华南沿海地区夏初PM2.5水溶性离子特征及来源解析

2018年6月7日—7月10日,利用在线气体和气溶胶成分监测仪(IGAC)在珠海市沿海站对PM_2.5中水溶性离子浓度和气体开展连续观测分析.结果发现,夏初沿海地区水溶性离子处于较低水平,SO₄^2-、NH₄⁺、NO₃^-、Cl^-、Na⁺、Ca²⁺、K⁺、Mg²⁺浓度分别为4.78、1.87、1.16、0.92、0.37、0.27、0.11和0.11μg·m^-3,其中,代表海洋来源的Na⁺和Cl^-浓度与珠江口东海岸的深圳沿海地区相当. Na⁺和Cl^-呈明显的白天高、夜晚低的日变化特征,与海盐排放在海陆风环流下的输送有关.基于天气形势分析、气团来源分析和PMF来源解析方法研究了观测期间发生的两次污染过程,一次是受到强热带风暴外...     

Secondary organic aerosol formation from straw burning using an oxidation flow reactor

Herein, we use an oxidation flow reactor, Gothenburg: Potential Aerosol Mass (Go: PAM) reactor, to investigate the secondary organic aerosol (SOA) formation from wheat straw burning. Biomass burning emissions are exposed to high concentrations of hydroxyl radicals (OH) to simulate processes equivalent to atmospheric oxidation of 0-2.55 days. Primary volatile organic compounds (VOCs) were investigated, and particles were measured before and after the Go: PAM reactor. The influence of water content (i.e. 5% and 11%) in wheat straw was also explored. Two burning stages, the flaming stage, and non-flaming stages, were identified. Primary particle emission factors (EFs) at a water content of 11% (∼3.89 g/kg-fuel) are significantly higher than those at a water content of 5% (∼2.26 g/kg-fuel) during the flaming stage. However, the water content showed no significant influence at the non-flaming stage. EFs of aromatics at a non-flaming stage (321.8±46.2 mg/kg-fuel) are larger than that at a flaming stage (130.9±37.1 mg/kg-fuel). The OA enhancement ratios increased with the increase in OH exposure at first and decreased with the additional increment of OH exposure. The maximum OA enhancement ratio is ∼12 during the non-flaming stages, which is much higher than ∼ 1.7 during the flaming stages. The mass spectrum of the primary wheat burning organic aerosols closely resembles that of resolved biomass burning organic aerosols (BBOA) based on measurements in ambient air. Our results show that large gap (∼60%-90%) still remains to estimate biomass burning SOA if only the oxidation of VOCs were included.     

稻草和玉米秸秆烟尘中的正构脂肪醇

在不同燃烧条件下,对6种稻草和4种玉米秸进行了燃烧试验,并测定了烟尘中正构脂肪醇的组成.结果表明,在稻草的明火烟尘中,正构脂肪醇由C14~C34组成.其总含量(Σ)为1 604.4~13 889.7 mg·kg-1;低碳数和高碳数正构脂肪醇的含量比(L/H)为0.02~0.09;C24/C30值为3.3%~19.6%;C32/C30值为8.4%~19.9%;C30Σ之比为53.9%~72.6%;CPI值为8.7~21.5;ACL值为29.0~30.1.正构脂肪醇呈双峰式分布,其主、次峰碳数分别是C30和C24.在稻草的闷烧烟尘中,正构脂肪醇的单体组成与明火烟尘相同.其Σ值为1 688.7~5 168.2 mg·kg-1;L/H值为0.08~0.14;C24/C30值为31.0%~70.5%;C32/C30值为6.9%~17.6%;C30Σ之比为39.5%~57.8%;CPI值为10.7~17.5;ACL值为27.2~28.5.其分布模式与明火烟尘极为相似.在玉米秸秆的明火烟尘中,正构脂肪醇由C12~C34组成.其Σ值为852.3~2 667.9 mg·kg-1;L/H值为0.2~1.0;C24/C28之比为104.3%~293.3%;C32/C28之比为42.2%~61.4%;C28Σ之比为7.3%~16.5%;CPI值为5.6~9.7;ACL值为23.1~26.9.其分布模式以双峰式为主,主峰碳数是C30、C24和C22.在玉米秸秆的闷烧烟尘中,正构脂肪醇的组成与明火烟尘相同.其Σ值为1 493.0~8 386.9 mg·kg-1;L/H之比为0.2~0.3;C24/C28之比为53.6%~217.6%;C32/C28之比为21.7%~75.9%;C28Σ之比为8.8%~27.3%;CPI值为4.2~6.5;ACL值为26.3~27.2.其分布模式呈双峰型,主峰碳数主要是C30,次峰碳数主要是C24.总之,秸秆烟尘中正构脂肪醇的组成已发生了明显的变化.C24/C30、C32/C30、C30Σ等参数可用于区别稻草及其燃烧来源的正构脂肪醇;L/H、C24/C28、C32/C28、C28Σ等参数可用于区分玉米秸秆及其燃烧来源的正构脂肪醇;L/H可用于区分上述两类秸秆及其燃烧来源的正构脂肪醇.     

