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2026 Vol. 44, No. 9
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2026, 44(9): 1-8.
doi: 10.13205/j.hjgc.202609001
Abstract:
Cryptosporidium， as a typical waterborne pathogen， poses a significant public health risk via environmental transmission and warrants urgent attention. However， systematic quantification of its regional-scale emission fluxes and spatial distribution remains limited in China， resulting in a “black box” in environmental safety management. This study aims to quantify the emission loads of Cryptosporidium oocysts in the aquatic environment， accurately identify key pollution sources and spatial hotspots， and thereby provide a basis for targeted regional risk prevention and control. Focusing on the Yangtze River Delta （YRD） as the study area， human and livestock pollution source data were integrated to develop an assessment model for Cryptosporidium oocyst emission loads. Key parameters （e.g.， infection rate， fecal oocyst concentration） were fitted using probability distributions， and the total emission loads and their uncertainty were quantified via Monte Carlo simulation. High-resolution visualization of the emission loads was achieved through spatial mapping techniques. The results indicate that the total annual emission of Cryptosporidium oocysts into the aquatic environment of the YRD is 4.78×1016 oocysts/year （95% CI： 4.34×1015 to 1.68×1017 oocysts/year）. Poultry farming is the dominant emission source， contributing 94.69%， primarily driven by the high oocyst concentration in poultry feces （mean OPG： 5.52 lg number/g） and the scale of intensive farming in the region. The emission loads exhibit significant spatial heterogeneity， with distinct pollution hotspots identified in northern Anhui （e.g.， Fuyang， Bozhou） and eastern Jiangsu （e.g.， Yancheng， Nantong）. Sensitivity analysis further reveals that the oocyst concentration in poultry feces is the core driving factor， while feces management process parameters （e.g.， storage loss rate， land application ratio） are actionable leverage points for intervention. This study provides practical insights for implementing the environmental safety strategy of “targeted identification and prioritized prevention” and improving the early warning system for biological pollution.
Cryptosporidium， as a typical waterborne pathogen， poses a significant public health risk via environmental transmission and warrants urgent attention. However， systematic quantification of its regional-scale emission fluxes and spatial distribution remains limited in China， resulting in a “black box” in environmental safety management. This study aims to quantify the emission loads of Cryptosporidium oocysts in the aquatic environment， accurately identify key pollution sources and spatial hotspots， and thereby provide a basis for targeted regional risk prevention and control. Focusing on the Yangtze River Delta （YRD） as the study area， human and livestock pollution source data were integrated to develop an assessment model for Cryptosporidium oocyst emission loads. Key parameters （e.g.， infection rate， fecal oocyst concentration） were fitted using probability distributions， and the total emission loads and their uncertainty were quantified via Monte Carlo simulation. High-resolution visualization of the emission loads was achieved through spatial mapping techniques. The results indicate that the total annual emission of Cryptosporidium oocysts into the aquatic environment of the YRD is 4.78×1016 oocysts/year （95% CI： 4.34×1015 to 1.68×1017 oocysts/year）. Poultry farming is the dominant emission source， contributing 94.69%， primarily driven by the high oocyst concentration in poultry feces （mean OPG： 5.52 lg number/g） and the scale of intensive farming in the region. The emission loads exhibit significant spatial heterogeneity， with distinct pollution hotspots identified in northern Anhui （e.g.， Fuyang， Bozhou） and eastern Jiangsu （e.g.， Yancheng， Nantong）. Sensitivity analysis further reveals that the oocyst concentration in poultry feces is the core driving factor， while feces management process parameters （e.g.， storage loss rate， land application ratio） are actionable leverage points for intervention. This study provides practical insights for implementing the environmental safety strategy of “targeted identification and prioritized prevention” and improving the early warning system for biological pollution.
2026, 44(9): 9-17.
doi: 10.13205/j.hjgc.202609002
Abstract:
Conventional bioretention systems often exhibit poor removal efficiency for humic-acid-type dissolved organic nitrogen （DON）， and the underlying transformation mechanisms remain unclear. In this study， biochar-pyrite composite bioretention systems were constructed to evaluate their performance and mechanisms in removing humic-acid-type DON under alternating rainfall-dry conditions. The results showed that systems amended with pyrite and/or biochar significantly enhanced UV254 and COD removal， achieving 55% to 66% and 32% to 50%， respectively. Total nitrogen （TN） and nitrate nitrogen （NO3--N） removal ranged from 43% to 57% and from 43% to 60%， respectively， with the biochar-pyrite system performing best. Dissolved oxygen （DO） and oxidation-reduction potential （ORP） in the effluent decreased markedly， indicating a shift to a reducing environment favorable for denitrification and organic nitrogen mineralization. During dry periods， pore-water UV254 decreased and then stabilized， while COD initially declined and later rebounded， suggesting slow microbial decomposition of adsorbed humic substances into smaller bioavailable molecules. High-throughput sequencing revealed enrichment of taxa related to complex organic degradation and sulfur/iron cycling， such as Thiobacillus and Pseudomonas. Integrating physicochemical and microbial evidence， a synergistic removal pathway of biochar adsorption and slow release-microbial degradation-pyrite-driven sulfur-based autotrophic denitrification was proposed. The biochar-pyrite composite demonstrated stable and efficient removal of humic-acid-type DON under wet-dry cycles， providing guidance for optimizing stormwater bioretention systems.
Conventional bioretention systems often exhibit poor removal efficiency for humic-acid-type dissolved organic nitrogen （DON）， and the underlying transformation mechanisms remain unclear. In this study， biochar-pyrite composite bioretention systems were constructed to evaluate their performance and mechanisms in removing humic-acid-type DON under alternating rainfall-dry conditions. The results showed that systems amended with pyrite and/or biochar significantly enhanced UV254 and COD removal， achieving 55% to 66% and 32% to 50%， respectively. Total nitrogen （TN） and nitrate nitrogen （NO3--N） removal ranged from 43% to 57% and from 43% to 60%， respectively， with the biochar-pyrite system performing best. Dissolved oxygen （DO） and oxidation-reduction potential （ORP） in the effluent decreased markedly， indicating a shift to a reducing environment favorable for denitrification and organic nitrogen mineralization. During dry periods， pore-water UV254 decreased and then stabilized， while COD initially declined and later rebounded， suggesting slow microbial decomposition of adsorbed humic substances into smaller bioavailable molecules. High-throughput sequencing revealed enrichment of taxa related to complex organic degradation and sulfur/iron cycling， such as Thiobacillus and Pseudomonas. Integrating physicochemical and microbial evidence， a synergistic removal pathway of biochar adsorption and slow release-microbial degradation-pyrite-driven sulfur-based autotrophic denitrification was proposed. The biochar-pyrite composite demonstrated stable and efficient removal of humic-acid-type DON under wet-dry cycles， providing guidance for optimizing stormwater bioretention systems.
2026, 44(9): 18-29.
doi: 10.13205/j.hjgc.202609003
Abstract:
In recent years， the existing secondary biochemical process has been difficult to achieve the standard COD discharge of coking wastewater. Although the electrochemical oxidation technology with Ti4O7 REM as the anode can effectively remove organic matter in the secondary biochemical effluent， there is a problem of high energy consumption. Enhancing the catalytic activity of the electrodes is the key to reducing the energy consumption. To enhance the catalytic activity of Ti4O7 REM， ordered nano-porous Ti4O7 particles were synthesized by self-assembly in this research. These particles were then loaded onto a porous titanium substrate， to obtain a Ti-based ordered nano-porous Ti4O7 electroactive membrane （named ordered nano-porous Ti4O7 REM）. Using ordered nano-porous Ti4O7 REM as the anode， the Ti4O7 REM superimposed reactor was constructed to deeply remove the organic substances in the biochemical effluent of coking wastewater. The result showed that the ordered nanoporous structure compressed the width of the charge layer （dsc = 0.97 nm）， increasing the probability of electron tunneling and shortening the electron transmission path， which enhanced the excitation activity of ·OH. Under the oxidative conditions of a current density of 15 mA/cm2 and the electrolysis time of 120 minutes， the energy consumption was 96.7 kW·h/kg COD， the TOC removal rate was 62.7%， the COD removal rate was 88.5%， and the effluent COD met the limit requirements of the Pollutant Discharge Standard for Coking Chemical Industry（GB 16171—2012）.
