2014
DOI: 10.5194/acp-14-7757-2014
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SO<sub>2</sub> noontime-peak phenomenon in the North China Plain

Abstract: Abstract.A phenomenon of frequent noontime SO 2 concentration peaks was discovered in a detailed analysis of the SO 2 concentrations in the North China Plain (NCP). The possible causes and their contributions are analyzed. The impacts of such a phenomenon on the sulphur cycle were studied and the implications of the phenomenon for atmospheric chemistry, cloud physics, and climate were discussed. Different from the more common SO 2 diurnal patterns with high nighttime concentrations, NCP witnessed high frequenc… Show more

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Cited by 41 publications
(34 citation statements)
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“…Furthermore, for all seasons the highest concentrations occurred at noon, which is in agreement with the measurements performed by Henschel et al (2013). The SO 2 noontime peak was investigated by Xu et al (2014) for measurements performed in the North China Plain (NCP). The group tried to explain the peaks observed in the NCP with different reasons.…”
Section: Gasessupporting
confidence: 83%
“…Furthermore, for all seasons the highest concentrations occurred at noon, which is in agreement with the measurements performed by Henschel et al (2013). The SO 2 noontime peak was investigated by Xu et al (2014) for measurements performed in the North China Plain (NCP). The group tried to explain the peaks observed in the NCP with different reasons.…”
Section: Gasessupporting
confidence: 83%
“…Such a diurnal cycle of SO 2 has been observed previously in China (Wang, 2002;Wang et al, 2014) and in other regions of the world (Khemani et al, 1987;Psiloglou et al, 2013), but in others, noontime SO 2 peaks have also been observed (e.g. Lin et al, 2012;Xu et al, 2014), possibly as a result of other meteorological/dynamical effects (Xu et al, 2014).…”
Section: Morning-evening Differencesmentioning
confidence: 79%
“…2 , NO 2 , and CO), when the standard eigenvector > 1, the factor with the largest variance was chosen as the first group, and the process was repeated. If the variables differ greatly, the PCA results will also vary greatly because a covariance or correlation matrix is used [52]. Data are reliable when the value of KMO (Kaiser-Meyer-Olkin) is greater than 0.6.…”
Section: Complex Pollutionmentioning
confidence: 99%