以经济学实验研究处罚机制对排污收费政策执行的影响

为研究处罚机制对排污收费政策执行效果的影响,建立了排污收费政策下风险中性企业的最优决策模型,设计了经济学实验.采用数据统计、线性随机效应模型、单因素不等重复实验方差分析等方法分析实验数据,验证了该模型得出的假设.结果表明,边际处罚期望对于企业的违法量和排放量决策均有显著负影响;企业边际减排成本对于企业的排放量决策有显著正影响,对于违法量决策没有显著影响;相同边际处罚期望下,监测频率越高,企业的服从率越高,且在边际处罚期望较高时,更为明显.因此,提高边际处罚期望可同时改善企业违法行为与促进企业减排.同时,为降低执行成本,在边际处罚期望较低时,可首先将线性罚款向梯级罚款转变.当边际处罚期望上升到较高水平时,则应注重监测频率的提高,并应重点监控那些排污量大而不是边际减排成本高的企业.     

Pollutants removal and simulation model of combined membrane process for wastewater treatment and reuse in submarine cabin for long voyage

A laboratory scale test was conducted in a combined membrane process (CMP) with a capacity of 2.91 m3/d for 240 d to treat the mixed wastewater of humidity condensate, hygiene wastewater and urine in submarine cabin during prolonged voyage. Removal performance of chemical oxygen demand (COD), ammonia nitrogen (NH4 +-N), turbidity and anionic surfactants (LAS) was investigated under di erent conditions. It was observed that the e uent COD, NH4 +-N, turbidity and LAS flocculated in ranges of 0.19–0.85 mg/L, 0.03–0.18 mg/L, 0.0–0.15 NTU and 0.0–0.05 mg/L, respectively in spite of considerable fluctuation in corresponding influent of 2120–5350 mg/L, 79.5–129.3 mg/L, 110–181.1NTU and 4.9–5.4 mg/L. The e uent quality of the CMP could meet the requirements of mechanical water and hygiene water according to the class I water quality standards in China (GB3838-2002). The removal rates of COD, NH4 +-N, turbidity and LAS removed in the MBR were more than 90%, which indicated that biodegradation is indispensable and plays a major role in the wastewater treatment and reuse. A model, built on the back propagation neural network (BPNN) theory, was developed for the simulation of CMP and produced high reliability. The average error of COD and NH4 +-N was 5.14% and 6.20%, respectively, and the root mean squared error of turbidity and LAS was 2.76% and 1.41%, respectively. The results indicated that the model well fitted the laboratory data, and was able to simulate the removal of COD, NH4 +-N, turbidity and LAS. It also suggested that the model proposed could reflect and manage the operation of CMP for the treatment of the mixed wastewaters in submarine.     

海上溢油扩散图像处理的非线性方法研究

针对海上溢油应急处理问题,本文主要对溢油的初级行为--扩散进行探讨.提出了采用溢油扩散图像来预测溢油扩散未来发展趋势的3步非线性处理过程,即图像边缘检测、面积计算和面积预测,对这一过程中应采用的方法进行了分析与比较.并以奥里油在静止海水中扩散为范例,在MATLAB环境下,利用非线性方法对扩散图像进行边缘监测,通过对梯度算子阀值的调整来计算完整的油膜覆盖面积,并将其计算结果进行BP神经网络预测.结果表明:采用Roberts边缘算子可以得到很好的边缘检测结果,采用BP神经网络获得的面积预测结果与实验结果吻合程度较好.     

改良A~2/O工艺预缺氧池中的脱氮作用和机理

改良A2/O工艺中预缺氧池有较强的脱氮作用,其脱氮作用占整个系统氮去除率的15.11%。通过对预缺氧池氮元素进行物料平衡,分析和证实改良A2/O预缺氧池中可以发生厌氧氨氧化反应,可以有效减少能耗和降低运行成本,这对我国污水厂的改造,提高出水水质,具有积极意义。     

活性污泥法处理甲苯废气吸收液的研究

以甲苯废气吸收液为研究对象,利用活性污泥法降解吸收液中的污染物,研究了吸收液与生活污水混合比,重点分析了反应体系降解中污染物COD、SS、SCOP和甲苯的浓度变化。实验结果表明,当吸收液与生活污水体积比为5:95,曝气量5L/min,连续曝气4h的条件下,COD、SS、SCOP和甲苯的去除率达到77.18%、94.59%、100%和89.47%,甲苯的好氧降解符合准一级动力学方程。     

基于厌氧氨氧化和中温亚硝化的可持续生物脱氮工艺

通过介绍厌氧氨氧化技术（ANAMMOX）和亚硝化技术（SHARON）在污水脱氯处理中的原理,着重从工艺特性分析以及控制因数方面介绍SHARON—ANAMMOX联合工艺,并通过与传统工艺的比较,指出SHARON—ANAMMOX联合工艺是可持续性处理工艺。     

燃煤锅炉烟气氨法脱硫技术的应用

电厂燃煤锅炉烟气脱硫是减少和控制酸雨的有效手段。LS氨法喷雾脱硫技术具有脱硫效率高、环境效益好、资源综合利用的特点。以合成氨生产装置回收的低浓度氨水为吸收剂,实施锅炉烟气脱硫技术改造．取得良好的应用效果。     

中欧节能减排政策比较

欧盟国家开展节能减排较早,并积累了丰富的经验。比较了在金融危机影响下欧盟与中国在节能减排法律框架、管理方式、经济政策、产业政策和技术创新方面的异同,提出中国应该借鉴欧盟国家的先进经验,完善现有的节能减排政策体系,实现经济和社会的可持续发展。     

流程制造业与循环经济

阐述了发展循环经济的意义与循环经济的内涵,提出技术-经济及时空因素的集成与协调是推进循环经济的有效手段。在我国实现新型工业化的过程中,流程制造业既是支柱产业、基础产业,也是推进循环经济的重要切入点。     

Collectively engaging complex socio-ecological systems: re-envisioning science, governance, and the California Delta

We address the future of science and governance for the California Delta, focusing on the CALFED Bay-Delta Program, an interagency, multi-stakeholder effort to understand and manage the Delta for multiple purposes. We portray a Delta history as a coevolutionary process between science, governance and ecosystems. Global integrated environmental assessments (IEA) provide insights into understanding complex, dynamic socio-ecological systems. Many of the discursive stakeholder and scientific activities that have arisen under CALFED are similar to IEA and remain essential to the shared learning needed to effectively interact with a dynamic Delta. More deliberately enmeshing environmental monitoring, analysis, and collective learning into Delta governance will improve outcomes.