Photochemical smog, or ground-level ozone, has been the most recalcitrant of air pollution problems, but reductions in emissions of sulfur and hydrocarbons may yield unanticipated benefits in air quality. While sulfate and some organic aerosol particles scatter solar radiation back into space and can cool Earth's surface, they also change the actinic flux of ultraviolet (UV) radiation. Observations and numerical models show that UV-scattering particles in the boundary layer accelerate photochemical reactions and smog production, but UV-absorbing aerosols such as mineral dust and soot inhibit smog production. Results could have major implications for the control of air pollution.

The Visible Infrared Imaging Radiometer Suite (VIIRS) instrument on board the Suomi National Polar‐orbiting Partnership (S‐NPP) spacecraft was launched in October 2011. The instrument has 22 spectral channels with band centers from 412 nm to 12,050 nm. The VIIRS aerosol data products are derived primarily from the radiometric channels covering the visible through the short‐wave infrared spectral regions (412 nm to 2250 nm). The major components of the VIIRS aerosol retrieval process are data screening, land inversion, ocean inversion, suspended matter typing, and aggregation. The primary data product produced is the aerosol optical thickness (AOT) environmental data record. A higher resolution AOT intermediate product is also produced. These AOT products and their corresponding retrieval algorithms are described in detail, including theoretical basis, retrieval limitations, and data quality flagging. Preliminary evaluation of the data products has been undertaken by the VIIRS aerosol calibration/validation team using Aerosol Robotic Network ground‐based observations to show that the performance of AOT retrievals meets the requirements specified in the Joint Polar Satellite System Level 1 requirements.

The Visible Infrared Imaging Radiometer Suite (VIIRS) is the next-generation polar-orbiting operational environmental sensor with a capability for global aerosol observations. The VIIRS aerosol Environmental Data Record (EDR) is expected to continue the decade-long successful multispectral aerosol retrieval from the NASA's Earth Observing System Moderate Resolution Imaging Spectroradiometer (MODIS) for scientific research and applications. Since the launch of the Suomi National Polar-orbiting Partnership (S-NPP), the VIIRS aerosol calibration/validation team has been continuously monitoring, evaluating, and improving the performance of VIIRS aerosol retrievals. In this study, the VIIRS aerosol optical thickness (AOT) at 550 nm EDR at current Provisional maturity level is evaluated by comparing it with MODIS retrievals and measurements from the Aerosol Robotic Network (AERONET) and the Maritime Aerosol Network (MAN). The VIIRS global mean AOT at 550 nm differs from that of MODIS by approximately À0.01 over ocean and 0.03 over land (0.00 and À0.01 for the collocated retrievals) but shows larger regional biases. Global validation with AERONET and with MAN measurements shows biases of 0.01 over ocean and À0.01 over land, with about 64% and 71% of retrievals falling within the expected uncertainty range established by MODIS over ocean (±(0.03 + 0.05AOT)) and over land (±(0.05 + 0.15AOT)), respectively. The VIIRS retrievals over land exhibit slight overestimation over vegetated surfaces and underestimation over soil-dominated surfaces. These results show that the VIIRS AOT at 550 nm product provides a solid global data set for quantitative scientific investigations and environmental monitoring.

An overview of the National Oceanic and Atmospheric Administration’s (NOAA) current operational Smoke Forecasting System (SFS) is presented. This system is intended as guidance to air quality forecasters and the public for fine particulate matter (≤2.5 μm) emitted from large wildfires and agricultural burning, which can elevate particulate concentrations to unhealthful levels. The SFS uses National Environmental Satellite, Data, and Information Service (NESDIS) Hazard Mapping System (HMS), which is based on satellite imagery, to establish the locations and extents of the fires. The particulate matter emission rate is computed using the emission processing portion of the U.S. Forest Service’s BlueSky Framework, which includes a fuel-type database, as well as consumption and emissions models. The Hybrid Single Particle Lagrangian Integrated Trajectory (HYSPLIT) model is used to calculate the transport, dispersion, and deposition of the emitted particulate matter. The model evaluation is carried out by comparing predicted smoke levels with actual smoke detected from satellites by the HMS and the Geostationary Operational Environmental Satellite (GOES) Aerosol/Smoke Product. This overlap is expressed as the figure of merit in space (FMS), the intersection over the union of the observed and calculated smoke plumes. Results are presented for the 2007 fire season (September 2006–November 2007). While the highest FMS scores for individual events approach 60%, average values for the 1 and 5 μg m−3 contours for the analysis period were 8.3% and 11.6%, respectively. FMS scores for the forecast period were lower by about 25% due, in part, to the inability to forecast new fires. The HMS plumes tend to be smaller than the corresponding predictions during the winter months, suggesting that excessive emissions predicted for the smaller fires resulted in an overprediction in the smoke area.

