The study of fine and coarse particles, and metallic elements for the daytime and night-time in a suburban area of central Taiwan, Taichung

Daily average concentrations of fine and coarse particulates, and TSP samples have been measured simultaneously at daytime and night-time periods by using Universal and PS-1 sampler in a suburban area of central Taiwan from June to August 1998. The samples were analyzed by atomic absorption spectrometry to determine the fine and coarse particulate concentrations of metallic elements (Ca, Fe, Mn, Pb, Cu, Zn and Cr). The concentration of PM2.5 and TSP showed a decreased trend for the daytime period. The fine particle concentrations were about two times as that of coarse particulate concentrations. The averaged fine particulate concentrations at daytime are higher than at night-time. Ca and Fe were mostly in the coarse particulate mode. The correlation coefficients were 0.63 and 0.69 for elements Ca and Fe in the coarse particle mode for day and night periods. Pb showed a similar distribution ratio with Mn for the fine to coarse particle ratios at both day and night period. Pb and Mn are highly correlated for the day (R = 0.78) and night period (R = 0.61) at particle size <2.5 microm. Cu and Zn were mainly in fine particles at both day and night period. Fe and Ca consist of the major parts of all the elements. Elemental Mn is the lowest among the rest of the heavy metals.     

Impact of meteorology and energy structure on solvent extractable organic compounds of PM2.5 in Beijing, China

Twenty-eight PM2.5 samples collected in Summer (July 2002) and Winter (November 2002) at two sites in Beijing, China were analyzed using GC/MS to investigate the impact of meteorology and coal burning on the solvent extractable organic compounds (SEOC). The characteristics and abundance of the n-alkanes, polycyclic aromatic hydrocarbons (PAHs), n-fatty acids and n-alkanols were determined. Source identification was made using organic species as molecular markers. Semi-volatile compounds of alkanes and PAHs had much higher concentrations in winter than summer because of the large difference in the temperature between the seasons. Plant wax emission was a major contributor to n-alkanes in summer, but fossil fuel residue was a major source (>80%) in winter. The seasonal differences in the distribution of pentacyclic triterpanes clearly shows the impact of coal burning for space heating in winter. The yield of PAHs in winter (148 ng m(-3) at the urban site and 277 ng m(-3) at the suburban site) was six to eight times higher than that in summer and was found to be mainly from coal burning. Higher pollutant concentrations were measured at the suburban site than the urban site in winter due to the rapid expansion of the city limit and the relocation of factories from urban to suburban areas over the last two decades.     

生物富集系数的快速测定法

以两室药物动力学模型为理论基础,提出了一种新的生物富集系数快速测定法;运用该法测定了六种疏水性有机化合物的BCF值。结果表明:该方法具有简便,快速、可靠的优点。     

介绍火焰原子吸收分光光度法中富集元素的新技术——原子捕集技术

<正> 一、前言火焰原于吸收分光光度法通常是原子以相同的流速迅速地通过分析光束,这对于在火焰气体内任何瞬间都具有足够数量的原子来说是可行的。但是,当原子数很少,又加上原子在火焰中停留时间很有限(约10~(-3)秒),那未,原子吸收的信号就很小,这就限制了常规的火焰法对低浓度样品的分析。为了提高浓度,就要做大量的预富集工作。 1976年Stephens等人实现了一种预富集的新技术,称为原子捕集技术(atomtrap)。把一根水冷却的硅管,置于火焰中,     

高效液相色谱法测定多环芳烃化合物辛醇/水的分配系数及其对水溶解度的估算

本文采用反相高效液相色谱法间接测定了29种多环芳烃化合物的辛醇/水分配系数,并估算其水溶解度,所得结果与文献值和计算值基本一致。     

Analysis on sensitivity and landscape ecological spatial structure of site resources

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2016~2018年中国城市臭氧浓度时空聚集变化规律

为揭示中国O₃浓度的时空格局及聚集变化规律,通过对2016~2018年全国338个城市1144个监测站点的O₃浓度观测数据,使用空间插值及空间自相关等方法进行分析研究.结果表明：2016~2018年全国O₃浓度（第90百分位数）总体呈现上升趋势（由2016年的141.54μg/m³上升到2018年的153.21μg/m³）,污染态势逐年加重,且华北及长江中下游等人口稠密地区O₃浓度最高,O₃浓度的空间分布呈现显著的聚集性和相似性规律,且聚集性逐年增强,O₃浓度的年聚集区主要呈现北高南低的分异,高高值聚集区主要集中在北方（城市占比22.19%~29.59%）,低低值聚集区则主要集中在南方（城市占比15.98%~22.19%）,此外,O₃浓度高高值聚集区与低低值聚集区空间分布的季节变化规律以顺时针周期性变化为主：3a来,春季集聚区分布与年集聚情况相同,夏季高高值,低低值聚集区逐渐向西扩大聚集范围,秋季则顺时针转变为东高西低的分异情况,随后高高值（低低值）聚集区沿顺时针方向南（北）移动,到冬季则转变为南高北低的空间分异情况.     

基于城市化的浙江省湾区经济带碳排放时空分布特征及影响因素分析

基于STIRPAT扩展模型与2003-2017年浙江省湾区经济带面板数据,分析碳排放时空分布特征并应用时空地理加权回归模型（GTWR）实证考察城市化视角下碳排放的驱动机制及其时空异质性。结果表明：（1）浙江省湾区经济带各地市碳排放规模逐年增加但增幅不大,增速放缓,碳排放量差异明显,碳排放强度逐年下降,空间上呈现自西南向东北逐渐加大的趋势;（2）经济发展水平和对外开放程度是碳排放的主导因素,其他依次为能源消费结构、技术进步和城市化;（3）各影响因素呈现较强的时空异质性,不同时间、地区各驱动要素的波动方向和强度并不相同。在此基础上具体分析各地区碳排放驱动因素影响情况,为实现区域差异化碳减排策略提供指导。