Improving surface PM 2.5 forecasts in the United States using an ensemble of chemical transport model outputs: 2. bias correction with satellite data for rural areas

2021 ◽  
Author(s):  
Huanxin Zhang ◽  
Jun Wang ◽  
Lorena Castro García ◽  
Meng Zhou ◽  
Cui Ge ◽  
...  
Keyword(s):  
United States ◽  
Satellite Data ◽  
Rural Areas ◽  
Bias Correction ◽  
Transport Model ◽  
Chemical Transport ◽  
The United States ◽  
Chemical Transport Model ◽  
Pm 2.5

scholarly journals Sensitivity of the recent methane budget to LMDz sub-grid scale physical parameterizations

2015 ◽  
Vol 15 (8) ◽  
pp. 11853-11888
Author(s):  
R. Locatelli ◽  
P. Bousquet ◽  
M. Saunois ◽  
F. Chevallier ◽  
C. Cressot
Keyword(s):  
Satellite Data ◽  
Transport Model ◽  
Deep Convection ◽  
Chemical Transport ◽  
Global Scale ◽  
Methane Emissions ◽  
Inverse Modelling ◽  
Chemical Transport Model ◽  
Methane Budget ◽  
Physical Parameterizations

Abstract. With the densification of surface observing networks and the development of remote sensing of greenhouse gases from space, estimations of methane (CH4) sources and sinks by inverse modelling face new challenges. Indeed, the chemical transport model used to link the flux space with the mixing ratio space must be able to represent these different types of constraints for providing consistent flux estimations. Here we quantify the impact of sub-grid scale physical parameterization errors on the global methane budget inferred by inverse modelling using the same inversion set-up but different physical parameterizations within one chemical-transport model. Two different schemes for vertical diffusion, two others for deep convection, and one additional for thermals in the planetary boundary layer are tested. Different atmospheric methane datasets are used as constraints (surface observations or satellite retrievals). At the global scale, methane emissions differ, on average, from 4.1 Tg CH4 per year due to the use of different sub-grid scale parameterizations. Inversions using satellite total-column retrieved by GOSAT satellite are less impacted, at the global scale, by errors in physical parameterizations. Focusing on large-scale atmospheric transport, we show that inversions using the deep convection scheme of Emanuel (1991) derive smaller interhemispheric gradient in methane emissions. At regional scale, the use of different sub-grid scale parameterizations induces uncertainties ranging from 1.2 (2.7%) to 9.4% (14.2%) of methane emissions in Africa and Eurasia Boreal respectively when using only surface measurements from the background (extended) surface network. When using only satellite data, we show that the small biases found in inversions using GOSAT-CH4 data and a coarser version of the transport model were actually masking a poor representation of the stratosphere–troposphere gradient in the model. Improving the stratosphere–troposphere gradient reveals a larger bias in GOSAT-CH4 satellite data, which largely amplifies inconsistencies between surface and satellite inversions. A simple bias correction is proposed. The results of this work provide the level of confidence one can have for recent methane inversions relatively to physical parameterizations included in chemical-transport models.

scholarly journals Interannual variability of ammonia concentrations over the United States: sources and implications

2016 ◽  
Vol 16 (18) ◽  
pp. 12305-12328 ◽  
Author(s):  
Luke D. Schiferl ◽  
Colette L. Heald ◽  
Martin Van Damme ◽  
Lieven Clarisse ◽  
Cathy Clerbaux ◽  
...  
Keyword(s):  
United States ◽  
Interannual Variability ◽  
Model Comparison ◽  
Transport Model ◽  
The United States ◽  
Ammonia Concentration ◽  
Phase Changes ◽  
Spatial And Temporal Variability ◽  
Ammonia Emissions ◽  
Chemical Transport Model

