IPAT Model Research Articles

A methodology to assess China's building energy savings at the national level: An IPAT–LMDI model approach

National building energy savings (NBES) plays an essential role in policymaking of China's building energy–efficiency (BEE) work. Numerous factors, such as technological progress and users' behavior, affect NBES while most of them are unquantifiable. One missing possibility along this direction is that there is currently no method to calculate China's NBES by summarizing all driving factors. To arrive at a solution, we proposed a concept of comparable building energy consumption per unit area and a method of China's NBES calculation based on an extended version of IPAT model (I = PAT, I = Human Impact, P = Population, A = Affluence, T = Technology) and LMDI decomposition (Logarithmic Mean Divisia Index, LMDI). Calculation revealed that China's NBES in “The 10th Five–Year Plan” period (2001–2005), “The 11th Five–Year Plan” period (2006–2010), and the first four years of “The 12th Five–Year Plan” period (2011–2014) was 165, 158, and 127 million tce, respectively. Based on these calculation results, we checked NBES data then successfully proved the validity of this calculation method. Furthermore, after comparing the calculated NBES with the official planned NBES, we found that China surpassed its BEE targets. In the third stage of China's BEE work (2006–2015), the implementation of BEE policies obtained good results.

Would Urban–Rural Income Gap Affect Carbon Dioxide Emissions? Empirical Research Based on the Extended IPAT Model

At present, there’s no agreement on how income gap affects carbon dioxide emissions. In this study, the author takes an empirical test of the relationship between income gap and carbon dioxide emissions based on the extended IPAT model, using China’s provincial panel data of from 2000 to 2012. The conclusion supports Boyce’s point of view that excessive income gap between urban and rural areas leads to environmental degradation. Meanwhile, the study introduces the cross terms of urban–rural income gap ratio and energy efficiency, and finds that excessive income gap would be an obstacle for China to achieve energy conservation and emission reduction by improving energy efficiency. Therefore, while promoting actions to climate change, energy conservation and emission reduction, governments should also narrow urban–rural income gap besides relying on the restrictions of relevant laws and regulations.

Does economic growth really reduce disaster damages? Index decomposition analysis for the relationship between disaster damages, urbanization and economic growth and its implications

ABSTRACTThis article aims to explore the characteristics of disaster damages in the context of economic growth and urbanization using index decomposition analysis. The key ideas of this study begin with two main research questions. First, does economic growth make any contribution to the reduction of disaster damages? Is the economic growth of a nation able to outweigh the respective disaster damages, particularly in advanced economies? Second, does urbanization tend to expand exposure to natural hazards and increase disaster damages? In this paper, a great deal of attention is paid to exploring answers to the above two questions using the case of Organization for Economic Cooperation and Development (OECD) countries. The main methodological concept starts with regarding disaster damages as one of various environmental impacts, which enables the proper application of the IPAT model. It is found that economic development contributed most to the decline of disaster damages and urbanization contributed slightly to the increase of disaster damages in OECD countries from 1990 to 2010.

How to Move China toward a Green-Energy Economy: From a Sector Perspective

With China’s rapid economic growth, energy-related CO2 emissions have experienced a dramatic increase. Quantification of energy-related CO2 emissions that occur in China is of serious concern for the policy makers to make efficient environmental policies without damaging the economic growth. Examining 33 productive sectors in China, this paper combined the extended “Kaya identity” and “IPAT model” with the Log-Mean Divisia Index Method (LMDI) to analyze the contribution of various factors driving of energy-related CO2 emissions in China during 1995–2009. Empirical results show that the main obstacle that hinders China’s transition to a green energy economy is the economic structure characterized by high carbon emissions. In contrast, the increased proportion of renewable energy sources (RES) and the improvement of energy efficiency play a more important role in reducing carbon emissions. Moreover, the power sector has a pivotal position in CO2 emissions reduction, primarily because of the expansion of electricity consumption. These findings suggest that policies and measures should be considered for various industrial sectors to maximize the energy efficiency potential. In addition, optimizing the industrial structure is more urgent than adjusting the energy structure for China.

