An investigation on correlation between traffic and climate variables with the amount of SO&lt;SUB align="right"&gt;2 and NO&lt;SUB align="right"&gt;2 pollutants and estimation of their emission using regression modelling analysis method (case study: Mazandaran - Iran)

Kebria, Daryoush Yousefi; Darvishi, Gholamreza; Haghighi, Farshidreza

doi:10.1504/ijep.2013.058459

Cited by 1 publication

(1 citation statement)

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“…Re-suspended road wear and particles exhausted by vehicles are often regarded as two other important contributors of PM10 [21,28]. According to statistics data issued by the Luzhou government, the number of automobiles in this city dramatically increased to 329,000 in 2010 from 60,400 in 2008, which might contribute to the degradation of air quality.…”

Section: Traffic Sourcementioning

confidence: 99%

Spatiotemporal Variations and Possible Sources of Ambient PM₁₀from 2003 to 2012 in Luzhou, China

Ren

Zhou

et al. 2014

Environmental Engineering Research

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Descriptive statistics methods were used to study the spatiotemporal variations and sources of ambient particulate matter (PM10) in Luzhou, China. The analyzed datasets were collected from four national air quality monitoring stations: Jiushi (S1), Xiaoshi (S2), Zhongshan (S3), Lantian (S4) over the period of 2003-2012. This city was subjected serious PM10 pollution, and the long-term annual average PM10 concentrations varied from 76 to 136 μg/m 3. The maximum concentration was more than 3-fold of the annual average (40 μg/m 3) issued by EPA-China for the ambient air quality. General temporal pattern was characterized by high concentrations in winter and low concentrations in summer, and general spatial gradient was in the reduction order of S2 > S4 > S3 > S1, which were both due to different particulate contributors and special meteorological conditions. The source apportionment indicated that vehicular emissions, road dusts, coal burning and chemical dusts were the major contributors of the identified PM10 pollution, and the vehicular emissions and the road wear re-suspended particles dominated the heavy PM10 pollution in recent years. Two other potential sources, agricultural and celebration activities could decrease the air quality in a short term. Finally, some corresponding suggestions and measures were provided to improve the air quality.

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Section: Traffic Sourcementioning

confidence: 99%

Spatiotemporal Variations and Possible Sources of Ambient PM₁₀from 2003 to 2012 in Luzhou, China

Ren

Zhou

et al. 2014

Environmental Engineering Research

View full text Add to dashboard Cite

show abstract

An investigation on correlation between traffic and climate variables with the amount of SO<SUB align="right">2 and NO<SUB align="right">2 pollutants and estimation of their emission using regression modelling analysis method (case study: Mazandaran - Iran)

Cited by 1 publication

References 11 publications

Spatiotemporal Variations and Possible Sources of Ambient PM₁₀from 2003 to 2012 in Luzhou, China

Spatiotemporal Variations and Possible Sources of Ambient PM₁₀from 2003 to 2012 in Luzhou, China

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An investigation on correlation between traffic and climate variables with the amount of SO<SUB align="right">2 and NO<SUB align="right">2 pollutants and estimation of their emission using regression modelling analysis method (case study: Mazandaran - Iran)

Cited by 1 publication

References 11 publications

Spatiotemporal Variations and Possible Sources of Ambient PM10from 2003 to 2012 in Luzhou, China

Spatiotemporal Variations and Possible Sources of Ambient PM10from 2003 to 2012 in Luzhou, China

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Spatiotemporal Variations and Possible Sources of Ambient PM₁₀from 2003 to 2012 in Luzhou, China

Spatiotemporal Variations and Possible Sources of Ambient PM₁₀from 2003 to 2012 in Luzhou, China