Urban heat and air pollution: A framework for integrating population vulnerability and indoor exposure in health risk analyses

Sociodemographic Determinants of Extreme Heat and Ozone Risk Among Older Adults in 3 Sun Belt Cities

BACKGROUND

Vulnerable populations across the United States are frequently exposed to extreme heat, which is becoming more intense due to a combination of climate change and urban-induced warming. Extreme heat can be particularly detrimental to the health and well-being of older citizens when it is combined with ozone. Although population-based studies have demonstrated associations between ozone, extreme heat, and human health, few studies focused on the role of social and behavioral factors that increase indoor risk and exposure among older adults.

METHODS

We conducted a household survey that aimed to understand how older adults are affected by extreme heat and ozone pollution inside and outside of their homes across Houston, Phoenix, and Los Angeles. We examine contributing factors to the risk of self-reported health effects using a generalized linear mixed-effects regression model of telephone survey data of 909 older adults in 2017.

RESULTS

We found an increased occurrence of self-reported symptoms for extreme heat with preexisting respiratory health conditions and a lack of air conditioning access; self-reported ozone symptoms were more likely with preexisting respiratory health conditions. The risk of heat-related symptoms was slightly higher in Los Angeles than Houston and Phoenix. We found several demographic, housing, and behavioral characteristics that influenced the risk of heat- and ozone-related symptoms.

CONCLUSIONS

The increased risk among older adults based on specific social and behavioral factors identified in this study can inform public health policy and help cities tailor their heat and ozone response plans to the specific needs of this vulnerable population.

Concurrent Heat and Air Pollution Exposures among People Experiencing Homelessness

BACKGROUND

Extreme heat and air pollution are important human health concerns; exposure can affect mental and physical well-being, particularly during periods of co-occurrence. Yet, the impacts on people are largely determined by underlying health conditions, coupled with the length and intensity of exposure. Preexisting adverse health conditions and prolonged exposure times are more common for people experiencing homelessness, particularly those with intersectional identity characteristics (e.g., disease, ability, age, etc.). Partially due to methodological limitations, such as data scarcity, there is a lack of research at the intersection of this at-risk population within the climate-health domain.

OBJECTIVES

We have three distinct objectives throughout this article: a) to advance critical discussions around the state of concurrent high heat and air pollution exposure research as it relates to people experiencing homelessness; b) to assert the importance of heat and air pollution exposure research among a highly vulnerable, too-often homogenized population-people experiencing homelessness; and c) to underline challenges in this area of study while presenting potential ways to address such shortcomings.

DISCUSSION

The health insights from concurrent air pollution and heat exposure studies are consequential when studying unhoused communities who are already overexposed to harmful environmental conditions. Without holistic data sets and more advanced methods to study concurrent exposures, appropriate and targeted prevention and intervention strategies cannot be developed to protect this at-risk population. We highlight that a) concurrent high heat and air pollution exposure research among people experiencing homelessness is significantly underdeveloped considering the pressing human health implications; b) the severity of physiological responses elicited by high heat and air pollution are predicated on exposure intensity and time, and thus people without means of seeking climate-controlled shelter are most at risk; and c) collaboration among transdisciplinary teams is needed to resolve data resolution issues and enable targeted prevention and intervention strategies. https://doi.org/10.1289/EHP13402.

Before the first breath: why ambient air pollution and climate change should matter to neonatal-perinatal providers

Common outdoor air pollutants present threats to fetal and neonatal health, placing neonatal-perinatal clinical specialists in an important role for harm reduction through patient counseling and advocacy. Climate change is intertwined with air pollution and influences air quality. There is increasing evidence demonstrating the unique vulnerability in the development of adverse health consequences from exposures during the preconception, prenatal, and early postnatal periods, as well as promising indications that policies aimed at addressing these toxicants have improved birth outcomes. Advocacy by neonatal-perinatal providers articulating the potential impact of pollutants on newborns and mothers is essential to promoting improvements in air quality and reducing exposures. The goal of this review is to update neonatal-perinatal clinical specialists on the key ambient air pollutants of concern, their sources and health effects, and to outline strategies for protecting patients and communities from documented adverse health consequences.

