Toward Heart-Healthy and Sustainable Cities: A Policy Statement From the American Heart Association.

Nearly 56% of the global population lives in cities, with this number expected to increase to 6.6 billion or >70% of the world's population by 2050. Given that cardiometabolic diseases are the leading causes of morbidity and mortality in people living in urban areas, transforming cities and urban provisioning systems (or urban systems) toward health, equity, and economic productivity can enable the dual attainment of climate and health goals. Seven urban provisioning systems that provide food, energy, mobility-connectivity, housing, green infrastructure, water management, and waste management lie at the core of human health, well-being, and sustainability. These provisioning systems transcend city boundaries (eg, demand for food, water, or energy is met by transboundary supply); thus, transforming the entire system is a larger construct than local urban environments. Poorly designed urban provisioning systems are starkly evident worldwide, resulting in unprecedented exposures to adverse cardiometabolic risk factors, including limited physical activity, lack of access to heart-healthy diets, and reduced access to greenery and beneficial social interactions. Transforming urban systems with a cardiometabolic health-first approach could be accomplished through integrated spatial planning, along with addressing current gaps in key urban provisioning systems. Such an approach will help mitigate undesirable environmental exposures and improve cardiovascular and metabolic health while improving planetary health. The purposes of this American Heart Association policy statement are to present a conceptual framework, summarize the evidence base, and outline policy principles for transforming key urban provisioning systems to heart-health and sustainability outcomes.

Impact of Circular, Waste-Heat Reuse Pathways on PM2.5-Air Quality, CO2 Emissions, and Human Health in India: Comparison with Material Exchange Potential.

India is home to 1.3 billion people who are exposed to some of the highest levels of ambient air pollution in the world. In addition, India is one of the fastest-growing carbon-emitting countries. Here, we assess how two strategies to reuse waste-heat from coal-fired power plants and other large sources would impact PM2.5-air quality, human health, and CO2 emissions in 2015 and a future year, 2050, using varying levels of policy adoption (current regulations, proposed single-sector policies, and ambitious single-sector strategies). We find that power plant and industrial waste-heat reuse as input to district heating systems (DHSs), a novel, multisector strategy to reduce local biomass burning for heating emissions, can offset 71.3-85.2% of residential heating demand in communities near a power plant (9.3-12.4% of the nationwide heating demand) with the highest benefits observed during winter months in areas with collocated industrial activity and higher residential heating demands (e.g., New Delhi). Utilizing waste-heat to generate electricity via organic Rankine cycles (ORCs) can generate an additional 22 (11% of total coal-fired generating capacity), 41 (8%), 32 (13%), and 6 (5%) GW of electricity capacity in the 2015, 2050-current regulations, 2050-single-sector, and 2050-ambitious-single-sector scenarios, respectively. Emission estimates utilizing these strategies were input to the GEOS-Chem model, and population-weighted, simulated PM2.5 showed small improvements in the DHS (0.2-0.4%) and ORC (0.3-3.4%) scenarios, where the minimal DHS PM2.5-benefit is attributed to the small contribution of biomass burning for heating to nationwide PM2.5 emissions (much of the biomass burning activity is for cooking). The PM2.5 reductions lead to ∼130-36,000 mortalities per year avoided among the scenarios, with the largest health benefits observed in the ORC scenarios. Nationwide CO2 emissions reduced <0.04% by DHSs but showed larger reductions using ORCs (1.9-7.4%). Coal fly-ash as material exchange in cement and brick production was assessed, and capacity exists to completely reutilize unused fly-ash toward cement and brick production in each of the scenarios.

Characterizing COVID-19 waves in urban and rural districts of India.

Understanding spatial determinants, i.e., social, infrastructural, and environmental features of a place, which shape infectious disease is critically important for public health. We present an exploration of the spatial determinants of reported COVID-19 incidence across India's 641 urban and rural districts, comparing two waves (2020-2021). Three key results emerge using three COVID-19 incidence metrics: cumulative incidence proportion (aggregate risk), cumulative temporal incidence rate, and severity ratio. First, in the same district, characteristics of COVID-19 incidences are similar across waves, with the second wave over four times more severe than the first. Second, after controlling for state-level effects, urbanization (urban population share), living standards, and population age emerge as positive determinants of both risk and rates across waves. Third, keeping all else constant, lower shares of workers working from home correlate with greater infection risk during the second wave. While much attention has focused on intra-urban disease spread, our findings suggest that understanding spatial determinants across human settlements is also important for managing current and future pandemics.

