中国西北侏罗纪煤系显微组分生烃潜力、产物地球化学特征及其意义

从吐哈盆地侏罗纪煤中分离富集了藻类体、孢子体、角质体、镜质体、基质镜质体和丝质体6种主要显微组分,进行了热解及热模拟实验,并对各显微组分热模拟生成的产物热解油进行了碳同位素组成等分析。各显微组分热解生烃潜力及其热解产物热解油的碳同位素组成表明,煤系有机质中藻类体的生油潜力最高,生成的液态烃类的碳同位素组成最轻;孢子体、角质体等陆源富氢组分生烃潜力低于藻类体,生成的液态烃类的碳同位素组成重于藻类体生成的液态烃类,与煤系含油气盆地中原油的碳同位素组成基本一致。这些富氢显微组分应该是煤系有机质中主要的生油显微组分。镜质体和基质镜质体的生油潜力相对较低,其生成的液态烃类的碳同位素组成比一般煤系原油重得多,而且这些组分本身对液态烃具有较强的吸附力,尽管其在煤系有机质中所占的比例很大,仍然难以成为生成液态石油的主要显微组分,只能在高成熟演化阶段成为良好的生气显微组分。丝质体等惰性组分生烃潜力极低,不可能成为生油组分。此外,结合原煤的显微组分组成、生烃潜力和元素分析,提出仅仅以壳质组的含量高低来评价煤的生烃潜力不完全可靠,热解是经济、快速、有效的评价方法。     

新疆准噶尔—东天山地区产于韧性剪切带中的金矿床成矿流体与碳、硫、铅同位素

韧性剪切带型金矿床是新疆准噶尔-东天山地区重要金矿类型。本文以科克萨依、康古尔、红石金矿为典型矿床,研究它们的流体包裹体均一温度、爆裂温度、包裹体成分、包裹体水的来源等,并进行了硫、铅同位素及近矿围岩碳同位素、矿体石英包裹体中CO2、CH4气体的碳同位素分析。结果表明,硫、铅为深源,暗示了本区金成矿物质的地幔来源。部分碳为有机碳,反映了本区年轻碳质沉积地层中有机碳参与了金的迁移与成矿作用。综合研究表明,在本区特定的后碰撞地质背景下,在构造挤压与伸展作用中形成的韧性剪切带中的金矿床金成矿物质源于深源,成矿流体主要是变质水。岩浆作用、变质作用、碳质围岩地层有机碳参与成矿,变质流体与岩浆热液及天水等流体的不同程度的混合与叠加,形成本区特征的韧性剪切带型金矿床。     

三极地区雪冰中黑碳研究进展

黑碳被认为是除温室气体外对气候变暖贡献最大的辐射强迫因子.三极(北极、南极和青藏高原)地区是全球雪冰分布最集中的区域,沉积至雪冰中的黑碳可反映人类活动的历史变化,并可能导致反照率降低而影响物质能量平衡.通过系统回顾三极地区雪冰黑碳的研究方法、空间分布、时间变化及其造成的辐射强迫,得到的研究结果表明:由于处于不同的地理位...     

赤道东北太平洋沉积物中生物钡的分布特征

分析了赤道东北太平洋海域沉积物中Ba、Ti、Al和有机碳(Corg)的含量。研究表明,研究区沉积物中钡为0.198%~0.792%;采用标准陆源物质扣除法获得的生物钡(Babio)的含量为0.162%~0.764%,占沉积物中总钡含量的81.6%~96.5%,平均为88.7%,其在沉积物中的分布表现为上部一致,下部变化较大;有机碳(Corg)的含量为0.18%~0.58%,并表现为随沉积物深度的增加而降低。沉积物中Babio/Ti的比值表现为东区高于西区,且向高纬度降低的特点,而沉积物中Corg/Ti和Babio/Ti则表现为负相关关系,表明研究区沉积物中钡可能和上层海洋生产力的相关性不明显。     

TOC-IRMS联用在线高温氧化测定溶解有机碳稳定同位素组成的方法研究

本研究利用总有机碳分析仪联用稳定同位素质谱仪(TOC-IRMS)技术,探讨了高温氧化法测试水体中溶解有机碳(Dissolved Organic Carbon, DOC)含量及稳定碳同位素组成。根据溶解有机碳的组成特征,从氧化难易程度、分子结构等方面选取5种可溶于水的化合物：咖啡因、葡萄糖、邻苯二甲酸、乙酸钾和腐殖酸钠,配置成DOC溶液。通过改变溶液碳含量、氧化温度、通氧量大小,载气流速等参数,研究不同实验条件对DOC碳转化率及δ¹³C值的影响。TOC-IRMS在氧化温度850℃,通氧时长20 s(流速10 cm³/min),载气流速80 cm³/min的条件下,测得5种化合物不同浓度DOC溶液的平均碳转化率为95.69%～103.57%;δ¹³C值与标定参考值基本一致,差值范围为-0.82‰～0.55‰。在上述实验条件下,测得不同类型水样的DOC含量相对标准偏差小于3.7%,δ¹³C值的标准偏差小于0.2‰,结果表明TOC-IRMS联用在线高温氧化法测定不同类型水样的DOC含量...     

