采集了忻州市4个监测点位采暖季和非采暖季环境空气PM10样品,利用Elementar Analysensysteme GmbH vario EL cube测定有机碳(organic carbon,OC)和元素碳(elemental carbon,EC)的质量浓度,通过OC和EC的时空分布、比值以及相关性分析揭...采集了忻州市4个监测点位采暖季和非采暖季环境空气PM10样品,利用Elementar Analysensysteme GmbH vario EL cube测定有机碳(organic carbon,OC)和元素碳(elemental carbon,EC)的质量浓度,通过OC和EC的时空分布、比值以及相关性分析揭示忻州市的碳组分污染特征.结果表明,忻州市PM10中OC和EC的平均质量浓度分别为(18.5±4.5)μg·m-3和(16.1±4.3)μg·m-3,采暖季和非采暖季TCA占PM10的比例分别为70.7%和43.8%;4个监测点位采暖季OC的质量浓度均高于非采暖季,XT、DC和KQ监测点采暖季EC的质量浓度高于非采暖季,SQ监测点则相反,采暖季燃煤是OC和EC的主要来源;监测点XT的OC质量浓度最高,为24.1μg·m-3,DC的EC质量浓度最高,为22.0μg·m-3,SQ的OC和EC质量浓度最低,分别为17.2μg·m-3和14.5μg·m-3,区域性污染特征存在差异;OC/EC均值小于2,一次污染严重;非采暖季OC与EC浓度相关性较好(R2=0.55),二者排放源单一,主要来源为机动车尾气排放,采暖季相关性不显著(R2=0.13),二者排放源复杂.忻州市主要通过控制燃煤、机动车尾气、生物质燃烧、工业源等的一次排放来减轻碳组分污染,进而提高环境空气质量.展开更多
采集朔州市市区4个点位采暖季和非采暖季环境空气PM2.5样品,利用Elementar Analysensysteme Gmb H vario EL cube型元素分析仪测定其中元素碳(elemental carbon,EC)和有机碳(organic carbon,OC)含量,并对碳组分的浓度水平、时空分布特...采集朔州市市区4个点位采暖季和非采暖季环境空气PM2.5样品,利用Elementar Analysensysteme Gmb H vario EL cube型元素分析仪测定其中元素碳(elemental carbon,EC)和有机碳(organic carbon,OC)含量,并对碳组分的浓度水平、时空分布特征和主要来源进行分析.结果表明,朔州市市区非采暖季PM2.5中OC和EC的平均浓度为(14.3±2.7)μg·m-3和(10.3±3.1)μg·m-3,采暖季OC、EC平均浓度分别为(23.3±5.9)μg·m-3和(20.0±5.7)μg·m-3;4个点位OC和EC的浓度均表现为采暖季大于非采暖季,其中在采暖季,点位SW中OC和EC浓度分别为28.5μg·m-3和28.1μg·m-3,高于其它采样点,在非采暖季,点位PS中OC和EC的浓度分别为17.7μg·m-3和14.1μg·m-3高于其它采样点;采暖季和非采暖季PM2.5中OC/EC值均小于2,但OC和EC相关性不好(在采暖季和非采暖季的相关系数分别为0.66和0.52),说明PM2.5中碳气溶胶来源复杂.控制碳组分一次排放来源,如燃煤烟尘、生物质燃烧及机动车尾气排放,同时关注二次污染是控制朔州市PM2.5的关键.朔州市市区采暖季和非采暖季PM2.5中二次有机碳(secondary organic carbon,SOC)浓度分别为(6.44±2.77)μg·m-3和(4.11±1.92)μg·m-3.展开更多
文章对神农架地区中元古界神农架群野马河组和温水河组碳酸盐岩开展研究,采用5%的HCl对新鲜碳酸盐岩样进行溶解,对溶液开展Fe、As、Ce测定,对酸溶残渣开展拉曼光谱和X射线衍射分析,同时采用分级提取法开展样品的黄铁矿矿化度(degree of ...文章对神农架地区中元古界神农架群野马河组和温水河组碳酸盐岩开展研究,采用5%的HCl对新鲜碳酸盐岩样进行溶解,对溶液开展Fe、As、Ce测定,对酸溶残渣开展拉曼光谱和X射线衍射分析,同时采用分级提取法开展样品的黄铁矿矿化度(degree of pyritization,DOP)测定。结果表明:石墨拉曼光谱法和绿泥石结晶度法测定的2套地层变质温度相同,均为300℃左右;野马河组样品DOP值均小于0.42,该地层沉积环境相对氧化;1/2温水河组样品的DOP值大于0.42,该地层沉积环境相对还原;野马河组中碳酸盐结合态(carbonated-associated)Fe(Feca)与Asca、Ceca均呈正相关性,而温水河组中Feca与Asca、Ceca均无相关性。研究发现:Feca与Asca、Ceca的相关性可以示踪沉积氧化还原条件,即正相关指示氧化性沉积条件,不相关指示还原性沉积条件;300℃左右的变质温度对该指标没有影响。展开更多
