Source apportionment of wintertime secondary organic aerosol during the California regional PM10/PM2.5 air quality study

The UCD/CIT air quality model with the Caltech Atmospheric Chemistry Mechanism (CACM) was used to predict source contributions to secondary organic aerosol (SOA) formation in the San Joaquin Valley (SJV) from December 15, 2000 to January 7, 2001. The predicted 24-day average SOA concentration had a maximum value of 4.26 μg m^?3 50 km southwest of Fresno. Predicted SOA concentrations at Fresno, Angiola, and Bakersfield were 2.46 μg m^?3, 1.68 μg m^?3, and 2.28 μg m^?3, respectively, accounting for 6%, 37%, and 4% of the total predicted organic aerosol. The average SOA concentration across the entire SJV was 1.35 μg m^?3, which accounts for approximately 20% of the total predicted organic aerosol. Averaged over the entire SJV, the major SOA sources were solvent use (28% of SOA), catalyst gasoline engines (25% of SOA), wood smoke (16% of SOA), non-catalyst gasoline engines (13% of SOA), and other anthropogenic sources (11% of SOA). Diesel engines were predicted to only account for approximately 2% of the total SOA formation in the SJV because they emit a small amount of volatile organic compounds relative to other sources. In terms of SOA precursors within the SJV, long-chain alkanes were predicted to be the largest SOA contributor, followed by aromatic compounds. The current study identifies the major known contributors to the SOA burden during a winter pollution episode in the SJV, with further enhancements possible as additional formation pathways are discovered.     

Estimation of economic costs of particulate air pollution from road transport in China

Valuation of health effects of air pollution is becoming a critical component of the performance of cost–benefit analysis of pollution control measures, which provides a basis for setting priorities for action. Beijing has focused on control of transport emission as vehicular emissions have recently become an important source of air pollution, particularly during Olympic games and Post-games. In this paper, we conducted an estimation of health effects and economic cost caused by road transport-related air pollution using an integrated assessment approach which utilizes air quality model, engineering, epidemiology, and economics. The results show that the total economic cost of health impacts due to air pollution contributed from transport in Beijing during 2004–2008 was 272, 297, 310, 323, 298 million US$ (mean value), respectively. The economic costs of road transport accounted for 0.52, 0.57, 0.60, 0.62, and 0.58% of annual Beijing GDP from 2004 to 2008. Average cost per vehicle and per ton of PM₁₀ emission from road transport can also be estimated as 106 US $/number and 3584 US $ t^?1, respectively. These findings illustrate that the impact of road transport contributed particulate air pollution on human health could be substantial in Beijing, whether in physical and economic terms. Therefore, some control measures to reduce transport emissions could lead to considerable economic benefit.     

Emission factors and particulate matter size distribution of polycyclic aromatic hydrocarbons from residential coal combustions in rural Northern China

Coal consumption is one important contributor to energy production, and is regarded as one of the most important sources of air pollutants that have considerable impacts on human health and climate change. Emissions of polycyclic aromatic hydrocarbons (PAHs) from coal combustion were studied in a typical stove. Emission factors (EFs) of 16 EPA priority PAHs from tested coals ranged from 6.25 ± 1.16 mg kg^?1 (anthracite) to 253 ± 170 mg kg^?1 (bituminous), with NAP and PHE dominated in gaseous and particulate phases, respectively. Size distributions of particulate phase PAHs from tested coals showed that they were mostly associated with particulate matter (PM) with size either between 0.7 and 2.1 μm or less than 0.4 μm (PM_0.4). In the latter category, not only were more PAHs present in PM_0.4, but also contained higher fractions of high molecular weight PAHs. Generally, there were more than 89% of total particulate phase PAHs associated with PM_2.5. Gas-particle partitioning of freshly emitted PAHs from residential coal combustions were thought to be mainly controlled by absorption rather than adsorption, which is similar to those from other sources. Besides, the influence of fuel properties and combustion conditions was further investigated by using stepwise regression analysis, which indicated that almost 57 ± 10% of total variations in PAH EFs can be accounted for by moisture and volatile matter content of coal in residential combustion.     

Chemical mass balance source apportionment for combined PM2.5 measurements from U.S. non-urban and urban long-term networks

