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Indoor air quality in new and renovated low-income apartments with mechanical ventilation and natural gas cooking in California

This work presents pollutant concentrations and performance data for code-required mechanical ventilation equipment in 23 low-income apartments at 4 properties constructed or renovated 2013-2017. All apartments had natural gas cooking burners. Occupants pledged to not use windows for ventilation during the study but several did. Measured airflows of range hoods and bathroom exhaust fans were lower than product specifications. Only eight apartments operationally met all ventilation code requirements. Pollutants measured over one week in each apartment included time-resolved fine particulate matter (PM 2.5 ), nitrogen dioxide (NO 2 ), formaldehyde and carbon dioxide (CO 2 ) and time-integrated formaldehyde, NO 2 and nitrogen oxides (NO X ). Compared to a recent study of California houses with code-compliant ventilation, apartments were smaller, had fewer occupants, higher densities, and higher mechanical ventilation rates. Mean PM 2.5 , formaldehyde, NO 2 , and CO 2 were 7.7 µg/m 3 , 14.1 ppb, 18.8 ppb, and 741 ppm in apartments; these are 4% lower, 25% lower, 165% higher, and 18% higher compared to houses with similar cooking frequency. Four apartments had weekly PM 2.5 above the California annual outdoor standard of 12 µg/m 3 and also discrete days above the World Health Organization 24-h guideline of 25 µg/m 3 . Two apartments had weekly NO 2 above the California annual outdoor standard of 30 ppb.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Indoor air quality in California homes with code-required mechanical ventilation

Data were collected in 70 detached houses built in 2011-2017 in compliance with the mechanical ventilation requirements of California's building energy efficiency standards. Each home was monitored for a 1-week period with windows closed and the central mechanical ventilation system operating. Pollutant measurements included time-resolved fine particulate matter (PM 2.5 ) indoors and outdoors and formaldehyde and carbon dioxide (CO 2 ) indoors. Time-integrated measurements were made for formaldehyde, NO 2 , and nitrogen oxides (NO X ) indoors and outdoors. Operation of the cooktop, range hood, and other exhaust fans was continuously recorded during the monitoring period. Onetime diagnostic measurements included mechanical airflows and envelope and duct system air leakage. All homes met or were very close to meeting the ventilation requirements. On average, the dwelling unit ventilation fan moved 50% more airflow than the minimum requirement. Pollutant concentrations were similar to or lower than those reported in a 2006-2007 study of California new homes built in 2002-2005. Mean and median indoor concentrations were lower by 44% and 38% for formaldehyde and 44% and 54% for PM 2.5 . Ventilation fans were operating in only 26% of homes when first visited, and the control switches in many homes did not have informative labels as required by building standards.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Assessment of the Impact of Discontinuity in Satellite Instruments and Retrievals on Global PM2.5

Exposure to fine particulate matter (PM2.5) is the leading environmental risk factor for mortality globally. Satellite-derived estimates of surface PM2.5 developed from a combination of satellites, simulations, and ground monitor data are relied upon for health impact studies. The ability to develop satellite-derived PM2.5 estimates requires the continued availability of aerosol optical depth (AOD) sources. This work examines the impact of the addition or loss of satellite AOD data sources on global PM2.5 estimation and the impact of continuing the longterm record with AOD from the Visible Infrared Imaging Radiometer Suite (VIIRS) on the Suomi-National Polar orbiting Partnership (S-NPP) satellite after the loss of the MODIS (MODerate resolution Imaging Spectroradiometer) and MISR (Multi-angle Imaging Spectroradiometer) instruments on board the Terra and Aqua satellites. We find that the addition of VIIRS S-NPP AOD products to geophysical PM2.5 estimates from satellites and simulations causes regional differences that correspond to differences in the VIIRS and MODIS Deep Blue AOD algorithms and sampling. Changes in long-term trends and timeseries due to the addition or loss of AOD data sources are generally within their uncertainties. Statistical fusion with ground monitor data partially corrects for changes due to sampling differences when introducing the VIIRS AOD products, but uncertainty remains over desert regions where ground monitor coverage is sparse. This work provides promise for the sustained development of global satellite-derived PM2.5 estimates, despite discontinuities in instruments and retrieval methods.

