|
|
|
题名
|
作者
|
年代
|
出处
|
被引量
|
| 1 | Chemical characteristics of haze particles in Xi'an during Chinese Spring Festival: Impact of fireworks burning显示文摘Fireworks burning releases massive fine particles and gaseous pollutants, significantly deteriorating air quality during Chinese Lunar New Year(LNY) period. To investigate the impact of the fireworks burning on the atmospheric aerosol chemistry, 1-hr time resolution of PM_(2.5) samples in Xi'an during the winter of 2016 including the LNY were collected and detected for inorganic ions, acidity and liquid water content(LWC) of the fine aerosols. PM_(2.5) during the LNY was 167 ± 87 μg/m^3, two times higher than the China National Ambient Air Quality Standard(75 μg/m^3). K^+(28 wt.% of the total ion mass) was the most abundant ion in the LNY period, followed by SO_4^(2-)(25 wt.%) and Cl-(18 wt.%). In contrast, NO_3^-(34 wt.%) was the most abundant species in the haze periods(hourly PM32-2.5> 75 μg/m), followed by SO_4(29.2 wt.%) and NH_4^+(16.3 wt.%), while SO_4^(2-)(35 wt.%) was the most abundant species in the clean periods(hourly PM_(2.5)< 75 μg/m^3), followed by NO_3^-(23.1 wt.%) and NH_4^+(11 wt.%). Being different from the acidic nature in the non-LNY periods, aerosol in the LNY period presented an alkaline nature with a pH value of 7.8 ± 1.3. LWC during the LNY period showed a robust linear correlation with K_2SO_4 and KCl, suggesting that aerosol hygroscopicity was dominated by inorganic salts derived from fireworks burning. Analysis of correlations between the ratios of NO--3/SO_4^(2-) and NH_4^+/SO_4^(2-) indicated that heterogeneous reaction of HNO_3 with NH_3 was an important formation pathway of particulate nitrate and ammonium during the LNY period. | Can Wu Gehui Wang Jiayuan Wang Jianjun Li Yanqin Ren Lu Zhang Cong Cao Jin Li Shuagshuang Ge Yuning Xie Xinpei Wang Guoyan Xue | 2018 | Journal of Environmental Sciences2018，30，9： | 10 |
| 2 | Single-/fused-band dual-mode mid-infrared imaging with colloidal quantum-dot triple-junctions显示文摘Image data acquired with fused multispectral information can be used for effective identification and navigation owing to additional information beyond human vision,including thermal distribution,night vision,and molecular composition.However,the construction of photodetectors with such capabilities is hindered by the structural complexity arising from the integration of multiple semiconductor junctions with distinct energy gaps and lattice constants.In this work,we develop a colloidal quantum-dot dual-mode detector capable of detecting,separating,and fusing photons from various wavelength ranges.Using three vertically stacked colloidal quantum-dot homojunctions with alternating polarity,single-band short-wave infrared imaging and fused-band imaging(short-wave and mid-wave infrared)can be achieved with the same detector by controlling bias polarity and magnitude.The dual-mode detectors show detectivity up to 8×10^(10)Jones at the fused-band mode and 3.1×10^(11)Jones at the single-band mode,respectively.Without image post-processing algorithms,the dual-mode detectors could provide both night vision and thermal information-enhanced night vision imaging capability.To the best of our knowledge,this is the first colloidal quantum-dot detector that can achieve such functionality.The operation mode can be changed at a high frequency up to 1.7 MHz,making it possible to achieve simultaneously dual-mode imaging and remote temperature sensing. | SHUO ZHANG GE MU JIE CAO YUNING LUO QUN HAO MENGLU CHEN YIMEI TAN PENGFEI ZHAO XIN TANG | 2022 | Photonics Research2022，10，8： | 3 |
| 3 | Mussel-inspired chemistryand Stober method for highly stabilized water-in-oil emulsions separation显示文摘 | Cao Yingze Chen Yuning Liu Na | 2014 | The Royal Society of Chemistry2014，，20： | 1 |
| 4 | Underflow concentration prediction model of deep-cone thickener based on data-driven显示文摘The underflow concentration prediction of deep-cone thickener is a difficult problem in paste filling. The existing prediction model only determines the influence of some parameters on the underflow concentration, but lacks a prediction model that comprehensively considers the thickening process and various factors. This paper proposed a model which analyzed the variation of the underflow concentration from a number of influencing factors in the concentrating process. It can accurately predict the underflow concentration. After preprocessing and feature selection of the history data set of the deep-cone thickener, this model uses the eXtreme gradient boosting(XGBOOST) in machine learning to deal with the relationship between the influencing factors and the underflow concentration, so as to achieve a more comprehensive prediction of the underflow concentration of the deep-cone thickener. The experimental results show that the underflow concentration prediction model based on XGBOOST shows a mean absolute error(MAE) of 0.31% and a running time of 1.6 s on the test set constructed in this paper, which fully meet the demand. By comparing the following three classical algorithms: back propagation(BP) neural network, support vector regression(SVR) and linear regression, we further verified the superiority of XGBOOST under the conditions of this study. | Wang Huan Liu Ting Cao Yuning Wu Aixiang | 2019 | The Journal of China Universities of Posts and Telecommunications2019，26，6： | 0 |
| 5 | Response of Distribution Range Against Climate Change and Habitat Preference of Four National Protected Diploderma Species in Tibetan Plateau显示文摘Understanding the spatial distribution and habitat preference for rare and endangered species are essential for effective conservation practice.We examined the spatial distribution and habitat preference of four Diploderma species(Diploderma drukdaypo,D.laeviventre,D.batangense,and D.vela),which are endemic to the Qinghai-Tibet Plateau and are currently under state protection.We used the ensembles of small models(ESM)approach and predicted potential distribution ranges of the species in current and two future climate scenarios(SSP126 and SSP585).The degree of overlap between the predicted distribution ranges and existing natural reserves was further analyzed.Habitat preference was examined using a paired quadrat method.Our results predicted that D.drukdaypo has a current distribution range of 600 km^(2),which would decrease to 50 km^(2)and 55 km^(2)under the SSP126 and SSP585 respectively.For D.laeviventre,the current distribution range is 817 km^(2),with minimum changes in the two future climate scenarios(774 km^(2)and 902 km^(2)).For D.batangense,the current distribution range is 875 km^(2),which would expand to 1522 km^(2)and 3340 km^(2)in the two future climate scenarios.Similarly for D.vela,the current distribution range is 1369 km^(2),which would change to 1825 km^(2)and 2043 km^(2)respectively under the two future climate scenarios.The effect of protection of current nature reserves are likely low for those species;we found no overlap(D.drukdaypo,D.laeviventre)or little overlap(D.batangense 2.04%–3.56%,D.vela 15.52%–16.87%)between the currently designated protection area and distribution range under current and future climate scenarios.For habitat preference,stones appear to be the critical habitat element for those species although different species had different stone requirements.Taken together,we provided critical information on potential distribution ranges and habitat preference for four endangered Diploderma species,and confirmed the inadequacy of current nature reserves.The establishment of new or expansion of existing nature reserves is urgent for the conservation of those species. | Lin SHI Xiudong SHI Yuning CAO Yayong WU Haijuan WEI Youhua CHEN Ziyan LIAO Yin QI | 2023 | Asian Herpetological Research2023，14，4： | 0 |
您所在的机构暂未开通此部分的功能，请联系管理员