Development of the Spatial Rainfall Generator (SRGEN) for the Agricultural Policy/Environmental Extender Model

Accurate spatial representation of climatic patterns is often a challenge in modeling biophysical processes at the watershed scale, especially where the representation of a spatial gradient in rainfall is not sufficiently captured by the number of weather stations. The spatial rainfall generator (SRGEN) is developed as an extension of the “weather generator” (WXGEN), a component of the Agricultural Policy/Environmental eXtender (APEX) model. SRGEN generates spatially distributed daily rainfall using monthly weather statistics available at multiple locations in a watershed. The spatial rainfall generator as incorporated in APEX is tested on the Cowhouse watershed (1,178 km²) in central Texas. The watershed presented a significant spatial rainfall gradient of 2.9 mm/km in the lateral (north‐south) directions based on four rainfall gages. A comparative analysis between SRGEN and WXGEN indicates that SRGEN performs well (PBIAS = 2.40%). Good results were obtained from APEX for streamflow (NSE = 0.99, PBIAS = 8.34%) and NO₃‐N and soluble P loads (PBIAS ≈ 6.00% for each, respectively). However, APEX underpredicted sediment yield and organic N and P loads (PBIAS: 24.75‐27.90%) with SRGEN, although its uncertainty in output was lower than WXGEN results (PBIAS: ?13.02 to ?46.13%). The overall improvement achieved in rainfall generation by SRGEN is demonstrated to be effective in the improving model performance on flow and water quality output.     

Auto-adaptive Air Distribution and Structure Optimization of Ejector Burner for Biomass Alcohol Fuels

A plenty of studies on the utilization of biomass alcohol fuels have been conducted, but combustion efficiency and stability of this fuels still need to be improved. Based on biomass alcohol fuels (bio-methanol and bio-ethanol), this paper studied auto-adaptive air distribution characteristics and optimum structure parameters of an ejector burner by numerical simulation method. Also, an experiment was conducted to verify the numerical results. The results show that the mole air entrainment ratio (MAER) keeps almost constant when the ejector fuel nozzle exit locates at the segment between the ejector throat and the suction chamber entrance, but a bigger ratio α would lead to a higher MAER till the α is bigger than 8.5 for bio-methanol and 11.5 for bio-ethanol. The bio-ethanol fuel is more beneficial for air carrying role because of its big molecular weight. Operation pressure (P_w) has a little impact on MAER of the two fuels, but the rise of back pressure (P_b) would lead to rapid decrease of MAER for the two fuels. For the optimum structure burners, the MAER can be maintained at the value of theoretical complete combustion. Its changing rate is less than 2.3% for bio-methanol and 2.5% for bio-ethanol when the burner load changes from 30% to 120%, which is highly consistent with the experimental results. The optimum burner can distribute air supply automatically with the changing of burner load.     

胎盘内多环芳烃分布及源解析研究

探讨多环芳烃在胎盘中的分布,并对其进行源解析。从2012年6月—2013年6月在云南省第一人民医院产科分娩的产妇中随机抽取30例,利用气相色谱-质谱联用仪(GC-MS)检测其胎盘中多环芳烃的含量;比较胎盘的中央部分和边缘部分多环芳烃含量的差异;对多环芳烃进行源解析,探讨其主要来源。胎盘中检测到多种多环芳烃成分;其中2~4个苯环的多环芳烃占总量的90%以上,尤其是萘、苊、芴、菲、蒽、芘、荧蒽的含量较高;萘、苊烯、苊、茚并(1,2,3-c,d)芘、二苯并(a,h)蒽5种多环芳烃在胎盘中央的含量高于边缘,具有显著性差异(P0.05),其他多环芳烃在胎盘中央和边缘的含量无显著性差异(P0.05)。多环芳烃源解析提示80%研究对象体内的多环芳烃主要来自石油产品的燃烧或暴露于石油产品。     

