Urban heat island mitigation by green infrastructure in European Functional Urban Areas

The Urban Heat Island (UHI) effect is one of the most harmful environmental hazards for urban dwellers. Climate change is expected to increase the intensity of the UHI effect. In this context, the implementation of Urban Green Infrastructure (UGI) can partially reduce UHI intensity, promoting a resilient urban environment and contributing to climate change adaptation and mitigation. In order to achieve this result, there is a need to systematically integrate UGI into urban planning and legislation, but this process is subject to the availability of widely applicable, easily accessible and quantitative evidence. To offer a big picture of urban heat intensity and opportunities to mitigate high temperatures, we developed a model that reports the Ecosystem Service (ES) of microclimate regulation of UGI in 601 European cities. The model simulates the temperature difference between a baseline and a no-vegetation scenario, extrapolating the role of UGI in mitigating UHI in different urban contexts. Finally, a practical, quantitative indicator that can be applied by policymakers and city administrations has been elaborated, allowing to estimate the amount of urban vegetation that is needed to cool summer temperatures by a certain degree. UGI is found to cool European cities by 1.07 °C on average, and up to 2.9 °C, but in order to achieve a 1 °C drop in urban temperatures, a tree cover of at least 16% is required. The microclimate regulation ES is mostly dependent on the amount of vegetation inside a city and by transpiration and canopy evaporation. Furthermore, in almost 40% of the countries, more than half of the residing population does not benefit from the microclimate regulation service provided by urban vegetation. Widespread implementation of UGI, in particular in arid regions and cities with insufficient tree cover, is key to ensure healthy urban living conditions for citizens

Supporting Disaster Reconnaissance with Social Media Data: A DesignOriented Case Study of the 2013 Colorado Floods

ABSTRACT Engineering reconnaissance following an extreme event is critical in identifying the causes of infrastructure failure and minimizing such consequences in similar future events. Typically, however, much of the data about infrastructure performance and the progression of geological phenomena are lost during the event or soon after as efforts move to the recovery phase. A better methodology for reliable and rapid collection of perishable hazards data will enhance scientific inquiry and accelerate the building of disaster-resilient cities. In this paper, we explore ways to support post-event reconnaissance through the strategic collection and reuse of social media data and other remote sources of information, in response to the September 2013 flooding in Colorado. We show how tweets, particularly with postings of visual data and references to location, may be used to directly support geotechnical experts by helping to digitally survey the affected region and to navigate optimal paths through the physical space in preparation for direct observation

Hourly Price-Based Demand Response for Optimal Scheduling of Integrated Gas and Power Networks Considering Compressed Air Energy Storage

Gas-fired plants are becoming an optimal and practical choice for power generation in electricity grids due to high efficiency and less emissions. Such plants with fast start-up capability and high ramp rate are flexible in response to stochastic load variations. Meanwhile, gas system constraints affect the flexibility and participation of such units in the energy market. Compressed air energy storage (CAES) as a flexible source with high ramp rate can be an alternative solution to reduce the impact of gas system constraints on the operation cost of a power system. In addition, demand response (DR) programs are expressed as practical approaches to overcome peak-demand challenges. This study introduces a stochastic unit commitment scheme for coordinated operation of gas and power systems with CAES technology as well as application of an hourly price-based DR. The introduced model is performed on a six-bus system with a six-node gas system to verify the satisfactory performance of the model

Application of functionalized nanofluid in thermosyphon

A water-based functionalized nanofluid was made by surface functionalizing the ordinary silica nanoparticles. The functionalized nanofluid can keep long-term stability. and no sedimentation was observed. The functionalized nanofluid as the working fluid is applied in a thermosyphon to understand the effect of this special nanofluid on the thermal performance of the thermosyphon. The experiment was carried out under steady operating pressures. The same work was also explored for traditional nanofluid (consisting of water and the same silica nanoparticles without functionalization) for comparison. Results indicate that a porous deposition layer exists on the heated surface of the evaporator during the operating process using traditional nanofluid; however, no coating layer exists for functionalized nanofluid. Functionalized nanofluid can enhance the evaporating heat transfer coefficient, while it has generally no effect on the maximum heat flux. Traditional nanofluid deteriorates the evaporating heat transfer coefficient but enhances the maximum heat flux. The existence of the deposition layer affects mainly the thermal performance, and no meaningful nanofluid effect is found in the present study

Experimental and theoretical studies of nanofluid thermal conductivity enhancement: a review

Nanofluids, i.e., well-dispersed (metallic) nanoparticles at low- volume fractions in liquids, may enhance the mixture's thermal conductivity, knf, over the base-fluid values. Thus, they are potentially useful for advanced cooling of micro-systems. Focusing mainly on dilute suspensions of well-dispersed spherical nanoparticles in water or ethylene glycol, recent experimental observations, associated measurement techniques, and new theories as well as useful correlations have been reviewed

Global burden and strength of evidence for 88 risk factors in 204 countries and 811 subnational locations, 1990–2021: a systematic analysis for the Global Burden of Disease Study 2021

