Relationship between surface, free tropospheric and total column ozone in two contrasting areas in South Africa

Combrink, J.; Diab, R. D.; Sokolic, F.; Brunke, Ernst-Günther

doi:10.1016/1352-2310(94)00313-a

Cited by 18 publications

(8 citation statements)

References 14 publications

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“…Although there is some variability between the sites, monthly O3 concentrations show a well-defined seasonal variation at all four sites, with maximum concentrations occurring in late winter and spring (August-November). This observed late winter and spring O3 peak are expected for the South African interior as previously reported (Zunckel et al, 2004;Diab et al, 2004;Combrink et al, 1995). These O3 peaks in continental South 30…”

Section: Seasonal and Diurnal Variation Of O3supporting

confidence: 69%

Seasonal influences on surface ozone variability in continental South Africa and implications for air quality

Laban¹,

Zyl²,

Beukes³

et al. 2018

Preprint

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Although elevated ozone (O3) concentrations are observed in many areas within continental southern Africa, few studies have investigated the regional atmospheric chemistry and dominant atmospheric processes driving surface O3 formation in this region. The aim of this study was to 20 conduct an assessment of comprehensive continuous surface O3 measurements performed at four sites located in continental South Africa. These sites were representative of regional background (Welgegund and Botsalano) and industrial regions (Marikana and Elandsfontein) in

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Section: Seasonal and Diurnal Variation Of O3supporting

confidence: 69%

Seasonal influences on surface ozone variability in continental South Africa and implications for air quality

Laban¹,

Zyl²,

Beukes³

et al. 2018

Preprint

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“…Combrink et al . [] analyzed surface ozone data from two sites on the Highveld: Elandsfontein in the middle of the industrialized area and Verkykkop that is generally downwind of the industrialized area. They found that on average at both locations, ozone typically peaks between 1400 and 1700 h (local time) due to photochemical formation , which is typical of a polluted environment.…”

Section: Introductionmentioning

confidence: 99%

“…Combrink et al . [] also analyzed monthly surface ozone cycles from 1988 to 1991 and reported maxima in SON and minima in DJF. Rorich and Galpin [] calculated trends of several trace gases at four monitoring stations located in and downwind of the industrialized areas on the Highveld—Elandsfontein, Verkykkop, Palmer, and Makalu—from 1984 to 1994 and found no significant trends in ozone concentrations at all of the sites except Verkykkop.…”

Section: Introductionmentioning

confidence: 99%

Surface ozone variability and trends over the South African Highveld from 1990 to 2007

et al. 2014

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Surface ozone is a secondary air pollutant formed from reactions between nitrogen oxides (NO x = NO + NO 2 ) and volatile organic compounds in the presence of sunlight. In this work we examine effects of the climate pattern known as the El Niño-Southern Oscillation (ENSO) and NO x variability on surface ozone from 1990 to 2007 over the South African Highveld, a heavily populated region in South Africa with numerous industrial facilities. Over summer and autumn (December-May) on the Highveld, El Niño, as signified by positive sea surface temperature (SST) anomalies over the central Pacific Ocean, is typically associated with drier and warmer than normal conditions favoring ozone formation. Conversely, La Niña, or negative SST anomalies over the central Pacific Ocean, is typically associated with cloudier and above normal rainfall conditions, hindering ozone production. We use a generalized regression model to identify any linear dependence that the Highveld ozone, measured at five air quality monitoring stations, may have on ENSO and NO x . Our results indicate that four out of the five stations exhibit a statistically significant sensitivity to ENSO at some point over the December-May period where El Niño amplifies ozone formation and La Niña reduces ozone formation. Three out of the five stations reveal statistically significant sensitivity to NO x variability, primarily in winter and spring. Accounting for ENSO and NO x effects throughout the study period of 18 years, two stations exhibit statistically significant negative ozone trends in spring, one station displays a statistically significant positive trend in August, and two stations show no statistically significant change in surface ozone.

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“…Other studies indicated that only 20% of the variances in the TOMS total O 3 data were from variations in tropospheric O 3 , with the remainder possibly because of long-range transport biomass burning. 19 There have been some innovative studies on tropospheric O 3 in the tropics; 20 however, the current errors in TOMS data make it unreliable from 2000 to the present. The new Scanning Imaging Absorption SpectroMeter for Atmospheric Chartography (SCIAMACHY) instrument and OMI may reinvigorate the published projects in this area in the next few years.…”

Section: Regional Air Quality Monitoringmentioning

confidence: 99%

Recommendations on the Use of Satellite Remote-Sensing Data for Urban Air Quality

Engel-Cox

Hoff

Haymet

2004

Journal of the Air & Waste Management Association

146

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In the last 5 yr, the capabilities of earth-observing satellites and the technological tools to share and use satellite data have advanced sufficiently to consider using satellite imagery in conjunction with ground-based data for urbanscale air quality monitoring. Satellite data can add synoptic and geospatial information to ground-based air quality data and modeling. An assessment of the integrated use of ground-based and satellite data for air quality monitoring, including several short case studies, was conducted. Findings identified current U.S. satellites with potential for air quality applications, with others available internationally and several more to be launched within the next 5 yr; several of these sensors are described in this paper as illustrations. However, use of these data for air quality applications has been hindered by historical lack of collaboration between air quality and satellite scientists, difficulty accessing and understanding new data, limited resources and agency priorities to develop new techniques, ill-defined needs, and poor understanding of the potential and limitations of the data. Specialization in organizations and funding sources has limited the resources for cross-disciplinary projects. To successfully use these new data sets requires increased collaboration between organizations, streamlined access to data, and resources for project implementation. INTRODUCTIONUrban air quality traditionally has been monitored with networks of ground monitoring stations and the use of models that evaluate emissions and predict changes in air quality at discrete points. Satellite remote sensing may provide a synoptic picture of air quality in an urban airshed, including information on sources for isolated events. Use of satellite data could help air quality professionals identify the location of peak concentrations and determine the concentration gradients between surface monitoring stations. To date, satellite sensors have yielded limited quantitative information for air quality compared with ground-based monitoring, yet the potential exists for quantitative applications. The integrated use of these two sources of data and models should better enable policy decisions and increase scientific understanding of an urban airshed than either method alone. Specifically, satellite sensors could provide a broad view of urban haze and help determine the impact on urban air quality by local fires, dust storms, or transport of pollutants from more distant sources, including those crossing national or regional boundaries. 1 Satellite remote-sensing

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Relationship between surface, free tropospheric and total column ozone in two contrasting areas in South Africa

Cited by 18 publications

References 14 publications

Seasonal influences on surface ozone variability in continental South Africa and implications for air quality

Seasonal influences on surface ozone variability in continental South Africa and implications for air quality

Surface ozone variability and trends over the South African Highveld from 1990 to 2007

Recommendations on the Use of Satellite Remote-Sensing Data for Urban Air Quality

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