300MW锅炉低NOx燃烧系统改造效果分析

针对日益严重的环境污染、锅炉热效率低等问题，阐述了燃煤锅炉炉内空间分级燃烧技术、煤粉浓淡高效分离技术改造项目和特点，提出了对燃烧器系统、一次风管道、二次风系统和空预器系统等系统进行具体的低氮改造措施。分析了300 MW燃煤锅炉低氮改造后的热经济性和安全性。经试验验证，1号锅炉低氮改造后，锅炉NOx 排放量大幅减少，排放浓度降到了280 mg／m3。     

循环载荷下煤裂隙演化试验研究

为了研究循环载荷下的煤体裂隙演化特征，在不同应力水平和不同频率条件下分别进行煤样破坏力学及声发射试验。结果表明:应力-应变曲线呈疏-密-疏的变化特征，对应的振铃数柱状图呈U型；上限应力点的应变值、累积能量、撞击计数均随循环次数增加而上升，曲线呈倒S型；煤裂隙演化经历了原始裂隙闭合、新生裂隙稳定发育和裂纹贯穿破坏等3个不同阶段；循环载荷的应力水平和加载频率对煤体疲劳寿命的影响具有差异性，对煤体裂隙演化和破坏模式均有明显影响。     

山西省绿色转型发展现状评价及路径研究

从经济、社会、资源、环境保护4个层面构建了切合山西省实际情况的绿色转型发展指标体系,采用熵权法及聚类分析方法对山西省的绿色转型发展现状进行了评价,根据评价结果,结合政策背景,提出了山西省实现绿色转型发展的路径,以实现山西省均衡快速的绿色转型发展。     

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.     

杭州市环境空气中黑碳质量浓度变化特征

采用2013年环境空气自动监测数据,分析杭州市空气中黑碳质量浓度的变化规律,并对变化特征的产生原因进行探讨。结果表明:黑碳测定年均值为4.10μg/m3,日变化有明显双峰结构,峰值出现在早7时和晚8时左右;从季节看,黑碳质量浓度冬季高(5.20μg/m3)、夏季低(3.00μg/m3);黑碳质量浓度与NO2、CO、PM10、PM2.5显著相关,与O3、风速、气温呈负相关,降水对黑碳的清除作用明显。     

The accounting method and application of CO2 emissions responsibility by the electricity sector at the provincial level in China

When accounting the CO₂ emissions responsibility of the electricity sector at the provincial level in China,it is of great significance to consider the scope of both producers’ and the consumers’ responsibility,since this will promote fairness in defining emission responsibility and enhance cooperation in emission reduction among provinces.This paper proposes a new method for calculating carbon emissions from the power sector at the provincial level based on the shared responsibility principle and taking into account interregional power exchange.This method can not only be used to account the emission responsibility shared by both the electricity production side and the consumption side,but it is also applicable for calculating the corresponding emission responsibility undertaken by those provinces with net electricity outflow and inflow.This method has been used to account for the carbon emissions responsibilities of the power sector at the provincial level in China since 2011.The empirical results indicate that compared with the production-based accounting method,the carbon emissions of major power-generation provinces in China calculated by the shared responsibility accounting method are reduced by at least 10%,but those of other power-consumption provinces are increased by 20% or more.Secondly,based on the principle of shared responsibility accounting,Inner Mongolia has the highest carbon emissions from the power sector while Hainan has the lowest.Thirdly,four provinces,including Inner Mongolia,Shanxi,Hubei and Anhui,have the highest carbon emissions from net electricity outflow- 14 million t in 2011,accounting for 74.42% of total carbon emissions from net electricity outflow in China.Six provinces,including Hebei,Beijing,Guangdong,Liaoning,Shandong,and Jiangsu,have the highest carbon emissions from net electricity inflow- 11 million t in 2011,accounting for 71.44% of total carbon emissions from net electricity inflow in China.Lastly,this paper has estimated the emission factors of electricity consumption at the provincial level,which can avoid repeated calculations when accounting the emission responsibility of power consumption terminals（e.g.construction,automobile manufacturing and other industries）.In addition,these emission factors can also be used to account the emission responsibilities of provincial power grids.     

活性炭吸附和两级Fenton氧化组合工艺处理高盐对氨基苯酚生产废水

采用活性炭吸附和两级Fenton氧化组合工艺对高盐度对氨基苯酚生产废水进行了处理实验研究。结果表明,p H值对活性炭去除有机物的影响较小。当活性炭投加量为4 g/L时,TOC去除率61%。分级加药可以有效提高Fenton氧化对有机物的去除效率。在温度为25℃、p H为3、30%H2O2投加量为3%(V/V)、Fe2+/H2O2摩尔比为0.05时,两级Fenton氧化处理后,出水TOC降至150 mg/L以下。此外,Fenton氧化后形成氢氧化铁污泥颗粒粒径为4.5μm,经过聚丙烯酰胺(PAM)絮凝之后,污泥的粒径明显增加,过滤特性改善。PAM絮凝效果依赖于溶液的p H值,当p H超过10后会失去作用,故在使用过程中需要严格控制溶液的p H值。     

石墨相氮化碳协同UV-H_2O_2光催化降解亚甲基蓝

以三聚氰胺为前驱体,经热解—回流法制备了石墨相氮化碳(g-C3N4),采用XRD、FTIR、SEM、EDS、PL等技术对g-C_3N_4进行了表征。研究了g-C_3N_4在UV-H_2O_2体系中对废水中亚甲基蓝(MB)的光降解效果。实验结果表明,UV+g-C_3N_4催化剂+H_2O_2体系能协同降解MB,在初始MB质量浓度为20 mg/L、初始废水p H为5、废水体积为250 mL、g-C_3N_4加入量为0.10 g、H_2O_2浓度为0.4 mmol/L、反应温度为25℃的优化工艺条件下,紫外光照射70 min时MB脱色率达98.32%。g-C_3N_4催化剂具有较好的重复使用性能,使用5次后MB脱色率仍保持在95.10%。     

Images of war: using satellite images for human rights monitoring in Turkish Kurdistan

In areas of war and armed conflict it is difficult to get trustworthy and coherent information. Civil society and human rights groups often face problems of dealing with fragmented witness reports, disinformation of war propaganda, and difficult direct access to these areas. Turkish Kurdistan was used as a case study of armed conflict to evaluate the potential use of satellite images for verification of witness reports collected by human rights groups. The Turkish army was reported to be burning forests, fields and villages as a strategy in the conflict against guerrilla uprising. This paper concludes that satellite images are useful to validate witness reports of forest fires. Even though the use of this technology for human rights groups will depend on some feasibility factors such as prices, access and expertise, the images proved to be key for analysis of spatial aspects of conflict and valuable for reconstructing a more trustworthy picture.     

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