[Objective]The study aimed to analyze the influencing factors of low-carbon economy and its mitigation countermeasures in Sichuan Province.[Method]Taking Sichuan Province as an example,an extended STIRPAT model was es...[Objective]The study aimed to analyze the influencing factors of low-carbon economy and its mitigation countermeasures in Sichuan Province.[Method]Taking Sichuan Province as an example,an extended STIRPAT model was established firstly,then the impacts of population,economy and technology on carbon emissions from 2000 to 2009 were analyzed econometrically by using the principal component analysis method.Finally,some corresponding countermeasures to reduce carbon dioxide emissions were put forward.[Result]At present,population scale had the greatest influence on carbon emissions in Sichuan Province,then energy consumption per industrial added value and the proportion of industrial added value to GDP.In addition,the influence of population scale on carbon emissions was still greater than that of population structure,and technical factor also has certain explanatory power on carbon emissions.Some countermeasures,like controlling population growth,advocating low-carbon life style and consumption model,paying more attention to the strategic adjustment of industrial structure to gradually reduce the proportion of high-carbon industries,encouraging energy consumption and emissions reduction plus scientific and technological innovation in a new energy technology filed,could be adopted to reduce carbon dioxide emissions,so as to adjust to the development of low-carbon economy in Sichuan Province.[Conclusion]The research could provide references for the establishment of policies for reducing carbon emissions.展开更多
Estimating heavy metal(HM) distribution with high precision is the key to effectively preventing Chinese medicinal plants from being polluted by the native soil. A total of 44 surface soil samples were gathered to det...Estimating heavy metal(HM) distribution with high precision is the key to effectively preventing Chinese medicinal plants from being polluted by the native soil. A total of 44 surface soil samples were gathered to detect the concentrations of eight HMs(As, Hg, Cu, Cr, Ni, Zn, Pb, and Cd) in the herb growing area of Luanping County, northeastern Hebei Province, China. An absolute principal component score-multiple linear regression(APCS-MLR) model was used to quantify pollution source contributions to soil HMs. Furthermore, the source contribution rates and environmental data of each sampling point were simultaneously incorporated into a stepwise linear regression model to identify the crucial indicators for predicting soil HM spatial distributions. Results showed that 88% of Cu, 72% of Cr, and 72% of Ni came from natural sources;50% of Zn, 49% of Pb, and 59% of Cd were mainly caused by agricultural activities;and 44% of As and 56% of Hg originated from industrial activities. When three-type(natural, agricultural, and industrial) source contribution rates and environmental data were simultaneously incorporated into the stepwise linear regression model, the fitting accuracy was significantly improved and the model could explain 31%–86% of the total variance in soil HM concentrations. This study introduced three-type source contributions of each sampling point based on APCS-MLR analysis as new covariates to improve soil HM estimation precision, thus providing a new approach for predicting the spatial distribution of HMs using small sample sizes at the county scale.展开更多
The distribution of diatoms from surface sediments of the West Philippine Basin was analyzed, with 68 species and varieties of diatoms from 26 genera identified. Diatom abundance varied spatially, with the absolute ab...The distribution of diatoms from surface sediments of the West Philippine Basin was analyzed, with 68 species and varieties of diatoms from 26 genera identified. Diatom abundance varied spatially, with the absolute abundance of diatoms ranging from 0 to 3.4× 104 frustules/g. The seven tropical pelagic diatoms were Alveus marinus, Azpeitia africana, Azpeitia nodulifera, Hemidiscus cuneiformis, Hernidiscus cuneiformis var. ventricosus, Roperia tesselata and Rhizosolenia bergonii. The relative abundance of these species was greater than 20%, and their distribution pattern in the sediments was overlaid by the flow of the Kuroshio Current. Ethmodiscus rex was present at 159 stations, formed the most abundant and dominant species in the diatomaceous ooze, and thus referred to as Ethmodiscus ooze. Ethmodiscus rex was also a major contributor to primary production in the region. A principal component analysis was employed to explain the relationship between samples and variations in diatom species from the WPB. Four diatom assemblages were distinguished, representing different oceanographic conditions; their spatial distributions were closely related with the North Equatorial Current and Kuroshio Current patterns in the region. These diatom assemblages can therefore be useful in deciphering late Quaternary palaeoceanographic reconstructions of the West Philippine Basin.展开更多
