微污染水体夜间曝气控藻效果研究

设计和开发了一种适用于小城镇的曝气控藻设备,通过底泥围隔实验,研究了夜间曝气对微污染水体的治理效果。结果表明:曝气可以有效抑制氮素循环中反硝化作用和底泥向上覆水中释放磷元素,对氮、磷营养元素的抑制率高达80%;曝气对叶绿素a浓度影响极其显著(p<0.01);曝气能有效抑制藻类增长,并防止围隔内的藻类优势种转变为容易引发"水华"的铜绿微囊藻(Microcystis aeruginosa)。     

耐热石油烃降解混合菌的筛选及其群落结构分析

对克拉玛依采集的部分石油污染土壤进行了筛选,得到了5组石油烃高效降解混合菌,其中混合菌KL9-1在45℃的条件下,通过7 d的降解,稀油的降解率达到43.27%,稠油的降解率达到20.09%。混合菌KL9-1经过多次分离纯化后,获得3株具有石油烃降解能力的优势单菌,3株单菌对稀油的降解率都在30%以上。结合分离单菌株的形态、生理生化特征和16S rDNA基因序列的分析结果,初步鉴定KL9-1-1为Pseudomonas putida,KL9-1-2和KL9-1-3为Pseudomonas sp.。     

辽河流域工业废水主要污染物排放强度单元差异分析

污染物排放强度反映了单位新创造经济价值的环境负荷大小,运用均方差赋权法对辽宁省辽河流域6个控制单元2006年度废水量、COD和氨氮等3种主要污染物排放强度的区域差异进行了评价,结果表明,当年3种主要污染物排放强度综合评价的平均水平为0.4411,低于和高于平均水平的单元各有3个,其中浑河中游单元的评价值最低,只有平均水平的11.74%;辽河上游单元的污染物排放强度综合评价值最高,是平均水平的1.8倍,更是浑河中游的15.6倍。然后,以流域污染物排放强度最低值作为流域污染物排放强度目标值,计算各单元污染物排放强度减排潜力,结果表明,各控制单元主要污染物排放强度减排潜力具有显著的区域间差异。最后,应用＂污染贡献率＂这一指标,分析了辽河流域COD和氨氮排放的重污染行业以及单元分布,指出了各单元控制的重点。     

滁州市一次持续性臭氧污染过程气象与传输特征分析

2019年6月8日至17日,安徽省滁州市发生一次持续性臭氧(O₃)污染过程,O₃浓度值超过国家二级标准浓度限值3%~45%。基于滁州市老年大学监测站点空气质量数据、滁州市气象站及全球资料同化系统(GDAS)气象数据,运用HYSPLIT后向轨迹模型、潜在源贡献因子(PSCF)和浓度权重轨迹(CWT)分析方法,研究污染发生时段的气象和区域传输特征。结果表明:①在此次O₃污染过程中,日最高温度的变化范围为25.5~34.7 ℃,风速整体小于4 m/s,风向以偏东风为主,午后的相对湿度在40%左右。在该时段内,滁州市基本处于均压场的控制之中,且受到锋面气旋外围下沉气流的影响,大气层结稳定。②O₃污染发生期间,滁州市主要受东南方向气流的影响,但来自山东省、安徽省北部和江苏省北部的气流的影响也不容忽视。6月9日夜间至10日上午的O₃浓度异常高值,与9日下午的气压异常低值及9日夜间的大气边界层高度异常高值密切相关。上述气压及大气边界层高度异常值的出现使得上风向高浓度O₃被输送至滁州。③此次污染过程的潜在贡献源区主要分布于安徽省东南部、江苏省中西部和浙江省北部等地。上述区域的加权潜在源贡献因子(WPSCF)值大于0.4,加权浓度权重轨迹(WCWT)值超过了100 μg/m³。今后,滁州市在O₃污染防控工作中应加强与上述区域的联防联控。     

微生物在污染环境中的分子生态效应[综述]

生物与环境之间构成了一个开放的自我控制的生态系统,即是一个耗散结构系统．通过物质、能量以及信息的流动构成了系统在功能上的统一性和时间的多样性．生态系统最大的特点是自我调节,自维持其稳态．生物发展进化的过程中,外界环境因子成为生物进化的主要因素和特定的目的物,生物必要朝着这目的物,通过负反馈,不断进行自我调节,以缩小与环境压力之间的差距,当这个差距为零时生物就适应了新的环境．生物就是通过一次又一次的负反馈从环境中获得适应性．众所周知,微生物对于异常环境的适应和抗性能力是任何其它生物所莫及的．探索自…     