In recent years， the existing secondary biochemical process has been difficult to achieve the standard COD discharge of coking wastewater. Although the electrochemical oxidation technology with Ti4O7 REM as the anode can effectively remove organic matter in the secondary biochemical effluent， there is a problem of high energy consumption. Enhancing the catalytic activity of the electrodes is the key to reducing the energy consumption. To enhance the catalytic activity of Ti4O7 REM， ordered nano-porous Ti4O7 particles were synthesized by self-assembly in this research. These particles were then loaded onto a porous titanium substrate， to obtain a Ti-based ordered nano-porous Ti4O7 electroactive membrane （named ordered nano-porous Ti4O7 REM）. Using ordered nano-porous Ti4O7 REM as the anode， the Ti4O7 REM superimposed reactor was constructed to deeply remove the organic substances in the biochemical effluent of coking wastewater. The result showed that the ordered nanoporous structure compressed the width of the charge layer （dsc = 0.97 nm）， increasing the probability of electron tunneling and shortening the electron transmission path， which enhanced the excitation activity of ·OH. Under the oxidative conditions of a current density of 15 mA/cm2 and the electrolysis time of 120 minutes， the energy consumption was 96.7 kW·h/kg COD， the TOC removal rate was 62.7%， the COD removal rate was 88.5%， and the effluent COD met the limit requirements of the Pollutant Discharge Standard for Coking Chemical Industry（GB 16171—2012）.
2026, 44(9): 30-38.
doi: 10.13205/j.hjgc.202609004
Abstract:
At present， biological nitrogen and phosphorus removal processes are generally adopted for wastewater treatment in expressway service areas. However， due to the large variation in water quality and low C/N ratio， the effluent quality is often poor. In this study， an iron autotrophic denitrification filter was employed to enhance the treatment of biologically treated effluent from expressway service areas， achieving deep nitrogen and phosphorus removal. Three types of iron autotrophic denitrifying biological filters with different fillers were constructed to evaluate their applicability and effectiveness in enhancing the treatment of biologically treated effluent from expressway service areas. The influence of key operating parameters on the treatment performance of the biological filters was studied， and the changes in microbial community structure and the mechanisms of nitrogen and phosphorus removal were analyzed. The results showed that the denitrification rate of the reactor filled with siderite， magnetite， and limestone was higher than that of the single siderite or magnetite system. When the influent NO3--N concentration was （10.95±1.2） mg/L and the hydraulic retention time was shortened from 6 h to 2 h， the NO3--N removal rate decreased from （82.9±2.3）% to （76.7±1.4）%. The effluent concentration could still reach （1.48±0.2） mg/L， meeting the discharge requirements. With the shortening of HRT， the half-order kinetic model constant K1/2v， R for the NO3--N removal process increased， which was not conducive to complete denitrification by iron autotrophs. PO43--P， on the one hand， formed FePO4 precipitate with Fe3+， and on the other hand， it might be adsorbed by FeOOH derived from Fe2+. The results of microbial sequencing showed that the addition of magnetite could achieve the enrichment of high-abundance Thiobacillus and Ferritrophicum. Ferritrophicum， as a genus of neutral microaerophilic ferrous-oxidizing bacteria， could utilize Fe2+ as an electron donor to complete the denitrification process. The mixed iron autotrophic filler could enhance the efficiency of nitrogen and phosphorus removal， providing a reference basis and theoretical value for the low-carbon wastewater treatment in expressway service areas.
At present， biological nitrogen and phosphorus removal processes are generally adopted for wastewater treatment in expressway service areas. However， due to the large variation in water quality and low C/N ratio， the effluent quality is often poor. In this study， an iron autotrophic denitrification filter was employed to enhance the treatment of biologically treated effluent from expressway service areas， achieving deep nitrogen and phosphorus removal. Three types of iron autotrophic denitrifying biological filters with different fillers were constructed to evaluate their applicability and effectiveness in enhancing the treatment of biologically treated effluent from expressway service areas. The influence of key operating parameters on the treatment performance of the biological filters was studied， and the changes in microbial community structure and the mechanisms of nitrogen and phosphorus removal were analyzed. The results showed that the denitrification rate of the reactor filled with siderite， magnetite， and limestone was higher than that of the single siderite or magnetite system. When the influent NO3--N concentration was （10.95±1.2） mg/L and the hydraulic retention time was shortened from 6 h to 2 h， the NO3--N removal rate decreased from （82.9±2.3）% to （76.7±1.4）%. The effluent concentration could still reach （1.48±0.2） mg/L， meeting the discharge requirements. With the shortening of HRT， the half-order kinetic model constant K1/2v， R for the NO3--N removal process increased， which was not conducive to complete denitrification by iron autotrophs. PO43--P， on the one hand， formed FePO4 precipitate with Fe3+， and on the other hand， it might be adsorbed by FeOOH derived from Fe2+. The results of microbial sequencing showed that the addition of magnetite could achieve the enrichment of high-abundance Thiobacillus and Ferritrophicum. Ferritrophicum， as a genus of neutral microaerophilic ferrous-oxidizing bacteria， could utilize Fe2+ as an electron donor to complete the denitrification process. The mixed iron autotrophic filler could enhance the efficiency of nitrogen and phosphorus removal， providing a reference basis and theoretical value for the low-carbon wastewater treatment in expressway service areas.
2026, 44(9): 39-47.
doi: 10.13205/j.hjgc.202609005
Abstract:
In this paper， magnetic chicken manure biochar Fe-KBC was prepared by chicken manure， and its adsorption performance for tetracycline in aqueous solution was systematically investigated. Combined with FT-IR， SEM and N2 adsorption-desorption techniques， the adsorption isotherms， adsorption kinetics， and adsorption mechanism were explored， and the effects of Fe-KBC dosage， initial tetracycline concentration， temperature， and pH on adsorption performance were systematically examined. Characterization results revealed that Fe-KBC possessed a large specific surface area of 1293.74 m2/g and a layered structure. The adsorption results showed that Fe-KBC exhibited excellent adsorption performance for tetracycline， and the saturated adsorption capacity reached 113 mg/g， 4.74 times higher than that of the original biochar. The optimal adsorption conditions for TC with an initial concentration of 50 mg/L were as follows： a Fe-KBC dosage of 0.5 mg/L， a temperature of 35 ℃， and a pH value of 4. The adsorption process fitted well with the pseudo-second-order kinetics and Freundlich model， and the adsorption mechanism was dominated by chemisorption. After 5 cycles of reuse， the TC adsorption rate of Fe-KBC still remained above 88%， indicating its excellent stability. These findings provide a theoretical reference for the high-value utilization of chicken manure and the preparation of green and high-efficiency adsorbent materials.
In this paper， magnetic chicken manure biochar Fe-KBC was prepared by chicken manure， and its adsorption performance for tetracycline in aqueous solution was systematically investigated. Combined with FT-IR， SEM and N2 adsorption-desorption techniques， the adsorption isotherms， adsorption kinetics， and adsorption mechanism were explored， and the effects of Fe-KBC dosage， initial tetracycline concentration， temperature， and pH on adsorption performance were systematically examined. Characterization results revealed that Fe-KBC possessed a large specific surface area of 1293.74 m2/g and a layered structure. The adsorption results showed that Fe-KBC exhibited excellent adsorption performance for tetracycline， and the saturated adsorption capacity reached 113 mg/g， 4.74 times higher than that of the original biochar. The optimal adsorption conditions for TC with an initial concentration of 50 mg/L were as follows： a Fe-KBC dosage of 0.5 mg/L， a temperature of 35 ℃， and a pH value of 4. The adsorption process fitted well with the pseudo-second-order kinetics and Freundlich model， and the adsorption mechanism was dominated by chemisorption. After 5 cycles of reuse， the TC adsorption rate of Fe-KBC still remained above 88%， indicating its excellent stability. These findings provide a theoretical reference for the high-value utilization of chicken manure and the preparation of green and high-efficiency adsorbent materials.
2026, 44(9): 48-58.
doi: 10.13205/j.hjgc.202609006
Abstract:
To realize the high-value utilization of iron-containing industrial wastes and to develop an efficient and stable technology for dye wastewater treatment， iron-containing solid waste from the pharmaceutical industry was used as the primary iron source and composited with activated carbon to prepare a waste iron-slag-derived iron-carbon filler （ICF）. Based on this material， a low-cost heterogeneous peroxymonosulfate （PMS） activation system was constructed. The effects of the Fe/C mass ratio， PMS dosage， initial pH， and aeration rate on dye degradation performance were systematically investigated. Under the optimal conditions ［m（Fe）∶m（C）=1∶1， PMS=3 g/L， pH=3， and aeration rate of 0.5 L/min］， the ICF/PMS system could almost completely degrade 100 mg/L of Orange Ⅱ within 30 min and exhibited good universality toward various dyes with different molecular structures. Mechanistic investigations revealed that， unlike conventional iron-based PMS systems dominated by free-radical pathways， this system primarily follows a non-radical oxidation mechanism centered on Fe-C interfacial Fe—C—PMS* surface complexes and their transformation into high-valent iron species， Fe（Ⅳ）＝O， with singlet oxygen （1O2） and superoxide radicals （·O2-） playing synergistic roles. These findings demonstrate that this strategy not only enables the resource utilization of industrial solid wastes， but also provides a promising new technical route for efficient， stable， and economically feasible dye wastewater treatment.
