scholarly journals A mechanistic model of global soil nitric oxide emissions: implementation and space based-constraints

2012 ◽  
Vol 12 (2) ◽  
pp. 3555-3594 ◽  
Author(s):  
R. C. Hudman ◽  
N. E. Moore ◽  
R. V. Martin ◽  
A. R. Russell ◽  
A. K. Mebust ◽  
...  
Keyword(s):  
Great Plains ◽  
Transport Model ◽  
Mechanistic Model ◽  
Chemical Transport ◽  
The United States ◽  
Decay Length ◽  
Nox Emissions ◽  
Chemical Transport Model ◽  
Atmospheric N Deposition ◽  
Available Nitrogen

Abstract. Soil emissions have been identified as a major source (~15%) of global nitrogen oxide (NOx) emissions. Parameterizations of soil NOx emissions (SNOx) for use in the current generation of chemical transport models were designed to capture mean seasonal behaviour. These parameterizations do not, however, respond quantitatively to the meteorological triggers that result in pulsed SNOx as are widely observed. Here we present a new mechanistic parameterization of SNOx implemented into a global chemical transport model (GEOS-Chem). The parameterization represents available nitrogen (N) in soils using biome specific emission factors, online wet- and dry-deposition of N as well as fertilizer and manure N derived from a spatially explicit dataset distributed using seasonality derived from data obtained by the Moderate Resolution Imaging Spectrometer. Moreover, it represents the functional form of emissions derived from point measurements and ecosystem scale experiments including pulsing following soil wetting by rain or irrigation, and emissions that are a smooth function of soil moisture. This parameterization yields global above-soil SNOx of 10.7 Tg N yr−1, including 1.8 Tg N yr−1 from fertilizer N input (0.68% of applied N) and 0.5 Tg N yr−1 from atmospheric N deposition. Over the United States Great Plains, SNOx are predicted to comprise 15–40% of the tropospheric NO2 column and increase column variability by a factor of 2–4 during the summer months due to chemical fertilizer application and warm temperatures. SNOx enhancements of 50–80% of the simulated NO2 column are predicted over the African Sahel during the monsoon onset (April–June). In this region the day-to-day variability of column NO2 is increased by a factor of 5 due to pulsed-N emissions. We evaluate the model by comparison to observations of the NO2 column from the OMI instrument. We find the model is able to reproduce observations of pulsed-N induced interannual variability over the US Great Plains. We also show that the OMI mean (median) NO2 on the overpass following first rainfall over the Sahel is 49% (23%) higher than in the five days preceding. The measured NO2 on the day after rainfall is still 23% (5%) higher, providing a direct measure of the pulse's decay time of 1–2 days. This is consistent with the pulsing representation used in our parameterization and much shorter than 5–14 day pulse decay length used in current models.

scholarly journals Steps towards a mechanistic model of global soil nitric oxide emissions: implementation and space based-constraints

2012 ◽  
Vol 12 (16) ◽  
pp. 7779-7795 ◽  
Author(s):  
R. C. Hudman ◽  
N. E. Moore ◽  
A. K. Mebust ◽  
R. V. Martin ◽  
A. R. Russell ◽  
...  
Keyword(s):  
Great Plains ◽  
Transport Model ◽  
Mechanistic Model ◽  
Chemical Transport ◽  
The United States ◽  
Decay Length ◽  
Nox Emissions ◽  
Ozone Monitoring Instrument ◽  
Atmospheric N Deposition ◽  
Us Great Plains

