Multi-scale social metabolism of China: An extended MuSIASEM analysis of energy, economy, and human activity

Rapid economic growth, expanding populations and increasing prosperity are driving up demand for energy, water and food, especially in developing countries. To understand the energy consumption of a country, we used the Multi-Scale Integrated Analysis of Societal and Ecosystem Metabolism (MuSIASEM) approach. The MuSIASEM is an innovative approach to accounting that integrates quantitative information generated by distinct types of conventional models based on different dimensions and scales of analysis. The main objective of this work is to enrich the MuSIASEM approach with information from multivariate methods in order to improve the efficiency of existing models of sustainability. The Biplot method permits the joint plotting, in a reduced dimension of the rows (individuals) and columns (variables) of a multivariate data matrix. We found, in the case study of Ecuador, that the highest values of the Exosomatic Metabolic Rate (EMR) per economic sector and Economic Labor Productivity (ELP) are located in the Productive Sector (PS). We conclude that the combination of the MuSIASEM variables with the HJ-Biplot allows us to easily know the detailed behavior of the labor productivity and energy consumption of a country.

Multiscale integrated analysis of societal and ecosystem metabolism of Qatar

Due to rapid urban development and increasing population, urban areas are facing more challenges in the area of sustainable development. In order to make sure that these cities are moving toward sustainable development, it is very important to highlight the human activities as significant elements in terms of energy metabolism. This paper employed the Multi-Scale Integrated Analysis of Societal and Ecosystem Metabolism (MuSIASEM) approach to analyze the energy metabolic pattern of Qatar from ecological, social, and economic dimensions. MuSIASEM has been introduced for the first time late 90’s, and it is trying to answer the questions of how and why humans use resources? how this use depends on and affects the stability of the ecosystems embedding the society? Therefore, this study aimed to track and record level of energy sustainability in Qatar, describe and analyze the energy and GDP flow in Qatar using MuSIASEM. Energy consumption per capita in Qatar reached 17,418 kg of oil equivalent in 2014, while the rate in US is 6793 kg of oil equivalent. That makes Qatar one of the biggest energy consumer around the world, and that's has negative impacts on our society e.g., CO2 emissions per Capita in Qatar reached 37.78 metric tons in 2013. A case study of Qatar was considered instead of the capital and largest city (Doha) because all the urban areas and human activities in Qatar are connected with Doha, especially with the small area of Qatar 11,627 km2. Thus, Qatar is the suitable study's area compared with the mega cities around the world. In addition, all the previous studies which used MuSIASEM as methodology focused on countries which import energy, but Qatar exports and produces energy, and that makes the study unique and valuable. The study investigated historical pattern changes of human activities in Qatar with focusing on working hours in line with Gross Domestic Product, then evaluated the possible results, so that the detailed metabolic patterns can be identified and appropriate development policies can be prepared to help decision makers with the implementation of Qatar Vision 2030 which consider sustainable development as fundamental pillar. The results investigated the correlation and interactions between Gross Domestic Product, added value, human activities, energy consumption, energy intensity, exosmotic energy metabolism, and future economic transition in Qatar. To make the results systematic and organized, it have been subdivided hierarchy into three levels: Level n studied The whole society of Qatar, Level n-1 studied both of consumptive sector (hose hold) and productive sector (work sector), Level n-2 focused on the subdivisions of work sectors and house hold typologies. Speaking of data resources, the economic and social data of study have been provided by Ministry of Statistics and Development Planning, While the electrical data has been provided by Qatar General Electricity and Water Corporation (KAHRAMA). World Bank, and International Energy Agency (IEA) provided all the date related to energy consumption. Other data like human time, energy intensity, and exosmotic metabolic rate have been calculated through some equations which will be explained in the study.

Going beyond energy intensity to understand the energy metabolism of nations: The case of Argentina

Variations of energy intensities and potential for improvements in energy utilisation on conventional and organic Norwegian dairy farms

Changes of human time and land use pattern in one mega city's urban metabolism: a multi-scale integrated analysis of Shanghai

Multi-scale integrated assessment of soybean biodiesel in Brazil

Rebound effect of energy intensity reduction on energy consumption

Generating better energy indicators: Addressing the existence of multiple scales and multiple dimensions

Energy intensity, target level of energy intensity, and room for improvement in energy intensity: An application to the study of regions in the EU

Low-carbon production of iron and steel: Technology options, economic assessment, and policy

Factors and actions for the sustainability of the residential sector. The nexus of energy, materials, space, and time use

This study aims to examine the effect of urbanization on energy intensity in SAARC countries and compare Sri Lanka’s status with other SAARC countries between 1990 and 2015. This study used the urban population as a proxy variable for urbanization. Other control variables in the model are per capita income and squared value of per capita income (PCI), capital formation, industrialization, labour and carbon dioxide emissions, squared value of carbon dioxide emissions and six country dummy variables to detect country effect. Fixed effects model and Least Squared Dummy Variable model (LSDV) with country-urbanization interactive variables model were employed in the estimation. Our results indicate urbanization in the SAARC region increases energy intensity in all countries except Sri Lanka. With urbanization, Pakistan has the fastest increase in energy intensity. Our results confirm Environmental Kuznets Curve (EKC) hypothesis which is consistent with the literature. Industrialization and labour force participation lower energy intensity. Carbon dioxide emission and the squared value of that variable show a U-shaped behaviour with energy intensity. This implies higher energy use further increases energy intensity and needs mitigating policies to curb higher energy use. According to the results, Pakistan has the lowest energy intensity and Sri Lanka has higher energy intensity among SAARC countries. Sri Lanka needs to lower the energy intensity by reducing inefficient energy use in all possible sectors such as transportation. Since urbanization significantly reduces energy intensity in Sri Lanka, efficient public transportation coupled with planned urbanization will help to lower our energy intensity in the long run.

Urban metabolism of megacities: A comparative analysis of Shanghai, Tokyo, London and Paris to inform low carbon and sustainable development pathways

Analogy between Sudoku and the multi-scale integrated analysis of societal metabolism