Molecular characterization of dissolved black nitrogen via electrospray ionization Fourier transform ion cyclotron resonance mass spectrometry

Combustion produces a complex mixture of polycondensed aromatic compounds known as black carbon (BC). Such products can become remobilized from char and soil in the form of dissolved BC (DBC). Ultra-high resolution Fourier transform ion cyclotron resonance mass spectrometry (ESI–FT-ICRMS) analysis of a variety of soil and char leachates showed that a significant proportion of DBC compounds contained one or more nitrogen atoms. While the presence of black nitrogen (DBN) in dissolved organic matter (DOM) has been reported, its molecular features were uncharacterized. Here we present results of FT-ICRMS characterization of DBN, where assigned formulae were validated on the basis on their ¹³C isotope signatures and fragmentation patterns obtained via collision induced dissociation. Possible chemical structures were assigned for several DBN formulae and suggest that nitrogen was incorporated into the core ring system as a pyrrole-type moiety. Most DBN compounds existed as part of homologous series where homologs differed by a mass corresponding to CO₂, suggesting that they were polysubstituted with carboxylic acid groups. The environmental contribution of such novel, aromatic, combustion-derived nitrogen compounds with respect to global nitrogen cycling remains elusive. The biogeochemical implications of the input of such fire-derived products to aquatic ecosystems as part of climate change therefore need to be assessed.     

Monitoring the impact of aerosol contamination on the drought-induced decline of gross primary productivity

Southwestern China experienced a period of severe drought from September 2009 to May 2010. It led to widespread decline in the enhanced vegetation index (EVI) and gross primary productivity (GPP) in the springtime of 2010 (March to May). However, this study observed a spatial inconsistency between drought-impacted vegetation decline and the precipitation deficit. Significant aerosol loads that correspond to inconsistent areas were also observed during the drought period. After analyzing both MODIS GPP/NPP Collection 5 (C5) and the newer Collection 5.5 (C55) data, a large area observed to be experiencing GPP decline in the eastern part of the study area proved to be unreliable. Based on EVI data, after atmospherically contaminated data were screened from analysis, approximately 20% of the study area exhibited browning whereas 33% displayed no change or greening and the remaining area (approximately 47%) lacked sufficient data to document changing conditions. Correlation analysis showed that fire occurrences, aerosol optical depth, and precipitation anomalies during the two drought periods (from September to February and from March to May) all contributed to a decrease in GPP. C55 data remains vulnerable to aerosol contamination due to a much higher correlation coefficient with aerosol optical depth compared to C5 data. In the future, users of remotely sensed data should be cautious of and take into account impacts related to atmospheric contamination, even during drought periods.     

The application of fire spread and evacuation simulation technology in large stadium

Fire is a major danger in the large stadium due to fire accompanied with smoke flow and evacuation path. As a part of an effort to improve the life safety in large stadium, the simulation technology combined with fire spread and evacuation had been developed. Besides that, in order to decrease the rate of people death in the large stadium fire, the interface between fire and the evacuation people must be designed according to simulation results, based on the influence laws to human behavior by smoke temperature, CO concentration and extinction coefficient in fire condition. Therefore, the investigation of effect of fire spread on life safety is needed. In this paper, the dynamic changes of walking speed, route choice and mental state is obtained from automatic reading of fire data during the simulation of evacuation. The effect abruptly changes due to time-varying fire smoke parameters, especially local jamming and uneven efficiency of routes. From the simulation, the visual and tried evidences would be provided for safe evacuation in fire emergency in large stadiums.     

