Carbon pools and fluxes in the China Seas and adjacent oceans

The China Seas include the South China Sea, East China Sea, Yellow Sea, and Bohai Sea. Located off the Northwestern Pacific margin, covering 4700000 km~2 from tropical to northern temperate zones, and including a variety of continental margins/basins and depths, the China Seas provide typical cases for carbon budget studies. The South China Sea being a deep basin and part of the Western Pacific Warm Pool is characterized by oceanic features; the East China Sea with a wide continental shelf, enormous terrestrial discharges and open margins to the West Pacific, is featured by strong cross-shelf materials transport; the Yellow Sea is featured by the confluence of cold and warm waters; and the Bohai Sea is a shallow semiclosed gulf with strong impacts of human activities. Three large rivers, the Yangtze River, Yellow River, and Pearl River, flow into the East China Sea, the Bohai Sea, and the South China Sea, respectively. The Kuroshio Current at the outer margin of the Chinese continental shelf is one of the two major western boundary currents of the world oceans and its strength and position directly affect the regional climate of China. These characteristics make the China Seas a typical case of marginal seas to study carbon storage and fluxes. This paper systematically analyzes the literature data on the carbon pools and fluxes of the Bohai Sea,Yellow Sea, East China Sea, and South China Sea, including different interfaces(land-sea, sea-air, sediment-water, and marginal sea-open ocean) and different ecosystems(mangroves, wetland, seagrass beds, macroalgae mariculture, coral reefs, euphotic zones, and water column). Among the four seas, the Bohai Sea and South China Sea are acting as CO_2 sources, releasing about0.22 and 13.86–33.60 Tg C yr~(-1) into the atmosphere, respectively, whereas the Yellow Sea and East China Sea are acting as carbon sinks, absorbing about 1.15 and 6.92–23.30 Tg C yr~(-1) of atmospheric CO_2, respectively. Overall, if only the CO_2 exchange at the sea-air interface is considered, the Chinese marginal seas appear to be a source of atmospheric CO_2, with a net release of 6.01–9.33 Tg C yr~(-1), mainly from the inputs of rivers and adjacent oceans. The riverine dissolved inorganic carbon (DIC) input into the Bohai Sea and Yellow Sea, East China Sea, and South China Sea are 5.04, 14.60, and 40.14 Tg C yr~(-1),respectively. The DIC input from adjacent oceans is as high as 144.81 Tg C yr~(-1), significantly exceeding the carbon released from the seas to the atmosphere. In terms of output, the depositional fluxes of organic carbon in the Bohai Sea, Yellow Sea, East China Sea, and South China Sea are 2.00, 3.60, 7.40, and 5.92 Tg C yr~(-1), respectively. The fluxes of organic carbon from the East China Sea and South China Sea to the adjacent oceans are 15.25–36.70 and 43.93 Tg C yr~(-1), respectively. The annual carbon storage of mangroves, wetlands, and seagrass in Chinese coastal waters is 0.36–1.75 Tg C yr~(-1), with a dissolved organic carbon(DOC) output from seagrass beds of up to 0.59 Tg C yr~(-1). Removable organic carbon flux by Chinese macroalgae mariculture account for 0.68 Tg C yr~(-1) and the associated POC depositional and DOC releasing fluxes are 0.14 and 0.82 Tg C yr~(-1), respectively. Thus, in total, the annual output of organic carbon, which is mainly DOC, in the China Seas is 81.72–104.56 Tg C yr~(-1). The DOC efflux from the East China Sea to the adjacent oceans is 15.00–35.00 Tg C yr~(-1). The DOC efflux from the South China Sea is 31.39 Tg C yr~(-1). Although the marginal China Seas seem to be a source of atmospheric CO_2 based on the CO_2 flux at the sea-air interface, the combined effects of the riverine input in the area, oceanic input, depositional export,and microbial carbon pump(DOC conversion and output) indicate that the China Seas represent an important carbon storage area.     

