Wound infections which caused by drug-resistance bacteria pose a seriously threaten to human health, making the advances of non-resistant antimicrobial optimal approaches is the key research hotspot. For the study, we advanced a homogeneous Cu/Cu2O@NC nanorhombic nanoplatform, which was systematically characterized to confirm the coexistence of Cu0 and Cu+ phases as a core-shell structure. This material exhibits both high-efficiency near-infrared (NIR) photothermal conversion capability and environmental-responsive multi-enzyme activities. The Cu/Cu2O@NC nanorhombic nanoplatform could efficiently catalyzes the generation of reactive oxygen species (ROS) through a Fenton-like reaction, thereby alleviating inflammatory responses which induced by bacterial infections. It turned out to be a broad-spectrum antimicrobial property against for mutilation of Staphylococcus aureus (Gram-positive S. aureus), Escherichia coli (Gram-negative E. coli), and Methicillin-resistant Staphylococcus aureus (MRSA) by synergistic photothermal therapy (PTT) and chemodynamic therapy (CDT). Multidimensional in vitro and in vivo biocompatibility evaluations confirmed its excellent biocompatibility. Finally, a murine MRSA-infected wound model demonstrated that this “photothermal-chemodynamic” synergistic therapy can intelligently regulate the local microenvironment of infection, achieving efficient eradication of drug-resistant bacteria, mitigating tissue oxidative damage during the remodeling phase, and significantly accelerating wound by epithelialization, collagen deposition, and angiogenesis. Which showcasing its potential as an integrated wound material.

Nitrate (NO3-) and hexavalent chromium (Cr(VI)) are pollutants in wastewater that share similar removal mechanisms. Advanced reduction processes are highly effective for the treatment of such oxidized contaminants; however, these processes typically rely on the addition of external chemicals to generate reactive species. This study addresses this critical gap by demonstrating that organic matter inherently present in municipal secondary effluent can be repurposed as a sustainable electron donor to construct a vacuum ultraviolet (VUV185)-driven ARP. Without any external chemical addition, efficient and simultaneous removal of NO3- and Cr(VI) was achieved. Under acidic condition (pH 2), removal efficiencies of 78.2% for NO3- and 90.1% for Cr(VI) were achieved in real wastewater matrices. Systematic investigations revealed that inorganic anions exerted negligible or inhibitory effects, whereas organic components, particularly hydrophilic fractions, played a dominant role in promoting reductive removal. Dissolved oxygen was found to delay pollutant removal during the initial reaction stage by competing for reductive species, but its influence on final removal efficiency was negligible under prolonged irradiation. Product analysis indicated that NO3- reduction followed multiple pathways, yielding NO2-. NH4+-N, and gaseous nitrogen species, depending on solution pH and organic carbon availability. Although higher total organic carbon enhanced NO3- removal, excessive residual TOC compromise effluent quality, highlighting the need for careful process integration. The findings of this study provide a novel, reagent-free strategy for the construction of ARP, offering a sustainable "waste-treats-waste" paradigm for the treatment of oxidized contaminants.

From 2013 to 2023, China implemented three phases clean air actions, resulted in significantly reduction in ambient fine particles matter (PM2.5) concentration. However, the phase-specific driving factors behind PM2.5 changes and associated health benefits over this period have not been comprehensively investigated. Here, we quantify the public health burden attributable to changes in PM2.5 concentration, using an integrated framework that combines an emission inventory model, a chemical transport model, and a health risk assessment model. We found that the national PM2.5 concentration decreased substantially by 20.7 μg m-3 (36.8%) during Phase Ⅰ (2013-2017), 4.3 μg m-3 (7.6%) during Phase Ⅱ (2017-2020), and 0.7 μg m-3 (12.1%) during Phase Ⅲ (2020-2023). These reductions led to approximately 0.46 (95% Confidence Interval: 0.40-0.51) million, 0.18 (95%CI: 0.16-0.21) million, and 0.27 (95%CI: 0.23-0.31) million avoided premature deaths, respectively. Considering the influence of driving factors for air pollution control, the contribution of anthropogenic emissions declined markedly from 18.2 μg m-3 in Phase Ⅰ to 3.5 μg m-3 in Phase Ⅱ and 2.0 μg m-3 in Phase Ⅲ, respectively. In contrast, meteorological conditions shifted from reducing PM2.5 concentration in Phases I and II (-2.5 and -0.8 μg m-3) to increasing it in Phase III (+1.3 μg m-3). The diminishing marginal effectiveness of air quality improvement during Phase Ⅱ and Phase Ⅲ was attributed to both the saturation of end-of-pipe control technologies and increasingly unfavorable meteorological conditions. Although PM2.5 reduction potentials substantially diminished after 2020, the PM2.5-related avoided deaths in Phase Ⅲ accounted for 29.8% of total cases, exceeding that of Phase Ⅱ (20.0%) and revealing a nonlinear health response. Our results underscore that health-oriented collaborative strategies for air pollution and climate mitigation are critical for achieving substantial air quality improvements in the future.

