Source apportionment of PM2.5 in Beijing by positive matrix factorization

Song, Yu; Zhang, Yuanhang; Xie, Shaodong; Zeng, Limin; Zheng, Mei; Salmon, Lynn G.; Shao, Min; Slanina, Sjaak

doi:10.1016/j.atmosenv.2005.10.039

Cited by 353 publications

(202 citation statements)

References 19 publications

Supporting

Mentioning

187

Contrasting

Unclassified

Order By: Relevance

“…SI3. Generally, vehicle emissions played an important role in contributing to PM 2.5 pollution in Beijing (Cheng et al 2013a;Song et al 2006;Sun et al 2004). LUR models for most of the periods contained road length variables, and road length variables were the only variables with positive model coefficients.…”

Section: Predictor Variablesmentioning

confidence: 99%

Applying land use regression model to estimate spatial variation of PM2.5 in Beijing, China

Peng

et al. 2014

Environ Sci Pollut Res

133

View full text Add to dashboard Cite

Fine particulate matter (PM 2.5 ) is the major air pollutant in Beijing, posing serious threats to human health. Land use regression (LUR) has been widely used in predicting spatiotemporal variation of ambient air-pollutant concentrations, though restricted to the European and North American context. We aimed to estimate spatiotemporal variations of PM 2.5 by building separate LUR models in Beijing. Hourly routine PM 2.5 measurements were collected at 35 sites from 4th March 2013 to 5th March 2014. Seventy-seven predictor variables were generated in GIS, including street network, land cover, population density, catering services distribution, bus stop density, intersection density, and others. Eight LUR models were developed on annual, seasonal, peak/non-peak, and incremental concentration subsets. The annual mean concentration across all sites is 90.7 μg/m 3 (SD=13.7). PM 2.5 shows more temporal variation than spatial variation, indicating the necessity of building different models to capture spatiotemporal trends. The adjusted R 2 of these models range between 0.43 and 0.65. Most LUR models are driven by significant predictors including major road length, vegetation, and water land use. Annual outdoor exposure in Beijing is as high as 96.5 μg/m 3 . This is among the first LUR studies implemented in a seriously air-polluted Chinese context, which generally produce acceptable results and reliable spatial air-pollution maps. Apart from the models for winter and incremental concentration, LUR models are driven by similar variables, suggesting that the spatial variations of PM 2.5 remain steady for most of the time. Temporal variations are explained by the intercepts, and spatial variations in the measurements determine the strength of variable coefficients in our models.

show abstract

Section: Predictor Variablesmentioning

confidence: 99%

Applying land use regression model to estimate spatial variation of PM2.5 in Beijing, China

Peng

et al. 2014

Environ Sci Pollut Res

133

View full text Add to dashboard Cite

show abstract

“…However, for PM 10 fraction, the 24 h World Health Organization PM 10 AQG (50 µg m -3 ) was slightly violated during the sampling period. This is not unexpected as PM 10 are usually made of re-entrained dust compared to PM 2.5 which emanates mostly due to anthropogenic contributions. Entrained dust is expected to contribute more to particulate loadings in an environment such as Lagos with many unpaved roads and walkways.…”

Section: Mass Concentrationsmentioning

confidence: 92%

“…PMF offers a viable alternative given the absence of a local source profile library for air pollutants especially in most developing countries such as Nigeria. PMF have been applied successfully in the studies of aerosol sources of many cities; Toronto, Canada [7]; Atlanta, USA [8] Pittsburg, USA [9]; Beijing, China [10]; Bangladesh [11] and Costa Rica [12]. An Trace Metals and Source Identification of Air-Borne Particulate Matter Pollution in A Nigerian Megacity achieved using ''Gent'' stacked filter sampler [14] capable of segregating both size fractions.…”

Section: Introductionmentioning

confidence: 99%

Trace Metals and Source Identification of Air-Borne Particulate Matter Pollution in A Nigerian Megacity

Gc¹,

Ib²,

Asubiojo³

2017

J Environ Anal Toxicol

View full text Add to dashboard Cite

“…After getting the chemical composition data of atmospheric aerosols, the sources are usually analyzed by using a receptor model (Watson et al, 2002;Song et al, 2006;Zhang et al, 2003). In the current study, the element concentration data of 32 aerosol samples at Datong were analyzed using the factor-analysis method.…”

Section: Factor Analysis Of Element Concentrationmentioning

confidence: 99%

“…Arising from both the impacts of aerosol on radiation and cloud microphysics and the influence of fine particles on human health, aerosols have created much scientific interest (Cao et al, 2003;Song et al, 2006;Yan et al, 2007;Zhang et al, 2007). In recent years, the atmosphere environment in northern China cities has been considerably polluted by particles .…”

Section: Introductionmentioning

confidence: 99%

Elemental Composition of Atmospheric Particles in Winter at Datong City, Shanxi Province, China, and Its Impact on Beijing

Zhang

Ling-Yun³

et al. 2009

Atmospheric and Oceanic Science Letters

View full text Add to dashboard Cite

Atmospheric particle samples were collected at an urban site of Datong, Shanxi Province, during December 2004 and their element concentrations at different sizes were analyzed by particle-induced X-ray emission (PIXE). Analysis of the observation data showed that particle pollution was heavy in winter at Datong and that concentrations of most elements were high in the coarse range. Factor analysis (FA) results indicated that the soil and dust, coal combustion dust, and industry dust are main sources for atmospheric particles in winter at Datong. The enrichment factors of element concentrations showed that particle pollution at Datong impacts the down-wind region-Beijing-in the dust season.

show abstract

Source apportionment of PM2.5 in Beijing by positive matrix factorization

Cited by 353 publications

References 19 publications

Applying land use regression model to estimate spatial variation of PM2.5 in Beijing, China

Applying land use regression model to estimate spatial variation of PM2.5 in Beijing, China

Trace Metals and Source Identification of Air-Borne Particulate Matter Pollution in A Nigerian Megacity

Elemental Composition of Atmospheric Particles in Winter at Datong City, Shanxi Province, China, and Its Impact on Beijing

Contact Info

Product

Resources

About