Calibration and verification of a dissolved oxygen management model for a highly polluted river with extreme flow variations in Pakistan

A dissolved oxygen (DO) model is calibrated and verified for a highly polluted River Ravi with large flow variations. The model calibration is done under medium flow conditions (431.5 m³/s), whereas the model verification is done using the data collected during low flow conditions (52.6 m³/s). Biokinetic rate coefficients for carbonaceous biochemical oxygen demand (CBOD) and nitrogenous biochemical oxygen demand (NBOD) (i.e, K _cr and K _n ) are determined through the measured CBOD and ammonia river profiles. The calculated values of K _cr and K _n are 0.36 day^?1 and 0.34 day^?1, respectively. The close agreement between the DO model results and the field values shows that the verified model can be used to develop DO management strategies for the River Ravi. The biokinetic coefficients are known to vary with degree of treatment (DOT) and therefore need to be adjusted for a rational water quality management model. The effect of this variation on level of treatment has been evaluated by using the verified model to attain a DO standard of 4 mg/L in the river using the biokinetic rate coefficients as determined during the model calibration and verification process. The required DOT in this case is found to be 96 %, whereas the DOT is 86 % if adjusted biokinetic rate coefficients are used to reflect the effect of wastewater treatment. The cost of wastewater treatment is known to increase exponentially as the removal efficiency increases; therefore, the use of appropriate biokinetic coefficients to manage the water quality in rivers is important.     

Advanced REACH Tool (ART): calibration of the mechanistic model

The mechanistic model of the Advanced Reach Tool (ART) provides a relative ranking of exposure levels from different scenarios. The objectives of the calibration described in this paper are threefold: to study whether the mechanistic model scores are accurately ranked in relation to exposure measurements; to enable the mechanistic model to estimate actual exposure levels rather than relative scores; and to provide a method of quantifying model uncertainty. Stringent data quality guidelines were applied to the collated data. Linear mixed effects models were used to evaluate the association between relative ART model scores and measurements. A random scenario and company component of variance were introduced to reflect the model uncertainty. Stratified analyses were conducted for different forms of exposure (abrasive dust, dust, vapours and mists). In total more than 2000 good quality measurements were available for the calibration of the mechanistic model. The calibration showed that after calibration the mechanistic model of ART was able to estimate geometric mean (GM) exposure levels with 90% confidence for a given scenario to lie within a factor between two and six of the measured GM depending upon the form of exposure.     

ICP-AES法多条谱线测定环境土壤中钒

选用钒的5条特征谱线用电感耦合-等离子发射光谱(ICP-AES)法测定环境土壤中的钒含量,运用干扰系数法对多个土壤标样和样品测定结果进行干扰校正,干扰系数用多个土壤标样的标准值和测定值的最小二乘法来确定.结果表明,未进行校正时,7个土壤标样5条特征谱线测定原始结果和标准值相差较大,不在标准值的范围内;校正后,土壤标样的311.071 nm.波长与309.311 nm波长谱线测定结果的均值在范围之内,且干扰系数为1.015(约等于1),不需折算,波长311.071 nm也在保证值范围内(校正系数为1.184).对土壤样品进行测定,5条谱线测试结果一致性好,相对标准偏差为2.2％～10.4％,平行相对偏差为0.3％～3.3％,加标回收率为88.4％ ～ 111.4％.建议用ICP-AES法对环境土壤中的钒测定时,选用波长311.071 nm谱线并用干扰系数法进行校正(系数为1.184),或用波长311.071 nm与309.311 nm谱线测定均值作为测定结果.     

