DRY AND WET WEATHER FLOW NUTRIENT LOADS FROM A LOS ANGELES WATERSHED1

Effective watershed management requires an accurate assessment of the pollutant loads from the associated point and nonpoint sources. The importance of wet weather flow (WWF) pollutant loads is well known, but in semi‐arid regions where urbanization is significant the pollutant load in dry weather flow (DWF) may also be important. This research compares the relative contributions of potential contaminants discharged in DWF and WWF from the Ballona Creek Watershed in Los Angeles, California. Models to predict DWF and WWF loads of total suspended solids, biochemical oxygen demand, nitrate‐nitrogen, nitrite‐nitrogen, ammonia‐nitrogen, total Kjeldahl nitrogen, and total phosphorus from the Ballona Creek Watershed for six water years dating from 1991 to 1996 were developed. The contaminants studied were selected based on data availability and their potential importance in the degradation of Ballona Creek and Santa Monica Bay beneficial uses. Wet weather flow was found to contribute approximately 75 percent to 90 percent of the total annual flow volume discharged by the Ballona Creek Watershed. Pollutant loads are also predominantly due to WWF, but during the dry season, DWF is a more significant contributor. Wet weather flow accounts for 67 to 98 percent of the annual load of the constituents studied. During the dry season, however, the portion attributable to DWF increases to greater than 40 percent for all constituents except biochemical oxygen demand and total suspended solids. When individual catchments within the watershed are considered, the DWF pollutant load from the largest catchment is similar to the WWF pollutant load in two other major catchments. This research indicates WWF is the most significant source of nonpoint source pollution load on an annual basis, but management of the effects of the nonpoint source pollutant load should consider the seasonal importance of DWF.     

Using a Bayesian network to clarify areas requiring research in a host–pathogen system

Bayesian network analyses can be used to interactively change the strength of effect of variables in a model to explore complex relationships in new ways. In doing so, they allow one to identify influential nodes that are not well studied empirically so that future research can be prioritized. We identified relationships in host and pathogen biology to examine disease‐driven declines of amphibians associated with amphibian chytrid fungus (Batrachochytrium dendrobatidis). We constructed a Bayesian network consisting of behavioral, genetic, physiological, and environmental variables that influence disease and used them to predict host population trends. We varied the impacts of specific variables in the model to reveal factors with the most influence on host population trend. The behavior of the nodes (the way in which the variables probabilistically responded to changes in states of the parents, which are the nodes or variables that directly influenced them in the graphical model) was consistent with published results. The frog population had a 49% probability of decline when all states were set at their original values, and this probability increased when body temperatures were cold, the immune system was not suppressing infection, and the ambient environment was conducive to growth of B. dendrobatidis. These findings suggest the construction of our model reflected the complex relationships characteristic of host–pathogen interactions. Changes to climatic variables alone did not strongly influence the probability of population decline, which suggests that climate interacts with other factors such as the capacity of the frog immune system to suppress disease. Changes to the adaptive immune system and disease reservoirs had a large effect on the population trend, but there was little empirical information available for model construction. Our model inputs can be used as a base to examine other systems, and our results show that such analyses are useful tools for reviewing existing literature, identifying links poorly supported by evidence, and understanding complexities in emerging infectious‐disease systems.     

Environmental assessment of garden waste management in the Municipality of Aarhus, Denmark

An environmental assessment of six scenarios for handling of garden waste in the Municipality of Aarhus (Denmark) was performed from a life cycle perspective by means of the LCA-model EASEWASTE. In the first (baseline) scenario, the current garden waste management system based on windrow composting was assessed, while in the other five scenarios alternative solutions including incineration and home composting of fractions of the garden waste were evaluated. The environmental profile (normalised to Person Equivalent, PE) of the current garden waste management in Aarhus is in the order of −6 to 8 mPE Mg⁻¹ ww for the non-toxic categories and up to 100 mPE Mg⁻¹ ww for the toxic categories. The potential impacts on non-toxic categories are much smaller than what is found for other fractions of municipal solid waste. Incineration (up to 35% of the garden waste) and home composting (up to 18% of the garden waste) seem from an environmental point of view suitable for diverting waste away from the composting facility in order to increase its capacity. In particular the incineration of woody parts of the garden waste improved the environmental profile of the garden waste management significantly.     

烟气脱硫系统调试方法

介绍了风洞式烟气脱硫系统的工艺流程及原理，重点对烟气脱硫系统调试过程进行了阐述，为相关工程测试人员提供参考。     

三峡库区腹地大气微量金属干湿沉降特征

为研究三峡库区腹地大气微量金属沉降特征,在万州城区采样点收集了2014年1月~6月的干湿沉降样品,在云阳晒经村(工厂区)、云阳高阳(场镇郊区)、开县白家溪(自然保护区)、开县野塘溪(县郊区)、开县大德(乡村区)收集了2014年4月的干湿沉降样品;分别测定了样品的p H值、电导率和微量金属元素(Al、As、B、Ba、Bi、Cd、Co、Cr、Cu、Fe、Li、Mn、Pb、Ni、Sb、Sr、Sn、Ti、Zn、V).结果表明:1万州城区酸雨频率为48.44%,酸雨主要集中在1~4月.不同功能区酸雨频率高低顺序为:工厂区万州城区县郊区场镇郊区自然保护区乡村区.2湿沉降中20种微量金属质量浓度均低于国家地表水环境质量标准Ⅲ级标准限值,而Cd、Cu、Pb和Zn不同程度超Ⅰ级标准限值,其中工厂区相对严重.3万州城区干沉降提取液p H值在4.91~6.74之间,平均为5.79.各功能区干沉降酸度高低顺序为:工厂区县郊区万州城区乡村区场镇郊区自然保护区,这与湿沉降酸度顺序完全一致,说明干湿沉降中主要酸性物质具有同源性.4万州城区Ba、Co、Cu、Cr、Li、Mn、Ni、Sr、Zn干沉降超过湿沉降,而Al、As、B、Bi、Cd、Fe、Pb、Sb、Sn、Ti、V湿沉降大于干沉降.富集因子分析表明,万州城区Al为中等富集,Bi和Cd显著富集.     

