Results for “pm2.5” — Page 9

NASA NTRS2013

El Nino and Health Risks from Landscape Fire Emissions in Southeast Asia

Emissions from landscape fires affect both climate and air quality. Here, we combine satellite-derived fire estimates and atmospheric modelling to quantify health effects from fire emissions in southeast Asia from 1997 to 2006. This region has large interannual variability in fire activity owing to coupling between El Nino-induced droughts and anthropogenic land-use change. We show that during strong El Nino years, fires contribute up to 200 micrograms per cubic meter and 50 ppb in annual average fine particulate matter (PM2.5) and ozone surface concentrations near fire sources, respectively. This corresponds to a fire contribution of 200 additional days per year that exceed the World Health Organization 50 micrograms per cubic metre 24-hr PM(sub 2.5) interim target and an estimated 10,800 (6,800-14,300)-person (approximately 2 percent) annual increase in regional adult cardiovascular mortality. Our results indicate that reducing regional deforestation and degradation fires would improve public health along with widely established benefits from reducing carbon emissions, preserving biodiversity and maintaining ecosystem services.

fires↗

NASA NTRS2014

Aura OMI Observations of Global SO2 and NO2 Pollution from 2005 to 2013

The Ozone Monitoring Instrument (OMI), a NASA partnership with the Netherlands and Finland, flies on the NASA Aura satellite and uses reflected sunlight to measure the two critical atmospheric trace gases: nitrogen dioxide (NO2) and sulfur dioxide (SO2) characterizing daily air quality. Both gases and the secondary pollutants they produce (particulate matter, PM2.5, and tropospheric ozone) are USEPA designated criteria pollutants, posing serious threats to human health and the environment (e.g., acid rain, plant damage and reduced visibility). Our group at NASA GSFC has developed and maintained OMI standard SO2 and NO2 data products. We have recently released an updated version of the standard NO2 L2 and L3 products (SP v2.1) and continue improving the algorithm. We are currently in the process of releasing next generation pollution SO2 product, based on an innovative Principal Component Analysis (PCA) algorithm, which greatly reduces the noise and biases. These new standard products provide valuable datasets for studying anthropogenic pollution on local to global scales. Here we highlight some of the OMI observed changes in air quality over several regions. Over the US average NO2 and SO2 pollution levels had decreased dramatically as a result of both technological improvements (e.g., catalytic converters on cars) and stricter regulations of emissions. We see continued decline in pollution over Europe. Over China OMI observed an increase of about 60 percent in NO2 pollution between 2005 and 2013, despite a temporal reversal of the growing trend due to both 2008 Olympic Games and the economic recession in 2009. Chinese SO2 pollution seems to have stabilized since peaking in 2007, probably due to government efforts to curb SO2 emissions from the power sector. We have also observed large increases in both SO2 and NO2 pollution particularly in Eastern India where a number of large new coal power plants had been built in recent years. We expect that further improvements in the OMI NO2 and SO2 products will allow more robust quantification of long-term trends in global air quality.

SO2↗

NASA NTRS2015

Investigation of the CCN Activity, BC and UVBC Mass Concentrations of Biomass Burning Aerosols during the 2013 BASELInE Campaign

Biomass-burning (BB) aerosols, acting as cloud condensation nuclei (CCN), can influence cloud microphysical and radiative properties. In this study, we present CCN measured near the BB source regions over northern Southeast Asia (Doi Ang Khang, Thailand) and at downwind receptor areas (Lulin Atmospheric Background Station, Taiwan), focusing exclusively on 13-20 March 2013 as part of 2013 spring campaign of the Seven SouthEast Asian Studies (7-SEAS) intensive observation. One of the campaigns objectives is to characterize BB aerosols serving as CCN in SouthEast Asia (SEA). CCN concentrations were measured by a CCN counter at 5 supersaturation (SS) levels: 0.15%, 0.30%, 0.45%, 0.60%, and 0.75%. In addition, PM2.5 and black carbon mass concentrations were analyzed by using a tapered element oscillating microbalance and an aethalometer. It was found the number-size distributions and the characteristics of hygroscopicity (e.g., activation ratio and k) of BB aerosols in SEA have a strong diurnal pattern, and different behaviors of patterns were characterized under two distinct weather systems. The overall average value was low (0.05-0.1) but comparable with previous CCN studies in other BB source regions. Furthermore, a large fraction of UV-absorbing organic material (UVBC) and high Delta-C among BB aerosols were also observed, which suggest the existence of substantial particulate organic matter in fresh BB aerosols. These data provide the most extensive characterization of BB aerosols in SEA until now.

