中国城市温室气体排放清单编制和方法概述

介绍中国国家层面的温室气体排放清单编制现状,概述了中国城市层面温室气体排放清单研究进展,总结国际通用的城市清单方法(Urban Inventory Methods),包括以排放为中心的IPCC和WRI/WBCSD温室气体排放模型、以需求为中心的混合生命周期方法和中国现状城市温室气体排放清单编制方法,阐述在目前的城市温室...     

日本城市碳排放清单计算方法——以横滨市为例

日本是关注全球气候变化并作出行动最早的国家之一,根据其法律大中城市以上的行政区必须编制温室气体减排规划,包括排放清单、趋势预测、减排目标、措施及效果分析、方案实施与监督等。日本环境省为了帮助地方政府编制该规划,提供了城市层面的温室气体排放清单的编制方法指导。本文以横滨市为例,比较完整地介绍日本城市CO2排放清单编制基本方法,为我国城市碳排放清单编制提供参考。     

北京城市温室气体排放清单基础研究

回顾中国城市,主要是北京温室气体排放研究和排放状况,结合目前国际上主要采用的城市清单方法,梳理北京温室气体排放清单,并利用收集的北京市基本资料进行相关分析,作为北京和洛杉矶温室气体清单比较研究的基础.通过分析可以看出,中国城市温室气体清单的编制需要大量精确的数据作为支撑,但目前由于在统计口径上与国际上通用的排放清单有差...     

中国温室气体排放清单信息库软件及网页的开发

中国温室气体排放清单信息库软件是基于《ＩＰＣＣ导则》１９９５年版本提供的方法设计的。与清单相关的网页将为国际互联网用户提供三项内容的服务：清单简介，中国若干年温室气体排放清单，以及排放清单信息库软件的下载。     

土壤温室气体测定方法研究进展

土壤温室气体测量方法复杂多样,不同方法之间的差异性为土壤温室气体测量带来较多不确定性,综合评估比对各类方法有助于提高测量土壤温室气体的准确性,进而对研究温室气体源汇机理、制定排放清单和减排措施具有重要意义.本文通过对国内外温室气体测量研究文献的梳理,总结常用的土壤温室气体观测方法:箱法/碱液吸收法、箱法/气相色谱法、箱法/吸收光谱法、微气象学法、土壤浓度廓线法、稳定同位素法等,系统阐述常用土壤温室气体测量方法的原理、优缺点、不确定性以及改进历程,分析其使用特点与范围.几乎每种方法都有其优势和局限性,箱法操作简单,目前应用较为广泛,但密闭静态箱对观测有一定的扰动,而微气象法对观测下垫面均有极为严格的要求,同位素法更精确,但价格昂贵,难以广泛使用.目前传统测量方法存在实验过程复杂、研究成本高、精度低、不可原位、参数有限等问题,未来土壤温室气体测量的仪器更注重与新技术的结合使用,例如连续量子级联合激光器(CW-QCL)与可调谐二极管激光吸收光谱技术(TDLAS)及波长调制技术(WMS)的结合,向着原位无损、长时间、全参数、高精度、便携式、一体化、自动化和远程操控等方向发展.(图9表3参180)     

天津市2005年温室气体清单编制项目

2010年9月,陶家发改委下发《关于启动省级温室气体清单编制工作有关事项的通知》,将天津市列为省级温室气体清单编制试点地区,明确提出加快推进2005年省级温室气体清单编制工作。为此,斟家设立了雨点基础研究发展计划（973计划）课题”编制省级2005年温室气体清单（试点省份）及其他省份能力建没”（2010CB955605）,7个试点省市分别承担分课题研究仟务。任务下达后,天津市高度重视清单编制工作,确定天津市环境保护科学研究院作为清单编制技术支持单位。在天津市发改委的指导和支持下,天津市环境保护科学研究院筹备组建低碳发展研究中心、建立清单编制：专业队伍并多次听取国家清单专家组的技术指导。     

发展一种估算石油工业温室气体排放的一致的方法

要获得有意义的温室气体清单,重要的是清单中包括的内容的方法论和定义应该是一致的.国际石油工业环境保护协会(IPIECA)、国际石油和天然气生产者协会(OGP)以及美国石油学会(API)已经制定了温室气体排放计算和报告的准则.国际石油工业环境保护协会(IPITCA)报告温室气体排放的石油工业指南的重点是放在石油工业温室气体排放的计算和报告上.为了提供排放估算一致的方法论,美国石油工业协会制定了石油和天然气工业温室气体排放估算方法论概要.从美国石油学会可以得到一个估算排放的工具--SANGEATM能源和排放估算系统.     

