Guo-Liang Shi

Potential source contributions and risk assessment of PAHs in sediments from Taihu Lake, China: Comparison of three receptor models

In this work, three receptor models (Principal Component Analysis-Multiple Linear Regression (PCA-MLR) model, Unmix model and Positive Matrix Factorization (PMF) model) were employed to investigate potential source apportionment of PAHs in sediments from Taihu Lake, China. A total of 15 priority PAHs in 29 sediments from Taihu Lake were measured, with ∑PAHs (sum of 15 PAHs) concentrations ranging from 209 to 1003 ng g(-1) dw. Source apportionment results derived from three different models were similar, indicating that the highest contribution to ∑PAHs was from vehicular emission (53.6-54.3%), followed by coal combustion (23.8-28.8%) and wood combustion (11.9-16.0%). The contribution of mixed wood and coal combustion source identified by PCA-MLR was 41.3%. For the first time the risk assessment for each identified source category was quantitatively calculated by combining the BaP equivalents (BaPE) values with estimated source contributions. The results showed that vehicular emission posed the highest toxic risk, with BaPE values of 26.9-31.5 ng g(-1) dw, and the BaPE values for coal combustion and wood combustion were 6.56-15.6 ng g(-1) dw and 2.94-6.11 ng g(-1) dw, respectively. The distributions of contribution and BaPE for each identified source category were studied as well, and showed similar trends among the sampling sites, for each source category.

Concentrations and sources of PAHs in surface sediments of the Fenhe reservoir and watershed, China

Sixteen PAHs in surface sediments at 28 sites throughout Fenhe reservoir and watershed were measured. The ∑PAHs concentrations ranged from 539.0 to 6281.7 with the mean of 2214.8ng/g. The 2-3 rings PAHs, contributing 55 percent to ∑PAHs, were the dominant species. Twenty-eight sites were grouped into three segments: Fenhe principal stream, estuaries of main branch streams, and Fenhe reservoir. ∑PAHs was highest in the estuaries of main branch streams. The ecological risk assessment was studied by biological thresholds. The results showed levels of PAHs might cause mild but not acute adverse biological effects. In addition, PAHs ratios, PCA/MLR and hierarchical clustering analysis were applied to evaluate the possible sources. Coal combustion (35 percent), diesel and gasoline emissions (29 percent and 16 percent, respectively) might be the important sources. For sites in Fenhe reservoir, the major sources were complex, while other two segments were mainly influenced by coal combustion source.

Relationships between PAHs and PCBs, and quantitative source apportionment of PAHs toxicity in sediments from Fenhe reservoir and watershed

Sedimentary samples from 28 sites throughout the Fenhe reservoir and upstream watershed in China were measured, to study the relationships between PAHs and PCBs as well as perform quantitative source apportionment of toxicity. The distributions of ∑16PAHs and ∑123PCBs showed high correlation. The ∑7C-PAHs (total concentrations of seven carcinogenic PAHs) varied from 87.7 to 2005.0ngg(-1)dw, and the ∑6DL-PCBs (total concentrations of six dioxin-like PCB congeners) were n.d.-5.96ngg(-1)dw. Toxicity and biological risk were assessed using toxic equivalent quantity (TEQ) and sediment quality guideline quotient (SQGQ). The BaP played the dominant role for TEQPAH at most sites (37.17-89.40%), although the CHR showed the highest concentration level. PCB-81 contributed the highest TEQPCB. High correlations were observed between ∑16PAHs and ∑7C-PAHs, ∑123PCBs and ∑6DL-PCBs, ∑7C-PAHs and ∑6DL-PCBs as well as TEQPAH and TEQPCB. Furthermore, quantitative source apportionments for PAHs concentrations and TEQ were carried out, combining the positive matrix factorization (PMF) with the formula of TEQ. For most sites, the vehicular sources were the largest contributors to TEQPAH (46.58%), while coal combustion sources were the highest contributor for PAHs concentrations (43.31%). The relatively higher correlations between PCBs and contributions of coal combustion to PAHs might imply the similar distribution of industrial sources for PAHs and PCBs.

