scholarly journals Quantification of Atmospheric Ammonia Concentrations: A Review of its Measurement and Modeling

2020 ◽  
Author(s):  
Arshad Arjunan Nair ◽  
Fangqun Yu
Keyword(s):  
Remote Sensing ◽  
Atmospheric Chemistry ◽  
Satellite Remote Sensing ◽  
Current Knowledge ◽  
North India ◽  
Aerosol Formation ◽  
Spatiotemporal Variations ◽  
Atmospheric Ammonia ◽  
Topographical Effects ◽  
Synergistic Approach

Ammonia (NH3), the most prevalent alkaline gas in the atmosphere, plays a significant role in PM2.5 formation, atmospheric chemistry, and new particle formation. This paper reviews quantification of [NH3] through measurements, satellite-remote-sensing, and modeling reported in over 500 publications towards synthesizing current knowledge of [NH3], focusing on spatiotemporal variations, controlling processes, and quantification issues. Most measurements are through regional passive sampler networks. [NH3] hotspots are typically over agricultural regions like the Midwest US and North China Plain, with elevated concentrations reaching monthly averages of 20 and 74 ppbv, respectively. Topographical effects dramatically increase [NH3] over the Indo-Gangetic Plains, North India and San Joaquin Valley, US. Measurements are sparse over oceans, where [NH3] ≈ few tens of ppbv, variations of which can affect aerosol formation. Satellite-remote-sensing (AIRS, CrIS, IASI, TANSO-FTS, TES) provides global [NH3] quantification in the column and at surface since 2002. Modeling is crucial for improving understanding of NH3 chemistry and transport, its spatiotemporal variations, source apportionment, exploring physicochemical mechanisms, and predicting future scenarios. GEOS-Chem (global) and FRAME (UK) models are commonly applied for this. A synergistic approach of measurements↔satellite-inference↔modeling is needed towards improved understanding of atmospheric ammonia, of concern from the standpoint of human health and the ecosystem.

scholarly journals Quantification of Atmospheric Ammonia Concentrations: A Review of Its Measurement and Modeling

Atmosphere ◽  
2020 ◽  
Vol 11 (10) ◽  
pp. 1092
Author(s):  
Arshad Arjunan Nair ◽  
Fangqun Yu
Keyword(s):  
Remote Sensing ◽  
Atmospheric Chemistry ◽  
Satellite Remote Sensing ◽  
Current Knowledge ◽  
North India ◽  
Aerosol Formation ◽  
Spatiotemporal Variations ◽  
Atmospheric Ammonia ◽  
The North ◽  
Topographical Effects

Ammonia (NH3), the most prevalent alkaline gas in the atmosphere, plays a significant role in PM2.5 formation, atmospheric chemistry, and new particle formation. This paper reviews quantification of [NH3] through measurements, satellite-remote-sensing, and modeling reported in over 500 publications towards synthesizing the current knowledge of [NH3], focusing on spatiotemporal variations, controlling processes, and quantification issues. Most measurements are through regional passive sampler networks. [NH3] hotspots are typically over agricultural regions, such as the Midwest US and the North China Plain, with elevated concentrations reaching monthly averages of 20 and 74 ppbv, respectively. Topographical effects dramatically increase [NH3] over the Indo-Gangetic Plains, North India and San Joaquin Valley, US. Measurements are sparse over oceans, where [NH3] ≈ a few tens of pptv, variations of which can affect aerosol formation. Satellite remote-sensing (AIRS, CrIS, IASI, TANSO-FTS, TES) provides global [NH3] quantification in the column and at the surface since 2002. Modeling is crucial for improving understanding of NH3 chemistry and transport, its spatiotemporal variations, source apportionment, exploring physicochemical mechanisms, and predicting future scenarios. GEOS-Chem (global) and FRAME (UK) models are commonly applied for this. A synergistic approach of measurements↔satellite-inference↔modeling is needed towards improved understanding of atmospheric ammonia, which is of concern from the standpoint of human health and the ecosystem.

scholarly journals Secondary organic aerosol formation in cloud droplets and aqueous particles (aqSOA): a review of laboratory, field and model studies

2011 ◽  
Vol 11 (21) ◽  
pp. 11069-11102 ◽  
Author(s):  
B. Ervens ◽  
B. J. Turpin ◽  
R. J. Weber
Keyword(s):  
Relative Humidity ◽  
Gas Phase ◽  
Atmospheric Chemistry ◽  
Secondary Organic Aerosol ◽  
Current Knowledge ◽  
Laboratory Data ◽  
Organic Aerosol ◽  
Current Data ◽  
Aerosol Formation ◽  
Model Studies

