The nexus between air pollution, green infrastructure and human health

Impact of single and combined local air pollution mitigation measures in an urban environment

Urban air pollution is one of the most important environmental problems for human health and several strategies have been developed for its mitigation. The objective of this study is to assess the impact of single and combined mitigation measures on concentrations of air pollutants emitted by traffic at pedestrian level in the same urban environment. The effectiveness of different scenarios of green infrastructure (GI), the implementation of photocatalytic materials and traffic low emission zones (LEZ) are investigated, as well as several combinations of LEZ and GI. A wide set of scenarios is simulated through Computational Fluid Dynamics (CFD) modelling for two different wind directions (perpendicular (0°) and 45° wind directions). Wind flow for the BASE scenario without any measure implemented was previously evaluated using wind-tunnel measurements. Air pollutant concentrations for this scenario are compared with the results obtained from the different mitigation scenarios. Reduction of traffic emissions through LEZ is found to be the most effective single measure to improve local air quality. However, GI enhances the effects of LEZ, which makes the combination of LEZ + GI a very effective measure. The effectiveness of this combination depends on the GI layout, the intensity of emission reduction in the LEZ and the traffic diversion in streets surrounding the LEZ. These findings, in line with previous literature, suggest that the implementation of GI may increase air pollutant concentrations at pedestrian level for some cases. However, this study highlights that this negative effect on air quality can turn into positive when used in combination with reductions of local traffic emissions.

Exploring the interplay between particulate matter capture, wash-off, and leaf traits in green wall species

The study investigated inter-species variation in particulate matter (PM) accumulation, wash-off, and retention on green wall plants, with a focus on leaf characteristics. Ten broadleaf plant species were studied in an experimental green wall. Ambient PM concentrations remained relatively stable throughout the measurement period: PM1: 16.60 ± 9.97 μgm-3, PM2.5: 23.27 ± 11.88 μgm-3, and PM10: 39.59 ± 25.72 μgm-3. Leaf samples were taken before and after three rainfall events, and PM deposition was measured using Scanning Electron Microscopy (SEM). Leaf micromorphological traits, including surface roughness, hair density, and stomatal density, exhibited variability among species and leaf surfaces. Notably, I.sempervirens and H.helix had relatively high PM densities across all size fractions. The study underscored the substantial potential of green wall plants for atmospheric PM removal, with higher Wall Leaf Area Index (WLAI) species like A.maritima and T.serpyllum exhibiting increased PM accumulation at plant level. Rainfall led to significant wash-off for smaller particles, whereas larger particles exhibited lower wash-off rates. Leaf micromorphology impacted PM accumulation, although effects varied among species, and parameters such as surface roughness, stomatal density, and leaf size did not consistently affect PM deposition. The composition of deposited particles encompassed natural, vehicular, salt, and unclassified agglomerates, with minimal changes after rainfall. Air Pollution Tolerance Index (APTI) assessments revealed that I.sempervirens displayed the highest air pollution tolerance, while O.vulgare had the lowest. APTI showed a moderate positive correlation with PM deposition across all fractions. The study concluded that the interplay of macro and micromorphology in green wall plant species determines their PM removal potential. Further research is needed to identify the key leaf characteristics for optimal green wall species selection for effective PM removal.

How do taxi drivers expose to fine particulate matter (PM2.5) in a Chinese megacity: a rapid assessment incorporating with satellite-derived information and urban mobility data

BACKGROUND

Taxi drivers in a Chinese megacity are frequently exposed to traffic-related particulate matter (PM2.5) due to their job nature, busy road traffic, and urban density. A robust method to quantify dynamic population exposure to PM2.5 among taxi drivers is important for occupational risk prevention, however, it is limited by data availability.

METHODS

This study proposed a rapid assessment of dynamic exposure to PM2.5 among drivers based on satellite-derived information, air quality data from monitoring stations, and GPS-based taxi trajectory data. An empirical study was conducted in Wuhan, China, to examine spatial and temporal variability of dynamic exposure and compare whether drivers' exposure exceeded the World Health Organization (WHO) and China air quality guideline thresholds. Kernel density estimation was conducted to further explore the relationship between dynamic exposure and taxi drivers' activities.

RESULTS

The taxi drivers' weekday and weekend 24-h PM2.5 exposure was 83.60 μg/m3 and 55.62 μg/m3 respectively, 3.4 and 2.2 times than the WHO's recommended level of 25 µg/m3. Specifically, drivers with high PM2.5 exposure had a higher average trip distance and smaller activity areas. Although major transportation interchanges/terminals were the common activity hotspots for both taxi drivers with high and low exposure, activity hotspots of drivers with high exposure were mainly located in busy riverside commercial areas within historic and central districts bounded by the "Inner Ring Road", while hotspots of drivers with low exposure were new commercial areas in the extended urbanized area bounded by the "Third Ring Road".

CONCLUSION

These findings emphasized the need for air quality management and community planning to mitigate the potential health risks of taxi drivers.

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.

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.

Cities and mental health: The role of the built environment, and environmental and lifestyle factors in Barcelona

Built environment characteristics and related environmental exposures and behaviors have been, separately, implicated in the development of poor mental health. However, it is unclear how these factors act together in relation to mental health. We studied these factors simultaneously to evaluate the impact of the built environment, and the mediating role of environmental exposures and physical activity, on mental health, while also studying moderation by sex, age, and length of residence. We used a cross-sectional population-based sample of 3145 individuals aged 15-97 years from Barcelona, Spain. Time spent walking and mental health status were assessed with validated questionnaires, administered through a face-to-face interview. We characterized the built environment (e.g., building, population and intersection density and green space), road traffic noise, and ambient air pollution at the residential level using land cover maps, remote sensing, noise maps and land use regression models. Adjusted regression models accounting for spatial clustering were analyzed to study associations between built environment attributes and mental health, and mediation and moderation effects. Density attributes were directly or indirectly, through air pollution and less consistently through walking, associated with poor mental health. Green space indicators were associated with lower prevalence of poor mental health, partly through lower air pollution exposure and more walking. In some cases, these associations differed by sex, age or length of residence. Non-linear associations of density indicators with environmental exposures, and of particulate matter with poor mental health indicated threshold effects. We conclude that living in dense areas with high air pollution concentrations was associated with poor mental health. On the other hand, green areas with lower air pollution concentrations were protective against poor mental health. Greater urban density might benefit health, but might only do so when air pollution concentrations are low.

Lichen biomonitoring to assess spatial variability, potential sources and human health risks of polycyclic aromatic hydrocarbons (PAHs) and airborne metal concentrations in Manchester (UK)

Airborne metals and organic pollutants are linked to severe human health impacts, i.e. affecting the nervous system and being associated with cancer. Airborne metals and polycyclic aromatic hydrocarbons (PAHs) in urban environments are derived from diverse sources, including combustion and industrial and vehicular emissions, posing a threat to air quality and subsequently human health. A lichen biomonitoring approach was used to assess spatial variability of airborne metals and PAHs, identify potential pollution sources and assess human health risks across the City of Manchester (UK). Metal concentrations recorded in lichen samples were highest within the city centre area and along the major road network, and lichen PAH profiles were dominated by 4-ring PAHs (189.82 ng g-1 in Xanthoria parietina), with 5- and 6-ring PAHs also contributing to the overall PAH profile. Cluster analysis and pollution index factor (PIF) calculations for lichen-derived metal concentrations suggested deteriorated air quality being primarily linked to vehicular emissions. Comparably, PAH diagnostic ratios identified vehicular sources as a primary cause of PAH pollution across Manchester. However, local more complex sources (e.g. industrial emissions) were further identified. Human health risk assessment found a "moderate" risk for adults and children by airborne potential harmful element (PHEs) concentrations, whereas PAH exposure in Manchester is potentially linked to 1455 (ILCR = 1.45 × 10-3) cancer cases (in 1,000,000). Findings of this study indicate that an easy-to-use lichen biomonitoring approach can aid to identify hotspots of impaired air quality and potential human health impacts by airborne metals and PAHs across an urban environment, particularly at locations that are not continuously covered by (non-)automated air quality measurement programmes.