Insights into the chemical characterization and sources of PM2.5 in Beijing at a 1-h time resolution

As the widespread application of online instruments penetrates the environmental fields, it is interesting to investigate the sources of fine particulate matter (PM2.5) based on the data monitored by online instruments. In this study, online analyzers with 1-h time resolution were employed to observe PM2.5 composition data, including carbon components, inorganic ions, heavy metals and gas pollutants, during a summer in Beijing. Chemical characteristics, temporal patterns and sources of PM2.5 are discussed. On the basis of hourly data, the mean concentration value of PM2.5 was 62.16±39.37 μg m(-3) (ranging from 6.69 to 183.67 μg m(-3)). The average concentrations of NO3(-), SO4(2-), NH4(+), OC and EC, the major chemical species, were 15.18±13.12, 14.80±14.53, 8.90±9.51, 9.32±4.16 and 3.08±1.43 μg m(-3), respectively. The concentration of PM2.5 varied during the online-sampling period, initially increasing and then subsequently decreasing. Three factor analysis models, including principal component analysis (PCA), positive matrix factorization (PMF) and Multilinear Engine 2 (ME2), were applied to apportion the PM2.5 sources. Source apportionment results obtained by the three different models were in agreement. Four sources were identified in Beijing during the sampling campaign, including secondary sources (38-39%), crustal dust (17-22%), vehicle exhaust (25-28%) and coal combustion (15-16%). Similar source profiles and contributions of PM2.5 were derived from ME2 and PMF, indicating the results of the two models are reasonable. The finding provides information that could be exploited for regular air control strategies.

Historical trends of concentrations, source contributions and toxicities for PAHs in dated sediment cores from five lakes in western China.

In this work, sixteen U.S. EPA priority PAH compounds in the dated sediment cores were detected from five lakes in western China. In most lakes, the concentrations of the total PAHs (ΣPAHs) increased from the deep layers to the surface sediments. Two source categories, i.e. vehicular emission and biomass & domestic coal combustion were identified by Unmix, a factor analysis receptor model to explore the source contributions of PAHs in the dated sediments. The source apportionment results showed that biomass & domestic coal combustion contributed larger proportion of PAHs in the five lakes. The toxicities of PAHs in the dated sediments, assessed by BaP equivalent (BaPE) values showed that the BaPE increased gradually from the deep layers to the surface sediments in most lakes. For the first effort, the contribution of each source to BaPE was apportioned by Unmix-BaPE method, and the result indicated that the vehicular emission posed the highest toxic risk. The percentage contribution of vehicular emission for PAHs and BaPE also increased from the deep layers to the surface sediments, while biomass & domestic coal combustion exhibited the opposite tendency.

Use of a nonnegative constrained principal component regression chemical mass balance model to study the contributions of nearly collinear sources.

In this study, a nonnegative constrained principal component regression chemical mass balance (NCPCRCMB) model was used to solve the near collinearity problem among source profiles for source apportionment. The NCPCRCMB model added the principle component regression route into the CMB model iteration. The model was tested with the synthetic data sets, which involved contributions from eleven actual sources, with a serious near collinearity problem among them. The actual source profiles were randomly perturbed and then applied to create the synthetic receptor. The resulting synthetic receptor concentrations were also randomly perturbed to simulate measurement errors. The synthetic receptors were separately apportioned by CMB and NCPCRCMB model. The result showed that source contributions estimated by the NCPCRCMB model were much closer to the true values than those estimated by the CMB model. Next, five real ambient data sets from five cities in China were analyzed using the NCPCRCMB model to test the model practicability. Reasonable results were obtained in all cases. It is shown that the NCPCRCMB model has an advantage over the traditional CMB model when dealing with near collinearity problems in source apportionment studies.

A new receptor model-incremental lifetime cancer risk method to quantify the carcinogenic risks associated with sources of particle-bound polycyclic aromatic hydrocarbons from Chengdu in China

PM10 and PM2.5 samples were simultaneously collected during a one-year monitoring period in Chengdu. The concentrations of 16 particle-bound polycyclic aromatic hydrocarbons (Σ16PAHs) were measured. Σ16PAHs concentrations varied from 16.85 to 160.24 ng m(-3) and 14.93 to 111.04ngm(-3) for PM10 and PM2.5, respectively. Three receptor models (principal component analysis (PCA), positive matrix factorization (PMF), and Multilinear Engine 2 (ME2)) were applied to investigate the sources and contributions of PAHs. The results obtained from the three receptor models were compared. Diesel emissions, gasoline emissions, and coal and wood combustion were the primary sources. Source apportionment results indicated that these models were able to track the ΣPAHs. For the first time, the cancer risks for each identified source were quantitatively calculated for ingestion and dermal contact routes by combining the incremental lifetime cancer risk (ILCR) values with the estimated source contributions. The results showed that gasoline emissions posed the highest cancer risk, even though it contributed less to Σ16PAHs. The results and method from this work can provide useful information for quantifying the toxicity of source categories and studying human health in the future.

