Review: recent advances in biogas purifying technologies

Biomethane production through biogas upgrading is a promising renewable energy for some industries which could be part of the equilibrium needed with fossil fuels consumption to achieve a sustainable society. This paper presents a comprehensive list of biogas upgrading technologies focused on carbon dioxide removal as well as recent advances reported by researcher with wide expertise in this topic. Additionally, an extensive costs–performance comparison among the technologies studied is discussed. Among the different alternatives, chemical scrubbing stood out to achieve high biomethane purities while cryogenic technologies proved to be effective against methane losses. Regarding the different costs, water scrubbing and membrane separation seem to be the most affordable techniques.     

Analysis of the Trend and Seasonal Cycle of Carbon Monoxide Concentrations in an Urban Area (4 pp)

Background, Aim and Scope Air quality is an field of major concern in large cities. This problem has led administrations to introduce plans and regulations to reduce pollutant emissions. The analysis of variations in the concentration of pollutants is useful when evaluating the effectiveness of these plans. However, such an analysis cannot be undertaken using standard statistical techniques, due to the fact that concentrations of atmospheric pollutants often exhibit a lack of normality and are autocorrelated. On the other hand, if long-term trends of any pollutant’s emissions are to be detected, meteorological effects must be removed from the time series analysed, due to their strong masking effects. Materials and Methods The application of statistical methods to analyse temporal variations is illustrated using monthly carbon monoxide (CO) concentrations observed at an urban site. The sampling site is located at a street intersection in central Valencia (Spain) with a high traffic density. Valencia is the third largest city in Spain. It is a typical Mediterranean city in terms of its urban structure and climatology. The sampling site started operation in January 1994 and monitored CO ground level concentrations until February 2002. Its geographic coordinates are W0°22′52″ N39°28′05″ and its altitude is 11 m. Two nonparametric trend tests are applied. One of these is robust against serial correlation with regards to the false rejection rate, when observations have a strong persistence or when the sample size per month is small. A nonparametric analysis of the homogeneity of trends between seasons is also discussed. A multiple linear regression model is used with the transformed data, including the effect of meteorological variables. The method of generalized least squares is applied to estimate the model parameters to take into account the serial dependence of the residuals of this model. This study also assesses temporal changes using the Kolmogorov-Zurbenko (KZ) filter. The KZ filter has been shown to be an effective way to remove the influence of meteorological conditions on O₃ and PM to examine underlying trends. Results The nonparametric tests indicate a decreasing, significant trend in the sampled site. The application of the linear model yields a significant decrease every twelve months of 15.8% for the average monthly CO concentration. The 95% confidence interval for the trend ranges from 13.9% to 17.7%. The seasonal cycle also provides significant results. There are no differences in trends throughout the months. The percentage of CO variance explained by the linear model is 90.3%. The KZ filter separates out long, short-term and seasonal variations in the CO series. The estimated, significant, long-term trend every year results in 10.3% with this method. The 95% confidence interval ranges from 8.8% to 11.9%. This approach explains 89.9% of the CO temporal variations. Discussion The differences between the linear model and KZ filter trend estimations are due to the fact that the KZ filter performs the analysis on the smoothed data rather than the original data. In the KZ filter trend estimation, the effect of meteorological conditions has been removed. The CO short-term componentis attributable to weather and short-term fluctuations in emissions. There is a significant seasonal cycle. This component is a result of changes in the traffic, the yearly meteorological cycle and the interactions between these two factors. There are peaks during the autumn and winter months, which have more traffic density in the sampled site. There is a minimum during the month of August, reflecting the very low level of vehicle emissions which is a direct consequence of the holiday period. Conclusions The significant, decreasing trend implies to a certain extent that the urban environment in the area is improving. This trend results from changes in overall emissions, pollutant transport, climate, policy and economics. It is also due to the effect of introducing reformulated gasoline. The additives enable vehicles to burn fuel with a higher air/fuel ratio, thereby lowering the emission of CO. The KZ filter has been the most effective method to separate the CO series components and to obtain an estimate of the long-term trend due to changes in emissions, removing the effect of meteorological conditions. Recommendations and Perspectives Air quality managers and policy-makers must understand the link between climate and pollutants to select optimal pollutant reduction strategies and avoid exceeding emission directives. This paper analyses eight years of ambient CO data at a site with a high traffic density, and provides results that are useful for decision-making. The assessment of long-term changes in air pollutants to evaluate reduction strategies has to be done while taking into account meteorological variability     

