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This work concerns the general issue of combined optimality in terms of time and space complexity. In this context, we study the problem of counting resource-limited and passively mobile nodes in the model of population protocols, in which the space complexity is crucial. The counted nodes are memory-limited anonymous devices (called agents) communicating asynchronously in pairs (according to a fairness condition). Moreover, we assume that these agents are prone to failures so that they cannot be correctly initialized. This study considers two classical fairness conditions, and for each we investigate the issue of time optimality of (exact) counting given optimal space. First, with randomly interacting agents (probabilistic fairness), we present a ``non-guessing'' time optimal protocol of O(n log n) expected interactions given an optimal space of only one bit (for a population of size n). We prove the time optimality of such protocol. Then, under weak fairness (where every pair of agents interacts infinitely often), we show that a space optimal (semi-uniform) solution cannot converge faster than in Ω(2n) time, in terms of non-null transitions (i.e, the transitions that affect the states of the interacting agents). This result together with the time complexity analysis of an already known space optimal protocol shows that it is also optimal in time (given the optimal space constraints).