商业房产共用面积分摊模型的研究

针对房产测绘中复杂商业房产分摊数据计算量大、分摊对象不明确易产生纠纷的问题,本文在传统的房产共用面积分摊模型的基础上,提出了改进的共用面积分摊模型。该模型灵活地应用功能区的概念,将功能和用途都不同的套内面积整合在一起,合并成为一个功能区,有效地解决了复杂房产分摊问题,在复杂房产分摊方面较传统模型大大减少了数据计算量,可以更加直观地体现出共用面积的服务对象。     

青岛市秋冬季霾期PM1及其含碳组分理化特征及来源研究

对2017年11月1日—2018年1月31日与2018年11月1日—2019年1月31日连续两年青岛市大气PM₁进行监测,获取了PM₁中含碳组分的变化趋势,结合国控站点监测数据和气象条件,分析了秋冬季PM₁来源.结果表明：2017、2018年秋冬季观测期间PM₁日均质量浓度分别为40.58±25.98、42.55±25.05 μg/m³;霾日质量浓度分别为84.71±16.70、81.52±18.39 μg/m³.与2017年相比,2018年同期PM₁质量浓度增长4.85%,霾日下降3.76%.2017年霾日PM₁中OC、EC质量浓度分别为13.67±3.95、3.95±1.02 μg/m³,2018年分别为16.48±6.34、3.34±1.16 μg/m³.与2017年相比,2018年霾日OC质量浓度增长20.56%,EC下降15.44%.2017、2018年霾日SOC质量浓度分别是非霾日的1.28和2.15倍,表明霾污染发生时易发生有机碳二次转化.含碳组分主成分分析均解析出3个因子.因子1解释变量均最大,分别为58.98%、67.14%,其表征含碳组分主要源于生物质燃烧、燃煤、道路扬尘及汽油车尾气等排放源.由后向气流轨迹分析得出,2017、2018年秋冬季气团轨迹多起源于内蒙古,经河北、天津、山东等省市抵达青岛.     

Origin and source regions of PM10 in the Eastern Mediterranean atmosphere

A set of daily PM₁₀ (n = 281) samples collected from April 2001 to April 2002 at a rural site (Erdemli), located on the coast of the Eastern Mediterranean, were analyzed applying Mass Closure (MC), absolute principal factor analysis (APFA) and Positive Matrix Factorization (PMF) to determine source contributions. The results from the three techniques were compared to identify the similarities and differences in the sources and source contributions. Source apportionment analysis indicated that PM₁₀ were mainly originated from natural sources (sea salt + crustal ≈ 60%) whilst secondary aerosols and residual oil burning accounted for approximately 20% and 10% of the total PM₁₀ mass, respectively. Calculations for sulfate showed that on average 8% and 12% of its total concentration were originated from sea salt and biogenic emissions, respectively. However, the contribution by biogenic emissions may reach up to a maximum of ~ 40% in the summer. Potential Source Contribution Function (PSCF) analysis for identification of source regions showed that the Saharan desert was the main source area for crustal components. For secondary aerosol components the analysis revealed one source region, (i.e. the south-Eastern Black Sea), whereas for residual oil, Western Europe and the western Balkans areas were found to be the main source regions.     

Compositions and source apportionments of atmospheric aerosol during Asian dust storm and local pollution in central Taiwan

A study has been carried out on water soluble ions, trace elements, as well as PM_2.5 and PM_2.5–10 elemental and organic carbon samples collected daily from Central Taiwan over a one year period in 2005. A source apportionment study was performed, employing a Gaussian trajectory transfer coefficient model (GTx) to the results from 141 sets of PM_2.5 and PM_2.5–10 samples. Two different types of PM₁₀ episodes, local pollution (LOP) and Asian dust storm (ADS) were observed in this study. The results revealed that relative high concentrations of secondary aerosols (NO₃⁻, SO₄²⁻ and NH₄⁺) and the elements Cu, Zn, Cd, Pb and As were observed in PM_2.5 during LOP periods. However, sea salt species (Na⁺ and Cl⁻) and crustal elements (e.g., Al, Fe, Mg, K, Ca and Ti) of PM_2.5–10 showed a sharp increase during ADS periods. Anthropogenic source metals, Cu, Zn, Cd, Pb and As, as well as coarse nitrate also increased with ADS episodes. Moreover, reconstruction of aerosol compositions revealed that soil of PM_2.5–10 elevated approximately 12–14% in ADS periods than LOP and Clear periods. A significantly high ratio of non-sea salt sulfate to elemental carbon (NSS-SO₄²⁻/EC) of PM_2.5–10 during ADS periods was associated with higher concentrations of non-sea-salt sulfates from the industrial regions of China. Source apportionment analysis showed that 39% of PM₁₀, 25% of PM_2.5, 50% of PM_2.5–10, 42% of sulfate and 30% of nitrate were attributable to the long range transport during ADS periods, respectively.     

Composition and major sources of organic compounds in urban aerosols

Total suspended particles (TSP), collected during June 2002 to July 2003 in Guangzhou, a typical economically developed city in South China, were analyzed for the organic compound compositions using gas chromatography–mass spectrometry (GC/MS). Over 140 organic compounds were detected in the aerosols and grouped into different classes including n-alkanes, hopanoids, polycyclic aromatic hydrocarbons, alkanols, fatty acids, dicarboxylic acids excluding oxalic acid, polyols/polyacids, lignin products, phytosterols, phthalates and water-soluble sugars. The total amounts of the identified organic compounds including unresolved complex mixture (UCM) ranged from 3112 ng/m³ in spring to 5116 ng/m³ in winter, comprising on seasonal average 2.8% of TSP. Primary organic compounds peaked in winter although there are no heating systems burning fuels in Guangzhou. The highest saccharide levels occurred in fall due to agricultural activities. This study demonstrated that utilization of fossil fuels, biomass burning, soil resuspension and plastic/refuse burning are the major contributors to the identified organic compounds in the urban atmosphere of South China.     