Mineral-associated organic matter (MAOM) constitutes a substantial reservoir of soil organic carbon (SOC), yet the mechanisms governing the fixation of fresh exogenous organic matter by minerals with varying degrees of organic saturation remain poorly understood. In this study, we synthesized ferrihydrite (Fh)-fulvic acid (FA) complexes via coprecipitation and adsorption pathways at initial C/Fe molar ratios of 0, 1 and 5 to simulate distinct soil MAOM precursors. Water-soluble organic matter (WSOM) derived from corn residues was subsequently introduced to represent fresh organic inputs. Elemental analysis, excitation-emission matrix (EEM) fluorescence spectroscopy with parallel factor analysis (PARAFAC), and two-dimensional correlation spectroscopy (2D-FTIR-COS) were used to quantify carbon/nitrogen fixation behavior and elucidate molecular binding mechanisms, which demonstrated that the carbon sequestration efficiency and molecular selectivity of Fh were strictly regulated by its saturation state and formation pathway. Our results demonstrate that the sequestration capacity for fresh WSOM is strictly governed by the pre-existing mineral saturation and formation pathways, leading to divergent fates for carbon (C) and nitrogen (N). Specifically, coprecipitates with partially saturated ferrihydrite surface binding sites (initial C/Fe = 1) exhibited a strong capacity to sequester fresh WSOM, retaining up to 214.2 mg C/g Fe, whereas this capacity dropped to 110.4 mg C/g Fe in highly saturated coprecipitates (initial C/Fe = 5). Furthermore, highly saturated adsorption complexes exhibited almost no additional net C fixation from WSOM. In contrast to C, N retention remained robust across all saturation levels. Spectroscopic analyses revealed that the limitation on C sequestration from WSOM is driven by two underlying mechanisms: first, Fh already coated with FA exhibits a changed surface charge, thus electrostatically repelling fresh inputs; and second, in saturated systems, weaker "OM-OM" interactions allow high-affinity WSOM fractions (e.g., polysaccharides) to competitively displace pre-adsorbed FA. In contrast, the sustained N accumulation is attributed to the specific affinity of N-rich components in WSOM, which maintain strong binding interactions that are relatively independent of the mineral's saturation state. Our research has confirmed the critical requirements of insufficient mineral saturation and formation pathways for the soil carbon pool, providing a theoretical basis for a more comprehensive assessment of the potential of soil carbon sinks and management strategies.

Periodate (PI) is a promising oxidant in advanced oxidation processes, and its effective and sustainable activation is crucial for generating reactive species. In this study, a photocatalytic fuel cell (PFC) was employed to achieve cathodic activation of PI for ciprofloxacin (CIP) degradation. Photogenerated electrons from the photoanode activated PI at cathode, generating reactive species responsible for pollutant oxidation. As a result, the PFC-PI system achieved efficient CIP removal, significantly outperforming the PFC-only and PI-only control systems, and simultaneously produced electrical power. Mechanistic investigation revealed a pH-dependent shift of oxidation pathways, where 1O2 dominated at pH 6, whereas radical-driven pathways prevailed under pH 3. PI was effectively converted to IO3- without forming iodinated byproducts, confirming a benign conversion route. The identification of transformation products, combined with the density functional theory calculations, confirmed the proposed reaction mechanism. Although several intermediates exhibited higher predicted toxicity, the toxicity test showed reduced acute toxicity toward Vibrio fischeri as well as the antibacterial activity. This work expands the application of photocatalytic fuel cells by enabling periodate activation, offering a promising platform for advanced oxidation of emerging contaminants.

