Sources, distribution, and risk assessment of organochlorine pesticides in Nairobi City, Kenya

The distribution and sources of organochlorine pesticides (OCPs) in air and surface waters were monitored in Nairobi City using triolein-filled semipermeable membrane devices (SPMDs). The SPMDs were extracted by dialysis using n-hexane, followed by cleanup by adsorption chromatography on silica gel cartridges. Sample analysis was done by GC-ECD and confirmed by GC–MS. Separation of means was achieved by analysis of variance, followed by pair-wise comparison using the t-test (p≤ 0.05). The total OCPs ranged between 0.018 – 1.277 ng/m³ in the air and <LOD – 1391.000 ng/m³ in surface waters. Based on the results, the means of Industrial Area, Dandora and Kibera were not significantly different (p≤ 0.05), but were higher (p≤ 0.05) than those of City square and Ngong’ Forest. The results revealed non-significant (p≤ 0.05) contribution of long-range transport to OCP pollution in Nairobi City. This indicated possible presence of point sources of environmental OCPs in the city. The water-air fugacity ratios indicated that volatilization and deposition played an important role in the spatial distribution of OCPs in Nairobi City. This indicated that contaminated surface waters could be major sources of human exposure to OCPs, through volatilization. The incremental lifetime cancer risks (ILCR) determined from inhalation of atmospheric OCPs were 2.3745  ×  10^?13 – 1.6845  ×  10^?11 (adult) and 5.5404  ×  10^?13 – 3.9306  ×  10^?11 (child) in the order: Dandora > Kibera > Industrial Area > City Square > Ngong’ Forest. However, these were lower than the USEPA acceptable risks, 10^?6 – 10^?4. This study concluded that atmospheric OCPs did not pose significant cancer risks to the residents.     

Particulate matter exchange between atmosphere and roads surfaces in urban areas

The deposition and the re-suspension of particulate matter (PM) in urban areas are the key processes that contribute not only to stormwater pollution, but also to air pollution. However, investigation of the deposition and the re-suspension of PM is challenging because of the difficulties in distinguishing between the resuspended and the deposited PM. This study created two Bayesian Networks (BN) models to explore the deposition and the re-suspension of PM as well as the important influential factors. The outcomes of BN modelling revealed that deposition and re-suspension of PM10 occurred under both, high-traffic and low-traffic conditions, and the re-suspension of PM2.5 occurred under low-traffic conditions. The deposition of PM10 under low-volume traffic condition is 1.6 times higher than under high-volume traffic condition, which is attributed to the decrease in PM10 caused by relatively higher turbulence under high-volume traffic conditions. PM10 is more easily resuspended from road surfaces compared to PM2.5 as the particles which larger than the thickness of the laminar airflow over the road surface are more easily removed from road surfaces. The increase in wind speed contributes to the increase in PM build-up by transporting particulates from roadside areas to the road surfaces and the airborne PM2.5 and PM10 increases with the increase in relative humidity. The study outcomes provide a step improvement in the understanding of the transfer processes of PM2.5 and PM10 between atmosphere and urban road surfaces, which in turn will contribute to the effective design of mitigation measures for urban stormwater and air pollution.     

Analytical methods and environmental processes of nanoplastics

The degradation of plastic debris may result in the generation of nanoplastics (NPs). Their high specific surface area for the sorption of organic pollutions and toxic heavy metals and possible transfer between organisms at different nutrient levels make the study of NPs an urgent priority. However, there is very limited understanding on the occurrence, distribution, abundant, and fate of NPs in the environment, partially due to the lack of suitable techniques for the separation and identification of NPs from complex environmental matrices. In this review, we first overviewed the state-of-the-art methods for the extraction, separation, identification and quantification of NPs in the environment. Some of them have been successfully applied for the field determination of NPs, while some are borrowed from the detection of microplastics or engineered nanomaterials. Then the possible fate and transport of NPs in the environment are thoroughly described. Although great efforts have been made during the recent years, large knowledge gaps still exist, such as the relatively high detection limit of existing method failing to detect ultralow masses of NPs in the environment, and spherical polystyrene NP models failing to represent the various compositions of NPs with different irregular shapes, which needs further investigation.     

