Modeling of a sequencing batch reactor treating municipal wastewater using multi-layer perceptron and radial basis function artificial neural networks

A sequencing batch reactor was modeled using multi-layer perceptron and radial basis function artificial neural networks (MLPANN and RBFANN). Then, the effects of influent concentration (IC), filling time (FT), reaction time (RT), aeration intensity (AI), SRT and MLVSS concentration were examined on the effluent concentrations of TSS, TP, COD and NH₄⁺-N. The results showed that the optimal removal efficiencies would be obtained at FT of 1 h, RT of 6 h, aeration intensity of 0.88 m³/min and SRT of 30 days. In addition, COD and TSS removal efficiencies decreased and TP and NH₄⁺-N removal efficiencies did not change significantly with increases of influent concentration. The TSS, TP, COD and NH₄⁺-N removal efficiencies were 86%, 79%, 94% and 93%, respectively. The training procedures of all contaminants were highly collaborated for both RBFANN and MLPANN models. The results of training and testing data sets showed an almost perfect match between the experimental and the simulated effluent of TSS, TP, COD and NH₄⁺-N. The results indicated that with low experimental values of input data to train ANNs the MLPANN models compared to RBFANN models are more precise due to their higher coefficient of determination (R²) and lower root mean squared errors (RMSE) values.     

CDM in the Kyoto Negotiations:

The Clean Development Mechanism (CDM) under the Kyoto Protocol to the UN Framework Convention on Climate Change (UNFCCC) has its origins in the decade of UNFCCC negotiations. ‘Joint implementation’ and ‘activities implemented jointly pilot’ opened the door for the project-based mechanisms between developed and developing countries. The US proposal of the Joint Implementation in the Kyoto Protocol negotiations was almost identical with CDM approved in Kyoto; however, a detour around the Clean Development Fund (CDF) concept raised by Brazil in the negotiations catalyzed the mutual understanding on the win-win nature of the concept of joint implementation.CDM has been played an important role to bridge the developed and developing countries in its development process initiated as the joint implementation in the UNFCCC, and can lead to the cooperative future in the implementation stage starting from the year 2003, including the development of future commitments beyond 2013. This revised version was published online in August 2006 with corrections to the Cover Date.     

论环境产业

本文在可持续发展视角下,把环境的保护、修复、维护的生产活动及与之直接相关的服务活动称为环境产韭,包括发挥减少、避免污染环境作用的资源再利用鼗和发挥治理污染物与修复、改善环境作用的环境维护业.通过探讨环境产业的内涵、发展历程、运行机制和在产业体系中的位置与作用,指出环境产业是在法规保障下政府强行推动产生和发展起来的,是产业体系中不可缺少的重要组成部分;考虑自然环境对社会行为的影响,改进政府行为构建适台环境产业与传统产业协调发展的经济体制是加快发展环境产业的关键.     

论土地持续利用

在世界上有两种可持续发展思路，一种是西方发达国家的重保护的可持续发展思路；一种是以发展为前提，保护自然资源的可持续发展思路。土地持续利用的思想是在可持续发展的进程中不断发展的。我国要保证土地持续利用，满足未来对食粮和建设的需求，应建立起同土地持续利用相适应的土地持续利用制度和土地持续利用机制     

硫化亚铁处理含砷废水中砷的形态变化

本文对用硫化亚铁处理含砷废水时，在气相、液相和固相中砷的形态进行了研究结果表明，在气相中无ＡａＨ３，但在Ａｓ（Ｖ）废水的液相中有Ａｓ（Ｖ）和Ａｓ（Ⅲ）共同存在，在固相中有Ａｓ（０），ＦｅＡｓＯ４（ＦｅＡｓＯ３），Ａｓ２Ｓ３（Ａｓ２Ｓ５）和吸附砷，砷的形态变化表明，硫化亚铁处理含砷废水能取得良好的效果，是沉淀、沉淀转化、氧化还原、吸附共沉淀和中和五种反应共同作用的结果。     

省以下生态转移支付制度环境保护激励效应

现有文献认为生态转移支付具有基本公共服务均等化与提升地方生态环境质量双目标,而目标的多样性会影响地方财政转移支付资金效果及目标的实现。文章基于环保支出和农林水支出的中介与调节效应,对生态转移支付的生态环境目标进行了理论分析,利用2010—2018年甘肃、贵州、湖北及河南四省的199个县的面板数据进行实证检验。实证研究表明:在样本期内,生态转移支付促进了地方生态环境质量的提升,中介效应和调节效应模型的结果表明,中国地方生态转移支付资金对辖区环境保护效果中,环境保护支出起到部分中介效应,农林水支出不仅调节了生态转移支付的地方环境保护支出效果,而且调节了环境保护支出对地方环境质量的影响。因此,由于地方政府具有环境治理信息优势,省以下制度目标更能体现辖区生态需求,省对县生态转移支付制度会有效促进地方生态环境质量的改善,环保激励效应较为明显。同时,县级地方政府应该逐步摆脱"先污染后治理"的路径依赖,逐步转向经济与环境"双目标协同发展"模式。为了协同生态转移支付的双目标,"自下而上参与式决策"可以作为环境治理的有益补充,通过地方政府多元化实践改善环境质量。     