发展一种估算石油工业温室气体排放的一致的方法

要获得有意义的温室气体清单,重要的是清单中包括的内容的方法论和定义应该是一致的.国际石油工业环境保护协会(IPIECA)、国际石油和天然气生产者协会(OGP)以及美国石油学会(API)已经制定了温室气体排放计算和报告的准则.国际石油工业环境保护协会(IPITCA)报告温室气体排放的石油工业指南的重点是放在石油工业温室气体排放的计算和报告上.为了提供排放估算一致的方法论,美国石油工业协会制定了石油和天然气工业温室气体排放估算方法论概要.从美国石油学会可以得到一个估算排放的工具--SANGEATM能源和排放估算系统.     

太湖地区两种典型水产养殖系统CH_4排放研究

水产养殖系统是大气CH4重要的人为源,位于中国东南部的太湖地区是水产养殖最活跃的地区之一,但CH4排放原位监测数据比较缺乏,对水产养殖系统温室气体排放进行原位观测,有助于降低当前湿地生态系统温室气体排放估算的不确定性,可为进一步准确估算全球温室气体排放清单提供数据支撑和依据。为了比较太湖地区两种典型水产养殖系统CH4排放规律,探明其影响因素,以混养鱼塘和蟹塘两种具有代表性的水产养殖系统为研究对象,于2016年3月—2017年3月采用漂浮箱(淹水期)和静态箱(排水期)结合气相色谱法监测其CH4排放通量。结果表明,水产养殖系统中CH4排放主要集中在淹水时期,其排放通量与沉积物温度(t)、沉积物溶解有机碳(DOC)和水体溶解氧浓度(DO)呈显著相关(P0.05)。混养鱼塘和蟹塘CH_4累积排放量分别为64.4 kg·hm~(-2)和51.6 kg·hm~(-2),差异显著(P0.05)。水生植物(伊乐藻Elodea nattalii)显著影响蟹塘CH_4排放,有水生植物覆盖区域CH4排放量较无水生植物覆盖区域高14%(P0.05)。与混养鱼塘相比,蟹塘单位收入的甲烷排放所引起净温室效应(NEB-scale·GWP-CH_4)提高了80%,达到显著水平(P0.05)。以上结果表明,在评估区域温室气体排放清单时应考虑水产养殖池塘的类型。     

发展一种估算石油工业温室气体排放的一致的方法

要获得有意义的温室气体清单,重要的是清单中包括的内容的方法论和定义应该是一致的.国际石油工业环境保护协会(IPIECA)、国际石油和天然气生产者协会(OGP)以及美国石油学会(API)已经制定了温室气体排放计算和报告的准则.国际石油工业环境保护协会(IPIECA)报告温室气体排放的石油工业指南的重点是放在石油工业温室气体排放的计算和报告上.为了提供排放估算一致的方法论,美国石油工业协会制定了石油和天然气工业温室气体排放估算方法论概要.从美国石油学会可以得到一个估算排放的工具——SANGEATM能源和排放估算系统.     

