With the rapid development of the world economy, the infrastructure of the nations is improving day by day. The transportation system is a backbone of infrastructure of any country. Transportation plays a vital role in environmental issues as well. For a country like China, municipal road plays an important role in the transportation system but the construction should be environmental friendly. The municipal road construction should be free from carbon emissions and the road should be of good quality to increase the efficiency of road transportation. The construction quality of the road is affected by the temperature, type of material, eco-friendly material, and material quality which makes the construction quality uncertain. The environmental issues are alarming. The natural resources are exploited in order to strengthen the infrastructure of any country. There is a need to find the ways to use eco-friendly material for infrastructure in all the developing nations. The traditional quality evaluation methods do not preprocess the construction quality data to keep track of the composition of environmental friendly material in the overall material. The collected dynamic monitoring data of municipal road construction quality are sparse and the key data is not accurate to evaluate the material and its consequences on the environment. Now is the time to pay attention to the environmental issues before any economic and social progress. The evaluation method of municipal road construction quality based on an improved genetic algorithm (GA) is proposed in this paper by considering carbon emissions to keep the environment free from pollution. In the process of quality evaluation of load, a spanning tree constraint method is also introduced to form a related constraint relationship. The improved GA is used to calculate municipal road construction flow parameters to ensure the optimal evaluation results. Experimental results show that the evaluation method is accurate and reliable and meets the requirement of the current era where environment issues are at priority.