A trait-based investigation into evergreen woody plants for traffic-related air pollution mitigation over time

This study investigated influences of leaf traits on particulate matter (PM) wash-off and (re)capture (i.e., net removal) over time. Leaf samples were taken before and after three rainfall events from a range of 10 evergreen woody plants (including five different leaf types), which were positioned with an optical particle counter alongside a busy road. Scanning electron microscopy was used to quantify the density (no./mm2), mass (μg/cm2), and elemental composition of deposited particles. To enable leaf area comparison between scale-like leaves and other leaf types, a novel metric (FSA: foliage surface area per unit branch length) was developed, which may be utilised by future research. Vehicle-related particles constituted 15 % of total deposition, and there was a notable 50 % decrease in the proportion of tyre wear particles after rainfall. T. baccata presented the lowest proportion (11.1 %) of vehicle-related particle deposition but the most consistent performance in terms of net PM removal. Only four of the 10 plant specimens (C. japonica, C. lawsoniana, J. chinensis, and T. baccata) presented effective PM wash-off across all particle size fractions and rainfall intensities, with a generally positive relationship observed between rainfall intensity and wash-off. Mass deposition was more significantly determined by particle size than number density. Interestingly, larger particles were also less easily washed off than smaller particles. Some traits typically considered to be advantageous (e.g., greater hairiness) may in fact hinder net removal over time due to retention under rainfall. Small leaf area is one trait that may promote both accumulation and wash-off. However, FSA was found to be the most influential trait, with an inverse relationship between FSA and wash-off efficacy. This finding poses trade-offs and opportunities for green infrastructure design, which are discussed. Finally, numerous areas for future research are recommended, underlining the importance of systems approaches in developing vegetation management frameworks.

Show me the money! Associations between tree canopy and hospital costs in cities for cardiovascular disease events in a longitudinal cohort study of 110,134 participants

Health benefits from urban greening are assumed to translate into reduced healthcare expenditure, yet few studies have tested this. A total of 110,134 participants in the Sax Institute's 45 and Up Study in the Australian cities of Sydney, Newcastle, or Wollongong were linked with hospital cost data for cardiovascular disease (CVD) events (e.g., acute myocardial infarctions) up to 30 June 2018. Associations between percentages of total green space, tree canopy, and open grass within 1.6 km of participants homes and annual per person measured CVD-related hospital costs were analysed using generalised linear model (GLM) with gamma density as a component of a two-part mixture model, adjusting for confounders. Overall, 26,243 participants experienced a CVD-related hospitalisation. Incidence was lower among participants with 10 % more tree canopy (OR 0.98, 95 %CI 0.96, 0.99), but not with higher total green space or open grass percentages. Total costs of hospitalisations per year were lower with 10 % more tree canopy (means ratio 0.96, 95 %CI 0.95, 0.98), but also higher with 10 % more open grass (means ratio 1.04, 95 %CI 1.02, 1.06). It was estimated that raising tree canopy cover to 30 % or more for individuals with currently less than 10 % could lead to a within-sample annual saving per person of AU$ 193 overall and AU$ 569 for those who experienced one or more CVD-related hospital admissions. This projects to an estimated annual health sector cost reduction of AU$ 19.3 million per 100,000 individuals for whom local tree canopy cover is increased from less than 10 % to 30 % or higher. In conclusion, this longitudinal study is among the first to analyse measured healthcare cost data in relation to urban green space in general, and with differentiation between major types of greenery relevant to urban planning policies in cities around the world. In sum, this study advances an increasingly important and international focus of research by reporting on the lower burden of CVD and fewer associated hospitalisations stemming from upstream investments that protect and restore urban tree canopy, which not only translates into substantial reduced costs for the health sector, but also helps to create regenerative cities and flourishing communities.

Possibilities and limits of modelling of long-range economic consequences of air pollution - A case study

Air pollution is the biggest environmental problem in modern societies, causing considerable health damage and requiring substantial financial resources for health care. The goal of the study is to demonstrate the adverse economic consequences of air pollution on example of a small, open Central European country, Hungary, and to provide quantified financial arguments for macroeconomic decision-making for the development of a long-term energy strategy. On the basis of the Cobb-Douglas production function and Solow-Swann model of dynamic economic systems a simple and robust model was constructed to estimate and predict economic losses, caused by the pollution. On base of results it is obvious, that on base of macroeconomic theory and combination of various, publicly available, quality-controlled statistical resources quantifiable models can be constructed to characterise the economic consequences of air pollution, but it should be taken into consideration, that the reliability of economic models considerably depends on their initial parameters and practical validity of assumptions, based on which the underlying economic theories were built. The most important economic burden of air pollution is caused by the loss of working-age population, resulting in a decrease of 4.1-9.4 % a year in Gross Domestic Product (GDP) in the next fifty years. The additional burden of health care costs amounts to 0.1 % of GDP. Reducing air pollution is not only a quality of life improvement but also an investment into the economic development. Notwithstanding of statistical biases it could be proven the importance of combination health economic and econometric methods in preparation of more efficient environmental-related socio-economic decisions.

A review of interconnected challenges in the water-energy-food nexus: Urban pollution perspective towards sustainable development

The swift growth of cities worldwide poses significant challenges in ensuring a sufficient water, energy, and food supply. The Nexus has innovated valuable systems to address these challenges. However, a crucial issue is the potential for pollution resulting from these systems, which directly and indirectly impacts public health and the overall quality of urban living. This study comprehensively reviews the interconnected challenges of the water-energy-food (WEF) nexus and various forms of pollution in cities. The primary focus of this review article is to showcase the findings of WEF nexus studies regarding various pollutions across different geographical regions and spatial scales. It aims to examine the problems resulting from these pollutions, specifically their effects on human health and urban life. It also delves into the sources of pollution as identified in these studies. Furthermore, the article will highlight the proposed solutions from the research aimed at effectively mitigating pollution in each sector studied. This article is a systematic review which analyses research sources from the Scopus database. It extensively reviewed 2463 peer-reviewed published articles and focused explicitly on articles related to the WEF nexus that discussed pollution. Our study emphasizes, firstly, raising awareness about the crucial link between the WEF nexus, pollution, urban environments, and human health among policymakers and key stakeholders, including urban planners, industry partners and municipalities. This is to promote the development of policies that encourage sustainable practices and key stakeholders. Secondly, it evaluates WEF nexus and pollution research methods and findings, aiding in identifying research gaps technological innovation and potential, as well as enhancing decision-making. Lastly, it outlines future research challenges, providing a roadmap for researchers and policymakers to advance understanding in this domain and identify opportunities for resource efficiency and collaboration between different sectors.

Reassessing the role of urban green space in air pollution control

The assumption that vegetation improves air quality is prevalent in scientific, popular, and political discourse. However, experimental and modeling studies show the effect of green space on air pollutant concentrations in urban settings is highly variable and context specific. We revisited the link between vegetation and air quality using satellite-derived changes of urban green space and air pollutant concentrations from 2,615 established monitoring stations over Europe and the United States. Between 2010 and 2019, stations recorded declines in ambient NO2, (particulate matter) PM10, and PM2.5 (average of -3.14% y-1), but not O3 (+0.5% y-1), pointing to the general success of recent policy interventions to restrict anthropogenic emissions. The effect size of total green space on air pollution was weak and highly variable, particularly at the street scale (15 to 60 m radius) where vegetation can restrict ventilation. However, when isolating changes in tree cover, we found a negative association with air pollution at borough to city scales (120 to 16,000 m) particularly for O3 and PM. The effect of green space was smaller than the pollutant deposition and dispersion effects of meteorological drivers including precipitation, humidity, and wind speed. When averaged across spatial scales, a one SD increase in green space resulted in a 0.8% (95% CI: -3.5 to 2%) decline in air pollution. Our findings suggest that while urban greening may improve air quality at the borough-to-city scale, the impact is moderate and may have detrimental street-level effects depending on aerodynamic factors like vegetation type and urban form.

The impact of vegetative and solid roadway barriers on particulate matter concentration in urban settings

A potentially important approach for reducing exposure to traffic-related air pollution (TRAP) is the use of roadside barriers to reduce dispersion from highway sources to adjacent populated areas. The Trees Reducing Environmental Exposures (TREE) study investigated the effect of vegetative and solid barriers along major controlled-access highways in Atlanta, Georgia, USA by simultaneously sampling TRAP concentration at roadside locations in front of barriers and at comparison locations down-range. We measured black carbon (BC) mass concentration, particle number concentration (PNC), and the size distribution of ultrafine aerosols. Our sample sites encompassed the range of roadway barrier options in the Atlanta area: simple chain-link fences, solid barriers, and vegetative barriers. We used Generalized Linear Mixed Models (GLMMs) to estimate the effect of barrier type on the ratio of particle concentrations at the comparison site relative to the roadside site while controlling for covariates including wind direction, temperature, relative humidity, traffic volume, and distance to the roadway. Vegetative barriers exhibited the greatest TRAP reduction in terms of BC mass concentration (37% lower behind a vegetative barrier) as well as PNC (6.7% lower), and sensitivity analysis was consistent with this effect being more pronounced when the barrier was downwind of the highway. The ultrafine size distribution was comprised of modestly smaller particles on the highway side of the barrier. Non-highway particle sources were present at all sample sites, most commonly motor vehicle emissions from nearby arterials or secondary streets, which may have obscured the effect of roadside barriers.

Environmental and social inequities in continental France: an analysis of exposure to heat, air pollution, and lack of vegetation

BACKGROUND

Cumulative environmental exposures and social deprivation increase health vulnerability and limit the capacity of populations to adapt to climate change.

