a r X i v :a s t r o -p h /0009063v 1 5 S e p 2000
A&A manuscript no.
(will be inserted by hand later)
ASTRONOMY
AND
ASTROPHY SICS
Key words:
galaxies:clusters:general —cosmology:observations —cosmology:large scale structure of universe 1.Introduction
Over the last 25years,there has been signi?cant e?ort in understanding the morphological evolution of galaxies and the dynamical evolution of the clusters of galaxies.The early work in this area proved very fruitful.It provided strong evidence for galaxy morphological segregation in
2times
lower than the blue galaxies (assumed to be later type galaxies).
We have also initiated a new study,the CFH Opti-cal PDCS (COP)survey,described in detail in Adami et al.(2000a)and Holden et al.(2000).The COP sur-vey contains approximately 650galaxy redshift measure-ments (from 6nights of CFHT time)towards more than 10PDCS clusters at a mean redshift of 0.4.We have also ob-tained R–band photometry at the CFHT for these targets.We have combined our R-band data with the published PDCS photometry in V and I.This combined data set is allowing us to study the dynamical and morphological status of optically selected distant clusters of galaxies.We
2Dynamical and content evolution of a sample of clusters from z～0to z～0.5
Table1.Description of the PDCS clusters sample.The corrected velocity dispersions are computed with a decreasing correction of15%for the PDCS clusters.
los mean z vel.disp.corrected vel.disp.sampling center(J2000)
can then directly compare with the ENACS(ESO Nearby Abell Cluster survey:e.g.Katgert et al.1996)and CNOC samples(Carlberg et al.1997).Due to the relatively low number of galaxies,the statistics of an individual cluster are too low to compare individually to nearby clusters. Therefore,we combined the data from all the clusters in our COP study(at z～0.4)whose velocity dispersions were greater than500km.s?1into one composite cluster.We also applied the same technique to the available CNOC data from which we built two composite clusters,one at z～0.32and one at z～0.48.Our results and conclusions, then,are based upon the comparison of the composite clusters constructed in the same way from the ENACS, COP and CNOC surveys.
In Section2,we summarize the data and describe the methods used in analyzing them.We then discuss evolu-tionary e?ects,since our clusters extent over a relatively large redshift range and have been all analyzed in the same manner.In Section3,we describe our measurements of galaxy segregation.In Section4we discuss the galaxy evolution in our cluster sample as a function of redshift and the implications that our data pose on the formation epoch of these clusters.We use q0=0andΛ=0.Distances are given in units of h=H0/100.
2.The data
In this paper we use the COP data described in Adami et al.(2000a)and Holden et al.(2000)as well as the ENACS and CNOC data.The COP survey is an imag-ing and spectroscopic follow-up of10PDCS(Postman et al.1996)lines–of–sight which contain15PDCS cluster candidates at z?0.4(Adami et al.2000a and Holden et al.2000).Here,we compare the dynamical characteris-tics of the galaxies belonging to those PDCS clusters to their ENACS(Adami et al1998)and CNOC counterparts. The low redshift data are based on a compilation from the ENACS database(Katgert et al.1996,Mazure et al.1996) and the literature(Adami et al.1998).All the galaxies in the nearby sample have a redshift and a magnitude that were derived in the same manner as the current data.They have also been classi?ed into morphological types,but no color data comparable to our COP data are available.
We also use5CNOC clusters available in the litera-ture(MS0016+16,MS0302+16,MS1008-12,MS1224+20 and MS0451-03).MS1358+62and MS1621+26were ex-cluded from the sample because of their distorded appar-ent shape.The CNOC galaxies have r and g magnitudes and are classi?ed into spectral types according to their color and spectral distribution(Yee et al.1996).We com-pute an absolute magnitude according to the redshift and the spectral type of each galaxy using the k-corrections given in Frei&Gunn(1994)(see below for the de?nition of the CNOC spectral types).
2.1.Velocity dispersions and de?nition of the PDCS
sample
We used the most massive(≥1014M )clusters in the PDCS sample in our comparison with the ENACS and CNOC surveys in order to match the same class of clus-ters.We compute the velocity dispersions of the massive systems detected in the COP survey(Adami et al.2000a) using the bi–weight robust estimators of Beers et al.(1990) and applying a“3-σclipping”.This is exactly the same methodology used by Adami et al.(1998)for the ENACS systems and this ensure us to have robust estimators de-spite the relatively low numbers of galaxies used.
Our?nal velocity dispersion measurements are within 5%of those presented in Holden et al.(2000)for all the clusters in common except PDCS30/45.This last group has a complicated structure in redshift space which prob-ably produced deviations from Holden et al.in the ve-locity dispersion determination.However,if we excluded that cluster from our sample,the results described in the following sections do not change by more than5%.We de-cided,therefore,to not exclude those galaxies when build-ing our composite cluster(see next section).
Due to the small number of redshifts per cluster in our sample(～10),we were unable to distinguish between inter-loper galaxies–those which are passing-through the cluster but are not physically bound to the cluster–and real cluster members.Katgert et al.(1996)showed that not excluding inter-lopers results in an increase of the ve-locity dispersion of the clusters by between10%and25%.
3
To account for this e?ect in our sample,we have,there-fore,systematically decreased our measured velocity dis-persions by15%.
For this paper,we selected only the clusters with a red-shift greater than0.25,a velocity dispersion greater than 500km.s?1and with more than7redshifts(see Table1). In total,we have6clusters at a mean redshift of0.4and 74cluster galaxies with measured redshift and V P DCS and I P DCS magnitudes(56have also measured R magni-tude).Only one of the clusters in our sample has fewer than9redshifts.This is not a problem because the ve-locity dispersion can be reliably estimated using bi-weight estimators with9or more redshifts(see Lax1985).
2.2.The CNOC sample
We analyzed the CNOC clusters in the same way as the PDCS and ENACS clusters.First of all,we de?ned groups along the lines of sight by using the same gap technique as in Adami et al.(1998)or Adami et al.(2000a).This technique searches for gaps of more than1000km.s?1in the distribution of the galaxies ordered by increasing red-shift.The choice of1000km.s?1is well adapted to the data we have(see also Katgert et al.1996).We checked, however,that values between600and1500km.s?1do not signi?cantly change the results.When more than5galax-ies were between two velocity gaps,we assumed that this was a structure.With this technique we detected all the groups de?ned in Carlberg et al.(1997)with very sim-ilar mean redshifts(see Table2)plus several small and probably di?use groups not listed by Carlberg et al.
In order to use a uniform set of selection criteria,we chose only groups with a velocity dispersion larger than 500km.s?1.When the detected groups were found to be listed in Carlberg et al.(1997),we used the velocity dis-persion quoted in that paper.For groups not detected by Carlberg et al,we computed the velocity dispersion by the same method described in the previous section. We kept only groups with velocity dispersions larger than 500km.s?1.In total,only one structure was added to the 5main structures in the CNOC sample(Carlberg et al. 1997).This group,in the MS0016+16?eld,is at a red-shift of0.328and has a velocity dispersion of610km.s?1 (denoted MS0016+162in the following).Excluding this group did not change the results signi?cantly.
Finally,we only used the CNOC galaxies within a radius of1h?1Mpc from the center in order to match approximately the PDCS and ENACS criteria.For MS0016+162,we used the position of the brightest galaxy as the center.
The end result was6CNOC structures(see Table 2):three of them at z～0.32(MS0016+162,MS1008-12 and MS1224+20);the other three in the redshift inter-val[0.4;0.55](MS0016+16,MS0302+16and MS0451-03, mean redshift of z～0.48).We built as described in Section 2.3two CNOC composite clusters with these structures.Table2.Description of the CNOC cluster samples.We have used the Carlberg et al.(1997)velocity dispersions, except for MS0016+162.
los mean z vel.disp.sampling
The z～0.32composite cluster has107galaxies and the z～0.48composite cluster has118galaxies.These num-bers are similar to the number of galaxies in the COP composite cluster.
