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At least 685 records · Page 38

Space Shuttle Main Engine Liquid Air Insulation Redesign Lessons Learned

The Space Shuttle Main Engine Liquid Air Insulation redesign was required to prevent the reoccurance of the STS-111 High Pressure Speed Sensor In-Flight Anomaly. The STS-111 In-Flight Anomaly Failure Investigation Team's initial redesign of the High Pressure Fuel Turbopump Pump End Ball Bearing Liquid Air Insulation failed the certification test by producing Liquid Air. The certification test failure indicated not only the High Pressure Fuel Turbopump Liquid Air Insulation, but all other Space Shuttle Main Engine Liquid Air Insulation. This paper will document the original Space Shuttle Main Engine Liquid Air STS-111 In-Flight Anomaly investigation, the heritage Space Shuttle Main Engine Insulation certification testing faults, the techniques and instrumentation used to accurately test the Liquid Air Insulation systems on the Stennis Space Center SSME test stand, the analysis techniques used to identify the Liquid Air Insulation problem areas and the analytical verification of the redesign before entering certification testing, Trade study down selected to three potential design solutions, the results of the development testing which down selected the final Liquid Air Redesign are also documented within this paper.

Darrell Gaddy↗

Asthma and Air Quality in the Presence of Fires - A Foundation for Public Health Policy in Florida

Outdoor air quality and its associated impacts on respiratory problems in Florida are of public health significance. Air quality in Florida can be poor during the extended wildfire season, threatening persons with compromised respiratory systems each year. Studies have demonstrated that particulate matter, which is generally elevated in the vicinity of wildfires, is associated with increases in hospital admissions and occurrences of acute asthma exacerbations. However, few studies have examined the modifying effect of socio-demographic characteristics of cities or regional areas on the relationship between air quality and health outcomes. In an ongoing university/multi-agency project, asthma hospital/emergency room (patient) data are being used to create a health outcome indicator of human response to environmental air quality. Environmental data are derived from satellite measurements, with special attention being given to the effect of wildfires and prescribed burns on air quality. This presentation will focus on the environmental data sets particulate matter, location of fires, smoke plumes that are being collected and processed for linkage with health data. After this linkage has been performed, space-time models of asthma rates as a function of air quality data and socio-demographic variables will be developed and validated. The Florida Department of Health (FDOH) will work with county health department staff and representatives from the medical community to establish a protocol with triggers for issuing public health advisories/alerts based on the developed and validated health outcome indicators. From this effort, a science-based policy for issuing public health advisories/alerts for asthma relating to air quality will be developed, giving FDOH the ability to (1) predict, with stated levels of uncertainty, case load of hospital admissions based on air quality, (2) reduce asthma exacerbations by forewarning asthmatics to limit outside activities on poor air quality days, (3) apply management practices on the rates of hospital/emergency room visits for asthma, and (4) provide information that would help translate interventions into policy decisions, thereby reducing the economic burden and increasing well being of asthmatics. Further, the results of the study will be incorporated into Florida s Environmental Public Health Tracking (EPHT) program, which is part of the Centers for Disease Control and Prevention's (CDC's) EPHT network.

Crosson, William↗

Operational use of the AIRS Total Column Ozone Retrievals along with the RGB Airmass Product as Part of the GOES-R Proving Ground

The Red, Green, Blue (RGB) Air Mass product has been demonstrated in the GOES ]R Proving Ground as a possible decision aid. Forecasters have been trained on the usefulness of identifying stratospheric intrusions and potential vorticity (PV) anomalies that can lead to explosive cyclogenesis, genesis of mesoscale convective systems (MCSs), or the transition of tropical cyclones to extratropical cyclones. It has also been demonstrated to distinguish different air mass types from warm, low ozone air masses to cool, high ozone air masses and the various interactions with the PV anomalies. To assist the forecasters in understanding the stratospheric contribution to high impact weather systems, the Atmospheric Infrared Sounder (AIRS) Total Column Ozone Retrievals have been made available as an operational tool. These AIRS retrievals provide additional information on the amount of ozone that is associated with the red coloring seen in the RGB Air Mass product. This paper discusses how the AIRS retrievals can be used to quantify the red coloring in RGB Air Mass product. These retrievals can be used to diagnose the depth of the stratospheric intrusions associated with different types of weather systems and provide the forecasters decision aid tools that can improve the quality of forecast products.