OBJECTIVE

Our study aimed at providing a fine-scale characterization of exposure to heat, air pollution, and lack of vegetation in continental France between 2000 and 2018, describing spatiotemporal trends and environmental hotspots (i.e., areas that cumulate the highest levels of overexposure), and exploring any associations with social deprivation.

METHODS

The European (EDI) and French (FDep) social deprivation indices, the normalized difference vegetation index, daily ambient temperatures, particulate matter (PM2.5 and PM10), nitrogen dioxide, and ozone (O3) concentrations were estimated for 48,185 French census districts. Reference values were chosen to characterize (over-)exposure. Hotspots were defined as the areas cumulating the highest overexposure to temperature, air pollution, and lack of vegetation. Associations between heat overexposure or hotspots and social deprivation were assessed using logistic regressions.

RESULTS

Overexposure to heat was higher in 2015-2018 compared with 2000-2014. Exposure to all air pollutants except for O3 decreased during the study period. In 2018, more than 79% of the urban census districts exceeded the 2021 WHO air quality guidelines. The evolution of vegetation density between 2000 and 2018 was heterogeneous across continental France. In urban areas, the most deprived census districts were at a higher risk of being hotspots (odds ratio (OR): 10.86, 95% CI: 9.87-11.98 using EDI and OR: 1.07, 95% CI: 1.04-1.11 using FDep).

IMPACT STATEMENT

We studied cumulative environmental exposures and social deprivation in French census districts. The 2015-2018 period showed the highest overexposure to heat between 2000 and 2018. In 2018, the air quality did not meet the 2021 WHO guidelines in most census districts and 8.6 million people lived in environmental hotspots. Highly socially deprived urban areas had a higher risk of being in a hotspot. This study proposes for the first time, a methodology to identify hotspots of exposure to heat, air pollution, and lack of vegetation and their associations with social deprivation at a national level.

Obesogenic environments as major determinants of a disease: It is time to re-shape our cities

Obesity rates are increasing in almost all high- and low-income countries, and population-based approaches are necessary to reverse this trend. The current global efforts are focused on identifying the root causes of obesity and developing effective methods for early diagnosis, screening, treatment, and long-term management, both at an individual and health system level. However, there is a relative lack of effective options for early diagnosis, treatment, and long-term management, which means that population-based strategies are also needed. These strategies involve conceptual shifts towards community- and environment-focused approaches. This review aimed to provide evidence on how environmental factors contribute to the risk of obesity and how reshaping cities can help slow down obesity prevalence rates and improve long-term management.

Spatiotemporal dynamics and driving factors of vegetation coverage around linear cultural heritage: A case study of the Beijing-Hangzhou Grand Canal

Linear cultural heritage, which plays significant roles in safeguarding the world's cultural and maintaining global civilization, has obtained rising concerns in purpose of sustainability. However, in view of existing publications, most attention has been paid on its values of recreation, history and culture. Its ecological environment is still poorly understood. As the longest linear cultural heritage in the world and spiritual symbol of China, the Beijing-Hangzhou Grand Canal (BHGC) was selected as the study area in this study. We focused on the vegetation coverage around the BHGC from 2000 to 2020 and aimed to practically investigate whether and why vegetation distributes imbalanced along the entire BHGC. The annual Normalized Difference Vegetation Index (NDVI), derived from Landsat images, was used to indicate the spatiotemporal dynamics of vegetation coverage. Based on ten natural and human interference factors, the geographic detector model was applied to analyze its driving mechanism. Results show that (1) vegetation coverage around the BHGC presented apparently spatial heterogeneity. Cities located at both ends of the BHGC showed lower vegetation coverage, whereas those in the middle were relatively higher. (2) Vegetation coverage in 23 cities around the BHGC was relatively stable over time, i.e., nearly 76.39% of the study area was measured unchanged trend. The slight degradation mainly occurred to the sub-urban and extra-urban areas. (3) The driving forces of human interferences on vegetation coverage dynamics around the BHGC surpassed natural factors from 2000 to 2020. Population density, GDP and cultural heritage density presented higher explanatory powers of vegetation growth compared to other seven factors. These findings provide a scientific basis for local governments to intervene in vegetation changes and ecological restoration through natural and human factors within the favorable scope.

Efficacy of green infrastructure in reducing exposure to local, traffic-related sources of airborne particulate matter (PM)

One aim of roadside green infrastructure (GI) is to mitigate exposure to local, traffic-generated pollutants. Here, we determine the efficacy of roadside GI in improving local air quality through the deposition and/or dispersion of airborne particulate matter (PM). PM was collected on both pumped air filters and on the leaves of a recently installed 'tredge' (trees managed as a head-high hedge) at an open road environment next to a primary school in Manchester, U.K. The magnetic properties of PM deposited on leaves and filters (size fractions PM10 and PM2.5) were deduced from hysteresis loops, first-order reversal curves (FORCs), and low-temperature remanence measurements. These were complemented with electron microscopy to identify changes in magnetic PM concentration downwind of the tredge/GI. We show that the tredge is permeable to airflow using a simple CO2 tracer experiment; hence, it allows interception and subsequent deposition of PM on its leaves. Magnetic loadings per m3 of air from filters (PM10 saturation magnetisation, Ms, at 5 K) were reduced by 40 % behind the tredge and a further 63 % in the playground; a total reduction of 78 % compared to roadside air. For the PM2.5 fraction, the reduction in magnetic loading behind the tredge was remarkable (82 %), reflecting efficient diffusional capture of sub-5 nm Fe-oxide particles by the tredge. Some direct mixing of roadside and playground air occurs at the back of the playground, caused by air flow over, and/or through gaps in, the slowly-permeable tredge. The magnetic loading on tredge leaves increased over successive days, capturing ~23 % of local, traffic-derived PM10. Using a heuristic two-dimensional turbulent mixing model, we assess the limited dispersion of PM < 22.5 μm induced by eddies in the tredge wake. This study demonstrates that PM deposition on leaves reduces exposure significantly in this school playground setting; hence, providing a cost-effective mitigation strategy.

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

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

The impact of urban irrigation on the temperature-carbon feedback in U.S. cities

Urban areas experience numerous environmental challenges, among which the anthropogenic emissions of heat and carbon are two major contributors, the former is responsible for the notorious urban heat effect, the latter longterm climate changes. Moreover, the exchange of heat and carbon dioxide are closely interlinked in the built environment, and can form positive feedback loops that accelerate the degradation of urban environmental quality. Among a handful countermeasures for heat and carbon mitigation, urban irrigation is believed to be effective in cooling, yet the understanding of its impact on the co-evolution of heat and carbon emission remains obscure. In this study, we conducted multiphysics urban climate modeling for all urban areas in the contiguous United States, and evaluated the irrigation-induced cooling and carbon mitigation. Furthermore, we assessed the impact of urban irrigation on the potential heat-carbon feedback loop, with their strength of coupling quantified by an advanced causal inference method using the convergent cross mapping algorithms. It is found that the impact of urban irrigation varies vastly in geographically different cities, with its local and non-local effect unraveling distinct pathways of heat-carbon feedback mechanism.

China's air quality improvement strategy may already be having a positive effect: evidence based on health risk assessment

Aiming to investigate the health risk impact of PM2.5 pollution on a heavily populated province of China. The exposure response function was used to assess the health risk of PM2.5 pollution. Results shows that the total number of premature deaths and diseases related to PM2.5 pollution in Shandong might reach 159.8 thousand people based on the new WHO (2021) standards. The health effects of PM2.5 pollution were more severe in men than in women. Five of the 16 cities in Shandong had higher health risks caused by PM2.5 pollution, including LinYi, HeZe, JiNing, JiNan, and WeiFang. PM2.5 pollution resulted in nearly 7.4 billions dollars in healthy economic cost, which accounted for 0.57% of GDP in Shandong in 2021. HeZe, LiaoCheng, ZaoZhuang, and LinYi were the cities where the health economic loss was more than 1% of the local GDP, accounted for 1.30, 1.26, 1.08, and 1.04%. Although the more rigorous assessment criteria, the baseline concentration was lowered by 30 μg/m3 compared to our previous study, there was no significant increase in health risks and economic losses. China's air quality improvement strategy may already be having a positive effect.

Green-blue space exposure changes and impact on individual-level well-being and mental health: a population-wide dynamic longitudinal panel study with linked survey data

Background

Cross-sectional evidence suggests that living near green and blue spaces benefits mental health; longitudinal evidence is limited.

Objectives

To quantify the impact of changes in green and blue spaces on common mental health disorders, well-being and health service use.

Design

A retrospective, dynamic longitudinal panel study.

Setting

Wales, UK.

Participants

An e-cohort comprising 99,682,902 observations of 2,801,483 adults (≥ 16 years) registered with a general practice in Wales (2008-2019). A 5312-strong 'National Survey for Wales (NSW) subgroup' was surveyed on well-being and visits to green and blue spaces.

Main outcome measures

Common mental health disorders, general practice records; subjective well-being, Warwick-Edinburgh Mental Well-being Scale.

