降雨对城市草坪温室气体源汇效应的影响

利用静态箱法研究了夏季降雨对上海市城市草坪温室气体排放的影响,结果表明,晴天上海市城市草坪是N_2O和CO_2的源,CH_4的汇;降雨会削弱N_2O和CO_2排放,使得草坪由CH_4的汇转变为排放源。N_2O通量在晴天和雨后分别为1.37±3.47和1.06±2.67μmol/(m2·h),CO_2通量在晴天和雨后分别为13.33±8.59和6.46±2.61mmol/(m~2·h),CH_4通量在晴天和降雨后分别为-0.08±3.77和0.22±6.27μmol/(m~2·h)。明暗箱对比实验显示,草坪生态系统能有效缓解土壤对大气N_2O和CO_2的贡献。N_2O和CO_2通量与光合有效辐射和温度呈显著负相关(p0.01),CH_4和二者相关性不显著。降雨通过降低光合作用和温度,间接削弱城市草坪CO_2和N_2O的排放。降雨可能通过提高含水率抑制城市草坪对CH_4的吸收,促进其排放。     

餐厨垃圾处理设备的现状与发展趋势研究

针对人类社会在日常运转中产生的大量餐厨垃圾,当下最有效的应对措施是发展相关的餐厨垃圾处理产业,以相关的工作模式和工作设备来应对餐厨垃圾的处理工作。由于餐厨垃圾的特殊性,不同于一般的日常生活垃圾,因此餐厨垃圾的处理设备自然也就有独特的特点与性质。当下社会中餐厨垃圾处理设备行业的发展可谓如火如荼,各种各样的餐厨垃圾处理设备应运而生,针对餐厨垃圾处理设备的发展现状与发展趋势详细的探讨,对促进中国餐饮垃圾处理行业的发展具有借鉴意义。     

含氯化工废水TOC和COD的相关性研究

COD和TOC均是表征水体有机污染程度的综合性指标,选取含氯有机化工废水和含氯有机无机混合化工废水2种废水,通过准确测定水样的COD与TOC数值,采用一元线性回归方程对所得数据进行拟合,判定高氯废水中COD与TOC的相关性,建立COD对TOC的转换方程.数据表明,样本水样的TOC与COD之间可以建立相应的线性回归方程,TOC与COD之间存在显著的相关性,证明采用TOC值对COD进行转换是可行的.定量关系验证结果表明,TOC对COD的转换系数是可以准确测定的,确定转换系数后,结果是可靠的.     

海南省废弃物处理温室气体排放估算研究

废弃物处理所释放的甲烷、二氧化碳和氧化亚氮是温室气体排放估算的组成部分之一.通过对海南省废弃物处理固体废弃物填埋、焚烧、生活污水以及工业废水过程中温室气体排放的估算,得出废弃物处理温室气体排放清单.2010年海南省城市废弃物处理温室气体排放以CO2当量计算总量为65.79万吨,同时进行了不确定性分析,不确定性约为30％,并提出拟采取的降低不确定性措施,为今后不断完善废弃物处理温室气体排放清单编制提供依据.     

固相膜萃取-气相色谱法测定地表水中有机氯农药研究

研究了固相膜萃取对地表水中有机氯农药(OCPs)物质的提取效果,并与液液提取法(LLE)进行比较.建立了固相膜萃取/气相色谱法检测地表水中20种有机氯农药的方法.结果表明:当萃取膜为HLB膜,洗脱液溶剂为丙酮和正己烷,萃取效果最理想,20种OCPs的回收率稳定在74.1%~94.3%之间,固相膜萃取法与传统液液提取法相比,既提高了萃取效率同时又减少了有机萃取溶剂的用量.该法检测实际样品时,同时加入2种内标指示剂对方法的性能进行了验证,2种内标示踪剂的回收率分别为71.6%~94.8%和69.9%~109.5%,样品中20种OCPs均未检出.     

HNO_3在气相及SiO_2表面的紫外光解反应

利用紫外及红外吸收光谱等分析手段对365 nm光照下HNO3在气相与SiO2表面的光解反应进行了研究.考察了HNO3浓度、光照时间、相对湿度等条件对反应的影响.结果表明:随着HNO3浓度及光照时间的增加,光解产生的NO2和NO浓度均呈指数增加;无水汽情况下,400 Pa的HNO3光解45 min后,产生NO2及NO浓度比气相光解产生的分别高约3及1.7倍.HNO3光解产生的HONO的浓度随相对湿度的增加而呈线性增加,在SiO2颗粒物表面光解产生的NO2浓度随着相对湿度的增加而减少,而NO浓度则随之增大.400 Pa的HNO3光照45 min后,SiO2表面光解产生的HONO浓度是气相光解的3倍、SiO2表面暗反应的约30倍.     

