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NASA NTRS2018

Bayesian Geostatistical Modelling of PM10 and PM2.5 Surface Level Concentrations in Europe Using High-Resolution Satellite-Derived Products

Air quality monitoring across Europe is mainly based on in situ ground stations which are too sparse to accurately assess the exposure effects of air pollution for the entire continent. The demand for precise predictive modelsthat estimate gridded geophysical parameters of ambient air at high spatial resolution has rapidly grown. Here, we investigate the potential of satellite derived products to improve particulate matter (PM) estimates. Bayesiangeostatistical models addressing confounding between the spatial distribution of pollutants and remotely sensed predictors were developed to estimate yearly averages of both, fine (PM2.5) and coarse (PM10) surface PM concentrations at 1 sq.km spatial resolution over 46 European countries and were compared to geostatistical, geographically weighted and land-use regression formulations. Rigorous model selection identified the Earth observation data which contribute most to pollutants' estimation. Geostatistical models outperformed the predictive ability of the frequently employed land-use regression. The resulting estimates of PM10 and PM2.5, which represent the main air quality indicators for the urban Sustainable Development Goal, indicate that in 2016, 66.2% of the European population was breathing air above the WHO Air Quality Guidelines thresholds. Our estimates are readily available to policy makers and scientists assessing the effects of long-term exposure to pollution on human and ecosystem health.

Beloconi, Anton↗

NASA NTRS2021

Southeast Michigan Health & Air Quality: Identifying Trends of Ground-level Ozone Precursors in Southeast Michigan and Northern Ohio

Pollutants resulting from industrial activity can react with sunlight to create ground-level ozone, a harmful pollutant that can exacerbate respiratory health issues such as asthma. Due to a history of heavy industrialization, residents of southeast Michigan and northern Ohio are especially susceptible to ground-level ozone. NASA DEVELOP, in partnership with the Michigan Department of Environment, Great Lakes, and Energy’s (EGLE) Air Quality Division and the Lake Michigan Air Directors Consortium (LADCO), investigated the effectiveness of Earth observations (EO) in monitoring pollutants that contribute to ground-level ozone. The team used the European Space Agency’s TROPOspheric Monitoring Instrument (TROPOMI) aboard Sentinel-5P, and NASA’s Ozone Monitoring Instrument (OMI) aboard Aura, to measure nitrogen dioxide (NO2), formaldehyde (HCHO), and methane (CH4) from 2019 to 2021 (May-September). The team oversampled the EO data on monthly, yearly, and 3-year time scales where possible to enhance more localized pollutant trends. Specifically, TROPOMI effectively monitored NO2 from space, indicating sub-city distributions on a monthly timescale. Contrastingly, the measurements of HCHO were predominately noisy, and therefore failed to show any distribution trends. Lastly, CH4 trends were identifiable yet coarse, hinting that EO monitoring in the case of CH4 is not beneficial for our partners. The end products provide the partners with insight on the utility of EO in measuring certain ozone precursors and can be used to guide ground-level ozone reduction strategies throughout the region.

Mariam Moeen↗

NASA NTRSDate not supplied

Application of Advanced Earth Observations and Model Simulations to Improve Air Quality Monitoring in the Hindu-Kush-Himalayan Region

Air pollution is a serious environmental health concern in the Hindu Kush Himalayan (HKH) region of south-central Asia, as rapid industrialization and population growth have led to increased anthropogenic emissions from transportation, residential, industrial, energy, and biomass burning sources. Natural emissions from dust and forest fires are additional sources of air pollutants that can exacerbate air quality in the region. The combination of the complex pollutant mixtures and atmospherically stable weather conditions during the winter monsoon can visibility reductions and hazardous air quality from persistent haze episodes. The Kathmandu Valley is especially vulnerable to extreme haze issues due to the surrounding mountains that restrict air movement and retains pollutants in the atmosphere. This study uses state-of-the-art satellite observations and modeling capabilities in conjunction with ground-based networks to provide a comprehensive data toolkit for advancing air quality monitoring and forecasting decisions in the HKH region. The toolkit includes new generation satellite observations from the TROPOspheric Monitoring Instrument (TROPOMI), Geostationary Environment Monitoring Spectrometer (GEMS), and Advanced Meteorological Imager, which provide high spatiotemporal information on NO2, HCHO, SO2, O3, and aerosol optical depth (AOD). Particulate matter with diameters less than 2.5 micrometers (PM2.5) are derived from the satellite-retrieved AOD using ground-based observations and forecast model data. The satellite observations are also used to initialize and constrain forecast model systems designed for the HKH region. This talk will highlight the performance of the air quality toolkit for enhancing decision-making processes during exceptional air quality events in the region. Note: Presentation includes additional attachment of full presentation with sound and animation (best when viewed as slide show) with runtime of 15 min 32 secs