The removal of antibiotics attracts increasing attention due to its high risks, and advanced oxidation processes (AOPs) are efficient ways to eliminate them from wastewater. Incomplete mineralization of antibiotics during AOPs can yield transformation products with greater toxicity than the parent compounds. In this study, electrochemical oxidation (EO) and vacuum UV (VUV185) irradiation were evaluated individually and in sequence for the removal and mineralization of sulfamethoxazole (SMX). While both processes rapidly degraded SMX to below detection limits, TOC removal remained limited (<= 59 %) when applied individually. Combining EO and VUV185 markedly improved mineralization. The EO-VUV185 sequence achieved up to 95.1 % TOC removal under optimal conditions (EO at pH 7, VUV185 at pH 3). Fluorescence excitation-emission matrix spectroscopy coupled with parallel factor analysis revealed distinct intermediate profiles for EO and VUV185. These intermediates were nearly eliminated by the combined process. HPLC-MS and FT-ICR-MS analyses confirmed that EO generated aromatic and humic-like intermediates resistant to further EO oxidation but susceptible to VUV185 photolysis. VUV185 generally favored the production of low-molecular-weight intermediates, with minimal coupling reactions. For polymerizable aromatic or unsaturated intermediates, EO pretreatment promotes polymerization during the VUV185 stage. In contrast, for saturated and highly oxidized intermediates, it facilitates further cleavage. These findings highlight the complementary mechanisms of EO and VUV185. Together, they enhance antibiotic mineralization by targeting both stable and transient intermediates.

Identification of the pollution source of surface water in a chemical park was difficult because many industrial enterprises with complex wastewater components and similar characteristics are located there. Therefore, a national-level chemical park in Jiaxing City was studied, and wastewater samples from ten batches of seven key enterprises in the park were collected and analyzed using 3D excitation emission matrix spectrometry （EEMS） and gas chromatography-mass spectrometry （GC-MS）. Parallel factor analysis was used to extract common components of EEMS spectra from different batches of drainage in the same enterprise to construct an EEMS characteristic data matrix. Furthermore, specific substances with high detection rates or that could effectively distinguish other enterprise drainage were screened out from the GC-MS data to construct a GC-MS characteristic data matrix. Pollution source identification was attempted with different models based on different data matrices. The results showed that regardless of whether being based on the EEMS original data matrix, the EEMS characteristic data matrix, or the GC-MS characteristic data matrix, the identification accuracy of the BP neural network model was not high, only 71.43%, 76.19%, and 71.43%, respectively, which was slightly higher than that of the support vector machine model （76.19%, 76.19%, and 57.14%）. However, when the EEMS and GC-MS characteristic data fusion matrix were used, the pollution source identification performance was significantly improved. The identification accuracy, macro precision, macro recall, and macro harmonic mean of the support vector machine model for the wastewater of the seven enterprises were 95.24%, 96.43%, 95.24%, and 95.10%, respectively, while the performance of the BP neural network model was better, with all four indicators close to 100%. The study provides an effective method for identifying surface water pollution sources in chemical parks.