The Minnesota Particulate Matter 2.5 (PM_2.5) Source Apportionment Study was undertaken to explore the utility of PM_2.5 mass, element, ion, and carbon measurements from long-term speciation networks for pollution source attribution. Ambient monitoring data at eight sites across the state were retrieved from the archives of the Interagency Monitoring of Protected Visual Environments (IMPROVE) and the Speciation Trends Network (STN; part of the Chemical Speciation Network [CSN]) and analyzed by an Effective Variance – Chemical Mass Balance (EV-CMB) receptor model with region-specific geological source profiles developed in this study. PM_2.5 was apportioned into contributions of fugitive soil dust, calcium-rich dust, taconite (low grade iron ore) dust, road salt, motor vehicle exhaust, biomass burning, coal-fired utility, and secondary aerosol. Secondary sulfate and nitrate contributed strongly (49–71% of PM_2.5) across all sites and was dominant (≥60%) at IMPROVE sites. Vehicle exhausts accounted for 20–70% of the primary PM_2.5 contribution, largely exceeding the proportion in the primary PM_2.5 emission inventory. The diesel exhaust contribution was separable from the gasoline engine exhaust contribution at the STN sites. Higher detection limits for several marker elements in the STN resulted in non-detectable coal-fired boiler contributions which were detected in the IMPROVE data. Despite the different measured variables, analytical methods, and detection limits, EV-CMB results from a nearby IMPROVE-STN non-urban/urban sites showed similar contributions from regional sources – including fugitive dust and secondary aerosol. Seasonal variations of source contributions were examined and extreme PM_2.5 episodes were explained by both local and regional pollution events.     

铁炭复配修复地下水中NO_3~--N的条件研究

采用了铁炭复配修复地下水中NO3--N,探讨了实验条件对修复效果的影响。结果表明,在pH值近中性条件(初始pH 6.42)下,反应时间为1 h时NO3--N修复率达到60.85%;Fe/C=1∶1时介质最佳用量分别为4~5 g;Fe/C=1/1.5时修复率为72.80%;反应速率在高振荡强度下大于低振荡强度;氧化铜的催化效果最好,可使修复率提高7.5个百分点。铁炭复配介质修复地下水中NO3--N是有效可行的,修复率随反应时间的增加而提高,在Fe/C=1∶1时修复率与介质用量呈正相关,无限减小Fe/C比并不能无限提高修复率,振荡强度对修复具有显著影响,低振荡强度下的修复过程较高强度存在滞后现象,并非所有金属氧化物催化剂对铁炭修复NO3--N均有促进作用。     

颗粒物对无电压作用下离子交换膜分离去除铜离子的影响

在无外加电压条件下研究了颗粒物对阳离子交换膜分离去除铜离子效果的影响。选用硅酸、二氧化硅、氧化铝和水杨酸等4种物质作为颗粒物分别进行实验,其添加量均为50 mg/L。Cu2+及其补偿离子K+的浓度分别为0.0787mmol/L(5 mg/L)和0.787 mmol/L,水温为25±1℃,搅拌强度为600 r/min,水力停留时间为12 h。在所述实验条件下运行96 h后,水中无颗粒物干扰时,铜离子去除率为84%;水中存在带负电荷颗粒物(硅酸)和不带电荷颗粒物(二氧化硅和氧化铝)时,铜离子去除率略为下降至81%;而当水中存在带正电荷颗粒物(水杨酸)时,铜离子的去除率进一步下降为79%。研究结果表明带正电荷颗粒物对铜离子的交换去除影响较带负电荷或不带电荷颗粒物大,因为带正电荷颗粒物更易迁移至阳离子交换膜表面甚至进入膜内,并与膜表或膜内离子交换基团结合,从而导致铜离子交换去除明显下降。     

反应沉淀一体式矩形环流反应器处理城市污水的影响因素研究

通过中试研究了不同溶解氧浓度、有机负荷、HRT条件下,反应沉淀一体式矩形环流反应器(RPIR)对深圳市南山污水处理厂低C/N城市污水的处理效果。结果表明,在控制溶解氧浓度为1 mg/L、COD容积负荷小于2.5 kg/m3.d、NH4+-N容积负荷不超过0.2 kg/(m3.d)、HRT为4 h时,COD平均去除率可达90%,NH4+-N平均去除率超过80%。RPIR在处理该城市污水过程中具有良好的抗冲击负荷能力,污染物去除效率高,运行稳定。     

聚铁混凝-臭氧-BAF对晚期垃圾渗滤液深度处理的研究

联合运用聚铁混凝-臭氧-曝气生物滤池(BAF)对晚期垃圾场的渗滤液进行深度处理。在废水进水COD=601mg/L,色度=400倍时,提出最佳工艺条件:聚铁0.6 mL/L,臭氧用量144 mg/L,BAF停留时间7 h。研究表明,聚铁去除大部分悬浮性有机物,臭氧降解难生物降解有机物并提高废水的可生化性,BAF进一步降解有机物,最终出水COD为75 mg/L,深度处理成本仅为5.5元/t。     

超声吹脱去除氨氮的机理和动力学研究

采用超声吹脱技术对某印染厂印染废水中的氨氮进行了处理实验,探索了其反应机理并进行了动力学研究。研究表明,叔丁醇的存在没有降低废水中氨氮的去除率,证明.OH不是超声吹脱去除氨氮反应中的主导氧化物种。通过对反应产物的分析发现,超声吹脱去除氨氮的机理主要是氨氮以游离态的方式在空化效应下高温高压热解成氮气和氢气排出,同时氨气在空化效应产生的超临界状态下传质速度加快,在吹脱条件下更易于从废水中散失。动力学分析表明,印染废水中氨氮的超声去除反应属于一级反应,符合一级反应动力学。