Using Mesoproterozoic sedimentary geochemistry to reconstruct basin tectonic geography and link organic carbon productivity to nutrient flux from a Northern Australian large igneous Province

The Beetaloo Sub-basin, northern Australia, is considered the main depocentre of the 1,000-km scale Mesoproterozoic Wilton package of the greater McArthur Basin – the host to one of the oldest hydrocarbon global resources. The ca. 1.40–1.31 Ga upper Roper Group and the latest Mesoproterozoic to early Neoproterozoic unnamed group of the Beetaloo Sub-basin, together, record ca. 500 million years of depositional history within the North Australia Craton. Whole-rock shale Sm–Nd and Pb isotope data from these sediments reveal sedimentary provenance and their evolution from ca. 1.35 to 0.85 Ga. Furthermore, these data, together with shale major/trace elements data from this study and pyrolysis data from previous publications, are used to develop a dynamic tectonic geography model that links the organic carbon production and burial to an enhanced weathering of nutrients from a large igneous province. The ca. 1.35–1.31 Ga Kyalla Formation of the upper Roper Group is composed of isotopically evolved sedimentary detritus that passes up, into more isotopically juvenile Pb values towards the top of the formation. The increase in juvenile compositions coincides with elevated total organic carbon (TOC) contents of these sediments. The coherently enriched juvenile compositions and TOC the upper portions of the Kyalla Formation are interpreted to reflect an increase in nutrient supply associated with the weathering of basaltic sources (e.g. phosphorous). Possible, relatively juvenile, basaltic sources include the Wankanki Supersuite in the western Musgraves and the Derim Derim–Galiwinku large igneous province (LIP). The transition into juvenile, basaltic sources directly before a supersequence-bounding unconformity is here interpreted to reflect uplift and erosion of the Derim Derim–Galiwinku LIP, rather than an influx of southern Musgrave sources. A new baddeleyite crystallisation age of 1,312.9 ± 0.7 Ma provides both a tight constraint on the age of this LIP, along with its associated magmatic uplift, as well as providing a minimum age constraint for Roper Group deposition. The unconformably overlying lower and upper Jamison sandstones are at least 300 million years younger than the Kyalla Formation and were sourced from the Musgrave Province. An up-section increase in isotopically juvenile compositions seen in these rocks is interpreted to document the progressive exhumation of the western Musgrave Province. The overlying Hayfield mudstone received detritus from both the Musgrave and Arunta regions, and its isotopic geochemistry reveals affinities with other early Neoproterozoic basins (e.g. Amadeus, Victoria and Officer basins), indicating the potential for inter-basin correlations.     

中国居民食物消费碳排放时空演变趋势及其驱动机制分析

食物生产是影响温室效应气体排放的重要方面,由于食物类型不同其碳排强度存在较大的差异,因此当前中国居民食物消费快速演替必然会对生态碳环境产生重要影响。论文利用洛伦兹曲线和基尼系数,研究1997—2016年中国城乡居民食物消费在生产过程中碳排放时空演变及其主要驱动因子。主要结论如下：① 在数量上,中国居民食物消费碳排放总量和人均量整体都呈现逐渐的增长刚性,但仍属于低碳消费模式;② 在结构上,各类型食物碳排放演变呈现显著的分异态势,整体上动物性食物碳排放增长速度快于植物性食物碳排放减少速度;③ 在城乡差异上,城镇和乡村居民食物消费碳排放在数量、结构和趋势上表现出显著的城乡二元属性,但近年城乡差异表现出减缓趋势;④ 在空间上,各地食物消费碳排放呈现较显著的民族性、地域性、集聚性和中心“塌陷”的特征,碳排放密度高值主要分布在直辖市和沿海经济相对发达地区;⑤ 在驱动力上,结构演替是全国居民食物消费碳排放总量整体变化的主要驱动因素,而人口数量是各地地域空间差异分布的主要驱动因子。     

