Modeling effects of temperature and precipitation on carbon characteristics and GHGs emissions in Abies fabric forest of subalpine

Abies fabric forest in the eastern slope of Gongga mountain is one type of subalpine dark coniferous forests of southwestern China. It is located on the southeastern edge of the Qinghai-Tibet plateau and is sensitive to climatic changes. A process-oriented biogeochemical model, Forest-DNDC, was applied to simulate the e ects of climatic factors, temperature and precipitation changes on carbon characteristics, and greenhouse gases (GHGs) emissions in A. fabric forest. Validation indicated that the Forest-DNDC could be used to predict carbon characteristics and GHGs emissions with reasonable accuracy. The model simulated carbon fluxes, soil carbon dynamics, soil CO2, N2O, and NO emissions with the changes of temperature and precipitation conditions. The results showed that with variation in the baseline temperature from –2℃ to +2℃, the gross primary production (GPP) and soil organic carbon (SOC) increased, and the net primary production (NPP) and net ecosystem production (NEP) decreased because of higher respiration rate. With increasing baseline precipitation the GPP and NPP increased slightly, and the NEP and SOC showed decreasing trend. Soil CO2 emissions increased with the increase of temperature, and CO2 emissions changed little with increased baseline precipitation. With increased temperature and decreased baseline temperature, the total annual soil N2O emissions increased.With the variation of baseline temperature from –2℃ to +2℃, the total annual soil NO emissions increased. The total annual N2O and NO emissions showed increasing trends with the increase of precipitation. The biogeochemical simulation of the typical forest indicated that temperature changes strongly a ected carbon fluxes, soil carbon dynamics, and soil GHGs emissions. The precipitation was not a principal factor a ecting carbon fluxes, soil carbon dynamics, and soil CO2 emissions, but changes in precipitation could exert strong e ect on soil N2O and NO emissions.     

活化处理活性炭纤维的表面特性及其汞吸附性能

选用了3种比表面积不同的粘胶基活性炭纤维(ACF-1、ACF-2和ACF-3),并对样品ACF-1进行了浓硝酸和氨水活化处理,获得样品ACF-N和ACF-NH3,最后对这5种ACF样品进行表面特性表征和单质汞的吸附实验.氮分子吸附(77.4K)实验结果表明,ACF-N和ACF-NH3的微孔容积与ACF-1相比有所减小,各样品的微孔(d2nm)分布有一定差异.ACF含有许多不规则的表面微结构,其X射线光电子能谱(XPS)分析表明,ACF-N的含氧官能团(CO、COOH)和ACF-NH3的含氮官能团含量与ACF-1相比均有明显增加.X射线衍射(XRD)分析结果表明,ACF-2和ACF-3的石墨化程度和晶体化程度较ACF-1有所提高.汞吸附实验表明,由于受到ACF表面微结构的影响,微孔容积与吸附能力之间并非简单的依附关系,增加含氧、含氮基团含量在一定程度上能提高ACF的汞吸附容量.     

北京市压缩天然气公交车的环境效果分析

经过对北京市2007年公交车队的详细技术构成与实际运营情况的调研,发现北京市公交车队的主力车型为国三和国四车辆,应用修正的COPERTIV模型计算出北京市各技术水平的汽油、柴油和压缩天然气(CNG)公交车的排放因子.2007年北京市国三CNG公交车PM2.5和NOx单车排放因子分别比国三柴油车削减了97%和30%,而公交车队中排放控制最为严格的EEV天然气公交车的PM2.5和NOx单车排放因子分别比国四柴油公交车削减了93%和69%.但由于CNG公交车的CH4排放水平较高,导致CNG公交车的总碳氢化合物(THC)单车排放因子显著高于相近控制水平的柴油公交车.在单车排放水平的基础上建立了北京市公交车排放清单,2007年北京市公交车排放的CO、NMHC、THC、NOx和PM2.5分别为9051t、955t、1222t、8553t和161t.与没有CNG公交车的对照情景进行比较,在使用了CNG公交车后,2007年北京市公交车CO、NMHC、NOx和PM2.5排放总量分别削减了293t、62t、775t和33t,削减比例分别为3.1%、6.1%、8.3%和17.2%.2007年北京市通过在公交车队中使用CNG车辆共减少了柴油消耗量约5.0×104t,相当于北京市各行业柴油总消耗量的2.6%.2007年北京市公交车尾气排放的温室气体的CO2当量为8.3×105t,比不使用CNG车辆的情景略微增加了2.4%.     