Remote sensing↗

Evaluation of CMIP6 Model Simulations of PM 2.5 and its Components Over China

Earth system models (ESMs) participating in the latest Coupled Model Intercomparison Project Phase 6 (CMIP6) simulate various components of fine particulate matter (PM 2.5 ) as major climate forcers. Yet the model performance for PM 2.5 components remains little evaluated due in part to a lack of observational data. Here, we evaluate near-surface concentrations of PM 2.5 and its five main components over China as simulated by 14 CMIP6 models, including organic carbon (OC; available in 14 models), black carbon (BC; 14 models), sulfate (14 models), nitrate (4 models), and ammonium (5 models). For this purpose, we collect observational data between 2000 and 2014 from a satellite-based dataset for total PM2.5 and from 2469 measurement records in the literature for PM 2.5 components. Seven models output total PM 2.5 concentrations, and they all underestimate the observed total PM 2.5 over eastern China, with GFDL-ESM4 (−1.5 %) and MPI-ESM-1-2-HAM (−1.1 %) exhibiting the smallest biases averaged over the whole country. The other seven models, for which we recalculate total PM 2.5 from the available component output, underestimate the total PM 2.5 concentrations partly because of the missing model representations of nitrate and ammonium. Concentrations of the five individual components are underestimated in almost all models, except that sulfate is overestimated in MPI-ESM-1-2-HAM by 12.6 % and in MRI-ESM2-0 by 24.5 %. The underestimation is the largest for OC (by −71.2 % to −37.8 % across the 14 models) and the smallest for BC (−47.9 % to −12.1 %). The multi-model mean (MMM) reproduces the observed spatial pattern for OC (R = 0.51), sulfate (R = 0.57), nitrate (R = 0.70) and ammonium (R = 0.74) fairly well, yet the agreement is poorer for BC (R = 0.39). The varying performances of ESMs on total PM 2.5 and its components have important implications for the modeled magnitude and spatial pattern of aerosol radiative forcing.

CMIP6↗

Independent and interactive effects of wet bulb globe temperature and air pollution exposures on suicide mortality

Background: Individual components of the ambient environment, such as temperature and air pollution, exist as part of a complex mixture and have been associated with suicide; however, their interactive effects remain poorly understood. This study examined the independent and interactive effects of wet bulb globe temperature (WBGT), nitrogen dioxide (NO 2 ), and fine particulate matter (PM 2.5 ) on suicide mortality. Methods: We identified 7,551 suicide cases in Utah, USA, from 2000 to 2016 and assigned exposure to daily maximum WBGT (sourced from the European Center for Medium-Range Weather Forecasts) and PM 2.5 and NO 2 concentrations (sourced from a national spatiotemporal ensemble model) using decedent’s residential address at the time of death. A case-crossover design with conditional logistic regression was used to estimate the independent and interactive effects of WBGT max , PM 2.5 , and NO 2 on suicide. For exposure windows, we considered single days preceding suicide (lag 0 to 6) and their averages across preceding days (lag 0–1, 0–3, and 0–6). Analyses were stratified by season. Results: We identified a significant association between WBGT max and suicide across all seasons (odds ratio [OR] = 1.05, 95% confidence interval [CI]: 1.01, 1.10; per 5 °C increase on lag 0–3 days). The associations were stronger in the warm season (March 22 to September 21), with ORs and 95% CIs ranging from 1.08 (1.02, 1.15) to 1.20 (1.10, 1.30) per 5 °C increase depending on the lag periods. We observed synergistic interactions between WBGT max and PM 2.5 and NO 2 in the warm season, associated with higher odds of suicide. The associations of WBGT max with suicide were most pronounced at high NO 2 levels. Conclusions: We found evidence of synergistic interactions between WBGT max and PM 2.5 and NO 2 on suicide in the warm season, emphasizing the need for considering the combined effects of heat stress and air pollution in suicide prevention strategies.

