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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 73 records · Page 4
All sourcesNASA NTRSDOE OSTI
NASA NTRS2010

MISSE 6 Polymer Film Tensile Experiment

The Polymer Film Tensile Experiment (PFTE) was flown as part of Materials International Space Station Experiment 6 (MISSE 6). The purpose of the experiment was to expose a variety of polymer films to the low Earth orbital environment under both relaxed and tension conditions. The polymers selected are those commonly used for spacecraft thermal control and those under consideration for use in spacecraft applications such as sunshields, solar sails, and inflatable and deployable structures. The dog-bone shaped samples of polymers that were flown were exposed on both the side of the MISSE 6 Passive Experiment Container (PEC) that was facing into the ram direction (receiving atomic oxygen, ultraviolet (UV) radiation, ionizing radiation, and thermal cycling) and the wake facing side (which was supposed to have experienced predominantly the same environmental effects except for atomic oxygen which was present due to reorientation of the International Space Station). A few of the tensile samples were coated with vapor deposited aluminum on the back and wired to determine the point in the flight when the tensile sample broke as recorded by a change in voltage that was stored on battery powered data loggers for post flight retrieval and analysis. The data returned on the data loggers was not usable. However, post retrieval observation and analysis of the samples was performed. This paper describes the preliminary analysis and observations of the polymers exposed on the MISSE 6 PFTE.

Miller, Sharon K. R.↗
NASA NTRS2014

Veggie Hardware Validation Test Preliminary Results and Lessons Learned

The Veggie hardware validation test, VEG-01, was conducted on the International Space Station during Expeditions 39 and 40 from May through June of 2014. The Veggie hardware and the VEG-01 experiment payload were launched to station aboard the SpaceX-3 resupply mission in April, 2014. Veggie was installed in an Expedite-the-Processing-of-Experiments-to-Space-Station (ExPRESS) rack in the Columbus module, and the VEG-01 validation test was initiated. Veggie installation was successful, and power was supplied to the unit. The hardware was programmed and the root mat reservoir and plant pillows were installed without issue. As expected, a small amount of growth media was observed in the sealed bags which enclosed the plant pillows when they were destowed. Astronaut Steve Swanson used the wet/dry vacuum to clean up the escaped particles. Water insertion or priming the first plant pillow was unsuccessful as an issue prevented water movement through the quick disconnect. All subsequent pillows were successfully primed, and the initial pillow was replaced with a backup pillow and successfully primed. Six pillows were primed, but only five pillows had plants which germinated. After about a week and a half it was observed that plants were not growing well and that pillow wicks were dry. This indicated that the reservoir was not supplying sufficient water to the pillows via wicking, and so the team reverted to an operational fix which added water directly to the plant pillows. Direct watering of the pillows led to a recovery in several of the stressed plants; a couple of which did not recover. An important lesson learned involved Veggie's bellows. The bellows tended to float and interfere with operations when opened, so Steve secured them to the baseplate during plant tending operations. Due to the perceived intensity of the LED lights, the crew found it challenging to both work under the lights and read crew procedures on their computer. Although the lights are not a safety hazard, for visual comfort crewmembers were advised to wear sunglasses when working with the plants and then they can lift glasses to read procedures. Steve Swanson had already trail-blazed this procedure when he initiated VEG-01. The temperature and humidity data logger was relocated mid-experiment to provide measurements on both sides of the unit. Images of the plants were downlinked weekly, and videos of installation and harvest were recorded. This imaging frequency was not sufficient to monitor and respond to changes in plant growth. Plants, samples, and data loggers will be returned on SpaceX-4, scheduled to return the fall of 2014. Lessons learned will be translated into hardware and operational modifications for future Veggie payloads.

International Space Station↗
NASA NTRS2017

Position Paper - pFLogger: The Parallel Fortran Logging framework for HPC Applications

In the context of high performance computing (HPC), software investments in support of text-based diagnostics, which monitor a running application, are typically limited compared to those for other types of IO. Examples of such diagnostics include reiteration of configuration parameters, progress indicators, simple metrics (e.g., mass conservation, convergence of solvers, etc.), and timers. To some degree, this difference in priority is justifiable as other forms of output are the primary products of a scientific model and, due to their large data volume, much more likely to be a significant performance concern. In contrast, text-based diagnostic content is generally not shared beyond the individual or group running an application and is most often used to troubleshoot when something goes wrong. We suggest that a more systematic approach enabled by a logging facility (or logger) similar to those routinely used by many communities would provide significant value to complex scientific applications. In the context of high-performance computing, an appropriate logger would provide specialized support for distributed and shared-memory parallelism and have low performance overhead. In this paper, we present our prototype implementation of pFlogger a parallel Fortran-based logging framework, and assess its suitability for use in a complex scientific application.

