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. 相似文献
ABSTRACTThe aim of this study was to assess the consequences of human impact on the characteristics of sediments heavy metal concentration, grain size and its influence on the structure of the microbial and meiofaunal community assemblages. A survey was carried out in July 2013 within six sites located in the Bizerte Lagoon (Tunisia), both downstream and upstream of industrial effluents. The highest total sediment metal concentrations were detected in stations located close to the industrial sewage discharge points. In these stations, the lowest densities of the total meiofauna (33?±?13?ind/10?cm?2) and conversely the highest densities of cultivable bacteria that are heavy metal resistant have been reported (16?±?80.34?CFU?g?1). Univariate (ANOVA) and multivariate (MDS/CCA) analyses demonstrate high dissimilarity (0.06) in meiofaunal and bacterial community structures between downstream and upstream industrial sewages. Furthermore, canonical correspondence analysis CCA results indicated that heavy metal sediment contamination promoted bacteria that are resistant to heavy metals, while heterotrophic bacteria supported the development of meiofauna taxa. The results highlight the importance of bacteria/meiofauna interactions, as both meiofaunal and microbial communities give indications of the ecological impact of heavy metal contamination in sediment. 相似文献
Phenolic compounds in olive oil mill wastewaters were analysed by HRGC–MS after extracting the acidified solution with ethyl acetate and derivatization with N,O-bis(trimethylsilyl)trifluoroacetamide. Both simple and complex phenols were detected with the latter being the most abundant. 1,2-dihydroxybenzene (catechol), p-hydroxyphenyl ethanol (tyrosol), 3,4-dihydroxyphenyl ethanol (hydroxytyrosol) and 4-hydroxy-3-methoxyphenyl ethanol (homovanillyl alcohol) predominated among the simple phenols using a gas chromatograph coupled with a mass selective detector. 相似文献
Previous studies that have investigated relationships between the lunar cycle and recreational fishing success have all suffered from various problems—most notably, the failure to account for potential confounders in a statistically rigorous manner. We propose methods to account for season, fisher identity, fishing effort, day, and variation in biomass, all of which have previously either been omitted or handled in an ad hoc way. These are applied to two sets of data on recreational fishing of the snapper Pagrus auratus in New Zealand. In addition to estimating effects due to lunar phase, we also implement these methods to analyse the performance of a lunar-based indigenous M${{\bar{\mathrm{a}}}}$ori fishing calendar. Recreational fishers in New Zealand often make use of such calendars in order to predict fishing success on specific days, however little is known about the performance of such predictions or whether they hold any practical use to the everyday angler. A relationship between lunar phase and fishing success is identified, as well as support for some aspects of the M${{\bar{\mathrm{a}}}}$ori fishing calendar predictions. The magnitudes of these effects are small, however, casting doubt on the practical relevance of lunar based fishing predictions. In addition to the known seasonal trend associated with annual migration, an unexpected second trend is detected, and postulated to be associated with intense local fishing pressure over the summer vacation period. 相似文献
Microwave irradiation has been used to prepare Al, Fe-pillared clays from a natural Tunisian smectite from the El Hicha deposit (province of Gabes). Chemical analysis, XRD spectra and surface properties evidenced the success of pillaring process. The obtained solids present higher surface area and pore volume than conventionally prepared Al-Fe pillared clays. The main advantages of the microwave methodology are the considerable reduction of the synthesis time and the consumption of water. The microwave-derived Al-Fe pillared clays have been tested for catalytic wet air oxidation (CWAO) of phenol in a stirred tank at 160°C and 20 bar of pure oxygen pressure. These materials are efficient for CWAO of phenol and are highly stable despite the severe operating conditions (acidic media, high pressure, high temperature). The catalyst deactivation was also significantly hindered when compared to conventionally prepared clays. Al-Fe pillared clays prepared by microwave methodology are promising as catalysts for CWAO industrial water treatment.