长春秋季生物质燃烧对PM2.5中WSOC吸光性的影响

为探究长春秋季生物质燃烧对PM_(2.5)中水溶性有机碳(water-soluble organic carbon,WSOC)吸光性的影响,于2017年10～11月进行PM_(2.5)样品采集,对PM_(2.5)中碳质组分、糖类化合物和WSOC的光吸收特征参数进行分析.研究表明:长春秋季PM_(2.5)中WSOC、有机碳(organic carbon,OC)、元素碳(elemental carbon,EC)的平均浓度分别为(10.12±3.47)、(17.07±5.64)和(1.34±0.75)μg·m~(-3),二次有机碳(secondary organic carbon,SOC)对OC的平均贡献率为38.93%.长春秋季总糖浓度为(1 049.39±958.85)ng·m~(-3),其中作为生物质燃烧示踪剂的脱水糖含量(左旋葡聚糖、半乳聚糖和甘露聚糖)在总糖中占比为91.69%,糖类相关性分析结果显示生物质燃烧源为长春秋季大气中糖类物质的主要贡献源.糖类物质的相关性分析及3种脱水糖的特征比值研究显示,作为长春秋季大气主要污染源的生物质燃烧的类型是硬木和作物残渣的燃烧.长春秋季WSOC的光吸收波长指数(AAE)为5.75±1.06,单位质量吸收效率(MAE)为(1.23±0.28)m~2·g~(-1),表明生物质燃烧对WSOC吸光性具有重要影响.利用生物质燃烧特征源参数量化计算生物质燃烧对WSOC浓度的贡献达58.82%,对总WSOC光吸收的贡献达40.92%.     

北京南部城区PM2.5中碳质组分特征

为了解《大气污染防治行动计划》实施后北京市大气PM_2.5中碳质组分特征,于2017年12月至2018年12月在北京污染较重的南部城区进行了PM_2.5连续采样,对其中的有机碳（OC）和元素碳（EC）进行了全面研究.结果表明,北京大气PM_2.5、OC和EC浓度变化范围分别为4.2~366.3、0.9~74.5和0.0~5.5 μg ·m^-3,平均浓度分别为（77.1±52.1）、（11.2±7.8）和（1.2±0.8）μg ·m^-3,碳质组分（OC和EC）整体占PM_2.5的16.1%.OC质量浓度季节特征表现为：冬季[（13.8±8.7）μg ·m^-3] > 春季[（12.7±9.6）μg ·m^-3] > 秋季[（11.8±6.2）μg ·m^-3] > 夏季[（6.5±2.1）μg ·m^-3],EC四季质量浓度水平均较低,范围为0.8~1.5 μg ·m^-3.二次有机碳（SOC）年均质量浓度为（5.4±5.8）μg ·m^-3,四季贡献比例范围为45.7%~52.3%,年均贡献为48.2%,凸显了二次形成的重要贡献.随污染加重,尽管OC和EC贡献比例均降低,但浓度水平却成倍升高,OC和EC浓度在严重污染天分别是空气质量为优天的6.3和3.2倍.与非供暖时段相比,供暖时段PM_2.5、OC和SOC浓度分别增加了14.4%、47.9%和72.1%,体现了OC对供暖季PM_2.5污染的重要贡献.PSCF分析表明,位于北京西南的山西省和河南省部分区域是PM_2.5和OC的主要潜在源区,且PM_2.5潜在源区更为集中;EC的PSCF高值（>0.7）区域较少,主要位于北京南部,如山东省和河南省部分地区,且北京市及周边地区贡献明显.     

固定化微藻流化床反应器去除低碳污水中氨氮的潜力

以固定化微藻颗粒为原料,通过搭建流化床反应器强化微藻对氨氮（NH₄⁺-N）的去除,设计了藻种、污水上升流速、光周期和光照强度四组单一变量实验,系统地研究了不同条件下微藻去除NH₄⁺-N的能力.结果表明,当以固定化斜生栅藻为原料、污水上升流速为6.8m/h、光周期为8：16h和光照强度为4800Lux时,NH₄⁺-N去除效果最优（96.7%）.在最优操作条件下,探究了COD为200mg/L时微藻去除NH₄⁺-N的潜力,结果表明,当NH₄⁺-N初始浓度不高于50mg/L时,NH₄⁺-N去除率高于95%.本实验建立了一套半连续微藻流化床实验方法,该方法显著减弱了微藻在生物同化过程中对有机碳源的依赖性,为低COD条件下微藻生物脱氮工艺的设计提供了技术参考和理论基础.     

岩溶地下河污染物运移模型对比研究

两区模型（TRM）和暂时存储模型（TSM）为两种常用的岩溶地下河（管道）污染物运移模型,为了更好表征岩溶地下河污染物运移过程,开展模型对比研究.采用两种模型拟合室内管道示踪实验穿透曲线,从概念模型框架、模型优缺点、参数校正过程和物理意义、参数敏感性等方面对比分析两种模型的异同.结果表明,OTIS软件提供TSM的数值解,而CXTFIT软件提供TRM的解析解,但两者均能通过下游不同位置的穿透曲线分段表征地下河不同阶段的污染物运移过程.两种模型的物理意义相近,均可近似描述岩溶地下河中溶质的暂时性存储现象,较好地拟合溶质运移曲线.采用TSM可校正得到暂时存储区的横截面积,但采用TRM只能获得非流动区所占的比例.两种模型中弥散系数和传质/交换系数的敏感度较低,并且弥散系数的变化对穿透曲线拖尾无显著影响.研究结果为岩溶地下河污染物运移模型的选取与应用提供了依据.     