We assess the strength of association between aerosol optical depth (AOD) retrievals from the GOES Aerosol/Smoke Product (GASP) and ground-level fine particulate matter (PM2.5) to assess AOD as a proxy for PM2.5 in the United States. GASP AOD is retrieved from a geostationary platform and therefore provides dense temporal coverage with half-hourly observations every day, in contrast to once per day snapshots from polar-orbiting satellites. However, GASP AOD is based on a less-sophisticated instrument and retrieval algorithm. We find that correlations between GASP AOD and PM2.5 over time at fixed locations are reasonably high, except in the winter and in the western U.S. Correlations over space at fixed times are lower. Simple averaging over time actually reduces correlations over space dramatically, but statistical calibration allows averaging over time that produces strong correlations. These results and the data density of GASP AOD highlight its potential to help improve exposure estimates for epidemiological analyses. On average 40% of days in a month have a GASP AOD retrieval compared to 14% for MODIS and 4% for MISR. Furthermore, GASP AOD has been retrieved since November 1994, providing the possibility of a long-term record that pre-dates the availability of most PM2.5 monitoring data and other satellite instruments. We assess the strength of association between aerosol optical depth (AOD) retrievals from the GOES 2 Aerosol/Smoke Product (GASP) and ground-level fine particulate matter (PM 2.5 ) to assess AOD as a 3 proxy for PM 2.5 in the United States. GASP AOD is retrieved from a geostationary platform and there-4 fore provides dense temporal coverage with half-hourly observations every day, in contrast to once per 5 day snapshots from polar-orbiting satellites. However, GASP AOD is based on a less-sophisticated in-6 strument and retrieval algorithm. We find that correlations between GASP AOD and PM 2.5 over time 7 at fixed locations are reasonably high, except in the winter and in the western U.S. Correlations over 8 space at fixed times are lower. Simple averaging over time actually reduces correlations over space dra-9 matically, but statistical calibration allows averaging over time that produces strong correlations. These 10 results and the data density of GASP AOD highlight its potential to help improve exposure estimates for 11 epidemiological analyses. On average 40% of days in a month have a GASP AOD retrieval compared to 12

[1] Near-real-time estimates of biomass burning emissions are crucial for air quality monitoring and forecasting. We present here the first near-real-time global biomass burning emission product from geostationary satellites (GBBEP-Geo) produced from satellite-derived fire radiative power (FRP) for individual fire pixels. Specifically, the FRP is retrieved using WF_ABBA V65 (wildfire automated biomass burning algorithm) from a network of multiple geostationary satellites. The network consists of two Geostationary Operational Environmental Satellites (GOES) which are operated by the National Oceanic and Atmospheric Administration, the Meteosat second-generation satellites (Meteosat-09) operated by the European Organisation for the Exploitation of Meteorological Satellites, and the Multifunctional Transport Satellite (MTSAT) operated by the Japan Meteorological Agency. These satellites observe wildfires at an interval of 15-30 min. Because of the impacts from sensor saturation, cloud cover, and background surface, the FRP values are generally not continuously observed. The missing observations are simulated by combining the available instantaneous FRP observations within a day and a set of representative climatological diurnal patterns of FRP for various ecosystems. Finally, the simulated diurnal variation in FRP is applied to quantify biomass combustion and emissions in individual fire pixels with a latency of 1 day. By analyzing global patterns in hourly biomass burning emissions in 2010, we find that peak fire season varied greatly and that annual wildfires burned 1.33 Â 10 12 kg dry mass, released 1.27 Â 10 10 kg of PM2.5 (particulate mass for particles with diameter <2.5 mm) and 1.18 Â 10 11 kg of CO globally (excluding most parts of boreal Asia, the Middle East, and India because of no coverage from geostationary satellites). The biomass burning emissions were mostly released from forest and savanna fires in Africa, South America, and North America. Evaluation of emission result reveals that the GBBEP-Geo estimates are comparable with other FRP-derived estimates in Africa, while the results are generally smaller than most of the other global products that were derived from burned area and fuel loading. However, the daily emissions estimated from GOES FRP over the United States are generally consistent with those modeled from GOES burned area and MODIS (Moderate Resolution Imaging Spectroradiometer) fuel loading, which produces an overall bias of 5.7% and a correlation slope of 0.97 AE 0.2. It is expected that near-real-time hourly emissions from GBBEP-Geo could provide a crucial component for atmospheric and chemical transport modelers to forecast air quality and weather conditions.

