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Harnessing the Digital Economy for Environmental Pollution Control: Policies, Practices, and Perspectives

A special issue of Sustainability (ISSN 2071-1050). This special issue belongs to the section "Economic and Business Aspects of Sustainability".

Deadline for manuscript submissions: closed (31 December 2025) | Viewed by 1589

Special Issue Editors

School of Business, Nanjing Normal University, Nanjing 210098, China
Interests: environmental economics; ecological economics and policy treatment

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Guest Editor
College of Economics and Management, Nanjing University of Aeronautics and Astronautics, 29 Jiangjun Avenue, Nanjing 211106, China
Interests: energy economics; carbon market; energy resource scheduling; energy efficiency

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Guest Editor
School of Economics and Business Administration, Chongqing University, Chongqing 400030, China
Interests: green finance; energy economics; carbon market; low-carbon development; energy efficiency
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Special Issue Information

Dear Colleagues,

The rapid development of the digital economy is now transforming industrial and economic structures around the world, providing new tools and approaches to address long-standing environmental challenges. For example, the digital economy, including big data, artificial intelligence (AI), and blockchain, offers innovative solutions to reduce environmental pollution, optimize resource use and promote green practices. From a government perspective, digital policies and regulations can streamline environmental governance, increase transparency, and enhance compliance with green standards. From a business perspective, digital transformation is reshaping business models, enabling organizations to reduce their carbon footprint, implement circular economy principles, and align with the Sustainable Development Goals.

This Special Issue aims to explore the role of the digital economy in promoting environmental sustainability. Key issues include, but are not limited to: digital policy, enterprise digitization, the platform economy, and the role of smart cities and the Internet of Things (IoT) in environmental regulation or in advancing environmental sustainability. This Special Issue welcomes contributors to submit papers that fall within the scope of our proposal. We encourage contributors to suggest ways to better integrate digital tools into environmental governance and to identify the main challenges faced by different sectors in implementing these strategies.

Dr. Zhen Liu
Dr. Xianyu Yu
Prof. Dr. Feng Wang
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 250 words) can be sent to the Editorial Office for assessment.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Sustainability is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • digital policy
  • digital transformation
  • sustainable development
  • environmental pollution control
  • corporate social responsibility

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Published Papers (2 papers)

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Research

22 pages, 663 KB  
Article
Digital Innovation and Regional Income Disparities in China: Impact, Mechanism, and Empirical Evidence
by Binqing Cai, Peipei Li, Jialu Shi and Xinhuan Huang
Sustainability 2026, 18(6), 2971; https://doi.org/10.3390/su18062971 - 18 Mar 2026
Viewed by 299
Abstract
In the era of an innovation-driven digital economy, whether digital innovation narrows or widens regional income disparities remains a controversial issue. This study constructs a comprehensive evaluation index system to measure digital innovation and empirically examines the impact mechanism of digital innovation on [...] Read more.
In the era of an innovation-driven digital economy, whether digital innovation narrows or widens regional income disparities remains a controversial issue. This study constructs a comprehensive evaluation index system to measure digital innovation and empirically examines the impact mechanism of digital innovation on regional income disparities in China from an economic perspective by employing panel regression, the spatial Durbin model, and the panel threshold model. A novel and key finding is that the marketization level acts as a critical threshold variable in the relationship between digital innovation and regional income disparities. Specifically, when the marketization level is below a certain threshold, digital innovation tends to widen regional income disparities; once it exceeds this threshold, digital innovation plays a significant role in narrowing such disparities. Moreover, the development of digital innovation has a significant narrowing effect on regional income disparities. Compared with its local impact, digital innovation can exert a more important effect on reducing income disparities in neighboring regions through significant spatial spillover effects. Accordingly, this paper puts forward targeted policy recommendations, including differentiated development strategies, enhanced spatial coordination, and accelerated digital innovation. Full article
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21 pages, 1499 KB  
Article
A Conceptual Framework for Sustainable Pollution Control in Informal Economies with Generative AI
by Akira Nagamatsu, Yuji Tou and Chihiro Watanabe
Sustainability 2026, 18(3), 1703; https://doi.org/10.3390/su18031703 - 6 Feb 2026
Viewed by 557
Abstract
Intangible environmental externalities in informal economies are hard to detect, attribute, and regulate because transaction records and evidentiary trails are fragmented. This conceptual paper reframes pollution control from improving model performance to designing institutions for verifiability and examines how generative AI (GAI) can [...] Read more.
Intangible environmental externalities in informal economies are hard to detect, attribute, and regulate because transaction records and evidentiary trails are fragmented. This conceptual paper reframes pollution control from improving model performance to designing institutions for verifiability and examines how generative AI (GAI) can both strengthen and undermine that verifiability. Integrating transaction-structure theory, institutional economics, and digital-governance research, we derive four propositions: (P1) standardized, interoperable evidence and hybrid auditing allow GAI to lower verification costs; (P2) opaque, multi-tier transactions and concentrated data control enable plausible falsification; (P3) detection reduces pollution only when linked to remediation through enforcement capacity; and (P4) incentives must reward verified, not merely claimed, circularity to deter greenwashing. We illustrate feasibility and boundary conditions through three precedents: Amazon’s unit-level identifiers and sustainability labeling, India’s CPCB extended producer responsibility portal for plastic packaging, and Brazil’s nationwide e-invoicing infrastructure (NF-e/SPED). The framework offers actionable design principles, testable hypotheses, and measurable indicators (evidence linkage, audit-log completeness, time-to-remediation) for future empirical work. The framework is intended to support analytic generalization for policy and practice across contexts. Full article
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