Abstract. Soils have been identified as a major source (~15%) of global nitrogen oxide (NOx) emissions. Parameterizations of soil NOx emissions (SNOx) commonly used in the current generation of chemical transport models were designed to capture mean seasonal behaviour. These parameterizations do not, however, respond quantitatively to the meteorological triggers that are observed to result in pulsed SNOx. Here we present a new parameterization of SNOx implemented within a global chemical transport model (GEOS-Chem). The parameterization represents available nitrogen (N) in soils using biome specific emission factors, online wet- and dry-deposition of N, and fertilizer and manure N derived from a spatially explicit dataset, distributed using seasonality derived from data obtained by the Moderate Resolution Imaging Spectrometer. Moreover, it represents the functional form of emissions derived from point measurements and ecosystem scale experiments including pulsing following soil wetting by rain or irrigation, and emissions that are a smooth function of soil moisture as well as temperature between 0 and 30 °C. This parameterization yields global above-soil SNOx of 10.7 Tg N yr−1, including 1.8 Tg N yr−1 from fertilizer N input (1.5% of applied N) and 0.5 Tg N yr−1 from atmospheric N deposition. Over the United States (US) Great Plains region, SNOx are predicted to comprise 15–40% of the tropospheric NO2 column and increase column variability by a factor of 2–4 during the summer months due to chemical fertilizer application and warm temperatures. SNOx enhancements of 50–80% of the simulated NO2 column are predicted over the African Sahel during the monsoon onset (April–June). In this region the day-to-day variability of column NO2 is increased by a factor of 5 due to pulsed-N emissions. We evaluate the model by comparison with observations of NO2 column density from the Ozone Monitoring Instrument (OMI). We find that the model is able to reproduce the observed interannual variability of NO2 (induced by pulsed-N emissions) over the US Great Plains. We also show that the OMI mean (median) NO2 observed during the overpass following first rainfall over the Sahel is 49% (23%) higher than in the five days preceding. The measured NO2 on the day after rainfall is still 23% (5%) higher, providing a direct measure of the pulse's decay time of 1–2 days. This is consistent with the pulsing representation used in our parameterization and much shorter than 5–14 day pulse decay length used in current models.

scholarly journals Improving WRF-Chem meteorological analyses and forecasts over aerosol polluted regions by incorporating NAAPS aerosol analyses

2021 ◽  
Author(s):  
Brittany N. Carson-Marquis ◽  
Jianglong Zhang ◽  
Peng Xian ◽  
Jeffrey S. Reid ◽  
Jared Marquis
Keyword(s):  
Boundary Conditions ◽  
Surface Temperature ◽  
Great Plains ◽  
Transport Model ◽  
Weather Prediction ◽  
The United States ◽  
Northern Great Plains ◽  
Chemical Transport Model ◽  
Near Surface ◽  
Initial And Boundary Conditions

AbstractWhen unaccounted for in numerical weather prediction (NWP) models, heavy aerosol events can cause significant unrealized biases in forecasted meteorological parameters such as surface temperature. To improve near-surface forecasting accuracies during heavy aerosol loadings, we demonstrate the feasibility of incorporating aerosol fields from a global chemical transport model as initial and boundary conditions into a higher resolution NWP model with aerosol-meteorological coupling. This concept is tested for a major biomass burning smoke event over the Northern Great Plains region of the United States that occurred during summer of 2015. Aerosol analyses from the global Navy Aerosol Analysis and Prediction System (NAAPS) are used as initial and boundary conditions for Weather Research and Forecasting with Chemistry (WRF-Chem) simulations. Through incorporating more realistic aerosol direct effects into the WRF-Chem simulations, errors in WRF-Chem simulated surface downward shortwave radiative fluxes and near-surface temperature are reduced compared with surface-based observations. This study confirms the ability to decrease biases induced by the aerosol direct effect for regional NWP forecasts during high-impact aerosol episodes through the incorporation of analyses and forecasts from a global aerosol transport model.

scholarly journals The contribution of plume-scale nucleation to global and regional aerosol and CCN concentrations: evaluation and sensitivity to emissions changes

2014 ◽  
Vol 14 (24) ◽  
pp. 13661-13679 ◽  
Author(s):  
R. G. Stevens ◽  
J. R. Pierce
Keyword(s):  
Power Plant ◽  
Particle Number ◽  
Transport Model ◽  
Chemical Transport ◽  
Nox Emissions ◽  
Size Distributions ◽  
Chemical Transport Model ◽  
Global Chemical Transport Model ◽  
First Time ◽  
Particle Formation And Growth