国家重点生态功能区县域环境监测质量评价方法及应用示范

以国家重点生态功能区县域环境监测质量评价为目标,综合应用德尔菲法、层次分析法和模糊综合评价法,构建了国家重点生态功能区县域环境监测质量评价方法,并确定了评价因子、权重系数、计算方法。该方法评价指标共分为三层:第一层为目标层,即国家重点生态功能区县域环境监测质量;第二层为准则层,包括人员及资质、现场监测、实验室管理、报告编制及数据上报;第三层为方案层,包括人员操作、持证上岗、资质认定、人员培训、水质布点采样流转情况、空气自动站运维情况、现场质控实施情况、实验室环境条件、样品试剂的保存与管理、仪器检定与校准、实验室质量控制实施情况、数据填报软件运行情况、监测报告规范性等13个评价要素。经矩阵一致性检验确定了各评价要素的权重,将该权重与各要素得分运算后得到县域环境监测质量评价结果。在此基础上,选取广东、山西、陕西、四川和青海等5个省份的15个国家重点生态功能区县域作为典型区开展了实地调研,并应用评价体系对其进行了监测质量等级评价。结果表明,15个典型县域中,环境监测质量等级为优的县域占13.3%,一般、较差的县域分别占66.7%、20%。县域环境监测承担单位在资质、报告编制及数据上报方面表现较好,在现场监测、人员操作方面问题突出,在实验室管理方面有待提升。     

检测质量监督检查结果的几点启示

分析了监督管理部门近2年对386个检测机构的监督检查结果,揭示了检测工作质量管理的薄弱环节,分别是记录管理、质量体系的建立、检测报告、设备检定/校准及管理,总结归纳了主要问题的表现形式,提出了提高检测质量的建议,以利于检测机构更有效开展相关工作。     

风云三号卫星气溶胶光学厚度产品的适用性验证

利用长三角地区浦东、东滩、太湖3个测站的太阳光度计CE318地基遥感观测得到的气溶胶光学厚度(AOD)数据对风云三号气象卫星FY-3A/B MERSI反演的550 nm波长AOD进行有效性验证。结果表明,FY-3A的反演结果相关系数高于0.96,仅有20%的样本表现出较大的偏差。FY-3B的相关系数最高为0.77,均方根误差(RMSE)最大为0.35。太湖站点的相关系数比浦东大,说明MERSI的反演算法在太湖更适用。FY-3A/B MERSI反演结果总体上偏小,存在一定的系统偏差,主要由气溶胶模型的假设、设备标定、选择像素比例等原因造成。     

氮氧化物检测结果可靠性影响因素研究

针对氮氧化物检测时分析方法及结果可能出现的问题进行了讨论,并对其可靠性进行了验证。以氮氧化物分析仪(化学发光原理)检测氮氧化物(NO_x)为例,分别对是否校准、定值标准的选择及不同工作模式3种情况下氮氧化物浓度测量结果的可靠性及影响因素进行评价,并用另外一种不同工作原理的傅里叶红外变换光谱法进行结果确认。结果表明:氮氧化物分析仪以自动模式进行工作时,不进行校准很可能得到完全错误的分析结果;浓度合适的标准物质的选择有利于提高分析结果的准确度。     

Three-dimensional Modelling of Radionuclides Dispersion in a Marine Environment with Application to the Fukushima Dai-ichi Case

In this work, we present the implementation, verification and validation of a three-dimensional model able to reproduce the propagation of \(^{137}C_{s}\) radionuclide in coastal waters and its interaction with suspended sediments, in the framework of the open-source TELEMAC-MASCARET modelling system. The validation of the model was realized by comparing numerical results with field measurements of radionuclides concentration in the Japan Sea nearby the Fukushima Dai-ichi nuclear power plant (NPP). The developed model uses as external forcing the data available immediately after or during the accident, as, e.g. weather conditions (wind, pressure, temperature) and/or the harmonic components of tides. In contrast with previous models implemented in the study area, the model presented here is limited to the coastal area near Fukushima and refined in the coastal area close to the NPP. Numerical results show that the model is able to reproduce the propagation and diffusion of the released \(^{137}C_{s}\) in the vicinity of the Fukushima Dai-ichi NPP. Consequently, we show that the numerical results obtained with a small-scale model with a simple forcing are consistent, at a coastal scale, with models which employed a general circulation model based on data assimilation techniques or variation method for hydrodynamics. Therefore, this model could be employed in an emergency situation, when the dissolved radioactivity is considered.

