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     

Fluctuations of Population Size and Structure in the Northern Mole Vole: Preliminary Analysis

Long-term stationary studies on the ecology of the northern mole vole (Ellobius talpinus Pall.), performed by the mark–recapture method from 1985 to 1997, have provided original data on population dynamics and structure. The analysis shows that, to reveal cyclic fluctuations of population size in this species, the period of three years should be taken as a unit of time for estimating the duration of one phase. The 12-year population cycle in E. talpinus has four distinct phases: an increase, a peak, a decline, and a minimum. At each phase, the population is characterized by certain features of family structure, age composition, birth and death rates, and the composition of migrants.     

区域水战略方案选优的动态组合评价模型研究

水安全危机是人类进入新世纪以来在生存及发展方面所面临的最严重挑战之一。研究科学合理的水安全战略成为区域可持续发展的重大课题。针对区域水战略问题涉及众多因素且各因素之间动态关联的特点，提出了基于水战略方案优选的兼容度极大化动态组合评价模型（CMM—DCEM），并将其成功地应用于我国广东省北江下游及其三角洲地区水安全战略方案优选评价。评价结果及模型基于不确定性的敏感性分析结果证明：CMM—DCEM实现了主、客观赋权方法以及单一评价模型的融合，使用实码加速遗传算法求解目标函数，克服了传统的组合评价方法计算繁琐的不足，评价过程更加科学合理。     

京津冀西北典型流域地下水化学特征及补给源分析

为揭示京津冀西北典型流域地下水循环特征,运用环境同位素和水化学技术等方法分析张家口市不同流域水体氢氧同位素特征、水化学特征及时空变化特征、地表地下水转化关系。结果表明：地表水化学类型主要为HCO₃-Mg·Na和HCO₃·Cl-Na型;地下水化学类型不同时期表现出不同的类型,水化学类型更为多样,主要以HCO₃-Mg·Na型、HCO₃·Cl-Na型、HCO₃·Cl-Na·Mg为主。地表河水和地下水中离子均主要来源于岩石风化作用;张北和桑干河流域地下水中离子偏向于蒸发浓缩作用控制。张家口市各流域地表地下水δ¹⁸O、δD组成较为接近,表明了当地地表水和地下水均受到大气降水的补给。大气降水和地表河水对地下水的补给比例均值分别为37.74%和62.26%,以地表河水的补给为主要方式。     

双酚F和双酚S联合暴露下的斑马鱼富集及神经毒性

为探究双酚F（BPF）和双酚S（BPS）联合暴露下斑马鱼富集及神经毒性,进行为期14d的1,10,100,1000 μg/L BPF和BPS的单一或联合暴露.结果表明,BPF和BPS在斑马鱼组织内的富集水平与暴露浓度和暴露时间呈正相关,BPF富集能力高于BPS,BPF和BPS联合暴露降低了斑马鱼对BPS的富集水平,但对BPF富集水平的影响较小.脑组织中的富集水平低于肠道但远高于肌肉.以脑为目标组织进行了毒性研究,结果表明,BPF诱导的丙二醛（MDA）、8-羟化脱氧鸟苷（8-OHdG）、白细胞介素1β（1L-1β）、肿瘤坏死因子α（TNF-α）等氧化损伤和炎症指标水平高于BPS,且联合暴露存在毒性增强效应.但BPS对皮质醇（COR）、肾上腺素（EPI）和乙酰胆碱酶（AChE）等神经毒性标志物和Syn2a、MBP、Gfap、MAP2、NSE2和S-100B等神经功能有关基因的毒性效应影响高于BPF,联合暴露削减了对AChE、COR和EPI等的影响.     

组配改良剂联合硅肥对Cd污染稻田的修复效果

选取湖南省浏阳市某Cd污染稻田进行田间试验,研究组配改良剂石灰石+海泡石（LS）、基施硅肥及叶面喷施硅肥对Cd污染稻田修复效果,结果表明：（1）基施硅肥90kg/hm²和叶面喷施硅肥（0.2,0.4g/L）对土壤pH值无明显影响,添加LS（2250,4500kg/hm²）的各处理均显著提高土壤pH值（P < 0.05）.（2）基施硅肥90kg/hm²分别降低土壤交换态、毒性特征浸出（TCLP）提取态Cd含量20.0%和18.5%,叶面喷施硅肥对土壤Cd两种提取态含量无明显影响,添加LS的各处理（2250,4500kg/hm²）分别使土壤交换态、TCLP提取态Cd含量降低25.8%~49.9%、26.4%~44.5%.（3）3种单一技术措施均能明显降低水稻各部位Cd含量,但降低糙米中Cd含量的效果低于3种技术措施的组合处理;“组配改良剂LS+基施硅肥+叶面喷施硅肥”各处理（JL1F1、JL1F2、JL2F1、JL2F2）使水稻糙米中Cd含量降低25.6%~70.5%.（4）“组配改良剂LS+基施硅肥+叶面喷施硅肥”的组合技术处理能显著降低土壤中Cd的有效性,显著降低水稻各部位中Cd含量,其中JL2F2处理效果最佳,能使对照糙米Cd含量从0.66mg/kg降低到0.19mg/kg,实现中重度Cd污染稻田的水稻安全生产.     

