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As seen in Table 4, as the concentration increases, the length of the mass transferzone (MTZ) increases and the fractional bed utilization (FBU) decreases. Therefore,in general terms, as the initial concentration increases, the driving force or masstransfer increases, and results in a decrease in the mass transfer zone (MTZ). Inlaboratory experiments, the fixed beds are not used long enough to ensure a fullydeveloped profile (a constant pattern behaviour); where the same operatingconditions, the value of MTZ remains constant. In this case, when working withvery short columns, the mass transfer zone moves to non-constant velocity, since theconstant pattern is not fully developed. In this case, an approximate expression forestimate MTZ parameter has been used (constant velocity supposed), so results thatmay not match those expected can be obtained (Wankat, 1990).Mass transfer zone increased with increasing flow rate, leading to faster saturation ata higher value of the volumetric flow rate. In this case, as the volumetric flow rateincreases, the mass transfer zone (MTZ) and the fractional bed utilization increases.If the concentration profile, C/Co versus length, is studied, an increase of thevolumetric flow rate leads to an increase of the mass transfer zone and worsens theuse of the bed.BREAKTHROUGH MODELLINGThe estimation of error between the experimental and predicted values of C/Co wasdone by using modified form of the Marquardt’s percent standard deviation (MPSD)represented by Eq. (5) in Table 1. Therefore, adsorption capacity obtained byThomas and Wolborska model and value obtained by Yoon-Nelson model werecompared with experimental parameters using standard error of estimate (SE)method: Eq (6) and (7), in Table 1.The Thomas ModelThomas model parameters, k T and q 0, were determined by not linearized expressionof Eq (1). K T and q 0 values are shown in Table 5. It can be observed from Table 4that the values of q 0 increased with an increase in the value of C 0 and with adecrease in the value of the volumetric flow rate.Table 5. Predicted parameters for Thomas model and model deviations forisoproturon adsorption on activated carbon.C 0(g.L -1 )Q(mL.min -1 )Z(cm)K T(L.h -1 .mg -1 )q 0 exp(mg.g -1 )q 0 cal(mg.g -1 )MPSD SE50 1.0 2.0 0.10 16.51 15.57 62.16 0.13150 1.0 2.0 0.06 16.75 18.86 21.46 0.42100 2.0 2.0 0.11 19.97 25.31 203.13 0.75100 3.0 2.0 0.09 13.69 20.75 40.87 1.21Fig. 3 (a-b) show the experimental and theoretical breakthrough curves obtained atdifferent operating conditions using Thomas model.AcademyPublish.org - The Impact of Pesticides346
Fig.3. Breakthrough curves of isoproturon removal by granular activated carbonpacked columns using Thomas model of a) different initial concentrations (bedweight = 0.2 g, initial, flow rate = 1.0 mL.min -1 ), b) different flow rates (bed weight= 0.2 g, initial isoproturon conc. = 100.0 µg.L -1 ).The Yoon-Nelson ModelThe values of k YN and were determined by not linearized expression of Eq (2).These values are listed in Table 6.Table 6. Predicted parameters for Yoon-Nelson model and model deviations forisoproturon adsorption on activated carbon.C 0 (g.L -1 )Q (mL.min -1 )Z(cm)K YN (h -1 ) exp(h) cal(h)MPSDSE50 1.0 2.0 0.005 620.14 677.92 60.03 7.86150 1.0 2.0 0.008 306.50 261.98 31.33 8.90100 2.0 2.0 0.011 405.11 421.90 139.17 2.35100 3.0 2.0 0.009 260.50 230.59 40.87 5.13AcademyPublish.org - The Impact of Pesticides347
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The Impactof PesticidesEdited by:Pr
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Other access free resources from Ac
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The Impact of PesticidesPrepared an
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Table of Contentsp.203-p.224 Behavi
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About authorspublished by Elsevier.
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About authorsof medical researchers
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About authorsdifferent spatial scal
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About authorsEducation:Bachelor’s
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About authorsSensors - A Nanotechno
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Section 1HUMAN EXPOSURE TO PESTICID
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ecently explored on preliminary stu
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individuals within 1 day (Jokanovic
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occupational environmental health r
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must be considered, since effective
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Jensen BH, Petersen A, and Christen
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Ragas AMJ, and Huijbregts MAJ (1998
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Weichenthal S, Moase C, and Chan P
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human poisoning, general acute symp
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Management of the cholinergic syndr
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1982; Lotti, 1992; Jokanović et al
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exposed populations, revealed high
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DiazepamBenzodiazepines are CNS dep
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Among the many classes of oximes in
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inhibited by dichlorvos (a dimethox
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Dawson, 1995). It appears that the
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Eddleston M, Eyer P, Worek F, Moham
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Jokanović M, Kosanović M (2010b).
