Impact of high-resolution sea surface temperature, emission spikes and wind on simulated surface ozone in Houston, Texas during a high ozone episode

Pan, Shuai; Choi, Yunsoo; Jeon, Wonbae; Roy, Anirban; Westenbarger, David A.; Kim, Hyun Cheol

doi:10.1016/j.atmosenv.2016.12.030

Cited by 24 publications

(17 citation statements)

References 31 publications

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“…Wind direction shifts caused variation of other meteorological factors and overshadowed their effects on O 3 . Independent high O 3 incidents related to cold fronts over the HGB area were studied in previous works [13][14][15][16][17][18][19][20]. The usual explanations for increased O 3 involved air mass stagnation, under cloud free conditions caused by wind direction shifts.…”

Section: Discussionmentioning

confidence: 99%

“…The northern trajectory percentages were still more than 30% after 72 h the cold front reached the HGB area. It suggests that the influence might be sustained more than 72 h. [16,17,25]. We chose 15:00 CST since the meteorological data is at 3-h interval.…”

Section: Event Days Definitionsmentioning

confidence: 99%

“…days. Since high O 3 events have been reported after cold front passes [14][15][16][17], post frontal day should be treated as a separate event as well. A post frontal day was defined as the day on which no cold front line passed the HGB area, but the previous day was a cold front day.…”

Section: Event Days Definitionsmentioning

confidence: 99%

“…To date, most of the researches on the influence of cold fronts on surface O 3 over the HGB have focused on a single or several cold front events [13][14][15][16][17][18][19][20]. The long-term effect and its mechanism remain unknown.…”

Section: Introductionmentioning

confidence: 99%

“…Li et al [16] used surface and aircraft data to validate that observational nudging helped the model yield improved O 3 predictions during a post frontal high O 3 event on 25 September in Houston by reproducing the wind shifts which missed by base case. Pan et al [17] hypothesized that episodic flare emissions, under dry sunny post frontal stagnated conditions, and land-bay/sea breeze transitions could be a potential cause of high O 3 .…”

Section: Introductionmentioning

confidence: 99%

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Influence of Cold Fronts on Variability of Daily Surface O3 over the Houston-Galveston-Brazoria Area in Texas USA during 2003–2016

et al. 2018

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Abstract:We investigated the impacts of cold fronts on area-wide peak O 3 and regional background O 3 mixing ratios on a daily scale over the Houston-Galveston-Brazoria (HGB) area of southeastern Texas during the O 3 seasons (April-October) of [2003][2004][2005][2006][2007][2008][2009][2010][2011][2012][2013][2014][2015][2016]. Back trajectories showed that an 18h time lag existed between arrival of cold fronts in the HGB area and onset of a predominately northerly flow. Cold fronts showed increasing effects on both peak and background O 3 over the HGB area. Compared to no front days, average peak O 3 mixing ratios during the cold front 1st days, cold front 2+ days, and post frontal days increased 0.7, 5.9, and 9.0 ppbv, respectively while average background O 3 increased 2.9, 6.8, and 8.6 ppbv, respectively. The change in wind direction from southerly to northerly was the most important factor causing increasing O 3 levels. Wind direction shifts caused variation of other meteorological factors (i.e., wind speed, precipitation, temperature, cloud cover, and relative humidity) and tended to overshadow their effects on O 3 over the HGB area. On a long-term and large-scale view, cold fronts over the HGB area could be regarded as interruptions in the cleansing effects of predominantly marine southerly flow from the Gulf of Mexico.

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Section: Discussionmentioning

confidence: 99%

Section: Event Days Definitionsmentioning

confidence: 99%

Section: Event Days Definitionsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Influence of Cold Fronts on Variability of Daily Surface O3 over the Houston-Galveston-Brazoria Area in Texas USA during 2003–2016

et al. 2018

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First Top‐Down Estimates of Anthropogenic NO_x Emissions Using High‐Resolution Airborne Remote Sensing Observations

