石家庄市冬季大气中VOCs污染特征分析

为弄清石家庄市冬季大气中VOCs的污染特征,采用美国环保局TO-15方法对石家庄市冬季大气中VOCs组成进行了定性和定量分析。在此基础上,进行了VOCs的月度变化分析、春节期间的变化分析,并进行了VOCs与空气质量指数AQI、PM2.5等之间的相关性分析;根据VOCs组成及变化情况和相关性,分析了其可能的来源。结果表明,石家庄市冬季大气中VOCs的质量浓度为145.7~1 410.7μg/m3,VOCs组分主要有丙酮、二氯甲烷、苯、乙酸乙酯、甲苯、1,2-二氯丙烷、三氯甲烷。春节期间,大气中VOCs的浓度有大幅的下降,比日常均值下降了40.9%。AQI较高时,大气中VOCs浓度有所升高。石家庄市冬季大气中丙酮、二氯甲烷、乙酸乙酯等主要来源于医药化工生产活动,苯、甲苯主要来源于煤燃烧。     

高效率颗粒物微物理模型简介与重污染过程应用分析

中国细颗粒物(PM2.5)导致的空气污染和雾霾天气问题越来越突出,在低层对流层中很多地方都有显著的二次颗粒物生成过程,因此对颗粒物物理化学转化过程的研究具有重要意义,其转化过程对空气质量模式模拟和预报的准确性有重要影响。高效率颗粒物微物理(APM)模型经过近20多年的研究和发展,在全球化学传输模型(GEOS-Chem)、区域性气象和化学预报模型(WRF-Chem)通用地球系统模型(CESM-CAM5)等气象及环境空气质量预报模型中取得了很好的应用验证,能够在全球/区域等不同尺度对粒子生成、长大、凝聚、消除等微物理过程以及气溶胶光学厚度(AOD)、直接/间接辐射强迫等进行模拟。应用GEOS-Chem-APM模式模拟了2014年2月京津冀区域的重污染过程。结果显示,湿度模拟的准确性对其他物理和污染物浓度等模拟结果有重要作用;2月20—26日的重污染过程模拟结果与实际观测较为吻合,主要污染特点是较高的湿度(90%以上),同时,二次颗粒物和包裹了二次物种的一次颗粒物(黑碳/有机碳)是低能见度的最大贡献者。     

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。     

重点流域水系沉积物中多环芳烃标准样品制备

环境标准样品是监测过程中重要的质量控制手段,中国受天然基体标准样品制备技术的制约,尚未拥有自己的沉积物中多环芳烃标准样品。为制备符合中国重点流域沉积物类型及多环芳烃浓度水平的沉积物标准样品,对中国6个重点流域的沉积物进行了采样,获得了制备多环芳烃标准样品的原料。分析常温及冷冻2种干燥方式对多环芳烃的影响,为制备大批量多环芳烃标准样品提供数据支持。对11个点位样品采用气相色谱质谱法测定16种优控多环芳烃化合物浓度,结果表明,样品均匀性良好,样品中多环芳烃检出率在99%以上,江河沉积物样品中多环芳烃浓度区间为664~2.91×103μg/kg,湖泊样品最高值达到1.25×105μg/kg,其主要污染源是化学燃料的燃烧。为中国制备水系沉积物中多环芳烃标准样品积累了技术基础。     

乌伦古湖水质现状、变化趋势及预测

通过对乌伦古湖现状水质及近十年来水质变化趋势的评价,分析了污染成因,并采用灰色预测法预测乌伦古湖未来几年的水质状况,为区域水环境保护和水体污染防治提供科学依据。     

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。     

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”.