Humans are exposed to a myriad of chemicals throughout their lifespan, including industrial pollutants, food nutrients and contaminants, synthetic products in cosmetics among many others. With that, an increasing interest in the measurement of known and novel chemicals as well as their possible effect in human health is now taking place specially under the recently coined idea of exposomics. First conceptualized by Wild , the exposome has been defined by Miller and Jones 2 as "the cumulative measure of environmental influences and associated biological responses throughout the lifespan, including exposures from the environment, diet, behavior, and endogenous processes". When designing any small molecules "omics" such as exposomics or metabolomics, one of the first decisions is typically the choice between targeted and untargeted approaches. The first normally relies on the use of low-resolution instruments (such as quadrupoles or ion traps) and aims at providing quantitative data with increased sensitivity when compared to high-resolution instruments, usually relying on time-of-flight or orbitrap analyzers. These methods normally include tens to hundreds of compounds and are commonly used for confirming previous hypotheses. In exposomics, for example, these methods are used for large biomonitoring studies due to their capability to provide quantitative information for trace-level chemicals , ultimately providing policy markers with information for the science-topolicy interface regarding chemical exposure . Untargeted approaches, on the other hand, have the advantage of detecting, in principle, any compound at a given concentration that is able to be ionized and detected. For that reason, untargeted methodologies have gained momentum in the last years specially under the strategies termed suspect screening analysis (SSA) and non-targeted analysis (NTA), which enables for the screening of hundreds to thousands of (potentially novel and relevant) chemicals . In addition, untargeted data acquisition approaches can be used for the assessment of the "effects" part of the exposure, i.e., the possible impact on the levels of endogenous metabolites due to a particular exposure pattern via metabolomics strategies. When acquiring such type of data using an LC-MS or LC-HRMS set ups, different acquisition modes can be selected. For targeted analysis, multiple reaction monitoring (MRM) is the common choice, and it is based on the detection of usually two transitions (precursor/product ion pairs) for each analyte, allowing for high sensitivity and specificity. For untargeted data, on the other hand, data dependent acquisition (DDA) and data independent acquisition (DIA) are the most commonly used approaches. The first relies on the selection of the n most intense m/z detected at MS1 level to further selection and fragmentation (MS 2 acquisition), normally leading to good quality MS 2 spectra of a few of the detected features. DIA, on the other hand, has the capability to fragment virtually all detected signals, later performing spectra deconvolution in order to assign each fragment to the most likely precursor. As a result, the number of MS 2 spectra acquired is higher, leading to better possibil-ities of identification specially for features with lower intensity that would not be selected by DDA experiments. As a downside, deconvolution algorithms are not 100% accurate and MS 2 spectra become either more polluted (with miss assigned fragments) or less informative (with missing fragments assigned to a different precursor), which ultimately leads to worsened spectra matching. SWATH (sequential window acquisition of all theoretical fragments) is one type of DIA acquisition mode in which sequential ranges of precursor isolation windows are selected and fragmented, allowing for the acquisition of MS 2 data for virtually all ions detected at MS 1 level. Fiehn and Cajka (2016) reviewed targeted and untargeted metabolomics data in order to evaluate the possibility of having one method with good performance for both using high resolution mass spectrometry (HRMS). As future directions, the authors highlight the efforts needed towards the combination of targeted and untargeted metabolomics approaches via untargeted MS1 data acquisition and high-resolution MRM transitions for targeting multiple metabolites. More recently, Bird et al (2023) have introduced a new workflow based on orbitrap and/or TOF systems (SQUAD, Simultaneous Quantitation and Discovery Analysis) aiming at combining both targeted and untargeted with the main objective of finding the equilibrium between untargeted and targeted approaches in a single experiment. This paper describes, to the best of our knowledge, the first targeted/untargeted, single-injection LC-MS method for integrated exposomics and metabolomics, combining the advantages of both approaches, i.e., high sensitivity (targeted) and broad coverage and retrospective data analysis (untargeted). The use of the recently introduced Zeno technology, a linear ion trap stage prior to the TOF analyzer that allows for increased duty cycles of up to 90% , resulting in significant increases in sensitivity. In addition to presenting the results obtained for different xenobiotics in targeted mode (135 compounds) as well as the results for the analysis of standard references materials (SRM 1950 and SRM 1958), we also describe the method development process that is expected to support other researchers working in the field of small molecule omics.