文摘[Objective]The study aimed to analyze the influencing factors of low-carbon economy and its mitigation countermeasures in Sichuan Province.[Method]Taking Sichuan Province as an example,an extended STIRPAT model was established firstly,then the impacts of population,economy and technology on carbon emissions from 2000 to 2009 were analyzed econometrically by using the principal component analysis method.Finally,some corresponding countermeasures to reduce carbon dioxide emissions were put forward.[Result]At present,population scale had the greatest influence on carbon emissions in Sichuan Province,then energy consumption per industrial added value and the proportion of industrial added value to GDP.In addition,the influence of population scale on carbon emissions was still greater than that of population structure,and technical factor also has certain explanatory power on carbon emissions.Some countermeasures,like controlling population growth,advocating low-carbon life style and consumption model,paying more attention to the strategic adjustment of industrial structure to gradually reduce the proportion of high-carbon industries,encouraging energy consumption and emissions reduction plus scientific and technological innovation in a new energy technology filed,could be adopted to reduce carbon dioxide emissions,so as to adjust to the development of low-carbon economy in Sichuan Province.[Conclusion]The research could provide references for the establishment of policies for reducing carbon emissions.
基金supported by the special project of the National Key Research and Development Program of China(Nos.2021YFC1809104 and 2018YFC1800104)。
文摘Estimating heavy metal(HM) distribution with high precision is the key to effectively preventing Chinese medicinal plants from being polluted by the native soil. A total of 44 surface soil samples were gathered to detect the concentrations of eight HMs(As, Hg, Cu, Cr, Ni, Zn, Pb, and Cd) in the herb growing area of Luanping County, northeastern Hebei Province, China. An absolute principal component score-multiple linear regression(APCS-MLR) model was used to quantify pollution source contributions to soil HMs. Furthermore, the source contribution rates and environmental data of each sampling point were simultaneously incorporated into a stepwise linear regression model to identify the crucial indicators for predicting soil HM spatial distributions. Results showed that 88% of Cu, 72% of Cr, and 72% of Ni came from natural sources;50% of Zn, 49% of Pb, and 59% of Cd were mainly caused by agricultural activities;and 44% of As and 56% of Hg originated from industrial activities. When three-type(natural, agricultural, and industrial) source contribution rates and environmental data were simultaneously incorporated into the stepwise linear regression model, the fitting accuracy was significantly improved and the model could explain 31%–86% of the total variance in soil HM concentrations. This study introduced three-type source contributions of each sampling point based on APCS-MLR analysis as new covariates to improve soil HM estimation precision, thus providing a new approach for predicting the spatial distribution of HMs using small sample sizes at the county scale.
基金Supported by the National Natural Science Foundation of China(Nos.41306083,41106076)the Special Fund for Scientific Research Foundation of the Third Institute of Oceanography,State Oceanic Administration,China(Nos.2010002,2013032)
文摘The distribution of diatoms from surface sediments of the West Philippine Basin was analyzed, with 68 species and varieties of diatoms from 26 genera identified. Diatom abundance varied spatially, with the absolute abundance of diatoms ranging from 0 to 3.4× 104 frustules/g. The seven tropical pelagic diatoms were Alveus marinus, Azpeitia africana, Azpeitia nodulifera, Hemidiscus cuneiformis, Hernidiscus cuneiformis var. ventricosus, Roperia tesselata and Rhizosolenia bergonii. The relative abundance of these species was greater than 20%, and their distribution pattern in the sediments was overlaid by the flow of the Kuroshio Current. Ethmodiscus rex was present at 159 stations, formed the most abundant and dominant species in the diatomaceous ooze, and thus referred to as Ethmodiscus ooze. Ethmodiscus rex was also a major contributor to primary production in the region. A principal component analysis was employed to explain the relationship between samples and variations in diatom species from the WPB. Four diatom assemblages were distinguished, representing different oceanographic conditions; their spatial distributions were closely related with the North Equatorial Current and Kuroshio Current patterns in the region. These diatom assemblages can therefore be useful in deciphering late Quaternary palaeoceanographic reconstructions of the West Philippine Basin.
