Formaldehyde and its relation to CO, PAN, and SO&amp;lt;sub&amp;gt;2&amp;lt;/sub&amp;gt; in the Houston-Galveston airshed

Rappenglück, Bernhard; Dasgupta, Purnendu Κ.; Leuchner, Michael; Li, Q.; Luke, Winston T.

doi:10.5194/acp-10-2413-2010

Cited by 66 publications

(73 citation statements)

References 36 publications

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“…However, previous studies [55,56] have reported high HCHO levels at noon and low HCHO levels in the morning from the Houston-Galveston Airshed (HGA) and Southern China, which are opposite to the diurnal pattern found in Seoul in this study. As discussed in [52], the different diurnal variations of HCHO seen among various urban areas might be related to differences in the HCHO sources and loss mechanisms at each site.…”

Section: Hcho Vcd Retrieval In Seoul Using Pandoracontrasting

confidence: 55%

Retrieval Accuracy of HCHO Vertical Column Density from Ground-Based Direct-Sun Measurement and First HCHO Column Measurement Using Pandora

et al. 2018

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Abstract:In the present study, we investigate the effects of signal to noise (SNR), slit function (FWHM), and aerosol optical depth (AOD) on the accuracy of formaldehyde (HCHO) vertical column density (HCHO VCD ) using the ground-based direct-sun synthetic radiance based on differential optical absorption spectroscopy (DOAS). We found that the effect of SNR on HCHO retrieval accuracy is larger than those of FWHM and AOD. When SNR = 650 (1300), FWHM = 0.6, and AOD = 0.2, the absolute percentage difference (APD) between the true HCHO VCD values and those retrieved ranges from 54 (30%) to 5% (1%) for the HCHO VCD of 5.0 × 10 15 and 1.1 × 10 17 molecules cm −2 , respectively. Interestingly, the maximum AOD effect on the HCHO accuracy was found for the HCHO VCD of 3.0 × 10 16 molecules cm −2 . In addition, we carried out the first ground-based direct-sun measurements in the ultraviolet (UV) wavelength range to retrieve the HCHO VCD using Pandora in Seoul. The HCHO VCD was low at 12:00 p.m. local time (LT) in all seasons, whereas it was high in the morning (10:00 a.m. LT) and late afternoon (4:00 p.m. LT), except in winter. The maximum HCHO VCD values were 2.68 × 10 16 , 3.19 × 10 16 , 2.00 × 10 16 , and 1.63 × 10 16 molecules cm −2 at 10:00 a.m. LT in spring, 10:00 a.m. LT in summer, 1:00 p.m. LT in autumn, and 9:00 a.m. LT in winter, respectively. The minimum values of Pandora HCHO VCD were 1.63 × 10 16 , 2.23 × 10 16 , 1.26 × 10 16 , and 0.82 × 10 16 molecules cm −2 at around 1:45 p.m. LT in spring, summer, autumn, and winter, respectively. This seasonal pattern of high values in summer and low values in winter implies that photo-oxidation plays an important role in HCHO production. The correlation coefficient (R) between the monthly HCHO VCD values from Pandora and those from the Ozone Monitoring Instrument (OMI) is 0.61, and the slope is 1.25.

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Section: Hcho Vcd Retrieval In Seoul Using Pandoracontrasting

confidence: 55%

Retrieval Accuracy of HCHO Vertical Column Density from Ground-Based Direct-Sun Measurement and First HCHO Column Measurement Using Pandora

et al. 2018

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“…In order to compare the PMF results directly with the CMAQ source apportionment results from this study, sources of PAN need to be studied to determine the sources of HCHO associated with PAN in the PMF analysis. Although it has been demonstrated during several high HCHO events that PAN is associated with SO 2 and thus is likely to have originated from industrial or petrochemical sources [Rappenglück et al, 2010], the PAN-dominated HCHO resolved by PMF in the study of Buzcu Guven and Olaguer [2011] needs further scrutiny because the PMF analysis identified a separate SO 2 related factor, suggesting that PAN is not always related to SO 2 emitted from industrial sources.…”

Section: Comparison With Pmfmentioning

confidence: 99%

“…More recently, Buzcu Guven and applied Positive Matrix Factorization (PMF) on the same dataset used by Rappenglück et al [2010] and found that HCHO associated with motor vehicle, industry and biogenic factors account for 23%, 17%, and 24% of the total HCHO, respectively.…”

