成云过程中云水pH值的参数化

该文找出了影响云水pH值的主要因素,用统计分析的方法得到它们与云水pH值之间的简单的函数关系。通过参数化研究发现,在一定的变量取值范围内,模式模拟的结果与用函数关系式得到的结果能很好地对应起来,相关系数为0.94。该文参数化所考虑的变量为:气相H₂O₂,O₃,SO₂与NH3的浓度,液相Fe3+与Mn2+的浓度,水的含量及温度。      

人工复合生态系统对太湖局部水域水质的净化作用

根据不同生态类型水生高等植物的净化能力及其微生境特点,设计建造了由漂浮、浮叶、沉水植物及其根际微生物等组成的人工复合生态系统（artificialcomplexecosystem;AcE）,并在太湖五里湖中桥湖湾内以动态模拟试验,从群落水平研究了多种水生植物镶嵌组合的人工复合生态系统对富营养化湖水的净化能力。结果表明,富营养化湖水经该系统净化后,藻类生物量（以Chla计）下降58％,氨氮下降66％,总氮下降60％,总磷下降72％,可溶性磷酸盐下降80％,水质得到明显改善。与以该湖湾湖水为水源的水厂出水相比,人工复合生态系统出水的氨氮比水厂出水的氨氮平均低45％,总氮低37％,可见经人工复合生态系统处理的湖水部分指标优于同源的自来水。     

运用回归分析与人工神经网络预测含硫芳香族化合物好氧生物降解速率常数

为了研究人工神经网络预测有机化合物生物降解的性能,运用多元线性回归方法和误差反向传递人工神经网络模型以基团代码作为结构描述符,分别拟合、预测了一批含硫芳香族化合物的一级好氧生物降解速率常数．结果表明,由于神经网络自动考虑了基团间的交互作用,它对生物降解这类复杂问题有极高的求解能力,预测的均方误差为０．００１０２,远低于线性回归模型的预测误差０．０１５９１     

煤、煤矸石中硫排放的影响因素及其与酸雨形成的相关性

通过对广东省粤北煤矿地区进行大气、水、雾等现场监测,同时将煤和煤矸石进行模拟实验,以了解其中硫排放的影响因素、排放过程化学形态的分布及排放速率．结果表明,自然堆放状态下的煤和煤矸石中硫的排放受湿度、光、热、氧化的影响;其排放速率与广东省的自然条件相关,与广东省酸雨频率吻合。     

常州市燃气管网破坏的人工神经网络预测模型

作为一种高效清洁的能源,燃气已经成为城市能源中的重要一员,燃气管网破坏亦成为城市所面临的重大安全隐患。城市埋地燃气管网的破坏风险,往往受到多种影响因素的共同作用。通过分析常州市埋地燃气管网破坏的影响因素,确定了地面沉降、地裂缝、城市内涝、土壤腐蚀等4个风险评价因子。运用MATLAB中的人工神经网络工具,通过人工神经网络计算,优化了模型网络结构,建立了常州市埋地燃气管网破坏风险预测的人工神经网络模型。分析计算结果,并为常州市埋地燃气管网的安全防护提供了建议。     

2009—2017年南充市城区酸雨特征分析

为了更为有效地治理酸雨污染,根据南充市环境监测中心站提供的2009—2017年降水监测数据,对南充市城区酸雨污染情况进行了分析及源解析。结果表明:2009—2017年,南充市降水pH从4.60波动上升至5.6以上,酸雨频率波动下降,酸雨污染情况有所改善;[SO4^2-]/[NO3^-]从4.92下降至0.86,酸雨污染类型从硫酸型转变为硝酸-硫酸型。同时,对比分析2014—2016年大气污染物排放源可知,NOx排放源中,工业污染源占比由14%降至11%,生活污染源由2%上升至5%;SO2排放源中,工业污染源占比由62%降至43%,生活污染源由38%上升至57%,表明南充市SO2污染已从以工业污染源为主转变为工业污染源与生活污染源并重。     

