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Influences of soil properties and leaching on nickel toxicity to barley root elongation

Influences of soil properties and leaching on nickel toxicity to barley root elongation
Influences of soil properties and leaching on nickel toxicity to barley root elongation

In?uences of soil properties and leaching on nickel toxicity to barley root elongation

Bo Li a ,Hongtao Zhang a ,Yibing Ma a ,b ,n ,Mike J.McLaughlin b ,c

a

Ministry of Agriculture Key Laboratory of Plant Nutrition and Nutrient Cycling,Institute of Agricultural Resources and Regional Planning,Chinese Academy of Agricultural Sciences,12Southern Street of Zhongguancun,Beijing 100081,China b

Sustainable Agriculture Flagship,CSIRO Land and Water,Commonwealth Scienti?c and Industrial Research Organization,Private Mail Bag 2,Glen Osmond,South Australia 5064,Australia c

Soil and Land Systems,University of Adelaide,Private Mail Bag 1,Glen Osmond,South Australia 5064,Australia

a r t i c l e i n f o

Article history:

Received 12January 2010Received in revised form 19September 2010

Accepted 9October 2010

Available online 28October 2010Keywords:Nickel Leaching

Phytotoxicity Risk assessment

a b s t r a c t

The in?uence of soil properties on Ni toxicity to barley root elongation was investigated using 17Chinese soils treated with soluble Ni salts,with and without leaching.The effective concentration of added Ni causing 50%inhibition (EC50)in barley root elongation ranged from 48to 2519mg/kg in unleached soils and 46to 42381mg/kg in leached soils.Leaching decreased Ni phytotoxicity signi?cantly for approximately 90%of soils,and the effect was most pronounced for soils with pH Z 8.2.Soil pH was the most important factor controlling Ni toxicity in soils,explaining approximately 68%of the variance in unleached and leached EC50values.Regression models between toxicity thresholds and soil pH,soil organic carbon content,or effective cation exchange capacity were developed.The models showed good agreement with those developed previously for European soils (r 2?0.87).These quantitative relationships between Ni toxicity and soil properties are helpful to develop soil-speci?c guidance on Ni toxicity thresholds for China.

&2010Elsevier Inc.All rights reserved.

1.Introduction

The in?uence of soil properties on metal toxicity to soil organisms is now well recognized.Quantitative relationships between the toxicity of metals added to soils and soil properties have been developed for copper (Cu),nickel (Ni),and zinc (Zn)in the last few years (Lock and Janssen,2001;Smolders et al.,2004;Daoust et al.,2006;Rooney et al.,2006,2007;Oorts et al.,2006a;Broos et al.,2007;Warne et al.,2008).It has been found that soil pH,cation exchange capacity (CEC),organic carbon (OC)content,and clay content were very important parameters in predicting the toxicity of metals in soils.It has been shown that high soil pH could signi?cantly decrease Ni phytotoxicity in soils (Wallace et al.,1977;Weng et al.,2003)and Rooney et al.(2007)concluded that soil effective cation exchange capacity (eCEC,measured at actual soil pH)was the best single predictor for Ni phytotoxicity in a range of European soils.Unfortunately,the effectiveness of phytotoxicity models developed for European soils in predicting toxicity for arid,sub-tropical,and tropical regions,which have very different soil properties,is not known.China has a wide range of soils developed in different agroclimatic zones,such as acidic sub-tropical red earth in south

China and calcareous soils under arid climates in west and north China.Furthermore,Chinese soils are usually poor in organic matter and have highly variable clay mineralogy (Xiong and Li,1987).It is therefore necessary to validate models of Ni phytotoxicity in soils for a wider range of soil environments,such as those found in China.

In developing models for Ni phytoxicity,it is important to examine the effects of soil Ni spiking procedures on the toxicity endpoints studied.It has previously been demonstrated that spiking soils with soluble metal salts induces many artifacts that need to be controlled if the toxicity data are to be representative of ?eld conditions (Smit and van Gestel,1998;Speir et al.,1999;Stevens et al.,2003;Bongers et al.,2004;Oorts et al.,2006b,2007;Smolders et al.,2009).Leaching excess salts out of the soil after spiking is particularly important to reduce overestimates of toxicity (Stevens et al.,2003),and aging of metal in soil,at least for short periods,is also important (Ma et al.,2006).For example,Oorts et al.(2007)showed that Ni toxicity,expressed as total Ni concentrations in soil,for potential nitri?cation rate (PNR),glucose-induced respiration (GIR),and maize residue mineralization (MRM)in two soils (Woburn,pH 6.1;Cordoba,pH 7.6),decreased 1.6-fold after leaching.Smolders et al.(2009)further suggested Ni toxicity was reduced 1–3-fold after leaching and aging and that this correction was needed to determine predicted no effect concentration (PNEC)values for European soils with a range of physico-chemical properties.

The aims of the present study were therefore to determine the effect of leaching on Ni phytotoxicity in Chinese soils using barley root elongation as the toxicity endpoint,and to develop quantitative relationships between soil properties and the toxicity

Contents lists available at ScienceDirect

journal homepage:https://www.sodocs.net/doc/729517887.html,/locate/ecoenv

Ecotoxicology and Environmental Safety

0147-6513/$-see front matter &2010Elsevier Inc.All rights reserved.doi:10.1016/j.ecoenv.2010.10.021

n

Corresponding author at:Ministry of Agriculture Key Laboratory of Plant Nutrition and Nutrient Cycling,Institute of Agricultural Resources and Regional Planning,Chinese Academy of Agricultural Sciences,12Southern Street of Zhongguancun,Beijing 100081,China.Fax:+861082106225.

E-mail address:ybma@https://www.sodocs.net/doc/729517887.html, (Y.Ma).Ecotoxicology and Environmental Safety 74(2011)459–466

thresholds.Furthermore,we aimed to test the hypothesis that the toxicity models developed for European soils could be applied to soils with different properties,such as those in China.