应用概率物种敏感度分布法研究太湖重金属水生生物水质基准

目前广泛使用的水质基准推导方法—物种敏感度分布法存在曲线拟合模型不确定、曲线拟合效果不佳、种内差异欠考虑、基准值不准确等诸多问题,概率物种敏感度分布法可有效解决上述问题。应用概率物种敏感度分布法构建了太湖水体中5种重金属Ag、Pb、Cd、Hg和Zn的概率物种敏感度分布曲线,在此基础上得到了保护水生生物的急性水质基准分别为1.079μg·L~(-1)、637.973μg·L~(-1)、19.465μg·L~(-1)、8.729μg·L~(-1)和105.506μg·L~(-1),慢性水质基准分别为0.108μg·L~(-1)、63.797μg·L~(-1)、1.947μg·L~(-1)、2.340μg·L~(-1)和52.753μg·L~(-1);不同类群间生物对重金属的敏感度存在差异,不同重金属对同一类群生物的毒性也存在差异;通过与国内外已有的重金属水质基准值比较,发现水质基准具有明显的区域性,目前基于国外水质基准或我国整体水域特点来制定的太湖水质标准,往往造成对太湖水生生物欠保护或过保护的状况。     

PBDEs的来源特征、环境分布及污染控制

多溴联苯醚(Polybrominated diphenyl ethers,PBDEs)生产应用、环境分布与生态风险之间的关系将如何影响我国的未来,具体涉及到工业、环境、健康、人类繁衍等的社会问题.由于PBDEs阻燃效率高,热稳定性好,价格便宜,作为添加剂被广泛应用在电子、电器、化工、交通、建材、纺织、石油等领域的阻燃产品中.PBDEs进入环境后迁移扩散并富集于沉积物和生物体内,进入人体后引起肝脏毒性、内分泌干扰、神经毒性和生育能力下降等而危害人类的健康.基于此,从生产应用、品种生产量、分子的物理化学特性以及毒性等的文献数据分析了PBDEs的来源特征与环境危害,分析这些性质对环境分布与污染控制的基础支持关系;从沉积物、水体、大气、水生生物、人体5个方面考察了PBDEs的环境本底浓度变化、分配关系、迁移规律、时间效应,分析了生产、应用与扩散的多因素影响关系,发现全球性PBDEs污染物蔓延的现象,沉积物是主要的归趋场所,室内空气中的浓度远高于室外,水中浓度较低,水生生物和人体均能富集PBDEs,通过饮食、母乳和呼吸摄入,可实现代际传播,污染的分布呈现介质与区域的不同特征;污染控制需要考虑点源技术与面源修复的联合,结合PBDEs的物理性质、分子结构及其化学特性,统计分析了微生物法、光化学降解法和零价铁还原法的原理及其有效性,根据PBDEs在产品中存在与分布的特点,提出收集-分离-富集-超临界催化还原和氧化毁毒的工艺,针对实际环境(以电子垃圾塑料和流域水体及沉积物为对象)中的PBDEs进行回收或处理,结合材料如催化剂的应用,从动力学和热力学方面提高PBDEs无害化的效率.最后,从生产管理、环境监测、风险评价、技术集成等方面提出了未来的努力方向.     

Pollution levels and characteristics of phthalate esters in indoor air of offices

The pollution status and characteristics of PAEs (phthalate esters) were investigated in indoor air of offices, and PAEs of both gas-phase and particulate-phase were detected in all the samples. The concentration (sum of the gas phase and the particulate phase) was 4748.24 ng/m³, ranging between 3070.09 and 6700.14 ng/m³. Diethyl phthalate, dibutyl phthalate, and di(2-ethylhexyl) phthalate were the most abundant compounds, together accounting for 70% of the Σ6PAEs. Dividing the particulate-phase PAEs into four size ranges (<2.5, 2.5-5, 5-10, >10 μm), the result indicated that PAEs in PM_2.5 were the most abundant, with the proportion of 72.64%. In addition, the PAE concentration in PM_2.5 correlated significantly with the total particulate-phase PAEs (R² = 0.85). Thus, the amount of PAEs in PM_2.5 can be estimated from the total amount of particulate-phase PAEs using this proportion. In a comparison between the offices and a newly decorated study room, it was found that pollution characteristics were similar between these two places. Thus, it is implied that the PAE concentration decreased by 50% 2 yr after decorating.     