Reviews of emission of biogenic volatile organic compounds (BVOCs) in Asia

Biogenic volatile organic compounds (BVOCs) in the atmosphere play important roles in the formation of ground-level ozone and secondary organic aerosol (SOA) in global scale and also in regional scale under some condition due to their large amount and relatively higher reactivity. In places with high plant cover in the tropics and in China where air pollution is serious, the effect of BVOCs on ozone and secondary organic aerosols is strong. The present research aims to provide a comprehensive review about the emission rate, emission inventory, research methods, the influencing factors of BVOCs emissions, as well as their impacts on atmospheric environment quality and human health in recent years in Asia based on the summary and analysis of literatures. It is suggested to use field direct measurement method to obtain the emission rate and model method to calculate the emission amount. Several recommendations are given for future investigation and policy development on BVOCs emission.     

生态调控后贵州花溪水库浮游植物群落结构的变化特征及影响因素

为了解生态调控后花溪水库浮游植物功能群变化特征与环境因子的关系,基于浮游植物功能群、NMDS（非度量多维尺度分析）、RDA（冗余分析）、Pearson相关性分析方法,于2017年3月-2018年3月逐月对浮游植物群落结构与水环境指标进行采样分析.结果表明:①生态调控前,花溪水库共鉴定浮游植物4门18种,共归类出10个功能群,且功能群H1占绝对优势,其代表藻种为水华束丝藻（Aphanizomenon flosaquae）;生态调控后,共鉴定浮游植物6门66种,共归类出20个功能群,主要优势功能群为B/Lo,其代表藻种为小环藻（Cyclotella sp.）和多甲藻（Peridinium sp.）.②生态调控后,花溪水库优势功能群结构发生了变化,其变化特征为B/Lo（春季）→D/B/Lo/X2/N/P（夏季）→D/B/Lo/N（秋季）→D/MP/B/Lo/W1/W2（冬季）.功能群B的生物量在春季达到峰值（3 056.3 μg/L）,与其对低营养环境有良好的耐受性有关;功能群Lo的生物量在秋季达到峰值（2 900.9 μg/L）,与组成功能群Lo的甲藻特性有关.③RDA结果表明,生态调控前影响浮游植物生长的环境因子为SD（透明度）、ρ（DIN）（DIN为无机氮）;生态调控后影响浮游植物生长的环境因子为WT（水温）、ρ（DO）、ρ（DIN）.研究显示,生态调控后花溪水库功能群结构发生了明显变化,影响功能群变化的主要环境因子为WT和ρ（DO）.      

保定市大气污染特征和潜在输送源分析

保定市是京津冀地区重要城市之一.为了解保定市大气污染物质量浓度特征和潜在输送源,对保定市国控点2017年1月1日-12月31日PM₁₀、PM_2.5、SO₂、NO₂、O₃、CO等常规大气污染物数据进行分析,并利用TrajStat后向轨迹模型进行区域传输研究.结果表明:①ρ（PM₁₀）、ρ（PM_2.5）、ρ（SO₂）、ρ（NO₂）分别为（138±96）（84±66）（29±23）和（50±24）μg/m3,与2016年相比分别下降5.9%、9.1%、25.5%和13.1%;ρ（CO）较2016年下降了14.0%;ρ（O₃）较2016年增长了25.2%.ρ（PM₁₀）、ρ（PM_2.5）、ρ（NO₂）和ρ（O₃）分别超过GB 3095-2012《环境空气质量标准》二级标准限值的0.97、1.40、0.25和0.34倍,ρ（SO₂）和ρ（CO）未超标.②除ρ（O₃）外,其他污染物质量浓度均呈冬季最高、夏季最低的季节性特征,其中,冬季PM_2.5污染最为严重,春季PM_2.5~10（粗颗粒物）污染严重.③空气质量模型源解析结果显示,保定市ρ（PM_2.5）约60.0%~70.0%来自本地污染源排放.后向轨迹结果表明,在外来区域传输影响中,保定市主要受到西北方向气团（占比为21.7%~60.0%）远距离传输和正南方向气团（占比为34.8%~50.5%）近距离传输的影响.④PSCF（潜在源贡献因子分析法）和CWT（浓度权重轨迹分析法）分析表明,除保定市及周边区县本地污染贡献外,位于太行山东麓沿线西南传输通道的邯郸市、邢台市、石家庄市是影响保定市PM_2.5的主要潜在源区.研究显示,PM_2.5为保定市大气中的主要污染物,并呈冬季高、夏季低的变化特征,其主要来自西北远距离输送和南部近距离传输.      

