Delta is not the probability of finishing in the money as suggested in another answer, N(d2) is. The foot note mentions this. See Understanding N(d1) and N(d2): Risk-Adjusted Probabilities in the Black-Scholes Model by Lars Tyge Nielsen for a detailed explanation. If time and vol is low, $d1 \approx d2$ and delta will be closer to the risk-adjusted probability of the event that the option
will finish in the money, which is $P(S_T > X) = N(d2)$.
Actual moneyness in terms of spot is unaffected by time. The same strike $K$ will always have the same moneyness against spot. E.g. is $S=1$ and $K= 1.05$, moneyness will be $1.05/1-1 = 5 \%
\ OTMS$, where OTMS stand for out-the-money-spot. However, moneyness in terms of forward is affected by time, but does usually not make it more ATM either. Using covered interest rate parity and continuous compounding
$$fwd(s,ccy2,ccy1,t) = s*exp^{(ccy2-ccy1)*t}$$
one can see how the value of the forward depends on the relative size of the two interest rates (and time). For a 10y forward, the moneyness in terms of forward would be $\approx 14\% \ ITMF$ with $F_{10y} \approx 1.22$ and $K=1.05$ as above. So this is actually further from ATM than spot moneyness (and it flips the side from OTM to ITM).

I think Iain Clark is eluding to something similar to the effect of implied vol on delta. IVOL and time are very similar in that sense.
Here, only one of the two "forces" mentioned in the link really matters: The term
$$\frac{log(\frac{S}{K})}{\sigma\sqrt t}$$ in d1 converges to 0 as $t \rightarrow \infty$ (the larger vol, the quicker it converges).
When t is very small, you can see that "time and vol adjusted (log) moneyness" is playing a significant role. If t increases, the difference between S and K eventually becomes negligible.

Just as delta is an increasing function in vol, it also grows in time. The probability of ending up in the money can counterintuitively turn zero for large vol and time. This is because the higher σ, the more the global maximum of the probability density function (the mode) shifts towards the lower bound of the lognormal distribution.

Comparing a 1y 10D call vs a 10y 10D call, with same $\sigma = 10\%$, $r_{CCY1}=-1\%$ and $r_{CCY2}=1\%$ gives use as @q.t.f wrote a strike that is much farther from the forward for the long maturity option.
function GKMSpot(S, K,t,ccy1,ccy2,σ)
d1 = ( log(S/K) + ( ccy2 -ccy1 + 0.5*σ^2)*t ) / (σ*sqrt(t))
d2 = d1 - σ*sqrt(t)
c = S*exp(-ccy1*t)*N(d1)-K*exp(-ccy2*t)*N(d2)
delta = exp(-ccy1*t)*N(d1)
return c, round(delta*100,digits=2)
end