Fine particulate matter↗

A14H-04 Analysis of Simulated and Observed Trends in Global Surface PM2.5 and Aerosol Optical Properties from 1958 to 2018 Using the NASA GEOSCCM

Modeling of long-term trends of aerosols and their properties is important for constraining aerosol-climate forcing, and for characterizing changes in particulate matter pollution speciation and exposure. Here we study global and regional long-term trends in surface fine particulate matter (PM ) and aerosol optical properties for 60 years from 1958 to 2018, using simulations performed with the NASA Goddard Earth Observing System Chemistry Climate Model (GEOSCCM), and evaluate the model hindcast with observations for the last three decades. Comparing the modeled aerosols with a diverse set of observations helps interpret observed and simulated trends, and serves as a benchmark for future GEOSCCM developments and input datasets improvements. We first characterize modeled global and regional temporal changes in surface PM and its components, aerosol optical depth (AOD) and single scattering albedo (SSA) and we interpret their link with emissions drivers. We then compare modeled surface PM with ground-based observations from monitoring networks and with global reconstructed PM datasets from observations-model data fusion. Total AOD is compared with long-term satellite measurements from the Moderate Resolution Imaging Spectroradiometer (MODIS) and measurements from the ground-based Aerosol Robotic Network (AERONET). Additional aerosol optical properties, such as absorption and scattering coefficients, are evaluated with ground-based observations from the Global Atmosphere Watch (GAW) records.

aerosols↗

Physical and Optical Characteristics of the October 2010 Haze Event Over Singapore: A Photometric and Lidar Analysis

Trans-boundary biomass burning smoke episodes have increased dramatically during the past 20-30 years and have become an annual phenomenon in the South‐East‐Asia region. On 15th October 2010, elevated levels of fire activity were detected by remote sensing satellites (e.g. MODIS). On the same date, measurements of fine particulate matter (PM2.5) at Singapore and Malaysia found high levels of fine mode particles in the local environment. All these observations were indicative of the initial onset of a smoke episode that lasted for several days. In this work, we investigate the temporal evolution of this smoke episode by analyzing the physical and optical properties of smoke particles with the aid of an AERONET Sun photometer, an MPLNet micropulse lidar, and surface PM2.5 measurements. Elevated levels of fire activity coupled with high aerosol optical depth and PM2.5 were observed over a period of nine days. Increased variability of parameters such as aerosol optical depth, Angstrom exponent number and its fine mode equivalents all indicated high levels of fine particulate presence in the atmosphere. Smoke particle growth due to aging, coagulation and condensation mechanisms was detected during the afternoons and over several days. Retrieved lidar ratios were compatible with the presence of fine particulate within the boundary/aerosol layer. Moreover, retrieved particle size distribution as well as single scattering albedo indicated the prevalence of the fine mode particulate regime as well as particles showing enhanced levels of absorption respectively.

Air quality↗

Wintertime particulate matter decrease buffered by unfavorable chemical processes despite emissions reductions in China

Extreme and persistent haze events frequently occur during wintertime China. While recent emissions reductions reduced annual mean fine particulate matter (PM2.5) concentrations over eastern China, their effectiveness on wintertime PM2.5 trend remains uncertain. We use observations and model simulations to quantify seasonal differences in PM2.5 trends and investigate the underlying chemical mechanisms driving such differences. We find a much slower decrease in observed wintertime PM2.5 (–3.2% yr-1) since 2014, in contrast to a drastic summertime decrease (–10.3% yr-1). Simulations show two previously underappreciated mechanisms buffering wintertime PM2.5 decrease, including an increase in oxidation capacity due to nitrogen oxides (NOx) reductions under wintertime volatile organic compound (VOC)- limited chemistry, and an enhanced conversion of nitric acid to nitrate by ammonia due to sulfur dioxide reductions. Our findings suggest that control policies targeting VOC and deep NOx reductions are needed to improve wintertime PM2.5 air quality over China.

Leung, Danny M.↗

High Resolution Global Coupled Chemistry-Meteorology Simulations Using the NASA GEOS Composition Forecast System, GEOS-CF

We will give an overview of the NASA Global Earth Observing System Composition Forecast system (GEOS-CF), a high-resolution (0.25 degree) global composition model developed by the NASA Global Modeling and Assimilation Office (GMAO). This system combines the GEOS weather and aerosol model with the GEOS-Chem chemistry module (version 12) to provide a holistic view of atmospheric composition that captures a wide range of air pollutants such as ozone, nitrogen oxides, volatile organic compounds, and fine particulate matter. The spatial resolution of 0.25 degrees (approx. 25 km) is fine enough to resolve local features such as nighttime ozone titration previously resolved only by urban or regional models. Furthermore, since there are no boundary conditions for a global model, the GEOS-CF captures large-scale processes such as long-range transport of air pollutants from forest fires. Comparisons against surface observations highlight the model’s overall capability to reproduce the diurnal variability of air pollutants under a variety of meteorological conditions. In addition, we show how machine learning techniques can be used to correct for sub-grid variability, which further improves model estimates at a given surface observation site. The GEOS-CF system offers a new tool for scientists and the public health community alike and is being developed jointly with several government and non-profit partners. As an example, we will show the use of GEOS-CF during the Satellite Coastal and Oceanic Atmospheric Pollution Experiment (SCOAPE). The campaign, conducted in collaboration between NASA and the Bureau of Ocean Energy Management (BOEM), aims to investigate the response of onshore air quality to Outer Continental Shelf (OCS) oil and gas exploration, development and production. Detailed gas-phase chemistry, as provided by GEOS-CF, is critical to understand the formation of air pollution related to hydrocarbon emissions from offshore oil and gas activities. The accuracy of GEOS-CF can be further improved by incorporating detailed offshore emissions compiled by BOEM.

