新建住宅小区噪声验收监测方法初探

住宅小区噪声监测是近年来房地产验收过程中的重要环节,围绕新建住宅小区噪声验收监测方法、评价标准、布点原则等方面进行初步探讨,并根据某住宅小区噪声验收监测实例,提出了相应的建议。     

PSO和SVM混合算法确定太湖入湖河流水质主要影响因子

以影响太湖入湖河流水质的24个因子值为研究对象,将PSO算法与SVM算法相结合。PSO算法用于优化SVM算法的参数c和g,以利于快速、高效地确定c和g的全局最优值;SVM算法基于最优的c和g,分别以24,21,18,15,12,9和6个因子作为特征向量预测水质的污染程度。结果表明,当特征向量为9个影响因子时预测率最高。其参数c=18.56,g=1.35,对应的预测率为：全局预测率92.59%,重度污染水质预测率88.89%,轻度污染水质预测率94.45%。因此,通过PSO和SVM混合算法,可以确定影响太湖入湖河流水质的主要因子,利用这些主要因子对水质进行预测预警,不但可以节省时间,而且可以得到精确的结果。     

渤海排污口邻近海域异养细菌的组成与分布

对渤海4个重点监测排污口（北塘、大蒲河、弥河和虞河）邻近海域异养细菌的组成和分布进行了调查研究。结果表明,分离到的各排污口邻近海域的细菌隶属于变形菌门（Proteobacteria）、厚壁菌门（Firmicutes）、放线菌门（Acti-nobacteria）和拟杆菌门（Bacteroidetes）4个细菌类群,其中变形菌门的细菌最丰富。各排污口的优势菌有所不同,北塘、弥河2个采样点的优势菌分别为Bacillus sp．、Pseudoalteromonas sp．,大蒲河采样点的优势菌为Vibrio sp．和Oceanospirillum sp．,虞河采样点的优势菌为 Shewanella sp．和 Bacillus sp．。多维尺度分析表明,北塘和虞河采样点的细菌种群特征较相近,细菌种群分布特征可能与排污口的海洋环境有一定的相关性。     

环境监测能力建设项目管理思路与实现

近年来,环境监测能力建设项目资金投入不断加大,项目规模增长迅速,实施任务日益繁重,项目绩效考核要求越来越高,但项目管理还处于比较粗放的状态。在分析环境监测能力建设项目管理现状和需求的基础上,提出通过转变项目管理模式、强化信息支撑手段、完善制度建设、培养管理人才等多种手段,提高项目管理的科学性和时效性,实现重点项目管理的精细化、科学化和规范化。     

基于EFDC的长江常州段污水排江浓度场数值模拟

长江感潮河段水流与污染排放引起的浓度场复杂多变,基于EFDC(Environmental Fluid Dynamic Code)模型,采用正交曲线网格拟合自然河道边界,建立了长江常州段的水动力和水质模型。采用现场同步实测资料,与计算结果比对,证明该模型在水动力和水质两个方面都与实测数据吻合较好,满足了实际工程的需要;同时由于长江水流运动较快,一阶降解动力学已经满足了化学需氧量(COD)、氨氮(NH3-N)和总磷(TP)浓度计算要求,可以不考虑它们复杂的生化反应过程。     

道路交通噪声自动监测应用探讨

结合城市道路路网状况及实际噪声监测数据和历史实验数据,对道路交通噪声自动监测数据的有效性、监测点位布设进行了研究,对道路交通噪声监测点位优化提出建议。     

Spatial and seasonal distribution of nitrogen in marsh soils of a typical floodplain wetland in Northeast China