2.3.Velocity normalization
Following Adami et al.(1998),we built”composite clus-ters”made by combining the data from all the individ-ual systems.We compute galaxy velocities relative to the mean velocity and normalized to the velocity dispersion of each cluster.The normalized velocity of galaxy”i”in cluster”j”,v i
j
,is de?ned as
v i
j
=(v i-v j
mean
)/σj,
with v j
mean
being the mean velocity of cluster j,σj be-ing its velocity dispersion and v i the original velocity of galaxy“i”.We merged these normalized velocities into the composite clusters.
The uncertainties could be introduced by systematic errors on theσj;however,the use of robust estimators prevents us from severe biases in the estimation of theσj. We stress that this technique of using composite clusters has been already used successfully,for example in Adami et al.(1998).
We have also investigated possible bias due to velocity dispersion inhomogeneity between the3composite clus-ters.We are not very likely to have such selection ef-fects because at z～0.32,0.40and0.48,the mean veloc-ity dispersions of the individual clusters used to make the composite clusters are966km.s?1,1047km.s?1and1119 km.s?1and they are overlapping if we consider error bars.
2.4.Estimating the morphological type of the PDCS
cluster galaxies
Before we begin to discuss the morphological content of the PDCS clusters,we must?rst establish a common lan-guage by which we can compare our results to past and present work in the?eld e.g.the use of the early and late morphological types.
4Dynamical and content evolution of a sample of clusters from z～0to z～0.5
Table3.The average V-I,V-R and R-I Colors for the el-liptical,the Sbc,the Scd and the Im galaxies at4di?erent redshifts.These values are taken from Frei&Gunn(1994). We have compared our values to these ones to de?ne an approximate morphological type.
color(z)E Sbc Scd Im
Our imaging data did not have the resolution neces-sary to allow us to assign galaxies a morphological type. We could,nevertheless,classify our galaxies in terms of their spectral energy distribution using our photometry and spectroscopy.Our?rst classi?cation scheme separates galaxies into emission line and non-emission line objects. This classi?cation relates well to the early/late morpho-logical type classi?cation(e.g.Biviano et al.1997).How-ever,in some cases early type galaxies,like SOs,can ex-hibit emission lines features in their spectra.In any case, Biviano et al.(1997)have shown that less than4%of El-liptical or SO cluster galaxies have emission lines.This implies that our spectroscopically–determined”late type galaxies”(see Fig.4)are probably free from signi?cant contamination by early type objects.
In other cases,some late type galaxy spectra do not have strong emission lines,however.Moreover,we used blocking?lters to obtain the spectra of the COP galaxies (see Adami et al.2000a)which signi?cantly reduced the available spectral range.It is possible,therefore,that we missed emission line features due to this reduced spectral coverage.Our”early type galaxies”bin may,therefore,be contaminated by late type objects.
The other classi?cation scheme we used was based on the three-color information(V,R and I)we had for most of the galaxies in the sample(56out of74).Once the redshift was known,the spectral energy distribution was constrained and a rough classi?cation between di?erent spectral types was assigned.We used the Frei&Gunn (1994)colors to classify our galaxies into4spectral types. Table3gives the V?I,V?R and R?I colors from Frei& Gunn(1994)for the4di?erent morphological types we used and for the4redshifts of our composite clusters.
We matched the3colors of each object with this table.First,we transformed the V P DCS?I P DCS,
V P DCS?R COP and R COP?I P DCS into the standard Johnson system used in Frei&Gunn(1994).As in Post-man et al.(1996)and Adami et al(2000a)we applied the following relations for the color transformations:
V?I=0.41+0.855(V P DCS?I P DCS)+ 0.012(V P DCS?I P DCS)2,
V?R=?0.02+(V P DCS?R COP)?0.056(V P DCS?I P DCS)+ 0.012(V P DCS?I P DCS)2,and
R?I=0.43+(R COP?I P DCS)?0.089(V P DCS?I P DCS).
Each color will,in principle,correspond to a single color-type,but this did not always happen.We therefore developed a method of using the colors to uniquely de-termine the galaxy color-type.First,if all3independent color-type determinations derived by the colors did yield
the same result,we selected that color-type.This occurred
for24%of the sample.Second,if2color-types among the
3were identical,and if the third color-type was close to these two(for example,Im is close to Scd),we selected
the two identical color-types(50%of the sample).Third,
if2color-types among the3were identical,but if the third color-type was not close to these two ones(for example,
Im is not close to Sbc)we again selected the two identical color-types(5%of the sample).Fourth,if the3color-types were di?erent and close(for example,E,Sbc and Scd),we selected the mean color-type(14%of the sample).Finally,
if the3color-types were di?erent but not close(for exam-ple,E,Sbc and Im),we selected the color-type providing
the lowest di?erence with the values of Table3(7%of the sample).
We have assumed that the E bin of Frei&Gunn(1994) was a mix of elliptical and SO galaxies,the Sbc bin was a
mix of Sa,Sb and Sc galaxies,the Scd bin was a mix of Sd
and Sm galaxies and the Im bin contained only irregular galaxies.
This classi?cation technique is similar to the one used
in the CNOC survey(Carlberg et al.1997),except that we used three colors instead of two,and we assigned a mor-phological type(called color-type hereafter)using the Frei
&Gunn(1994)templates.The classi?cation estimates with the largest uncertainties are for the last two cases
and they constitute only21%of the sample.The main uncertainties in the color classi?cation scheme came from
the uncertainties in the magnitudes.Possible dust obscu-ration found,for example,in Cl0039+4713(z=0.41:Smail
et al.1999)can lead to misclassi?cations,but we ignored
this e?ect.
We also compare the predicted types of our two clas-
si?cation schemes.Overall,emission line galaxies should
be mostly late type galaxies and absorption line galaxies should be mostly early type galaxies.The direct compar-ison shows that,on one hand,100%of the emission line galaxies of our sample have a color-type later than Sbc (Sbc:33%,Scd:42%,Im:25%).On the other hand,14%
of the non-emission line galaxies have a color-type later
5
than Scd(e:50%,Sbc:36%,Scd:0%,Im:14%).These per-centages are well within our expectations(see above)and these results give strength to our classi?cation schemes.
However,we must consider this color classi?cation scheme(red galaxies:early types,blue galaxies:late types) only as an indication of the true morphological type.The spectral assignment is clearly not as reliable as the real morphological types obtained,for example,via HST ob-servations by Dressler et al.(1999)or Lubin et al.(1998). The morphology and the stellar content of a galaxy can be a?ected di?erently by various astrophysical processes and consequently the two tentative classi?cations by col-ors or spectral features described in this section must be considered only as an approximation of the morphological types.However,in order to compare our distant cluster with their local counterparts(ENACS)we needed to es-tablish such a relation between spectral and morphological classi?cations.
2.5.Morphological type of the CNOC cluster galaxies
In order to relate the CNOC composite clusters with the rest of our sample(signi?cantly increasing the number of galaxies),we decided to split the CNOC spectral classi?-cation into two bins that could be related to our previous classi?cation.Hereafter,we refer to these subsamples as early and late type CNOC galaxies
We assigned the CNOC spectral types1,2(elliptical galaxies)and3(E+A galaxies)to the early type class. These are mainly elliptical galaxies because the CNOC type3galaxies represent less than2.5%of the sample. The CNOC types4and5are assumed to be late type galaxies.In order to compare with the ENACS data,we associated this late type bin to the bin Sc+Sd+Sm+Irr of Adami et al.(1998).
