Establishment of apparent quantum yield and maximum ecosystem assimilation on Tibetan Plateau alpine meadow ecosystem

The alpine meadow is widely distributed on the Tibetan Plateau with an area of about 1.2×106kn2. Damxung County, located in the hinterland of the Tibetan Plateau, is the place covered with this typical vegetation. An open-path eddy covariance system was set up in Damxung rangeland station to measure the carbon flux of alpine meadow from July to October,2003. The continuous carbon flux data were used to analyze the relationship between net ecosystem carbon dioxide exchange (NEE) and photosynthetically active radiation (PAR), as well as the seasonal patterns of apparent quantum yield (α) and maximum ecosystem assimilation (Pmax).Results showed that the daytime NEE fitted fairly well with the PAR in a rectangular hyperbola function, with α declining in the order of peak growth period (0.0244 μmolCO2 · μmol-1pAR) ＞early growth period ＞ seed maturing period ＞ withering period (0.0098 μmolCO2 · μmol-1pAR).The Pmax did not change greatly during the first three periods, with an average of 0.433mgCO2· m-2· s-1, i.e. 9.829 μmolCO2· m-2· s-1. However, during the withering period, Pmax was only 0.35 mgCO2 · m-2 · s-1, i.e. 7.945 μmolCO2 · m-2 · s-1. Compared with other grassland ecosystems, the α of the Tibetan Plateau alpine meadow ecosystem was much lower.     

Study of statistically correcting model CMAQ-MOS for forecasting regional air quality

Based on analysis of the air pollution observational data at 8 observation sites in Beijing including outer suburbs during the period from September 2004 to March 2005, this paper reveals synchronal and in-phase characteristics in the spatial and temporal variation of air pollutants on a city-proper scale at deferent sites; describes seasonal differences of the pollutant emission influence between the heating and non-heating periods, also significantly local differences of the pollutant emission influence between the urban district and outer suburbs, i.e. the spatial and temporal distribution of air pollutant is closely related with that of the pollutant emission intensity. This study shows that due to complexity of the spatial and temporal distribution of pollution emission sources, the new generation Community Multi-scale Air Quality (CMAQ) model developed by the EPA of USA produced forecasts, as other models did, with a systematic error of significantly lower than observations, albeit the model has better capability than previous models had in predicting the spatial distribution and variation tendency of multi-sort pollutants. The reason might be that the CMAQ adopts average amount of pollutant emission inventory, so that the model is difficult to objectively and finely describe the distribution and variation of pollution emission sources intensity on different spatial and temporal scales in the areas, in which the pollution is to be forecast. In order to correct the systematic prediction error resulting from the average pollutant emission inventory in CMAQ, this study proposes a new way of combining dynamics and statistics and establishes a statistically correcting model CMAQ-MOS for forecasts of regional air quality by utilizing the relationship of CMAQ outputs with corresponding observations, and tests the forecast capability. The investigation of experiments presents that CMAQ-MOS reduces the systematic errors of CMAQ because of the uncertainty of pollution emission inventory and improves the forecast level of air quality. Also this work employed a way of combining point and area forecasting, i.e. taking the products of CMAQ for a center site to forecast air pollution for other sites in vicinity with the scheme of model products "reanalysis" and average over the "area".     

The diurnal and seasonal characteristics of urban heat island variation in Beijing city and surrounding areas and impact factors based on remote sensing satellite data

Based on the land surface temperature (LST), the land cover classification map,vegetation coverage, and surface evapotranspiration derived from EOS-MODIS satellite data, and by the use of GIS spatial analytic technique and multivariate statistical analysis method, the urban heat island (UHI) spatial distribution of the diurnal and seasonal variabilities and its driving forces are studied in Beijing city and surrounding areas in 2001. The relationships among UHI distribution and landcover categories, topographic factor, vegetation greenness, and surface evapotranspiration are analyzed. The results indicate that: (i) The significant UHI occur in Beijing city areas in the four seasons due to high heat capacity and multi-reflection of compression building, as well as with special topographic features of its three sides surrounded by mountains,especially in the summer. The UHI spatial distribution is corresponding with the urban geometry structure profile. The LST difference is approximately 4-6℃ between Beijing city and suburb areas, comparatively is 8- 10℃ between Beijing city area and outer suburb area in northwestern regions. (ii) The UHI distribution and intensity in daytime are different from nighttime in Beijing city area, the nighttime UHI is obvious. However, in the daytime, the significant UHI mainly appears in the summer, the autumn takes second place, and the UHI in the winter and the spring seem not obvious. The surface evapotranspiration in suburb areas is larger than that in urban areas in the summer, and high latent heat exchange is evident, which leads to LST difference between city area and suburb area. (iii) The reflection of surface landcover categories is sensitive to the UHI, the correlation between vegetation greenness and UHI shows obviously negative.The scatterplot shows that there is the negative correlation between NDVI and LST (R2 = 0.6481).The results demonstrate that the vegetation greenness is an important factor for reducing the UHI,and large-scale construction of greenbelts can considerably reduce the UHI effect.     