Measuring social equity in urban energy use and interventions using fine-scale data.

Cities seek nuanced understanding of intraurban inequality in energy use, addressing both income and race, to inform equitable investment in climate actions. However, nationwide energy consumption surveys are limited (<6,000 samples in the United States), and utility-provided data are highly aggregated. Limited prior analyses suggest disparity in energy use intensity (EUI) by income is ∼25%, while racial disparities are not quantified nor unpacked from income. This paper, using new empirical fine spatial scale data covering all 200,000 households in two US cities, along with separating temperature-sensitive EUI, reveals intraurban EUI disparities up to a factor of five greater than previously known. We find 1) annual EUI disparity ratios of 1.27 and 1.66, comparing lowest- versus highest-income block groups (i.e., 27 and 66% higher), while previous literature indicated only ∼25% difference; 2) a racial effect distinct from income, wherein non-White block groups (highest quintile non-White percentage) in the lowest-income stratum reported up to a further ∼40% higher annual EUI than less diverse block groups, providing an empirical estimate of racial disparities; 3) separating temperature-sensitive EUI unmasked larger disparities, with heating-cooling electricity EUI of lowest-income block groups up to 2.67 times (167% greater) that of highest income, and high racial disparity within lowest-income strata wherein high non-White (>75%) population block groups report EUI up to 2.56 times (156% larger) that of majority White block groups; and 4) spatial scales of data aggregation impact inequality measures. Quadrant analyses are developed to guide spatial prioritization of energy investment for carbon mitigation and equity. These methods are potentially translatable to other cities and utilities.

All urban areas' energy use data across 640 districts in India for the year 2011.

India is the third-largest contributor to global energy-use and anthropogenic carbon emissions. India's urban energy transitions are critical to meet its climate goals due to the country's rapid urbanization. However, no baseline urban energy-use dataset covers all Indian urban districts in ways that align with national totals and integrate social-economic-infrastructural attributes to inform such transitions. This paper develops a novel bottom-up plus top-down approach, comprehensively integrating multiple field surveys and utilizing machine learning, to model All Urban areas' Energy-use (AllUrE) across all 640 districts in India, merged with social-economic-infrastructural data. Energy use estimates in this AllUrE-India dataset are evaluated by comparing with reported energy-use at three scales: nation-wide, state-wide, and city-level. Spatially granular AllUrE data aggregated nationally show good agreement with national totals (<2% difference). The goodness-of-fit ranged from 0.78-0.95 for comparison with state-level totals, and 0.90-0.99 with city-level data for different sectors. The relatively strong alignment at all three spatial scales demonstrates the value of AllUrE-India data for modelling urban energy transitions consistent with national energy and climate goals.

Understanding subjective well-being: perspectives from psychology and public health.

BACKGROUND: Individual subjective well-being (SWB) is essential for creating and maintaining healthy, productive societies. The literature on SWB is vast and dispersed across multiple disciplines. However, few reviews have summarized the theoretical and empirical tenets of SWB literature across disciplinary boundaries. METHODS: We cataloged and consolidated SWB-related theories and empirical evidence from the fields of psychology and public health using a combination of online catalogs of scholarly articles and online search engines to retrieve relevant articles. For both theories and determinants/correlates of SWB, PubMed, PsychINFO, and Google Scholar were used to obtain relevant articles. Articles for the review were screened for relevance, varied perspectives, journal impact, geographic location of study, and topicality. A core theme of SWB empirical literature was the identification of SWB determinants/correlates, and over 100 research articles were reviewed and summarized for this review. RESULTS: We found that SWB theories can be classified into four groups: fulfillment and engagement theories, personal orientation theories, evaluative theories, and emotional theories. A critical analysis of the conflicts and overlaps between these theories reveals the lack of a coherent theoretical and methodological framework that would make empirical research systematically comparable. We found that determinants/correlates of SWB can be grouped into seven broad categories: basic demographics, socioeconomic status, health and functioning, personality, social support, religion and culture, and geography and infrastructure. However, these are rarely studied consistently or used to test theories. CONCLUSIONS: The lack of a clear, unifying theoretical basis for categorizing and comparing empirical studies can potentially be overcome using an operationalizable criterion that focuses on the dimension of SWB studied, measure of SWB used, design of the study, study population, and types of determinants and correlates. From our review of the empirical literature on SWB, we found that the seven categories of determinants/correlates identified may potentially be used to improve the link between theory and empirical research, and that the overlap in the determinant/correlates as they relate to multiple theory categories may enable us to test theories in unison. However, doing so in the future would require a conscious effort by researchers in several areas, which are discussed.