Coupling mechanism of activated carbon mixed with dust for flue gas desulfurization and denitrification

To clarify the effect of coking dust, sintering dust and fly ash on the activity of activated carbon for various industrial flue gas desulfurization and denitrification, the coupling mechanism of the mixed activated carbon and dust was investigated to provide theoretical reference for the stable operation. The results show that coking dust had 34% desulfurization efficiency and 10% denitrification efficiency; correspondingly, sintering dust and fly ash had no obvious desulfurization and denitrification activities. For the mixture of activated carbon and dust, the coking dust reduced the desulfurization and denitrification efficiencies by blocking the pores of activated carbon, and its inhibiting effect on activated carbon was larger than its own desulfurization and denitrification activity. The sintering dust also reduced the desulfurization efficiency on the activated carbon while enhancing the denitrification efficiency. Fly ash blocked the pores of activated carbon and reduced its reaction activity. The reaction activity of coking dust mainly came from the surface functional groups, similar to that of activated carbon. The reaction activity of sintering dust mainly came from the oxidative property of Fe₂O₃, which oxidized NO to NO₂ and promoted the fast selectively catalytic reduction (SCR) of NO to form N₂. Sintering dust was activated by the joint action of activated carbon, and both had a coupling function. Sintering dust enhanced the adsorption and oxidation of NO, and activated carbon further promoted the reduction of NO_x by NH₃; thus, the denitrification efficiency increased by 5%-7% on the activated carbon.     

尕海湿地植被退化过程中有机碳及相关土壤酶活性变化特征

以青藏高原东缘尕海湿地不同植被退化程度样地为研究对象,采用定位研究与室内试验相结合的方法,研究植被退化过程对土壤有机碳和土壤酶活性的影响。结果表明：植被退化显著影响土壤有机碳含量和土壤酶活性,降低了土壤有机碳的含量和酶促反应效率,且这种影响随土层深度变化有所不同。四种植被退化阶段有机碳含量和酶活性均值总体上（0~100 cm）表现为未退化>轻度退化>中度退化>重度退化。不同土层中,20~40 cm土层的有机碳含量中度退化>轻度退化;0~10 cm土层中淀粉酶和纤二糖酶中度退化阶段活性值较高;20~100 cm土层中蔗糖酶重度退化阶段活性值最高,纤二糖酶活性重度退化>中度退化。同一退化程度土壤有机碳含量、蔗糖酶和纤二糖酶活性随土层深度增加显著降低（P<0.05）;淀粉酶和纤维素酶活性在>40 cm土层中活性值有所上升,整体呈波动下降趋势。     

珠江口夏季海陆源有机碳的模拟研究——分布特征、贡献比重及其迁移转化过程

基于经过验证的三维水动力-水质模型,对珠江口夏季有机碳进行海陆源区分,并对海陆源有机碳的分布特征、贡献比重及其通量过程进行研究.结果表明,水平方向上,珠江口夏季陆源（海源）有机碳浓度从口门到外海逐渐降低（升高）,在表、底层海水中平均浓度分别为1.45和0.87mg/L（0.97和1.05mg/L）;垂直方向上,在层化水域陆源（海源）有机碳浓度从上到下逐渐递减（升高）,在非层化水域海陆源有机碳浓度垂向分布较为均匀.珠江口夏季海源有机碳贡献率表层海水低于底层海水,平均贡献率为48.26%,沿向海方向海源有机碳贡献率逐渐增加--从内伶仃洋水域的4.43%逐渐提升到外伶仃洋东侧水域的81.20%.珠江口水动力条件复杂,在径流、潮汐、季风等因素的作用下陆源有机碳向海输送且向海输送量逐渐递减;海源有机碳在不同水域动力输送特征不同,西南水域向海输送,向海输送量逐渐递增;东北水域向岸输送,向岸输送量逐渐递减.陆源有机碳生化反应活性较弱,只有小部分被生化过程消耗,其迁移转化主要由沉降过程控制,而海源有机碳的迁移转化,则由口门的动力输送过程主控向外海的生化耗碳过程主控过渡.此外,海源有机碳沉降作用明显低于陆源有机碳,生化作用明显高于陆源有机碳.     

三江源植被碳利用率动态变化及其对气候响应

本文基于MODIS GPP/NPP数据估算了三江源植被碳利用率（CUE）,结合气象数据和高程数据采用一元线性回归和相关分析法,探讨了2001~2017年三江源植被CUE的时空变化特征及植被CUE对气温、降水量和蒸散量变化的响应.结果表明：（1）三江源植被CUE年内3~10月表现为先增加后降低的变化趋势,其中6月植被CUE最高.（2）三江源年植被碳利用率位于0.73~1,平均水平为0.85;植被CUE空间上呈现北高南低,西高东低的分布特征.（3）整体上,三江源4~10月植被碳利用率与同期气温、降水量和蒸散量分别呈现正相关、负相关和负相关关系,降水量是影响三江源植被CUE变化的主要影响因素,气温为次要因素,蒸散量影响程度最小.