Urban Form, Air Pollution, and Health

Short-Term Relationship Between Air Pollution and Mortality from Respiratory and Cardiovascular Diseases in China, 2008-2020

Most existing epidemiological studies on the impact of air pollution on noncommunicable diseases have focused on urban areas, rather than nationwide studies that include rural areas. This study utilized a time-stratified case-crossover study that included deaths registered in the National Mortality Surveillance System from 2008 to 2020. Atmospheric particulate matter (PM10 and PM2.5), nitrogen dioxide (NO2), sulfur dioxide (SO2), and carbon monoxide (CO) were evaluated via the National Nested Air Quality Prediction Modeling System. Conditional logistic regression was used to assess the associations between short-term air pollution exposure and the risk of respiratory disease and cardiovascular disease (CVD) mortality. There were increases in the risk of respiratory diseases (0.12%, 0.10%, 0.10%, 0.05%, and 0.40%) and CVDs (0.08%, 0.07%, 0.03%, 0.02%, and 0.22%) for each 10 μg/m3 increase in the concentrations of PM10, PM2.5, NO2, and SO2, respectively, and for each 1 mg/m3 increase in the concentration of CO, which may be associated with the participants' characteristics. The results of these national analyses indicate that ambient air pollutants are significantly associated with increased risks of respiratory disease and CVD death in both urban and rural areas, which is critical for air pollution control, especially in low- and middle-income areas.

Higher population density is associated with worse air quality and related health outcomes in Tāmaki Makaurau

OBJECTIVES

To explore associations between population density, air pollution concentrations, and related health outcomes in Tāmaki Makaurau Auckland, Aotearoa New Zealand.

METHODS

Concentrations of nitrogen dioxide (NO2) and fine particulate matter (PM2.5) and associated health outcomes (premature mortality, cardiovascular and respiratory hospitalisations, and childhood asthma) were obtained from the Health and Air Pollution in New Zealand 2016 study. The possible mediating factors assessed were motor vehicle traffic, domestic fires, local industry, and green space.

RESULTS

Higher population density was associated with higher concentrations of NO2 (β: 0.18, p < 0.01) and PM2.5 (β: 0.04, p < 0.01). Adverse health outcomes related to NO2 and respiratory hospitalisations attributed to PM2.5 exposure increased incrementally with the density of urban areas. The mediating factor with the strongest effect was motor vehicle traffic.

CONCLUSIONS

Higher population density in Auckland is associated with worse air quality and related health outcomes. Motor vehicle traffic is the most important source of pollution and is highest in the most densely populated parts of the city.

IMPLICATIONS FOR PUBLIC HEALTH

Housing intensification in Auckland will likely increase ill health from air pollution unless steps are taken to reduce exposure to emissions from motor vehicles.

Association of urban green and blue space with accelerated ageing: A cohort Study in the UK Biobank

OBJECTIVE

We investigated the associations between urban green and blue spaces and the incidence of accelerated ageing, which have rarely been studied.

METHODS

Analyzed UK Biobank data (2006-2010) on 440,785 participants, focusing on urban green and blue space (UGBS). General linear models and logistics models assessed links between UGBS and accelerated ageing (Klemera-Doubal method, telomere length and frailty). Mediation analysis examined the role of pollution and other factors.

RESULTS

After controlling for random effects and various types of covariates, we found that 1) populations with higher levels of UGBS exposure are associated with accelerated ageing and slowing down; 2) UGBS has the greatest impact on accelerated ageing within a 1000-m street network buffer distance; 3) Participants living in heavily polluted areas should pay more attention to UGBS; 4) Intermediary analysis found that UGBS mainly accelerates aging by reducing harm, rather than affecting the population's ability to recover and build.

CONCLUSIONS

UGBS with a composite weighted score showed a better correlation with accelerated ageing than green spaces. Other factors such as gender, race and lifestyle also influence the impact of the environment on accelerated ageing.

Inequitable Spatial and Temporal Patterns in the Distribution of Multiple Environmental Risks and Benefits in Metro Vancouver

The urban environment impacts residents' health and well-being in many ways. Environmental benefits and risks may be interactively and inequitably distributed across different populations in cities, and these patterns may change over time. Here, we assess the spatial distribution of environmental risks and benefits in pairs, considering synergies and trade-offs, in an illustrative metropolitan area (Metro Vancouver) in Canada in the years 2006 and 2016. We classify census dissemination areas as sweet, sour, risky, or medium spots based on relative exposures for six environmental combinations: Walkability and NO2; heat stress and NO2; vegetation coverage and NO2; vegetation coverage and heat stress; walkability and accessibility to natural recreational areas; and heat stress and accessibility to natural recreational areas. We evaluate whether different population groups are disproportionately exposed to lower environmental quality based on linear regressions and other metrics. We find that while performance for individual environmental variables improved over the decade, considering their combinations, sweet spots became sweeter and sour spots became sourer. Residents with high material and social deprivation and visible minorities were disproportionately exposed to lower environmental quality in both years for most of the environmental combinations. Further, we find that these inequities were not improving over time for all groups: for instance, South Asian residents in the region faced higher disproportionate burdens or diminished access to benefits in 2016, as compared to 2006. Given these findings, we suggest considerations of cumulative exposure in prioritizing areas for intervention, targeting the sour and risky spots persistently experienced by overburdened populations.

A Review of Urban Planning Approaches to Reduce Air Pollution Exposures

PURPOSE OF REVIEW

With only 12% of the human population living in cities meeting the air quality standards set by the WHO guidelines, there is a critical need for coordinated strategies to meet the requirements of a healthy society. One pivotal mechanism for addressing societal expectations on air pollution and human health is to employ strategic modeling within the urban planning process. This review synthesizes research to inform coordinated strategies for a healthy society. Through strategic modeling in urban planning, we seek to uncover integrated solutions that mitigate air pollution, enhance public health, and create sustainable urban environments.

RECENT FINDINGS

Successful urban planning can help reduce air pollution by optimizing city design with regard to transportation systems. As one specific example, ventilation corridors i.e. aim to introduce natural wind into urban areas to improve thermal comfort and air quality, and they can be effective if well-designed and managed. However, physical barriers such as sound walls and vegetation must be carefully selected following design criteria with significant trade-offs that must be modeled quantitatively. These tradeoffs often involve balancing effectiveness, cost, aesthetics, and environmental impact. For instance, sound walls are highly effective at reducing noise, provide immediate impact, and are long-lasting. However, they are expensive to construct, visually unappealing, and may block views and sunlight. To address the costly issue of sound walls, a potential solution is implementing vegetation with a high leaf area index or leaf area density. This alternative is also an effective method for air pollution reduction with varying land-use potential. Ultimately, emission regulations are a key aspect of all such considerations. Given the broad range of developments, concerns, and considerations spanning city management, ventilation corridors, physical barriers, and transportation planning, this review aims to summarize the effect of a range of urban planning methods on air pollution considerations.

Sociodemographic inequalities in residential nighttime light pollution in urban Bulgaria: An environmental justice analysis

INTRODUCTION

Outdoor nighttime light (NTL) is a potential anthropogenic stressor in urban settings. While ecological studies have identified outdoor NTL exposure disparities, uncertainties remain about disparities in individual exposure levels, particularly in Europe.

AIM

To assess whether some populations are disproportionately affected by outdoor NTL at their residences in urban Bulgaria.

METHODS

We analyzed 2023 data from a representative cross-sectional survey of 4,270 adults from the five largest Bulgarian cities. Respondents' annual exposures to outdoor artificial nighttime luminance were measured using satellite imagery and assigned at their places of residence. We calculated the Gini coefficient as a descriptive NTL inequality measure. Associations between respondents' NTL exposure levels and sociodemographic characteristics were assessed by estimating quantile mixed regression models. Stratified regressions were fitted by gender and for each city.

RESULTS

We found moderate distributive NTL inequalities, as indicated by a Gini coefficient of 0.214. Regression analyses showed associations between greater NTL exposure and higher educational attainment. Respondents with incomes perceived as moderate experienced less NTL exposure at the 0.5 and 0.8 quantiles, while unemployed respondents experienced lower exposure at the 0.2 and 0.5 quantiles. We observed null associations for the elderly and non-Bulgarian ethnicities. Regardless of the quantile, greater population density was associated with higher NTL levels. Stratification by sex did not yield substantial differences in the associations. We observed notable city-specific heterogeneities in the associations, with differences in the magnitudes and directions of the associations and the NTL quantiles.