Knowland, K. Emma↗

Root traits of perennial C 4 grasses contribute to cultivar variations in soil chemistry and species patterns in particulate and mineral‐associated carbon pool formation

Abstract Recent studies have indicated that the C 4 perennial bioenergy crops switchgrass ( Panicum virgatum ) and big bluestem ( Andropogon gerardii ) accumulate significant amounts of soil carbon (C) owing to their extensive root systems. Soil C accumulation is likely driven by inter‐ and intraspecific variability in plant traits, but the mechanisms that underpin this variability remain unresolved. In this study we evaluated how inter‐ and intraspecific variation in root traits of cultivars from switchgrass (Cave‐in‐Rock, Kanlow, Southlow) and big bluestem (Bonanza, Southlow, Suther) affected the associations of soil C accumulation across soil fractions using stable isotope techniques. Our experimental field site was established in June 2008 at Fermilab in Batavia, IL. In 2018, soil cores were collected (30 cm depth) from all cultivars. We measured root biomass, root diameter, specific root length, bulk soil C, C associated with coarse particulate organic matter (CPOM) and fine particulate organic matter plus silt‐ and clay‐sized fractions, and characterized organic matter chemical class composition in soil using high‐resolution Fourier‐transform ion cyclotron resonance mass spectrometry. C 4 species were established on soils that supported C 3 grassland for 36 years before planting, which allowed us to use differences in the natural abundance of stable C isotopes to quantify C 4 plant‐derived C. We found that big bluestem had 36.9% higher C 4 plant‐derived C compared to switchgrass in the CPOM fraction in the 0–10 cm depth, while switchgrass had 60.7% higher C 4 plant‐derived C compared to big bluestem in the clay fraction in the 10–20 cm depth. Our findings suggest that the large root system in big bluestem helps increase POM‐C formation quickly, while switchgrass root structure and chemistry build a mineral‐bound clay C pool through time. Thus, both species and cultivar selection can help improve bioenergy management to maximize soil carbon gains and lower CO 2 emissions.

60 APPLIED LIFE SCIENCES↗

NASA's GEOS Composition Model Assessment of PM2.5 During Wildfires: Inferring the Impact of PM2.5 Exposure on Adverse Respiratory & Cardiovascular Conditions

Particulate matter pollution is a mixture of solid and liquid droplets floating in the air that can lead to reduced air quality and increased adverse health impact. Fine particulate matter (PM2.5) can be emitted into the air from anthropogenic sources such as the burning of fossil fuels, motor vehicles, and powerplant emissions. Exposure to PM2.5 can aggravate pre-existing respiratory and cardiovascular conditions. When PM2.5 is inhaled it can cause damage to the lungs such as reduced lung function and shortness of breath. After being inhaled PM2.5 can enter the bloodstream and cause harm to the heart. One major natural source of PM2.5 exposure is from wildfire smoke. The particulates within the smoke from the wildfires can spread from the initial source region, potentially impacting communities both near and far. During and after wildfire events, PM2.5 levels can exceed the WHO air quality guidelines (10 m.g/m^3 annual mean; 25 m.g/m^3 daily mean), becoming hazardous to an individual's health. Global models can be used to simulate the emission and transport of these particulates and subsequently they can be valuable to air quality forecasting in highly polluted areas. The NASA Goddard Earth Observing System (GEOS) Composition Forecast (GEOS-CF) system has been used to produce near-real time air quality forecasts of atmospheric composition at a high global resolution of 25x25 km2. The GEOS-CF system utilizes the GEOS weather forecast model coupled with GEOS-Chem (version 11) chemistry module to provide analyses and forecasts of various toxic air pollutants, including PM2.5. The GEOS-CF simulated high levels of PM2.5 (40 m.g/m^3 to 250 m.g/m^3 ), exceeding the WHO guidelines, during multiple recent regional and global wildfire seasons, including the 2017 Washington State and Northern and Southern California wildfire seasons. Furthermore, the GEOS-CF simulated PM2.5 applied to a human health assessment model, BenMAP (The Environmental Benefits Mapping and Analysis Program, version 1.3), estimates the impact on adverse respiratory health conditions due to PM2.5 exposure from wildfires. The GEOS-CF predicted PM2.5 during the wildfire season with the corresponding BenMAP results provides an assessment of the human health impact of PM2.5 exposure.