Aaron Naeger↗

NASA NTRS2022

Climate Change Penalty and Benefit on Surface Ozone: A Global Perspective Based on CMIP6 Earth System Models

This work presents an analysis of the effect of climate change on surface ozone discussing the related penalties and benefits around the globe from the global modelling perspective based on simulations with five CMIP6 (Coupled Model Intercomparison Project Phase 6) Earth System Models. As part of AerChemMIP (Aerosol Chemistry Model Intercomparison Project) all models conducted simulation experiments considering future climate (ssp370SST) and present-day climate (ssp370pdSST) under the same future emissions trajectory (SSP3-7.0). A multi-model global average climate change benefit on surface ozone of −0.96 ± 0.07 ppbv °C−1 is calculated which is mainly linked to the dominating role of enhanced ozone destruction with higher water vapour abundances under a warmer climate. Over regions remote from pollution sources, there is a robust decline in mean surface ozone concentration on an annual basis as well as for boreal winter and summer varying spatially from −0.2 to −2 ppbv °C−1, with strongest decline over tropical oceanic regions. The implication is that over regions remote from pollution sources (except over the Arctic) there is a consistent climate change benefit for baseline ozone due to global warming. However, ozone increases over regions close to anthropogenic pollution sources or close to enhanced natural biogenic volatile organic compounds emission sources with a rate ranging regionally from 0.2 to 2 ppbv C−1, implying a regional surface ozone penalty due to global warming. Overall, the future climate change enhances the efficiency of precursor emissions to generate surface ozone in polluted regions and thus the magnitude of this effect depends on the regional emission changes considered in this study within the SSP3_7.0 scenario. The comparison of the climate change impact effect on surface ozone versus the combined effect of climate and emission changes indicates the dominant role of precursor emission changes in projecting surface ozone concentrations under future climate change scenarios.

surface ozone↗

NASA NTRS2021

Satellite Monitoring for Air Quality and Health

Data from satellite instruments provide estimates of gas and particle levels relevant to human health, even pollutants invisible to the human eye. However, the successful interpretation of satellite data requires an understanding of how satellites relate to other data sources, as well as factors affecting their application to health challenges. Drawing from the expertise and experience of the 2016–2020 NASA HAQAST (Health and Air Quality Applied Sciences Team), we present a review of satellite data for air quality and health applications. We include a discussion of satellite data for epidemiological studies and health impact assessments, as well as the use of satellite data to evaluate air quality trends, support air quality regulation, characterize smoke from wildfires, and quantify emission sources. The primary advantage of satellite data compared to in situ measurements, e.g., from air quality monitoring stations, is their spatial coverage. Satellite data can reveal where pollution levels are highest around the world, how levels have changed over daily to decadal periods, and where pollutants are transported from urban to global scales. To date, air quality and health applications have primarily utilized satellite observations and satellite-derived products relevant to near-surface particulate matter <2.5 μm in diameter (PM(sub 2.5)) and nitrogen dioxide (NO2). Health and air quality communities have grown increasingly engaged in the use of satellite data, and this trend is expected to continue. From health researchers to air quality managers, and from global applications to community impacts, satellite data are transforming the way air pollution exposure is evaluated.