To realize the high-value utilization of iron-containing industrial wastes and to develop an efficient and stable technology for dye wastewater treatment， iron-containing solid waste from the pharmaceutical industry was used as the primary iron source and composited with activated carbon to prepare a waste iron-slag-derived iron-carbon filler （ICF）. Based on this material， a low-cost heterogeneous peroxymonosulfate （PMS） activation system was constructed. The effects of the Fe/C mass ratio， PMS dosage， initial pH， and aeration rate on dye degradation performance were systematically investigated. Under the optimal conditions ［m（Fe）∶m（C）=1∶1， PMS=3 g/L， pH=3， and aeration rate of 0.5 L/min］， the ICF/PMS system could almost completely degrade 100 mg/L of Orange Ⅱ within 30 min and exhibited good universality toward various dyes with different molecular structures. Mechanistic investigations revealed that， unlike conventional iron-based PMS systems dominated by free-radical pathways， this system primarily follows a non-radical oxidation mechanism centered on Fe-C interfacial Fe—C—PMS* surface complexes and their transformation into high-valent iron species， Fe（Ⅳ）＝O， with singlet oxygen （1O2） and superoxide radicals （·O2-） playing synergistic roles. These findings demonstrate that this strategy not only enables the resource utilization of industrial solid wastes， but also provides a promising new technical route for efficient， stable， and economically feasible dye wastewater treatment.
2026, 44(9): 59-68.
doi: 10.13205/j.hjgc.202609007
Abstract:
Aromatic phenolic pollutants， due to their high concentration and widespread distribution characteristics， have posed a systematic threat to the stability of the ecosystem and human health. In this study， the pollutant-degrading bacterium Rhodococcus ruber-MSA14 was taken as the research object. A genome-scale metabolic model （GEMs） was constructed based on the COBRA framework. Methods such as flux balance analysis （FBA） and flux variability analysis （FVA） were employed to correct and validate the model. The substrate range of the model was broadened by using 37 carbon sources， and the advanced enzyme prediction tool （ECRECer） was utilized to supplement the annotation of key genes for m-cresol and 4-chlorophenol degradation. A high-quality model， GEMs_3， was constructed to simulate the metabolic flux analysis of m-cresol， 4-chlorophenol， and phenol. Fitting analysis were carried out between the actual growth and degradation and the model predictions. The research shows that there was a high correlation between the pollutant degradation trends simulated by the model and the experimental data. Specifically， for the degradation simulation of m-cresol， the R2 value was 0.9497； for the degradation simulation of 4-chlorophenol， the R2 value was 0.9556； and for the degradation simulation of phenol， the R2 value was 0.8281. Furthermore， the constructed model was used to analyze the potential over-expression targets of Rhodococcus ruber-MSA14 in pollutant degradation，and it provided specific targeting information for optimizing the degradation ability of the strain and its genetic modification. This study provides a theoretical basis for the application of Rhodococcus ruber-MSA14 in the degradation of aromatic phenolic pollutants and offers guidance for gene modification and bioremediation strategies based on metabolic networks.
Aromatic phenolic pollutants， due to their high concentration and widespread distribution characteristics， have posed a systematic threat to the stability of the ecosystem and human health. In this study， the pollutant-degrading bacterium Rhodococcus ruber-MSA14 was taken as the research object. A genome-scale metabolic model （GEMs） was constructed based on the COBRA framework. Methods such as flux balance analysis （FBA） and flux variability analysis （FVA） were employed to correct and validate the model. The substrate range of the model was broadened by using 37 carbon sources， and the advanced enzyme prediction tool （ECRECer） was utilized to supplement the annotation of key genes for m-cresol and 4-chlorophenol degradation. A high-quality model， GEMs_3， was constructed to simulate the metabolic flux analysis of m-cresol， 4-chlorophenol， and phenol. Fitting analysis were carried out between the actual growth and degradation and the model predictions. The research shows that there was a high correlation between the pollutant degradation trends simulated by the model and the experimental data. Specifically， for the degradation simulation of m-cresol， the R2 value was 0.9497； for the degradation simulation of 4-chlorophenol， the R2 value was 0.9556； and for the degradation simulation of phenol， the R2 value was 0.8281. Furthermore， the constructed model was used to analyze the potential over-expression targets of Rhodococcus ruber-MSA14 in pollutant degradation，and it provided specific targeting information for optimizing the degradation ability of the strain and its genetic modification. This study provides a theoretical basis for the application of Rhodococcus ruber-MSA14 in the degradation of aromatic phenolic pollutants and offers guidance for gene modification and bioremediation strategies based on metabolic networks.
2026, 44(9): 69-78.
doi: 10.13205/j.hjgc.202609008
Abstract:
3D bioprinting technology demonstrates significant potential in environmental science field， particularly in the construction of microbial active materials. This study successfully developed a biohydrogel loaded with Shewanella oneidensis MR-1 using extrusion-based bioprinting technology. The hydrogel enhances microbial metabolic activity and electron transfer efficiency by integrating adsorption and biological decolorization mechanisms， thereby improving the decolorization efficiency of azo dyes. Experimental results indicated that the three-dimensional porous network structure of the biohydrogel exhibits a superior decolorization rate compared to traditional bacterial suspensions. Further analysis of biomass and microbial metabolic activity reveals that the biohydrogel provides effective protection for the encapsulated bacteria， reducing the oxidative stress levels （ROS） in the system and significantly promoting biomass increase. Additionally， the content of cytochrome C in the hydrogel system increased by 1.31 times compared to the bacterial suspension， and the electron transfer system activity （ETSA） rose by 26.05%. These findings suggest that the protective effect of the hydrogel substantially enhances the electron transfer capacity within the system. This research， constructs a biohydrogel loaded with S. oneidensis MR-1 by bioprinting technology， which significantly improves the decolorization efficiency of azo dyes and reveals the synergistic mechanism between the hydrogel and the microbe， thus providing a novel strategy for the efficient degradation of water pollutants.
3D bioprinting technology demonstrates significant potential in environmental science field， particularly in the construction of microbial active materials. This study successfully developed a biohydrogel loaded with Shewanella oneidensis MR-1 using extrusion-based bioprinting technology. The hydrogel enhances microbial metabolic activity and electron transfer efficiency by integrating adsorption and biological decolorization mechanisms， thereby improving the decolorization efficiency of azo dyes. Experimental results indicated that the three-dimensional porous network structure of the biohydrogel exhibits a superior decolorization rate compared to traditional bacterial suspensions. Further analysis of biomass and microbial metabolic activity reveals that the biohydrogel provides effective protection for the encapsulated bacteria， reducing the oxidative stress levels （ROS） in the system and significantly promoting biomass increase. Additionally， the content of cytochrome C in the hydrogel system increased by 1.31 times compared to the bacterial suspension， and the electron transfer system activity （ETSA） rose by 26.05%. These findings suggest that the protective effect of the hydrogel substantially enhances the electron transfer capacity within the system. This research， constructs a biohydrogel loaded with S. oneidensis MR-1 by bioprinting technology， which significantly improves the decolorization efficiency of azo dyes and reveals the synergistic mechanism between the hydrogel and the microbe， thus providing a novel strategy for the efficient degradation of water pollutants.
2026, 44(9): 79-90.
doi: 10.13205/j.hjgc.202609009
Abstract:
Sintering flue gas is the main source of CO emissions in the iron and steel industry， and its high toxicity and impact on atmospheric quality have prompted China to set strict emission standards. Catalytic oxidation has become a mainstream technology due to its high efficiency and low energy consumption， but the poisoning problem of catalysts under complex flue gas components （e.g.， SO2， H2O） restricts its application. In this paper， the research progress of noble metal （Pt， Pd， Au） and non-precious metal （Cu， Mn， Fe） catalysts is systematically reviewed， and their CO oxidizing activity and anti-poisoning performance are compared. Although the noble metal catalysts have excellent activity， they are usually costly； the non-precious metal catalysts can be significantly improved by carrier modification （e.g.， CeO2， TiO2） and doping （e.g.， Mn， V）， which can bring the performance close to the level of the noble metals. Poisoning mechanism analysis showed that SO2 inhibits the reaction by forming sulfides to cover the active site or competing adsorption， while H2O affects the catalytic efficiency by competing adsorption or altering the distribution of oxygen species. Anti-toxicity strategies include optimization of carriers （e.g.， CeO2 preferentially binds SO2）， construction of bimetallic synergistic systems （e.g.， Cu-V composite oxides）， and surface capping techniques （e.g.， isolation of the active site by SiO2 shell layers）. Challenges such as low-temperature activity， high humidity adaptability， and stability need to be further addressed in the future to promote the industrial application of non-precious metal catalysts.