Horizontal and profile distributions of nitrogen in marsh soils in different seasons were studied in a typical site within the Erbaifangzi wetland in Northeast China. Results showed that there was higher spatial heterogeneity for nitrate nitrogen (NO₃^--_{3}^{-}-N) and ammonium nitrogen (NH₄⁺_{4}^{+}–N), as well as available nitrogen (AN), in surface soils in July compared to that in September. Relative to July, the mean nitrogen contents in surface soils were slightly higher in September; however, in November, soils contained significantly lower NO₃^--_{3}^{-}-N and NH₄⁺_{4}^{+}–N, higher AN, organic nitrogen (Org-N), and total nitrogen (TN). Except for mineral nitrogen, no significant differences were observed between Org-N and TN contents in September and November. Nitrogen contents generally declined exponentially with depth along soil profiles in three sampling dates (July, September, and November), except for a significant accumulation peak of NO₃^--_{3}^{-}-N at the 20–30 cm depth in September. However, NH₄⁺_{4}^{+}–N contents showed a vertical alternation of “increasing and decreasing” in both July and September, while nearly kept constant with depth in November. The depth ranking of nitrogen showed the shallowest distribution for AN, followed by Org-N and TN, while deeper distributions for NO₃^--_{3}^{-}-N and NH₄⁺_{4}^{+}–N. TN, Org-N, and AN were significantly correlated with soil organic matter and total phosphorus. Soil pH values were significantly correlated with TN and AN contents in surface soils. Clay contents showed significant correlations with nitrogen contents except for NO₃^--_{3}^{-}-N in surface soils and NH₄⁺_{4}^{+}–N in profile soils. However, soil moisture was not significantly correlated with nitrogen contents among all soil samples.     

Vegetation NDVI Linked to Temperature and Precipitation in the Upper Catchments of Yellow River

Vegetation in the upper catchment of Yellow River is critical for the ecological stability of the whole watershed. The dominant vegetation cover types in this region are grassland and forest, which can strongly influence the eco-environmental status of the whole watershed. The normalized difference vegetation index (NDVI) for grassland and forest has been calculated and its daily correlation models were deduced by Moderate Resolution Imaging Spectroradiometer products on 12 dates in 2000, 2003, and 2006. The responses of the NDVI values with the inter-annual grassland and forest to three climatic indices (i.e., yearly precipitation and highest and lowest temperature) were analyzed showing that, except for the lowest temperature, the yearly precipitation and highest temperature had close correlations with the NDVI values of the two vegetation communities. The value of correlation coefficients ranged from 0.815 to 0.951 (p?<?0.01). Furthermore, the interactions of NDVI values of vegetation with the climatic indicators at monthly interval were analyzed. The NDVI of vegetation and three climatic indices had strong positive correlations (larger than 0.733, p?<?0.01). The monthly correlations also provided the threshold values for the three climatic indictors, to be used for simulating vegetation growth grassland under different climate features, which is essential for the assessment of the vegetation growth and for regional environmental management.     

Heavy metal concentration and speciation of seven representative municipal sludges from wastewater treatment plants in Northeast China

The analysis of heavy metals is very important for assessing the feasibility of the agricultural utilization for the municipal sludge. In this paper, a four-step sequential extraction method was applied to extract heavy metals (Cu, Zn, Mn, Cr, and Ni) in municipal sludges from seven individual wastewater treatment plants located in Jilin and Heilongjiang Province, China, for estimating the mobility and bioavailability of the metal ions in the agricultural application. The total concentrations of heavy metals and their chemical fractions after the sequential extraction were determined. Principal component analysis (PCA) was applied to analyze the relations of heavy metals fractions in the municipal sludges. Experimental results indicated that the total concentrations of Cu, Zn, Cr, and Ni in all sludge samples were below the threshold values set out by the Chinese legislation (GB18918-2002). Specially, Zn had a high bioavailability and mobility, Cu and Cr had potential bioavailability, while Mn mainly existed in the residual fraction of municipal sludge. On the other hand, Ni had different mobility in different municipal sludge. PCA results were confirmed by the environmental behavior of heavy metals.     

Biodegradation of Poly(Aspartic Acid-Itaconic Acid) Copolymers by Miscellaneous Microbes from Natural Water

Poly(aspartic acid-itaconic acid) copolymers (PAI) is a new scale inhibitor for water treatment. Thus, it is necessary to investigate its biodegradability. The biodegradability of PAI was investigated through CO₂ evolution tests under different conditions based on determination of carbon dioxide production. The investigation results showed that the degradation rate of PAI on day 10 and day 28 were respectively 38.7 and 79.5%, indicating that PAI was one kind of easily biodegradable scale inhibitors. With the increase in the content of itaconic acid in copolymerization process, the biodegradability of PAI was significantly reduced. In addition, the high biodegradability might be attributed to the existence of C–N bone-structure and more –COO–. Finally, Cu²⁺ could decrease the degradation percentage and the enzyme inhibition effect of Cu²⁺ was not the linear effect, but the “low-dosage effect”.