Abstract. We implement the Predicting Particles Produced in Power-Plant Plumes (P6) sub-grid sulphate parameterization for the first time into a global chemical-transport model with online aerosol microphysics, the GEOS-Chem-TOMAS model. Compared to simulations using two other previous treatments of sub-grid sulphate, simulations using P6 sub-grid sulphate predicted similar or smaller increases (depending on other model assumptions) in globally, annually averaged concentrations of particles larger than 80 nm (N80). We test in simulations using P6 sub-grid sulphate the sensitivity of particle number concentrations to changes in SO2 or NOx emissions to represent recent emissions control changes. For global increases of 50% in emissions of either SO2 or NOx, or both SO2 and NOx, we find that globally, annually averaged N80 increase by 9.00, 1.47, or 10.24% respectively. However, both sub-grid and grid-resolved processes contribute to these changes. Finally, we compare the model results against observations of particle number concentrations. Compared with previous treatments of sub-grid sulphate, use of the P6 parameterization generally improves correlation with observed particle number concentrations. The P6 parameterization is able to resolve spatial heterogeneity in new-particle formation and growth that cannot be resolved by any constant assumptions about sub-grid sulphate. However, the differences in annually averaged aerosol size distributions due to the treatment of sub-grid sulphate at the measurement sites examined here are too small to unambiguously establish P6 as providing better agreement with observations.

scholarly journals The contribution of plume-scale nucleation to global and regional aerosol and CCN concentrations: evaluation and sensitivity to emissions changes

2014 ◽  
Vol 14 (15) ◽  
pp. 21473-21521 ◽  
Author(s):  
R. G. Stevens ◽  
J. R. Pierce
Keyword(s):  
Power Plant ◽  
Particle Number ◽  
Transport Model ◽  
Chemical Transport ◽  
Nox Emissions ◽  
Size Distributions ◽  
Chemical Transport Model ◽  
Global Chemical Transport Model ◽  
First Time ◽  
Particle Formation And Growth

Abstract. We implement the Predicting Particles Produced in Power-Plant Plumes (P6) sub-grid sulphate parameterization for the first time into a global chemical-transport model with online aerosol microphysics, the GEOS-Chem-TOMAS model. Compared to simulations using two other previous treatments of sub-grid sulphate, simulations using P6 sub-grid sulphate predicted similar or smaller increases (depending on other model assumptions) in globally, annually averaged concentrations of particles larger than 80 nm (N80). We test the sensitivity of particle number concentrations in simulations using P6 sub-grid sulphate to changes in SO2 or NOx emissions to represent recent emissions control changes. For global increases in emissions of SO2, NOx, or both SO2 and NOx by 50%, we find increases in globally, annually averaged N80 of 9.00%, 1.47%, or 10.24%, respectively; however, these changes include changes to both sub-grid and grid-resolved processes. Finally, we compare the model results against observations of particle number concentrations. Compared with previous treatments of sub-grid sulphate, use of the P6 parameterization generally improves correlation with observed particle number concentrations. The P6 parameterization is able to resolve spatial heterogeneity in new-particle formation and growth that cannot be resolved by any constant assumptions about sub-grid sulphate. However, the differences in annually averaged aerosol size distributions due to the treatment of sub-grid sulphate at the measurement sites examined here are too small to unambiguously establish P6 as providing better agreement with observations.

scholarly journals The UIUC three-dimensional stratospheric chemical transport model: Description and evaluation of the simulated source gases and ozone

1999 ◽  
Vol 104 (D9) ◽  
pp. 11755-11781 ◽  
Author(s):  
Eugene V. Rozanov ◽  
Vladimir A. Zubov ◽  
Michael E. Schlesinger ◽  
Fanglin Yang ◽  
Natalia G. Andronova
Keyword(s):  
Transport Model ◽  
Three Dimensional ◽  
Chemical Transport ◽  
Model Description ◽  
Chemical Transport Model ◽  
Simulated Source

scholarly journals Record-breaking ozone loss in the Arctic winter 2010/2011: comparison with 1996/1997

2012 ◽  
Vol 12 (15) ◽  
pp. 7073-7085 ◽  
Author(s):  
J. Kuttippurath ◽  
S. Godin-Beekmann ◽  
F. Lefèvre ◽  
G. Nikulin ◽  
M. L. Santee ◽  
...  
Keyword(s):  
Transport Model ◽  
Chemical Transport ◽  
The Arctic ◽  
Altitude Range ◽  
Chemical Transport Model ◽  
Model Simulations ◽  
Ozone Loss ◽  
Elevated Ozone ◽  
Record Value ◽  
First Time