Sintering flue gas is the main source of CO emissions in the iron and steel industry， and its high toxicity and impact on atmospheric quality have prompted China to set strict emission standards. Catalytic oxidation has become a mainstream technology due to its high efficiency and low energy consumption， but the poisoning problem of catalysts under complex flue gas components （e.g.， SO2， H2O） restricts its application. In this paper， the research progress of noble metal （Pt， Pd， Au） and non-precious metal （Cu， Mn， Fe） catalysts is systematically reviewed， and their CO oxidizing activity and anti-poisoning performance are compared. Although the noble metal catalysts have excellent activity， they are usually costly； the non-precious metal catalysts can be significantly improved by carrier modification （e.g.， CeO2， TiO2） and doping （e.g.， Mn， V）， which can bring the performance close to the level of the noble metals. Poisoning mechanism analysis showed that SO2 inhibits the reaction by forming sulfides to cover the active site or competing adsorption， while H2O affects the catalytic efficiency by competing adsorption or altering the distribution of oxygen species. Anti-toxicity strategies include optimization of carriers （e.g.， CeO2 preferentially binds SO2）， construction of bimetallic synergistic systems （e.g.， Cu-V composite oxides）， and surface capping techniques （e.g.， isolation of the active site by SiO2 shell layers）. Challenges such as low-temperature activity， high humidity adaptability， and stability need to be further addressed in the future to promote the industrial application of non-precious metal catalysts.
2026, 44(9): 91-98.
doi: 10.13205/j.hjgc.202609010
Abstract:
Quantum electric furnaces are a type of steelmaking electric arc furnace capable of achieving efficient preheating of scrap steel，and have been widely applied in China in recent years. However， research on dioxin emissions and control from quantum electric furnaces is still in its infancy， and urgently requires systematic exploration and empirical supplementation. To study the emissions of dioxins from quantum electric furnaces， a 100-ton quantum electric furnace for smelting all scrap steel in East China was selected for test. Combined with the actual smelting process of the electric furnace， the concentration， three-phase distribution， and types of dioxins in the flue gas under different process cycles were tested and analyzed. The emission characteristics and spatio-temporal laws of dioxins from quantum electric furnaces were clarified， and the critical period for the generation of dioxins was determined. Combined with the preheating characteristics of scrap steel in the quantum electric furnace and the actual operation of the flue gas treatment system of the test electric furnace， the generation of dioxins and the reasons for exceeding the standard were analyzed， and an attempt was made to reduce the emission concentration of dioxins through the efficient activated carbon injection method. Finally， based on the analysis results and the current industry characteristics of electric furnace steelmaking in China， targeted strategies for dealing with dioxin emissions from electric furnaces were proposed.
Quantum electric furnaces are a type of steelmaking electric arc furnace capable of achieving efficient preheating of scrap steel，and have been widely applied in China in recent years. However， research on dioxin emissions and control from quantum electric furnaces is still in its infancy， and urgently requires systematic exploration and empirical supplementation. To study the emissions of dioxins from quantum electric furnaces， a 100-ton quantum electric furnace for smelting all scrap steel in East China was selected for test. Combined with the actual smelting process of the electric furnace， the concentration， three-phase distribution， and types of dioxins in the flue gas under different process cycles were tested and analyzed. The emission characteristics and spatio-temporal laws of dioxins from quantum electric furnaces were clarified， and the critical period for the generation of dioxins was determined. Combined with the preheating characteristics of scrap steel in the quantum electric furnace and the actual operation of the flue gas treatment system of the test electric furnace， the generation of dioxins and the reasons for exceeding the standard were analyzed， and an attempt was made to reduce the emission concentration of dioxins through the efficient activated carbon injection method. Finally， based on the analysis results and the current industry characteristics of electric furnace steelmaking in China， targeted strategies for dealing with dioxin emissions from electric furnaces were proposed.
2026, 44(9): 99-107.
doi: 10.13205/j.hjgc.202609011
Abstract:
Nitrogen dioxide （NO2） is a significant gaseous air pollutant， primarily originating from various human activities such as industrial production， coal combustion， and vehicle exhaust emissions. It poses substantial risks to both human health and the atmospheric environment. Adsorption technology has been widely applied in the fields of gaseous pollutant treatment， including NO2， as well as in the development of concentration detection sensors. Graphene， with its excellent two-dimensional structure， is considered a highly promising material for the adsorption of gaseous molecules. Graphene not only possesses a large specific surface area and excellent mechanical stability， but also has outstanding electron mobility and rapid photoresponse. In particular， its gas adsorption performance is significantly enhanced after doping and modification. Therefore， this study employed density functional theory （DFT） and the VASP computational software to conduct a systematic theoretical investigation into the adsorption behaviour of NO2 molecules on manganese-doped graphene. The results indicated that after doping with Mn， the adsorption capacity of the graphene material for NO2 molecules was significantly enhanced， and the doped Mn atoms became the key active adsorption sites for NO2 molecules. Unlike the predominantly physical adsorption process occurring on the surface of undoped graphene， the NO2 molecules exhibited a typical chemisorption process on the surface of Mn-doped graphene. Significant electron transfer occurred between the NO2 molecule and the Mn atom， and a stable chemical bond was formed between them. The optical properties of the entire system changed significantly before and after adsorption. The introduction of Mn not only enhanced the adsorption capacity for NO2 but also significantly altered the optical properties of the adsorption system. This demonstrates the excellent application potential of manganese-doped graphene materials in the adsorption and treatment of NO2， as well as in the field of gas concentration detection sensors.
Nitrogen dioxide （NO2） is a significant gaseous air pollutant， primarily originating from various human activities such as industrial production， coal combustion， and vehicle exhaust emissions. It poses substantial risks to both human health and the atmospheric environment. Adsorption technology has been widely applied in the fields of gaseous pollutant treatment， including NO2， as well as in the development of concentration detection sensors. Graphene， with its excellent two-dimensional structure， is considered a highly promising material for the adsorption of gaseous molecules. Graphene not only possesses a large specific surface area and excellent mechanical stability， but also has outstanding electron mobility and rapid photoresponse. In particular， its gas adsorption performance is significantly enhanced after doping and modification. Therefore， this study employed density functional theory （DFT） and the VASP computational software to conduct a systematic theoretical investigation into the adsorption behaviour of NO2 molecules on manganese-doped graphene. The results indicated that after doping with Mn， the adsorption capacity of the graphene material for NO2 molecules was significantly enhanced， and the doped Mn atoms became the key active adsorption sites for NO2 molecules. Unlike the predominantly physical adsorption process occurring on the surface of undoped graphene， the NO2 molecules exhibited a typical chemisorption process on the surface of Mn-doped graphene. Significant electron transfer occurred between the NO2 molecule and the Mn atom， and a stable chemical bond was formed between them. The optical properties of the entire system changed significantly before and after adsorption. The introduction of Mn not only enhanced the adsorption capacity for NO2 but also significantly altered the optical properties of the adsorption system. This demonstrates the excellent application potential of manganese-doped graphene materials in the adsorption and treatment of NO2， as well as in the field of gas concentration detection sensors.
2026, 44(9): 108-116.
doi: 10.13205/j.hjgc.202609012
Abstract:
The accurate prediction of SO2 concentration at the outlet of the desulfurization system in thermal power plants is crucial for operation optimization and pollution control. However， due to its nonlinearity， lag and multiple interfering factors， it is difficult to accurately predict the SO2 concentration at the outlet. A dynamic prediction model of SO2 concentration at the exit of the desulfurization system based on a temporal convolutional network （TCN） and bidirectional long short-term memory network （BiLSTM） was proposed. Firstly， the characteristic variables were selected by analyzing the mechanism and influencing factors of desulphurization. Then， the combined feature extraction algorithm was used to screen the variables highly related to the outlet SO2 concentration， and the redundant items were removed. Then， the optimal set of input variables was determined by using the black-winged kite algorithm （BKA） to intelligently optimize the order combination of input and output variables. Finally， based on the TCN-BiLSTM deep learning algorithm， the dynamic prediction model of SO2 concentration at the exit of the desulfurization system was constructed. Based on the actual operation data of the power plant， the experimental results showed that： after variable screening and order optimization， the accuracy of the model was significantly improved. The proposed TCN-BiLSTM model had excellent performance， with the best average absolute percentage error of 0.94%， the average absolute error of 0.15， and the root-mean-square error of 0.24. Compared with other models， the error performance index and prediction effect had been significantly improved， showing higher prediction accuracy and stronger fitting ability， which can effectively meet the actual field needs， to achieve real-time prediction of SO2 concentration at the exit of the desulfurization system， and to provide a reference basis for the optimization control of SO2 emission.
The accurate prediction of SO2 concentration at the outlet of the desulfurization system in thermal power plants is crucial for operation optimization and pollution control. However， due to its nonlinearity， lag and multiple interfering factors， it is difficult to accurately predict the SO2 concentration at the outlet. A dynamic prediction model of SO2 concentration at the exit of the desulfurization system based on a temporal convolutional network （TCN） and bidirectional long short-term memory network （BiLSTM） was proposed. Firstly， the characteristic variables were selected by analyzing the mechanism and influencing factors of desulphurization. Then， the combined feature extraction algorithm was used to screen the variables highly related to the outlet SO2 concentration， and the redundant items were removed. Then， the optimal set of input variables was determined by using the black-winged kite algorithm （BKA） to intelligently optimize the order combination of input and output variables. Finally， based on the TCN-BiLSTM deep learning algorithm， the dynamic prediction model of SO2 concentration at the exit of the desulfurization system was constructed. Based on the actual operation data of the power plant， the experimental results showed that： after variable screening and order optimization， the accuracy of the model was significantly improved. The proposed TCN-BiLSTM model had excellent performance， with the best average absolute percentage error of 0.94%， the average absolute error of 0.15， and the root-mean-square error of 0.24. Compared with other models， the error performance index and prediction effect had been significantly improved， showing higher prediction accuracy and stronger fitting ability， which can effectively meet the actual field needs， to achieve real-time prediction of SO2 concentration at the exit of the desulfurization system， and to provide a reference basis for the optimization control of SO2 emission.