Data sources

Common mental health disorder and use of general practice services were extracted quarterly from the Welsh Longitudinal General Practice Dataset. Annual ambient greenness exposure, enhanced vegetation index and access to green and blue spaces (2018) from planning and satellite data. Data were linked within the Secure Anonymised Information Linkage Databank.

Methods

Multilevel regression models examined associations between exposure to green and blue spaces and common mental health disorders and use of general practice. For the National Survey for Wales subgroup, generalised linear models examined associations between exposure to green and blue spaces and subjective well-being and common mental health disorders.

Results and conclusions

Our longitudinal analyses found no evidence that changes in green and blue spaces through time impacted on common mental health disorders. However, time-aggregated exposure to green and blue spaces contrasting differences between people were associated with subsequent common mental health disorders. Similarly, our cross-sectional findings add to growing evidence that residential green and blue spaces and visits are associated with well-being benefits: Greater ambient greenness (+ 1 enhanced vegetation index) was associated with lower likelihood of subsequently seeking care for a common mental health disorder [adjusted odds ratio (AOR) 0.80, 95% confidence interval, (CI) 0.80 to 0.81] and with well-being with a U-shaped relationship [Warwick-Edinburgh Mental Well-being Scale; enhanced vegetation index beta (adjusted) -10.15, 95% CI -17.13 to -3.17; EVI2 beta (quadratic term; adj.) 12.49, 95% CI 3.02 to 21.97]. Those who used green and blue spaces for leisure reported better well-being, with diminishing extra benefit with increasing time (Warwick-Edinburgh Mental Well-being Scale: time outdoors (hours) beta 0.88, 95% CI 0.53 to 1.24, time outdoors2 beta -0.06, 95% CI -0.11 to -0.01) and had 4% lower odds of seeking help for common mental health disorders (AOR 0.96, 95% CI 0.93 to 0.99). Those in urban areas benefited most from greater access to green and blue spaces (AOR 0.89, 95% CI 0.89 to 0.89). Those in material deprivation benefited most from leisure time outdoors (until approximately four hours per week; Warwick-Edinburgh Mental Well-being Scale: time outdoors × in material deprivation: 1.41, 95% CI 0.39 to 2.43; time outdoors2 × in material deprivation -0.18, 95% CI -0.33 to -0.04) although well-being remained generally lower.

Limitations

Longitudinal analyses were restricted by high baseline levels and limited temporal variation in ambient greenness in Wales. Changes in access to green and blue spaces could not be captured annually due to technical issues with national-level planning datasets.

Future work

Further analyses could investigate mental health impacts in population subgroups potentially most sensitive to local changes in access to specific types of green and blue spaces. Deriving green and blue spaces changes from planning data is needed to overcome temporal uncertainties.

Funding

This project was funded by the National Institute for Health and Care Research (NIHR) Public Health Research programme (Project number 16/07/07) and will be published in full in Public Health Research; Vol. 11, No. 10. Sarah Rodgers is part-funded by the NIHR Applied Research Collaboration North West Coast.

Air pollutant dispersion around high-rise building cluster forms: the case of Port City, Colombo, Sri Lanka

Air quality in dense urban environments is a growing concern, especially in rapidly developing cities. In the face of growing traffic associated with urbanisation, there is evidence for high levels of pollutant concentration at street level which is influenced by building forms. In this paper, we examine the potential effects of high-rise, cluster developments permitted by the local planning authorities in the newly established Port City development in Colombo, Sri Lanka. We designed possible building forms based on specific guidelines for the development in terms of plot coverage, floor area ratio, and maximum height. The three-dimensional building clusters were simulated using the RANS RNG k-epsilon turbulence model, to determine pollutant dispersion of a complex street formation in a high-dense high-rise building cluster, within the development and the surrounding context (existing Colombo). Results show that while increased porosity within the built fabric facilitates better pollution dispersion, a low correlation was seen between wind velocity and pollution concentration, especially in deep narrow high-rise canyons. Dispersion patterns at street level and at the urban canopy differed with each built form and are dependent on each canyon geometry. Thus, the study highlights the need for building regulations to take a holistic approach to capture the various elements of a complex urban cluster rather than the current two-dimensional parameters proposed for Port City, Colombo.

Efficacy assessment of green-blue nature-based solutions against environmental heat mitigation

Nature-based solutions (NBS) such as green (vegetation) and blue (waterbodies) infrastructure are being promoted as cost-effective and sustainable strategies for managing the heatwaves risks, but long-term monitoring evidence is needed to support their implementation. This work aims to conduct a comparative assessment of the cooling efficiency of green (woodland and grassland) and blue (waterbody) NBS in contrast to a built-up area. Over a year of continuous fixed monitoring showed that the average daily maximum temperatures at NBS locations were 2-3 °C (up-to 15%) lower than the built-up area. Woodland showed the maximum temperature reduction in almost all seasons, followed by waterbody and grassland. NBS performed the best during the summers, peak sunshine, and heatwave hours (up to ∼ 6 °C cooler than built-up area). Using an e-bike for mobile monitoring, the areas where green-blue NBS were combined showed the highest spatial cooling extent, followed by waterbody, woodland, and grassland areas. The database generated can validate city-scale environmental models and assist city planners to incorporate NBS into urban dwellings based on the opportunity, need and scope, aligning with Sustainable Development Goals 11 (sustainable cities and communities) and 13 (climate action).

Modeling and exploring the coordination relationship between green infrastructure and land use eco-efficiency: an urban agglomeration perspective

In limited land space, improving the construction of infrastructure with ecological services can help to achieve the goal of promoting land use eco-efficiency (LUEE). In view of this, this study constructed interactive coordination relationship model of green infrastructure (GI) and LUEE that involves entropy method model, super-efficiency slack-based measure (SBM) model with undesirable outputs, and coupling coordination degree model. The interactive coordination relationship model can help to study and reveal the mechanisms of interaction and the coordination relationship between GI and LUEE from a land benefit and ecological perspective. We took the Beijing-Tianjin-Hebei urban agglomeration as the study area. The results showed that the assessment results of GI showed a decreasing trend from 2000 to 2020. LUEE in different cities displayed obvious variability with efficiency values ranging from 0.5666 to 2.4437. The relationship between GI and LUEE is in the stage of uncoordinated development in 53.8% of cities, mainly concentrated in the eastern and southern parts of the study area. The unnatural human activities are the critical factors affecting interactive coupling coordination degree of LUEE and GI. It is clarified that the level of coordination relationship of the two can be used as an important indicator to judge the sustainable development of urban agglomerations. Intensive use of land, optimal connection of geographic information, and localization of policies would help improve the balance and coordination between the two. This study provides interesting research ideas and novel modeling approaches for the study of green and sustainable development of urban agglomerations.

The heterogeneity-diversity-system performance nexus

Ever-growing human population and nutritional demands, supply chain disruptions, and advancing climate change have led to the realization that changes in diversity and system performance are intimately linked. Moreover, diversity and system performance depend on heterogeneity. Mitigating changes in system performance and promoting sustainable living conditions requires transformative decisions. Here, we introduce the heterogeneity-diversity-system performance (HDP) nexus as the conceptual basis upon which to formulate transformative decisions. We suggest that managing the heterogeneity of systems will best allow diversity to provide multiple benefits to people. Based on ecological theory, we pose that the HDP nexus is broadly applicable across systems, disciplines, and sectors, and should thus be considered in future decision making as a way to have a more sustainable global future.

Spatial and temporal coupling characteristics of industrial structure optimization and air quality in Chinese cities and multi-scale driver analysis

This paper takes the panel data of 283 prefecture-level cities in China from 2011 to 2020 as the research sample, measures the comprehensive index of industrial structure optimization and air quality by using GRA-TOPSIS comprehensive evaluation method, explores the spatial and temporal divergence characteristics of industrial structure optimization and air quality and the spatial and temporal evolution pattern of coupled and coordinated development by using ArcGIS spatial analysis and coupled coordination degree model, and analyzes the driving factors of coupled coordination degree of industrial structure optimization and air quality by combining multi-scale geographically weighted regression model. The study found the following: (1) The overall level of China's urban industrial structure is low, and shows an obvious eastern > central > western decreasing trend; urban air quality has a strong spatial clustering and spatial locking effect. (2) During the study period, the coupling coordination degree of industrial structure optimization and air quality showed an inverted "W" shape fluctuation from 2011 to 2020. The coupling degree and coupling coordination degree in 2020 were both higher than that in 2011, and most cities were in the run-in stage and moderate coordination stage. (3) There is a consistency in the temporal evolution trend and spatial evolution pattern of industrial structure optimization and air quality coupling degree and coupling coordination degree. (4) The driving factors are ranked according to the scale of action: public transportation intensity > population density > government intervention > GDP per capita > industrialization level. At present, China is in a critical period of promoting high-quality development by ecological civilization, and it is recommended to optimize regional industrial structure, improve urban air quality, and promote coordinated urban development.

