Recharge signal identification based on groundwater level observations

This study applied a method of the rotated empirical orthogonal functions to directly decompose the space-time groundwater level variations and determine the potential recharge zones by investigating the correlation between the identified groundwater signals and the observed local rainfall records. The approach is used to analyze the spatiotemporal process of piezometric heads estimated by Bayesian maximum entropy method from monthly observations of 45 wells in 1999-2007 located in the Pingtung Plain of Taiwan. From the results, the primary potential recharge area is located at the proximal fan areas where the recharge process accounts for 88% of the spatiotemporal variations of piezometric heads in the study area. The decomposition of groundwater levels associated with rainfall can provide information on the recharge process since rainfall is an important contributor to groundwater recharge in semi-arid regions. Correlation analysis shows that the identified recharge closely associates with the temporal variation of the local precipitation with a delay of 1-2 months in the study area.     

A novel approach to rapid detection of acute water toxicity and its policy implications for grassroots sustainable environmental monitoring

Unknown chemicals, emerging contaminants, and the resulting reactions among them make early detection and warning of acute water toxicity extremely challenging. The conventional approach using small fish for toxicity monitoring normally requires a designated species of fish and over a week's time to complete, including dilution of the wastewater, a pre-test, and a full test. It often increases chances for error and delays emergency management. This paper reports a novel approach, based on grassroots knowledge and field and lab experience in Jilin, China. This approach uses a combination of different species of aquarium fish to achieve fast and reliable monitoring. It tests the original source water directly without going through the dilution procedure, while paying attention to the time factor. The approach does not require a pre-test and may shorten the time needed for detecting acute toxicity to a few minutes, using a new classification of aquatic toxicity levels. It is inexpensive to use and may be easily adopted by grassroots organizations. The approach is "greener" and more financially and socially sustainable than traditional approaches. The wide use of the approach has the potential to encourage policy innovations for making toxicity monitoring grassroots based and more effective in reducing acute contamination emergencies.     

Chlorinated and brominated dibenzo-p-dioxins and dibenzofurans in surface sediment from Taihu Lake, China

Polychlorinated dibenzo-p-dioxins and dibenzofurans (PCDD/Fs) and polybrominated dibenzo-p-dioxins and dibenzofurans (PBDD/Fs) in surface sediment samples from Taihu Lake--an important water supply of the Yangtze River Delta, China--were investigated in the present study. Concentrations of PCDD/Fs ranged from 0.91 to 4.8 pg TEQ g(-1) dw (mean: 2.9 pg TEQ g(-1) dw, TEQ: Toxic Equivalent), which were all higher than the threshold effect level established by interim sediment quality guidelines in Canada (0.85 pg TEQ g(-1) dw). The levels of PBDD/Fs ranged from 0.16 to 1.6 pg TEQ g(-1) dw (mean: 0.52 pg TEQ g(-1) dw) and accounted for 5-33% (mean: 14%) of the total PCDD/Fs and PBDD/Fs TEQ. Comparatively, the abundance of sedimentary PCDD/Fs in the three regions (Meiliang Bay, Gonghu Bay, and Xukou Bay) showed a decreasing trend from the inflow region to the outflow region, while no significant difference was observed among their 2,3,7,8-PBDD/Fs levels, which suggested that the sources of PCDD/Fs and PBDD/Fs differed in this area. Principal component analysis suggested that the historical production/usage of pentachlorophenol and sodium pentachlorophenate was the dominant source of PCDD/Fs in the sediment of these regions. Although the specific sources of PBDD/Fs in the sediment of Taihu Lake were unclear, it was suspected to be due to atmospheric deposition; however, an additional study is needed to confirm this.     

北京城区冬季道路灰尘粒度特征分析

对2013年1月于北京城区采集的40组道路灰尘样品用激光粒度仪进行粒度测定。结果表明:北京城区冬季道路灰尘频率曲线呈单峰态或双峰态分布,单峰型峰值粒径为112~237μm,双峰型第一峰值粒径为189~286μm,第二峰值粒径为42~57μm。道路灰尘平均粒径为183μm,分选性差,呈极不对称的极正偏宽峰态到窄峰态,属砂土。道路灰尘是局地灰尘和区域灰尘的混合物,且主要为跃移或短时悬浮颗粒物,对大气悬浮颗粒污染物的贡献量不大。研究4种不同道路类型灰尘发现,平均粒径从大到小顺序为快速路支路次干路主干路,分选系数与偏度为快速路主干路次干路支路,峰度无较大区别,细颗粒含量主干路次干路(支路、快速路)。主干路灰尘污染贡献率更高,对大气环境和人体健康的危害潜力不容忽视。     

