基于FCM算法的BDS三频载波相位组合观测值优化选取

针对传统GNSS载波相位组合观测值选取过程中效率低、工作量大的问题,在对BDS三频载波相位组合观测值的波长标准、电离层延迟标准、观测噪声标准进行误差分析的基础上,以长波长、弱电离层、弱观测噪声标准作为聚类指标,采用模糊C均值聚类算法对BDS三频载波相位组合观测值进行优化分类选取,最后通过矩阵变换法和实测数据对优化组合进行整周模糊度解算,对组合模糊度方差-协方差阵以及历元间模糊度差值进行分析,证明该方法的可行性和可靠性。     

基于夜间灯光数据的晋陕蒙能源消费碳排放时空格局

晋陕蒙三省区既是能源生产基地又是碳排放主要地区。对晋陕蒙市县的碳排放估算难度较大,如何准确快捷地获取其碳排放时空动态信息,对于合理制定区域碳减排规划具有重要的应用价值。本文选取中国晋陕蒙三省作为研究对象,基于夜间灯光数据,模拟晋陕蒙地区碳排放空间分布,进而系统地刻画其碳排放空间分布特征和规律。研究结果表明：① 1997-2016年,晋陕蒙三省区夜间灯光像元总值与能源消耗碳排放量之间的相关系数较高,均通过了1%的显著性检验;② 1997-2016 年,晋陕蒙地区的CO₂排放总量呈逐年增长趋势,鄂尔多斯市属于“高碳”地区;铜川市、安康市、商洛市、汉中市、阿拉善盟和阳泉市属于“低碳”地区;③ 陕西省碳排放清晰地呈现出“陕北>关中>陕南”的格局。晋陕蒙地区碳排放空间分布规律分析为该区域制定切实可行的碳减排政策提供了重要的理论依据。     

Analysis of CO2 Emissions and the Mechanism of the Industrial Enterprises above Designated Size (IEDS) in Resource-based Cities by Application of Geographical Detector Technology

Resource-based cities are the most important players in responding to climate change and achieving low carbon development in China. An analysis of relevant data (such as the energy consumption) showed an inter-city differentiation of CO₂ emissions from energy consumption, and suggested an influence of the Industrial Enterprises above Designated Size (IEDS) in resource-based industrial cities at the prefecture level and above in different regions. Then by geographical detector technology, the sizes of each influencing mechanism on CO₂ emissions from energy consumption of the IEDS were probed. This analysis showed that significant spatial differences exist for CO₂ emissions from energy consumption and revealed several factors which influence the IEDS in resource-based cities. (1) In terms of unit employment, Eastern and Western resource-based cities are above the overall level of all resource-based cities; and only Coal resource-based cities far exceeded the overall level among all of the cities in the analysis. (2) In terms of unit gross industrial output value, the Eastern, Central and Western resources-based cities are all above the overall level for all the cities. Here also, only Coal resource-based cities far exceeded the overall level of all resources-based cities. Economic scale and energy structure are the main factors influencing CO₂ emissions from energy consumption of the IEDS in resource-based cities. The factors influencing CO₂ emissions in different regions and types of resource-based cities show significant spatial variations, and the degree of influence that any given factor exerts varies among different regions and types of resource-based cities. Therefore, individualized recommendations should be directed to different regions and types of resource-based cities, so that the strategies and measures of industrial low carbon and transformation should vary greatly according to the specific conditions that exist in each city.     

