Changes in PM2.5 emissions in China: An extended chain and nested refined laspeyres index decomposition analysis

2021 ◽  
Vol 294 ◽  
pp. 126248 ◽  
Author(s):  
Jiandong Chen ◽  
Ming Gao ◽  
Ding Li ◽  
Li Li ◽  
Malin Song ◽  
...  
2020 ◽  
Vol 08 (04) ◽  
pp. 2050020
Author(s):  
Shenning QU

As an analytical framework for studying the characteristics of changes in things and their action mechanisms, the decomposition analysis of greenhouse gas emissions has been increasingly used in environmental economics research. The author introduces several decomposition methods commonly used at present and compares them. The index decomposition analysis (IDA) of carbon emissions usually uses energy identities to express carbon emissions as the product of several factor indexes, and decomposes them according to different weight-determining methods to clarify the incremental share of each index, in which way it is possible to decompose the models that contain less factors, process time series data, and conduct cross-country comparisons. It mainly includes the Laspeyres index decomposition and the Divisia index decomposition. Among them, the LMDI I method has been widely used for its advantages such as generating no residuals and easy to use. The structural decomposition analysis (SDA) can be used to conduct a more systematic analysis, decompose models with more influencing factors, and analyze the impacts of various factors on emissions, but this method has higher requirements for data collection. The biggest difference between the SDA method and the IDA methods of carbon emissions is that the former is based on an input–output system, while the latter only needs to use sectors’ aggregate data.


2021 ◽  
Vol 27 (1) ◽  
Author(s):  
Marlon Salazar

A indústria é um dos setores da economia que mais consomem energia, sendo responsável por 32% do consumo final em 2019. Compreender como se comporta o consumo da indústria ao longo das décadas, decompondo a variação do consumo entre os efeitos atividade, estrutura e intensidade, através da decomposição de números índices, é de grande importância e é o objetivo principal deste trabalho. Este trabalho inova ao utilizar o método “Index Decomposition Analysis (IDA)” para os dados de consumo de energia industrial. Conclui-se que o efeito atividade é o principal responsável pelo aumento no consumo de energia, já que captura a participação do aumento da produção industrial sobre o consumo de energia. Por outro lado, o efeito intensidade cresce no período, o que indica que a indústria brasileira está se tornando menos eficiente no consumo de energia. Já o efeito estrutura contribui reduzindo o consumo no período estudado, o que indica que os setores energo intensivos perderam participação na produção industrial. Além disso, a partir da estimação da equação de demanda de energia utilizando como proxy do consumo o efeito atividade, constata-se que a elasticidade renda da demanda de energia foi de 1,57% no período, já que a elasticidade preço da demanda não é significante.


2020 ◽  
Vol 12 (8) ◽  
pp. 3185 ◽  
Author(s):  
Enkhjargal Enkhbat ◽  
Yong Geng ◽  
Xi Zhang ◽  
Huijuan Jiang ◽  
Jingyu Liu ◽  
...  

Ulaanbaatar, the capital city of Mongolia, is facing serious air pollution challenges—especially during the cold and long winter months—mainly due to fossil fuel combustion. This study investigates the socioeconomic drivers of the sulfur dioxide (SO2), nitrogen dioxide (NO2), and particulate matter (PM2.5) concentration changes in Ulaanbaatar between 2005 and 2015 by applying the index decomposition analysis (IDA) method. Five socio-economic driving forces are considered in the decomposition analysis. All the driving forces contributed to more air pollution concentration changes in 2015 than in 2005, despite the decreasing trends of decomposition results for the period of 2010–2015. In general, economic growth, pollution intensity, and energy intensity significantly contributed to the changes of air pollutant concentrations, while energy structure and population growth had marginal effects. Finally, appropriate policy recommendations are proposed to the local government so that they can initiate feasible policies to effectively reduce air pollution, protect human health, and respond to climate change in Ulaanbaatar.


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