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.

Previous studies indicated that exposure to air pollution was associated with the progress of atherosclerosis, but evidence is very limited in China and even in the world. This study aims to assess the associations of long-term exposures to air pollution and greenness with the occurrence of carotid plaque. Participants of this cohort study were urban residents and office workers who visited Hebei General Hospital for routine physical examination annually from September 2016 through to December 2018. Eligible participants were people diagnosed the absence of carotid plaque clinically at their first hospital visit and were followed up at their second or third hospital visit. Exposure to particulate matter with aerodynamic diameter less than 2.5 μm (PM₂.₅), nitrogen dioxide (NO₂) and ozone (O₃) were estimated using an inverse distance weighted (IDW) method. The level of greenness was assessed using the Normalized Difference Vegetation Index (NDVI) and Enhanced Vegetation Index (EVI). The associations were evaluated using Cox proportional hazards regression models. Among 4,137 participants, 575 showed the occurrence of carotid plaque during the follow-up period. After controlling for potential confounders, the hazard ratios (HRs) and 95% confidence intervals (95%CIs) of carotid plaque associated with per interquartile range (IQR) increase in PM₂.₅, NO₂, and O₃ were 1.78 (1.55, 2.03), 1.32 (1.14, 1.53) and 1.99 (1.71, 2.31), respectively. Increased EVI and NDVI were significantly associated with lower risk of carotid plaque [HR (and 95%CI): 0.84 (0.77, 0.93) and 0.87 (0.80, 0.94)]. PM₂.₅ significantly mediated 80.47% or 93.00% of the estimated association between EVI or NDVI and carotid plaque. In light of the significant associations between air pollution, greenness and carotid plaque in this study, continued efforts are needed to curb air pollution and plan more green space considering their effects on vascular disease.

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

Trace elements can be toxic when they cannot be easily removed after entering an ecosystem, so a long-term assessment is fundamental to guide ecosystem restoration after catastrophic pollution. In 1998, a pyrite mining accident in Aznalcóllar (south-western Spain) spilled toxic waste over a large area of the Guadiamar river basin, where, after restoration tasks, the Guadiamar Green Corridor was established. Eight years after the mine accident (2005–2006), the ground-dwelling insectivorous lizard Psammodromus algirus registered high trace-element levels within the study area compared to specimens from a nearby unpolluted control site. In 2017, 20 years after the accident, we repeated the sampling for this lizard species and also quantified trace elements in vegetation as well as in arthropod samples in order to identify remnant trace-element accumulation with the aim of assessing the transfer of these elements through the trophic web. We found remnant trace-element contamination in organisms of the polluted site compared to those from the unpolluted site. All trace-element concentrations were higher in arthropods than in plants, suggesting these compounds bioaccumulate through the trophic web. Lizards from the polluted areas had higher As, Cd, and Hg concentrations than did individuals from the unpolluted area. Lizard abundance between sampling periods (2005–06 and 2017) did not vary in unpolluted transects but strongly declined at polluted ones. By contrast, the Normalized Difference Vegetation Index indicated that in the study period, the vegetation was similar at the two sampling sites. These results suggest that, 20 years after the accident, the trace-element pollution could be the cause of a severe demographic decline of the lizard in the polluted area.

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.

Scots pine (Pinus sylvestris L.) is a widespread tolerant forest tree-species; however, its adaptability to environmental change differs among sites with various buffering capacity. In this study, we compared the spatial effects of aridity index (AI) and nitrogen deposition (ND) on biomass density in natural and man-made pine stands of differing soil fertility using geographically weighted multiple lag regression. Soil fertility was defined using soil series as zonal trophic (27.9%), acidic (48.2%), gleyed (15.2%) and as azonal exposed (2.5%), maple (2.4%), ash (0.8%), wet (2.1%) and peat (0.9%) under pine stands in the Czech Republic (Central Europe; 4290.5 km²; 130–1298 m a.s.l.). Annual AI and ND in every pine stand were estimated by intersection between raster and vector from 1 × 1 km grid for years 2000, 2003, 2007 and 2010 of severe non-specific forest damage spread. Biomass density was obtained from a MODIS 250 × 250 m raster using the enhanced vegetation index (EVI) for years 2000–2015, with a decrease in EVI indicating non-specific damage. Environmental change was assessed by comparing predictor values at EVI time t and t+λ. Non-specific damage was registered over 51.9% of total forest area. Less than 8.8% of damaged stands were natural and the rest (91.2%) of damaged stands were man-made. Pure pine stands were more damaged than mixed. The ND effect prevailed up to 2007, while AI dominated later. Temporal increasing ND effect under AI effectiveness led to the most significant pine stand damage in 2008 and 2014. Predictors from 2000 to 2007 afflicted 58.5% of non-specifically damaged stands at R² 0.09–0.76 (median 0.38), but from 2000 to 2010 afflicted 57.1% of the stands at R² 0.16–0.75 (median 0.40). The most damaged stands occurred on acidic sites. Mixed forest and sustainable management on natural sites seem as effective remediation reducing damage by ND.