2.Materials and methods 2.1.Soil samples and treatments

Seventeen soil samples from multiple locations in China were collected (0–20cm)and their locations were shown in Fig.1.The soils were selected to be representative of the major soil types and the distributions of soil pH and organic matter content of agricultural soils in China (Table 1).The physico-chemical properties of the soils were determined as outlined in Li et al.(2010).The silver–thiourea method was used for soil eCEC measurement (Rooney et al.,2006).Soil pH varied from 4.93to 8.90,OC content from 0.60%to 4.28%,eCEC from 6.36to 33.59cmol +/kg and clay content from 10%to 66%.

Triplicate air-dried soil samples (o 2mm)were spiked (50ml/kg soil)using different concentrations of NiCl 2solution (from 4.26?10à3to 8.18?10à1M)and thoroughly mixed by hand until the disappearance of all wet lumps to produce nominal concentrations of 37.5–2400mg Ni/kg dry weight soil for soils with pH 47;25–1600mg/kg dry weight soil for soils with pH 5–7and 12.5–800mg/kg dry

weight soil for soils with pH o 5,according to preliminary dose-range ?nding tests.The spiked soils were left to equilibrate for 2d at 100%maximum water holding capacity (MWHC)(Jenkinson and Powlson,1976),then air-dried and sieved again through a 2-mm plastic mesh.

Sub-samples of the spiked soil were leached by arti?cial rainwater (Oorts et al.,2007)for each Ni treatment and each soil before use.The arti?cial rainwater for leaching consisted of 5?10à4M CaCl 2,5?10à4M Ca(NO 3)2,5?10à4M MgCl 2,10à4M Na 2SO 4,and 10à4M KCl (pH 5.9).Soils were ?rst saturated with this solution by placing a perforated ?owerpot (bottom covered with ?lter cloth;mesh size,140–150m m)with the spiked soil in a bucket containing the leaching solution.Soils were left to equilibrate overnight.When the water table was above the soil surface,more solution was gently poured directly into the ?owerpots with saturated soil to increase the leaching volume to approximately two pore volumes.Finally,the pots were taken out of the buckets and left to drain overnight.Leached soil samples were air-dried and sieved through a 2-mm plastic mesh before use.All soil samples with or without leaching were stored at room temperature before toxicity evaluation.Total Ni concentrations were measured in both leached and unleached soils according to Zarcinas et al.(1996).The concentrations of Ni added (Ni added )to soil were calculated by subtracting total Ni concentrations in unspiked soils from those in spiked soils.Soil pore waters (two replications)were extracted according to Thibault and Sheppard (1992)by centrifugation of soil samples after incubation overnight at 50cm water tension at 201C.The extracted soil pore water was passed through 0.45m m ?lters.The pH and electrical conductivity (EC)of the soil pore waters were measured using a microelectrode pH and EC meter (Thermo Fisher Scienti?c Inc.,New York,USA).The concentrations of Ni in the soil pore waters were measured either by inductively coupled plasma–atomic emission spectrometry (Spectro?ame Modula,Spectro,Boschstr,Kleve,Germany)or inductively coupled plasma–mass spectrometry (Spectro?ame Modula,Spectro,Boschstr,Kleve,Germany)depending on their concentrations in the solution (Zarcinas et al.,1996).Assessment of metal retention of soils was determined using partition coef?cients.The soil–solution partition coef?cient (K d )is de?ned as the ratio of the metal concentration associated with the solid to the metal concentration in the surrounding aqueous solution when the

system is at equilibrium and was calculated according to the following equation (Sauve

′et al.,2000):

K d ?

Ni t àNi s ?V W

àás where Ni t is total Ni in soils (mg/kg),Ni s is dissolved Ni in soil solutions (mg/L),and V/W is the ratio of volume of soil solution to weight of soil sample (L/kg);hence,the unit for K d values is L/kg.

2.2.Barley root elongation assay

The barley root elongation assay was performed according to ISO 11269-1(1993).Before commencing the barley root elongation assay,the soils were equilibrated for 1week at 70%of pF 1.9(80cm water tension).The assay was performed in a growth chamber with 20-W tungsten lamps to maintain a maximum light intensity of 24,000lx/m 2for 5d under day (14h at 221C)/night conditions (10h at 181C).Soil moisture content was maintained at 70%of pF 1.9throughout the whole experiment ($60%water holding capacity).Pre-germinated barley

seeds

Fig.1.The location of the soil sampling sites.

Table 1

Selected properties of Chinese soils used in the present study.No.Site name

Soil type

pH a (1:5)EC a (m S/cm)eCEC b (cmol +/kg)Org.C c (%)CaCO 3(%)Clay d (%)S1Haikou,Hainan Latersol 4.931118.75 1.51o 0.566S2Qiyang,Hunan

Red earth 5.31747.470.87o 0.546S3Hailun,Heilongjiang Black soil 6.5615333.6 3.03o 0.540S4Jiaxing,Zhejiang Paddy soil 6.7015919.3 1.42o 0.541S5Hangzhou,Zhejiang Paddy soil 6.8020312.8 2.46o 0.539S6Chongqing,Sichuan

Purplish soils 7.127122.30.99o 0.527S7Guangzhou,Guangdong Paddy soil 7.271378.30 1.470.1525S8Lingshan,Beijing Brown earth 7.489322.7 4.28 4.2720S9Hulunber,Neimeng Chernozem 7.6688822.7 2.660.2737S10Gongzhuling,Jilin Black soil

7.8214728.8 2.170.2745S11Shijiazhuang,Heibei Cinnamon soil 8.1930211.7 1.01 3.8421S12Urumchi,Xinjiang Gray desert soil 8.7222710.30.87 5.0825S13Yangling,Shanxi Loessial soil 8.83838.460.628.9228S14Langfang,Hebei Fluvo-aquic soil 8.84 5.7 6.360.60 2.4210S15Zhengzhou,Henan Fluvo-aquic soil 8.861098.50 1.570.1516S16Zhangye,Gansu Irrigated desert soil 8.861528.08 1.027.7520S17

Dezhou,Shandong,

Fluvo-aquic soil

8.90

112

8.33

0.69

6.17

18

a

Measured in deionized water (soil:solution ratio 1:5).

b

Effective cation exchange capacity,determined using the unbuffered silver–thiourea method.c

Determined by difference between total carbon and inorganic carbon content.d

Sedimentary method.