2026, 44(9): 117-124.
doi: 10.13205/j.hjgc.202609013
Abstract:
Aiming at problems such as poor pollution control efficiency， high environmental protection energy consumption， and significant impact on material moisture content caused by the extensive operation of sprayer equipment in fugitive dust control of enclosed material yards， this study proposes a three-flow synergy theoretical framework of "production-energy-pollution" by integrating the characteristics of production operations， changes in pollution emissions， and energy consumption. A machine vision-guided dynamic spray dust suppression system is constructed. Through machine vision， real-time capture of characteristics of operating vehicles in the material yard is realized， and by integrating monitoring information of the material yard， a closed-loop linkage control system consisting of source identification， precise spraying， and effect feedback is established. This system achieves precise control of fog sprayers， realizing the transformation from passive response to active feedback in dust control of enclosed material yards. Application results in industrial sites show that the synchronization rate between the operation of yard vehicles and the operation of sprayers has increased by 60%， with a significant reduction in water and electricity consumption and a substantial improvement in dust collection efficiency. These improvements not only enhance equipment operating efficiency but also effectively control the problem of increased material moisture content caused by excessive spraying， thereby avoiding additional energy consumption in subsequent processes and helping the enterprise achieve annual comprehensive benefits of tens of millions of yuan. This study provides a practical demonstration of the intelligent application of three-flow synergy in the field of industrial environmental protection.
Aiming at problems such as poor pollution control efficiency， high environmental protection energy consumption， and significant impact on material moisture content caused by the extensive operation of sprayer equipment in fugitive dust control of enclosed material yards， this study proposes a three-flow synergy theoretical framework of "production-energy-pollution" by integrating the characteristics of production operations， changes in pollution emissions， and energy consumption. A machine vision-guided dynamic spray dust suppression system is constructed. Through machine vision， real-time capture of characteristics of operating vehicles in the material yard is realized， and by integrating monitoring information of the material yard， a closed-loop linkage control system consisting of source identification， precise spraying， and effect feedback is established. This system achieves precise control of fog sprayers， realizing the transformation from passive response to active feedback in dust control of enclosed material yards. Application results in industrial sites show that the synchronization rate between the operation of yard vehicles and the operation of sprayers has increased by 60%， with a significant reduction in water and electricity consumption and a substantial improvement in dust collection efficiency. These improvements not only enhance equipment operating efficiency but also effectively control the problem of increased material moisture content caused by excessive spraying， thereby avoiding additional energy consumption in subsequent processes and helping the enterprise achieve annual comprehensive benefits of tens of millions of yuan. This study provides a practical demonstration of the intelligent application of three-flow synergy in the field of industrial environmental protection.
2026, 44(9): 125-136.
doi: 10.13205/j.hjgc.202609014
Abstract:
This study developed a 1-km resolution emission inventory for Shanghai's vehicle sector in 2023， conducting detailed vehicle-type source analysis and high-resolution spatiotemporal analysis of vehicular air pollutant emissions. In 2023， Shanghai's vehicle emissions of carbon monoxide （CO）， hydrocarbons （HC）， nitrogen oxides （NOx ）， and fine particulate matter （PM2.5） were 103143 tons， 25301 tons， 89428 tons， and 1191 tons， respectively. CO and HC emissions were primarily from small passenger cars， contributing 71.3% and 75.4%， respectively， while NOx and PM2.5 emissions were mainly from heavy-duty trucks， contributing 77.5% and 57.6%， respectively. Temporal variations showed seasonal differences， with peak emissions in winter， significantly higher weekday emissions compared to weekends， and a bimodal daily emission pattern with morning and evening peaks. Spatially， vehicle pollutant emissions exhibited distinct patterns closely coupled with ring road structures， road types， and land functions. The central urban area， dominated by passenger cars， had the highest CO and HC emission intensities， decreasing with distance. In contrast， NOx and PM2.5 emissions were highest from the outer ring to suburban areas due to concentrated freight transport. Main roads were the primary emission sources， with gasoline vehicles contributing mainly to CO and HC， and diesel trucks contributing to NOx and PM2.5 on expressways. Emission hotspots were identified at road intersections and logistics nodes， reflecting the decisive impact of traffic structure and vehicle types on pollution distribution.
This study developed a 1-km resolution emission inventory for Shanghai's vehicle sector in 2023， conducting detailed vehicle-type source analysis and high-resolution spatiotemporal analysis of vehicular air pollutant emissions. In 2023， Shanghai's vehicle emissions of carbon monoxide （CO）， hydrocarbons （HC）， nitrogen oxides （NOx ）， and fine particulate matter （PM2.5） were 103143 tons， 25301 tons， 89428 tons， and 1191 tons， respectively. CO and HC emissions were primarily from small passenger cars， contributing 71.3% and 75.4%， respectively， while NOx and PM2.5 emissions were mainly from heavy-duty trucks， contributing 77.5% and 57.6%， respectively. Temporal variations showed seasonal differences， with peak emissions in winter， significantly higher weekday emissions compared to weekends， and a bimodal daily emission pattern with morning and evening peaks. Spatially， vehicle pollutant emissions exhibited distinct patterns closely coupled with ring road structures， road types， and land functions. The central urban area， dominated by passenger cars， had the highest CO and HC emission intensities， decreasing with distance. In contrast， NOx and PM2.5 emissions were highest from the outer ring to suburban areas due to concentrated freight transport. Main roads were the primary emission sources， with gasoline vehicles contributing mainly to CO and HC， and diesel trucks contributing to NOx and PM2.5 on expressways. Emission hotspots were identified at road intersections and logistics nodes， reflecting the decisive impact of traffic structure and vehicle types on pollution distribution.
2026, 44(9): 137-148.
doi: 10.13205/j.hjgc.202609015
Abstract:
To investigate the pollution characteristics and source variations of volatile organic compounds （VOCs） in Lanzhou's main urban area， hourly VOCs concentration data for 2021， 2022， and the first quarter of 2023 from the Atmospheric Composition Superstation at Lanzhou University were analyzed， and source apportionment was conducted using the positive matrix factorization （PMF） model. The analysis of pollution characteristics revealed that the annual average VOCs concentrations in Lanzhou's main urban area were 121.51 μg/m3 in 2021 and 104.43 μg/m3 in 2022. Oxygenated compounds， alkanes， and halogenated hydrocarbons were the dominant components of VOCs， collectively accounting for over 80% of the total VOCs composition. VOCs pollution exhibited seasonal variation， with lower concentrations in spring and summer and higher concentrations in autumn and winter. Most VOCs reached their peak concentrations in winter. The source apportionment results indicated that VOCs emissions in Lanzhou's main urban area were derived from six major sources： fuel combustion， industrial solvent use， transportation emissions， industrial production， petrochemical processing， and oil volatilization. The three major emission sources of VOCs were fuel combustion， industrial solvent use， and transportation emissions. The source apportionment results for typical seasons showed that industrial solvent use was the dominant emission source in summer， though its contribution share in 2022 decreased compared to 2021. Fuel combustion was the dominant emission source during the heating season， and its contribution share during the heating seasons of 2022-2023 increased significantly compared to the heating seasons of 2021-2022. These findings provide a basis for relevant authorities to formulate VOCs control policies.
To investigate the pollution characteristics and source variations of volatile organic compounds （VOCs） in Lanzhou's main urban area， hourly VOCs concentration data for 2021， 2022， and the first quarter of 2023 from the Atmospheric Composition Superstation at Lanzhou University were analyzed， and source apportionment was conducted using the positive matrix factorization （PMF） model. The analysis of pollution characteristics revealed that the annual average VOCs concentrations in Lanzhou's main urban area were 121.51 μg/m3 in 2021 and 104.43 μg/m3 in 2022. Oxygenated compounds， alkanes， and halogenated hydrocarbons were the dominant components of VOCs， collectively accounting for over 80% of the total VOCs composition. VOCs pollution exhibited seasonal variation， with lower concentrations in spring and summer and higher concentrations in autumn and winter. Most VOCs reached their peak concentrations in winter. The source apportionment results indicated that VOCs emissions in Lanzhou's main urban area were derived from six major sources： fuel combustion， industrial solvent use， transportation emissions， industrial production， petrochemical processing， and oil volatilization. The three major emission sources of VOCs were fuel combustion， industrial solvent use， and transportation emissions. The source apportionment results for typical seasons showed that industrial solvent use was the dominant emission source in summer， though its contribution share in 2022 decreased compared to 2021. Fuel combustion was the dominant emission source during the heating season， and its contribution share during the heating seasons of 2022-2023 increased significantly compared to the heating seasons of 2021-2022. These findings provide a basis for relevant authorities to formulate VOCs control policies.
