基于RF-LSTM的鸡舍恶臭气体预测研究

以鸡舍氨气为研究对象,对鸡舍氨气预测模型进行了研究.首先,利用随机森林算法（RF）对影响鸡舍氨气浓度的环境变量进行重要性排序,选取温度、湿度、光照、气象温度、降雨量作为模型的输入变量;在此基础上,构建了基于长短时记忆神经网络（LSTM）的鸡舍氨气浓度预测模型,并将提出的预测模型应用于江苏省宜兴市某养鸡场的氨气浓度预测中,并与LSTM模型、RF-Elman模型和RF-BP模型进行了对比实验,结果表明,基于RF-LSTM模型的预测效果最好,其平均绝对误差（MAE）、平均绝对百分误差（MAPE）和均方根误差（RMSE）分别为0.9183、4.9637%和1.4262;同时,为了验证该模型的性能,本文还实现了不同时间尺度的鸡舍氨气浓度预测,提前2h、3h、4h、5h氨气预测的平均绝对误差（MAE）分别为1.6218、2.1991、2.8553和3.0677.本文提出的预测模型提高了鸡舍氨气浓度的预测精度,可为减少鸡舍恶臭气体排放提供科学依据.     

建筑垃圾堆放点样本集构建与优化研究

为更好地解决手工制作的建筑垃圾堆放点样本集效率低、数据量少,难以支撑基于深度学习的遥感图像目标检测算法训练需求的问题,采用基于像素的遥感分类方法构建建筑垃圾堆放点样本集,在此基础上结合直方图均衡化,CS-LBP算子约束以及迁移学习的方法对Wasserstein生成对抗模型（WGAN）进行优化,实现了样本集扩充。研究结果表明:相对于纯手工制作的样本集,基于像素的遥感分类方法可以显著提升样本集制作的效率;同时,经过WGAN优化后,生成样本模拟了原始数据的颜色与纹理特征分布规律,增加了原始数据的多样性,满足了扩充样本集的需求。     

中国工业园区绿色发展政策对比分析及对策研究

为了提升我国工业园区绿色发展水平,对目前我国工业园区发展历程、现状特征进行了分析,对工业园区绿色发展政策进行了梳理和对比,并结合工业园区绿色发展中存在的问题提出了对策建议.研究表明:①我国工业园区经历了快速发展、调整发展和科学发展等阶段,在经济发展、资源与能源优化利用、污染减排等方面成效显著.②我国工业园区绿色发展的相关政策主要体现在国家生态工业示范园区创建、园区循环化改造、国家低碳工业园区试点、绿色园区建设和UNIDO绿色工业园区创建等工作中,这些政策在推动主体、实施路径、侧重方向上各不相同又各有特色,对推动工业园区节能减排绩效明显.③目前,我国工业园区绿色发展存在的问题主要表现在重视程度有待提升、风险防范意识有待加强、创新能力有待提高等方面.为此,提出了我国工业园区绿色发展对策建议:积极践行绿色发展理念,推进园区绿色化、生态化、低碳化建设,实现经济环境双赢;注意环境风险防控,确保环境安全;创新管理机制,强化监督管理.      

Performance of different macrophytes in the decontamination of and electricity generation from swine wastewater via an integrated constructed wetland-microbial fuel cell process

Plants constitute a major element of constructed wetlands(CWs).In this study,a coupled system comprising an integrated vertical flow CW(IVCW) and a microbial fuel cell(MFC) for swine wastewater tre atment was developed to research the effects of macrophytes commonly employed in CWs,Canna indica,Acorus calamus,and Ipomoea aquatica,on decontamination and electricity production in the system.Because of the different root types and amounts of oxygen released by the roots,the rates of chemical oxygen demand(COD) and ammonium nitrogen(NH_4~+-N) removal from the swine wastewater differed as well.In the unplanted,Canna indica,Acorus calamus,and Ipomoea aquatica systems,the COD removal rates were 80.20%,88.07%,84.70%,and 82.20%,respectively,and the NH_4~+-N removal rates were 49.96%,75.02%,70.25%,and 68.47%,respectively.The decontamination capability of the Canna indica system was better than those of the other systems.The average output voltages were 520±42,715±20,660±27,and 752±26 mV for the unplanted,Canna indica,Acorus calamus,and Ipomoea aquatica systems,respectively,and the maximum power densities were 0.2230,0.4136,0.3614,and0.4964 W/m~3,respectively.Ipomoea aquatica had the largest effect on bioelectricity generation promotion.In addition,electrochemically active bacteria,Geobacter and Desulfuromonas,were detected in the anodic biofilm by high-throughput sequencing analysis,and Comamonas(Proteobacteria),which is widely found in MFCs,was also detected in the anodic biofilm.These results confirmed the important role of plants in IVCW-MFCs.     