The Yangtze River Delta (YRD) suffers severe surface ozone (O-3) pollution during summer (June-July-August, JJA). Elucidating the role of meteorology and emissions is crucial for effective controls on O-3 pollution. We used the Weather Research and Forecasting (WRF) - Community Multiscale Air Quality (CMAQ) modeling system to quantify the influences of meteorology, anthropogenic and biogenic emissions on O-3 variations in the YRD between 2019 and 2022. Contrasting trends in surface O-3 were found in the Hangzhou Bay (HZB) (3.3 mu g m(-3) yr(-1)) and the rest of the YRD (-1.9 mu g m(-3) yr(-1)). Underlying factors affecting surface O-3 differed between these two subregions. In HZB, meteorological variations dominated the strong O-3 increase with a contribution of similar to 94 %. By contrast, in the rest of the YRD, meteorology (42 %) and anthropogenic emissions (53 %) were both key contributors to the modest O-3 decrease. Our results reveal a shift in O-3 drivers in contrast to 2013-2019, characterized by an increasing importance of meteorology and a decreasing contribution of anthropogenic emissions. Consequently, the anthropogenically driven O-3 decrease, which ensues from current pollutant control policies, is difficult to offset the strong positive meteorological influence such as in HZB. There is an urgent need for stricter and more efficient control of O-3 precursor emissions to mitigate the substantial influences of meteorology. Emissions of non-methane volatile organic compounds are of particular concern, as they are still on the rise.

Sewage effluent and reclaimed water usually contain elevated concentrations of bacteria-derived endotoxins, which may have serious public health implications upon exposure. Both conventional disinfection methods, such as chlorine, ultraviolet, and ozone disinfection, and the new potassium ferrate disinfection process have limited endotoxin removal capacity. Therefore, it is necessary to find new methods of removing endotoxins. In this study, we investigated the effects of ultraviolet/ferrate (UV/Fe(VI)) combination treatment on endotoxin elimination and inhalation hazard control. Our results indicate that UV or Fe(VI) alone cannot sufficiently eliminate endotoxins but can instead exacerbate endotoxin release during bacterial inactivation. However, the UV/Fe(VI) combination rapidly eliminated approximately 85.6 % of both pure and bacteria-derived endotoxins. The optimal conditions for this disinfection process were determined to be 10 mg/L of Fe(VI) and 160 mu W/cm2 of UV exposure for 15 min. Furthermore, the pH value, bicarbonate (HCO3 -), humic acid, and turbidity were determined as potential factors that may affect UV/Fe(VI)-mediated endotoxin removal in reclaimed water. The potential mechanism underlying UV/Fe(VI)-induced endotoxin degradation involves several strongly oxidizing species, among which Fe(IV)/Fe(V) is regarded as the primary contributor, followed by the superoxide anion (center dot O2-) and hydroxyl (center dot OH) radicals. These active substances induce the breakdown of the endotoxin molecular structure into smaller, non-toxic fragments. Furthermore, pure endotoxins, Escherichia coli, and Pseudomonas aeruginosa were disinfected with UV/Fe(VI), and then these aerosolized samples were inhaled exposed to mice. Our results demonstrated that combined use of UV and Fe(VI), rather than administration alone, remarkably blunted bacterial- and endotoxin-induced lung injury. In conclusion, these results demonstrate that the UV/Fe(VI) approach successfully eliminates endotoxins and related inhalation hazards from reclaimed water.

Haloacetic acids (HAAs) are among the most common drinking water disinfection byproducts (DBPs) and are of widespread concern due to their potential carcinogenicity and reproductive health risks. However, data on human exposure to HAAs are scarce. HAAs in urine have been identified as useful biomarkers for assessing exposure to DBPs via drinking chlorinated water. In this study, a suitable method for determining eight HAAs (including iodoacetic acid (IAA)) in human urine was developed and validated based on USEPA 552.3. HAAs were extracted from 5 mL of urine with methyl tert-butyl ether (MTBE), derivatized with acidified methanol and analyzed via gas chromatography with an electron capture detector (GC-ECD). Several optimization experiments were performed for the sample pretreatment step to establish a more sensitive and efficient analysis scheme. The method was tested in terms of linearity, accuracy, precision, and detection limits. The linear range of the method was 0.1-100 μg L-1, with recovery rates from blank matrix-spiked samples ranging from 84.9% to 122.6%, relative standard deviations between 1.7% and 14.2%, detection limits from 0.013 to 0.3 μg L-1, and quantitation limits from 0.043 to 1.0 μg L-1. Finally, the method was applied to detect HAAs in actual human urine samples. Six HAAs were detected in 460 urine samples to varying degrees, with geometric mean concentrations ranging from 0.07 to 0.89 μg L-1. The results demonstrate that the method is practical, and suitable for routine biomonitoring of HAAs in populations.