Abstract. The variability of atmospheric ammonia (NH3), emitted largely from agricultural sources, is an important factor when considering how inorganic fine particulate matter (PM2.5) concentrations and nitrogen cycling are changing over the United States. This study combines new observations of ammonia concentration from the surface, aboard aircraft, and retrieved by satellite to both evaluate the simulation of ammonia in a chemical transport model (GEOS-Chem) and identify which processes control the variability of these concentrations over a 5-year period (2008–2012). We find that the model generally underrepresents the ammonia concentration near large source regions (by 26 % at surface sites) and fails to reproduce the extent of interannual variability observed at the surface during the summer (JJA). Variability in the base simulation surface ammonia concentration is dominated by meteorology (64 %) as compared to reductions in SO2 and NOx emissions imposed by regulation (32 %) over this period. Introduction of year-to-year varying ammonia emissions based on animal population, fertilizer application, and meteorologically driven volatilization does not substantially improve the model comparison with observed ammonia concentrations, and these ammonia emissions changes have little effect on the simulated ammonia concentration variability compared to those caused by the variability of meteorology and acid-precursor emissions. There is also little effect on the PM2.5 concentration due to ammonia emissions variability in the summer when gas-phase changes are favored, but variability in wintertime emissions, as well as in early spring and late fall, will have a larger impact on PM2.5 formation. This work highlights the need for continued improvement in both satellite-based and in situ ammonia measurements to better constrain the magnitude and impacts of spatial and temporal variability in ammonia concentrations.

scholarly journals Global observations of tropospheric BrO columns using GOME-2 satellite data

2010 ◽  
Vol 10 (11) ◽  
pp. 28635-28685 ◽  
Author(s):  
N. Theys ◽  
M. Van Roozendael ◽  
F. Hendrick ◽  
X. Yang ◽  
I. De Smedt ◽  
...  
Keyword(s):  
Quantitative Study ◽  
Satellite Data ◽  
Transport Model ◽  
Chemical Transport ◽  
Sea Salt ◽  
Polar Regions ◽  
Blowing Snow ◽  
Chemical Transport Model ◽  
Sea Salt Aerosols ◽  
Good Level

Abstract. Measurements from the GOME-2 satellite instrument have been analyzed for tropospheric BrO using a residual technique that combines measured BrO columns and estimates of the stratospheric BrO content from a climatological approach driven by O3 and NO2 observations. Comparisons between the GOME-2 results and BrO vertical columns derived from correlative ground-based and SCIAMACHY nadir observations, present a good level of consistency. We show that the adopted technique enables separation of stratospheric and tropospheric fractions of the measured total BrO columns and allows quantitative study of the BrO plumes in polar regions. While some satellite observed plumes of enhanced BrO can be explained by stratospheric descending air, we show that most BrO hotspots are of tropospheric origin, although they are often associated to regions with low tropopause heights as well. Elaborating on simulations using the $p$-TOMCAT tropospheric chemical transport model, this result is found to be consistent with the mechanism of bromine release through sea salt aerosols production during blowing snow events. Outside polar regions, evidence is provided for a global tropospheric BrO background with column of 1–3×1013 molec/cm2, consistent with previous estimates.

scholarly journals Application of a Fusion Method for Gas and Particle Air Pollutants between Observational Data and Chemical Transport Model Simulations Over the Contiguous United States for 2005–2014

2019 ◽  
Vol 16 (18) ◽  
pp. 3314
Author(s):  
Niru Senthilkumar ◽  
Mark Gilfether ◽  
Francesca Metcalf ◽  
Armistead G. Russell ◽  
James A. Mulholland ◽  
...  
Keyword(s):  
United States ◽  
Air Quality ◽  
Spatial Variation ◽  
Temporal Variation ◽  
Observational Data ◽  
Transport Model ◽  
Chemical Transport ◽  
Daily Basis ◽  
Quality Data ◽  
Chemical Transport Model

