The Synergism between Methanogens and Methanotrophs and the Nature of their Contributions to the Seasonal Variation of Methane Fluxes in a Wetland: The Case of Dajiuhu Subalpine Peatland

Wetland ecosystems are the most important natural methane (CH₄) sources, whose fluxes periodically fluctuate. Methanogens (methane producers) and methanotrophs (methane consumers) are considered key factors affecting CH₄ fluxes in wetlands. However, the symbiotic relationship between methanogens and methanotrophs remains unclear. To help close this research gap, we collected and analyzed samples from four soil depths in the Dajiuhu subalpine peatland in January, April, July, and October 2019 and acquired seasonal methane flux data from an eddy covariance (EC) system, and investigated relationships. A phylogenetic molecular ecological networks (pMENs) analysis was used to identify keystone species and the seasonal variations of the co-occurrence patterns of methanogenic and methanotrophic communities. The results indicate that the seasonal variations of the interactions between methanogenic and methanotrophic communities contributed to CH₄ emissions in wetlands. The keystone species discerned by the network analysis also showed their importance in mediating CH₄ fluxes. Methane (CH₄) emissions in wetlands were lowest in spring; during this period, the most complex interactions between microbes were observed, with intense competition among methanogens while methanotrophs demonstrated better cooperation. Reverse patterns manifested themselves in summer when the highest CH₄ flux was observed. Methanoregula formicica was negatively correlated with CH₄ fluxes and occupied the largest ecological niches in the spring network. In contrast, both Methanocella arvoryzae and Methylocystaceae demonstrated positive correlations with CH₄ fluxes and were better adapted to the microbial community in the summer. In addition, soil temperature and nitrogen were regarded as significant environmental factors to CH₄ fluxes. This study was successful in explaining the seasonal patterns and microbial driving mechanisms of CH₄ emissions in wetlands.     

Seasonal Variations of CH_4 Emissions in the Yangtze River Delta Region of China Are Driven by Agricultural Activities

Developed regions of the world represent a major atmospheric methane(CH_4) source, but these regional emissions remain poorly constrained. The Yangtze River Delta(YRD) region of China is densely populated(about 16% of China's total population) and consists of large anthropogenic and natural CH_4 sources. Here, atmospheric CH_4 concentrations measured at a 70-m tall tower in the YRD are combined with a scale factor Bayesian inverse(SFBI) modeling approach to constrain seasonal variations in CH_4 emissions. Results indicate that in 2018 agricultural soils(AGS, rice production) were the main driver of seasonal variability in atmospheric CH_4 concentration. There was an underestimation of emissions from AGS in the a priori inventories(EDGAR—Emissions Database for Global Atmospheric Research v432 or v50), especially during the growing seasons. Posteriori CH_4 emissions from AGS accounted for 39%(4.58 Tg, EDGAR v432) to 47%(5.21 Tg, EDGAR v50) of the total CH_4 emissions. The posteriori natural emissions(including wetlands and water bodies) were1.21 Tg and 1.06 Tg, accounting for 10.1%(EDGAR v432) and 9.5%(EDGAR v50) of total emissions in the YRD in2018. Results show that the dominant factor for seasonal variations in atmospheric concentration in the YRD was AGS,followed by natural sources. In summer, AGS contributed 42%(EDGAR v432) to 64%(EDGAR v50) of the CH_4 concentration enhancement while natural sources only contributed about 10%(EDGAR v50) to 15%(EDGAR v432). In addition, the newer version of the EDGAR product(EDGAR v50) provided more reasonable seasonal distribution of CH_4 emissions from rice cultivation than the old version(EDGAR v432).     

利用FY-4A卫星光学数据对中国近地面PM2.5浓度的估算和检验分析

对FY-4A卫星的气溶胶光学厚度（AOD）产品进行检验,并根据卫星相关观测资料,通过改进后的PMRS方法,反演得到中国近地面PM_2.5质量浓度网格化分布。结果表明,FY-4A卫星反演不同站点AOD与地基观测网（AERONET）观测结果吻合较好,但存在一定的低估或高估现象,相关系数区间为0.54—0.87。将细粒子比（FMF）以0.4为界进行划分,FMF＞0.4时,拟合结果较FMF≤0.4时更接近于AERONET观测结果;但FMF≤0.4时,卫星反演的AOD稳定性优于FMF＞0.4时。通过引入AOD的大小,改进FMF＞0.4时对细粒子柱状体积消光比（VE_f）的估算算法,并通过改进后的PMRS方法对中国近地面PM_2.5浓度进行逐时反演,其反演结果和地面观测结果相关较好,其中,乌鲁木齐、石家庄和徐州观测点的相关系数均高于0.7,但数值上仍存在高估或低估,误差结果由多种因素决定。空间分布中,卫星反演的中国2019年近地面PM_2.5浓度月均值与近地面观测的结果有较好的对应关系,二者逐月演变趋势基本一致,基本可以反映出中国近地面大气细粒子的空间分布,特别是秋、冬季京津冀周边区域、汾渭平原等污染高值区均与地面观测对应较好。      