Satellites↗

NASA NTRS2022

Spacecraft Maximum Allowable Concentrations for Airborne Contaminants: Revision B

The enclosed table lists official Spacecraft Maximum Allowable Concentrations (SMACs) for selected airborne contaminants. They are based upon experiments conducted at standard pressure and oxygen environments and may or may not be applicable to altered atmospheres. These are guideline values set by the National Aeronautics and Space Administration (NASA)/Johnson Space Center (JSC) Toxicology Group in cooperation with the National Research Council Committee on Toxicology (NRCCOT) or through publication in the peer-reviewed scientific literature. Based on documented guidance (NRC, 1992; NRC, 2016), NASA has established SMACs for 60 chemical compounds that are particularly relevant to atmospheric contamination of the International Space Station (ISS) and targets of Exploration. Some long‐term limits (1000‐days) have also been established to support manned deep‐space exploration. Summaries of these SMACs are presented in tabular form as part of this publication. Short-term (1- and 24-hour) SMACs apply to off nominal situations, such as accidental releases aboard a spacecraft. These limits permit risk of minor, reversible effects, such as mild mucosal irritation. In contrast, the long term SMACs are set to fully protect healthy crewmembers from adverse effects resulting from continuous exposure to specific air pollutants for up to 1000 days. Because allergic reactions or chemical idiosyncrasy to certain airborne pollutants are very difficult to predict, crewmembers with allergies or unusual sensitivity to trace pollutants may not be afforded complete protection, even when long-term SMACs are not exceeded. Conversely, exceedance of a SMAC does not mean that health impairment is certain (there are many other factors that influence ultimate health outcomes), although it does indicate that the crew may be subject to increased risks that must be closely evaluated. Environmental pollutant control to mitigate exposure will likely be triggered.

SMACs↗

NASA NTRSDate not supplied

ASDC Distribution and Services of TEMPO Data

The Tropospheric Emissions: Monitoring of POllution (TEMPO) instrument represents a groundbreaking advancement in remote sensing technology, providing real-time and high-resolution measurements of atmospheric pollutants and air quality monitoring. This presentation will highlight the significance of TEMPO and its data distribution by NASA’s Atmospheric Science Data Center (ASDC) to facilitate the analyses by the research and end user communities. TEMPO's geostationary orbit allows for continuous and high-resolution measurements of key atmospheric pollutants, including nitrogen dioxide (NO 2 ), ozone (O 3 ), and formaldehyde (HCHO). As a result, researchers can investigate the distribution patterns of these pollutants on an hourly basis, providing valuable information for understanding regional and temporal variations in air quality. Furthermore, this presentation will highlight the usability of TEMPO data in complementing ground-based air quality monitoring networks. ASDC distribution services and tools facilitate efficient data handling and analysis to support research and application uses of TEMPO data. As part of NASA’s Earthdata ecosystem, TEMPO will be available through Earthdata Search and Worldview, as well as have variable and spatial subsetting capabilities. This presentation will provide an overview of data access and services available for TEMPO data.

Hazem Mahmoud↗

NASA NTRSDate not supplied

Satellite-Assisted Particulate Matter (SAPM) for the Models, In situ, and Remote Sensing of Aerosols (MIRA) Working Group