农业污染对土壤的危害及防治措施

伴随着我国经济的高速增长,环境问题也日益突出,特别是环境污染和生态破坏日益严重。城市环境问题日益得到重视,而农村的环境保护与治理相对来说是一个薄弱环节,农村环境也正日趋恶化。农村环境污染的加剧和农业生态环境的破坏,已成为制约我国农村经济健康发展的因素之一,农业减排势在必行。结合农村实际情况,本文从环境保护的角度阐述了农业生产过程中几种典型（农药、化肥、农作物秸秆）的污染及其对农田土壤造成的危害,同时针对化肥污染和农业污染提出了防治措施。     

长三角地区秸秆焚烧PM2.5排放量估算与分析研究

根据长三角地区的实际情况,对该地区两省一市的秸秆焚烧PM2.5排放量状况进行估算.通过长三角地区2002年-2012年主要农作物产量、草谷比、焚烧比例和PM2.5排放因子,估算了该地区内秸秆焚烧量,同时对由秸秆焚烧引起的PM2.5排放量进行了估算,并进行了分析.结果表明：长三角地区2002年-2012年秸秆焚烧量最高的为农业发达的江苏省,高峰都集中在每年的10月份前后,由秸秆焚烧引起的PM2.5排放量呈逐年上升趋势,2012年达到55 218.96 t,其中江苏省每年的PM2.5排放量占到该地区的75％以上,2012年占到80％.研究结果将为制定该地区污染控制政策,改善区域环境空气质量提供科学理论依据.     

生活垃圾和医疗垃圾混烧研究

阐述了生活垃圾焚烧和医疗垃圾焚烧市场的现状;研究了垃圾的物理成分、组成元素、毒理性,以及执行标准、焚烧炉炉型等,分析了生活垃圾与医疗垃圾混烧会出现的问题;从投资估算和技术经济角度对混烧及分别处理方式的投资收益进行对比,最终得出不推荐生活垃圾和医疗垃圾混烧的结论。     

环氧氯丙烷改性稻草的光降解研究

利用QUV耐候加速仪对天然稻草、预处理稻草和环氧氯丙烷改性稻草进行了光降解老化实验,研究其在光降解后的失重率和红外光谱图变化。结果表明,经过576h光降解实验后,改性稻草的失重率接近于天然稻草的失重率,分别为2．50％和2．49％,而预处理稻草的失重率仅为1．71％。红外光谱图显示,天然稻草光降解后,木质素含量明显降低;预处理后稻草中的木质素和半纤维素被去除;预处理稻草经环氧氯丙烷改性后,醚键增多,改性稻草光降解后-CH2和-CH2的含量降低,说明脂肪族化合物发生分解。     