Fortran↗
NASA NTRS2017

POSITION PAPER - pFLogger: The Parallel Fortran Logging Framework for HPC Applications

In the context of high performance computing (HPC), software investments in support of text-based diagnostics, which monitor a running application, are typically limited compared to those for other types of IO. Examples of such diagnostics include reiteration of configuration parameters, progress indicators, simple metrics (e.g., mass conservation, convergence of solvers, etc.), and timers. To some degree, this difference in priority is justifiable as other forms of output are the primary products of a scientific model and, due to their large data volume, much more likely to be a significant performance concern. In contrast, text-based diagnostic content is generally not shared beyond the individual or group running an application and is most often used to troubleshoot when something goes wrong. We suggest that a more systematic approach enabled by a logging facility (or 'logger') similar to those routinely used by many communities would provide significant value to complex scientific applications. In the context of high-performance computing, an appropriate logger would provide specialized support for distributed and shared-memory parallelism and have low performance overhead. In this paper, we present our prototype implementation of pFlogger - a parallel Fortran-based logging framework, and assess its suitability for use in a complex scientific application.

Clune, Thomas L.↗
NASA NTRS2017

pFlogger: The Parallel Fortran Logging Utility

In the context of high performance computing (HPC), software investments in support of text-based diagnostics, which monitor a running application, are typically limited compared to those for other types of IO. Examples of such diagnostics include reiteration of configuration parameters, progress indicators, simple metrics (e.g., mass conservation, convergence of solvers, etc.), and timers. To some degree, this difference in priority is justifiable as other forms of output are the primary products of a scientific model and, due to their large data volume, much more likely to be a significant performance concern. In contrast, text-based diagnostic content is generally not shared beyond the individual or group running an application and is most often used to troubleshoot when something goes wrong. We suggest that a more systematic approach enabled by a logging facility (or 'logger)' similar to those routinely used by many communities would provide significant value to complex scientific applications. In the context of high-performance computing, an appropriate logger would provide specialized support for distributed and shared-memory parallelism and have low performance overhead. In this paper, we present our prototype implementation of pFlogger - a parallel Fortran-based logging framework, and assess its suitability for use in a complex scientific application.

Clune, Tom↗
DOE OSTI2016

Cosmic-Ray Moisture Probe on North Slope of Alaska Field Campaign Report

In September of 2014 a wide-area snow monitoring device was installed at the U.S. Department of Energy (DOE)’s Barrow, Alaska Atmospheric Radiation Measurement (ARM) Climate Research Facility site. The device is special in that it uses measurements of cosmic-ray neutrons as a proxy for snow water equivalent (SWE) depth. A unique characteristic of the technology is that it integrates over a wide area (as much as 40 ha), in contrast to conventional ground-based technologies, which essentially give point samples. Conventional point-scale technologies are problematic in the Arctic, both because extreme weather conditions are taxing on equipment, and because point measurements can fail to accurately characterize the average SWE over a larger area, even when excellent precision is obtained. The sensor installed in Barrow is, by far, the northernmost of a constellation of sites that makeup the U.S. COsmic ray Soil Moisture Observing System (COSMOS). The sensor is used for SWE measurements in winter and soil moisture measurements in summer. The ability of this type of sensor to operate in the Arctic had not been verified until now. The cosmic-ray sensor was installed on a tripod located approximately 150 m south of the ARM User Facility (Figure 1), and within boundaries of land managed by the ARM Facility. The sensor consists of both “bare” and “moderated” channels, where the moderated channel is the primary output used to calculate SWE. A QDL2100 data logger with pressure sensor was located inside of the User Facility, and a Campbell CS215 temperature and humidity sensor was attached to a rail on the upper deck of the User Facility, to enable near-real-time absolute humidity corrections to the data. The cosmic-ray sensors are connected to the data logger using an armored Cat5e cable that lies on top of the tundra. Data are retrieved hourly via Iridium satellite link.