Estimating Root Zone Soil Moisture at Continental Scale Using Neural Networks

This study investigates the feasibility of artificial neural networks (ANNs) to retrieve root zone soil moisture (RZSM) at the depths of 20 cm (SM20) and 50 cm (SM50) at a continental scale, using surface information. To train the ANNs to capture interactions between land surface and various climatic patterns, data of 557 stations over the continental United States were collected. A sensitivity analysis revealed that the ANNs were able to identify input variables that directly affect the water and energy balance in root zone. The data important for RZSM retrieval in a large area included soil texture, surface soil moisture, and the cumulative values of air temperature, surface soil temperature, rainfall, and snowfall. The results showed that the ANNs had high skill in retrieving SM20 with a correlation coefficient above 0.7 in most cases, but were less effective at estimating SM50. The comparison of the ANNs showed that using soil texture data improved the model performance, especially for the estimation of SM50. It was demonstrated that the ANNs had high flexibility for applications in different climatic regions. The method was used to generate RZSM in North America using Soil Moisture and Ocean Salinity (SMOS) soil moisture data, and achieved a spatial soil moisture pattern comparable to that of Global Land Data Assimilation System Noah model with comparable performance to the SMOS surface soil moisture retrievals. The models can be efficient alternatives to assimilate remote sensing soil moisture data for shallow RZSM retrieval.     

Chemical Characteristics of Rain Water at an Urban Site of South Western Turkey

In this study, chemical composition of the rain water in Mugla was investigated from February to April 2002. Rain water samples were obtained from Mugla, a small city in south western Turkey. The Yatagan Power Plant is located 30 km northwest of Mugla city. The values of pH and the concentrations of major ions (Ca²⁺, Na⁺, K⁺, SO₄ ²⁻, NO₃ ⁻, NH₄ ⁺) in the rainwater samples were analyzed. The pH varied from 4.5 to 7.7 with an average of 6.9 which was in alkaline range considering 5.6 as the neutral pH of cloud water with atmospheric CO₂ equilibrium. In the total 30 rain events, only two events were observed in acidic range (< 5.6) which occurred after continuous rains. The equivalent concentration of components followed the order: Ca²⁺ > SO₄ ²⁻ > NH₄ ⁺ > NO₃ ⁻ > Na⁺ > K⁺ > H⁺. The volume-weighted mean (VWM) of the measured ionic sum is 371.62 μeq/l. The ratio of between sum cations and sum anions (∑cations /∑ anions) is 1.52 μeq/l. The alkaline components (Ca²⁺, Na⁺, K⁺) contribute 52%, NH₄ ⁺ 8%, whereas, the contribution from the acidic components is relatively small (40%). The low concentrations of H⁺ found in rainwater samples from Mugla suggest that an important portion of H₂SO₄ and HNO₃ have been neutralized by alkaline particles in the atmosphere. The dust-rich local and surrounding limestone environment might have caused the high concentration of Ca²⁺ in Mugla area. The relatively high concentration of NH₄ ⁺ observed at Mugla is suspected to be due to surrounding agricultural. The results obtained in this study are compared with those other studies conducted at various places in the world.     

酸雨环境对轻质土的工程性质的影响

酸雨是在大气环境发生变化后引起的环境污染之一,其特征是分布范围广、作用时间长。轻质土作为一种新型的地基基础材料,在建设工程具有广泛的应用前景。探讨酸雨环境对轻质土工程性质的影响,对于掌握轻质土的基本特性具有重要意义。     

北京市近二十年(1987～2004)湿沉降特征变化趋势分析

通过分析降水酸度和沉降量2个酸沉降控制指标,得出北京市近二十年(1987～2004)湿沉降特征变化趋势.研究发现,1998年以后北京市的湿沉降污染有严重的趋势.pH值逐年下降至5.52,酸雨频率逐年上升.湿沉降中的硫组分来自北京本地污染源排放的SO2和远距离输送.含氮组分对湿沉降的贡献作用明显增加.钙沉降是湿沉降中变化最大的因素,钙沉降量明显下降.1998年以后所采取的使总悬浮颗粒物浓度大幅下降的污染控制措施,可能直接导致了湿沉降酸化的加剧.酸沉降污染控制是一个复杂的控制过程,不能单纯地依靠控制本地的SO2排放量,北京市SO2排放量虽然得到了削减,但是湿沉降污染并未减缓.