Measuring eddy covariance fluxes of ozone with a slow-response analyser

Ozone (O₃) fluxes above a temperate mountain grassland were measured by means of the eddy covariance (EC) method using a slow-response O₃ analyser. The resultant flux loss was corrected for by a series of transfer functions which model the various sources of high- and, in particular, low-pass filtering. The resulting correction factors varied on average between 1.7 and 3.5 during night and daytime, respectively. A cospectral analysis confirmed the accuracy of this approach. O₃ fluxes were characterised by a comparatively large random uncertainty, which during daytime typically amounted to 60%. EC O₃ fluxes were compared against O₃ flux measurements made concurrently with the flux-gradient (FG) method. The two methods generally agreed well, except for a period between sunrise and early afternoon, when the FG method was suspected of being affected by the presence of photochemical sources/sinks. O₃ flux magnitudes and deposition velocities determined with the EC method compared nicely with the available literature from grassland studies. We conclude that our understanding of the causes and consequences of various sources of flux loss (associated with any EC system) has sufficiently matured so that also less-than-ideal instrumentation may be used in EC flux applications, albeit at the cost of relatively large empirical corrections.     

A hybrid plume model for local-scale atmospheric dispersion

This paper presents a local-scale dispersion model, based on atmospheric boundary layer scaling theory. In the vicinity of the source, Gaussian equations are used in both the horizontal and vertical directions. After a specified transition distance, gradient transfer theory is applied in the vertical direction, while the horizontal dispersion is still assumed to be Gaussian. The dispersion parameters and eddy diffusivity are modelled in a form, which facilitates the use of a meteorological pre-processor. We present a novel model of the vertical eddy diffusivity (K_z), which is a continuous function of height in various atmospheric scaling regions. The model also includes a treatment of the dry deposition of gases and particulate matter. The accuracy of the numerical model was analysed by comparing the model predictions with two analytical solutions; the numerical deviations from these solutions were less than 2% for the computational regime. The model has been tested against the Kincaid experimental field data. The agreement of the predictions and the data is good on the average, although the internal variation of the predictions versus data scatter plot is substantial.     

A hybrid method for inverse characterization of subsurface contaminant flux

The methods presented in this work provide a potential tool for characterizing contaminant source zones in terms of mass flux. The problem was conceptualized by considering contaminant transport through a vertical "flux plane" located between a source zone and a downgradient region where contaminant concentrations were measured. The goal was to develop a robust method capable of providing a statement of the magnitude and uncertainty associated with estimated contaminant mass flux values. In order to estimate the magnitude and transverse spatial distribution of mass flux through a plane, the problem was considered in an optimization framework. Two numerical optimization techniques were applied, simulated annealing (SA) and minimum relative entropy (MRE). The capabilities of the flux plane model and the numerical solution techniques were evaluated using data from a numerically generated test problem and a nonreactive tracer experiment performed in a three-dimensional aquifer model. Results demonstrate that SA is more robust and converges more quickly than MRE. However, SA is not capable of providing an estimate of the uncertainty associated with the simulated flux values. In contrast, MRE is not as robust as SA, but once in the neighborhood of the optimal solution, it is quite effective as a tool for inferring mass flux probability density functions, expected flux values, and confidence limits. A hybrid (SA-MRE) solution technique was developed in order to take advantage of the robust solution capabilities of SA and the uncertainty estimation capabilities of MRE. The coupled technique provided probability density functions and confidence intervals that would not have been available from an independent SA algorithm and they were obtained more efficiently than if provided by an independent MRE algorithm.     