火烧对洞庭湖湿地荻(Miscanthus sacchariflorus)和苔草(Carex brevicuspis)群落土壤性质的影响

火烧作为调控因子,对植物群落结构和生态系统功能具有重要影响,但在湖泊湿地中研究较少.通过野外调查取样与实验室分析,探讨火烧对洞庭湖湿地主要群落类型——荻(Miscanthus sacchariflorus)和苔草(Carex brevicuspis)土壤化学性质的影响.结果表明:火烧后,苔草群落土壤硝态氮含量显著减少64.6%,有机质含量增加26.3%;而荻群落土壤与之相反,硝态氮含量增加186.9%,有机质含量减少22.9%.火烧后,苔草群落的全氮、铵态氮、全碳和全磷含量均显著增加,分别增加了75.4%、36.3%、102.7%和76.9%,而荻群落土壤与对照组间无显著差异.总体上,火烧对荻群落土壤养分影响不大,可作为芦苇场的一种管理方式,但火烧促进苔草群落土壤养分释放,有助于苔草群落提前萌芽和生长,并引起牲畜牧食增加.     

Load characteristics of steel and concrete tubular members under jet fire: An experimental and numerical study

The aim of this study was to evaluate the load characteristics of steel and concrete tubular members under jet fire, with the motivation to investigate the jet fire load characteristics in FPSO topsides. This paper is part of Phase II of the joint industry project on explosion and fire engineering of FPSOs (EFEF JIP) ( [Paik and Czujko, 2009] and [Paik, 2010]). To obtain reliable load values, jet fire tests were carried out in parallel with a numerical study. Computational fluid dynamics (CFD) simulation was used to set up an adiabatic wall boundary condition for the jet fire to model the heat transfer mechanism. A concrete tubular member was tested under the assumption that there is no conduction effect from jet fire. A steel tubular member was tested and considered to transfer heat through conduction, convection, and radiation. The temperature distribution, or heat load, was analyzed at specific locations on each type of member. ANSYS CFX, (2008) and KFX, 2007 codes were used to obtain similar fire action in the numerical and experimental methods. The results of this study will provide a useful database to determine design values related to jet fire.     

Predictive fire occurrence modelling to improve burned area estimation at a regional scale: A case study in East Caprivi,Namibia

Fires threaten human lives, property and natural resources in Southern African savannas. Due to warming climate, fire occurrence may increase and fires become more intense. It is crucial, therefore, to understand the complexity of spatiotemporal and probabilistic characteristics of fires. This study scrutinizes spatiotemporal characteristics of fires and the role played by abiotic, biotic and anthropogenic factors for fire probability modelling in a semiarid Southern African savanna environment. The MODIS fire products: fire hot spots (MOD14A2 and MYD14A2) and burned area product MODIS (MCD45A1), and GIS derived data were used in analysis. Fire hot spots occurrence was first analysed, and spatial autocorrelation for fires investigated, using Moran's I correlograms. Fire probability models were created using generalized linear models (GLMs). Separate models were produced for abiotic, biotic, anthropogenic and combined factors and an autocovariate variable was tested for model improvement. The hierarchical partitioning method was used to determine independent effects of explanatory variables. The discriminating ability of models was evaluated using area under the curve (AUC) from the receiver operating characteristic (ROC) plot. The results showed that 19.2–24.4% of East Caprivi burned when detected using MODIS hot spots fire data and these fires were strongly spatially autocorrelated. Therefore, the autocovariate variable significantly improved fire probability models when added to them. For autologistic models, i.e. models accounting for spatial autocorrelation, discrimination was good to excellent (AUC 0.858–0.942). For models not counting spatial autocorrelation, prediction success was poor to moderate (AUC 0.542–0.745). The results of this study clearly showed that spatial autocorrelation has to be taken in to account in the fire probability model building process when using remotely sensed and GIS derived data. This study also showed that fire probability models accounting for spatial autocorrelation proved to be superior in regional scale burned area estimation when compared with MODIS burned area product (MCD45A1).     