et al. 2018

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A number of satellite‐based instruments have become an essential part of monitoring emissions. Despite sound theoretical inversion techniques, the insufficient samples and the footprint size of current observations have introduced an obstacle to narrow the inversion window for regional models. These key limitations can be partially resolved by a set of modest high‐quality measurements from airborne remote sensing. This study illustrates the feasibility of nitrogen dioxide (NO2) columns from the Geostationary Coastal and Air Pollution Events Airborne Simulator (GCAS) to constrain anthropogenic NOx emissions in the Houston‐Galveston‐Brazoria area. We convert slant column densities to vertical columns using a radiative transfer model with (i) NO2 profiles from a high‐resolution regional model (1 × 1 km2) constrained by P‐3B aircraft measurements, (ii) the consideration of aerosol optical thickness impacts on radiance at NO2 absorption line, and (iii) high‐resolution surface albedo constrained by ground‐based spectrometers. We characterize errors in the GCAS NO2 columns by comparing them to Pandora measurements and find a striking correlation (r > 0.74) with an uncertainty of 3.5 × 1015 molecules cm−2. On 9 of 10 total days, the constrained anthropogenic emissions by a Kalman filter yield an overall 2–50% reduction in polluted areas, partly counterbalancing the well‐documented positive bias of the model. The inversion, however, boosts emissions by 94% in the same areas on a day when an unprecedented local emissions event potentially occurred, significantly mitigating the bias of the model. The capability of GCAS at detecting such an event ensures the significance of forthcoming geostationary satellites for timely estimates of top‐down emissions.

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A real-time hourly ozone prediction system using deep convolutional neural network

Eslami

Choi

Lops

et al. 2019

Neural Comput & Applic

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This study uses a deep learning approach to forecast ozone concentrations over Seoul, South Korea for 2017. We employ a deep convolutional neural network (CNN). We apply this method to predict the hourly ozone concentration on each day for the entire year using several predictors from the previous day, including the wind fields, temperature, relative humidity, pressure, and precipitation, along with in-situ ozone and NO2 concentrations. We refer to a history of all observed parameters between 2014 and 2016 for training the predictive models. Model-measurement comparisons for the 25 monitoring sites for the year 2017 report average indexes of agreement (IOA) of 0.84-0.89 and a Pearson correlation coefficient of 0.74-0.81, indicating reasonable performance for the CNN forecasting model. Although the CNN model successfully captures daily trends as well as yearly high and low variations of the ozone concentrations, it notably underpredicts high ozone peaks during the summer. The forecasting results are generally more accurate for the stations located in the southern regions of the Han River, the result of more stable topographical and meteorological conditions. Furthermore, through two separate daytime and nighttime forecasts, we find that the monthly IOA of the CNN model is 0.05-0.30 higher during the daytime, resulting from the unavailability of some of the input parameters during the nighttime. While the CNN model can predict the next 24 hours of ozone concentrations within less than a minute, we identify several limitations of deep learning models for real-time air quality forecasting for further improvement.

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Impact of high-resolution sea surface temperature, emission spikes and wind on simulated surface ozone in Houston, Texas during a high ozone episode

Cited by 24 publications

References 31 publications

Influence of Cold Fronts on Variability of Daily Surface O3 over the Houston-Galveston-Brazoria Area in Texas USA during 2003–2016

Influence of Cold Fronts on Variability of Daily Surface O3 over the Houston-Galveston-Brazoria Area in Texas USA during 2003–2016

First Top‐Down Estimates of Anthropogenic NO_x Emissions Using High‐Resolution Airborne Remote Sensing Observations

A real-time hourly ozone prediction system using deep convolutional neural network

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Impact of high-resolution sea surface temperature, emission spikes and wind on simulated surface ozone in Houston, Texas during a high ozone episode

Cited by 24 publications

References 31 publications

Influence of Cold Fronts on Variability of Daily Surface O3 over the Houston-Galveston-Brazoria Area in Texas USA during 2003–2016

Influence of Cold Fronts on Variability of Daily Surface O3 over the Houston-Galveston-Brazoria Area in Texas USA during 2003–2016

First Top‐Down Estimates of Anthropogenic NOx Emissions Using High‐Resolution Airborne Remote Sensing Observations

A real-time hourly ozone prediction system using deep convolutional neural network

Contact Info

Product

Resources

About

First Top‐Down Estimates of Anthropogenic NO_x Emissions Using High‐Resolution Airborne Remote Sensing Observations