High-density housing in close proximity to freeways in conjunction with high concentrations of traffic emissions may contribute to significant degradation of indoor air quality. Densely populated areas may also be targeted for intentional releases of biological or chemical agents because an urban release could result in higher morbidity and mortality from the attack. Since people tend to spend the majority of their time indoors, it is paramount to explore the relationships between outdoor and indoor air quality and, specifically, the time scales that characterize transport of airborne contaminants from outdoors to indoors. In the Brooklyn Traffic Real-Time Ambient Pollutant Penetration and Environmental Dispersion (B-TRAPPED) study, a three-story row house with a flat face and roof and multiple rooms was used to investigate outdoor-to-indoor contaminant time scales. The building was located in the Sunset Park neighborhood of Brooklyn, NY, USA, in the vicinity of a major expressway and a heavily trafficked arterial road. It was found that the building shell has a profound impact on the indoor concentrations. A strong hourly periodicity (see Eisner et al., this issue, DOI: 10.1039/b907132f) in concentration outside the building during the morning "rush hour" was used as evidence to suggest that indoor contaminants originated from outdoor air penetration. Although the indoor concentrations followed a similar pattern, indoor concentrations were found to be more persistent than outdoor concentrations. Stronger persistency is used here to describe the tendency of the indoor concentration to continue to rise even if the outdoor concentration has started to drop, or vice versa. This may be an important factor in assessing negative health risks to inhabitants or first responders. A cross-correlation technique was employed to study the correlation between outdoor and indoor time series. In the high-density housing residential building used in the study, it was found that a long lag time exists (11 min) before indoor and outdoor concentrations reach maximal correlation.
The Brooklyn Traffic Real-Time Ambient Pollutant Penetration and Environmental Dispersion (B-TRAPPED) study, conducted in Brooklyn, NY, USA, in 2005, was designed with multiple goals in mind, two of which were contaminant source characterization and street canyon transport and dispersion monitoring. In the portion of the study described here, synchronized wind velocity and azimuth as well as particulate matter (PM) concentrations at multiple locations along 33rd Street were used to determine the feasibility of using traffic emissions in a complex urban topography as a sole tracer for studying urban contaminant transport. We demonstrate in this paper that it is possible to link downwind concentrations of contaminants in an urban street canyon to the vehicular traffic cycle using Eigen-frequency analysis. In addition, multivariable circular histograms are used to establish directional frequency maxima for wind velocity and contaminant concentration.
An anatomically accurate, x20 enlarged scale model of a healthy right human adult nasal cavity was constructed from computerized axial tomography scans for the study of nasal airflow patterns. Detailed velocity profiles for inspiratory and expiratory flow through the model and turbulence intensity were measured with a hot-film anemometer probe with 1 mm spatial resolution. Steady flow rates equivalent to 1,100, 560, and 180 ml/s through one side of the real human nose were studied. Airflows were determined to be moderately turbulent, but changes in the velocity profiles between the highest and lowest flow rates suggest that for normal breathing laminar flow may be present in much of the nasal cavity. The velocity measurements closest to the model wall were estimated to be inside the laminar sublayer, such that the slopes of the velocity profiles are reasonably good estimates of the velocity gradients at the walls. The overall longitudinal pressure drop inside the nasal cavity for the three inspiratory flow rates was estimated from the average total shear stress measured at the central nasal wall and showed good agreement with literature values measured in human subjects.
