Investigation of the Successive Ozone Episodes in the El Paso–Juarez Region in the Summer of 2017

Karle, Nakul N.; Mahmud, Suhail; Sakai, Ricardo K.; Fitzgerald, Rosa M.; Morris, Vernon R.; Stockwell, William R.

doi:10.3390/atmos11050532

Cited by 17 publications

(24 citation statements)

References 44 publications

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“…In these regions, fine particular matter (PM2.5; particles with an aerodynamic diameter of 2.5 microns or lower in ambient air) often attains extremely high concentrations during the winter haze period (Ding et al 2013a;Huang et al, 2014;Guo et al, 2014;Zhang et al, 2014;Chen et al, 2017;Ma et al, 2017;Liu et al, 2019). High levels of air pollution can significantly modify the weather by changing air temperature, cloud conditions, and even precipitation (Banta et al, 1998, Fiore et al, 2002, Ding et al, 2013b, Huang et al, 2016, Karle et al, 2020. The increase in atmospheric aerosols over China has been shown to heat the atmosphere and generate a cyclonic circulation anomaly that weakens the East Asian winter monsoon (F. .…”

Section: Accepted Manuscript Introductionmentioning

confidence: 99%

Observed Interactions Among Haze, Fog and Atmospheric Boundary Layer during a Haze-fog Episode in the Yangtze River Delta Region, Eastern China

Zou

Sun

et al. 2021

Aerosol Air Qual. Res.

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A severe haze-fog episode occurred in the Yangtze River Delta region of eastern China during 22-30 November, 2018. In this period, the PM2.5 mass concentration and meteorological parameters at the surface were collected at the Station for Observing Regional Processes of the Earth System site in Nanjing. The vertical distributions of PM2.5, humidity and potential temperature below 500 m were observed simultaneously by an unmanned aerial vehicle, and the profile of potential temperature at 1400 local standard time on each day was also observed by radiosonde at the same site. During the first four days, the PM2.5 mass concentration increased, the maximum convective planetary boundary layer height (CBLH) decreased, and the air humidity increased. These are favorable conditions for fog formation. In the latter five days, fog formed on four days, with a lowering of the CBLH and a further increase in PM2.5 mass concentration. We found that the fog top cooling induced a potential temperature jump (i.e., sharp increase of potential temperature) with much warmer temperatures above the cloud top cooling and that this particular thermal structure was maintained until the end of the fog period, which significantly suppressed the daytime development of the planetary boundary layer after fog dissipation. The fog-induced reduction of the CBLH further increased the PM2.5 mass concentration. We also found that the wet deposition of fog on PM2.5 was negligible. The scavenging effect of fog on aerosols only acts during a fog period. When the fog dissipates, the aerosols are liberated from the fog droplets to the atmosphere.

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Section: Accepted Manuscript Introductionmentioning

confidence: 99%

Observed Interactions Among Haze, Fog and Atmospheric Boundary Layer during a Haze-fog Episode in the Yangtze River Delta Region, Eastern China

Zou

Sun

et al. 2021

Aerosol Air Qual. Res.

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“…The Lagrange multiplier (LM) statistics were used to examine whether the model had the EGARCH effect with a sequence [29]. The LM statistics were shown as T×R 2 , which obeyed a chi-square distribution with degree of freedom being P. T represented the sample size of the sequence (which is 12,000 in this study), and R 2 represented the coefficients of determination obtained using OLS regression. When the LM statistic of a model was significant, the sequence had the EGARCH effect.…”

Section: Examination Of Egarch Effectivenessmentioning

confidence: 99%

“…VOCs play a significant role in the formation of ozone and particulates, which form smog. When exposed to sunlight and precursors, such as nitrogen oxide, VOCs form ozone and particulates that have a pronounced impact on outdoor air pollution in cities [1][2][3]. In addition, the VOC family consists of a wide range of chemical compounds with varying degrees of toxicity: benzene is an example of a highly toxic substance that is known to be a carcinogen; there are others whose impact on human health remains unknown.…”

Section: Introductionmentioning

confidence: 99%

Study on Air Pollution Behavior of VOCs with Photochemical Monitoring Stations Using EGARCH Model in Southern Taiwan