     

Airborne observations of vegetation and implications for biogenic emission characterization

Measuring hydrocarbons from aircraft represents one way to infer biogenic emissions at the surface. The focus of this paper is to show that complementary remote sensing information can be provided by optical measurements of a vegetation index, which is readily measured with high temporal coverage using reflectance data. We examine the similarities between the vegetation index and in situ measurements of the chemicals isoprene, methacrolein, and alpha-pinene to estimate whether the temporal behavior of the in situ measurements of these chemicals could be better understood by the addition of the vegetation index. Data were compared for flights conducted around Houston in August and September 2000. The three independent sets of chemical measurements examined correspond reasonably well with the vegetation index curves for the majority of flight days. While low values of the vegetation index always correspond to low values of the in situ chemical measurements, high values of the index correspond to both high and low values of the chemical measurements. In this sense it represents an upper limit when compared with in situ data (assuming the calibration constant is adequately chosen). This result suggests that while the vegetation index cannot represent a purely predictive quantity for the in situ measurements, it represents a complementary measurement that can be useful in understanding comparisons of various in situ observations, particularly when these observations occur with relatively low temporal frequency. In situ isoprene measurements and the vegetation index were also compared to an isoprene emission inventory to provide additional insight on broad issues relating to the use of vegetation indices in emission database development.     

Development of Dissolved Oxygen Model for a Highly Variable Flow River: A Case Study of Ravi River in Pakistan

A framework for dissolved oxygen (DO) modeling of the Ravi River has been developed based on a combination of laboratory measurements and field and monitoring data. Both the classical Streeter-Phelps (CSP) and the modified Streeter-Phelps (MSP) models are used for DO simulations. The MSP model considers the carbonaceous biochemical oxygen demand (CBOD) and nitrogenous biochemical oxygen demand (NBOD) separately, whereas the CSP model is evaluated considering only the CBOD and NBOD is incorporated in the overall BOD utilization rate. CBOD, NBOD and BOD rates have been determined through long-term BOD analysis of five main wastewater outfalls and two surface drains discharging into the Ravi River over a 98 km stretch. Analysis by Thomas Method manifests strong coefficient of determination “R²” between 0.72 and 0.98 for all the three types of BOD rates. Sensitivity analyses have also been carried out to find out a suitable reaeration rate formula for highly variable flows in the Ravi River. The CSP model results based on classical approach of considering only CBOD show significant difference between the model predictions and field measurements suggesting that NBOD needs to be incorporated for the model development. The dissolved oxygen values calculated using the MSP model and the CSP model based on overall BOD rate are in close agreement with field measurements and are thus suitable to model DO levels in the Ravi River.     

Determination of response of real-time SidePak AM510 monitor to secondhand smoke, other common indoor aerosols, and outdoor aerosol

The amount of light scattered by airborne particles inside an aerosol photometer will vary not only with the mass concentration, but also with particle properties such as size, shape, and composition. This study conducted controlled experiments to compare the measurements of a real-time photometer, the SidePak AM510 monitor (SidePak), with gravimetric mass. PM sources tested were outdoor aerosols, and four indoor combustion sources: cigarettes, incense, wood chips, and toasting bread. The calibration factor for rescaling the SidePak measurements to agree with gravimetric mass was similar for the cigarette and incense sources, but different for burning wood chips and toasting bread. The calibration factors for ambient urban aerosols differed substantially from day to day, due to variations in the sources and composition of outdoor PM. A field evaluation inside a casino with active smokers yielded calibration factors consistent with those obtained in the controlled experiments with cigarette smoke.     

Development of geomorphologic instantaneous unit hydrograph for a large watershed

Hill torrents cause a lot of environmental and property damage in Pakistan every year. Proper assessment of direct runoff in the form of hill torrents is essential for protection of environment, property, and human life. In this paper, direct surface runoff hydrograph (DSRH) was derived for a large catchment using the geomorphologic instantaneous unit hydrograph concept. The catchment with hill torrent flows in semi-arid region of Pakistan was selected for this study. It was divided into series of linear cascades and hydrologic parameters required for Nash's conceptual model, and were estimated using geomorphology of the basin. Geomorphologic parameters were derived from satellite images of the basin and ERDAS and ArcGIS were used for data processing. Computer program was developed to systematically estimate the dynamic velocity, its related parameters by optimization and thereby to simulate the DSRH. The data regarding rainfall-runoff and satellite images were collected from Punjab Irrigation and Power Department, Pakistan. Model calibration and validation was made for 15 rainfall-runoff events. Ten events were used for calibration and five for validation. Model efficiency was found to be more than 90% and root mean square error to be about 5%. Impact of variation in model parameters (shape parameter and storage coefficient) on DSRH was investigated. For shape parameter, the number of linear cascades varied from 1 to 3 and it was found that the shaper parameter value of 3 produced the best DSRH. Various values of storage coefficient were used and it was observed that the value determined from geomorphology and the dynamic velocity produced the best results.     

