Research On The Climatic Characteristics And Factors Of Sand Emission Index As Well As Its Environmental Effects In The North Of China

There is a vast area of deserts and Gobi in the areas to the north of 35°N in China, which makes it one of the most important source regions of sandstorm in China, Asia or even the world, so it has a certain significance to make an analysis of it. An index was built and the characteristics of sand emission was analyzed on the basis of the days of dust storms and blowing sand of 277 weather stations in Northern China. Then the roles of relevant factors——vegetation coverage, wetness, strong wind days and thermal unstable days on sand emission were discussed and the environmental impacts was analyzed. The main conclusions are as follows:(1)By analyzing the temporal and spatial distribution of the sand emission index in Northern China, we found:①South Xinjiang District and Hexi District were the areas where it was most easy to blow sand away. The center was concentrated in Minfeng, Hetian in South Xinjiang District and Guaizihu, Minqin in Hexi District. It was not easy to blow sand up in Dongbei District. ② The sand emission index was higher in spring and summer while lower in autumn and winter. Spring was the most easy to blow sand and most of the regions reached the peak of the year in April. The smallest sand emission index occurred in winter in the districts of North Xinjiang District, South Xinjiang and Dongbei, and that of the other sub regions was in autumn. ③ The sand emission index has decreased since 1961 and the change key was in the 80s of twentieth century. After that, the sand emission index is gradually becoming smaller and smaller, especially in the 90s, when the decreasing trend was more obvious. And it’s harder to blow sand after 2000.(2) By analyzing the spatial correlation as well as temporal correlation of the sand emission index and its climatic factors, we found:① The vegetation coverage, wetness and unstable days showed significantly negative, negative and positive spatial correlation with the sand emission index, respectively. This illustrated that the land surface conditions of sand sources and unstable stratification factors played an important role on the regional distribution of sand. ② The roles of the climatic factors of which could impact the changes of sand emission index were different. There was a significantly positive correlation between strong wind days and sand emission index, which showed that the reduction of wind power, i.e.the decrease of strong wind days was the mainly reason for the decrease of sand emission index in Northern China. Moreover, the strong wind days mainly affected the districts of South Xinjiang, Hexi and Hetao in summer and autumn, while it had no significant effect on the district of Beijiang or Dongbei in winter. There was a negative correlation between vegetation coverage and sand emission index, which showed the rise of vegetation coverage may cause the decrease of sand emission index.The negative correlation was significant in the changes of the year as well as spring, while it was significant in part of the regions of Western Xinjiang, Hexi District, Qinghai District and Hetao District, but no significance in autumn or winter. There was a negative correlation between wetness and sand emission index, which was weaker than that of vegetation coverage. It only affected the sand land in spring, which showed that the rise of wetness may mainly decrease sand emission index in spring.(3)The PM50 sand emission rate in the north of China was calculated by the semi empirical formula of US EPA, we found:①The annual PM50 sand emission rate was higher in the west while lower in the east. The maximum was over 10 t/(km2·a) while the minimum was less than 0.001 t/(km2·a), so the maximum could be 104 times of the minimum. The contour of 0.1 t/(km2·a) could be used as the main dividing line of the sand sources, the west of which nearly covered all sandy areas in Northern China. ② The PM50 sand emission rate in the north of China showed a descending trend and the turning point was the late 80’s. The areas contained by the contour of 1 t/(km2·a) was shrinking. A similar performance was found on the annual sand rate series of the typical sites of the five deserts in northwest China.(4) By analyzing the influence of the upstream sand emission index on the air quality of Lanzhou, Yinchuan, Xining and Xi’an, we found:① The main atmospheric pollutants of the four cities of the year was PM10, and it was more obvious in spring, which showed the effect of PM10 on the urban air quality was significant.There was a significantly positive correlation between PM10 concentration and the reciprocal of visibility, especially that of Yinchuan and Lanzhou, which showed that the higher the reciprocal of visibility was, the higher the PM10 concentration was and the worse the air quality was.② Different lag time was chosen to calculate the correlation coefficient between the upstream sand emission index and the reciprocal of visibility. The results showed that the correlation coefficient distribution curves of Lanzhou and Yinchuan were similar. The effects by Tengger Desert was the most significant, followed by the Badanjilin Desert, and the two tendencies were similar. But the influence of Western Qaidam Basin Desert on the visibility of the two cities was not obvious. The lag time of the influence of Western Qaidam Basin Desert on the visibility of Xining and Xi’an was the shortest, while Tengger Desert and Badanjilin Desert affected later and the worst case response time was Eastern Xinjiang Gobi Desert. Therefore, the closer the distance between the sand sources and the city was, the earlier the urban air quality was influenced and the worse the air quality was.Above all, the sand emission index was showing a downward trend since 60s. Spring was the most easy to emit sand and centers were in the districts of Southern Xinjiang and Hexi. Vegetation coverage, wetness and unstable days influenced the spatial distribution of the sand emission index while strong wind days affected its temporal changes. The PM50 sand emission rate was higher in the west while lower in the east. The maximum could be 104 times of the minimum. The contour of 0.1 t/(km2·a) could be used as the main dividing line of sand sources zone. The closer the distance between the sand sources and the city was, the more the urban air quality was influenced.