Asthma remains a significant global health burden, associated with high morbidity, mortality and widespread societal impact. Nitric oxide (NO), commonly measured as the fractional exhaled nitric oxide (FeNO), is a byproduct of type-2 inflammation in conducting airways. Although FeNO has been recognised as a valuable biomarker in the diagnosis and management of asthma, there is no established methodology for estimating NO production depth along the airways, which may provide valuable insights into asthma pathophysiology and its management. This thesis presents the development of such methodology with the following approach adopted: (i) Measurement of NO (and CO2) expirograms using a novel Rapid FeNO Device (RFD) and estimation of the personalised parameters of lung physiology using Computed Cardiopulmonography(CCP); (ii) Development of a Dead Space Pipes (DSP) model that incorporates measurements from the RFD and CCP to reconstruct simulated NO expirograms ('wallpaper'); (iii) Derivation of NO depth parameters by comparing the 'wallpaper' with measured NO profiles, reflecting depth and spread of NO production; (iv) Development of a quality control criteria to assess breath-by-breath data quality. Finally, a study with human volunteers demonstrated the repeatability and reliability of these NO depth parameters. The thesis subsequently presents preliminary clinical studies to demonstrate the application and potential of this methodology in clinical settings. Applying this methodology, I found that treatment-naïve individuals with asthma (TN group) had a more proximal NO depth production site, which was also more widely spread along the airways, compared with patients with more severe difficult-to-treat asthma receiving high-dose inhaled corticosteroid (ICS), referred to as the HD group. Further follow-up studies showed that the TN group initiating low-dose ICS had no change in NO depth parameters, while a subgroup of the HD group demonstrated a reduction in NO depth following anti-IL5/5R therapy. Furthermore, bronchodilator administration had no effect on the NO depth parameters. In addition, CCP is introduced as a tool for measuring lung inhomogeneity and providing personalised lung physiological parameters. Its application in two clinical studies in healthy volunteers with high type-2 biomarkers and patients with asthma is presented to demonstrate its sensitivity as an emerging lung function measurement. Additionally, the thesis includes a separate section providing an overview of published work on V̇/Q̇ distributions in severe COVID-19 patients, completed during the pandemic period when I was not able to conduct experimental work.