荷电水雾振弦栅除尘效率影响因素及相关性分析

为进一步提高荷电水雾振弦栅除尘器除尘效率,在自制模型基础上进行实验,在喷雾水压、喷嘴孔径一定时,以除尘效率η为实验结果,针对入口风速(V)、电场强度(E)和放电距离(L)3个影响因素进行实验研究。根据实验结果得到各影响因素与除尘效率的线性关系,利用MATLAB进行曲线拟合,得到拟合线性方程,通过SPSS软件分析了各因素针对除尘效率的权重关系为V>E>L,并得到V、E和L的相关性系数分别为:-0.264、1.529、0.016;实验结果表明:η与V成负相关、与E和L成正相关;V和E对η具有非常显著的影响,而L的影响相对较弱;综合拟合方程和相关性系数,建立了该项实验3因素对除尘效率影响的经验公式。效验表明该公式可靠,具有一定参考价值。     

我国能源结构-产业结构协调性演进规律研究

从我国目前实际发展现状来看,只有能源结构与产业结构协调发展、共同调整,才能实现经济增长和保障能源安全的目标。运用灰色系统理论的灰色关联分析方法建立能源结构一产业结构协调度定量评价模型,引入熵权法客观赋权,根据各个指标值的变异程度,引用信息熵所反映数据本身的效用值来计算指标的权重系数,有效地避免了由于人的主观因素而形成的权重分配偏差。研究表明从1990年至2007年之间,中国的能源结构一产业结构协调度值经历了增长——下降——再增长的波浪演进过程,目前的能源结构与产业结构并没有达到充分的良性互动作用。研究结论为中国能源结构一产业结构协调度评价的解析化、定量化提供了有力的手段和理论参考依据。     

Monitoring bioaccumulation and toxic e ects of hexachlorobenzene using the polyurethane foam unit method in the microbial communities of the Fuhe River,Wuhan

Hexachlorobenzene （HCB） is a chlorinated aromatic hydrocarbon that was widely used for seed dressing in prevention of fungal growth on crops, and also as a component of fireworks, ammunition, and synthetic rubbers. Because of its resistance to degradation and mobility, HCB is widely distributed throughout the environment and is accumulated through food chains in different ecosystems. In this study, a preliminary investigation was carried out on the bioaccumulation and the toxic effects of HCB in the microbial （protozoan in particular） communities in the Fuhe River, Wuhan, a water body receiving industrial wastewaters containing HCB and other pollutants, using the standardized polyurethane foam units （PFU） method. Field samples were taken from eight stations established along the Fuhe River in January and August 2006. The concentration ratios of HCB in microbial communities and in water were 9.66-18.64, and the microbial communities accumulated 13.29-56.88 μg/L of HCB in January and 0.82-10.25 μg/L HCB in August. Correlation analysis showed a negative correlation between the HCB contents in the microbial assemblage, and the number of species and the diversity index of the protozoan communities. This study demonstrated the applicability of the PFU method in monitoring the effects of HCB on the level of microbial communities.     

淀浦河水体中氨氮、总氮和总磷污染变化趋势及相关性分析

根据2005年至2011年的监测结果,分析了淀浦河中下游河段的氨氮、总氮和总磷近几年污染变化趋势,并探讨了氨氮、总氮和总磷的相关性。结果表明,淀浦河总氮和总磷的年均浓度均超过水体富营养化的临界浓度,水体富营养化严重。氨氮、总氮和总磷相互之间存在显著相关性,可以通过氨氮、总氮和总磷中某一参数的测定,确定其他两个参数的数值范围,进而确定测定时的稀释倍数,有利于提高监测效率。     

上海大气质量与材料腐蚀速度的相关关系

为了研究材料腐蚀速度与大气质量的相关关系，进行了材料暴露试验。结果表明：⑴碳钢、铜、铜合金和大理石等材料，其完全暴露的腐蚀速度约为遮蔽暴露腐蚀速度的1倍；⑵铜、铜合金的腐蚀速度与SO2浓度非常相关，与TSP浓度显著相关，碳钢的腐蚀速度与SO2和TSP浓度也有一定的相关性；⑶铜、铜合金的腐蚀速度与SO4^2-湿沉降强度明显相关，而与NO^-3湿沉降强度无明显相关；⑷碳钢的腐蚀速度约为青天铜的50倍，纯铜的15倍。     

2013-2018年北京市PM2.5污染波动特征研究

利用2013—2018年北京市大气污染物监测数据及气象条件等资料,分析了北京市PM_(2.5)污染波动变化趋势及其影响因素。结果表明,2013—2018年北京市空气质量呈现整体改善趋势,优良天数由2013年的176 d增加至2018年的227d;重污染天数显著减少,由2013年的58 d逐年递减至2018年的14 d。受污染源排放、特殊气候现象、气象条件等多因素影响,近6年北京市ρ(PM_(2.5))月均值呈现波动下降趋势,其中秋、冬季波动性更加突显。2014—2016年北京市秋冬季PM_(2.5)污染突出,其中2014年10月、2015年11—12月、2016年12月ρ(PM_(2.5))月均值均达到中度污染级别;而2017—2018年北京市秋、冬季ρ(PM_(2.5))月均值均处于优良水平。相关性分析结果显示,地面相对湿度、中层温度与大气污染物呈现较强的正相关性,中层北风频率、地面风速则呈现负相关性。基于上述气象条件及CO、SO_2和NO_2等气态污染物共同构建的拟合方程对ρ(PM_(2.5))估算结果较好,多站点的拟合值与实际值的相关系数为0.900～0.947,进一步说明气象条件及相关污染源排放对PM_(2.5)污染具有显著影响。     

颗粒物质量浓度对大气能见度水平影响分析

通过观察不同天气条件下颗粒物质量浓度水平上升伴随大气能见度水平下降,对颗粒物质量浓度-大气能见度相关性分析,得到相关方程,根据颗粒物污染水平分析预测大气能见度,为灰霾预报提供依据.     

Influence of urban spatial and socioeconomic parameters on PM2.5 at subdistrict level: A land use regression study in Shenzhen, China

The intraurban distribution of PM_2.5 concentration is influenced by various spatial, socioeconomic, and meteorological parameters. This study investigated the influence of 37 parameters on monthly average PM_2.5 concentration at the subdistrict level with Pearson correlation analysis and land-use regression (LUR) using data from a subdistrict-level air pollution monitoring network in Shenzhen, China. Performance of LUR models is evaluated with leave-one-out-cross-validation (LOOCV) and holdout cross-validation (holdout CV). Pearson correlation analysis revealed that Normalized Difference Built-up Index, artificial land fraction, land surface temperature, and point-of-interest (POI) numbers of factories and industrial parks are significantly positively correlated with monthly average PM_2.5 concentrations, while Normalized Difference Vegetation Index and Green View Factor show significant negative correlations. For the sparse national stations, robust LUR modelling may rely on a priori assumptions in direction of influence during the predictor selection process. The month-by-month spatial regression shows that RF models for both national stations and all stations show significantly inflated mean values of R² compared with cross-validation results. For MLR models, inflation of both R² and R²_CV was detected when using only national stations and may indicate the restricted ability to predict spatial distribution of PM_2.5 levels. Inflated within-sample R² also exist in the spatiotemporal LUR models developed with only national stations, although not as significant as spatial LUR models. Our results suggest that a denser subdistrict level air pollutant monitoring network may improve the accuracy and robustness in intraurban spatial/spatiotemporal prediction of PM_2.5 concentrations.