Elucidating the relationships among various microorganisms and their reactions to environmental fluctuations, such as dissolved organic matter (DOM), remains a key objective in the anaerobic cofermentation (ACF) of sewage sludge (SS) and protein-rich waste (PRW); however, this topic is inadequately understood. In this study, the microbial traits associated with the biosynthesis of short-chain fatty acids (SCFAs) were investigated in the ACF of SS in conjunction with four distinct PRWs (pupa, fishmeal, maize gluten, and soybean meal). Compared with those in the SS-only reactor, the first-order rate constants for biosolid dissolution in the SS/PRW reactors were increased by 1.9-4.0-fold. Pupa performed best among the four PRWs in the ACF process, with the solubilization rate increasing from 9.4% (SS-only reactor) to 33.5%. The copious and readily biodegradable DOM created a unique niche for functional microbes, leading to reframing of the microfloral structure. Specialized genera, such as Holophaga, Alistipes, and Geothrix, were responsible for SCFA biosynthesis in the SS/pupa reactor. The highly differentiated, low-redundancy microecosystem constructed in the SS/pupa reactor contributed to the independent functioning of the hydrolyzers and acidogens, resulting in an SCFA yield that was 6.9-fold greater than that in the SS-only reactor. In addition, the ACF of SS/pupa resulted in the genes encoding the NiFe hydrogenase and Wood-Ljungdahl pathway being intact, which promoted the synthesis of SCFAs, especially acetate. These findings offer new insights into the microbiological mechanisms that augment SCFA generation by the ACF of SS/PRW in terms of microorganism fate, metabolic network relationships, and microecosystem niche.

Halogenated organic compounds are common byproducts of advanced oxidation processes (AOPs) and have become a major concern for AOP applications. This study investigated AOX (adsorbable organic halogens) formation during UV/PDS and UV/H2O2 treatment of dyestuff wastewater secondary effluent, and evaluated AOX removal via UV/sulfite (UV/S). Both AOPs increased AOX concentrations, with UV/PDS generating more (45.7 % higher) than UV/H2O2. UV/S significantly reduced AOX by 62.4 % (UV/PDS effluent) and 47.8 % (UV/H2O2 effluent), outperforming UV or sulfite alone (<3 %). Higher pH and sulfite dosages enhanced removal by promoting reductive radicals. Dissolved oxygen only impacted removal under sustained high levels. Genotoxicity mirrored AOX trends, rising post-AOPs but declining after UV/S. Eight and nine new halogenated byproducts were identified in UV/H2O2 and UV/PDS effluents, respectively. UV/S eliminated most organic halogens, though about 5 mg/L AOX persisted, highlighting the necessity of sum parameter monitoring. This study confirms UV/S effectively mitigates toxic AOX byproducts from AOPs, addressing critical environmental risks in wastewater treatment.

In this study, a ternary co-fermentation system was developed using iron-phosphorus precipitates (FePs)-bearing sludge, peroxydisulfate (PDS), and corn gluten meal (CGM) to activate PDS through a microbe-mediated endogenous iron cycle, thereby promoting phosphorus (P) release and acidogenesis. Fe(II) was released along with P via the dissolution of Fe(II)Ps, resulting from Fe(III)Ps bioreduction. Subsequently, the released Fe(II) induced PDS activation, which avoided the negative impact of external activators on P release by precipitation with P. The optimal PDS dosage for ternary co-fermentation was 0.2 mM/g TSS. At this dosage, P release efficiency increased from 27.3 % (sludge-only group) to 71.6 % and volatile fatty acids (VFAs) production increased from 41.0 (sludge-only group) to 158.5 mg COD/g VSS. SO4 center dot- and center dot OH generated through PDS activation disintegrated sludge flocs to promote encapsulated Fe(II)Ps dissolution and organics release. The concentration of soluble chemical oxygen demand in the sludge-CGM-PDS group was 4.4 times greater than that in the sludgeonly group. The increased content and biodegradability of hydrolysates (e.g., protein-like, tryptophan-like, and tyrosine-like substances) contributed to the enrichment of hydrolytic-acidogenic bacteria, resulting in a relative abundance of 40.7 %. Unclassified_c__Ignavibacteria, Clostridium, and Rubrivivax were the dominant hydrolytic-acidogenic biomarkers, which enhanced the intracellular metabolisms of glycolysis, amino acid degradation, and acetogenesis, leading to notable increases in VFAs yields. The relative abundance of phosphate acetyltransferase, a key enzyme in acetate biosynthesis, increased by 8.9 %, thus facilitating acetogenesis. In addition, unclassifiedcIgnavibacteria, as putative iron reducers, were the primary microbes mediating endogenous iron reduction. This study provides valuable insights into the PDS self-activation mechanism and microfloral traits during ternary co-fermentation, contributing to the valorization of FePs-bearing sludge waste.