A hybrid method for inverse characterization of subsurface contaminant flux

The methods presented in this work provide a potential tool for characterizing contaminant source zones in terms of mass flux. The problem was conceptualized by considering contaminant transport through a vertical “flux plane” located between a source zone and a downgradient region where contaminant concentrations were measured. The goal was to develop a robust method capable of providing a statement of the magnitude and uncertainty associated with estimated contaminant mass flux values.In order to estimate the magnitude and transverse spatial distribution of mass flux through a plane, the problem was considered in an optimization framework. Two numerical optimization techniques were applied, simulated annealing (SA) and minimum relative entropy (MRE). The capabilities of the flux plane model and the numerical solution techniques were evaluated using data from a numerically generated test problem and a nonreactive tracer experiment performed in a three-dimensional aquifer model. Results demonstrate that SA is more robust and converges more quickly than MRE. However, SA is not capable of providing an estimate of the uncertainty associated with the simulated flux values. In contrast, MRE is not as robust as SA, but once in the neighborhood of the optimal solution, it is quite effective as a tool for inferring mass flux probability density functions, expected flux values, and confidence limits.A hybrid (SA-MRE) solution technique was developed in order to take advantage of the robust solution capabilities of SA and the uncertainty estimation capabilities of MRE. The coupled technique provided probability density functions and confidence intervals that would not have been available from an independent SA algorithm and they were obtained more efficiently than if provided by an independent MRE algorithm.     

A hybrid statistical decision-making optimization approach for groundwater vulnerability considering uncertainty

Environmental Science and Pollution Research - Recognizing the vulnerable areas for contamination is a feasible way to protect groundwater resources. The main contribution of the paper is...     

A hybrid biological process of indoor air treatment for toluene removal

Bioprocesses, such as biofiltration, are commonly used to treat industrial effluents containing volatile organic compounds (VOCs) at low concentrations. Nevertheless, the use of biofiltration for indoor air pollution (IAP) treatment requires adjustments depending on specific indoor environments. Therefore, this study focuses on the convenience of a hybrid biological process for IAP treatment. A biofiltration reactor using a green waste compost was combined with an adsorption column filled with activated carbon (AC). This system treated a toluene-micropolluted effluent (concentration between 17 and 52 µg/m³), exhibiting concentration peaks close to 733 µg/m³ for a few hours per day. High removal efficiency was obtained despite changes in toluene inlet load (from 4.2 × 10^?3 to 0.20 g/m³/hr), which proves the hybrid system’s effectiveness. In fact, during unexpected concentration changes, the efficiency of the biofilter is greatly decreased, but the adsorption column maintains the high efficiency of the entire process (removal efficiency [RE] close to 100%). Moreover, the adsorption column after biofiltration is able to deal with the problem of the emission of particles and/or microorganisms from the biofilter.

ImplicationsIndoor air pollution is nowadays recognized as a major environmental and health issue. This original study investigates the performance of a hybrid biological process combining a biofilter and an adsorption column for removal of indoor VOCs, specifically toluene.     

A hybrid modeling approach to resolve pollutant concentrations in an urban area

A modeling tool that can resolve contributions from individual sources to the urban environment is critical for air-toxics exposure assessments. Air toxics are often chemically reactive and may have background concentrations originated from distant sources. Grid models are the best-suited tools to handle the regional features of these chemicals. However, these models are not designed to resolve pollutant concentrations on local scales. Moreover, for many species of interest, having reaction time scales that are longer than the travel time across an urban area, chemical reactions can be ignored in describing local dispersion from strong individual sources making Lagrangian and plume-dispersion models practical. In this study, we test the feasibility of developing an urban hybrid simulation system. In this combination, the Community Multi-scale Air Quality model (CMAQ) provides the regional background concentrations and urban-scale photochemistry, and local models such as Hybrid Single Particle Lagrangian Integrated Trajectory model (HYSPLIT) and AMS/EPA Regulatory Model (AERMOD) provide the more spatially resolved concentrations due to local emission sources. In the initial application, the HYSPLIT, AERMOD, and CMAQ models are used in combination to calculate high-resolution benzene concentrations in the Houston area. The study period is from 18 August to 4 September of 2000. The Mesoscale Model 5 (MM5) is used to create meteorological fields with a horizontal resolution of 1×1 km². In another variation to this approach, multiple HYSPLIT simulations are used to create a concentration ensemble to estimate the contribution to the concentration variability from point sources. HYSPLIT simulations are used to model two sources of concentration variability; one due to variability created by different particle trajectory pathways in the turbulent atmosphere and the other due to different flow regimes that might be introduced when using gridded data to represent meteorological data fields. The ensemble mean concentrations determined by HYSPLIT plus the concentrations estimated by AERMOD are added to the CMAQ calculated background to estimate the total mean benzene concentration. These estimated hourly mean concentrations are also compared with available field measurements.     

