scholarly journals Nitrogen deposition to the United States: distribution, sources, and processes

2012 ◽  
Vol 12 (10) ◽  
pp. 4539-4554 ◽  
Author(s):  
L. Zhang ◽  
D. J. Jacob ◽  
E. M. Knipping ◽  
N. Kumar ◽  
J. W. Munger ◽  
...  
Keyword(s):  
Nitrogen Deposition ◽  
Total Nitrogen ◽  
Transport Model ◽  
The United States ◽  
Horizontal Resolution ◽  
Deposition Flux ◽  
Chemical Transport Model ◽  
The West ◽  
Deposition Fluxes ◽  
The Us

Abstract. We simulate nitrogen deposition over the US in 2006–2008 by using the GEOS-Chem global chemical transport model at 1/2°×2/3° horizontal resolution over North America and adjacent oceans. US emissions of NOx and NH3 in the model are 6.7 and 2.9 Tg N a−1 respectively, including a 20% natural contribution for each. Ammonia emissions are a factor of 3 lower in winter than summer, providing a good match to US network observations of NHx (≡NH3 gas + ammonium aerosol) and ammonium wet deposition fluxes. Model comparisons to observed deposition fluxes and surface air concentrations of oxidized nitrogen species (NOy) show overall good agreement but excessive wintertime HNO3 production over the US Midwest and Northeast. This suggests a model overestimate N2O5 hydrolysis in aerosols, and a possible factor is inhibition by aerosol nitrate. Model results indicate a total nitrogen deposition flux of 6.5 Tg N a−1 over the contiguous US, including 4.2 as NOy and 2.3 as NHx. Domestic anthropogenic, foreign anthropogenic, and natural sources contribute respectively 78%, 6%, and 16% of total nitrogen deposition over the contiguous US in the model. The domestic anthropogenic contribution generally exceeds 70% in the east and in populated areas of the west, and is typically 50–70% in remote areas of the west. Total nitrogen deposition in the model exceeds 10 kg N ha−1 a−1 over 35% of the contiguous US.

scholarly journals Nitrogen deposition to the United States: distribution, sources, and processes

2012 ◽  
Vol 12 (1) ◽  
pp. 241-282 ◽  
Author(s):  
L. Zhang ◽  
D. J. Jacob ◽  
E. M. Knipping ◽  
N. Kumar ◽  
J. W. Munger ◽  
...  
Keyword(s):  
Nitrogen Deposition ◽  
Total Nitrogen ◽  
Transport Model ◽  
The United States ◽  
Horizontal Resolution ◽  
Deposition Flux ◽  
Chemical Transport Model ◽  
The West ◽  
Deposition Fluxes ◽  
The Us

Abstract. We simulate nitrogen deposition over the US in 2006–2008 by using the GEOS-Chem global chemical transport model at 1/2° × 2/3° horizontal resolution over North America and adjacent oceans. US emissions of NOx and NH3 in the model are 6.7 and 2.9 Tg N a−1 respectively, including a 20% natural contribution for each. Ammonia emissions are a factor of 3 lower in winter than summer, providing a good match to US network observations of NHx (≡NH3 gas + ammonium aerosol) and ammonium wet deposition fluxes. Model comparisons to observed deposition fluxes and surface air concentrations of oxidized nitrogen species (NOy) show overall good agreement but excessive wintertime HNO3 production over the US Midwest and Northeast. This suggests a model overestimate N2O5 hydrolysis in aerosols, and a possible factor is inhibition by aerosol nitrate. Model results indicate a total nitrogen deposition flux of 6.5 Tg N a−1 over the contiguous US, including 4.2 as NOy and 2.3 as NHx. Domestic anthropogenic, foreign anthropogenic, and natural sources contribute respectively 78%, 6%, and 16% of total nitrogen deposition over the contiguous US in the model. The domestic anthropogenic contribution generally exceeds 70% in the east and in populated areas of the west, and is typically 50–70% in remote areas of the west. Total nitrogen deposition in the model exceeds 10 kg N ha−1 a−1 over 35% of the contiguous US.

