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The strong increase of urban parcel delivery creates significant pressure on delivery enterprises. Nowadays, delivery enterprises do not only reduce operating costs, but also undertake a social responsibility: to reduce environmental costs caused by carbon emissions. This paper investigates the crowdsourcing framework to deliver urban parcels greenly by utilizing private cars that will be in passing. The bonus incentive strategy is introduced to improve the delivery willingness of private car drivers. Aiming at minimizing the sum of environmental costs caused by carbon emissions and enterprise costs, we establish a mixed-integer programming (MIP). To solve the problem, a hybrid genetic algorithm (GA) that combines adaptive large neighbourhood search (ALNS) and GA is proposed. The proposed approach is verified by standard instances. The results show that the green crowdsourcing framework with the participation of private cars will reduce the total costs. This approach has a great potential of reducing urban traffic growth and environmental pollution. Based on the real-word network in Dalian, the influences of the number of private cars, bonus incentive coefficient and time slack coefficient on the environmental costs and enterprise costs were investigated. Our research conclusion can provide a more reasonable decision-making basis of green urban parcel delivery for delivery enterprises. • Design a green crowdsourcing framework for urban parcel delivery. • Propose an incentive strategy to establish drivers' willingness function. • Construct a green crowdsourcing model considering carbon emissions. • Traffic growth and carbon emissions are reduced by the crowdsourcing framework. [ABSTRACT FROM AUTHOR]