基于多模态感知的水下目标检测应用构想

水下目标检测在海洋生物研究、考古探索、军事防御等多领域广泛应用,随着人工智能快速发展,水下目标检测也朝着无人化、智能化发展。深度学习采用神经网络挖掘信息特征,在速度和精度上均表现出优异的性能,成为了计算机视觉技术的主流算法,然而水下环境复杂,将其应用于水下图像目标检测仍存在较大的挑战。水下目标各模态信息互补,特征丰富,有利于目标检测识别,因此结合应用场景调研现有技术,然后设计基于深度学习的多模态水下目标检测系统,同时对比分析了现有关键技术的优缺点,最后对多模态目标检测系统未来发展进行总结与展望,具有重要意义。     

基于YOLO算法的海洋中尺度涡三维结构构建

海洋中尺度涡是一种常见的中尺度海洋现象,研究海洋中尺度涡的分布及运动特性对航运、气候、军事等具有重要作用,海洋中尺度涡的识别是海洋学和计算机科学领域的一个热门研究课题。运用深度学习的方法和框架,对中尺度涡的二维识别和三维结构构建展开研究分析。首先,获取全球海洋再分析数据并进行流线可视化,构建涡旋流线数据集;其次,利用YOLO v5s卷积神经网络对涡旋流线数据集进行训练,并对南海区域中尺度涡进行有效检测。实验结果表明,YOLO v5s训练后得到最优模型经过测试,平均检测精度均值达到了86.10%;最后,根据涡旋检测结果,对检测出的同时刻不同深度的涡旋判断是否属于同一涡旋,确定后进行该涡旋的三维结构构建。     

采用泵喷补偿技术的近底拖体水压场数值模拟研究

采用标准 k-ε 模型,结合 Fluent 软件,对采用泵喷补偿技术的拖体水下被拖行运动所产生的压力场变化进行了数值模拟实验。结果表明：采用泵喷补偿技术对拖体水压场的“马鞍形”分布特性影响较小, 但随着喷水速度的增加,拖体首端压力负值略有增加,而中段的负峰幅值显著增加,当喷水速度达到一定值后,拖体的压力特性曲线已经较为接近期望值,证明泵喷补偿技术具有一定的可行性。     

辽宁省精细化暴雨洪涝灾害风险评估与预评估

基于辽宁省61个国家气象站1961—2020年和998个区域自动气象观测站建站至2020年逐小时、逐日降水资料,分析了辽宁省暴雨洪涝灾害主要致灾因子,计算了暴雨洪涝孕灾环境指标,完成了辽宁省暴雨洪涝灾害危险性评估。结果表明：暴雨洪涝高危险性地区主要位于丹东;暴雨洪涝灾害人口高风险区主要位于沈阳和大连市区;经济高风险区主要位于大连和盘锦市区;水稻、玉米高风险区主要位于锦州、盘锦和丹东。利用辽宁省无缝隙智能网格预报数据对2022年7月28—29日的暴雨过程灾害风险进行了预评估,发现暴雨灾害危险性高值区域主要分布在朝阳、葫芦岛以及辽宁中部。暴雨灾害可能造成的人口、经济高风险区域主要位于辽宁西部和中部地区;暴雨灾害可能造成的水稻和玉米高风险区主要位于沈阳、铁岭和朝阳北部等地区。预计高风险区主要影响人口约为449万人,经济损失约为1432万元,受影响的水稻面积约为1.028万公顷、玉米面积约为1.798万公顷。通过灾后效果检验,发现预评估模型效果良好,可在实际的暴雨洪涝灾害风险评估业务中使用。     

广西钦江河口枯季水动力特征及其对冷空气的响应

河口作为陆海相互作用的关键带,是河流入海泥沙及污染物的主要归宿地。钦江作为广西第二大河流,在茅尾海资源开发利用和生态环境保护与修复中发挥着重要作用。为进一步认识钦江河口地区的沉积动力过程,2021年10月27日至12月8日在此展开水动力和水体环境要素的连续观测。现场观测与分析结果表明,观测期间钦江河口潮汐类型为正规全日潮,浅水分潮显著,平均潮差为3.07 m,具有落潮优势;潮流以全日分潮流为主导,平均流速为0.12 m/s,运动形式主要为往复流;余流流向主要为西南方向。钦江河口潮汐和潮流性质较外湾和茅尾海中部海域全日潮特征更显著。枯季期间河口表层沉积物随潮汐运动表现为侵蚀-沉降交替的变化规律,垂向上侵蚀通量大于沉降通量,水平方向上悬沙净向海输运。冷空气过境带来的降雨使得钦江河口水体盐度降低、浊度增大,悬沙浓度及输沙量增加,同时冷空气南下时北风增强引起钦江河口减水效应并使潮差略有增加,水动力强度增大,增加表层沉积物的活动性,从而引起底部沉积物再悬浮强度和频率增加。     