Models, In situ, and Remote sensing of Aerosols (MIRA) is an international working group that provides a forum for collaborations amongst these three atmospheric aerosol communities. MIRA consists of a collection of interdisciplinary and independently funded Topic/Project groups with clear goals and generally characterized by requests for additional scientific data. The Satellite-Assisted Particulate Matter (SAPM) Topic group focuses on the study of fine particulate matter (PM2.5), as it is a major contributor to air pollution and negatively impacts human health. Our group aims to provide intercomparisons of various methods and techniques for estimating surface PM2.5 assisted by satellite remote sensors (passive and active), global aerosol models, and in situ aerosol measurements. The overall motivation of our work is to enhance PM2.5 coverage beyond in situ ground stations, which can be limited. In this presentation, we provide an overview of various PM2.5 estimation approaches by current SAPM team members, as each approach has its own strengths and limitations. One approach uses near-surface aerosol extinction retrievals from the spaceborne Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) and an assumed value of mass extinction efficiency to derive PM2.5 concentrations (Toth et al 2019). A study using this method found a promising agreement (R=0.60; slope=0.89) with U.S. Environmental Protection Agency (EPA) in situ PM2.5 measurements over the contiguous United States (CONUS) for a 12-year (2007-2018) period (Toth et al 2022). In a different approach combining spaceborne lidar and a model, the Cloud Aerosol Transport System (CATS) lidar and Goddard Earth Observing System (GEOS) model are blended in an ensemble variational assimilation scheme to retrieve aerosol extinction and convert speciated mass concentrations to total PM2.5. A recent study (Matus et al in prep.) found agreement within 2 μg/m3 over the CONUS on the 2016 annual mean when compared to EPA ground-based measurements. Another study explored trends in city aerosol optical depth (AOD) from a spaceborne passive remote sensor, Moderate Resolution Imaging Spectroradiometer (MODIS), and found that these trends agree well with trends in city surface PM2.5, which provides confidence in the use of city AOD for city PM2.5 trend studies (Vohra et al 2021). In a follow-on study, steep and significant trends (~2.5 to 7.8% a-1) in AOD are found for several South Asian cities (e.g., Bangalore and Hyderabad), suggesting rapid growth in PM2.5 (Vohra et al 2022). Also in this presentation, we report results on our current collective SAPM study of India, a country that exhibits high levels of PM2.5 pollution. We show the temporal (i.e., seasonal) and spatial variability of PM2.5 over India using the CALIOP and CATS+model approaches, comparisons between the estimated PM2.5 from the retrieval schemes, and validation with in situ PM2.5 ground-based observations from the Central Pollution Control Board in India. This region provides us with an excellent case study to test our PM2.5 retrievals in heavily polluted scenes and over a complex and varying topography. The SAPM Topic group actively seeks international participants/collaborators in our group, including those working with in situ aerosol measurements (e.g., ACTRIS). We are interested in aerosol datasets in order to either improve our PM2.5 estimates from various approaches (e.g., using in situ mass scattering/absorption coefficient and aerosol hygroscopic properties for various aerosol species) and/or validate the PM2.5 estimates (e.g., using in situ ground-based PM2.5 concentrations).

Travis D Toth↗

DOE OSTI2020

DIGITAL APPLICATIONS USING REAL-TIME VEHICLE EXHAUST INFORMATION

Vehicle emission is a major source of air pollution that causes a significant number of deaths globally. It has a profound impact on energy and the environment as well. The existing vehicle emission monitoring system is unable to help mitigating the pollution properly and therefore, requires precise real-time pollution measurement. The purpose of this paper is to discuss novel applications using the real-time measurement of pollutants from a vehicle tailpipe where exhaust gases enter the environment. Today, it is possible to measure such emission due to the emergence of affordable digital technologies such as the Internet of Things (IoT), wireless connectivity, cloud platform, and artificial intelligence. This paper discusses how digital technologies can be used for real-time monitoring of NOx gas as a measure of vehicle emission and predictive analytics applications. A description of data collection and pre-processing methodologies, actual collected data, and an approach to identify patterns between inputs such as vehicle speed and altitude and output such as NOx emission are included. Applying a simple neural network has produced promising results and is a first step towards developing predictive applications.

Digital, Vehicle Exhaust, IoT, AI, 1.4.2, Predicti↗

DOE OSTI2021

Idaho National Laboratory Annual Report for Permit to Construct P-2015.0023 for Calendar Year 2020

The U.S. Department of Energy (DOE) Idaho National Laboratory (INL) Site operates facilities with potential emissions criteria and hazardous air pollutants. This report documents the calendar year 2020 criteria and hazardous air pollutants emissions and has been prepared to comply with permit to construct (PTC) P-2015-0023, Condition 2.9 and Idaho Administrative Procedures Act (IDAPA) 58.01.01.178, Standard Contents of Permits Establishing a Facility Emissions Cap (FEC). IDAPA 58.01.01.178.04 requires that all permits establishing a FEC shall include sufficient reporting to assure compliance with the permit establishing the FEC. Total hazardous air pollutant (HAP) emissions for the year were 0.59 tons in aggregate and the maximum individual HAP was hydrochloric acid at 0.35 tons. Criteria pollutant emissions were 1.23 tons for sulfur dioxide, 40.96 tons for oxides of nitrogen, 11.7 tons of carbon monoxide, 3.01 tons of total particulate matter and 1.98 tons of volatile organic compounds (VOC).