Given the importance of decarbonizing industrial parks to low-carbon transformation of industrial sectors, this study aims to unveil the dynamic evolution and progress of low-carbon development in such parks through descriptive, bibliometric, and manifest content analysis. The review goes in two parallel ways: the pros and cons of diverse carbon emission accounting methods and carbon mitigation measures targeting industrial parks, and the three main-stream national policy innovations during the past four years. State-of-the-art scientific research and policy practices have been reviewed to panoramically depict the low-carbon transformation of Chinese industrial parks and distinguish their future bioeconomy pathways. The key findings include: (1) Despite large-scale explorations of carbon accounting for parks, the consistent boundaries of their physical systems and emission inventories must be resolved. (2) Carbon reduction actions are mainly concentrated on unit-level including energy and industrial infrastructure, but the decarbonization of system-level such as multisectoral collaborative systems requires more exploration. (3) Government policies are important for low-carbon development in industrial parks concerning efficiency improvement, synergy of pollution reduction and carbon mitigation, circular economy, performance assessment, structural upgrading, and industrialization–urbanization integration. (4) The bioeconomy must be innovated from both perspectives and the effective combination of unit-level processes (highlighting the application of biobased energy, materials, and equipment) and system-level processes (emphasizing biomimetic industries, biorefinery solutions, and symbiotic ecosystems). This unit–system integrated model is oriented to further bioeconomy both in Chinese industrial parks and similar industrial clusters in other developing countries.

In this study, we analyzed the characteristics of three-dimensional excitation-emission matrix spectra (EEMs) of 150 samples from five industrial wastewater types and domestic sewage to track water pollution sources effectively. We then developed a recognition model for wastewater EEMs by establishing a feature dataset containing fluorescence peak values and parameters derived from EEMs, integrated with machine learning techniques. This model enables the rapid and precise identification of pollution sources. Our findings suggest that although the EEMs of the six wastewater categories are distinct, visual differentiation is challenging. This was confirmed by cosine similarity assessments, showing some samples with low within-group (< 0.8) and high between-group (> 0.95) similarities. Despite significant variations in EEMs features across wastewater categories, identifying specific pollutants remains difficult, especially for pulp mills and leather effluents. Among the tested classification algorithms, Support Vector Machine (SVM) achieved the highest performance with 91.7 % accuracy, 94 % precision, 91 % recall, and 92 % F1-score, outperforming K-Nearest Neighbors and Partial Least Squares Discriminant Analysis. The SVM significantly improved identification accuracy for pulp mill and leather processing wastewaters compared to other models. To enhance identification accuracy, further exploration of EEMs features and expanding the training dataset are recommended. Combining EEMs features with machine learning presents a promising method for improving water pollution supervision and source tracing in environmental management practices.

