Responses to COVID-19 altered environmental exposures and health behaviours associated with non-communicable diseases. We aimed to (1) quantify changes in nitrogen dioxide (NO₂), noise, physical activity, and greenspace visits associated with COVID-19 policies in the spring of 2020 in Barcelona (Spain), Vienna (Austria), and Stockholm (Sweden), and (2) estimated the number of additional and prevented diagnoses of myocardial infarction (MI), stroke, depression, and anxiety based on these changes. We calculated differences in NO₂, noise, physical activity, and greenspace visits between pre-pandemic (baseline) and pandemic (counterfactual) levels. With two counterfactual scenarios, we distinguished between Acute Period (March 15th – April 26th, 2020) and Deconfinement Period (May 2nd – June 30th, 2020) assuming counterfactual scenarios were extended for 12 months. Relative risks for each exposure difference were estimated with exposure-risk functions. In the Acute Period, reductions in NO₂ (range of change from −16.9 μg/m³ to −1.1 μg/m³), noise (from −5 dB(A) to −2 dB(A)), physical activity (from −659 MET*min/wk to −183 MET*min/wk) and greenspace visits (from −20.2 h/m to 1.1 h/m) were largest in Barcelona and smallest in Stockholm. In the Deconfinement Period, NO₂ (from −13.9 μg/m³ to −3.1 μg/m³), noise (from −3 dB(A) to −1 dB(A)), and physical activity levels (from −524 MET*min/wk to −83 MET*min/wk) remained below pre-pandemic levels in all cities. Greatest impacts were caused by physical activity reductions. If physical activity levels in Barcelona remained at Acute Period levels, increases in annual diagnoses for MI (mean: 572 (95% CI: 224, 943)), stroke (585 (6, 1156)), depression (7903 (5202, 10,936)), and anxiety (16,677 (926, 27,002)) would be anticipated. To decrease cardiovascular and mental health impacts, reductions in NO₂ and noise from the first COVID-19 surge should be sustained, but without reducing physical activity. Focusing on cities’ connectivity that promotes active transportation and reduces motor vehicle use assists in achieving this goal.

Spatiotemporal variability complicates source apportionment of metals in urban lakes, especially when rainfall drives urban non-point source pollution. As, Cd, Cr, Pb, Hg, Ag, Co, Cu, Fe, Mn, Ni, Sb, Sr and Zn concentrations in 648 water samples collected before and after rain in 6 urban lakes of Beijing, China were determined during 2013–2015. The response of metals concentrations after rain to the interaction between rainfall and antecedent dry days was significant. Metals concentrations were normalized pursuant to the interaction effect as the input of positive matrix factorization (PMF) to develop the interaction normalized-PMF (IN-PMF). Four primary pollution sources were diagnosed. Sediment release was considered to be the main source of Fe, Co and Ni independent of rainfall. Hg, As and some Cr associated with pesticides and fertilizers were likely to come from soil erosion and runoff from green space. It is probable that road runoff was the dominant source for heavy metals related to traffic emissions, including Pb, Cd, Cu, Sb, Mn and Zn. Cr, Sr and some Cu and Zn as key elements of rooftops can be regarded as from roof runoff. The IN-PMF lowered roof and road runoff contributions and raised the contribution of soil erosion from green space, with Pb, Sb, Cu, Zn, Cd and Mn increasing by 15.9%, 10.7%, 13.1%, 12.2%, 13.3% and 16.8%. The results shed more light on the stormwater runoff pollution mitigation on impervious surfaces and metals enrichment problems in infiltration soil on green space in the low impact development (LID) setting. The Bayesian network revealed the spatial variability of transport and fate of metal elements from land surfaces to urban lakes, supplementing the secondary pollution sources from different land use. This study will provide new insights for source apportionment of non-point source pollution under the background of sponge city construction.