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Ray DE (1998). Chronic effects of l
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Worek F, Eyer P, Kiderlen D, Thierm
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developing countries is due to suic
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count and morphology, as well as se
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PON1 modulation of genetic damageFe
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elationship between OP exposure and
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Blatter-Garin MC, James RW, Dussoix
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Hung RJ, Hall J, Brennan P, Boffett
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Rojas-García AE., Solís-Heredia M
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Occupational Exposure to Pesticides
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considered as conditions typical of
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observed adverse health outcome. Su
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within cells can oxidize biomolecul
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of the study. A face-to-face questi
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PesticidesFungicideInsecticide-Nema
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Table 4. Mixtures of pesticides use
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In pesticide applicators, Table 7 s
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DISCUSSIONThe agricultural workers
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changes in the antioxidant enzyme C
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Bajpayee, M.; Pandey, A. K.; Parmar
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Environmental health criteria 155.
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Palus, J.; Rydzynski, K.; Dziubalto
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Singh, N.P.; McCoy, M.T.; Tice, R.R
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INTRODUCTIONPopulations may be occu
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exposure scenarios on the basis of
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not present adverse health effects
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greenhouse workers exposed to malat
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Paraoxon is then either metabolized
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cyclohexene-1,2-dicarboximide, CAS
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metabolite of phthalates, such that
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scenarios were simulated, assuming
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Table 2. Biological reference value
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References N a urinarybiomarkeStudi
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Figure 2. Representation of a BRV d
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Figure 4. Conceptual representation
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Figure 6 Conceptual representation
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REFERENCESACGIH, 2011. Documentatio
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Bradway, D.E., Shafik, T.M., 1977.
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EPA, 1999b. Registration Eligibilit
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Hines, C.J., Deddens, J.A., Jaycox,
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McCollister, S.B., Kociba, R.J., Hu
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Verberk, M.M., Brouwer, D.H., Brouw
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important IGFBP for binding IGF-1 i
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secretion of IGF-1 (Tannheimer et a
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FIGURESFig. 1. An “hormetic” ef
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Landi F, Capoluongo E, Russo A, Ond
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Smith WJ, Underwood LE, Clemmons DR
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Section 2PESTICIDES IN THEENVIRONME
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vicinity of subsoil waters and ther
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Hieracium pilosella, southernwood -
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formed clusters (Figure 3). Ultrast
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Fig. 5. Fragment of hepatocyte of t
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Szarek, J, Skibniewska, K, Wojtacka
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negative effects (ZALUCKI et al., 2
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Figure 2. Appropriated sampling pro
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Figure 4. Illustration of the conse
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(HAILE et al., 1998). Earlier resul
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Table 1. Distribution of the applic
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Means followed by the same letter i
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(involving pests and natural enemie
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efore the pest emergence and their
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Table 3 (continuation)…AcademyPub
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Table 5. Effect of different fungic
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Table 6. Magament used including do
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adopted by Brazilian soybean grower
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Pickle, C.S.; Caviness, C.E. Yield
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This chapter reports on Dutch surfa
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several different occasions at any
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The greatest number of pesticides a
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Accumulated ExceedanceIt is useful
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For the years 2003-2009 the calcula
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Bonzini S, Verro R, Otto S, Lazzaro
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atios of the pesticide amounts in t
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Table 1. (Cont.) Runoff ratios of p
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mefenacet and simetrin were observe
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Table 2. (Cont.)Pesticide concentra
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Table 2. (Cont.)Pesticide concentra
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Fig. 3. Typical weekly variation of
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(BAM) in water (Pukkila et al. 2009
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Table 5. Concentrations of pesticid
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Table 6. Maximum concentrations of
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Iwafune, T, Inao, K, Horio, T, Iwas
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Suzuki, M, Takemine, S, Yoshida, M,
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factor, etc. Levels of pesticides i
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factor of 10 above ambient sea wate
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weight sample. Minimum were shown f
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Figure 3. DDTs in mussel samples fo
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Figure 5. HCB in mussel samples for
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Figure 8. Methoxychlor in mussel sa
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ACKNOWLEDGEMENTAuthors thank UNEP/M
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Pesticide Risk Index of Del Azul Wa
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on that presented in Swanson et al.
