To implement the goal of carbon peak and carbon neutralization, all provinces and cities in China should achieve the goal of carbon peak as scheduled, which maintain economic growth and ensure the realization of the goal of modernization in 2035. The realization path is the low-carbon green transformation, but the situation of provinces, cities and regions in China is different. Can we achieve carbon peak at the same time? Therefore, it is of great significance to study the difference of regional carbon emission intensity for realizing the carbon peak of provinces and cities in 2030. According to the provisions of the National Development and Reform Commission, the four cities of Jinan, Qingdao, Yantai and Weifang are approved low-carbon pilot cities. In order to study the contribution to the difference of carbon emission intensity of every factor between low-carbon cities and non-low carbon cities, the paper chose the panel data of 17 prefecture-level cities in Shandong Province from 2007 to 2016 by the Oaxaca-Blinder decomposition method to investigate the difference of carbon emission intensity between them. We have concluded that they are important influence factors on carbon emission intensity in per capita GDP, industrial structure, urbanization level and energy consumption intensity. The improvement of urbanization rate and energy consumption intensity makes the carbon emission intensity increase; the decrease of the proportion of secondary industry in low-carbon cities is beneficial to the reduction of carbon emission intensity, but it is opposite to the carbon emission in non-low carbon cities. By the O-B decomposition method, we can conclude that the energy consumption intensity has the greatest impact on the difference of carbon emission intensity between low-carbon cities and non-low carbon cities, and the urbanization rate has greater impact on the difference between them. The level of economic development and industrial structure will also have impact on the difference. The textual innovation lies in using the carbon productivity of low-carbon cities as the dependent variable, that is, the carbon emission intensity per unit GDP. At the same time, we select factors from the economic, energy and social indicators in the low-carbon city rating index system to reveal the contribution of different factors to the carbon emission intensity difference between low-carbon cities and non-low carbon cities. It is useful to develop non-low-carbon cities, decrease the gap between them, and speed up the transformation from low carbon cities to non-low carbon cities.