“Biophilic Cities”: Quantifying the Impact of Google Street View-Derived Greenspace Exposures on Socioeconomic Factors and Self-Reported Healthh

[Image: see text] According to the biophilia hypothesis, humans have evolved to prefer natural environments that are essential to their thriving. With urbanization occurring at an unprecedented rate globally, urban greenspace has gained increased attention due to its environmental, health, and socioeconomic benefits. To unlock its full potential, an increased understanding of greenspace metrics is urgently required. In this first-of-a-kind study, we quantified street-level greenspace using 751 644 Google Street View images and computer vision methods for 125 274 locations in Ireland’s major cities. We quantified population-weighted exposure to greenspace and investigated the impact of greenspace on health and socioeconomic determinants. To investigate the association between greenspace and self-reported health, a negative binomial regression analysis was applied. While controlling for other factors, an interquartile range increase in street-level greenspace was associated with a 2.78% increase in self-reported “good or very good” health [95% confidence interval: 2.25–3.31]. Additionally, we observed that populations in upper quartiles of greenspace exposure had higher levels of income and education than those in lower quartiles. This study provides groundbreaking insights into how urban greenspace can be quantified in unprecedented resolution, accuracy, and scale while also having important implications for urban planning and environmental health research and policy

Modelling & Spatial Mapping of Residential-Sector Emissions for Sub-National & Urban Areas

The residential sector accounts for 33% of energy-related Greenhouse Gas (GHG) emissions globally and must undergo rapid emissions reductions in order to support broader society-wide sustainability and net-zero transitions. Additionally, urban areas account for approximately 70% of global GHG emissions. To provide a baseline for urban climate action plans and mitigation strategies, sub-national municipalities must quantify their sectoral baseline emissions in detail and develop strategies for reducing emissions relative to these baselines. Therefore, it is important to establish clear methodologies for computing these baselines in accordance with the best available science. This paper establishes a novel methodology for developing a residential sector emissions model using a data-driven and spatial mapping approach. This would form an important component of future multi-sectoral baseline emissions inventories. • The residential sector emissions model combines publicly available census and building energy performance datasets in order to model and visualize the distribution of energy demand and resultant emissions across an urban study domain in Ireland. • The methodology presented was developed in line with the approaches and requirements of the Global Covenant of Mayors and the Intergovernmental Panel on Climate Change. • It is envisioned that this residential sector emissions model methodology could be applied in any urban area worldwide

Associations between ambient particle radioactivity and lung function

Previous studies have suggested increased risk of respiratory diseases and mortality following short-term exposures to ionizing radiation. However, the short-term respiratory effects of low-level environmental radiation associated with air pollution particles have not been considered. Although ambient particulate matter (PM) has been reproducibly linked to decreased lung function and to increased respiratory related morbidity, the properties of PM promoting its toxicity are uncertain. As such, we evaluated whether lung function was associated with exposures to radioactive components of ambient PM, referred to as particle radioactivity (PR). For this, we performed a repeated-measures analysis of 839 men to examine associations between PR exposure and lung function using mixed-effects regression models, adjusting for potential confounders. We examined whether PR-lung function associations changed after adjusting for PM2.5 (particulate matter≤2.5 μm) or black carbon, and vice versa. PR was measured by the USEPA\u27s radiation monitoring network. We found that higher PR exposure was associated with a lower forced vital capacity (FVC) and forced expiratory volume in 1 second (FEV1). An IQR increase in 28-day PR exposure was associated with a 2.4% lower FVC [95% confidence interval (CI): 1.4, 3.4% p < 0.001] and a 2.4% lower FEV1 (95% CI: 1.3, 3.5%, p < 0.001). The PR-lung function associations were partially attenuated with adjustment for PM2.5 and black carbon. This is the first study to demonstrate associations between PR and lung function, which were independent of and similar in magnitude to those of PM2.5 and black carbon. If confirmed, future research should account for PR exposure in estimating respiratory health effects of ambient particles. Because of widespread exposure to low levels of ionizing radiation, our findings may have important implications for research, and environmental health policies worldwide

Associations Between Ambient Particle Radioactivity and Blood Pressure: The NAS (Normative Aging Study)

Background: The cardiovascular effects of low‐level environmental radiation exposures are poorly understood. Although particulate matter (PM) has been linked to cardiovascular morbidity and mortality, and elevated blood pressure (BP), the properties promoting its toxicity remain uncertain. Addressing a knowledge gap, we evaluated whether BP increased with higher exposures to radioactive components of ambient PM, herein referred to as particle radioactivity (PR). Methods and Results: We performed a repeated‐measures analysis of 852 men to examine associations between PR exposure and BP using mixed‐effects regression models. As a surrogate for PR, we used gross β activity, measured by the US Environmental Protection Agency's radiation monitoring network. Higher PR exposure was associated with increases in both diastolic BP and systolic BP, for exposures from 1 to 28 days. An interquartile range increase in 28‐day PR exposure was associated with a 2.95–mm Hg increase in diastolic BP (95% confidence interval, 2.25–3.66; P<0.001) and a 3.94–mm Hg increase in systolic BP (95% confidence interval, 2.62–5.27; P<0.001). For models including both PR and PM ≤2.5 µm, the PR‐BP associations remained stable and significant. For models including PR and black carbon or PR and particle number, the PR‐BP associations were attenuated; however, they remained significant for many exposure durations. Conclusions: This is the first study to demonstrate the potential adverse effects of PR on both systolic and diastolic BPs. These were independent and similar in magnitude to those of PM ≤2.5 µm, black carbon, and particle number. Understanding the effects of particle‐bound radionuclide exposures on BP may have important implications for environmental and public health policy