京津冀地区霾成因机制研究进展与展望

为满足当前对京津冀地区霾研究和控制的迫切要求,本文梳理了近年来京津冀地区霾的长期变化特征、天气学特征、污染物来源等相关研究成果,发现:从2000年以后,京津冀地区的霾日数呈现出了下降趋势;北京细颗粒物(PM2.5)质量浓度也在总体上呈现下降的趋势,但2013年年均质量浓度仍高达89.5μg m–3,约为我国空气质量标准的3倍(35μg m–3),京津冀空气污染的形势依然严峻;近年来京津冀地区的霾污染事件频发可以归因为不利天气条件与大量污染物人为排放的共同作用;大量的研究表明,区域输送对京津冀地区霾事件的形成和维持有不可忽视的影响;京津冀地区的大气污染不再局限于一时一地,针对重污染天气的预警以及应急控制应该以区域预报为基础实现区域联动;京津冀地区独特的地理环境条件加上城市群的快速发展,形成的局地大气环流也会对局地的污染过程产生重大的影响;大气边界层内气象要素的变化对重污染发生具有显著贡献。京津冀地区的污染控制需要城市群的联动应对治理。     

南京市PM2.5物理化学特性及来源解析

在夏、冬两季,分别在南京市4个站点进行为期7天的气溶胶PM2.5采样,同步采集并分离主要排放源的PM2.5样品,用X射线荧光光谱仪(XRF)分析得到气样及源样中PM2.5的化学成分,对南京市PM2.5的物理化学特性、富集因子进行了分析,并应用化学质量平衡法(CMB)计算各类源对气溶胶PM2.5的贡献。结果表明,南京市PM2.5的夏、冬平均值分别为69.1、139.5μg.m-3,PM2.5/PM10的全年平均值为63.9%;富集成分中,S、As、Zn、Pb等主要来源于人为污染源,Na则主要来源于海洋。来源解析的结果表明,各类污染源对南京市气溶胶PM2.5的贡献率分别为:扬尘37.28%、煤烟尘30.34%、硫酸盐9.87%、建筑尘7.95%、汽车尘2.98%、冶炼尘2.57%、其他源9.01%。作者还对扬尘中的PM2.5进行了来源解析。     

南京北郊气溶胶中多环芳烃的污染特征及来源解析

利用2010年8月采集的南京北郊气溶胶样品,使用GC-MS对美国环保总局推荐的16种优先控制的多环芳烃含量、分布特征进行了研究。在此基础上,用特征比值法、主因子分析法分析得到南京市北郊大气中PAHs的主要来源为车辆尾气、燃煤、天然气和草木秸秆燃烧,并应用绝对因子分析法进一步定量计算主要源对PAHs的浓度贡献率。结果表明:1)大气颗粒物中16种多环芳烃的平均总质量浓度为135.85 ng/m~3,多环芳烃以4环为主,在可吸入颗粒物中的浓度占总浓度的88.7%;2)PM10中多环芳烃呈双模态分布,在9~10μm的粗模态和0.65~1.10μm的积聚模态上各出现一个峰值;3)天然气等对PAHs的贡献率为5.7%~44.1%,燃煤源的贡献率为20.7%~57.8%,汽车尾气的贡献率为4.6%~46.7%,木材燃烧的贡献率为2.9%~38.1%。本地交通排放和燃料燃烧是南京北郊大气颗粒物中PAHs的主要来源,远距离输送也对南京北郊气溶胶中的PAHs有重要贡献。     

乌江磷浓度与通量变化及来源解析

磷(P)是长江流域备受关注的污染物。乌江是长江八大支流之一,位于三峡水库近库尾江段。武隆断面是乌江入长江控制断面。对1998—2019时期武隆断面径流量、悬浮泥沙浓度(SS)与输沙量、磷浓度与通量(包括总磷(TP)、溶解态磷(DP)和颗粒态磷(PP))年际变化及季节特征进行研究,并基于河流基流分割原理对磷的来源进行了解析。结果表明,(1)1998—2019年,乌江武隆断面径流量在一定幅度内上下波动,而悬浮泥沙浓度和输沙量下降剧烈。(2)22年来,乌江TP和DP浓度与通量总体上呈先升高后下降的趋势,2009—2013年为磷污染峰值期,TP和DP浓度与通量远高于其它时期。(3)2007年是一个重要的时间节点,该节点前,TP的赋存形态以颗粒态为主,颗粒态磷在总磷中的占比均值为65%;该节点后,TP的赋存形态转变为以溶解态为主,颗粒态磷占比均值下降为16%,相应地,溶解态磷占比由35%上升为84%。水沙条件改变是磷形态发生显著变化的主要驱动力,磷污染程度亦是磷形态变化的重要影响因素。(4)磷通量在年内的季节分布发生了显著变化,丰水期磷通量减少,枯水期磷通量增加。(5)1998—2012、2009—2013和2014—2019年3个时期点源负荷占比分别为23.5%、36.8%和62.1%,呈增加趋势。(6)建议制定适宜的总磷控制目标,结合目前所存在的磷污染风险点,进一步强化监管,侧重源头治理。