Folmer, M.↗

Use Of The Operational Air Quality Monitor (AQM) For In-Flight Water Testing Project

A primary requirement for manned spaceflight is Environmental Health which ensures air and water contaminants, acoustic profiles, microbial flora, and radiation exposures within the cabin are maintained to levels needed for crew health and for vehicle system functionality. The reliance on ground analyses of returned samples is a limitation in the current environmental monitoring strategy that will prevent future Exploration missions beyond low-Earth orbit. This proposal attempts to address this shortcoming by advancing in-flight analyses of water and air. Ground analysis of in-flight, air and water samples typically employ vapor-phase analysis by gas chromatography-mass spectrometry (GC-MS) to identify and quantify organic compounds present in the samples. We envision the use of newly-developed direct ionization approaches as the most viable avenue leading towards an integrated analytical platform for the monitoring of water, air, and, potentially bio-samples in the cabin environment. Development of an in-flight instrument capable of analyzing air and water samples would be the logical next step to meeting the environmental monitoring needs of Exploration missions. Currently, the Air Quality Monitor (AQM) on-board ISS provides this specific information for a number of target compounds in the air. However, there is a significant subset of common target compounds between air and water. Naturally, the following question arises, "Can the AQM be used for both air and water quality monitoring?" Previous directorate-level IR&D funding led to the development of a water sample introduction method for mass spectrometry using electrothermal vaporization (ETV). This project will focus on the integration of the ETV with a ground-based AQM. The capabilities of this integrated platform will be evaluated using a subset of toxicologically important compounds.

Macatangay, Ariel↗

Detection of Extremes with AIRS and CrIS

Climate change is expected to be detected first as changes in extreme values rather than in mean values. The availability of data of from two instruments in the same orbit, AIRS data for the past eleven years and AIRS and CrIS data from the past year, provides an opportunity to evaluate this using examples of climate relevance: Desertification, seen as changes in hot extremes, severe storm, seen as a change in extremely cold clouds and the warming of the polar zone. We use AIRS to establish trends for the 1%tile, the mean and 99%tile brightness temperatures measured with the 900 cm(exp -1) channel from AIRS for the past 11 years. This channel is in the clearest part of the 11 micron atmospheric window. Substantial trends are seen for land and ocean, which in the case of the 1%tile (cold) extremes are related to the current shift of deep convection from ocean to land. Changes are also seen in the 99%tile for day tropical land, but their interpretation is at present unclear. We also see dramatic changes for the mean and 99%tile of the North Polar area. The trends are an order of magnitude larger than the instrument trend of about 3 mK/year. We use the statistical distribution from the past year derived from AIRS to evaluate the accuracy of continuing the trends established with AIRS with CrIS data. We minimize the concern about differences in the spectral response functions by limiting the analysis to the channel at 900 cm(exp -1).While the two instruments agree within 100 mK for the global day/night land/ocean mean values, there are significant differences when evaluating the1% and 99%tiles. We see a consistent warm bias in the CrIS data relative to AIRS for the 1%tile (extremely cold, cloudy) data in the tropical zone, particularly for tropical land, but the bias is not day/night land/ocean consistent. At this point the difference appears to be due to differences in the radiometric response of AIRS and CrIS to differences in the day/night land/ocean cloud types. Unless the effect can be mitigated by a future reprocessing the CrIS data, it will significantly complicate the concatenation of the AIRS and CrIS data records for the continuation of trends in extreme values.

sampling bias↗

Results from CrIS/ATMS Obtained Using an AIRS "Version-6 like" Retrieval Algorithm

We tested and evaluated Version-6.22 AIRS and Version-6.22 CrIS products on a single day, December 4, 2013, and compared results to those derived using AIRS Version-6. AIRS and CrIS Version-6.22 O3(p) and q(p) products are both superior to those of AIRS Version-6All AIRS and CrIS products agree reasonably well with each other. CrIS Version-6.22 T(p) and q(p) results are slightly poorer than AIRS over land, especially under very cloudy conditions. Both AIRS and CrIS Version-6.22 run now at JPL. Our short term plans are to analyze many common months at JPL in the near future using Version-6.22 or a further improved algorithm to assess the compatibility of AIRS and CrIS monthly mean products and their interannual differences. Updates to the calibration of both CrIS and ATMS are still being finalized. JPL plans, in collaboration with the Goddard DISC, to reprocess all AIRS data using a still to be finalized Version-7 retrieval algorithm, and to reprocess all recalibrated CrISATMS data using Version-7 as well.