Socio-demographic and neighbourhood factors influencing urban green space use and development at home: A population-based survey in Accra, Ghana

In Sub-Saharan Africa and other developing regions, there has been very little systematic attempt to document the uses and perceived health benefits of urban green spaces in cities and the factors influencing usage. We therefore sought to establish the availability, accessibility and use of urban green spaces, and the perceived health benefits in an African population. We also ascertained the factors influencing use and development of green spaces at home. A population-based survey was conducted in Accra, the capital city of Ghana, spanning 11 Municipal and 3 Sub-Metropolitan areas. Multivariable binary logistic regression adjusting for potential confounders was used to establish the association between green space use and development at home, and socio-demographic, neighbourhood and health factors. Odds ratios and their corresponding 95% confidence intervals were estimated from the models. Several socio-demographic (gender, age, marital status, occupation, ethnicity, religion) and district-level (population density, income level, neighbourhood greenness) factors were associated with use of green spaces and development of green spaces at home in Accra. Residents who were worried about depletion of green spaces in their community were more likely to develop green spaces at home. In neighbourhoods with moderate and high level of greenness, residents were less likely to develop green spaces at home. Five-percent and 47% of green space users in Accra reported witnessing an improvement in their physical and mental health, respectively, from use of green spaces. The study findings can inform policy action for promoting use and development of green spaces in African cities and for mitigating depletion and degradation of the limited urban greenery.

Gene-environment interaction in the association of residential greenness and 25(OH) vitamin D

There is increasing awareness for beneficial health effects of green space surrounding the home, but the underlying mechanisms are not yet fully understood and challenging to study given the correlation with other exposures. Here, the association of residential greenness and vitamin D including a gene-environment interaction is investigated. 25-hydroxyvitamin D (25(OH)D) was measured by electrochemiluminescence at ages 10 and 15 years in participants of two German birth cohorts GINIplus and LISA. Greenness was measured using the Landsat-derived Normalized Difference Vegetation Index (NDVI) in a 500 m buffer surrounding the home. Linear and logistic regression models were applied at both time points adjusted for several covariates (N_10Y = 2,504, N_15Y = 2,613). In additional analyses vitamin D-related genes, physical activity, time spent outdoors, supplements, and measurement season were investigated as potential confounders or effect modifiers. A 1.5-SD increase in NDVI was significantly associated with increased 25(OH)D values at ages 10 and 15 years (β_10y = 2.41 nmol/l, p=<0.01; β_15y = 2.03 nmol/l, p = 0.02). In stratified analyses, the associations were not seen in participants spending more than 5 h/day outside in summer, having a high physical activity level, taking supplements, or being examined during the winter season. In a subset (n = 1,732) with genetic data, a significant gene-environment interaction of NDVI with CYP2R1, an upstream gene in 25(OH)D synthesis, was observed at age 10 years. When investigating 25(OH)D sufficiency, defined as values above 50 nmol/l, a 1.5-SD increase in NDVI was associated with significantly higher odds of having sufficient 25 (OH)D levels at age 10 years (OR = 1.48, 1.19-1.83). In conclusion, robust associations between residential greenness and 25 (OH)D levels were observed in children and adolescents independent of other confounders and additionally supported by the presence of a gene-environment interaction. Effects of NDVI were stronger in those having lower vitamin D levels at age 10 years due to their covariate profile or genetically lower 25(OH)D synthesis.

Why might urban tree canopy reduce dementia risk? A causal mediation analysis of 109,688 adults with 11 years of hospital and mortality records

Urban tree canopy is associated with lower dementia risk, but no mediation analysis has been attempted to reveal potential mechanisms. We examined 3,639 dementia diagnoses in 109,688 participants of the Sax Institute's 45 and Up Study. Adjusted models indicated ≥20% tree canopy lowered the odds of developing dementia by 14% over 11 years (Odds Ratio = 0.86, 95%CI = 0.79-0.93). Association between tree canopy and dementia was partially mediated by physical activity (4.5%) and absences of psychological distress (5.7%), social support (2.9%), sleep duration (2.3%) and diabetes (1.8%). Social loneliness and absence of heart disease or hypertension did not mediate the tree canopy-dementia association.

A precision environmental health approach to prevention of human disease

Human health is determined by the interaction of our environment with the genome, epigenome, and microbiome, which shape the transcriptomic, proteomic, and metabolomic landscape of cells and tissues. Precision environmental health is an emerging field leveraging environmental and system-level ('omic) data to understand underlying environmental causes of disease, identify biomarkers of exposure and response, and develop new prevention and intervention strategies. In this article we provide real-life illustrations of the utility of precision environmental health approaches, identify current challenges in the field, and outline new opportunities to promote health through a precision environmental health framework.

The association between residential greenness and hearing impairment

Growing evidence shows that residential greenness is beneficial for various health outcomes, but the link between residential greenness and hearing impairment has not been explored. We aimed to explore the link between residential greenness and hearing impairment using baseline data from the UK Biobank. We used data from 107,516 participants between the ages of 40 and 69 years in the UK Biobank from 2006 to 2010. The normalized difference vegetation index (NDVI) was used to measure the residential greenness. We defined hearing impairment using the digital triplet test. Logistic regression models were conducted to examine the association of residential greenness with hearing impairment. Each interquartile increment in NDVI was associated with 19% lower odds of hearing impairment (odds ratio, OR 0.81; 95% confidence interval, 95% CI 0.79-0.83). Compared with participants in the first NDVI quartile, those in the second, third, and fourth NDVI quartiles had lower odds of hearing impairment (OR 0.69, 95% CI 0.65-0.73 for the second; OR 0.76, 95% CI 0.72-0.81 for the third; OR 0.68, 95% CI 0.65-0.72 for the fourth). Age and Townsend deprivation index showed moderating effects on this association. Our findings showed a negative association between residential greenness and hearing impairment, which might provide potential value for developing cost-effective greenness design and configuration interventions to reduce the risk of hearing impairment.

Associations between Residential Greenspace and Fecundability in a North American Preconception Cohort Study

BACKGROUND

Residential green space can have positive physiological effects on human health through various mechanisms, including reducing stress and/or depression or facilitating physical activity. Although green space has been consistently associated with improved birth outcomes in several studies, there has been limited study of its effect on other reproductive outcomes, including fertility.

OBJECTIVE

We examined associations between residential green space and fecundability, the per-cycle probability of conception.

METHODS

We analyzed data from 8,563 female participants enrolled between 2013 and 2019 in Pregnancy Study Online (PRESTO), a prospective preconception cohort study of North American couples attempting conception. Participants completed a baseline questionnaire on sociodemographic, behavioral, and reproductive factors, and bimonthly follow-up questionnaires for up to 12 months to ascertain pregnancies. Using geocoded addresses, we calculated residential green space exposure using the Normalized Difference Vegetation Index (NDVI) within 50-, 100-, 250-, and 500 -m buffers across multiple temporal scales: annual maximum, seasonal maximum, and seasonal mean. We used proportional probabilities regression models to estimate fecundability ratios (FRs), adjusting for sociodemographic, behavioral, and neighborhood characteristics. We also evaluated the extent to which associations were mediated by reductions in perceived stress or depressive symptoms and increased physical activity.

RESULTS

When comparing the highest (≥ 0.8 ) with the lowest (< 0.2 ) NDVI exposures within 50 m , we observed positive associations in the annual maximum NDVI [FR: 1.33; 95% confidence interval (CI): 1.06, 1.67] and seasonal maximum NDVI (FR: 1.19; 95% CI: 1.00, 1.41) models, but little association in the seasonal mean NDVI models (FR: 0.98; 95% CI: 0.73, 1.30). Restricted cubic splines showed evidence of nonlinearity in this association. Results were similar across buffer distances. Perceived stress, depressive symptoms, and physical activity explained ≤ 5 : 0 % of mediation across all NDVI metrics.

DISCUSSION

In this cohort, greater residential green space was associated with a modest increase in fecundability. https://doi.org/10.1289/EHP10648.