Forecast of steel demand and the availability of depreciated steel scrap in China

Economic development has contributed to the rapid expansion of the Chinese iron and steel industry during the past two decades, which has resulted in numerous problems including increased energy consumption and excessive environmental pollution. Steel scrap as an important resource in the steelmaking process is attracting greater attention for its energy efficiency, low carbon emissions, and cyclic regeneration. This study examines changes in crude steel production, steel scrap consumption per ton steel, and steel scrap consumption from 1980 to 2012. A modified IPAT model, which can quantitatively and directly evaluate the influence level of environment, economy, population, technology and national policy on future steel production, is adopted to forecast Chinese steel production from 2010 to 2030. In 2020, the value of steel production and steel stocks per capita are expected to reach 901 million tons and 8.01 tons, respectively. Improved steel-scrap usage will decrease the demand on natural resources and lessen the overall environmental impact. According to steel production forecasts, the calculated scrap ratio will continue to increase from 2020 to 2030 in China, the value of which is expected to reach 0.366 by 2030. Otherwise, two major challenges expected to emerge within the next 20 years are discussed in detail. Finally, several policy suggestions are provided regarding the regulation of steel production and the integrated recycling scrap utilization.

Identifying the main contributors of air pollution in Beijing

Air pollution has become an emerging environmental issue in developing countries like China in the last two decades. Sulphur dioxide (SO2) is one of the major air pollutants that poses significant risks in many areas undergoing a process of industrialization such as Beijing. Realizing the main factor causing environmental quality changes is the key to solving this problem. By using an extended version of IPAT model, this paper aims to identify the main contributors of air pollution in Beijing from 1989 to 2012. The result shows that the most influential factors affecting air pollution in Beijing are affluence and emission intensity. From analyzing the historical background, we conclude that the air pollution change in Beijing is heavily policy-driven.

Forecasting China's Per Capita Carbon Emissions Under a New Three-Step Economic Development Strategy

Abstract: Under the context of the New Three-step strategy of Chinese economic development, we use the reverse tracing method and petroleum, natural gas and coal as sources of carbon emissions. To eliminate the impact of regional and technological levels in the energy conversion process we improved the IPAT model and used it to predict and analyze China's per capita carbon emissions in three assumed scenarios up to 2050. We found that China's per capita carbon emissions peak will occur respectively in 2020 and 2030 in different assumed scenarios; national per capita carbon emissions will reach 2.0127–2.6791 tons; China's per capita carbon emissions will grow continuously at an average rate of 2.25%–3.40% per year before the peak year and then will decline at a rate of 1.33%–1.78% per year. By the year of 2050, national per capita carbon emissions will be 1.3147–1.8817 tons.

Drivers of environmental impact: A proposal for nonlinear scenario designing

Drivers of environmental impact are commonly studied in the related literature through the IPAT and STIPAT models. The first is an accounting model and the second is a stochastic approach that enables both statistical tests of significance of the drivers and the consideration of a larger set of drivers. These methodologies, however, are unable to take account of the level of all drivers in a nonlinear structure, i.e., different impacts according to the level of the variable. This paper presents a global Ordered Logistic Model that estimates the probability of four ordinal categories of environmental impact (four defined categories of Ecological Footprint). The results further the analysis of environmental impact offering an additional understanding of what to expect in terms of environmental pressure when the current level of the drivers are changing. The study demonstrates the proposed methodology by offering some examples of scenario analysis based on the estimated model.

The Scenario Analysis of Low-Carbon Development on the Basis of Improved IPAT Model in China

It is an important strategic choice for countries to develop low-carbon economy while dealing with climate change. The paper gives a forecast and analysis on population, economic development, technology, energy consumption and CO2 emissions variation in China before 2020 as setting the year 2007 as the base year by using IPAT model. Three scenarios of CO2 emissions are set including business as usual (BAU), energy efficiency improvement scenario (EEI), and low carbon scenario (LC). The result shows that the LC scenario is the most appropriate and the most feasible scenario for China to achieve the low-carbon development in the future. Assuming that China’s future development follows the LC scenario, we give three suggestions of low-carbon transformation in China: technological innovation, energy structure optimization and policy advice.

Understanding Water Consumption and Demand in China

The impact factors of the water consumption changes from 1999 to 2002 and from 2002 to 2007 in China are studied with structural decomposition analysis(SDA) model.Firstly, we combine the classical IPAT model with consumer endogenous input-output local closed model, then decompose the impact factors of water consumption changes with the combined model.Secondly, we analyze the direct effect of final demand on water consumption changes. The main results are as follows: (1) At the structural level, the increase of the GDP per capita is the main factor of water consumption increase, the decrease of water use intensity is the main factor of water consumption decrease.(2)At the final demand level, the total final demand change is the main factor of water consumption change, whose effect exceeds water use intensity decrease and the change of technical level. Among the components of final demand, investment is the main factor of water consumption growth, which exceeds the effects of government consumption and net exports.

