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     

长江流域的昆虫病毒资源及其开发利用

在长江流域已发现约１３０种昆虫病毒，其中多数属杆状病毒科。昆虫病毒作为杀虫剂在本地区广泛应用，防治棉花、森林、茶树、蔬菜和牧草上的害虫，克服了化学农药的一些缺点，取得了良好的生态效益和经济效益。近年来还进行了杆状病毒表达载体的研究，该系统的研制已用于高水平表达具有生物活性的外源基因产物，获得医药产品，或者组建更有效的基因工程病毒杀虫剂。     

Biological productivity of bogs in the middle taiga subzone of Western Siberia

New experimental data on biological productivity of plant communities in oligotrophic and mesotrophic bogs of the middle taiga subzone over the past five years are presented. The relationship between net primary production and the stock of live phytomass is estimated. The stock of necromass in oligotrophic bog ecosystems increases from west to east, while the stock of live phytomass and net primary production decrease.     

不同低碳氮比废水中好氧颗粒污泥的长期运行稳定性

为了研究好氧颗粒污泥系统处理低碳氮比废水的长期运行稳定性,采用低碳氮比（C/N）条件下逐步增加碳氮负荷的进水方法,分别在反应器A和B中接种好氧颗粒污泥,考察其长期运行过程中的理化性质、处理性能及应对冲击负荷的稳定性.其中A反应器的碳氮比一直维持在2,而B则由4逐步降至2.结果表明,在4℃存储30d的好氧颗粒污泥,经过25d的培养,其活性基本恢复,A、B反应器化学需氧量（COD）和氨氮（NH₄⁺-N）的去除效率均达到90%以上.在其后的稳定阶段,B反应器COD和NH₄⁺-N去除率达到90%以上,实现了完全硝化;而A反应器COD去除率仅80%左右,虽然NH₄⁺-N去除率最终也达到90%以上,但仅实现短程硝化.在冲击负荷阶段,A和B反应器COD去除率仍维持在80%以上,但是NH₄⁺-N去除受到很大冲击.A反应器NH₄⁺-N去除效率恶化,B反应器仅实现了部分硝化.整个运行过程,好氧颗粒污泥的物理性质受到的影响不大,A和B反应器的污泥容积指数（SVI₃₀）分别维持在60 mL ·g^-1和75 mL ·g^-1左右,混合液悬浮固体（MLSS）在5g ·L^-1和3.7g ·L^-1左右.颗粒污泥微生物群落分析表明,B反应器相对于A反应器丰富度和多样性更高.同时B反应器具有更高丰度的Zoogloea属,在颗粒中能产生更多的胞外蛋白促使颗粒结构更稳定,保证系统的长期稳定运行.以上结果表明,与C/N为2的好氧颗粒污泥系统相比,C/N为4的系统脱碳硝化效果好,抗冲击负荷能力强,更有利于颗粒污泥的长期稳定运行.     

焦化废水处理过程中固相物质的形成及处置方法评价

焦化废水处理过程中产生的焦油、污泥和结晶杂盐等固相物质,既有资源属性,又有污染特性,但目前缺乏基于能源、经济及环境影响方面的评估.本研究阐述了3类固相物质的形成机制,建立了质量当量计算及处置方法评价模型.以宝武集团韶关钢铁股份有限公司焦化厂（二期）焦化废水处理工程的A/O/H/O（厌氧/好氧/水解/好氧）流化床工艺作为考察对象,利用工程运行参数和水质统计数据进行固相物质的产量推算,结果发现,焦油、物化污泥、生物污泥（含水率为80%）和工业杂盐的产率分别为0.186、5.80、4.24和1.97 kg·m^-3.通过处置方法评价模型明确了焦油焚烧、污泥热解、结晶杂盐分盐提纯后工业应用是最佳处置方案,在60 m³·h^-1废水处理规模的固相物质处置过程中,每年约产生1177 MWh的能源,获得135.0万元的经济效益,排放627.0 t CO₂,表明能源回收、经济效益和环境影响的协同存在.     

水库沉积物贫营养型好氧反硝化菌(Pseudomonas sp.)分离及其对微污染水体脱氮效率分析

为探究深水水库沉积物微生物功能特征及利用价值,于2019年在实验室对小湾水库表层沉积物微生物进行了驯化分离,并分析了其中一株细菌的脱氮效率.结果表明,分离出的细菌XW731经鉴定属于假单胞菌属（Pseudomonas sp.）,是一种贫营养型好氧反硝化菌;在分别以NH₄⁺-N、NO₃^--N和NO₂^--N为唯一氮源时,该菌对NH₄⁺-N、NO₃^--N和NO₂^--N去除率分别为33.6%、68.5%和9.1%;以NH₄⁺-N和NO₃^--N为氮源时,对NH₄⁺-N和NO₃^--N去除率分别为66.4%、89.6%,同步硝化反硝化能力更强.将该菌投加到两种城市微污染水体后测试表明,该菌对城市河道水体的NH₄⁺-N和NO₃^--N去除率分别为38.3%和42.4%,对城市降雨水体的NH₄⁺-N和NO₃^--N去除率分别为22.2%和7.7%.     

水源水库贫营养好氧反硝化菌群脱氮特性研究

为削减微污染水库中氮素的浓度,通过对西安市李家河水库沉积物进行定向富集驯化,筛选出以Pseudomonas菌为主、具有高效好氧反硝化特性的混合菌群-A1.摇床实验表明,贫营养好氧反硝化菌群A1在15h时硝酸盐氮去除率可达93.39%,硝酸盐氮平均去除速率为0.2073mg/（L·h）;总氮去除率为52.11%,总氮平均去除速率为0.1153mg/（L·h）,无亚硝酸盐积累.氮平衡分析表明,约45%的初始氮被去除转化为气体产物.响应面法（RSM）结果表明,C/N比9.96,温度22.67℃,pH8.01,转速91r/min,溶解氧8.55mg/L是去除总氮（TN）的最优条件.     

滤纸法测定悬浮物的干扰及其消除

提出了滤纸法测定悬浮物时，水样的酸碱度，取样量的多少对悬浮物测定有直接的影响。通过实验验证，对于偏酸，偏碱的水样用酸碱中和后再过滤即可消除影响，取样量应根据悬浮物的不同而定。     

Application of the benthic index of biotic integrity to environmental monitoring in Chesapeake Bay

The Chesapeake Bay benthic index of biotic integrity (B-IBI) was developed to assess benthic community health and environmental quality in Chesapeake Bay. The B-IBI provides Chesapeake Bay monitoring programs with a uniform tool with which to characterize bay-wide benthic community condition and assess the health of the Bay. A probability-based design permits unbiased annual estimates of areal degradation within the Chesapeake Bay and its tributaries with quantifiable precision. However, of greatest interest to managers is the identification of problem areas most in need of restoration. Here we apply the B-IBI to benthic data collected in the Bay since 1994 to assess benthic community degradation by Chesapeake Bay Program segment and water depth. We used a new B-IBI classification system that improves the reliability of the estimates of degradation. Estimates were produced for 67 Chesapeake Bay Program segments. Greatest degradation was found in areas that are known to experience hypoxia or show toxic contamination, such as the mesohaline portion of the Potomac River, the Patapsco River, and the Maryland mainstem. Logistic regression models revealed increased probability of degraded benthos with depth for the lower Potomac River, Patapsco River, Nanticoke River, lower York River, and the Maryland mainstem. Our assessment of degradation by segment and water depth provided greater resolution of relative condition than previously available, and helped define the extent of degradation in Chesapeake Bay.