2026, 44(9): 149-160.
doi: 10.13205/j.hjgc.202609016
Abstract:
This study analyzed the variations in PM2.5 pollution characteristics in Xi'an before and after the COVID-19 lockdown， based on seasonal observation data from 2019 to 2020. The results showed that during the lockdown period， PM2.5 concentrations in winter increased significantly， with the proportion of heavy pollution days rising by 23.4%， primarily due to the enhanced contribution of natural sources，such as dust. The chemical composition analysis revealed that the concentrations of anthropogenic secondary inorganic aerosols （e.g.， SO42-， NO3-） and organic matter （OM） decreased significantly， while the relative proportion of non-anthropogenic components （e.g.， dust） increased markedly due to the reduction in anthropogenic emissions. Principal component analysis （PCA） indicated that the pollution source structure shifted from coal combustion and biomass burning，to a dual-source pattern dominated by mixed pollution sources and natural dust. Additionally， air mass trajectory simulation demonstrated that enhanced long-range transport in winter further aggravated dust pollution. These findings provide new insights into the evolution mechanisms of air pollution under extreme emission reduction scenarios and offer a scientific basis for optimizing pollution control strategies in the post-pandemic era.
This study analyzed the variations in PM2.5 pollution characteristics in Xi'an before and after the COVID-19 lockdown， based on seasonal observation data from 2019 to 2020. The results showed that during the lockdown period， PM2.5 concentrations in winter increased significantly， with the proportion of heavy pollution days rising by 23.4%， primarily due to the enhanced contribution of natural sources，such as dust. The chemical composition analysis revealed that the concentrations of anthropogenic secondary inorganic aerosols （e.g.， SO42-， NO3-） and organic matter （OM） decreased significantly， while the relative proportion of non-anthropogenic components （e.g.， dust） increased markedly due to the reduction in anthropogenic emissions. Principal component analysis （PCA） indicated that the pollution source structure shifted from coal combustion and biomass burning，to a dual-source pattern dominated by mixed pollution sources and natural dust. Additionally， air mass trajectory simulation demonstrated that enhanced long-range transport in winter further aggravated dust pollution. These findings provide new insights into the evolution mechanisms of air pollution under extreme emission reduction scenarios and offer a scientific basis for optimizing pollution control strategies in the post-pandemic era.
2026, 44(9): 161-170.
doi: 10.13205/j.hjgc.202609017
Abstract:
Rapid temperature flips， characterized by abrupt transitions between warm and cold extremes within a short period， pose substantial challenges to regional climate variability， ecosystem stability， and socio-economic systems. Based on the CN05.1 High-Resolution Daily Gridded Temperature Dataset over China for 1979—2021 and concurrent reanalysis atmospheric circulation data， a regional-scale identification framework for rapid temperature flip events was developed by explicitly accounting for their temporal evolution and spatial continuity. By integrating rotated empirical orthogonal function （REOF） analysis with K-means clustering， China was divided into 14 homogeneous temperature regions. Within representative regions， rapid temperature flip events were further classified using a set of composite indices， including event duration， spatial coverage， transition time， and transition intensity. Composite analyses were then conducted to examine the evolution of atmospheric dynamical and thermodynamical variables before and after different types of events. The results reveal pronounced regional differences in both the frequency and structural characteristics of rapid temperature flips across China. Overall， cold-related flips occur more frequently than warm-related flips， with higher event frequency observed over the Pearl River Basin， the middle and lower reaches of the Yangtze River， and the Hetao region （the Great Bend of the Yellow River）. Distinct event types exhibit clear separations in spatial scale， persistence， and intensity. Despite these differences， the lifecycle evolution of precipitation， vertical motion， geopotential height， surface pressure， and specific humidity anomalies shows strong consistency across event types， indicating that rapid temperature flips can be understood within a unified large-scale circulation adjustment framework. These findings advance the understanding of rapid temperature reversals at the regional scale and provide a scientific basis for mechanism studies， monitoring strategies， and impact assessments of rapid temperature flip events.
Rapid temperature flips， characterized by abrupt transitions between warm and cold extremes within a short period， pose substantial challenges to regional climate variability， ecosystem stability， and socio-economic systems. Based on the CN05.1 High-Resolution Daily Gridded Temperature Dataset over China for 1979—2021 and concurrent reanalysis atmospheric circulation data， a regional-scale identification framework for rapid temperature flip events was developed by explicitly accounting for their temporal evolution and spatial continuity. By integrating rotated empirical orthogonal function （REOF） analysis with K-means clustering， China was divided into 14 homogeneous temperature regions. Within representative regions， rapid temperature flip events were further classified using a set of composite indices， including event duration， spatial coverage， transition time， and transition intensity. Composite analyses were then conducted to examine the evolution of atmospheric dynamical and thermodynamical variables before and after different types of events. The results reveal pronounced regional differences in both the frequency and structural characteristics of rapid temperature flips across China. Overall， cold-related flips occur more frequently than warm-related flips， with higher event frequency observed over the Pearl River Basin， the middle and lower reaches of the Yangtze River， and the Hetao region （the Great Bend of the Yellow River）. Distinct event types exhibit clear separations in spatial scale， persistence， and intensity. Despite these differences， the lifecycle evolution of precipitation， vertical motion， geopotential height， surface pressure， and specific humidity anomalies shows strong consistency across event types， indicating that rapid temperature flips can be understood within a unified large-scale circulation adjustment framework. These findings advance the understanding of rapid temperature reversals at the regional scale and provide a scientific basis for mechanism studies， monitoring strategies， and impact assessments of rapid temperature flip events.
2026, 44(9): 171-181.
doi: 10.13205/j.hjgc.202609018
Abstract:
The rapid expansion of rare earth elements （REEs） in high-tech and military fields and the shortage of exploitable resources are constantly widening the international supply gap. Since traditional REE enrichment processes （physical/chemical methods） are often associated with environmental pollution， microbial adsorption has been regarded as an important research focus for achieving the efficient utilization of REE resources and ensuring their sustainable development. Functional strains can effectively enrich REEs from low-concentration solutions through multi-level mechanisms， such as surface adsorption， biomineralization， and intracellular accumulation. At present， although this technology still faces challenges in practical applications， including insufficient environmental tolerance and high costs， the increasing number of related studies， such as strain modification， composite material development， and multi-process integration， is continuously promoting its large-scale application. In the future， continued exploration of functional strains， elucidation of their adsorption mechanisms， directional optimization of strain functionality， and further investigation of multi-process coupling technology， etc.， are expected to enable the industrial application of microbial technology for REE （ions） adsorption.
The rapid expansion of rare earth elements （REEs） in high-tech and military fields and the shortage of exploitable resources are constantly widening the international supply gap. Since traditional REE enrichment processes （physical/chemical methods） are often associated with environmental pollution， microbial adsorption has been regarded as an important research focus for achieving the efficient utilization of REE resources and ensuring their sustainable development. Functional strains can effectively enrich REEs from low-concentration solutions through multi-level mechanisms， such as surface adsorption， biomineralization， and intracellular accumulation. At present， although this technology still faces challenges in practical applications， including insufficient environmental tolerance and high costs， the increasing number of related studies， such as strain modification， composite material development， and multi-process integration， is continuously promoting its large-scale application. In the future， continued exploration of functional strains， elucidation of their adsorption mechanisms， directional optimization of strain functionality， and further investigation of multi-process coupling technology， etc.， are expected to enable the industrial application of microbial technology for REE （ions） adsorption.
2026, 44(9): 182-192.
doi: 10.13205/j.hjgc.202609019
Abstract:
This study employed the Life Cycle Assessment （LCA） methodology to systematically compare the environmental impacts of two waste oil regeneration processes： membrane separation purification and distillation purification. A comprehensive evaluation based on characterization， standardization， and uncertainty and sensitivity analyses indicates that the membrane separation process offers significant environmental advantages. The environmental impacts at each stage were consistently lower than those of the distillation process， with reductions of approximately 57.5% and 56.2% in climate change and fossil resource depletion， respectively. End-point damage analysis revealed that the total environmental damage score for the membrane separation process was 7.219 Pt， a reduction of 59.6% compared to the distillation process （17.863 Pt）， and it performed better in terms of human health， ecosystem quality， and resource consumption. Uncertainty analysis indicated that the membrane separation process had a lower coefficient of variation （9.79%）， yielding more robust results. Sensitivity analysis further revealed that energy consumption was the primary driver of environmental damage for both processes. In summary， the membrane separation refining process is the preferred choice for waste oil regeneration technology， offering superior environmental performance and more reliable results； improvements to the distillation refining process should prioritise energy conservation and optimisation of the energy mix. This study provides a scientific basis for green decision-making regarding waste oil regeneration technologies.