An increasing body of evidence has linked greenspace and various health outcomes in children and adolescents, but the conclusions were inconsistent. For this review, we comprehensively summarized the measurement methods of greenspace, resultant health outcomes, and potential mechanisms from epidemiological studies in children and adolescents (aged ≤19 years). We searched for studies published and indexed in MEDLINE and EMBASE (via Ovid) up to April 11, 2022. There were a total of 9,291 studies identified with 140 articles from 28 countries finally assessed and included in this systematic review. Over 70% of the studies were conducted in highly urbanised countries/regions, but very limited research has been done in low-and middle-income countries and none in Africa. Measures of greenspace varied. Various health outcomes were reported, including protective effects of greenspace exposure on aspects of obesity/overweight, myopia, lung health, circulatory health, cognitive function, and general health in children and adolescents. The associations between greenspace exposure and other health outcomes were inconsistent, especially for respiratory health studies. We pooled odds ratios (OR) using random-effects meta-analysis for health outcomes of asthma (OR = 0.94, 95%CI: 0.84 to 1.06), allergic rhinitis (OR = 0.95; 95% CI: 0.73 to 1.25), and obesity/overweight (OR = 0.91, 95%CI: 0.84 to 0.98) with per 0.1 unit increase in normalized difference in vegetation index (NDVI). These associations have important implications for the assessment and management of urban environment and health in children and adolescents.

The presence of urban greenspace may lead to reduced personal exposure to air pollution via several mechanisms, for example, increased dispersion of airborne particulates; however, there is a lack of real-time evidence across different urban contexts. Study participants were 79 adolescents with asthma who lived in Delhi, India and were recruited to the Delhi Air Pollution and Health Effects (DAPHNE) study. Participants were monitored continuously for exposure to PM₂.₅ (particulate matter with an aerodynamic diameter of less than 2.5 μm) for 48 h. We isolated normal day-to-day walking journeys (n = 199) from the personal monitoring dataset and assessed the relationship between greenspace and personal PM₂.₅ using different spatial scales of the mean Normalised Difference Vegetation Index (NDVI), mean tree cover (TC), and proportion of surrounding green land use (GLU) and parks or forests (PF). The journeys had a mean duration of 12.7 (range 5, 53) min and mean PM₂.₅ personal exposure of 133.9 (standard deviation = 114.8) μg/m³. The within-trip analysis showed weak inverse associations between greenspace markers and PM₂.₅ concentrations only in the spring/summer/monsoon season, with statistically significant associations for TC at the 25 and 50 m buffers in adjusted models. Between-trip analysis also indicated inverse associations for NDVI and TC, but suggested positive associations for GLU and PF in the spring/summer/monsoon season; no overall patterns of association were evident in the autumn/winter season. Associations between greenspace and personal PM₂.₅ during walking trips in Delhi varied across metrics, spatial scales, and season, but were most consistent for TC. These mixed findings may partly relate to journeys being dominated by walking along roads and small effects on PM₂.₅ of small pockets of greenspace. Larger areas of greenspace may, however, give rise to observable spatial effects on PM₂.₅, which vary by season.

Although many researchers have identified the potential psychological benefits offered by greenness, the association between green space structures and mental disorders is not well understood. The purpose of this study was to identify associations between green space structures and the incidence of bipolar disorder. To this end, we investigated 1,907,776 individuals collected from Taiwan’s National Health Insurance Research Database. After a follow-up investigation from 2005 to 2016, among those with no history of bipolar disorder, 20,548 individuals were further found to be diagnosed with bipolar disorder. A geographic information system and landscape index were used to quantify three indices of green space structures: mean patch area (area and edge), mean fractal dimension index (shape), and mean proximity index (proximity). Additionally, greenness indices, the normalized difference vegetation index, and the enhanced vegetation index were used to confirm the association between greenness and incidence of bipolar disorder. These five indices were used to represent the individual’s exposure according to the township of the hospital that they most frequently visited with symptoms of the common cold. Spearman’s correlation analysis was performed to select variables by considering their collinearity. Subsequently, the frailty model for each index was used to examine the specific associations between those respective indices and the incidence of bipolar disorder by adjusting for related risk factors, such as socioeconomic status, metabolic syndrome, and air pollution. A negative association was identified between the mean patch area and the mean proximity index, and the incidence of bipolar disorder. In contrast, a positive association was found between the mean fractal dimension index and the incidence of bipolar disorder. We observed similar results in sensitivity testing and subgroup analysis. Exposure to green spaces with a larger area, greater proximity, lower complexity, and greener area may reduce the risk of bipolar disorder.

