生物炭添加和灌溉对温室番茄地土壤反硝化损失的影响

生物炭添加和灌溉是番茄地常用的田间管理措施,然而其对反硝化的影响还不清楚.本研究种植试验设置3个灌溉量水平分别为估算作物生育期需水量ET0的50%(W50%)、75%(W75%)、100%(W100%)和3个生物炭添加水平分别为B0(折合纯碳,0)、B25(折合纯碳,25 t·hm-2)、B50(折合纯碳,50 t·hm-2),在2014年和2015年番茄收获后,每个试验小区采集具有代表性的土样进行室内培养试验,采用乙炔抑制法来研究土壤的反硝化损失和不加乙炔研究N_2O的排放量.结果表明生物炭和灌溉量显著改变了土壤的理化性质.与B0相比,添加生物炭能够提高土壤全碳、全氮含量和pH值,降低铵态氮、硝态氮含量,而灌水量降低了土壤中全氮和全碳的含量.因此,与B0/W50%相比,B25/W75%和B50/W100%处理显著减少了反硝化损失量(P0.05).生物炭和灌溉量的交互作用对土壤无机氮含量和反硝化损失的影响均达到显著水平(P0.05),且对硝态氮的影响表现为灌溉量生物炭添加量两者交互作用,对铵态氮的影响表现为生物炭添加量灌溉量两者交互作用,对反硝化损失的影响表现为灌溉量生物炭添加量两者交互作用.反硝化损失量与土壤中无机氮含量、(CO_2-C)矿化量与N_2O排放量均呈正相关关系.不同生物炭添加量和灌溉量处理后明显影响了N_2O/DN(P0.05),培养结束时,各处理下的N_2O累积排放量/DN累积排放量差异较大,介于0.31%~1.88%.     

我国区域空气污染治理效率及其影响机制——基于超效率SBM模型和门槛回归模型

随着人民对美好生活需求的日益增长,政府空气污染治理的效率问题日益得到重视。本文从地方政府空气污染治理效率及其影响因素的视角入手,以全国30个省份为研究对象,运用超效率SBM模型测算2003—2015年各省级区域的空气污染治理效率。在此基础上,运用门槛回归模型分析政府空气污染治理效率的影响机制。研究表明:①地区间空气污染治理效率差异性较为显著。中部、西部空气污染治理效率整体呈下降趋势。东部和东北地区空气污染治理效率则上升比较平稳。②政策规划、碳源、污染物排放和环境治理投入表现出双重门槛特征,其中碳源对空气污染治理效率影响显著,而以碳为首的能源消费结构则主要对中部和西部空气污染治理效率产生影响。落后地区政府应注重产业升级,财政上应对碳税等税目进行征收,产业上应鼓励企业创新,并对落后企业进行倒逼升级。     

基于超效率DEA模型的三峡库区生态效率评价及空间演化格局分析

本文基于2010—2017年的统计数据,首先采用超效率DEA模型对三峡库区26个区县的生态效率进行测算,然后运用空间自相关分析方法对三峡库区生态效率的演化格局进行了实证分析,探索三峡库区生态效率的时空动态演变特征。研究表明:2010—2017年三峡库区生态效率平均水平处于0.5601～1.1920,整体呈现波动性变化趋势,生态效率在一定程度上有所改善,但是整体水平仍然较低;从区域层面看,各个区县间生态效率水平不平衡,空间分布上呈现"西高东低"的非均衡性特征。局部空间自相关分析表明,三峡库区2010—2017年集聚性呈逐渐减弱态势,空间异质性逐渐增加,整体的生态效率差异变大。最后依据实证研究分析结果,本文对如何提升三峡库区生态效率提出了相应的政策建议。     

Natech风险研究:现状、理论及展望

由自然灾害引发的工业企业环境安全事故又称为自然灾害诱发的技术事故(Natech).我国是工业大国,重化工业是我国的主导产业之一;同时我国还是世界上自然灾害严重的国家之一,Natech风险不容忽视.开展Natech风险识别、评估和管理研究,有助于我国Natech风险管理体系的完善,防范和降低区域Natech风险.目前,我国Natech风险基础研究尚处于起步阶段,难以支撑我国Natech风险防控实践.本文从Natech风险发生机制、风险评估、风险感知与最大可接受风险水平、风险管理体系等四个方面回顾了国内外Natech风险研究现状,初步梳理了Natech风险的基本理论,并对我国未来Natech风险的研究方向进行了展望,为我国Natech风险研究领域的发展提供参考.     

对燃油征税的区域能源环境影响研究:以中国为例

控制汽柴油消费对中国的能源安全和环境保护有着重要意义.燃油税和碳税是中国近期两种主要的已经或可能施加于燃油的税收政策.以自回归分布滞后模型为核心,本研究构建了一个燃油税和碳税的区域能源环境影响评估模型.利用模型估计了我国的燃油需求价格弹性,测算了燃油需求响应,计算了在相同CO2减排目标下,提高汽油消费税、提高柴油消费税、引入碳税三种政策情景下各省份预计产生的节能效应、减排效应和税收效益.研究结果显示,在相同的CO2减排目标下,第一,在不同情景下,各省份节能程度差异均有限,但节能数量均体现出区域匹配性,燃油消费越多的省份,节能数量一般越多,且提高汽油消费税的全国节能总量最大;第二,在引入碳税情景下,各省份CO2减排比例差异最小;第三,在全国层面,三种政策情景中空气污染物(PM2.5和NOx和SO2)减排数量均为提高汽油消费税>引入碳税>提高柴油消费税,但在提高柴油消费税情景下,有4/5的省份预计PM2.5排放减少程度超过14%.除此之外,提高汽油消费税的税收收益最大.     

