Optimal production with carbon trading market in China

Abstract

As a significant carbon dioxide-emitting country globally, China has set a concrete short-term target of carbon dioxide
emissions peak in 2030 and an ambitious long-term plan to reach carbon neutrality by 2060. One essential policy is to
set up a carbon trading market to reduce high-pollution enterprises’ carbon emissions by rationally allocating carbon
quotas among different firms and regions and setting carbon quotas trading market.
In reality, firms obtain carbon quotas in three ways, initial allocation from the government, carbon market trading, and
purification. By using carbon quotas, firms are required to meet the limitation of carbon emissions by regulations. To
help firms make the cost-optimal decision in both short-term and long-term management, this paper focuses on the
impact and trading of carbon quota for emission-depending firms.
The short-term optimal production model suits firms less than a year from meeting emission limitation requirements. It
is considered that during this time, firms cannot upgrade production equipment with less carbon emission but can only
sell or buy carbon quotas in the carbon trading market. Furthermore, this paper builds a carbon quota price predicting
model based on the long-short-term memory neural networks(LSTM) method to help firms develop a better trading
strategy. In the long term, firms can update their technique to less carbon-emitting production technology. Therefore,
a long-term optimal production model is established, and variable purifying levels are discussed. Finally, this paper
calculates the optimal production strategy under different restraints of carbon emission.