Review of techniques, challenges, and gaps in the subsurface gas release knowledge base.

Underground pipelines serve as critical infrastructure for gas transmission, strategically buried for safety, environmental, and economic considerations. Despite their importance, operational challenges and external interferences can lead to underground gas leaks with potentially catastrophic consequences for both human safety and the environment. The presence of a protective soil bed introduces complexities in understanding subsurface transport phenomena and quantifying gas releases accurately. Herein, this review presents a systematic analysis of published research in the field of underground gas releases, with an emphasis on interdisciplinary approaches that connect the lithosphere and atmosphere. The analysis highlights the broad spectrum of employed methods, including theoretical models based on fundamental principles, empirical formulations derived from experimental data, and sophisticated computational tools. A clear fundamental understanding and computational analysis, and to a lesser extent experimental, have been established to describe the migration regime. In contrast, more empirical research has addressed the crater formation regime, though focus was given to the far-field modelling following the soil ejection rather than the transient phenomena leading to the formation of the crater. Additionally, this review touches upon practical and conceptual topics, such as detection and localization techniques, and flow regimes in other gaseous flows through soil and powder beds, putting into question the applicability of some presumed granulated concepts to the flowing behavior expected beyond migration. The research landscape predominantly focuses on investigating the influence of release parameters on the release phenomena only from the atmospheric or soil domain perspective. This work provides insights that aim to first transcend both domains and then bridge the three distinct flow regimes-migration, uplift, and crater formation-despite the limited acknowledgment of the necessity of addressing all regimes concurrently through a universal approach. This review serves as a valuable resource for engineers to develop innovative solutions for the management of risks associated with underground gas leaks.

A scalable approach using a gC3N4-covalent organic framework hybrid catalyst towards sustainable hydrogen production from seawater and wastewater.

The photocatalytic generation of H2 using covalent organic frameworks (COFs) is gaining more interest. While numerous reports have focused on the production of H2 from deionized water using COFs, the inability to produce H2 from industrial wastewater or seawater is a common limitation in many reported catalysts. Additionally, many of these reports lack a clear path to scale up the catalyst synthesis. In this study, we explore the prospect of hybridizing a COF with gC3N4 to create a robust photocatalyst for efficient H2 generation. This hybrid exhibits outstanding performance not only in deionized water, but also in wastewater, and simulated seawater. Furthermore, we explore the feasibility of the bulk-scale synthesis and successfully produce a 20 g hybrid catalyst in a single batch, and the synthesis method is scalable to achieve the commercial target. Remarkably, a maximum HER rate of 94 873 µmol g-1 h-1 and 109 125 µmol g-1 h-1 was obtained for the hybrid catalyst from industrial wastewater and simulated seawater, respectively. The performance of bulk-scale batches closely matches that of the small-scale ones. This research paves the way for the utilization of organic photocatalysts on a commercial scale, offering a promising solution for sustainable large-scale H2 production.

The impact of local fugitive particulate matter and emission inventories on air quality and health in dry and arid areas.

The arid and semi-arid regions are facing a huge brunt of fugitive Particulate Matter (fPM) pollution, usually ascribed to the natural dust generated at the regional level (>100 km). In this study, the contribution of locally generated fPM to air pollution and it's environmental risk were assessed at a typical dry-arid area in the Middle East (i.e., State of Qatar, 200 × 200 km2 domain) with the use of different emission and dispersion models. Four modelling scenarios were constructed to reflect standard practices (e.g., regional emission models and the World Health Organization's (WHO) Environmental Burden of Disease (EBD) method) and higher resolution calculations with emission models that were developed in past field campaigns. Emphasis was given to the effect on the WHO methodology beyond the typical emission estimates and ambient concentration levels. Eventually, the use of higher spatial resolution population and concentration data revealed fPM hot spots yielding up to 11.0 times higher short-term excess mortalities (an average increase of 1.8 times) compared to the baseline WHO methodology, where the whole population was exposed to a single average concentration. A difference that could be attributed to the improvement of the emission estimations for barren lands and traffic. For example, the estimated PM10 emission fluxes from barren lands, within the main metropolitan area, using the improved emissions model ranged from 0.05 to 42.0 µg m-2 s-1, which is considerably higher than the emissions predicted using just the literature models (0.03 to 2.0 µg m-2 s-1). Overall, the barren lands emissions accounted for more than 90% of the fPM emissions during the study period. Consequently, this study is one of the first to quantify the significance of locally induced fPM and highlight the need for dedicated field studies and improved emissions estimation tools.