99 GENERAL AND MISCELLANEOUS↗

DOE OSTI2022

Annual FEC-PTC Report - CDRL F.70

The U.S. Department of Energy (DOE) Idaho National Laboratory (INL) Site operates facilities with potential emissions of criteria and hazardous air pollutants. This report documents the calendar year 2021 criteria and hazardous air pollutants emissions and has been prepared to comply with permit to construct (PTC) P-2015.0023 for the period of 1-1-2021 up to the effective date of PTC P 2020.0045 (1-29-2021), and PTC P-2020.0045 for the period from 1-29-2021 through 12-31-2021. The Idaho Administrative Procedures Act (IDAPA) 58.01.01.178, Standard Contents of Permits Establishing a Facility Emissions Cap (FEC) requires that all permits establishing a FEC shall include sufficient reporting to assure compliance with the permit establishing the FEC. Total hazardous air pollutant (HAP) emissions for the year were 0.10 tons in aggregate and the maximum individual HAP was toluene at 0.04 tons. Criteria pollutant emissions were 0.75 tons for sulfur dioxide, 24.33 tons for oxides of nitrogen, 6.07 tons of carbon monoxide, 2.53 tons of total particulate matter and 0.99 tons of volatile organic compounds (VOC).

99 GENERAL AND MISCELLANEOUS↗

DOE OSTI2018

Decoupling relationship between economic output and carbon emission in the Chinese construction industry

By positioning in the discourse that economic output is always coupled with natural resource depletion, pollution, and carbon emission, decoupling analysis is widely adopted to evaluate how “quality” economic growth can lead to fewer such downsides so as to encourage sustainable development. This paper aims at examining the decoupling relationship between economic output and carbon emission by focusing on China's construction industry, which is a pillar industry for national economic growth, meanwhile contributes a huge amount of carbon emission. The method of Tapio decoupling model is used to examine the decoupling relationships at both national and provincial levels from 2005 to 2015. It continues to identify the driving force leading to a certain decoupling state by adopting the logarithmic mean Divisia index (LMDI). Results show that: (1) there existed an expansive decoupling relationship between economic growth and construction carbon emission in most provinces of China during 2005–2015; (2) Shanghai presented the best decoupling performance, while in contrast, other provinces such as Guizhou and Fujian displayed expansive negative decoupling state; and (3) “Economic output” played the most significant role in inhibiting the decoupling at both national and provincial levels, while “Indirect carbon intensity” was the main driver for promoting the national decoupling. Although the paper refers to the specific construction of China, the decoupling analysis approach can be extended to other countries as well as to other pollutants such as land pollution, waste water and haze. The understanding of driving forces for the decoupling state in China's construction industry provides international policy-makers with valuable reference for formulating effective measures to balance the dilemma between economic output and carbon emission.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2015

Effect of prolonged exposure to sublethal concentrations of DDT and DDE on protein expression in human pancreatic beta cells

Pollution of the environment represents one of less explored potential reasons for the worldwide epidemic of type 2 diabetes. One of the most prevalent organochlorine pollutants remains the pesticide DDT and its degradation product DDE. Despite some epidemiologic correlations between levels of DDT and DDE in human organism and the prevalence of diabetes, there is almost no information about the exact targets of these compounds inside pancreatic beta cells. To detect functional areas of pancreatic beta cells that could be affected by exposure to DDT and DDE, we analyzed changes in protein expression in the NES2Y human pancreatic beta cell line exposed to three sublethal concentrations (0.1 μM, 1 μM, 10 μM) of DDT and DDE for 1 month. Protein separation and identification was achieved using high-resolution 2D-electrophoresis, computer analysis and mass spectrometry. With these techniques, four proteins were found downregulated after exposure to 10 μM DDT: three cytoskeletal proteins (cytokeratin 8, cytokeratin 18 and actin) and one protein involved in glycolysis (alpha-enolase). Two proteins were downregulated after exposure to 10 μM DDE: cytokeratin 18 and heterogenous nuclear ribonucleoprotein H1 (HNRH1). These changes correlate with previously described effects of other stress conditions (e.g. exposure to palmitate, hyperglycemia, imidazoline derivative, and cytokines) on protein expression in pancreatic beta cells. We conclude that cytoskeletal proteins and their processing, glucose metabolism, and mRNA processing may represent targets affected by exposure to conditions hostile to pancreatic beta cells, including exposure to DDT and DDE. - Highlights: • Epidemiologic studies connect pollution with incidence of diabetes mellitus. • We explored the effect of DDT and DDE on protein expression in the NES2Y pancreatic beta cell line. • One month exposure to three sublethal concentrations of DDT and DDE was employed. • Expression of alpha-enolase, actin, cytokeratin 8 and 18 was reduced in NES2Y/DDT. • Expression of HNRH1 and cytokeratin 18 was reduced in NES2Y/DDE.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2017