Application of the HY-1 satellite to sea ice monitoring and forecasting

The HY-1A satellite is the first oceanic satellite of China. During the winter of 2002～2003, the data of the HY-1A were applied to the sea ice monitoring and forecasting for the Bohai Sea of China for the first time. The sea ice retrieval system of the HY-1A has been constructed. It receives 1B data from the satellite, outputs sea ice images and provides digital products of ice concentration, ice thickness and ice edge, which can be used as important information for sea ice monitoring and the initial fields of the numeric sea ice forecast and as one of the reference data for the sea ice forecasting verification. The sea ice retrieval system of the satellite is described, including its processes, methods and parameters. The retrieving results and their application to the sea ice monitoring and forecasting for the Bohai Sea are also discussed.     

秦岭造山带南秦岭地区发现石英脉型黑钨矿点

正1研究目的(Objective)钨矿是中国的优势矿种,储量占世界总储量的61%以上(张洪川,2017)。国内已经探明的钨资源主要分布在江西、湖南、河南、广东、甘肃等9省,秦岭成矿带有没有钨矿?前人根据华南地区钨矿床空间分布规律曾提出"南钨北扩""、东钨西扩"的认识(王登红等,2012),而"南钨北扩"是否能够延伸至秦岭中央造山带?2014年陕西省镇安西部整装勘查区金铜钨     

2020年6月26日新疆于田6.4级地震前中期和短期预测依据与启示

2020年6月26日新疆于田6.4级地震发生在2020年度全国地震危险区内,震前作出了较好的中期（年度）和短期（月尺度和周尺度）预测,是少有的地球物理观测能力较低地区的强震前中期和短临预测较好震例。本文梳理了中期和短期预测的主要依据及其预测效能,研究表明,震前中期异常主要有流动地磁、多方法组合、5.0级地震平静打破、6.0级地震的准周期活动等;短期异常有4.0级地震活动图像、中源地震影响、于田垂直摆倾斜EW、于田GNSS基准站EW位移、和田GNSS基准站EW位移等。在总结震前分析预测过程的基础上,提出针对地球物理观测密度低地区的地震危险区论证和短临跟踪的建议,为该类地区的地震危险区判定及跟踪工作提供宝贵经验。     

2020年5月6日新疆乌恰5.0级和5月9日柯坪5.2级地震总结

2020年5月6日、5月9日,新疆地区南天山西段先后发生乌恰5.0级和柯坪5.2级地震,系统总结2次地震发生前出现的地震活动和地球物理观测异常,其中：①地震活动：震前存在调制地震集中、地震窗、5级以上地震成组等中短期异常;②地球物理观测：2次地震震中附近震前出现形变、电磁和流体观测异常,其中形变异常3项、电磁异常4项、流体异常1项,主要分布在柯坪5.2级地震震中附近。通过对2次地震序列进行跟踪,发现：乌恰5.0级地震余震较少,震后60天内共记录M_L 3.0以上余震4次,最大震级为M_L 4.5;柯坪5.2级地震后余震较丰富,震后60天内共记录M_L 3.0以上余震10次,最大震级为M_L 4.7,计算得到序列h值为1.6,b值为0.73。综合分析认为,2020年5月新疆地区2次5级以上地震前存在的地震活动异常较少,但区域地震活动水平较强,主要存在具有中短期指示意义的地球物理观测异常。     

2020年2月3日四川青白江5.1级地震总结

针对2020年2月3日四川青白江5.1级地震发生前的地震活动和地球物理观测异常、构造背景、震源物理参数,以及地震序列特征等进行系统总结。结果表明,青白江5.1级地震发生前存在小震调制比高值、地磁低点位移、重力固体潮高噪声等中短期异常;地震序列活动特征显示,此次地震为一次孤立型地震序列,序列参数计算结果与当前余震活动水平基本相符。另外,青白江地震发生在龙泉山断裂带上,震源机制计算结果显示为一次逆冲型破裂事件,与龙泉山断裂构造性质一致。同时,此次地震发生在四川盆地的少震弱震区,对于川滇及川滇藏交界地区后续7级以上地震的发生具有一定预测意义。     

