分层开采工艺对地表沉降的影响研究

分层开采是厚煤开采的经典工艺,这种工艺对地表沉降的影响比较复杂。通过测试原岩物理力学参数,利用有限元软件flac3D对分层和一次采全高时地表沉降进行了数值模拟。结果表明,如果采高较小,砌体梁距煤层较近,且采完上分层后长时间停采,给顶板再生留足时间,分层开采较一次采全高对地表沉降影响要小。     

Analysis of the Trend and Seasonal Cycle of Carbon Monoxide Concentrations in an Urban Area (4 pp)

Background, Aim and Scope Air quality is an field of major concern in large cities. This problem has led administrations to introduce plans and regulations to reduce pollutant emissions. The analysis of variations in the concentration of pollutants is useful when evaluating the effectiveness of these plans. However, such an analysis cannot be undertaken using standard statistical techniques, due to the fact that concentrations of atmospheric pollutants often exhibit a lack of normality and are autocorrelated. On the other hand, if long-term trends of any pollutant’s emissions are to be detected, meteorological effects must be removed from the time series analysed, due to their strong masking effects. Materials and Methods The application of statistical methods to analyse temporal variations is illustrated using monthly carbon monoxide (CO) concentrations observed at an urban site. The sampling site is located at a street intersection in central Valencia (Spain) with a high traffic density. Valencia is the third largest city in Spain. It is a typical Mediterranean city in terms of its urban structure and climatology. The sampling site started operation in January 1994 and monitored CO ground level concentrations until February 2002. Its geographic coordinates are W0°22′52″ N39°28′05″ and its altitude is 11 m. Two nonparametric trend tests are applied. One of these is robust against serial correlation with regards to the false rejection rate, when observations have a strong persistence or when the sample size per month is small. A nonparametric analysis of the homogeneity of trends between seasons is also discussed. A multiple linear regression model is used with the transformed data, including the effect of meteorological variables. The method of generalized least squares is applied to estimate the model parameters to take into account the serial dependence of the residuals of this model. This study also assesses temporal changes using the Kolmogorov-Zurbenko (KZ) filter. The KZ filter has been shown to be an effective way to remove the influence of meteorological conditions on O₃ and PM to examine underlying trends. Results The nonparametric tests indicate a decreasing, significant trend in the sampled site. The application of the linear model yields a significant decrease every twelve months of 15.8% for the average monthly CO concentration. The 95% confidence interval for the trend ranges from 13.9% to 17.7%. The seasonal cycle also provides significant results. There are no differences in trends throughout the months. The percentage of CO variance explained by the linear model is 90.3%. The KZ filter separates out long, short-term and seasonal variations in the CO series. The estimated, significant, long-term trend every year results in 10.3% with this method. The 95% confidence interval ranges from 8.8% to 11.9%. This approach explains 89.9% of the CO temporal variations. Discussion The differences between the linear model and KZ filter trend estimations are due to the fact that the KZ filter performs the analysis on the smoothed data rather than the original data. In the KZ filter trend estimation, the effect of meteorological conditions has been removed. The CO short-term componentis attributable to weather and short-term fluctuations in emissions. There is a significant seasonal cycle. This component is a result of changes in the traffic, the yearly meteorological cycle and the interactions between these two factors. There are peaks during the autumn and winter months, which have more traffic density in the sampled site. There is a minimum during the month of August, reflecting the very low level of vehicle emissions which is a direct consequence of the holiday period. Conclusions The significant, decreasing trend implies to a certain extent that the urban environment in the area is improving. This trend results from changes in overall emissions, pollutant transport, climate, policy and economics. It is also due to the effect of introducing reformulated gasoline. The additives enable vehicles to burn fuel with a higher air/fuel ratio, thereby lowering the emission of CO. The KZ filter has been the most effective method to separate the CO series components and to obtain an estimate of the long-term trend due to changes in emissions, removing the effect of meteorological conditions. Recommendations and Perspectives Air quality managers and policy-makers must understand the link between climate and pollutants to select optimal pollutant reduction strategies and avoid exceeding emission directives. This paper analyses eight years of ambient CO data at a site with a high traffic density, and provides results that are useful for decision-making. The assessment of long-term changes in air pollutants to evaluate reduction strategies has to be done while taking into account meteorological variability     

Risk-evaluation of Hi-tech Enterprise in the Process of Approaching Global Market

In the high technology industry, small and medium sized technology enterprises (SMSTEs) play a pivotal role in advancing the whole industry. To achieve sustainable development, they need to extend their scope of business activities beyond a national view and exploit international market actively to meet international competitions that increase quickly in the form of allocating resources within the scope of the world. However, the SMSTEs are also facing risks associated with themselves during the process of exploiting international market owing to their own restrictions, so what they should do is to consider risk evaluations in exploiting the international market.     