Ionomic profiles are primarily influenced by genetic and environmental factors.Identifying ionomic responses to varietal effects is necessary to understand the ionomic variations among species or subspecies and to pot...Ionomic profiles are primarily influenced by genetic and environmental factors.Identifying ionomic responses to varietal effects is necessary to understand the ionomic variations among species or subspecies and to potentially understand genetic effects on ionomic profiles.We cultivated 120 rice(Oryza sativa)varieties to seedling stage in identical hydroponic conditions and determined the concentrations of 26 elements(including 3 anions)in the shoots and roots of rice.Although the subspecies effects were limited by the genus Oryza pre-framework and its elemental chemical properties,we found significant differences in ionomic variations in most elements among the aus,indica and japonica subspecies.Principal component analysis of the correlations indicated that variations in the root-to-shoot ionomic transport mechanisms were the main causes of ionomic differences among the subspecies.Furthermore,the correlations were primarily associated with the screening of varieties for elemental covariation effects that can facilitate breeding biofortified rice varieties with safe concentrations of otherwise toxic elements.The japonica subspecies exhibited the strongest elemental correlations and elemental covariation effects,therefore,they showed greater advantages for biofortification than the indica and aus subspecies,whereas indica and aus subspecies were likely safer in metal(loid)polluted soils.We also found that geographical and historical distribution significantly defined the ionomic profiles.Overall,the results of this study provided a reference for further association studies to improve the nutritional status and minimize toxicity risks in rice production.展开更多
文摘采集了忻州市4个监测点位采暖季和非采暖季环境空气PM10样品,利用Elementar Analysensysteme GmbH vario EL cube测定有机碳(organic carbon,OC)和元素碳(elemental carbon,EC)的质量浓度,通过OC和EC的时空分布、比值以及相关性分析揭示忻州市的碳组分污染特征.结果表明,忻州市PM10中OC和EC的平均质量浓度分别为(18.5±4.5)μg·m-3和(16.1±4.3)μg·m-3,采暖季和非采暖季TCA占PM10的比例分别为70.7%和43.8%;4个监测点位采暖季OC的质量浓度均高于非采暖季,XT、DC和KQ监测点采暖季EC的质量浓度高于非采暖季,SQ监测点则相反,采暖季燃煤是OC和EC的主要来源;监测点XT的OC质量浓度最高,为24.1μg·m-3,DC的EC质量浓度最高,为22.0μg·m-3,SQ的OC和EC质量浓度最低,分别为17.2μg·m-3和14.5μg·m-3,区域性污染特征存在差异;OC/EC均值小于2,一次污染严重;非采暖季OC与EC浓度相关性较好(R2=0.55),二者排放源单一,主要来源为机动车尾气排放,采暖季相关性不显著(R2=0.13),二者排放源复杂.忻州市主要通过控制燃煤、机动车尾气、生物质燃烧、工业源等的一次排放来减轻碳组分污染,进而提高环境空气质量.