Interventions for improving indoor and outdoor air quality in and around schools

Students spend nearly one third of their typical day in the school environment, where they may be exposed to harmful air pollutants. A consolidated knowledge base of interventions to reduce this exposure is required for making informed decisions on their implementation and wider uptake. We attempt to fill this knowledge gap by synthesising the existing scientific literature on different school-based air pollution exposure interventions, their efficiency, suitability, and limitations. We assessed technological (air purifiers, HVAC - Heating Ventilation and Air Conditioning etc.), behavioural, physical barriers, structural, school-commute and policy and regulatory interventions. Studies suggest that the removal efficiency of air purifiers for PM_2.5, PM₁₀, PM₁ and BC can be up to 57 %, 34 %, 70 % and 58 %, respectively, depending on the air purification technology compared with control levels in classroom. The HVAC system combined with high efficiency filters has BC, PM₁₀ and PM_2.5 removal efficiency up to 97 %, 34 % and 30 %, respectively. Citizen science campaigns are effective in reducing the indoor air pollutants' exposure up to 94 %. The concentration of PM₁₀, NO₂, O₃, BC and PNC can be reduced by up to 60 %, 59 %, 16 %, 63 % and 77 %, respectively as compared to control conditions, by installing green infrastructure (GI) as a physical barrier. School commute interventions can reduce NO₂ concentration by up to 23 %. The in-cabin concentration reduction of up to 77 % for PM_2.5, 43 % for PNC, 89 % for BC, 74 % for PM₁₀ and 75 % for NO₂, along with 94 % reduction in tailpipe emission of total particles, can be achieved using clean fuels and retrofits. No stand-alone method is found as the absolute solution for controlling pollutants exposure, their combined application can be effective in most of the scenarios. More research is needed on assessing combined interventions, and their operational synchronisation for getting the optimum results.

The Effectiveness of Local Governments' Policies in Response to Climate Change: An Evaluation of Structure Planning in Arden, Melbourne

It is widely acknowledged that climate change has caused serious environmental issues, including drought, bushfires, floods, and heatwaves, and urban sustainability is currently seriously threatened as a result. Arden is one of the key urban regeneration areas set to experience dramatic residential changes under Melbourne's development blueprint within the next 20 years. The Arden Structure Plan (2022) outlines specific implementation steps but does not go into detail about the strategies and tactics used to address climate change and urban sustainability. Therefore, there are still problems with the plan, including a lack of information and time-bound development targets, ambiguous public engagement, little focus on urban crime, and insufficient climate change adaptation measures. The plan also considers affordable housing, a mixed-use development pattern that will significantly decrease environmental harm, and active transportation options, primarily walking and bicycling. Considering climate change, this plan will make Arden a suitable location for population growth. This paper aims to evaluate the Arden Structure Plan and make recommendations on how to improve the plan's urban sustainability and climate change considerations. Furthermore, it provides guidance on whether Arden is a suitable location for Melbourne's population growth in light of the climate change impacts anticipated to occur by 2100.

Urban Air Pollution and Greenness in Relation to Public Health

Background

Air pollution is the result of economic growth and urbanization. Air pollution has been progressively recognized as a serious problem for cities, through widespread effects on health and well-being. There is less concern from stakeholders about greenness and air pollution mitigating factors in an urban area. This research targeted to indicate the spatial dissemination of greenery, air quality levels (PM_2.5, PM₁₀, CO₂, and AQI), and exposure to air quality-related health risks for the people in the urban area.

Method

The data were collected by measuring air quality at transportation stations and manufacturing industries with Air visual pro, then observing and mapping greenness in the city within the administrative boundary by GIS (street greenery, forest, availability of greenness in the manufacturing industry), and lastly questionnaire and interview were employed for air quality-related health issues. Then, the air quality data were analyzed by using USAQI standards and health messages. Both quantitative and qualitative research approach had employed to explore air pollution levels, availability of greenness, and air quality-related health issues. Moreover, Health questionnaires and greenness were correlated with air quality levels by a simple linear regression model.

Result

The result indicated that there was unhealthy air quality in the transportation and manufacturing industries. The measured air quality showed in a range of 50.13-96.84 μg/m³ of PM_2.5, 645-1764 ppm of CO_2, and 137-179 Air quality index (AQI). The highest mean of PM_2.5 and air quality concentrations at Addis Ababa transportation stations and manufacturing sites ranged between 63.46 and 104.45 μg/m³ and 179-326, respectively. It was observed with less street greenery and greenness available in residential, commercial areas, and manufacturing industries. The pollution level was beyond the limit of WHO standards. The result has shown a health risk to the public in the city, particularly for drivers, street vendors, and manufacturing industry employees. Among 480 respondents, 57.92% experienced health risks due to air pollution by medical evidence.

Conclusion

High health risks due to industries and old motor vehicles in the city need to be reduced by introducing policies and strategies for low-carbon, minimizing traveling distance, encouraging high occupancy vehicles, and promoting a green legacy in the street network and green building.

Leafier Communities, Healthier Hearts: An Australian Cohort Study of 104,725 Adults Tracking Cardiovascular Events and Mortality Across 10 Years of Linked Health Data

OBJECTIVE

Green space reduces cardiovascular disease (CVD) risk, but few studies examine what types of green space matter, which is an important consideration as cities densify and apartments become more common.

METHOD

Participants were 86,727 in houses and 17,998 in apartments from the 45 and Up Study (Sax Institute) baseline survey with 10 years of linked hospitalisation and death data used to define: (i) all-cause; and (ii) CVD-mortality; (iii) fatal and non-fatal CVD events; and (iv) acute myocardial infarction (AMI). Associations with total green space, tree canopy cover and open grass within 1.6 km buffers were assessed using survival analysis adjusted for potential confounders.

RESULTS

Mean percentage green space indicators were all higher among participants in houses than in apartments. Among residents of houses, a 10% increase in total green space was associated with reduced risk of CVD mortality (HR 0.97, 95%CI 0.95-1.00). A 10% increase in tree canopy cover was associated with reduced risks of all-cause mortality (HR 0.97, 95%CI 0.95-0.99), CVD mortality (HR 0.96, 95%CI 0.93-0.98), and fatal or non-fatal AMI (HR 0.93, 95%CI 0.89-0.96). In contrast, a 10% increase in open grass was associated with an increased risk of fatal or non-fatal AMI (HR 1.15, 95%CI 1.09-1.20) in residents of houses. Among residents of apartments, a 10% increase in total green space was associated with increased risk of all-cause mortality (HR 1.04, 95%CI 1.00-1.08) and CVD mortality (HR 1.03, 95%CI 1.00-1.08).

CONCLUSIONS

Urban reforestation may be a population-level intervention to protect cardiovascular health, especially for people living in houses. The intersection of urban greening and cardiovascular health among residents of apartments warrants further investigation.

Need and Interest in Nature Prescriptions to Protect Cardiovascular and Mental Health: A Nationally-Representative Study With Insights for Future Randomised Trials

OBJECTIVE

"Nature prescriptions" are increasingly being adopted by health sectors as an adjunct to standard care to attend to health and social needs. We investigated levels of need and interest in nature prescriptions in adults with cardiovascular diseases, psychological distress and concomitants (e.g. physical inactivity, sedentary behaviour, obesity, loneliness, burn-out).

METHODS

A nationally-representative survey of 3,319 adults across all states and territories of Australia was completed in February 2021 (response 84.0%). Participants were classified across 15 target groups using validated health indicators and surveyed on (1) time and frequency of visits to green and blue spaces (nature spaces), (2) interest in a nature prescription, and (3) potential confounders (e.g. age, income). Analyses were done using weighted logistic regressions.

RESULTS

The sample was 50.5% female, 52.0% were aged ≥45 years, 15.2% were living alone and 19.3% were born overseas in non-English-speaking countries. Two-thirds of the sample spent 2 hours or more a week in nature, but these levels were generally lower in target groups (e.g. 57.7% in adults with type 2 diabetes). Most participants (81.9%) were interested in a nature prescription, even among those spending fewer than 2 hours a week in nature (76.4%). For example, 2 hours a week or more in nature was lowest among sedentary adults (36.9%) yet interest in nature prescriptions in this group was still high (74.0%). Lower levels of nature contact in target groups was not explained by differences in access to or preference for local nature spaces.

CONCLUSIONS

High levels of interest in nature prescriptions amid low levels of nature contact in many target health groups provides impetus for developing randomised trials of interventions that enable people to spend more time in nature. These findings can inform intervention co-design processes with a wide range of community stakeholders, end-users in target health groups, and the health professionals who support them.

Associations and pathways between residential greenness and metabolic syndromes in Fujian Province

Background

Greenness exposure is beneficial to human health, but its potential mechanisms through which the risk for metabolic syndrome (MetS) could be reduced have been poorly studied. We aimed to estimate the greenness-MetS association in southeast China and investigate the independent and joint mediation effects of physical activity (PA), body mass index (BMI), and air pollutants on the association.

Methods

A cross-sectional study was conducted among the 38,288 adults based on the Fujian Behavior and Disease Surveillance (FBDS), established in 2018. MetS was defined as the presence of three or more of the five components: abdominal obesity, elevated triglyceride, reduced high-density lipoprotein cholesterol (HDL-C), high blood pressure, and elevated fasting glucose. The residential greenness exposure was measured as the 3-year mean values of the normalized difference vegetation index (NDVI) and enhanced vegetation index (EVI) within the 250, 500, and 1,000 meters (m) buffer zones around the residential address of each participant. Logistic regression models were used to estimate the greenness-MetS association. The causal mediation analysis was used to estimate the independent and joint mediation effects of PA, BMI, particulate matter with an aerodynamic diameter of 2.5 μm (PM_2.5), particulate matter with an aerodynamic diameter ≤ 10 μm (PM₁₀), nitrogen dioxide (NO₂), and sulfur dioxide (SO₂).

