Analysis and prediction of $$\mathrm{PM}_{10}$$ concentration levels in Tunisia using statistical learning approaches

Over the past years, the health impact of airborne particulate matter \(\mathrm{PM}_{10}\) has become a very topical subject. Thereby, a lot of research effort in the environmental sciences goes towards the modeling and the prediction of ambient \(\mathrm{PM}_{10}\) concentrations. In this paper, we are interested in the statistical classification of the daily mean \(\mathrm{PM}_{10}\) concentration in Tunisia according to the authority regulation. We consider two monitoring stations: a big industrial station and a traffic station. The main goal of this work is to determine the pertinent predictors of \(\mathrm{PM}_{10}\) concentration within a nonlinear multiclass framework. To do this, we used two popular statistical learning methods; the support vector machines (SVM) and the random forests (RF). The statistical results obtained on the real datasets, show that RF outperform SVM for the purpose of variable selection even with a reduced number of observations compared to the number of explicative variables. It was also demonstrated that the \(\mathrm{PM}_{10}\) concentration measured yesterday is the most relevant predictor of its present-day value. Moreover, we found that the more delayed values of \(\mathrm{PM}_{10}\) concentration may be crucial to get an accurate prediction.     

Vertical oil dispersion profile under non-breaking regular waves

An experimental program was conducted to investigate vertical oil dispersion of surface oil spills under non-breaking regular waves. The variation in oil concentration caused by oil dispersion in a water column was studied to determine the vertical oil dispersion profile. The experiments were performed using different waves characteristics for different volumes of oil spill to evaluate the variation in oil concentration at three depths at two sampling stations. The correlations between oil concentration and the main parameters of wave characteristics, oil spill volume, sampling depth, and distance of sampling stations to spill location were assessed. The results revealed that the trend of variation in oil concentration versus wave steepness is linear. The results obtained from experimental measurements indicated that the oil concentrations at mid-depth were 44–77 % and the concentrations near the flume bed were 12–33 % of the concentration near the water surface.     

Simulations of the flow in the Mahakam river–lake–delta system,Indonesia

Large rivers often present a river–lake–delta system, with a wide range of temporal and spatial scales of the flow due to the combined effects of human activities and various natural factors, e.g., river discharge, tides, climatic variability, droughts, floods. Numerical models that allow for simulating the flow in these river–lake–delta systems are essential to study them and predict their evolution under the impact of various forcings. This is because they provide information that cannot be easily measured with sufficient temporal and spatial detail. In this study, we combine one-dimensional sectional-averaged (1D) and two-dimensional depth-averaged (2D) models, in the framework of the finite element model SLIM, to simulate the flow in the Mahakam river–lake–delta system (Indonesia). The 1D model representing the Mahakam River and four tributaries is coupled to the 2D unstructured mesh model implemented on the Mahakam Delta, the adjacent Makassar Strait, and three lakes in the central part of the river catchment. Using observations of water elevation at five stations, the bottom friction for river and tributaries, lakes, delta, and adjacent coastal zone is calibrated. Next, the model is validated using another period of observations of water elevation, flow velocity, and water discharge at various stations. Several criteria are implemented to assess the quality of the simulations, and a good agreement between simulations and observations is achieved in both calibration and validation stages. Different aspects of the flow, i.e., the division of water at two bifurcations in the delta, the effects of the lakes on the flow in the lower part of the system, the area of tidal propagation, are also quantified and discussed.     

新生鼠PFOS低剂量慢暴露对成年后神经行为的影响

为观察新生鼠全氟辛烷磺酸(PFOS)低剂量慢暴露对其成年后神经行为和海马组织影响,选取出生后5-7 d雄性SD幼鼠80只,按体重随机分为4组,分别为对照组(Con)、低剂量组(P5)、中剂量组(P10)、高剂量组(P20),每组各20只。从PND7开始染毒,共染毒12周,动态记录体重,并进行水迷宫、旷场实验、滚轮实验观察神经行为变化,同时取材进行HE染色,观察海马形态学改变。结果显示与Con组比较,P20组染毒8 d后出现体重增长减缓(P0.05),4周时P10和P20组死亡率明显升高;并且P10、P20组在4周,P5组在8周时,水迷宫实验逃逸潜伏期延长,目标象限停留时间缩短;P10、P20组大鼠在4周,P5组在8周时,旷场实验中央格停留时间延长,站立次数减少,行走总距离缩短;滚轮试验中,对照组和P5组肢体运动协调能力无显著性差异。P5组在染毒12周时出现海马神经元排列紊乱,胞核固缩及胞体胀大,CA1区细胞和齿状回闩区神经前体细胞数量明显少于Con组(P0.01)。上述结果表明,大鼠幼年PFOS低剂量慢暴露可损害其成年后空间学习记忆及自主探究能力,这种损害可能与海马神经元发生不足有关     