CrIS ATMS↗

The Safe Removal of Frozen Air from the Annulus of an LH2 Storage Tank

Large Liquid Hydrogen (LH2) storage tanks are vital infrastructure for NASA. Eventually, air may leak into the evacuated and perlite filled annular region of these tanks. Although the vacuum level is monitored in this region, the extremely cold temperature causes all but the helium and neon constituents of air to freeze. A small, often unnoticeable pressure rise is the result. As the leak persists, the quantity of frozen air increases, as does the thermal conductivity of the insulation system. Consequently, a notable increase in commodity boil-off is often the first indicator of an air leak. Severe damage can result from normal draining of the tank. The warming air will sublimate which will cause a pressure rise in the annulus. When the pressure increases above the triple point, the frozen air will begin to melt and migrate downward. Collection of liquid air on the carbon steel outer shell may chill it below its ductility range, resulting in fracture. In order to avoid a structural failure, as described above, a method for the safe removal of frozen air is needed. A thermal model of the storage tank has been created using SINDA/FLUINT modeling software. Experimental work is progressing in an attempt to characterize the thermal conductivity of a perlite/frozen nitrogen mixture. A statistical mechanics model is being developed in parallel for comparison to experimental work. The thermal model will be updated using the experimental/statistical mechanical data, and used to simulate potential removal scenarios. This paper will address methodologies and analysis techniques for evaluation of two proposed air removal methods.

cryogenic insulation↗

HESTIA Phase I Test Results: The Air Revitalization System

In any human spaceflight mission, a number of Environmental Control & Life Support System (ECLSS) technologies work together to provide the conditions astronauts need to live healthily, productively, and comfortably in space. In a long-duration mission, many of these ECLSS technologies may use materials supplied by In-Situ Resource Utilization (ISRU), introducing more interactions between systems. The Human Exploration Spacecraft Test-bed for Integration & Advancement (HESTIA) Project aims to create a test-bed to evaluate ECLSS and ISRU technologies and how they interact in a high-fidelity, closed-loop, human-rated analog habitat. Air purity and conditioning are essential components within any ECLSS and for HESTIA's first test they were achieved with the Air Revitalization System (ARS) described below. The ARS provided four essential functions to the test-bed chamber: cooling the air, removing humidity from the air, removing trace contaminants, and scrubbing carbon dioxide (CO2) from the air. In this case, the oxygen supply function was provided by ISRU. In the current configuration, the ARS is a collection of different subsystems. A fan circulates the air, while a condensing heat exchanger (CHX) pulls humidity out of the air. A Trace Contaminant Removal System (TCRS) filters the air of potentially harmful contaminants. Lastly, a Reactive Plastic Lithium Hydroxide (RP-LiOH) unit removes CO2 from the breathing air. During the HESTIA Phase I test in September 2015, the ARS and its individual components each functioned as expected, although further analysis is underway. During the Phase I testing and in prior bench-top tests, the energy balance of heat removed by the CHX was not equal to the cooling it received. This indicated possible instrument error and therefore recalibration of the instruments and follow-up testing is planned in 2016 to address the issue. The ARS was tested in conjunction with two other systems: the Human Metabolic Simulator (HMS) and the Electrolyzer. They behaved as anticipated as well. The HMS added humidity, CO2, and heat to the chamber while removing oxygen, and the Electrolyzer (an ISRU technology) added oxygen. The objective for HESTIA in 2015 was achieved: the creation of a high-fidelity test-bed for ECLSS and ISRU technologies. With the 'backbone' technologies installed, more technologies will be added to increase the analog habitat's fidelity over the next few years. The ARS was designed with this in mind, and as new technologies develop and mature, the strategic installation of the existing components will allow for them to be replaced with the new technologies.