3.Evolution of the magnitude and morphological
segregation
As shown in Adami et al.(1998),there exists both a magnitude and a morphological segregation of galaxies in nearby clusters that agrees with simple dynamical mod-els of cluster formation and evolution.The bright galaxies have a lower velocity dispersion compared to the fainter ones.This variation is expected from energy equipartition in clusters.The elliptical galaxies have a lower velocity dispersion compared to the later morphological types in nearby clusters.The ratio of these dispersions between the elliptical and the late type spiral galaxies is consistent with a model where the late type spirals are currently falling into the cluster.
3.1.Magnitude segregation
We now compare the results of Adami et al.(1998)for nearby clusters with the results from the3distant
com-Fig.1.Magnitude segregation of the z～0.32and z～0.07 cluster galaxies.The x-axis is the R magnitudes in unit of 2.5log10(h)+mag.,the y-axis is the normalized velocity dispersion.The open circles are the data at z?0.07from Adami et al.(1998)with their error bars(dotted lines). The?lled squares are the data at z?0.32with their error bars(solid lines).The thick solid line is the theoretical variation if we assume the energy equipartition.
posite clusters.We plot in Figures1,2and3the variation of the normalized velocity dispersions versus the absolute magnitude for the3distant composite clusters.We made4 bins of17distant galaxies for the PDCS composite cluster at z～0.4(Fig.2),5bins of17galaxies for the CNOC com-posite cluster at z～0.32(Fig.1)and6bins of17galaxies for the CNOC composite cluster at z～0.48(Fig.3).
We transformed the V P DCS magnitudes into R mag-nitudes(V P DCS?R?1)to over plot the results for the PDCS composite cluster on the results for the nearby clus-ters(which used R magnitudes).We have not modi?ed the values of the CNOC r magnitudes because according to Frei&Gunn(1994),the correction between R and r magnitudes is less than0.2magnitudes.This uncertainty is negligible compared,for example,to the uncertainty in the V P DCS?R value.
We have excluded galaxies whose velocities were≥3-σaway from the mean in each bin for the z～0.4and z～0.32composite clusters.The?gures show qualitatively the same results of Adami et al.(1998)superposed to each composite cluster.For the z～0.32and z～0.4composite clusters,the agreement is apparently good except for the faintest bin of the z～0.4composite cluster and the R～-21.5point of the z～0.32composite cluster(see the dis-cussion section for an explanation of this peculiar value). For the z～0.48composite cluster,the R～-22.3and R～-22 points seem to be higher than the corresponding z～0.07 points as well as the energy equipartition prediction(thick solid line).The energy equipartition law(e.g.Adami et al. 1998:σ=100.2M with M the magnitude)has been normal-
6Dynamical and content evolution of a sample of clusters from z ～0to z ～
0.5
Fig.2.Magnitude segregation of the z ～0.4and z ～0.07cluster galaxies.The x-axis is the R magnitudes in unit of 2.5log 10(h)+mag.,the y-axis is the normalized velocity dispersion.The open circles are the data at z ?0.07from Adami et al.(1998)with their error bars (dotted lines).The ?lled squares are the data at z ?0.4with their error bars (solid lines).The thick solid line is the theoretical variation if we assume the energy
equipartition.
Fig.3.Magnitude segregation of the z ～0.48and z ～0.07cluster galaxies.The x-axis is the R magnitudes in unit of 2.5log 10(h)+mag.,the y-axis is the normalized velocity dispersion.The open circles are the data at z ?0.07from Adami et al.(1998)with their error bars (dotted lines).The ?lled squares are the data at z ?0.48with their error bars (solid lines).The thick solid line is the theoretical variation if we assume the energy equipartition.
ized to R =?21.5(+5×log 10(h)).The agreement with the low redshift data and the energy equipartition for this last composite cluster seems to be worse compared to the other two composite clusters at z ～0.32and z ～0.4.How-ever,taking into account the error bars,the di?erences are
very signi?cant and we need to estimate quantitatively level of agreement.
In order to ?nd a way to quantify more e?ciently the di?erences between the z ～0.07results and the redshift distributions,we used a two dimensional test (e.g.Press et al.1992)in the velocity dispersion-R magnitude phase https://www.doczj.com/doc/c016095563.html,ed all the individual values of each galaxy (without in the magnitude interval R=[-23.;-19.5].Each test was run 1000times (bootstrap to estimate the signi?cance level.At the 10%we found no signi?cant di?erences between the nor-velocity dispersion versus R magnitude for the 0.07,z ～0.32and z ～0.4composite clusters.However,distribution of the z=0.48cluster was found to be sig-di?erent (even at 1%level)from the three lower redshift composite clusters.
The results show,therefore,a signi?cant evolution of the magnitude segregation in the most distant composite cluster,but none for the z ～0.07,z ～0.32and z ～0.4com-posite clusters.
3.2.Morphological segregation
this section,we also compared the variation of the velocity dispersion versus the spectral types .a ?rst step,we do not consider the spatial distribution the galaxies (see next Section).
The types 1,2,3and 4of Fig.4were respectively to the closest galaxy types:elliptical,SO,Sa+Sb Sc+Sd+Sm+Irr.We stress that the error bars are too to draw ?rm conclusions regarding the morphological shown in Fig.4.However,the variation of the values is still suggestive.We now comment on this.
For the z ～0.4galaxy sample,we used both the emis-line (large ?lled squares)and color (large empty classi?cations to assign morphological types.We the previously de?ned early and late spectral types the z ～0.32and z ～0.48CNOC samples.The results shown in Figure 4,together with the z ～0.07results empty circles)of Adami et al.(1998).To plot these results on the same ?gure,we assumed that the z ～0.4PDCS galaxies with:
–only absorption lines were an equal mix of elliptical and SO galaxies
–only emission lines were an equal mix of spiral and irregular galaxies
–a color-type equal to the E type of Frei &Gunn (1994)corresponded to type 1of Adami et al.(1998)
–a color-type equal to the Sbc type of Frei &Gunn (1994)corresponded to type 3of Adami et al.(1998)
–a color-type equal to the Scd +Im type of Frei &Gunn (1994)corresponded to type 4of Adami et al.(1998)
Further,we assumed that the CNOC galaxies which are classi?ed as early types were Elliptical galaxies and
7
Fig.4.Morphological segregation.The x-axis is the type (1:Ellipticals,2:SO,3:Sa+Sb,4:Sc+Sd+Sm+Irr),the y-axis is the normalized velocity dispersion.The linked crossed small circles are the data at z ?0.07from Adami et al.(1998)with their error bars.The ?lled diamonds are the CNOC data at z ?0.32with their error bars.The large ?lled circles are the CNOC data at z ?0.48with their error bars.The large squares (?lled:emission line/absorption line classi?cation,opened:color classi?ca-tion)are the PDCS data at z ?0.4with their error bars.We note that we have applied a small shift in x to the points at x=1,x=3and x=4in order to make the ?gure clearer.
that those classi?ed as late types were type 4of Adami et al.(1998)
The results were found to be qualitatively similar for the z ～0.07,z ～0.32and z ～0.4cluster galaxies.The trend shown is in agreement with the theoretical predictions.For example the ratio between the two z ～0.32bins is close to the
√2is still
observed.There seems to be a systematic shift towards higher values of the normalized velocity dispersions,how-ever.These distant clusters could be dynamically younger compared to the other not so distant clusters.3.3.Spatial distribution segregations
We now consider the spatial distribution of the galaxies with respect to their magnitude and spectral type.
