scholarly journals Impact of the 2008 Global Recession on air quality over the United States: Implications for surface ozone levels from changes in NOxemissions

2016 ◽  
Vol 43 (17) ◽  
pp. 9280-9288 ◽  
Author(s):  
Daniel Tong ◽  
Li Pan ◽  
Weiwei Chen ◽  
Lok Lamsal ◽  
Pius Lee ◽  
...  
Keyword(s):  
United States ◽  
Air Quality ◽  
Surface Ozone ◽  
The United States ◽  
Global Recession ◽  
Ozone Levels

scholarly journals Linking global to regional models to assess future climate impacts on surface ozone levels in the United States

2008 ◽  
Vol 113 (D14) ◽  
Author(s):  
Christopher G. Nolte ◽  
Alice B. Gilliland ◽  
Christian Hogrefe ◽  
Loretta J. Mickley
Keyword(s):  
United States ◽  
Surface Ozone ◽  
The United States ◽  
Climate Impacts ◽  
Future Climate ◽  
Regional Models ◽  
Ozone Levels

scholarly journals The long-term trend and production sensitivity change in the US ozone pollution from observations and model simulations

2020 ◽  
Vol 20 (5) ◽  
pp. 3191-3208 ◽  
Author(s):  
Hao He ◽  
Xin-Zhong Liang ◽  
Chao Sun ◽  
Zhining Tao ◽  
Daniel Q. Tong
Keyword(s):  
United States ◽  
Air Quality ◽  
Surface Ozone ◽  
The United States ◽  
Early Morning ◽  
Ozone Pollution ◽  
Late Afternoon ◽  
The Past ◽  
The Us

Abstract. We investigated the ozone pollution trend and its sensitivity to key precursors from 1990 to 2015 in the United States using long-term EPA Air Quality System (AQS) observations and mesoscale simulations. The modeling system, a coupled regional climate–air quality model (CWRF-CMAQ; Climate-Weather Research Forecast and the Community Multiscale Air Quality), captured well the summer surface ozone pollution during the past decades, having a mean slope of linear regression with AQS observations of ∼0.75. While the AQS network has limited spatial coverage and measures only a few key chemical species, CWRF-CMAQ provides comprehensive simulations to enable a more rigorous study of the change in ozone pollution and chemical sensitivity. Analysis of seasonal variations and diurnal cycle of ozone observations showed that peak ozone concentrations in the summer afternoon decreased ubiquitously across the United States, up to 0.5 ppbv yr−1 in major non-attainment areas such as Los Angeles, while concentrations at certain hours such as the early morning and late afternoon increased slightly. Consistent with the AQS observations, CMAQ simulated a similar decreasing trend of peak ozone concentrations in the afternoon, up to 0.4 ppbv yr−1, and increasing ozone trends in the early morning and late afternoon. A monotonically decreasing trend (up to 0.5 ppbv yr−1) in the odd oxygen (Ox=O3+NO2) concentrations are simulated by CMAQ at all daytime hours. This result suggests that the increased ozone in the early morning and late afternoon was likely caused by reduced NO–O3 titration, driven by continuous anthropogenic NOx emission reductions in the past decades. Furthermore, the CMAQ simulations revealed a shift in chemical regimes of ozone photochemical production. From 1990 to 2015, surface ozone production in some metropolitan areas, such as Baltimore, has transited from a VOC-sensitive environment (>50 % probability) to a NOx-sensitive regime. Our results demonstrated that the long-term CWRF-CMAQ simulations can provide detailed information of the ozone chemistry evolution under a changing climate and may partially explain the US ozone pollution responses to regional and national regulations.

Characterizing long-term changes in surface ozone levels in the United States (1980–2005)

2008 ◽  
Vol 42 (35) ◽  
pp. 8252-8262 ◽  
Author(s):  
Allen S. Lefohn ◽  
Douglas Shadwick ◽  
Samuel J. Oltmans
Keyword(s):  
United States ◽  
Surface Ozone ◽  
The United States ◽  
Long Term Changes ◽  
Ozone Levels

scholarly journals Variability in surface ozone background over the United States: Implications for air quality policy

2003 ◽  
Vol 108 (D24) ◽  
pp. n/a-n/a ◽  
Author(s):  
A. Fiore ◽  
D. J. Jacob ◽  
H. Liu ◽  
R. M. Yantosca ◽  
T. D. Fairlie ◽  
...  
Keyword(s):  
United States ◽  
Air Quality ◽  
Surface Ozone ◽  
The United States ◽  
Quality Policy

Correction to “Variability in surface ozone background over the United States: Implications for air quality policy”

2004 ◽  
Vol 109 (D4) ◽  
pp. n/a-n/a ◽  
Author(s):  
A. Fiore ◽  
D. J. Jacob ◽  
H. Liu ◽  
R. M. Yantosca ◽  
T. D. Fairlie ◽  
...  
Keyword(s):  
United States ◽  
Air Quality ◽  
Surface Ozone ◽  
The United States ◽  
Quality Policy

scholarly journals Impact of lightning-NO on eastern United States photochemistry during the summer of 2006 as determined using the CMAQ model

