The behaviour of suppliers and consumers in mandated markets: the introduction of the ethanol–petrol blend E10 in Germany

In December 2010, the German government increased the maximum ethanol content that can be blended with petrol from 5% to 10%, which facilitated the introduction of the ethanol–petrol blend E10. The revised ethanol–petrol blend was introduced with ambitions towards decarbonizing the transport sector as well as to support energy security and rural development. While usually supportive of actions aimed to combat climate change, the great majority of German motorists have refused to buy E10. The lacking demand for E10 is the empirical phenomenon addressed by this study. How did the fuel suppliers comply with the policy provisions? Which actors made attempts to influence the motorists’ demand for the new ethanol–petrol blend? Which actor was assigned the responsibility for the problems that occurred upon the rollout of the new fuel type? These research questions guide this study, which concentrates on the behaviour of transport fuel suppliers and consumers in mandated markets, that is, markets created by policy provisions.     

不同磷质量浓度体系中pH变化对铜绿微囊藻和四尾栅藻竞争的影响

铜绿微囊藻和四尾栅藻分别是太湖中最为常见的蓝藻和绿藻.微囊藻在湖泊中形成优势是微囊藻水华发生的重要条件.在模拟太湖水的竞争实验(ρ(磷)分别为0.012,0.112,0.412和1.612 mg/L)中,四尾栅藻均形成优势,而且在稳定期时pH达到10以上.但用0.04 mol/L HCl将pH都降到5.8后,2种藻的增殖都出现明显的变化,在ρ(磷)低于0.412 mg/L时,四尾栅藻优势变得更加明显;而在ρ(磷)为1.612 mg/L时,铜绿微囊藻则形成优势.说明pH对蓝藻和绿藻竞争的影响在不同ρ(磷)的水体中是不同的.      

Characteristics of PM10, PM2.5, CO2 and CO monitored in interiors and platforms of subway train in Seoul, Korea

This study was performed to investigate the concentration of PM₁₀ and PM_2.5 inside trains and platforms on subway lines 1, 2, 4 and 5 in Seoul, KOREA. PM₁₀, PM_2.5, carbon dioxide (CO₂) and carbon monoxide (CO) were monitored using real-time monitoring instruments in the afternoons (between 13:00 and 16:00). The concentrations of PM₁₀ and PM_2.5 inside trains were significantly higher than those measured on platforms and in ambient air reported by the Korea Ministry of Environment (Korea MOE). This study found that PM₁₀ levels inside subway lines 1, 2 and 4 exceeded the Korea indoor air quality (Korea IAQ) standard of 150 μg/m³. The average percentage that exceeded the PM₁₀ standard was 83.3% on line 1, 37.9% on line 2 and 63.1% on line 4, respectively. PM_2.5 concentration ranged from 77.7 μg/m³ to 158.2 μg/m³, which were found to be much higher than the ambient air PM_2.5 standard promulgated by United States Environmental Protection Agency (US-EPA) (24 h arithmetic mean: 65 μg/m³). The reason for interior PM₁₀ and PM_2.5 being higher than those on platforms is due to subway trains in Korea not having mechanical ventilation systems to supply fresh air inside the train. This assumption was supported by the CO₂ concentration results monitored in tube of subway that ranged from 1153 ppm to 3377 ppm. The percentage of PM_2.5 in PM₁₀ was 86.2% on platforms, 81.7% inside trains, 80.2% underground and 90.2% at ground track. These results indicated that fine particles (PM_2.5) accounted for most of PM₁₀ and polluted subway air. GLM statistical analysis indicated that two factors related to monitoring locations (underground and ground or inside trains and on platforms) significantly influence PM₁₀ (p < 0.001, R² = 0.230) and PM_2.5 concentrations (p < 0.001, R² = 0.172). Correlation analysis indicated that PM₁₀, PM_2.5, CO₂ and CO were significantly correlated at p < 0.01 although correlation coefficients were different. The highest coefficient was 0.884 for the relationship between PM₁₀ and PM_2.5.     

