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Appendix A: Targeted lines and measurements

Table A.1 lists the species and transitions observed in the PACS range with the line spectroscopy mode in the decreasing wavelength order. Information about the upper level energies, E_u/k_B, the Einstein coefficients, A, the weights, g_up, and frequencies, ν, are obtained from the Cologne Database for Molecular Spectroscopy (Müller et al. 2001, 2005), the Leiden Atomic and Molecular Database (Schöier et al. 2005) and the JPL Catalog (Pickett et al. 1998).

Tables A.2 and A.3 list line fluxes for all our sources in units of 10^-20 W cm^-2. The uncertainties are 1σ measured in the continuum on both sides of each line; calibration uncertainty of 30% of the flux should be included for comparisons with other modes of observations or instruments.

Appendix B: Extended source correction method

To account for the combination of real spatial extent in the emission and the wavelength-dependent PSF, we developed an “extended source correction” method. We first inspected the 5 × 5 spectral (or contour) maps. Contributions from NGC 1333-IRAS4A, Ser SMM6, and an unlabeled object were subtracted from the observations of NGC 1333-IRAS4B, Ser SMM3, and SMM4 (e.g. Yıldız et al. 2012; Dionatos et al. 2013). In the next step, we used two long-wavelength lines of CO and H₂O (CO 14–13 at 185.999 μm and H₂O 2₁₂ − 1₀₁ at 179.527 μm) to visualize the spatial extent of the line emission attributed to each object and summed all the spaxels that contained emission. Since all of our lines, except the [O i] line at 63.2 μm, are spectrally unresolved by PACS, single or double (for OH doublets, closeby and blended lines) Gaussian fits to the resulting spectra are used to calculate the line fluxes of the detected lines.

Summing the spectra from all 25 spaxels increases the noise and often prevents detecting weak lines. Using only those spaxels that contain most of the emission results in a much higher signal-to-noise and ultimately a higher detection rate for lines but fails to include emission that leaks out of those spaxels because of real spatial extent in the line and the instrumental PSF. Therefore, our “extended source correction” method provides a wavelength-dependent correction factor to account for the missing flux. The main idea of the method is to use the brightest spaxels, which contain most of the emission, to measure the line fluxes and then correct the value for the missing flux, contained in the omitted spaxels. This method assumes that weak lines are similarly distributed to the strong ones, with observed differences in spatial distributions caused only by the wavelength dependence in the PSF.

The correction factors are derived using the strongest lines, i.e. those that can be measured in the brightest spaxels as well as in all spaxels that contain emission from the object (usually 25 of them). The ratio of flux in the small, bright extraction region and the large extraction region yields a wavelength-dependent correction curve (see Fig. B.1). A 0th-order fit (horizontal line) is used for the short-λ part of the spectrum, whereas a 1st- or 2nd-order polynomial is used for the long-λ part of the spectrum (≥100–110 μm). All line fluxes are then measured in only the brightest spaxels and multiplied by this correction factor. This method was used primarily for the full spectral scans.

Appendix C: Spectral energy distributions

Figure C.1 shows the SEDs for all of our sources obtained from our PACS spectroscopy and literature measurements from Spitzer-IRAC and MIPS (Evans et al. 2009), 2MASS (Skrutskie et al. 2006), SCUBA (Shirley et al. 2000; Di Francesco et al. 2008), as well as APEX/LABOCA, Bolocam, SEST, ISO and IRAS telescopes. The PACS measurements cover the peak of dust emission and are in good agreement with the previous observations (for more details, see Kristensen et al. 2012).

For PACS, the overlap regions of different orders cause the regions of 70–73 μm, 98–105 μm and 190–220 μm to be less reliable in terms of continuum shapes and flux densities. These regions were thus excluded from our SED analysis. New values of L_bol and T_bol are calculated following the standard definitions of the two physical quantities (e.g., Dunham et al. 2010). Several methods of interpolation were tested for consistency of the results including linear interpolation, midpoint, prismodial method and trapezoidal summation. Among them the trapezoidal summation offered the most stable values and is used in this study.

Appendix D: Spatial extent of line emission

Figures D.1 and D.2 show the spectra in the on-source and outflow positions for objects with extended emission and objects with compact emission, respectively (see Sect. 3.2).