"North Slope of Alaska, Barrow, soil moisture, cos↗
DOE OSTI2026

Scalable GPS Data Logging To Support Advanced Fleet Analysis

This highlight details the key takeaways from a project that utilized NLR's Fleet Research, Energy Data, and Insights (FleetREDI) data analysis pipeline. National Laboratory of the Rockies researchers developed and demonstrated low-cost, open-source Arduino data loggers with 3D-printed cases that are compatible with global navigational systems and built with components available ubiquitously worldwide, enabling cost-effective collection and analysis of fleet operational data. Validated on an overseas transit bus fleet, NLR analysis showed that, with sufficient charging opportunities, 90% of observed duty cycles could be accomplished by electric buses with no modifications to operations.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2025

Raspberry Pi–powered temperature monitoring of growth chamber microclimates

While controlled environments are desirable for growing and measuring plants, growth chambers and greenhouses typically have microclimates that impact plant growth, development, and stress responses. Furthermore, opening and closing the doors of a controlled environment introduces variation in the environment, especially at temperature extremes, affecting both the measurements and the organisms within. Using multiple temperature data loggers to normalize results can be cost-prohibitive and rarely offers real-time feedback on temperature status. We used low-cost single-board computers, cameras, and temperature sensors to manage and capture growth chamber temperatures while acquiring plant image data. Detailed here are methods to document microclimates within a growth chamber so that data can be normalized to measured temperature information. This protocol describes a low-cost method for automated temperature monitoring, which enables both high-throughput measurements of temperature along with plant growth and stress responses via plant imaging.

Plant Sciences↗
DOE OSTI2024

A semi–automatic analytical methodology for characterizing the energy consumption of MRI systems using load duration curves

Background and purpose: Magnetic resonance imaging (MRI) scanners are a major contributor to greenhouse gas emissions from the healthcare sector, and efforts to improve energy efficiency and reduce energy consumption rely on quantification of the characteristics of energy consumption. The purpose of this work was to develop a semi-automatic analytical methodology for the characterization of the energy consumption of MRI systems using only the load duration curve (LDC). LDCs are a fundamental tool used across various fields to analyze and understand the behavior of loads over time. Methods: An electric current transformer sensor and data logger were installed on two 3T MRI scanners from two vendors, termed M1 (outpatient scanner) and M2 (inpatient/emergency scanner). Data was collected for 1 month (7/11/2023 to 8/11/2023). Active power was calculated, assuming a balanced three-phase system, using the average current measured across all three phases, a 480 V reference voltage for both machines, and vendor-provided power factors. An LDC was constructed for each system by sorting the active power values in descending order and computing the cumulative time (in units of percentage) for each data point. The first derivative of the LDC was then computed (LDC’), smoothed by convolution with a window function (sLDC’), and used to detect transitions between different system modes including (in descending power levels): scan, prepared-to-scan, idle, low-power, and off. The final, segmented LDC was used to measure time (% total time), total energy (kWh), and mean power (kW) for each system mode on both scanners. The method was validated by comparing mean power values, computed using the segmented 1-month LDC, for each nonproductive system mode (i.e., prepared-to-scan, idle, lower-power, and off) against power levels measured after a deliberate system shutdown was performed for each scanner (1 day worth of data). Results: The validation revealed differences in mean power values <1.4% for all nonproductive modes and both scanners. In the scan system mode, the mean power values ranged from 29.8 to 37.2 kW and the total energy consumed for 1 month ranged from 11 106 to 14 466 kWh depending on the scanner. Over the course of 1 month, the portion of time the scanners were in nonproductive modes ranged from 76% to 80% across scanners and the nonproductive energy consumption ranged from 8010 to 6722 kWh depending on the scanner. The M1 (outpatient) scanner consumed 99.9 and 183.9 kWh/day in idle mode for weekdays and weekends, respectively, because the scanner spent 23% more time proportionally in idle mode on the weekends. Conclusions: A semi-automatic method for quantifying energy consumption characteristics of MRI scanners was introduced and validated. This method is relatively simple to implement as it requires only power data from the scanners and avoids the technical challenges associated with extracting and processing scanner log files. Finally, the methodology enables quantitative evaluation of the power, time, and energy characteristics of MRI scanners in scan and nonproductive system modes, providing baseline data and the capability of identifying potential opportunities for enhancing the energy efficiency of MRI scanners.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2018