Evaluation of CFD simulations of transient pool fire burning rates

Fire is the most commonly occurring major accident hazard in the chemical and process industries, with industry accident statistics highlighting the liquid pool fire as the most frequent fire event. Modelling of such phenomena feeds heavily into industry risk assessment and consequence analyses. Traditional simple empirical equations cannot account for the full range of factors influencing pool fire behaviour or increasingly complex plant design. The use of Computational Fluid Dynamics (CFD) modelling enables a greater understanding of pool fire behaviour to be gained numerically and provides the capability to deal with complex scenarios.This paper presents an evaluation of the Fire Dynamics Simulator (FDS) for predictive modelling of liquid pool fire burning rates. Specifically, the work examines the ability of the model to predict temporal variations in the burning rate of open atmosphere pool fires. Fires ranging from 0.4 to 4 m in diameter, involving ethanol and a range of liquid hydrocarbons as fuels, are considered and comparisons of predicted fuel mass loss rates are compared to experimental measurements.The results show that the liquid pyrolysis sub-model in FDS gives consistent model performance for fully predictive modelling of liquid pool fire burning rates, particularly during quasi-steady burning. However, the model falls short of predicting the subtleties associated with each phase of the transient burning process, failing to reliably predict fuel mass loss rates during fire growth and extinction. The results suggest a range of model modifications which could lead to improved prediction of the transient fire growth and extinction phases of burning for liquid pool fires, specifically, investigation of: ignition modelling techniques for high boiling temperature liquid fuels; a combustion regime combining both infinite and finite-rate chemistry; a solution method which accounts for two- or three-dimensional heat conduction effects in the liquid-phase; alternative surrogate fuel compositions for multi-component hydrocarbon fuels; and modification of the solution procedure used at the liquid-gas interface during fire extinction.     

北京市2014年10月重霾污染特征及有机碳来源解析

2014年10月北京市出现了多次重霾天气,与此同时,通过全国秸秆燃烧卫星遥感监测发现,北京周边河南、河北等地区恰存在一定规模的秸秆燃烧活动. 对2014年10月4—27日北京市大气PM_2.5中的水溶性离子、金属、OC(有机碳)、EC(元素碳)和有机物示踪物等化学成分进行了分析,对霾天和非霾天PM_2.5中化学成分进行了比较,并使用CMB(化学质量平衡)模型对PM_2.5中有机物的来源进行了解析,采用后向轨迹模拟和卫星遥感图像定量评估生物质燃烧(秸秆燃烧等)对重霾污染的影响. 结果表明:霾天ρ(PM_2.5)〔(229.0±96.3)μg/m3〕是非霾天的5.0倍,水溶性离子总质量浓度〔(125.3±59.3)μg/m3〕是非霾天的6.5倍,ρ(SO₄2-)、ρ(NO₃-)和ρ(NH₄+)分别是非霾天的6.1、8.6和7.1倍,ρ(OC)〔(81.8±39.5)μg/m3〕是非霾天的7.8倍,ρ(EC)〔(6.7±3.4)μg/m3〕是非霾天的4.2倍;霾天生物质燃烧的示踪物——左旋葡聚糖和K+的质量浓度平均值分别是非霾天的9.1和3.3倍. 生物质燃烧、机动车排放以及二次污染物对有机细颗粒物的贡献率分别为18.9%、36.9%和41.9%;二次细颗粒物质量浓度增加了1倍左右;气象条件同样在很大程度上促进了霾的形成. 常规的源解析方法仅可对生物质燃烧的一次污染贡献进行定量,但对重霾污染贡献的全面评价尚需进一步探讨.      

城市生活垃圾露天焚烧PM2.5及其组分排放特征

利用稀释采样系统,针对桶内燃烧和自然堆积两种常见露天焚烧方式,分别对橡塑类、纸类和木竹类这3种组分生活垃圾露天焚烧PM_(2.5)排放特征进行实测,计算PM_(2.5)、OC、EC、水溶性离子和无机元素排放因子.结果表明,木竹类生活垃圾PM_(2.5)排放因子(7.44±0.76)g·kg~(-1)最高,纸类PM_(2.5)排放因子(2.72±0.52)g·kg~(-1)最低.桶内燃烧的条件会造成更多污染物排放.在不同的燃烧方式下,橡塑类和纸类生活垃圾在桶内燃烧的条件下PM_(2.5)排放因子是自然堆积燃烧的2.5~3.5倍.PM_(2.5)中OC和EC为主要组成成分,PM_(2.5)组分构成占比约为46.6%~67.2%.不同垃圾组分OC/EC比率差异较大,但该比率受焚烧条件影响较小,有助于解析不同组分垃圾焚烧排放贡献.水溶性离子中NH+4离子、Cl-离子含量最高,在PM_(2.5)中所占比例范围分别为2.28%~6.35%和1.04%~14.31%.无机元素中Ca、K、Fe和Ba元素排放因子较高.重金属元素中Zn元素排放因子最高,Cu、Cr、Sb和Pb等元素也有一定富集.Zn元素含量主要由燃烧方式决定,桶内燃烧大约是自然堆积燃烧的20倍左右.