The Brooklyn traffic real-time ambient pollutant penetration and environmental dispersion (B-TRAPPED) study was a multidisciplinary field research project that investigated the transport, dispersion, and infiltration processes of traffic emission particulate matter (PM) pollutants in a near-highway urban residential area. The urban PM transport, dispersion, and infiltration processes were described mathematically in a theoretical model that was constructed to develop the experimental objectives of the B-TRAPPED study. In the study, simultaneous and continuous time-series PM concentration and meteorological data collected at multiple outdoor and indoor monitoring locations were used to characterize both temporal and spatial patterns of the PM concentration movements within microscale distances (<500 m) from the highway. Objectives of the study included (1) characterizing the temporal and spatial PM concentration fluctuation and distribution patterns in the urban street canyon; (2) investigating the effects of urban structures such as a tall building or an intersection on the transport and dispersion of PM; (3) studying the influence of meteorological variables on the transport, dispersion, and infiltration processes; (4) characterizing the relationships between the building parameters and the infiltration mechanisms; (5) establishing a cause-and-effect relationship between outdoor-released PM and indoor PM concentrations and identifying the dominant mechanisms involved in the infiltration process; (6) evaluating the effectiveness of a shelter-in-place area for protection against outdoor-released PM pollutants; and (7) understanding the predominant airflow and pollutant dispersion patterns within the neighborhood using wind tunnel and CFD simulations. The 10 papers in this first set of papers presenting the results from the B-TRAPPED study address these objectives. This paper describes the theoretical background and models representing the interrelated processes of transport, dispersion, and infiltration. The theoretical solution for the relationship between the time-dependent indoor PM concentration and the initial PM concentration at the outdoor source was obtained. The theoretical models and solutions helped us to identify important parameters in the processes of transport, dispersion, and infiltration. The B-TRAPPED study field experiments were then designed to investigate these parameters in the hope of better understanding urban PM pollutant behaviors.
Analyses of outdoor traffic-related particulate matter (PM) concentration distribution and fluctuation patterns in urban street canyons within a microscale distance of less than 500 m from a highway source are presented as part of the results from the Brooklyn Traffic Real-Time Ambient Pollutant Penetration and Environmental Dispersion (B-TRAPPED) study. Various patterns of spatial and temporal changes in the street canyon PM concentrations were investigated using time-series data of real-time PM concentrations measured during multiple monitoring periods. Concurrent time-series data of local street canyon wind conditions and wind data from the John F. Kennedy (JFK) International Airport National Weather Service (NWS) were used to characterize the effects of various wind conditions on the behavior of street canyon PM concentrations.
A theoretical model of olfaction involving all the major mechanisms in the mass transport of odorant molecules from inspired air to the olfactory receptors is developed. The mechanisms included are: (i) convective bulk flow of odorant molecules to the olfactory region of the nasal cavity by inhaled air, (ii) lateral transport of odorant molecules from the flowing gas stream in the olfactory region onto the olfactory mucus surface, (iii) sorption of odorant molecules into the mucus at the air-mucus interface, (iv) diffusion of odorant molecules through the mucus layer, and (v) interaction of odorant molecules with the olfactory receptor cells. The model is solved to yield the olfactory response as a function of various physical variables such as the inspiratory flow rate, the mass transfer coefficient, the initial concentration of odorant molecules in the inhaled air, the length of the olfactory mucosa, the thickness of the olfactory mucosa, and the air-mucus partitioning (or solubility in the mucus) of odorant molecules. It was determined that the flow rate of the odorant carrier gas, length of the olfactory mucus surface, and the solubility of odorant molecules in the olfactory mucus should play important roles in determining the odor intensity for these odorants. The model predicts that, given adequate mucus surface for sorption, increase in the flow rate results in an increase in perceived odor intensity for the readily sorbed or highly soluble odorants (such as carvone) and a decrease in odor intensity for the poorly sorbed or insoluble odorants (such as octane). With a substantial decrease in the mucus surface for sorption, increase in the flow rate results in a decrease in perceived odor intensity for all odorants. The theoretical results show good agreement with various experimental data obtained from both psychophysical and electrophysiological studies of olfaction using animals and human subjects.