GENERAL-CIRCULATION-MODEL SIMULATIONS OF FUTURE SNOWPACK IN THE WESTERN UNITED STATES1

ABSTRACT: April 1 snowpack accumulations measured at 311 snow courses in the western United States (U.S.) are grouped using a correlation-based cluster analysis. A conceptual snow accumulation and melt model and monthly temperature and precipitation for each cluster are used to estimate cluster-average April 1 snowpack. The conceptual snow model is subsequently used to estimate future snowpack by using changes in monthly temperature and precipitation simulated by the Canadian Centre for Climate Modeling and Analysis (CCC) and the Hadley Centre for Climate Prediction and Research (HADLEY) general circulation models (GCMs). Results for the CCC model indicate that although winter precipitation is estimated to increase in the future, increases in temperatures will result in large decreases in April 1 snowpack for the entire western U.S. Results for the HADLEY model also indicate large decreases in April 1 snowpack for most of the western US, but the decreases are not as severe as those estimated using the CCC simulations. Although snowpack conditions are estimated to decrease for most areas of the western US, both GCMs estimate a general increase in winter precipitation toward the latter half of the next century. Thus, water quantity may be increased in the western US; however, the timing of runoff will be altered because precipitation will more frequently occur as rain rather than as snow.     

VARIABILITY CHARACTERISTICS OF MONTHLY PRECIPITATION IN CENTRAL OKLAHOMA1

ABSTRACT: To fully take advantage of regional climate forecast information for agricultural applications, the relationship between divisional and station scale precipitation characteristics must be quantified. The spatial variability of monthly precipitation is assumed to consist of two components: a systematic and a random component. The systematic component is defined by differences in long-term mean precipitation between stations within a climate division, and the random component by differences between station and divisional standardized values. For the Central Climate Division of Oklahoma, the systematic component has a positive precipitation gradient from west to east with a slope ranging between 3 to 16 mm of precipitation per 100 km depending on the month of the year. On the other hand, the random component ranges between 27 to 48 percent of the mean temporal variation of the monthly precipitation. This significant random spatial variability leads to large localized departures from divisional values, and clearly demonstrates the critical influence of the random component in the utilization of divisional climate forecasts for local agricultural applications. The results of this study also provide an uncertainty range for local monthly precipitation projections that are derived from divisional climate information.     

ESTIMATES OF RUNOFF USING WATER-BALANCE AND ATMOSPHERIC GENERAL CIRCULATION MODELS1

ABSTRACT: The effects of potential climate change on mean annual runoff in the conterminous United States (U.S.) are examined using a simple water-balance model and output from two atmospheric general circulation models (GCMs). The two GCMs are from the Canadian Centre for Climate Prediction and Analysis (CCC) and the Hadley Centre for Climate Prediction and Research (HAD). In general, the CCC GCM climate results in decreases in runoff for the conterminous U.S., and the HAD GCM climate produces increases in runoff. These estimated changes in runoff primarily are the result of estimated changes in precipitation. The changes in mean annual runoff, however, mostly are smaller than the decade-to-decade variability in GCM-based mean annual runoff and errors in GCM-based runoff. The differences in simulated runoff between the two GCMs, together with decade-to-decade variability and errors in GCM-based runoff, cause the estimates of changes in runoff to be uncertain and unreliable.     

PRECIPITATION DIFFERENCES AMONGST GCMs USED FOR THE U.S. NATIONAL ASSESSMENT1

ABSTRACT: Two general circulation models (GCMs) used in the U.S. national assessment of the potential consequences of climate variability and change (CGCM1 and HadCM2) show a large increase in precipitation in the future over the southwestern U.S., particularly during winter. This precipitation increase is an extension of a larger region of increased precipitation in the Pacific Ocean off the west coast of North America that is associated with a deepened and southward-shifted Aleutian Low, a weaker subtropical high, and warmer sea surface temperatures (SSTs). The models differ in their simulation of precipitation anomalies over the southeastern U.S., with CGCM1 showing drier conditions and HadCM2 showing wetter conditions in the future. While both models show decreased frequency of Atlantic storms, consistent with decreased meridional and land/sea temperature gradients, the more coastal position of the storm track in CGCM1 results in less precipitation than modern along the eastern seaboard of the U.S. During summer, differences in land surface models within the two GCMs sometimes lead to differences in soil moisture that feed back to the precipitation over land due to available moisture.     

俄罗斯土壤污染防治立法研究及其对构建我国《土壤污染防治法》的启示

俄罗斯土壤污染防治立法有其自己的特色,通过研究总结出七点立法特点。中国的土壤污染形势严峻,现行土壤污染防治立法多采分散立法的模式,缺乏系统性、专门针对性和可操作性,既不能适应日益严峻的土壤污染形式,也不能满足对我国土壤污染保护的客观需求。因此,制定专门的《土壤污染防治法》有其必要性和紧迫性。针对我国土壤污染立法现状,吸收俄罗斯土壤防治立法的先进之处,近而得出了构建我国专门的《土壤污染防治法》,树立整体的立法观念;制定明确的土壤保护标准及土壤污染防治标准;建立土壤污染预防制度和土壤污染修复制度;加强土壤的国家监督、国家监测和许可等管理制度;注重环境影响评价制度以及信息公开,扩大公民的公众参与权等几点启示。