集合预报误差在GRAPES全球四维变分同化中的应用研究Ⅱ：参数选取与数值试验

研究的第一部分讨论了如何有效应用集合预报误差的科学方案,确定了集合预报误差在GRAPES（Global Regional Assimilation and PrEdiction System）全球4DVar（four dimensional variational data assimilation）中应用的分析框架。在此基础上研究了针对集合预报误差实际应用于GRAPES全球4DVar,解决接近或超过100个集合样本数时高效生成的计算效率问题,以及与GRAPES全球4DVar匹配的同化关键参数确定问题。选择基于4DVar的集合资料同化方法生成集合样本,通过将第1个样本极小化迭代过程中产生的预调节信息用于其他样本极小化做预调节,将计算效率提高了2倍。通过时间错位扰动方法增加集合样本数,实现集合样本增加到3倍。对集合方差进行膨胀,并选择水平局地化相关尺度为流函数背景误差水平相关的1.4倍。通过批量数值试验方法确定背景误差与集合预报误差的权重系数,对60个集合样本当集合预报误差权重为0.7时预报效果最好。对北半球夏、冬两季各52 d的批量试验表明,对于南、北半球En4DVar （ensemble 4DVar）较4DVar的改进在冬季主要集中在700—30 hPa,而在夏季主要集中在400—150 hPa。赤道地区受季节影响较小,En4DVar对位势高度、风场与温度的改进都较为明显,且经向风场的改进最为显著。文中研发的集合预报误差在GRAPES全球4DVar中应用的方法合理可行。      

西安地铁四号线沿线地裂缝的灾害分析与对策研究

西安地裂缝是一种地区性的地质灾害现象。目前西安共发育有14条地裂缝。地铁四号线将穿越13条,给隧道施工造成了诸多考验。文章选取西安市地铁四号线沿线的地裂缝灾害作为研究对象。探讨了地裂缝对隧道工程的影响因素和致灾特点、以及相关的评估理论方法。最后针对地裂缝灾害特征以及工程特点提出若干防治措施,对于科学研究地裂缝的灾害特点、合理防治地裂缝的灾害发生具有一定的指导意义。     

EH4电磁系统在云南红河地区地下水勘查中的应用

本文介绍了EH4电磁成像系统的基本原理、技术特点和适用范围,结合该系统在云南红河地区不同类型地下水勘查中的应用实例,证明该系统能够查清厚覆盖层下的地质构造、地下河形态及含水岩溶带。利用该系统确定的井位已成功地打出地下水,有效地解决了当地的供水问题。     

珠江口盆地西江凹陷南部文昌组层序地层及沉积体系研究

珠江口盆地西江凹陷南部包括两个相邻洼陷:西江36洼和番禺4洼,钻探结果却揭示了截然不同的油气勘探前景,其中,番禺4洼探明储量已过亿吨,而西江36洼却未有商业发现,导致勘探上对西江36洼烃源潜力有所顾虑.为了揭示这种差异油气地质条件产生的原因,亟待开展两个洼陷的对比研究.以主要烃源层系文昌组为切入点,通过开展精细的层序-...     

Carbon fluxes from eroding peatlands – the carbon benefit of revegetation following wildfire

Peatlands are among the largest long‐term soil carbon stores, but their degradation can lead to significant carbon losses. This study considers the carbon budget of peat‐covered sites after restoration, following degradation by past wildfires. The study measured the carbon budget of eight sites: four restored‐revegetated sites, two unrestored bare soil control sites, and two intact vegetated controls over two years (2006–2008). The study considered the following flux pathways: dissolved organic carbon (DOC); particulate organic carbon (POC); dissolved carbon dioxide (CO₂); primary productivity; net ecosystem respiration, and methane (CH₄). The study shows that unrestored, bare peat sites can have significant carbon losses as high as 522 ± 3 tonnes C/km²/yr. Most sites showed improved carbon budgets (decreased source and/or increased sink of carbon) after restoration; this improvement was mainly in the form of a reduction in the size of the net carbon source, but for one restored site the measured carbon budget after four years of restoration was greater than observed for vegetated controls. The carbon sequestration benefit of peatland restoration would range between 122 and 833 tonnes C/km²/yr. Copyright © 2011 John Wiley & Sons, Ltd.     

GM4磁通门磁力仪的供电设备对观测数据的影响

通过对我国GM4磁通门磁力仪使用的各种电源设备所产出的观测数据动态曲线的对比研究,认为电源设备对观测数据的影响不容忽视,市电结合UPS方式是最为合适的供电选择。     

Strategies to Overcome Filter Divergence in the DRP-4-DVar Approach

This paper discusses an important issue related to filter divergence in the dimension-reduced projection,four-dimensional variational data assimilation(DRP-4-DVar) approach.Idealized experiments with the Lorenz-96 model over a period of 200 days showed that the amplitudes of the root mean square errors(RMSEs) reached the same levels as those of the state variables after approximately 100 days because of the accumulation of sampling errors following the cycle of assimilation.Strategies to reduce sampling errors are critical to ensure the quality of ensemble-based assimilation.Numerical experiments showed that localization and reducing observational errors can alleviate,but cannot completely overcome,the filter divergence in the DRP-4-DVar approach,while the method of perturbing observations and the inflation technique can efficiently eliminate the filter divergence problem.