Key Takeaways & Executive Findings
- •• • The 'Zero-Waste City' initiative in Mianyang increased the comprehensive utilization rate of solid waste from 84.7% to 89.3%, and the incineration share of household waste rose to 87.3%, while hazardous waste storage rate dropped by 28.6%, indicating systemic improvements in waste management infrastructure. • • Intensity-based accounting, which normalizes for economic and population growth, reveals a net carbon reduction of 10.8×10^4 tCO2eq over the two-year period, contrasting with an absolute-quantity net increase of 127.6×10^4 tCO2eq, underscoring the critical role of intensity metrics in policy evaluation. • • The industrial sector achieved the largest carbon reduction of 40.2×10^4 tCO2eq, followed by the construction sector at 32.8×10^4 tCO2eq, demonstrating that targeted industrial upgrades and construction waste valorization are effective levers for decarbonization. • • Domestic solid waste generation intensity increased, leading to a net carbon increase of 46.1×10^4 tCO2eq, which signals an urgent need for source reduction and improved classification systems to align with consumption-driven waste growth.
Abstract
The 'Zero-Waste City' initiative, centered on source reduction, resource utilization, and safe disposal of solid waste, aims to minimize environmental impact. To quantitatively assess its carbon reduction contribution, this study took Mianyang as a case, systematically collecting data on solid waste generation, utilization, and disposal across industrial, agricultural, and other sectors from 2021 to 2024. Employing an improved WARM model and emission factor method, and incorporating generation, utilization, and disposal intensities, the carbon reduction benefits before (2021–2022) and after (2023–2024) the initiative were evaluated. Results show that despite significant improvements in comprehensive utilization and safe disposal rates, total solid waste generation increased, leading to a net negative carbon effect of -127.6×10^4 tCO2eq based on absolute quantities. However, after stripping economic and population growth factors, intensity-based accounting revealed a cumulative reduction of 10.8×10^4 tCO2eq, demonstrating significant synergistic benefits. The industrial sector contributed the most, with a reduction of 40.2×10^4 tCO2eq, driven by green transformation and enhanced utilization capacity. Conversely, the rising intensity of domestic solid waste generation resulted in a negative benefit of -46.1×10^4 tCO2eq, highlighting a key area for future improvement. The study underscores the necessity of considering both intensity and absolute quantity dimensions in evaluating rapidly developing cities. These findings provide practical evidence and reference pathways for advancing 'Zero-Waste City' construction and synergistic pollution reduction and carbon mitigation under the 'dual carbon' goals.
1. Introduction
The 'Zero-Waste City' initiative is a cornerstone of China's strategy to decouple economic growth from environmental degradation, yet its carbon reduction benefits remain difficult to quantify. Conventional assessments often rely on absolute waste quantities, which conflate policy effects with economic and population growth, leading to misleading conclusions. For rapidly developing cities like Mianyang, where industrial output and urbanization are expanding, such metrics obscure the true efficacy of waste management interventions. This study addresses this bottleneck by introducing intensity-based indicators—normalizing waste generation, utilization, and disposal against economic activity or population—thereby isolating the structural improvements attributable to the policy.
Prior research has largely focused on single waste streams or end-of-pipe treatments, lacking a holistic, city-wide perspective that includes source reduction. Moreover, the absence of construction waste data in many studies has left a significant gap. By systematically covering five major waste categories (industrial, agricultural, domestic, construction, and hazardous) and employing a localized WARM model with emission factors, this work provides a comprehensive framework. The intensity-based approach not only corrects for growth confounding but also reveals sector-specific dynamics, such as the industrial sector's substantial contribution and the domestic sector's rising emissions, offering actionable insights for policy refinement.
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LONG Fei, JIANG Zhonglin, TANG Xiujuan, JIANG Yingying, DING Xia, CHEN Mengjun, JU (Corresponding Author: CHEN Mengjun) (2026). Intensity-Based Carbon Reduction Benefits of 'Zero-Waste City' Construction: A Case Study of Mianyang. Chinese Journal of Environmental Engineering. https://doi.org/10.12030/j.cjee.202509120
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Frequently Asked Questions
How does the intensity-based metric differ from absolute quantity in evaluating carbon reduction, and why is it more appropriate for rapidly developing cities?
Absolute quantity metrics conflate policy effects with economic and population growth, which can mask genuine improvements. In Mianyang, absolute net emissions increased by 127.6×10^4 tCO2eq, but when normalized by economic output and population, the intensity-based calculation revealed a net reduction of 10.8×10^4 tCO2eq. This distinction is critical for cities experiencing rapid growth, as it isolates the structural efficiency gains from waste management policies, providing a fairer assessment of their impact.
What specific industrial transformations contributed to the 40.2×10^4 tCO2eq reduction, and can these be replicated in other industrial cities?
The reduction was driven by green transformation and enhanced comprehensive utilization capacity, particularly for general industrial solid waste such as fly ash, slag, and tailings. The utilization rate for industrial solid waste reached near-total levels, indicating a shift from disposal to resource recovery. These measures are replicable in other industrial cities, provided there is investment in recycling infrastructure and market demand for secondary materials.
Why did domestic solid waste generation intensity increase, leading to a net carbon increase of 46.1×10^4 tCO2eq, and what policy interventions are recommended?
The increase is attributed to rising consumption and urbanization, which outpaced waste reduction efforts. The study recommends strengthening source reduction, enhancing waste classification, and promoting circular economy practices. Specific measures include implementing extended producer responsibility, expanding pay-as-you-throw schemes, and investing in composting and anaerobic digestion for organic waste.
How were emission factors for different waste types and treatment methods localized to the Mianyang context, and what is the uncertainty range?
Emission factors were derived from the WARM model and adjusted using local data on waste composition and treatment technologies. The study employed cross-verification with official statistics to ensure consistency. While the paper does not explicitly report uncertainty ranges, the use of localized factors and sensitivity analysis (implied) helps reduce errors. Future work should conduct Monte Carlo simulations to quantify uncertainties.
What are the scalability challenges of the intensity-based approach for other cities, and how can data availability be improved?
The approach requires detailed waste generation, utilization, and disposal data across multiple sectors, which may not be readily available in all cities. To improve scalability, standardized reporting protocols and centralized databases are needed. Additionally, integrating waste data with economic and demographic statistics is essential. The study's methodology can be adapted, but cities must invest in robust data collection systems.
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