures, and two (11 %) reported both built environment and green space exposures. Studies reported diverse definitions of green space and the built environment, such as availability, accessibility, and quality, particularly around participants' homes. The outcomes focused on metabolic syndrome; however, studies applied different definitions of metabolic syndrome. Meta-analysis results showed that an increase in normalized difference vegetation index (NDVI) within a 500-m buffer was associated with a lower risk of metabolic syndrome (odds ratio [OR] = 0.90, 95%CI = 0.87-0.93, I2 = 22.3 %, n = 4). A substantial number of studies detected bias for exposure classification and residual confounding. Overall, the extant literature shows a 'limited' strength of evidence for green space protecting against metabolic syndrome and an 'inadequate' strength of evidence for the built environment associated with metabolic syndrome. Studies with more robust study designs, better controlled confounding factors, and stronger exposure measures are needed to understand better what types of green spaces and built environment features influence metabolic syndrome.

Associations between residential greenness and obesity phenotypes among adults in Southwest China

BACKGROUND

Although exposure to greenness has generally benefited human metabolic health, the association between greenness exposure and metabolic obesity remains poorly studied. We aimed to investigate the associations between residential greenness and obesity phenotypes and the mediation effects of air pollutants and physical activity (PA) level on the associations.

METHODS

We used the baseline of the China Multi-Ethnic Cohort (CMEC) study, which enrolled 87,613 adults. Obesity phenotypes were defined based on obesity and metabolic status, including metabolically unhealthy obesity (MUO), non-obesity (MUNO), metabolically healthy obesity (MHO), and non-obesity (MHNO). Greenness exposure was measured as the 3-year mean values of the normalized difference vegetation index (NDVI) and enhanced vegetation index (EVI) within the 500-m buffer zones around the participants' residence. Multivariable logistic regression was used to estimate the associations between greenness and obesity phenotypes. Stratified analyses by age, sex, educational level, and urbanicity were performed to identify how the effect varies across different subgroups. Causal mediation analysis was used to examine the mediation effects of air pollutants and PA level.

RESULTS

Compared with MHNO, each interquartile range (IQR) increase in greenness exposure was associated with reduced risks of MHO (ORNDVI [95% CI] = 0.87 [0.81, 0.93]; OREVI = 0.91 [0.86, 0.97]), MUO (ORNDVI = 0.83 [0.78, 0.88]; OREVI = 0.86 [0.81, 0.91]), and MUNO (ORNDVI = 0.88 [0.84, 0.91]; OREVI = 0.89 [0.86, 0.92]). For each IQR increase in both NDVI and EVI, the risks of MHO, MUO, and MUNO were reduced more in men, participants over 60 years, those with a higher level of education, and those living in urban areas, compared to their counterparts. Concentrations of particulate matter (PM) and PA level partially mediated the associations between greenness exposure and obesity phenotypes.

CONCLUSIONS

Exposure to residential greenness was associated with decreased risks of MHO, MUO, and MUNO, which was mediated by concentrations of PM and PA level, and modified by sex, age, educational level, and urbanicity.

Joint effects of green space and air pollutant exposure on preterm birth: evidence from a nationwide study in China

An association between green space exposure and preterm birth has been reported. However, evidence on the joint effects of air pollutant and green space exposure on preterm birth from nationwide research is limited in China. Based on a nationwide cohort, this study aims to explore the effect of green space exposure on preterm birth and analyze the joint effects of green space and air pollutant. Logistic regression models were developed to analyze the effects of green space exposure, and interaction effects were evaluated by adding interaction terms between green space and air pollutants. From 2013 to 2019, this study included 2,294,188 records of newborn births, of which 82,921 were preterm births. The results show that for buffer zones with 250 m, 500 m, 1000 m, and 1500 m, every 0.1 unit increase in NDVI exposure was associated with a decrease in the risk of preterm birth by 5.5% (95% CI: 4.6-6.4%), 5.8% (95% CI: 4.9-6.6%), 6.1% (95% CI: 5.3-7.0%), and 5.6% (95% CI: 4.7-6.5%), respectively. Under high-level exposure to air pollutants, high-level NDVI exposure was more strongly negatively correlated with preterm birth than low-level NDVI exposure. High-level green space exposure might mitigate the adverse effect of air pollutants on preterm birth by promoting physical activity, reducing stress, and adsorbing pollutants. Further investigation is needed to explore how green space and air pollution interact and affect preterm birth, in order to improve risk management and provide a reference for newborn health.