Results

Each interquartile range (IQR) increase in greenness was associated with a decrease of 13% (OR = 0.87 [95%CI: 0.83, 0.92] for NDVI_500m and OR = 0.87 [95%CI: 0.82, 0.91] for EVI_500m) in MetS risk after adjusting for covariates. This association was stronger in those aged < 60 years (e.g., OR = 0.86 [95%CI: 0.81, 0.92] for NDVI_500m), males (e.g., OR = 0.73 [95%CI: 0.67, 0.80] for NDVI_500m), having an educational level of primary school or above (OR = 0.81 [95%CI: 0.74, 0.89] for NDVI_500m), married/cohabitation (OR = 0.86 [95%CI: 0.81, 0.91] for NDVI_500m), businessman (OR = 0.82 [95%CI: 0.68, 0.99] for NDVI_500m), other laborers (OR = 0.77 [95%CI: 0.68, 0.88] for NDVI_500m), and non-smokers (OR = 0.77 [95%CI: 0.70, 0.85] for NDVI_500m). The joint effect of all six mediators mediated about 48.1% and 44.6% of the total effect of NDVI_500m and EVI_500m on the MetS risk, respectively. Among them, BMI showed the strongest independent mediation effect (25.0% for NDVI_500m), followed by NO₂ and PM₁₀.

Conclusion

Exposure to residential greenness was associated with a decreased risk for MetS. PA, BMI, and the four air pollutants jointly interpreted nearly half of the mediation effects on the greenness-MetS association.

Green spaces, especially nearby forest, may reduce the SARS-CoV-2 infection rate: A nationwide study in the United States

The coronavirus pandemic is an ongoing global crisis that has profoundly harmed public health. Although studies found exposure to green spaces can provide multiple health benefits, the relationship between exposure to green spaces and the SARS-CoV-2 infection rate is unclear. This is a critical knowledge gap for research and practice. In this study, we examined the relationship between total green space, seven types of green space, and a year of SARS-CoV-2 infection data across 3,108 counties in the contiguous United States, after controlling for spatial autocorrelation and multiple types of covariates. First, we examined the association between total green space and SARS-CoV-2 infection rate. Next, we examined the association between different types of green space and SARS-CoV-2 infection rate. Then, we examined forest-infection rate association across five time periods and five urbanicity levels. Lastly, we examined the association between infection rate and population-weighted exposure to forest at varying buffer distances (100 m to 4 km). We found that total green space was negative associated with the SARS-CoV-2 infection rate. Furthermore, two forest variables (forest outside park and forest inside park) had the strongest negative association with the infection rate, while open space variables had mixed associations with the infection rate. Forest outside park was more effective than forest inside park. The optimal buffer distances associated with lowest infection rate are within 1,200 m for forest outside park and within 600 m for forest inside park. Altogether, the findings suggest that green spaces, especially nearby forest, may significantly mitigate risk of SARS-CoV-2 infection.

Cost and Quality Optimization Taguchi Design with Grey Relational Analysis of Halloysite Nanotube Hybrid Composite: CNC Machine Manufacturing

Researchers who work on manufacturing hybrid composites have significant concerns about holistically optimizing more than one performance characteristic, as in the case of cost and quality optimization. They usually trade off one for the other. Hence, this study employed statistical tools and grey relational analyses (GRA) design to model and optimize the surface roughness and cutting force of Computer Numerical Control (CNC) machine settings to manufacture halloysite nanotube hybrid composite. In this paper, the GRA was able to address the multiple optimization complications by producing 0.6 mm depth of cut, 1500 rpm spindle speed, and 40 mmpm feed rate as the CNC machine settings for high-quality and low-cost hybrid composite. It was noticed that the mathematical and interaction modeling of surface roughness, cutting force, and grey relational grade (GRG) allowed different CNC machines to manufacture hybrid composites. This can assist researchers and production engineers of CNC machines. Variance analysis and delta statistical characteristics revealed that the depth of a cut is the most significant machine setting, with a contribution of 49.12%. This paper outlines the possible CNC machine settings for high-quality composite manufacturing. In future studies, it is recommended for researchers in the field of CNC machine manufacturing to consider the modeling analysis aspect of the optimization, which comprehensively provides the opportunity for the adjustment of CNC machines for better material performance, which has been lacking in the literature.

Green space and loneliness: A systematic review with theoretical and methodological guidance for future research

Persistent loneliness troubles people across the life span, with prevalence as high as 61 % in some groups. Urban greening may help to reduce the population health impacts of loneliness and its concomitants, such as hopelessness and despair. However, the literature lacks both a critical appraisal of extant evidence and a conceptual model to explain how green space would work as a structural intervention. Both are needed to guide decision making and further research. We conducted a systematic review of quantitative studies testing associations between green space and loneliness, searching seven databases. Twenty two studies were identified by 25/01/2022. Most of the studies were conducted in high-income countries and fifteen (68 %) had cross-sectional designs. Green space was measured inconsistently using either objective or subjective indicators. Few studies examined specific green space types or qualities. The majority of studies measured general loneliness (e.g. using the UCLA loneliness scale). Different types of loneliness (social, emotional, existential) were not analysed. Of 132 associations, 88 (66.6 %) indicated potential protection from green space against loneliness, with 44 (33.3 %) reaching statistical significance (p < 0.05). We integrated these findings with evidence from qualitative studies to elaborate and extend the existing pathway domain model linking green space and health. These elaborations and extensions acknowledge the following: (a) different types of green space have implications for different types of loneliness; (b) multilevel circumstances influence the likelihood a person will benefit or suffer harm from green space; (c) personal, relational, and collective processes operate within different domains of pathways linking green space with loneliness and its concomitants; (d) loneliness and its concomitants are explicitly positioned as mediators within the broader causal system that links green space with health and wellbeing. This review and model provide guidance for decision making and further epidemiological research on green space and loneliness.

Endogenous Development Models and Paths Selection of Rural Revitalization from the Perspective of Ecological Environment Advantages: A Case Study of Nanshi Village, China

This article aims to discuss how to give full play to the comparative advantages of the rural ecological environment and realize the endogenous development of rural society and economy in China. First, based on the ecological economy theory of "lucid waters and lush mountains are golden and silver mountains" (the "two mountains" theory), we integrated the theories and methods of ecology, economics, and geography disciplines to examine the transformation of "ecological advantages" into "economic development" from a comprehensive perspective. Second, based on the matching relationship between the division of major function zones and the classification of ecological services, we creatively constructed a theoretical framework for the endogenous development of rural areas. Third, accounting indicators and methods for rural ecological products' biophysical quantity and monetary value are established. Finally, we conducted an empirical study of Nanshi Village in central China as a case. The results showed that: The benefits provided by ecosystems to the development of human society would be underestimated if it is measured only by the provisioning services; the per capita Gross Ecosystem Product (GEP) of the case area was three times the per capita disposable income of rural permanent residents in the same period. Taking advantage of the rural ecological environment to promote the actual transformation of the potential value of ecological products is the feasible path for rural revitalization. One of the implications of this study is that it links the rural ecological and environmental advantages with social and economic development from the perspective of ecological economics and provides decision-making support for this case and other similar rural ecological industry revitalization practices.

Quantification of green infrastructure effects on airborne nanoparticles dispersion at an urban scale

Many dispersion models are available to simulate the mass concentrations of particulate matter in an urban environment. Still, fewer are capable of simulating the effect of green infrastructure (GI) on the airborne nanoparticles represented by total particle number concentration (ToNC). We developed an integrated approach capable of simulating the dispersion of airborne nanoparticles under the various scenarios of green infrastructure. We demonstrated the usefulness of this approach by simulating a high-resolution spatial (250 × 250 m) concentration of traffic-emitted airborne nanoparticles at an urban scale under eight GI urban planning scenarios: the base year 2015 (2015-Rl-GI); business-as-usual for 2039 (2039-BAU-GI); three hypothetical future scenarios with maximum possible coniferous (2039-HMax-Con), deciduous (2039-HMax-Dec) trees, and grassland (2039-HMax-Grl) over the available land; and three alternative future scenarios by considering coniferous (2039-HNR-Con), deciduous (2039-HNR-Dec) trees, and grassland (2039-HNR-Grl) around traffic lanes. We assessed both the parametric and structural uncertainties due to particle transformation processes (nucleation, coagulation and deposition) and uncertainty in particle number emission factors (PNEFs) on ToNC, respectively. We also simulated the combined impact of deposition and aerodynamic dispersion of GI on ToNC reduction. The annual average ToN emission (ToNE) reduced from 5.36 × 10²² (2015) to 2.84 × 10²¹ (2039) particles due to the UK's air quality plan in future. Parametric uncertainty due to variable PNEFs might cause variation in annual ToNC from -57% to +60%. However, structural uncertainties in ToNC, due to particle transformation processes were up to -12%, -11% and +0.14% for deposition, coagulation, and nucleation, respectively. The annual ToN deposition (ToND) and concentration were 28-4800 × 10¹⁹ particles and 3.94-19.10 × 10³ # cm^-3, respectively, depending on the percentage share of GI type and annual traffic emissions. Planting maximum coniferous trees (2039-HMax-Con) simulated maximum reduction in annual ToNC. Coniferous trees near traffic lanes (2039-HNR-Con) also found to be more effective to reduce annual ToNC.