Accurate spatiotemporal air quality data are critical for use in assessment of regulatory effectiveness and for exposure assessment in health studies. A number of data fusion methods have been developed to combine observational data and chemical transport model (CTM) results. Our approach focuses on preserving the temporal variation provided by observational data while deriving the spatial variation from the community multiscale air quality (CMAQ) simulations, a type of CTM. Here we show the results of fusing regulatory monitoring observational data with 12 km resolution CTM simulation results for 12 pollutants (CO, NOx, NO2, SO2, O3, PM2.5, PM10, NO3−, NH4+, EC, OC, SO42−) over the contiguous United States on a daily basis for a period of ten years (2005–2014). An annual mean regression between the CTM simulations and observational data is used to estimate the average spatial fields, and spatial interpolation of observations normalized by predicted annual average is used to provide the daily variation. Results match the temporal variation well (R2 values ranging from 0.84–0.98 across pollutants) and the spatial variation less well (R2 values 0.42–0.94). Ten-fold cross validation shows normalized root mean square error values of 60% or less and spatiotemporal R2 values of 0.4 or more for all pollutants except SO2.

scholarly journals Global modeling of organic aerosol: the importance of reactive nitrogen

2010 ◽  
Vol 10 (9) ◽  
pp. 21259-21301 ◽  
Author(s):  
H. O. T. Pye ◽  
A. W. H. Chan ◽  
M. P. Barkley ◽  
J. H. Seinfeld
Keyword(s):  
United States ◽  
Transport Model ◽  
Organic Aerosol ◽  
The United States ◽  
Oxidation Products ◽  
Reactive Nitrogen ◽  
Nitrate Radical ◽  
Chemical Transport Model ◽  
Radical Oxidation ◽  
High Volatility

Abstract. Reactive nitrogen compounds, specifically NOx and NO3, likely influence global organic aerosol levels. To assess these interactions, GEOS-Chem, a chemical transport model, is updated to include improved biogenic emissions (following MEGAN v2.1/2.04), a new organic aerosol tracer lumping scheme, aerosol from nitrate radical (NO3) oxidation of isoprene, and NOx-dependent terpene aerosol yields. As a result of significant nighttime terpene emissions, fast reaction of monoterpenes with the nitrate radical, and relatively high aerosol yields from NO3 oxidation, biogenic hydrocarbon-NO3 reactions are expected to be a major contributor to surface level aerosol concentrations in anthropogenically influenced areas such as the United States. By including aerosol from nitrate radical oxidation in GEOS-Chem, terpene aerosol approximately doubles and isoprene aerosol is enhanced by 30 to 40% in the Southeast United States. In terms of the global budget of organic aerosol, however, aerosol from nitrate radical oxidation is somewhat minor (slightly more than 3 Tg/yr) due to the relatively high volatility of organic-NO3 oxidation products. Globally, 69 to 88 Tg/yr of organic aerosol is predicted to be produced annually, of which 14–15 Tg/yr is from oxidation of monoterpenes and sesquiterpenes and 8–9 Tg/yr from isoprene.

scholarly journals Trends and spatial shifts in lightning fires and smoke concentrations in response to 21st century climate over the forests of the Western United States

2020 ◽  
Author(s):  
Yang Li ◽  
Loretta J. Mickley ◽  
Pengfei Liu ◽  
Jed O. Kaplan
Keyword(s):  
Climate Change ◽  
United States ◽  
21St Century ◽  
Transport Model ◽  
Fine Particulate Matter ◽  
The United States ◽  
Western United States ◽  
Fire Season ◽  
Future Climate Change ◽  
Chemical Transport Model

Abstract. Almost US$ 3bn per year is appropriated for wildfire management on public land in the United States. Recent studies have suggested that ongoing climate change will lead to warmer and drier conditions in the Western United States with a consequent increase in the number and size of wildfires, yet large uncertainty exists in these projections. To assess the influence of future changes in climate and land cover on lightning-caused wildfires in National Forests and Parks of the Western United States and the consequences of these fires on air quality, we link a dynamic vegetation model that includes a process-based representation of fire (LPJ-LMfire) to a global chemical transport model (GEOS-Chem). Under a scenario of moderate future climate change (RCP4.5), increasing lightning-caused wildfire enhances the burden of smoke fine particulate matter (PM), with mass concentration increases of ~ 53 % by the late-21st century during the fire season. In a high-emissions scenario (RCP8.5), smoke PM concentrations double by 2100. RCP8.5 also shows large, northward shifts in dry matter burned, leading to enhanced lightning-caused fire activity especially over forests in the northern states.

