Density functional theory (DFT) studies of vanadium-titanium based selective catalytic reduction (SCR) catalysts

Based on density functional theory (DFT) and basic structure models, the chemical reactions on the surface of vanadium-titanium based selective catalytic reduction (SCR) denitrification catalysts were summarized. Reasonable structural models (non-periodic and periodic structural models) are the basis of density functional calculations. A periodic structure model was more appropriate to represent the catalyst surface, and its theoretical calculation results were more comparable with the experimental results than a non-periodic model. It is generally believed that the SCR mechanism where NH₃ and NO react to produce N₂ and H₂O follows an Eley-Rideal type mechanism. NH₂NO was found to be an important intermediate in the SCR reaction, with multiple production routes. Simultaneously, the effects of H₂O, SO₂ and metal on SCR catalysts were also summarized.     

Coupling mechanism of activated carbon mixed with dust for flue gas desulfurization and denitrification

To clarify the effect of coking dust, sintering dust and fly ash on the activity of activated carbon for various industrial flue gas desulfurization and denitrification, the coupling mechanism of the mixed activated carbon and dust was investigated to provide theoretical reference for the stable operation. The results show that coking dust had 34% desulfurization efficiency and 10% denitrification efficiency; correspondingly, sintering dust and fly ash had no obvious desulfurization and denitrification activities. For the mixture of activated carbon and dust, the coking dust reduced the desulfurization and denitrification efficiencies by blocking the pores of activated carbon, and its inhibiting effect on activated carbon was larger than its own desulfurization and denitrification activity. The sintering dust also reduced the desulfurization efficiency on the activated carbon while enhancing the denitrification efficiency. Fly ash blocked the pores of activated carbon and reduced its reaction activity. The reaction activity of coking dust mainly came from the surface functional groups, similar to that of activated carbon. The reaction activity of sintering dust mainly came from the oxidative property of Fe₂O₃, which oxidized NO to NO₂ and promoted the fast selectively catalytic reduction (SCR) of NO to form N₂. Sintering dust was activated by the joint action of activated carbon, and both had a coupling function. Sintering dust enhanced the adsorption and oxidation of NO, and activated carbon further promoted the reduction of NO_x by NH₃; thus, the denitrification efficiency increased by 5%-7% on the activated carbon.     

综合生态修复系统治理城市河道富营养化

以河道富营养化治理为研究对象,通过引清入河、水下种植沉水植物、混养鲢鳙等水生动物,并应用原位修复装置等形成1个相互配合的综合生态修复系统,对河道富营养化进行治理。于2017年8月-2018年7月,对5个采样点河道水体富营养化指标进行测量,结果表明:河道水体中总氮（TN）浓度、总磷（TP）浓度、高锰酸钾盐（COD_{M n}）、氨氮（NH₃-N）浓度显著下降,水体透明度明显提升。这说明采用综合生态修复系统治理城市河道治理风险低、治理效果佳,可以推广使用。     

洪泽湖不同入湖河流沉积物磷形态特征及生物有效性

为揭示洪泽湖入湖河流沉积物磷形态空间差异性及影响因素,分析了洪泽湖自西北向西南7条入湖河流65个表层沉积物中不同磷（P）形态,并探讨了磷形态空间赋存特征的影响因素及环境意义.研究表明：沉积物总磷（TP）含量为488.90mg/kg~960.22mg/kg,无机磷（Pi）为主要形态,相对含量为65.81%~76.16%.西部入湖流域沉积物有机磷（Po）以非活性有机磷（NLOP）为主,汴河最高,相对含量约占Po的50.41%,生物有效态无机磷（BAP）相对含量最高,占Pi的66.84%,污染程度最高;西南和西北入湖流域Po则以中活性有机磷（MLOP）为主,Pi以钙结合态无机磷（HCl-Pi）为主.西北入湖流域由于受当地地质背景的影响,HCl-Pi所占Pi相对含量最高（43.02%）,从而减缓了磷的移动能力,污染程度最低.随着沉积物污染程度的增加,生物有效态Po含量增加,但所占Po相对含量降低;HCl-Pi含量增加,所占Pi相对含量降低,这一现象和我国其它典型地区沉积物磷形态空间分布类似.西部和西南入湖流域主要受水土流失、有机面源污染及藻类生长的影响,有机质环境较高,水交换能力弱,可被有机质降解的Po组分高于可被矿化的Po组分,大部分难降解Po组分易沉积,导致西部和西南入湖流域较高的BAP和NLOP含量,富营养化程度较高.沉积物OM是各形态磷之间相互转化的关键因素,和沉积物内源磷地球生物化学循环密切相关.洪泽湖入湖流域沉积物磷形态空间差异性主要由农业面源污染物的输入而导致内源磷负荷加剧.洪泽湖西部和西南入湖流域应重点控制农田水土流失及养殖业面源污染,建设滨岸修复带,遵循少量多次增施有机肥原则,减少农用地水土流失.健全农村养殖业废水废渣处理;划定科学养殖区;提倡铜围网箱,增加水体交换率.而对于洪泽湖西北入湖流域则应重点防止过度城镇化带来的水土流失及对生态功能保护区过高的污染负荷.     

