The high temperatures, long residence times, and alkaline environment of cement kilns enable effective degradation of organic pollutants and stabilization of heavy metals, making them a highly promising solution for industrial hazardous waste disposal. This study investigates a typical co-processing cement kiln plant in China as a case study [Scenario 1 (S1)]. Applying the system expansion method, it evaluates the environmental impacts and benefits of S1 relative to those of conventional cement production combined with independent hazardous waste incineration [Scenario 2 (S2)]. This study innovatively applies a Chinese localized life cycle impact assessment (LCIA) model, based on the Goddard Earth Observing System-Chem atmospheric chemistry transport model and the global exposure mortality model exposure-response model, to analyze the health impacts of fine particulate matter formation (FPMF). The results are then compared with those obtained using the ReCiPe 2016 model. The ReCiPe model shows that S1 outperforms S2, reducing impacts by 3.4%-7.1% across the categories of human health, ecosystem quality, and fossil resource scarcity. Applying the localized LCIA model, yielded an FPMF environmental impact over 3.4 times that calculated by the ReCiPe model, and a total environmental impact over 1.7 times that. This study underscores the need for localized LCIA models with high spatiotemporal resolution to better capture domestic heterogeneity. Such models can enable more precise industrial decision-making and inform policies on seasonal operation strategies, region-specific environmental access mechanisms, and coordinated regional approaches within the hazardous waste co-processing industry.

Fragmentation and edge exposure have caused major, spatially structured carbon losses in once-intact forests globally, yet most carbon methodologies, though central to conservation finance, still rely primarily on projected deforestation and fail to explicitly capture degradation-driven losses spatially. Here, we develop a Risk-Adaptive Conservation Zone (RACZ) model that integrates landscape ecology, spatial gradients of deforestation, and mechanistic edge-effect dynamics to delineate evidence-based carbon crediting zones. Using the distance to the nearest deforestation as a proxy for spatial risk, and incorporating pressure intensity and landscape structure, the model generates a dynamic, project-specific RACZ that adapts to both external pressure and internal resistance. Two tropical, similarly sized areas with contrasting deforestation pressures were tested. The model yielded a small RACZ of 1,150 ha in the intact, low-pressure landscape, concentrated in narrow bands near isolated edges, covering 0.27% of the total area. While for the highly fragmented frontier, RACZ expanded to 337,985 ha, covering 99.4% of the total area and reflecting pervasive, far-reaching degradation risk. These results show that RACZ restricts crediting to genuinely vulnerable areas in intact regions while capturing extensive risk in heavily fragmented frontiers. Therefore, this ecologically grounded approach complements core principles of the Integrity Council for the Voluntary Carbon Market by improving environmental integrity and credibility in carbon accounting through aligning credit zones with spatial degradation risk.