This study was to explore a bibliometric approach to quantitatively assessing current research trends on atmospheric aerosol, using the related literature in the Science Citation Index (SCI) database from 1991 to 2006. Articles were concentrated on the analysis by scientific output, research performances by individuals, institutes and countries, and trends by the frequency of keywords used. Over the years, there had been a notably growth trend in research outputs, along with more participation and collaboration of institutes and countries. Research collaborative papers shifted from national inter-institutional to international collaboration. The decreasing share of world total and independent articles by the seven major industrialized countries (G7) was examined. Aerosol research in environmental and chemical related fields other than in medical fields was the mainstream of current years. Finally, author keywords, words in title and keywords plus were analyzed contrastively, with research trends and recent hotspots provided.

Source contributions to ambient PM10 (particles with an aerodynamic diameter of 10 μm or less) in Beijing, China were determined with positive matrix factorization (PMF) based on ambient PM10 composition data including concentrations of organic carbon (OC), elemental carbon (EC), ions and metal elements, which were simultaneously obtained at six sites through January, April, July and October in 2004. Results from PMF indicated that seven major sources of ambient PM10 were urban fugitive dust, crustal soil, coal combustion, secondary sulfate, secondary nitrate, biomass burning with municipal incineration, and vehicle emission, respectively. In paticular, urban fugitive dust and crustal soil as two types of dust sources with similar chemical characteristics were differentiated by PMF. Urban fugitive dust contributed the most, accounting for 34.4% of total PM10 mass on an annual basis, with relatively high contributions in all four months, and even covered 50% in April. It also showed higher contributions in southwestern and southeastern areas than in central urban areas. Coal combustion was found to be the primary contributor in January, showing higher contributions in urban areas than in suburban areas with seasonal variation peaking in winter, which accounted for 15.5% of the annual average PM10 concentration. Secondary sulfate and secondary nitrate combined as the largest contributor to PM10 in July and October, with strong seasonal variation peaking in summer, accounting for 38.8% and 31.5% of the total PM10 mass in July and October, respectively. Biomass burning with municipal incineration contributions were found in all four months and accounted for 9.8% of the annual average PM10 mass concentration, with obviously higher contribution in October than in other months. Incineration sources were probably located in southwestern Beijing. Contribution from vehicle emission accounted for 5.0% and exhibited no significant seasonal variation. In sum, PM10 source contributions in Beijing showed not only significant seasonal variations but also spatial differences.

Theoretical molecular descriptors were tested against log KOW values for polybrominated diphenyl ethers (PBDEs) using the Partial Least-Squares Regression method which can be used to analyze data with many variables and few observations. A quantitative structure–property relationship (QSPR) model was successfully developed with a high cross-validated value (Qcum2)">(Qcum2) of 0.961, indicating a good predictive ability and stability of the model. The predictive power of the QSPR model was further cross-validated. The values of log KOW for PBDEs are mainly governed by molecular surface area, energy of the lowest unoccupied molecular orbital and the net atomic charges on the oxygen atom. All these descriptors have been discussed to interpret the partitioning mechanism of PBDE chemicals. The bulk property of the molecules represented by molecular surface area is the leading factor, and KOW values increase with the increase of molecular surface area. Higher energy of the lowest unoccupied molecular orbital and higher net atomic charge on the oxygen atom of PBDEs result in smaller KOW. The energy of the lowest unoccupied molecular orbital and the net atomic charge on PBDEs oxygen also play important roles in affecting the partition of PBDEs between octanol and water by influencing the interactions between PBDEs and solvent molecules.

Multiyear emission inventories of anthropogenic NMVOCs in China for 1980–2005 were established based on time-varying statistical data, literature surveyed and model calculated emission factors, which were further gridded at a high spatial resolution of 40 km×40 km using the GIS methodology. Results show a continuous growth trend of China's historical NMVOCs emissions during the period of 1980–2005, with the emission increasing by 4.2 times at an annual average rate of 10.6% from 3.91 Tg in 1980 to 16.49 Tg in 2005. Vehicles, biomass burning, industrial processes, fossil fuel combustion, solvent utilization, and storage and transport generated 5.50 Tg, 3.84 Tg, 2.76 Tg, 1.98 Tg, 1.87 Tg, and 0.55 Tg of NMVOCs, respectively, in 2005. Motorcycles, biofuel burning, heavy duty vans, synthetic fibre production, biomass open burning, and industrial and commercial consumption were primary emission sources. Besides, source contributions of NMVOCs emissions showed remarkable annual variation. However, emissions of these sources had been continuously increasing, which coincided well with China's economic growth. Spatial distribution of NMVOCs emissions illustrates that high emissions mainly concentrates in developed regions of northern, eastern and southern coastal areas, which produced more emissions than the relatively underdeveloped western and inland regions. Particularly, southeastern, northern, and central China covering 35.2% of China's territory, generated 59.4% of the total emissions, while the populous capital cities covering merely 4.5% of China's territory, accounted for 24.9% of the national emissions. Annual variation of regional emission intensity shows that emissions concentrating in urban areas tended to transfer to rural areas year by year. Moreover, eastern, southern, central, and northeastern China were typical areas of high emission intensity and had a tendency of expanding to the northwestern China, which revealed the transfer of emission-intensive plants to these areas, together with the increase of biomass open burning.