biomass burning aerosol↗

NASA NTRS2017

Testing Extensions of Our Quantitative Daily of San Joaquin Wintertime Aerosols Using MAIAC and Meteorology Without Transport/Transformation Assumptions

The Western US and many regions globally present daunting difficulties in understanding and mapping PM2.5 episodes. We evaluate extensions of a method independent of source-description and transport/transformation. These regions suffer frequent few-day episodes due to shallow mixing; low satellite AOT and bright surfaces complicate the description. Nevertheless, we expect residual errors in our maps of less than 8 ug/m^3 in episodes reaching 60-100 ug/m^3; maps which detail pollution from Interstate 5. Our current success is due to use of physically meaningful functions of MODIS-MAIAC-derived AOD, afternoon mixed-layer height, and relative humidity for a basin in which the latter are correlated. A mixed-effects model then describes a daily AOT-to-PM2.5 relationship. (Note: in other published mixed-effects models, AOT contributes minimally. We seek to extend on these to develop useful estimation methods for similar situations. We evaluate existing but more spotty information on size distribution (AERONET, MISR, MAIA, CALIPSO, other remote sensing). We also describe the usefulness of an equivalent mixing depth for water vapor vs meteorological boundary layer height. Each has virtues and limitations. Finally, we begin to evaluate methods for removing the complications due to detached but polluted layers (which don't mix to the surface) using geographical, meteorological, and remotely sensed data.

Chatfield, Robert B.↗

NASA NTRS2017

Air Quality Forecasts Using the NASA GEOS Model: A Unified Tool from Local to Global Scales

We provide an introduction to a new high-resolution (0.25 degree) global composition forecast produced by NASA's Global Modeling and Assimilation office. The NASA Goddard Earth Observing System version 5 (GEOS-5) model has been expanded to provide global near-real-time forecasts of atmospheric composition at a horizontal resolution of 0.25 degrees (approximately 25 km). Previously, this combination of detailed chemistry and resolution was only provided by regional models. This system combines the operational GEOS-5 weather forecasting model with the state-of-the-science GEOS-Chem chemistry module (version 11) to provide detailed chemical analysis of a wide range of air pollutants such as ozone, carbon monoxide, nitrogen oxides, and fine particulate matter (PM2.5). The resolution of the forecasts is the highest resolution compared to current, publically-available global composition forecasts. Evaluation and validation of modeled trace gases and aerosols compared to surface and satellite observations will be presented for constituents relative to health air quality standards. Comparisons of modeled trace gases and aerosols against satellite observations show that the model produces realistic concentrations of atmospheric constituents in the free troposphere. Model comparisons against surface observations highlight the model's capability to capture the diurnal variability of air pollutants under a variety of meteorological conditions. The GEOS-5 composition forecasting system offers a new tool for scientists and the public health community, and is being developed jointly with several government and non-profit partners. Potential applications include air quality warnings, flight campaign planning and exposure studies using the archived analysis fields.