Saunders, Emily↗

Trans-Pacific Transport of Saharan Dust to Western North America: A Case Study

The first documented case of long range transport of Saharan dust over a pathway spanning Asia and the Pacific to Western North America is described. Crustal material generated by North African dust storms during the period 28 February - 3 March 2005 reached western Canada on 13-14 March 2005 and was observed by lidar and sunphotometer in the Vancouver region and by high altitude aerosol instrumentation at Whistler Peak. Global chemical models (GEOS-CHEM and NRL NAAPS) confirm the transport pathway and suggest source attribution was simplified in this case by the distinct, and somewhat unusual, lack of dust activity over Eurasia (Gobi and Takla Makan deserts) at this time. Over western North America, the dust layer, although subsiding close to the boundary layer, did not appear to contribute to boundary layer particulate matter concentrations. Furthermore, sunphotometer observations (and associated inversion products) suggest that the dust layer had only subtle optical impact (Aerosol Optical Thickness (Tau(sub a500)) and Angstrom exponent (Alpha(sub 440-870) were 0.1 and 1.2 respectively) and was dominated by fine particulate matter (modes in aerodynamic diameter at 0.3 and 2.5microns). High Altitude observations at Whistler BC, confirm the crustal origin of the layer (rich in Ca(++) ions) and the bi-modal size distribution. Although a weak event compared to the Asian Trans-Pacific dust events of 1998 and 2001, this novel case highlights the possibility that Saharan sources may contribute episodically to the aerosol burden in western North America.

Kendry, Ian G. M.↗

Variation in Global Chemical Composition of PM2.5: Emerging Results from SPARTAN

The Surface PARTiculate mAtter Network (SPARTAN) is a long-term project that includes characterization of chemical and physical attributes of aerosols from filter samples collected worldwide. This paper discusses the ongoing efforts of SPARTAN to define and quantify major ions and trace metals found in fine particulate matter (PM (sub 2.5). Our methods infer the spatial and temporal variability of PM (sub 2.5) in a cost-effective manner. Gravimetrically weighed filters represent multi-day averages of PM (sub 2.5), with a collocated nephelometer sampling air continuously. SPARTAN instruments are paired with AErosol RObotic NETwork (AERONET) sun photometers to better understand the relationship between ground-level PM (sub 2.5) and columnar aerosol optical depth (AOD). We have examined the chemical composition of PM (sub 2.5) at 12 globally dispersed, densely populated urban locations and a site at Mammoth Cave (US) National Park used as a background comparison. So far, each SPARTAN location has been active between the years 2013 and 2016 over periods of 2-26 months, with an average period of 12 months per site. These sites have collectively gathered over 10 years of quality aerosol data. The major PM (sub 2.5) constituents across all sites (relative contribution plus or minus Standard Deviation) are ammoniated sulfate (20 percent plus or minus 11 percent), crustal material (13.4 percent plus or minus 9.9 percent), equivalent black carbon (11.9 percent plus or minus 8.4 percent), ammonium nitrate (4.7 percent plus or minus 3.0 percent), sea salt (2.3 percent plus or minus 1.6 percent), trace element oxides (1.0 percent plus or minus 1.1 percent), water (7.2 percent plus or minus 3.3 percent) at 35 percent relative humidity, and residual matter (40 percent plus or minus 24 percent). Analysis of filter samples reveals that several PM (sub 2.5) chemical components varied by more than an order of magnitude between sites. Ammoniated sulfate ranges from 1.1 microns per cubic meter (Buenos Aires, Argentina) to 17 microns per cubic meter (Kanpur, India in the dry season). Ammonium nitrate ranged from 0.2 microns per cubic meter (Mammoth Cave, in summer) to 6.8 microns per cubic meter (Kanpur, dry season). Equivalent black carbon ranged from 0.7 microns per cubic meter (Mammoth Cave) to over 8 microns per cubic meter (Dhaka, Bangladesh and Kanpur, India). Comparison of SPARTAN vs. coincident measurements from the Interagency Monitoring of Protected Visual Environments (IMPROVE) network at Mammoth Cave yielded a high degree of consistency for daily PM (sub 2.5) (r squared equals 0.76, slope equals 1.12), daily sulfate (r squared equals 0.86, slope equals 1.03), and mean fractions of all major PM (sub 2.5) components (within 6 percent). Major ions generally agree well with previous studies at the same urban locations (e.g. sulfate fractions agree within 4 percent for 8 out of 11 collocation comparisons). Enhanced anthropogenic dust fractions in large urban areas (e.g. Singapore, Kanpur, Hanoi, and Dhaka) are apparent from high Zn to Al ratios. The expected water contribution to aerosols is calculated via the hygroscopicity parameter kappa (sub v (volume)) for each filter. Mean aggregate values ranged from 0.15 (Ilorin) to 0.28 (Rehovot). The all-site parameter mean is 0.20 plus or minus 0.04. Chemical composition and water retention in each filter measurement allows inference of hourly PM (sub 2.5) at 35 percent relative humidity by merging with nephelometer measurements. These hourly PM (sub 2.5) estimates compare favourably with a beta attenuation monitor (MetOne) at the nearby US embassy in Beijing, with a coefficient of variation r squared equals 0.67 (number equals 3167), compared to r squared equals 0.62 when v (volume) was not considered. SPARTAN continues to provide an open-access database of PM (sub 2.5) compositional filter information and hourly mass collected from a global federation of instruments.

