No abstract

To reveal the multivariate relationships between man-made and meteorological factors on dust storm frequency, the LUCC data, NDVI remote sensing data and meteorological data for the period of 1983-2013 were combined with dust storm frequency data, and the possible impacts of meteorological and anthropogenic factors on dust storm frequency were analyzed by using regression analysis and PCA (Principal Component Analysis). Results show that the inter-annual dust storm frequency increased gradually. In particular, an increasing trend in recent years, after 2009, is conspicuous. The monthly frequency of dust storms shows higher values between the months of February and May, with the highest mean number of events occurring in April, which accounts for 29% of the annual dust storm frequency. The annual dust storm frequency is positively correlated with wind speed and negatively correlated with precipitation; the monthly dust storm frequency is positively correlated with wind speed, but no significant correlation can be found with precipitation. The relationship between temperature and dust storms is not simply linear, however, a certain correlation with an unremarkable statistical significance can be found between them. Human activities also affect the dynamics of dust storms indirectly via changing vegetation coverage and direct dust emissions. The multivariate analysis further confirmed the association between dust storm frequency and meteorological factors and NDVI. The high loadings of dust storm frequency, wind speed, precipitation and NDVI on a PC indicate that the increased precipitation and NDVI will decrease dust storm frequency, and increased wind speed will increase dust storm frequency.

The Taklimakan Desert in Northwest China is the major source of dust storms in China. The northeast edge of this desert is a typical arid area which houses a fragile oasis eco-environment. Frequent dust storms cause harmful effects on the oasis ecosystem and negative impacts on agriculture, transportation, and human health. In this study, the major source region, transport pathway, and the potential contribution of dust storms to particulate air pollution were identified by using both trajectory analysis and monitoring data. To assess the source regions of dust storms, 48 h backward trajectories of air masses arriving at the Bugur (Luntai) County, which is located at the northeast edge of Taklimakan Desert, China on the dusty season (spring) and non-dusty month (August, representing non-dusty season) in the period of 1999–2013, were determined using Hybrid Single Particle Lagrangian Integrated Trajectory model version 4 (HYSPLIT 4). The trajectories were categorized by k-means clustering into 5 clusters (1a–5a) in the dusty season and 2 clusters (1b and 2b) in the non-dusty season, which show distinct features in terms of the trajectory origins and the entry direction to the site. Daily levels of three air pollutants measured at a station located in Bugur County were analyzed by using Potential Source Contribution Function (PSCF) for each air mass cluster in dusty season. The results showed that TSP is the major pollutant, with an average concentration of 612 µg/m3, as compared to SO2 (23 µg/m3) and NO2 (32 µg/m3) in the dusty season. All pollutants were increased with the dust weather intensity, i.e., from suspended dust to dust storms. High levels of SO2 and NO2 were mostly associated with cluster 1a and cluster 5a which had trajectories passing over the anthropogenic source regions, while high TSP was mainly observed in cluster 4a, which has a longer pathway over the shifting sand desert area. Thus, on strong dust storm days, not only higher TSP but also higher SO2 and NO2 levels were observed as compared to normal days. The results of this study could be useful to forecast the potential occurrence of dust storms based on meteorological data. Research focusing on this dust-storm-prone region will help to understand the possible causes for the changes in the dust storm frequency and intensity, which can provide the basis for mitigation of the negative effects on human health and the environment.

Dust storms have already become the most serious environmental problem on the south edge of the Taklimakan desert because of their frequent occurrences. To investigate the health effects of dust storms on public health in Moyu County, one of the most severe dust-storm-affected areas located at the south edge of the Taklimakan desert, China, primary data were collected from 1200 respondents by using a questionnaire survey for 15 health symptoms. The data were analyzed by comparing the mean tool (independent t-test and ANOVA) and the severity of different symptoms among different age groups. Principal component analysis (PCA) was applied to further analyze the multivariate relationships between meteorological factors, dust storm intensity, air pollution level, and severity degree of the different symptoms. The results show that significant correlations exist between dust storm intensity, air pollutants (PM2.5, PM10, O3, SO2, NO2, and CO), meteorological factors, and health symptoms. During dusty weather, no matter the age group, the number of respondents who suffered from different health symptoms was higher compared to non-dusty days. Three types of dusty days were considered in this study: suspended dust, blowing dust, and sand storms. The impacts of sand storm weather on public health are stronger than those from blowing dust weather, suspended dust weather (haze), and non-dust weather. The people in the age groups above 60 years and below 15 years were more sensitive to different dust weather than people in the age groups between 15 and 60. “Dry throat with bitter taste”, “Depression”, “Dry and itchy throat”, and “Mouth ulcer” are the main symptoms caused by dust storms.