基于BP神经网络的北京城区公园土壤PAHs含量预测

城市公园是城市生态环境的重要组成部分,其环境质量与人类健康息息相关.选择北京市121个城区公园,采集公园土壤样品并分析其中7种多环芳烃（PAHs）含量,评价城区公园土壤中PAHs的含量水平,并基于BP神经网络预测了2020年和2023年土壤PAHs含量.结果表明:北京城区公园土壤中w（PAHs）（7种PAHs总含量）范围为0.033~4.182 mg/kg,低于GB 36600—2018《土壤环境质量建设用地土壤污染风险管控标准（试行）》土壤污染风险筛选值,且7种PAHs的毒性当量浓度（TEQ）均低于世界卫生组织标准值（1 mg/kg）,对人体健康的毒性风险较小.将14个影响指标（8个社会经济因子与6个公园特征因子）作为输入层、土壤w（PAHs）作为输出层,建立BP神经网络的拟合优度达0.845.预测结果显示,2020年和2023年北京城区公园土壤中w（PAHs）范围分别为0.008~0.969 mg/kg和0.022~1.988 mg/kg,整体均低于GB 36600—2018土壤污染风险筛选值,但随时间推移呈上升趋势,尤其朝阳区和海淀区将有大幅增长.研究显示:城市化发展因素对土壤w（PAHs）的增加有明显影响,城市发展进程影响不容忽视;至2023年,北京城区公园土壤若不加管理,其w（PAHs）将持续增长.      

Risk assessment of xenoestrogens in a typical domestic sewage-holding lake in China

Release of domestic sewage leads to accumulation of xenoestrogens in holding waters, especially in closed or semi-enclosed waters such as lakes. In the study, the occurrence, distribution, estrogenic activity and risk of eight xenoestreogens were evaluated in Lake Donghu, China. Nonylphenol (NP), octylphenol (OP), and bisphenol A (BPA) were identified as the main xenoestrogens ranging from tens of ng L⁻¹ (in the surface water) or ng g⁻¹ dw (in the suspended particles and sediment) to tens of μg L⁻¹ or μg g⁻¹ dw. The sum of 17β-estradiol equivalents (∑EEQs) ranged from 0.32 to 45.02 ng L⁻¹ in the surface water, 0.53 to 71.86 ng g⁻¹ dw in the suspended particles, and 0.09 to 24.73 ng g⁻¹ dw in the sediment. Diethylstilbestrol (DES) was determined as the main contributor to ∑EEQs followed by NP. The risk assessment showed a higher risk in the surface water than in the suspended particles and sediment in such domestic sewage-holding lake.     

基于熵权理论的室内环境评价

以室内环境的空气品质以及声、光、热环境为研究对象,根据实测数据,建立不满意百分比指标PD(predicteddissatisfied),基于熵权理论对整个室内环境进行评价。在多因素的室内环境评价过程中,该方法在以实测数据确定评价指标的相对重要程度后,根据各评价对象之间某些评价指标重要度的差异,自动调节各种差异对评价过程的影响,合理的优化了评价过程。以某小区6户人家家庭环境的物理、化学因素测试的数据进行综合评价,其结果与实际情况相吻合。说明该方法所得到的评价结果具有说服力。     

基于我国物种毒性数据的多溴联苯醚预测无效应浓度分析

采用多溴联苯醚(PBDEs)对我国广泛分布生物物种的生态毒性数据,根据欧盟现有化学物质风险评价技术指导文件,对不同环境介质中PBDEs预测无效应浓度(PNEC)进行了推导。结果表明:我国淡水环境PBDEs(四溴、五溴、八溴)的PNEC水分别为50μg·L~(-1)、0.53μg·L~(-1)、0.017μg·L~(-1)。沉积物环境PBDEs(四溴、五溴、八溴和十溴)的PNEC沉积物分别为823.35 mg·kg~(-1)wt、1.55 mg·kg~(-1)dw、12.72 mg·kg~(-1)dw、38.41 mg·kg~(-1)dw。土壤环境PBDEs(四溴、五溴、八溴和十溴)的PNEC土壤分别为668.3mg·kg~(-1)wt、0.38 mg·kg~(-1)dw、147 mg·kg~(-1)dw、98 mg·kg~(-1)dw。次生毒性PBDEs(五溴、八溴和十溴)的PNEC经口分别为0.3~0.7 mg·kg~(-1)、0.56 mg·kg~(-1)、2 500 mg·kg~(-1)。该数值期为我国PBDEs的环境风险评价提供科学基础。     

