The renewed increase in atmospheric methane (CH₄) concentrations since 2007, culminating in record growth rates in 2021, poses a critical challenge to achieving global climate targets. The TROPOspheric Monitoring Instrument (TROPOMI) onboard the Sentinel-5 Precursor satellite provides unprecedented daily global observations of CH₄ at a spatial resolution (7 × 7 km², improved to 5.5 × 7 km² since August 2019), enabling substantial advances in space-based CH₄ monitoring and emission quantification. Here, we synthesize and categorize 133 published studies spanning global, regional and local scales and covering both anthropogenic and natural CH₄ sources. Collectively, these studies demonstrate TROPOMI's capability to quantify emissions across diverse spatiotemporal scales, as well as its synergy with other satellite instruments for detecting and attributing facility-level sources, such as fossil fuel infrastructure and landfills. However, emission estimates remain challenged by uncertainties in column-averaged CH4 (XCH₄) retrievals related to surface albedo effects and persistent cloud cover, particularly in tropical and high-latitude regions. These limitations can be mitigated through improved retrieval algorithms, refined quality filtering, multisatellite fusion, and integration with ground-based observations and airborne campaigns. Furthermore, we assess the suitability of different quantification approaches for specific source types, such as Gaussian plume models for large isolated emitters and inverse modeling for spatially diffuse emissions. Finally, we outline key methodological priorities and opportunities in the context of the recent MetOp-SG-A satellite, which will complement TROPOMI with a morning overpass. By consolidating current applications of TROPOMI XCH₄ observations, this review provides guidance for enhancing space-based methane monitoring and supports targeted mitigation strategies aligned with achieving Sustainable Development Goal 13.

We present a new divergence method to estimated methane (CH₄) emissions from satellite observed mean mixing ratio of methane (XCH₄) by deriving the regional enhancement of XCH₄ in the Planetary Boundary Layer (PBL). The applicability is proven by comparing the estimated emissions with its known emission inventory from a 3-month GEOS-Chem simulation. When applied to TROPOspheric Monitoring Instrument observations, sources from well-known oil/gas production areas, livestock farms and wetlands in Texas become clearly visible in the emission maps. The calculated yearly averaged total CH₄ emission over the Permian Basin is 3.06 (2.82, 3.78) Tg a⁻¹ for 2019, which is consistent with previous studies and double that of EDGAR v4.3.2 for 2012. Sensitivity tests on PBL heights, on the derived regional background and on wind speeds suggest our divergence method is quite robust. It is also a fast and simple method to estimate the CH₄ emissions globally.

Realistic microscopic traffic simulation is essential for prospective evaluation of the potential impacts of new traffic control strategies. Freeway corridors with interacting bottlenecks and dedicated lanes generate complex traffic flow phenomena and congestion patterns, which are difficult to reproduce with existing microscopic simulation models. This paper discusses two alternative driving behavior models that are capable of modeling freeways with multiple bottlenecks and dedicated lanes over an extended period with varying demand levels. The models have been calibrated using archived data from a complicated 13-mile long section of the northbound SR99 freeway near Sacramento, California, for an 8-hour time period in which the traffic fluctuated from free-flow to congested conditions. The corridor includes multiple bottlenecks, multiple entry and exit ramps, and an HOV lane. Calibration results show extremely good agreement between field data and model predictions. The models have been cross-validated and produced similar macroscopic traffic performance. The main behavior that should be captured for successful modeling of such a complex corridor includes the anticipative and cooperative driver behavior near merges, lane preference in presence of dedicated lanes, and variations in desired headway along the corridor.