Simulation of PM<Subscript>10</Subscript> concentration patterns for a 2010 traffic scenario in Bologna,Italy

Three state of the art traffic–emission–dispersion models dealing with particulate matter have been tested and validated over the Bologna metropolitan area with 2001 data and a future scenario has been developed in order to estimate expected PM concentrations in 2010. The modelling system is composed by a traffic model (VISUM) evaluating vehicle fluxes as a function of mobility demand and road network in the area, an emission model (Trefic) estimating pollutants emitted in atmosphere as a function of vehicle fluxes amount and composition and of environmental conditions and a dispersion model (ADMS) evaluating PM concentrations on the area, given the meteorological variables. The three models compose a cascade sequence and results of the previous one feed the next one. PM concentrations computed by the model suite for the town of Bologna, in northern Italy, for the reference period (January 2001) have been compared with air quality stations measurements suggesting the modelling system being especially suitable for evaluating traffic induced PM. Qualitative and quantitative changes in the circulating vehicle fleet have been supposed in order to obtain a realistic scenario for year 2010. Forecasted concentrations have been then compared with limits fixed by current EU legislation for particulate matter.     

Estimation of suspended sediment concentration in rivers using acoustic methods

Acoustic Doppler current meters (ADV, ADCP, and ADP) are widely used in water systems to measure flow velocities and velocity profiles. Although these meters are designed for flow velocity measurements, they can also provide information defining the quantity of particulate matter in the water, after appropriate calibration. When an acoustic instrument is calibrated for a water system, no additional sensor is needed to measure suspended sediment concentration (SSC). This provides the simultaneous measurements of velocity and concentration required for most sediment transport studies. The performance of acoustic Doppler current meters for measuring SSC was investigated in different studies where signal-to-noise ratio (SNR) and suspended sediment concentration were related using different formulations. However, these studies were each limited to a single study site where neither the effect of particle size nor the effect of temperature was investigated. In this study, different parameters that affect the performance of an ADV for the prediction of SSC are investigated. In order to investigate the reliability of an ADV for SSC measurements in different environments, flow and SSC measurements were made in different streams located in the Aegean region of Turkey having different soil types. Soil samples were collected from all measuring stations and particle size analysis was conducted by mechanical means. Multivariate analysis was utilized to investigate the effect of soil type and water temperature on the measurements. Statistical analysis indicates that SNR readings ob tained from the ADV are affected by water temperature and particle size distribution of the soil, as expected, and a prediction model is presented relating SNR readings to SSC mea surements where both water temperature and sediment characteristics type are incorporated into the model. The coefficients of the suggested model were obtained using the multivariate anal ysis. Effect of high turbidity conditions on ADV performance was also investigated during and after rain events.     

The development of stream temperature model in a mountainous river of Taiwan

Formosan landlocked salmon is an endangered species and is very sensitive to stream temperature change. This study attempts to improve a former stream temperature model (STM) which was developed for the salmon’s habitat to simulate stream temperature more realistically. Two modules, solar radiation modification (SRM) and surface/subsurface runoff mixing (RM), were incorporated to overcome the limitation of STM designed only for clear-sky conditions. It was found that daily temperature difference is related to cloud cover and can be used to adjust the effects of cloud cover on incident solar radiation to the ground level. The modified model (STM + SRM) improved the simulation during a baseflow period in both winter and summer with the Nash-Sutcliffe efficiency coefficient improved from 0.37 (by STM only) to 0.71 for the winter and from ?0.18 to 0.70 for the summer. On the days with surface/subsurface runoff, the incorporation of the two new modules together (STM + SRM + RM) improved the Nash-Sutcliffe efficiency coefficient from 0.00 to 0.65 and from 0.29 to 0.83 in the winter and the summer, respectively. Meanwhile, the contributions of major thermal sources to stream temperature changes were identified. Groundwater is a major controlling factor for regulating seasonal changes of stream temperature while solar radiation is the primary factor controlling daily stream temperature variations. This study advanced our understanding on short-term stream temperature variation, which could be useful for the authorities to restore the salmon’s habitat.     