Impacts of hydrogeological characteristics on groundwater-level changes induced by earthquakes

Changes in groundwater level during earthquakes have been reported worldwide. In this study, field observations of co-seismic groundwater-level changes in wells under different aquifer conditions and sampling intervals due to near-field earthquake events in Taiwan are presented. Sustained changes, usually observed immediately after earthquakes, are found in the confined aquifer. Oscillatory changes due to the dynamic strain triggered by passing earthquake waves can only be recorded by a high-frequency data logger. While co-seismic changes recover rapidly in an unconfined aquifer, they can sustain for months or longer in a confined aquifer. Three monitoring wells with long-term groundwater-level data were examined to understand the association of co-seismic changes with local hydrogeological conditions. The finite element software ABAQUS is used to simulate the pore-pressure changes induced by the displacements due to fault rupture. The calculated co-seismic change in pore pressure is related to the compressibility of the formation. The recovery rate of the change is rapid in the unconfined aquifer due to the hydrostatic condition at the water table, but slow in the confined aquifer due to the less permeable confining layer. Fracturing of the confining layer during earthquakes may enhance the dissipation of pore pressure and induce the discharge of the confined aquifer. The study results indicated that aquifer characteristics play an important role in determining groundwater-level changes during and after earthquakes.

58 GEOSCIENCES↗
DOE OSTI2018

Recharge estimation from discrete water-table datasets in a coastal shallow aquifer in a humid subtropical climate

A time-series approach to the estimation of recharge rate in unconfined aquifers of highly variable water level is proposed. The approach, which is based on the water-table fluctuation method (WTF), utilizes discrete water-level measurements. Other similar techniques require continuous measurements, which makes them impossible to apply in cases where no data from automatic loggers are available. The procedure is deployed at the Ressacada Farm site, southern Brazil, on a coastal shallow aquifer located in a humid subtropical climate where diurnal water-level variations of up to 1 m can follow a precipitation event. The effect of tidal fluctuations on the groundwater levels is analyzed using a harmonic component builder, while a time-variable drainage term is evaluated through an independent analysis and included in the assessment. The estimated recharge values are compared with those obtained from the continuous measurements showing a good agreement with the approaches for discrete dataset intervals of up to 15 days. Subsequently, the estimated recharge rates are incorporated into a transient groundwater-flow model and the water levels are compared showing a good match. Henceforth, the approach extends the applicability of WTF to noncontinuous water-level datasets in groundwater recharge studies.

58 GEOSCIENCES↗
DOE OSTI2018

Behaviour related flight speeds of Sandwich Terns and their implications for wind farm collision rate modelling and impact assessment

Highlights: • Flight speeds of Sandwich Terns vary with behavioural states. • Flight speed is a vital part of wind turbine collision rate models (CRM) for birds. • The variation in flight speed has major consequences for CRM output. • CRM output is vital for adequate Environmental Impact Assessments. - Abstract: Accurate quantification of flight speeds is a prerequisite to accurately predict the numbers of collision victims of proposed wind farms using collision rate models that are a vital part of Environmental Impact Assessments. We used GPS-loggers on Sandwich Terns to collect novel data on instantaneous flight speeds during foraging trips, separated for different behavioural stages, and applied these estimates in a widely used collision rate model. Average flight speed during a foraging trip corrected for individual variation and flight type was 36.9 ± 12.3 SD km h{sup −1} and flight speed was highest during inbound commuting (44.4 ± 12.0 km h{sup −1}) and lowest during foraging (29.9 ± 10.7 km h{sup −1}). Our results show significant differences in flight speeds of Sandwich Terns between behaviour stages during foraging trips, which resulted in divergent estimates of collision victims due to wind turbines depending on the function of the area in which wind farms are proposed. Since these conclusions are likely to hold for many other bird species, we conclude that behaviour of birds in a proposed wind farm is a factor to take into account when modelling collision rates as part of the Environmental Impact Assessment.

