[Retrieving Dustfall Distribution in Beijing City Based on Ground Spectral Data and Remote Sensing].

Dust-fall distribution of vegetation leaves can indicate the degree of air pollution; therefore the analysis of spatial characteristics of urban vegetation dust-fall has important practical significance for making more effective air pollution control policy. Based on the data of weight of dust, spectral reflectance and leaf area of Euonymus japonicus, Sophora japonica, poplar and davidiana collected in the main area of Beijing city, we compared the curve of spectrum of four plants "dust leaves" to "clean leaves"; the correlation analysis between leaf spectral reflectance ratio (Dust/Clean) of narrow band and satellite band was processed with the weight of dust-fall respectively, with application of four plants leaf data. Then, we built the regression model of the satellite band reflectance and NDVI with dustfall weight respectively, and we used the best model to retrieve the dust-fall distribution of vegetation coverage area in Beijing city, furthermore, we obtained the dust distribution of the whole Beijing city through interpolation. Finally, we carried out the rationality verification of the result by the land cover and land use of the high dust region, as well as the average concentration of PM10. The results showed that, dust leaves had an obviously lower reflectance than clean leaves in 780~1 300 nm which belonged to near-infrared bands; therewas a higher correlation between narrow band reflectance and dust-fall weight in 520~620 and 1 390~1 600 nm, up to -0.626; the coefficients of determination (R2) of inversion models were respectively 0.446 and 0.465,which were constructed by green band and NDVI of Landsat8 with dust-fall weight. Using the model established with NDVI to retrieving the dust-fall distribution of Beijing city, the results demonstrate that the distribution of dust-fall is high in north and low in south, high in east and low in west, high in downtown and low in the suburbs. This study offers a low-cost and effective method for investigating dust-fall distribution in urban area, and provides data support to analysis sources of pollution for the environmental protection department.

Dustfall Heavy Metal Pollution During Winter in North China.

In order to study heavy metal pollution in dustfall during Winter in North China, forty-four dustfall samples were collected in North China Region from November 2013 to March 2014. Then forty trace elements content were measured for each sample by inductively coupled plasma-mass spectrometry. Finally, the contamination characteristics of the main heavy metals were studied through a multi-method analysis, including variability analysis, Pearson correlation analysis and principal component analysis. Results showed that the relative contents of cadmium (Cd), zinc (Zn), copper (Cu), bismuth (Bi), lead (Pb) exceeded the standards stipulated in Chinese soil elements background values by amazing 4.9 times. In this study, conclusions were drawn that dustfall heavy metal pollution in the region was mainly caused by transport pollution, metallurgy industrial pollution, coal pollution and steel industrial pollution.

[The Study Based on Rectification of Vegetation Indices with Dust Impact].

Vegetation indices are the simplest and most effective metric parameters representing the features of vegetation cover and growth condition. This paper used Euonymus japonicas Thunb as a study case and collected 200 leaf samples in 20 locations. Using electronic analytical balance and ASD hyperspectral radiometer with Win FOLIA leaf area meter obtained the data of the amount of dust, spectral information and leaf area. Through comparative analysis between dust and clean leaves, differences of spectral curve and vegetation indices were apparent. Then, combined with dust weight and spectral data, dust correction models-for vegetation indices were built. The analysis results showed that the spectral curve between clean and dust leaves have typical characteristics: blue edge and red edge were at 520 and 705 nm; however, dust influenced leaf reflectance significantly in range of 350-700, 750-1 350, 1 500-1 850, 1 900-2 100 nm wavelength, and had a greater impact on vegetation indices. With dust weight increasing, the linear correlation of dust with NDVI AND PRI was non-significant, but that with NDWI, NDII and CAI was still significant. The verification of correction models showed that coefficient of determination (R2) of NDVI, NDII, CAI and PRI were 0.547, 0.430, 0.653 and 0.96 and their root mean square error (RMSE) was 0.035, 0.020, 0.112 and 0.009 respectively. Furthermore, it showed that applying dust correction models can improve the accuracy of vegetation indices calculation.

[Distribution Characteristics and Source Analysis of Dustfall Trace Elements During Winter in Beijing].

The dustfall content is one of the evaluation indexes of atmospheric pollution. Trace elements especially heavy metals in dustfall can lead to risks to ecological environment and human health. In order to study the distribution characteristics of trace elements, heavy metals pollution and their sources in winter atmospheric dust, 49 dustfall samples were collected in Beijing City and nearby during November 2013 to March 2014. Then the contents (mass percentages) of 40 trace elements were measured by Elan DRC It type inductively coupled plasma mass (ICP-MS). Test results showed that more than half of the trace elements in the dust were less than 10 mg x kg(-1); about a quarter were between 10-100 mg x kg-1); while 7 elements (Pb, Zr, Cr, Cu, Zn, Sr and Ba) were more than 100 mg x kg(-1). The contents of Pb, Cu, Zn, Bi, Cd and Mo of winter dustfall in Beijing city.were respectively 4.18, 4.66, 5.35, 6.31, 6.62, and 8.62 times as high as those of corresponding elements in the surface soil in the same period, which went beyond the soil background values by more than 300% . The contribution of human activities to dustfall trace heavy metals content in Beijing city was larger than that in the surrounding region. Then sources analysis of dustfall and its 20 main trace elements (Cd, Mo, Nb, Ga, Co, Y, Nd, Li, La, Ni, Rb, V, Ce, Pb, Zr, Cr, Cu, Zn, Sr, Ba) was conducted through a multi-method analysis, including Pearson correlation analysis, Kendall correlation coefficient analysis and principal component analysis. Research results indicated that sources of winter dustfall in Beijing city were mainly composed of the earth's crust sources (including road dust, construction dust and remote transmission of dust) and the burning of fossil fuels (vehicle emissions, coal combustion, biomass combustion and industrial processes).