In urban areas, the demand for local assessment of air quality is high. The existing monitoring stations cannot fulfill the needs. This study assesses the potential of hyperspectral tree leaf reflectance for monitoring traffic related air pollution. Hereto, 29 Carpinus betulus saplings were exposed to an environment with either high or low traffic intensity. The local air quality was estimated by leaf saturation isothermal remanent magnetization (SIRM). The VIS-NIR leaf reflectance spectrum (350–2500 nm) was measured using a handheld AgriSpec spectroradiometer (ASD Inc.). Secondary, leaf chlorophyll content index (CCI), specific leaf area (SLA) and water content (WC) were determined. To gain insight in the link between leaf reflectance and air quality, the correlation between SIRM and several spectral features was determined. The spectral features that were tested are plain reflectance values, derivative of reflectance, two-band indices using the NDVI formula and PCA components. Spectral reflectance for wavelength bands in the red and short wave IR around the red edge, were correlated to SIRM with Pearson correlations of up to R = −0.85 (R² = 0.72). Based on the spectral features and combinations thereof, binomial logistic regression models were trained to classify trees into high or low traffic pollution exposure, with classification accuracies up to 90%. It can be concluded that hyperspectral reflectance of C. betulus leaves can be used to detect different levels of air pollution within an urban environment.

Rising tropospheric ozone concentrations in Asia necessitate the breeding of adapted rice varieties to ensure food security. However, breeding requires field-based evaluation of ample plant material, which can be technically challenging or very costly when using ozone fumigation facilities. The chemical ethylenediurea (EDU) has been proposed for estimating the effects of ozone in large-scale field applications, but controlled experiments investigating constitutive effects on rice or its suitability to detect genotypic differences in ozone tolerance are missing. This study comprised a controlled open top chamber experiment with four treatments (i) control (average ozone concentration 16 ppb), (ii) control with EDU application, (iii) ozone stress (average 77 ppb for 7 h daily throughout the season), and (iv) ozone stress with EDU application. Three contrasting rice genotypes were tested, i.e. the tolerant line L81 and the sensitive Nipponbare and BR28. The ozone treatment had significant negative effects on plant growth (height and tillering), stomatal conductance, SPAD value, spectral reflectance indices such as the normalized difference vegetation index (NDVI), lipid peroxidation, as well as biomass and grain yields. These negative effects were more pronounced in the a priori sensitive varieties, especially the widely grown Bangladeshi variety BR28, which showed grain yield reductions by 37 percent. EDU application had almost no effects on plants in the absence of ozone, but partly mitigated ozone effects on foliar symptoms, lipid peroxidation, SPAD value, stomatal conductance, several spectral reflectance parameters, panicle number, grain yield, and spikelet sterility. EDU responses were more pronounced in sensitive genotypes than in the tolerant L81. In conclusion, EDU had no constitutive effects on rice and partly offset negative ozone effects, especially in sensitive varieties. It can thus be used to diagnose ozone damage in field grown rice and for distinguishing tolerant (less EDU-responsive) and sensitive (more EDU-responsive) genotypes.

The global demand for fossil energy is triggering oil exploration and production projects in remote areas of the world. During the last few decades hydrocarbon production has caused pollution in the Amazon forest inflicting considerable environmental impact. Until now it is not clear how hydrocarbon pollution affects the health of the tropical forest flora. During a field campaign in polluted and pristine forest, more than 1100 leaf samples were collected and analysed for biophysical and biochemical parameters. The results revealed that tropical forests exposed to hydrocarbon pollution show reduced levels of chlorophyll content, higher levels of foliar water content and leaf structural changes. In order to map this impact over wider geographical areas, vegetation indices were applied to hyperspectral Hyperion satellite imagery. Three vegetation indices (SR, NDVI and NDVI705) were found to be the most appropriate indices to detect the effects of petroleum pollution in the Amazon forest.

Residential green space and neighborhood walkability are important foundations of a healthy and sustainable city. Yet, their associations with atherosclerosis, the disease underlying clinical coronary heart disease (CHD), is unknown, especially in susceptible populations. We aim to explore the associations of exposure to residential green space and neighborhood walkability with coronary atherosclerosis. In this study of 2021 adults with suspected CHD, we evaluated the associations of exposure to green space (using Normalized Difference Vegetation Index [NDVI] and enhanced vegetation index [EVI] surrounding each participant's home) and neighborhood walkability (using walkability index and number of parks near home) with atherosclerosis (using coronary artery calcium score, CAC) using linear regression model adjusted for individual-level characteristics. Mediation analysis was further applied to explore potential mechanisms through the pathways of physical activity, air pollution, and psychological stress. In the primary model, an interquartile increase in annual mean NDVI and EVI within the 1-km area was associated with −15.8% (95%CI: 28.7%, −0.7%), and −18.6% (95%Cl: 31.3%, −3.6%) lower CAC score, respectively. However, an interquartile increase in the walkability index near home was associated with a 7.4% (95% CI: 0.1%, 15.2%) higher CAC score. The combined exposure to a green space area in a 1-km area and the walkability index were inversely associated with atherosclerosis, albeit with a smaller magnitude than a single-exposure model. The findings from a mediation analysis suggested that increased physical exercise and ameliorated particulate matter <2.5 μm (PM₂.₅) may partially contribute to the relationship between green space and atherosclerosis, and for walkability index, partially explained by increased PM₂.₅ exposure. Our study suggested a beneficial association between green space and atherosclerosis, but an adverse association between neighborhood walkability and atherosclerosis. Therefore, urban development that aims to improve neighborhood walkability should jointly account for enhancing green space properties from a public health perspective.