A hybrid atdl-gamma distribution model for predicting area source acid gas concentrations

An air quality model is developed to predict the distribution of concentrations of acid gas in an urban airshed. The model is hybrid in character, combining reliable features of a deterministic ATDL-based model with statistical distributional approaches. The gamma distribution was identified from a range of distributional models as the best model. The paper shows that the assumptions of a previous hybrid model may be relaxed and presents a methodology for characterizing the uncertainty associated with model predictions. Results are demonstrated for the 98-percentile predictions of 24-h average data over annual periods at six monitoring sites. This percentile relates to the World Health Organisation goal for acid gas concentrations.     

A hybrid micro-scale model for transport in connected macro-pores in porous media

This paper presents a hybrid model for transport in connected macro-pores in porous media. A pore-scale model is used to parameterize the hybrid model. The hybrid model explicitly models the advection and diffusion of species in the connected macro-pores and treats the porous media around the connected macro-pores as a continuum with effective transport properties. The pore-scale model is used to calculate the effective transport properties of the porous continuum. This approach negates the need to calibrate the hybrid model against experimental data, which is common for continuum-scale models of porous media, and allows an arbitrary microstructure to be considered. The paper presents the multi-scale modeling approach along with the details of the hybrid and pore-scale models. Validation of the model is also presented along with several case studies investigating the applicability of the multi-scale modeling approach to different geometries and transport conditions. The case studies show that the multi-scale modeling approach is accurate for various connected macro-pore geometries given that the porosity of the porous medium around the connected macro-pores is sufficiently small. The accuracy of the hybrid model decreases with increasing porosity of the matrix.     

聚醚砜/改性凹凸棒杂化微球对双酚A的吸附性能

以酸热、有机改性凹凸棒和聚醚砜为原料,利用液-液分离技术制备了聚醚砜/改性凹凸棒毫米级杂化微球。利用扫描电镜和比表面仪分析所制杂化微球表观特征。实验探讨了改性凹凸棒掺杂比和溶液pH对杂化微球吸附双酚A效果的影响,并深入研究了吸附动力学和热力学原理。实验结果表明：杂化微球对双酚A的吸附性能受pH影响较小;相比纯聚醚砜微球,掺杂后的杂化微球对双酚A吸附量从1.97 μmol·g-1提升到11.80 μmol·g-1;吸附过程符合准二级动力学模型和Langmuir模型。根据Langmuir模型计算可知,25 ℃时杂化微球最大吸附量为116.28 μmol·g-1。5次乙醇再生后,杂化微球对双酚A的去除效果依然保持在95%以上。杂化微球作为吸附剂在水处理中具有潜在应用价值。     

Multi-stage optimal design for groundwater remediation: A hybrid bi-level programming approach

This paper presents the development of a hybrid bi-level programming approach for supporting multi-stage groundwater remediation design. To investigate remediation performances, a subsurface model was employed to simulate contaminant transport. A mixed-integer nonlinear optimization model was formulated in order to evaluate different remediation strategies. Multivariate relationships based on a filtered stepwise clustering analysis were developed to facilitate the incorporation of a simulation model within a nonlinear optimization framework. By using the developed statistical relationships, predictions needed for calculating the objective function value can be quickly obtained during the search process. The main advantage of the developed approach is that the remediation strategy can be adjusted from stage to stage, which makes the optimization more realistic. The proposed approach was examined through its application to a real-world aquifer remediation case in western Canada. The optimization results based on this application can help the decision makers to comprehensively evaluate remediation performance.     

随身自动空气净化处理器的研究

随身自动空气净化器,采用了活性炭、光催化技术相结合的空气过滤装置.空气污染传感器与单片机组成空气质量监测电路,当空气污染超标时,产生语音提示,液晶屏显示空气质量的等级,自动(或手动)控制引风机工作,供给个人清新无污染的空气.     

