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%。     

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     

Soil and vegetation carbon stocks in Brazilian Western Amazonia: relationships and ecological implications for natural landscapes

The relationships between soils attributes, soil carbon stocks and vegetation carbon stocks are poorly know in Amazonia, even at regional scale. In this paper, we used the large and reliable soil database from Western Amazonia obtained from the RADAMBRASIL project and recent estimates of vegetation biomass to investigate some environmental relationships, quantifying C stocks of intact ecosystem in Western Amazonia. The results allowed separating the western Amazonia into 6 sectors, called pedo-zones: Roraima, Rio Negro Basin, Tertiary Plateaux of the Amazon, Javari-Juruá-Purus lowland, Acre Basin and Rondonia uplands. The highest C stock for the whole soil is observed in the Acre and in the Rio Negro sectors. In the former, this is due to the high nutrient status and high clay activity, whereas in the latter, it is attributed to a downward carbon movement attributed to widespread podzolization and arenization, forming spodic horizons. The youthful nature of shallow soils of the Javari-Juruá-Purus lowlands, associated with high Al, results in a high phytomass C/soil C ratio. A similar trend was observed for the shallow soils from the Roraima and Rondonia highlands. A consistent east–west decline in biomass carbon in the Rio Negro Basin sector is associated with increasing rainfall and higher sand amounts. It is related to lesser C protection and greater C loss of sandy soils, subjected to active chemical leaching and widespread podzolization. Also, these soils possess lower cation exchangeable capacity and lower water retention capacity. Zones where deeply weathered Latosols dominate have a overall pattern of high C sequestration, and greater than the shallower soils from the upper Amazon, west of Madeira and Negro rivers. This was attributed to deeper incorporation of carbon in these clayey and highly pedo-bioturbated soils. The results highlight the urgent need for refining soil data at an appropriate scale for C stocks calculations purposes in Amazonia. There is a risk of misinterpreting C stocks in Amazonia when such great pedological variability is not taken into account.     

期权理论在排污权初始分配中的应用

排污权交易是当前总量控制目标下最具潜力的环境政策,它兼有环境质量保障和成本效率优化的特点.在对国内外排污权交易和初始分配充分考察的基础上,提出了在排污权初次分配中引入期权机制的尝试,并对这种方法的理论基础作了分析和讨论.     

西藏农村能源消费及环境影响研究

西藏农村人口现有220多万，占全区总人口80％以上，农村经济落后，城乡差距很大。西藏农村能源资源主要有水力、地热、太阳能、风力、林木和畜粪等，煤炭、石油、天然气等高热值的优质能源很少。在这种经济发展水平及能源资源基础条件下，农村能源消费中高热值的现代能源比重很低，主要以生物质能如薪柴、牛粪、草皮等为主。这种低水平的能源消费结构已经对西藏脆弱的生态环境造成了巨大的破坏，西藏未来的能源发展战略迫切需要改变农村目前的消费结构，应发展太阳能、风能、农村小水电及输入高热值的化石能源替代目前生物质能的消费，减少因能源消费对西藏生态环境的破坏。     

Magnetic mapping of fly-ash pollution and heavy metals from soil samples around a point source in a dry tropical environment

The Singrauli region in the southeastern part of Uttar Pradesh, India is one of the most polluted industrial sites of Asia. It encompasses 11 open cast coalmines and six thermal power stations that generate about 7,500 MW (about 10% of India’s installed generation capacity) electricity. Thermal power plants represent the main source of pollution in this region, emitting six million tonnes of fly-ash per annum. Fly-ash is deposited on soils over a large area surrounding thermal power plants. Fly-ashes have high surface concentrations of several toxic elements (heavy metals) and high atmospheric mobility. Fly ash is produced through high-temperature combustion of fossil fuel rich in ferromagnetic minerals. These contaminants can be identified using rock-magnetic methods. Magnetic susceptibility is directly linked to the concentration of ferromagnetic minerals, primarily high values of magnetite. In this study, magnetic susceptibility of top soil samples collected from surrounding areas of a bituminous-coal-fired power plant were measured to identify areas of high emission levels and to chart the spatial distribution of airborne solid particles. Sites close to the power plant have shown higher values of susceptibility that decreases with increasing distance from the source. A significant correlation between magnetic susceptibility and heavy metal content in soils is found. A comparison of the spatial distribution of magnetic susceptibility with heavy-metal concentrations in soil samples suggests that magnetic measurements can be used as a rapid and inexpensive method for proxy mapping of air borne pollution due to industrial activity.     