Recent aspects of uranium toxicology in medical geology

Uranium (U) is a chemo-toxic, radiotoxic and even a carcinogenic element. Due to its radioactivity, the effects of U on humans health have been extensively investigated. Prolonged U exposure may cause kidney disease and cancer. The geological distribution of U radionuclides is still a great concern for human health. Uranium in groundwater, frequently used as drinking water, and general environmental pollution with U raise concerns about the potential public health problem in several areas of Asia. The particular paleo-geological hallmark of India and other Southern Asiatic regions enhances the risk of U pollution in rural and urban communities. This paper highlights different health and environmental aspects of U as well as uptake and intake. It discusses levels of U in soil and water and the related health issues. Also described are different issues of U pollution, such as U and fertilizers, occupational exposure in miners, use and hazards of U in weapons (depleted U), U and plutonium as catalysts in the reaction between DNA and H{sub 2}O{sub 2,} and recycling of U from groundwater to surface soils in irrigation. For use in medical geology and U research, large databases and data warehouses are currently available in Europe and the United States. - Highlights: • Uranium (U) is a chemo-toxic, radiotoxic and even a carcinogenic element. • Effects of U on humans health have been extensively studied in recent years. • Prolonged U exposure may cause kidney disease and cancer. • Drinking water is a source of U exposure in some parts of the world.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2018

Cause-specific stillbirth and exposure to chemical constituents and sources of fine particulate matter

Highlights: • Explored associations between cause-specific stillbirth and PM{sub 2.5} sources. • Gestational age-adjusted exposure was estimated in nested case-control study design. • Different causes of stillbirth were associated with different pollutants. • Highlighted the importance of investigating cause-specific stillbirth. The stillbirth rate in the United States is relatively high, but limited evidence is available linking stillbirth with fine particulate matter (PM{sub 2.5}), its chemical constituents and sources. In this study, we explored associations between cause-specific stillbirth and prenatal exposures to those pollutants with using live birth and stillbirth records from eight California locations during 2002–2009. ICD-10 codes were used to identify cause of stillbirth from stillbirth records. PM{sub 2.5} total mass and chemical constituents were collected from ambient monitors and PM{sub 2.5} sources were quantified using Positive Matrix Factorization. Conditional logistic regression was applied using a nested case-control study design (N = 32,262). We found that different causes of stillbirth were associated with different PM{sub 2.5} sources and/or chemical constituents. For stillbirths due to fetal growth, the odds ratio (OR) per interquartile range increase in gestational age-adjusted exposure to PM{sub 2.5} total mass was 1.23 (95% confidence interval (CI): 1.06, 1.44). Similar associations were found with resuspended soil (OR=1.25, 95% CI: 1.10, 1.42), and secondary ammonium sulfate (OR=1.45, 95% CI: 1.18, 1.78). No associations were found between any pollutants and stillbirths caused by maternal complications. This study highlighted the importance of investigating cause-specific stillbirth and the differential toxicity levels of specific PM{sub 2.5} sources and chemical constituents.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2018

Localized real-time information on outdoor air quality at kindergartens in Oslo, Norway using low-cost sensor nodes