Vertical characteristics of levels and potential sources of water-soluble ions in PM10 in a Chinese megacity

To investigate the vertical characteristics of ions in PM10 as well as the contributions and possible locations of their sources, eight water-soluble ions were measured at four heights simultaneously along a meteorological tower in Tianjin, China. The total ion concentrations showed a general decreasing trend with increasing height, ranging from 64.94μgm(-3) at 10m to 44.56μgm(-3) at 220m. NH4(+), SO4(2-) and NO3(-) showed higher height-to-height correlations. In addition, relationships between ions are discussed using Pearson correlation coefficients and hierarchical clustering analysis (HCA), which implied that, for each height, the correlations among NH4(+), SO4(2-) and NO3(-) were higher. Finally, sources were identified qualitatively by the ratio of certain ions and quantitatively by principal component analysis/multiple linear regression (PCA/MLR) and positive matrix factorisation (PMF). Secondary sources played a dominant role for PM10 and water-soluble ions at four heights and became more important at greater heights (the percentage contributions were 43.04-66.41% for four heights by PCA/MLR and 46.93-67.62% by PMF). Then, the redistributed concentration field (RCF) combined with PCA/MLR and PMF was applied, which indicated the high potential source regions. The vertical characteristics of the levels, relationships, source contributions and locations would support the effective management of the water-soluble ions in particulate matter.

Chemical characteristic and toxicity assessment of particle associated PAHs for the short-term anthropogenic activity event: during the Chinese New Year's Festival in 2013.

PM10 and PM2.5 samples were simultaneously collected during a period which covered the Chinese New Years (CNY) Festival. The concentrations of particulate matter (PM) and 16 polycyclic aromatic hydrocarbons (PAHs) were measured. The possible source contributions and toxicity risks were estimated for Festival and non-Festival periods. According to the diagnostic ratios and Multilinear Engine 2 (ME2), three sources were identified and their contributions were calculated: vehicle emission (48.97% for PM10, 53.56% for PM2.5), biomass & coal combustion (36.83% for PM10, 28.76% for PM2.5), and cook emission (22.29% for PM10, 27.23% for PM2.5). An interesting result was found: although the PAHs are not directly from the fireworks display, they were still indirectly influenced by biomass combustion which is affiliated with the fireworks display. Additionally, toxicity risks of different sources were estimated by Multilinear Engine 2-BaP equivalent (ME2-BaPE): vehicle emission (54.01% for PM10, 55.42% for PM2.5), cook emission (25.59% for PM10, 29.05% for PM2.5), and biomass & coal combustion source (20.90% for PM10, 14.28% for PM2.5). It is worth to be noticed that the toxicity contribution of cook emission was considerable in Festival period. The findings can provide useful information to protect the urban human health, as well as develop the effective air control strategies in special short-term anthropogenic activity event.

Long-term variation of the levels, compositions and sources of size-resolved particulate matter in a megacity in China.

To investigate the long-term trends and variations of the levels, compositions, size distribution and sources of particulate matter (PM), long-term monitoring campaigns of PM10 and PM2.5 were performed in a megacity in China (Chengdu) during the period from 2009 to 2011. The average concentration of PM10 was 172.01±89.80 μg/m(3) and that of PM2.5 was 103.15±59.83 μg/m(3), with an average PM2.5/PM10 of 0.60. Enrichments of the important species indicated that the fractions of crustal elements were higher in PM10 than those in PM2.5, while the abundance of organic carbon (OC) and secondary ions was enriched in the fine PM. Quantitative source apportionments of both PM10 and PM2.5 were performed by PMF. PM10 and PM2.5 in Chengdu were influenced by similar source categories, and their percentage contributions were in the same order: crustal dust was the highest contributor, followed by vehicular exhaust, secondary sulfate, secondary nitrate and cement dust. Crustal dust and cement dust contributed a higher percentage to PM10 than to PM2.5, while vehicular exhaust and secondary particles provided higher percentage contributions to PM2.5. In addition, PMF-HCA was performed to investigate the characteristics of the sources of the clustered samples, identifying three periods: crustal dust dominant-period, secondary sulfate dominant-period and comprehensive source influenced-period. Planting, reduction of precursors, and banning high-emission vehicles should be implemented to control crustal dust, secondary particles and vehicular exhaust in Chengdu. Furthermore, the size-resolved and the period-resolved control would be more effective.