Under EPA's overarching mission to protect human health and the environment, one of the major research priorities of the EPA's Office of Research & Development (ORD) Sustainable and Healthy Communities (SHC) National Research Program1 is to promote and build healthy and resilient communities2 (description of both programs available online). Many communities and their supporting ecosystems3 face high pollutant exposures and risks. Human exposure and effects can be exacerbated by nonchemical stressors (also known as modifying factors) such as poverty, limited access to services, pre-existing health conditions, and aging infrastructure that undermines pollution-control efforts. Nonchemical stressors that may intensify ecosystem exposures and effects include, for instance, habitat disturbance and destruction, life-stage-specific vulnerabilities and invasive species in addition to aging infrastructure. Fig. 1 illustrates a conceptual model for how environmental stressors, ecosystem services, and human health and well-being are inter-related and influence one another (EPA 2016). Impacted communities often lack the technical expertise, environmental knowledge, and community capacity to address these risks. EPA is making efforts to better evaluate, quantify, and incorporate cumulative impacts both quantitatively and qualitatively, and seeks to foster better integration of ecosystem services and human health and well-being by providing the knowledge, data, and tools needed while supporting local communities build capacity to become more sustainable and resilient. In order to successfully address this problem, understanding scientific framework for how ecosystem services may support human health and well-being (Millennium Ecosystem Assessment 2005) is important (Fig. 2). In 2015, the Intergovernmental Science-Policy Platform on Biodiversity and Ecosystem Services (IPBES) has presented the IPBES Conceptual Framework—connecting nature and people, illustrating complex inter-relationships connecting ecosystem services and human well-being (Fig. 3; Diaz et al. 2015). In 2017, EPA, under the STAR RFA, "Integrating Human Health and Well-Being with Ecosystem Services"4 has provided $2 million funding for four collaborative, community-based research projects (EPA STAR Grants, RD836938, RD836939, RD836942, and RD8369465) that will foster better understanding of how ecosystems support human health and well-being. Specifically, the major goals were to examine how communities can integrate ecosystem services with human health and well-being to (1) inform their decision-making and management practices; (2) develop information that allows communities to integrate environmental, societal, and economic information; (3) better manage multiple stressors and their cumulative impacts on humans and ecosystems; and (4) help communities achieve their own objectives. A common goal of these projects was to develop scientific evidence-based tools, models, or approaches to better enable communities to integrate environmental, societal, and economic information for optimal outcomes. The four research presentations, along with two EPA tools, EnviroAtlas and DASEES: Decision Analysis for a Sustainable Environment, Economy, and Society (Dyson and Canfield 2018) presentations aimed to integrate, synthesize, and generalize these different challenges into solutions for communities that can use for a variety of environmental/ecological problems. The main purposes of the symposium were to present compelling case studies and examples on how communities may make the most optimal decisions regarding its important ecology and human residents; to have open discussion with ESA members on how a community can bring about meaningful and impactful changes to bridge ecosystem and human health; and to have open dialogue about how scientific research results can be applied to real-world issues in actual communities, narrowing the gap between theory and practice in achieving the optimal ecological health and human health. Here are the summaries and results of each presentation: Human health and well-being are closely tied to the environment, which provides benefits such as clean water, clean air, and protection from natural hazards, also known as ecosystem goods and services. EnviroAtlas provides geospatial data, easy-to-use tools, and other resources related to ecosystem services, their chemical and nonchemical stressors, and human health. Ecosystem goods and services, often shortened to ecosystem services (ES), are the benefits that humans receive from nature. These benefits underpin almost every aspect of human well-being, including our food and water, security, health, and economy. Many of the decisions we make, from how to develop community infrastructure, to managing the land surrounding our communities, impact the provision of ES. We are not always conscious of the links between our surrounding environment and our well-being, and thus, we may not always take the true value of ecosystems into account in our decision-making processes. Considering the true value of ES in our policies and decision-making could help us better manage our resources in a way that would benefit us economically, environmentally, and socially. EnviroAtlas uses seven broad benefit categories to organize its information and data on ecosystem services: (1) Clean Air, (2) Clean and Plentiful Water, (3) Natural Hazard Mitigation, (4) Climate Stabilization, (5) Recreation, Culture, and Aesthetics, (6) Food, Fuel, and Materials, and (7) Biodiversity Conservation. EnviroAtlas contains over 400 map layers spanning the conterminous United States with about 100 additional layers at a finer resolution for almost 1,200 cities and towns across the United States. It features two primary tools: (1) an interactive map which makes