2015年北京采暖季城市森林内外SO2浓度的时空变化特征

为探讨采暖季城市森林内外ρ(SO₂)动态变化及差异性,基于西山国家森林公园林内空气质量监测站数据,结合北京市环境保护监测中心植物园监测站的实时数据,分析2015年采暖季城市森林内外ρ(SO₂)变化和影响因素.结果表明:林内外ρ(SO₂)日变化基本呈双峰双谷型,在09:00-11:00和20:00-22:00左右达到高峰;采样期间ρ(SO₂)月变化呈不显著"V"型,最高值出现在1月,林内外分别为(25.8±9.2)和(31.7±23.4)μg/m3,最低值出现在11月,林内外分别为(19.0±5.2)和(13.0±11.2)μg/m3.林内ρ(SO₂)在1-3月低于林外,11-12月高于林外,林内ρ(SO₂)变化较林外平缓;气象条件对采暖季城市森林ρ(SO₂)变化有重要影响:降水对ρ(SO₂)消减效应明显,大风有驱散SO₂的作用,同时受风向影响;ρ(SO₂)和温度关系不显著(P=0.05,R < 0.40),但和空气相对湿度线性关系显著(α=0.05,Sig=0.00),林内受气象因素影响低于林外.研究显示,城市森林对气态污染物具有一定的缓冲、抵抗和吸收能力,因此应重视发展城市森林生态系统,充分发挥其生态效益,以提高城市大气环境质量.      

松花江流域冰封期水体中多环芳烃的污染特征研究

在松花江流域的3个主要江段：嫩江、第二松花江和松花江干流,于2010年冰封期采集了21个水体样品,分析了多环芳烃的污染特征.结果表明,15种PAHs的浓度范围为23.4～85.1 ng·L-1,平均浓度为（50.3±17）ng·L-1,与我国其它地区地表水中PAHs的污染程度相当.松花江流域水体中PAHs具有明显的空间分布特征,城市下游浓度高于上游,说明沿岸城市的污水排放可能是松花江水体中PAHs的主要污染源,主成分分析表明,PAHs的主要来源是化石燃料的燃烧源.商值法生态风险评价结果显示,相对分子质量高的PAHs造成的生态风险可以忽略,相对分子质量低的PAHs对松花江水体会造成一定的危害.     

昆明市主城区三种温室气体的月份和干、湿季的小时变化规律及原因分析

研究了昆明市主城区3种温室气体浓度的最新变化情况,采用2009年、2010年和2011年的月份和小时平均浓度数据,结合昆明市气候特点,对3种温室气体浓度的月份和干、湿季的小时变化规律及原因进行了分析。     

催化剂Ru/ZrO2-CeO2催化湿式氧化苯酚

催化剂Ru/ZrO₂-CeO₂催化湿式氧化苯酚的过程表明,Ru/ZrO₂-CeO₂可以显著提高COD和苯酚去除效果,当反应温度为170℃,压力为3 MPa,反应120 min后,COD和苯酚的去除率分别达到了99％和100％.试验还考察了不同反应条件对苯酚溶液COD去除的影响,并获得了最优的反应条件：温度为170℃,压力为3 MPa,催化剂的投加量为5　g/Ｌ,搅拌速度为500 r/min.通过对中间产物的分析,本研究提出了催化湿式氧化苯酚的简单路径图,认为苯酚首先被氧化成小分子有机酸,接着小分子有机酸被氧化成二氧化碳和水.前一个过程是快速反应,后一个过程中的乙酸氧化是慢速过程,需要在高温下才能完成.乙酸的氧化主要是自由基攻击α碳上的C—H键,先生成甲酸,并最终生成二氧化碳和水.     

好氧亚硝化颗粒污泥特性的研究

对在小试曝气上流式污泥床反应器中成功培养出的好氧亚硝化颗粒污泥的特性进行了研究.工艺稳定运行时,亚硝化颗粒污泥的VSS/SS稳定在80%左右,粒径大于1.0 mm的颗粒污泥约占总数的70%,粒径大于0.8 mm的颗粒污泥的湿密度约为1?022 kg/m³.荧光原位杂交结果表明,亚硝化细菌主要分布在颗粒污泥的表层,而硝化细菌则分布在表层之下;最大可能数结果显示,亚硝化工艺稳定运行时亚硝化细菌的数量远多于硝化细菌,甚至可高于硝化细菌4个数量级以上.上述结果表明,硝化细菌（AOB和NOB）以接种的产甲烷颗粒污泥或其碎片为载体,通过在其表层附着生长,最终形成好氧亚硝化颗粒污泥.