Snider, Graydon↗

Biochemical Conversion of Herbaceous Biomass to Renewable Diesel: Net Greenhouse Gas and Air Pollutant Trade-offs

This study examines greenhouse gas (GHG) and criteria air pollutant (CAP) emissions trade-offs for renewable diesel across 12 scenarios, involving different biochemical conversion designs, biorefinery scales, and feedstocks. A conventional design uses lignin for on-site heat and power, which exports excess power to the grid. An alternative design exports lignin pellets, offsetting other pellet production methods but requiring grid electricity to meet biorefinery power demands. Net emissions were quantified in Iowa and Georgia, selected considering feedstock availability, coproduct displacement, and regional power grids, assuming grid-exported power avoids coal or low-carbon electricity. Results for the conventional design remained consistent across the electricity displacement scenarios. When comparing lignin utilization strategies, pelletizing lignin reduces sulfur dioxide, carbon monoxide, nitrogen oxides, and volatile organic compounds (net emissions –0.66 mg MJ –1 , 25 mg MJ –1 , 25 mg MJ –1 , 7.8 mg MJ –1 , respectively). However, lignin pelletization increases net particulate matter (fine and coarse) and ammonia (net emissions of 4.7 mg MJ –1 , 13 mg MJ –1 , and 0.26 mg MJ –1 , respectively), alongside indirect GHG emissions due to grid electricity dependence. Additionally, processing 2000 tonnes corn stover daily minimizes emissions for both designs. Only lignin pelletization with renewable electricity and additional particulate matter and ammonia controls reduces all CAP and GHG emissions simultaneously.

09 BIOMASS FUELS↗

Use of Tracer Elements for Estimating Community Exposure to Marcellus Shale Development Operations

Since 2009, unconventional natural gas development (UNGD) has significantly increased in Appalachia’s Marcellus Shale formation. Elevations of fine particulate matter <2.5 µm (PM2.5), have been documented in areas surrounding drilling operations during well stimulation. Furthermore, many communities are experiencing increased industrial activities and probable UNGD air pollutant exposures. Recent studies have associated UNGD emissions with health effects based on distances from well pads. In this study, PM2.5 filter samples were collected on an active gas well pad in Morgantown, West Virginia, and three locations downwind during hydraulic stimulation. Fine particulate samples were analyzed for major and trace elements. An experimental source identification model was developed to determine which elements appeared to be traceable downwind of the UNGD site and whether these elements corresponded to PM2.5 measurements. Results suggest that 1) magnesium may be useful for detecting the reach of UNGD point source emissions, 2) complex surface topographic and meteorological conditions in the Marcellus Shale region could be modeled and confounding sources discounted, and 3) well pad emissions may be measurable at distances of at least 7 km. If shown to be more widely applicable, future tracer studies could enhance epidemiological studies showing health effects of UNGD-associated emissions at ≥15 km.

