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 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 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.

Natural environments have been linked to decreased risk of cardiovascular disease (CVD) and respiratory disease (RSD) mortality. However, few cohort studies have looked at associations of natural environments with CVD or RSD hospitalization. The aim of this study was to evaluate these associations in a cohort of U.S. Medicare beneficiaries (∼63 million individuals). Our open cohort included all fee-for-service Medicare beneficiaries (2000–2016), aged ≥65, living in the contiguous U.S. We assessed zip code-level park cover based on the United States Geological Survey Protected Areas Database, average greenness (Normalized Difference Vegetation Index, NDVI), and percent blue space cover based on Landsat satellite images. Cox-equivalent Poisson models were used to estimate associations of the exposures with first CVD and RSD hospitalization in the full cohort and among those living in urban zip codes (≥1000 persons/mile²). NDVI was weakly negatively correlated with percent park cover (Spearman ρ = −0.23) and not correlated with percent blue space (Spearman ρ = 0.00). After adjustment for potential confounders, percent park cover was not associated with CVD or RSD hospitalization in the full or urban population. An IQR (0.27) increase in NDVI was negatively associated with CVD (HR: 0.97, 95%CI: 0.96, 0.97), but not with RSD hospitalization (HR: 0.99, 95%CI: 0.98, 1.00). In urban zip codes, an IQR increase in NDVI was positively associated with RSD hospitalization (HR: 1.02, 95%CI: 1.00, 1.03). In stratified analyses, percent park cover was negatively associated with CVD and RSD hospitalization for Medicaid eligible individuals and individuals living in low socioeconomic status neighborhoods in the urban population. We observed no associations of percent blue space cover with CVD or RSD hospitalization. This study suggests that natural environments may benefit cardiorespiratory health; however, benefits may be limited to certain contexts and certain health outcomes.

Ammonia (NH₃) emissions could have significant impacts on both ecosystems and human health. Ice cores from the Tibetan Plateau contain information about past ammonium (NH₄⁺) deposition, which could yield important insights into historical NH₃ emissions in the surrounding source regions as well as long-distance NH₄⁺ aerosol transport via atmospheric circulation. In this paper, we present a high-resolution atmospheric NH₄⁺ deposition record for the period, 1951–2008, reconstructed from the Zangser Kangri (ZK) ice core in the northern Tibetan Plateau. An empirical orthogonal function (EOF) analysis of major soluble ions (NH₄⁺, NO₃⁻, SO₄²⁻, Cl⁻, Na⁺, K⁺, Mg²⁺ and Ca²⁺) reveals that EOF 1 has significant loadings of all ions, therefore representing common transport pathways, while EOF 2 is only significantly loaded by NH₄⁺ (0.86) and NO₃⁻ (0.35), suggesting a unique signal possibly representing emissions from the surrounding terrestrial ecosystems on the Tibetan Plateau. Backward trajectory analysis indicates that the air masses over the ZK ice core drilling site primarily come from the northwestern Indian Peninsula. NH₃ emissions from agricultural activities in this area likely contribute to the NH₄⁺ deposition of the ZK ice core via the Indian monsoon. Correlations between EOF 2 time series and temperature, normalized difference vegetation index (NDVI) suggest that increasing temperature and vegetation after 1980 likely promoted NH₃ emissions from terrestrial ecosystems. Our results provide a reliable and valuable assessment of NH₄⁺ deposition from human activities and terrestrial ecosystems in the ZK ice core, and help in understanding air pollution over the past few decades in the northern Tibetan Plateau.

Few studies have reported the association between greenspace and academic performance at school level. We examined associations between both residential and school greenspace and individual school grades in German adolescents.German and maths grades from the latest school certificate, residential and school greenspace, and covariates were available for 1351 10 and 15 years old Munich children and 1078 Wesel children from two German birth cohorts – GINIplus and LISA. Residential and school greenspace was assessed by the Normalized Difference Vegetation Index (NDVI), tree cover, and (in Munich only) proportion of agricultural land, forest, and urban green space in 500-m and 1000-m circular buffers. Longitudinal associations between each exposure-outcome pair were assessed by logistic mixed effects models with person and school as random intercepts and adjusted for potential confounders.No associations were observed between any of the greenspace variables and grades in Wesel children. Several statistically significant associations were observed with German and maths grades in Munich children, however associations were inconsistent across sensitivity analyses.There is no evidence of an association of higher greenspace at residence, school or combined with improved academic performance in German adolescents from the GINIplus and LISA longitudinal studies.

Ecosystem services are present everywhere, green vegetation coverage (or green areas) is one of the primary sources of ecosystem services considering urban areas sustainability and peoples urban life quality. Urban vegetation cover loss decreases the capacity of nature to provision ecosystem services; the loss of urban vegetation is also observed within the Amazon. This study aims at identifying urban vegetation loss and relate it to the provision of ecosystem services of reduction of air quality, reduction of air pollution, and climate regulation. Urban vegetation coverage loss was calculated using NDVI on LANDSAT 5 imagery over a 23-year period from 1986 to 2009. NDVI thresholds were arbitrarily selected, and complemented by in locus observation, to establish guidelines for quantitative (area) and qualitative (density) evolution of green cover, divided in six different categories, named as water, bare soil, poor vegetation, moderate vegetation, dense vegetation and very dense vegetation. Data on air pollution, noise pollution and temperature were outsourced from previous works. Measurement show a significant loss of very dense, dense and moderate vegetation coverage and an increase in poor vegetation and bare soil areas, in accordance to increase in air and noise pollution, and local temperature, and provides positive refashions between the loss of urban green coverage and decrease in ecosystem services.

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.

Long-term exposure to air pollution has been associated with increased natural-cause mortality, but the evidence on diagnoses-specific mortality outcomes is limited. Few studies have examined the potential synergistic effects of exposure to pollutants and greenness. We investigated the association between exposure to air pollution and greenness with nervous system related mortality, cardiometabolic and chronic obstructive pulmonary diseases (COPD) mortality in Greece, using an ecological study design. We collected socioeconomic and mortality data for 1035 municipal units from the 2011 Census. Annual PM₂.₅, NO₂, BC and O₃ concentrations for 2010 were predicted at 100 × 100 m grids by hybrid land use regression models. The normalized difference vegetation index (NDVI) was used for greenness. We applied single and two-exposure Poisson regression models on standardized mortality rates accounting for spatial autocorrelation. We assessed interactions between pollutants and greenness. An interquartile range increase in PM₂.₅, NO₂ and BC was associated with increased risk in mortality from diseases of the nervous system (relative risk (RR): 1.14, 95% confidence interval (CI): 1.01, 1.28); 1.03 (95% CI: 0.99, 1.07); 1.05 (95% CI: 1.00, 1.10) respectively) and from cerebrovascular disease (RR: 1.14, 95% CI: 1.10, 1.18); 1.02 (95% CI: 1.01, 1.04); 1.02 (95% CI: 1.00, 1.04) respectively). PM₂.₅ was associated with ischemic heart disease mortality (RR: 1.05, 95% CI: 1.01, 1.10). We estimated inverse associations for all outcomes with O₃ and for mortality from diseases of the nervous system or COPD with greenness. Estimates were mostly robust to co-exposure adjustment. Interactions were identified between NDVI and O₃ or PM₂.₅ on mortality from the diseases of the nervous system, with higher effect estimates in greener areas.Our findings support the adverse effects of air pollution and the beneficial role of greenness on cardiovascular and nervous system related mortality. Further research is needed on diabetes mellitus.