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Li Y.-W.,National Research Center for Environmental Analysis and Measurements | Sun P.-Q.,National Accreditation Service for Conformity Assessment | Sun H.-R.,National Accreditation Service for Conformity Assessment
Yejin Fenxi/Metallurgical Analysis

Quartile and iteration are two robust statistic methods used to calculate target standard deviation of data of proficiency testing, whose results are directly applied to evaluate whether the laboratory data are qualified. The analysis results of the two robust statistic methods are compared based on 195 sets of data (more than 100 test items) of proficiency testing. The calculation results of both simulation and real data show that the results of two methods are basically consistent when data tend to normal distribution. But when the testing item data obviously deviates from normal distribution, the standard deviation from quartile method is so strict that the pass rate of laboratory data is obviously decreased and it appears to make statistically "abandoning true" mistake. The rationality of two methods is evaluated based on the results from classic statistics deleted outliers. The average of relative deviation between two results results is 5.7%, which means the two results are relatively closed to each other for solid samples. The relative deviation of two methods' results is 13.8% for liquid samples, which means the difference of two methods is relatively large. Iteration method not only reduces the effect of outliers on statistical analysis results but also avoids the human factor in the identification of outliers. It is suggested that the iteration method should be applied in domestic standards system in proficiency testing as soon as possible. Source

Widory D.,Bureau de Recherches Geologiques et Minieres | Liu X.,Chinese Research Academy of Environmental Sciences | Dong S.,National Research Center for Environmental Analysis and Measurements
Atmospheric Environment

Even after its being phased out in gasoline in the late 90s, lead (Pb) is still present at relatively high levels in the atmosphere of Beijing, China (0.10-0.18μgm-3). Its origin is subject to debate as several distinct sources may contribute to the observed pollution levels. This study proposes to constrain the origin(s) of Pb and strontium (Sr) in aerosols, by coupling both Pb and Sr isotope systematics. The characterisation of the main pollution sources (road traffic, smelters, metal refining plants, coal combustion, cement factories, and soil erosion) shows that they can unambiguously be discriminated by the multi-isotope approach (206Pb/204Pb and 87Sr/86Sr). The study of total suspended particulates (TSP) and fine particles (PM2.5) from Beijing and its vicinity indicates that both size fractions are controlled by the same sources. Lead isotopes indicate that metal refining plants are the major source of atmospheric lead, followed by thermal power stations and other coal combustion processes. The role of this latter source is confirmed by the study of strontium isotopes. Occasionally, emissions from cement plants and/or input from soil alteration are isotopically detectable. © 2010 Elsevier Ltd. Source

Jung H.-J.,Inha University | Song Y.-C.,Inha University | Liu X.,Chinese Research Academy of Environmental Sciences | Li Y.,National Research Center for Environmental Analysis and Measurements | Ro C.-U.,Inha University
Asian Journal of Atmospheric Environment

China has been a top producer and exporter of refined lead products in the world since the year 2000. After the phasing-out of leaded gasoline in the late 1990s, non-ferrous metallurgy and coal combustion have been identified as potential major sources of aerosol lead in China. This paper presents the single particle analytical results of ambient aerosol particles collected near a lead smelter using a scanning electron microscopy-energy dispersive x-ray spectroscopy (SEMEDX). Aerosol particle samples were collected over a 24-hour period, starting from 8 pm on 31 May 2002, using a high volume TSP sampler. For this near source sample, 73 particles among 377 particles analyzed (accounting for 19.4%) were lead-containing particles mixed with other species (S, Cl, K, Ca, and/or C), which probably appeared to be from a nearby lead smelter. Lead-containing particles of less than 2 μm size in the near source sample were most frequently encountered with the relative abundances of 42%. SEM-EDX analysis of individual standard particles, such as PbO, PbS, PbSO 4, PbCl 2, and PbCO 3, was also performed to assist in the clear identification of lead-containing aerosol particles. Lead-containing particles were frequently associated with arsenic and zinc, indicating that the smelter had emitted those species during the non-ferrous metallurgical process. The frequently encountered particles following the lead-containing particles were mineral dust particles, such as aluminosilicates (denoted as AlSi), SiO 2, and CaCO 3. Nitrate- and sulfate-containing particles were encountered frequently in 2-4 μm size range, and existed mostly in the forms of Ca(NO 3, SO 4)/C, (Mg, Ca)SO 4/C, and AlSi+(NO 3, SO 4). Particles containing metals (e.g., Fe, Cu, and As) in this near source sample had relative abundances of approximately 10%. Although the airborne particles collected near the lead smelter contained elevated levels of lead, other types of particles, such as CaCO3-containing, carbonaceous, metal-containing, nitrates, sulfates, and fly-ash particles, showed the unique signatures of samples influenced by emissions from the lead smelter. Source