B.Li et al./Ecotoxicology and Environmental Safety 74(2011)459–466

460

(Hordeum vulgare cv.Pinggu No.1)with radicles o 2mm in length were planted in each pot.Parallel-sided pots described in ISO 11269-1(1993)were replaced with a polyvinyl chloride cylinder with an inner diameter of 35mm and soil depth of 100mm according to Rooney et al.(2006),and the number of seeds was reduced to four per pot.Soils were packed into the cylinders to approximate the bulk density of each soil (1.20–1.35g/cm 3).After 5d,plant roots were removed intact from soils and washed twice in deionized water,and the length of the longest root on each plant recorded.Each replicate value represents the mean root lengths of four plants per pot.The percentage of barley root elongation with respect to controls (RE,%)in a test medium was calculated using the equation,RE ?

RE t

RE c

?100where RE t is the root length in the test medium and RE c is the root length in the control without added Ni.2.3.Data statistical analysis

The dose–response data was ?tted to a log–logistic curve (Haanstra et al.,1985)in Microsoft Excel (Eq.(1))for each of the soils using a specialized curve ?tting macroroutine developed by Barnes et al.(2003):Y ?

Y 0

1te b eX àM T

e1T

where Y is relative barley root elongation (%),X is log 10of Ni added (mg/kg).M is the log 10of ECx (effective concentration of added Ni that decreases barley root elongation by a user de?ned percentage,i.e.,EC10,EC20,or EC50),Y 0and b are curve ?tting parameters.The metal doses in soils causing 10%(EC10),20%(EC20),and 50%(EC50)inhibition in root elongation and their 95%con?dence intervals were derived from the ?tted curve parameters and standard errors according to Haanstra et al.(1985).

Hormesis,a stimulation of response that can occur at low doses followed by inhibition at higher doses,was modeled according to Schabenberger et al.(1999)using Tablecurve 2D V5.01.The EC10,EC20,and EC50values,with respective 95%con?dence limits were determined as follows:Y ?

a tbX 1tk 100àk t100100àk bc a

!

e

d ln eX =c T

e2T

where Y is relative barley root elongation,X is added Ni concentration,a ,b ,c ,and d

are curve ?tting parameters,k is a variable relating to effective concentrations (such as EC10and EC50).When k equals to 10,20,or 50,the parameter c is de?ned as EC10,EC20,or EC50values,respectively,and their con?dence intervals can be calculated by Tablecurve 2D V5.01.Estimated initial parameter values of a ,b ,c and d were used as input parameters into Tablecurve 2D V5.01before ?tting,and optimal values were calculated by minimizing the RMSE of predicted and measured EC values.The parameter b is used to examine the signi?cant level of hormesis relative to the

control;when 95%con?dence intervals of parameter b are above zero,the hormesis response is considered to be signi?cant.

The adequacy of the predicted equations were checked by examining the distribution of the residuals and ensuring the minimum of calculated root mean squared error (RMSE)based on the differences of observed values and predicted values.Stepwise multiple liner regression was employed using SPSS 12.0for Windows (SPSS,Chicago,IL,USA)to examine the relationships between toxicity thresholds (EC10,EC20,and EC50)and soil properties (Table 1).Parameters were only log transformed if necessary after testing the data for normality and homogeneity of variance.Relationships were deemed signi?cant at p r 0.05.

3.Results

3.1.Dose–response curves and toxicity thresholds in unleached and leached soils

For unleached soils,EC10values ranged from 10(Haikou soil)to 896mg/kg (Hulunber soil),EC20values ranged from 18(Haikou soil)to 1029mg/kg (Hulunber soil),and EC50values ranged from 48(Haikou soil)to 2519mg/kg (Zhengzhou soil),representing an 89.6-,57.2-,and 52.5-fold variation among soils (Table 2).For leached soils,EC10,EC20,and EC50values varied from 17to 2372,25to 42381,and 46to 42381mg/kg,respectively,representing a 139.5-,495.2-,and 451.8-fold variations among soils.A signi?cant (p r 0.05)increase in barley root elongation (i.e.,hormesis)with initial increase in doses of Ni was observed in leached Langfang soil (Fig.2E),where 95%con?dence intervals of parameter b in Tablecurve 2D V5.01were above zero.Three of the EC20values and six of the EC50values could not be calculated due to the highest measured added Ni dose (2276–2381mg/kg)causing less toxicity than a 20%or 50%inhibition (Fig.2G–L and Table 2).3.2.The effect of leaching on Ni toxicity

The in?uence of leaching on Ni toxicity was found to be variable among soils (Fig.2).A signi?cant (p r 0.05)decrease in Ni toxicity was found with leaching for 8soils (47%of soils)for EC10values,10soils (59%)for EC20values,and 15soils (88%)for EC50values.The leaching factor (LF)for Ni toxicity thresholds was determined by calculating

Table 2

Toxicity thresholds for Ni added to soils (mg/kg)measured by barley root elongation for 17Chinese soils.No.