We used a two dimensional Kolmogorov-Smirnov test based on the distance from the center versus normalized velocity dispersion phase space (d-σphase space hereafter)to investigate the segregation as a function of spectral type and magnitude.In the z ～0.32,z ～0.4and z ～0.48compos-
clusters,we showed that the distribution of the early is signi?cantly di?erent,at the 10%level,compared the late type galaxies.This agrees with the results of et al.(1998):early type galaxies in nearby clusters more concentrated at the cluster center than late type We also investigated the spatial distribution of the dif-spectral types as a function of magnitude using test (with 1000bootstrap resam-for each case).The results are given in Table 4.For z ～0.32cluster,we show that the distribution in the phase space of early type galaxies brighter than R ?-±0.25is signi?cantly di?erent at the 10%level com-to the distribution of late type galaxies.In the same there is no signi?cant di?erence between late type early type galaxies fainter than R ?-21.75±0.25.This means that only the bright early type galaxies are more concentrated at the center than the late type galaxies.Biviano et al.(2000)found a similar result in nearby clus-ters.For the z ～0.4cluster,we found the same trend if we used the emission line /absorption line classi?cation.This time,the segregation appears at magnitudes brighter than R ?-21.25±0.25.For the z ～0.48cluster,however,the seg-regation starts to be signi?cant at R ?-22.5±0.25,brighter than for the z ～0.32and z ～0.4clusters.Once again,the most distant composite cluster seems to be di?erent form the less distant composite clusters.Only the very bright early type galaxies show a more concentrated distribution than the late type galaxies.
3.4.X-ray selected versus optically selected clusters The COP clusters are optically ?selected while the CNOC clusters are X ?ray selected.We now consider whether these di?erent selection methods are responsible for the di?erences seen between the z ～0.48composite cluster (X-ray selected)and the other composite clusters at lower red-shift.For the magnitude and the spatial distribution segre-gations,these di?erent selection methods did not seem to play a signi?cant role because the z ～0.32(X-ray selected)composite cluster exhibits the same characteristics as the z ～0.07and z ～0.4composite clusters (optically selected)and it was selected in the same way as the z ～0.48compos-ite cluster.In the case of the morphological segregations,this e?ect is not statistically signi?cant.We,therefore,assume that our results do not depend on whether the clusters were X-ray or optically selected.4.Discussion
We stress that our conclusions are strictly valid only for the clusters of our sample.However,these clusters are a fair sample of the general massive cluster population,and the results presented here can probably be generalized to other clusters.
8Dynamical and content evolution of a sample of clusters from z～0to z～0.5
Table4.Kolmogorov-Smirnov tests regarding the spatial distribution segregation of the early type and late type galaxies and as a function of the R limiting magnitude.A value lower than0.90means that the compared samples are di?erent at the10%level.For a given z bin and a given limiting magnitude,the values in the table are the probabilities of the spatial distribution of the early type galaxies brighter than the limiting magnitude to be di?erent compared to the spatial distribution of all the late type galaxies.We give the values only when we have more than10early type galaxies.
z bin/R-22.75-22.5-22.25-22-21.75-21.5-21.25-21-20.75-20.5
4.1.How the clusters are evolving?
Based on our previous analyses we found no evidence for redshift evolution of the dynamical state in our cluster sample from z～0.07to z～0.4.We detected,however, signi?cant evolution between the z～0.4and z～0.48com-posite clusters using a Kolmogorov-Smirnov test.We also ?nd that the cluster galaxy content changes from z～0.07, z～0.32,z～0.4to z～0.48.In the nearby sample of cluster galaxies of Adami et al.(1998:z～0.07),
–the type”1”galaxies(ellipticals)are24%of the sam-ple,
–the type”2”(SO)are49%,
–the type”3”(Sa+Sb)are20%and
–the type”4”(Sc+Sd+Sm+Irr)are only7%.
In the sample at z～0.32,
–the early type galaxies are78%,
–the late type galaxies are22%(type”4”).
In the sample at z～0.4,
–the redder galaxies(assumed to be”1”+”2”:ellipti-cals+SO)are44%of the sample(versus24%+49%for the nearby sample),
–the intermediate color galaxies(assumed to be type ”3”)are38%and
–the bluer galaxies(type”4”)are18%.
And?nally,in the sample at z～0.48,
–the early type galaxies are70%,
–the late type galaxies are30%(type”4”).
The percentages of late type galaxies are higher in the distant cluster samples.The estimate of the uncertain-ties in these percentages is not straightforward but we assumed the Section2.4maximum contamination of21% (～3-σ)in assigning spectral types when using colors in the z～0.4sample.To be conservative,we applied this to the relative percentages of red,intermediate and blue galaxies of our sample.The uncertainties on the numbers given in this paragraph are,therefore,based on a7%uncertainty.
In other words,the distant cluster galaxies are statisti-cally bluer(or present later types)than the nearby cluster galaxies.This is the”classical”Butcher&Oemler(1984) e?ect that already has been extensively reported in the literature.At even higher redshifts,Van Dokkum et al.
(1999)found the same e?ect in the cluster MS1054-03at z～0.83.They showed clear evidences of further evolution
of late type galaxies into early types(SO and E).
In order to compare results free from possible bias in
our classi?cation for the z～0.4sample,we also compare the percentage of emission line galaxies in this sample
(19±3%)to the ENACS sample of nearby clusters(Bi-viano et al.1997:10±1%),without using any color clas-
si?cation.We see that the emission line galaxy fraction
increases by a factor of～2.In principle,our ability to measure redshifts for emission line galaxies is higher than
that for absorption line galaxies,but this e?ect is canceled
out by the short spectral ranges we used(see Adami et al. 2000a)which occasionally can lead to missed emission line
features.The region(r～1h?1Mpc)covered by the COP and ENACS surveys are similar(see Adami et al.2000a
and Adami et al.1998),which is important as we discuss
below.
The evolution in the galaxy content of the clusters in our sample between z～0and z～0.48seems to be real.It
does not depend on the sample used to test it,whether it
is selected according to their spectral features or to their colors.These results are consistent with the recent studies
of Dressler et al.(1999)of z～0.4clusters.They?nd evolution of the morphological types of cluster galaxies.
The metric aperture used,however,plays a key role
in determining the blue fraction:For example,the im-
plied evolution of the blue fraction with redshift was not con?rmed by Lubin et al.(1998)and Postman et al.
(1998).They showed that the massive cluster1604+4304 at z=0.84has a morphological content similar to that of
nearby clusters.But,these studies used images of the inner
core of the cluster(～2′×2′)which is signi?cantly smaller than the area sampled in Adami et al.(1998),our com-
parison study.If we assume that the percentage of late
type galaxies increases from the inner part to the outer parts of the clusters(e.g.Adami et al.1998),then this is an explanation of the discrepancy between our results and the results of Lubin et al.(1998)and Postman et al. (1998).In order to check this point,we have computed the
9
percentage of red,intermediate and blue galaxies in our z～0.4sample but in the same physical area as in Lubin et al.(1998):the core of the clusters.We found in this region,65%red galaxies,18%intermediate galaxies and 17%very blue galaxies.These percentages are in agree-ment with the work of Lubin et al.(1998).The choice of metric aperture is therefore important,and it could be an explanation for why the longer look–back time studies of Lubin and Postman did not yield evidence for evolution. It may be that at longer look back times(z～0.8)other e?ects could lead to a relatively low blue galaxy fraction (see section5).