Different greenness exposure in Europe and respiratory outcomes in youths. A systematic review and meta-analysis

The existing evidence on the association between greenness and respiratory outcomes remains inconclusive. We aimed at systematically summarizing existing literature on greenness exposure and respiratory outcomes in European children and adolescents, with a preliminary attempt to qualify the distribution of dominant tree species across different geographical areas and bioclimatic regions. Overall, 4049 studies were firstly identified by searching PubMed/MEDLINE, EMBASE, Scopus, Web of Science, GreenFile and CAB direct, up to 29 August 2023. Eighteen primary studies were included in the systematic review and six were meta-analyzed. No overall significant association was observed between the Normalized Difference Vegetation Index, assessed within 500-m buffers (i.e. NDVI-500), and the odds of asthma for 0.3-increase in the exposure (OR: 0.97, 95% CI from 0.53 to 1.78). Similarly, an overall exposure to the NDVI-300 highest tertile, as compared to the lowest tertile, was not significantly associated with asthma (OR: 0.65, 95% CI from 0.22 to 1.91): heterogeneity among studies was significant (p = 0.021). We delineated some key elements that might have mostly contributed to the lack of scientific consensus on this topic, starting from the urgent need of harmonized approaches for the operational definition of greenness. Additionally, the complex interplay between greenness and respiratory health may vary across different geographical regions and climatic conditions. At last, the inconsistent findings may reflect the heterogeneity and complexity of this relationship, rather than a lack of scientific consensus itself. Future research should compare geographical areas with similar bioclimatic parameters and dominant or potentially present vegetation species, in order to achieve a higher inter-study comparability.

Temporal variation of the PM2.5/PM10 ratio and its association with meteorological factors in a South American megacity: Metropolitan Area of Lima-Callao, Peru

The Metropolitan Area of Lima-Callao (MALC) is a South American megacity that has suffered a serious deterioration in air quality due to high levels of particulate matter (PM2.5 and PM10). Studies on the behavior of the PM2.5/PM10 ratio and its temporal variability in relation to meteorological parameters are still very limited. The objective of this study was to analyze the temporal trends of the PM2.5/PM10 ratio, its temporal variability, and its association with meteorological variables over a period of 5 years (2015-2019). For this, the Theil-Sen estimator, bivariate polar plots, and correlation analysis were used. The regions of highest mean concentrations of PM2.5 and PM10 were identified at eastern Lima (ATE station-41.2 µg/m3) and southern Lima (VMT station-126.7 µg/m3), respectively. The lowest concentrations were recorded in downtown Lima (CDM station-16.8 µg/m3 and 34.0 µg/m3, respectively). The highest average PM2.5/PM10 ratio was found at the CDM station (0.55) and the lowest at the VMT station (0.27), indicating a predominance of emissions from the vehicular fleet within central Lima and a greater emission of coarse particles by resuspension in southern Lima. The temporal progression of the ratio of PM2.5/PM10 showed positive and highly significant trends in northern and central Lima with values of 0.03 and 0.1 units of PM2.5/PM10 per year, respectively. In the southern region of Lima, the trend was also significant, showcasing a value of 0.02 units of PM2.5/PM10 per year. At the hourly and monthly level, the PM2.5/PM10 ratio presented a negative and significant correlation with wind speed and air temperature, and a positive and significant correlation with relative humidity. These findings offer insights into identifying the sources of PM pollution and are useful for implementing regulations to reduce air emissions considering both anthropogenic sources and meteorological dispersion patterns.

Associations of residential greenness with bone mineral density and osteoporosis: the modifying effect of genetic susceptibility

OBJECTIVES

To investigate the associations of residential greenness with bone mineral density and incident osteoporosis, and further evaluate the potential modifying effect of genetic susceptibility.

METHODS

We used the Normalised Difference Vegetation Index (NDVI) at various buffer distances, including 300 m (NDVI300m), 500 m (NDVI500m), 1000 m (NDVI1000m) and 1500 m (NDVI1500m), to serve as indicators of greenness. We fitted linear regression, logistic regression and Cox proportional hazard models to assess the associations of residential greenness with estimated bone mineral density (eBMD), prevalent osteoporosis and incident osteoporosis, respectively. With the Polygenic Risk Score (PRS) for osteoporosis, we further assessed the joint effects of genetic risk and greenness on the risk of osteoporosis. We conducted causal mediation analyses to explore potential mediators.