Pollution levels and characteristics of phthalate esters in indoor air of offices

The pollution status and characteristics of PAEs(phthalate esters) were investigated in indoor air of offices, and PAEs of both gas-phase and particulate-phase were detected in all the samples. The concentration(sum of the gas phase and the particulate phase) was4748.24 ng/m3, ranging between 3070.09 and 6700.14 ng/m3. Diethyl phthalate, dibutyl phthalate, and di(2-ethylhexyl) phthalate were the most abundant compounds, together accounting for 70% of the ∑ 6PAEs. Dividing the particulate-phase PAEs into four size ranges( 2.5, 2.5–5, 5–10, 10 μm), the result indicated that PAEs in PM2.5were the most abundant,with the proportion of 72.64%. In addition, the PAE concentration in PM2.5correlated significantly with the total particulate-phase PAEs(R2= 0.85). Thus, the amount of PAEs in PM2.5can be estimated from the total amount of particulate-phase PAEs using this proportion. In a comparison between the offices and a newly decorated study room, it was found that pollution characteristics were similar between these two places. Thus, it is implied that the PAE concentration decreased by 50% 2 yr after decorating.     

东江流域表层土中全氟化合物的空间分布及来源解析

为探究东江流域土壤中全氟化合物(perfluorinated compounds,PFCs)分布特征和潜在来源,2013年8月采集东江流域19份表层土样品,利用高效液相色谱-串联质谱联用(HPLC-MS/MS)技术分析了16种PFCs的含量。结果表明,东江流域表层土总PFCs(∑PFCs)含量范围在2.15~5.49μg/kg dw。所采集的表层土样品中,东江东莞段土壤∑PFCs含量明显高于惠州段,全氟辛烷磺酸(0.65~1.28μg/kg dw)为最主要的污染物。与国内相关研究数据相比,东江流域土壤PFCs含量水平整体较高,这可能与流域产业结构和经济活动有关。主成分分析结果表明,电镀防雾剂、食品包装和全氟羧酸的生产过程、大气沉降、电化学氟化过程为东江流域土壤中PFCs的主要来源。与土壤有机质含量相关性研究表明,PFCs更容易分配到有机质含量高的土壤中,且随着PFCs分子碳链的增加,这种趋势更加显著。     

某农药厂废弃场地土壤中甲拌磷垂向分布特征

为了解废弃农药厂土壤中甲拌磷的垂向分布特征,在前期表层土壤筛查的基础上,进一步在原甲拌磷生产车间开展了钻孔取样工作,布置了3个钻孔,钻孔深度43.0、41.0和45.0m,根据土壤颜色、岩性、电导率和pH的变化,共采集土壤样品39个,利用高效液相色谱仪对土壤中的甲拌磷进行了定量分析,同时测试了总有机碳、阳离子交换量、土壤粘粒含量、土壤含水率和温度等土壤的理化性质参数。测试结果显示,甲拌磷主要富集在表层土壤中,随着深度的增加,甲拌磷含量逐渐降低。根据相关性分析,土壤中甲拌磷含量和总有机碳含量有着显著的相关性,R分别为0.767、0.893和0.917,这表明土壤总有机碳含量对甲拌磷垂向分布有着非常重要的影响。     

鄱阳湖及周边经济区土壤镉的含量与分布

采用双层网格布点法,在研究区分别采集表层和深层土壤样品9829和2467个,测定了样品的镉含量和pH值。表层土壤镉含量呈对数正态分布,含镉范围0.024~4.619mg/kg,宜用几何平均值0.157mg/kg表征其平均含量。深层土壤镉含量显著低于表层,含量范围0.010~1.982mg/kg,算术平均值和几何平均值分别为0.098mg/kg和0.080mg/kg。研究区7地市表层土壤镉含量几何平均值较30年前上升34.6%~165%。据《土壤环境质量标准GB15618-1995》,以镉为评价指标时,研究区以Ⅰ类土壤为主,分布面积占总面积的78.36%,次为Ⅱ类土壤、分布面积占总面积的15.92%,Ⅲ类和劣Ⅲ类土壤仅占总面积的5.72%,显示土壤环境质量良好,但仍须采取有效措施遏制镉污染的迅猛发展。