大气污染物排放清单的建立及不确定性

本文在调研国内外大气污染物排放清单的基础上,总结了清单编制的基本程序,介绍大气污染物排放清单的建立,包括技术路线和计算方法,以及清单的管理、改善及质量保证与控制计划。不确定性分析是完善清单的重要方面,本文阐述了清单不确定性的来源及定量、定性的评价方法。     

Comparative study on the efficiency and environmental impact of two methods of utilizing polyvinyl chloride waste based on life cycle assessments

Two processes of utilizing polyvinyl chloride （PVC） waste, an incineration process and a vacuum pyrolysis process, for energy conversion were compared to determine their efficiency and environmental perfor- mance. We carried out a life cycle assessment with each of the two processes to evaluate their environmental impact and defined the goals and limits of our remit. As well, we established an inventory of PVC waste from incineration and vacuum pyrolysis based on process analysis, data collection and calculations. The results show that electrical power output per unit mass of PVC waste in the incineration process was twice as high as that of the vacuum pyrolysis process. Incineration had a larger total environmental impact potential than vacuum pyrolysis. The total environmental impact potential of PVC waste from incineration was three times higher than that from vacuum pyrolysis. Incineration of PVC disposed 300 ng. 100 kgI of dioxins and vacuum pyrolysis 98.19 ng- 100 kgI of dioxins. As well, we analyzed the data for their uncertainty with results quantified in terms of three uncertainties： basic uncertainty, additional uncertainty, and computational uncertainty. The coefficients of variation of the data were less than 25% and the quality of the inventory data was acceptable with low uncertainty. Both PVC waste disposal processes were of similar quality and their results comparable. The results of our life cycle impact assessment （LCIA） showed considerable reliability of our methodology. Overall, the vacuum pyrolysis process has a number advantages and greater potential for development of PVC disposal than the incineration process.     

Learning and climate feedbacks: Optimal climate insurance and fat tails

We study the effect of potentially severe climate change on optimal climate change policy, accounting for learning and uncertainty in the climate system. In particular, we test how fat upper tailed uncertainty over the temperature change from a doubling of greenhouse gases (the climate sensitivity), affects economic growth and emissions policy. In addition, we examine whether and how fast uncertainties could be diminished through Bayesian learning. Our results indicate that while overall learning is slow, the mass of the fat tail diminishes quickly, since observations near the mean provide evidence against fat tails. We denote as “tail learning” the case where the planner rejects high values of the climate sensitivity with high confidence, even though significant uncertainty remains. Fat tailed uncertainty without learning reduces current emissions by 38% relative to certainty, indicating significant climate insurance, or paying to limit emissions today to reduce the risk of very high temperature changes, is optimal. However, learning reduces climate insurance by about 50%. The optimal abatement policy is strongly influenced by the current state of knowledge, even though greenhouse gas (GHG) emissions are difficult to reverse. Once the mass of the fat tail diminishes, the remaining uncertainty is largely irrelevant for optimal emissions policy.     

Uncertainty analysis of a pharmacokinetic modeling for inorganic arsenic

This paper presents an uncertainty and sensitivity analysis of a pharmacokinetic modeling of inorganic arsenic deposition in rodents for a short‐term exposure. Efforts to develop the pharmacokinetic model are directed towards predicting the kinetic behavior of inorganic arsenic in the body, including tissue and blood concentrations, and especially, the urinary excretion of arsenic and its methylated metabolites. However, the use of the model raises an important question when fixed values of model parameters are used: how is the uncertainty in the model prediction based on the collective uncertainties in the model inputs? This study focuses on an “epistemic”; uncertainty in order to handle this problem. In this case, the uncertainty refers to an input that has a single value which cannot be known with precision due to a lack of knowledge about items or its measurement. The combination of the pharmacokinetic model and the uncertainty analysis would help understand the uncertainties in risk assessment associated with inorganic arsenic.     

Development of a probabilistic blood lead prediction model

A partially probabilistic blood lead prediction model has been developed, based on the US Environmental Protection Agency integrated exposure-uptake-biokinetic blood lead model (IEUBK model). This study translated the IEUBK model into a spreadsheet format. The uptake submodel incorporates uncertainty distributions for exposure and bioavailability parameters. The biokinetic submodel is duplicated with a table incorporating partitioning and decay of lead levels in the body. As a case study, the probabilistic model is applied to a lead exposure scenario involving a former smelter site in Sandy, Utah. The probabilistic model produces less biased estimates of means and standard deviations than the deterministic model. Parameter uncertainty is propagated in the model by the use of Monte Carlo simulation. Thus, sensitivity analysis is possible, and driving variables can be determined.     