Wright, Sarah E.↗

The Effect of Future Ambient Air Pollution on Human Premature Mortality to 2100 Using Output from the ACCMIP Model Ensemble

Ambient air pollution from ground-level ozone and fine particulate matter (PM(sub 2.5)) is associated with premature mortality. Future concentrations of these air pollutants will be driven by natural and anthropogenic emissions and by climate change. Using anthropogenic and biomass burning emissions projected in the four Representative Concentration Pathway scenarios (RCPs), the ACCMIP ensemble of chemistry climate models simulated future concentrations of ozone and PM(sub 2.5) at selected decades between 2000 and 2100. We use output from the ACCMIP ensemble, together with projections of future population and baseline mortality rates, to quantify the human premature mortality impacts of future ambient air pollution. Future air-pollution-related premature mortality in 2030, 2050 and 2100 is estimated for each scenario and for each model using a health impact function based on changes in concentrations of ozone and PM(sub 2.5) relative to 2000 and projected future population and baseline mortality rates. Additionally, the global mortality burden of ozone and PM(sub 2.5) in 2000 and each future period is estimated relative to 1850 concentrations, using present-day and future population and baseline mortality rates. The change in future ozone concentrations relative to 2000 is associated with excess global premature mortality in some scenarios/periods, particularly in RCP8.5 in 2100 (316 thousand deaths per year), likely driven by the large increase in methane emissions and by the net effect of climate change projected in this scenario, but it leads to considerable avoided premature mortality for the three other RCPs. However, the global mortality burden of ozone markedly increases from 382000 (121000 to 728000) deaths per year in 2000 to between 1.09 and 2.36 million deaths per year in 2100, across RCPs, mostly due to the effect of increases in population and baseline mortality rates. PM(sub 2.5) concentrations decrease relative to 2000 in all scenarios, due to projected reductions in emissions, and are associated with avoided premature mortality, particularly in 2100: between 2.39 and 1.31 million deaths per year for the four RCPs. The global mortality burden of PM(sub 2.5) is estimated to decrease from 1.70 (1.30 to 2.10) million deaths per year in 2000 to between 0.95 and 1.55 million deaths per year in 2100 for the four RCPs due to the combined effect of decreases in PM(sub 2.5) concentrations and changes in population and baseline mortality rates. Trends in future air-pollution-related mortality vary regionally across scenarios, reflecting assumptions for economic growth and air pollution control specific to each RCP and region. Mortality estimates differ among chemistry climate models due to differences in simulated pollutant concentrations, which is the greatest contributor to overall mortality uncertainty for most cases assessed here, supporting the use of model ensembles to characterize uncertainty. Increases in exposed population and baseline mortality rates of respiratory diseases magnify the impact on premature mortality of changes in future air pollutant concentrations and explain why the future global mortality burden of air pollution can exceed the current burden, even where air pollutant concentrations decrease.

Silva, Raquel A.↗

Flexible Data Fusion for Air Quality Estimation and Forecasting in Google Earth Engine to support Global Health Management Needs

The assessment and forecasting of air quality around the world at high spatial and temporal resolution can be enhanced by integrating data from multiple sources including models, satellites, regulatory monitors, and low-cost sensors. Such integration is subject to numerous technical challenges, however, including heterogeneous data resolution and formatting, different levels of data availability and reliability, and computational and capacity challenges to developing data fusion tools and platforms. This presentation will provide an overview of a NASA-funded effort to develop a data fusion system within the Google Earth Engine platform which integrates these air quality data sources to produce comprehensive assessments and forecasts of key air pollutants at sub-daily and sub-city scales. The system is being developed in collaboration with city- and regional-level air quality managers, and will provide them with information to the assess and anticipate the health impacts of poor air quality, track local changes in air quality due to ongoing transportation and land use changes, and identify potential gaps in their current air quality monitoring strategies. The presentation will report advances achieved through the project, including bringing local air quality monitoring data into Google Earth Engine, quantifying uncertainties in air quality estimates and forecasts, and tailored communications tools providing integration into end-user processes to meet their needs.