Revealing the practical strategies for promoting Chinese migrant workers' health and well-being: Organizational empowerment perspective

The health and well-being of migrant workers struggling to make ends meet are being compromised, especially with the uncertainty of the COVID-19 pandemic. The aim is to analyze how organizational empowerment promotes health and well-being from an applied psychological perspective, taking into account the shaping role of individual vulnerability. Links between theory and practice will be established to achieve equitable health and well-being. The underlying mechanism by which organizational empowerment mitigated workplace-induced adverse outcomes was validated in the analysis of construction workers (n = 966). In addition, individual characteristics, namely, excitability, low perceptual threshold, control, and knowledge, attitude, and practice, were identified as critical factors, as well-being consequences vary from person to person. Moderating effect analysis showed that high excitability enhanced the association between work environment exposure and health and well-being. Control and knowledge, attitude, and practice have opposite effects. Moreover, the dual effects of the low perception threshold are verified, that is, facing the work environment produces more negative consequences, whereas perceiving more resources stimulates more positive consequences. Overall, the research provides a clearer dialectical view of vulnerability, contributing wisdom toward accurate management based on empowerment theory, which lays a solid foundation for bridging gaps in health and well-being.

A Review of Artificial Neural Network Models Applied to Predict Indoor Air Quality in Schools

BACKGROUND

Indoor air quality (IAQ) in schools can affect the performance and health of occupants, especially young children. Increased public attention on IAQ during the COVID-19 pandemic and bushfires have boosted the development and application of data-driven models, such as artificial neural networks (ANNs) that can be used to predict levels of pollutants and indoor exposures.

METHODS

This review summarises the types and sources of indoor air pollutants (IAP) and the indicators of IAQ. This is followed by a systematic evaluation of ANNs as predictive models of IAQ in schools, including predictive neural network algorithms and modelling processes. The methods for article selection and inclusion followed a systematic, four-step process: identification, screening, eligibility, and inclusion.

RESULTS

After screening and selection, nine predictive papers were included in this review. Traditional ANNs were used most frequently, while recurrent neural networks (RNNs) models analysed time-series issues such as IAQ better. Meanwhile, current prediction research mainly focused on using indoor PM2.5 and CO2 concentrations as output variables in schools and did not cover common air pollutants. Although studies have highlighted the impact of school building parameters and occupancy parameters on IAQ, it is difficult to incorporate them in predictive models.

CONCLUSIONS

This review presents the current state of IAQ predictive models and identifies the limitations and future research directions for schools.

Unpacking the inter- and intra-urban differences of the association between health and exposure to heat and air quality in Australia using global and local machine learning models

Environmental stressors including high temperature and air pollution cause health problems. However, understanding how the combined exposure to heat and air pollution affects both physical and mental health remains insufficient due to the complexity of such effects mingling with human society, urban and natural environments. Our study roots in the Social Ecological Theory and employs a tri-environmental conceptual framework (i.e., across social, built and natural environment) to examine how the combined exposure to heat and air pollution affect self-reported physical and mental health via, for the first time, the fine-grained nationwide investigation in Australia and highlight how such effects vary across inter- and intra-urban areas. We conducted an ecological study to explore the importance of heat and air quality to physical and mental health by considering 48 tri-environmental confounders through the global and local random forest regression models, as advanced machine learning methods with the advantage of revealing the spatial heterogeneity of variables. Our key findings are threefold. First, the social and built environmental factors are important to physical and mental health in both urban and rural areas, and even more important than exposure to heat and air pollution. Second, the relationship between temperature and air quality and health follows a V-shape, reflecting people's different adaptation and tolerance to temperature and air quality. Third, the important roles that heat and air pollution play in physical and mental health are most obvious in the inner-city and near inner-city areas of the major capital cities, as well as in the industrial zones in peri-urban regions and in Darwin city with a low-latitude. We draw several policy implications to minimise the inter- and intra-urban differences in healthcare access and service distribution to populations with different sensitivity to heat and air quality across urban and rural areas. Our conceptual framework can also be applied to examine the relationship between other environmental problems and health outcomes in the era of a warming climate.

Mapping health vulnerability to short-term summer heat exposure based on a directional interaction network: Hotspots and coping strategies

Health risk resulting from non-optimal temperature exposure, referred to as "systematic risk", has been a sustainable-development challenge in the context of global warming. Previous studies have recognized interactions between and among system components while assessing the vulnerability to climate change, but have left open the question of indicator directional interactions. The question is important, not least because indicator directional association analysis provides guidance to address climate risks by revealing the key nodes and pathways. The purpose of this work was to assess health vulnerability to short-term summer heat exposure based on a directional interaction network. Bayesian network model and network analysis were used to conduct a directional interaction network. Using indicator directional associations as weights, a weighted technique for the order of preference by similarity to ideal solution method was then proposed to assess heat-related health vulnerability. Finally, hotspots and coping strategies were explored based on the directional interaction network and health vulnerability assessments. The results showed that (1) indicator directional interactions were revealed in the health vulnerability framework, and the interactions differed between northern and southern China; (2) there was a dramatic spatial imbalance of health vulnerability in China, with the Beijing-Tianjin-Hebei Region and the Yangtze River Basin identified as hotspots; (3) particulate matter and ozone were recognized as priority indicators in the most vulnerable cities of northern China, while summer heat exposure level and variation were priority indicators in southern China; and (4) adaptive capacity could alter the extent of risk; thus, mitigation and adaptation should be implemented in an integrated way. Our study has important implications for strengthening the theoretical basis for the vulnerability assessment framework by providing indicator directional associations and for guiding policy design in dealing with heat-related health vulnerability in China.