基于遥感尾气监测的柴油车气态污染物排放因子计算方法研究

采用遥感尾气测试系统实测了柴油车在实际道路工况下的CO、HC和NO排放特征,修正了排放因子的计算方法,并与车载排放测试系统（PEMS）实测结果进行了验证,获得了实测车辆的CO、HC和NO排放因子.测试结果显示,在各种遥感监测的工况下柴油车尾气中均含有较高浓度的氧气,未考虑氧气影响的燃烧方程反演获得的各污染物体积浓度计算值与PEMS实测值的偏差较大,且氧气浓度越大,偏差越大.经过氧气修正的燃烧方程反演计算的尾气浓度与PEMS实测值吻合度大幅提升,适用于实际工况下遥感检测车辆尾气的反演计算.修正算法得到CO、HC和NO的排放因子离散性较小,精确度较高,可以为量化柴油车尾气排放贡献提供科学依据.     

农户分化、技术约束与耕地保护技术选择差异——基于不同约束条件下的农户技术采纳理论分析框架

在不完全要素市场和农户分化背景下,探索不同类型农户、耕地保护技术约束与技术选择之间内在行为逻辑,以期为保障我国耕地质量可持续发展提供参考。利用Probit和Logit方法,通过微观数据剖析不同类型农户技术选择意愿、行为逻辑及不同约束条件下的技术选择差异。研究表明：纯农户、I类兼业户和II类兼业户在耕地保护意愿方面具有统一性,但随着非农收入的增加农户耕地保护意愿逐渐降低;在行为逻辑方面,异质性农户耕地保护技术选择上差异显著,不同类型农户的禀赋特征与不同耕地保护技术间存在非对称性和偏差,主要受不同技术属性和风险偏好的约束。因此在耕地保护技术实施与推广应用时,应当更多地考虑不同农户禀赋优势与农户风险偏好程度。     

科技创新投入对环境全要素生产率的影响机制

使用2004~2015年的中国280个地级市的面板数据,对科技创新投入与环境全要素生产率间的非线性关系、内部影响机理和空间异质性进行分析,结果显示：科技创新投入与环境全要素生产率之间呈现倒N型关系,两个拐点的位置分别为7.722（2257.47万元）和9.610（14913.17万元）;在外部资本进入、污染治理、市场规模效应3种影响路径中,科技创新投入影响下的外部资本进入对环境全要素生产率依然存在污染避难所的负向效应,科技创新投入与外部资本间效应为0.1363,外部资本与环境全要素生产率间效应为-0.0065;科技创新投入能够增强企业的污染治理技术并提高环境全要素生产率,三者间前后效应分别为-0.0277和-0.0311;科技创新的投入与高效益增强了市场规模效应,有效促进生产结构的转型进而提高环境全要素生产率,三者间前后效应为0.0186和0.4346.空间异质性中,外部资本进入与溢出效应带来的污染避难所负效应在中部地区显著,在西部和东北部地区不显著,而污染天堂正效应在东部地区存在但不显著;污染创新治理投入的技术正溢出效应在东部和西部地区效应显著,在中部和东北部不显著;科技创新投入与市场需求规模效应在空间区域无差异且显著为正.建议依据科技创新投入的不同影响路径来实施空间差异化策略.     

