相关论文: Second-generation stoichiometric mathematical mode…

Bitumen extraction for the production of synthetic crude oil in Canada's Athabasca Oil Sands industry has recently come under spotlight for being a significant source of greenhouse gas emission. A major cause of concern is methane, a…

Methane (CH4) is the second most critical greenhouse gas after carbon dioxide, contributing to 16-25% of the observed atmospheric warming. Wetlands are the primary natural source of methane emissions globally. However, wetland methane…

Methane (CH4) emissions estimates from top-down studies over oil and gas basins have revealed systematic under-estimation of CH4 emissions in current national inventories. Sparse but extremely large amounts of CH4 from oil and gas…

The CH4 Livestock Emission (CH4rLiE) project explores the development of a prototype system for capturing methane emissions in barn environments, offering an alternative approach to mitigating greenhouse gas emissions from livestock…

Methane ($CH_4$) is a potent anthropogenic greenhouse gas, contributing 86 times more to global warming than Carbon Dioxide ($CO_2$) over 20 years, and it also acts as an air pollutant. Given its high radiative forcing potential and…

Methane (CH4) is a potent greenhouse gas, and its detection and quantification are crucial for mitigating the greenhouse effect. This study presents a comparative analysis of methane emissions observed using near-simultaneous observations…

We use satellite observations of atmospheric methane from the TROPOMI instrument to estimate total annual methane emissions for 2019-2023 from four large Southeast US landfills with gas collection and control systems. The emissions are on…

Monitoring the abundance of greenhouse gases (GHGs) such as carbon dioxide (CO$_2$) and methane (CH$_4$) is necessary to quantify their impact on global warming and climate change. Although a number of satellites and ground-based networks…

Methane (CH4) is a primarily biogenic greenhouse gas. As such, it represents an essential biosignature to search for life on exoplanets. Atmospheric CH4 abundance on Earth-like inhabited exoplanets is likely controlled by marine biogenic…

The environmental impacts of global warming driven by methane (CH4) emissions have catalyzed significant research initiatives in developing novel technologies that enable proactive and rapid detection of CH4. Several data-driven machine…

Bitumen residues in the oil sand tailings can be a threat to the environment that separating them from tailings before disposal is crucial. However, low bitumen concentration in the tailings slurry and the complex transport characteristics…

Methane emissions from oil and gas (O&G) production and transmission represent a significant contribution to climate change. These emissions comprise sporadic releases of large amounts of methane during maintenance operations or equipment…

Cement production is among the largest contributors to industrial air pollution, emitting ~3 Mt NOx/year. The industry-standard mitigation approach, selective non-catalytic reduction (SNCR), exhibits low NH3 utilization efficiency,…

Methane (CH$_4$) is the second most powerful greenhouse gas after carbon dioxide and plays a crucial role in climate change due to its high global warming potential. Accurately modeling CH$_4$ fluxes across the globe and at fine temporal…

The United Nations Environmental Program's (UNEP) Emissions Gap Report, 2023, Temperatures hit new highs, yet world fails to cut emissions (again)'', and in 2024, No more hot air, emissions' massive gap between rhetoric and reality''. A…

Ecological processes depend on the flow and balance of essential elements such as carbon (C) and phosphorus (P), and changes in these elements can cause adverse effects to ecosystems. The theory of Ecological Stoichiometry offers a…

This paper introduces the Oilfield Pollutant Graphical Model (OPGM), an innovative approach designed to improve the benchmarking and uncertainty analysis of greenhouse gas (GHG) emissions in oilfields. Building on the robust foundation…

Stochastic precipitation generators (SPGs) are a class of statistical models which generate synthetic data that can simulate dry and wet rainfall stretches for long durations. Generated precipitation time series data are used in climate…

This research introduces a new ML framework designed to enhance the robustness of out-of-sample hydrocarbon production forecasting, specifically addressing multivariate time series analysis. The proposed methodology integrates Productivity…

As of 2022, greenhouse gases (GHG) emissions reporting and auditing are not yet compulsory for all companies and methodologies of measurement and estimation are not unified. We propose a machine learning-based model to estimate scope 1 and…