Impact of Urban Expansion and In Situ Greenery on Community-Wide Carbon Emissions: Method Development and Insights from 11 US Cities.

Biogenic CO2 emissions in cities are shaped by urban land cover change which can release carbon stocks, and, carbon sequestration by in situ vegetation. To date, these two processes have not been studied together and compared with transboundary fossil fuel-based CO2 emissions of urban energy use. We leverage remote sensing and machine learning to quantify biogenic CO2 emissions between 2006 and 2012, across 11 U.S cities, including central and suburban cities, in different climate zones. Results indicate that in situ carbon sequestration by greenery varied moderately across cities (-2.1 to -0.87 Mg CO2 ha-1 yr-1), while emissions from the carbon stock change due to land conversion varied much more (-3.4 to 9.8 Mg CO2 ha-1 yr-1), indicating that the latter dominates biogenic CO2 emissions. Net biogenic CO2 emissions were negative (carbon sink) in four cities, while large net positive emissions were present in rapidly growing suburbs. As a ratio of community-wide energy use for travel and buildings, biogenic CO2 emissions were a small proportion in the core cities Denver (0.17%) and Minneapolis (0.33%) and as high as 38.2% in growing exurban communities. These results show that land cover change and greenery will be important policy levers in zero-carbon city planning.

Transboundary Environmental Footprints of the Urban Food Supply Chain and Mitigation Strategies.

Food supply has been the central issue of human development for millennia and has become increasingly critical in an urbanizing world. However, the environmental footprints and associated mitigation strategies of food consumption have rarely been comprehensively characterized at urban or regional scales. Here, we analyze the water, carbon, reactive nitrogen, and phosphorus footprints of food consumption in Chinese urban regions and demonstrate how such information can help to formulate tailored mitigation strategies. The results show that in three of the largest urban regions of China, 44-93% of the four footprints are embodied in transboundary food supply. The size of the footprints and the effectiveness of mitigation measures in food supply chain vary across the environmental footprints and urban regions. However, targeting agriculture and food processing sectors in Hebei, Shandong, and Henan provinces can reduce these footprints by up to 47%. Our findings show that the analysis of the environmental footprints along the transboundary food supply chains could inform individualized and effective mitigation targets and strategies.

Connecting Air Quality with Emotional Well-Being and Neighborhood Infrastructure in a US City.

Cities in the United States have announced initiatives to become more sustainable, healthy, resilient, livable, and environmentally friendly. However, indicators for measuring all outcomes related to these targets and the synergies between them have not been well defined or studied. One such relationship is the linkage between air quality with emotional well-being (EWB) and neighborhood infrastructure. Here, regulatory monitoring, low-cost sensors (LCSs), and air quality modeling were combined to assess exposures to PM2.5 and traffic-related NOx in 6 Minneapolis, MN, neighborhoods of varying infrastructure parameters (median household income, urban vs suburban, and access to light rail). Residents of the study neighborhoods concurrently took real-time EWB assessments using a smart phone application, Daynamica, to gauge happiness, tiredness, stress, sadness, and pain. Both LCS PM2.5 observations and mobile-source-simulated NOx were calibrated using regulatory observations in Minneapolis. No statistically significant (α = 0.05) PM2.5 differences were found between urban poor and urban middle-income neighborhoods, but average mobile-source NOx was statistically significantly (α = 0.05) higher in the 4 urban neighborhoods than in the 2 suburban neighborhoods. Close proximity to light rail had no observable impact on average observed PM2.5 or simulated mobile-source NOx. Home-based exposure assessments found that PM2.5 was negatively correlated with positive emotions such as happiness and to net affect (the sum of positive and negative emotion scores) and positively correlated (ie, a higher PM2.5 concentration led to higher scores) for negative emotions such as tiredness, stress, sadness, and pain. Simulated mobile-source NOx, assessed from both home-based exposures and in situ exposures, had a near-zero relationship with all EWB indicators. This was attributed to low NOx levels throughout the study neighborhoods and at locations were the EWB-assessed activities took place, both owing to low on-road mobile-source NOx impacts. Although none of the air quality and EWB responses were determined to be statistically significant (α = 0.05), due in part to the relatively small sample size, the results are suggestive of linkages between air quality and a variety of EWB outcomes.