Influence of different nitrate–N monitoring strategies on load estimation as a base for model calibration and evaluation

Model-based predictions of the impact of land management practices on nutrient loading require measured nutrient flux data for model calibration and evaluation. Consequently, uncertainties in the monitoring data resulting from sample collection and load estimation methods influence the calibration, and thus, the parameter settings that affect the modeling results. To investigate this influence, we compared three different time-based sampling strategies and four different load estimation methods for model calibration and compared the results. For our study, we used the river basin model Soil and Water Assessment Tool on the intensively managed loess-dominated Parthe watershed (315 km²) in Central Germany. The results show that nitrate–N load estimations differ considerably depending on sampling strategy, load estimation method, and period of interest. Within our study period, the annual nitrate–N load estimation values for the daily composite data set have the lowest ranges (between 9.8% and 15.7% maximum deviations related to the mean value of all applied methods). By contrast, annual estimation results for the submonthly and the monthly data set vary in greater ranges (between 24.9% and 67.7%). To show differences between the sampling strategies, we calculated the percentage deviation of mean load estimations of submonthly and monthly data sets as related to the mean estimation value of the composite data set. For nitrate–N, the maximum deviation is 64.5% for the submonthly data set in the year 2000. We used average monthly nitrate–N loads of the daily composite data set to calibrate the model to achieve satisfactory simulation results [Nash–Sutcliffe efficiency (NSE) 0.52]. Using the same parameter settings with submonthly and monthly data set, the NSE dropped to 0.42 and 0.31, respectively. Considering the different results from the monitoring strategy and the load estimation method, we recommend both the implementation of optimized monitoring programs and the use of multiple load estimation methods to improve water quality characterization and provide appropriate model calibration and evaluation data.     

Temporal Moment Analysis of Multi-Species Radionuclide Transport in a Coupled Fracture-Skin-Matrix System with a Variable Fracture Aperture

This paper presents an analysis using temporal moments to study multi-species radionuclide transport along a single fracture with variable fracture aperture in a fracture-skin-matrix system. In the present study, a decay chain having three elements is considered and transport of each member in the decay chain is modeled by solving a coupled system of partial differential equations for fracture, fracture-skin, and rock matrix using explicit finite difference method. Having obtained the concentration distribution, lower order temporal moments of radionuclide distribution are computed to analyze the effective velocity and macro-dispersion coefficient of radionuclides in the fracture. In the present study, effect of varying fracture aperture on transport characteristics of radionuclides is also analyzed. It is found that the fracture aperture variation profile has significant impact on radionuclide distribution along the fracture. Sensitivity analysis is carried out in a fracture-skin-matrix system with sinusoidal fracture aperture to study the effect of various parameters like fracture aperture thickness, fracture-skin porosity, fracture-skin diffusion coefficient, flow rate, radioactive decay constant, and Freundlich sorption isotherm exponent on transport characteristics of radionuclide. The results suggest that the above mentioned parameters significantly influence concentration, distribution, mobility, and effective macro-dispersion coefficient of radionuclides along the fracture.     

System Dynamics Modeling and Policy Simulation for Urban Traffic: a Case Study in Beijing

This paper constructs a system dynamics model for simulating the impact of different strategies on urban traffic’s energy consumption and carbon emissions. Based on a case study in Beijing, the model includes three subsystems: (1) urban traffic, (2) population and economy, and (3) energy consumption and carbon emissions. First, the model is used to decompose the impact of different vehicles on energy consumption and carbon emissions. Decomposition results show that private cars have the most significant impact on urban traffic’s energy consumption and carbon emissions; however, total vehicle kilometers traveled by private cars are the smallest among four trip modes. Then, the model is used to simulate different urban traffic policies. Policies are categorized as follows: (a) driving restrictions on vehicle registration numbers, (b) a scheme for vehicle registrations via a lottery system, and (c) development of public transportation infrastructures. Scenario simulation results show that all those measures can reduce energy consumption and carbon emissions. Though the last strategy (c) contains several delays, its effect is more stable and far-reaching. Finally, some recommendations about easing traffic pressure and reducing traffic emissions are given.     