CONCLUSIONS

NTL exposures appeared to embody an environmental injustice dimension in Bulgaria. Our findings suggest that some sociodemographic populations experience higher exposure levels to NTL; however, those are not necessarily the underprivileged or marginalized. Identifying populations with high exposure levels is critical to influencing lighting policies to ease related health implications.

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

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

Signalling Pathways of Inflammation and Cancer in Human Mononuclear Cells: Effect of Nanoparticle Air Pollutants

Fine inhalable particulate matter (PM) triggers an inflammatory response in the airways and activates mononuclear cells, mediators of tissue homeostasis, and tumour-promoting inflammation. We have assessed ex vivo responses of human monocytes and monocyte-derived macrophages to standardised air pollutants: carbon black, urban dust, and nanoparticulate carbon black, focusing on their pro-inflammatory and DNA-damaging properties. None of the PM (100 μg/mL/24 h) was significantly toxic to the cells, aside from inducing oxidative stress, fractional DNA damage, and inhibiting phagocytosis. TNFα was only slightly increased. PM nanoparticles increase the expression and activate DNA-damage-related histone H2A.X as well as pro-inflammatory NF-κB. We have shown that the urban dust stimulates the pathway of DNA damage/repair via the selective post-translational phosphorylation of H2A.X while nanoparticulate carbon black increases inflammation via activation of NF-κB. Moreover, the inflammatory response to lipopolysaccharide was significantly stronger in macrophages pre-exposed to urban dust or nanoparticulate carbon black. Our data show that airborne nanoparticles induce PM-specific, epigenetic alterations in the subsets of cultured mononuclear cells, which may be quantified using binary fluorescence scatterplots. Such changes intercede with inflammatory signalling and highlight important molecular and cell-specific epigenetic mechanisms of tumour-promoting inflammation.

Urban spatial structure and air quality in the United States: Evidence from a longitudinal approach

Previous studies on the relationship between urban form and air quality: (1) report mixed results among specific aspects of urban spatial structure (e.g., urban expansion, form, or shape) and (2) use primarily cross-sectional approaches with a single year of data. This study takes advantage of a multi-decade, longitudinal approach to investigate the impact of urban spatial structure on population-weighted concentrations of PM2.5 and NO2. Based on fixed-effect regression models for 481 urban areas in the United States spanning from 1990 to 2015, we found significant associations between various aspects of urban spatial structure and air quality after controlling for meteorological and socio-economic factors. Our results show that population density, compact urban form, circularity, and green space are associated with lower concentrations. Conversely, higher rates of urban expansion, industrial area, and polycentricity are associated with higher concentrations. For large cities (total population: 180,262,404), we found that increasing key factors from each urban spatial structure category (i.e., greenness, population density, compactness, circularity) by a modest 10% results in 10,387 (12,376) fewer deaths for PM2.5 (NO2). We recommend that policymakers adopt comprehensive strategies to increase population density, compactness, and green spaces while slowing urban expansion to reduce the health burden of air quality in US cities.

Use of lichens as bioindicators of contamination by agrochemicals and metals

The presence or absence of lichens serves as an indicator of the condition of an ecosystem and the degree to which it is contaminated by various agents, such as agrochemicals and metals. Evaluating the use of lichens as bioindicators of agrochemical contamination could provide a more comprehensive perspective of current contamination levels. Monitoring was conducted over a 4-month period in two study areas: one was a well-conserved area contaminated by metals, and the other was an area surrounded by agricultural crops contaminated by agrochemicals. Data on the presence and abundance of lichens in each study area were recorded at 10 monitoring points, a procedure that was repeated 16 times (every 15 days), and concentrations of heavy metals and "organophosphate" agrochemicals in the lichens collected were measured by means of Inductively Coupled Plasma Atomic Emission Spectroscopy (ICP-OES) and Gas Chromatography (GC), respectively. Generalized linear mixed models were used to assess abundance and richness, while general linear mixed models were used to attain Shannon diversity and Simpson dominance indices. Moreover, a multivariate analysis was performed in order to compare the lichen communities in both areas. The results indicated differences between the area contaminated by metals and that contaminated by agrochemicals in terms of abundance and Simpson's dominance index, while no differences were found in the case of the richness and diversity models. The PERMANOVA analysis additionally showed differences between the lichen communities in the two areas. The results also demonstrated that Canoparmelia caroliniana bioaccumulated metals in both areas. The levels of barium, cadmium, and sodium were higher in the area contaminated by metals, while concentrations of chromium and copper were higher in the area contaminated by agrochemicals. Finally, the concentrations of agrochemicals were higher in the area contaminated by agrochemicals and included toxic substances such as Methylparathion and Parathion, which are prohibited in Ecuador. In conclusion, this research underscores the importance of lichens as precise indicators of environmental health and contamination by agrochemicals and metals.

The impact of urban configuration types on urban heat islands, air pollution, CO2 emissions, and mortality in Europe: a data science approach

BACKGROUND

The world is becoming increasingly urbanised. As cities around the world continue to grow, it is important for urban planners and policy makers to understand how different urban configuration patterns affect the environment and human health. However, previous studies have provided mixed findings. We aimed to identify European urban configuration types, on the basis of the local climate zones categories and street design variables from Open Street Map, and evaluate their association with motorised traffic flows, surface urban heat island (SUHI) intensities, tropospheric NO2, CO2 per person emissions, and age-standardised mortality.

METHODS

We considered 946 European cities from 31 countries for the analysis defined in the 2018 Urban Audit database, of which 919 European cities were analysed. Data were collected at a 250 m × 250 m grid cell resolution. We divided all cities into five concentric rings based on the Burgess concentric urban planning model and calculated the mean values of all variables for each ring. First, to identify distinct urban configuration types, we applied the Uniform Manifold Approximation and Projection for Dimension Reduction method, followed by the k-means clustering algorithm. Next, statistical differences in exposures (including SUHI) and mortality between the resulting urban configuration types were evaluated using a Kruskal-Wallis test followed by a post-hoc Dunn's test.

FINDINGS

We identified four distinct urban configuration types characterising European cities: compact high density (n=246), open low-rise medium density (n=245), open low-rise low density (n=261), and green low density (n=167). Compact high density cities were a small size, had high population densities, and a low availability of natural areas. In contrast, green low density cities were a large size, had low population densities, and a high availability of natural areas and cycleways. The open low-rise medium and low density cities were a small to medium size with medium to low population densities and low to moderate availability of green areas. Motorised traffic flows and NO2 exposure were significantly higher in compact high density and open low-rise medium density cities when compared with green low density and open low-rise low density cities. Additionally, green low density cities had a significantly lower SUHI effect compared with all other urban configuration types. Per person CO2 emissions were significantly lower in compact high density cities compared with green low density cities. Lastly, green low density cities had significantly lower mortality rates when compared with all other urban configuration types.

INTERPRETATION

Our findings indicate that, although the compact city model is more sustainable, European compact cities still face challenges related to poor environmental quality and health. Our results have notable implications for urban and transport planning policies in Europe and contribute to the ongoing discussion on which city models can bring the greatest benefits for the environment, climate, and health.

FUNDING

Spanish Ministry of Science and Innovation, State Research Agency, Generalitat de Catalunya, Centro de Investigación Biomédica en red Epidemiología y Salud Pública, and Urban Burden of Disease Estimation for Policy Making as a Horizon Europe project.

Weather and the City: Machine Learning for Predicting and Attributing Fine Scale Air Quality to Meteorological and Urban Determinants

Urban air quality persists as a global concern, with critical health implications. This study employs a combination of machine learning (gradient boosting regression, GBR) and spatial analysis to better understand the key drivers behind air pollution and its prediction and mitigation strategies. Focusing on New York City as a representative urban area, we investigate the interplay between urban characteristics and weather factors, showing that urban features, including traffic-related parameters and urban morphology, emerge as crucial predictors for pollutants closely associated with vehicular emissions, such as elemental carbon (EC) and nitrogen oxides (NOx). Conversely, pollutants with secondary formation pathways (e.g., PM2.5) or stemming from nontraffic sources (e.g., sulfur dioxide, SO2) are predominantly influenced by meteorological conditions, particularly wind speed and maximum daily temperature. Urban characteristics are shown to act over spatial scales of 500 × 500 m2, which is thus the footprint needed to effectively capture the impact of urban form, fabric, and function. Our spatial predictive model, needing only meteorological and urban inputs, achieves promising results with mean absolute errors ranging from 8 to 32% when using full-year data. Our approach also yields good performance when applied to the temporal mapping of spatial pollutant variability. Our findings highlight the interacting roles of urban characteristics and weather conditions and can inform urban planning, design, and policy.