Knowland, E. Emma↗

NASA NTRS2018

Air Quality Forecasts Using the NASA GEOS Model

We provide an introduction to a new high-resolution (0.25 degree) global composition forecast produced by NASA's Global Modeling and Assimilation office. The NASA Goddard Earth Observing System version 5 (GEOS-5) model has been expanded to provide global near-real-time forecasts of atmospheric composition at a horizontal resolution of 0.25 degrees (~25 km). Previously, this combination of detailed chemistry and resolution was only provided by regional models. This system combines the operational GEOS-5 weather forecasting model with the state-of-the-science GEOS-Chem chemistry module (version 11) to provide detailed chemical analysis of a wide range of air pollutants such as ozone, carbon monoxide, nitrogen oxides, and fine particulate matter (PM2.5). The resolution of the forecasts is the highest resolution compared to current, publically-available global composition forecasts. Evaluation and validation of modeled trace gases and aerosols compared to surface and satellite observations will be presented for constituents relative to health air quality standards. Comparisons of modeled trace gases and aerosols against satellite observations show that the model produces realistic concentrations of atmospheric constituents in the free troposphere. Model comparisons against surface observations highlight the model's capability to capture the diurnal variability of air pollutants under a variety of meteorological conditions. The GEOS-5 composition forecasting system offers a new tool for scientists and the public health community, and is being developed jointly with several government and non-profit partners. Potential applications include air quality warnings, flight campaign planning and exposure studies using the archived analysis fields.

Keller, Christoph A.↗

NASA NTRS2015

The Quick Fire Emissions Dataset (QFED): Documentation of Versions 2.1, 2.2 and 2.4: Technical Report Series on Global Modeling and Data Assimilation - Volume 38

Biomass burning is an important source of particulates and trace gases and a major element of the terrestrial carbon cycle. Well constrained emissions from vegetation fires are needed to model direct and indirect effects of biomass burning aerosols, to model homogeneous and heterogeneous chemistry in the atmosphere, and to perform credible Earth system analysis, and climate and air pollution studies. To improve the performance of NASA Goddard Earth Observing System Model (GEOS) in the areas of atmospheric constituent modeling with a focus on biomass burning we developed the Quick Fire Emissions Dataset (QFED). The QFED emissions are based on the fire radiative power (top-down) approach and draw on the cloud correction method developed in the Global Fire Assimilation System (GFAS). Location and fire radiative power of fires are obtained from the Moderate Resolution Imaging Spectroradiometer (MODIS) Level 2 fire products (MOD14 and MYD14) and the MODIS Geolocation products (MOD03 and MYD03). QFED strengths are high spatial and temporal resolutions and near-real time availability. Daily mean emissions are available at 0.3125 times 0.25 degrees and in recent versions also at 0.1 times 0.1 degrees. QFED provides emissions of black carbon, organic carbon, sulfur dioxide, carbon monoxide, carbon dioxide, PM2.5, ammonia, nitrogen oxides, methyl ethyl ketone, propylene, ethane, propane, n- and i-butane, acetaldehyde, formaldehyde, acetone and methane. Two QFED product systems are maintained by the NASA Global Modeling and Assimilation Office (GMAO): one that produces near real-time daily emissions used operationally in the GEOS-5 Data Assimilation System, and one that produces an extended historical dataset with daily emissions from March 2000 to the present. The historical dataset also provides monthly mean and monthly climatological emissions.

Koster, Randal D.↗

NASA NTRS2018

Air Quality Forecasts Using the NASA GEOS Model

We provide an introduction to a new high-resolution (0.25 degree) global composition forecast produced by NASA's Global Modeling and Assimilation office. The NASA Goddard Earth Observing System version 5 (GEOS-5) model has been expanded to provide global near-real-time forecasts of atmospheric composition at a horizontal resolution of 0.25 degrees (~25 km). Previously, this combination of detailed chemistry and resolution was only provided by regional models. This system combines the operational GEOS-5 weather forecasting model with the state-of-the-science GEOS-Chem chemistry module (version 11) to provide detailed chemical analysis of a wide range of air pollutants such as ozone, carbon monoxide, nitrogen oxides, and fine particulate matter (PM2.5).

