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.     

碘化阶层孔氧化硅纳米球对水中典型有机氯污染物的吸附性能研究

采用共缩聚法,成功地原位合成了碘改性的阶层多孔氧化硅纳米球（SiO₂-I）,研究了其基于卤键作用对典型有机氯污染物六六六的吸附性能,并考察了改性剂I-硅烷含量和pH值对吸附效果的影响.实验结果表明,该纳米材料对六六六表现出优异的吸附富集性能,吸附速率快,60 min内对六六六的去除率为71.6%,240 min内达到吸附平衡,去除率可达98.3%,最大吸附量为178.6 mg·g^-1;吸附动力学符合拟二级动力学模型;碘物种的加入提高了阶层多孔氧化硅的吸附速率和吸附效率.另外,为了便于纳米吸附材料的分离,本研究对SiO₂-I纳米球进行了磁性化.研究发现,磁性化修饰后,SiO₂-I纳米材料仍然保留对六六六优异的吸附富集性能,240 min时的吸附去除率达90.3%.     

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.     

酸性紫色水稻土颗粒有机质对镉的吸附特性

采集典型的酸性紫色水稻土（APPS）,从中分离出颗粒有机质（POM）,通过批量试验研究POM及其来源土壤Cd²⁺的吸附动力学、等温吸附和热力学特征,通过扫描电镜-能谱仪、傅里叶红外光谱仪等手段及吸附前后镉的形态变化的测定,研究了POM对Cd²⁺的吸附机制.结果表明：POM对Cd²⁺的亲和力远高于其来源土壤.POM及土壤对Cd²⁺的吸附动力学最优模型均为准二级动力学.Langmuir、Freundlich方程均能较好地描述其等温吸附特征,其中对POM,以Freundlich方程更优,表明POM对Cd²⁺的吸附属于多分子层的非均质吸附.吸附热力学参数△G^θ均小于0、△H^θ和△S^θ均大于0,表明吸附属于自发吸热过程.根据△H^θ值及解吸试验判定POM对Cd²⁺的吸附以化学吸附为主,土壤对Cd²⁺的吸附过程以物理吸附为主.吸附平衡后,土壤中可交换态镉比例提高,而POM中交换态和络合态镉比例增加.综上及吸附前后POM的表征结果说明,POM对Cd²⁺的吸附机制包括含氧官能团的络合、离子交换、阳离子-π键、沉淀作用和静电吸附.     

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。     

硅胶表面TEOS疏水化改性及吸附VOCs特性

以正硅酸乙酯（TEOS）为疏水改性剂,通过硅胶表面的羟基接枝反应,得到具备一定疏水性的改性硅胶;利用BET、FT-IR、XRD和TG-DTG等手段对改性硅胶的结构及稳定性进行了表征;在此基础上考察了改性硅胶对各类有机废气的吸附性能.结果表明,TEOS成功接枝在了硅胶表面,改性硅胶不仅具备一定的疏水性,而且机械强度增加到原来的66.85%,稳定性也都得到了提高; 550℃空气下焙烧后的改性硅胶仍具有疏水性且吸附容量是焙烧之前的2倍;在高湿度高浓度的废气治理中,TEOS改性硅胶表现出更高的吸附能力和优良的热再生性能.高浓度下改性硅胶的吸附容量是低浓度下的10倍且不受水汽的影响;改性硅胶循环10次的吸附/脱附几乎不变,且在一定条件下,15~30min就达到90%的脱附率.