2020年1月25日西藏丁青5.1级地震总结

2020年1月25日,藏东昌都丁青地区发生5.1级地震,尽管此次地震发生在监测能力较低地区,但震前仍监测到小震调制比高值、低b值等地震活动中短期异常。文中系统总结了地震构造背景、震源物理参数、序列特征以及震前出现的地震活动和地球物理观测等异常,结果发现：震源机制解显示为拉张型破裂,最近断裂为巴青—类乌齐断裂;序列活动特征、序列h值和b值计算结果显示,此次地震为主余型地震序列。目前,藏东地区仍存在一些地震活动和地球物理观测异常,表明该地区存在发生6级以上地震的强震背景,丁青5.1级地震的发生未能缓解该地区强震危险性。     

基于贝叶斯定理的地震危险性概率预测研究

由于地震孕育过程的复杂性和观测技术的局限性,不同地震观测资料表现出异常变化与后续较大地震的对应关系存在不确定性,因此对预测意见进行概率表达是一种科学恰当的做法。本文基于泊松分布的危险区背景地震概率预测和单项预测方法(包括测震、流体、形变、电磁等学科)的历史预测效能,采用贝叶斯定理计算得到单项预测方法的短期或年度地震危险概率预测结果,进而采用综合概率方法,给出基于多种单项预测方法的短期或年度地震危险概率预测结果。短期概率预测初步结果表明,2018年2～9月,中国大陆72%的5级以上地震都位于相对高概率预测区域。     

外源NO对野生早熟禾幼苗抗寒性的影响

以野生草地早熟禾（Poa pratensis）和硬质早熟禾（Poa sphondylodes）为材料,通过人工室内模拟低温逆境胁迫,研究外源一氧化氮（NO）供体亚硝基铁氰化钠（硝普钠,SNP）对低温胁迫下野生早熟禾幼苗生长、渗透调节和抗氧化系统的影响,探讨外源NO提高早熟禾抗寒性的生理机制。结果表明,低温胁迫下：0~700 μmol·L^-1浓度范围内,随SNP浓度的增大,两个供试材料的地上生物量和生长速度先增大后减小,相对膜透性、丙二醛（MDA）含量、游离脯氨酸（F-Pro）含量先减小后增大,可溶性糖（SS）和可溶性蛋白（SP）含量先增加后减小,超氧化物歧化酶（SOD）、过氧化物酶（POD）和过氧化氢酶（CAT）活性先增强后减弱;高浓度NO产生伤害,低浓度NO则有保护作用;SNP浓度100 μmol·L^-1时,膜脂过氧化水平最低,渗透调节物质积累最多,保护酶活性最强,对低温胁迫的缓解效果最佳。硬质早熟禾对低温胁迫下外源NO的缓解较草地早熟禾敏感。     

东南极内陆格罗夫山地区冰厚及冰下地形特征

中国第30次南极科学考察队格罗夫山分队(CHINARE30, 2013-2014年)利用雪地车载深层探冰雷达在东南极格罗夫山地区开展了测线总长度超过200 km大范围、高分辨率的冰厚及冰下地形调查, 获得了哈丁山北部和萨哈罗夫岭与阵风悬崖之间详细的冰厚及冰下地形特征. 通过对雷达数据分析表明, 哈丁山北部区域平均冰厚为580 m, 最大冰厚超过1 000 m, 出现在该区域的东北方向, 而东南方向冰厚相对较小; 萨哈罗夫岭与阵风悬崖之间区域的平均冰厚为610 m, 最大冰厚超过1 100 m, 该区域槽谷发育十分成熟, 槽谷形态近似呈U型. 通过对雷达剖面影像的筛选和分析, 推测在格罗夫山地区可能存在2个液态冰下湖泊.