基于PBPK模型的大鼠体内镉分布的比较:联合暴露及单独暴露

环境中同时存在着多种重金属元素,联合暴露与单独暴露时,重金属在体内的蓄积分布情况也可能有所差异。为探究重金属元素(汞、铬、砷、铅)对镉(Cd)在体内分布的影响,建立了大鼠在Cd暴露下的药代动力学(PBPK)模型,并进行了包括Cd在内5种重金属的联合毒性实验,比较了Cd单独给药与重金属混合物给药2种方式下大鼠肝脏、肾脏中的Cd浓度水平。结果表明,联合暴露高(Hg Cl23.67 mg·kg~(-1),NaAsO_2 3.67 mg·kg~(-1),CdCl_2 10.55 mg·kg~(-1),K_2Cr_2O_7 6.40 mg·kg~(-1),Pb(OOCCH_3)_2·3H_2O 133.33 mg·kg~(-1))、中(HgCl_20.367 mg·kg~(-1),NaAsO_2 0.367 mg·kg~(-1),CdCl_2 1.055 mg·kg~(-1),K2Cr2O70.640 mg·kg~(-1),Pb(OOCCH_3)_2·3H_2O 13.333 mg·kg~(-1))、低(HgCl_2 0.0367 mg·kg~(-1),Na As O20.0367 mg·kg~(-1),Cd Cl20.1055 mg·kg~(-1),K_2Cr_2O_7 0.0640 mg·kg~(-1),Pb(OOCCH3)2·3H2O 1.3333 mg·kg~(-1))剂量组大鼠肝脏中Cd浓度分别为13.37、0.78和0.06μg·g~(-1);肾脏中Cd浓度分别为14.41、1.64和0.15μg·g~(-1)。与对照组相比,暴露组中Cd浓度有显著升高,且不同剂量组之间均有显著性差异。同剂量Cd单独暴露的PBPK模拟结果显示,肝脏及肾脏中的Cd浓度水平落在联合毒性实验结果的浓度范围内,初步推断其他4种重金属的联合暴露并没有影响Cd在大鼠肾脏和肝脏中的浓度分布。     

The prediction of adsorption isotherms of ester vapors on hypercrosslinked polymeric adsorbent

Adsorption isotherms of methyl acetate, ethyl acetate, propyl acetate, isopropyl acetate and ethyl propionate on hypercrosslinked polymeric resin (ND- 100) were measured at 303K, 318K and 333K,respectively, and well fitted by Dubinin–Astakhov (DA) equation. The plots of the adsorbed volume (q _v ) versus the adsorption potential (ε) at three different temperatures all fell basically onto one single curve for every ester. A predicted model based on DA equation was obtained on the basis of adsorption equilibrium data of methyl acetate, ethyl acetate and ethyl propionate at 318K. The model equation successfully predicted the adsorption isotherms of methyl acetate, ethyl acetate and ethyl propionate on ND-100 at 303K, and 333K, and also gave accurate predictive results for adsorption isotherms of the other two ester compounds (propyl acetate and isopropyl acetate) on ND-100 at 303K, 318K and 333K. The results proved the effectiveness of DA model for predicting the adsorption isotherms of ester compounds onto ND-100. In addition, the relationship between physico-chemical properties of adsorbates and their adsorption properties was also investigated. The results showed that molecular weight, molar volume and molar polarizability had good linear correlations with the parameter E (which represents adsorption characteristic energy) of DA equation.     

Improved blending strategy for membrane modification by virtue of surface segregation using surface-tailored amphiphilic nanoparticles

Membrane modification is one of the most feasible and effective solutions to membrane fouling problem which tenaciously hampers the further augmentation of membrane separation technology. Blending modification with nanoparticles (NPs), owing to the convenience of being incorporated in established membrane production lines, possesses an advantageous viability in practical applications. However, the existing blending strategy suffers from a low utilization efficiency due to NP encasement by membrane matrix. The current study proposed an improved blending modification approach with amphiphilic NPs (aNPs), which were prepared through silanization using 3-(Trimethoxysilyl)propyl methacrylate (TMSPMA) as coupling agents and ZnO or SiO₂ as pristine NPs (pNPs), respectively. The Fourier transform infrared and X-ray photoelectron spectroscopy analyses revealed the presence of appropriate organic components in both the ZnO and SiO₂ aNPs, which verified the success of the silanization process. As compared with the pristine and conventional pNP-blended membranes, both the ZnO aNP-blended and SiO₂ aNP-blended membranes with proper silanization (100% and 200%w/w) achieved a significantly increased blending efficiency with more NPs scattering on the internal and external membrane surfaces under scanning electron microscope observation. This improvement contributed to the increase of membrane hydrophilicity. Nevertheless, an extra dosage of the TMSPMA led to an encasement of NPs, thereby adversely affecting the properties of the resultant membranes. On the basis of all the tests, 100% (w/w) was selected as the optimum TMSPMA dosage for blending modification for both the ZnO and SiO₂ types.