60 APPLIED LIFE SCIENCES↗

Near Real Time Air Quality Forecasts Using the NASA GEOS Model

This presentation provides an overview of NASA's Global Modeling and Assimilation Office (GMAO) high-resolution global forecast and reanalysis products for weather, aerosols, and air quality. The NASA Global Earth Observing System (GEOS) model radiatively coupled to GOCART aerosol module assimilates 2-dimensional column-integrated aerosol optical depth (AOD) at one wavelength (550 nm) in order to constrain the model's background AOD in order to have the best historical estimate and forecasts of AOD and particulate matter. Furthermore, the GEOS model has been expanded to provide global near-real-time 5-day forecasts of atmospheric composition at unprecedented horizontal resolution of 0.25 degrees (~25 km). This composition forecast system (GEOS-CF) combines the operational GEOS weather forecasting model with the state-of-the-science GEOS-Chem chemistry module (version 12) to provide detailed analysis of a wide range of air pollutants such as ozone, carbon monoxide, nitrogen oxides, and fine particulate matter (PM2.5).

K Emma Knowland↗

Near Real Time Air Quality Forecasts Using the NASA GEOS Model

This presentation provides an overview of NASA's Global Modeling and Assimilation Office (GMAO) high-resolution global forecast and reanalysis products for weather, aerosols, and air quality. The NASA Global Earth Observing System (GEOS) model radiatively coupled to GOCART aerosol module assimilates 2-dimensional column-integrated aerosol optical depth (AOD) at one wavelength (550 nm) in order to constrain the model's background AOD in order to have the best historical estimate and forecasts of AOD and particulate matter. Furthermore, the GEOS model has been expanded to provide global near-real-time 5-day forecasts of atmospheric composition at unprecedented horizontal resolution of 0.25 degrees (~25 km). This composition forecast system (GEOS-CF) combines the operational GEOS weather forecasting model with the state-of-the-science GEOS-Chem chemistry module (version 12) to provide detailed analysis of a wide range of air pollutants such as ozone, carbon monoxide, nitrogen oxides, and fine particulate matter (PM2.5).

K Emma Knowland↗

Variabilities in Pm2.5 and Black Carbon Surface Concentrations Reproduced by Aerosol Optical Properties Estimated by In-Situ Data, Ground Based Remote Sensing and Modeling

Because of the increased temporal and spatial resolutions of the sensors onboard recently launched satellites, satellite-based surface aerosol concentration, which is usually estimated from the aerosol optical depth (AOD), is expected to become a strategic tool for air quality studies in the future. By further exploring the relationships of aerosol concentrations and their optical properties using ground observations, the accuracies of these products can be improved. Here, we analyzed collocated observations of surface mass concentrations of fine particulate matter (PM2.5) and black carbon (BC), as well as columnar aerosol optical properties from a sky radiometer and aerosol extinction profiles obtained by multi-axis differential optical absorption spectroscopy (MAX-DOAS), during the 2019–2020 period. We focused the analyses on a daily scale, emphasizing the role of the ultraviolet (UV) spectral region. Generally, the correlation between the AOD of the fine fraction (i.e., fAOD) and the PM2.5 surface concentration was moderately strong, regardless of considerations of boundary layer humidity and altitude. In contrast, the fAOD of the partial column below 1 km, which was obtained by combining sky radiometer and MAX-DOAS retrievals, better reproduced the variability of the PM2.5 and resulted in a linear relationship. In the same manner, we demonstrated that the absorption AOD of the fine fraction (fAAOD) of the partial column was related to the variability of the BC concentration. Analogous analyses based on aerosol products from the Modern-Era Retrospective analysis for Research and Applications, Version 2 (MERRA-2) confirmed these findings and highlighted the importance of the shape of the aerosol profile. Overall, our results indicated a remarkable consistency among the retrieved datasets, and between the datasets and MERRA-2 products. These results confirmed the well-known sensitivity to aerosol absorption in the UV spectral region; they also highlighted the efficacy of combined MAX-DOAS and sky radiometer observations.

Alessandro Damiani↗