Unleached soil (mg/kg)Leached soil (mg/kg)NOEC

EC1095%CI EC2095%CI EC5095%CI NOEC EC1095%CI EC2095%CI EC5095%CI S1–105–141811–244837–64–1712–242519–324638–54S2–1914–263024–386758–77

–2415–383826–487156–82

S3618781660–923913818–102011941152–1238734684561–834963834–11121729*1551–1927S466735711–760795777–813909897–920–488*437–546649*599–7021055*1014–1097S5161364337–392480455–507773744–804148754*685–831903*842–9671226*1179–1276S6112181159–206238213–266382343–425128168145–195265236–296574*534–617S7–258222–301328287–356495429–571250913*487–1156980*556–14171105*719–1619S8105550495–611702651–75610651021–1110667875*825–9271053*1007–11021448*1398–1498S958896740–10861029906–117013041203–141332973894–105911751101–12541622*1554–1692S10–772415–1436889583–153411301024–1247129491

457–529639606–6731280*1250–1310S11–404333–489688603–78417091604–1821252Z 2372*–

NC *

–NC *–S12–358241–530544407–7271115940–1322–14916–1407Z 2381*–NC *–S1364265163–431475339–66612941123–14892511065*441–2570Z 2286*–

NC *–

S14a –790653–955936821–106712511168–133910251420798–25271457948–22381522*1274–1817S1522551401–759966795–117425192243–28291230Z 2276*–NC *–NC *–S1628733636–845911827–100313201264–1378111Z 1845–

NC *

–NC *–S17

60

119

93–153

256

213–307

942

856–1038

121

894*

742–1691

Z 2380*

NC *

NOEC:The highest concentration of added Ni that did not reduce barley root elongation signi?cantly (p r 0.05).

ECx (x ?10,20,and 50):The effective concentration of added Ni that decreased barley root elongation by 10,20and 50%of control.95%CI:Ranges given as 795%con?dence interval.

–:The 95%CI could not be determined as the corresponding ECx values could not be determined.

NC:Toxicity thresholds could not be calculated due to highest Ni dose measured without resulting in 50%inhibition.

a

Signi?cant hormesis of barley root elongation in leached Langfang soil.

n

Signi?cant difference between unleached and leached EC10(EC20or EC50)using T -test at p r 0.05signi?cance level.

B.Li et al./Ecotoxicology and Environmental Safety 74(2011)459–466

461

the ratio of leached toxicity thresholds (effect concentrations:EC10,EC20,and EC50)to corresponding unleached toxicity threshold effect concentrations.The LF varied from 0.42to 44.13(average 42.39)for EC10and from 0.72to 49.29(average 42.42)for EC20.For the 11soils where root elongation was inhibited suf?ciently to determine the EC50values (Table 2),LF values ranged from 0.96to 2.23(average 1.35).For soils having a pH of 48.2(i.e.,Yangligh,Zhengzhou,Zhangye,Dezhou,Shijiazhuang,and Urumchi soils)(Fig.2G–L)leaching was found to dramatically decrease toxicity,

while for the two acidic soils (Haikou (pH 4.9)and Qiyang (pH 5.3))leaching had no signi?cant effect (Fig.2A and B).

3.3.Multiple linear regression models to predict Ni toxicity in soils Soil pH was the most important single factor in predicting Ni toxicity (Table 3).Incorporating soil eCEC into the regression models for unleached soils decreased the RMSE from 0.43to

02040608010012002040608010012010-210-210-210-110010110210310410-110010110210310410-11001011021031040

20

406080100120020406080100120105

B a r l e y r e l a t i v e r o o t l e n g t h (%)

Ni added (mg/kg)

Fig.2.Dose–response curves for the barley root elongation test in Chinese soils:(A–F)represent soils with pH values o 8.2and (G–L)represent soils with pH values Z 8.2.UL and L represented unleached and leached soils,respectively.Ni added represents added Ni concentrations (mg/kg)in soils and was determined by subtracting total Ni concentration in unspiked soils from those in spiked soils.

B.Li et al./Ecotoxicology and Environmental Safety 74(2011)459–466

462

0.29for EC10,from0.35to0.24for EC20,and from0.25to0.17for EC50values among soils(Table3).Incorporating OC content into regression models for unleached soils gave a signi?cant but slightly smaller improvement in predictability for EC10and EC20endpoints,and a similar improvement in predictability for EC50compared with incorporating eCEC.For leached soils, including eCEC in regression models with soil pH offered no additional improvement for predicting EC10and EC20values. However,pH and eCEC explained82%of the variance of EC50 values.Including OC content in the regression models for leached soils improved all models,by decreasing the RMSE from0.39to 0.32for EC10,from0.28to0.21for EC20,and from0.29to0.21for EC50values(Table3).However,developing toxicity models for all leached soils was compromised as EC50values could not be determined(due to lack of toxicity)for several high pH soils (Eqs.15and16,Table3).The predicted EC50values based on soil pH and eCEC for unleached soils were found to mostly lie within a 2.5-fold range of the measured values.Factors such as clay content, CaCO3content,and Fe oxide concentrations did not offer any signi?cant improvement to model accuracy and were therefore excluded from the regression equations.

4.Discussion

4.1.The effect of soil factors on Ni toxicity

Soil pH was found to be the most important single factor in predicting Ni toxicity to barley root elongation,explaining approx-imate70%of the variance in EC50values for unleached and leached soils.Incorporation of soil eCEC or OC content signi?cantly improved the pH-based models further and explained82–86%of the variance in EC50values.Rooney et al.(2007)developed models of Ni phytoxicity in European soils(pH3.3–8.7)and also found soil pH,eCEC,clay content,and OC content to be important soil factors for explaining the variance in toxicity thresholds.In the same set of soils,Oorts et al.(2006a)also reported soil eCEC was the most important factor in predicting toxicity for potential nitri?cation rate(PNR),glucose-induced respiration(GIR),and maize residue mineralization(MRM).Although soil eCEC was found to be the best predictor of Ni ecotoxicity for the European soils used by Rooney et al.(2007),it was not the most important predictor of Ni phytotoxicity for the Chinese soils used in the present study, explaining only17%and13%of the variance in unleached and leached EC50values,respectively(Table3).This difference may be explained by the different relationship between eCEC and other soil properties in these two studies because the variation of eCEC in the European soils(Rooney et al.,2007)was mainly explained by differences in soil clay content,OC content,and soil pH(r2?0.93); moreover,the variation of eCEC in Chinese soils was related only weakly to soil OC content(r2?0.46)and was not related to clay content as clay mineralogy in Chinese soils varies between kaolinite,illite,and montmorillonite(Xiong and Li,1987).

