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.

Metabolic syndrome is an important risk factor for non-communicable diseases, particularly type 2 diabetes, coronary heart disease, and stroke. Long-term exposure to greenspace could be protective of metabolic syndrome, but evidence for such an association is lacking. Accordingly, we investigated the association between long-term exposure to greenspace and risk of metabolic syndrome.The present longitudinal study was based on data from four clinical examinations between 1997 and 2013 in 6076 participants of the Whitehall II study, UK (aged 45–69 years at baseline). Long-term exposure to greenspace was assessed by satellite-based indices of greenspace including Normalized Difference Vegetation Index (NDVI) and Vegetation Continuous Field (VCF) averaged across buffers of 500 and 1000 m surrounding the participants’ residential location at each follow-up. The ascertainment of metabolic syndrome was based on the World Health Organization (WHO) definition. Hazard ratios for metabolic syndrome were estimated using Cox proportional hazards regression models, controlling for age, sex, ethnicity, lifestyle factors, and socioeconomic status.Higher residential surrounding greenspace was associated with lower risk of metabolic syndrome. An interquartile range increase in NDVI and VCF in the 500 m buffer was associated with 13% (95% confidence interval (CI): 1%, 23%) and 14% (95% CI: 5%, 22%) lower risk of metabolic syndrome, respectively. Greater exposure to greenspace was also associated with each individual component of metabolic syndrome, including a lower risk of high levels of fasting glucose, large waist circumference, high triglyceride levels, low HDL cholesterol, and hypertension. The association between residential surrounding greenspace and metabolic syndrome may have been mediated by physical activity and exposure to air pollution.The findings of the present study suggest that middle-aged and older adults living in greener neighbourhoods are at lower risk of metabolic syndrome than those living in neighbourhoods with less greenspace.

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.

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.

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.

Increasingly, studies suggest benefits of natural environments or greenness on children's health. However, little is known about cumulative exposure or windows of susceptibility to greenness exposure. Using inverse probability weighting of marginal structural models (IPW/MSM), we estimated effects of greenness exposure from birth through adolescence on executive function and behavior. We analyzed data of 908 children from Project Viva enrolled at birth in 1999–2002 and followed up until early adolescence. In mid-childhood (median 7.7 years) and early adolescence (13.1 years), executive function and behavior were assessed using the Behavior Rating Inventory of Executive Function and the Strengths and Difficulties Questionnaire (SDQ). Greenness was measured at birth, early childhood, mid-childhood, and early adolescence, using the Normalized Difference Vegetation Index. We used inverse probability weighting of marginal structural models to estimate effects of interventions that ensure maximum greenness exposure versus minimum through all intervals; and that ensure maximum greenness only in early childhood (vs. minimum through all intervals). Results of the effects of “maximum (vs. minimum) greenness at all timepoints” did not suggest associations with mid-childhood outcomes. Estimates of “maximum greenness only in early childhood (vs. minimum)” suggested a beneficial association with mid-childhood SDQ (−3.21, 99 %CI: −6.71,0.29 mother-rated; −4.02, 99 %CI: −7.87,-0.17 teacher-rated). No associations were observed with early adolescent outcomes. Our results for “persistent” maximum greenness exposure on behavior, were not conclusive with confidence intervals containing the null. The results for maximum greenness “only in early childhood” may shed light on sensitive periods of greenness exposure for behavior regulation.

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.

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.

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.

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.