Background: Understanding the health consequences associated with exposure to risk factors is necessary to inform public health policy and practice. To systematically quantify the contributions of risk factor exposures to specific health outcomes, the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2021 aims to provide comprehensive estimates of exposure levels, relative health risks, and attributable burden of disease for 88 risk factors in 204 countries and territories and 811 subnational locations, from 1990 to 2021. Methods: The GBD 2021 risk factor analysis used data from 54 561 total distinct sources to produce epidemiological estimates for 88 risk factors and their associated health outcomes for a total of 631 risk–outcome pairs. Pairs were included on the basis of data-driven determination of a risk–outcome association. Age-sex-location-year-specific estimates were generated at global, regional, and national levels. Our approach followed the comparative risk assessment framework predicated on a causal web of hierarchically organised, potentially combinative, modifiable risks. Relative risks (RRs) of a given outcome occurring as a function of risk factor exposure were estimated separately for each risk–outcome pair, and summary exposure values (SEVs), representing risk-weighted exposure prevalence, and theoretical minimum risk exposure levels (TMRELs) were estimated for each risk factor. These estimates were used to calculate the population attributable fraction (PAF; ie, the proportional change in health risk that would occur if exposure to a risk factor were reduced to the TMREL). The product of PAFs and disease burden associated with a given outcome, measured in disability-adjusted life-years (DALYs), yielded measures of attributable burden (ie, the proportion of total disease burden attributable to a particular risk factor or combination of risk factors). Adjustments for mediation were applied to account for relationships involving risk factors that act indirectly on outcomes via intermediate risks. Attributable burden estimates were stratified by Socio-demographic Index (SDI) quintile and presented as counts, age-standardised rates, and rankings. To complement estimates of RR and attributable burden, newly developed burden of proof risk function (BPRF) methods were applied to yield supplementary, conservative interpretations of risk–outcome associations based on the consistency of underlying evidence, accounting for unexplained heterogeneity between input data from different studies. Estimates reported represent the mean value across 500 draws from the estimate's distribution, with 95% uncertainty intervals (UIs) calculated as the 2·5th and 97·5th percentile values across the draws. Findings: Among the specific risk factors analysed for this study, particulate matter air pollution was the leading contributor to the global disease burden in 2021, contributing 8·0% (95% UI 6·7–9·4) of total DALYs, followed by high systolic blood pressure (SBP; 7·8% [6·4–9·2]), smoking (5·7% [4·7–6·8]), low birthweight and short gestation (5·6% [4·8–6·3]), and high fasting plasma glucose (FPG; 5·4% [4·8–6·0]). For younger demographics (ie, those aged 0–4 years and 5–14 years), risks such as low birthweight and short gestation and unsafe water, sanitation, and handwashing (WaSH) were among the leading risk factors, while for older age groups, metabolic risks such as high SBP, high body-mass index (BMI), high FPG, and high LDL cholesterol had a greater impact. From 2000 to 2021, there was an observable shift in global health challenges, marked by a decline in the number of all-age DALYs broadly attributable to behavioural risks (decrease of 20·7% [13·9–27·7]) and environmental and occupational risks (decrease of 22·0% [15·5–28·8]), coupled with a 49·4% (42·3–56·9) increase in DALYs attributable to metabolic risks, all reflecting ageing populations and changing lifestyles on a global scale. Age-standardised global DALY rates attributable to high BMI and high FPG rose considerably (15·7% [9·9–21·7] for high BMI and 7·9% [3·3–12·9] for high FPG) over this period, with exposure to these risks increasing annually at rates of 1·8% (1·6–1·9) for high BMI and 1·3% (1·1–1·5) for high FPG. By contrast, the global risk-attributable burden and exposure to many other risk factors declined, notably for risks such as child growth failure and unsafe water source, with age-standardised attributable DALYs decreasing by 71·5% (64·4–78·8) for child growth failure and 66·3% (60·2–72·0) for unsafe water source. We separated risk factors into three groups according to trajectory over time: those with a decreasing attributable burden, due largely to declining risk exposure (eg, diet high in trans-fat and household air pollution) but also to proportionally smaller child and youth populations (eg, child and maternal malnutrition); those for which the burden increased moderately in spite of declining risk exposure, due largely to population ageing (eg, smoking); and those for which the burden increased considerably due to both increasing risk exposure and population ageing (eg, ambient particulate matter air pollution, high BMI, high FPG, and high SBP). Interpretation: Substantial progress has been made in reducing the global disease burden attributable to a range of risk factors, particularly those related to maternal and child health, WaSH, and household air pollution. Maintaining efforts to minimise the impact of these risk factors, especially in low SDI locations, is necessary to sustain progress. Successes in moderating the smoking-related burden by reducing risk exposure highlight the need to advance policies that reduce exposure to other leading risk factors such as ambient particulate matter air pollution and high SBP. Troubling increases in high FPG, high BMI, and other risk factors related to obesity and metabolic syndrome indicate an urgent need to identify and implement interventions