融合Lamb-Jenkinson分型法和LSTM神经网络的PM2.5预测研究

文章采用NCEP/NCAR逐日海平面气压场资料,利用Lamb-Jenkinson环流分型法对张家口大气环流进行分型,分析环流型与PM_(2.5)质量浓度之间的关系,并针对PM_(2.5)浓度的预测,提出一种融合Lamb-Jenkinson环流分型和LSTM神经网络混合模型的方法,即以环流指数为预测因子基于LSTM方法搭建PM_(2.5)质量浓度的预测模型。结果表明:影响张家口地区的主要环流型有反气旋型、气旋型、偏北平直型、西南平直型、偏西平直型、东北平直型等、西北平直型、偏东平直型。PM_(2.5)污染日出现的主要环流型为南气旋平直型、东南平直型、偏南平直型、偏东气旋型、西南气旋平直型、偏东平直型、气旋型等,而反气旋型和反气旋式平直环流型不利于污染出现。张家口地区的PM_(2.5)污染与地面环流有着密切的联系,当存在PM_(2.5)污染时,张家口地区处于日本海高压后部的均压场区域,污染越严重,日本海高压中心强度越强。模型预测结果的均方根误差为9.88、平均绝对误差为5.84、拟合优度达0.80,表明该模型具有一定的预报能力。     

Cr(Ⅵ)踪迹指标现场测定用于铬污染地下水源解析

根据研究区地下水样品测试结果,该文选定与Cr(Ⅵ)极强相关,且物理化学性质较稳定的钠离子作为研究地下水中Cr(Ⅵ)迁移规律的踪迹指标,并采用钠离子复合电极建立了踪迹指标现场检测方法。实验结果表明,钠离子浓度在5～500 mg/L线性范围内的电极响应斜率为-61.09 mV/pNa(103%),方法检出限为0.69 mg/L,加标回收率为92.8%～103.4%,现场测试结果与实验室测试结果一致。该研究根据踪迹指标钠离子与污染物现场检测数据,构建了钠离子与Cr(Ⅵ)浓度比值的对数函数,并有效识别出主污染源、次级污染源、污染物迁移主路径、潜在污染区、潜在影响区及背景区,为铬渣类污染场地土壤和地下水环境风险评价及污染修复提供了技术支撑和参考依据。     

长江经济带水质目标管理平台总体设计

为强化长江经济带资源整合与共享,集成统一规范的大数据平台,基于“十一五”“十二五”国家水体污染控制与治理科技重大专项数据和模型库资源,以面向服务的架构(SOA)和模块化设计为支撑,遵循“五横两纵四统一”的平台架构设计思路,应用大数据挖掘、云计算等现代信息技术,构建长江经济带水质目标管理平台.平台基于长江经济带水生态环境功能分区,兼顾不同类别水质目标管理技术的协调性、衔接性和适应性,对水质目标管理相关信息进行跟踪、模拟、分析和三维可视化表达,在水生态环境功能分区管理、数据汇交与信息共享、容量总量管理、风险评估与预警等方面实现业务化运行,实现全景式水质达标形势研判、一体化风险联防联控.平台已在国家长江生态环境保护修复联合研究中心进行业务化运行,将有效提升长江经济带水环境综合管理能力,同时可为其他重要流域水质目标管理提供信息化工作参考.      

Adjusting sowing date and cultivar shift improve maize adaption to climate change in China

Mitigation and Adaptation Strategies for Global Change - This study investigates the impact of climate change on spring and summer maize (Zea mays) yield and evaluates several adaptation measures...     

Optimal range of plug-in electric vehicles in Beijing and Shanghai

Both China’s national subsidy policies for plug-in electric vehicles (PEVs) purchasers and passenger cars corporate average fuel consumption and new vehicle credit regulation (dual-credit policy) favor long-range 300+ km battery electric vehicles (BEVs) and 80+ km plug-in hybrid electric vehicles (PHEVs). However, these electric vehicles tend to have lower energy efficiency and higher purchase and operation costs. Vehicle with larger batteries can also be less equitable because the subsidies are often provided to more expensive vehicles and wealthier owners. This study takes advantage of a novel dataset of daily driving data from 39,854 conventional gasoline vehicles in Beijing and 4999 PHEVs in Shanghai to determine the optimal range of BEVs and PHEVs within their respective cities. We simulate a model to explore ranges with which PEVs emit less GHGs than that of a baseline hybrid and conventional gasoline vehicle while ensuring that all daily travel demands are met. Our findings indicate that in both cities, the optimal ranges to balance cost and travel demand for BEVs are 350 km or less and for PHEVs are 60 km or less in Beijing and 80 km or less in Shanghai. We also find that to minimize carbon dioxide (CO₂) emissions, the ranges are even lower 10 km in Beijing and 30 km in Shanghai. Our study suggests that instead of encouraging long-range PEVs, governments should subsidize PEV models with shorter ranges. Parallel efforts should also be made to both increase renewable energy over fossil fuels and expand charging facilities. Although individual mobility demand varies, the government could reduce occasional long-distance driving by subsidizing alternative transportation choices. Providing week-long driving trials to consumers before their purchases may help decrease the demand of very long range PEVs by alleviating the range anxiety through a learning process.