1986-2020年上海苏州河水质时空变化特征

以1986-2020年苏州河水质监测数据为依据,将水质变化过程划分成1986-1996年、1997-2006年和2007-2020年3个阶段,系统分析了苏州河水质状况及多年时空变化特征。结果表明,在第1阶段(1986-1996年),苏州河整体处于重度污染水平,从上游到下游水质显著恶化,市区段污染严重;在第2阶段(1997-2006年),苏州河市区段水质显著改善,有机污染指标消除劣Ⅴ类,氨氮和总磷仍处于较高污染水平,上下游水质逐渐趋同;在第3阶段(2007-2020年),苏州河水质持续改善,特别是2016年以来改善明显,2020年水质达到34年来的最好水平。苏州河水质改善与上海市实施的全市及苏州河多轮环境综合治理工程、上游来水水质改善等密切相关,反映了苏州河30多年环境综合治理的突出成效,并为城市黑臭水体治理提供经验。     

苏州高新区典型行业VOCs排放特征及控制对策探讨

通过资料收集和现场调研估算苏州高新技术产业园区VOCs排放量,对区内典型行业VOCs污染物特征组分做分析,并简述其区域内典型行业VOCs治理技术的现况,分析了排放现状特征和控制难点。基于对国内外工业VOCs污染控制措施研究,提出对VOCs污染控制的对策和建议。     

苏州河底泥对上复水水质污染影响

研究了上海市苏州河底泥中有机物及营养盐释放对上复水水质的影响,分析了微生物与底栖生物底泥再悬浮对底泥释放过程的影响。研究表明,底泥中化学需氧量与水体中的化学需氧量成正比,底泥中生化需氧量与水体中的生化需氧量呈正比,再悬浮促进底泥中污染物向上复水体释放。底泥SOD与水体中DO成正比,底泥污染是影响苏州河水质的重要因素;对苏州河底泥进行疏浚工程可较好地提高水体中溶解氧的浓度、降低化学需氧量、生化需氧量及氨氮的浓度。     

沪苏边缘区经济合作的时空关系及其对策 --以南通和苏州为例

沪苏边缘区是沪苏经济联系较为密切的区域.以江苏省的南通和苏州两市为研究对象,首先对沪苏边缘区经济合作进展的时空关系进行了总结,时间上表现为三个阶段的历史演进,空间上表现为合作的地区性差异.接着,分析了沪苏边缘区经济合作地区性差异的主要原因,包括经济距离、思想观念和投资环境的差异.在此基础上,对沪苏边缘区的合作绩效进行了评价,认为沪苏边缘区合作绩效明显,合作的方向是经济一体化.基于对北美自由贸易区、欧盟和APEC三个典型的区域合作组织模式的成功经验的对比分析,最后提出了进一步推进沪苏边缘区合作的对策.     

小型岸边站技术在水质自动监测中稳定性和可靠性分析

以苏州河水质自动监测岸边站为例,根据近3年实际运行情况,从实样验收比对、连续运行比对等方面系统比较自动监测和实验室分析数据,深入探讨小型岸边站技术的稳定性和可靠性。结果表明:岸边站在线监测数据总体较为稳定,水温、溶解氧、p H、氨氮等监测结果和变化规律与实验室数据具有较好的相关性和一致性,其中,水温、p H、氨氮等指标均不存在明显差异,苏州河水质自动在线岸边站测定的数据真实可靠。加强自动站运维管理等可以进一步提高自动站数据质量。     

吹扫捕集-GC/MS法测定南宁市竹排冲黑臭河道水体嗅味物质

利用吹扫捕集-GC/MS法对引起南宁市竹排冲河道水体黑臭的嗅味物质进行检测分析。结果表明,导致竹排冲水体黑臭的嗅味物质主要为苯系物、硫类化合物和氯苯类化合物,其中甲硫醚(相对含量1.70%)、二甲基二硫醚(相对含量3.19%)、甲基丙基二硫醚(相对含量6.11%)等挥发性有机物为竹排冲水体中的主要致嗅物质,是竹排冲水体嗅味产生的主要原因。     