Bayesian calibration of the nitrous oxide emission module of an agro-ecosystem model

Nitrous oxide (N₂O) is the main biogenic greenhouse gas contributing to the global warming potential (GWP) of agro-ecosystems. Evaluating the impact of agriculture on climate therefore requires a capacity to predict N₂O emissions in relation to environmental conditions and crop management. Biophysical models simulating the dynamics of carbon and nitrogen in agro-ecosystems have a unique potential to explore these relationships, but are fraught with high uncertainties in their parameters due to their variations over time and space. Here, we used a Bayesian approach to calibrate the parameters of the N₂O submodel of the agro-ecosystem model CERES-EGC. The submodel simulates N₂O emissions from the nitrification and denitrification processes, which are modelled as the product of a potential rate with three dimensionless factors related to soil water content, nitrogen content and temperature. These equations involve a total set of 15 parameters, four of which are site-specific and should be measured on site, while the other 11 are considered global, i.e. invariant over time and space. We first gathered prior information on the model parameters based on the literature review, and assigned them uniform probability distributions. A Bayesian method based on the Metropolis–Hastings algorithm was subsequently developed to update the parameter distributions against a database of seven different field-sites in France. Three parallel Markov chains were run to ensure a convergence of the algorithm. This site-specific calibration significantly reduced the spread in parameter distribution, and the uncertainty in the N₂O simulations. The model’s root mean square error (RMSE) was also abated by 73% across the field sites compared to the prior parameterization. The Bayesian calibration was subsequently applied simultaneously to all data sets, to obtain better global estimates for the parameters initially deemed universal. This made it possible to reduce the RMSE by 33% on average, compared to the uncalibrated model. These global parameter values may be used to obtain more realistic estimates of N₂O emissions from arable soils at regional or continental scales.     

农业残留物燃烧温室气体排放清单研究:以江苏省为例

通过问卷调查确定了江苏省农业残留物在不同时间阶段(1990～1995、1996～2000、2001～2005和2006～2008年)作为生活燃料和田间直接燃烧的比例,利用燃烧炉模拟秸秆燃烧试验确定了6种农业残留物(水稻、小麦、玉米、油菜、棉花和大豆)燃烧产生的CO2、CO、CH4和N2O的排放因子;基于此,结合江苏省不...     

基于投入产出法的北京能源消耗温室气体排放清单分析

城市是一个巨大能源物资消耗体和温室气体排放体,相关研究受到广泛关注.本文以2007年为例基于投入产出法研究北京市能源消耗的温室气体排放量,计算得出CH4和N2O这两种常规温室气体排放量.结果表明,北京市2007年能源消耗温室气体排放量为3531.72万tCO2当量,其中CO2排放量为3514.40万t,CH4排放量为1734.32t,N2O排放量为435.83t.北京市工业部门仍然是主要的温室气体排放部门,其排放的温室气体占CO2总量的98.96%,CH4总量的88.48%和N2O总量的98.99%.不同最终使用部门中,政府部门消费产生的温室气体排放量超过总量的15%,高于城镇消费和农村消费之和;调出和出口部门的碳排放量超过总量的40%,所占比例最大.贸易中,隐含在调出和出口部门中温室气体排放量是隐含在调入和进口部门的十几倍.北京市不同行业的温室气体排放强度略优于全国水平.降低北京市温室气体排放量可从进一步优化产业结构,发挥科技减排的作用,提高不同产业的能源利用率等方面采取措施.     

