Effects of population and affluence on CO₂ emissions

Abstract

We developed a stochastic version of the Impact ‫؍‬ Population⅐Affluence⅐Technology (IPAT) model to estimate the effects of population, affluence, and technology on national CO 2 emissions. Our results suggest that, for population, there are diseconomies of scale for the largest nations that are not consistent with the assumption of direct proportionality (loglinear effects) common to most previous research. In contrast, the effects of affluence on CO 2 emissions appear to reach a maximum at about $10,000 in per-capita gross domestic product and to decline at higher levels of affluence. These results confirm the general value of the IPAT model as a starting point for understanding the anthropogenic driving forces of global change and suggest that population and economic growth anticipated over the next decade will exacerbate greenhouse gas emissions.It is certain that the atmospheric concentrations of greenhouse gases (GHGs) are increasing (1, 2). These growing concentrations threaten to produce disruptive changes in global climate. There is widespread scientific agreement that the increased concentrations are the consequence of human activities around the globe. Among these anthropogenic factors, the principal ones (often called ''driving forces'') are (i) population, (ii) economic activity, (iii) technology, (iv) political and economic institutions, and (v) attitudes and beliefs (3). These forces usually are assumed to drive not just GHG emissions but all anthropogenic environmental change.Despite agreement about the list of forces that affect anthropogenic GHG emissions, we have little understanding of the relative importance of each driving force. Thus, our basic knowledge of the biosphere and our ability to choose appropriate policy responses will remain significantly incomplete until we better understand the human dimensions of the system (3-5). Our goals here are to suggest an approach for analyzing anthropogenic environmental changes and to apply that approach to anthropogenic emissions of the principal GHG: CO 2 .To organize our analysis, we adopted the Impact ϭ Population⅐Aff luence⅐Technology (IPAT) framework first proposed in the early 1970s (6) as part of an ongoing debate on the driving forces of environmental change (7-11). It still finds wide use as an orienting perspective (12-20). The framework incorporates key features of human dimensions of environmental change into a model as follows:where I is environmental impact, P is population, and A is affluence or economic activity per person. T is the environmental impact per unit of economic activity, which is determined by the technology used for the production of goods and services and by the social organization and culture that determine how the technology is mobilized. The model is simple, systematic, and robust: simple because it incorporates key anthropogenic driving forces with parsimony; systematic because it specifies the mathematical relationship between the driving forces and their impacts; and robust because it is applicable to a...

Global demographic trends and future carbon emissions

“…climate change | energy | integrated assessment | population | households S tatistical analyses of historical data suggest that population growth has been one driver of emissions growth over the past several decades (1)(2)(3) and that urbanization (2), aging (3), and changes in household size (2) can also affect energy use and emissions. Demographers expect major changes in these dimensions of populations over the coming decades (4).…”

Air pollution indicators in Brazil, Russia, India and China (BRIC) countries

“…According to the World Population Data Sheet (2015), in 2010 China had a population of 1,330.141.295 (1 st most populous country in the world), while Russia had a population of 139,390,205 (9 th most populous country in the world). Some scholars (Rohde, 1990;Lashof and Ahuja, 1990;Jenkinson et al, 1991;Dietz, 1997;Fearnside, 1997;Shine et al, 2005) consider the elevation of CO 2 levels in the atmosphere to be largely responsible for the intensification of the greenhouse effect. In historical terms, this elevation is attributed to the burning of fossil fuels (coal, oil, and natural gas) for power generation and, secondarily, to agricultural processes and the destruction of natural vegetation, such as forests (Andreae, 1991;Bodansky, 2001).…”

Modeling of Electricity Demand for Azerbaijan: Time-Varying Coefficient Cointegration Approach

“…STIRPAT is for Stochastic Impacts by Regression on Population, Affluence, and Technology. Please refer to [28,29] for a detailed information. Results from the ARDLBT method showed that income has a negative association with the electricity.…”