Development of a static test apparatus for evaluating the performance of three PM2.5 separators commonly used in China

PM_(2.5) separator directly affects the accuracy of PM_(2.5) sampling.The specification testing and evaluation for PM_(2.5) separator is particularly important,especially under China's wide variation of terrain and climate.In this study,first a static test apparatus based on polydisperse aerosol was established and calibrated to evaluate the performance of the PM_(2.5) separators.A uniform mixing chamber was developed to make particles mix completely.The aerosol concentration relative standard deviations of three test points at the same horizontal chamber position were less than 0.57%,and the particle size distribution obeyed logarithmic normal distribution with an R~2 of 0.996.The flow rate deviation between the measurement and the set point flow rate agreed to within ± 1.0% in the range of -40 to 50℃.Secondly,the separation,flow and loading characteristics of three cyclone separators(VSCC-A,SCC-A and SCC112) were evaluated using this system.The results showed that the 50% cutoff sizes(D_(50)) of the three cyclones were 2.48,2.47 and 2.44 μm when worked at the manufacturer's recommended flow rates,respectively.The geometric standard deviation(GSD) of the capture efficiency of VSCCA was 1.23,showed a slightly sharper than SCC-A(GSD = 1.27),while the SCC112 did not meet the relevant indicator(GSD = 1.2 ± 0.1) with a GSD = 1.44.The flow rate and loading test had a great effect on D_(50),while the GSD remained almost the same as before.In addition,the maintenance frequency under different air pollution conditions of the cyclones was summarized according to the loading test.     

基于野外原位抽注试验和同位素技术的含水层反硝化速率研究

反硝化作用是地下水硝酸盐污染去除最重要的过程.由于水文地质条件和水文地球化学环境的复杂性和不确定性,精准测定含水层反硝化速率是反硝化过程的研究难点.选取潮白河冲洪积扇中部中国环境科学研究院地下水创新野外基地作为研究区,基于野外原位试验和15N同位素示踪法提出一种含水层反硝化速率的测定方法.该方法综合体现了研究区实际水文地质条件和水文地球化学环境对反硝化作用的影响,并充分考虑了硝酸盐在含水层中稀释弥散作用对计算结果的影响.结果表明:①潮白河冲洪积扇中部某地地下26~28 m处于还原环境,含水介质以粉细砂为主,ρ（NO₃-N）平均值为2.77 mg/L.②地下26~28 m反硝化速率在349.52~562.99 μg/（kg·d）（以N计,下同）之间,平均值为450.31 μg/（kg·d）.通过与研究区含水介质、采样深度和硝酸盐背景值相似的国内外案例对比研究,初步评估结果处于合理区间.③测试结果具有一定不确定性,主要来自忽略中间产物NO₂-和NO的计算方法、扰动采样方法、N₂O的操作规范程度及采样频率等方面.研究方法为测定含水层硝酸盐速率研究提供了新的思路,研究结果可为地下水中硝酸盐转化过程机理研究、地下水硝酸盐污染修复及风险管控提供关键的理论支撑数据.      

人工智能技术对长江流域水污染治理的思考

随着经济的快速发展和城市化进程的不断加速,促使水污染严重的长江流域需从污染物去除过程的建模与优化、污水处理过程的优化控制、水污染监测系统的构建开展水污染治理研究.传统的水污染处理技术存在污染物去除效率预测精度较低、污水优化控制成本较高、水污染监测滞后效应严重的问题.人工智能技术能够有效克服上述问题,因此通过梳理国内外学者利用人工智能技术在污水污染物去除过程的建模与优化、污水处理过程的优化控制及水污染监测系统的构建等方面的研究成果,为全面加强长江流域水污染治理能力提供科学可靠的技术指导.结果表明:①利用人工神经网络技术（径向基神经网络、多层前馈网络-人工神经网络、多层感知器神经网络）对污水污染物去除过程进行建模与优化,为精确预测长江流域重金属（Cr、Cu）、营养盐（TN、TP）、持久性有机污染物〔PBDEs（多溴二苯醚）、HCH（六氯环己烷）〕的去除率提供重要参考价值.②采用污水处理的自动控制技术与人工智能技术（递归神经网络、支持向量机、模糊神经网络等）构建污水智能控制系统,为长江流域实现高效节能的污水优化控制提供重要的技术指导.③利用在线监测仪器和人工智能技术（小波神经网络、多元线性回归-人工神经网络、叠层去噪自动编码器等）建立水污染智能监测系统,为解决长江流域水污染监测响应滞后问题提供有力的技术支持.因此,人工智能技术对长江流域提高污水污染物去除率,降低污水优化控制成本,提升水污染监测时效性具有重要的推广价值.