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Photochemical indicators of ozone sensitivity: application in the Pearl River Delta,China

Surface O₃ production has a highly nonlinear relationship with its precursors. The spatial and temporal heterogeneity of O₃-NO _x -VOC-sensitivity regimes complicates the control-decision making. In this paper, the indicator method was used to establish the relationship between O₃ sensitivity and assessment indicators. Six popular ratios indicating ozone-precursor sensitivity, HCHO/NO _y , H₂O₂/ HNO₃, O₃/NO _y , O₃/NO _z , O₃/HNO₃, and H₂O₂/NO _z , were evaluated based on the distribution of NO_x- and VOC-sensitive regimes. WRF-Chem was used to study a serious ozone episode in fall over the Pearl River Delta (PRD). It was found that the south-west of the PRD is characterized by a VOCsensitive regime, while its north-east is NO _x -sensitive, with a sharp transition area between the two regimes. All indicators produced good representations of the elevated ozone hours in the episode on 6 November 2009, with H₂O₂/HNO₃ being the best indicator. The threshold sensitivity levels for HCHO/NO_y, H₂O₂/HNO₃, O₃/NO _y , O₃/NO _z , O₃/HNO₃, and H₂O₂/NO _z were estimated to be 0.41, 0.55, 10.2, 14.0, 19.1, and 0.38, respectively. Threshold intervals for the indicators H₂O₂/HNO₃, O₃/NO _y , O₃/NO _z , O₃/HNO₃, and H₂O₂/NO _z were able to identify more than 95% of VOC- and NO _x -sensitive grids. The ozone episode on 16 November 16 2008 was used to independently verify the results, and it was found that only H₂O₂/HNO₃ and H₂O₂/NO _z were able to differentiate the ozone sensitivity regime well. Hence, these two ratios are suggested as the most appropriate indicators for identifying fall ozone sensitivity in the PRD. Since the species used for indicators have seasonal variation, the utility of those indicators for other seasons should be investigated in the future work.

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Improving simulations of sulfate aerosols during winter haze over Northern China: the impacts of heterogeneous oxidation by NO<Subscript>2</Subscript>

We implemented the online coupled WRF-Chem model to reproduce the 2013 January haze event in North China, and evaluated simulated meteorological and chemical fields using multiple observations. The comparisons suggest that temperature and relative humidity (RH) were simulated well (mean biases are–0.2K and 2.7%, respectively), but wind speeds were overestimated (mean bias is 0.5 m?s^–1). At the Beijing station, sulfur dioxide (SO₂) concentrations were overpredicted and sulfate concentrations were largely underpredicted, which may result from uncertainties in SO₂ emissions and missing heterogeneous oxidation in current model. We conducted three parallel experiments to examine the impacts of doubling SO₂ emissions and incorporating heterogeneous oxidation of dissolved SO₂ by nitrogen dioxide (NO₂) on sulfate formation during winter haze. The results suggest that doubling SO₂ emissions do not significantly affect sulfate concentrations, but adding heterogeneous oxidation of dissolved SO₂ by NO₂ substantially improve simulations of sulfate and other inorganic aerosols. Although the enhanced SO₂ to sulfate conversion in the HetS (heterogeneous oxidation by NO₂) case reduces SO₂ concentrations, it is still largely overestimated by the model, indicating the overestimations of SO₂ concentrations in the North China Plain (NCP) are mostly due to errors in SO₂ emission inventory.

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Approaching the binding between Cu(II) and aerobic granules by a modified titration and µ-XRF

Interactions between metals and activated sludge can substantially affect the fate and transport of heavy metals in wastewater treatment plants. Therefore, it is important to develop a simple, fast and efficient method to elucidate the interaction. In this study, a modified titration method with a dynamic mode was developed to investigate the binding of Cu(II), a typical heavy metal, onto aerobic granules. The titration results indicated that pH and ionic strength both had a positive effect on the biosorption capacity of the granular sludge. The µ-XRF results demonstrated that the distribution of metals on the granular surface was heterogeneous, and Cu showed strong correlations and had the same “hot spots” positions with other metal ions (e.g., Ca, Mg, Fe etc.). Ion exchange and complexing were the main mechanisms for the biosorption of Cu(II) by aerobic granules. These results would be beneficial for better understanding of Cu(II) migration and its fate in wastewater treatment plants.