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Green space could influence adult cognition and childhood neurodevelopment , and is hypothesized to be partly driven by epigenetic modifications. However, it remains unknown whether some of these associations are already evident during foetal development. Similar biological signals shape the developmental processes in the foetal brain and placenta.Therefore, we hypothesize that green space can modify epigenetic processes of cognition-related pathways in placental tissue, such as DNA-methylation of the serotonin receptor HTR2A. HTR2A-methylation was determined within 327 placentas from the ENVIRONAGE (ENVIRonmental influence ON early AGEing) birth cohort using bisulphite-PCR-pyrosequencing. Total green space exposure was calculated using high-resolution land cover data derived from the Green Map of Flanders in seven buffers (50 m-3 km) and stratified into low (

Background: Residential green space may improve human health, for example by promoting physical activity and by reducing stress. Conversely, residential green space may increase stress by emitting aeroallergens and exacerbating allergic disease. Here we examine impacts of exposure to residential green space on distress in the susceptible subpopulation of adults sensitized to tree pollen allergens. Methods: In a panel study of 88 tree pollen allergy patients we analyzed self-reported mental health (GHQ-12), perceived presence of allergenic trees (hazel, alder, birch) near the residence and residential green space area within 1 km distance [high (>= 3 m) and low (< 3 m) green]. Results were adjusted for patients' background data (gender, age, BMI, smoking status, physical activity, commuting distance, education level, allergy medication use and chronic respiratory problems) and compared with distress in the general population (N = 2467). Results: Short-term distress [mean GHQ-12 score 2.1 (95% confidence interval 1.5-2.7)] was higher in the study population than in the general population [1.5 (1.4-1.7)]. Residential green space had protective effects against short-term distress [high green, per combined surface area of 10 ha: adjusted odds ratio OR = 0.94 (95% confidence interval 0.90-0.99); low green, per 10 ha: OR = 0.85 (0.78-0.93)]. However, distress was higher in patients who reported perceived presence of allergenic trees near their residence [present vs. absent: OR = 2.04 (1.36-3.07)]. Conclusions: Perceived presence of allergenic tree species in the neighbourhood of the residence of tree pollen allergy patients modulates the protective effect of residential green space against distress during the airborne tree pollen season. The RespirIT study has been supported by a project grant from the Belgian Science Policy Office BELSPO (grant nr. BR/154/A1/RespirIT). The GHQ-12 questionnaire was used under license from GL Assessment Ltd. Aerts, R (reprint author), Sciensano, Juliette Wytsmanstr 14, BE-1050 Brussels, Belgium. raf.aerts@sciensano.be

Mapping the distribution of allergenic plants in urbanized landscapes is of high importance to evaluate its impact on human health. However, data is not always available for the allergy-relevant species such as alder, birch, hazel, especially within cities where systematic inventories are often missing or not readily available. This research presents an approach to produce high-resolution abundance maps of allergenic tree species using existing forest inventories and opportunistic open-access citizen science data. Following a two-step approach, we first built species distribution models (SDMs) to predict species habitat suitability, using environmental characteristics as predictors. Second, we used statistical regressions to model the relationships between abundance, the habitat suitability predicted by the SDMs, and additional vegetation cover covariates. The combination of forest inventory data with citizen science data improves the accuracy of abundance distribution models of allergenic tree species. This produces a continuous, 1-hectare resolution map of alder, birch, and hazel showing spatial variations of abundance distributions both within the urban fabric and along the urban–rural gradient. Species abundance modelling can offer a better understanding of the existing and potential future allergy risk posed by green spaces and pave the way for a wide variety of applications at fine-scale, which is indispensable for evidence-based urban green space policy and planning in support of public health. ispartof: Landscape And Urban Planning vol:218 status: Published online

Background: The prevalence of pollen allergy has increased due to urbanization, climate change and air pollution. The effects of green space and air pollution on respiratory health of pollen allergy patients are complex and best studied in spatio-temporal detail. Methods:We tracked 144 adults sensitized to Betulaceae pollen during the tree pollen season (January–May) of 2017 and 2018 and assessed their spatio-temporal exposure to green space, allergenic trees, air pollutants and birch pollen. Participants reported daily symptom severity scores.We extracted 404 case days with high symptomseverity scores and matched these to 404 control days. The data were analyzed using conditional logistic regression with a 1:1 case-crossover design. Results: Case days were associated with exposure to birch pollen concentration (100 grains/m3) [adjusted odds ratio 1.045 and 95% confidence interval (1.014–1.078)], O3 concentration (10 μg/m3) [1.504 (1.281–1.766)] and PM10 concentration (10 μg/m3) [1.255 (1.007–1.565)] on the day of the severe allergy event andwith the cumulative exposure of one and two days before. Exposure to grass cover (10% area fraction) [0.655 (0.446–0.960)], forest cover (10% area fraction) [0.543 (0.303–0.973)] and density of Alnus (10%) [0.622 (0.411–0.942)] were protective for severe allergy, but only on the day of the severe allergy event. Increased densities of Betula trees (10%) were a risk factor [unadjusted OR: 2.014 (1.162–3.490)]. Conclusion: Exposure to green space may mitigate tree pollen allergy symptom severity but only when the density of allergenic trees is low. Air pollutants contribute to more severe allergy symptoms. Spatio-temporal tracking allows for a more realistic exposure assessment. ispartof: Science Of The Total Environment vol:781 ispartof: location:Netherlands status: Published online