Geospatial analysis of short-term exposure to air pollution and risk of cardiovascular diseases and mortality-A systematic review

The cardiovascular risk associated with short-term ambient air pollution exposure is well-documented. However, recent advancements in geospatial techniques have provided new insights into this risk. This systematic review focuses on short-term exposure studies that applied advanced geospatial pollution modelling to estimate cardiovascular disease (CVD) risk and accounted for additional unconventional neighbourhood-level confounders to analyse their modifier effect on the risk. Four databases were investigated to select publications between 2018 and 2023 that met the inclusion criteria of studying the effect of particulate matter (PM2.5 and PM10), SO2, NOx, CO, and O3 on CVD mortality or morbidity, utilizing pollution modelling techniques, and considering spatial and temporal confounders. Out of 3277 publications, 285 were identified for full-text review, of which 34 satisfied the inclusion criteria for qualitative analysis, and 12 of them were chosen for additional quantitative analysis. Quality assessment revealed that 28 out of 34 included articles scored 4 or above, indicating high quality. In 30 studies, advanced pollution modelling techniques were used, while in 4 only simpler methods were applied. The most pertinent confounders identified were socio-demographic variables (e.g., socio-economic status, population percentage by race or ethnicity) and neighbourhood-level built environment variables (e.g., urban/rural area, percentage of green space, proximity to healthcare), which exhibited varying modifier effects depending on the context. In the quantitative analysis, only PM 2.5 showed a significant positive association to all-cause CVD-related hospitalisation. Other pollutants did not show any significant effect, likely due to the high inter-study heterogeneity and a limited number of cases. The application of advanced geospatial measurement and modelling of air pollution exposure, as well as its risk, is increasing. This review underscores the importance of accounting for unconventional neighbourhood-level confounders to enhance the understanding of the CVD risk associated with short-term pollution exposure.

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.

Biological effects of diesel exhaust inhalation. III cardiovascular function

OBJECTIVE

Inhalation of diesel exhaust (DE) has been shown to be an occupational hazard in the transportation, mining, and gas and oil industries. DE also contributes to air pollution, and therefore, is a health hazard to the general public. Because of its effects on human health, changes have been made to diesel engines to reduce both the amounts of particulate matter and volatile fumes they generate. The goal of the current study was to examine the effects of inhalation of diesel exhaust.

MATERIALS AND METHODS

The study presented here specifically examines the effects of exposure to 0.2 and 1.0 mg/m3 DE or filtered air (6h/d for 4 d) on measures of peripheral and cardio-vascular function, and biomarkers of heart and kidney dysfunction in male rats. A Tier 2 engine used in oil and gas fracking operations was used to generate the diesel exhaust.

RESULTS

Exposure to 0.2 mg/m3 DE resulted in an increase in blood pressure 1d following the last exposure, and increases in dobutamine-induced cardiac output and stroke volume 1 and 27d after exposure. Changes in peripheral vascular responses to norepinephrine and acetylcholine were minimal as were changes in transcript expression in the heart and kidney. Exposure to 1.0 mg/m3 DE did not result in major changes in blood pressure, measures of cardiac function, peripheral vascular function or transcript expression.

DISCUSSION AND CONCLUSIONS

Based on the results of this study, we suggest that exposure to DE generated by a Tier 2 compliant diesel engine generates acute effects on biomarkers indicative of cardiovascular dysfunction. Recovery occurs quickly with most measures of vascular/cardiovascular function returning to baseline levels by 7d following exposure.

Particulate matter 2.5 causally increased genetic risk of autism spectrum disorder

BACKGROUND

Growing evidence suggested that particulate matter (PM) exhibit an increased risk of autism spectrum disorder (ASD). However, the causal association between PM and ASD risk remains unclear.

METHODS

We performed two-sample Mendelian randomization (MR) analyses, using instrumental variables (IVs) sourced from the largest genome-wide association studies (GWAS) databases. We employed three MR methods: inverse-variance weighted (IVW), weighted median (WM), and MR-Egger, with IVW method serving as our primary MR method. Sensitivity analyses were performed to ensure the stability of these findings.

RESULTS

The MR results suggested that PM2.5 increased the genetic risk of ASD (β = 2.41, OR = 11.13, 95% CI: 2.54-48.76, P < 0.01), and similar result was found for PM2.5 absorbance (β = 1.54, OR = 4.67, 95% CI: 1.21-18.01, P = 0.03). However, no such association was found in PM10 (β = 0.27, OR = 1.30, 95% CI: 0.72-2.36, P = 0.38). After adjusting for the false discovery rate (FDR) correction, our MR results remain consistent. Sensitivity analyses did not find significant heterogeneity or horizontal pleiotropy.

CONCLUSIONS

Our findings indicate that PM2.5 is a potential risk factor for ASD. Effective strategies to mitigate air pollutants might lead to a reduced incidence of ASD.

Spatiotemporal patterns and drivers of the urban air pollution island effect for 2273 cities in China

Air pollution levels tend to be higher in urban areas than in surrounding rural areas, and this air pollution has a negative effect on human health. However, the spatiotemporal patterns of urban-rural air pollution differences and the determinants of these differences remain unclear. Here, we calculate the Urban Air Pollution Island (UAPI) intensity for PM2.5 and PM10 on a monthly, seasonal, and annual scale for 2273 cities in China from 2000 to 2020. Subsequently, we analyze the influence of urban characteristics using a combined approach of a two-way fixed effects model and a spatial Durbin model. Results show a strong downward trend in the UAPI intensity since 2013, with reductions ranging from 42 % to 61 % until 2020, for both pollutants and in summer as well as winter. Consistently, the proportion of the cities experiencing the UAPI phenomenon decreased from 94.5 % to 77.3 % for both PM2.5 and PM10. We find a significant influence of urban morphology on UAPI. Specifically, urban sprawl, polycentric development, and an increase in urban green spaces are associated with a reduction in UAPI, while dense urban areas intensify it. Our study also reveals a robust inverted U-shaped relationship between stages of economic development and UAPI. Moreover, economic development and air pollution itself show spillover effects that oppose their direct impacts. These results suggest that urban and regional planning and more ambitious climate change mitigation policies could be more effective strategies for mitigating air pollution in cities than end-of-pipe control.

How to Achieve a Healthy City: a Scoping Review with Ten City Examples

This scoping review of the literature explores the following question: what systematic measures are needed to achieve a healthy city? The World Health Organization (WHO) suggests 11 characteristics of a healthy city. Measures contributing to these characteristics are extracted and classified into 29 themes. Implementation of some of these measures is illustrated by examples from Freiburg, Greater Vancouver, Singapore, Seattle, New York City, London, Nantes, Exeter, Copenhagen, and Washington, DC. The identified measures and examples indicate that a healthy city is a system of healthy sectors. A discussion section suggests healthy directions for nine sectors in a healthy city. These sectors include transportation, housing, schools, city planning, local government, environmental management, retail, heritage, and healthcare. Future work is advised to put more focus on characteristic 5 (i.e., the meeting of basic needs for all the city's people) and characteristic 10 (i.e., public health and sick care services accessible to all) of a healthy city.

Non-response bias in the analysis of the association between mental health and the urban environment: a cross-sectional study in Brussels, Belgium

BACKGROUND

This paper aims at analysing the impact of partial non-response in the association between urban environment and mental health in Brussels. The potential threats of the partial non-response are biases in survey estimates and statistics. The effect of non-response on statistical associations is often overlooked and evidence in the research literature is lacking.

METHODS

Data from the Belgian Health Interview Survey 2008 and 2013 were used. The association between non-response and potential determinants was explored through logistic regressions.

RESULTS

Participants with low income, low educational levels, lower or higher age or in households with children were less likely to respond. When adjusting for socio-economic variables, non-response was higher in areas which are less vegetated, more polluted or more urbanised. Because the determinants of non-response and depressive disorders were similar, it is reasonable to assume that there will be more people with mental health problems among the non-respondents. And because more non-responses were found in low vegetation areas, the protective association between green spaces and mental health may be underestimated.

CONCLUSION

Our capacity to measure the association between the urban environment and health is affected by non-response in surveys. The non-random spatial and socio-economic distribution of this bias affects the research findings.