RESULTS

Each IQR increase in NDVI300m was associated with 0.0007 (95% CI 0.0002 to 0.0013) increase in eBMD, 6% lower risk of prevalent osteoporosis (OR 0.94; 95% CI 0.92 to 0.97) and 5% lower risk of incident osteoporosis (HR 0.95; 95% CI 0.93 to 0.98). The joint effects of greenness and PRS on the risk of osteoporosis displayed a clear dose-response pattern. Compared with individuals exposed to low NDVI levels and high genetic risk, those exposed to high NDVI levels and low genetic risk had a 56% (95% CI 51% to 61%) lower risk of osteoporosis. The primary mediators in the association between greenness and incident osteoporosis were identified as PM2.5 and NO2.

CONCLUSIONS

Residential greenness was associated with higher bone mineral density and decreased risk of incident osteoporosis.

A comprehensive review of urban vegetation as a Nature-based Solution for sustainable management of particulate matter in ambient air

Air pollution is one of the most pressing environmental threats worldwide, resulting in several health issues such as cardiovascular and respiratory disorders, as well as premature mortality. The harmful effects of air pollution are particularly concerning in urban areas, where mismanaged anthropogenic activities, such as growth in the global population, increase in the number of vehicles, and industrial activities, have led to an increase in the concentration of pollutants in the ambient air. Among air pollutants, particulate matter is responsible for most adverse impacts. Several techniques have been implemented to reduce particulate matter concentrations in the ambient air. However, despite all the threats and awareness, efforts to improve air quality remain inadequate. In recent years, urban vegetation has emerged as an efficient Nature-based Solution for managing environmental air pollution due to its ability to filter air, thereby reducing the atmospheric concentrations of particulate matter. This review characterizes the various mitigation mechanisms for particulate matter by urban vegetation (deposition, dispersion, and modification) and identifies key areas for further improvements within each mechanism. Through a systematic assessment of existing literature, this review also highlights the existing gaps in the present literature that need to be addressed to maximize the utility of urban vegetation in reducing particulate matter levels. In conclusion, the review emphasizes the urgent need for proper air pollution management through urban vegetation by integrating different fields, multiple stakeholders, and policymakers to support better implementation.

A scoping review of human health co-benefits of forest-based climate change mitigation in Europe

Climate change is a pressing global challenge with profound implications for human health. Forest-based climate change mitigation strategies, such as afforestation, reforestation, and sustainable forest management, offer promising solutions to mitigate climate change and simultaneously yield substantial co-benefits for human health. The objective of this scoping review was to examine research trends related to the interdisciplinary nexus between forests as carbon sinks and human health co-benefits. We developed a conceptual framework model, supporting the inclusion of exposure pathways, such as recreational opportunities or aesthetic experiences, in the co-benefit context. We used a scoping review methodology to identify the proportion of European research on forest-based mitigation strategies that acknowledge the interconnection between mitigation strategies and human impacts. We also aimed to assess whether synergies and trade-offs between forest-based carbon sink capacity and human co-benefits has been analysed and quantified. From the initial 4,062 records retrieved, 349 reports analysed European forest management principles and factors related to climate change mitigation capacity. Of those, 97 studies acknowledged human co-benefits and 13 studies quantified the impacts on exposure pathways or health co-benefits and were included for full review. Our analysis demonstrates that there is potential for synergies related to optimising carbon sink capacity together with human co-benefits, but there is currently a lack of holistic research approaches assessing these interrelationships. We suggest enhanced interdisciplinary efforts, using for example multideterminant modelling approaches, to advance evidence and understanding of the forest and health nexus in the context of climate change mitigation.

Green space, genetic susceptibility, and risk of osteoporosis:a cohort study from the UK Biobank

OBJECTIVE

This study aimed to investigate the effect of residential exposure to green space on the incident osteoporosis and further explore the modification effect of genetic susceptibility.

METHODS

Participants from the UK Biobank were followed from 2006 to 2010 (baseline) to December 31st, 2022. Using land use coverage, we evaluated exposure to residential surrounding green space, natural environment, and domestic gardens. We used the Cox regression to examine the association between the residential environment and incident osteoporosis. The interactive effects between polygenic risk score (PRS) of osteoporosis and residential environments on incident osteoporosis were investigated.