大兴安岭5种乔木树种燃烧释放PM2.5中水溶性元素特性

采用自主设计的生物质燃烧实验装置,在不同燃烧状态（明燃、阴燃）下,对大兴安岭林区5种典型乔木树种的不同部位（枝、叶、皮）燃烧释放PM_2.5中的水溶性元素特性进行研究.结果显示,不同树种间PM_2.5的排放因子差异显著,排放范围为（2.408±0.854）~（9.227±1.172）g/kg.5种乔木树种燃烧释放PM_2.5中主要检测到Mg、Ca、K等16 种元素,其中Ca、K、Zn、Mg 4种元素的排放因子明显大于其它元素.不同树种间元素排放因子差异较大,针叶树的排放因子一般高于阔叶树.除Cd元素外,不同器官间排放的元素总量无明显差异.不同树种不同器官燃烧释放PM_2.5中水溶性元素的占比顺序较为一致,其中Ca、K、Zn和Mg 4种元素的排放因子在枝、叶、皮中均较高.此外,燃烧状态对元素排放特征影响较大,Li、Mg、Ca等7种元素的排放因子均表现为明燃显著高于阴燃.     

联合改良剂对桉树吸收重金属的作用——以矿区土壤中Cd、Zn和Cu为例

通过5种矿区土壤的盆栽试验,研究了联合改良剂对桉树部分生理指标、根中Cd、Zn和Cu的含量、以及土壤中Cd、Zn和Cu的BCR提取形态的影响,探讨了其对矿区土壤还林的作用.结果表明,与对照相比,施用改良剂后桉树的生物量和叶绿素含量的增幅分别为-7.6%~158.8%和-0.7%~23.1%,丙二醛含量的降幅为2.6%~37.9%,其中部分处理的生物量和丙二醛含量的变化达到显著水平（P<0.05）;土壤中有效态Cd、Zn和Cu的含量分别下降12.5%~63.8%、1.6%~54.7%和16.2%~57.6%,桉树根中Cd、Zn和Cu的含量分别下降3.1%~56.6%、-1.5%~21.3%和9.3%~50.1%.土壤对桉树根中Cd、Zn和Cu的含量有显著影响（P<0.05）,改良剂的配比或施用量无显著影响（P>0.05）,但在5种矿区土壤中G3降低桉树根中Cu含量的效果优于G1和G2;在重金属含量最高的2种土壤中,G1降低桉树根中Cd和Zn含量的效果优于G2和G3.研究表明施用联合改良剂能降低桉树对重金属的吸收,有利于矿区土壤的还林.     

微塑料对黑麦草吸收和累积水体中环丙沙星的影响

微塑料（microplastics,MPs）和抗生素作为新型环境污染物,引起了国内外学者对其生态风险的关注.以黑麦草（Lolium perenne L.）为供试植物,以聚苯乙烯微塑料和环丙沙星（ciprofloxacin,CIP）为研究对象,探讨微塑料对水培黑麦草吸收和富集抗生素的影响及MPs-CIP复合污染对植物生长的毒性作用.结果表明:黑麦草对单一CIP和MPs-CIP复合污染中的CIP均有吸收去除能力,底物中微塑料的存在会促进黑麦草对低浓度CIP的吸收去除,去除率最高可达100%,但对高浓度（1.0、2.0 mg/L）CIP吸收的影响不显著（P>0.05）.同时,微塑料可促进黑麦草根部积累的CIP向地上部转运,当CIP浓度分别为0.1、2.0 mg/L时,投加微塑料后根部积累的CIP含量与单一CIP处理组相比分别降低了44.0%、21.2%,叶片中CIP的积累量分别增加了2.9、3.0倍.微塑料的加入显著加重了CIP对黑麦草生长和叶绿素含量的抑制作用.与2.0 mg/L CIP处理组相比,50.0 mg/L MPs-2.0 mg/L CIP复合污染处理组对黑麦草根长和鲜质量的抑制率分别增加了53.7%和79.6%,而叶绿素a、b含量则分别降低了38.5%和44.4%.研究显示,水体中微塑料与CIP的共存会影响黑麦草吸收和体内积累CIP,并加重CIP对植物生长的毒性作用.      

土壤调理剂对土壤-水稻系统Cd、Zn迁移累积的影响及健康风险评价

选取湖南省长沙市北山镇某中重度Cd污染稻田,研究了土壤调理剂(石灰石+偏高岭土+钙镁磷肥)对稻田土壤重金属Cd、Zn的钝化效果,以及对水稻各部位累积Cd和Zn的影响,并进行了Cd的健康风险评价.结果表明,使用土壤调理剂提高了稻田土壤p H值.Cd的CaCl_2提取态含量降低了0.9%~24.1%,Zn的CaCl_2提取态含量降低了22.5%~69.6%.土壤调理剂显著降低了水稻糙米中Cd与Zn的含量,与对照相比分别降低了10.8%~47.3%、10.3%~17.5%;土壤调理剂对水稻糙米Cd的吸收和累积的影响要远大于Zn,水稻糙米中的Cd/Zn比随着土壤调理剂施用量的增加而显著降低.研究区大米重金属Cd目标危害系数THQ值大于1,说明当地人群通过食用大米途径摄入重金属Cd存在健康风险.土壤调理剂有效地抑制了水稻植株对土壤中Cd的吸收,并降低了Cd/Zn比,使糙米中的Cd含量显著降低,从而降低了当地人群通过食用大米途径摄入重金属Cd的健康风险.