Geng H.,Shanxi University | Hwang H.,Korea Polar Research Institute | Liu X.,Chinese Research Academy of Environmental Sciences | Dong S.,National Research Center for Environmental Analysis and Measurements | Ro C.-U.,Inha University
Atmospheric Chemistry and Physics

This is the first study of Asian dust storm (ADS) particles collected in Beijing, China, and Incheon, Korea, during a spring ADS event. Using a seven-stage May impactor and a quantitative electron probe X-ray microanalysis (ED-EPMA, also known as low-Z particle EPMA), we examined the composition and morphology of 4200 aerosol particles at stages 1-6 (with a size cut-off of 16, 8, 4, 2, 1, and 0.5 μm in equivalent aerodynamic diameter, respectively) collected during an ADS event on 28-29 April 2005. The results showed that there were large differences in the chemical compositions between particles in sample S1 collected in Beijing immediately after the peak time of the ADS and in samples S2 and S3, which were collected in Incheon approximately 5 h and 24 h later, respectively. In sample S1, mineral dust particles accounted for more than 88% in relative number abundance at stages 1-5; and organic carbon (OC) and reacted NaCl-containing particles accounted for 24% and 32%, respectively, at stage 6. On the other hand, in samples S2 and S3, in addition to approximately 60% mineral dust, many sea spray aerosol (SSA) particles reacted with airborne SO2 and NOx (accounting for 24% and 14% on average in samples S2 and S3, respectively), often mixed with mineral dust, were encountered at stages 1-5, and (C, N, O, S)-rich particles (likely a mixture of water-soluble organic carbon with (NH4)2SO4 and NH4NO3) were abundantly observed at stage 6 (accounting for 68% and 51% in samples S2 and S3, respectively). This suggests that an accumulation of sea-salt components on individual ADS particles larger than 1 μm in diameter occurred and many secondary aerosols smaller than 1 μm in diameter were formed when the ADS particles passed over the Yellow Sea. In the reacted or aged mineral dust and SSA particles, nitrate-containing and both nitrate- and sulfate-containing species vastly outnumbered the sulfate-containing species, implying that ambient NOx had a greater influence on the atmospheric particles than SO2 during this ADS episode. In addition to partially- or totally-reacted CaCO3, reacted or aged Mg-containing aluminosilicates were observed frequently in samples S2 and S3; furthermore, a student's t test showed that both their atomic concentration ratios of [Mg] / [Al] and [Mg] / [Si] were significantly elevated (P < 0.05) compared to those in samples S1 (for [Mg] / [Al], 0.34 ± 0.09 and 0.40 ± 0.03 in samples S2 and S3, respectively, vs. 0.24 ± 0.01 in sample S1; for [Mg] / [Si], 0.21 ± 0.05 and 0.22 ± 0.01 in samples S2 and S3, respectively, vs. 0.12 ± 0.02 in sample S1). The significant increase of [Mg] / [Al] and [Mg] / [Si] ratios in Mg-containing aluminosilicates indicates that a significant evolution or aging must have occurred on the ADS particles in the marine atmosphere during transport from China to Korea. © Author(s) 2014. Source

Yang B.,Chinese Research Academy of Environmental Sciences | Zhou L.,Chinese Research Academy of Environmental Sciences | Xue N.,Chinese Research Academy of Environmental Sciences | Li F.,Chinese Research Academy of Environmental Sciences | And 6 more authors.
Science of the Total Environment

Receptor models are useful tools to identify sources of a specific pollutant and to estimate the quantitative contributions of each source based on environmental data. This paper reports on similarities and differences in results achieved when testing three receptor models for estimating the sources of polycyclic aromatic hydrocarbons (PAHs) in soils from Huanghuai Plain, China. The three tested models are Principal Component Analysis with Multiple Linear Regression (PCA-MLR), Positive Matrix Factorization (PMF) and Unmix. Overall source contributions as well as modeled ∑ PAHs concentrations compared well among models. All three models apportioned three common PAH sources: wood/biomass burning, fossil fuel combustion and traffic emission, which contributed on average 27.7%, 53.0% and 19.3% by PCA-MLR, 36.9%, 27.2% and 16.3% by PMF, and 47.8%, 21.1% and 18.3% by Unmix to the total sum of PAHs (∑ PAHs), respectively. Moreover, the spatial evolution of the common sources were well correlated among models (r = 0.83-0.99, p<0.001). In addition, the PMF and Unmix models allowed segregating an additional source from the fossil fuel combustion source, with 19.6% and 11.8% contributions to ∑ PAHs, respectively. The current findings further validate that different receptor models provide divergent source profiles, which are mainly attributed to both the model itself and/or the underlying dataset. It is therefore generally recommended to apply multiple techniques to determine the source apportionment in order to minimize individual-method weaknesses and thereby to strengthen the conclusion. © 2012 Elsevier B.V. Source

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