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.

scholarly journals Sources contributing to background surface ozone in the US Intermountain West

2014 ◽  
Vol 14 (11) ◽  
pp. 5295-5309 ◽  
Author(s):  
L. Zhang ◽  
D. J. Jacob ◽  
X. Yue ◽  
N. V. Downey ◽  
D. A. Wood ◽  
...  
Keyword(s):  
Transport Model ◽  
Stratospheric Ozone ◽  
Surface Ozone ◽  
Horizontal Resolution ◽  
Ozone Production ◽  
Intermountain West ◽  
Chemical Transport Model ◽  
Ozone Concentrations ◽  
The Us ◽  
Stratospheric Intrusions

Abstract. We quantify the sources contributing to background surface ozone concentrations in the US Intermountain West by using the GEOS-Chem chemical transport model with 1 / 2° × 2 / 3° horizontal resolution to interpret the Clean Air Status and Trends Network (CASTNet) ozone monitoring data for 2006–2008. We isolate contributions from lightning, wildfires, the stratosphere, and California pollution. Lightning emissions are constrained by observations and wildfire emissions are estimated from daily fire reports. We find that lightning increases mean surface ozone in summer by 10 ppbv in the Intermountain West, with moderate variability. Wildfire plumes generate high-ozone events in excess of 80 ppbv in GEOS-Chem, but CASTNet ozone observations in the Intermountain West show no enhancements during these events nor do they show evidence of regional fire influence. Models may overestimate ozone production in fresh fire plumes because of inadequate chemistry and grid-scale resolution. The highest ozone concentrations observed in the Intermountain West (> 75 ppbv) in spring are associated with stratospheric intrusions. The model captures the timing of these intrusions but not their magnitude, reflecting numerical diffusion intrinsic to Eulerian models. This can be corrected statistically through a relationship between model bias and the model-diagnosed magnitude of stratospheric influence; with this correction, models may still be useful to forecast and interpret high-ozone events from stratospheric intrusions. We show that discrepancy between models in diagnosing stratospheric influence is due in part to differences in definition, i.e., whether stratospheric ozone is diagnosed as produced in the stratosphere (GEOS-Chem definition) or as transported from above the tropopause. The latter definition can double the diagnosed stratospheric influence in surface air by labeling as "stratospheric" any ozone produced in the troposphere and temporarily transported to the stratosphere. California pollution influence in the Intermountain West frequently exceeds 10 ppbv but is generally not correlated with the highest ozone events.

scholarly journals Simulation of nitrate, sulfate, and ammonium aerosols over the United States

2012 ◽  
Vol 12 (8) ◽  
pp. 19499-19527 ◽  
Author(s):  
J. M. Walker ◽  
J. H. Seinfeld ◽  
L. Clarisse ◽  
P.-F. Coheur ◽  
C. Clerbaux ◽  
...  
Keyword(s):  
United States ◽  
Emission Inventory ◽  
Transport Model ◽  
The United States ◽  
Ammonia Emission ◽  
Chemical Transport Model ◽  
Emissions Inventory ◽  
Nh3 Emission ◽  
The Us ◽  
Nitrate Aerosol

Abstract. Atmospheric concentrations of inorganic gases and aerosols (nitrate, sulfate, and ammonium) are simulated for 2009 over the United States using the chemical transport model GEOS-Chem. This work is motivated, in part, by the inability of previous modeling studies to reproduce observed high nitrate aerosol concentrations in California. Nitrate aerosol concentrations over most of the US are over-predicted relative to Interagency Monitoring of Protected Visual Environments (IMPROVE) and Clean Air Status and Trends Network (CASTNET) data. In California, on the other hand, nitrate and ammonium are under-predicted as compared to California Air Resources Board (CARB) measurements. Over-prediction of nitrate in the East and Midwest is consistent with results of recent studies, which have suggested that nighttime nitric acid formation by heterogeneous hydrolysis of N2O5 is over-predicted with current values of the N2O5 uptake coefficient, γ, onto aerosols. Accordingly, the value of γ is reduced here by a factor of 10. Despite this, predicted nitrate levels in the US Midwest remain higher than those measured and over-prediction of nitrate in this region remains to be explained. Data from the Infrared Atmospheric Sounding Interferometer (IASI) onboard the MetOp-A satellite indicate the presence of a strong ammonia maximum in central and southern California that is not present in the simulations, which are based on the EPA National Emissions Inventory (NEI) NH3 emission inventory. In order to predict ammonia columns similar to the satellite measurements in the San Joaquin Valley, CA and Riverside, CA, the current ammonia emission inventory in California would need to be increased substantially. Based on the sensitivity of ammonium nitrate formation to the availability of ammonia, the present results suggest that under-prediction of ammonia emissions is likely the main cause for the under-prediction of nitrate aerosol in California.

scholarly journals Sources contributing to background surface ozone in the US Intermountain West

2013 ◽  
Vol 13 (10) ◽  
pp. 25871-25909
Author(s):  
L. Zhang ◽  
D. J. Jacob ◽  
X. Yue ◽  
N. V. Downey ◽  
D. A. Wood ◽  
...  
Keyword(s):  
Transport Model ◽  
Stratospheric Ozone ◽  
Surface Ozone ◽  
Horizontal Resolution ◽  
Intermountain West ◽  
Chemical Transport Model ◽  
Fire Plume ◽  
Ozone Concentrations ◽  
The Us ◽  
Stratospheric Intrusions