The Contribution of Environmental Science to Mental Health Research: A Scoping Review

Mental health is influenced by multiple complex and interacting genetic, psychological, social, and environmental factors. As such, developing state-of-the-art mental health knowledge requires collaboration across academic disciplines, including environmental science. To assess the current contribution of environmental science to this field, a scoping review of the literature on environmental influences on mental health (including conditions of cognitive development and decline) was conducted. The review protocol was developed in consultation with experts working across mental health and environmental science. The scoping review included 202 English-language papers, published between 2010 and 2020 (prior to the COVID-19 pandemic), on environmental themes that had not already been the subject of recent systematic reviews; 26 reviews on climate change, flooding, air pollution, and urban green space were additionally considered. Studies largely focused on populations in the USA, China, or Europe and involved limited environmental science input. Environmental science research methods are primarily focused on quantitative approaches utilising secondary datasets or field data. Mental health measurement was dominated by the use of self-report psychometric scales. Measures of environmental states or exposures were often lacking in specificity (e.g., limited to the presence or absence of an environmental state). Based on the scoping review findings and our synthesis of the recent reviews, a research agenda for environmental science's future contribution to mental health scholarship is set out. This includes recommendations to expand the geographical scope and broaden the representation of different environmental science areas, improve measurement of environmental exposure, prioritise experimental and longitudinal research designs, and giving greater consideration to variation between and within communities and the mediating pathways by which environment influences mental health. There is also considerable opportunity to increase interdisciplinarity within the field via the integration of conceptual models, the inclusion of mixed methods and qualitative approaches, as well as further consideration of the socio-political context and the environmental states that can help support good mental health. The findings were used to propose a conceptual model to parse contributions and connections between environmental science and mental health to inform future studies.

Associations between short-term PM2.5 exposure and daily hospital admissions for circulatory system diseases in Ganzhou, China: A time series study

Objective

Previous epidemiological studies have shown that both long-term and short-term exposure to fine particulate matters (PM2.5) were associated with the morbidity and mortality of circulatory system diseases (CSD). However, the impact of PM2.5 on CSD remains inconclusive. This study aimed to investigate the associations between PM2.5 and circulatory system diseases in Ganzhou.

Methods

We conducted this time series study to explore the association between ambient PM2.5 exposure and daily hospital admissions for CSD from 2016 to 2020 in Ganzhou by using generalized additive models (GAMs). Stratified analyses were also performed by gender, age, and season.

Results

Based on 201,799 hospitalized cases, significant and positive associations were found between short-term PM2.5 exposure and hospital admissions for CSD, including total CSD, hypertension, coronary heart disease (CHD), cerebrovascular disease (CEVD), heart failure (HF), and arrhythmia. Each 10 μg/m3 increase in PM2.5 concentrations was associated with a 2.588% (95% confidence interval [CI], 1.161%–4.035%), 2.773% (95% CI, 1.246%–4.324%), 2.865% (95% CI, 0.786%–4.893%), 1.691% (95% CI, 0.239%–3.165%), 4.173% (95% CI, 1.988%–6.404%) and 1.496% (95% CI, 0.030%–2.983%) increment in hospitalizations for total CSD, hypertension, CHD, CEVD, HF, and arrhythmia, respectively. As PM2.5 concentrations rise, the hospitalizations for arrhythmia showed a slow upward trend, while other CSD increased sharply at high PM2.5 levels. In subgroup analyses, the impacts of PM2.5 on hospitalizations for CSD were not materially changed, although the females had higher risks of hypertension, HF, and arrhythmia. The relationships between PM2.5 exposure and hospitalizations for CSD were more significant among individuals aged ≤65 years, except for arrhythmia. PM2.5 had stronger effects on total CSD, hypertension, CEVD, HF, and arrhythmia during cold seasons.

Conclusion

PM2.5 exposure was positively associated with daily hospital admissions for CSD, which might provide informative insight on adverse effects of PM2.5.

Sex-differences in the effects of indoor air pollutants and household environment on preschool child cognitive development

Air pollution, outdoor residential environment, indoor household characteristics, and parental mental health are potential factors associated with child development. However, few studies have simultaneously analyzed the association between the aforementioned factors and preschool child (aged 2-5 years) development. This study investigated the effects of those factors on child development and their potential modifying effects. A total of 142 participants were recruited from a birth cohort study in the Greater Taipei Area, and the evaluation was conducted at each participant's home from 2017 to 2020. Child cognitive development was assessed by psychologists using the Bayley Scales of Infant and Toddler Development and the Wechsler Preschool & Primary Scale of Intelligence. Household air pollutants, outdoor residential environment, indoor household characteristics, parental mental health, and other covariates were evaluated. Multiple regressions were used to examine the relationships between child development and covariates. Stratified analysis by child sex and parental mental health was conducted. Average indoor air pollutant levels were below Taiwan's Indoor Air Quality Standards. After adjustment for covariates, the indoor total volatile organic compounds (TVOCs) level was significantly associated with poor child development (per interquartile range increase in the TVOC level was associated with a 5.1 percentile decrease in child cognitive development). Sex difference was observed for the association between TVOC exposure and child development. Living near schools, burning incense at home, purchasing new furniture, and parental anxiety were related to child development. Indoor TVOC level was associated with poor child cognitive development, specifically with the girls. Indoor and outdoor residential environment and parental anxiety interfered with child development. TVOCs should be used cautiously at home to minimize child exposure. A low-pollution living environment should be provided to ensure children's healthy development.

Changing trends in the air pollution-related disease burden from 1990 to 2019 and its predicted level in 25 years

In the twenty-first century, exposure to air pollution has become a threat to human health worldwide due to industrial development. Timely, comprehensive, and reliable assessment and prediction of disease burden can help mitigate the health hazards of air pollution. This study conducted a two-stage analysis. First, we reported the air pollution-related disease burden globally and for different subgroups like socio-demographic index (SDI), sex, and age. We analyzed the trend of the disease burden from 1990 to 2019. In addition, we explored whether and how some national indicators modified the disease burden. Second, we predicted the number and the age-standardized rates of death and disability-adjusted life years (DALYs) attributable to air pollution from 2020 to 2044 by the autoregressive integrated moving average (ARIMA) model and exponential smoothing model. The age-period-cohort (APC) model in the maximum likelihood framework and the Bayesian APC model integrated nested Laplace approximations (INLAs) were further applied to perform sensitivity analysis. In 2019, air pollution accounted for 11.62% of death and 0.84% of DALY worldwide. The corresponding age-standardized rate was 85.62 (95% uncertainty interval (UI): 75.71, 96.07) and 2791.08 (95% UI: 2468.81, 3141.39) per 100,000 population. From 1990 to 2019, the number of death attributable to air pollution remained stable, and the number of DALY exhibited a downward trend. The corresponding age-standardized rates both declined. In some countries with larger population densities, higher proportions of elders, and lower proportions of females, the disease burden attributable to air pollution was lower. The predicted results showed that the number of air pollution-related death and DALY would increase. This study comprehensively assessed and predicted the air pollution-related disease burden worldwide. The results indicated that the disease burden would remain very serious in the future. Hence, some relevant policies should be developed to prevent and manage air pollution.

Effects of urban form on air quality: A case study from China comparing years with normal and reduced human activity due to the COVID-19 pandemic

This study explored the dynamic and complex relationships between air quality and urban form when considering reduced human activities. Applying the random forest method to data from 62 prefecture-level cities in China, urban form-air quality relationships were compared between 2015 (a normal year) and 2020 (which had significantly reduced air pollution due to COVID-19 lockdowns). Significant differences were found between these two years; urban compactness, shape, and size were of prime importance to air quality in 2020, while fragmentation was the most critical factor in improving air quality in 2015. An important influence of traffic mode was also found when controlling air pollution. In general, in the pursuit of reducing air pollution across society, the best urban forms are continuous and compact with reasonable building layouts, population, and road densities, and high forest area ratios. A polycentric urban form that alleviates the negative impacts of traffic pollution is preferable. Urban development should aim to reduce air pollution, and optimizing the effects of urban form on air quality is a cost-effective way to create better living environments. This study provides a reference for decision-makers evaluating the effects of urban form on air pollution emission, dispersion, and concentration in the post-pandemic era.