Geographic and demographic variation in worry about extreme heat and COVID-19 risk in summer 2020

Extreme heat is a major health hazard that is exacerbated by ongoing human-caused climate change. However, how populations perceive the risks of heat in the context of other hazards like COVID-19, and how perceptions vary geographically, are not well understood. Here we present spatially explicit estimates of worry among the U.S. public about the risks of heat and COVID-19 during the summer of 2020, using nationally representative survey data and a multilevel regression and poststratification (MRP) model. Worry about extreme heat and COVID-19 varies both across states and across demographic groups, in ways that reflect disparities in the impact of each risk. Black or African American and Hispanic or Latino populations, who face greater health impacts from both COVID-19 and extreme heat due to institutional and societal inequalities, also tend to be much more worried about both risks than white, non-Hispanic populations. Worry about heat and COVID-19 were correlated at the individual and population level, and patterns tended to be related to underlying external factors associated with the risk environment. In the face of a changing climate there is an urgent need to address disparities in heat risk and develop responses that ensure the most at-risk populations are protected.

Spatial Differentiation of PM2.5 Concentration and Analysis of Atmospheric Health Patterns in the Xiamen-Zhangzhou-QuanZhou Urban Agglomeration

Exploring the spatial differentiation of PM2.5 concentrations in typical urban agglomerations and analyzing their atmospheric health patterns are necessary for building high-quality urban agglomerations. Taking the Xiamen-Zhangzhou-Quanzhou urban agglomeration as an example, and based on exploratory data analysis and mathematical statistics, we explore the PM2.5 spatial distribution patterns and characteristics and use hierarchical analysis to construct an atmospheric health evaluation system consisting of exposure-response degree, regional vulnerability, and regional adaptation, and then identify the spatial differentiation characteristics and critical causes of the atmospheric health pattern. This study shows the following: (1) The average annual PM2.5 value of the area in 2020 was 19.16 μg/m3, which was lower than China's mean annual quality concentration limit, and the overall performance was clean. (2) The spatial distribution patterns of the components of the atmospheric health evaluation system are different, with the overall cleanliness benefit showing a "north-central-south depression, the rest of the region is mixed," the regional vulnerability showing a coastal to inland decay, and the regional adaptability showing a "high north, low south, high east, low west" spatial divergence pattern. (3) The high-value area of the air health pattern of the area is an "F-shaped" spatial distribution; the low-value area shows a pattern of "north-middle-south" peaks standing side by side. The assessment of health patterns in the aforementioned areas can provide theoretical references for pollution prevention and control and the construction of healthy cities.

"When people see me, they know me; they trust what I say": characterizing the role of trusted sources for smoke risk communication in the Okanogan River Airshed Emphasis Area

INTRODUCTION

As wildfire smoke events increase in intensity and frequency in the Pacific Northwest, there is a growing need for effective communication on the health risks of smoke exposure. Delivery through a trusted source or intermediary has been shown to improve reception of risk communication messages. This is especially salient in rural and tribal communities who may be hesitant to trust information from state and federal agency sources. This study aims to identify and characterize trusted sources for smoke risk information in the Okanogan River Airshed Emphasis Area (ORAEA), a rural region of North Central Washington state that is heavily impacted by smoke from wildfires and prescribed fire.

METHODS

The research team conducted a qualitative study using data collected through key informant interviews and focus groups to assess the role of various sources and intermediaries in disseminating smoke risk information. We used a consensual coding approach in NVivo Qualitative Analysis Software to sort data into preliminary categories, which were grouped into themes using a thematic analysis approach. We used member checking and iterative feedback processes with local project partners throughout the project to ensure credibility of results.

RESULTS

Through the analysis, we identified three themes characterizing trusted sources for smoke risk communication in the ORAEA. These themes were: (1) local and tribal sources of information are perceived as more trustworthy than state and federal government sources, (2) trustworthiness is determined by an evaluation of multiple factors, in particular, perceived credibility, quality of information, and relationship with the source, and (3) conservative political ideology and perceived parallels with COVID-19 communication influence perception of trust. Within each theme, we identified several sub-themes, which contributed additional nuance to our analysis.