Abstract. Progress has been made over the past decade in predicting secondary organic aerosol (SOA) mass in the atmosphere using vapor pressure-driven partitioning, which implies that SOA compounds are formed in the gas phase and then partition to an organic phase (gasSOA). However, discrepancies in predicting organic aerosol oxidation state, size and product (molecular mass) distribution, relative humidity (RH) dependence, color, and vertical profile suggest that additional SOA sources and aging processes may be important. The formation of SOA in cloud and aerosol water (aqSOA) is not considered in these models even though water is an abundant medium for atmospheric chemistry and such chemistry can form dicarboxylic acids and "humic-like substances" (oligomers, high-molecular-weight compounds), i.e. compounds that do not have any gas phase sources but comprise a significant fraction of the total SOA mass. There is direct evidence from field observations and laboratory studies that organic aerosol is formed in cloud and aerosol water, contributing substantial mass to the droplet mode. This review summarizes the current knowledge on aqueous phase organic reactions and combines evidence that points to a significant role of aqSOA formation in the atmosphere. Model studies are discussed that explore the importance of aqSOA formation and suggestions for model improvements are made based on the comprehensive set of laboratory data presented here. A first comparison is made between aqSOA and gasSOA yields and mass predictions for selected conditions. These simulations suggest that aqSOA might contribute almost as much mass as gasSOA to the SOA budget, with highest contributions from biogenic emissions of volatile organic compounds (VOC) in the presence of anthropogenic pollutants (i.e. NOx) at high relative humidity and cloudiness. Gaps in the current understanding of aqSOA processes are discussed and further studies (laboratory, field, model) are outlined to complement current data sets.

scholarly journals ACE-FTS observations of acetonitrile in the lower stratosphere

2013 ◽  
Vol 13 (15) ◽  
pp. 7405-7413 ◽  
Author(s):  
J. J. Harrison ◽  
P. F. Bernath
Keyword(s):  
Remote Sensing ◽  
Atmospheric Chemistry ◽  
Satellite Remote Sensing ◽  
Lower Stratosphere ◽  
Measurement Noise ◽  
Fourier Transform Spectrometer ◽  
Mixing Ratio ◽  
Solar Occultation ◽  
Retrieval Scheme ◽  
Chemistry Experiment

Abstract. This work reports the first infrared satellite remote-sensing measurements of acetonitrile (CH3CN) in the Earth's atmosphere using solar occultation measurements made by the Atmospheric Chemistry Experiment Fourier transform spectrometer (ACE-FTS) between 2004 and 2011. The retrieval scheme uses new quantitative laboratory spectroscopic measurements of acetonitrile (Harrison and Bernath, 2012). Although individual ACE-FTS profile measurements are dominated by measurement noise, median profiles in 10° latitude bins show a steady decline in volume mixing ratio from ~150 ppt (parts per trillion) at 11.5 km to < 40 ppt at 25.5–29.5 km. These new measurements agree well with the scant available air- and balloon-borne data in the lower stratosphere. An acetonitrile stratospheric lifetime of 73 ± 20 yr has been determined.

scholarly journals Secondary organic aerosol formation in cloud droplets and aqueous particles (aqSOA): a review of laboratory, field and model studies

2011 ◽  
Vol 11 (8) ◽  
pp. 22301-22383 ◽  
Author(s):  
B. Ervens ◽  
B. J. Turpin ◽  
R. J. Weber
Keyword(s):  
Relative Humidity ◽  
Gas Phase ◽  
Atmospheric Chemistry ◽  
Secondary Organic Aerosol ◽  
Current Knowledge ◽  
Laboratory Data ◽  
Organic Aerosol ◽  
Current Data ◽  
Aerosol Formation ◽  
Model Studies

Abstract. Progress has been made over the past decade in predicting secondary organic aerosol (SOA) mass in the atmosphere using vapor pressure-driven partitioning, which implies that SOA compounds are formed in the gas phase and then partition to an organic phase (gasSOA). However, discrepancies in predicting organic aerosol oxidation state, size and product (molecular mass) distribution, relative humidity (RH) dependence, color, and vertical profile suggest that additional SOA sources and aging processes may be important. The formation of SOA in cloud and aerosol water (aqSOA) is not considered in these models even though water is an abundant medium for atmospheric chemistry and such chemistry can form dicarboxylic acids and "humic-like substances" (oligomers, high-molecular-weight compounds), i.e., compounds that do not have any gas phase sources but comprise a significant fraction of the total SOA mass. There is direct evidence from field observations and laboratory studies that organic aerosol is formed in cloud and aerosol water, contributing substantial mass to the droplet mode. This review summarizes the current knowledge on aqueous phase organic reactions and combines evidence that points to a significant role of aqSOA formation in the atmosphere. Model studies are discussed that explore the importance of aqSOA formation and suggestions for model improvements are made based on the comprehensive set of laboratory data presented here. A first comparison is made between aqSOA and gasSOA yields and mass predictions for selected conditions. These simulations suggest that aqSOA might contribute almost as much mass as gasSOA to the SOA budget, with highest contributions from biogenic VOC emissions in the presence of anthropogenic pollutants (i.e., NOx) at high relative humidity and cloudiness. Gaps in the current understanding of aqSOA processes are discussed and further studies (laboratory, field, model) are outlined to complement current data sets.

