The potential of statistical state space models in urban ozone forecasting

State space models for tropospheric urban ozone prediction are introduced and compared with linear regression models. The linear and non-linear state space models make accurate short-term predictions of the ozone dynamics. The average prediction error one hour in advance is 7 μg/m³ and increases logarithmically with time until it reaches 26 μg/m³ after 30 days. For a given sequence of solar radiation inputs, predictions converge exponentially with a time scale of 8 hours, so that the model is insensitive to perturbations of more than 150 μg/m³ O₃. The slow increase of the prediction error in addition to the uniqueness of the prediction are encouraging for applications of state space models in forecasting ozone levels when coupled with a model that predicts total radiation. Since a radiation prediction model will be more accurate during cloud-free conditions, in addition to the fact that the state space models perform better during the summer months, state space models are suitable for applications in sunny environments.     

The role of wind field, mixing height and horizontal diffusivity investigated through two lagrangian particle models

Two Lagrangian particle models, APOLLO and MILORD, were used to simulate the first ETEX experiment. The role played by wind field, mixing height h and horizontal diffusivity K_H appeared to be the most important aspects to be studied. The sensitivity to the accuracy of the input advection field was studied through the application of APOLLO using different ECMWF data sets differing in space and time resolution and in being forecasted or analysed, corresponding to the real-time, emergency-like condition, and to the a posteriori benchmark simulation. The role of h and K_H was investigated by running both APOLLO and MILORD with different parameterisations, and comparing the model results between them and with the available observations.The model evaluation was carried out through a set of statistical indexes computed on three hourly average concentrations paired in space and time and time-integrated concentrations. It was found that the quality of the input wind field plays a major role in predicting with sufficient accuracy the plume position and extension after the first 24 h from the beginning of the release. The best-model results are obtained with large values of K_H (in the range of 2.5×10⁴–4.5×10⁴ m² s^-1), which confirms the need to enhance the horizontal diffusion, in order to include the advection fluctuations unresolved by large-scale meteorological fields. A fixed value of h in the range 1000–1500 m seems to be more efficient than space and time variable h computed with standard algorithms. A reasonable explanation for this result is given, based on the consideration that in the long range, particles diffuse also in the residual layer above the stable nocturnal boundary layer.     

Determination of some pesticide residues in conventional-grown and IPM-grown tomato by using QuEChERS method

The present study was conducted to determine pesticide (emamectin-benzoate, penconazole and imidacloprid) residues over tomatoes by using QuEChERS method. The method was validated by spiking tomato matrix at 0.1, 1.0, and 10.0 MRL levels of the pesticides. Tomatoes were harvested from two conventional and two Integrated Pest Management-grown fields. Laboratory samples were taken from the bulk samples. Analyses of spiked and real-field tomatoes were performed with QuEChERS procedure. Experimental samples were subjected to LC-MS/MS analysis. As indicated in “CAC/GL 40-1993,” representative sample matrix (apple) calibration was used for quantification. The overall recovery was 107.12% with a relative standard deviation of 17.96% (n?=?162). Present values were within the specified recovery ranges (60-140%) and repeatability value of (RSD ≤20%) of SANCO. Analysis of field experiment samples showed that both conventional tomato plots had trace levels (less than MRL) of emamectin-benzoate and imidacloprid, whereas there were not any pesticide residues in both IPM tomato plots     

Determination of glyphosate residue in maize and rice using a fast and easy method involving liquid chromatography–mass spectrometry (LC/MS/MS)

A fast and easy method was developed for the determination of glyphosate in maize and rice by using liquid chromatography triple quadrupole mass spectrometry with a Dionex Ion Pack column and phosphate buffer mobile phase. Samples were extracted with an acidified methanol solution. An isotope-labeled internal standard was added to the sample before extraction to ensure accurate tracking and quantification. The method’s performance was evaluated through a series of assessments to determine the accuracy, precision, linearity, matrix effect, limit of detection (LOD), and limit of quantification (LOQ). The mean recoveries for both matrices were within 70–105% at three fortification levels, including the LOQ. The precision for replicates was <20% (RSD%) for both matrices. Good linearity (R²=0.9982) was obtained over the concentration range of 0.01–1.5?mg kg^?1. The LOD was determined to be 0.002?mg kg^?1 for rice and 0.004?mg kg^?1 for maize. The LOQ was 0.01?mg kg^?1 for both maize and rice. Due to its versatility, the proposed method could be considered useful for the determination of glyphosate in cereals in routine analysis.     