Highlights: • We show that low-cost sensors can provide an indication of outdoor air quality. • We employed a data fusion method to provide real-time air quality maps. • Localized real-time air quality information can help parents and kindergarten staff. In Norway, children in kindergartens spend significant time outdoors under all weather conditions, and there is thus a natural concern about the quality of outdoor air. It is well known that air pollution is associated with a wide variety of adverse health impacts for children, with greater impact on children with asthma. Especially during winter and spring, kindergartens in Oslo that are situated close to streets with busy traffic, or in areas where wood burning is used for house heating, can experience many days with bad air quality. During these periods, updated information on air quality levels can help the kindergarten teachers to plan appropriate outdoor activities and thus protect children's health. We have installed 17 low-cost air quality nodes in kindergartens in Oslo. These nodes are smaller, cheaper and less complex to use than traditional equipment. Performance evaluation shows that while they are less accurate and suffer from higher uncertainty than reference equipment, they still can provide reliable coarse information about local pollution. The main challenge when using this technology is that calibration parameters might change with time depending on the atmospheric conditions. Thus, even if the sensors are calibrated a priori, once deployed, and especially if they are deployed for a long time, it is not possible to determine if a node is over- or under-estimating the concentration levels. To enhance the data from the sensors, we employed a data fusion technique that allows generating a detailed air quality map merging the data from the sensors and the data from an urban model, thus being able to offer air quality information to any location within Oslo. We arranged a focus group with the participation of local administration, kindergarten staff and parents to understand their opinion and needs related to the air quality information that was provided to the participant kindergartens. They expressed concern about the data quality but agree that having updated information on the air quality in the surroundings of kindergartens can help them to reduce children's exposure to air pollution.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2018

Isolation and characterization of a respirable particle fraction from residential house-dust

Highlights: • House dust is an important environmental matrix to monitor. • A method for the isolation of dust particles in the respirable size range was developed. • The study presents a comprehensive characterization of house dust in the respirable size range. • This method may be a valuable for risk assessment following an inhalation exposure to house dust. Indoor air pollution has caused increasing concern in recent years. As we spend most of our lives indoors, it is crucial to understand the health effects caused by indoor air pollution. Household dust serve as good proxy for accessing indoor air pollution, especially smaller dust particles that can pass into the lungs are of interest. In this study we present an efficient method for the isolation of dust particles in the respirable size range. The respirable fraction was recovered from vacuum cleaner bags, separated by stepwise sieving, followed by characterization for size, morphology, surface area, organic content and elemental composition. The respirable fraction was obtained in a yield of 0.6% with a specific surface area of 2.5 m{sup 2}/g and a Mass Median Aerodynamic Diameter of 3.73 ± 0.15 µm. Aluminum and zink were the dominating metals measured in the dust, whereas the major mineral components were found to be silicon dioxide and calcium carbonate. The fraction of organic matter in the dust was measured to be 69 ± 1%. The organic matrix contained bacterial and fungi and a presence of skin fragments. We present here an efficient and fast method for the isolation of dust particles in the respirable size range. That is of considerable value due to the need for large quantities of respirable particle fractions to conduct toxicological studies and risk assessment work.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2017

Facile fabrication of micro-floriated AgBr/Bi{sub 2}O{sub 3} as highly efficient visible-light photocatalyst

Highlights: • We successfully fabricate micro-floriated AgBr/Bi{sub 2}O{sub 3} composites by one simple hydrothermal react with precusor BiOBr. This micro-floriated Bi{sub 2}O{sub 3} heterojunction composite is rarely reported by others. • Heterojunction AgBr/Bi{sub 2}O{sub 3} composite exhibits highly efficient photocatalytic activity to decompose pollutant. • The enhanced photocatalytic activity was attributed to the improved visible light harvesting ability and higher separation efficiency of photogenerated electron–hole pairs by the introduction of AgBr. • This composite is beneficial to industrial applications to eliminate the organic pollutants from waste water. - Abstract: Semiconductor with photocatalytic property is the potential solution to solve the problem about water pollution. Novel floriated AgBr/Bi{sub 2}O{sub 3} fabricated through a facile simple two-step hydrothermal method is an efficient photocatalyst. The eminent performance for degradation of methyl orange (MO) was evaluated under visible light irradiation. Many characterization methods, including XPS, XRD, FT-IR, SEM, TEM and UV–vis diffuse reflection spectroscopy, were used to investigate the structure, elemental composition, morphology and catalytic activity. Broad contact between AgBr and Bi{sub 2}O{sub 3} interface enabled hybrid materials possess superior efficiency for the decomposition of MO under visible light irradiation. The optimum photocatalytic activity of samples was approximately 11.7 times higher than pure Bi{sub 2}O{sub 3}. In addition, the photo-generated reactive species were identified based on free radicals trapping experiments, which revealed that superoxide radical is the key factor to the photocatalytic process.

36 MATERIALS SCIENCE↗