CONCLUSION

This study provides insights into which sources of information are trusted by rural and tribal community members in the ORAEA and why. Results from our study emphasize the importance of relationships and collaboration with local and tribal partners in smoke risk communication. In this paper, we discuss implications for state and federal agency practitioners and present recommendations for how to work with local and tribal partners on smoke risk communication.

Vector maps and spatial autocorrelation of carbon emissions at land patch level based on multi-source data

An accurate carbon emissions map is of great significance for urban planning to reduce carbon emissions, mitigate the heat island effect, and avoid the impact of high temperatures on human health. However, little research has focused on carbon emissions maps at the land patch level, which makes poor integration with small and medium-sized urban planning based on land patches. In this study, a vectorization method for spatial allocation of carbon emissions at the land patch level was proposed. The vector maps and spatial autocorrelation of carbon emissions in Zhangdian City, China were explored using multi-source data. In addition, the differences between different streets were analyzed, and the carbon emissions ratio of the land patch was compared. The results show that the vector carbon emissions map can help identify the key carbon reduction land patches and the impact factors of carbon emissions. The vector maps of Zhangdian City show that in 2021, the total carbon emissions and carbon absorptions were 4.76 × 10⁹kg and 4.28 × 10⁶kg respectively. Among them, industrial land accounted for 70.16% of carbon emissions, mainly concentrated in three industrial towns. Forest land carbon absorption accounted for 98.56%, mainly concentrated in the peripheral streets away from urban areas. The Moran's I of land patch level carbon emissions was 0.138, showing a significant positive spatial correlation. The proportion of land patches is an important factor in determining carbon emissions, and the adjustment of industrial structure is the most critical factor in reducing carbon emissions. The results achieved can better help governments develop different carbon reduction strategies, mitigate the heat island effect, and support low-carbon and health-oriented urban planning.

A holistic modeling framework for estimating the influence of climate change on indoor air quality

The IPCC 2021 report predicts rising global temperatures and more frequent extreme weather events in the future, which will have different effects on the regional climate and concentrations of ambient air pollutants. Consequently, changes in heat and mass transfer between the inside and outside of buildings will also have an increasing impact on indoor air quality. It is therefore surprising that indoor spaces and occupant well-being still play a subordinate role in the studies of climate change. To increase awareness for this topic, the Indoor Air Quality Climate Change (IAQCC) model system was developed, which allows short and long-term predictions of the indoor climate with respect to outdoor conditions. The IAQCC is a holistic model that combines different scenarios in the form of submodels: building physics, indoor emissions, chemical-physical reaction and transformation, mold growth, and indoor exposure. IAQCC allows simulation of indoor gas and particle concentrations with outdoor influences, indoor materials and activity emissions, particle deposition and coagulation, gas reactions, and SVOC partitioning. These key processes are fundamentally linked to temperature and relative humidity. With the aid of the building physics model, the indoor temperature and humidity, and pollutant transport in building zones can be simulated. The exposure model refers to the calculated concentrations and provides evaluations of indoor thermal comfort and exposure to gaseous, particulate, and microbial pollutants.

Temperature and indoor environments

From the thermodynamic perspective, the term temperature is clearly defined for ideal physical systems: A unique temperature can be assigned to each black body via its radiation spectrum, and the temperature of an ideal gas is given by the velocity distribution of the molecules. While the indoor environment is not an ideal system, fundamental physical and chemical processes, such as diffusion, partitioning equilibria, and chemical reactions, are predictably temperature-dependent. For example, the logarithm of reaction rate and equilibria constants are proportional to the reciprocal of the absolute temperature. It is therefore possible to have non-linear, very steep changes in chemical phenomena over a relatively small temperature range. On the contrary, transport processes are more influenced by spatial temperature, momentum, and pressure gradients as well as by the density, porosity, and composition of indoor materials. Consequently, emergent phenomena, such as emission rates or dynamic air concentrations, can be the result of complex temperature-dependent relationships that require a more empirical approach. Indoor environmental conditions are further influenced by the thermal comfort needs of occupants. Not only do occupants have to create thermal conditions that serve to maintain their core body temperature, which is usually accomplished by wearing appropriate clothing, but also the surroundings must be adapted so that they feel comfortable. This includes the interaction of the living space with the ambient environment, which can vary greatly by region and season. Design of houses, apartments, commercial buildings, and schools is generally utility and comfort driven, requiring an appropriate energy balance, sometimes considering ventilation but rarely including the impact of temperature on indoor contaminant levels. In our article, we start with a review of fundamental thermodynamic variables and discuss their influence on typical indoor processes. Then, we describe the heat balance of people in their thermal environment. An extensive literature study is devoted to the thermal conditions in buildings, the temperature-dependent release of indoor pollutants from materials and their distribution in the various interior compartments as well as aspects of indoor chemistry. Finally, we assess the need to consider temperature holistically with regard to the changes to be expected as a result of global emergencies such as climate change.