Urban green infrastructure is closely linked to the alleviation of pollution from atmospheric particulate matter. Although particle deposition has been shown to depend on leaf characteristics, the findings from earlier studies are sometimes ambiguous due to the lack of controlling variables. In this study, we investigated the impact of leaf morphological characteristics on PM₂.₅ dry deposition velocity by employing a control-variable approach. We focused on four indices: trichome density, petiole length, aspect ratio (width-to-length ratio), and fractal deviation. For each index, tree species were chosen from the same family or genus to minimize the influence of other factors and make a group of treatments for an individual index. The dry deposition velocities of PM₂.₅ were determined through application of an indirect method. The results revealed that the presence of leaf trichomes had a positive effect on PM₂.₅ dry deposition velocity, and a higher trichome density also led to a greater particle deposition velocity. Lower leaf aspect ratio, shorter petioles, and higher leaf fractal deviation were associated with greater PM₂.₅ dry deposition velocity. The control-variable approach allows to investigate the correlation between deposition velocity and a certain leaf characteristic independently while minimizing the effects of others. Thus, our study can clarify how a single leaf characteristic affects particle deposition velocity, and expound its potential mechanism more scientifically than the published studies. Our research points out the importance of controlling variables, and also provides ideas for future researches on related factors to be found. Meanwhile the results would help provide insight into design improvements or adaptive management for the alleviation of air pollution.

Urban environments are characterized by multiple exposures that may influence body mass index (BMI) growth in early life. Previous studies are few, with inconsistent results and no evaluation of simultaneous exposures. Thus, this study aimed to assess the associations between exposure to air pollution, green spaces and built environment characteristics, and BMI growth trajectories from 0 to 5 years. This longitudinal study used data from an electronic primary care health record database in Catalonia (Spain), including 79,992 children born between January 01, 2011 and December 31, 2012 in urban areas and followed until 5 years of age. Height and weight were measured frequently during childhood and BMI (kg/m²) was calculated. Urban exposures were estimated at census tract level and included: air pollution (nitrogen dioxide (NO₂), particulate matter <10 μm (PM₁₀) and <2.5 μm (PM₂.₅₎), green spaces (Normalized Difference Vegetation Index (NDVI) and % green space) and built environment (population density, street connectivity, land use mix, walkability index). Individual BMI trajectories were estimated using linear spline multilevel models with several knot points. In single exposure models, NO₂, PM₁₀, PM₂.₅, and population density were associated with small increases in BMI growth (e.g. β per IQR PM₁₀ increase = 0.023 kg/m², 95%CI: 0.013, 0.033), and NDVI, % of green spaces and land use mix with small reductions in BMI growth (e.g. β per IQR % green spaces increase = −0.015 kg/m², 95%CI: −0.026, −0.005). These associations were strongest during the first two months of life. In multiple exposure models, most associations were attenuated, with only those for PM₁₀ and land use mix remaining statistically significant. This large longitudinal study suggests that early life exposure to air pollution, green space and built environment characteristics may be associated with small changes in BMI growth trajectories during the first years of life, and that it is important to account for multiple exposures in urban settings.