Is air pollution detrimental to regional innovation? An empirical heterogeneity test based on Chinese cities

Nowadays, innovation seems to be the inevitable choice to achieve stable economic growth. However, the negative impact of air pollution on health and economy makes air pollution an important factor in regional innovation, which deserves our discussion. The overall regional innovation level from 2014 to 2019 has an upward trend, while the overall air pollution has a downward trend during the period, which provides foundation for our research. Based on the data of 285 prefecture-level cities in China from 2014 to 2019, this paper uses the fixed effect and mediation model to verify the impact and mechanism of air pollution on regional innovation. The results show that the increase in air pollution, measured by the air quality index, significantly inhibits regional innovation. Air pollution has significant funds crowding-out effect and human capital loss effect, thereby decreasing the regional innovation level, which means innovation funds and researchers play a conductive role between air pollution and regional innovation. In heterogeneity analysis, it is found that the detrimental effect of air pollution on regional innovation is significant in eastern and central China, in large- and medium-sized cities, and in cities with poor or general air quality. It indicates that developed and large-scale regions should pay more attention to air pollution control. For polluted regions, more emphasis and endeavors are needed to address air pollution problems. Besides, the inhibitory effect is more severe on incremental innovation rather than on radical innovation, which deserves the attention of enterprises engaged in incremental innovation. Therefore, we propose that targeted environmental policies and effective measures should be developed to improve air quality in the long run. Moreover, policymakers could provide strong support for innovation grants, talent subsidies, and rewards and encourage clean technological innovation through short-term trade-offs between heavily polluting and low polluting enterprises.

The relationship between the built environment and respiratory health: Evidence from a longitudinal study in Indonesia

Multiple studies have discussed the relationship between the built environment and non-infectious diseases, but research involving infectious diseases and the built environment is scarce. How the built environment is associated with infectious diseases varies across areas, and previous literature produces mixed results. This study investigated the relationship between the built environment and infectious diseases in Indonesia, which has different settings compared to developed countries. We combined the longitudinal panel data, Indonesian Family Life Survey (IFLS), and land cover data to examine the relationship between the built environment and the likelihood of contracting respiratory infectious diseases. We focused on the sprawl index to measure the built environment. The study confirmed that a sprawling neighbourhood is linked to lower respiratory infection symptoms by employing a fixed effect method. The association is more evident in urban areas and for females. The results also suggested that the linkage works through housing quality, such as housing crowdedness and ventilation, and neighbourhood conditions like neighbourhood transportation modes and air pollution levels. Thus, our results underlined the need to consider the health consequences of the densification policy and determine the direction of landscape planning and policy.

Integrated single-cell RNA-seq and DNA methylation reveal the effects of air pollution in patients with recurrent spontaneous abortion

Background

Maternal air pollutants exposure is associated with a number of adverse pregnancy outcomes, including recurrent spontaneous abortion (RSA). However, the underlying mechanisms are still unknown. The present study aimed to understand the mechanism of RSA and its relationship with air pollution exposure. We compared data of decidual tissue from individuals with induced abortions and those with RSA by bulk RNA sequencing (RNA-seq), reduced representation bisulfite sequencing (RRBS), and single-cell RNA sequencing (scRNA-seq). Differentially expressed genes (DEGs) were verified using RT-qPCR and pyrosequencing. A logistic regression model was used to investigate the association between air pollutants exposure and RSA.

Results

We identified 98 DEGs with aberrant methylation by overlapping the RRBS and RNA-seq data. Nineteen immune cell subsets were identified. Compared with normal controls, NK cells and macrophages accounted for different proportions in the decidua of patients with RSA. We observed that the methylation and expression of IGF2BP1 were different between patients with RSA and controls. Furthermore, we observed significant positive associations between maternal air pollutants exposure during the year prior to pregnancy and in early pregnancy and the risk of RSA. Mediation analyses suggested that 24.5% of the effects of air pollution on the risk of RSA were mediated through IGF2BP1 methylation.

Conclusion

These findings reveal a comprehensive cellular and molecular mechanism of RSA and suggest that air pollution might cause pregnancy loss by affecting the methylation level of the IGF2BP1 promoter.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13148-022-01327-2.

Leveraging Citizen Science and Low-Cost Sensors to Characterize Air Pollution Exposure of Disadvantaged Communities in Southern California

Assessing exposure to fine particulate matter (PM2.5) across disadvantaged communities is understudied, and the air monitoring network is inadequate. We leveraged emerging low-cost sensors (PurpleAir) and engaged community residents to develop a community-based monitoring program across disadvantaged communities (high proportions of low-income and minority populations) in Southern California. We recruited 22 households from 8 communities to measure residential outdoor PM2.5 concentrations from June 2021 to December 2021. We identified the spatial and temporal patterns of PM2.5 measurements as well as the relationship between the total PM2.5 measurements and diesel PM emissions. We found that communities with a higher percentage of Hispanic and African American population and higher rates of unemployment, poverty, and housing burden were exposed to higher PM2.5 concentrations. The average PM2.5 concentrations in winter (25.8 µg/m3) were much higher compared with the summer concentrations (12.4 µg/m3). We also identified valuable hour-of-day and day-of-week patterns among disadvantaged communities. Our results suggest that the built environment can be targeted to reduce the exposure disparity. Integrating low-cost sensors into a citizen-science-based air monitoring program has promising applications to resolve monitoring disparity and capture "hotspots" to inform emission control and urban planning policies, thus improving exposure assessment and promoting environmental justice.

Decision Tree Analyses to Explore the Relevance of Multiple Sex/Gender Dimensions for the Exposure to Green Spaces: Results from the KORA INGER Study

Recently, attention has been drawn to the need to integrate sex/gender more comprehensively into environmental health research. Considering theoretical approaches, we define sex/gender as a multidimensional concept based on intersectionality. However, operationalizing sex/gender through multiple covariates requires the usage of statistical methods that are suitable for handling such complex data. We therefore applied two different decision tree approaches: classification and regression trees (CART) and conditional inference trees (CIT). We explored the relevance of multiple sex/gender covariates for the exposure to green spaces, measured both subjectively and objectively. Data from 3742 participants from the Cooperative Health Research in the Region of Augsburg (KORA) study were analyzed within the INGER (Integrating gender into environmental health research) project. We observed that the participants’ financial situation and discrimination experience was relevant for their access to high quality public green spaces, while the urban/rural context was most relevant for the general greenness in the residential environment. None of the covariates operationalizing the individual sex/gender self-concept were relevant for differences in exposure to green spaces. Results were largely consistent for both CART and CIT. Most importantly we showed that decision tree analyses are useful for exploring the relevance of multiple sex/gender dimensions and their interactions for environmental exposures. Further investigations in larger urban areas with less access to public green spaces and with a study population more heterogeneous with respect to age and social disparities may add more information about the relevance of multiple sex/gender dimensions for the exposure to green spaces.

Determining thresholds for spatial urban design and transport features that support walking to create healthy and sustainable cities: findings from the IPEN Adult study

An essential characteristic of a healthy and sustainable city is a physically active population. Effective policies for healthy and sustainable cities require evidence-informed quantitative targets. We aimed to identify the minimum thresholds for urban design and transport features associated with two physical activity criteria: at least 80% probability of engaging in any walking for transport and WHO's target of at least 15% relative reduction in insufficient physical activity through walking. The International Physical Activity and the Environment Network Adult (known as IPEN) study (N=11 615; 14 cities across ten countries) provided data on local urban design and transport features linked to walking. Associations of these features with the probability of engaging in any walking for transport and sufficient physical activity (≥150 min/week) by walking were estimated, and thresholds associated with the physical activity criteria were determined. Curvilinear associations of population, street intersection, and public transport densities with walking were found. Neighbourhoods exceeding around 5700 people per km², 100 intersections per km², and 25 public transport stops per km² were associated with meeting one or both physical activity criteria. Shorter distances to the nearest park were associated with more physical activity. We use the results to suggest specific target values for each feature as benchmarks for progression towards creating healthy and sustainable cities.

City-level greenness exposure is associated with COVID-19 incidence in China

Accumulating studies have suggested an important role of environmental factors (e.g. air pollutants) on the occurrence and development of coronavirus disease 2019 (COVID-19). Evidence concerning the relationship of greenness on COVID-19 is still limited. This study aimed to assess the association between greenness and COVID-19 incidence in 266 Chinese cities. A total of 12,377 confirmed COVID-19 cases were identified through February 29th, 2020. We used the average normalized difference vegetation index (NDVI) during January and February 2020 from MOD13A2 product, to represent the city-level greenness exposure. A generalized linear mixed-effects model was used to estimate the association between NDVI exposure and COVID-19 incidence using COVID-19 cases as the outcome. We evaluated whether the association was modified by population density, GDP per capita, and urbanization rate, and was mediated by air pollutants. We also performed a series of sensitivity analyses to discuss the robustness of our results. Per 0.1 unit increment in NDVI was negatively associated with COVID-19 incidence (IRR: 0.921, 95% CI: 0.898, 0.944) after adjustment for confounders. Associations with COVID-19 incidence were stronger in cities with lower population density, lower GDP per capita, and lower urbanization rate. We failed to detect any mediation effect of air pollutants on the association between NDVI and COVID-19 incidence. Sensitivity analyses also indicated consistent estimates. In conclusion, our study suggested a beneficial association between city-level greenness and COVID-19 incidence. We could not establish which mechanisms may explain this relationship.

