In order to follow the chemical evolution of a galaxy, it is without any doubt important to know how stars with different masses enrich the ISM with various chemical elements. The term stellar yields is commonly used to indicate the masses of fresh elements produced and ejected by a star of initial mass m and metallicity Z. However, the term yields was originally introduced to indicate the ratio between the mass of a specific chemical element ejected by a stellar generation and the mass locked up in remnants (white dwarfs, neutron stars and black holes; see also Sect. 9).
Many groups in the past few decades calculated the stellar yields of both massive and intermediate-mass stars for different metallicities [232, 346, 102, 217, 185, 151, 152, 121, 198]. Unfortunately, except for a handful of elements whose nucleosynthesis in stars is well understood, yields of other elements calculated by different authors can vary by orders of magnitude. This is especially true for the majority of the iron-peak elements, but also for much more abundant species such as carbon and nitrogen (see the review of Nomoto et al. ). Of course, model predictions are significantly affected by the choice of the set of yields. This has been shown by Romano et al.  by means of neat and clear numerical tests (see their figs 3 and 15, for instance). One of the most significant sources of uncertainty in the calculation of stellar yields is the presence of stellar mass loss. Massive stars with solar metallicity might in fact lose a large amount of matter rich of He and C, thus subtracting those elements to further processing, which would eventually lead to the production of oxygen and other heavy elements. The models of Maeder  for instance predict that a 40 M star ejects only ~ 2 M of O, whereas in most of nucleosynthetic calculations without winds [346, 219, 151] the production of oxygen is a factor of ~ 3 larger.
The yields from dying stars not only directly affect the chemical composition of the ISM in chemo-dynamical evolution of galaxies, but can also affect the dynamics by means of chemical feedback. The main effect is due to cooling. In fact, it is known that the cooling function of an optically thin plasma has a strong dependence on metallicity, at least in the temperature range between ~ 104 and 105 K [23, 296, 258]. Moreover, different chemical elements contribute differently to the plasma radiative emission. Clearly, the assumption of different yields in chemo-dynamical models affects the chemical composition of the ISM, which in turn changes the cooling timescales. An example of the effect of different sets of yields on the dynamical evolution of galaxies is given in Fig. 2. Two models of galaxy evolution (taken from the suite of simulations of Recchi et al. ) differ only in the adopted nucleosynthetic prescriptions for intermediate-mass stars:  (MM02) on the left panels and  (VG97) on the right panels. Yields of high-mass stars are in both cases taken from . Feedback from SNeII and stellar winds creates a network of cavities and tunnels. The superbubble evolution is faster in the MM02 model. Indeed, MM02 produces on average more metals, therefore leading to larger cooling rates. On the one hand, it reduces the thermal energy content inside the superbubble, but on the other hand this increased cooling favours the process of star formation, leading to a more powerful feedback. The latter effect prevails, and a larger energy is available in model MM02 to drive the expansion of the supershell. Within the timespan of 100 Myr covered by these two simulations, the differences between the two models are not huge. They are, however, non-negligible and they tend to increase with time. This simple test shows the effect of chemical feedback on the evolution of a galaxy, an aspect that has been often overlooked in the literature.
Figure 2. Density and temperature contours at 4 evolutionary times (labelled on each of the right panels) for a model adopting MM02 (left) and VG97 (right) yields, respectively. The (logarithmic) density scale (in g cm-3) ranges between -27 (dark) and -23 (bright). The (logarithmic) temperature scale (in K) ranges between 3 and 7.
One should also be aware that other forms of chemical feedback operate in galaxies. The photoelectric emission from small dust grains and PAHs can substantially contribute to the heating of the ISM . The amount of dust and PAH in a galaxy strongly correlates with its metallicity  and, consequently, the metallicity affects the photoelectric heating of the gas. It is commonly assumed that for ISM metallicities below Zcr ~ 10-5 Z, the star formation process is substantially different and leads to a top-heavy IMF producing, on average, very massive stars, the so-called PopIII stars . As the ISM metallicity approaches Zcr, the transition to a Salpeter-like IMF occurs.
Under some circumstances, chemical reactions can affect the chemical evolution, as well. Astrochemistry is a vibrant and very active astrophysical discipline [68, 311] and nowadays the details of many important atomic and molecular reactions occurring in the ISM are known. Although the chemistry of the dense gas in clouds is very rich and variegate, less happens in the more dilute diffuse gas. Global, galactic-scale simulations usually do not require the implementation of complicated reaction networks. However, the presence of dust can significantly affect the chemical evolution. It is in fact well known that a large fraction of some chemical elements (particularly Fe, Co, Ni, Ca, C and Si) is locked into dust grains . Clearly, it is impossible to have a complete picture of the evolution of these chemical elements in the ISM without considering the dust. There have been several works about the chemical evolution of galaxies with dust [70, 348, 41, 214, 349]. It is more complicated to include dust into chemo-dynamical simulations of galaxies. On the one hand, still not much is known about the sources and composition of interstellar dust . On the other hand, the physics of the dust-gas coupling is still poorly known and typically assumed drag forces lead to numerical problems . In spite of these difficulties, progresses have been made and simulations of galaxies taking into account dust are becoming available [308, 141]. Clearly, this is a field where more needs to be done. Observations of dust in our own Galaxy and in external galaxies are becoming extremely accurate and the astronomical community is in dire need of detailed chemo-dynamical simulations of dusty gases in order to help interpreting the observations.