The Green Heart Project is a community-based trial to evaluate the effects of increasing greenery on urban environment and community health. The study was initiated in 2018 in a low-to-middle-income mixed-race residential area of nearly 28,000 residents in Louisville, KY. The 4 square mile area was surveyed for land use, population characteristics, and greenness, and assigned to 8 paired clusters of demographically- and environmentally matched "target" (T) and adjacent "control" (C), clusters. Ambient levels of ultrafine particles, ozone, oxides of nitrogen, and environmental noise were measured in each cluster. Individual-level data were acquired during in-person exams of 735 participants in Wave 1 (2018-2019) and 545 participants in Wave 2 (2021) to evaluate sociodemographic and psychosocial factors. Blood, urine, nail, and hair samples were collected to evaluate standard cardiovascular risk factors, inflammation, stress, and pollutant exposure. Cardiovascular function was assessed by measuring arterial stiffness and flow-mediated dilation. After completion of Wave 2, more than 8,000 mature, mostly evergreen, trees and shrubs were planted in the T clusters in 2022. Post planting environmental and individual-level data were collected during Wave 3 (2022) from 561 participants. We plan to continue following changes in area characteristics and participant health to evaluate the long-term impact of increasing urban greenery.

INTRODUCTION:Previous investigations have reported that individuals living in greener neighborhoods have better cardiovascular health. It is unclear whether the effects reported at large geographic scales persist when examined at an intra-neighborhood level. The effects of greenness have not been thoroughly examined using high-resolution metrics of greenness exposure, and how they vary with spatial scales of assessment or participant characteristics. METHODS:We conducted a cross-sectional assessment of associations between blood pressure and multiple high-resolution measures of residential area greenness in spatially concentrated HEAL Study cohort of the Green Heart Project. We employed generalized linear models, accounting for individual-level covariates, to examine associations between different high-resolution measures of greenness and blood pressure among 667 participants in a 4 sq. mile contiguous neighborhood area in Louisville, KY. RESULTS:In adjusted models, we observed significant inverse associations between residential greenness, measured by leaf area index (LAI), and systolic blood pressure (SBP) within 150-250 m and 500 m of homes, but not for Normalized Difference Vegetation Index (NDVI) or grass cover. Weaker associations were also found with diastolic blood pressure (DBP). Significant positive associations were observed between LAI and SBP among participants who reported being female, White, without obesity, non-exercisers, non-smokers, younger age, of lower income, and who had high nearby roadway traffic. We found few significant associations between grass cover and SBP, but an inverse association in those with obesity, but positive associations for those without obesity. CONCLUSIONS:We found that leaf surface area of trees around participants home is strongly associated with lower blood pressure, with little association with grass cover. These effects varied with participant characteristics and spatial scales. More research is needed to test causative links between greenspace types and cardiovascular health and to develop population-, typology-, and place-based evidence to inform greening interventions.

The extent to which urban vegetation improves environmental quality and affects the health of nearby residents is dependent on typological attributes of “greenness”, such as canopy area to alleviate urban heat, grass to facilitate exercise and social interaction, leaf area to disperse and capture air pollution, and biomass to absorb noise pollution. The spatial proximity of these typologies to individuals further modifies the extent to which they impart benefits and influence health. However, most evaluations of associations between greenness and health utilize a single metric of greenness and few measures of proximity, which may disproportionately represent the effect of a subset of mediators on health outcomes. To develop an approach to address this potentially substantial limitation of future studies evaluating associations between greenness and health, we measured and evaluated distinct attributes, correlations, and spatial dependency of 13 different metrics of greenness in a residential study area of Louisville, Kentucky, representative of many urban residential areas across the Eastern United States. We calculated NDVI, other satellite spectral indices, LIDAR derived leaf area index and canopy volume, streetview imagery derived semantic view indices, distance to parks, and graph-theory based ecosystem connectivity metrics. We utilized correlation analysis and principal component analysis across spatial scales to identify distinct groupings and typologies of greenness metrics. Our analysis of correlation matrices and principal component analysis identified distinct groupings of metrics representing both physical correlates of greenness (trees, grass, their combinations and derivatives) and also perspectives on those features (streetview, aerial, and connectivity / distance). Our assessment of typological greenness categories contributes perspective important to understanding strengths and limitations of metrics evaluated by past work correlating greenness to health. Given our finding of inconsistent correlations between many metrics and scales, it is likely that many past investigations are missing important context and may underrepresent the extent to which greenness may influence health. Future epidemiological investigations may benefit from these findings to inform selection of appropriate greenness metrics and spatial scales that best represent the cumulative influence of the hypothesized effects of mediators and moderators. However, future work is needed to evaluate the effect of each of these metrics on health outcomes and mediators therein to better inform the understanding of metrics and differential influences on environments and health.