scholarly journals Interannual Variability of Ammonia Concentrations over the United States: Sources and Implications

2016 ◽  
Author(s):  
Luke D. Schiferl ◽  
Colette L. Heald ◽  
Martin Van Damme ◽  
Lieven Clarisse ◽  
Cathy Clerbaux ◽  
...  
Keyword(s):  
United States ◽  
Interannual Variability ◽  
Model Comparison ◽  
Transport Model ◽  
The United States ◽  
Ammonia Concentration ◽  
Phase Changes ◽  
Spatial And Temporal Variability ◽  
Ammonia Emissions ◽  
Chemical Transport Model

Abstract. The variability of atmospheric ammonia (NH3), emitted largely from agricultural sources, is an important factor when considering how inorganic fine particulate matter (PM2.5) concentrations and nitrogen cycling are changing over the United States. This study combines new observations of ammonia concentration from the surface, aboard aircraft, and retrieved by satellite to both evaluate the simulation of ammonia in a chemical transport model (GEOS-Chem) and identify which processes control the variability of these concentrations over a 5-year period (2008–2012). We find that the model generally underrepresents the ammonia concentration near large source regions and fails to reproduce the extent of interannual variability observed at the surface during the summer (JJA). Variability in the base simulation surface ammonia concentration is dominated by meteorology (64 %) as compared to reductions in SO2 and NOx emissions imposed by regulation (32 %) over this period. Introduction of year-to-year varying ammonia emissions based on animal population, fertilizer application, and meteorologically driven volatilization does not substantially improve the model comparison with observed ammonia concentrations, and these ammonia emissions changes have little effect on the simulated ammonia concentration variability compared to those caused by the variability of meteorology and acid-precursor emissions. There is also little effect on the PM2.5 concentration due to ammonia emissions variability in the summer when gas-phase changes are favored, but variability in wintertime emissions, as well as in early spring and late fall, will have a larger impact on PM2.5 formation. Further, this work highlights the need for continued improvement in both satellite-based and in situ ammonia measurements to better constrain the magnitude and impacts of spatial and temporal variability in ammonia concentrations.

scholarly journals Trends and spatial shifts in lightning fires and smoke concentrations in response to 21st century climate over the national forests and parks of the western United States

2020 ◽  
Vol 20 (14) ◽  
pp. 8827-8838
Author(s):  
Yang Li ◽  
Loretta J. Mickley ◽  
Pengfei Liu ◽  
Jed O. Kaplan
Keyword(s):  
Climate Change ◽  
United States ◽  
21St Century ◽  
Transport Model ◽  
The United States ◽  
Western United States ◽  
Fire Season ◽  
Future Climate Change ◽  
National Forests ◽  
Chemical Transport Model

Abstract. Almost USD 3 billion per year is appropriated for wildfire management on public land in the United States. Recent studies have suggested that ongoing climate change will lead to warmer and drier conditions in the western United States, with a consequent increase in the number and size of wildfires, yet large uncertainty exists in these projections. To assess the influence of future changes in climate and land cover on lightning-caused wildfires in the national forests and parks of the western United States and the consequences of these fires on air quality, we link a dynamic vegetation model that includes a process-based representation of fire (LPJ-LMfire) to a global chemical transport model (GEOS-Chem). Under a scenario of moderate future climate change (RCP4.5), increasing lightning-caused wildfire enhances the burden of smoke fine particulate matter (PM), with mass concentration increases of ∼53 % by the late 21st century during the fire season in the national forests and parks of the western United States. In a high-emissions scenario (RCP8.5), smoke PM concentrations double by 2100. RCP8.5 also shows enhanced lightning-caused fire activity, especially over forests in the northern states.

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