The development of low‐carbon transportation is growing rapidly, which plays an increasingly important functional role in economic growth and dealing with climate change. The transport carbon emissions in China between 1995 and 2014 using the Intergovernmental Panel on Climate Change emission‐factor approach are estimated in this research. This article analyzes the decoupling relationship between transport carbon emissions and economic growth in China and puts forward a decoupling volatility index to evaluate the stability of decoupling by applying Tapio's decoupling model which is composed of structure, technology, and scale decoupling elasticity. From the results, the relationships between transport carbon emissions and Gross Domestic Product (GDP), and transport carbon emission and its added value, appear to be complex characteristics of the stages and experience a process of weak decoupling. The relationship between added value of transportation and energy consumption intensity is relatively simple and experience a process of strong negative decoupling, while energy consumption intensity and GDP show a strong decoupling relationship. The four elastic decoupling fluctuation indices are large, which illustrate that the state of decoupling is not stable. Policies are made available to facilitate a better understanding of transportation structure, fuel type, and energy efficiency. Future research will focus on aspects of spatial analysis, formation mechanism, and driver factor analysis. © 2018 American Institute of Chemical Engineers Environ Prog, 37: 1696–1704, 2018

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Online food delivery (OFD) is one of the top industries in the Online-to-offline (O2O) commerce sector. Deliverymen need to complete a large number of delivery orders in limited default time every day, which cause high working stress to them. Therefore, a high level of traffic violations and crashes by deliverymen and corresponding negative impact on public safety are observed. To reduce traffic violations by deliverymen and resulting crashes, a hierarchical online food delivery framework is proposed, which is based on data from questionnaire surveys conducted in Xi'an City, China. The study includes the analysis of the root cause correlated with traffic violations during online food delivery as part of an empirical study on the priority delivery fee by applying a conditional price sensitivity measurement (PSM) model. The feasibility and rationality of the framework are further investigated by using cross analysis of urban dwellers' occupation, income, and commuting cost. The results identify that, through rationally shunting the demand of online food delivery, prolonging the default delivery duration, and providing diversified delivery services, the proposed hierarchical online food delivery mechanism is able to relieve the stress of deliverymen during peak hours of food requests. This reduces the willingness of deliverymen to engage in traffic violations, and other risky behaviors during food delivery trips. All of which facilitate high-quality and timely online food delivery service while enabling improved safety of deliverymen and others as part of enhanced public safety and health.