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Abstract Physical, Regulatory and Brand value risks due to climate change challenges are foreseen by businesses globally. This paper is oriented towards these challenges and prepared a comprehensive Greenhouse gases (GHG) footprint plan and identification of mitigation opportunities for ONGC, a fortune 500 and national oil company of India. Internationally recognized standards and guidelines like Greenhouse Gas Protocol, ISO-14064, and American Petroleum Institute compendium have been referred for quantifying carbon emissions in nearly real 400 + operation control facilities. The GHG inventory is based on Operational Control approach to identify the boundary for which emissions are to be quantified and two significant scopes of emissions viz Direct Emissions and Indirect Emissions are identified and quantified. The quantification concluded that GHG emission footprint for the year 2016–17 is in the range of 9 million tons of CO 2 equivalent. GHG emissions mainly account due to stationary combustion, fugitive emissions and wastewater treatment, which share the around 56% of total emissions. Another 24–26% of emissions are contributed due to flaring, processes by glycol dehydrator, acid gas removal units, and by electricity purchased from the grid. As a result, it has been found that ONGC emits 187 kg CO 2 e emissions per tonne throughput and also compared with its global peer organizations. At the organization level, "Key Industrial Sites" have been identified as contributing higher GHG emissions and accordingly key "hot-spots," a list of 15 GHG mitigation opportunities have been proposed in the paper. Two GHG mitigation initiatives based on solar energy and bioenergy application undertaken at ONGC has also been briefed on case studies. Highlights • Comprehensive carbon footprint plan and identification of mitigation opportunities for Oil and Natural Gas Corporation (ONGC), a fortune 500 and national oil company of India. • Guidelines like Greenhouse Gas Protocol, ISO-4064 and American Petroleum Institute compendium are referred for quantifying carbon emissions from direct and indirect sources. • Green policy, incentives and mandatory compliance. • CO2e emissions per tonne throughput and also compared with its peer global organisations. • Key hot-spots, with a list of 15 GHG mitigation opportunities. [ABSTRACT FROM AUTHOR]

In 2022, Saudi Arabia's anthropogenic greenhouse gas emissions amounted to 810 million tons of CO 2 e. The country has pledged to cut its emissions by 278 million tons of CO 2 e per year by 2030. This paper contributes a modeling view on the climate-related effects of various energy policies on the Saudi energy system. We use an energy system model designed to represent seven sectors in the Saudi economy. In addition to a baseline, which entails the continuation of current domestic policies, we look at a scenario that incorporates some of the plans announced by the Saudi government. We also examine the baseline scenario with a cap on total CO 2 emissions equal to those exhibited with the announced plans. The model then makes the necessary decisions to abate CO 2. We find that the energy system contributes 130 million tons of CO 2 e to the nationally determined contribution amount in 2030. Also, a non-prescriptive scenario that caps energy-system CO 2 emissions produces the same emissions reductions as the announced plans while lowering the present cost by 2030 by $70 billion. The corresponding implicit marginal abatement cost of CO 2 approaches 35 $/tonCO 2 by 2045. This cost would displace around half of crude and fuel oil use in the Saudi energy system. • Saudi Arabia plans to cut annual greenhouse gas emissions by 278 million tonsCO 2 e. • We use a multi-sector model built from the ground up for Saudi Arabia. • The energy system can contribute 130 million tons of CO 2 e in reductions in 2030. • We find a scenario that achieves GHG abatement at a lower cost than official plans. • The marginal value attributed to CO 2 approaches 35 $ per tonCO 2 by 2045. [ABSTRACT FROM AUTHOR]

The industrial sector has significantly contributed to global climate change and urban air pollution while driving economic development. This paper takes the synergistic CO2 and SO2 emission reduction in China's industrial sector as an entry point quantifies the synergistic CO2 and SO2 emission reduction effect using the Kaya extension model and analyzes the synergistic emission reduction expansion mechanism in depth. It is found that the synergistic effect of CO2 and SO2 in the industrial sector is prevalent in most provinces in China. Every 10,000 tons of CO2 emission reduction leads to 1600 tons of SO2 emission reduction. Regional heterogeneity also clarifies that there are differences in synergistic emission reduction among different provinces, with most regions having a significant positive effect of synergistic emission reduction, while a small number of regions have an inverse effect, and direct SO2 reduction measures should be considered separately. The interaction effect analysis found that energy efficiency improvement in the industrial sector is the critical path to synergistic effect enhancement. At the same time, R&D expenditure and fixed asset investment have a weak effect on synergistic emission reduction. The interaction of the three factors can synergize the emission reduction effect by more than twice. The study's findings can be used as a reference for China's industrial sector to achieve the goal of reducing pollution and carbon emissions and for the practice of regional synergistic emission reduction, as well as for the formulation of international synergistic emission reduction policies. [ABSTRACT FROM AUTHOR]

Global warming, climate change, and resource depletion have forced us to reconsider energy usage and efficiencies over the last few decades. Residential and commercial buildings are both large energy consumers, so improving energy and material usage efficiency in this sector is a common research topic. According to a recent study, the Building Sector (BS) accounts for 40% of greenhouse gas emissions. The primary objective of this paper is to examine and assess the potential of Renewable Energy Systems (RES) and their combinations for enhancing energy efficiency in the BS. Specifically, the focus will be on converting low energy-efficient buildings into highly efficient ones. The potential of the RES and their combinations for the BS is evaluated based on payback durations, energy generation, and reduction of CO 2 emissions. The optimization flow charts for the RES, feasibility studies, commercialization road maps of energy storage systems and the necessity of control mechanisms for enhancing RES efficiency were discussed. Additionally, the technology drawbacks are discussed, along with various innovative techniques recommended to direct future study in this area. Finally, this article assists the audience clear idea in the selection of the right combination of potential RES based on different conditions to achieve deep decarbonization in BSs. • Buildings sector (BS) responsible for 40% of GHG emissions. • Study assesses potential of Renewable Energy System (RES) in BS. • RES evaluated on payback, energy generation, and CO 2 reduction. • Optimization, feasibility and commercialization studies were discussed. • Article recommends right RES combinations for deep decarbonization in BS. [ABSTRACT FROM AUTHOR]

Rising global temperatures in the Arabian Peninsula region caused by climate change have increased the demand for air conditioning, resulting in more electricity consumption and CO 2 emissions. This paper treats Qatar as a representative country for understanding the effect of future regional warming on the electricity demand and CO 2 emissions We first develop a model that relates daily electricity demand with temperature. By combining this model with temperature projections from the CMIP6 database (bias adjusted and statistically downscaled) and population and GDP projections from four shared socioeconomic pathways (SSPs), we can calculate Qatar's demand for electricity until the end of the century. The model identifies an average sensitivity of +4.2%/°C for the electricity demand and projects an increase in electricity demand by 5–35% due to warming alone at the end of this century. The model suggests that under SSP1-2.6, warming-induced CO 2 emissions could be offset by carbon intensity improvements. Furthermore, under SSP5-8.5, assuming no carbon intensity improvement, future warming could add 20–35% of CO 2 emissions per year by the end of the century, with half of the electricity demand related to more frequent hot days. We further found that the temperature effect on power demand and CO 2 emissions is small compared to the effects from socioeconomic factors such as population, GDP, and carbon intensity. • Data-based model to predict electricity demand from daily temperature regionally. • Projection of power demand with CMIP6 temperature projections for different SSPs. • Inclusion of the effect of the evolution of the population and the GDP on the demand. • Assumption on the evolution of the carbon intensity to deduce the CO 2 emissions. • Application to Middle East countries and implication for global temperatures. [ABSTRACT FROM AUTHOR]