Abstract. We quantify the sources contributing to background surface ozone concentrations in the US Intermountain West by using the GEOS-Chem chemical transport model with 1/2° × 2/3° horizontal resolution to interpret CASTNet ozone monitoring data for 2006–2008. We isolate contributions from lightning, wildfires, the stratosphere, and California pollution. Lightning increases mean surface ozone in summer by 10 ppbv in the Intermountain West, with moderate variability; constraining the model source with flash rate observations is important. Using a daily wildfire inventory compiled from fire reports in the western US generates high-ozone events in excess of 80 ppbv in GEOS-Chem. The CASTNet observations show no evidence of such events. Models in general may overestimate ozone concentrations in fresh plumes because of inadequate fire plume chemistry. The highest ozone concentrations observed in the Intermountain West (>75 ppbv) in spring are associated with stratospheric intrusions. The model captures the timing of these intrusions but not their magnitude, reflecting numerical diffusion intrinsic to Eulerian models. This can be corrected statistically through a relationship between model bias and the model-diagnosed magnitude of stratospheric influence; with this correction, models may still be useful to forecast and interpret high-ozone events from stratospheric intrusions. We show that discrepancy between models in diagnosing stratospheric influence is due in part to differences in definition, i.e., whether stratospheric ozone is diagnosed as produced in the stratosphere (GEOS-Chem definition) or as transported from above the tropopause. The latter definition can double the diagnosed stratospheric influence in surface air by labeling as "stratospheric" any ozone produced in the troposphere and temporarily transported to the stratosphere. California pollution influence in the Intermountain West frequently exceeds 10 ppbv but is generally not correlated with the highest ozone events.

scholarly journals Meteorological modes of variability for fine particulate matter (PM<sub>2.5</sub>) air quality in the United States: implications for PM<sub>2.5</sub> sensitivity to climate change

2011 ◽  
Vol 11 (11) ◽  
pp. 31031-31066 ◽  
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.

The Communist Contest for Status

2019 ◽  
pp. 82-133
Author(s):  
Deborah Welch Larson ◽  
Alexei Shevchenko
Keyword(s):  
Soviet Union ◽  
The United States ◽  
Social Competition ◽  
The West ◽  
Republic Of China ◽  
The Soviet Union ◽  
Economic Production ◽  
Communist Ideology ◽  
The Us ◽  
Catch Up

This chapter argues that both the Soviet Union and the People's Republic of China (PRC) pursued social competition with the Western states while at the same time seeking recognition from the states they were trying to subvert. Stalin sought to increase the power and prestige of the Soviet state through coerced industrialization, and Khrushchev made an effort to “catch up and surpass” the West in economic production. The PRC sought to improve its status by allying with the Soviet Union, but the Chinese chafed under their status as “younger brothers” to their senior ally, and eventually Mao challenged the Soviets for leadership of the international communist movement. In the 1970s, China took advantage of the US need to balance Soviet military power by putting aside communist ideology to become a tacit ally of the United States, part of a “strategic triangle.”

scholarly journals Evaluation of chemical transport model predictions of primary organic aerosol for air masses classified by particle-component-based factor analysis

2012 ◽  
Vol 12 (2) ◽  
pp. 5939-6018
Author(s):  
C. A. Stroud ◽  
M. D. Moran ◽  
P. A. Makar ◽  
S. Gong ◽  
W. Gong ◽  
...  
Keyword(s):  
Factor Analysis ◽  
Transport Model ◽  
Chemical Transport ◽  
Organic Aerosol ◽  
Point Sources ◽  
Urban Site ◽  
Stable Model ◽  
Chemical Transport Model ◽  
The Us ◽  
Model Predictions