The green infrastructure (GI) is identified as a passive exposure control measure of air pollution. This work examines particulate matter (PM) reduction by a roadside hedge and its deposition on leaves. The objectives of this study are to (i) quantify the relative difference in PM concentration in the presence of GI and at an adjacent clear area; (ii) estimate the total mass and number density of PM deposited on leaves of a hedge; (iii) ascertain variations in PM deposition at adult (1.5m) and child (0.6 m) breathing levels on either side of a hedge; (iv) illustrate the relationship between PM deposition to leaves and ambient PM concentration reductions; and (v) quantify the elemental composition of collected particles of the leaves on different heights and sides of hedge. PM reduction of 2–9% was observed behind hedge compared to a clear area and followed a trend of ΔPM₁ >ΔPM₁₀ >ΔPM₂.₅. Counting of particles was found to be an effective method to quantify deposition than weighting methods. Sub-micron particles (PM₁) dominated particle deposition on leaves at all sampling points on both sides of the hedge. PM mass deposition and number concentration to the leaves on traffic-facing side was up to 36% and 58% higher at 0.6m compared with 1.5m height, respectively. Such a difference was absent on the backside of the hedge. The SEM-EDS analysis showed up to 12% higher traffic-originated particles deposited to leaves on the traffic-facing side compared to the backside. The naturally occurring particles dominated in identified particles on leaf samples from all collection points on the hedge. These new evidence expand our understanding of PM reduction of GI in the near-road environment and its variations in particle deposition, depending on height and sides of GI, which could allow a better parameterisation of dispersion-deposition models for GI assessment at micro-scale.

Microbiota in urban green spaces underpin ecosystem services that are essential to environmental health and human wellbeing. However, the factors shaping the microbial communities in urban green spaces, especially those associated with turf grass phyllosphere, remain poorly understood. The lack of this knowledge greatly limits our ability to assess ecological, social and recreational benefits of urban green spaces in the context of global urbanization. In this study, we used amplicon sequencing to characterize soil and grass phyllosphere bacterial communities in 40 urban green spaces and three minimally disturbed national parks in Victoria, Australia. The results indicated that urbanization might have shown different impacts on soil and grass phyllosphere microbial communities. The bacterial diversity in soil but not in grass phyllosphere was significantly higher in urban green spaces than in national parks. Principal coordinate analysis revealed significant differences in the overall patterns of bacterial community composition between urban green spaces and national parks for both soil and grass phyllosphere. Industrial development, as represented by the number of industries in the region, was identified as a key driver shaping the bacterial community profiles in urban green spaces. Variation partitioning analysis suggested that industrial factors together with their interaction with other factors explained 20% and 28% of the variances in soil and grass phyllosphere bacterial communities, respectively. The findings highlight the importance of industrial development in driving the spatial patterns of urban microbiomes, and have important implication for the management of microbiomes in urban green spaces.

Urban development has led to an increase in urban runoff, accompanied with a decrease in water quality during rain events. One of the major causes of the decrease in water quality is the presence of trace organic contaminants in urban runoff. However, little is known about the sources of organic contaminants in urban runoff, especially related to land-use and temporal trends in those associated land uses. The objective of this study was to assess the occurrence and concentration trends of organic contaminants for a high-density residential site and commercial strip site in Madison, WI. Flow-weighted samples of urban stormwater runoff, collected with an auto-sampler, were composited and analyzed, producing mean organic contaminants concentrations for each storm event. The contaminants, which include pesticides, flame retardants, polycyclic aromatic hydrocarbons, corrosion inhibitors, among others, were extracted and analyzed by gas chromatography coupled with mass spectrometry or liquid chromatography coupled with tandem mass spectrometry. There were 30 organic contaminants that had greater than 50% detections in at least one of the sites, and those organic contaminants did provide information on similarities and differences of organic contaminants in urban runoff derived from different land uses. The sum of the total measured pesticides showed no significant difference between sites; this was likely due to the considerable green space and associated pesticide use in both sites. However, there were higher total concentrations of organophosphate flame retardants and corrosion inhibitors in the residential site. The reason for this is unknown and will require follow-up studies; however, several hypotheses are presented. Conversely, there were higher total concentrations of polycyclic aromatic hydrocarbons in the commercial site; this is most likely due to higher vehicle traffic in the commercial site. These data show that land-use may be important in determining the composition and concentrations of trace organic contaminants in urban stormwater runoff.