environmental resources, policy implications, stressor, and demographic and other data discovery available to anyone with an internet connection and (2) an Eco-Health Browser which allows users to readily investigate the many linkages between ecosystems, ecosystem services, and human health and well-being as well as the pointing to the literature supporting those relationships. We discovered that while researchers do not seem to have any problems finding and using EnviroAtlas resources, the sheer amount and novelty of geospatial data can be overwhelming for decision-makers. Some decision-makers require explicit guidance on how to use the data in a decision context. One of the ways in which EnviroAtlas has met this need is by developing "use cases" which walk the user through the steps of a specific decision using EnviroAtlas resources. The case studies in this Symposium demonstrate how tools such as EnviroAtlas could successfully aid multidirectional engagements among decision-makers and communities trying to make the most optimal use of their ecosystem services and goods for promoting human health (see Presentations 3, 3 and 4, 4). DASEES is an application for structured decision-making (SDM), a process for evaluating scientific assessments with stakeholder objectives and preferences. A central insight of SDM is that environmental management may be more fruitfully accomplished as a decision to be made, rather than a problem to be studied. This shift in thinking provides opportunities for integration of the social, economic, and ecological issues facing communities such as ecosystem restoration and human well-being. The DASEES approach helps identify technical/scientific expertise and data needs for integrated multi-objective evaluation of decision alternatives. DASEES was used supporting a component of ongoing research into integrating human well-being and ecosystem services into near-term action planning in the Puget Sound (see Presentation 5). Through a combination of online and in-person support, various watershed restoration groups in Puget Sound were trained on the concepts of SDM and their implementation via DASEES. DASEES was then used by these groups to investigate the effectiveness of including human well-being measures into strategic funding decisions regarding watershed restoration. The analysis of decision consequences in DASEES is performed with supplied tools such as consequence tables and Bayesian networks. Consequence tables are suited for quicker screening evaluations where there is minimal uncertainty, while the use of Bayesian network evaluations is more suited for characterizing socio-ecologic causal linkages with uncertainty. These tools can be used separately or together depending on decision problem specific conditions. These tools provide the basis for prioritization and trade-off analyses among alternatives and yield examples for other watershed groups interested in better inclusion of social and ecological data for resource management. Direct engagement with group wrestling with these multifaceted funding decisions has resulted in useful feedback and insight on potential improvements to DASEES design and application with similar groups in the future. Harmful algal blooms (HABs) impede ecosystem services and enhance ecosystem dis-services. This study, conducted in a Vermont lakeside community, elucidates links between HABs and human well-being, and investigates how and why a community has taken action based on data about those links. The study has multiple objectives: to (1) determine relationships between HABs and the nutritional value of fish; (2) understand the impact of aerosolized neurotoxins from HABs on human health; (3) explore community members' mental models of HABs, including HABs' impact on nonmaterial benefits from human-lake relationships; (4) analyze 50+ years of local media coverage of HABs to understand messaging and treatment of scientific data; and (5) assess the effectiveness of informational framings to motivate action to reduce HABs. Overall, the study develops nuanced understanding of how communities accept, process, and understand scientific information related to HABs, and how they feel empowered or disempowered to affect change. Each component of the study employs an approach appropriate to its objective and the discipline(s) from which it draws. To test hypotheses about the links between HABs and multiple components of human well-being, we analyze the fatty acid and toxin content of fish, sample ambient aerosols within the community, and conduct an experiment to determine whether visual exposure to HABs leads to increases in stress. To elucidate how a community responds to information about HABs' impacts, we work with community partners to analyze historical media sources for factors influencing the failure of past initiatives to combat HABs, conduct an experimental survey that frames HAB impacts in multiple ways and observes motivations to take action, and conduct a community-based study of how people absorb, process, and (do not) act upon the increasing amount of HAB-related data with which they are presented. We also describe the use of EnviroAtlas outputs in our community engaged discussions of scientific information. This study will be completed in July 2021. Preliminary results include that fatty acid content is lower in fish tissue sampled during HABs; analysis of neurotoxins in aerosol samples is ongoing. Mental models research demonstrates that people of different backgrounds (e.g., farmers vs. lakeside property owners) understand the HABs and the actions required to address them differently. Media analysis demonstrates that the framing of and responses to HABs have changed dramatically over five decades and that they respond to scientific understanding in complex yet patterned