Data Analysis Of Pm_2.5 And Study On Green Economic Efficiency Of Cities In China Based On Python

Dust particles in the fog and haze（PM）are extremely harmful to society and individuals,of which PM_2.5 is the most serious.Taking Beijing city as an example,the use of Python programming language on the air pollution data of 2014-2016 are analyzed,to explore the geographical distribution of PM_2.5 concentration in Beijing City,changing with time and the proportion of PM_2.5 accounted for PM₁₀.In order to reduce the pollution of PM_2.5 in the country,it is important to change the extensive mode of economic development as a model for sustainable development.The evaluation method of economic development must be transformed from the traditional mode to the mode of green economy,and PM_2.5 will be included in the assessment of local issues related to people’s livelihood together,so as to realize the comprehensive coordinated sustainable development of social-economy-environment.Efficiency considering the environmental costs of economic development,and even the people’s welfare is called green economic efficiency.Based on Data Envelopment Analysis（DEA）evaluation method in operational research,this paper evaluates the relative green economic efficiency of cities in China.The classical DEA model calculating efficiency of DEA according to the given data,and each decision making unit（DMU）always selecting the optimal combination of weights,what lead to the decision making unit efficiency evaluating in different conditions.In order to solve this problem,the paper introduces the appropriate weight lower bound condition into the traditional DEA model after the standardization of data,and applies the DEA cross efficiency model evaluation method.Coding Python program to solve the DEA problem.This paper collects the data of economy and people’s livelihood of each city in 2015,taking the annual average concentration of PM_2.5 as an indicator,to evaluate the relative green economic efficiency of 270 cities in China using the DEA method,and to calculate the green economy coefficient using the evaluation method of DEA cross efficiency model.