The new‐generation polar‐orbiting operational environmental sensor, the Visible Infrared Imaging Radiometer Suite (VIIRS) on board the Suomi National Polar‐orbiting Partnership (S‐NPP) satellite, provides critical daily global aerosol observations. As older satellite sensors age out, the VIIRS aerosol product will become the primary observational source for global assessments of aerosol emission and transport, aerosol meteorological and climatic effects, air quality monitoring, and public health. To prove their validity and to assess their maturity level, the VIIRS aerosol products were compared to the spatiotemporally matched Aerosol Robotic Network (AERONET) measurements. Over land, the VIIRS aerosol optical thickness (AOT) environmental data record (EDR) exhibits an overall global bias against AERONET of −0.0008 with root‐mean‐square error (RMSE) of the biases as 0.12. Over ocean, the mean bias of VIIRS AOT EDR is 0.02 with RMSE of the biases as 0.06. The mean bias of VIIRS Ocean Ångström Exponent (AE) EDR is 0.12 with RMSE of the biases as 0.57. The matchups between each product and its AERONET counterpart allow estimates of expected error in each case. Increased uncertainty in the VIIRS AOT and AE products is linked to specific regions, seasons, surface characteristics, and aerosol types, suggesting opportunity for future modifications as understanding of algorithm assumptions improves. Based on the assessment, the VIIRS AOT EDR over land reached Validated maturity beginning 23 January 2013; the AOT EDR and AE EDR over ocean reached Validated maturity beginning 2 May 2012, excluding the processing error period 15 October to 27 November 2012. These findings demonstrate the integrity and usefulness of the VIIRS aerosol products that will transition from S‐NPP to future polar‐orbiting environmental satellites in the decades to come and become the standard global aerosol data set as the previous generations' missions come to an end.

[1] The GOES Aerosol/Smoke Product (GASP) is a retrieval of the aerosol optical depth (AOD) using visible imagery. The product currently runs operationally at NOAA/NESDIS in near-real time at 30 min intervals. This high temporal resolution is not possible with polar orbiting instruments which produce one daily image. This work evaluates the GASP AOD from the GOES-12 Imager over North America at various temporal and spatial scales based on comparisons with AOD from the Aerosol Robotic Network (AERONET) and the Moderate Resolution Imaging Spectroradiometer (MODIS). We find a mean GASP/AERONET correlation of 0.79, rms difference of 0.13 and slope of 0.8, based on a statistical analysis at 10 northeastern U.S. and Canadian sites. The GASP AOD has a slight negative bias when the AOD is greater than 0.35 and a positive bias elsewhere. The absolute bias is less than 30% when the AOD is greater than 0.1. When the AOD is less than 0.15 we find poor correlation and biases greater than 30%. The GASP/ AERONET statistics also indicate that GASP can be used to examine the seasonal and diurnal variability in the AOD over the eastern United States between 1215 and 2115 UTC. GASP/AERONET AOD correlations were generally less than 0.5 elsewhere in the continental United States. Comparisons between the MODIS and GASP AOD over the eastern United States in the summer of 2004 showed agreement within 20% and correlations greater than 0.7 under elevated AOD conditions. Simultaneous comparisons between GASP, MODIS, and AERONET AODs showed good agreement over the northeastern United States and Canada, with higher correlation and lower rms differences in the MODIS/AERONET comparisons than in the GASP/AERONET comparisons.