What next? Expanding our view of city planning and global health, and implementing and monitoring evidence-informed policy

This Series on urban design, transport, and health aimed to facilitate development of a global system of health-related policy and spatial indicators to assess achievements and deficiencies in urban and transport policies and features. This final paper in the Series summarises key findings, considers what to do next, and outlines urgent key actions. Our study of 25 cities in 19 countries found that, despite many well intentioned policies, few cities had measurable standards and policy targets to achieve healthy and sustainable cities. Available standards and targets were often insufficient to promote health and wellbeing, and health-supportive urban design and transport features were often inadequate or inequitably distributed. City planning decisions affect human and planetary health and amplify city vulnerabilities, as the COVID-19 pandemic has highlighted. Hence, we offer an expanded framework of pathways through which city planning affects health, incorporating 11 integrated urban system policies and 11 integrated urban and transport interventions addressing current and emerging issues. Our call to action recommends widespread uptake and further development of our methods and open-source tools to create upstream policy and spatial indicators to benchmark and track progress; unmask spatial inequities; inform interventions and investments; and accelerate transitions to net zero, healthy, and sustainable cities.

Entitlement, Indeterminacy and Professional Discretion in Urban Planning: Problematising a Child’s Right to Clean Air for Play in London

The interaction between air quality and play space receives less focus in planning than it has in public health and environmental sciences research. In this paper, seven local planning authorities of inner London (UK) were sampled from the 10 boroughs with the worst air quality in parks. Greenwich, with significantly better air quality, was included for comparison. The selected authorities were validated against deprivation data, ensuring variance in socio-economic terms. Across this sample, 21 major residential planning applications were assessed, alongside a document analysis of planning policy documents for each authority. Lastly, five semi-structured interviews with different practitioners collectively provided multi-disciplinary perspectives on the planning processes across the sample. Despite the national government having conferred children a right to leisure space and a healthy environment via international conventions, the English planning system, as an institutional rights framework, is not consistently prioritising the delivery of children’s play space nor delivering play space where the air quality has been robustly assessed. In other words, such rights have been subjugated to other priorities in limited urban space in London. Therefore, a discretionary planning system does not preclude individual human rights from becoming disadvantaged under democratically controlled decision-making processes.

Frequent occurrence of respiratory symptoms in children is associated with exposure to air pollution, land use types, and parental mental health in the Greater Taipei area

Although studies have investigated the individual effects of air pollution, land use types, and parental mental health on children's respiratory health, few studies have examined the effects of these risk factors simultaneously in children aged <2 years. We investigated the effects of exposure to air pollution, land use types surrounding residences, and parental mental health on the frequent occurrence of respiratory symptoms in children aged <2 years in the Greater Taipei area. Participants were recruited from an ongoing Taiwanese birth cohort study. We analyzed the data of the participants who had been recruited from January 2011 to April 2014 and had responded to the follow-up questionnaires at 6, 12, and 24 months. Self-administered questionnaires were used to collect participants' sociodemographic background and health, such as respiratory symptoms, and parental mental health. Pre- and postnatal pollution levels were estimated using the spatial interpolation technique (ordinary kriging) at children's residential addresses. Land use types surrounding participants' homes were evaluated by performing buffer analysis. Multiple logistic regression analyses were conducted to examine the effects of risk factors on the frequent occurrence of child respiratory symptoms in children aged 6, 12, and 24 months. We included 228, 360, and 441 children aged 6, 12, and 24 months, respectively. Our results indicated that postnatal exposure to PM_2.5 and O₃ was positively associated with children's respiratory symptoms. Traffic-related land-use types, sports facilities, and commercial land surrounding homes exerted adverse effects on children's respiratory symptoms, whereas the presence of schools in the neighborhood was beneficial. Parental mental health was also associated with children's respiratory symptoms. Postnatal exposure to air pollution and land use types surrounding residences were associated with respiratory health in children aged <2 years. The residential environment is a critical factor affecting children's respiratory health of children aged <2 years.

Residential greenness is associated with disease severity among COVID-19 patients aged over 45 years in Wuhan, China

Evidence regarding environmental factors associated with disease severity of COVID-19 remained scarce. This study aimed to investigate the association of residential greenness exposure with COVID-19 severity applying a retrospective cross-sectional study in Wuhan, China. We included 30,253 COVID-19 cases aged over 45 years from January 1 to February 27, 2020. Residential greenness was quantitatively assessed using normalized difference vegetation index (NDVI) and enhanced vegetation index (EVI). A multilevel generalized linear model using Poisson regression was implemented to analyze the association between greenness exposure and disease severity of COVID-19, after adjusting for potential covariates. A linear exposure-response relationship was found between greenness and COVID-19 severity. In the adjusted model, one 0.1 unit increase of NDVI and EVI in the 1000-m buffer radius was significantly associated with a 7.6% (95% confidence interval (CI): 4.0%, 11.1%) and 10.0% (95% CI: 5.1%, 14.7%) reduction of the prevalence of COVID-19 severity, respectively. The effect of residential greenness seemed to be more pronounced among participants with lower population density and economic levels. Air pollutants mediated 0.82~12.08% of the greenness and COVID-19 severity association, particularly to nitrogen dioxide. Sensitivity analyses suggested the robustness of the results. Our findings suggested that residential greenness exposure was beneficial to reduce the prevalence of COVID-19 severity.

Residential greenness and prevalence of chronic kidney disease: Findings from the China National Survey of Chronic Kidney Disease

Green space is associated with many health benefits, but evidence concerning the effects on chronic kidney disease (CKD) has not been investigated. Using the nationwide cross-sectional study of 47,204 adults from the China National Survey of Chronic Kidney Disease dataset and residential greenness assessed by the normalized difference vegetation index (NDVI), this study evaluated the association between residential greenness and CKD prevalence. An interquartile range increase in NDVI_1000m (0.26) was associated with decreased odds of CKD for all participants with an odds ratio (OR) of 0.79 (95% confidence interval [CI]: 0.73-0.86). Subgroup analyses demonstrated more apparent inverse associations in younger adults <65 years, male participants, people in higher socio-economic status, as well as people with smoking and alcohol drinking habit. In addition, more apparent inverse associations were found in regions with higher fine particulate matter (PM_2.5) concentration levels, with OR of 0.56 (95% CI: 0.49, 0.65) for higher pollution regions, and OR of 0.95 (95% CI: 0.83, 1.09) for lower pollution regions (P for interaction <0.001). The exposure-response curves captured more apparent declines in OR of CKD when in lower NDVI_1000m exposure ranges (<0.6), even controlling for the PM_2.5 concentration. Our results indicated that residential greenness might be beneficial for the prevention and control of CKD at the population level, suggesting the positive significance of strengthening green space construction, particularly in regions with low greenness.

Can Industrial Restructuring Improve Urban Air Quality?—A Quasi-Experiment in Beijing during the COVID-19 Pandemic

The conflict between economic growth and environmental pollution has become a considerable bottleneck to future development throughout the world. The industrial structure may become the possible key factor in resolving the contradiction. Using the daily data of air quality from January to April in 2019 and 2020, we used the DID model to identify the effects of industrial structure on air quality by taking the COVID-19 pandemic as a quasi-experiment. The results show that, first, the impact of profit of the secondary industry on air quality is ten times higher than that of the tertiary industry. Therefore, the secondary industry is the main factor causing air pollution. Second, the effect of the reduction in the secondary industry on the improvement of air quality is better than that of the tertiary industry in Beijing. Therefore, the implementation of Beijing’s non-capital function relief policy is timely and reasonable, and the adjustment of the industrial structure is effective in the improvement of air quality. Third, PM2.5, NO2, and CO are affected by the secondary and tertiary industries, where PM2.5 is affected most seriously by the second industry. Therefore, the transformation from the secondary industry to the tertiary industry can not only solve the problem of unemployment but also relieve the haze. Fourth, the result of O3 is in opposition to other pollutants. The probable reason is that the decrease of PM2.5 would lead to an increase in the O3 concentration. Therefore, it is difficult to reduce O3 concentrationby production limitation and it is urgent to formulate scientific methods to deal with O3 pollution. Fifth, the air quality in the surrounding areas can also influence Beijing. As Hebei is a key area to undertake Beijing’s industry, the deterioration of its air quality would also bring pressure to Beijing’s atmospheric environment. Therefore, in the process of industrial adjustment, the selection of appropriate regions for undertaking industries is very essential, which is worth our further discussion.