The entire evolutionary process is complicated,how-ever,and it probably also relates to the dynamical state of the clusters as well as its redshift.For example,Wang et al.(1997)showed a correlation between cluster ellip-ticity and blue galaxy fraction,and Metevier et al.(2000) showed that there exist nearby clusters that have bi-modal galaxy or X-ray distributions which have relatively high blue fractions and are yet at low(～0.1)redshifts.
4.2.Morphological evolution versus dynamical evolution When we compared the dynamical and the cluster con-tent evolution of our composite clusters between z～0.4 and z～0.48,the situation is consistent:we both found ”younger”clusters and a”younger”population at higher redshift.However,the composite clusters from z～0.07to z～0.4give the following puzzle:How did the cluster con-tents evolve in morphological type,while the clusters have not apparently evolved in terms of their dynamical state? We now examine this point.
The answer is,it is possible to have the bright galaxies virialize before changing morphological type.This would explain why our composite nearby and distant clusters have the same distribution of galaxies versus magnitude, but they do not have the same ratio of late to early type galaxies.We can see this by assuming that galax-ies virialize via dynamical friction,which takes0.1Gyrs for the brightest galaxies for example in our z～0.4sam-ple and1to1.5Gyrs for the faintest galaxies(Sarazin, 1986).Yet,if galaxy-galaxy interactions cause the galax-ies to change morphological type,the galaxies take about 1Gyr to change(crossing time),and clearly the more mas-sive(brighter)galaxies can reach a“relaxed state”before changing morphological type.Without additional assump-tions,however,this scenario runs into a di?culty;namely, the time between z～0.07and z～0.4is about4Gyrs, and the nearby clusters should have virialized such that the dynamical state of the nearby and distant clusters should not be the same.
A way to deal with this is to assume that clusters are(not surprisingly)continually evolving(e.g.Ulmer et al1992and references therein).This scenario is clearly not new and has been investigated in details by authors such as Oemler(1974),Melnick&Sargent(1977),Dressler (1980)or Whitmore&Gilmore(1991).However,here,we have a unique case to check this scenario with homoge-neously analyzed clusters from z～0to z～0.5.Clusters are evolving being fed continuously by the in-fall of?eld galax-ies and groups(or other clusters).The majority of the in-falling?eld galaxies are late-type.The most recent episode of in-fall could have been such that the relative low mass late type galaxies in the outer regions have been able to evolve into early type galaxies(～1Gyr)while yet not virializing(～1.5Gyr).This leads to the nearby clusters having higher velocity dispersions in their outer portions while,at the same time,having relatively low fractions of late-type galaxies.
This hypothesis is consistent with?nding a correlation with dynamical age and blue fraction(Wang et al.1997). It is not completely clear how this hypothesis relates to ?nding nearby clusters which have bi-modal distributions and appear to have relatively large blue fraction(Metevier et al.2000).In a high matter density Universe,however, the cluster formation occurs at late epochs(close to the present time)and a high density Universe could then leads to the production of dynamically young structures until relatively recent epochs.
If we assume the general picture of cluster evolution and formation,we can extrapolate this scenario back in time to place a lower limit on when clusters formed and also suggest what clusters should look like in terms of morphology and dynamical state if we are able to extend studies to redshifts up to～0.8.This is discussed in the next subsection.
4.3.Cluster formation epoch?
An interesting question to ask is:when did all these clus-ters form?This epoch depends strongly of the cosmolog-ical model(e.g.Oukbir&Blanchard1992and1997).In a high?m Universe,the clusters form later than in a low ?m Universe,but they evolve faster.To adress this ques-tion,we can use the composite clusters of our sample from z～0.07to z～0.4.These are already,at least partially,re-laxed.We can then assume that the”formation”process has occurred at an epoch earlier than z～0.4.The clusters of the z～0.48sample have younger dynamical character-istics and we can assume that they are close to the end of their”?rst formation”process,which probably occured around z～0.5.Now we have to estimate the time needed to form such a cluster to estimate the epoch of the beginning of the formation process.
The surface covered by the clusters of our samples is a circle of about～1h?1Mpc radius.The minimal time to form such a cluster is then less than1Gyear in a vio-lent relaxation process(1crossing time,see Sarazin1986). Adding1Gyear to z～0.5gives the epoch of the begin-ning of the cluster formation,i.e.in a q0=0Universe～7.2 Gyears(not signi?cantly di?erent from when we use low values of q0but di?erent from0).We then conclude that
10Dynamical and content evolution of a sample of clusters from z～0to z～0.5
the cluster formation process for the clusters of our sample began at z≥0.8.
Consistent with this hypothesis are the recent detec-tions of clusters of galaxies at z～0.8(in addition to the two quoted in section4.1:MS1054-03and1604+4304).Nichol et al.(1999)and Ebeling et al.(1999)report the discov-ery of an X-ray luminous cluster(RXJ0152)at z=0.83, Gioia et al.(1999)has also discovered a young X-ray lu-minous cluster at z=0.81and Donahue et al.(1998)re-ported one at z=0.82.There is also the detection of an X-ray cluster(Rosati et al.1999)at z=1.26with a low X-ray luminosity.Nearly all these clusters at z≥0.8have a disturbed X-ray shape(elongated and clumpy)and their nature(partially relaxed clusters or proto-clusters)is not clear yet.The formation epoch of these massive clusters of galaxies,though,was probably only slightly greater than z=0.8,which is consistent with our estimates of the min-imum z of cluster formation.Selection e?ects may also have played a role in?nding only distorded clusters(cf. Adami et al.2000b),however,and the cluster formation may occur at even higher redshifts(cf.Rosati et al.1999) for(at least)the low mass clusters.
5.Summary and conclusions
We have produced di?erent composite clusters based on combining the results of6rich optically selected clusters with redshifts near0.4,and6X-ray selected clusters with redshifts near0.3and0.5.We compared these to a similar composite cluster at redshift0.07.We have shown that in terms of brightness,type and radius versus velocity dispersion,the z～0.07,～0.32and～0.4composite clusters are very similar(at least within the statistical limitations of the data)while the～0.48composite cluster is signi?cantly di?erent.We conclude from this work that the clusters of the sample have at least partially virialized by a redshift of0.5and that massive clusters(～1015solar masses)have formed at the very latest at z=0.8.Our derived lower limit to the time of cluster formation epoch is consistent with work on?nding massive clusters at z= 0.8or higher.
We have con?rmed that the more distant clusters of our sample contain more late-type galaxies that nearby clusters,as found many times before.At the same time, however,we have shown that the dynamical state of these clusters does not seem to evolve for the redshifts lower than0.4.In order to explain this,to the extent that there are some bright blue galaxies in the core of the clusters,we hypothesize that these massive blue galaxies have virial-ized before changing morphological classi?cation.This is not a large e?ect,however,as the cores of the clusters are mainly red(cf.Section4.1).We must,therefore,conclude (at the level of statistics we have here)that it is primarily the outer regions of the clusters that contribute the rel-atively large blue fractions of distant clusters.Although the nearby clusters should have virialized completely,the outer portions of these clusters are not virialized and yet are dominated by red galaxies.Continuous in-fall of rela-tively numerous,low mass galaxies such that the galaxies have evolved into early type galaxies is just consistent with the time scales involved(1Gy for relaxation for low mass or faint galaxies and1.5Gy for virialization).