Section: Introductionmentioning

confidence: 99%

“…[7] The differences in the estimations of primary and secondary sources to HCHO can be at least partially attributed to the fact that direct measurement of HCHO alone cannot determine whether it is primary or secondary, and other relationships, such as the ratios of HCHO to CO, SO 2 , or PAN, along with meteorological analysis must assist the source apportionment Rappengluck et al, 2010]. Due to potentially significant variations in ratios of HCHO emissions to those of other species, as well as in meteorological conditions, different conclusions can be arrived at for different locations and times using receptororiented techniques.…”

Section: Introductionmentioning

confidence: 99%

“…[5] Linear regression analysis conducted by Friedfeld et al [2002] and Rappenglück et al [2010] showed that approximately 45-50% of HCHO at an industrially influenced urban site (Deer Park, south of HSC) and an urban site (Moody Tower [MT] in University of Houston) can be attributed to primary emissions of HCHO. More recently, Buzcu Guven and applied Positive Matrix Factorization (PMF) on the same dataset used by Rappenglück et al [2010] and found that HCHO associated with motor vehicle, industry and biogenic factors account for 23%, 17%, and 24% of the total HCHO, respectively.…”

Section: Introductionmentioning

confidence: 99%

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Source apportionment of formaldehyde during TexAQS 2006 using a source‐oriented chemical transport model

Zhang

Ying

et al. 2013

JGR Atmospheres

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[1] In this study, a source-oriented version of the Community Multiscale Air Quality (CMAQ) model was developed and used to quantify the contributions of five major local emission source types in Southeast Texas (vehicles, industry, natural gas combustion, wildfires, biogenic sources), as well as upwind sources, to regional primary and secondary formaldehyde (HCHO) concentrations. Predicted HCHO concentrations agree well with observations at two urban sites (the Moody Tower [MT] site at the University of Houston and the Haden Road #3 site operated by Texas Commission on Environmental Quality). However, the model underestimates concentrations at an industrial site (Lynchburg Ferry). Throughout most of Southeast Texas, primary HCHO accounts for approximately 20-30% of total HCHO, while the remaining portion is due to secondary HCHO (30-50%) and upwind sources (20-50%). Biogenic sources, natural gas combustion, and vehicles are important sources of primary HCHO in the urban Houston area, respectively, accounting for 10-20%, 10-30%, and 20-60% of total primary HCHO. Biogenic sources, industry, and vehicles are the top three sources of secondary HCHO, respectively, accounting for 30-50%, 10-30%, and 5-15% of overall secondary HCHO. It was also found that over 70% of PAN in the Houston area is due to upwind sources, and only 30% is formed locally. The model-predicted source contributions to HCHO at the MT generally agree with source apportionment results obtained from the Positive Matrix Factorization (PMF) technique.

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Overview of the SHARP campaign: Motivation, design, and major outcomes

et al. 2014

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The Study of Houston Atmospheric Radical Precursors (SHARP) was a field campaign developed by the Houston Advanced Research Center on behalf of the Texas Environmental Research Consortium. SHARP capitalized on previous research associated with the Second Texas Air Quality Study and the development of the State Implementation Plan (SIP) for the Houston-Galveston-Brazoria (HGB) ozone nonattainment area. These earlier studies pointed to an apparent deficit in ozone production in the SIP attainment demonstration model despite the enhancement of simulated emissions of highly reactive volatile organic compounds in accordance with the findings of the original Texas Air Quality Study in 2000. The scientific hypothesis underlying the SHARP campaign was that there are significant undercounted primary and secondary sources of the radical precursors, formaldehyde, and nitrous acid, in both heavily industrialized and more typical urban areas of Houston. These sources, if properly taken into account, could increase the production of ozone in the SIP model and the simulated efficacy of control strategies designed to bring the HGB area into ozone attainment. This overview summarizes the precursor studies and motivations behind SHARP, as well as the overall experimental design and major findings of the 2009 field campaign. These findings include significant combustion sources of formaldehyde at levels greater than accounted for in current point source emission inventories; the underestimation of formaldehyde and nitrous acid emissions, as well as CO/NO x and NO 2 /NO x ratios, by mobile source models; and the enhancement of nitrous acid by atmospheric organic aerosol.

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Formaldehyde and its relation to CO, PAN, and SO<sub>2</sub> in the Houston-Galveston airshed

Cited by 66 publications

References 36 publications

Retrieval Accuracy of HCHO Vertical Column Density from Ground-Based Direct-Sun Measurement and First HCHO Column Measurement Using Pandora

Retrieval Accuracy of HCHO Vertical Column Density from Ground-Based Direct-Sun Measurement and First HCHO Column Measurement Using Pandora

Source apportionment of formaldehyde during TexAQS 2006 using a source‐oriented chemical transport model

Overview of the SHARP campaign: Motivation, design, and major outcomes

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