A systematic review of the mental health risks and resilience among pollution-exposed adolescents

Pollution is harmful to human physical health and wellbeing. What is less well established is the relationship between adolescent mental health - a growing public health concern - and pollution. In response, we systematically reviewed studies documenting associations between pollution and mental health in adolescents. We searched Africa Wide, Medline, PsycArticles, PsycInfo, PubMed, CINAHL, ERIC, SciELO, Scopus, and Web of Science Core Collection for studies published up to 10 April 2020 that investigated exposure to any pollutant and symptoms of anxiety; depression; disruptive, impulse-control, and conduct disorders; neurodevelopmental disorders; psychosis; or substance abuse in 10-24-year-olds (i.e., adolescents as per expanded and more inclusive definition of adolescence). This identified 2291 records and we assessed 128 papers for inclusion. We used a narrative synthesis to coalesce the studies' findings. This review is registered on PROSPERO, CRD42020176664. Seventeen studies from Asia, Europe, the Middle East, and North America were included. Air and water pollution exposure was associated with elevated symptoms of depression, generalised anxiety, psychosis, and/or disruptive, impulse control and conduct disorder. Exposure to lead and solvents was associated with neurodevelopmental impairments. Most studies neglected factors that could have supported the mental health resilience of adolescents exposed to pollution. Notwithstanding the limited quality of most reviewed studies, results suggest that pollution exposure is a risk to adolescent mental health. High-quality research is urgently required, including the factors and processes that protect the mental health of pollution-exposed adolescents. Studies with adolescents living in low- and lower middle-income countries and the southern hemisphere must be prioritized.

Interrelationship of Indoor Particulate Matter and Respiratory Dust Depositions of Women in the Residence of Dhanbad City, India

Women spend relatively more time in indoor environments in developing countries. Exposure to various indoor air pollutants leads them to higher health risks according to household air quality in which they reside. Particulate matter (PM) exposure with their exposure duration inside the household plays a significant role in women's respiratory problems. This study measured size-segregated particulate matter concentrations in 63 residences at different locations. Respiratory dust depositions (RDDs) for 118 women in their different respiratory regions like head airway (HD), tracheobronchial (TB), and alveolar (AL) regions for the three PM size fractions (PM₁₀, PM_2.5, and PM₁) were investigated. For different positions like light exercise and the sitting condition, RDDs values found for AL region were 0.091 μgmin^-1 (SD: 0.067, 0.012-0.408) and 0.028 μgmin^-1 (SD: 0.021, 0.003-0.126) for PM₁₀, 0.325 μgmin^-1 (SD: 0.254, 0.053-1.521) and 0.183 μgmin^-1 (SD: 0.143, 0.031-0.857) for PM_2.5, 0.257 μgmin^-1 (SD: 0.197, 0.043-1.04) and 0.057 μgmin^-1 (SD: 0.044, 0.009-0.233) respectively for PM₁ to females. RDDs values in the AL region significantly increase as PM₁₀ (11%), PM_2.5 (68%), and PM₁ (21%), confirming that for women, the AL region is the most prominent affected zone by fine particles (PM_2.5).

The effects of air pollution, meteorological parameters, and climate change on COVID-19 comorbidity and health disparities: A systematic review

Air pollutants, especially particulate matter, and other meteorological factors serve as important carriers of infectious microbes and play a critical role in the spread of disease. However, there remains uncertainty about the relationship among particulate matter, other air pollutants, meteorological conditions and climate change and the spread of the Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2), hereafter referred to as COVID-19. A systematic review was conducted using PRISMA guidelines to identify the relationship between air quality, meteorological conditions and climate change, and COVID-19 risk and outcomes, host related factors, co-morbidities and disparities. Out of a total of 170,296 scientific publications screened, 63 studies were identified that focused on the relationship between air pollutants and COVID-19. Additionally, the contribution of host related-factors, co-morbidities, and health disparities was discussed. This review found a preponderance of evidence of a positive relationship between PM_2.5, other air pollutants, and meteorological conditions and climate change on COVID-19 risk and outcomes. The effects of PM_2.5, air pollutants, and meteorological conditions on COVID-19 mortalities were most commonly experienced by socially disadvantaged and vulnerable populations. Results however, were not entirely consistent, and varied by geographic region and study. Opportunities for using data to guide local response to COVID-19 are identified.