Polycentric or monocentric, which kind of spatial structure is better for promoting the green economy? Evidence from Chinese urban agglomerations

The green economy has gained worldwide attention, especially in the urban agglomerations where population and economic activities are highly concentrated. However, what kind of urban agglomeration spatial structure is more conducive to promoting the green economy? No clear conclusions have been made. To bridge this gap, by employing the data of 16 urban agglomerations in China in 2003-2017 and a comprehensive analytic framework including dynamic panel threshold model, this paper studies the impact of urban agglomeration spatial structure on the green economy and the three subsystems of green economy to shed light on which kind of urban agglomeration spatial structure better drives the green economy. The main findings are shown below: (1) urban agglomeration spatial structural evolution is closely related to green economy, while in the research period, most urban agglomerations are not located in the optimal range of the spatial structure that drives the green economy. (2) Towards polycentric spatial structure is contributive to green economic growth; however, the excessively polycentric could not benefit green economy. (3) The evolution of urban agglomeration spatial structure exerts heterogeneous impacts on the three subsystems when green economy is decomposed into economic subsystem, resources subsystem, and environmental subsystem. Towards polycentric is more conducive to the improvement of economic subsystem and resource subsystem, while the tendency to monocentric drives the environmental subsystem. (4) Lastly, the conclusions enlighten the urban agglomeration development planning and spatial mode for approaching a better performance in green economy.

Evolution of Romania's Economic Structure and Environment Degradation - An Assessment Through LMDI Decomposition Approach

Purpose

This paper studies the relationships between air pollutants (PM₁₀, PM_2.5, N₂O) and different diseases (tumors, skin and respiratory) and the factors influencing air pollutant emissions in Romania.

Methods

The methods are Toda-Yamamoto procedure of non-causality Granger test, grey relational analysis and logarithmic mean Divisia index method (LMDI).

Results

Air pollutants intensities dropped significantly over 2008–2017 period due to structural changes. The only economic activity that showed an increase both in volume and intensity of air pollutants, despite a downward trend of farming activities output is agriculture. Technology improvements play a significant role in mitigation of PM_2.5 emissions and a moderate role in mitigation of PM₁₀ emissions. For N₂O emissions technology used contributed to an increase of N₂O intensities.

Conclusion

Health policy makers should address the issue of technology improvements and mitigation of agriculture emissions to improve health of individuals and air quality.

Ambient fine particulate matter in Latin American cities: Levels, population exposure, and associated urban factors

BACKGROUND

Exposure to particulate matter (PM_2.5) is a major risk factor for morbidity and mortality. Yet few studies have examined patterns of population exposure and investigated the predictors of PM_2.5 across the rapidly growing cities in lower- and middle-income countries.

OBJECTIVES

Characterize PM_2.5 levels, describe patterns of population exposure, and investigate urban factors as predictors of PM_2.5 levels.

METHODS

We used data from the Salud Urbana en America Latina/Urban Health in Latin America (SALURBAL) study, a multi-country assessment of the determinants of urban health in Latin America, to characterize PM_2.5 levels in 366 cities comprising over 100,000 residents using satellite-derived estimates. Factors related to urban form and transportation were explored.

RESULTS

We found that about 172 million or 58% of the population studied lived in areas with air pollution levels above the defined WHO-AQG of 10 μg/m³ annual average. We also found that larger cities, cities with higher GDP, higher motorization rate and higher congestion tended to have higher PM_2.5. In contrast cities with higher population density had lower levels of PM_2.5. In addition, at the sub-city level, higher intersection density was associated with higher PM_2.5 and more green space was associated with lower PM_2.5. When all exposures were examined adjusted for each other, higher city per capita GDP and higher sub-city intersection density remained associated with higher PM_2.5 levels, while higher city population density remained associated with lower levels. The presence of mass transit was also associated with lower PM_2.5 after adjustment. The motorization rate also remained associated with PM_2.5 and its inclusion attenuated the effect of population density.

DISCUSSION

These results show that PM_2.5 exposures remain a major health risk in Latin American cities and suggest that urban planning and transportation policies could have a major impact on ambient levels.

Road Traffic and Urban Form Factors Correlated with the Incidence of Lung Cancer in High-density Areas: An Ecological Study in Downtown Shanghai, China

The incidence of lung cancer is affected by air pollution, especially in high-density urban areas with heavy road traffic and dense urban form. Several studies have examined the direct relationship between lung cancer incidence and road traffic as well as urban form. However, the results are still inconsistent for high-density urban areas. This study focused on urban form and road traffic, aiming at revealing their relationship with lung cancer incidence in high-density urban areas at the neighborhood level. For this, an ecological study was conducted in downtown Shanghai to identify important indicators and explore quantitative associations. Negative binomial regression was fitted with lung cancer incidence as the dependent variable. The independent variables included indicators for road traffic and urban form, greenness, demographic, and socio-economic factors. The results showed that building coverage, averaged block perimeter area ratio, density of metro station without the glass barrier system, and the percentage of low-quality residential land were positively correlated with lung cancer incidence in the neighborhood, while population density was negatively correlated with lung cancer incidence. This study found a strong self-selection effect of socio-economic factors in the relationship between lung cancer incidence and greenness. These results may be useful for conducting health impact assessments and developing spatial planning interventions for respiratory health in high-density urban areas.

Outdoor green space exposure and brain health measures related to Alzheimer's disease: a rapid review

OBJECTIVES

Summarise studies of outdoor green space exposure and brain health measures related to Alzheimer's disease and related disorders (ADRD), and determine scientific gaps for future research.

DESIGN

Rapid review of primary research studies.

METHODS AND OUTCOMES

PubMed, Embase and Web of Science Core Collection were searched for articles meeting the criteria published on/before 13 February 2020. The review excluded papers not in English, focused on transient states (eg, mental fatigue) or not using individual-level measures of brain health (eg, average school test scores). Brain health measures of interest included cognitive function, clinical diagnosis of cognitive impairment/dementia/ADRD and brain biomarkers such as those from MRI, measures typically associated with ADRD risk and disease progression.

RESULTS

Twenty-two papers were published from 2012 to 2020, 36% on <18 years old, 32% on 18-64 years old and 59% on ≥65 years old. Sixty-four per cent defined green space based on the Normalised Difference Vegetation Index ('greenness'/healthy vegetation) and 68% focused on cognitive measures of brain health (eg, memory). Seventeen studies (77%) found green space-brain health associations (14 positive, 4 inverse). Greater greenness/green space was positively associated various cognitive domains in 10 studies and with MRI outcomes (regional brain volumes, cortical thickness, amygdala integrity) in three studies. Greater neighbourhood greenness was associated with lower odds/risk of cognitive impairment/ADRD in some studies but increased odds/risk in others (n=4 studies).

CONCLUSIONS

Published studies suggest positive green space-brain health associations across the life course, but the methods and cohorts were limited and heterogeneous. Future research using racially/ethnically and geographically diverse cohorts, life course methods and more specific green space and brain health measures (eg, time spent in green spaces, ADRD biomarkers) will strengthen evidence for causal associations.

The Complexity of Space Utilization and Environmental Pollution Control in the Main Corridor of Makassar City, South Sulawesi, Indonesia

Population mobility, increasing demand for transportation, and the complexity of land use have an impact on environmental quality degradation and air quality pollution. This study aims to analyze (1) the effect of population mobility, increased traffic volume, and land use change on air quality pollution, (2) direct and indirect effects of urban activities, transportation systems, and movement patterns on environmental quality degradation and air pollution index, and (3) air pollution strategy and sustainable urban environmental management. The research method used is a sequential explanation design. Data were obtained through observation, surveys, in-depth interviews, and documentation. The results of the study illustrate that the business center and Daya terminal with a value of 0.18 µgram/m3 is polluted, the power plant and Sermani industrial area with a value of 0.16 µgram/m3 is polluted, the Makassar industrial area with a value of 0.23 is heavily polluted, and the Hasanuddin International Airport area with a value of 0.04 µgram/m3 is not polluted. Population mobility, traffic volume, and land use changes have a significant effect on environmental quality degradation, with a determination coefficient of 94.1%. The direct effect of decreasing environmental quality on the air pollution index is 66.09%. This study recommends transportation management on the main road corridor of Makassar City, which is environmentally friendly with regard to sustainable environmental management.