Knowland, K. Emma↗

NASA NTRS2018

Satellite and Reanalysis Air Quality Data and Services at NASA GES DISC for Public Health Study

Outbreaks of infectious diseases and health can be influenced by airborne and water-borne pollutants. Furthermore, air and water quality are associated with climate variability, industrialization, land use and land cover change, and water resource management. It is therefore crucial to understand environment-disease connections with existing long-term observed and modeled data, particularly for development of early warning systems for infectious disease outbreaks. The NASA Goddard Earth Sciences Data and Information Services Center (GES DISC) (https://disc.gsfc.nasa.gov) archives large volumes of global environment data that are useful for research and applications regarding environmental factors and public health. Examples of air quality measurements are: Daily satellite remotely sensed data, including Aerosol Index (AI), O3, SO2, CO, and NO2 from Aura/OMI (October 2014 to present), and OMPS-NPP (January 2012 to present, currently research data products only) Hourly and monthly reanalysis modeled data, including PM2.5, O3, CO, SO2, BC, dust, AOD, and aerosol types from MERRA-2 (January 1980 to present) Examples of surface meteorology and land surface measurements are: hourly, daily, and monthly satellite precipitation from TRMM (December 1997 to March 2015) 30-minute and monthly satellite precipitation from GPM (March 2014 to present); Hourly and monthly modeled surface meteorology and land surface condition from MERRA-2 (January 1980 to present) and land surface assimilation models (January 1948 to present), including precipitation, surface temperature, relative humidity, wind, and soil moisture.This presentation will give an overview of relevant environmental data at the NASA GES DISC. Through a number of use cases, such as dust events and active fires, we will introduce data services that assist in finding the right data, enable visualization and analysis of the data online, and allow downloading of data in user-preferred format.

remote sensing data↗

NASA NTRS2018

Extreme Air Pollution Events in Hokkaido, Japan Traced Back to Early Snowmelt and Large-Scale Wildfires Over East Eurasia: Case Studies

To identify the unusual climate conditions and their connections to air pollutions in a remote area due to wildfires, we examine three anomalous large-scale wildfires in May 2003, April 2008, and July 2014 over East Eurasia, as well as how products of those wildfires reached an urban city, Sapporo, in the northern part of Japan (Hokkaido), significantly affecting the air quality. NASA's MERRA-2 (the Modern-Era Retrospective analysis for Research and Applications, Version 2) aerosol re-analysis data closely reproduced the PM2.5 variations in Sapporo for the case of smoke arrival inJuly 2014. Results show that all three cases featured unusually early snowmelt in East Eurasia, accompanied by warmer and drier surface conditions in the months leading to the fires, inducing long-lasting soil dryness and producing environmental conditions conductive to active wildfires. Due to prevailing anomalous synoptic-scale atmospheric motions, smoke from those fires eventually reached a remote area, Hokkaido, and worsened the air quality in Sapporo. In futurestudies, continuous monitoring of the timing of Eurasian snowmelt and the air quality from the source regions to remote regions, coupled with the analysis of atmospheric and surface conditions, may be essential in more accurately predicting the effects of wildfires on air quality.

MERRA-2↗

NASA NTRS2019

Near Real-Time Global Composition Forecasts at 25km Horizontal Resolution

We present a new high-resolution global composition forecast system produced by NASA's Global Modeling and Assimilation Office. The NASA Goddard Earth Observing System (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) system 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). Satellite observations are assimilated into the system for improved representation of weather and smoke.

Knowland, K. Emma↗

NASA NTRS2019

Near Real-Time Air Quality Forecasts Using the NASA GEOS Model

We present a new high-resolution global composition forecast system produced by NASA's Global Modeling and Assimilation Office. The NASA Goddard Earth Observing System (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) system 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). Satellite observations are assimilated into the system for improved representation of weather and smoke.

Knowland, K. Emma↗

NASA NTRS2019

Near Real-Time Air Quality Forecasts Using the NASA GEOS Model

We present a new high-resolution global composition forecast system produced by NASA's Global Modeling and Assimilation Office. The NASA Goddard Earth Observing System (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) system 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). Satellite observations are assimilated into the system for improved representation of weather and smoke.