It has been widely recognized that soil pH is the most important soil factor controlling Ni toxicity and partitioning in soils(Wallace et al.,1977;Gerritse and van Driel,1984;McBride,1989;Weng et al.,2003,2004;Echevarria et al.,2006;Everhart et al.,2006; Oorts et al.,2007).Weng et al.(2003,2004)showed that EC50 values for oat growth increased from42.2to1321mg Ni/kg soil in 13soils with the increase in soil pH from4.0to7.0,and free Ni2+ concentration in soil solution was in?uenced by both the binding of Ni added to the soil solid phase and the pH.Oorts et al.(2007)found that EC50values based on free Ni2+activity were closely correlated with soil solution pH for PNR,GIR,and MRM(r2Z0.73).Everhart et al.(2006)also reported that Ni toxicity to oats was reduced as soil pH increased due to transformation of soluble Ni into non-labile fractions in soils.Soil pH has also been found to be the most signi?cant factor affecting Ni binding in soils,accounting for58%of the variability in the logarithm of the Ni partitioning coef?cient across a wide range of soils(Sauve′et al.,2000).Ponizovsky et al. (2008)also reported that Ni concentrations in an acidic soil solution were over40times higher than those in a calcareous soil spiked to the same total Ni concentration(600mg/kg).These ?ndings further indicate that soil pH plays a crucial role in Ni partitioning in soil,and partitioning is a key property controlling Ni phytotoxicity in soil ecosystems.However,the soluble Ni in calcareous soils might be controlled by dissolution of surface precipitates either on the surface of soil carbonates(i.e.,NiCO3 or NiCO3á2Ni(OH)2)or on the surface of clay minerals.Adsorption and precipitation of Ni in alkaline soils are different from those in

Table3

Simple and multiple linear regressions between Ni toxicity thresholds based on added Ni concentrations(Ni added)(mg/kg)and soil properties.

Regression equations r2p RMSE

Unleached soil(n?17)

1Log EC10?0.344+0.281pH0.390.0080.43

2Log EC10?à0.547+0.376pH+1.291log OC0.68o0.0010.0030.31

3Log EC10?à1.679+0.341pH+1.418log eCEC0.72o0.0010.0010.29

4Log EC20?0.422+0.290pH0.490.0020.35

5Log EC20?à0.342+0.371pH+1.117log OC0.76o0.0010.0020.25

6Log EC20?à1.284+0.341pH+1.201log eCEC0.78o0.0010.0010.24

7Log EC50?0.555+0.306pH0.68o0.0010.25

8Log EC50?à0.632+0.341pH+0.836log eCEC0.85o0.0010.0010.17

9Log EC50?à0.008+0.366pH+0.824log OC0.86o0.0010.0010.17

Leached soil

10Log EC10?à0.172+0.381pH(n?17)0.58o0.0010.39

11Log EC10?à0.858+0.454pH+1.000log OC(n?17)0.72o0.0010.0190.32

12Log EC20?à0.385+0.434pH(n?14)0.78o0.0010.28

13Log EC20?à0.920+0.492pH+0.730log OC(n?14)0.88o0.0010.0150.21

14Log EC50?à0.063+0.419pH(n?11)0.690.0010.29

15Log EC50?à0.758+0.385pH+0.789log eCEC(n?11)0.820.0010.0430.22

16Log EC50?à0.251+0.418pH+0.845log OC(n?11)0.84o0.0010.0240.21

pH?soil pH,OC?soil organic carbon content,eCEC?effective cation exchange capacity;r2?coef?cient of determination(percentage of variance accounted for by the regression model);p?signi?cance level of independent variables(pH,log OC,or log eCEC),Root mean squared error(RMSE)represents the distribution of the residuals of the observed and predicted logarithm EC values.

B.Li et al./Ecotoxicology and Environmental Safety74(2011)459–466463

acidic soils;precipitation of Ni hydroxides may explain the strong Ni partitioning to soils with high pH in our study,which resulted in decreasing Ni phytotoxicity with the increase in soil pH.

4.2.In?uence of soil leaching on Ni toxicity

In general,leaching increased EC10,EC20,and EC50values by factors of 42.39,42.42,and 41.33,respectively (Table 2).The most dramatic decrease in Ni toxicity to barley root elongation induced by leaching occurred in the soils with pH values Z 8.2(Fig.2G–L).Oorts et al.(2007)also showed Ni toxicity to PNR and MRM was decreased by leaching to a greater extent in an alkaline soil (pH 7.6)than that in acidic and neutral soils (pH 4.5–6.1),which is consistent with results in the present study.High-pH soils have much higher Ni partitioning coef?cients,so that there was a relationship between ECx values and soil pH.Hence,high-pH soils must be spiked to higher total Ni concentrations to induce toxicity,and this increased the difference in ionic strength of soil solutions between leached and unleached treatments (Stevens et al.,2003).Ionic strength plays an important role in partitioning of cationic metals in soils (Garcia-Miragaya and Page,1976;Mattigod et al.,1979;Barrow and Ellis,1986;Zhu and Alva,1993)through several possible reactions.High ionic strength