Exercise heat acclimation causes human responses and safety performance improvements

Heat acclimation (HA) is a widely recognized physiological phenomenon of human body in hot environments. HA has many benefits, such aspreventing hyperthermia responses, and is an efficient way to improve human responses to hyperthermal environments. However, it is not known whether HA is dependent on the environmental conditions. Moreover, its mechanism and effect on the safety performance remain unexplored. In this study, we created a climate chamber to simulate a hyperthermal environment. Thirty healthy males were recruited for this study, who were then trained under the same ambient conditions (temperature of 38 °C and relative humidity (RH) of 40%). The training involved running on treadmills (at 5 km/h) to simulate heavy manual labor, and performing heat stress tests (HST) under six different conditions (32 °C/40% RH, 35 °C/40%, 38 °C/40%, 32 °C/70%, 35 °C/70%, and 38 °C/70%). Their physiological indices (rectal temperature, heart rate, sweat loss and skin temperature) and one psychological index (thermal sensation) were measured. Furthermore, a hazard avoidance test device (HATD) was designed to evaluate the individual safety performance by detecting human errors. The results show that training and environmental conditions have different effects on HA. After HA, the physiological and psychological strain were significantly improved. More importantly, HA also helped improve the participants' awareness of the dangers and required emergency responses to face potential hazards. Overall, a reasonable HA training under proper conditions is helpful to ensure the safety of human beings. More research is needed to study the role of HA on safety performance.

Disproportionate exposure to urban heat island intensity across major US cities

Urban heat stress poses a major risk to public health. Case studies of individual cities suggest that heat exposure, like other environmental stressors, may be unequally distributed across income groups. There is little evidence, however, as to whether such disparities are pervasive. We combine surface urban heat island (SUHI) data, a proxy for isolating the urban contribution to additional heat exposure in built environments, with census tract-level demographic data to answer these questions for summer days, when heat exposure is likely to be at a maximum. We find that the average person of color lives in a census tract with higher SUHI intensity than non-Hispanic whites in all but 6 of the 175 largest urbanized areas in the continental United States. A similar pattern emerges for people living in households below the poverty line relative to those at more than two times the poverty line.

Potential overall heat exposure reduction associated with implementation of heat mitigation strategies in Los Angeles

We analyzed two historical extreme heat events in Los Angeles to explore the potential of increasing vegetative cover and surface solar reflectance (albedo) to reduce total exposure (indoor and outdoor) to dangerously hot conditions. We focus on three population subgroups, the elderly, office workers, and outdoor workers, and explore the extreme case where each subgroup does not have functioning air conditioning in their residences. For each heat event, we conducted atmospheric model simulations for a control case and four mitigation cases with varying levels of increased albedo and vegetation cover. Simultaneously, we conducted building simulations of representative residential buildings that lacked mechanical air conditioning. These simulations factored in both the indirect cooling effects associated with neighborhood implementation of mitigation strategies and the direct effects of high albedo roofing on the individual buildings. From both the atmospheric and building models, we exported hourly values of air temperature and dew point temperature, and used this information in combination with various scenarios of occupant behavior to create profiles of individual heat exposure. We also gathered heat-mortality data for the two heat events and developed a synoptic climatology-based relationship between exposure and excess mortality. This relationship was then applied to the scenarios in which albedo and canopy cover were increased. The results suggest that improvements in indoor thermal conditions are responsible for a sizable portion of the health benefit of large-scale implementation of heat mitigation strategies.

The CHASMS conceptual model of cascading disasters and social vulnerability: The COVID-19 case example

Complex environmental, economic, and social conditions in the places we live provide strong cues to our longevity, livelihood, and well-being. Although often distinct and evolving relatively independently, health disparity, social vulnerability and environmental justice research and practice intertwine and inform one another. Together, they increasingly provide evidence of how social processes intensify disasters almost predictably giving rise to inequitable disruptions and consequences. The domino and cumulative effects of cascading disasters invariably reveal inequities through differential impacts and recovery opportunities across communities and subgroups of people. Not only do cascading disasters reveal and produce inequitable effects, the cascade itself can emerge out of compounded nested social structures. Drawing on, and integrating, theory and practice from social vulnerability, health inequity, and environmental justice, this paper presents a comprehensive conceptual model of cascading disasters that offers a people-centric lens. The CHASMS conceptual model (Cascading Hazards to disAsters that are Socially constructed eMerging out of Social Vulnerability) interrogates the tension between local communities and the larger structural forces that produce social inequities at multiple levels, capturing how those inequities lead to cascading disasters. We apply the model to COVID-19 as an illustration of how underlying inequities give rise to foreseeable inequitable outcomes, emphasizing the U.S. experience. We offer Kenya and Puerto Rico as examples of cumulative effects and possible cascades when responding to other events in the shadow of COVID-19. COVID-19 has vividly exposed the dynamic, complex, and intense relevance of placing social conditions and structures at the forefront of cascading disaster inquiry and practice. The intensity of social disruption and the continuation of the pandemic will, no doubt, perpetuate and magnify chasms of injustice.