Knowland, K. Emma↗

NASA NTRS2019

Air Pollution Forecasts Using the NASA GEOS Model: A Unified Tool from Local to Global Scales

We present a new high-resolution global composition forecast system produced by NASA's Global Modeling and Assimilation Office. The NASA Goddard Earth Observing System (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) system 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). Satellite observations are assimilated into the system for improved representation of weather and smoke.

Knowland, K. Emma↗

NASA NTRS2019

NASA GEOS Aerosol Modeling and Assimilation Activities

The current assimilation of Aerosol Optical Depth (AOD) in GEOS involves very careful cloud screening and homogenization of the observing system by means of a neural network that translates satellite reflectances from MODIS into AERONET calibrated AOD. In this talk we will present an update of the GEOS aerosol assimilation system, with emphasis on the improved treatment of MODIS observations. We will then proceed to assess the impact of geostationary aerosol observations from the ABI and AHI sensors on the GOES-16 and Himawari-8 satellites. The GEOS assimilated aerosol fields will be validated by comparison to independent in-situ and remotely-sensed measurements (PM2.5 concentrations, surface dust concentrations, Maritime Aerosol Network, airborne and ground based lidars, UV based measurements, etc.).

Castellanos, Patricia↗

NASA NTRS2019

File Specification for GEOS-CF Products

The NASA Global Earth Observing System (GEOS) model has been expanded to provide global near-real-time forecasts of atmospheric composition at a horizontal resolution of 0.25 degrees (about 25 km). This GEOS Composition Forecast (GEOS-CF) system combines the GEOS weather analysis and forecasting system with the state-of-the-science GEOS-Chem chemistry module (Bey et al., 2001; Keller et al., 2014; Long et al., 2015) to provide detailed chemical analysis of a wide range of air pollutants including ozone, carbon monoxide, nitrogen oxides, and fine particulate matter (PM2.5).

Knowland, Katherine E.↗

NASA NTRS2019

Assimilation of Aerosol Observations in the NASA GEOS Model

In the GEOS near real-time system, as well as in MERRA-2 which is the latest reanalysis produced at NASA's Global Modeling Assimilation Office (GMAO), the assimilation of aerosol observations is performed by means of a so-called analysis splitting method. The prognostic model is based on the GEOS model radiatively coupled to GOCART aerosol module and includes assimilation of bias-corrected Aerosol Optical Depth (AOD) at 550 nm from various space-based remote sensing platforms. In line with the transition of the GEOS meteorological data assimilation system to a hybrid Ensemble-Variational formulation, we are updating the aerosol component of our assimilation system to a variational ensemble type of scheme. In this talk we will examine the impact of replacing the current analysis splitting scheme with this new approach. Starting with the assimilation of satellite based single-channel retrievals; we will discuss the impact of this aerosol data assimilation technique on the 3D aerosol distributions by means of innovation statistics and verification against independent datasets such as the Aerosol Robotic Network (AERONET) and surface PM2.5. We will also present preliminary results related to the introduction of new aerosol data types in GEOS, including multi-spectral AOD retrievals.

AERONET↗

NASA NTRS2019

Connecting Crop Productivity, Residue Fires, and Air Quality over Northern India

Northwestern India is known as the “breadbasket” of the country producing two-thirds of food grains, with wheat and rice as the principal crops grown under the crop rotation system. Agricultural data from India indicates a 25% increase in the post-monsoon rice crop production in Punjab during 2002–2016. NASA’s A-train satellite sensors detect a consistent increase in the vegetation index (net 21%) and post-harvest agricultural fire activity (net ~60%) leading to nearly 43% increase in aerosol loading over the populous Indo-Gangetic Plain in northern India. The ground-level particulate matter (PM2.5) downwind over New Delhi shows a concurrent uptrend of net 60%. The effectiveness of a robust satellite-based relationship between vegetation index—a proxy for crop amounts, and post-harvest fires—a precursor of extreme air pollution events, has been further demonstrated in predicting the seasonal agricultural burning. An efficient crop residue management system is critically needed towards eliminating open field burning to mitigate episodic hazardous air quality over northern India.

Hiren Jethva↗