银川市冬季PM2.5重污染特征、来源与成因分析

近年来银川市冬季重污染过程频发,为明确银川市冬季PM_2.5重污染的特征,分析其主要来源及成因,于2016年12月-2017年1月在银川市选取3个采样点开展PM_2.5的样品采集与化学组分分析,利用CMB（化学质量平衡）模型对银川市冬季PM_2.5进行来源解析,对比分析了重污染日与非重污染日污染特征的差异.结果表明:①银川市冬季重污染日ρ（PM_2.5）[（181±33.6）μg/m3]是非重污染日的2.1倍;重污染日和非重污染日的ρ（NO₃-）/ρ（SO₄2-）均小于1,表明燃煤仍是银川市冬季PM_2.5的重要来源.银川市冬季PM_2.5中ρ（SOC）为（14.4±7.34）μg/m3,约占ρ（OC）的65.2%.②与非重污染日相比,重污染日人为源无机元素As、Pb、Cd和Zn质量浓度在ρ（PM_2.5）中的占比分别升高33.2%、18.4%、9.8%和2.9%,表明银川市冬季重污染主要受人为源贡献影响.③源解析结果表明,燃煤源、机动车尾气源、二次离子源和扬尘源是银川市PM_2.5的主要污染源,与非重污染日相比,重污染日机动车尾气源的贡献率明显降低.研究显示,银川市冬季重污染受人为源污染物排放的影响较大,燃煤源是银川市冬季PM_2.5的重要来源.      

基于TMVOC的地下水位波动带苯系物迁移转化模拟

为探究水位波动情况下苯系物的迁移转化规律,提高石油污染场地地下水污染治理精度,以西北某傍河石化场地为研究对象,基于TMVOC模型对特征污染物苯系物开展泄漏模拟,通过情景模拟比较水位波动对苯系物迁移转化的影响,并从污染分布、相间转化等方面,解析地下水位稳定和波动状态下苯系物迁移转化过程差异.结果表明:①TMVOC模型较好地模拟了水位波动状态下苯系物迁移转化过程.②相较于水位稳定状态下,水位波动作用下苯系物污染深度增加0.5 m,污染面积增加25%,总质量增加12 kg.③水位稳定和波动状态下苯系物"气-液-NAPL（Non-Aqueous Phase Liquids）相"占比分别为0.17%、2.03%、97.8%和0.04%、3.69%、96.27%.④NAPL相苯系物饱和度分布与苯系物质量分布呈正相关,水位波动造成NAPL相初始饱和度降低,且初始水位面以下NAPL相饱和度升高.⑤对于苯而言,水位波动状态下非饱和带中苯在液相中的质量是水位稳定状态下的1.11倍,饱和带为10.15倍.研究显示,水位波动显著地影响了苯系物的迁移转化过程,促进了苯系物的溶解,并使更多的苯系物残留在地下介质中.      