文摘采集朔州市市区4个点位采暖季和非采暖季环境空气PM2.5样品,利用Elementar Analysensysteme Gmb H vario EL cube型元素分析仪测定其中元素碳(elemental carbon,EC)和有机碳(organic carbon,OC)含量,并对碳组分的浓度水平、时空分布特征和主要来源进行分析.结果表明,朔州市市区非采暖季PM2.5中OC和EC的平均浓度为(14.3±2.7)μg·m-3和(10.3±3.1)μg·m-3,采暖季OC、EC平均浓度分别为(23.3±5.9)μg·m-3和(20.0±5.7)μg·m-3;4个点位OC和EC的浓度均表现为采暖季大于非采暖季,其中在采暖季,点位SW中OC和EC浓度分别为28.5μg·m-3和28.1μg·m-3,高于其它采样点,在非采暖季,点位PS中OC和EC的浓度分别为17.7μg·m-3和14.1μg·m-3高于其它采样点;采暖季和非采暖季PM2.5中OC/EC值均小于2,但OC和EC相关性不好(在采暖季和非采暖季的相关系数分别为0.66和0.52),说明PM2.5中碳气溶胶来源复杂.控制碳组分一次排放来源,如燃煤烟尘、生物质燃烧及机动车尾气排放,同时关注二次污染是控制朔州市PM2.5的关键.朔州市市区采暖季和非采暖季PM2.5中二次有机碳(secondary organic carbon,SOC)浓度分别为(6.44±2.77)μg·m-3和(4.11±1.92)μg·m-3.
文摘文章对神农架地区中元古界神农架群野马河组和温水河组碳酸盐岩开展研究,采用5%的HCl对新鲜碳酸盐岩样进行溶解,对溶液开展Fe、As、Ce测定,对酸溶残渣开展拉曼光谱和X射线衍射分析,同时采用分级提取法开展样品的黄铁矿矿化度(degree of pyritization,DOP)测定。结果表明:石墨拉曼光谱法和绿泥石结晶度法测定的2套地层变质温度相同,均为300℃左右;野马河组样品DOP值均小于0.42,该地层沉积环境相对氧化;1/2温水河组样品的DOP值大于0.42,该地层沉积环境相对还原;野马河组中碳酸盐结合态(carbonated-associated)Fe(Feca)与Asca、Ceca均呈正相关性,而温水河组中Feca与Asca、Ceca均无相关性。研究发现:Feca与Asca、Ceca的相关性可以示踪沉积氧化还原条件,即正相关指示氧化性沉积条件,不相关指示还原性沉积条件;300℃左右的变质温度对该指标没有影响。
基金partly financially supported by a Grant-in-Aid for Scientific Research from the Japan Society for the Promotion of Science(Grant No.20K05762)China Scholarship Council(Grant No.201806990031)。
文摘Ionomic profiles are primarily influenced by genetic and environmental factors.Identifying ionomic responses to varietal effects is necessary to understand the ionomic variations among species or subspecies and to potentially understand genetic effects on ionomic profiles.We cultivated 120 rice(Oryza sativa)varieties to seedling stage in identical hydroponic conditions and determined the concentrations of 26 elements(including 3 anions)in the shoots and roots of rice.Although the subspecies effects were limited by the genus Oryza pre-framework and its elemental chemical properties,we found significant differences in ionomic variations in most elements among the aus,indica and japonica subspecies.Principal component analysis of the correlations indicated that variations in the root-to-shoot ionomic transport mechanisms were the main causes of ionomic differences among the subspecies.Furthermore,the correlations were primarily associated with the screening of varieties for elemental covariation effects that can facilitate breeding biofortified rice varieties with safe concentrations of otherwise toxic elements.The japonica subspecies exhibited the strongest elemental correlations and elemental covariation effects,therefore,they showed greater advantages for biofortification than the indica and aus subspecies,whereas indica and aus subspecies were likely safer in metal(loid)polluted soils.We also found that geographical and historical distribution significantly defined the ionomic profiles.Overall,the results of this study provided a reference for further association studies to improve the nutritional status and minimize toxicity risks in rice production.