RESULTS

This study included 292,662 participants. Over a median follow-up period of 13.65 years, we documented 9177 incidents of osteoporosis. Per interquartile (IQR) increase in greenness and natural environment at a 300 m buffer was associated with a 4% lower risk of incident osteoporosis [HR = 0.96 (95% CI: 0.93, 0.99)] and [HR = 0.96 (95% CI: 0.93, 0.98)], respectively. We did not identify any interactive effects between genetic risk and residential environment on incident osteoporosis.

CONCLUSIONS

This study found that public greenness and natural environments could reduce the risk of incident osteoporosis regardless of genetic predisposition. Developing sustainable and publicly accessible natural environments might benefit populations' bone health.

Proximity to public green spaces and depressive symptoms among South African residents: a population-based study

BACKGROUND

Exposure to green spaces has been suggested to improve mental health and may reduce the risk of depression. However, there is generally limited evidence on the association between green spaces and depression originating from low-and middle-income countries and Africa in particular. Here, we investigate the association between proximity to public green spaces and depressive symptoms among residents of Gauteng Province, South Africa.

METHODS

We used data from the 2017/2018 Gauteng quality of life survey. We included all individuals aged 18 years or older residing in the nine municipalities of Gauteng Province that completed the survey (n = 24,341). Depressive symptoms were assessed using the Patient Health Questionnaire-2. Proximity to public green spaces was defined as self-reported walking time (either less or greater than 15 min) from individuals' homes to the nearest public green space. To assess the association between access to public green spaces and depressive symptoms, we used mixed-effects models, adjusted for age, sex, population group (African, Indian/Asian, Coloured (mixed race), and White), educational attainment, and municipality. We additionally performed stratified analyses by age, sex, educational attainment, and population group to evaluate whether associations differed within subgroups. Associations are expressed as prevalence ratios (PR) and their 95% confidence intervals (95% CI).

RESULTS

We observed a 6% (PR = 0.94, 95%CI = 0.92-0.96) prevalence reduction in depressive symptoms for individuals who reported that the nearest public green space was less than 15 min from their homes as compared to those who reported > 15 min. After stratification, this inverse association was stronger among females, individuals aged 35-59 years,those with higher levels of educational attainment, and Coloured individuals as compared to their counterparts.

CONCLUSION

Our findings suggest that public green spaces close to residential homes may be associated with a reduction in the occurrence of depressive symptoms among urban populations in resource-constrained settings like South Africa.

Residential greenness and lower breast and prostate cancer incidence: Evidence from a retrospective cohort study of 977,644 participants from Israel

BACKGROUND

There is limited evidence on the associations between residential greenness and cancer incidence in longitudinal studies.

OBJECTIVES

The aim of the study was to evaluate the associations between weighted mean residential greenness exposure and cancer incidence.

METHODS

This is a registry based retrospective cohort study of 977,644 participants. The residential greenness exposure was estimated for every participant, as the weighted mean residential greenness exposure. This was based on the mean Normalized Difference Vegetation Index (NDVI) in the residential small geographic area and the duration of the residence in this area. Cancer incidence cases included consecutive newly diagnosed cases of primary cancer. Analyses were conducted for all cancer sites, lung cancer, bladder cancer, breast cancer, prostate cancer and melanoma-skin cancer. Cox regression models were used to evaluate the crude and adjusted associations (hazards ratios (HR) and its 95 % confidence intervals (CIs)) between tertiles of residential greenness and cancer incidence. Further adjusted models to nitrogen oxides (NOx) were estimated.

RESULTS

After adjustment to covariates, exposure to the highest tertile of residential greenness, compared to the lowest, were associated with lower risk for all cancer sites (HR = 0.88, 95 % CI: 0.86-0.90), breast cancer (HR = 0.85, 95 % CI: 0.80-0.89) and prostate cancer (HR = 0.85, 95 % CI: 0.79-0.91). In addition, lower risk were observed for the middle tertile of exposure and all cancer sites (HR = 0.88, 95 % CI: 0.86-0.90), breast cancer (HR = 0.88, 95 % CI: 0.84-0.92) and prostate cancer (HR = 0.83, 95 % CI: 0.79-0.89). There was no evidence for mediation by air pollution (NOx).