滇池浮游藻类群落构成调查

对滇池浮游藻类群落组成和空间分布开展了2次调查,鉴定出藻类8门66属159种及变种,绿藻种类最多,蓝藻次之。5、12月滇池全湖平均藻类密度分别为1.398×108、2.180×108个/升,蓝藻门微囊藻属为优势藻类。5月的调查中滇池外海藻类生物量呈北高南低的格局,而12月则呈现南部和中部高,北部低。外海的藻类生物量明显高于草海,草海藻类群落构成与外海明显不同,主要表现为绿藻门藻类所占比例较高。12月滇池外海及全湖藻类生物量都显著高于5月。与上一次(2006—2007年)滇池浮游藻类的系统调查相比,滇池(主要是外海)浮游藻类在物种数量、常见藻类、优势藻类及生物量水平方面与之接近。     

北京地区冬季典型PM2.5重污染案例分析

对2013年1月10—14日发生的持续性PM2.5重污染过程从污染过程演变、气象条件影响、与气态污染物关系、区域污染背景、PM2.5浓度空间分布演变及其与地面风场的关系、PM2.5组分特征等多个方面进行全面的分析,较为完整地还原了该次重污染案例的形成原因以及主要影响因素。主要结论包括:该次重污染过程是稳定气象条件下导致的局地污染物积累,再叠加华北区域性污染的影响共同造成,其中10、12日北京地区PM2.5浓度的快速增长反映了周边污染传输的显著影响;逆温不但造成污染物难以扩散,且不同的逆温类型对PM2.5浓度水平有显著影响,同时还发现逆温的破坏导致近地面高浓度污染物向上扩散,造成百花山出现峰值高污染浓度现象;NO2与PM2.5浓度水平的高相关性反映交通污染二次转化对PM2.5浓度水平的影响,在较高湿度条件下,SO2浓度水平对湿度敏感且表现为负相关性;该次污染过程中OM、SO2-4、NO-3、NH+4等组分在PM2.5质量浓度中的占比超过70%,说明燃煤、机动车等仍是北京地区最主要的污染来源,同时SO2-4占比最高也说明区域污染传输对该次重污染的显著贡献。     

农药企业搬迁土地挥发性有机物风险评价

对常州某农药生产场地土壤中挥发性有机物(VOCs)污染状况以及健康风险和生态风险进行了调查评价。结果表明,该场地土壤中挥发性有机物污染以苯系物和卤代烃为主。苯系物质量浓度为0~56.6 mg/kg,卤代烃质量浓度为0~1.14 mg/kg。健康风险评价结果均在可接受范围内,而生态风险评价显示生产车间内的土壤VOCs生态风险较大,存在着对生物的危害。     

2013年北京市PM2.5重污染日时空分布特征研究

根据2013年北京市环境保护监测中心监测的PM2.5数据,系统分析了北京市重污染日PM2.5污染的时空分布特征,并利用克里格插值初步统计了全年和重污染日PM2.5不同浓度区间的国土面积。2013年全市PM2.5年均浓度为89.5μg/m3,重污染日平均浓度为218μg/m3,重污染日主要集中在冬季;PM2.5年均浓度呈现明显的南高北低梯度分布特征,而重污染日空间分布较均匀,南部及城六区存在明显的高污染区,平均浓度在180μg/m3以上;2013年北京市重污染日PM2.5平均浓度为150~250μg/m3,其对应的国土面积约为12 656 km2,PM2.5平均浓度在250μg/m3以上的国土面积约为883 km2,而全年无PM2.5平均浓度在150μg/m3以上所对应的国土面积。     

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。     

渤海湾入海溶解无机氮总量控制研究

基于渤海湾近岸海域的实际调查结果,采取生态物理耦合模型,对渤海湾的主要污染物-溶解无机氮(DIN)的基准环境容量和极小剩余海洋环境容量进行了计算。结果表明,渤海湾DIN的极小剩余海洋环境容量在Ⅰ类和Ⅱ类水质标准下均为负值,渤海湾的DIN已经超标。结合实际的海水功能区水质管理目标,应重点控制非点源的排放,加强上游携带入境污染物的处理,从总量上控制DIN入海污染通量,改善渤海湾水质。