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eference value for that substance.
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predict the aquatic toxicity of a s
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Calculation Model of Aggravating Fa
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To estimate the values of Human Hea
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water in comparison with the durati
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Cypermethrin (95 th percentile (P 9
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Table 8 shows the results of the De
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are many ranking systems of dangero
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REFERENCESAres J. (2004). “Estima
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Mackay D. and Paterson S. (1991).
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Long-term Monitoring of Pesticides
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Sampling sites of the survey in 200
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than those in Lake Biwa and Seta Ri
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Fig. 7 Detection of fungicides in R
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Fig. 11 Detection of herbicides in
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Monitoring of pesticides in Yanamun
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A measured volume (1000 mL) of the
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SimetrynePretilachlorConcentration
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Fig. 18 Maximum concentrations of t
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Ecological risk assessmentFig. 20 Y
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REFERENCESAgradi E, Baga R, Cillo F
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Time Trend Variation of Selected Pe
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Table 1. Physical and chemical prop
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marketed under variety of trade nam
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Figure 3. Long-term trends of globa
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laboratory animals fed or injected
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Page 298 and 299: Soil samplingSoil sampling was foll
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Page 308 and 309: Contrary to the results of ΣDDT, t
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Page 314 and 315: Mean concentration (ng g -1 dw)3002
Page 316 and 317: CONCLUSIONSAn evaluation of selecte
Page 318 and 319: Hung, D.Q., Thiemann, W., (2002),
Page 320 and 321: Viet, P.H., Hoai, P.M., Minh, N.H.,
Page 322 and 323: found in tissues or fluids samples
Page 324 and 325: Study area and SamplingThis study w
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Page 330 and 331: Increase in crops area (x1000)Ha)25
Page 332 and 333: Table 1. Blood concentrations of or
Page 334 and 335: Council Directive 90/533/EEC of 15
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Page 338 and 339: Smith, AG (2004). “Toxicology of
Page 340 and 341: Pesticides are used in order to pro
Page 342 and 343: EXPERIMENTALMaterialsIsoproturon wa
Page 344 and 345: RESULTS AND DISCUSIONEquilibrium is
Page 348 and 349: Fig.4. Breakthrough curves of isopr
Page 350 and 351: Fig.6. Breakthrough curves of isopr
Page 352 and 353: Fig.8. Experimental and theoretical
Page 354 and 355: Section 3PESTICIDE ANALYSISAcademyP
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Page 370 and 371: chromatography with negative-ion el
Page 372 and 373: GPC was applied as a nondestructive
Page 374 and 375: Charlton A.J.A., Stuckey, V. (2009)
Page 376 and 377: Lehotay, S.J., Mastvoska, K. & Yun,
Page 378 and 379: Rodrigues, F. M., Mesquita, P. R. R
Page 380 and 381: Analytical methods to assess the im
Page 382 and 383: acetylcholine, a neurotransmitter t
Page 384 and 385: 1.3 to 22.3% for all pesticides. Li
Page 386 and 387: Malathion, parathion, fenitrothion,
Page 388 and 389: Fuller, BH and Berger, GMB (1990).
Page 390 and 391: Table 1. Largest exporters of coffe
Page 392 and 393: Fig. 1: Structures of (a) Phosphate
Page 394 and 395: ELECTROCHEMICAL BIOSENSORBiosensors
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inorganic and organic species a lar
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surface area and be easily modified
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Acetylcholine + H 2 O AChE Choline
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Wang, 2010) and tetracyanoquinodime
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PDDA/AChE/PDDA/CNT/GCAChE-Au-PPy/GC
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ng/mL and good precision (RSD ) 5.3
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FUTURE PERSPECTIVESThe detection of
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Du, D; Wang, M; Cai, J; Qin, Y; Zha
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Martorell, D; Cespedes, F; Fabreaga
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The Pesticide Action Network (PAN).
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About EditorMilan JokanovićProfess
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THE IMPACT OF PESTICIDESPesticides
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