DISCUSSION

Residential greenness demonstrated beneficial associations with lower risk for all cancers, breast and prostate cancers. If our observations will be replicated, it may present a useful avenue for public-health intervention to reduce cancer burden through the provision of greenness exposure.

Air pollution exposure may impact the composition of human milk oligosaccharides

Human milk oligosaccharides (HMOs) impact neonate immunity and health outcomes. However, the environmental factors influencing HMO composition remain understudied. This study examined the associations between ambient air pollutant (AAP) exposure and HMOs at 1-month postpartum. Human milk samples were collected at 1-month postpartum (n = 185). AAP (PM2.5, PM10, NO2) exposure included the 9-month pregnancy period through 1-month postpartum. Associations between AAP with (1) HMO diversity, (2) the sum of sialylated and fucosylated HMOs, (3) 6 a priori HMOs linked with infant health, and (4) all HMOs were examined using multivariable linear regression and principal component analysis (PCA). Exposure to AAP was associated with lower HMO diversity. PM2.5 and PM10 exposure was positively associated with the HMO 3-fucosyllactose (3FL); PM2.5 exposure was positively associated with the sum of total HMOs, sum of fucosylated HMOs, and the HMO 2'-fucosyllactose (2'FL). PCA indicated the PM2.5, PM10, and NO2 exposures were associated with HMO profiles. Individual models indicated that AAP exposure was associated with five additional HMOs (LNFP I, LNFP II, DFLNT, LNH). This is the first study to demonstrate associations between AAP and breast milk HMOs. Future longitudinal studies will help determine the long-term impact of AAP on human milk composition.

Ambient particulate matter and surrounding greenness in relation to sleep quality among pregnant women: A nationwide cohort study

Background

Particulate air pollution and residential greenness are associated with sleep quality in the general population; however, their influence on maternal sleep quality during pregnancy has not been assessed.

Objective

This cross-sectional study investigated the individual and interactive effects of exposure to particulate matter (PM) air pollution and residential greenness on sleep quality in pregnant women.

Methods

Pregnant women (n = 4933) enrolled in the Korean Children's Environmental Health Study with sleep quality information and residential address were included. Sleep quality was assessed using the Pittsburgh Sleep Quality Index (PSQI). The average concentrations of PM (PM2.5 and PM10) during pregnancy were estimated through land use regression, and residential greenness in a 1000 m buffer area around participants' residences was estimated using the Normalized Difference Vegetation Index (NDVI1000-m). Modified Poisson regression models were used to estimate the associations between PM and NDVI and poor sleep quality (PSQI >5) after controlling for a range of covariates. A four-way mediation analysis was conducted to examine the mediating effects of PM.

Results

After adjusting for confounders, each 10 μg/m3 increase in PM2.5 and PM10 exposure was associated with a higher risk of poor sleep quality (relative risk [RR]: 1.06; 95% confidence interval [CI]: 1.01, 1.11; and RR: 1.09; 95% CI: 1.06, 1.13, respectively), and each 0.1-unit increase in NDVI1000-m was associated with a lower risk of poor sleep quality (RR: 0.97; 95% CI: 0.95, 0.99). Mediation analysis showed that PM mediated approximately 37%-56% of the association between residential greenness and poor sleep quality.

Conclusions

This study identified a positive association between residential greenness and sleep quality. Furthermore, these associations are mediated by a reduction in exposure to particulate air pollution and highlight the link between green areas, air pollution control, and human health.

Green and blue space exposure and non-communicable disease related hospitalizations: A systematic review

The global increase in non-communicable diseases (NCDs) presents a critical public health concern. Emerging evidence suggests that exposure to natural environments may reduce the risk of developing NCDs through multiple pathways. The present systematic review aims to synthesize and evaluate the observational evidence regarding associations between exposure to green and blue spaces and hospital admissions related to NCDs. A comprehensive literature search strategy was conducted in Embase (Ovid), PubMed, and Web of Science. The risk of bias and quality of the evidence were assessed using The Navigation Guide methodology, an approach specifically designed for environmental health research. Of 3060 search results, 17 articles were included. Notably, the majority of the studies (n = 14; 82.4%) were published from 2020 onwards. Most studies were conducted in the United States (n = 6; 35.3%) and China (n = 4; 23.5%). Exposure to green spaces was assessed through all studies, while only three included blue spaces. In terms of study design, cohort design was employed in nearly half of the studies (n = 8; 47.1%), followed by case-crossover design (n = 3, 17.6%). Over 75% of the included studies (n = 13) had a high or probably high rating in the risk of bias assessment. The studies encompassed diverse NCD outcome domains; cardiovascular diseases (CVDs) (n = 10), respiratory diseases (RSDs) (n = 2), heat-related diseases (n = 1), metabolic diseases (n = 2), cancer (n = 1), neurodegenerative diseases (NDDs) (n = 2), and mental health disorders (n = 2). The present review suggests that a clear link between blue space exposure and NCD hospital admissions is not evident. However, exposure to green spaces appears to predominantly have a protective effect, although the direction of the association varies across different outcome domains. The heterogeneity among the outcome domains together with the limited number of studies, emphasizes the need for more robust evidence.