Carl Malings↗

Flexible Data Fusion for Air Quality Estimation and Forecasting in Google Earth Engine to support Global Health Management Needs

The assessment and forecasting of air quality around the world at high spatial and temporal resolution can be enhanced by integrating data from multiple sources including models, satellites, regulatory monitors, and low-cost sensors. Such integration is subject to numerous technical challenges, however, including heterogeneous data resolution and formatting, different levels of data availability and reliability, and computational and capacity challenges to developing data fusion tools and platforms. This presentation will provide an overview of a NASA-funded effort to develop a data fusion system within the Google Earth Engine platform which integrates these air quality data sources to produce comprehensive assessments and forecasts of key air pollutants at sub-daily and sub-city scales. The system is being developed in collaboration with city- and regional-level air quality managers and will provide them with information to the assess and anticipate the health impacts of poor air quality, track local changes in air quality due to ongoing transportation and land use changes, and identify potential gaps in their current air quality monitoring strategies. The presentation will report advances achieved through the project, including bringing local air quality monitoring data into Google Earth Engine, quantifying uncertainties in air quality estimates and forecasts, and tailored communications tools providing integration into end-user processes to meet their needs.

Nathan R. Pavlovic↗

Scoping of an Air Supply Configuration for AFC on a Commercial Transport Airplane High Lift System

A scoping study is being conducted on the air supply fora microjet-based active flow control (AFC) system on a twin-turbofan commercial transport airplane. Microjets provide circulation control using small surface-normal pneumatic jets located near the trailing edge of a lifting surface such as a wing or flap. When located on the pressure side of the lifting surface they increase the lift, and when located on the suction side they decrease lift. In this study, microjets are considered for installation in the flaps of the high-lift version of the Common ResearchModel (CRM-HL). Two different architectures to supply the air for the microjets are considered: (1) bleed air from the airplane’s auxiliary power unit (APU) plus ram air, and (2) engine fan bleed air plus ram air. A model based on the 1D compressible flow equations is applied to analyze the air supply system architectures and predict the microjet flow rate with the resulting airplane performance changes based on Reynolds-averaged Navier-Stokes modeling of microjets on the CRM-HL. The results of this scoping study are encouraging in that pressurized air from the APU or the engine fan can be used to entrain ram air and thereby increase the AFC mass flow rate to achieve effective lift control and airplane performance enhancement during takeoff and landing.

AATT↗

Application of Structured Decision Making to Hanford Site Radiological Air Monitoring - 17924

Radiological air monitoring is a component of an Environmental Surveillance (ES) program that has been in operation at the Department of Energy Hanford Site for several decades. The primary objectives of the ES program are protection of human health and the environment (on and off-site) as well as regulatory compliance. The ES program was designed decades ago when the plutonium-production reactors and related facilities at the Hanford Site were operational and air emissions were more widespread and significant than today. We employed a structured decision making (SDM) approach that integrates science with values and preferences to a Hanford Site air monitoring program decision. Specifically, a decision was necessary pertaining to the possible replacement of three air monitoring stations located in the 100 Area of the Hanford Site because the power line that supports these stations was near the end of its lifecycle. Although focused on this specific decision, the SDM model is more broadly applicable to decisions pertaining to adapting the air monitoring network to current Hanford operations. The value focused thinking approach that underlies SDM facilitates transparent and defensible decision making, and aids in communicating monitoring rationale. Some of the fundamental objectives elicited from the decision makers regarding management options for the three air monitoring stations included maximizing the ability to measure releases, minimizing environmental impacts, and maximizing social and economic sustainability. The fundamental objectives were linked to six objectives that could be measured (quantified) to allow a decision-analytic solution to the decision problem. Value functions and preference weights were developed for each of the objectives measures based on information obtained during a project workshop as well as by review and analysis of environmental data. Lastly, a set of five management options was identified that might achieve at least one of the objectives. A Bayes Network was developed as a solution to the decision problem pertaining to the three air stations (the 3 air stations decision). The Bayes Network describes the decision model graphically, and also serves as the computational engine for the decision analysis. The Bayes Network defines the relationship among the five management options and six objectives measures. In addition to the weights and value functions noted above, key inputs to the Bayes Network include a set of probabilities related to the different model states defined by the network. These include the probability of a significant release occurring, the probability that a release would be detected under each of the five management options, and the probability of achieving the other objective measures under each management option. In this manner the Bayesian Network captures the uncertainty in the components of the decision model. Replacing the three air monitoring stations with thermoluminescent dosimeters was identified as the preferred management option. A brief report was developed documenting the SDM model, including the workshop notes and analyses that were used to develop the objectives and model input variable values. This application demonstrates SDM's utility for supporting monitoring program decisions and, critically, providing a transparent and traceable basis for the decision. This relatively simple SDM model also provides a basis for an SDM model for monitoring decisions related to the more complex and holistic goal of achieving ES program objectives. (authors)