氯氧化锆生产排放废硅渣中锆资源的回收

开展了氯氧化锆生产排放废硅渣中锆资源的回收工艺研究,结果表明,当废硅渣在50℃条件下溶解废碱液时,硅渣中夹带的未熔锆英砂可以沉积,回收率可达到98.5%以上。继续加热溶硅碱液,可溶锆可与硅产生凝聚,形成锆富集物沉淀,锆富集物中湿基的ZrO2含量最高可达6.5%,可溶锆的回收率在97%以上。回收得到的未熔砂和锆富集物可直接返回氯氧化锆主流程中再利用,从而实现硅渣中锆的资源化利用。     

Decision-support tools for dynamic management

Spatial management is a valuable strategy to advance regional goals for nature conservation, economic development, and human health. One challenge of spatial management is navigating the prioritization of multiple features. This challenge becomes more pronounced in dynamic management scenarios, in which boundaries are flexible in space and time in response to changing biological, environmental, or socioeconomic conditions. To implement dynamic management, decision-support tools are needed to guide spatial prioritization as feature distributions shift under changing conditions. Marxan is a widely applied decision-support tool designed for static management scenarios, but its utility in dynamic management has not been evaluated. EcoCast is a new decision-support tool developed explicitly for the dynamic management of multiple features, but it lacks some of Marxan's functionality. We used a hindcast analysis to compare the capacity of these 2 tools to prioritize 4 marine species in a dynamic management scenario for fisheries sustainability. We successfully configured Marxan to operate dynamically on a daily time scale to resemble EcoCast. The relationship between EcoCast solutions and the underlying species distributions was more linear and less noisy, whereas Marxan solutions had more contrast between waters that were good and poor to fish. Neither decision-support tool clearly outperformed the other; the appropriateness of each depends on management purpose, resource-manager preference, and technological capacity of tool developers. Article impact statement: Marxan can function as a decision-support tool for dynamic management scenarios in which boundaries are flexible in space and time.     

Factors affecting the quantitative uncertainty of the estimated short-term intake. Part II—Practical examples

ABSTRACT

The effects of the spread of residue concentrations in the samples derived from the selected supervised trials and the number of trials were studied on the magnitude and uncertainty of the short-term dietary intakes calculated with the proposed new procedure (IESTI_p) and that one used currently by the FAO (Food and Agriculture Organization) and WHO (World Health Organization) Joint meeting on Pesticide Residues (JMPR) (IESTI_c). The residue data of 10 pesticides were obtained from supervised trials conducted on apples and pears. The methods described in Part I were used for the calculations of the uncertainty. The results indicate that the ratio of IESTI_P to IESTI_c (φ_IESTI) is directly proportional to the ratio of the estimated maximum residue level (MRL), recommended by the JMPR; to the highest residue (HR) observed in supervised trials, and it may have a wide range depending on the particular conditions. The φ_IESTI becomes greater with the increase of the difference between the mrl or maximum residue limit (MRL, established by the Codex Alimentarius Commission, CAC) and HR, and becomes smaller if the difference between the large portion (LP) and unit mass (U) decreases. The φ_IESTI ranged between 2 and 5.1 in the 16 cases examined indicating that the IESTI_p calculation method leads to higher intake estimates. The ratio of CV_IESTIp and CV_IESTIc ranged typically between 0.62 and 1.71. It rapidly increased up to 12 trials. For a larger number of trials, the ratio remained practically constant (1.69–1.71). The processing factor (PF) equally affects the MRL and HR values, therefore, it will not practically influence the φ_IESTI. The uncertainty of the estimated median residues depends on the spread and number of values in the residue datasets, which affects the uncertainty of the conversion factor (CF) and subsequently the uncertainty of the estimated IESTI_p. Residue values obtained from minimum nine independent trials are required for the correct calculation of the 95% confidence intervals of the calculated median residues. The uncertainty of the analytical results directly affects the median, HR values and indirectly the calculated mrl and the MRL derived from it. Therefore, it should also be considered for the calculation of the combined uncertainty of the conversion factors. For the correct interpretation of the results of dietary exposure calculations, the upper 95% confidence limit of the short-term intake should also be considered. However, it is not the current practice of regulatory agencies or JMPR.     

