基于LCA的北京市公交车节能及温室气体减排潜力分析

新能源公交车是未来城市公交行业节能及温室气体减排的重点发展方向.新能源公交车在行驶阶段具有良好的节能及温室气体减排效果,而汽车制造、能源生产等相关生命周期阶段的能耗及温室气体排放常被忽视,且目前新能源公交车的乘客运载功能相对较弱,可能对节能及温室气体减排的潜力造成较为显著的影响.因此,本文基于北京市公交车的运营特征,采用生命周期评价(LCA)方法,选择客运周转量作为功能单位,核算了天然气公交车、混合动力公交车和纯电动公交车等新能源公交车相对于柴油公交车的节能及温室气体减排效益.结果表明:发展新能源公交车对促进北京市公交行业及城市节能低碳发展具有积极的作用,但相对于基于运营里程的核算结果,本研究新能源公交车节能及温室气体减排潜力均较低,主要原因是新能源公交车的实际载客量相对较低;混合动力公交车和纯电动公交车在空调开启时的节能潜力与温室气体减排潜力均远低于天然气公交车;通过发展情景分析,建议北京市现阶段应优先发展天然气公交车,适当发展纯电动公交车和混合动力公交车,以减少北京市公交车的总体能耗,同时降低温室气体排放强度.     

Stepwise multiple regression method of greenhouse gas emission modeling in the energy sector in Poland

The energy sector in Poland is the source of 81% of greenhouse gas (GHG) emissions. Poland, among other European Union countries, occupies a leading position with regard to coal consumption. Polish energy sector actively participates in efforts to reduce GHG emissions to the atmosphere, through a gradual decrease of the share of coal in the fuel mix and development of renewable energy sources. All evidence which completes the knowledge about issues related to GHG emissions is a valuable source of information. The article presents the results of modeling of GHG emissions which are generated by the energy sector in Poland. For a better understanding of the quantitative relationship between total consumption of primary energy and greenhouse gas emission, multiple stepwise regression model was applied. The modeling results of CO₂ emissions demonstrate a high relationship (0.97) with the hard coal consumption variable. Adjustment coefficient of the model to actual data is high and equal to 95%. The backward step regression model, in the case of CH₄ emission, indicated the presence of hard coal (0.66), peat and fuel wood (0.34), solid waste fuels, as well as other sources (− 0.64) as the most important variables. The adjusted coefficient is suitable and equals R² = 0.90. For N₂O emission modeling the obtained coefficient of determination is low and equal to 43%. A significant variable influencing the amount of N₂O emission is the peat and wood fuel consumption.     

Stepwise multiple regression method of greenhouse gas emission modeling in the energy sector in Poland

The energy sector in Poland is the source of 81% of greenhouse gas (GHG) emissions. Poland, among other European Union countries, occupies a leading position with regard to coal consumption. Polish energy sector actively participates in efforts to reduce GHG emissions to the atmosphere, through a gradual decrease of the share of coal in the fuel mix and development of renewable energy sources. All evidence which completes the knowledge about issues related to GHG emissions is a valuable source of information. The article presents the results of modeling of GHG emissions which are generated by the energy sector in Poland. For a better understanding of the quantitative relationship between total consumption of primary energy and greenhouse gas emission, multiple stepwise regression model was applied. The modeling results of CO₂ emissions demonstrate a high relationship (0.97) with the hard coal consumption variable. Adjustment coefficient of the model to actual data is high and equal to 95%. The backward step regression model, in the case of CH₄ emission, indicated the presence of hard coal (0.66), peat and fuel wood (0.34), solid waste fuels, as well as other sources (-0.64) as the most important variables. The adjusted coefficient is suitable and equals R² = 0.90. For N₂O emission modeling the obtained coefficient of determination is low and equal to 43%. A significant variable influencing the amount of N₂O emission is the peat and wood fuel consumption.     

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.     

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。     

昆明市主城区三种温室气体的月份和干、湿季的小时变化规律及原因分析

研究了昆明市主城区3种温室气体浓度的最新变化情况,采用2009年、2010年和2011年的月份和小时平均浓度数据,结合昆明市气候特点,对3种温室气体浓度的月份和干、湿季的小时变化规律及原因进行了分析。     

天津市夏季蜂窝状溶蚀器涂层溶液浓度确定的实验研究

于2013年7月1日～8月31日,在天津市南开大学理化楼楼顶,采用蜂窝状溶蚀器进行了溶蚀器涂层溶液最适浓度的探究实验.结果表明,在天津夏季,蜂窝状溶蚀器的碳酸钠涂层溶液最适浓度为3%,柠檬酸涂层溶液最适浓度为6%.含有溶蚀器系统的颗粒物采样法与传统采样法对比发现,含蜂窝状溶蚀器的采样系统所得到的PM2.5样品浓度有86%低于传统方法所得到的PM2.5样品浓度,其原因主要为1酸/碱性气体被去除,使其无法与富集在采样膜上的颗粒物发生反应,也无法吸附到颗粒物上;2溶蚀器系统采样过程中,部分颗粒物被捕集到溶蚀器上;3酸/碱性气体被去除,导致气-粒平衡被打破,部分颗粒物组分向气态转化.     

重庆主城区降水中重金属的分布特征及其沉降量

于2011年12月~2012年11月,在重庆主城区设置了3个采样点,利用湿沉降自动采样器收集降水样品,用ICP-MS对样品中13种重金属进行分析,并通过引入富集因子,研究了重庆主城区降水中重金属含量分布特征、污染水平及沉降量.结果表明,重庆主城区降水中大部分重金属元素的含量水平和年沉降量高于国内其他城市和国外一些地区,其中,Cd、Pb、As含量和沉降量分别为0.55μg·L-1和0.44 mg·(m2·a)-1、37.94μg·L-1和30.25 mg·(m2·a)-1、5.65μg·L-1和4.50mg·(m2·a)-1,相对较高.另外,重庆主城区降水中重金属含量和沉降量空间差异不大,但都有明显的季节差异,含量在秋季和冬季出现较大值,而沉降量在春季和夏季出现较大值.富集因子计算结果显示,多种重金属元素的富集因子相对较高,其中Cd和Se的富集因子分别为1 740和4 133,污染较为严重.     

弹药库房密闭期间有害气体的分析

弹药在长期储存过程中,受储存环境影响,其装药会发生缓慢的分解、水解反应,产生易燃易爆及有害气体.为深入研究弹药在密闭过程中有害气体对弹药库房及人员可能造成的危害,对弹药库房密闭期间产生的有毒、有害及可燃气体成分作定性和定量检测,深入分析影响弹药安全和人员身体健康的有害气体的测试结果.     

热污染及其防治

对热污染状况进行了介绍.概括了热污染的危害,包括危害人体健康、影响全球气候变化、污染大气、污染水体、加快水分蒸发、增加能量消耗等.分析了热污染的原因,自然气候的异常变化和人为因素是热污染产生的两大原因.最后提出了几点防治热污染的措施.