61 RADIATION PROTECTION AND DOSIMETRY↗

Field demonstration of a tracer method to track simulated exhaled air trajectories and mixing in three connected rooms with upper-room GUV

We conducted tracer gas experiments in three connected nursery rooms to track simulated exhaled air trajectories and mixing. We emulated exhaled air with a pulse release of ethanol and measured its concentration with 2s time resolution with spatially distributed metal oxide sensors in both the upper and occupied levels of the room. We found that the overhead cooling supply air enhanced vertical air mixing within the rooms. When a room had higher supply airflow than the others, the tracer gas mixed quickly in that room because the supply air dominated the room mixing, thereby isolating it from air mixing with the other rooms. When the forced air system was not operating, the tracer gas resided longer in the upper room before descending. The tracer method also depicts air trajectories from different release locations by detecting the release point and affecting nearby sensors. These experiments support the potential of this method to be used in the field for understanding air trajectories in rooms with upper-room GUV.

Um, Chai Yoon↗

Measuring greenhouse gas emissions from international air travel of a country’s residents methodological development and application for Sweden

Highlights: • A new method for estimating a country's GHG emissions from international air travel. • A reliable method based on total statistics of departures and on surveys for distance to final destination. • Total emissions for Swedish residents' air travel increased by 61% between 1990 and 2014 • In 2014 Swedish residents air travel emissions was on par with emissions from Swedish car traffic - Abstract: Global civil aviation accounts for 4–5% of total greenhouse gas emissions and these emissions are increasing. In the absence of sufficiently effective global climate instruments, national instruments might be considered as a complement, in which case some way of allocating emissions from international air travel between countries is needed. The purpose of this paper is to develop an accounting method that reflects one country's greenhouse gas emissions from international air travel, and to apply this methodology to Sweden. The new methodology consists of three parts: the number of international air trips made by the country's residents; the average distance of these trips; and the greenhouse gas emissions per passenger km. For Sweden, data for 1990 to 2014 show an increase in the number of trips by Sweden's population of 3.6% per year, resulting in, on average, one international journey (round trip 5800 km) per capita in 2014. The average distance to the final destination has increased only marginally due to simultaneous growth in both long and short trips. However, global average greenhouse gas emissions per passenger km have decreased by 1.9% per year between 1990 and 2014. Because the increase in the number of their trips has outweighed the decrease in emissions per km, the total emissions from Swedish residents' international air travel have increased by 61% between 1990 and 2014. The total emissions from Swedish residents' air travel, including both CO{sub 2} and non-CO{sub 2}-effects, were 11 Mt CO{sub 2} equivalents in 2014, which is the same level as the emissions from Swedish car traffic. This type of reliable data is important when designing policies and for getting public support for new policies.