Impact of Locational Choices and Consumer Behaviors on Personal Land Footprints: An Exploration Across the Urban-Rural Continuum in the United States.

Land is a scarce resource. We develop consumption-based land footprints (CBLF) for urban and rural U.S. residents to evaluate new levers for reducing land-demand by combining (1) direct land-use for human settlements including housing, (2) indirect land-use associated with personal consumption, for example, food and clothing. Results show that an average urban resident's indirect land-use (199 176 ft2/capita) is ∼23 times the direct land-use (8519 ft2/capita), for a total urban CBLF of 207 695 ft2/capita. Rural residents have a slightly higher (∼6%) indirect land-use and ∼10 times larger direct land-use compared to urban. Because in both cases, indirect land-use is much larger than direct, a strategic mix of individual actions including halving food waste (-4.7%), one-day weekly plant-based diet (-3.3%), reducing clothing consumption (-2.8%), and others, can together reduce CBLF by -12.8%. Meanwhile, housing and locational choices across the urban-rural continuum evaluated for the median-density Minneapolis-St. Paul Metropolitan Statistical Area (MSP MSA) yield CBLF reductions from -1.9% (from single- to multifamily housing) to -10.6% (from rural to the urban core). The analysis demonstrates that consumer behavior changes could rival housing/locational choices in order to reduce personal CBLF. Our method of combining input-output analysis with parcel data could be applied in different regions to provide customized information on CBLF mitigation strategies.

Review on City-Level Carbon Accounting.

Carbon accounting results for the same city can differ due to differences in protocols, methods, and data sources. A critical review of these differences and the connection among them can help to bridge our knowledge between university-based researchers and protocol practitioners in accounting and taking further mitigation actions. The purpose of this study is to provide a review of published research and protocols related to city carbon accounting, paying attention to both their science and practical actions. To begin with, the most cited articles in this field are identified and analyzed by employing a citation network analysis to illustrate the development of city-level carbon accounting from three perspectives. We also reveal the relationship between research methods and accounting protocols. Furthermore, a timeline of relevant organizations, protocols, and projects is provided to demonstrate the applications of city carbon accounting in practice. The citation networks indicate that the field is dominated by pure-geographic production-based and community infrastructure-based accounting; however, emerging models that combine economic system analysis from a consumption-based perspective are leading to new trends in the field. The emissions accounted for by various research methods consist essentially of the scope 1-3, as defined in accounting protocols. The latest accounting protocols include consumption-based accounting, but most cities still limit their accounting and reporting from pure-geographic production-based and community infrastructure-based perspectives. In conclusion, we argue that protocol practitioners require support in conducting carbon accounting, so as to explore the potential in mitigation and adaptation from a number of perspectives. This should also be a priority for future studies.

Demographic Inequities in Health Outcomes and Air Pollution Exposure in the Atlanta Area and its Relationship to Urban Infrastructure.