It is not clear what our proposed scenario predicts at greater look back times.One possibility is that early type galaxies formed?rst and formed the initial clusters(this hypothesis is,however,not supported by van Dokkum et al.1999).Then the later type galaxies,having formed later in the?eld are just beginning to fall into the cluster and even the bright,massive ones have not yet fallen in.In this scenario,the cluster core will have a low blue fraction/low fraction of late type galaxies even at the bright end.This is approximately consistent with the?nding of Wirth et al. (1994)on CL0016+16(albeit an X-ray luminous cluster) or of Butcher&Oemler(1984)or as suggested by Lubin et al(1998)and Postman et al(1998)(see,however,section 4.1regarding the Lubin et al.1998and Postman et al. 1998results)
The detailed scenario we suggested to explain the re-sults of our analysis and comparisons with a nearby op-tically selected sample should be considered only that,a suggestion.More elaborate theoretical work,that is be-yond the scope of this paper,is necessary to develop the full range of possibilities.The statistics of the results we found here also clearly need to be improved by analyzing the data from more clusters with larger telescopes.What our discussion has showed is the power of the analysis we performed here,and how more analysis of z≥0.5systems coupled with an extension to even higher redshift systems will do much to clarify picture of how galaxy populations evolve within clusters.
Acknowledgements.AC thanks the sta?of the Dearborn Ob-servatory for their hospitality during his postdoctoral fellow-ship.The authors thanks the CFHT TAC for support for the COP survey.
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注意：以下内容请进一步总结！ 青岛恒源热电有限公司 目标公司主要从事蒸汽、热水的生产及供应、蒸汽余热发电业务，同时提供供热管道及设施维修、安装业务。据介绍，目标公司开发了循环水供热工程项目，该项目是青岛市获批的第一个清洁发展机制(CDM)项目；前处该项目处于施工建设阶段，预计将于2009年上半年内正式投产。据介绍，目标公司主要负责临港工业区辖区内的蒸汽供应及热网管理，发电业务，对居民的用热服务。 公司成立于2001年，主要从事蒸汽、热水的生产及供应、蒸汽余热发电业务。 青岛恒源热电有限公司位于开发区B区供热范围，拥有12MW的抽凝式汽轮发电机组1台及12MW的背压机组1台，75t/h循环流化床锅炉3台和150t/h锅炉1台，最大供热能力是355t/h，担负着B区的生产、民用供热负荷，主要满足热电厂东部居民小区供热和山东科技大学供热。 青岛恒源热电有限公司位于青岛经济技术开发区临港工业区的中北部，海尔大道与渭河路交界处东北角，渭河路777号。厂区所在地东侧隔宽约100m绿化地为鑫龙物流公司，该公司东侧、距离本项目最近300m处为澳柯玛人才公寓；厂区南侧隔渭河路、绿化带100m处为东小庄村（原村庄平房已搬迁，现建有多座两层复式楼房），该村庄南侧、距离本项目约420m处为山孚日水食品有限公司；项目隔渭河路东南方向约200m处为澳柯玛工业园；西及西南方向隔海尔大道、渭河路均为浦项制铁有限公司；北侧与开发区消防大队以及正友砼业相邻。 企业所在地厂址东南距市中心约8km，东面距前湾港区约4.5km。 现有工程内容：青岛恒源热电有限公司主要服务于黄岛供热分区B 区（齐长城路以北、疏港高速以南、镰湾河以西、柳花泊和珠山以东片区（包括柳花泊），总占地面积约60平方公里）。企业现有锅炉规模为3×75t/h+1×130t/h 循环流化床蒸汽锅炉，总计约355t/h锅炉容量；发电机组规模为1×12MW C12-34.9/0.98（抽凝）+1×12MW B12-4.9/0.98（背压），总计发电装机容量24 MW。 近几年，恒源热电强化能源管理，合理调整运行方式，加强节能技术改造，企业能源管理工作上了一个新台阶，先后通过了“企业能源审计”、“热电联产机组认定”等审核认证工作，被评为“青岛市清洁生产企业”，2007年度“山东省节能先进企业”。 为进一步加强企业能源管理，完善优化企业节能减排工作，公司在本年度开始推行循环经济试点工作。目前，作为试点工作重点项目之一的企业冷渣机改造项目已基本完成，初步具备投运条件，预计本年度六月份正式投入运行。该项目是将循环流化床锅炉的人工排渣（温度一般在900℃），通过加装冷渣机把炉渣余热加热除盐水，将锅炉效率提高1-3%，同时解决人工放渣存在安全隐患、能源浪费以及不环保等问题，项目投资为85万元，年可节标煤700吨。
热能与动力工程专业制热方向认识 实习报告 学院：机电工程学院 班级：热能一班 姓名：徐国庆 学号：201240502013