This study employed the Life Cycle Assessment （LCA） methodology to systematically compare the environmental impacts of two waste oil regeneration processes： membrane separation purification and distillation purification. A comprehensive evaluation based on characterization， standardization， and uncertainty and sensitivity analyses indicates that the membrane separation process offers significant environmental advantages. The environmental impacts at each stage were consistently lower than those of the distillation process， with reductions of approximately 57.5% and 56.2% in climate change and fossil resource depletion， respectively. End-point damage analysis revealed that the total environmental damage score for the membrane separation process was 7.219 Pt， a reduction of 59.6% compared to the distillation process （17.863 Pt）， and it performed better in terms of human health， ecosystem quality， and resource consumption. Uncertainty analysis indicated that the membrane separation process had a lower coefficient of variation （9.79%）， yielding more robust results. Sensitivity analysis further revealed that energy consumption was the primary driver of environmental damage for both processes. In summary， the membrane separation refining process is the preferred choice for waste oil regeneration technology， offering superior environmental performance and more reliable results； improvements to the distillation refining process should prioritise energy conservation and optimisation of the energy mix. This study provides a scientific basis for green decision-making regarding waste oil regeneration technologies.
2026, 44(9): 193-201.
doi: 10.13205/j.hjgc.202609020
Abstract:
The extensive release of plastic waste into the environment has caused severe pollution. The development and application of biodegradable plastics， such as poly（butylene adipate-co-terephthalate） （PBAT） represent a critical measure to address plastic pollution. However， the actual degradation process of biodegradable plastics in natural environments often proceeds slowly and incompletely， still carrying risks of environmental accumulation and microplastic formation. Therefore， rapid and complete degradation of PBAT and other biodegradable plastics is necessary， and there is an urgent need to develop efficient degradation technologies to mitigate their ecotoxicity. Microbial action is an important part of plastic degradation， and the discovery of highly efficient plastic-degrading strains is the key to the technology involved. A bacterial strain capable of efficiently degrading PBAT plastic was isolated from PBAT-contaminated farmland soil. It was identified as Bacillus sp. HYX-38 through 16S rRNA gene sequencing. Degradation efficiency assays under various conditions revealed that strain HYX-38 efficiently degrades PBAT in nutrient-rich environments without being subject to carbon catabolite repression. When cultivated in 100 mL of TSB medium at 30 ℃， strain HYX-38 exhibited its highest degradation rate within the first 10 days， averaging 3.41 mg/d， with a degradation rate of 17.03%， demonstrating superior performance compared to other known PBAT-degrading strains. Enzyme activity assays confirmed that strain HYX-38 produces protease， lipase， amylase， and catalase. Characterizations using scanning electron microscopy （SEM）， gel permeation chromatography （GPC）， Fourier transform infrared spectroscopy （FTIR）， thermogravimetric analysis （TGA）， and X-ray diffraction （XRD） revealed significant surface cracks， lower molecular weight， structural alterations， reduced thermal stability， and decreased crystallinity in the degraded PBAT film， confirming substantial degradation. The LC-MS results indicated that strain HYX-38 degraded the PBAT film into its monomers： 1，4-butanediol， adipic acid， and terephthalic acid. Whole-genome sequencing identified multiple protein-coding genes in the strain HYX-38， which show high similarity to known plastic-degrading enzyme genes， suggesting that these enzymes could serve as potential targets for future engineering applications. The highly efficient PBAT-degrading strain HYX-38 enriches the microbial resources for plastic degradation， contributes significantly to addressing plastic pollution， and promotes the rational utilization of biodegradable plastics.
The extensive release of plastic waste into the environment has caused severe pollution. The development and application of biodegradable plastics， such as poly（butylene adipate-co-terephthalate） （PBAT） represent a critical measure to address plastic pollution. However， the actual degradation process of biodegradable plastics in natural environments often proceeds slowly and incompletely， still carrying risks of environmental accumulation and microplastic formation. Therefore， rapid and complete degradation of PBAT and other biodegradable plastics is necessary， and there is an urgent need to develop efficient degradation technologies to mitigate their ecotoxicity. Microbial action is an important part of plastic degradation， and the discovery of highly efficient plastic-degrading strains is the key to the technology involved. A bacterial strain capable of efficiently degrading PBAT plastic was isolated from PBAT-contaminated farmland soil. It was identified as Bacillus sp. HYX-38 through 16S rRNA gene sequencing. Degradation efficiency assays under various conditions revealed that strain HYX-38 efficiently degrades PBAT in nutrient-rich environments without being subject to carbon catabolite repression. When cultivated in 100 mL of TSB medium at 30 ℃， strain HYX-38 exhibited its highest degradation rate within the first 10 days， averaging 3.41 mg/d， with a degradation rate of 17.03%， demonstrating superior performance compared to other known PBAT-degrading strains. Enzyme activity assays confirmed that strain HYX-38 produces protease， lipase， amylase， and catalase. Characterizations using scanning electron microscopy （SEM）， gel permeation chromatography （GPC）， Fourier transform infrared spectroscopy （FTIR）， thermogravimetric analysis （TGA）， and X-ray diffraction （XRD） revealed significant surface cracks， lower molecular weight， structural alterations， reduced thermal stability， and decreased crystallinity in the degraded PBAT film， confirming substantial degradation. The LC-MS results indicated that strain HYX-38 degraded the PBAT film into its monomers： 1，4-butanediol， adipic acid， and terephthalic acid. Whole-genome sequencing identified multiple protein-coding genes in the strain HYX-38， which show high similarity to known plastic-degrading enzyme genes， suggesting that these enzymes could serve as potential targets for future engineering applications. The highly efficient PBAT-degrading strain HYX-38 enriches the microbial resources for plastic degradation， contributes significantly to addressing plastic pollution， and promotes the rational utilization of biodegradable plastics.
2026, 44(9): 202-213.
doi: 10.13205/j.hjgc.202609021
Abstract:
In urban carbon inventories， wastewater treatment plants （WWTPs） represent a considerable emission source that cannot be overlooked. As urbanization progresses， the continuous increase in newly constructed and expanded small-town WWTPs necessitates a clear understanding of their carbon emission characteristics to promote the effective implementation of the dual-carbon policy. This study， based on the IPCC methodology and national accounting guidelines， cond ucted carbon emission accounting and characteristic analysis on four small-town WWTPs in a certain area of Suzhou. These plants have similar treatment scales and chemical usage but differ in biological treatment processes. The analysis was performed on annual， seasonal， and consecutive monthly scales. The results showed that electricity and chemical consumption were the primary sources of carbon emissions， with comparable contributions. The carbon emission intensity ranged from 0.43 to 0.99 kg CO2/m3. Emissions varied by process type in the following order： mpa A2O-OD + mA2O < ASAO < SBR + CASS < AA/RPIR + rA2O. Seasonal analysis revealed that the share of chemical-related emissions was higher in summer and winter. The correlation analysis of factors such as electricity consumption， chemicals consumption， operation characteristics of biochemical section， and water quality on carbon emission level showed that carbon emissions were affected by multi-factor coupling， with no single significant determinant. Compared with medium-scale and large-scale WWTPs， small-town plants exhibited higher carbon emissions per unit of treated wastewater. Based on these findings， targeted low-carbon optimization strategies were proposed for small-town WWTPs.
In urban carbon inventories， wastewater treatment plants （WWTPs） represent a considerable emission source that cannot be overlooked. As urbanization progresses， the continuous increase in newly constructed and expanded small-town WWTPs necessitates a clear understanding of their carbon emission characteristics to promote the effective implementation of the dual-carbon policy. This study， based on the IPCC methodology and national accounting guidelines， cond ucted carbon emission accounting and characteristic analysis on four small-town WWTPs in a certain area of Suzhou. These plants have similar treatment scales and chemical usage but differ in biological treatment processes. The analysis was performed on annual， seasonal， and consecutive monthly scales. The results showed that electricity and chemical consumption were the primary sources of carbon emissions， with comparable contributions. The carbon emission intensity ranged from 0.43 to 0.99 kg CO2/m3. Emissions varied by process type in the following order： mpa A2O-OD + mA2O < ASAO < SBR + CASS < AA/RPIR + rA2O. Seasonal analysis revealed that the share of chemical-related emissions was higher in summer and winter. The correlation analysis of factors such as electricity consumption， chemicals consumption， operation characteristics of biochemical section， and water quality on carbon emission level showed that carbon emissions were affected by multi-factor coupling， with no single significant determinant. Compared with medium-scale and large-scale WWTPs， small-town plants exhibited higher carbon emissions per unit of treated wastewater. Based on these findings， targeted low-carbon optimization strategies were proposed for small-town WWTPs.