Effects of SO2 and H2O on low-temperature NO conversion over F-V2O5-WO3/TiO2 catalysts

F-V_2 O_5-WO3/Ti02 catalysts were prepared by the impregnation method.As the content of F ions increased from 0.00 to 0.35 wt.%,the NO conversion of F-V_2 O_5-WO_3/TiO_2 catalysts initially increased and then decreased.The 0.2 F-V_2 O_5-WO_3/TiO_2 catalyst(0.2 wt.% F ion)exhibited the best denitration(De-NOx) performance,with more than 95% NO conversion in the temperature range 160-360℃,and 99.0% N2 selectivity between 110 and 280℃.The addition of an appropriate amount of F ions eroded the surface morphology of the catalyst and reduced its grain size,thus enhancing the NO conversion at low temperature as well as the sulfur and water resistance of the V_2 O_5-WO3/Ti02 catalyst.After selective catalytic reduction(SCR) reaction in a gas flow containing SO_2 and H_2 O,the number of NH3 adsorption sites,active component content,specific surface area and pore volume decreased to different degrees.Ammonium sulfate species deposited on the catalyst surface,which blocked part of the active sites and reduced the NO conversion performance of the catalyst.On-line thermal regeneration could not completely recover the catalyst activity,although it prolonged the cumulative life of the catalyst.In addition,a mechanism for the effects of S02 and H_2 O on catalyst NO conversion was proposed.     

Fast and efficient aqueous arsenic removal by functionalized MIL-100(Fe)/rGO/δ-MnO2 ternary composites: Adsorption performance and mechanism

Because of its significant toxicological effects on the environment and human health,arsenic(As) is a major global issue.In this study,an Fe-based metal-organic framework(MOF)(Materials of Institut Lavoisier:MIL-100(Fe)) which was impregnated with reduced graphene oxide(rGO) by using a simple hydrothermal method and coated with birnessitetype manganese oxide(δ-MnO_2) using the one-pot reaction process(MIL-100(Fe)/rGO/δ-MnO_2 nanocomposites) was synthesized and applied successfully in As removal.The removal efficiency was rapid,the equilibrium was achieved in 40 min and 120 min for As(Ⅲ) and As(Ⅴ),respectively,at a level of 5 mg/L.The maximum adsorption capacities of As(Ⅲ) and As(Ⅴ) at pH 2 were 192.67 mg/g and 162.07 mg/g,respectively.The adsorbent revealed high stability in pH range 2-9 and saturated adsorbent can be fully regenerated at least five runs.The adsorption process can be described by the pseudo-second-order kinetic model and Langmuir monolayer adsorption.The adsorption mechanisms consisted of electrostatic interaction,oxidation and inner sphere surface complexation.     

基于模糊PI控制的瞬态高温控制策略研究

目的通过地面环境试验研究气动热引起的瞬态高温环境对飞行器结构的影响。方法设计基于石英灯和离心机的瞬态高温-加速度复合试验系统,研究温度和加速度同步控制系统的结构和原理,分析无制冷装置环境下瞬态高温控制的难点,提出基于模糊PI控制器的温度控制策略。结果通过MATLAB仿真验证,设计的模糊PI控制器相比传统的PI控制器能够有效提高温度控制的动态性能与精确性。结论将基于模糊PI控制的瞬态加热控制策略应用于瞬态高温控制是可行、有效的,能为地面气动热模拟环境试验提供技术保障。     

含菌气溶胶扩散对人群的潜在影响风险

为分析生物气溶胶释放对人群潜在影响风险的情况,利用CALPUFF模型定量模拟了2019年7月24~8月20日中牧兰州生物药厂含菌气溶胶扩散、浓度空间分布、对人群潜在健康风险,并结合公开报道的检测数据开展验证.结果显示：生物药厂的含菌气溶胶排放源附近高值区主要集中于厂区四周,影响范围主要以厂区为中心,并向四周逐渐扩散;检测结果中兰州兽研所1#,兰州大学2#地区健康风险比例41.49：1,在模拟的相对风险大小的误差区间（36.15±8.48）范围内,说明本研究含菌气溶胶对人群潜在影响风险的模拟结果可信.     

北京市气温与黑碳和PM2.5对疾病死亡影响的交互效应

通过收集北京市2010~2016年逐日呼吸和心脑血管疾病死亡数据、污染物（BC、PM_2.5、SO₂、O₃和NO₂）日均浓度资料以及同期的气象资料,采用广义相加模型（GAMs）中的主效应模型、非参数二元响应模型和温度分层模型探讨了北京市气温、PM_2.5和BC单效应,以及气温与PM_2.5和BC交互作用分别对呼吸和心脑血管疾病死亡人数的影响.单效应分析结果表明,气温与两种疾病死亡人数的累计暴露-反应关系均呈“J”型分布特征,最适温度为24℃;累计滞后一天情况下PM_2.5和BC的健康效应均最显著,此时PM_2.5和BC浓度每升高四分位间距（IQR）,呼吸系统疾病死亡人数超额增加百分比（ER）分别为2.21%和1.80%,心脑血管疾病死亡人数ER分别为2.02%和1.48%.交互作用的研究结果表明,高温与高浓度的PM_2.5（或BC）对疾病死亡的影响存在协同效应,且高温条件下BC对疾病死亡影响的健康风险大于PM_2.5,当气温大于24℃时,BC和PM_2.5浓度每升高IQR对应的呼吸系统疾病死亡人数ER分别为6.22%和6.17%,心脑血管疾病死亡人数ER分别为5.01%和3.97%.虽然BC只占PM_2.5的一部分,但BC对人群健康的影响不容忽视,应该引起足够的重视.