地方政府土地出让干预对区域工业碳排放影响的对比分析——以中国8大经济区为例

探讨不同区域地方政府干预对碳排放的影响差异,对于中国推进碳减排战略、协调区域经济社会发展具有重要意义。鉴于此,论文基于地方政府土地出让的视阈,以中国8大经济区为研究对象,有机耦合STIRPAT模型与CKC模型,构建形成STIRPAT拓展模型,并使用2007—2016年中国28个省(市、自治区)的工业面板数据,对比考察8大经济区政府土地出让干预对区域碳排放的影响差异。结果表明:不同经济区的地方政府土地出让干预对区域碳排放的影响存在显著差异。其中,同为CKC“倒N”型的北部沿海、南部沿海、长江中游经济区,其政府土地出让干预对区域碳排放的影响呈现出北部沿海经济区为负、南部沿海经济区为正、长江中游经济区无显著影响的差异效果;同为CKC“倒U”型的东北、西南和西北经济区,其政府土地出让干预对区域碳排放的影响,东北和西南经济区都显著为负,西北经济区未表现出显著影响;同为CKC“U”型的东部沿海和黄河中游经济区,其政府土地出让干预对碳排放也呈现出前者为负、后者为正的相反影响。研究结果可为制定碳减排差别化政策、协调区域可持续发展提供参考。     

Ecosystem carbon storage under different scenarios of land use change in Qihe catchment,China

Regional land use change is the main cause of the ecosystem carbon storage changes by affecting emission and sink process.However,there has been little research on the influence of land use changes for ecosystem carbon storage at both temporal and spatial scales.For this study,the Qihe catchment in the southern part of the Taihang Mountains was taken as an example;its land use change from 2005 to 2015 was analyzed,the Markov-CLUE-S composite model was used to predict land use patterns in 2025 under natural growth,cultivated land protection and ecological conservation scenario,and the land use data were used to evaluate ecosystem carbon storage under different scenarios for the recent 10-year interval and the future based on the carbon storage module of the In VEST model.The results show the following:(1) the ecosystem carbon storage and average carbon density of Qihe catchment were 3.16×107 t and 141.9 t/ha,respectively,and decreased by 0.07×107 t and 2.89 t/ha in the decade evaluated.(2) During 2005–2015,carbon density mainly decreased in low altitude areas.For high altitude area,regions with increased carbon density comprised a similar percentage to regions with decreased carbon density.The significant increase of the construction areas in the middle and lower reaches of Qihe and the degradation of upper reach woodland were core reasons for carbon density decrease.(3) For 2015–2025,under natural growth scenario,carbon storage and carbon density also significantly decrease,mainly due to the decrease of carbon sequestration capacity in low altitude areas;under cultivated land protection scenario,the decrease of carbon storage and carbon density will slow down,mainly due to the increase of carbon sequestration capacity in low altitude areas;under ecological conservation scenario,carbon storage and carbon density significantly increase and reach 3.19×107 t and 143.26 t/ha,respectively,mainly in regions above 1100 m in altitude.Ecological conservation scenario can enhance carbon sequestration capacity but cannot effectively control the reduction of cultivated land areas.Thus,land use planning of research areas should consider both ecological conservation and cultivated land protection scenarios to increase carbon sink and ensure the cultivated land quality and food safety.     

Regional soil organic carbon prediction model based on a discrete wavelet analysis of hyperspectral satellite data

Most studies have the achieved rapid and accurate determination of soil organic carbon (SOC) using laboratory spectroscopy; however, it remains difficult to map the spatial distribution of SOC. To predict and map SOC at a regional scale, we obtained fourteen hyperspectral images from the Gaofen-5 (GF-5) satellite and decomposed and reconstructed the original reflectance (OR) and the first derivative reflectance (FDR) using discrete wavelet transform (DWT) at different scales. At these different scales, as inputs, we selected the 3 optimal bands with the highest weight coefficient using principal component analysis and chose the normalized difference index (NDI), ratio index (RI) and difference index (DI) with the strongest correlation with the SOC content using a contour map method. These inputs were then used to build regional-scale SOC prediction models using random forest (RF), support vector machine (SVM) and back-propagation neural network (BPNN) algorithms. The results indicated that: 1) at a low decomposition scale, DWT can effectively eliminate the noise in satellite hyperspectral data, and the FDR combined with DWT can improve the SOC prediction accuracy significantly; 2) the method of selecting inputs using principal component analysis and a contour map can eliminate the redundancy of hyperspectral data while retaining the physical meaning of the inputs. For the model with the highest prediction accuracy, the inputs were all derived from the wavelength range of SOC variations; 3) the differences in prediction accuracy among the different prediction models are small; and 4) the SOC prediction accuracy using hyperspectral satellite data is greatly improved compared with that of previous SOC prediction studies using multispectral satellite data. This study provides a highly robust and accurate method for predicting and mapping regional SOC contents.