17 WIND ENERGY↗
DOE OSTI2015

Low correlation between household carbon monoxide and particulate matter concentrations from biomass-related pollution in three resource-poor settings

Household air pollution from the burning of biomass fuels is recognized as the third greatest contributor to the global burden of disease. Incomplete combustion of biomass fuels releases a complex mixture of carbon monoxide (CO), particulate matter (PM) and other toxins into the household environment. Some investigators have used indoor CO concentrations as a reliable surrogate of indoor PM concentrations; however, the assumption that indoor CO concentration is a reasonable proxy of indoor PM concentration has been a subject of controversy. We sought to describe the relationship between indoor PM{sub 2.5} and CO concentrations in 128 households across three resource-poor settings in Peru, Nepal, and Kenya. We simultaneously collected minute-to-minute PM{sub 2.5} and CO concentrations within a meter of the open-fire stove for approximately 24 h using the EasyLog-USB-CO data logger (Lascar Electronics, Erie, PA) and the personal DataRAM-1000AN (Thermo Fisher Scientific Inc., Waltham, MA), respectively. We also collected information regarding household construction characteristics, and cooking practices of the primary cook. Average 24 h indoor PM{sub 2.5} and CO concentrations ranged between 615 and 1440 μg/m{sup 3}, and between 9.1 and 35.1 ppm, respectively. Minute-to-minute indoor PM{sub 2.5} concentrations were in a safe range (<25 μg/m{sup 3}) between 17% and 65% of the time, and exceeded 1000 μg/m{sup 3} between 8% and 21% of the time, whereas indoor CO concentrations were in a safe range (<7 ppm) between 46% and 79% of the time and exceeded 50 ppm between 4%, and 20% of the time. Overall correlations between indoor PM{sub 2.5} and CO concentrations were low to moderate (Spearman ρ between 0.59 and 0.83). There was also poor agreement and evidence of proportional bias between observed indoor PM{sub 2.5} concentrations vs. those estimated based on indoor CO concentrations, with greater discordance at lower concentrations. Our analysis does not support the notion that indoor CO concentration is a surrogate marker for indoor PM{sub 2.5} concentration across all settings. Both are important markers of household air pollution with different health and environmental implications and should therefore be independently measured. - Highlights: • We summarized indoor PM2.5 and CO concentrations across three resource-poor settings. • Overall correlations between indoor PM2.5 and CO were low to moderate. • Agreement between observed indoor PM2.5 vs. those estimated based on indoor CO was poor.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Route Optimization for Energy Efficient Airport Shuttle Operations - A Case Study from Dallas Fort Worth International Airport

Air travel and requisite surface traffic supporting passenger arrival/departure constitutes a significant portion of travel and emissions in cities with large airports. An airport trip can segment into three parts namely: i) travel from a location in the city to the airport; ii) travel from a parking lot or rental car center to the terminal (i.e., within the airport premises), and iii) travel inside the terminal. Depending on the airport access mode all or a part of these legs comprise a traveler’s journey to the airport. The priority of airport ground transport management teams is to provide passengers with a seamless travel experience within the airport, so it is understandable that within airport shuttle routes might not be optimized for minimizing energy consumption. Solutions that meet the dual objective of reducing energy consumption from airport shuttle operations without compromising on passenger travel experience are key to improving system efficiency. There is currently a dearth of research and tools that can inform airports in making such decisions. Addressing this need, this research effort puts forth an optimization model that generates optimal shuttle routes for a given set of constraints, and a discrete-event simulator that evaluates the optimal solutions in a stochastic environment to understand the tradeoffs between passenger wait times, and within airport shuttle energy consumption. The proposed set of tools are tested in the context of optimizing airport shuttles routes within the Dallas Fort Worth International Airport (DFW). In addition to shuttle spatial positioning, and passenger demand information, high-fidelity vehicle data was collected using data loggers installed on DFW shuttles. Results show that 20% energy reduction in shuttle operations is possible with a modest two-minute increase in average passenger wait times. The tools developed in this research effort are designed to be generalizable and can help optimize shuttle operations planning at any major airport.

air travel↗
DOE OSTI2015

Riverbed Clogging Associated with a California Riverbank Filtration System: An Assessment of Mechanisms and Monitoring Approaches