Long-term dynamics of household size and their environmental implications

Little is known about the environmental implications of long-term historical trends in household size. This paper presents the first historical assessment of global shifts in average household size based on a variety of datasets covering the period 1600–2000. Findings reveal that developed nations reached a threshold in 1893 when average household size began to drop rapidly from approximately 5.0 to 2.5. A similar threshold was reached in developing nations in 1987. With the notable exceptions of Ireland, and England and Wales in the early 1800s, and India and the Seychelles in the late 1900s, the number of households grew faster than population size in every country and every time period. These findings suggest accommodating housing may continue to pose one of the greatest environmental challenges of the twenty-first century because the impacts of increased housing present a threat to sustainability even when population growth slows. Future research addressing environmental impacts of declining household size could use an adapted IPAT model, I = PHoG: where environmental impact (I) = population × personal goods (P) + households × household goods (HoG).

The effect of ESCOs on carbon dioxide emissions

Proponents of energy service companies (ESCOs) argue that these firms provide a crucial instrument for delivering improved energy efficiency in public and private sectors, thus contributing to carbon dioxide (CO2) emission reduction around the world. Do ESCOs reduce CO2 emissions? To answer this question, we develop an estimating equation, which approximates the IPAT model, from a simple model of production. We estimate a dynamic panel of 129 countries over the period 1980–2007 to show that the ESCOs effectively reduce CO2 emissions and that this effect increases over time. These findings also prove robust to the inclusion of a set of control variables, different dates of the first ESCO and the Kyoto Protocol. Finally, we discuss energy policy implications.

Scenario Analysis and Path Selection of Low-Carbon Transformation in China Based on a Modified IPAT Model

This paper presents a forecast and analysis of population, economic development, energy consumption and CO2 emissions variation in China in the short- and long-term steps before 2020 with 2007 as the base year. The widely applied IPAT model, which is the basis for calculations, projections, and scenarios of greenhouse gases (GHGs) reformulated as the Kaya equation, is extended to analyze and predict the relations between human activities and the environment. Four scenarios of CO2 emissions are used including business as usual (BAU), energy efficiency improvement scenario (EEI), low carbon scenario (LC) and enhanced low carbon scenario (ELC). The results show that carbon intensity will be reduced by 40–45% as scheduled and economic growth rate will be 6% in China under LC scenario by 2020. The LC scenario, as the most appropriate and the most feasible scheme for China’s low-carbon development in the future, can maximize the harmonious development of economy, society, energy and environmental systems. Assuming China's development follows the LC scenario, the paper further gives four paths of low-carbon transformation in China: technological innovation, industrial structure optimization, energy structure optimization and policy guidance.

The optimal CO2 emissions reduction path in Jiangsu province: An expanded IPAT approach

This study aimed to determine the optimal CO2 reduction path for Jiangsu province to achieve the target of 40–45% reduction of CO2 emissions intensity by 2020 based on the 2005 level. Using the IPAT model combined with scenario analysis, we consider four parameters: economic growth, population growth, energy intensity and renewable-energy share. Each parameter is measured from different scenarios, and 54 kinds of scheme are set to forecast the CO2 emissions. The forecast results show that it is likely for Jiangsu province to achieve the target. Rapid economic growth is the main determinant that causes increase in CO2 emissions. Energy-intensity reduction and renewable-energy-share increase have beneficial influences on reducing CO2 emissions. The effect of energy-share increase is larger than that of energy-intensity reduction. As for the reduction of CO2 emissions intensity, energy-intensity reduction has a larger influence than renewable-energy-share increase. The optimal development mode until the year 2020 is as follows: the economy and population grow at appropriate rates, energy intensity reaches the level in developed countries, and the renewable-energy share increases to 15% in 2020.

