Locating pollutant emission sources with optical remote sensing measurements and an improved one-dimensional radial plume mapping technique

Previous studies have shown that there was a relatively large amount of uncertainty along the major wind direction in the results of locating emission sources using the one-dimensional radial plume mapping (RPM(1D)) technique based on optical remote sensing measurements. This paper proposes setting up an additional monitoring line that is perpendicular to the original scanning beam geometry to reduce this uncertainty. We first conducted a computer simulation study using the Gaussian dispersion model to generate the downwind concentrations of plumes from 400 source locations in a 201 m × 201 m spatial domain under various wind directions (n = 181). The optical remote sensing instrument was assumed to be at (0, 0) with two perpendicular monitoring lines, each of which had three beam segments of equal length. Each pair of the reconstructed downwind concentration profiles was then used to trace back to the source locations. The results showed that the accuracy of the method and its uncertainty were improved by using the proposed two-line RPM(1D) approach rather than the original one-line RPM(1D) approach at most simulated source locations. In a follow-up field experiment, a tracer gas was released at the coordinate of (100, 100). The release location was covered within the 0.25- to 0.5-probability area of the estimated results, and the distance between the actual and estimated source locations was 18.4 m (9.2% of the longest beam path).     

盲样考核浓度预判及稀释方法——以原子荧光法测定水中砷为例

以原子荧光法测定水中砷为例,探讨了实验室盲样考核浓度预判及稀释方法.分析了3个砷盲样考核实例,归纳了“直接稀释法”“系列稀释法”“最大稀释法”3种方法,分别适用于盲样浓度范围窄、适中、宽3种情况,检测人员可根据考核机构给定的浓度范围合理选用.     

The backend design of an environmental monitoring system upon real-time prediction of groundwater level fluctuation under the hillslope

The groundwater level represents a critical factor to evaluate hillside landslides. A monitoring system upon the real-time prediction platform with online analytical functions is important to forecast the groundwater level due to instantaneously monitored data when the heavy precipitation raises the groundwater level under the hillslope and causes instability. This study is to design the backend of an environmental monitoring system with efficient algorithms for machine learning and knowledge bank for the groundwater level fluctuation prediction. A Web-based platform upon the model-view controller-based architecture is established with technology of Web services and engineering data warehouse to support online analytical process and feedback risk assessment parameters for real-time prediction. The proposed system incorporates models of hydrological computation, machine learning, Web services, and online prediction to satisfy varieties of risk assessment requirements and approaches of hazard prevention. The rainfall data monitored from the potential landslide area at Lu-Shan, Nantou and Li-Shan, Taichung, in Taiwan, are applied to examine the system design.     

Chemical forms and ecological risk of arsenic in the sediment of the Daliao River System in China

The chemical forms and ecological risk of As were characterized in the sediment of the Daliao River System (DRS), which has been affected by long-term intensive industrial, urban, and agricultural activities. Twenty-seven samples of surface sediment were collected and analyzed for total As content and that of its chemical forms. The results indicated that the average total As content in the sediment was 9.83 mg kg^− 1 but that the levels ranged from 1.57 to 83.09 mg kg^− 1. At the sites near cities, mining sites, and the estuary of the DRS, it is likely that adverse effects on aquatic organisms occur, due to As levels in the sediment that are often higher than the threshold effect level and occasionally higher than the probable effect level. A selectively sequential extraction indicated that the majority of As in the sediment was bound to Fe oxides (62.1%), with moderate proportions of residual As (19.8%), specifically adsorbed As (17.9%), and a low proportion of non-specifically adsorbed As (1.1%). In addition, the content of Fe in the sediment was positively and significantly correlated with the contents of amorphous and crystalline Fe oxide-bound As, confirming the crucial role of Fe oxides in immobilizing high amounts of As in superficial environments. The average molar ratio of As to Fe was 1.18 × 10^− 4 in the surface sediment of the DRS, similar to that of natural Fe oxides, but much lower than that of synthesized Schwertmannite. Therefore, the release of As under reduced and low pH conditions can cause serious problems for water resources and for living organisms.     

钢铁企业大型低位料仓汽车卸料的粉尘控制

某钢企大型低位料仓为汽车卸料,料仓厂房内空高,跨度大,料仓上部贯通,物料落差大,卸料中产生大量粉尘,环境污染问题典型突出。通过对低位料仓汽车卸料产尘特性分析,采取加强生产管理、组织汽车有序卸料、料仓厂房有效密闭、合理设计捕尘方式和布袋除尘系统等措施,能够有效地控制粉尘污染。除尘系统具有投资及运行费用少,除尘效果明显的优点。     

蔬菜常用农药在地下水中残留风险评估

为明确蔬菜常用农药在地下水中的环境风险,运用China-Pearl和SCI-GROW模型开展地下水环境暴露评估,并根据我国成人和儿童暴露参数推导25种农药预测无效应浓度(PNEC)。研究发现,25种农药PECgw为0~18.340μg·L-1,成年人PNECgw为0.003~19.654 mg·L-1,儿童PNECgw为0.001~23.253 mg·L-1。成年人和儿童的RQgw值均小于1,表明25种农药按照登记用量使用,我国成人和各年龄阶段儿童直接饮用施用农药区域地下水的环境风险可接受。     

农药环境风险评估中常用的计算毒理学模型软件

农药的大量使用为我国带来了严重的环境和健康问题,仅依靠传统生物测试和环境监测的方法已经不能满足农药风险评估的需要。利用计算毒理学模型,可以实现农药的高通量风险评估。本文主要介绍了农药环境风险评估中常用免费的EPI Suite、QSAR Toolbox和PBT Profiler等定量结构-活性关系(Quantitative Structure-Activity Relationship,QSAR)模型软件和SCIGROW、PRZM-GW、China-PEARL和EQC等环境多介质模型软件,以期能为农药的风险评估和科学管理提供参考。     

The use of ultrasound-assisted anaerobic compost tea washing to remove poly-chlorinated dibenzo-p-dioxins (PCDDs), dibenzo-furans (PCDFs) from highly contaminated field soils

The remediation of dioxin-contaminated soil of a specific coastal area previously employed for the manufacture of pentachlorophenol (PCP) in southern Taiwan’s Tainan City has attracted much attention of researchers there. This work addresses the possibility of providing an effective and environmentally friendly option for removing PCDD/Fs from soil in that field. Soil screening/sieving was first conducted to assess particle distribution. Fine sand was observed to be the major component of the soil, accounting for more than 60% of the total mass. A combination of ultrasonification and mechanical double-blade agitation was used to facilitate the washing of the soil using the biosurfactant anaerobic compost tea. More than 85 and 95% of total removal efficiencies were achieved for moderately and highly contaminated soils after 6 and 10 washing cycles, respectively, under ambient temperature, a soil/liquid ratio 1:2.5, 700 rpm, and over a relatively short duration. These results were achieved through the collision and penetration effects of this combined treatment as well as PCDD/F partitioning between the particles and anaerobic compost tea. This study represents the first to report the use of anaerobic compost tea solvent to wash soil highly contaminated by dioxin. It was concluded that anaerobic compost tea, rich in non-toxic bio-surfactants (e.g., alcohols, humic acids), can be used to improve bioavailability and bioactivity of the soil making bio-attenuation and full remediation more efficient.     

Effects of fine particulate matter and its constituents on emergency room visits for asthma in southern Taiwan during 2008–2010: a population-based study

Environmental Science and Pollution Research - This population-based study evaluated the short-term association between fine particulate matter (PM2.5) concentrations and its constituents and...