一．认识实习的目的和任务 1.认识实习的目的： （1）认识实习是四年制高等学校教学活动的实践环节之一； （2）认识实习是对学生进行火力发电厂主机（锅炉、汽轮机）、辅机（换热器、风机、水泵）及其制造厂的设备系统、生产工艺进行认识性训 练，对发电厂热力系统进行整体初步了解。 2.认识实习的任务： （1）对火力发电厂主机的认识实习 实习对象：锅炉本体、汽轮发电机本体。锅炉形式包括煤粉锅炉、循 环流化床锅炉、链条炉、余热锅炉等。汽轮机形式包括凝气式汽轮机、 背压式汽轮机、调节抽汽式汽轮机。 认识内容：设备外形特点、摆放位置、主要性能参数、安全生产常识。 （2）对火力发电厂辅助机械设备的认识实习 实习对象：制粉系统、除尘除灰系统、烟风系统、回热系统、润滑冷 却系统、水油净化系统等。 认识内容：设备外形特点、摆放位置、主要性能参数、安全生产常识。 （3）对火力发电厂设备系统的认识实习 实习对象：火力发电厂主机和辅机工程的系统。 认识内容：设备之间的空间关系、安全生产常识。 3.认识实习的意义 （1）强化学生对专业基础课程的理解 （2）国内火力发电厂的技术发展出现了新进展 CFB锅炉、燃气轮机、余热锅炉、超临界机组、烟气脱硫、布袋除尘、集中控制运行等新技术。 （3）认识实习有利于培养学生的职业精神 （4）认识实习有利于了解机组 （5）认识实习有利于了解机组建设过程 二．捷能汽轮机厂 （1）简介：汽轮机是火力发电厂三大主要设备之一。它是以蒸汽为工质，将热能转变为机械能的高速旋转式原动机。它为发电机的能量转换提供机 械能。 青岛捷能汽轮机集团股份有限公司始建于1950年，是我国汽轮机行业重 点骨干企业。拥有各种数控、数显等机械加工设备2200余台，以200MW 及以下“捷能牌”汽轮机为主导产品，拥有电站汽轮机和工业拖动汽轮 机两大系列产品，能够满足发电、石化、水泥、冶金、造纸、垃圾处理、燃气-蒸汽联合循环、城市集中供热等领域需求，年产能达500台/600万 千瓦以上。中小型汽轮机市场占有率居国内同行业首位，是目前国内中 小型汽轮机最大最强的设计制造供应商和电站成套工程总包商。 公司积极推进品牌战略，率先在汽轮机行业内取得了美国FMRC公司双重 ISO9001国际质量体系认证和ISO1400环境管理体系认证，率先在汽轮机 行业内第一个获得了“中国名牌产品”称号，先后获得了“全国AAA级 信用企业”、“中国优秀诚信企业”、“全国用户满意产品”、“山东
供热管网检修作业指导手册[青岛热电集团] 供热管网检修作业指导手册[青岛热电集团] 供热管网检修作业指导手册[青岛热电集团] 作者:佚名更新时间:2008-12-5 15:55:38 字体: 供热管网检修作业指导手册 1 总则 1.1 为使公司供热管网的维护、检修工作更为规范和科学合理，确保安全运行，制定作业指导手册。 1.2 本作业指导手册适用于公司供热管网的维护、检修及事故抢修。 本作业指导手册供热管网的工作压力限定为: 工作压力不大于1.6MPa(表压)，介质温度不大于300?的蒸汽供热管网。 1.3 管网的检修工作应符合原设计要求。 1.4 执行本作业指导手册时，尚应符合国家现行有关标准的规定。 2 术语 2.1 热网维修 热网的维护和检修。本作业指导手册中简称维修。 2.2 热网维护 供热运行期间，在不停热条件下对热网进行的维护工作。本作业指导手册中简称维护。 2.3 热网检修 在停热条件下对热网进行的检修工作。本作业指导手册中简称检修。 2.4 热网抢修
供热管道设备突发故障引起蒸汽大量泄漏，危及管网安全运行或对周边环境、人身安全造成威胁时进行的紧急检修工作。本作业指导手册中简称抢修。 2.5 供热管网 由热源向热用户输送和分配供热介质的管线系统。本作业指导手册中简称热网。 3 维护、检修机构设置、检修人员及设备 3.1 维护、检修机构设置及人员要求 3.1.1客户服务中心是公司高新区内供热管网运行、调度、维护、检修的责任机构，负责高新区内供热管网的维护、检修工作。 3.1.2 供热管冈的维护、检修人员必须经过培训和专业资格考 试合格后，方可独立进行维护、检修工作。供热管网维护、检修人员必须熟悉管辖范围内的管道分布情况、设备及附件位置。维护、检修人员必须掌握管辖范国内供热管线各种附件的作用、性能、构造以及安装操作和维护、检修方法。 3.1.3检修人员出门检修时应穿公司工作服，配戴上岗证，注意礼貌用语，维护公司形象。 3.2 维护、检修用主要设备与器材 3.2.1 供热管网的维护检修部门，应备有维护、检修及故障抢修时常用的设备与器材。 3.2.2检修设备、工具平时摆放在规定位置，检修设备和专用工具要有专人保管，所有设备、工具应保证完好，须保证检修时能够立即投入使用。检修物资也应分门别类码放整齐，方便查找，以保证检修、抢修时不会因为寻找物资配件而耽误时间。每次检修完后都应检查备品备件数量，发现不够时要及时与物质采购部联系进行必要地补充，确保检修时不会因无备品备件而影响检修时间与质量。
招标投标企业报告 青岛西海岸公用事业集团易通热电有限公司新 能源分公司
本报告于 2019年9月22日 生成 您所看到的报告内容为截至该时间点该公司的数据快照 目录 1. 基本信息：工商信息 2. 招投标情况：中标/投标数量、中标/投标情况、中标/投标行业分布、参与投标 的甲方排名、合作甲方排名 3. 股东及出资信息 4. 风险信息：经营异常、股权出资、动产抵押、税务信息、行政处罚 5. 企业信息：工程人员、企业资质 * 敬启者：本报告内容是中国比地招标网接收您的委托，查询公开信息所得结果。中国比地招标网不对该查询结果的全面、准确、真实性负责。本报告应仅为您的决策提供参考。
一、基本信息 1. 工商信息 企业名称：青岛西海岸公用事业集团易通热电有限公司新能 源分公司 统一社会信用代码：91370211334195493K 工商注册号：370211120004502组织机构代码：334195493法定代表人：赵军田成立日期：2015-04-23 企业类型：有限责任公司分公司(非自然人投资或控股的法人 独资) 经营状态：注销 注册资本：/ 注册地址：山东省青岛市黄岛区相公山路723号 营业期限：2015-04-23 至 / 营业范围：为上级公司联系业务。（依法须经批准的项目，经相关部门批准后方可开展经营活动）联系电话：*********** 二、招投标分析 2.1 中标/投标数量 企业中标/投标数： 个 （数据统计时间：2017年至报告生成时间）
2.2 中标/投标情况（近一年） 截止2019年9月22日，根据国内相关网站检索以及中国比地招标网数据库分析，未查询到相关信息。不排除因信息公开来源尚未公开、公开形式存在差异等情况导致的信息与客观事实不完全一致的情形。仅供客户参考。 2.3 中标/投标行业分布（近一年） 截止2019年9月22日，根据国内相关网站检索以及中国比地招标网数据库分析，未查询到相关信息。不排除因信息公开来源尚未公开、公开形式存在差异等情况导致的信息与客观事实不完全一致的情形。仅供客户参考。 2.4 参与投标的甲方前五名（近一年） 截止2019年9月22日，根据国内相关网站检索以及中国比地招标网数据库分析，未查询到相关信息。不排除因信息公开来源尚未公开、公开形式存在差异等情况导致的信息与客观事实不完全一致的情形。仅供客户参考。 2.5 合作甲方前五名（近一年） 截止2019年9月22日，根据国内相关网站检索以及中国比地招标网数据库分析，未查询到相关信息。不排除因信息公开来源尚未公开、公开形式存在差异等情况导致的信息与客观事实不完全一致的情形。仅供客户参考。 三、股东及出资信息 截止2019年9月22日，根据国内相关网站检索以及中国比地招标网数据库分析，未查询到相关信息。不排除因信息公开来源尚未公开、公开形式存在差异等情况导致的信息与客观事实不完全一致的情形。仅供客户参考。 四、风险信息 4.1 经营异常() 截止2019年9月22日，根据国内相关网站检索以及中国比地招标网数据库分析，未查询到相关信息。不排除因信息公开来源尚未公开、公开形式存在差异等情况导致的信息与客观事实不完全一致的情形。仅供客户参考。 4.2 股权出资() 截止2019年9月22日，根据国内相关网站检索以及中国比地招标网数据库分析，未查询到相关信息。不排除因信息公开来源尚未公开、公开形式存在差异等情况导致的信息与客观事实不完全一致的情形。仅供客户参考。 4.3 动产抵押() 截止2019年9月22日，根据国内相关网站检索以及中国比地招标网数据库分析，未查询到相关信息。不排除因信息公开来源尚未公开、公开形式存在差异等情况导致的信息与客观事实不完全一致的情形。仅供客户参考。 4.4 税务信息() 截止2019年9月22日，根据国内相关网站检索以及中国比地招标网数据库分析，未查询到相关信息。不排除因信息公开来源尚未公开、公开形式存在差异等情况导致的信息与客观事实不完全一致的情形。仅供客户参考。
