鸭绿江（丹东段）江水中未知有机污染物分析鉴定与有毒有机物名录筛选

采用美国惠普公司MC/GS联用仪,对鸭绿江（丹东段）江水中有机污染物种类、组成进行了分析鉴定,进而采用高压液相色谱法对多环芳烃类进行定量测定与评价,进行了该江段有毒有机物名录筛选,提出由27种有毒有机污染物组成的名单。     

污水土地处理CAD系统设计

针对污水土地处理设计实际,以提高设计速度和质量为目标,结合计算机辅助设计技术和软件技术的发展,采用成熟而先进的参数化设计技术及ADS开发工具,对土地处理设计中的几个关系问题进行了探讨。     

地表水水质自动监测数据技术评估

对地表水水质自动监测站取水口直接采样和模拟水样,用自动监测和实验室方法监测相应的指标,对两者的监测结果进行比较,研究和分析两者之间差异的原因,评估自动监测数据,提出建议。     

水环境监测信息集成、共享与决策支持平台构建

以水环境监测数据可靠传输交换与集成、信息规范化处理分析、高效共享与决策支持为应用主线,对水环境监测信息集成、共享与决策支持平台的建设目标、总体架构、主要功能进行了研究,设计了平台的总体架构及主要功能,以实现涉水部门水环境信息的采集、传输、交换、存储、分析、发布、共享、展现等,为环境管理与决策人员、为公众、为各级(国家级流域级省级地市级县级)环境监测业务人员提供信息支撑。     

大数据解析技术在大气环境监测中的应用研究

针对近年来新兴的大数据及挖掘、分析技术,对大数据解析技术在环境科学研究中的应用进行了分析和探析。以城市局部地区大气细颗粒污染物PM2.5浓度计算为例,筛选了PM2.5浓度历史数据、气象条件、交通状况、人群活动情况、网格道路状况等数据为影响特征量,分析了用神经网络法进行大数据解析和推演的原理和数学过程,是用数学、计算机、统计等方法研究解决多元、非线性复杂环境问题的一种新的探索。     

Application of statistical modeling to optimize a coastal water quality monitoring program

The long-term water quality monitoring program implemented by the Massachusetts Water Resources Authority in 1992 is extensive and has provide substantial understanding of the seasonality of the waters in both Boston Harbor and Massachusetts Bay and the response to improvements in effluent quality and offshore transfer of the effluent in September 2000. The monitoring program was designed with limited knowledge of spatial and temporal variability and long-term trends within the system. This led to an extensive spatial and temporal sampling program. The data through 2003 showed high correlation within physical parameters measured (e.g., salinity, dissolved oxygen) and in biological measures such as chlorophyll fluorescence. To address the potential sampling redundancies in the measurement program, an assessment of the impact of reduced levels of monitoring on the ability to make water quality decisions was completed. The optimization was conducted by applying statistical models that took into account whether there was evidence of a seasonal pattern in the data. The optimization used model survey average readings to identify temporal fixed effects, model survey-average-corrected individual station readings to identify spatial fixed effects, corrected the individual station readings for temporal and spatial fixed effects and derived a correlation model for the corrected data, and applied the correlation model to characterize the correlation of annual average readings from reduced monitoring programs with true parameter levels. Reductions in the number of sampling stations were found less detrimental to the quality of the data for annual decision-making than reductions in the number of surveys per year, although there is less of a difference in this regard for dissolved oxygen than there is for chlorophyll. The analysis led to recommendations for a substantially lower monitoring effort with minimal loss of information. The recommendation supported an annual budget savings of approximately $183,000. Most of the savings was from fewer surveys as approximately $21,000 came from the reduction in the number of stations monitored from 21 to 7 and associated laboratory analytical costs.     

Artificial neural network based carbon monoxide persistence models for episodic urban air quality management

This paper describes the development of artificial neural network (ANN) based carbon monoxide (CO) persistence (ANNCOP) models to forecast 8-h average CO concentration using 1-h maximum predicted CO data for the critical (winter) period (November–March). The models have been developed for three 8-h groupings of 10 p.m. to 6 a.m., 6 a.m. to 2 p.m. and 2–10 p.m., at two air quality control regions (AQCRs) in Delhi city, representing an urban intersection and an arterial road consisting heterogeneous traffic flows. The result indicates that time grouping of 2–10 pm is dominantly affected by inversion conditions and peak traffic flow. The ANNCOP model corresponding to this grouping predicts the 8-h average CO concentrations within the accuracy range of 68–71%. The CO persistence values derived from ANNCOP model are comparable with the persistence values as suggested by the Environmental Protection Agency (EPA), USA. This work demonstrates that ANN based model is capable of describing winter period CO persistence phenomena.     

Spatial modelling of the probability of obtaining a detectable concentration of ammonia in Moreton Bay, Australia

Ammonia is an important water quality variable, which in excess, can be detrimental to waterways and their ecosystems. In the Ecosystem Health Monitoring Program in South-east Queensland ammonia is monitored monthly, however, often more than 50% of the ammonia observations in Moreton Bay are below detection limit, making it difficult to draw useful inferences. In this paper a clipped Gaussian random field is used to spatially model and map the probability of detectable concentration of ammonia. The methodology is applied to the Moreton Bay samples collected in February 2005. The results suggest that for this month the oceanic impacted areas have higher probability of detectable ammonia concentration than the areas closer to the main sources of anthropogenic inputs.     

论固体废物排放统计指标体系设计

固体废物排放统计对象应覆盖固体废物从原材料到最终处置的整个生命周期的各个环节(机构),即矿业--加工制造业--产品流通领域--用户--固体废物收运体系--固体废物中间处理厂--固体废物最终处置场.统计指标体系包括固体废物排放统计指标和排放管理指标;统计指标区分为指标、主要参数和辅助参数,既便于理解也便于管理.根据固体废物排放量和已知的固体废物资源化技术,对固体废物重新分类、统计并分类填埋,以便将来实现再利用.固体废物排放控制统计的对象主要是规模以上的污染源,实施统计的污染源的规模应当是全国统一的.     

岛津TNP-4110在线分析仪的日常维护

从数据比对、硬件维护两个方面探讨岛津TNP-4110在线仪的日常维护问题。通过分析各种干扰因素来查找造成数据比对差异的原因并提出相应解决措施。在仪器日常维护上设立不同周期保养计划、共享设备维护经验,结合实践制定了合适的检修流程图。