54 ENVIRONMENTAL SCIENCES↗

Enhanced data validation strategy of air quality monitoring network

Quick validation and detection of faults in measured air quality data is a crucial step towards achieving the objectives of air quality networks. Therefore, the objectives of this paper are threefold: (i) to develop a modeling technique that can be used to predict the normal behavior of air quality variables and help provide accurate reference for monitoring purposes; (ii) to develop fault detection method that can effectively and quickly detect any anomalies in measured air quality data. For this purpose, a new fault detection method that is based on the combination of generalized likelihood ratio test (GLRT) and exponentially weighted moving average (EWMA) will be developed. GLRT is a well-known statistical fault detection method that relies on maximizing the detection probability for a given false alarm rate. In this paper, we propose to develop GLRT-based EWMA fault detection method that will be able to detect the changes in the values of certain air quality variables; (iii) to develop fault isolation and identification method that allows defining the fault source(s) in order to properly apply appropriate corrective actions. In this paper, reconstruction approach that is based on Midpoint-Radii Principal Component Analysis (MRPCA) model will be developed to handle the types of data and models associated with air quality monitoring networks. All air quality modeling, fault detection, fault isolation and reconstruction methods developed in this paper will be validated using real air quality data (such as particulate matter, ozone, nitrogen and carbon oxides measurement).

54 ENVIRONMENTAL SCIENCES↗

Long-term exposure to ambient air pollution (including PM1) and metabolic syndrome: The 33 Communities Chinese Health Study (33CCHS)

Highlights: • Associations of ambient air pollution with metabolic syndrome were scarcely studied. • Data from 15,477 Chinese adults were analyzed. • Long-term exposure to air pollution was associated with metabolic syndrome. • Demographic and lifestyle factors modified the association between metabolic syndrome and air pollution. Little evidence exists about the effects of long-term exposure to ambient air pollution on metabolic syndrome (MetS). This study aimed to determine the association between long-term ambient air pollution and MetS in China. A total of 15,477 adults who participated in the 33 Communities Chinese Health Study (33CCHS) in 2009 were evaluated. MetS was defined based on the recommendation by the Joint Interim Societies. Exposure to air pollutants was assessed using data from monitoring stations and a spatial statistical model (including particles with diameters ≤ 1.0 µm (PM{sub 1}), ≤ 2.5 µm (PM{sub 2.5}), and ≤ 10 µm (PM{sub 10}), sulfur dioxide (SO{sub 2}), nitrogen dioxide (NO{sub 2}), and ozone (O{sub 3})). Two-level logistic regression analyses were utilized to assess the associations between air pollutants and MetS. The prevalence of MetS was 30.37%. The adjusted odds ratio of MetS per 10 µg/m{sup 3} increase in PM{sub 1}, PM{sub 2.5}, PM{sub 10}, SO{sub 2}, NO{sub 2}, and O{sub 3} were 1.12 (95% CI = 1.00–1.24), 1.09 (95% CI = 1.00–1.18), 1.13 (95% CI = 1.08–1.19), 1.10 (95% CI = 1.02–1.18), 1.33 (95% CI = 1.12–1.57), and 1.10 (95% CI = 1.01–1.18), respectively. Stratified analyses indicated that the above associations were stronger in participants with the demographic variables of males, < 50 years of age, and higher income, as well as with the behavioral characteristics of smoking, drinking, and consuming sugar-sweetened soft drinks frequently. This study indicates that long-term exposure to ambient air pollutants may increase the risk of MetS, especially among males, the young to middle aged, those of low income, and those with unhealthy lifestyles.

54 ENVIRONMENTAL SCIENCES↗

The burden of ischemic heart disease related to ambient air pollution exposure in a coastal city in South China

Highlights: • Burden of ischemic heart disease related to PM{sub 2.5}, SO{sub 2} and NO{sub 2} were estimated. • Stronger impacts of gaseous pollutants versus particulate matter were found. • SO{sub 2} exposure was positively associated with YLL in widowed group. Air pollution is considered one of the most important risk factors for ischemic heart disease (IHD), which is a major public health concern. The disease burden of IHD has continued to rise in China in the past two decades. However, epidemiological studies examining the associations between air pollution and IHD have been scarce in China, and the only studies were conducted in severe air pollution areas, where air pollution levels seriously exceed the World Health Organization Air Quality Guidelines. Whether the influence of air pollution on IHD in areas with relatively low levels of air pollution differs from the influence of high pollution levels in heavily studied areas was unknown until now. Furthermore, the estimation of the disease burden of IHD related to air pollution has been very limited.

54 ENVIRONMENTAL SCIENCES↗