基于放射性碳分析的多环芳烃源解析:技术进展和准确性评估

化石燃料燃烧和生物质燃烧是污染物多环芳烃(polycyclic aromatic hydrocarbon,PAHs)的两大来源.放射性碳(14C)分析近年用于评估这两类源对环境中PAHs的相对贡献.此方法基于化石燃料和生物质的14C含量差异,即化石燃料不含14C,而生物质的14C浓度有一个较稳定值.14C的自然丰度极低(约10-12),因此检测PAHs这样的痕量污染物的14C含量一度极具挑战.1990年代中期,加速器质谱的技术突破使得对环境样品PAHs的14C分析具有实用价值.要准确测出PAHs的14C含量,须先从化学成分复杂的环境样品中分离出高纯度的PAHs.制备气相色谱因其出色的分离能力而成为目前环境样品PAHs14C分析必备的工具.本文意在简介基于14C分析的PAHs源解析的基本原理、技术进展,以及评估该方法获得的PAHs源解析结果的准确性.     

CFD-based assessment and visualization of the failure consequences of LPG tankers

This paper presents a simulation analysis of the explosions following an LPG leak and visualizes the consequences of the accident to reduce the consequences of the LPG leak explosion. Firstly, this paper proposes a CFD numerical simulation-based method for visualizing the consequences of LPG tanker failure. The method combines satellite maps and CFD numerical simulation data to visualize the consequences of LPG leaks and explosions, taking into account the influence of obstacles on the danger range of leaks and explosions; Secondly, this paper applies the method to a liquefied petroleum gas accident that occurred in the Wenling section of the Shenhai Expressway and performs CFD numerical simulation on the accident process and visualizes the consequences of the accident. Therefore, this method can provide a theoretical reference for the prior prevention of LPG accidents and the analysis of the consequences of accidents, as well as certain practical guidance instructive.     

An integrated EDIB model for probabilistic risk analysis of natural gas pipeline leakage accidents

Natural gas pipeline construction is developing rapidly worldwide to meet the needs of international and domestic energy transportation. Meanwhile, leakage accidents occur to natural gas pipelines frequently due to mechanical failure, personal operation errors, etc., and induce huge economic property loss, environmental damages, and even casualties. However, few models have been developed to describe the evolution process of natural gas pipeline leakage accidents (NGPLA) and assess their corresponding consequences and influencing factors quantitatively. Therefore, this study aims to propose a comprehensive risk analysis model, named EDIB (ET-DEMATEL-ISM-BN) model, which can be employed to analyze the accident evolution process of NGPLA and conduct probabilistic risk assessments of NGPLA with the consideration of multiple influencing factors. In the proposed integrated model, event tree analysis (ET) is employed to analyze the evolution process of NGPLA before the influencing factors of accident evolution can be identified with the help of accident reports. Then, the combination of DEMATEL (Decision-making Trial and Evaluation Laboratory) and ISM (Interpretative Structural Modeling) is used to determine the relationship among accident evolution events of NGPLA and obtain a hierarchical network, which can be employed to support the construction of a Bayesian network (BN) model. The prior conditional probabilities of the BN model were determined based on the data analysis of 773 accident reports or expert judgment with the help of the Dempster-Shafer evidence theory. Finally, the developed BN model was used to conduct accident evolution scenario analysis and influencing factor sensitivity analysis with respect to secondary accidents (fire, vapor cloud explosion, and asphyxia or poisoning). The results show that ignition is the most critical influencing factor leading to secondary accidents. The occurrence time and occurrence location of NGPLA mainly affect the efficiency of emergency response and further influence the accident consequence. Meanwhile, the weight ranking of economic loss, environmental influence, and casualties on social influence is determined with respect to NGPLAs.     

Dynamic risk assessment for underground gas storage facilities based on Bayesian network

Loss of the underground gas storage process can have significant effects, and risk analysis is critical for maintaining the integrity of the underground gas storage process and reducing potential accidents. This paper focuses on the dynamic risk assessment method for the underground gas storage process. First, the underground gas storage process data is combined to create a database, and the fault tree of the underground gas storage facility is built by identifying the risk factors of the underground gas storage facility and mapping them into a Bayesian network. To eliminate the subjectivity in the process of determining the failure probability level of basic events, fuzzy numbers are introduced to determine the prior probability of the Bayesian network. Then, causal and diagnostic reasoning is performed on the Bayesian network to determine the failure level of the underground gas storage facilities. Based on the rate of change of prior and posterior probabilities, sensitivity and impact analysis are combined to determine the significant risk factors and possible failure paths. In addition, the time factor is introduced to build a dynamic Bayesian network to perform dynamic assessment and analysis of underground gas storage facilities. Finally, the dynamic risk assessment method is applied to underground gas storage facilities in depleted oil and gas reservoirs. A dynamic risk evaluation model for underground gas storage facilities is built to simulate and validate the dynamic risk evaluation method based on the Bayesian network. The results show that the proposed method has practical value for improving underground gas storage process safety.