Concept and demonstration of a fully coupled and dynamic exposure-response methodology for crowd evacuation numerical modelling in airborne-toxic environments.

Evacuation simulation plays an indispensable role when planning for emergencies and evaluating the consequences of disasters related to airborne toxics. Various attempts have been made to improve simulation of evacuation in toxic environments and to account for the varying concentration levels and the dynamic exposure. However, most studies neglect the reverse effect, how the exposure and dosage levels affect the physical and psychological state of an evacuee and consequently the evacuation path and process. In this work, a fully coupled exposure-response-evacuation and agent based algorithm is proposed, focusing on the H2S airborne toxic. Accordingly, the dynamically estimated exposure of the evacuee affects, non-linearly, the evacuation speed and thus the overall evacuation. This coupling is challenging and thus it depends on the available epidemiological and toxicological data. Nevertheless, the diversity and advantages of the algorithm is successfully demonstrated over three case studies including single- and multi-agent in straight-path and building evacuation scenarios. For example, the building evacuation time increased by more than 50% by inclusion of the aforementioned coupling. In conclusion, herein, a gap on the evacuation modelling is addressed by a fully coupled methodology that could be easily adapted by safety engineers and further improved by researchers as more data become available.

The spatial relationship between traffic-related air pollution and noise in two Danish cities: Implications for health-related studies.

Air pollution and noise originating from urban road traffic have been linked to the adverse health effects e.g. cardiovascular disease (CVD), although their generation and propagation mechanisms vary. We aimed to (i) develop a tool to model exposures to air pollution and noise using harmonized inputs based on similar geographical structure (ii) explore the relationship (using Spearman's rank correlation) of both pollutions at residential exposure level (iii) investigate the influence of traffic speed and Annual Average Daily Traffic (AADT) on air-noise relationship. The annual average (2005) air pollution (NOx, NO2, PM10, PM2.5) and noise levels (Lday, Leve, Lnight, Lden, LAeq,24h) are modelled at address locations in Copenhagen and Roskilde (N = 11,000 and 1500). The new AirGIS system together with the Operational Street Pollution Model (OSPM®) is used to produce air pollution estimates. Whereas, noise is estimated using Common Noise Assessment Methods in the EU (CNOSSOS-EU, hereafter CNOSSOS) with relatively coarser inputs (100 m CORINE land cover, simplified vehicle composition). In addition, noise estimates (Lday, Leve, Lnight) from CNOSSOS are also compared with noise estimates from Road Traffic Noise 1996 (RTN-96, one of the Nordic noise prediction standards). The overall air-noise correlation structure varied significantly in the range |rS| = 0.01-0.42, which was mainly affected by the background concentrations of air pollution as well as non-traffic emission sources. Moreover, neither AADT nor traffic speed showed substantial influence on the air-noise relationship. The noise levels estimated by CNOSSOS were substantially lower, and showed much lower variation than levels obtained by RTN-96. CNOSSOS, therefore, needs to be further evaluated using more detailed inputs (e.g. 10 m land cover polygons) to assess its feasibility for epidemiological noise exposure studies in Denmark. Lower to moderate air-noise correlations point towards significant potential to determine the independent health effects of air pollution and noise.

Micro-scale modelling of the urban wind speed for air pollution applications.