青岛热电集团有限公司成立于1993年，属于国有独资大型热电联产企业，主要担负着青岛市企、事业单位和居民供热及部分发电任务，同时，供热市场辐射黄岛、平度、莱西、即墨、城阳等县市区域。集团公司先后成立了工程公司和具有甲级设计资质的设计院，逐步形成了热电联产、区域锅炉、热网输配等多种供热形式并存，集供热、发电、热力设计、工程施工、热力产品制造经营为一体的完整产业链。 目前，热电集团为全省地方最大供热企业。企业资产总额48亿元，年销售收入16.2亿元，所属企业16个，职工2200余人，年供蒸汽312万吨，年发电能力9.3万千瓦，已建成蒸汽管网145.43公里，热水管网1552.93公里，供（换）热站294座，供热面积3561万平方米，拥有单位用户292家，居民用户28.8万余户。 集团公司先后被评为全国AAA级信用企业、全国建设系统文明服务示范窗口单位、思想政治工作先进单位、企业文化建设先进单位、精神文明建设先进单位；山东省文明单位、节能先进企业、思想政治工作优秀企业；青岛市和工商年度免检企业、安全生产先进单位、廉洁勤政先进单位；山东省供热协会副理事长单位。 自成立以来，公司始终秉承“关爱社会、服务民生”的企业宗旨和“励精图治、锲而不舍”的企业精神，贯彻科学发展，创新经营管理，实现了企业快速发展。1996年在全国供热行业首家推出社会服务责任赔偿制度，1997年在山东省供热行业首家进行了股份制改造，1998年在山东省供热行业首家成功地进行了集团产权制度改革，1999年在全国同行业中首家通过了ISO9001国际质量认证，并先后通过了ISO14001环境管理体系和GB/T28001-2001职业健康安全管理体系认证，2001年公司成为全国供热行业中首家申请注册服务商标的企业，推出“暖到家”服务品牌，并被评为山东省著名商标和服务名牌。“青岛热电”正在逐步步入标准化、规范化、品牌化的发展轨道。 招聘专业及人数: 1、结构专业1人(研究生)； 2、建筑专业1人(研究生)； 3、技经专业1人(研究生)； 4、焊接技术与工程1人； 5、无损检测专业1人；
华能集团所属电厂： 华能丹东电厂华能大连电厂华能上安电厂华能德州电厂华能威海电厂华能济宁电厂华能日照电厂华能太仓电厂华能淮阴电厂华能南京电厂华能南通电厂华能上海石洞口第一电厂华能上海石洞口第二电厂华能长兴电厂华能福州电厂华能汕头燃煤电厂华能汕头燃机电厂华能玉环电厂华能沁北电厂华能榆社电厂华能辛店电厂华能重庆分公司华能井冈山电厂华能平凉电厂华能岳阳电厂华能营口电厂华能邯峰电厂 大唐集团所属： 长山热电厂湖南省石门电厂鸡西发电厂洛阳首阳山电厂洛阳热电厂三门峡华阳发电公司河北马头电力公司唐山发电总厂北京大唐张家口发电总厂兰州西固热电有限公司合肥二电厂田家庵发电厂北京大唐高井发电厂永昌电厂北京大唐陡河电厂南京下关发电厂安徽淮南洛河发电厂保定热电厂略阳发电厂微水发电厂峰峰发电厂含岳城电站天津大唐盘山发电公司内蒙大唐托克托发电公司保定余热电厂华源热电有限责任公司阳城国际发电有限公司辽源热电有限责任公司四平发电运营中心长春第二热电有限公司晖春发电有限责任公司鸡西热电有限责任公司佳木斯第二发电厂台河第一电厂江苏徐塘发电有限公司安徽省淮北发电厂安徽淮南洛能发电公司安阳华祥电力有限公司许昌龙岗发电有限公司华银电力株洲发电厂华银株洲发电公司金竹山电厂华银金竹山火力发电厂湘潭发电有限责任公司湖南省耒阳发电厂灞桥热电有限责任公司灞桥热电厂陕西渭河发电厂陕西延安发电厂陕西韩城发电厂永昌发电厂甘肃甘谷发电厂甘肃八0三发电厂甘肃连城发电厂甘肃兰西热电有限公司广西桂冠电力股份公司桂冠大化水力发电总厂广西岩滩水电厂陈村水力发电厂王快水电厂张家界水电开发公司贺龙水电厂鱼潭水电厂陕西石泉水力发电厂石泉发电有限责任公司甘肃碧口水电厂百龙滩电厂华电所属： 1中国华电工程(集团)有限公司2华电煤业集团有限公司3华电财务有限公司4华电招标有限公司5华信保险经纪有限公司6北京华信保险公估有限公司7河北热电有限责任公司8包头东华热电有限公司（在建）9内蒙古华电乌达热电有限公司（在建）10华电国际电力股份有限公司11华电国际电力股份有限公司邹县发电厂（扩建）12华电国际电力股份有限公司莱城发电厂13华电国际电力
青热电〔2010〕121号 青岛热电集团有限公司 关于实施供热计量收费工作的意见 各单位、处室： 为全面贯彻《山东省物价局、山东省住房和城乡建设厅关于推进供热计量改革的指导意见》，根据青热办【2010】25号文件要求，自2010年开始，新供热建筑及完成供热计量改造的既有居住建筑，取消以面积计价收费，实行按用热量计价收费，为做好供热计量收费工作，经研究确定以下实施意见： 一、实施计划 （一）对已经改造完成的既有居住建筑实施供热计量收费，明细如下：第一热力海信慧谷、丰华园、弘信花园、都市名家小区；第二热力公司天宝苑小区；金河热力公司荣馨苑小区。
（二）对新竣工非居住建筑全面按用热量计量收费。 二、实施措施： （一）加强组织领导，责任到位。 职责明确，责任到人。集团成立以董事长为组长，总经理为副组长的供热计量工作领导小组，工程开发处、生安处、财务处、服务处各司其职，全力做好供热计量收费实施工作。各所属生产单位必须成立工作领导小组，将宣传、收费、数据公示、政策答疑等工作落实到位，各单位要有专门的供热计量工作负责人。 （二）措施到位，计划周密。 责任部门要全力做好实施热计量收费工作的计划安排，配合相关科室做好用户协调、宣传、合同签订、数据公示以及收、退费工作。 （三）做好新建、竣工项目供热计量设施的管理工作。各相关部门要严格新建、在建、新竣工项目供热计量设施的审核、把关、验收和问题汇总工作。 三、工作要求 （一）做好用户宣传、解释工作。在张贴用户通知进行宣传的同时，相关人员要明确供热计量工作实施相关要求规定，收费方式以及供热调节方式等，做好对用户的宣传解释工作，让用户明白调节方式和收退费方式、时间等。 （二）做好用户结算工作。用户的供热计量数据要真实、准确，各单位要认真做好用户仪表底数（正式供热时间和停止供热时间）确认工作，并定时张贴通知公开热量数据。 （三）做好数据分析和总结。对供热数据按周期进行定
1建设项目概况 1.1建设项目背景及建设地点 1.1.1建设项目背景 青岛钢铁有限公司（以下简称青钢）始建于1958年，位于青岛市北李沧区，属城市钢铁厂。厂区东邻重庆路、南渠村；西围墙距胶济铁路约85m；北距流亭国际机场约3.8km；南靠遵义路。距市中心约15km，厂内铁路专线与胶济铁路娄山站接轨，全厂总占地面积不足1.3km2。 青钢是集焦化、烧结、炼铁、炼钢、轧钢、发电等为一体的钢铁联合企业，是山东省重要的优质棒线材生产基地，山东省三大钢铁支柱企业。 目前，青钢已形成年产铁、钢、材各400×104t的生产能力。其主要生产设施有：60×104t焦化厂；2×50m2烧结机，2×105m2烧结机；5×500+1×625m3高炉；一炼钢有4×35t转炉，5座30tLF精炼炉，3台4机4流R5m小方坯连铸机和1台4机4流R8m连铸机；二炼钢有2×80t 顶底复吹转炉，3座90tLF精炼炉，1座90tRH精炼炉，2台6机6流R9m 连铸机；轧钢车间有1＃、2＃、3＃高速线材车间，复二重线材车间，半连续小型车间，横列式小型车间，还有与之配套的相应公辅设施。 青钢产品有：热轧盘条，热轧带肋钢筋、圆钢、扁钢等型钢。主要品种有：焊接用钢盘条、汽车用弹簧扁钢、硬线盘条、冷镦钢、PC钢棒用线材、拉丝线材、易切削钢、优质碳素结构圆钢、建筑用线材与螺纹钢等。2011年，青钢生产生铁330.69×104t、钢318.27×104t、钢材301.99×104t。2011年工业总产值297.79亿元，工业销售产值299.47亿元。青钢现有产品以优特钢为主，品种结构具有特色，产品附加值高。青钢现有职工1万余人，其中各类工程技术人员约1500余人。 自1997年以来，青钢经过不断的技术改造，其生产能力和经济效益均有了较大幅度的提高，但由于历史原因，还存在许多问题，如产品结构性矛盾仍