A Case-Crossover Analysis of Indoor Heat Exposure on Mortality and Hospitalizations among the Elderly in Houston, Texas

BACKGROUND

Despite the substantial role indoor exposure has played in heat wave-related mortality, few epidemiological studies have examined the health effects of exposure to indoor heat. As a result, knowledge gaps regarding indoor heat-health thresholds, vulnerability, and adaptive capacity persist.

OBJECTIVE

We evaluated the role of indoor heat exposure on mortality and morbidity among the elderly (≥65 years of age) in Houston, Texas.

METHODS

Mortality and emergency hospital admission data were obtained through the Texas Department of State Health Services. Summer indoor heat exposure was modeled at the U.S. Census block group (CBG) level using building energy models, outdoor weather data, and building characteristic data. Indoor heat-health associations were examined using time-stratified case-crossover models, controlling for temporal trends and meteorology, and matching on CBG of residence, year, month, and weekday of the adverse health event. Separate models were fitted for three indoor exposure metrics, for individual lag days 0-6, and for 3-d moving averages (lag 0-2). Effect measure modification was explored via stratification on individual- and area-level vulnerability factors.

RESULTS

We estimated positive associations between short-term changes in indoor heat exposure and cause-specific mortality and morbidity [e.g., circulatory deaths, odds ratio per 5°C increase=1.16 (95% CI: 1.03, 1.30)]. Associations were generally positive for earlier lag periods and weaker across later lag periods. Stratified analyses suggest stronger associations between indoor heat and emergency hospital admissions among African Americans compared with Whites.

DISCUSSION

Findings suggest excess mortality among certain elderly populations in Houston who are likely exposed to high indoor heat. We developed a novel methodology to estimate indoor heat exposure that can be adapted to other U.S.

LOCATIONS

In locations with high air conditioning prevalence, simplified modeling approaches may adequately account for indoor heat exposure in vulnerable neighborhoods. Accounting for indoor heat exposure may improve the estimation of the total impact of heat on health. https://doi.org/10.1289/EHP6340.

Volatile Organic Compounds (VOCs) Removal from Indoor Air by Heterostructures/Composites/Doped Photocatalysts: A Mini-Review

The impact of volatile organic compounds (VOCs) on indoor air quality and, furthermore, on human health is still a subject of research investigations considering the large increase in forms of cancer and related diseases. VOCs can be 10 times higher in indoor air concentrations then that of the outdoors, as a consequence of emissions from electronics, building materials and consumer goods. Direct transformation of VOCs in mineralization products seems to be an alternative to reduce indoor air contaminants. The advantage of photocatalysis implementation in indoor air treatment is given by the absence of additional chemicals (such as H2O2) and waste. The present mini-review presents a comparative study on VOCs photocatalytic removal considering the photocatalyst composition, morphology and specific surface. The sheet-like morphology seems to provide a higher number of active sites which may contribute to oxidative reactions. The insertion of materials able to increase light absorbance or to mediate the charge carrier's transport will have a beneficial impact on the overall photocatalytic efficiency. Additionally, surface chemistry must be considered when developing photocatalysts for certain gas pollutants in order to favor molecule absorbance in the interfacial region. An energy consumption perspective is given based on the light intensity and irradiation period.

Housing as a critical determinant of heat vulnerability and health

Municipalities use Heat Vulnerability Indices (HVIs) to quantify and map relative distribution of risks to human health in the event of a heatwave. These maps ostensibly allow public agencies to identify the highest-risk neighborhoods, and to concentrate emergency planning efforts and resources accordingly (e.g., to establish the locations of cooling centers). The method of constructing an HVI varies by municipality, but common inputs include demographic variables such as age and income - and to some extent, metrics such as land cover. However, taking demographic data as a proxy for heat vulnerability may provide an incomplete or inaccurate assessment of risk. A critical limitation in HVIs may be a lack of focus on housing characteristics and how they mediate indoor heat exposure. To provide an objective assessment of this limitation, we first reviewed HVIs in the literature and those published or commissioned by municipalities. We subsequently verified that most of these HVIs excluded housing factors. Next, to scope the potential consequences, we used physics-based simulations of housing prototypes (46,000 housing permutations per city) to estimate the variation in indoor heat exposure within high-vulnerability neighborhoods in Boston and Phoenix. The results show that by excluding building-level determinants of exposure, HVIs fail to capture important components of heat vulnerability. Moreover, we demonstrate how these maps currently overlook important nuances regarding the impact of building age and air conditioning functionality. Finally, we discuss the challenges of implementing housing stock characteristics in HVIs and propose methods for overcoming these challenges.

