The Source Profiles Replacement And Receptor Data Expansion And Their Application In Source Apportionment Of PM₁₀ In Lanzhou

Many studies have found that the particulate matters (PM) have several adverse effects on human health, air pollution and global climate change. The development of effective control strategies for understanding the sources that contribute to the particulate matter concentrations and their emission features are important. Source apportionment is an exactly method which is using qualitative and quantitative analysis to identify the different sources and their contributions to PM. In recent years, receptor models have become important tools for identifying and quantifing the PM in which chemical mass balance (CMB) model and multivariate models are commonly used methods. The reliability of the analytical results of the CMB model was directly determined by the reasonableness and accuracy of source profiles, while the stability of multivariate receptor models’ results increased with the number of samples. Therefore, the feasibility and rationality of replaceable source profiles were considered and vertified in this paper, and the principle of normal distribution method was adopted to generate the simulate receptor data. On the basis of the establishment of replaceable source profiles and simulate receptor data, the source apportionment of atmospheric inhalable particulate matter (PM10) and polycyclic aromatic hydrocarbons in PM10in Lanzhou was performed by using data collected in2010and from December2010to January2012, and determined the main pollution sources and source contribution.(1) Determine the establishment method of replaceable source profiles of PM10.The effective source profiles of same kind source which were collected in35cities were clustered to the appropriate classes by hierarchical cluster analysis and evaluated by variance analysis. Then, the replaceable source profiles were established based on the weighting sum of the calculating component scores which were obtained by principal components method. The reasonability and feasibility of the established replaceable source profiles were evaluated with correlation coefficient (R), coefficient of divergence (CD) and relative error (RE) of source contributions apportioned by CMB model between the determined and replaceable source profiles. It was established that replaceable profiles for six kinds of pollutant source were three kinds of coal fly ash dust and re-suspended dust, two kinds of soil dust, metal smelt dust and construction cement dust, and only one kind of vehicle exhaust dust. The replaceable source profiles of coal combustion fly ash, soil dust and metal smelt dust could be directly used to source apportionment as they are similar with the determined source profiles. There was no obviously regional division for construction cement dust profiles, and it could be considered by the type of cement and chemical characteristics of building materials, whether could be replaced by the replaceable source profile. Source profile of vehicle exhaust dust was suggested to be determined due to the lack of representative source data. It showed that there were certain correlations among re-suspended dust, soil dust, and construction cement dust, and this correlation reduced within the process of establishment of replaceable source profiles, so more works were needed to be done for its replacement.(2) The method for the expansion of receptor dataFollowing the principle of the pollutant dispersion transmission and the requirement of ambient receptor samples for multivariate receptor models, the mean mass concentration and standard deviation were used in the method of normal distribution by setting the limitations of none negative values and small variances between simulate data and the means for the expansion of the receptor data.The models of PCA/APCS and PMF were applied to verify the feasibility and reasonability of the data expansion, which predicted that the normal expansion could meet the basic distribution characteristics of the PM in ambient environment, and the expansion of receptor data could let the species correlation more stable, and could derive more reasonable and stable apportionment results.(3) Source apportionment of PM10in Lanzhou city.The models of CMB and PMF were applied to apportion the inorganic constituents including metal elements and water soluble ions in PM10. Mixed sources would be derived by the multivariate receptor models since the number of sources and correlation among species would affect the accuracy of apportionment results. Base on the replaceable source profiles, more detailed concentrations and contributions of each source were obtained by CMB model.It seemed that there were some differences between two models’results, but the same source types were obtained. Soil dust and construction cement dust (37.2%), vehicle exhaust dust (22.5%), coal fly ash dust (31.9%) and second dust (8.5%) were obtained by PMF model. Meanwhile, the CMB results showed that soil dust (27.4%), construction cement dust (5.2%), vehicle exhaust dust (26.8%), coal fly ash dust (26.6%), second dust (8.6%) and metal smelt dust (1.3%) were the major source contributors in PM10.It’s failed to establish replaceable source profiles for PAHs because of the highly variability and diversity of PAHs. The receptor data which got by normal expansion was used by the multivariate receptor models to identify the sources of PAHs in PM10in Lanzhou. Qualitative and quantitative analysis methods were applied; and the results showed that vehicle exhaust (29.8%), coal combustion (22.8%) and cook oil combustion (15.7%) were the major source contributors of PAHs in PM10. In addition, the judgement to the source of petroleum refineries (31.4%) has some uncertainty, and further studies were needed to decide the source more accurately by analyzing the determined source profile.