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能源、农业、宏观经济及人为因素指标对环境污染的影响:来自加纳的证据。

The impact of energy, agriculture, macroeconomic and human-induced indicators on environmental pollution: evidence from Ghana.

作者信息

Asumadu-Sarkodie Samuel, Owusu Phebe Asantewaa

机构信息

Sustainable Environment and Energy Systems, Middle East Technical University, Northern Cyprus Campus, Guzelyurt, Turkey.

出版信息

Environ Sci Pollut Res Int. 2017 Mar;24(7):6622-6633. doi: 10.1007/s11356-016-8321-6. Epub 2017 Jan 12.

Abstract

In this study, the impact of energy, agriculture, macroeconomic and human-induced indicators on environmental pollution from 1971 to 2011 is investigated using the statistically inspired modification of partial least squares (SIMPLS) regression model. There was evidence of a linear relationship between energy, agriculture, macroeconomic and human-induced indicators and carbon dioxide emissions. Evidence from the SIMPLS regression shows that a 1% increase in crop production index will reduce carbon dioxide emissions by 0.71%. Economic growth increased by 1% will reduce carbon dioxide emissions by 0.46%, which means that an increase in Ghana's economic growth may lead to a reduction in environmental pollution. The increase in electricity production from hydroelectric sources by 1% will reduce carbon dioxide emissions by 0.30%; thus, increasing renewable energy sources in Ghana's energy portfolio will help mitigate carbon dioxide emissions. Increasing enteric emissions by 1% will increase carbon dioxide emissions by 4.22%, and a 1% increase in the nitrogen content of manure management will increase carbon dioxide emissions by 6.69%. The SIMPLS regression forecasting exhibited a 5% MAPE from the prediction of carbon dioxide emissions.

摘要

在本研究中,使用偏最小二乘(SIMPLS)回归模型的统计启发式修正方法,研究了1971年至2011年期间能源、农业、宏观经济和人为因素指标对环境污染的影响。有证据表明能源、农业、宏观经济和人为因素指标与二氧化碳排放之间存在线性关系。SIMPLS回归的证据表明,作物生产指数每增加1%,二氧化碳排放量将减少0.71%。经济增长每增加1%,二氧化碳排放量将减少0.46%,这意味着加纳经济增长的增加可能导致环境污染的减少。水力发电产生的电力每增加1%,二氧化碳排放量将减少0.30%;因此,增加加纳能源组合中的可再生能源将有助于减少二氧化碳排放。肠道排放每增加1%,二氧化碳排放量将增加4.22%,粪便管理中的氮含量每增加1%,二氧化碳排放量将增加6.69%。SIMPLS回归预测在二氧化碳排放预测中表现出5%的平均绝对百分比误差(MAPE)。

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