We studied residential green space exposure of 157 adults with tree pollen allergy. Residential green space was associated with reduced mental distress and perceived stress. Allergenic tree species within 2 km distance contributed to mental distress. Residential green space exposure was associated with more severe allergy symptoms. Green space had mixed health effects during the pollination season. ispartof: Landscape And Urban Planning vol:210 status: published

Airborne pollen are important aeroallergens affecting human health. Local airborne pollen compositions can pose health-risks for the sensitized population, but at present little is known about fine-scale pollen composition patterns. The overall objective of this study is to determine local variations in tree pollen composition with passive samplers and to identify the surrounding landscape characteristics that drive them. In February–May 2017, during the tree pollen season, airborne tree pollen were measured by passive sampling at 2 m height above ground-level in 14 sites in the Flanders and Brussels-Capital region (Belgium). Non-metric multidimensional scaling was used to investigate environmental gradients that determine the pollen composition and amounts. Land cover types were identified across spatial scales ranging between 20 m and 5 km. The passive samplers detected the same pollen taxa during the same time windows as the validated volumetric Burkard samplers. Using passive samplers, we were able to measure local airborne pollen compositions. Corylus and Platanus pollen were associated to urban areas; Populus, Juglans and Fraxinus pollen to agricultural areas; forests and wetlands were sources of Alnus and Quercus pollen. Salix, Populus and Betula pollen were also mainly associated to wetlands. The landscape context drives the airborne tree pollen composition at a meso-scale (1−5 km) rather than at finer scale (20−500 m). Thus, land cover types (e.g. forest, bush land, agricultural lands and wetlands) surrounding urban areas may increase exposure to allergenic pollen in the urban area, potentially affecting the health of a large proportion of the population. ispartof: Urban Forestry & Urban Greening vol:61 status: published

Trees provide ecosystem services that improve the environment and human health. The magnitude of these improvements may be related to tree diversity within green spaces, yet spatially explicit diversity data necessary to investigate such associations are often missing. Here, we evaluate two methods to model tree diversity at genus level based on environmental covariates and presence point data. We want to identify the drivers and suitable methods for urban and rural tree diversity models in the heterogeneous region of Flanders, Belgium. We stratified our research area into dominantly rural and dominantly urban areas and developed distribution models for 13 tree genera for both strata as well as for the area as a whole. Occurrence data were obtained from an open-access presence-only database of validated observations of vascular plants. These occurrence data are combined with environmental covariates in MaxEnt models. Tree diversity is modelled by adding up the individual species distribution models. Models in the dominantly rural areas are driven by soil characteristics (soil texture and drainage class). Models in the dominantly urban areas are driven by environmental covariates explaining urban heterogeneity. Nevertheless, the stratification into urban and rural did not contribute to a higher model quality. Generic tree diversity estimates were better when presences derived from distribution models were simply added up (binary stacking, True Positive Rate of 0.903). The application of macro-ecological constraints resulted in an underestimation of generic tree diversity (probability stacking, True Positive Rate of 0.533). We conclude that summing presences derived from species distribution models (binary stacking) is a suitable approach to increase knowledge on regional diversity. ispartof: Landscape And Urban Planning vol:198 status: Published online

This study compares two machine learning algorithms to predict regional winter wheat yields. The models, based on Boosted Regression Trees (BRT) and Support Vector Machines (SVM), are constructed of Normalized Difference Vegetation Indices (NDVI) derived from low resolution SPOT VEGETATION imagery. Three types of NDVI-related predictors were used: Single NDVI, Incremental NDVI and Targeted NDVI. BRT and SVM were first used to select features with high relevance for predicting the yield. Periods of high influence spanning from March to June were detected by both machine learning methods. After feature selection, BRT and SVM models were applied to the subset of selected features for yield forecasting. BRT seems to consistently outperform SVM.