Association of residential greenness with obstructive sleep apnea among Chinese old adults and the mediation role of PM2.5 and leisure-time physical activity

Few studies have investigated the association of residential greenness with obstructive sleep apnea (OSA). This study was to comprehensively examine the association of residential greenness exposure with OSA and explore the mediating effect of leisure-time physical activity (LTPA) and PM2.5 on the association among Chinese old adults. A prospective cohort study that enrolled 2027 adults aged ≥65 was conducted between 1st July 2015 and 30th September 2019 in Southern China. OSA was ascertained by Berlin Questionnaire. Greenness exposure was measured by contemporaneous and cumulative average normalized difference vegetation index (NDVI) in the 1000 m radius around each participant's residential address. Hazard ratios (HRs) with 95 % confidence intervals (CIs) were calculated by Cox proportional hazards model to assess the impact of greenness exposure on the incidence of OSA after adjusting for confounders. LTPA and PM2.5 were examined as potential mediators in the aforementioned models. A total of 293, nearly 14.5 %, participants developed OSA within 59,251 person-months of follow-up. When comparing the highest with lowest tertiles, both contemporaneous NDVI (>0.351 vs. ≤0.325: HR = 0.20, 95 % CI = 0.13-0.31) and cumulative NDVI (> 0.346 vs. ≤ 0.317: HR = 0.32, 95 % CI = 0.21-0.47) were associated with a reduced risk of OSA after adjusting for confounders. LTPA and PM2.5 significantly mediated the association between greenness and OSA. In conclusion, this study indicated that exposure to higher residential greenness could decrease OSA risk, and this benefit may be achieved by promoting physical activity and decreasing PM2.5 concentration. The findings suggest to formulate targeted interventional strategies by expanding residential greenness to prevent OSA and reduce disease burden.

Assessment of vegetation change using NDVI, LST, and carbon analyses in Çankırı Karatekin University, Turkey

Due to a rising population and urbanization, the green areas have been decreasing in cities, with a negative impact on air pollution, human health, and ecosystem. As part of the urban environment, university campuses contribute to urban ecosystem with their vegetation. This study aims to (1) assess the change of vegetative land cover of the Çankırı Karatekin University in Turkey and (2) evaluate its benefits to the ecosystem in terms of carbon sequestration, storage, and improvement of air quality by means of a simulation. In the study, the density and vegetation change were assessed with NDVI and LST analyses in ArcGIS; carbon emissions and air pollution benefits were estimated in i-Tree Canopy tool. The study showed that the healthy vegetation consisting of trees/shrubs and grass/herbaceous, which was 32.2% (28 ha) in 2000, increased to 85% (74 ha) in 2020 NDVI maps, and the surface temperature also increased between 2000 and 2020 in LST maps.The rise in vegetation as grass/herbaceous areas instead of trees/shrubs and the use of impervious buildings/roads on the land surface increased the land surface temperature. As a result of the analyses in the i-Tree-Canopy tool, it was estimated that the trees/shrubs and grass/herbaceous vegetation canopy covering 31.42% of the study area removed a total of 512,845.65 g of pollutant gas and particles from the air, 20.79 tonnes of carbon sequestered annually, and 522.01 tonnes of carbon stored by vegetative land cover. In the simulation, where 32.62% soil/bare ground areas were converted to trees/shrubs in order to improve vegetation cover in the area, it was determined that it contributed 5 times more to the ecosystem service value for removing pollutants from the air, carbon storage, and improving the ecosystem. It was revealed that the vegetative land cover formed by tree/shrub species should be increased in the campus in the future. The study method model serves as a tool for planning and designing eco-friendly urban environment.