reduces free metal ion activity in solution (Zhu and Alva,1993),hence reducing partitioning to the solid phase.High ionic strength also means that concentrations of other cations (e.g.,Ca,Mg,and Na)in soil solution are high (displaced by the added metal cation),thus competing with metal cations for sorption sites and hence reducing partitioning of the added metal (Garcia-Miragaya and Page,1976,1977;Mattigod et al.,1979).High ionic strength also reduces the electrostatic potential of charged soil surfaces (above the zero point of salt effect)thus reducing cationic metal binding (Barrow and Ellis,1986).In this study,effects of high ionic strength and competing cations (e.g.,Ca,Mg,and Na)on Ni partitioning are the most likely reasons of reduced Ni partitioning in unleached treatments,and these effects would be more marked in high pH soils where higher Ni doses were needed to observe phytotoxicity.The EC of soil solutions in leached soils were generally lower than those in unleached soils (Fig.3A),and Ni partitioning (expressed as K d values)in leached soils was generally higher (Fig.3B).As well as effects of high ionic strength on Ni partitioning,a further factor confounding ecotoxicity in unleached metal-spiked soils is the effect of osmotic stress on the organism (Stevens et al.,2003).In our soils,EC of the soil solution was very high in unleached pots at higher Ni doses.However,barley is relatively tolerant to salinity (Maas and Hoffman,1977;Belkhodja et al.,1994);the EC of soil solution in the treatments

0510152025300

01

2

3

4

Electrical conductivity (UL) (mS/cm)

E l e c t r i c a l c o n d u c t i v i t y (L ) (m S /c m )

Log K d (UL) (L/kg)

L o g K d (L ) (L /k g )

51015202530

1

2

3

4

Fig.3.Relationship between (A)electrical conductivities of soil solutions in leached and unleached treatments and (B)relationship between log K d values for Ni partitioning in leached and unleached treatments.UL and L represent unleached and leached soils,respectively.

y b = 0.9571

23

45

1Measured log EC50

P r e d i c t e d l o g E C 50

r 2 = 0.04

y = 0.9131

2

3

4

5

Measured log EC50

P r e d i c t e d l o g E C 50

2345

123

45

Fig.4.The measured EC50values for barley root elongation in unleached soils versus the predicted EC50values:(A)from Eq.9in the present study and (B)from the regression model based on European soils (log EC50?1.60+0.89log eCEC)from Rooney et al.(2007).y a represents the predicted thresholds for unleached Chinese soils in this paper and y b represents the predicted thresholds for European soils.

B.Li et al./Ecotoxicology and Environmental Safety 74(2011)459–466

464

exhibiting50%of inhibition in root length by Ni was lower than the critical EC which causes osmotic stress to barley(around15mS/cm). Hence,effects of osmotic stress did not confound Ni phytotoxicity.

https://www.sodocs.net/doc/729517887.html,parison of Ni phytotoxicity models

The multiple regression models developed for selected Chinese soils were compared to those published previously by Rooney et al. (2007)based on selected European soils(Fig.4).As Rooney et al. (2007)assessed toxicity without pre-leaching of the soils,we compared the relevant model for unleached soils from this study (Eq.9).When regression models for Chinese soils(Eq.9in Table3) and some of the European soils(log EC50?1.60+0.89log eCEC, r2?0.91)were compared,it was found that the model using soil pH and eCEC developed in the present study was not a good predictor of Ni phytotoxicity in the European soils studied by Rooney et al. (2007)(r2?0.55,Fig.4A).Furthermore,the eCEC model developed by Rooney et al.(2007)for European soils was unable to predict Ni phytotoxicity in Chinese soils(r2?0.04,Fig.4B).A comparison of the soil properties of the Chinese in this study and the European soils used by Rooney et al.(2007)showed that OC contents in two of the European soils(Rhydtalog and Zegveld,12.9%and23.3%OC, respectively)were much higher than those in our Chinese soils. When these two soils were excluded from regression models,the regression model for Chinese soils(Eq.9)was more successful in predicting toxicity,but still did not predict toxicity well(r2?0.52). Another difference in the soil properties between the European study and ours was the inclusion of more alkaline soils in our experiments—7out of17soils had pH values48.0,while there were no highly alkaline soils in the European study(pH3.6–7.7). Given the prevalence of highly alkaline soils in the northern and western provinces of China,inclusion of highly alkaline soils in the regression model data set was important for setting regionally relevant soil quality criteria.Furthermore,the large effect of leaching on decreasing toxicity thresholds in alkaline soils indi-cated that it is important to include regionally relevant soils in any toxicity model development.

5.Conclusions

Phytotoxicity of Ni to barley root elongation in Chinese varied widely with a Z52-fold difference among soils,indicating that soil properties strongly in?uenced Ni phytotoxicity.Pre-leaching of soils prior to toxicity assessment signi?cantly reduced Ni phytotoxicity, especially in alkaline soils,and con?rms that metal-spiking protocols need to consider salt-induced artifacts in metal chemistry that can affect toxicity assessment.Multiple linear regression analysis showed that soil pH was the most important factor controlling Ni toxicity in Chinese soils.There was poor compatibility of models developed from European and Chinese soils,mainly due to the differences in the ranges of soil properties used to develop the models(higher organic matter contents in some European soils studied by Rooney et al. (2007),and higher pH in Chinese soils in the present study).This indicates the importance of model validation prior to extrapolation to regions with different soil properties.These empirical models to predict the soil-speci?c ecotoxicity thresholds using easily measured soil properties have the potential to signi?cantly improve risk assessments for Ni in soils.

Acknowledgment

The authors thank the?nancial support by the Natural Science Foundation of China(Project nos.20677077and40620120436), the International Copper Association,Rio Tinto Pty Ltd.,and the Nickel Producers Environmental Research Association.The authors also thank the national long-term soil experimental stations in China for soil collection,and Gillian Cozens and Cathy Fiebiger for technical assistance.