The Scenario Analysis of Carbon Emissions Based on Improved IPAT Model in China

The coordination development of economy-energy-environment was discussed with traditional environmental loads model, combined with "decoupling" theory. Considering the possibilities of social and economic development, this paper set out three scenarios, and analyzed quantitatively the indexes, which affected carbon dioxide emissions, including population, per capita GDP, industrial structure and energy structure. Based on this, it forecasted carbon dioxide emissions in China in future. By comparing the prediction results, it held that policy scenario was the more realistic scenario, what’s more it can achieve emission reduction targets with the premise of meeting the social and economic development goals. At last, it put forward suggestions to implement successfully policy scenario, from energy structure, industrial structure, low-carbon technology and so on.

Greenhouse gas emissions and the role of the Kyoto Protocol

Our study empirically investigates the effects of the Kyoto Protocol’s quantified emission limitation or reduction commitments on various greenhouse gas (GHG) emissions such as CO2, CH4, N2O and other greenhouse gases, consisting of HFCs, PFCs and SF6. These GHG emissions are considered to be the main source of global warming issues and 39 countries approved to meet the commitments by ratifying the Kyoto Protocol. Our empirical analysis is based on the STIRPAT model, the stochastic version of the IPAT model, using the data of 119 countries in 1990, 1995, 2000 and 2005. Our main findings are that the effects of the commitments to the Kyoto Protocol (1) are significantly negative for the cases of CO2 and CH4 emissions, (2) are not significant for the case of N 2O emissions and (3) are significantly positive for the case of other greenhouse gas emissions. These results have important policy implications for global warming issues.

The effect of ESCOs on energy use

Energy saving can importantly help prevent greenhouse gas emissions and, thus, climate change. Energy service companies (ESCOs) provide a crucial instrument for delivering improved energy efficiency and potentially contributing to substantial energy savings in the public and private sectors. This paper investigates empirically the effect of ESCO activities on energy use. Based on a dynamic IPAT model, using a panel data of 94 countries over the period 1981 to 2007, we provide significant evidence that ESCOs reduce energy use. This finding proves robust to different dates of the first ESCO. The negative ESCO effect increases over time. The dynamic adjustment process produces small effects in the short run, but large effects in the long run. Moreover, the long-run ESCO effect differs across the stages of development. That is, for the high- and low-income countries, the short-run ESCO effect remains negative, but the long-run effects differ, remaining negative in high-income countries, but becoming positive in low-income countries. Finally, we discuss energy policy implications.

The Effect of ESCOs on Carbon Dioxide Emissions

Proponents of energy service companies (ESCOs) argue that these firms provide a crucial instrument for delivering improved energy efficiency in public and private sectors, thus contributing to carbon dioxide (CO2) emissions reduction around the world. Do ESCOs reduce CO2 emissions? To answer this question, we develop an estimating equation, which approximates the IPAT model, from a simple model of production. Based on the modified dynamic IPAT model, using the panel data of 129 countries over the period 1980 to 2007, we provide significant evidence to show that the ESCOs effectively reduce CO2 emissions and this effect increases over time. These findings also prove robust to the inclusion of a set of control variables, different dates of the first ESCO, and the Kyoto Protocol. Finally, we discuss energy policy implications.

The Effect of ESCOs on Energy Use

Energy saving can importantly help prevent greenhouse gas emissions and, thus, climate change. Energy service companies (ESCOs) provide a crucial instrument for delivering improved energy efficiency and potentially contributing to substantial energy savings in the public and private sectors. This paper investigates empirically the effect of ESCO activities on energy use. Based on a dynamic IPAT model, using a panel data of 94 countries over the period 1981 to 2007, we provide significant evidence that ESCOs reduce energy use. This finding proves robust to different dates of the first ESCO. The negative ESCO effect increases over time. The dynamic adjustment process produces small effects in the short run, but large effects in the long run. Moreover, the long-run ESCO effect differs across the stages of development. That is, for the high- and low-income countries, the short-run ESCO effect remains negative, but the long-run effects differ, remaining negative in high-income countries, but becoming positive in low-income countries. Finally, we discuss energy policy implications.

Green economy: scenari di sviluppo, competitività e occupazione nel campo dell'efficienza energetica

In this paper we argue that a rise in energy efficiency can help in improving both economic and environmental scenarios. We estimate the impact of energy efficiency on economy, looking at employment and polluting emissions. To show this, we assess the analytical utility of the IPAT and ImPACT models presenting here a new developed identity named Augmented ImPACT.