ways. Ecologists and geologists provide increasingly unequivocal data about HABs and their deleterious impacts. This study will help communities to draw on these data to effectively reduce HABs. Systematic land-use planning for ecological sustainability does not typically include human health and well-being as explicit inputs. We tested the effects of including issues related to human health, ecosystem services, and community well-being on the outputs of a standard land use planning process which is primarily focused on environmental variables. We interviewed regional stakeholders to identify the health issues that have environmental links in the Sacramento, California region, and to identify potential indicators and datasets that can be used to assess and track these issues. We developed formal ontologies describe the relationships between individuals, organizations, sustainability issues, indicators, datasets, and legal mandates that influence sustainability planning in the region. Marxan planning software was used to identify efficient land-use patterns to maximize both ecological conservation and human health outcomes. Economic valuation of ecosystem services and health indicators associated with alternate land-use patterns allowed comparisons between these land-use scenarios. Economic valuation of ecosystem services was used to quantify changes in people's well-being—as measured by their own preferences—due to incremental changes in their environments. In particular, we assembled a database of 780 environment- and health-related actors of particular relevance in the region including organizational affiliation and areas of expertise. This was developed into an "expertise ontology." Health-focused issues, indicators, and datasets were integrated with a growing Environment Issues and Indicators ontology representing classes of regional environmental information. Interviews, online searches, and other information were used to assemble an ontology of people, projects, organizations, and datasets. Finally, a "mandates & guidelines" ontology was developed to formally track the linkages from policies and guidelines to regional sustainability issues and data. Encoding these data and information sources into interlinked ontologies permits query across multiple entry points and perspectives. A focus of the resulting databases and ontologies was the linkage of EPA tools and data to the region. For example, data found in EnviroAtlas were linked to regional sustainability issues to provide capacity to identify useful data sources in regional sustainability assessments. Marxan outputs were derived for four different land-use scenarios that varied in thematic focus. Ecosystem service valuations explicitly quantified trade-offs between scenarios. Preliminary results indicate likely co-benefits to be realized for both ecological and human health outcomes when both are included in regional planning processes. State and regional governments in the Puget Sound of Washington State are increasing their attention to the social and ecological benefits of ecosystem restoration, largely because it fulfills their dual mandates of protecting public goods and protecting the public. Natural resource managers, however, have little training in integrating social and ecological data to prioritize multi-benefit restoration strategies. This study sought to (1) understand how watershed restoration groups in the Puget Sound basin make strategic funding decisions and in what ways they considered human well-being in their planning and (2) experiment with three pathways for integrating human well-being and ecosystem service data to prioritize restoration activities that cumulatively contribute to both ecosystem service and human well-being outcomes. We answered the first question by conducting semi-structured interviews that included a cognitive map activity with 37 individuals from nine watershed boards that make biennial funding decisions for restoration priorities. The second component was addressed using participatory research with four of the nine boards, taking detailed notes as the research team facilitated the use of three tools to structure decisions: consequence tables (from DASEES), Bayesian networks (from DASEES), and spatial overlays of human well-being trends and ecosystem services (from EnviroAtlas and regional data). We found that while social and economic benefits were embedded as evaluative criteria within agency-prescribed decision-making tools, none of the nine watershed groups explicitly emphasized human well-being in their decision-making because they did not have the resources, stakeholders, understanding, or support to adequately do so. All recognized common factors needed for such integration: (1) access to and knowledge of data, (2) experience and understanding of human well-being and social science more broadly, (3) understanding socio-ecological linkages, (4) the presence of structures or systems that inform their decision-making (e.g., planning processes, prescribed decision-making tools), and (5) stakeholder inclusion and equity. While most watershed groups expressed similar enabling factors to human well-being integration, there were some distinctions, reflecting place-based variations. The use of both consequence tables from DASEES and spatial overlays from EnviroAtlas and regional monitoring data will be used by some, but not all of the groups due to limit capacity in their annual workplans, technological confidence of the lead restoration planner, and willingness to engage with new planning terminology. All projects will be wrapped up in fall of 2020, with full data analyses and documentation available by the end of 2021. Our hope is that this study may guide institutions in this and other regions that are still grappling with how to integrate