Environmental burdens such as air pollution are inequitably distributed with groups of lower socioeconomic statuses, which tend to comprise of large proportions of racial minorities, typically bearing greater exposure. Such groups have also been shown to present more severe health outcomes which can be related to adverse pollution exposure. Air pollution exposure, especially in urban areas, is usually impacted by the built environment, such as major roadways, which can be a significant source of air pollution. This study aims to examine inequities in prevalence of cardiovascular and respiratory diseases in the Atlanta metropolitan region as they relate to exposure to air pollution and characteristics of the built environment. Census tract level data were obtained from multiple sources to model health outcomes (asthma, chronic obstructive pulmonary disease, coronary heart disease, and stroke), pollution exposure (particulate matter and nitrogen oxides), demographics (ethnicity and proportion of elderly residents), and infrastructure characteristics (tree canopy cover, access to green space, and road intersection density). Conditional autoregressive models were fit to the data to account for spatial autocorrelation among census tracts. The statistical model showed areas with majority African-American populations had significantly higher exposure to both air pollutants and higher prevalence of each disease. When considering univariate associations between pollution and health outcomes, the only significant association existed between nitrogen oxides and COPD being negatively correlated. Greater percent tree canopy cover and green space access were associated with higher prevalence of COPD, CHD, and stroke. Overall, in considering health outcomes in connection with pollution exposure infrastructure and ethnic demographics, demographics remained the most significant explanatory variable.

Assessing Current Local Capacity for Agrifood Production To Meet Household Demand: Analyzing Select Food Commodities across 377 U.S. Metropolitan Areas.

Increasing food production in local urban and peri-urban areas is articulated as a potential way for local governments to achieve multiple sustainability outcomes (environmental, social, and human health). However, scientific judgements on localization are difficult to make because the degree of current food localization has not been systematically measured or defined across large numbers of cities. We develop new methods to quantify current local capacity for food production to meet total household agrifood demand, harmonizing bottom-up and top-down approaches to assess direct-plus-embodied agrifood demand of both fresh and processed foods. We find unique patterns of localization for different agrifoods, with 21% of U.S. metropolitan statistical areas (MSAs) currently capable of local self-sufficiency for eggs and milk equivalents embodied in diet, versus 12% and 16% of MSAs self-sufficient in fruits and vegetables, respectively. Focusing only on the direct fresh food demand, increased current local capacity (e.g., 45% MSAs self-sufficient in direct fluid milk), which also increases with production distances around cities. Overall, significant agricultural production is found to already occur in and around U.S. MSAs for these items. Multivariable analysis finds that state policies that promote urban agriculture may influence greater localization, which, interestingly, is independent of population density. Such spatial demand-production analysis is the first step in informing sustainable city or regional food policies and envisioning spatial food supply chains to urban areas.

What Is the Contribution of City-Scale Actions to the Overall Food System's Environmental Impacts?: Assessing Water, Greenhouse Gas, and Land Impacts of Future Urban Food Scenarios.

This paper develops a methodology for individual cities to use to analyze the in- and trans-boundary water, greenhouse gas (GHG), and land impacts of city-scale food system actions. Applied to Delhi, India, the analysis demonstrates that city-scale action can rival typical food policy interventions that occur at larger scales, although no single city-scale action can rival in all three environmental impacts. In particular, improved food-waste management within the city (7% system-wide GHG reduction) matches the GHG impact of preconsumer trans-boundary food waste reduction. The systems approach is particularly useful in illustrating key trade-offs and co-benefits. For instance, multiple diet shifts that can reduce GHG emissions have trade-offs that increase water and land impacts. Vertical farming technology (VFT) with current applications for fruits and vegetables can provide modest system-wide water (4%) and land reductions (3%), although implementation within the city itself may raise questions of constraints in water-stressed cities, with such a shift in Delhi increasing community-wide direct water use by 16%. Improving the nutrition status for the bottom 50% of the population to the median diet is accompanied by proportionally smaller increases of water, GHG, and land impacts (4%, 9%, and 8%, systemwide): increases that can be offset through simultaneous city-scale actions, e.g., improved food-waste management and VFT.

Exploring social and infrastructural factors affecting open burning of municipal solid waste (MSW) in Indian cities: A comparative case study of three neighborhoods of Delhi.