Uncertainty analysis of transient population dynamics

Two types of demographic analyses, perturbation analysis and uncertainty analysis, can be conducted to gain insights about matrix population models and guide population management. Perturbation analysis studies how the perturbation of demographic parameters (survival, growth, and reproduction parameters) may affect the population projection, while uncertainty analysis evaluates how much uncertainty there is in population dynamic predictions and where the uncertainty comes from. Previously, both perturbation analysis and uncertainty analysis were conducted on the long-term population growth rate. However, the population may not reach its equilibrium state, especially when there is management by harvesting or hunting. Recently, there has been an increased interest in short-term transient dynamics, which can differ from asymptotic long-term dynamics. There are currently techniques to conduct perturbation analyses of short-term transient dynamics, but no techniques have been proposed for uncertainty analysis of such dynamics. In this study, we introduced an uncertainty analysis technique, the general Fourier Amplitude Sensitivity Test (FAST), to study uncertainties in transient population dynamics. The general FAST is able to identify the amount of uncertainty in transient dynamics and contributions by different demographic parameters. We applied the general FAST to a mountain goat (Oreamnos americanus) matrix population model to give a clear illustration of how uncertainty analysis can be conducted for transient dynamics arising from matrix population models.     

Cost‐effective conservation of an endangered frog under uncertainty

How should managers choose among conservation options when resources are scarce and there is uncertainty regarding the effectiveness of actions? Well‐developed tools exist for prioritizing areas for one‐time and binary actions (e.g., protect vs. not protect), but methods for prioritizing incremental or ongoing actions (such as habitat creation and maintenance) remain uncommon. We devised an approach that combines metapopulation viability and cost‐effectiveness analyses to select among alternative conservation actions while accounting for uncertainty. In our study, cost‐effectiveness is the ratio between the benefit of an action and its economic cost, where benefit is the change in metapopulation viability. We applied the approach to the case of the endangered growling grass frog (Litoria raniformis), which is threatened by urban development. We extended a Bayesian model to predict metapopulation viability under 9 urbanization and management scenarios and incorporated the full probability distribution of possible outcomes for each scenario into the cost‐effectiveness analysis. This allowed us to discern between cost‐effective alternatives that were robust to uncertainty and those with a relatively high risk of failure. We found a relatively high risk of extinction following urbanization if the only action was reservation of core habitat; habitat creation actions performed better than enhancement actions; and cost‐effectiveness ranking changed depending on the consideration of uncertainty. Our results suggest that creation and maintenance of wetlands dedicated to L. raniformis is the only cost‐effective action likely to result in a sufficiently low risk of extinction. To our knowledge we are the first study to use Bayesian metapopulation viability analysis to explicitly incorporate parametric and demographic uncertainty into a cost‐effective evaluation of conservation actions. The approach offers guidance to decision makers aiming to achieve cost‐effective conservation under uncertainty.     

Assessing carbon footprint in the life cycle of accommodation services: the case of an international tourist hotel

The accommodation sector is the most demanding energy consumer among all building stock categories. This study quantifies an international tourist hotel in Taiwan to holistically estimate the greenhouse gas emissions of hotel accommodation services through a complete life cycle inventory. The study also investigates the difference between the carbon emissions of the baseline and reduction years to understand the effects of carbon emission reduction on the hotel industry. Results show that energy consumption is the main source of carbon footprint. However, the carbon emissions of other activities, such as the production and transportation of hotel amenities and laundry services, are 15.90% for the baseline year and 16.03% for the reduction year. These values are larger than the 5% cutoff rule according to PAS 2050. Thus, these factors should also be considered in assessing the carbon emissions of accommodation services. Hotel occupancy rate significantly affects carbon emissions during a one-night stay in a standard room as the functional unit. The selection of the functional unit should be considered in the hotel strategy. Although this case study involves an international tourist hotel in Taiwan, the findings and recommendations for improvements can be applied elsewhere.