social and ecological benefits into resource-management decisions. Intensive agricultural practices can lead to trade-offs between economic benefits and environmental and human health costs. For example, Concentrated Animal Feeding Operations (CAFOs) support local economies but are associated with air, surface, and groundwater pollution. Community-level management of pollution-related health risks requires (1) identifying neighborhoods that are vulnerable to contaminants and (2) understanding how community investments into physical capital and natural capital relate to one another in their capacity to reduce human exposure to contaminants. Examination of nearly 50,000 well water samples from 2013 to 2018 and over 1.3 million birth outcomes from 2007 to 2019 reveals that major hurricane events impair birth outcomes, such as reducing birthweight and increasing the likelihood of a preterm birth, near animal agriculture facilities. However, these birth impacts appear unrelated to the contamination of private wells and are driven primarily from stress and the disruption of access to prenatal services in rural underserved areas. Further analysis of private well water sampling and well construction trends reveals two behaviors that understate the social cost of groundwater pollution downstream of swine lagoons. First, we discover a uniform sampling schedule but a highly variable risk of bacterial contamination within each calendar year. We document a threshold of 90° Fahrenheit where total coliform and E. coli detection spikes in private wells near swine lagoons. The high-temperature bacterial contamination is absent during cooler temperatures suggesting that "cold-weather sampling" is unlikely to reflect year-round groundwater contamination risk. The annual gap between sampling and maximum air temperatures implies that annual total coliform and E. coli contamination rates near swine lagoons are 25% and 103% higher than prior thought. Alternative contamination sources cannot explain the contamination spike that is also absent in nearby wells upstream from swine lagoons. Second, for each 1-km increase in CAFO proximity, homeowners extend their well casing depth by 30 feet. We show that this avoidance-of-risk effect is isolated on wells known to be drinking water sources and is robust to a variety of specifications including controlling for soil profiles. Together, these findings suggest that the social cost of groundwater pollution from swine lagoons (human health cost + private adaptation cost) is likely to be larger than prior thought. Findings highlight that atmospheric stressors near animal agriculture operations influence local human health through many channels. State regulations and federal guidelines that coordinate domestic well water sampling with a seasonally fluctuating risk of groundwater contamination have the potential to improve public health by closing a gap between perceived and actual risks of drinking water contamination. Given the lifespan of wells, the distributional burden of private adaptation, and the size of the local animal agriculture industry, targeted and agriculture-funded subsidies for well construction and public water supply expansion may generate tremendous social benefits. Such a program should (1) account for spatially and temporally varying contamination risks and (2) be weighed against similar investments that ensure public health services to vulnerable populations, such as prenatal care, are undisrupted during severe weather events. More information about this ESA Symposium can be found on the 2019 ESA Annual Meeting website7.
Understanding infiltration of outdoor pollutants was an integral part of the Brooklyn Traffic Real-Time Ambient Pollutant Penetration and Environmental Dispersion (B-TRAPPED) study. For this reason, the structural and air exchange properties of the three-story row house in Brooklyn, NY, USA, that was used in the B-TRAPPED experiments were fully characterized. Factors investigated included representativeness of the construction and impact of building design features on the natural ventilation and infiltration of outdoor aerosol. Both blower door and perfluorocarbon tracer (PFT) air exchange rate (AER) experiments showed that the ventilation rates of the building were quite typical of similar structures in the New York City (NYC) metropolitan area. Indoor/outdoor (I/O) aerosol count ratios by particle size were comparable to a similar vintage naturally ventilated building in Boston, MA, USA. I/O ratio analyses were consistent with literature findings and showed I/O ratios ranging from 0.310 to 0.601, varying across particle sizes (from 0.3 to 0.5 μm) and between first and second floor apartments. An effort to apply the rebound method of Thatcher et al. (Aerosol Sci. Technol., 2003, 37, 847–864) in determining aerosol infiltration rates proved unsuccessful due to unexpectedly long (>60 min) equilibration times after the filtration period. Uninsulated interior wall renovations in the study house created a cavity that resulted in a large intermediate dead volume (for infiltration) that apparently could not be accommodated by a simple infiltration model. Simple two-compartment models evidently have finite application limitations for even modestly complex settings.
As part of the Brooklyn Traffic Real-Time Ambient Pollutant Penetration and Environmental Dispersion (B-TRAPPED) study, a field investigation was conducted of the mechanisms involved in infiltration of outdoor particles (0.02 μm to 1 μm) into a near-highway urban residential building. Using continuous real-time total number concentration time-series data measured simultaneously at multiple outdoor and indoor locations, the infiltration time was estimated for various indoor sites by using the cross-correlation analysis method.