Wave prediction in a port using a fully nonlinear Boussinesq wave model

A wave forecasting system using FUNWAVE-TVD which is based on the fully nonlinear Boussinesq equations by Chen(2006) was developed to provide an accurate wave prediction in the Port of Busan, South Korea. This system is linked to the Korea Operational Oceanographic System(KOOS) developed by Park et al.(2015). The computational domain covers a region of 9.6 km×7.0 km with a grid size of 2 m in both directions, which is sufficient to resolve short waves and dominant sea states. The total number of grid points exceeds 16 millions,making the model computational expensive. To provide real-time forecasting, an interpolation method, which is based on pre-calculated results of FUNWAVE-TVD and SWAN forecasting results at the FUNWAVE-TVD offshore boundary, was used. A total of 45 cases were pre-calculated, which took 71 days on 924 computational cores of a Linux cluster system. Wind wave generation and propagation from the deep water were computed using the SWAN in KOOS. SWAN results provided a boundary condition for the FUNWAVE-TVD forecasting system. To verify the model, wave observations were conducted at three locations inside the port in a time period of more than 7 months. A model/model comparison between FUNWAVE-TVD and SWAN was also carried out. It is found that, FUNWAVE-TVD improves the forecasting results significantly compared to SWAN which underestimates wave heights in sheltered areas due to incorrect physical mechanism of wave diffraction, as well as large wave heights caused by wave reflections inside the port.     

Galileo导航系统观测值的质量分析

从信噪比、伪距多路径效应、单差残差和非差观测值精度等方面对进入初始服务初期Galileo导航系统观测值的质量进行了对比分析,最后简要评估了Galileo导航系统的单点定位精度。结果表明:在信噪比方面,Galileo E5最高,E1、E5a和E5b次之且基本相当;在伪距多路径方面,Galileo E1最大,其次分别为E5b和E5a,而E5最小;在单差残差方面,Galileo导航系统单差相位残差基本在±4 mm内,单差伪距残差基本在±0.3 m内;在非差观测值精度方面,Galileo导航系统相位观测值精度E1最高,E5a、E5b和E5次之且基本相当,而伪距观测值精度E5最高,E5b最差;整体上而言,Galileo导航系统观测值的数据质量略优于GPS和BDS;Galileo导航系统单频伪距单点定位的水平精度约为2.2 m,与GPS和BDS的水平定位精度基本相当,而高程精度约为5.2 m,稍差于GPS和BDS,这与可观测卫星数和PDOP有很大的关系。     

多尺度交通出行碳排放影响因素研究进展

减少交通出行碳排放是全球共同面对的重大议题之一,同时也是城市和交通可持续发展的重要目标。论文首先基于文献计量方法对近20年来的全球交通出行碳排放研究现状与趋势进行梳理与分析,在此基础上,分别从国家、城市和社区3个尺度对国家交通能源消耗及其碳排放的驱动力因素、城市形态对交通碳排放的影响以及社区建成环境对居民出行碳排放的影响研究进行了文献综述与归纳凝练。研究发现：① 国家尺度的研究早期大多基于时间序列数据,采用分解法探究交通能源消耗的主要驱动力;近年来,研究进一步根据能源消耗数据“自上而下”地测算交通碳排放,并通过构建面板数据模型探究社会经济、城市形态和交通发展因素对交通碳排放的影响。② 城市尺度的研究早期围绕紧凑城市是否一种低碳的城市形态而进行讨论,主要使用截面数据和相关分析方法;近年来,进一步拓展使用情景预测、GIS空间分析、空间回归、空间模拟等方法探究城市交通碳排放的空间差异及其与城市形态、城市中心分布形式之间的关系。③ 在社区尺度,研究多以截面、非集计的问卷调查数据为主,采用定量的数学模型探究居民社会经济属性和人口密度,土地利用混合度,与就业地、城市中心的距离,路网与交叉口密度、公共交通供给水平等建成环境要素对居民出行碳排放的影响。最后有针对性地提出了未来中国城市交通出行碳排放影响因素的研究趋势。     

氮添加降低了半干旱草原土壤呼吸但未改变其温度敏感性

半干旱生态系统土壤呼吸(Rs)对氮添加的响应机制仍有待探索。本研究在中国半干旱草原设置不同氮添加水平(0、2、4、8、16、32 gN m-2 yr-1),测定土壤呼吸速率、土壤温湿度、微生物磷脂脂肪酸、土壤理化性质与地上生物量等指标,探讨氮添加对土壤呼吸及其温度敏感性(Q10)的影响。结果表明:氮添加显著增加了土壤可溶性有机碳(DOC)和无机氮(IN)的含量,降低了土壤pH值,对地上生物量(ABM)无显著影响。氮添加降低了磷脂脂肪酸(PLFAs)的总量,降低了真菌细菌比(F:B),提高了革兰氏阳性阴性菌比(G+:G–)。氮添加显著降低了土壤呼吸,N2、N4、N8、N16和N32处理下的土壤呼吸分别比对照N0变化了–2.58%、14.86%、22.62%、23.97%和19.87%,结构方程模型表明,氮添加通过降低PLFAs总量和改变微生物组成降低土壤呼吸。氮添加对温度敏感性(Q10)、土壤总有机碳(TOC)和总氮(TN)的影响均不显著,表明氮添加减轻了土壤碳的损失,且不会改变全球变暖背景下土壤有机碳矿化的潜力。     