Impact of a proposed revision of the IESTI equation on the acute risk assessment conducted when setting maximum residue levels (MRLs) in the European Union (EU): A case study

ABSTRACT

Proposals to update the methodology for the international estimated short-term intake (IESTI) equations were made during an international workshop held in Geneva in 2015. Changes to several parameters of the current four IESTI equations (cases 1, 2a, 2b, and 3) were proposed. In this study, the overall impact of these proposed changes on estimates of short-term exposure was studied using the large portion data available in the European Food Safety Authority PRIMo model and the residue data submitted in the framework of the European Maximum Residue Levels (MRL) review under Article 12 of Regulation (EC) No 396/2005. Evaluation of consumer exposure using the current and proposed equations resulted in substantial differences in the exposure estimates; however, there were no significant changes regarding the number of accepted MRLs. For the different IESTI cases, the median ratio of the new versus the current equation is 1.1 for case 1, 1.4 for case 2a, 0.75 for case 2b, and 1 for case 3. The impact, expressed as a shift in the IESTI distribution profile, indicated that the 95th percentile IESTI shifted from 50% of the acute reference dose (ARfD) with the current equations to 65% of the ARfD with the proposed equations. This IESTI increase resulted in the loss of 1.2% of the MRLs (37 out of 3110) tested within this study. At the same time, the proposed equations would have allowed 0.4% of the MRLs (14 out of 3110) that were rejected with the current equations to be accepted. The commodity groups that were most impacted by these modifications are solanacea (e.g., potato, eggplant), lettuces, pulses (dry), leafy brassica (e.g., kale, Chinese cabbage), and pome fruits. The active substances that were most affected were fluazifop-p-butyl, deltamethrin, and lambda-cyhalothrin.     

Odor dispersion modeling with CALPUFF: Case study of a waste and residue treatment incineration and utilization plant in Kocaeli,Turkey

This study addresses the odor problem at a waste and residue treatment incineration and utilization plant located within the borders the Alikahya district of the Kocaeli province in Turkey. In the first stage of the study, odor measurements were made at designated sampling points, while in the second stage, odor concentrations were determined at the receptor points through dispersion modelling using a USEPA (United States Environmental Protection Agency) certified long-range (>50 km) CALPUFF lagrangian puff model. In the final stage, an analysis of the predicted and observed values was carried out using such statistical methods as geometric mean bias (MG), geometric variance (VG) and fractions of predictions within a factor of two observations (FAC2).

During the modelling study, the highest one-hour concentration level was found to be 1868.10 OU (Odor Units), and the 24-hour concentration level was found to be 1316 OU, representing a decrease of approximately 30 percent. According to the measurement made, the maximum concentration value was 2455 OU. Odor measurements were carried out at 13 points within the area in order to assess the prediction results. When the results were assessed using the MG, VG and FAC2 statistical methods, it was observed that an acceptable model performance was not achieved for the whole sampling point. When the reason for this was investigated, it was concluded that the observed values were lower than the predicted values due to the fact on the measurement days, the odor was dispersed by wind. It was further concluded that the observed values were higher than the predicted values as a result of odors emitted by other plants in the area. When the measurements in residential areas were examined to identify the effect of the odors, it was determined that although the primary density of settlement is to the southwest of the plant, it was not this area that was affected most, but rather the area to the northeast, where there is a lower settlement density.     

铁矿石烧结烟气脱硫灰处理含铬废水

在分析铁矿石烧结烟气脱硫灰成分的基础上,利用脱硫灰中的亚硫酸盐还原废水中的Cr(Ⅵ),再加碱中和,通过沉淀去除铬。在初始废水pH 1.0、脱硫灰加入量0.06 g/mg(以Cr(Ⅵ)计)、振荡转速160 r/min、振荡时间25 min、中和pH 7.5的最佳工艺条件下处理模拟含铬废水,Cr(Ⅵ)质量浓度由10.00 mg/L降至0.18 mg/L,去除率达98.2%。最佳工艺条件下处理3种实际含铬废水,处理后出水的Cr(Ⅵ)和总铬的质量浓度及pH均满足GB 8978—1996《污水综合排放标准》。实现了对脱硫灰的综合利用、化害为利和以废治废的目标。