An experimental field study was performed to investigate riverbed clogging processes and associated monitoring approaches near a dam-controlled riverbank filtration facility in Northern California. Motivated by previous studies at the site that indicated riverbed clogging plays an important role in the performance of the riverbank filtration system, we investigated the spatiotemporal variability and nature of the clogging. In particular, we investigated whether the clogging was due to abiotic or biotic mechanisms. A secondary aspect of the study was the testing of different methods to monitor riverbed clogging and related processes, such as seepage. Monitoring was conducted using both point-based approaches and spatially extensive geophysical approaches, including: grain-size analysis, temperature sensing, electrical resistivity tomography, seepage meters, microbial analysis, and cryocoring, along two transects. The point monitoring measurements suggested a substantial increase in riverbed biomass (2 orders of magnitude) after the dam was raised compared to the small increase (~2%) in fine-grained sediment. These changes were concomitant with decreased seepage. The decreased seepage eventually led to the development of an unsaturated zone beneath the riverbed, which further decreased infiltration capacity. Comparison of our time-lapse grain-size and biomass datasets suggested that biotic processes played a greater role in clogging than did abiotic processes. Cryocoring and autonomous temperature loggers were most useful for locally monitoring clogging agents, while electrical resistivity data were useful for interpreting the spatial extent of a pumping-induced unsaturated zone that developed beneath the riverbed after riverbed clogging was initiated. The improved understanding of spatiotemporally variable riverbed clogging and monitoring approaches is expected to be useful for optimizing the riverbank filtration system operations.

58 GEOSCIENCES↗
DOE OSTI2021

Comparison of fiber-optic distributed temperature sensing and high-sensitivity sensor spatial surveying of stream temperature

Measuring surface water temperature spatial variability is needed to estimate the interaction between surface water and groundwater, evaluate fish habitat and thermal inertia, and to estimate streamflow frequency and duration. Fiber optic distributed temperature sensing (FO-DTS) has been used in rivers and lakes, providing high-resolution and sensitive temperature monitoring over large temporal and spatial scales. However, in streams with cobbly or bedrock-lined streambeds and variable bathymetry, use of FO-DTS to measure temperature close to the surface water and groundwater interface can be challenging if even feasible. FO-DTS can also be costly, involve difficult installations, and require an advanced understanding of the technology, calibration, and data processing. In this study, we compared FO-DTS stream temperature survey results to an alternative temperature survey method employing a towed transect of high-resolution temperature loggers spaced at 1-m and transported in the stream along the study reach, to measure the spatial distribution of stream-water temperature in East Fork Poplar Creek near Oak Ridge, Tennessee, USA. We assessed the applicability and limitations of the two methods, and quantitatively compared in-situ temperature survey results measured simultaneously with each method. Regression results showed strong temporal and spatial correlation between the two methods. Differences were only elevated near the stream banks in areas that were coincident with correlation slope deviations from unity, which was attributed to shallower water and lower data density. Kriging standard errors were also low at channel center with minor increases near the stream banks. Furthermore, the results suggested that the array of the individual temperature sensors can provide a practical alternative to FO-DTS for thermal characterization of surface water, providing slightly lower spatial and temporal resolution, but with higher accuracy of temperature measurement, with greater simplicity, and with a broader range of conditions where it may be applied.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Range Hood Use and Effectiveness in Reducing Indoor Air Pollution During Gas and Induction Cooking

The Cooking Energy and Ventilation Impacts on Children's Asthma (CEVICA) study measured cooking frequency, range hood use, indoor air quality and respiratory health indicators of children with asthma living in homes with gas stoves in California's San Joaquin Valley. The study installed electric induction stoves and repeated measurements over three 2-week intensive periods, at baseline and at the end of two consecutive 3-month study phases. Stove replacements occurred at the start of Phase 1 or Phase 2 by random assignment. There were 4184 cooking events identified by automated analysis of time-series data from temperature sensors mounted above the cooktops and 1038 related range hood usage events detected from data recorded by anemometers, smart plugs, or motor loggers. Analysis of 1-minute resolved PM2.5 and NO 2 data identified and quantified 2685 PM 2.5 events and 2606 NO 2 events. Range hood use was characterized as a binary variable (>3 min vs. <3 min use). Range hood use was more common during cooking events associated with particle emissions and longer cooking durations. PM 2.5 concentrations during events with range hood use were comparable to those without use, which could result from limited effectiveness or if range hoods were preferentially used during higher-emission cooking scenarios. In homes with gas cooking, integrated NO 2 concentrations were about 45 percent higher during cooking events with no range hood use compared to those range hood use. The lowest pollutant levels were observed when the range hood operated for more than half of the cooking duration. These findings show that operation of venting range hood during cooking can substantially reduce short-term indoor exposure NO 2 in homes with gas cooking.

Fang, Yi↗