随身自动空气净化处理器的研究

随身自动空气净化器，采用了活性炭、光催化技术相结合的空气过滤装置。空气污染传感器与单片机组成空气质量监测电路，当空气污染超标时，产生语音提示，液晶屏显示空气质量的等级，自动（或手动）控制引风机工作，供给个人清新无污染的空气。     

A new hybrid system of QSAR models for predicting bioconcentration factors (BCF)

The aim was to develop a reliable and practical quantitative structure-activity relationship (QSAR) model validated by strict conditions for predicting bioconcentration factors (BCF). We built up several QSAR models starting from a large data set of 473 heterogeneous chemicals, based on multiple linear regression (MLR), radial basis function neural network (RBFNN) and support vector machine (SVM) methods. To improve the results, we also applied a hybrid model, which gave better prediction than single models. All models were statistically analysed using strict criteria, including an external test set. The outliers were also examined to understand better in which cases large errors were to be expected and to improve the predictive models. The models offer more robust tools for regulatory purposes, on the basis of the statistical results and the quality check on the input data.     

A new hybrid system of QSAR models for predicting bioconcentration factors (BCF)

The aim was to develop a reliable and practical quantitative structure–activity relationship (QSAR) model validated by strict conditions for predicting bioconcentration factors (BCF). We built up several QSAR models starting from a large data set of 473 heterogeneous chemicals, based on multiple linear regression (MLR), radial basis function neural network (RBFNN) and support vector machine (SVM) methods. To improve the results, we also applied a hybrid model, which gave better prediction than single models. All models were statistically analysed using strict criteria, including an external test set. The outliers were also examined to understand better in which cases large errors were to be expected and to improve the predictive models. The models offer more robust tools for regulatory purposes, on the basis of the statistical results and the quality check on the input data.     

生物脱氮除磷活性污泥系统复合模拟方法

为避免繁琐的参数校核工作,提出了活性污泥2 d号模型(ASM2d)和人工神经网络(ANNs)相结合的复合模拟方法。考察了复合方法在某污水处理厂生物脱氮除磷工艺中的应用情况。研究表明,ANNs能够准确地模拟出水实测值与未经校核的ASM2d机理模型的估计值之间的差值。利用Levenberg-Marquardt算法,对出水氨氮、总氮和总磷分别建立网络结构为5-12-1、5-8-1和5-8-1的ANNs子模型,将这些子模型输出同ASM2d机理模型输出相加便得到复合模型输出。复合模型估计值对前10.4 d(ANNs子模型训练数据时段)出水氨氮、总氮和总磷浓度的拟合平均绝对百分比误差分别为0.267、0.055和0.048;其对后2.6 d(ANNs子模型测试数据时段)出水氨氮、总氮和总磷浓度的预测平均绝对百分比误差分别为0.332、0.083和0.069。均方根误差、平均绝对误差等评价指标也表明复合模型能够给出合理的模拟结果。     

A hybrid fenton oxidation-microbial treatment for soil highly contaminated with benz(a)anthracene

In order to mitigate the strong microbial resistance of benz(a)anthracene [B(a)A] in soil, a hybrid treatment of Fenton oxidation followed microbial culture was carried out. Based on optimal Fenton oxidation, i.e., 1.0 ml of ethanol, 0.2 ml of 0.5 M Fe²⁺, and 0.3 ml of 30% H₂O₂ per 1 g of 500 mg B(a)A/kg soil, about 43% of B(a)A-7,12-dione was generated during oxidation of 97% B(a)A. When the comparative biodegradability between B(a)A-contaminated soil and B(a)A-contaminated soil after Fenton oxidation was examined, it was found that 98% of B(a)A-7,12-dione degraded after 63 d in comparison with only 12% of B(a)A over the same period; results demonstrating that Fenton oxidation enhances biodegradability of B(a)A through B(a)A-7,12-dione.     

A hybrid model for robust design of sustainable closed-loop supply chain in lead-acid battery industry

Environmental Science and Pollution Research - Considering supply chain efficiency during the network design process significantly affect chain performance improvement. In this paper, the design...     

自动分选-除渣-厌氧消化处理有机垃圾

城市有机垃圾已经成为重要的污染源和迫切需要处理的问题,传统处理工艺存在各种问题。现以某市有机垃圾处理为工程实例,介绍自动分选、碎浆除渣、厌氧消化处理工艺。该工艺经实践运营可处理餐厨垃圾150 t/d,粪便200 t/d。无论在沼气产生量、有机质回收率和降解率等方面,还是在工艺稳定、设备运行可靠等方面,该工艺都具有独到的特点。