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操作系统文件管理_答案

第六部分文件管理 1、文件系统的主要目的就是( )。 A、实现对文件的按名存取 B、实现虚拟存储 C、提供外存的读写速度 D、用于存储系统文件 2、文件系统就是指( )。 A、文件的集合 B、文件的目录集合 C、实现文件管理的一组软件 D、文件、管理文件的软件及数据结构的总体 3、文件管理实际上就是管理( )。 A、主存空间 B、辅助存储空间 C、逻辑地址空间 D、物理地址空间 4、下列文件的物理结构中,不利于文件长度动态增长的文件物理结构就是( )。 A、顺序文件 B、链接文件 C、索引文件 D、系统文件 5、下列描述不就是文件系统功能的就是( )。 A、建立文件目录 B、提供一组文件操作 C、实现对磁盘的驱动调度 D、实现从逻辑文件到物理文件间的转换 6、文件系统在创建一个文件时,为它建立一个( )。 A、文件目录 B、目录文件 C、逻辑结构 D、逻辑空间 7、索引式(随机)文件组织的一个主要优点就是( )。 A、不需要链接指针 B、能实现物理块的动态分配 C、回收实现比较简单 D、用户存取方便 8、面向用户的文件组织机构属于( )。 A、虚拟结构 B、实际结构 C、逻辑结构 D、物理结构 9、按文件用途来分,编译程序就是( )。 A、用户文件 B、档案文件 C、系统文件 D、库文件 10、将信息加工形成具有保留价值的文件就是( )。 A、库文件 B、档案文件 C、系统文件 D、临时文件 11、文件目录的主要作用就是( )。 A、按名存取 B、提高速度 C、节省空间 D、提高外存利用率 12、如果文件系统中有两个文件重名,不应采用( )。 A、一级目录结构 B、树型目录结构 C、二级目录结构 D、A与C 13、文件系统采用树型目录结构后,对于不同用户的文件,其文件名( )。 A、应该相同 B、应该不同 C、可以不同,也可以相同 D、受系统约束 14、文件系统采用二级文件目录可以( )。 A、缩短访问存储器的时间 B、实现文件共享 C、节省内存空间 D、解决不同用户间的文件命名冲突

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精品文档 一.背景描述: 江南海岸总体规划和设计均体现了传统中国居家理想和现代生 活方式的有机融合,是依照21世纪人居标准精心打造的高级住宅小区。 整个小区无不营造一个舒适休闲的生活空间,是一所环境优雅,闹中 取静的花园式住宅小区,满足住户对高品质生活的追求。 二.工程说明: 江南海岸位于三明市列东区,由14栋高层住宅小区组成,总建 筑面积29.7627万平方米,其中包括4栋27层,6栋25层,4栋29 层,会所1间,负一层,一层。住户总数为1182户。 项目要求: 江南海岸,是集住宅、花园、会所于一体的高级住宅小区。小区智能化系统的工程建设具有投资大、工程复杂、专业性强等特点。小区要求建设成具有国内先进水平的,既具有自身特点,又具有时代潮流特色的高尚住宅楼宇。 整个工程规划、设计、实施上要求充分体现技术的先进性、系统的复杂性、严密的安防集控管理。注重整体功能强大,中心设备完善,系统配置科学合 理,真正体现高技术、高标准、高水平的现代化智能小区。 四.需求分析: 4.1分析与评估:

本方案以江南海岸小区住宅智能化管理及安全防范为设计目标为将力求建设成为高水平、高质量、高标准的信息化智能小区。我方提出以下见解,请发包方领导参考。 ①小区建设要求基于系统可靠、稳定、先进的基础上,既能满足用户住宅 的实际需求,同时又力求经济、实用、合理。 ②整个系统的结构要求清晰合理,小区实现全封闭管理,各个子系统既 相互关联又相对独立,形成一个全方位智能安防管理系统。 ③要求考虑未来系统扩展的需求,为小区以后系统功能的增加、升级,提 供良好的环境空间。 因此,考虑江南海岸属于大型的综合住宅小区,建筑规模庞大、结构复杂,小区各项功能模块齐备,因此在智能化建设方面,产品的集成度、统一化、高效管理方面尤为重要,同时,还必须考虑小区规模的不断扩大,智能化产品必须具备高度的扩展及冗余,顺应小区的发展。 我方进行多项分析与评估,结合小区建筑结构的分布特点、规模发展,以及对小区各功能模块的深层了解,建议江南海岸智能化系统工

linux下各目录作用和功能

/bin:是binary的缩写,这个目录是对Unix系统习惯的沿袭,存放着使用者最经常使用的命令。如:ls,cp,cat等。 /boot:这里存放的是启动Linux时使用的一些核心文档。 /dev:是device的缩写.这个目录下是任何Linux的外部设备,其功能类似Dos下的.sys 和Win下的.vxd。在Linux中设备和文档是用同种方法访问的。例如:/dev/hda代表第一个物理IDE硬盘。 /etc:这个目录用来存放任何的系统管理所需要的配置文档和子目录。 /home:用户主目录,比如说有个用户叫sina,那他的主目录就是/home/sina,说到这里打个岔.您现在应该明白,在我们访问一些个人网页。如:https://www.sodocs.net/doc/729517887.html,/sina的时候,sina就是表示访问 https://www.sodocs.net/doc/729517887.html, 站点中的用户sina的用户主目录.假如这个网站的操作系统是Linux,那就是表示/home/sina。 /lib:这个目录里存放着系统最基本的动态链接共享库,其作用类似于Windows里的.dll文档。几乎任何的应用程式都需要用到这些共享库。 /lost+found:这个目录平时是空的,当系统不正常关机后,这里就成了一些无家可归的文档的避难所。对了,有点类似于Dos下的.chk文档。 /mnt:这个目录是空的,系统提供这个目录是让用户临时挂载别的文档系统。 /proc:这个目录是个虚拟的目录,他是系统内存的映射,我们能够通过直接访问这个目录来获取系统信息。也就是说,这个目录的内容不在硬盘上而是在内存里啊。 /root:系统管理员,也叫终极权限者的用户主目录。当然系统的拥有者,总要有些特权啊。/sbin:s就是Super User的意思,也就是说这里存放的是一些系统管理员使用的系统管理程式。 /tmp:这个目录不用说,一定是用来存放一些临时文档的地方了。 /usr:这是个最庞大的目录,我们要用到的很多应用程式和文档几乎都存放在这个目录了。具体来说: /usr/X11R6:存放X-Windows的目录。 /usr/bin:存放着许多应用程式. /usr/sbin:给终极用户使用的一些管理程式就放在这. /usr/doc:这就是Linux文档的大本营. /usr/include:Linux下研发和编译应用程式需要的头文档在这里找. /usr/lib:存放一些常用的动态链接共享库和静态档案库. /usr/local:这是提供给一般用户的/usr目录,在这安装软件最适合. /usr/man:是帮助文档目录. /usr/src:Linux开放的源代码,就存在这个目录,爱好者们别放过哦! /var:这个目录中存放着那些不断在扩充着的东西,为了保持/usr的相对稳定,那些经常被修改的目录能够放在这个目录下,实际上许多系统管理员都是这样干的.顺便说一下,系统的日志文档就在/var/log目录中. /usr/local/bin 本地增加的命令 /usr/local/lib 本地增加的库根文件系统 通常情况下,根文件系统所占空间一般应该比较小,因为其中的绝大部分文件都不需要, 经常改动,而且包括严格的文件和一个小的不经常改变的文件系统不容易损坏。 除了可能的一个叫/ v m l i n u z标准的系统引导映像之外,根目录一般不含任何文件。所有其他文件在根文件系统的子目录中。