中国经济的“阿基米德支点”

资源是经济发展的“阿基米德支点”：世界十大经济国每年能源的生产占全球的６２．１％，消费为７１．０％。重要矿产资源的生产多排在世界前１０名生产国之，外面是消费则多排在１０名之内，且对这些矿产资源的消费量多在９５％以上。     

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%.     

北京市农业机械排放因子与排放清单

利用车载排放测试技术对典型的联合收割机、拖拉机、农用运输车和农田建设机械实际工况下的尾气进行测试,建立了实际工况下农业机械的排放因子和2017年北京市农用机械排放清单.结果表明,不同的工作状态对农业机械尾气排放有较大的影响,怠速和行走时CO、NO_x、HC和PM排放趋于平稳;而切地和翻地模式下的波动较为明显.根据各类机械的分类和排放标准对排放因子进行细化,建立了较为完整的实际工况下的排放因子.根据农业机械排放因子和燃油消耗量计算出2017年北京市CO、NO_x、HC和PM的排放量分别是2 566.60、 1 239.29、 563.08和538.32 t.拖拉机、运输机械和联合收割机的污染物总量占CO、NO_x、HC和PM这4种污染物总量的98%、 95%、 95%和98%.因此,农用拖拉机、运输机械和联合收割机在农业机械污染减排中应作为重点控制对象.     

岗南水库沉积物间隙水有色溶解有机物的时空分布特征及差异分析

有色可溶性有机物(CDOM)作为溶解性有机物的重要组分,影响着水体中污染物质的形态特征和迁移转化过程.本研究运用紫外-可见光谱技术(UV-vis)以及三维荧光光谱(EEMs)技术结合平行因子分析法(PARAFAC),对岗南水库自入库河口到坝前主库区四季演变过程中沉积物间隙水CDOM的分布、光谱特征以及来源进行解析.结果表明,岗南水库沉积物间隙水CDOM的相对浓度a_(254)、a_(260)、a_(280)和a_(355)存在显著的季节差异,并且相对浓度大小为夏季春季秋季冬季;沉积物间隙水CDOM的E2/E3、E3/E4、E4/E6以及S_R存在显著的季节差异,呈现冬季高夏季低的特征;秋冬季的E2/E3以及E3/E4明显高于春夏季,并且秋冬季的E3/E4大部分均大于3.5,表明秋冬季沉积物间隙水CDOM具有更小的分子量和更低的腐殖化程度;三维荧光光谱通过PARAFAC解析出3种组分,分别为类酪氨酸(C1)、短波类富里酸(C2)和降解的腐殖类物质(C3),并且3种荧光组分间具有显著的正相关性(P0.001);岗南水库沉积物间隙水的CDOM总荧光强度和各荧光组分荧光强度呈现显著的季节差异,总荧光强度以及各组分的荧光强度呈现春季的最高、秋冬季次之、夏季最低的分布特征;秋冬季各个荧光组分占比不存在显著差异,春夏季各个荧光组分占比不存在显著差异,秋冬季与春夏季各个荧光组分占比存在显著差异;秋冬季沉积物间隙水CDOM生物源指数(BIX)和荧光指数(FI)均高于春夏季,表明秋冬季CDOM的自生源强于春夏季,与腐殖程度指标(HIX)的结果相吻合;PCA结合Adonis分析显示沉积物间隙水CDOM的光谱特征呈现显著的季节差异(P0.001);并且组分C1、C2、C3以及水质参数[氨氮、硝氮、亚硝氮、溶解性总氮以及溶解性总磷]均有很好的线性回归方程.综上,通过对岗南水库沉积物间隙水CDOM光谱特征进行研究,可以为分析岗南水库有机物污染特征和水质管理提供技术支持.