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61.
Yang Xinghua Zhou Chenglong Huo Wen Yang Fan Liu Xinchun Mamtimin Ali 《Natural Hazards》2019,97(3):1069-1081
Natural Hazards - Soil and the atmospheric conditions are important factors that affect wind speed threshold of surface dust emissions. Based on the observed data of surface dust emissions in the... 相似文献
62.
Organochlorine pesticides (OCPs) are a class of toxic and harmful persistent organic pollutants widely found in environment. Hexachlorocyclohexane (HCHs) and DDTs are two of the most widely used OCPs (Qiu et al., 2004), so it is important to find out their compositional characteristics and sources in surface sediments. Guanghai Bay is located in the south of Guanghai Bay Industrial Park in Taishan City, Guangdong Province. It borders Huangmaohai to the east and Zhenhai Bay to the west, covering an area of about 236 square kilometers. In this study, surface sediments were collected at 16 sites in Guanghai Bay (Fig. 1). After the surface sediments were pretreated, GC‐MS was used to analyze OCPs. A total of 14 OCPs were detected and their content was shown in Table 1. The concentration of ΣOCPs ranged between 0.507~0.860ng·g‐1, with an average of 0.680 ng?g‐1. In general, the content of ΣOCPs was the highest at No. A12 site. The concentrations of these 14 detected OCPs ordered as dieldrin > epoxy heptachlor > P, P'‐DDD > γ‐HCH >endrin >aldrin > P, P'‐DDE >mirex >hexachlorobenzene >P, P'‐DDT > α‐HCH > δ‐HCH >β‐HCH > heptachlor. 相似文献
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Yu Zhi Shi Xiuzhi Zhou Jian Gou Yonggang Rao Dijun Huo Xiaofeng 《Natural Resources Research》2021,30(6):4063-4078
Natural Resources Research - In the process of open-pit bench blasting for many mines, rock fragments move in the direction of loose space after fragmentation under explosive energy, leading to ore... 相似文献
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Journal of Oceanology and Limnology - The increases of atmospheric carbon dioxide and other greenhouse gases have caused fundamental changes to the physical and biogeochemical properties of the... 相似文献
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69.
A new prediction model for grain yield in Northeast China based on spring North Atlantic Oscillation and late-winter Bering Sea ice cover
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Accurate estimations of grain output in the agriculturally important region of Northeast China are of great strategic significance for guaranteeing food security. New prediction models for maize and rice yields are built in this paper based on the spring North Atlantic Oscillation index and the Bering Sea ice cover index. The year-to-year increment is first forecasted and then the original yield value is obtained by adding the historical yield of the previous year. The multivariate linear prediction model of maize shows good predictive ability, with a low normalized root-mean-square error (NRMSE) of 13.9%, and the simulated yield accounts for 81% of the total variance of the observation. To improve the performance of the multivariate linear model, a combined forecasting model of rice is built by considering the weight of the predictors. The NRMSE of the model is 12.9% and the predicted rice yield explains 71% of the total variance. The corresponding cross-validation test and independent samples test further demonstrate the efficiency of the models. It is inferred that the statistical models established here by applying year-to-year increment approach could make rational prediction for the maize and rice yield in Northeast China before harvest. The present study may shed new light on yield prediction in advance by use of antecedent large-scale climate signals adequately. 相似文献
70.
GPS Solutions - We evaluate the performance of Galileo broadcast NeQuick model by comparing it with GPS broadcast Klobuchar and the original NeQuick2 models. The broadcast coefficients of Galileo... 相似文献