  Dark Energy Spectroscopic Instrument (DESI) uses more than 2.4 million
Emission Line Galaxies (ELGs) for 3D large-scale structure (LSS) analyses in
its Data Release 1 (DR1). Such large statistics enable thorough research on
systematic uncertainties. In this study, we focus on spectroscopic systematics
of ELGs. The redshift success rate ($f_{\rm goodz}$) is the relative fraction
of secure redshifts among all measurements. It depends on observing conditions,
thus introduces non-cosmological variations to the LSS. We, therefore, develop
the redshift failure weight ($w_{\rm zfail}$) and a per-fibre correction
($\eta_{\rm zfail}$) to mitigate these dependences. They have minor influences
on the galaxy clustering. For ELGs with a secure redshift, there are two
subtypes of systematics: 1) catastrophics (large) that only occur in a few
samples; 2) redshift uncertainty (small) that exists for all samples. The
catastrophics represent 0.26\% of the total DR1 ELGs, composed of the confusion
between O\,\textsc{ii} and sky residuals, double objects, total catastrophics
and others. We simulate the realistic 0.26\% catastrophics of DR1 ELGs, the
hypothetical 1\% catastrophics, and the truncation of the contaminated
$1.31<z<1.33$ in the \textsc{AbacusSummit} ELG mocks. Their $P_\ell$ show
non-negligible bias from the uncontaminated mocks. But their influences on the
redshift space distortions (RSD) parameters are smaller than $0.2\sigma$. The
redshift uncertainty of \Yone ELGs is 8.5 km/s with a Lorentzian profile. The
code for implementing the catastrophics and redshift uncertainty on mocks can
be found in https://github.com/Jiaxi-Yu/modelling_spectro_sys.