Abstract. Observations from the 2007 Border Air Quality and Meteorology Study (BAQS-Met 2007) in southern Ontario (ON), Canada, were used to evaluate Environment Canada's regional chemical transport model predictions of primary organic aerosol (POA). Environment Canada's operational numerical weather prediction model and the 2006 Canadian and 2005 US national emissions inventories were used as input to the chemical transport model (named AURAMS). Particle-component-based factor analysis was applied to aerosol mass spectrometer measurements made at one urban site (Windsor, ON) and two rural sites (Harrow and Bear Creek, ON) to derive hydrocarbon-like organic aerosol (HOA) factors. Co-located carbon monoxide (CO), PM2.5 black carbon (BC), and PM1 SO4 measurements were also used for evaluation and interpretation, permitting a detailed diagnostic model evaluation. At the urban site, good agreement was observed for the comparison of daytime campaign PM1 POA and HOA mean values: 1.1 μg m−3 vs. 1.2 μg m−3, respectively. However, a POA overprediction was evident on calm nights due to an overly-stable model surface layer. Biases in model POA predictions trended from positive to negative with increasing HOA values. This trend has several possible explanations, including (1) underweighting of urban locations in particulate matter (PM) spatial surrogate fields, (2) overly-coarse model grid spacing for resolving urban-scale sources, and (3) lack of a model particle POA evaporation process during dilution of vehicular POA tail-pipe emissions to urban scales. Furthermore, a trend in POA bias was observed at the urban site as a function of the BC/HOA ratio, suggesting a possible association of POA underprediction for diesel combustion sources. For several time periods, POA overprediction was also observed for sulphate-rich plumes, suggesting that our model POA fractions for the PM2.5 chemical speciation profiles may be too high for these point sources. At the rural Harrow site, significant underpredictions in PM1 POA concentration were found compared to observed HOA concentration and were associated, based on back-trajectory analysis, with (1) transport from the Detroit/Windsor urban complex, (2) longer-range transport from the US Midwest, and (3) biomass burning. Daytime CO concentrations were significantly overpredicted at Windsor but were unbiased at Harrow. Collectively, these biases provide support for a hypothesis that combines a current underweighting of PM spatial surrogate fields for urban locations with insufficient model vertical mixing for sources close to the urban measurement sites. The magnitude of the area POA emissions sources in the US and Canadian inventories (e.g., food cooking, road and soil dust, waste disposal burning) suggests that more effort should be placed at reducing uncertainties in these sectors, especially spatial and temporal surrogates.

scholarly journals A three-dimensional model study of long-term mid-high latitude lower stratosphere ozone changes

2003 ◽  
Vol 3 (1) ◽  
pp. 1081-1107 ◽  
Author(s):  
M. P. Chipperfield
Keyword(s):  
High Latitude ◽  
Lower Stratosphere ◽  
Transport Model ◽  
Three Dimensional ◽  
Horizontal Resolution ◽  
Chemical Transport Model ◽  
Three Dimensional Model ◽  
Detailed Chemistry ◽  
Basic Model ◽  
Column Ozone

Abstract. We have used a 3D off-line chemical transport model (CTM) to study the causes of the observed changes in ozone in the mid-high latitude lower stratosphere from 1979–1998. The model was forced by European Centre for Medium Range Weather Forecasts (ECMWF) analyses and contains a detailed chemistry scheme. A series of model runs were performed at a horizontal resolution of 7.5°×7.5° and covered the domain from about 12 km to 30 km. The basic model performs well in reproducing the decadal evolution of the springtime depletion in the northern hemisphere (NH) and southern hemisphere (SH) high latitudes in the 1980s and early 1990s. After about 1994 the modelled interannual variability does not match the observations as well, which is probably due in part to changes in the operational ECMWF analyses – which places limits on using this dataset to diagnose dynamical trends. For mid-latitudes (35°–60°) the basic model reproduces the observed column ozone decreases from 1980 until the early 1990s. Model experiments show that the halogen trends appear to dominate this modelled decrease and of this around 30–50% is due to high-latitude processing on polar stratospheric clouds (PSCs). Dynamically induced ozone variations in the model correlate with observations over the timescale of a few years. Large discrepancies between the modelled and observed variations in the mid 1980s and mid 1990s can be largely resolved by assuming that the 11-year solar cycle (not explicitly included in the 3D model) causes a 2% (min-max) change in mid-latitude column ozone.

scholarly journals Go West: surgical fellowships in the US

2008 ◽  
Vol 90 (8) ◽  
pp. 272-274
Author(s):  
Matt Freudmann ◽  
Lucy Wales
Keyword(s):  
United States ◽  
Vascular Surgery ◽  
Surgical Training ◽  
The United States ◽  
University Of Minnesota ◽  
The West ◽  
Transplant Centre ◽  
Transplant Center ◽  
The Us ◽  
The University

As a final-year trainee in vascular surgery, I was working at the West London Renal and Transplant Centre for Professor Nadey Hakim and Vassilios Papalois. I am very grateful to both of them for encouraging me to apply for a visiting fellowship to the United States, enabling me to experience some of the benefits of surgical training abroad and to broaden my perspectives in transplantation. I was awarded a visiting fellowship to the University of Minnesota Transplant Center by Professor David Sutherland, head of the division of transplant surgery.

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