Modelling wind speeds in urban areas have many applications e.g. in relation to assessment of wind energy, modelling air pollution, and building design and engineering. Models for extrapolating the urban wind speed exist, but little attention has been paid to the influence of the upwind terrain and the foundations for the extrapolation schemes. To analyse the influence of the upwind terrain and the foundations for the extrapolation of the urban wind speed, measurements from six urban and non-urban stations were explored, and a model for the urban wind speed with and without upwind influence was developed and validated. The agreement between the wind directions at the stations is found to be good, and the influence of atmospheric stability, horizontal temperature gradients, land-sea breeze, temperature, global radiation and Monin-Obukhov Length is found to be small, although future work should explore if this is valid for other urban areas. Moreover, the model is found to perform reasonably well, but the upwind influence is overestimated. Areas of model improvement are thus identified. The upwind terrain thus influences the modelling of the urban wind speed to a large extent, and the fundamental assumptions for the extrapolation scheme are fulfilled for this specific case.

Source reconstruction of airborne toxics based on acute health effects information.

The intentional or accidental release of airborne toxics poses great risk to the public health. During these incidents, the greatest factor of uncertainty is related to the location and rate of released substance, therefore, an information of high importance for emergency preparedness and response plans. A novel computational algorithm is proposed to estimate, efficiently, the location and release rate of an airborne toxic substance source based on health effects observations; data that can be readily available, in a real accident, contrary to actual measurements. The algorithm is demonstrated by deploying a semi-empirical dispersion model and Monte Carlo sampling on a simplified scenario. Input data are collected at varying receptor points for toxics concentrations (C; standard approach) and two new types: toxic load (TL) and health effects (HE; four levels). Estimated source characteristics are compared with scenario values. The use of TL required the least number of receptor points to estimate the release rate, and demonstrated the highest probability (>90%). HE required more receptor points, than C, but with lesser deviations while probability was comparable, if not better. Finally, the algorithm assessed very accurately the source location when using C and TL with comparable confidence, but HE demonstrated significantly lower confidence.

Road traffic air and noise pollution exposure assessment - A review of tools and techniques.

Road traffic induces air and noise pollution in urban environments having negative impacts on human health. Thus, estimating exposure to road traffic air and noise pollution (hereafter, air and noise pollution) is important in order to improve the understanding of human health outcomes in epidemiological studies. The aims of this review are (i) to summarize current practices of modelling and exposure assessment techniques for road traffic air and noise pollution (ii) to highlight the potential of existing tools and techniques for their combined exposure assessment for air and noise together with associated challenges, research gaps and priorities. The study reviews literature about air and noise pollution from urban road traffic, including other relevant characteristics such as the employed dispersion models, Geographic Information System (GIS)-based tool, spatial scale of exposure assessment, study location, sample size, type of traffic data and building geometry information. Deterministic modelling is the most frequently used assessment technique for both air and noise pollution of short-term and long-term exposure. We observed a larger variety among air pollution models as compared to the applied noise models. Correlations between air and noise pollution vary significantly (0.05-0.74) and are affected by several parameters such as traffic attributes, building attributes and meteorology etc. Buildings act as screens for the dispersion of pollution, but the reduction effect is much larger for noise than for air pollution. While, meteorology has a greater influence on air pollution levels as compared to noise, although also important for noise pollution. There is a significant potential for developing a standard tool to assess combined exposure of traffic related air and noise pollution to facilitate health related studies. GIS, due to its geographic nature, is well established and has a significant capability to simultaneously address both exposures.

Experimental and numerical study of liquefied natural gas (LNG) pool spreading and vaporization on water.

The investigation of pool spreading and vaporization phenomenon is an essential part of consequence analysis to determine the severity of LNG spills on water. In this study, release of LNG on water during marine operations is studied through experimental and numerical methods The study involves emulation of an LNG leak from transfer arms during side by side loading operations. The experimental part involves flow of LNG in a narrow trench filled with water and subsequent measurement of pool spreading and vaporization parameters. The numerical part involves CFD simulation using a three dimensional hybrid homogenous Eulerian multiphase solver to model the pool spreading and vaporization phenomenon. In this method, LNG is modeled as dispersed phase droplets which can interact with continuous phases - water and air through interphase models. The numerical study also employs a novel user-defined routine for capturing the LNG vaporization process. The CFD solver was capable of capturing the salient features of LNG pool spreading and vaporization phenomena. It was observed from experiment and CFD simulation that wind influenced both pool spreading and vaporization phenomenon through entrainment and convection.