Guidance to Reduce the Cardiovascular Burden of Ambient Air Pollutants: A Policy Statement From the American Heart Association

In 2010, the American Heart Association published a statement concluding that the existing scientific evidence was consistent with a causal relationship between exposure to fine particulate matter and cardiovascular morbidity and mortality, and that fine particulate matter exposure is a modifiable cardiovascular risk factor. Since the publication of that statement, evidence linking air pollution exposure to cardiovascular health has continued to accumulate and the biological processes underlying these effects have become better understood. This increasingly persuasive evidence necessitates policies to reduce harmful exposures and the need to act even as the scientific evidence base continues to evolve. Policy options to mitigate the adverse health impacts of air pollutants must include the reduction of emissions through action on air quality, vehicle emissions, and renewable portfolio standards, taking into account racial, ethnic, and economic inequality in air pollutant exposure. Policy interventions to improve air quality can also be in alignment with policies that benefit community and transportation infrastructure, sustainable food systems, reduction in climate forcing agents, and reduction in wildfires. The health care sector has a leadership role in adopting policies to contribute to improved environmental air quality as well. There is also potentially significant private sector leadership and industry innovation occurring in the absence of and in addition to public policy action, demonstrating the important role of public-private partnerships. In addition to supporting education and research in this area, the American Heart Association has an important leadership role to encourage and support public policies, private sector innovation, and public-private partnerships to reduce the adverse impact of air pollution on current and future cardiovascular health in the United States.

Healthy built environment: Spatial patterns and relationships of multiple exposures and deprivation in Toronto, Montreal and Vancouver

BACKGROUND

Various aspects of the urban environment and neighbourhood socio-economic status interact with each other to affect health. Few studies to date have quantitatively assessed intersections of multiple urban environmental factors and their distribution across levels of deprivation.

OBJECTIVES

To explore the spatial patterns of urban environmental exposures within three large Canadian cities, assess how exposures are distributed across socio-economic deprivation gradients, and identify clusters of favourable or unfavourable environmental characteristics.

METHODS

We indexed nationally standardized estimates of active living friendliness (i.e. "walkability"), NO₂ air pollution, and greenness to 6-digit postal codes within the cities of Toronto, Montreal and Vancouver. We compared the distribution of within-city exposure tertiles across quintiles of material deprivation. Tertiles of each exposure were then overlaid with each other in order to identify potentially favorable (high walkability, low NO₂, high greenness) and unfavorable (low walkability, high NO₂, and low greenness) environments.

RESULTS

In all three cities, high walkability was more common in least deprived areas and less prevalent in highly deprived areas. We also generally saw a greater prevalence of postal codes with high vegetation indices and low NO₂ in areas with low deprivation, and a lower greenness prevalence and higher NO₂ concentrations in highly deprived areas, suggesting environmental inequity is occurring. Our study showed that relatively few postal codes were simultaneously characterized by desirable or undesirable walkability, NO₂and greenness tertiles.

DISCUSSION

Spatial analyses of multiple standardized urban environmental factors such as the ones presented in this manuscript can help refine municipal investments and policy priorities. This study illustrates a methodology to prioritize areas for interventions that increase active living and exposure to urban vegetation, as well as lower air pollution. Our results also highlight the importance of considering the intersections between the built environment and socio-economic status in city planning and urban public health decision-making.

Combining expert and crowd-sourced training data to map urban form and functions for the continental US

Although continental urban areas are relatively small, they are major drivers of environmental change at local, regional and global scales. Moreover, they are especially vulnerable to these changes owing to the concentration of population and their exposure to a range of hydro-meteorological hazards, emphasizing the need for spatially detailed information on urbanized landscapes. These data need to be consistent in content and scale and provide a holistic description of urban layouts to address different user needs. Here, we map the continental United States into Local Climate Zone (LCZ) types at a 100 m spatial resolution using expert and crowd-sourced information. There are 10 urban LCZ types, each associated with a set of relevant variables such that the map represents a valuable database of urban properties. These data are benchmarked against continental-wide existing and novel geographic databases on urban form. We anticipate the dataset provided here will be useful for researchers and practitioners to assess how the configuration, size, and shape of cities impact the important human and environmental outcomes.

Analyzing Links between Spatio-Temporal Metrics of Built-Up Areas and Socio-Economic Indicators on a Semi-Global Scale

Manifold socio-economic processes shape the built and natural elements in urban areas. They thus influence both the living environment of urban dwellers and sustainability in many dimensions. Monitoring the development of the urban fabric and its relationships with socio-economic and environmental processes will help to elucidate their linkages and, thus, aid in the development of new strategies for more sustainable development. In this study, we identified empirical and significant relationships between income, inequality, GDP, air pollution and employment indicators and their change over time with the spatial organization of the built and natural elements in functional urban areas. We were able to demonstrate this in 32 countries using spatio-temporal metrics, using geoinformation from databases available worldwide. We employed random forest regression, and we were able to explain 32% to 68% of the variability of socio-economic variables. This confirms that spatial patterns and their change are linked to socio-economic indicators. We also identified the spatio-temporal metrics that were more relevant in the models: we found that urban compactness, concentration degree, the dispersion index, the densification of built-up growth, accessibility and land-use/land-cover density and change could be used as proxies for some socio-economic indicators. This study is a first and fundamental step for the identification of such relationships at a global scale. The proposed methodology is highly versatile, the inclusion of new datasets is straightforward, and the increasing availability of multi-temporal geospatial and socio-economic databases is expected to empirically boost the study of these relationships from a multi-temporal perspective in the near future.

Turbulent Flows and Pollution Dispersion around Tall Buildings Using Adaptive Large Eddy Simulation (LES)

The motivation for this work stems from the increased number of high-rise buildings/skyscrapers all over the world, and in London, UK, and hence the necessity to see their effect on the local environment. We concentrate on the mean velocities, Reynolds stresses, turbulent kinetic energies (TKEs) and tracer concentrations. We look at their variations with height at two main locations within the building area, and downstream the buildings. The pollution source is placed at the top of the central building, representing an emission from a Combined Heat and Power (CHP) plant. We see how a tall building may have a positive effect at the lower levels, but a negative one at the higher levels in terms of pollution levels. Mean velocities at the higher levels (over 60 m in real life) are reduced at both locations (within the building area and downstream it), whilst Reynolds stresses and TKEs increase. However, despite the observed enhanced turbulence at the higher levels, mean concentrations increase, indicating that the mean flow has a greater influence on the dispersion. At the lower levels (Z < 60 m), the presence of a tall building enhanced dispersion (hence lower concentrations) for many of the configurations.

Environmental determinants of population health in urban settings. A systematic review

Background

Population health is influenced by interactions between environmental determinants, which are captured by dimensions and indicators. This study aims to systematically review key environmental determinants and respective dimensions and indicators, relevant to evaluate population health in urban settings, and to understand their potential implications into policies.

Methods

A search of literature published between 2008 and 2018 was conducted in PubMed, Web of Science, Scopus and SciELO Portugal databases, on studies with evidence on association between an environmental determinant and a health outcome in urban contexts. Health determinants, dimensions and indicators researched in the selected studies were synthetized, and associations analyzed. An independent assessment of quality of the studies was performed. Key conclusions and policy recommendations were extracted to build a framework to analyze environment related population health and policies in urban settings.

Results

Ninety four studies of varied methodological approaches and quality met the inclusion criteria. The review identified positive associations between all environmental determinants -socioeconomic, built environment, natural environment, healthcare, behaviors, and health outcomes - overall mortality and morbidity, in urban settings. Improvements in income, education, air quality, occupation status, mobility and smoking habits indicators have positive impact in overall mortality and chronic diseases morbidity indicators. Initiatives to improve population health in which policymakers can be more evidence-informed include socioeconomic, natural environment and built environment determinants.

Conclusions

There is scope and need to further explore which environmental determinants and dimensions most contribute to population health to create a series of robust evidence-based measures to better inform urban planning policies.