Construction and Application Analysis of Carbon Emission Influence Factor Model of Energy Consumption in Mining Industry

With the proposal of China’s “double carbon goal,” as a high energy-consuming industry, it is urgent for the mining industry to adopt a low-carbon development strategy. Therefore, in order to better provide reasonable suggestions and references for the low-carbon development of mining industry, referring to the methods and parameters of the 2006 IPCC National Greenhouse Gas Inventory Guidelines and China’s Provincial Greenhouse Gas Inventory Preparation Guidelines (Trial), a carbon emission estimation model is established to estimate the carbon emission of energy consumption of China's mining industry from 2000 to 2020. Then, using the extended Kaya identity, the influencing factors of carbon emission in mining industry are decomposed into energy carbon emission intensity, energy structure, energy intensity, industrial structure, and output value. On this basis, an LMDI model is constructed to analyze the impact of five factors on carbon emission from mining industry. The research shows that the carbon emission and carbon emission intensity of energy consumption in China’s mining industry first rise and then fall and then rise slightly. The carbon emission intensity in recent three years is about 2 tons/10000 yuan. The increase in output value is the main factor to increase carbon emission. The reduction in energy intensity is the initiative of carbon emission reduction. The current energy structure of mining industry is not conducive to carbon emission reduction.

Assessment of the applicability of methodological guidelines and guidelines for the quantitative determination of greenhouse gas emissions

The article deals with the problem of climate change. The aim of the study is to analyze and improve methodological recommendations for calculating greenhouse gas emissions. The urgency of reducing the volume of greenhouse gas emissions has been substantiated. Statistical data of emissions volumes are analyzed, the reason for the growth of emissions and the main contributors are determined. The main gases that give the greenhouse effect are identified, and their brief characteristics are given. The need to improve the monitoring and reporting system of greenhouse gas emissions at the global level has been substantiated. The goal of a perfect system for accounting and reporting of greenhouse gas emissions is to timely obtain relevant data for the systematic reduction of greenhouse gas emissions. The methodological tools for quantifying greenhouse gas emissions, approved by the Ministry of Natural Resources and Environment of Russia, are analyzed from the point of view of their applicability by organizations. Measures for their improvement are proposed, based on the international experience of building guidelines for the IPCC greenhouse gas inventory. The results obtained may be of interest to energy companies when developing corporate guidelines for quantifying greenhouse gas emissions.

Building Land Cover Objects Following the IPCC Guidelines for Carbon Emission Estimation. Case Study in the Central Highlands of Vietnam

We estimated the carbon emissions in the field of Land Use, Land Use Change, and Forestry (LULUCF) by using advanced technology to build the input data. Remote sensing, including satellite remote sensing and Unmanned Aerial Vehicles (UAV) with transparency, multi-time, and wide coverage characteristics, is useful in this area. The article focuses on the proposed regulations and building process of subjects in the land cover of the Vietnamese mainland following the guidance of the Intergovernmental Panel on Climate Change as applied to carbon emission estimation. We propose a process to estimate carbon emissions using the Agriculture and Land Use Greenhouse Gas Inventory software with input data extracted from the remote sensing images. An experiment on land cover change was carried out over ten years between 2006 and 2016 in the Central Highlands of Vietnam. The results obtained with remote sensing data classification for land cover categories achieved a reliability of 69% for the year 2006 and 66% for the year 2016. The carbon emission estimation data were checked and used in Vietnam’s biennial update report to the United Nations Framework Convention on Climate Change, including content and updated information on the greenhouse gas inventory.