The anaerobic co-fermentation of iron bound phosphorus (P) compounds (FePs)-bearing sludge with corn gluten meal (CGM) and the underlying mechanisms associated with P release and volatile fatty acids (VFAs) production were investigated. The optimal CGM dosage for P release was 0.6 g chemical oxygen demand (COD)/g total suspended solid (TSS), which resulted in an increase in efficiency from 7 % (control sample) to 39 %. However, the optimal CGM dosage for VFAs production was 0.4 g COD/g TSS, and the yield increased from 37.4 (control sample) to 331.7 mg COD/g volatile suspended solid. The addition of CGM enhanced hydrolysis and acidogenesis by supplying abundant organic substrates to promote the growth of hydrolytic and acidogenic bacteria. A higher VFAs/ammonium-nitrogen ratio resulted in a lower pH, which promoted greater FePs dissolution and P release from the sludge. This study provides novel insights into the effects of CGM on P release and VFAs production.

Pollution from chemical and industrial wastes has farreaching effects on ecosystems. Harmful substances such as heavy metals, persistent organic pollutants (e.g., polychlorinated biphenyls (PCBs) and polycyclic aromatic hydrocarbons (PAHs)), acid and alkali waste streams and other harmful substances enter the coastal and marine environments through rivers, sewage pipelines and other pathways, posing a serious threat to marine ecosystems and human health. Not only do these pollutants tend to accumulate in sediments, but they are also gradually amplified through the food chain, eventually reaching high concentrations in top predators and leading to biomagnification effects. In addition, ocean acidification and discharge of highly alkaline waste streams further affect carbonate-dependent marine organisms and disrupt the marine ecological balance. Understanding the environmental behavior of these pollutants and their ecological impacts is essential for developing effective pollution control and ecological protection measures.

Promoting the synergy between carbon mitigation and pollution reduction (SCMPR) is pivotal for global green and sustainable development. Industrial parks, as crucial economic hubs, require effective SCMPR strategies considering land, economy, and the environment, but present research seldom proposes methods that consider multiple factors and stakeholders together and fit for practical application. Given this, this study establishes a multi-factor industrial structural adjustment model for industrial parks incorporating scenario analysis to unveil optimal adjustment schemes and then develops an efficient spreadsheet tool based on the model. The model results convincingly fulfill SCMPR requirement after applying to a typical industrial park: After adjustments, 50 main industries in the park can achieve SCMPR targets, with carbon intensity and total phosphorous intensity predicted to achieve relative decoupling and other regular pollutant emissions anticipated to absolute decoupling by 2030. The proposed optimal scheme indicates that wastewater, waste gas, and solid waste volumes in the park will rise by 39%–54% by 2025 and 76%–113% from 2025 to 2030, and then translate into a 50% increase in waste treatment costs by 2025 and a subsequent 98% increase by 2030. The carbon intensity of the park will decrease from 154 tonnes of CO2 per million Chinese Yuan in 2020 to 94 in 2030. The results culminate in three strategic recommendations for industrial parks: (1) prioritize reducing total pollutant emissions and carbon intensity, (2) customize carbon mitigation and pollution reduction strategies for each industry, and (3) regulate material and energy flows at multiple levels. This study can provide a pragmatic tool for industrial parks to make science-based decision-making toward dual carbon goals.

工业园区是中国制造业发展的重要载体与做好碳达峰碳中和的关键支撑,建立统一规范的碳核算方法,是园区科学推进低碳发展的必要前提.本研究剖析了园区碳核算的复杂性,明确了园区"双碳"工作的核心要义,建立了"一芯四核"互馈式园区碳核算方法框架.该框架主要包括应用目标与范围定义、流分析与排放清单建立、碳排放计算、结果解释与决策支撑四个核心环节,四"核"间相互作用、迭代优化,根据园区发展实际进行具象化,并充分考虑向上与所在行政区域碳核算清单、向下与企业碳排放核算兼容,最终服务于准确把握低碳发展内涵、锻造新的产业竞争优势这一关键内"芯".进一步地,研究阐述了"一芯四核"方法框架各主要步骤,分析了园区碳核算实践中面临的园区边界、核算范围、清单建立、数据质量等方面的难点,提出了基于检验清单的各环节工作原则、操作步骤及注意事项.研究为"千园千面"的工业园区提供了科学统一的碳核算理论框架,可为工业园区在低碳转型中锻造新的产业竞争优势提供决策支撑,为建立统一规范碳排放统计核算体系奠定方法基础.