1996-2022年黄河三角洲行水河口岸线稳定性研究

黄河清八汊现行河口自改汊以来发生了巨大变化,监测其岸线变化,探讨其稳定程度对海岸带可持续发展以及海岸带韧性评估具有重要意义。本研究利用GPS、GIS、RS技术从1996—2022年黄河三角洲行水河口的220幅遥感影像中推断出年平均海岸线位置,同时根据行水河口摆动次数划分为5个阶段,并以此为基础对海岸线变迁及其稳定性进行定量分析。结果表明：行水河口岸线长期处于动态变化过程中,整体呈淤进状态,各岸段岸线时空变化特征不同,最大侵蚀（-73.89m/a）区出现在两丁坝之间,最大淤积（393.20m/a）区出现在河口区附近。研究区90%的岸线表现为较强淤积至严重淤积,稳定性指数由两丁坝之间（0.135）、2007年出汊前旧河口（0.068）、2007年出汊后新生河口（0.006）依次降低。入海水沙量、河口位置变迁以及沿岸输沙是影响岸线稳定性出现时空差异的主要原因。     

茯苓酸调节AMPK/GSK-3β/Nrf2信号通路对子宫内膜异位症大鼠内膜基质细胞铁死亡的影响

目的：探索茯苓酸调节腺苷酸活化蛋白激酶（AMPK）/糖原合成酶激酶3β（GSK-3β）/核因子E2相关因子2（Nrf2）信号通路对子宫内膜异位症（EM）大鼠基质细胞铁死亡的影响。方法：将51只SD大鼠于腹腔内异位移植子宫内膜组织构建EM大鼠模型,并将其随机分为模型组、茯苓酸低剂量（3.5 mg/kg）组、茯苓酸高剂量（7.0 mg/kg）组、茯苓酸高剂量（7.0 mg/kg）+盐酸多索啡（0.2 mg/kg）组,每组各12只,另取12只SD大鼠只开腹不移植,设为假手术组,药物分组处理后测定各组大鼠异位子宫内膜体积、异位子宫内膜组织铁死亡指标［谷胱甘肽（GSH）、丙二醛（MDA）水平、铁含量］、血清及异位子宫内膜组织炎症因子［肿瘤坏死因子α（TNF-α）、白细胞介素-6（IL-6）］水平、异位子宫内膜组织铁死亡相关蛋白［长链脂酰辅酶A合成酶4（ACSL4）、环加氧酶2（PTGS2）］与AMPK/GSK-3β/Nrf2通路相关蛋白表达。原代培养EM大鼠子宫内膜基质细胞,并将其随机分为对照组、茯苓酸低浓度（40 mg/L）组、茯苓酸高浓度（80 mg/L）组、茯苓酸高浓度（80 mg/L）+盐酸多索啡（10 μmol/L）组,以药物分组处理后,以CCK-8法、流式细胞术分别测定各组细胞增殖及凋亡;以试剂盒检测各组细胞铁死亡指标GSH及MDA水平、铁含量;以免疫印迹实验检测各组细胞铁死亡相关蛋白及AMPK/GSK-3β/Nrf2通路相关蛋白表达。结果：与假手术组相比,模型组大鼠异位子宫内膜体积、MDA水平及铁含量、血清及异位子宫内膜组织TNF-α及IL-6水平、ACSL4及PTGS2蛋白表达升高（P<0.05）,GSH水平、p-AMPK/AMPK、p-GSK-3β/GSK-3β及Nrf2蛋白表达降低（P<0.05）;与模型组相比,茯苓酸低、高剂量组大鼠异位子宫内膜体积、MDA水平及铁含量、血清及异位子宫内膜组织TNF-α及IL-6水平、ACSL4及PTGS2蛋白表达降低（P<0.05）,GSH水平、p-AMPK/AMPK、p-GSK-3β/GSK-3β及Nrf2蛋白表达升高（P<0.05）,且高剂量茯苓酸作用更强;盐酸多索啡可减弱高剂量茯苓酸对EM模型大鼠的作用。与对照组相比,茯苓酸低、高浓度组大鼠子宫内膜基质细胞活力、MDA水平及铁含量、ACSL4及PTGS2蛋白表达降低（P<0.05）,凋亡率、GSH水平、p-AMPK/AMPK、p-GSK-3β/GSK-3β及Nrf2蛋白表达升高（P<0.05）,且高浓度茯苓酸作用更强;盐酸多索啡可减弱高剂量茯苓酸对EM大鼠内膜基质细胞的作用。结论：茯苓酸可减轻EM大鼠炎症及铁死亡,抑制其子宫内膜基质细胞增殖及异位内膜生长,其作用机制可能是通过激活AMPK/GSK-3β/Nrf2信号通路来实现的。