Mitigating Impact of Devils Lake Flooding on the Sheyenne River Sulfate Concentration

Devils Lake is a terminal lake located in northeast North Dakota. Because of its glacial origin and accumulated salts from evaporation, the lake has a high concentration of sulfate compared to the surrounding water bodies. From 1993 to 2011, Devils Lake water levels rose by ~10 m, which flooded surrounding communities and increased the chance of an overspill to the Sheyenne River. To control the flooding, the State of North Dakota constructed two outlets to pump the lake water to the river. However, the pumped water has raised concerns about of water quality degradation and potential flooding risk of the Sheyenne River. To investigate these perceived impacts, a Soil and Water Assessment Tool (SWAT) model was developed for the Sheyenne River and it was linked to a coupled SWAT and CE‐QUAL‐W2 model that was developed for Devils Lake in a previous study. While the current outlet schedule has attempted to maintain the total river discharge within the confines of a two‐year flood (36 m³/s), our simulation from 2012 to 2018 revealed that the diversion increased the Sheyenne River sulfate concentration from an average of 125 to >750 mg/L. Furthermore, a conceptual optimization model was developed with a goal of better preserving the water quality of the Sheyenne River while effectively mitigating the flooding of Devils Lake. The optimal solution provides a “win–win” outlet management that maintains the efficiency of the outlets while reducing the Sheyenne River sulfate concentration to ≤600 mg/L.     

Integrated energy management strategy of powertrain and cooling system for PHEV

ABSTRACT

Energy management strategy (EMS) is crucial in improving the fuel economy of plug-in hybrid electric vehicle (PHEV). Existing studies on EMS mostly manage powertrain and cooling system separately which cannot get the minimum total energy consumption. This paper aims to propose a novel EMS for a new type of dual-motor planetary-coupled PHEV, which considers cooling power demand and effect of temperature on fuel economy. Temperature-modified engine model, lithium-ion battery model, two motors, and cooling system models are established. Firstly, the separated EMS (S-EMS) is designed which manages powertrain and cooling system separately. Sequentially, after the analysis of thermal characteristics of the powertrain and cooling system, the thermal-based EMS (T-EMS) is then proposed to manage two systems coordinately. In T-EMS, cooling power demand and the charging/discharging energy of motors are calculated as equivalent fuel consumption and integrated into the object function. Besides, a fuzzy controller is also established to deicide the fuel-electricity equivalent factor with consideration of the effect of temperature and state of charge on powertrain efficiency. Finally, the hardware-in-loop experiment is carried out to validate the real-time effect of EMS under the New European Driving Cycle. The result shows that cooling power demand and temperature can significantly affect the fuel economy of the vehicle. T-EMS shows better performance in fuel economy than S-EMS. The equivalent fuel consumption of the cooling system of T-EMS decreases by 27% compared with that of S-EMS. The total equivalent fuel consumption over the entire trip of PHEV using T-EMS is reduced by 9.7%.     

Energy consumption estimation model for dual-motor electric vehicles based on multiple linear regression

ABSTRACT

The drive range of electric vehicle (EV) is one of the major limitations that impedes its universalism. A great deal of research has been devoted to drive range improvement of EV, an accurate and efficiency energy consumption estimation plays a crucial role in these researches. However, the majority of EV’s energy consumption estimation models are based on single motor EV, these models are not suitable for dual-motor EVs, which are composed of more complex transmission mechanisms and multiple operating modes. Thus, an energy consumption estimation model for dual-motor EV is proposed to estimate battery power. This article focuses on studying the operating modes and system efficiency in each operating mode. The limitation of working area of each mode ensures the vehicle dynamic performance, then PSO algorithm is adopted to optimize the torque (speed) distribution between two motors to improve the system efficiency in the coupled driving mode. Finally, the energy consumption estimation model is established by multiple linear regression (MLR). The result shows that the proposed model has a high precision in energy consumption estimation of dual-motor EV.     

采油作业“三废”控制技术研究与应用

针对采油作业产生的废酸、固废、废水处理成本高、技术不成熟等问题,研发改性废酸降压增注、深部调剖技术;高比重污泥悬浮研磨后的固废处理技术;低耗水打塞、原井液+CaCl2压井、原井液处理再利用技术,减少了"三废"的产生,解决了"三废"环保处理费高等问题,消除了环保隐患,实现了清洁生产,环境效益显著。     

涪陵页岩气田钻井岩屑资源化利用实践

总结了涪陵页岩气田开发初期钻井岩屑采用固化填埋方式处置存在占地面积大且易产生二次污染隐患等问题,因地制宜地探索钻井岩屑的资源化利用。分析了水基岩屑随钻预处理和油基岩屑热脱附技术,结合钻井岩屑的理化性质,开展了水基岩屑脱水后干渣制路基材料、制砖及水泥窑协同处置,油基岩屑灰渣制混凝土、制砖及水泥窑协同处置的探索和实践,基于环境安全、技术稳定可靠、消纳量大的原则,最终形成了涪陵页岩气田钻井岩屑资源化方案:水基岩屑"随钻预处理、水泥窑协同处置",油基岩屑"热脱附、水泥窑协同处置",实现了钻井岩屑的资源化综合利用。