Developing Vulnerability Index to Quantify Urban Heat Islands Effects Coupled with Air Pollution: A Case Study of Camden, NJ

Extreme heat events at urban centers in combination with air pollution pose a serious risk to human health. Among these are financially distressed cities and neighborhoods that are facing enormous challenges without the scientific and technical capacity for planning and mitigation. The city of Camden is one of those economically distressed areas with a predominantly minority population, a high unemployment rate, high poverty rates, and poor air quality (PM2.5 and ozone), and it remains vulnerable to heat events. This paper focuses on studying a coupled effect of Urban Heat Islands (UHIs) and Ozone-PM2.5 pollution at the neighborhood-scale in the city of Camden, using fine scale remotely sensed land-surface temperature and air quality data from the Community Multiscale Air Quality (CMAQ) Modelling System in the Geographic Information Systems (GIS) platform. To assess the impact of urban microclimate on the city of Camden, NJ, residents’ health, we identified several environmental and social parameters as the root causes of vulnerability imposed by extreme-heat and poor air quality. Vulnerability in terms of environment and social wellbeing was spatially quantified as two conceptual vulnerability-index models (i.e., environmental vulnerability index (EVI) and a social vulnerability index (SVI)) using multiple linear regression algorithm. Factors such as remotely sensed earth surface properties, built-environment components, air quality, and socio-economic data were incorporated in a holistic geographic approach to quantify the combined effect. Surface temperature gradient and Proportional Vegetation (Pv) generated from 30 m resolution Landsat 8 were sampled along with other variables in the city of Camden, NJ. Models incorporating Pv suggest better fit than models with normalized difference vegetation index (NDVI). Water fraction (33.5%, 32.4%), percentage imperviousness (32.5%, 32%), Pv (20.5%, 19.6%), and digital elevation model (DEM) (9%, 8%) have the highest contributions in both models. Two output maps identified the vulnerable neighborhoods in the city through comprehensive GIS analysis: Lanning Square, Bergen Square, Central Waterfront, Gateway, Liberty Park, and Parkside. This can provide useful information for planners and health officials in targeting areas for future interventions and mitigations.

On the environmental effectiveness analysis of energy policies: A case study of air pollution in the megacity of Tehran

The present study compared different approaches to assessing the environmental cost-effectiveness of energy policy scenarios. As a case study, the megacity of Tehran in Iran was studied. A key policy challenge in this city is to curb high concentrations of PM_2.5 and mitigate the associated adverse impacts. The results demonstrated that in the business as usual case, the spatially averaged primary and secondary PM_2.5 concentration in Tehran will increase by 30% in the 2010-2030 period. Adopting certain planned policy scenarios and the corresponding pollutant concentration reductions in Tehran shows that although most of the emission comes from industrial activities around the city, the distribution of the transportation emission sources may play the most effective role in decreasing pollution levels in transport-related energy policies. Next, based on environmental damage costs and abatement costs in different pollution mitigation scenarios, the best (most environmentally cost-effective) scenarios were evaluated. The eco-efficiencies of the energy policies were assessed based on two proxies of environmental impacts: the reduced damage cost as a function of the reduced emission rates of the pollutants and the decreased number of polluted days in the year. In a sample area in which the simulated concentrations were verified by local measurements, the most efficient mitigation scenario would decrease the average concentration of PM_2.5 by 35% in 2030 and the number of polluted days by 20%. These findings indicate how far the linear functionality of the damage cost from emission levels may mislead environmental impact assessments. This is due to neglecting the source distribution effects and geographical conditions of the environment.

The human imperative of stabilizing global climate change at 1.5°C

Increased concentrations of atmospheric greenhouse gases have led to a global mean surface temperature 1.0°C higher than during the pre-industrial period. We expand on the recent IPCC Special Report on global warming of 1.5°C and review the additional risks associated with higher levels of warming, each having major implications for multiple geographies, climates, and ecosystems. Limiting warming to 1.5°C rather than 2.0°C would be required to maintain substantial proportions of ecosystems and would have clear benefits for human health and economies. These conclusions are relevant for people everywhere, particularly in low- and middle-income countries, where the escalation of climate-related risks may prevent the achievement of the United Nations Sustainable Development Goals.