Figure D.3 presents the spectra of the [O i] 63.2 μm line, the OH 84.6 μm line, the H₂O 7₁₆–6₀₇ line, and the CO 30–29 line for the central target, two spaxels in the red-shifted outflow, and two spaxels in the blue-shifted outflow of NGC 1333-IRAS4A.

Appendix E: Comparing PACS and ISO far-IR spectra

Higher sensitivity of Herschel/PACS compared to ISO-LWS allows us to improve the detection rate of H₂O (15 out of

16 Class 0/I sources) and higher-J CO transitions (14 out of 16 sources detected in CO 24–23). In particular, water detections in Class I sources are now possible for the majority of the sources. Detection of the more highly excited CO transitions allows to distinguish the hot component on the rotational diagram, which was not possible with ISO (Nisini et al. 2010).

The chopping capabilities and the spatial resolution of Herschel at the distances of our objects allow us to distinguish the YSO–related atomic emission from the emission from the nearby objects or the surrounding cloud. Herschel observations show that only two objects (Ser SMM1 and TMC1) show [C ii] emission associated with the YSO. The [O i] emission, on the other hand, is clearly extended in the outflow direction and most probably traces the hidden jet. For some of the outflow-dominated emission sources, the Herschel beam does not cover the full extent of the [O i] emission, whereas the ISO beam can suffer from the cloud or nearby sources emission. Table E.1 shows the comparison between the [O i] emission for the sources observed with both instruments.

Appendix F: Rotational diagrams

Figures F.1 and F.2 show CO and H₂O rotational diagrams for all sources from our sample. Two-component fits are used for the CO diagrams and one-component fits for the H₂O diagrams. These fits are used to determine the total cooling budget in the two molecules for each objects, as discussed in Sect. 4. The errors in the temperatures reflect the statistical error of the fit taking the uncertainties in individual line fluxes as listed in Table A.2 into account. They do not include the absolute flux uncertainties since the relative fluxes between lines within a single spectrum have much lower uncertainties.

Appendix G: Correlations

Figure G.1 shows correlations between selected line luminosities and bolometric temperature (T_bol) and density at 1000 AU (n_H2). Strong correlations are found with the latter quantity.

Appendix H: Rotational temperature uncertainties

Figure H.1 shows the CO and H₂O rotational diagrams for the NGC 1333-IRAS4B and Serpens SMM1, using the data published in Herczeg et al. (2012) and Goicoechea et al. (2012). The full spectroscopy data is shown, with the full line coverage in the PACS range, as well as the selected lines only, typically observed in our line spectroscopy mode for 16 sources in our sample.

Rotational temperatures calculated from the rotational diagrams constructed using the full and limited line configurations are in good agreement for the CO. For the assumed ranges of the two components, the warm component T_rot error of the fit is ±15 K and the hot component T_rot error is ±50 − 100 K.

The change of the energy break in a wide range of transitions results in ±20 K error for the T_rot(warm) and ±40 K for the T_rot(hot) for the full spectroscopy data. Those ranges are not well determined by line spectroscopy data only and thus in this work we always use 1700 K for this kind of observations.

H₂O rotational temperatures, on the other hand, are less accurately determined for the line spectroscopy observations than the formal error of the fit would imply. The scatter due to the subthermal excitation and very likely high opacities of the water lines result in significant differences in T_rot calculation, depending on the choice of observed lines. The fit to the water lines chosen in our program underestimates the resulting temperature by about 50–80 K for the NGC 1333-IRAS4B and Serpens SMM1.

Appendix I: Cooling budget calculations

Since different methods of cooling budget calculation exist in the literature and will appear due to the availability of new Herschel observations, we perform here a comparison between the methods and estimate the differences between the resulting budgets.

Appendix I.1: Carbon monoxide

In order to calculate the CO cooling, Nisini et al. (2002b) calculated LVG models that reproduced the detected transitions and used them to determine the fluxes for the first 60 transitions of CO. Due to the limited ISO sensitivity, CO transitions from J = 14–13 to J = 22–21 (Class I) and J = 29–28 (Class 0) were available for the brightest sources only which did not allow them to distinguish the hot component. Their method corresponds to a single-component fit to the excitation diagrams.