2012 ◽  
Vol 12 (4) ◽  
pp. 1737-1758 ◽  
Author(s):  
D. J. Allen ◽  
K. E. Pickering ◽  
R. W. Pinder ◽  
B. H. Henderson ◽  
K. W. Appel ◽  
...  
Keyword(s):  
United States ◽  
Air Quality ◽  
Wet Deposition ◽  
Surface Ozone ◽  
The United States ◽  
South Central ◽  
Southeastern Us ◽  
The Mean ◽  
The Impact ◽  
No Emissions

Abstract. A lightning-nitrogen oxide (NO) algorithm is implemented in the Community Multiscale Air Quality Model (CMAQ) and used to evaluate the impact of lightning-NO emissions (LNOx) on tropospheric photochemistry over the United States during the summer of 2006. For a 500 mole per flash lightning-NO source, the mean summertime tropospheric NO2 column agrees with satellite-retrieved columns to within −5 to +13%. Temporal fluctuations in the column are moderately well simulated; however, the addition of LNOx does not lead to a better simulation of day-to-day variability. The contribution of lightning-NO to the model column ranges from ∼10% in the northern US to >45% in the south-central and southeastern US. Lightning-NO adds up to 20 ppbv to upper tropospheric model ozone and 1.5–4.5 ppbv to 8-h maximum surface layer ozone, although, on average, the contribution of LNOx to model surface ozone is 1–2 ppbv less on poor air quality days. LNOx increases wet deposition of oxidized nitrogen by 43% and total deposition of nitrogen by 10%. This additional deposition reduces the mean magnitude of the CMAQ low-bias in nitrate wet deposition with respect to National Atmospheric Deposition monitors to near zero. Differences in urban/rural biases between model and satellite-retrieved NO2 columns were examined to identify possible problems in model chemistry and/or transport. CMAQ columns were too large over urban areas. Biases at other locations were minor after accounting for the impacts of lightning-NO emissions and the averaging kernel on model columns. In order to obtain an upper bound on the contribution of uncertainties in NOy chemistry to upper tropospheric NOx low biases, sensitivity calculations with updated chemistry were run for the time period of the Intercontinental Chemical Transport Experiment (INTEX-A) field campaign (summer 2004). After adjusting for possible interferences in NO2 measurements and averaging over the entire campaign, these updates reduced 7–9 km biases from 32 to 17% and 9–12 km biases from 57 to 46%. While these changes lead to better agreement, a considerable unexplained NO2 low-bias remains in the uppermost troposphere.

Improving Air Quality Predictions over the United States with an Analog Ensemble

2020 ◽  
Vol 35 (5) ◽  
pp. 2145-2162 ◽  
Author(s):  
Luca Delle Monache ◽  
Stefano Alessandrini ◽  
Irina Djalalova ◽  
James Wilczak ◽  
Jason C. Knievel ◽  
...  
Keyword(s):  
United States ◽  
Air Quality ◽  
Surface Ozone ◽  
The United States ◽  
Lead Times ◽  
Random Errors ◽  
Probabilistic Forecasts ◽  
Dynamical Method ◽  
First Time ◽  
Air Quality Forecasting

AbstractAir quality forecasts produced by the National Air Quality Forecasting Capability (NAQFC) help air quality forecasters across the United States in making informed decisions to protect public health from acute air pollution episodes. However, errors in air quality forecasts limit their value in the decision-making process. This study aims to enhance the accuracy of NAQFC air quality forecasts and reliably quantify their uncertainties using a statistical–dynamical method called the analog ensemble (AnEn), which has previously been found to efficiently generate probabilistic forecasts for other applications. AnEn estimates of the probability of the true state of a predictand are based on a current deterministic numerical prediction and an archive of prior analogous predictions paired with prior observations. The method avoids the complexity and real-time computational expense of model-based ensembles and is proposed here for the first time for air quality forecasting. AnEn is applied with forecasts from the Community Multiscale Air Quality (CMAQ) model. Relative to CMAQ raw forecasts, deterministic forecasts of surface ozone (O3) and particulate matter of aerodynamic diameter smaller than 2.5 μm (PM2.5) based on AnEn’s mean have lower systemic and random errors and are overall better correlated with observations; for example, when computed across all sites and lead times, AnEn’s root-mean-square error is lower than CMAQ’s by roughly 35% and 30% for O3 and PM2.5, respectively, and AnEn improves the correlation by 50% for O3 and PM2.5. Probabilistic forecasts from AnEn are statistically consistent, reliable, and sharp, and they quantify the uncertainty of the underlying prediction.

Urban form and air quality in the United States

2015 ◽  
Vol 139 ◽  
pp. 168-179 ◽  
Author(s):  
Joshua McCarty ◽  
Nikhil Kaza
Keyword(s):  
United States ◽  
Air Quality ◽  
Urban Form ◽  
The United States
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