高影响天气对苏州市大气污染物特征的影响

利用苏州市2010—2012年大气污染物逐时质量浓度数据和气象条件资料,分析4类高影响天气对该市大气污染物扩散的影响。研究表明:暴雨对污染物的清除作用主要与降水时间和强度等因子有关,且降水时间的影响大于降水强度;夏季高温日污染物平均质量浓度高于非高温日,PM10、PM2.5、O3、NO2分别增长了29.5%、19.2%、51.3%和13.5%,且O3质量浓度大于321.6μg/m3的日最高气温均在33℃以上;寒潮过境对污染物有很好的清除效应,可对不同污染物影响程度不同;台风带来的大风和降雨能使污染物浓度迅速降低,其来临前的外围下沉气流可能对污染物浓度升高有影响。     

苏州河干流水质自动监测系统数据的可靠性分析

以苏州河干流水质自动监测系统为例,通过与实验室数据之间的统计分析,分析苏州河水质在线自动监测系统数据的可靠性。对比分析自动监测系统和实验室的温度、p H、DO、CODMn、NH3-N数据,自动监测系统数据合格,在0.01水平上两者不存在显著性差异,2种方法的结果高度相关,苏州河水质在线自动监测系统测定的数据真实可靠。在自动监测系统的维护中,要对系统关键部分进行不定期的清洗,特别是出现较可疑数据时,应及时寻找原因,解决问题。     

A conceptual framework of agricultural land use planning with BMP for integrated watershed management

Land use planning is an important element of the integrated watershed management approach. It not only influences the environmental processes such as soil and stream bed erosion, sediment and nutrient concentrations in streams, quality of surface and ground waters in a watershed, but also affects social and economic development in that region. Although its importance in achieving sustainable development has long been recognized, a land use planning methodology based on a systems approach involving realistic computational modeling and meta-heuristic optimization is still lacking in the current practice of integrated watershed management. The present study proposes a new approach which attempts to combine computational modeling of upland watershed processes, fluvial processes and modern heuristic optimization techniques to address the water-land use interrelationship in its full complexity. The best land use allocation is decided by a multi-objective function that minimizes sediment yields and nutrient concentrations as well as the total operation/implementation cost, while the water quality and the production benefits from agricultural exploitation are maximized. The proposed optimization strategy considers also the preferences of land owners. The runoff model AnnAGNPS (developed by USDA), and the channel network model CCHE1D (developed by NCCHE), are linked together to simulate sediment/pollutant transport process at watershed scale based on any assigned land use combination. The greedy randomized adaptive Tabu search heuristic is used to flip the land use options for finding an optimum combination of land use allocations. The approach is demonstrated by applying it to a demonstrative case study involving USDA Goodwin Creek experimental watershed located in northern Mississippi. The results show the improvement of the tradeoff between benefits and costs for the watershed, after implementing the proposed optimal land use planning.     

River environmental decision support system development for Suzhou Creek in Shanghai

The Suzhou Creek Rehabilitation Project (SCRP) is one of the largest water-related environmental rehabilitation schemes ever undertaken in the vicinity of Shanghai, China. This paper details the development and application of a River Environmental Decision Support System (REDSS) for scientific planning and decision-making on the Suzhou Creek project, and illustrates the flexibility of the REDSS framework. We developed the following components: (1) a GIS-based analysis employing Component technology; (2) a "data mart" for multi-dimensional, multi-level, integrated, dynamic, and flexible data querying; and (3) a set of hydrodynamic and water quality models which can simulate complex tidal river networks. In addition, we detail how a water quality assessment model is embedded into the REDSS by employing an Identification Index Method. With the REDSS, all GIS and non-GIS components are integrated seamlessly and data from different sources can be queried simultaneously. This allows for various scenarios to be simulated and analyzed in advance to predict and assess the effects of proposed engineering and management measures. Generated information can thus support effective decisions. All operations of the REDSS can be implemented conveniently through user-friendly interfaces. The function of the REDSS framework is demonstrated through an application to Suzhou Creek. Because the REDSS characteristics are quite general, it may be applied in different geographic regions.