北京南部城区PM2.5中碳质组分特征

为了解《大气污染防治行动计划》实施后北京市大气PM_2.5中碳质组分特征,于2017年12月至2018年12月在北京污染较重的南部城区进行了PM_2.5连续采样,对其中的有机碳（OC）和元素碳（EC）进行了全面研究.结果表明,北京大气PM_2.5、OC和EC浓度变化范围分别为4.2~366.3、0.9~74.5和0.0~5.5 μg ·m^-3,平均浓度分别为（77.1±52.1）、（11.2±7.8）和（1.2±0.8）μg ·m^-3,碳质组分（OC和EC）整体占PM_2.5的16.1%.OC质量浓度季节特征表现为：冬季[（13.8±8.7）μg ·m^-3] > 春季[（12.7±9.6）μg ·m^-3] > 秋季[（11.8±6.2）μg ·m^-3] > 夏季[（6.5±2.1）μg ·m^-3],EC四季质量浓度水平均较低,范围为0.8~1.5 μg ·m^-3.二次有机碳（SOC）年均质量浓度为（5.4±5.8）μg ·m^-3,四季贡献比例范围为45.7%~52.3%,年均贡献为48.2%,凸显了二次形成的重要贡献.随污染加重,尽管OC和EC贡献比例均降低,但浓度水平却成倍升高,OC和EC浓度在严重污染天分别是空气质量为优天的6.3和3.2倍.与非供暖时段相比,供暖时段PM_2.5、OC和SOC浓度分别增加了14.4%、47.9%和72.1%,体现了OC对供暖季PM_2.5污染的重要贡献.PSCF分析表明,位于北京西南的山西省和河南省部分区域是PM_2.5和OC的主要潜在源区,且PM_2.5潜在源区更为集中;EC的PSCF高值（>0.7）区域较少,主要位于北京南部,如山东省和河南省部分地区,且北京市及周边地区贡献明显.     

铝系混凝剂优势形态分析及其混凝特性

聚合氯化铝（PACl）是常用的水处理混凝剂,在应用过程中通常表现出比传统铝盐更为优异的效果.研究表明,这种优异性能主要得益于其特殊的组成,特别是高分子聚合物Al₁₃和Al₃₀独特的物化特性.Al₁₃和Al₃₀是铝离子水解过程中的中间产物,在地球科学和环境化学等领域有着重要的研究价值.于水处理而言,二者的结构和分子特性是研究者关注的重点,大量研究基于此展开,很多重要的发现为实际应用奠定了基础.基于对PACl及其组成性质的研究,本文对PACl的混凝特性及其优势形态分子的分析进行了综合阐述.     

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.     

Role of glycine on sulfuric acid-ammonia clusters formation: Transporter or participator

Glycine(Gly) is ubiquitous in the atmosphere and plays a vital role in new particle formation(NPF).However,the potential mechanism of its on sulfuric acid(SA)-ammonia(A)clusters formation under various atmospheric conditions is still ambiguous.Herein,a(Gly)_x·(SA)_y·(A)_z(z≤x+y≤3) multicomponent system was investigated by using density functional theory(DFT) combined with Atmospheric Cluster Dynamics Code(ACDC) at different temperatures and precursor concentrations.The results show that Gly,with one carboxyl(-COOH) and one amine(-NH_2) group,can interact strongly with SA and A in two directions through hydrogen bonds or proton transfer.Within the relevant range of atmospheric concentrations,Gly can enhance the formation rate of SA-A-based clusters,especially at low temperature,low [SA],and median [A].The enhancement(R) of Gly on NPF can be up to 340 at T=218.15 K,[SA]=10~4,[A]=10~9,and [Gly]=10~7 molecules/cm~3.In addition,the main growth paths of clusters show that Gly molecules participate into cluster formation in the initial stage and eventually leave the cluster by evaporation in subsequent cluster growth at low [Gly],it acts as an important "transporter" to connect the smaller and larger cluster.With the increase of [Gly],it acts as a "participator" directly participating in NPF.