Estimating water quality pollution impacts based on economic loss models in urbanization process in Xi'an；China

IEECAS SKLLQG

The air pollution caused by the burning of fireworks during the lantern festival in Beijing

IEECAS SKLLQG

Carbonaceous aerosols in PM10 and pollution gases in winter in Beijing

IEECAS SKLLQG

Chemical composition of dust storms in Beijing and implications for the mixing of mineral aerosol with pollution aerosol on the pathway

IEECAS SKLLQG

Water-soluble part of the aerosol in the dust storm season - evidence of the mixing between mineral and pollution aerosols

IEECAS SKLLQG

Dinoflagellate cysts as potential indicators of industrial pollution in a Norwegian Fjord

Variation in dinoflagellate cyst assemblages through the last approximately 300 years was studied in two sediment cores, one from the heavily polluted Frierfjord, and one from the adjoining, relatively unpolluted Brevikfjord, in order to docu1ent possible dinoflagellate responses to pollution. Changes in the cyst-flora were compared with historical information on the development of industry and also with geochemistry of the sediments, reflecting aspects of pollution. In the Frierfjord core, increasing pollution was accompanied by a decrease in cyst concentration, possibly reflecting reduced production, at least of dinoflagellates, and a shift toward more heterotrophic species, possibly reflecting reduced light penetration in the euphotic zone, or increased production of prey for the heterotrophs. These trends seem to have reversed as pollution decreased after about 1975, suggesting that cyst assemblages contain signals that may prove useful for tracing the development of pollution. Cyst assemblages in the Brevikfjord core only showed minor changes.

A QUANTITATIVE ASSESSMENT OF SOURCE CONTRIBUTIONS TO INHALABLE PARTICULATE MATTER POLLUTION IN METROPOLITAN BOSTON

In this paper, source apportionment techniques are employed to identify and quantify the major particle pollution source classes affecting a monitoring site in metropolitan Boston, MA. A Principal Component Analysis (PCA) of paniculate elemental data allows the estimation of mass contributions for five fine mass panicle source classes (soil, motor vehicle, coal related, oil and salt aerosols), and six coarse panicle source classes (soil, motor vehicle, refuse incineration, residual oil, salt and sulfate aerosols). Also derived are the elemental characteristics of those source aerosols and their contributions to the total recorded elemental concentrations (i.e. an elemental mass balance). These are estimated by applying a new approach to apportioning mass among various PCA source components: the calculation of Absolute Principal Component Scores, and the subsequent regression of daily mass and elemental concentrations on these scores.

Spatial distribution of soil heavy metal pollution estimated by different interpolation methods: Accuracy and uncertainty analysis

Mapping the spatial distribution of contaminants in soils is the basis of pollution evaluation and risk control. Interpolation methods are extensively applied in the mapping processes to estimate the heavy metal concentrations at unsampled sites. The performances of interpolation methods (inverse distance weighting, local polynomial, ordinary kriging and radial basis functions) were assessed and compared using the root mean square error for cross validation. The results indicated that all interpolation methods provided a high prediction accuracy of the mean concentration of soil heavy metals. However, the classic method based on percentages of polluted samples, gave a pollution area 23.54-41.92% larger than that estimated by interpolation methods. The difference in contaminated area estimation among the four methods reached 6.14%. According to the interpolation results, the spatial uncertainty of polluted areas was mainly located in three types of region: (a) the local maxima concentration region surrounded by low concentration (clean) sites, (b) the local minima concentration region surrounded with highly polluted samples; and (c) the boundaries of the contaminated areas. (C) 2010 Elsevier Ltd. All rights reserved.