scholarly journals Fusing Observational, Satellite Remote Sensing and Air Quality Model Simulated Data to Estimate Spatiotemporal Variations of PM2.5 Exposure in China

2017 ◽  
Author(s):  
Tao Xue ◽  
Yixuan Zheng ◽  
Guannan Geng ◽  
Bo Zheng ◽  
Xujia Jiang ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Air Quality ◽  
Satellite Remote Sensing ◽  
Ground Surface ◽  
Stage Model ◽  
Spatiotemporal Variations ◽  
Air Quality Model ◽  
Quality Model ◽  
Future Health ◽  
Spatiotemporal Resolution

Estimating ground surface PM2.5 with fine spatiotemporal resolution is a critical technique for exposure assessments in epidemiological studies of its health risks. Previous studies have utilized monitoring, satellite remote sensing or air quality modeling data to evaluate the spatiotemporal variations of PM2.5 concentrations, but such studies rarely combined these data simultaneously. We develop a three-stage model to fuse PM2.5 monitoring data, satellite-derived aerosol optical depth (AOD) and community multi-scale air quality (CMAQ) simulations together and apply it to estimate daily PM2.5 at a spatial resolution of 0.1˚ over China. Performance of the three-stage model is evaluated using a cross-validation (CV) method step by step. CV results show that the finally fused estimator of PM2.5 is in good agreement with the observational data (RMSE = 23.00 &mu;g/m^3 and R2 = 0.72) and outperforms either AOD-retrieved PM2.5 (R2 = 0.62) or CMAQ simulations (R2 = 0.51). According to step-specific CVs, in data fusion, AOD-retrieved PM2.5 plays a key role to reduce mean bias, whereas CMAQ provides all-spacetime-covered predictions, which avoids sampling bias caused by non-random incompleteness in satellite-derived AOD. Our fused products are more capable than either CMAQ simulations or AOD-based estimates in characterizing the polluting procedure during haze episodes and thus can support both chronic and acute exposure assessments of ambient PM2.5. Based on the products, averaged concentration of annual exposure to PM2.5 was 55.75 &mu;g/m3, while averaged count of polluted days (PM2.5 &gt; 75 &mu;g/m3) was 81, across China during 2014. Fused estimates will be publicly available for future health-related studies.

Evaluation of Earth Systems Models and Atmospheric Inversions using Total Column CO2 Observations from GOSAT and OCO-2

2020 ◽  
Author(s):  
Prabir K Patra ◽  
Tomohiro Hajima ◽  
Ryu Saito ◽  
Naveen Chandra ◽  
Yukio Yoshida ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Greenhouse Gases ◽  
Atmospheric Chemistry ◽  
Satellite Remote Sensing ◽  
Seasonal Cycle ◽  
Inverse Model ◽  
Earth System ◽  
Area Index ◽  
In Situ Data

Abstract The measurements of one of the major greenhouse gases, carbon dioxide (CO 2 ), are being made using dedicated satellite remote sensing since the launch of the greenhouse gases observing satellite (GOSAT) by JAXA in 2009 and NASA’s Orbiting Carbon Observatory-2 (OCO-2). In the past 10 years, estimation of CO 2 fluxes from land and ocean using the earth system models (ESMs) and inverse modelling of in situ atmospheric CO 2 data have also made significant progress. In this article, we attempt, for the first time, to evaluate the CO 2 fluxes simulated by an earth system model (MIROC-ES2L) using GOSAT observations and the fluxes estimated by an inverse model (MIROC4-Inv) for the period 2009-2014. Further, we use the OCO-2 measurements for testing the consistency of inversion results for the period 2014-2018, along with the GOSAT data. Both MIROC-ES2L and MIROC4-Inv fluxes are used in the MIROC4-atmospheric chemistry transport model (referred to as ACTM_ES2LF and ACTM_InvF, respectively) for calculating CO 2 concentrations that are sampled at the time and location of the satellite measurements. Our results suggest the inverse model using in situ data are more consistent with the OCO-2 retrievals, compared to those of the GOSAT XCO 2 data, suggesting possible improvements in the present GOSAT retrieval system by better accounting for the degradation correction of the TANSO-FTS. The ACTM_ES2LF simulation shows a slightly weaker seasonal cycle for the meridional profiles of CO 2 fluxes, compared to that from the ACTM_InvF. This difference is revealed by greater ACTM_ES2LF vs GOSAT differences, compared to those of ACTM_InvF vs GOSAT. We also find that the simulated seasonal cycle amplitude of XCO 2 by ACTM_ES2LF are slightly weaker compared to those observed by GOSAT or ACTM_InvF. Using remote sensing based global products of leaf area index (LAI) and gross primary productivity (GPP) over land, we show a weaker sensitivity of MIROC-ES2L biospheric activities to the weather and climate in the tropical regions. Our results clearly suggest the usefulness of XCO 2 measurements by satellite remote sensing for evaluation of large-scale ESMs, which so far remained untested by the sparse in situ data.

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