某垃圾焚烧厂投产前后周边土壤二英类化合物的分布

为研究垃圾焚烧厂运行对周边土壤二英类化合物（PCDD/Fs）含量的影响,采集了珠三角地区某垃圾焚烧厂投产前和投产后周边土壤样品,分析研究了该垃圾焚烧厂运行对周边土壤中PCDD/Fs含量和组分的变化.结果表明:①2012年（投产前）珠三角地区某垃圾焚烧厂周边土壤PCDD/Fs含量较低,范围为163~591 ng/kg（毒性当量范围为0.198~0.863 ng I-TEQ/kg,I-TEQ为国际毒性当量因子折算的毒性当量值）;2017—2019年（投产后）周边土壤PCDD/Fs含量范围为151~1.75×103 ng/kg（毒性当量范围为0.812~3.88 ng I-TEQ/kg）,与其他研究相比处于较低的水平.②投产后,距该垃圾焚烧厂较近（1.5 km）的采样点（S1）土壤PCDD/Fs含量逐年增长,在较远（5.2 km）但人口较密集的采样点（S3）土壤PCDD/Fs含量整体较高,但呈逐年下降趋势.③投产后,土壤中的17种PCDD/Fs单体组分中,毒性当量贡献率最高的单体为八氯二苯并二英（OCDD）和2,3,4,7,8-五氯二苯并呋喃（2,3,4,7,8-PeCDF）,二者毒性当量贡献率范围为15.7%~45.4%.④在同一采样点土壤PCDD/Fs单体组分年间差异不明显,但同一年份不同采样点差异明显.研究显示,目前该垃圾焚烧厂周边土壤PCDD/Fs含量较低,但仍需要长期监测其可能带来的风险.      

外加氮源影响下铁铝氧化物在土壤氮素转化中的作用

土壤中铁铝氧化物在团聚体稳定性和有机碳吸附方面具有重要作用,而氮添加对土壤氮循环影响的变化也可能与其有关,但是目前尚缺乏在氮循环方面的研究.为了探究铁铝氧化物在土壤氮素转化中的作用,选择福建省建瓯罗浮栲森林土壤为研究对象,采用选择性溶提技术准备不同的土壤——未经处理（T1）的土壤和去除游离态铁铝氧化物（T2）土壤、去除非晶质铁铝氧化物（T3）土壤、去除络合态铁铝氧化物（T4）土壤,在这些土壤中添加不同形态氮（40 mg/kg）——丙氨酸（氨基酸态氮,AA）、硫酸铵（铵态氮,AN）、硝酸钠（硝态氮,NAN）和亚硝酸钠（亚硝态氮,NIN）,进行室内培养试验,分析氮含量变化和氮素转化情况.结果表明:①与CK处理相比,AA和AN处理均增加了T1土壤中w（NH₄+-N）,NAN处理增加了w（NO₃--N）,但低于添加量,表明添加氨基酸和铵态氮均会促进氮矿化,添加硝态氮会增加NO₃--N的固定且抑制其硝化.②在CK处理下,与T1土壤相比,T2和T4土壤中w（NH₄+-N）、w（NO₃--N）和w（氨基酸）均降低,但T3土壤中w（NH₄+-N）和w（氨基酸）增加、w（NO₃--N）降低,表明土壤中游离态氧化铁铝和络合态氧化铁铝的存在有助于氮素矿化,非晶质氧化铁铝有助于硝化.③在不同氮处理下,各土壤的氮含量及其转化速率与CK处理规律相似.与CK处理相比,各氮处理均未显著增加T2和T4土壤中w（NH₄+-N）,且AA和AN处理均未影响T2、T3和T4土壤中w（NO₃--N）和w（氨基酸）.结果显示,氮添加并没有改变铁铝氧化物的作用,其中,矿化和氨化作用均表现为游离氧化铁铝>络合氧化铁铝>非晶质氧化铁铝,硝化作用表现为非晶质氧化铁铝>游离氧化铁铝>络合态氧化铁铝.因此,土壤铁铝氧化物的不同存在状态应该是调节氮素转化的重要土壤条件.