水稻土中外源Cd老化的动力学特征与老化因子

选择5种不同性质的水稻土,通过外源添加制备了6个不同浓度梯度的Cd污染土壤,研究了外源Cd在几种水稻土中的老化动力学特征与影响因子;同时利用盆栽实验,结合Log-logistic分布模型,研究了5个不同老化时间(14、30、60、90和180d)与土壤中Cd对二种不同Cd敏感性水稻生长毒性的影响.结果表明,不同浓度外源Cd进入土壤后,0.05mol/L EDTA-2Na浸提的有效态Cd含量随着老化时间的增加而逐渐下降;与14d处理相比,老化30d后土壤中有效态Cd降幅达21.5%(红壤)~38.0%(黑土);老化90d后,土壤中Cd进入慢反应阶段. 基于二级动力学方程的拟合参数显示,土壤中Cd的老化特征表现为有效态Cd含量在30~60d内快速降低,随后变化减缓,经过90d的老化后,土壤中有效态Cd含量逐渐趋于平衡.基于老化动力学方程参数(C∞及K2)与土壤性质间的相关性分析表明,土壤pH值是影响Cd有效态含量变化的主控因子,其次是土壤CEC和OC含量.在不同性质土壤中,随着老化时间的增加,土壤中外源Cd对水稻生长毒性的半抑制浓度(EC50)值显著升高;与14d老化处理相比,经过180d老化后土壤中Cd对水稻生长毒性的EC50增加72.1%~195.0%;在大于90d的长期老化过程中,土壤pH值对Cd老化过程的影响逐渐降低,而CEC的影响逐渐上升,尽管如此,土壤中Cd老化过程的主要影响因子仍然是土壤pH,而与测试的2种水稻品种无关.     

海南地区新型雷电预警系统预警效率的评估与分析

基于2017年5-8月全国雷电监测定位系统ADTD探测到的闪电定位数据,根据标准IEC-62793中对雷电预警系统预警效率评估的定义,对海南地区部分雷电预警站点的预警效率进行了统计分析。海南地区新型雷电预警系统的平均有效预警率(MPOD)约为85%,高于大部分雷电预警系统的有效预警率;对闪电事件的预警率平均可达到95%,表明可以对发生在预警站点有效覆盖范围内95>的闪电提供有效预警;平均错误预警率(MFAR)约为73%,与各类预警系统相比,错误预警率偏高;预警提前期的平均值和中值分别为13.9min和9.6min。     

Using Niche-Based Models to Improve the Sampling of Rare Species

Abstract:  Because data on rare species usually are sparse, it is important to have efficient ways to sample additional data. Traditional sampling approaches are of limited value for rare species because a very large proportion of randomly chosen sampling sites are unlikely to shelter the species. For these species, spatial predictions from niche-based distribution models can be used to stratify the sampling and increase sampling efficiency. New data sampled are then used to improve the initial model. Applying this approach repeatedly is an adaptive process that may allow increasing the number of new occurrences found. We illustrate the approach with a case study of a rare and endangered plant species in Switzerland and a simulation experiment. Our field survey confirmed that the method helps in the discovery of new populations of the target species in remote areas where the predicted habitat suitability is high. In our simulations the model-based approach provided a significant improvement (by a factor of 1.8 to 4 times, depending on the measure) over simple random sampling. In terms of cost this approach may save up to 70% of the time spent in the field.     

Pharmaceuticals and personal care products found in the Great Lakes above concentrations of environmental concern

The monitoring of pharmaceuticals and personal care products (PPCPs) has focused on the distribution in rivers and small lakes, but data regarding their occurrence and effects in large lake systems, such as the Great Lakes, are sparse. Wastewater treatment processes have not been optimized to remove influent PPCPs and are a major source of PPCPs in the environment. Furthermore, PPCPs are not currently regulated in wastewater effluent. In this experiment we evaluated the concentration, and corresponding risk, of PPCPs from a wastewater effluent source at varying distances in Lake Michigan. Fifty-four PPCPs and hormones were assessed on six different dates over a two-year period from surface water and sediment samples up to 3.2 km from a wastewater treatment plant and at two sites within a harbor. Thirty-two PPCPs were detected in Lake Michigan and 30 were detected in the sediment, with numerous PPCPs being detected up to 3.2 km away from the shoreline. The most frequently detected PPCPs in Lake Michigan were metformin, caffeine, sulfamethoxazole, and triclosan. To determine the ecological risk, the maximum measured environmental concentrations were compared to the predicted no-effect concentration and 14 PPCPs were found to be of medium or high ecological risk. The environmental risk of PPCPs in large lake systems, such as the Great Lakes, has been questioned due to high dilution; however, the concentrations found in this study, and their corresponding risk quotient, indicate a significant threat by PPCPs to the health of the Great Lakes, particularly near shore organisms.