Low-carbon pathways for the booming express delivery sector in China

Express delivery services are booming in both developed and emerging economies due to their low cost, convenience, and the fast growth in online shopping. The increasing environmental impacts of express delivery services and mitigation potentials, however, remain largely unexplored. Here we addressed such a gap for China, a country which is expanding online retail sales and express delivery rapidly. We found a total of 8.8 Mt of scrap packaging materials were generated by the express delivery sector in China in 2018. Its transportation-related GHG emissions surged from 0.3 Mt in 2007 to 13.7 Mt of CO2-equivalent (CO2e) in 2018, with an average of 0.27 kgCO2e per piece. Over 80% from online shopping deliveries. We predict these emissions will reach 75 MtCO2e by 2035. Nevertheless, it is possible to mitigate such GHG emissions by 102~134 MtCO2e between 2020 and 2035 if a suite of policies is adopted, including a slowdown of delivery speed, fuel system upgrades, packaging materials reduction, logistics optimization, and carbon pricing.

This study addresses an important issue which is appropriate for this journal. The research design is rigorous and the statistical analysis is appropriate and valid. The details provided for data collection and analysis help understand the research. The findings provide valuable insights to understanding the environmental impact (GHG emissions) of express deliveries and mitigation effects of some proposed strategies. Overall it is a well written paper. I have only a few minor concerns that require the authors to respond. The extremely high R2 makes me worrisome. We usually don't see such high R2. It is almost 100% correlation. Can you provide more explanation on this? Some potential strategies on reducing GHG emissions of express deliveries were proposed by the authors. However, there lack sufficient justifications for these strategies. The justifications need to be provided.
The limitations and future studies should be included.

Responses to reviewers' comments
We greatly appreciate the opportunity to submit a revised manuscript along with our responses to two reviewers' comments. Many thanks the two reviewers for providing the invaluable and constructive comments. The manuscript has been carefully revised, including fixing language and formatting errors. We are providing both a clean and a track-change version of the revised manuscript.

REVIEWER COMMENTS
Reviewer #1 (Remarks to the Author): The idea is quite interesting and novel to explore the effects of packaging pollution of express delivery companies on environmental sustainability. There are sufficient references provided by the authors. Work appears convincing and the rationale is logical. I recommend the publication of your paper after following improvements.
Reply: We highly appreciate your positive comments. We have thoroughly updated the manuscript and shown more details of our study based on the comments of the editor and the two reviewers.
Please add a brief conclusion of your research in a single paragraph, particularly highlighting your finding of the logistic growth model. Reply: We agree that the environmental issues are strongly linked with the level of corporate social responsibility of the firms. The suggested references were carefully reviewed and indeed helped our analyses and have been cited in the revised paper.
In the conclusion and limitation section, we explained that this concern is worth further study. "…the environmental impacts of an industry or a company probably strongly correlate with firm-level corporate social responsibility (CSR) efforts.2,728 An in-depth analysis of how various CSR initiatives or measures can affect the GHG emissions of the express delivery industry will be useful to guide companies to develop appropriate CSR strategies…" Actually, we just completed a survey of consumers and other stakeholders related to the express delivery service to examine potential behavioral changes for GHG mitigation, which will be reported in a future publication.
Please see revised main text in lines 284-288 in pages 15-16.
Please improve the English language of your paper. In the present form, it seems a little difficult to understand.
Reply: The manuscript has been carefully revised, including fixing typographical and grammatical errors. A professional language editor from the U.S., Ms. Marian Rhys, has further revised the manuscript thoroughly.
Overall, I am satisfied with your research and recommend its publication after minor revision.
Reply: Thank you! $ Reviewer #2 (Remarks to the Author): This study addresses an important issue which is appropriate for this journal. The research design is rigorous and the statistical analysis is appropriate and valid. The details provided for data collection and analysis help understand the research. The findings provide valuable insights to understanding the environmental impact (GHG emissions) of express deliveries and mitigation effects of some proposed strategies.
Overall, it is a well written paper. I have only a few minor concerns that require the authors to respond.

Reply: Thank you!
The extremely high R 2 makes me worrisome. We usually don't see such high R 2 . It is almost 100% correlation. Can you provide more explanation on this?
Reply: Thank you for the careful observation. We double-checked our data and analyses, and confirm the high R 2 for the stepwise regression of GHG emissions from express deliveries with various factors, including the road transportation distance per piece (x1) and the urbanization rate (x2). We provide the explanation as follows.
First, we used the European Norm EN 16258 methodology to estimate energy consumption and GHG emissions for transportation. European Norm EN 16258 is a standardized methodology for the calculation and declaration of energy consumption and GHG emissions related to any transportation operation. The key parameter for this method is the transportation distance.
Second, in our stepwise regression, we indeed found a high correlation between the transportation distance and the GHG emissions per piece delivered for all three transportation modes. The correlation coefficient is more than 93% with high statistical significance, as shown in Table R1 in this document. This is the main reason for the high correlation in the results. % In order to reduce the collinearity among the distance of the three transportation modes, the value with the highest correlation (road transportation distance per piece) is selected as the explanatory variable in the stepwise regression model.
We have added these discussions in the revised manuscript.
The main reason was the key parameter for this method is the transportation distance, especially the road transportation distance per piece.  The transportation and logistics network is one of the most important asset of express delivery companies. Constantly optimizing the network by increasing delivery volume and speed is a major undertaking for the companies to reduce cost and improve custom satisfaction. As a result, it also reduce GHG emissions and other environmental imapcts. 20 Express delivery companies are constantly optimizing their transportation and logistics networks, by introducing innovative technologies (such as cloud computing, big data, artificial intelligence, and blockchain). 21 Note: References can be found in Table S11 in Supporting Information file.
The limitations and future studies should be included.
Reply: We summarized the limitations of the research from the aspects of the 'big data' features, system boundary, and the major trends of the express delivery industry.
We also put forward suggestions for future study.
Please see revised main text in lines 272-288 in pages 15-16.
The "9571 program" means: the proportion of electronic waybill will account for 95% of the total, over 50% of the parcels will not use external packaging materials for delivering purposes, the reusable transshipment packaging bags will reach 70% of the total, and more than 100,000 express delivery service centers will recycle packaging materials.