(CN) – A mathematical model by researchers in China found that taxing carbon emissions would spur green development and energy sustainability without curtailing economic growth, according to a study released Wednesday.
The Intergovernmental Panel on Climate Change in 2018 recommended a 35% drop in methane emissions worldwide from 2010 levels to curb a 1.5 degrees Celsius rise in global temperatures.
In China – where 70% of the globe’s most polluted cities are found and where half of cities’ water sources are unsafe – curbing greenhouse gas emissions has been a particular challenge.
Pricing and taxing carbon emissions has been embraced by countries worldwide seeking to reduce greenhouse gas emissions and more efficient use of fossil fuel resources.
Researchers at Jiangsu University in Zhenjiang, China, said in a statement that their study utilizes mathematical modeling to examine the impact of environmental taxation on countries’ economic expansion.
Xinghua Fan and colleagues developed a mathematical model that could factor pollution emissions, economic growth over time in China and the nation’s use of resources, such as water and fossil fuels, in relation to a carbon tax.
Researchers call the interaction between all these variables the “green development dynamical system,” which also contemplates the impact of technological advancement and its impact on sustainability and self-recovery of environments.
The model was then applied to real-world data to examine the impact on China’s “green development.”
The study, published in the journal PLOS ONE, found that “green development” taxation, including carbon pricing, could stimulate economic growth in China while reducing emissions and curtailing overuse of energy resources.
“Firm government control” of taxing mechanisms and widespread awareness among China’s massive consumer base would also support the success of a carbon tax, the study said.
Researchers said in the statement that the model could be improved by factoring specific industries or sectors of the economy as opposed to entire countries or regions.
The study was supported by the National Natural Science Foundation of China and the Ministry of Education of China’s Humanistic and Social Science Foundation.