南极苔原沼泽温室气体通量变化特征及其对气候变化的响应

以南极阿德雷岛苔原沼泽为研究区域,2016年12月至2017年1月南极夏季期间观测研究了温室气体CH_4、CO_2和N_2O通量的变化规律及其对环境因子的响应关系。结果表明:光照条件下干旱苔原沼泽表现为CH_4吸收,通量为(–5.4±4.3)μg CH_4·m~(–2)·h~(–1),半干旱苔原与淹水苔原沼泽表现为净排放;三个类型苔原沼泽观测点均表现为N_2O净吸收,最高吸收通量出现在淹水苔原,为(–2.6±2.4)μg N_2O·m~(–2)·h~(–1);黑暗条件下苔原沼泽一致表现为CH_4和N_2O净排放。光照与土壤水分减少增加了苔原CH_4有氧氧化吸收,同时促进了反硝化作用对N_2O的还原转化。观测期间所有观测点均表现为CO_2的汇,最高CO_2净交换量与光合作用强度都出现在淹水苔原区,分别为(–40.1±17.6)μg CO_2·m~(–2)·h~(–1)和(91.2±26.5) mg CO_2·m~(–2)·h~(–1);而最高苔原沼泽呼吸速率出现在干旱苔原观测点,为(73.1±17.6)μg CO_2·m~(–2)·h~(–1)。夏季适宜的温度、降水条件促进了苔原植被的光合作用,增加了苔原沼泽CO_2吸收量。CO_2、N_2O、CH_4通量随时间变化的相互关系规律不显著(P0.05),但在降水与温度波动下,N_2O与CH_4通量都随CO_2通量呈现相似的波动。三种温室气体与各种环境因子之间的响应关系值得进一步研究;不同光照条件对CH_4、N_2O排放量的估算有重要影响。     

极区通量观测系统及其在国际极地年(IPY)全球协同观测中的应用

本文对极区通量观测系统作了介绍,在国际极地年(IPY)全球协同观测中,极区通量观测系统在南极中山站进行了连续14个月的观测。结果表明,中山站年净辐射通量为12.9 W/m2。感热通量夏半年(10～2月)为正值,冬半年(3～9月)为负值,年平均1.9 W/m2。潜热通量全年都为正值,年平均11.2 W/m2。总体而言,地表通过净辐射获得热能,又通过感热和潜热方式向大气输送。观测得到的CO2通量全为负值,年平均为-0.031 mg/m2,表明南极中山站是CO2汇。     

黄河流域硅酸盐风化的讨论

根据2007年6月和7月采集的黄河干流及部分支流水样和河床砂样品数据,对黄河流域硅酸盐化学风化进行了探讨。在充分评估黄河流域的K+,Na+来源的基础上,确定了硅酸盐风化的K+量,并通过选定的硅酸盐风化(K/Na)比值,得到了硅酸盐风化的Na+量;通过测定流域内不同岩石类型分布的河床砂样品,得到河床砂样品硅酸盐部分(Ca/Na)和(Mg/K)的比值,确定了钙镁硅酸盐风化的Ca2+,Mg2+量;并据此估算了流域硅酸盐化学风化的CO2消耗率。如果选用黄河入海多年径流量58.02×109km3/a进行计算,则得到全流域硅酸盐风化CO2消耗率约为26.22×103mol/km2/a。若选用2007年的平均径流量24.83×109km3/a进行计算,则黄河流域硅酸盐风化引起的CO2消耗率约为11.19×103mol/km2/a。