北京市“十四五”时期大气污染物与温室气体协同控制效果评估研究

面对国家碳达峰、碳中和战略目标,“十四五”时期,北京市提出推进大气污染物和温室气体排放协同控制,因此,开展协同控制效果评估对于持续改善空气质量和减少碳排放具有重要意义 .本研究在减排措施筛选和减排量测算的基础上,分析了主要大气污染物和 CO₂的减排潜力,采用协同控制效应坐标系法、协同控制交叉弹性分析法和协同评估指数法,对减排措施主要大气污染物 SO₂、NO_x、PM₁₀、VOCs 和温室气体CO₂的协同控制效果进行评估 . 结果表明,减排措施对于 SO₂、NO_x的减排潜力均在 20% 以上,对于 CO₂的减排潜力约为 7%. 各项措施对 NO_x、PM₁₀、VOCs和 CO₂排放具有协同控制效果 .从坐标系法和评估指数法分析结果来看,浅山区煤改清洁能源和压减本地火力发电量对 SO₂和 CO₂的协同控制效果较好...     

广东省居民生活直接能源消费大气污染物与温室气体排放趋势研究

居民生活直接能源消费是重要的大气污染物和温室气体排放来源,识别其历史排放趋势是科学制定管控策略的基础.然而目前我国尚缺乏省级尺度居民生活能源消费排放趋势的研究.以广东省为研究对象,通过广泛收集居民生活直接能源消费数据和排放因子,建立了2006—2017年广东省居民生活直接能源消费大气污染物和温室气体排放清单,并采用情景分析法量化了能源结构变化对居民生活直接能源消费大气污染物与温室气体排放的影响.结果表明：①2006—2017年居民生活直接能源消费排放的大气污染物和温室气体均呈下降趋势,CO、PM_2.5、BC、OC、CH₄、CO₂和N₂O排放量分别下降70%、59%、59%、66%、77%、30%和73%;②城乡贡献上,乡村居民生活直接能源消费是大气 污染物和温室气体排放的主要来源,排放分担率分别在70%和60%以上;③空间分布上,2017年广东省居民生活直接能源消费大气污染物和温室气体排放主要集中在粤东、粤西传统燃料消费量较高的地区,以及广州、东莞和深圳等人口密度较大的城市地区;④能源结构清洁化所致的2006—2017年广东省居民生活直接能源消费大气污染物和温室气体减排比例为38%~88%;⑤以2025年为目标年,居民生活能源结构持续清洁化发展能够进一步降低居民生活直接能源消费大气污染物和温室气体排放,尤其对CO、PM_2.5、BC、CH₄和N₂O的减排比例均在80%以上.     

温室气体对气候环境的影响预测及其不确定性

随着温室气体排放量的增加,联系温室气体特有的保温效应,大气平均气温将升高。在采用气候模式对未来近百年的气候变化做出一定预测的基础上,分析未来可能出现的气候变化所造成的对气候环境方面的影响。详细分析了现阶段预测未来气候环境变化存在的不确定性,正是这些不确定性影响了预测的可信度。     

城市生活垃圾筛上物制备RDF及其燃烧特性研究

利用城市垃圾筛上物制备RDF可以实现垃圾处理的减量化和资源化。研究了北京市城市生活垃圾筛上物制备RDF的工艺条件,探讨不同成型压力、含水率以及助燃剂含量对RDF成型特性的影响,在此基础上研究添加CaO对其燃烧特性的影响。结果表明:含水率10%,成型压力1 MPa的RDF在加入1%的KClO4后成型较好,燃烧后残渣少。随着CaO添加量的增加,RDF燃烧SO2的释放量减少;而当CaO添加量大于2%时,HCl的释放量基本保持不变。在RDF中加入CaO可以将其中的氯元素和硫元素有效固定在残渣中,从而有效减少了酸性气体排放。