Open municipal solid waste (MSW)-burning is a major source of particulate matter emissions in developing world cities. Despite a legal ban, MSW-burning is observed ubiquitously in Indian cities with little being known about the factors shaping it. This study seeks to uncover social and infrastructural factors that affect MSW-burning at the neighborhood level. We couple physical assessments of the infrastructure provision and the MSW-burning incidences in three different neighborhoods of varying socio-economic status in Delhi, with an accompanying study of the social actors (interviews of waste handlers and households) to explore the extent to which, and potential reasons why, MSW-burning occurs. The observed differences in MSW-burning incidences range from 130 km-2 day-1 in low-income to 30 km-2 day-1 in the high-income areas. However, two high-income areas neighborhoods with functional infrastructure service also showed statistical differences in MSW-burning incidences. Our interviews revealed that, while the waste handlers were aware of the health risks associated with MSW-burning, it was not a high priority in the context of the other difficulties they faced. The awareness of the legal ban on MSW-burning was low among both waste handlers and households. In addition to providing infrastructure for waste pickup, informal restrictions from residents and neighborhood associations can play a significant role in restricting MSW-burning at the neighborhood scale. A more efficient management of MSW requires a combined effort that involves interplay of both social and infrastructural systems.

Meta-principles for developing smart, sustainable, and healthy cities.

Policy directives in several nations are focusing on the development of smart cities, linking innovations in the data sciences with the goal of advancing human well-being and sustainability on a highly urbanized planet. To achieve this goal, smart initiatives must move beyond city-level data to a higher-order understanding of cities as transboundary, multisectoral, multiscalar, social-ecological-infrastructural systems with diverse actors, priorities, and solutions. We identify five key dimensions of cities and present eight principles to focus attention on the systems-level decisions that society faces to transition toward a smart, sustainable, and healthy urban future.

Characterizing the Spatial and Temporal Patterns of Open Burning of Municipal Solid Waste (MSW) in Indian Cities.

Open-burning of municipal solid waste (MSW) is a major source of PM emissions in developing world cities, but few studies have characterized this phenomenon at the city and intracity (neighborhood) scale relevant to human health impacts. This paper develops a consistent field method for measuring the spatial frequency of the incidence of MSW-burning and presents results in three neighborhoods of varying socioeconomic status (SES) in Delhi, India, observed in winter and summer over 2 years. Daily MSW-burning incidents ranged from 24 to 130/km2-day during winter and 5-87/km2-day during summer, with the highest intensity in low SES neighborhoods. Distinct seasonal and diurnal patterns are observed. The daily mass of MSW-burned was also estimated at 90-1170 kg/km2-day and 13-1100 kg/km2-day in highest to low SES neighborhoods, in winter and summer, respectively. The scaled-up estimate of total MSW-burned for Delhi city ranged from 190 to 246 tons/day, about 2%-3% of total generated MSW; morning-burning contributed >65% of the total. MSW composition varied systematically across neighborhoods and season. Agra had much higher MSW-burning (39-202 incidents/km2-day; 672-3485 kg/km2-day) in the summer. The field method thus captures differences in MSW-burning across cities, neighborhoods, diurnally and seasonally, important for more fine grained air pollution modeling, and for tracking/monitoring policy effectiveness on-ground.

Life cycle energy use and greenhouse gas emission analysis for a water resource recovery facility in India.

This paper quantifies life cycle energy use and greenhouse gas (GHG) emissions associated with water resource recovery facilities (WRRFs) in India versus water quality improvements achieved from infrastructure investments. A first such analysis is conducted using operating data for a WRRF, which employs upflow anaerobic sludge blanket (UASB) reactors and oxidation. On-site operations energy use, process GHG emissions, and embodied energy in infrastructure were quantified. The analysis showed energy use and GHG emissions of 0.2 watt-hours (Wh) and 0.3 gram carbon dioxide (CO2) equivalents per liter (gCO2e/L) wastewater treated, and 1.3 Wh and 2.1 gCO2e/gBOD removed, achieving 81% biochemical oxygen demand (BOD) and 999% fecal coliform removal annually. Process emissions of WRRFs contributed 44% of life cycle GHG emissions, similar in magnitude to those from electricity (46%), whereas infrastructure contributed 10%. Average WRRF-associated GHG emissions (0.9gCO2e/L) were lower than those expected if untreated wastewater was released to the river. Investments made by WRRFs in developing world cities improve water quality and may mitigate overall GHG emissions.