告诉你C盘里面每个文件夹是什么作用

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文档正文之前,并将光标定位到该插入点。具体操作步骤如下: 1、 选择?插入(I)?菜单中的〖分隔 符(B)〗命令后,屏幕上显示“分隔符” 对话框,右图所示,点击〖分页符〗中 的“下一页”选项,然后再单击?确定? 按钮。(主要功能是将目录与正文的页 码断开,即确保目录和正文的页码都分 别从“1”开始。) 2、 将光标 定位在分节符 前,选择?插入 (I)?菜单中的〖索 引和目录(D)…〗 命令后,屏幕上 显示“索引和目 录”对话框,如右 上图所示。 3、 激活〖目录(C)〗选项后,在〖格式(T)〗选项下选择合适的目录格式,并在对话框中部查看其预览效果。 4、 在〖显示级别(L)〗选项下输入不同数字以改变目录中包含的标题样式级别数目。 5、 单击?确定?按钮,就会将 目录添加到文档中。右图所示的是用 Word 自动生成的《科研成果简介)》 目录。 二、目录的更新 当对文档的标题作了修改之后, 自然需要对新文档的目录进行更新。如果用手工更新目录的话,就要

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Windows下各个文件夹的作用分别是什么

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│├—srchasst(搜索助手文件夹,用来存放系统搜索助手文件,与msagent文件夹类似) │├—repair(系统修复文件夹,用来存放修复系统时所需的配置文件) │├—Downloaded Program Files(下载程序文件夹,用来存放扩展IE功能的ActiveX等插件) │├—inf(用来存放INF文件。INF文件最常见的应用是为硬件设备提供驱动程序服务,不建议删除其中文件) │├—Help(Windows帮助文件) │├—Config(系统配置文件夹,用来存放系统的一些临时配置的文件) │├—msagent(微软助手文件夹,存放动态的卡通形象,协助你更好地使用系统。若觉的没有必要,可直接删除) │├—Cursors(鼠标指针文件夹) │├—Media(声音文件夹,开关机等wav文件存放于此) │├—Mui(多语言包文件夹,用来存放多国语言文件。简体中文系统中这个文件夹默认是空的,但不建议删除此文件夹) │├—java(存放java运行的组件及其程序文件。不建议删除其中文件) │├—Web ││├—Wall*****(存放桌面壁纸的文件夹) ││ │├—addins(系统附加文件夹,用来存放系统附加功能的文件) │├—Connection Wizard(连接向导文件夹,用来存放“Internet连接向导”的相关文件) │├—Driver Cache(驱动缓存文件夹,用来存放系统已知硬件的驱动文件) ││└—i386(Windows操作系统自带的已知硬件驱动文件,可删除以节省空间)

计算机中各种文件的作用说明

----------给你一个WINDOWS 文件夹内容的介绍,看了你就明白了. ├—WINDOWS │ ├—system32(存放Windows的系统文件和硬件驱动程序) │ │ ├—config(用户配置信息和密码信息) │ │ │ └—systemprofile(系统配置信息,用于恢复系统) │ │ ├—drivers(用来存放硬件驱动文件,不建议删除) │ │ ├—spool(用来存放系统打印文件。包括打印的色彩、打印预存等) │ │ ├—wbem(存放WMI测试程序,用于查看和更改公共信息模型类、实例和方法等。请勿删除) │ │ ├—IME(用来存放系统输入法文件,类似WINDOWS下的IME文件夹) │ │ ├—CatRoot(计算机启动测试信息目录,包括了计算机启动时检测的硬软件信息) │ │ ├—Com(用来存放组件服务文件) │ │ ├—ReinstallBackups(电脑中硬件的驱动程序备份) │ │ ├—DllCache(用来存放系统缓存文件。当系统文件被替换时,文件保护机制会复制这个文件夹下的文件去覆盖非系统文件) │ │ ├—GroupPolicy(组策略文件夹) │ │ │ ├—system(系统文件夹,用来存放系统虚拟设备文件) │ ├—$NtUninstall$(每给系统打一个补丁,系统就会自动创建这样的一个目录,可删除) │ ├—security(系统安全文件夹,用来存放系统重要的数据文件) │ ├—srchasst(搜索助手文件夹,用来存放系统搜索助手文件,与msagent文件夹类似) │ ├—repair(系统修复文件夹,用来存放修复系统时所需的配置文件)

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linux文件目录作用

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