Kuo

2021

Atmosphere

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This study adopted the exponential generalized autoregressive conditional heteroscedasticity (EGARCH) model to examine the 10 ozone precursors of the highest concentrations among the 54 that were assessed over a number of years at the four photochemical assessment monitoring stations (PAMSs) in the Kaohsiung–Pingtung Area in Taiwan. First, the 10 ozone precursors, which were all volatile organic compounds (VOCs), were analyzed using the factor analyses in multiple statistical analyses that had the most significant impact on the area’s ozone formation: mobile pollution factor, which included 1,2,4-Trimethylbenzene (C9H12), toluene (C7H8), and Isopropyl benzene (C9H12). Then, taking into consideration that the number sequences might be affected by standardized residuals, this study applied the vector autoregressive moving average-EGARCH (VARMA-EGARCH) model to analyze the correlation between the three VOCs under different polluting activities. The VARMA-EGARCH model in this research included dummy variables representing changing points of variance structures in the variance formula to predict the conditional variance. This process proved able to effectively estimate the relevant coefficients of the three VOCs’ dynamic conditions that changed with time. The model also helped to prevent errors from occurring when estimating the conditional variance. Based on the testing results, this study determined the VARMA(2,1)-EGARCH(1,0) as the most suitable model for exploring the correlation between the three VOCs and meteorological phenomena, as well as the interplay between them in regard to interaction and formation. With the most representative of the three, toluene (TU), as the dependent variable and 1,2,4-Trimethylbenzene (TB) and Isopropyl benzene (IB) as the independent variables, this study found it impossible to calculate the TU concentration with TB and IB concentrations in the same period; estimations of TB and IB concentrations with a period of lag time were required because TU was mainly contributed by automobiles and motorcycles in Kaohsiung. TB and IB resulted from other stationary pollution sources in the region besides cars and motorbikes. When TU was evenly distributed and stayed longer in the atmosphere, the TB and IB concentrations were lower, so distribution conditions and concentrations could not be used to effectively estimate the concentration of toluene. This study had to wait until the next period, or when stationary pollution sources started producing TB and IB of higher concentrations during the daytime, in order to estimate the TU concentrations in a better photochemical situation.

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“…At the same time, the 2nd domain (d02) covered mostly southeast part of Texas, some parts of Juarez city, and some counties of New Mexico state as well. The smallest domain or d03 focused on the Paso Del Norte region, which is the region of interest for this paper (Mahmud et al 2020;Karle et al 2020). Domain 2 and Domain 3 were a two-way nested domain.…”

Section: Wrf Simulationmentioning

confidence: 99%

“…Several air quality studies have been conducted in the PdN region in the past (Macdonald et al 2001;Brown et al 2001;Hicks et al 2015;Mahmud et al 2016;Karle et al 2017a, b;Stewart et al 2019;Karle et al 2018Karle et al , 2019Karle et al , 2020. Based on the 1996 ozone study campaign (Macdonald et al 2001), several research articles had been published (Lu et al 2008;Pearson and Fitzgerald 2001;Pearson et al 2007;Stockwell et al 2013).…”

Section: Introductionmentioning

confidence: 99%

Intercomparison of Sonde, WRF/CAMx and Satellite Sounder Profile Data for the Paso Del Norte Region

et al. 2020

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The Paso Del Norte (PdN) region comprises the city of El Paso, TX, Ciudad Juarez, Mexico, and some neighboring cities in the state of New Mexico. Developing a regional weather model for this specific region has always been challenging due to its complex terrain. To obtain more accurate weather and pollution forecasting for the PdN region, the results of the downscaled WRF (Weather Research and Forecast) model were intercompared with meteorological satellite data, with ground and radiosonde dataset. In addition, it is critical to analyze the distributions of ozone concentrations to better understand atmospheric aerosol concentrations and predict them both more accurately. Hence, in this study the ozone results of CAMx (Comprehensive Air Quality Model with Extensions) were extensively intercompared with ozonesonde data. The radiosonde/ozonesonde data were obtained throughout a campaign conducted during the summer of 2017 in the PdN region. Different meteorological variables such as temperature, pressure, relative humidity, wind speed, and ozone concentrations were used for comparison at several locations in the PdN region. The TCEQ (Texas Commission of Environment Quality) data from different CAMS (Continuous Ambient Monitoring Stations) were used for ground data intercomparison with the WRF results. The meteorological satellite sounding data were retrieved using an in-house satellite antenna receiver. The results of this research paper will not only provide better pollution forecasting capability for the PdN region but also for other regions with similar topography and terrain.

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Investigation of the Successive Ozone Episodes in the El Paso–Juarez Region in the Summer of 2017

Cited by 17 publications

References 44 publications

Observed Interactions Among Haze, Fog and Atmospheric Boundary Layer during a Haze-fog Episode in the Yangtze River Delta Region, Eastern China

Observed Interactions Among Haze, Fog and Atmospheric Boundary Layer during a Haze-fog Episode in the Yangtze River Delta Region, Eastern China

Study on Air Pollution Behavior of VOCs with Photochemical Monitoring Stations Using EGARCH Model in Southern Taiwan

Intercomparison of Sonde, WRF/CAMx and Satellite Sounder Profile Data for the Paso Del Norte Region

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