Associations between neighborhood greenness and socioeconomic status (SES) are established, yet intraneighborhood context and SES-related barriers to tree planting remain unclear. Large-scale tree planting implementation efforts are increasingly common and can improve human health, strengthen climate adaptation, and ameliorate environmental inequities. Yet, these efforts may be ineffective without in-depth understanding of local SES inequities and barriers to residential planting. We recruited 636 residents within and surrounding the Oakdale Neighborhood of Louisville, Kentucky, USA, and evaluated associations of individual and neighborhood-level sociodemographic indicators with greenness levels at multiple scales. We offered no-cost residential tree planting and maintenance to residents within a subsection of the neighborhood and examined associations of these sociodemographic indicators plus baseline greenness levels with tree planting adoption among 215 eligible participants. We observed positive associations of income with Normalized Difference Vegetation Index (NDVI) and leaf area index (LAI) within all radii around homes, and within yards of residents, that varied in strength. There were stronger associations of income with NDVI in front yards but LAI in back yards. Among Participants of Color, associations between income and NDVI were stronger than with Whites and exhibited no association with LAI. Tree planting uptake was not associated with income, education, race, nor employment status, but was positively associated with lot size, home value, lower population density, and area greenness. Our findings reveal significant complexity of intra-neighborhood associations between SES and greenness that could help shape future research and equitable greening implementation. Results show that previously documented links between SES and greenspace at large scales extend to residents' yards, highlighting opportunities to redress greenness inequities on private property. Our analysis found that uptake of no-cost residential planting and maintenance was nearly equal across SES groups but did not redress greenness inequity. To inform equitable greening, further research is needed to evaluate culture, norms, perceptions, and values affecting tree planting acceptance among low-SES residents.

The transition of the automotive industry towards electro-mobility is highly dependent on the performance of batteries. Those batteries need a temperature management system, often realized as sheet metal cold plates with integrated channel structures for liquid cooling. Rollbonding technology is one of the most promising methods for industrial mass production of battery cooling systems in the automotive industry due to its competitive cost for low and high-volume applications and its great degree of design freedom. Designing cold plates is a challenging task due to conflicting thermal and hydraulic objectives, manufacturing requirements and the enormous design freedom offered by the rollbondig technology. Topology optimization is a well-known method for optimal design in multi-physics problems, such as cold plate design. Using a thermofluid topology optimization, the optimum channel patterns in a given design space can be found. However, the industrial application of such a design approach is challenging, as well-established topology optimization software often is designed for a wide variety of applications and, therefore, lacks manufacturing constraints and parametrization strategies feasible for the specific production process. This paper demonstrates how well-known parametrization and optimization strategies can be combined and adapted to generate topologies feasible for the manufacturing of cold plates by rollbonding. The integration of commercial solvers into an external, solver agnostic framework, considering custom manufacturing, continuation and filtering strategies is demonstrated. A density-based topology optimization is applied to the linear potential Darcy flow model, considering length scale constraints on the solid and fluid domain. A specific constraint is developed to assure the manufacturability of the design using the rollbonding technology. Further, a feasible continuation strategy considering projection parameters, penalization and length scale constraint activation and continuation is presented. The temperature distribution is optimized while considering pressure drop and manufacturing requirements. The topology optimization results are remodeled and validated using a high-fidelity RANS solver. The thermal-hydraulic performance is compared with a manually designed benchmark cold plate. Finally manufacturability of the outcomes is evaluated to prove the successful application of the proposed design technology.

Background and aim: Residential greenness, often measured through NDVI, has been linked to cardiovascular disease (CVD) outcomes and associated risk factors. However, physiological mechanisms underlying these associations are not well understood, nor is the influence of differing types and scales of greenness. Therefore, we examined associations between CVD risk markers of systolic blood pressure (SBP) and arterial index (AI), a measure of arterial stiffness, with residential greenness at multiple greenness metrics and spatial scales. Methods: We recruited 723 adult participants from a 4.5sqmi area of Louisville, Kentucky, USA, and measured SBP and AI. We collected high resolution greenness metrics of NDVI, canopy, and leaf area in spatial radii of 20m to 500m around participants' residence via Aerial LiDAR and Sentinel-2 satellite imagery. We utilized adjusted linear regression with a hierarchical modeling approach to examine associations between greenness and hemodynamic markers. Results: We observed inverse associations between SBP and multiple greenness metrics at radii of 300m and 500m (-0.26 to -2.66% per IQR), but not 20m or 100m. We observed inverse associations between AI and metrics of greenness with all models at a 100m radius (-1.41 to -2.25% per IQR), but only leaf area and models with basic adjustments at 300m and 500m radii (-1.79 and -1.9% per IQR). When stratified, we observed significant associations between greenness and SBP among only females and those with higher levels of education. Among stratified results between greenness and AI, we observed significant associations only in females, participants <50 years of age, and higher educational attainment. Conclusions: Greenness is associated with hemodynamic markers of SBP and AI with inconsistent associations between metrics and spatial scales. Future investigations of such high-resolution data may inform links between greenness and health and could help to design targeted greening interventions to address CVD. Keywords: Greenness, Blood Pressure, Hypertension, CVD

Exposure to greenness has been studied through objective measures of remote visualization of greenspace; however, the link to how individuals interpret spaces as green is missing. We examined the associations between three objective greenspace measures with perceptions of greenness. We used a subsample (n = 175; 2018–2019) from an environmental cardiovascular risk cohort to investigate perceptions of residential greenness. Participants completed a 17-item survey electronically. Objective measurements of greenness within 300 m buffer around participants home included normalized difference vegetation index (NDVI), tree canopy and leaf area index. Principal component analysis reduced the perceived greenspaces to three dimensions reflecting natural vegetation, tree cover and built greenspace such as parks. Our results suggest significant positive associations between NDVI, tree canopy and leaf area and perceived greenness reflecting playgrounds; also, associations between tree canopy and perceived greenness reflecting tree cover. These findings indicate that the most used objective greenness measure, NDVI, as well as tree canopy and leaf area may most align with perceptions of parks, whereas tree canopy alone captures individuals’ perceptions of tree cover. This highlights the need for research to understand the complexity of green metrics and careful interpretation of data based on the use of subjective or objective measures of greenness.