Charcoal morphotypes in lake sediments from British Columbia (Canada): an assessment of their utility for the reconstruction of past fire and precipitation

Quantitative analysis of variations in morphological types of charcoal were undertaken in sediment cores from three lakes on the Interior Plateau (BC, Canada) over the period AD 1919–2000. Seven distinct morphological types of charcoal were identified based on particle shape and structural features and were compared with seasonal precipitation and recorded area burned within 20 km-radius of study lakes. Fragile-type charcoal fragments, termed type M, displayed significant relationships to recorded area burned in sediment cores from Prosser (r ² = 0.5; p = 0.0001) and Opatcho (r ² = 0.2; p = 0.02) lakes. However, nonsignificant correlations (p > 0.05) were found between total charcoal and area burned. Robust and highly elongated morphotypes C and F were correlated to recorded spring precipitation (r ² = 0.5; p = 0.002) in Opatcho Lake. Charcoal from a sediment core from Big Lake, the lake with the largest watershed, was significantly but inversely related to past fires (r ² = 0.44; p = 0.0003), suggesting important contributions from secondary transportation and deposition. Models were developed to infer relative area burned and precipitation for the study lakes. Our results suggest that charcoal morphotypes are related to the biogeoclimatic and lake watershed characteristics. This study also suggest that charcoal morphotypes can provide insights on past fire and climate, which was not possible based on traditional analysis of total charcoal.     

火烧对湿地生态系统影响研究进展

火烧对湿地生态系统的影响是国内外火生态学和湿地生态系统研究中的一个热点。综述了国内外关于火烧对湿地生态系统各组成部分影响的研究进展,总结了湿地火烧的特点,火烧对湿地植物生长发育、群落特征的影响,火烧对土壤理化性质、对土壤中碳氮等元素形态及分布特征的影响。并针对目前湿地火烧在研究内容和方法上存在的问题,结合国外研究特点,提出了今后国内湿地火烧的研究展望。     

基于雷达组合反射率拼图和深度学习的中尺度对流系统识别、追踪与分类方法

中尺度对流系统（Mesoscale Convective System,MCS）是很多对流性天气的主要致灾体,可导致严重的气象和水文灾害,如雷暴大风、冰雹、龙卷风和山洪。对MCS进行准确的识别和追踪,并根据追踪轨迹及获得的MCS特征实现MCS的分类,对灾害天气的分析和预报有重要意义。基于京津冀地区2010—2019年的雷达组合反射率拼图资料,分别使用支持向量机（SVM）、随机森林（RF）、极度梯度提升决策树（XGBoost）和深度神经网络（DNN）4种机器学习方法,研发了京津冀地区MCS的自动识别算法。使用时、空重叠追踪法对识别的MCS进行追踪匹配,得到包含强度、时间和空间信息的MCS追踪数据资料。在区分线状对流系统和非线状对流系统的基础上,进一步从经典的尾随层云（Trailing Stratiform,TS）、前导层云（Leading Stratiform,LS）和平行层云（Parallel Stratiform,PS）三类准线性MCS的概念模型和结构特征出发,根据追踪轨迹计算MCS的运动方向和MCS近似长轴两侧层状云和强对流云的面积占比,建立准线性MCS的分类算法。MCS的识别属于二分分类问题,以命中率（POD）、虚警率（FAR）、临界成功指数（CSI）和准确率（ACC）为评价指标,综合对比各项指标发现DNN模型较SVM、RF和XGBoost模型对MCS的识别效果更好。使用时、空重叠追踪法对DNN模型识别的MCS进行追踪,结合对两个追踪实例的分析,发现本研究所用的算法取得了很好的追踪结果,也进一步说明了深度学习方法识别MCS的准确性和优势。根据追踪轨迹计算某时刻MCS的运动方向,结合识别的层状云和强对流云的分布位置,准确实现了TS、LS和PS型准线性MCS的分类,为准线性MCS的生命史预测及其致灾天气特别是短时强降水的强度、位置和持续时间的客观预报提供了一种技术思路。      

多普勒天气雷达在扑灭"7.29"井冈山火警中的应用

从多普勒天气雷达产品和天气形势分析入手,对利用人工增雨手段扑灭"7·29"井冈山火警过程进行了技术总结,得到了一些有益的结论一是井冈山区处副热带高压西南象限时,有利于人工增雨;二是中低空弱的冷平流有利于井冈山局部对流的发展;三是井冈山区对流单体在初始阶段的移向移速与700hPa风向风速对应较好;四是罗霄山脉中部的低空平均径向速度入流区的演变,与井冈山局部对流单体关系密切;五是应按山脉走向来布设人工增雨作业炮点.