龙岩市PMl0污染受山谷风出现频率的影响分析

利用福建省龙岩市2006—2009年PM10的监测数据和龙岩市地区山谷风各风向的统计数据,进行了单因素方差分析、一元线性相关分析等统计分析,结果表明龙岩市区PM10浓度与N风向、NW风向、NNW风向的出现频率之间有较密切的关系。这些风向的出现会导致污染物堆积在谷底范围之内,阻碍了PM10污染物向谷外的扩散,使得处于谷底的龙岩市大气中的PMl0浓度不断增加。     

PM10中重金属的分布及其在模拟酸雨中的释放

运用扫描电镜-X射线能谱分析方法(SEM-EDS)和电感耦合等离子体-原子发射光谱法(ICP-AES),分析和测定了佛山市可吸入颗粒物(PM₁₀)及其中重金属的赋存状态和质量分布.同时研究了模拟酸雨淋溶条件下PM₁₀中重金属Cu、Pb、Zn和Cd的释放过程.结果表明,颗粒物在大气中存在的形态各异,主要以簇状集合体形式存在.PM₁₀日平均浓度为0.19 mg/m³,与国家二级标准(0.15 mg/m³)相比,超标率为79%.PM₁₀中含有一定量的Zn、Pb、Cu和Cd,其中Zn、Pb的含量要高于Cd和Cu.模拟酸雨淋溶实验显示,PM₁₀中Cu、Pb、Zn、Cd均有不同程度的释放,Cd和Zn的释放率明显高于Cu和Pb,且释放速率较快;pH值是影响4种重金属释放的主要因素,随模拟淋溶液pH值降低,重金属的释放强度显著提高.     

Identification of PM sources by principal component analysis (PCA) coupled with wind direction data

The effectiveness of combining principal component analysis (PCA) with multi-linear regression (MLRA) and wind direction data was demonstrated in this study. PM data from three grain-size fractions from a highly industrialised area in Northern Spain were analysed. Seven independent PM sources were identified by PCA: steel (Pb, Zn, Cd, Mn) and pigment (Cr, Mo, Ni) manufacture, road dust (Fe, Ba, Cd), traffic exhaust (P, OC + EC), regional-scale transport (, , V), crustal contributions (Al2O3, Sr, K) and sea spray (Na, Cl). The spatial distribution of the sources was obtained by coupling PCA with wind direction data, which helped identify regional drainage flows as the main source of crustal material. The same analysis showed that the contribution of motorway traffic to PM10 levels is 4-5 microg m-3 higher than that of local traffic. The coupling of PCA-MLRA with wind direction data proved thus to be useful in extracting further information on source contributions and locations. Correct identification and characterisation of PM sources is essential for the design and application of effective abatement strategies.     

Spatiotemporal Features of Severe Air Pollution in Northern Taiwan (8 pp)

Background, Aims and Scope This research attempted to identify the dominant factors simultaneously affecting the airborne concentrations of five air pollutants with principal component analysis and to determine the meteorologically related parameters that cause severe air-pollution events. According to the definition of subPSI and PSI values through the U.S. EPA, the historical raw data of five criteria air pollutants, SO2, CO, O3, PM10 and NO2, were calculated as daily subPSI values. In addition to the airborne concentrations, this study simultaneous collected the surface meteorological parameters of the Taipei meteorological station, established by the Central Weather Bureau. Methods Principal component analysis was conducted to screen severe air pollution scenarios for five air pollutants: SO2, CO, O3, PM10 and NO2. The concentrations of various air pollutants measured at 17 air-quality stations in northern Taiwan from 1995 to 2001 were transformed into daily subPSI values. The correlation analysis of the five air pollutants and four meteorological parameters (wind speed, temperature, mixing height and ventilation rate) were included in this research. After screening severe air pollution scenarios, this study recognized the synoptic patterns easily causing the severe air-pollution events. Results and Discussion Analytical results showed that the eigenvalues of the first two principal components for SO2, CO, O3, PM10 and NO2 were greater than 1. The first component of five air pollutants explained 64, 64, 67, 76 and 63% of subPSI variance for SO2, CO, O3, PM10 and NO2, respectively. Only the correlation coefficient of NO2 and CO had statistically significant positive values (0.82); other pollutant pairs presented medium (0.4 to 0.7) or low (0 to 0.4) positive values. The correlation coefficients for air pollutants and three meteorological parameters (wind speed, mixing height and ventilation index) were medium or low negative values. In northern Taiwan, spring was most likely induced high concentrations and the component scores of the first component for SO2, CO, PM10 and NO2; summer was the worst season that caused high O3 episodes. Consequently, the analytical results of factor loadings for the first principal component and emission inventory of various sources revealed that mobile sources were dominant factors affecting ambient air quality in northern Taiwan. Conclusion According to the results of principal component analysis for the five air pollutants, the first two of 17 components were cited as major factors and explained 71% of subPSI variance. Based on the inventory of NOx emissions and the isopleth diagram of factor loading for the first component, mobile sources in the southwest Taipei City accounted for the highest factor loading values and emission inventory values. Synoptic analysis and principal component analysis demonstrated that three types of weather patterns (high-pressure recirculation, prefrontal warm sector and the southwesterly wind system) easily caused the severe air-pollution scenarios. In summary, if severe air-pollution days occurred, the average meteorological parameters experienced adverse conditions for diffusing air pollutants; that is, the average values of wind speed, mixing height and ventilation index were lower than 2.1 ms-1, 360 m and 800 m2s-1, respectively. If one of the three synoptic patterns were to occur in combination with adverse meteorological conditions, severe air-pollution events would be developed. Recommendation and Outlook By utilizing synoptic patterns, this work found three weather systems easily caused severe air-pollution events over northern Taiwan. Analytical results showed, respectively, the wind speed and mixing height were less than 2.1 m/s and 360 m during severe air-pollution events.     