Caregiver perceptions of neighbourhood green space quality, heavy traffic conditions, and asthma symptoms: Group-based trajectory modelling and multilevel longitudinal analysis of 9,589 Australian children

BACKGROUND

This study assessed the associations between changes in exposure to green space quality, heavy traffic conditions, and asthma symptoms among children.

METHODS

10-year cohort data of 9589 children, retrieved from the Longitudinal Study of Australian Children, were analysed. Caregiver-reported neighbourhood green space quality, heavy traffic conditions, and asthma symptoms were measured biennially. Group-based trajectory mixture models were used to develop trajectory groups, denoting different patterns of, or changes in, exposure to green space quality, heavy traffic conditions, and asthma symptoms across childhood. Multilevel multinomial logistic regression was used to identify factors associated with trajectory group membership and examine the confounders-adjusted associations between trajectory groups of green space quality, heavy traffic conditions, and asthma symptoms.

RESULTS

Four trajectory groups for each green space quality and heavy traffic conditions, and five trajectory groups for asthma symptoms were developed. Children in less disadvantaged areas were more likely to be in trajectory groups with exposure to quality green space, but less likely to be exposed to heavy neighbourhood traffic. Living in more remote areas was associated with the decreased likelihood to be in groups with exposure to both quality green space and heavy traffic conditions over time. Accumulation of exposure to quality green space across childhood was not found to be protective against asthma symptoms. However, children whose caregiver perceptions of heavy traffic conditions trended from low to moderate levels; or were consistently in high levels across childhood had a higher likelihood to be in trajectory groups with a higher risk of asthma symptoms.

CONCLUSION

Exposure to quality green space was not associated with the reduced risk of asthma symptoms. The accumulation of exposure to heavy traffic conditions increased the likelihood of asthma symptoms among children. Reducing the presence of heavy traffic in neighbourhoods might reduce the risk of childhood asthma.

Proposal and Efficacy of a Nurse-Led Pain Management Model for Neurointensive Care Based on the Precede-Proceed Model

Objective

This study's objective is to establish a nurse-led pain management model for neurointensive care based on the Precede-Proceed model to provide a theoretical basis for clinical pain management in neurointensive care. Methods. ICU nurses were randomly divided into a control group (giving conventional routine pain care) and an experimental group (managed pain based on the Precede-Proceed model). The nurses from the experimental group were trained in the Precede-Proceed-based management. The nurses then treated a total of 410 critically ill patients, and the patients were randomly divided into a control and an intervention group (205 cases/nursing group), and the data were prospectively recorded. Before and after the intervention, the pain assessment ability, discomfort level, satisfaction degree, usage of the analgesic drug, and the incidence of delirium of the patients from the two groups were evaluated. Nurses from both groups also assessed their knowledge of pain, attitude, and pain nursing behaviors using indicated self-designed questionnaires.

Results

Before the intervention, there was no statistical difference between the two groups of nurses in their baseline characteristics, pain knowledge, attitude, pain nursing behavior, and pain assessment ability for the patients. After the intervention, the nurses in the experimental group had better pain knowledge, attitude, pain nursing behavior, and pain assessment ability to patients than the nurses in the control group. Patients in the intervention group felt less discomfort, a higher satisfaction degree, reduced use of analgesics, and a lower incidence of delirium than patients in the control group. Conclusion. Pain management based on the Precede-Proceed model was beneficial in improving the care of neurointensive patients.

Beyond green environments: Multi-scale difference in human exposure to greenspace in China

Greenspace exposure metrics can allow for comparisons of green space supply across time, space, and population groups, and for inferring patterns of variation in opportunities for people to enjoy the health and recreational benefits of nearby green environments. A better understanding of greenspace exposure differences across various spatial scales is a critical requirement for lessening environmental health disparities. However, existing studies are typically limited to a single city or across selected cities, which severely limits the use of results in measuring systemic national and regional scale differences that might need policy at above individual city planning level. To close this knowledge gap, our study aims to provide a holistic assessment of multi-scale greenspace exposure across provinces, cities, counties, towns, and land parcels for the whole of China. We mapped the nationwide fractional greenspace coverage at 10 m with Sentinel-2 satellite imagery, and then modeled population-weighted greenspace exposure to examine variation of greenspace exposure across scales. Our results show a prominent scaling effect of greenspace exposure across multi-scale administrative divisions in China, suggesting, as expected, an increase in heterogeneity with finer spatial scales. We also identify an asymmetric pattern of the difference between greenspace exposure and greenspace coverage, across a geo-demographic demarcation boundary (i.e., along the Heihe-Tengchong Line). In general, the greenspace coverage rate will overestimate more realistic human exposure to greenspace in East China while underestimating in West China. We further found that, in China, more recently urbanized areas have much better greenspace exposure than older urban areas. Our study provides a spatially explicit greenspace exposure metric for discovering multi-scale greenspace exposure difference, which will enhance governments' capacity to quantify environmental justice, detect vulnerable greenspace exposure risk hotspots, prioritize greenspace management at the supra-city scale, and monitor the balance between greenspace supply and demand.

Impact of Different Combinations of Green Infrastructure Elements on Traffic-Related Pollutant Concentrations in Urban Areas

Urban air quality is a major problem for human health and green infrastructure (GI) is one of the potential mitigation measures used. However, the optimum GI design is still unclear. The purpose of this study is to provide some recommendation that could help in the design of the GI (mainly, the selection of locations and characteristics of trees and hedgerows). Aerodynamic and deposition effects of each vegetation element of different GI scenarios are investigated. Computational fluid dynamics (CFD) simulations of a wide set of GI scenarios in an idealized three-dimensional urban environment are performed. In conclusion, it was found that trees in the middle of the avenue (median strip) reduce street ventilation, and traffic-related pollutant concentrations increase, in particular for streets parallel to the wind. Trees in the sidewalks act as a barrier for pollutants emitted outside, specifically for a 45° wind direction. Regarding hedgerows, the most important effect on air quality is deposition and the effects of green walls and green roofs are limited to their proximity to the building surfaces.

Namares—A Surface Inventory and Intervention Assessment Model for Urban Resource Management

Densely built-up areas are challenged by reduced biodiversity, high volumes of runoff water, reduced evaporation, and heat accumulation. Such phenomena are associated with imperviousness and low, unsustainable utilisation of land and exterior building surfaces. Local authorities have multiple objectives when (re-)developing future-proof districts. Hence, exploiting local potentials to mitigate adverse anthropogenic effects and managing the resource of urban land/surfaces have become key priorities. Accordingly, a five-level hierarchy for a land-sensitive urban development strategy was derived. To support the operationalisation of the hierarchy, we present the model Namares, a highly resolved GIS-based approach to enable spatially explicit identification and techno-economic and environmental assessment of intervention measures for advantageous utilisation of available surfaces per land parcel. It uses existing data and covers the management of economic, natural, and technical resources. Nine intervention measures are implemented to identify potentials, estimate investments and annual costs, and assess the appeal of existing subsidies. The approach was applied to a case study redevelopment area in a large city in Germany. The results provide spatially explicit information on greening potentials, estimated investments, subsidy demand, and other quantified benefits. The case study results show the limited potential for additional unsealing of impervious surfaces by transforming ca. 10% of sealed ground surface area into new urban gardens. At the same time, up to 47% of roof and 30% of facade surfaces could be utilised for greening and energy harvesting. The approach enables a comprehensive localisation and quantitative assessment of intervention potentials to enhance decision support in land-sensitive urban development strategies.

Functional Data Analysis for the Detection of Outliers and Study of the Effects of the COVID-19 Pandemic on Air Quality: A Case Study in Gijón, Spain

Air pollution, especially at the ground level, poses a high risk for human health as it can have serious negative effects on the population of certain areas. The high variability of this type of data, which are affected by weather conditions and human activities, makes it difficult for conventional methods to precisely detect anomalous values or outliers. In this paper, classical analysis, statistical process control, and functional data analysis are compared for this purpose. The results obtained motivate the development of a new outlier detector based on the concept of functional directional outlyingness. The validation of this algorithm is perfomed on real air quality data from the city of Gijón, Spain, aiming to detect the proven reduction in NO2 levels during the COVID-19 lockdown in that city. Three more variables (SO2, PM10, and O3) are studied with this technique. The results demonstrate that functional data analysis outperforms the two other methods, and the proposed outlier detector is well suited for the accurate detection of outliers in data with high variability.