Numerical modelling of the groundwater inflow to an advancing open pit mine: Kolahdarvazeh pit,Central Iran

The groundwater inflow into a mine during its life and after ceasing operations is one of the most important concerns of the mining industry. This paper presents a hydrogeological assessment of the Irankuh Zn-Pb mine at 20 km south of Esfahan and 1 km northeast of Abnil in west-Central Iran. During mine excavation, the upper impervious bed of a confined aquifer was broken and water at high-pressure flowed into an open pit mine associated with the Kolahdarvazeh deposit. The inflow rates were 6.7 and 1.4 m³/s at the maximum and minimum quantities, respectively. Permeability, storage coefficient, thickness and initial head of the fully saturated confined aquifer were 3.5?×?10^?4 m/s, 0.2, 30 m and 60 m, respectively. The hydraulic heads as a function of time were monitored at four observation wells in the vicinity of the pit over 19 weeks and at an observation well near a test well over 21 h. In addition, by measuring the rate of pumping out from the pit sump, at a constant head (usually equal to height of the pit floor), the real inflow rates to the pit were monitored. The main innovations of this work were to make comparison between numerical modelling using a finite element software called SEEP/W and actual data related to inflow and extend the applicability of the numerical model. This model was further used to estimate the hydraulic heads at the observation wells around the pit over 19 weeks during mining operations. Data from a pump-out test and observation wells were used for model calibration and verification. In order to evaluate the model efficiency, the modelling results of inflow quantity and hydraulic heads were compared to those from analytical solutions, as well as the field data. The mean percent error in relation to field data for the inflow quantity was 0.108. It varied between 1.16 and 1.46 for hydraulic head predictions, which are much lower values than the mean percent errors resulted from the analytical solutions (from 1.8 to 5.3 for inflow and from 2.16 to 3.5 for hydraulic head predictions). The analytical solutions underestimated the inflow compared to the numerical model for the time period of 2–19 weeks. The results presented in this paper can be used for developing an effective dewatering program.     

Stochastic approaches for time series forecasting of boron: a case study of Western Turkey

In the present study, a seasonal and non-seasonal prediction of boron concentrations time series data for the period of 1996–2004 from Büyük Menderes river in western Turkey are addressed by means of linear stochastic models. The methodology presented here is to develop adequate linear stochastic models known as autoregressive integrated moving average (ARIMA) and multiplicative seasonal autoregressive integrated moving average (SARIMA) to predict boron content in the Büyük Menderes catchment. Initially, the Box–Whisker plots and Kendall’s tau test are used to identify the trends during the study period. The measurements locations do not show significant overall trend in boron concentrations, though marginal increasing and decreasing trends are observed for certain periods at some locations. ARIMA modeling approach involves the following three steps: model identification, parameter estimation, and diagnostic checking. In the model identification step, considering the autocorrelation function (ACF) and partial autocorrelation function (PACF) results of boron data series, different ARIMA models are identified. The model gives the minimum Akaike information criterion (AIC) is selected as the best-fit model. The parameter estimation step indicates that the estimated model parameters are significantly different from zero. The diagnostic check step is applied to the residuals of the selected ARIMA models and the results indicate that the residuals are independent, normally distributed, and homoscadastic. For the model validation purposes, the predicted results using the best ARIMA models are compared to the observed data. The predicted data show reasonably good agreement with the actual data. The comparison of the mean and variance of 3-year (2002–2004) observed data vs predicted data from the selected best models show that the boron model from ARIMA modeling approaches could be used in a safe manner since the predicted values from these models preserve the basic statistics of observed data in terms of mean. The ARIMA modeling approach is recommended for predicting boron concentration series of a river.