We use the entire PACS array line fluxes of NGC 1333-IRAS4B and Ser SMM1 from Herczeg et al. (2012) and Goicoechea et al. (2012) to compare the observed CO total luminosities with those calculated using fits to the excitation diagrams (see Table I.1). In particular, we show the results of the two-components fits for PACS data and three-components fits for PACS and SPIRE data, available for Ser SMM1. Three wavelength ranges are included: (i) the PACS range from 54–60 to 190 μm; (ii) the Nisini et al. 2002 range, namely 44–2601 μm; (iii) the PACS + SPIRE range, from 60 to 650 μm (for SMM1 only). Additionally, we include the fitting results to the observed lines only, in order to check how good our two/three-component linear fits reproduce the observations.

The calculations in Table I.1 show that multi-component linear fits to the excitation diagrams agree well with the observed values of the total CO luminosity from the detected lines (rows 1+2 and 5+6). The uncertainties correspond to different choice of the break energy for the two components. The fits are then used to extrapolate the fluxes of the lines which are either blends or fall in the region of ~100 μm, where the measured line fluxes are less reliable (row 3 for PACS range and row 7 for PACS+SPIRE range). The resultant total CO luminosities are a good measure of the far-IR CO cooling (for the PACS range) and total CO cooling (for PACS+SPIRE range).

The example of SMM1 shows that the additional CO emission from the entrained outflow gas increases the CO luminosity by a factor of 1.3 with respect to the extrapolated values from the warm CO component (5.23 × 10^-2L_⊙ versus 6.93 × 10^-2L_⊙).

The relative CO luminosity in different spectral regions (A: J = 4–3 to J = 13–12 B: J = 14–13 to J = 24–23 and C: J = 25–24 to J = 44–43) for SMM1 is ~2:2:1 (A:B:C) and for IRAS4B is ~2:1 (B:C), when the additional cold CO component is included. Thus, approximately 80% of the CO luminosity comes from transitions lower than CO 24–23, roughly equally in both SPIRE and PACS ranges. The poorer determination of the hot component rotational temperature does not affect significantly the total cooling determination.

Appendix I.2: Water

Nisini et al. (2002) have calculated H₂O luminosities based on the assumption that H₂O emission arises from the same gas as CO, for which large velocity gradient (LVG) models determined the gas temperature and density. The model prediction were used to extrapolate H₂O line fluxes for rotational transitions with J < 10 and E_u/k_B < 2031 K.

Total H₂O cooling in this work (see Sect. 4.2) is calculated based on the full spectroscopy data for the NGC 1333-IRAS4A and Serpens SMM1 (Herczeg et al. 2012 and Goicoechea et al. 2012). The average scaling factor than transfers the luminosity observed in the selected lines in the line spectroscopy mode to the total water luminosities (as observed in the range spectroscopy) is 2.4 ± 0.3.

An alternative method considered for the water cooling calculation is the extrapolation of the non-observed line fluxes based on the H₂O rotational temperature. Table I.2 compares the results of this method with the values obtained when the scaling factor was used. The extrapolation is done for (i) the 328 lowest rotational transitions of water (J < 10, E_u/k_B < 2031 K, so called “Nisini et al. range”); (ii) the same transitions but only for PACS range. Molecular information is obtained from the JPL and CDMS catalogs (Pickett et al. 1998; Müller et al. 2001, 2005).

Calculations for Serpens SMM3 show that the extrapolation of the fluxes based on the fitted rotational temperature results in a factor of ~ 2 higher total water luminosities than the value calculated using the scaling factor of 2.4. Even higher values are obtained when we extend the range used in Nisini et al. (2002). Additionally, the rotational temperature of H₂O derived from the line scan data is very likely underestimated by a factor of ~ 1.3 − 1.6 (see Appendix H). This uncertainty has an effect on the derived, extrapolated, H₂O total cooling.

In summary, from the comparisons it is concluded that the total luminosity of both CO and H₂O in the PACS range is accurate to 30% or better.

Appendix J: PACS maps for all sources

Figures J.1–J.16 show PACS 5 × 5 maps for all the sources, except NGC 1333-IRAS4A and L1489 presented in the main text, in the [O i] , H₂O 2₁₂–1₀₁, CO 14–13 and OH lines (unless stated otherwise in the captions). In each map the CO 6–5 blue and red outflow direction are overplotted for comparison (Yıldız et al., in prep.). Color frames show the blue and red outflow positions used to create Figs. D.1 and D.2.

© ESO, 2013