Abstract. We present a detailed discussion of the chemical and dynamical processes in the Arctic winters 1996/1997 and 2010/2011 with high resolution chemical transport model (CTM) simulations and space-based observations. In the Arctic winter 2010/2011, the lower stratospheric minimum temperatures were below 195 K for a record period of time, from December to mid-April, and a strong and stable vortex was present during that period. Simulations with the Mimosa-Chim CTM show that the chemical ozone loss started in early January and progressed slowly to 1 ppmv (parts per million by volume) by late February. The loss intensified by early March and reached a record maximum of ~2.4 ppmv in the late March–early April period over a broad altitude range of 450–550 K. This coincides with elevated ozone loss rates of 2–4 ppbv sh−1 (parts per billion by volume/sunlit hour) and a contribution of about 30–55% and 30–35% from the ClO-ClO and ClO-BrO cycles, respectively, in late February and March. In addition, a contribution of 30–50% from the HOx cycle is also estimated in April. We also estimate a loss of about 0.7–1.2 ppmv contributed (75%) by the NOx cycle at 550–700 K. The ozone loss estimated in the partial column range of 350–550 K exhibits a record value of ~148 DU (Dobson Unit). This is the largest ozone loss ever estimated in the Arctic and is consistent with the remarkable chlorine activation and strong denitrification (40–50%) during the winter, as the modeled ClO shows ~1.8 ppbv in early January and ~1 ppbv in March at 450–550 K. These model results are in excellent agreement with those found from the Aura Microwave Limb Sounder observations. Our analyses also show that the ozone loss in 2010/2011 is close to that found in some Antarctic winters, for the first time in the observed history. Though the winter 1996/1997 was also very cold in March–April, the temperatures were higher in December–February, and, therefore, chlorine activation was moderate and ozone loss was average with about 1.2 ppmv at 475–550 K or 42 DU at 350–550 K, as diagnosed from the model simulations and measurements.

scholarly journals Meteorological modes of variability for fine particulate matter (PM2.5) air quality in the United States: implications for PM2.5 sensitivity to climate change

2012 ◽  
Vol 12 (6) ◽  
pp. 3131-3145 ◽  
Author(s):  
A. P. K. Tai ◽  
L. J. Mickley ◽  
D. J. Jacob ◽  
E. M. Leibensperger ◽  
L. Zhang ◽  
...  
Keyword(s):  
Climate Change ◽  
General Circulation ◽  
Transport Model ◽  
Circulation Model ◽  
Multiple Linear Regression Model ◽  
The United States ◽  
Chemical Transport Model ◽  
Modes Of Variability ◽  
The Us ◽  
Cyclone Frequency

Abstract. We applied a multiple linear regression model to understand the relationships of PM2.5 with meteorological variables in the contiguous US and from there to infer the sensitivity of PM2.5 to climate change. We used 2004–2008 PM2.5 observations from ~1000 sites (~200 sites for PM2.5 components) and compared to results from the GEOS-Chem chemical transport model (CTM). All data were deseasonalized to focus on synoptic-scale correlations. We find strong positive correlations of PM2.5 components with temperature in most of the US, except for nitrate in the Southeast where the correlation is negative. Relative humidity (RH) is generally positively correlated with sulfate and nitrate but negatively correlated with organic carbon. GEOS-Chem results indicate that most of the correlations of PM2.5 with temperature and RH do not arise from direct dependence but from covariation with synoptic transport. We applied principal component analysis and regression to identify the dominant meteorological modes controlling PM2.5 variability, and show that 20–40% of the observed PM2.5 day-to-day variability can be explained by a single dominant meteorological mode: cold frontal passages in the eastern US and maritime inflow in the West. These and other synoptic transport modes drive most of the overall correlations of PM2.5 with temperature and RH except in the Southeast. We show that interannual variability of PM2.5 in the US Midwest is strongly correlated with cyclone frequency as diagnosed from a spectral-autoregressive analysis of the dominant meteorological mode. An ensemble of five realizations of 1996–2050 climate change with the GISS general circulation model (GCM) using the same climate forcings shows inconsistent trends in cyclone frequency over the Midwest (including in sign), with a likely decrease in cyclone frequency implying an increase in PM2.5. Our results demonstrate the need for multiple GCM realizations (because of climate chaos) when diagnosing the effect of climate change on PM2.5, and suggest that analysis of meteorological modes of variability provides a computationally more affordable approach for this purpose than coupled GCM-CTM studies.

Sign in / Sign up

Export Citation Format

Share Document