忻州市环境空气PM10中有机碳和元素碳污染特征分析

采集了忻州市4个监测点位采暖季和非采暖季环境空气PM10样品,利用Elementar Analysensysteme GmbH vario EL cube测定有机碳(organic carbon,OC)和元素碳(elemental carbon,EC)的质量浓度,通过OC和EC的时空分布、比值以及相关性分析揭示忻州市的碳组分污染特征.结果表明,忻州市PM10中OC和EC的平均质量浓度分别为(18.5±4.5)μg·m-3和(16.1±4.3)μg·m-3,采暖季和非采暖季TCA占PM10的比例分别为70.7%和43.8%;4个监测点位采暖季OC的质量浓度均高于非采暖季,XT、DC和KQ监测点采暖季EC的质量浓度高于非采暖季,SQ监测点则相反,采暖季燃煤是OC和EC的主要来源;监测点XT的OC质量浓度最高,为24.1μg·m-3,DC的EC质量浓度最高,为22.0μg·m-3,SQ的OC和EC质量浓度最低,分别为17.2μg·m-3和14.5μg·m-3,区域性污染特征存在差异;OC/EC均值小于2,一次污染严重;非采暖季OC与EC浓度相关性较好(R2=0.55),二者排放源单一,主要来源为机动车尾气排放,采暖季相关性不显著(R2=0.13),二者排放源复杂.忻州市主要通过控制燃煤、机动车尾气、生物质燃烧、工业源等的一次排放来减轻碳组分污染,进而提高环境空气质量.     

珍珠岩对蚯蚓同步处理污泥-狐尾藻的研究

本研究利用太平二号蚯蚓构建生物反应器,以污水处理厂脱水污泥和粉绿狐尾藻作为研究对象,探究添加不同比例的珍珠岩对蚯蚓动物反应器处理混合物的减量化、无害化和资源化效果.结果表明,添加珍珠岩能够显著提高蚯蚓动物反应器同步处理污泥-狐尾藻的效率,经反应器处理后,混合物减量化效果明显,处理后产物的pH、有机质、碱解氮和重金属含量(Cu、Pb、Cr)均表现为明显下降,电导率(EC)和速效磷显著上升.经反应器处理后,产物品质符合在pH6.5的中性和碱性土壤上的施用标准.结果显示,当珍珠岩添加比例为4%时,对动物反应器的实用性和经济性效果最佳.     

重庆地区区域灰霾观测初步研究

2012年灰霾试点监测结果表明,灰霾日天数有明显减少。细颗粒物(PM2.5)浓度限值增加,使仅因重庆城市地域和气候原因造成部分相对湿度较低,而实际环境空气质量较好的灰霾日排除在外,更客观评价灰霾日发生规律。结合气象条件和颗粒物质量浓度对比情况表明,局域气候条件的变化将促使PM2.5和PM1吸湿增长明显,一定程度上促使粗颗粒物PM10质量浓度增加,局域污染物传输扩散不利,能见度减低,灰霾现象频增。