2026, 44(9): 214-220.
doi: 10.13205/j.hjgc.202609022
Abstract:
Against the backdrop of the “dual carbon” goals， exploring how underground wastewater treatment plants can enhance process innovation and scientific regulation based on their own characteristics， and maximize the use of existing conditions to achieve energy conservation and consumption reduction， remains an urgent issue for the wastewater treatment industry. By analyzing the main power consumption components and operating modes of high-power electrical equipment， an underground wastewater treatment plant in Zhengzhou successfully reduced its average annual power consumption from 0.416 kW·h/m3 to 0.340 kW·h/m3 through precise aeration， optimized equipment operation， and technological innovation， representing an 18.27% effective decrease in specific power consumption. Notably， indicators including the air-water ratio， electricity consumption per ton of water for blowers， annual electricity consumption per ton of water for influent pumps， and annual electricity consumption of ventilation fans and lighting facilities all decreased significantly， with each reduction exceeding 5%. This practice has yielded remarkable results in energy conservation and consumption reduction， and the plant's production and operation capacity has reached an advanced level in terms of energy consumption for urban wastewater treatment in some regions. It provides a practical reference for the low-carbon operation of similar underground wastewater treatment plants.
Against the backdrop of the “dual carbon” goals， exploring how underground wastewater treatment plants can enhance process innovation and scientific regulation based on their own characteristics， and maximize the use of existing conditions to achieve energy conservation and consumption reduction， remains an urgent issue for the wastewater treatment industry. By analyzing the main power consumption components and operating modes of high-power electrical equipment， an underground wastewater treatment plant in Zhengzhou successfully reduced its average annual power consumption from 0.416 kW·h/m3 to 0.340 kW·h/m3 through precise aeration， optimized equipment operation， and technological innovation， representing an 18.27% effective decrease in specific power consumption. Notably， indicators including the air-water ratio， electricity consumption per ton of water for blowers， annual electricity consumption per ton of water for influent pumps， and annual electricity consumption of ventilation fans and lighting facilities all decreased significantly， with each reduction exceeding 5%. This practice has yielded remarkable results in energy conservation and consumption reduction， and the plant's production and operation capacity has reached an advanced level in terms of energy consumption for urban wastewater treatment in some regions. It provides a practical reference for the low-carbon operation of similar underground wastewater treatment plants.
2026, 44(9): 221-227.
doi: 10.13205/j.hjgc.202609023
Abstract:
Current methods for detecting CO2 concentration in flue gas pollution sources rely heavily on manual statistics， which leads to significant errors and poor real-time performance. To address these issues， this paper proposed a CO2 monitoring method based on dual-channel infrared differential spectroscopy， and developed an online CO2 concentration monitoring system. A 10-cm-long direct-type circular gas cell was designed and fabricated， guided by Zemax optical path simulation. A signal detection hardware and software system was developed， featuring a Cortex-M3 core microcontroller and the FreeRTOS real-time operating system， enabling online monitoring of CO2 concentrations in flue gas pollution sources. Experimental results demonstrated that within the volume fraction range of 0% to 20%， the indicated value error reached 0.78% of full scale. The 24-hour zero drift and span drift were -0.15% and -0.9%， respectively， and the system response time was as low as 27 seconds. This monitoring system offers high accuracy， strong stability， and fast response， providing reliable data support for online monitoring of flue gas pollution sources.
Current methods for detecting CO2 concentration in flue gas pollution sources rely heavily on manual statistics， which leads to significant errors and poor real-time performance. To address these issues， this paper proposed a CO2 monitoring method based on dual-channel infrared differential spectroscopy， and developed an online CO2 concentration monitoring system. A 10-cm-long direct-type circular gas cell was designed and fabricated， guided by Zemax optical path simulation. A signal detection hardware and software system was developed， featuring a Cortex-M3 core microcontroller and the FreeRTOS real-time operating system， enabling online monitoring of CO2 concentrations in flue gas pollution sources. Experimental results demonstrated that within the volume fraction range of 0% to 20%， the indicated value error reached 0.78% of full scale. The 24-hour zero drift and span drift were -0.15% and -0.9%， respectively， and the system response time was as low as 27 seconds. This monitoring system offers high accuracy， strong stability， and fast response， providing reliable data support for online monitoring of flue gas pollution sources.
2026, 44(9): 228-235.
doi: 10.13205/j.hjgc.202609024
Abstract:
Railway transportation is an essential part of the transportation sector and faces increasingly severe challenges in emission reduction. Research on carbon quota allocation serves as a prerequisite for improving the carbon quota management efficiency of railway transportation enterprises and promoting the low-carbon development of the railway industry. This study calculated the carbon emissions of 18 railway bureaus and constructed a carbon quota allocation model based on the ESG （Environmental， Social， and Governance） principles to ensure the sustainability of carbon quota distribution. The results showed that from 2016 to 2023， the carbon emissions of railway transportation enterprises increased from 57.03 million tons to 66.93 million tons， representing an increase of 17.36%. Under the ESG principles， Shanghai Railway Bureau， Beijing Railway Bureau， and Guangzhou Railway Bureau， which are characterized by higher transportation intensity and lower emission intensity， were allocated higher quotas of 6.3550 million tons， 6.1814 million tons， and 5.4883 million tons， respectively； whereas ecologically sensitive regions such as Qinghai-Tibet Railway Group and Kunming Railway Bureau obtained additional quotas of 2.3085 million tons and 2.7956 million tons， respectively， through inter-regional coordination. To promote the green transformation of the railway industry， measures such as establishing special funds for low-carbon technology research and development， creating provincial carbon trading platforms， and building dynamic evaluation mechanisms should be implemented. These initiatives will lay the foundation for extending the carbon trading market to the transportation sector.
Railway transportation is an essential part of the transportation sector and faces increasingly severe challenges in emission reduction. Research on carbon quota allocation serves as a prerequisite for improving the carbon quota management efficiency of railway transportation enterprises and promoting the low-carbon development of the railway industry. This study calculated the carbon emissions of 18 railway bureaus and constructed a carbon quota allocation model based on the ESG （Environmental， Social， and Governance） principles to ensure the sustainability of carbon quota distribution. The results showed that from 2016 to 2023， the carbon emissions of railway transportation enterprises increased from 57.03 million tons to 66.93 million tons， representing an increase of 17.36%. Under the ESG principles， Shanghai Railway Bureau， Beijing Railway Bureau， and Guangzhou Railway Bureau， which are characterized by higher transportation intensity and lower emission intensity， were allocated higher quotas of 6.3550 million tons， 6.1814 million tons， and 5.4883 million tons， respectively； whereas ecologically sensitive regions such as Qinghai-Tibet Railway Group and Kunming Railway Bureau obtained additional quotas of 2.3085 million tons and 2.7956 million tons， respectively， through inter-regional coordination. To promote the green transformation of the railway industry， measures such as establishing special funds for low-carbon technology research and development， creating provincial carbon trading platforms， and building dynamic evaluation mechanisms should be implemented. These initiatives will lay the foundation for extending the carbon trading market to the transportation sector.
2026, 44(9): 236-244.
doi: 10.13205/j.hjgc.202609025
Abstract:
The revised Industrial and Livestock Rearing Emissions Directive （IED 2.0） is not only the European Union's primary legislation regulating pollutant emissions from industrial facilities and livestock farming， but also a key policy for promoting the synergistic reduction of pollution and carbon emissions. Based on the EU's revision and release of IED 2.0， this study reviews the background and main amendments of the directive， summarizes its requirements and features regarding the synergistic control of pollution and carbon reduction， and analyzes its implications for China in light of its actual conditions. IED 2.0 emphasizes achieving high-quality protection of the “overall environment” with many provisions aimed at promoting the synergistic reduction of pollution and carbon emissions. Key features include： 1）Using assessment results as an important basis for the revision of IED 2.0； 2）Integrating pollutant reduction and decarbonization into emission reduction targets； 3）Utilizing permits and environmental management systems as key tools； 4）Ensuring the maximization of benefits from selected and implemented emission reduction technologies； 5）Emphasizing the enhancement of synergies between environmental and climate policies； 6）Focusing on the multiple benefits of reducing non-CO2 greenhouse gas emissions； 7）Promoting corporate emission reduction and industrial transformation through technological innovation. Implications for China include： 1）Promote the synergistic reduction of pollution and carbon emissions in key sectors through legal and regulatory frameworks； 2）Strengthen the evaluation of the effectiveness of policies and actions related to synergistic pollution and carbon reduction； 3）Incorporate greenhouse gas emission reduction requirements into the management of stationary source emission permits； 4）Develop best available technology guidelines for synergistic pollution and carbon reduction in key industries； 5）Require energy-intensive industries to establish management systems for synergistic pollution and carbon reduction； 6）Emphasize the synergistic reduction of non-CO2 greenhouse gases （such as methane） and pollutants； 7）Encourage stakeholders to participate in decision-making for synergistic pollution and carbon reduction.
The revised Industrial and Livestock Rearing Emissions Directive （IED 2.0） is not only the European Union's primary legislation regulating pollutant emissions from industrial facilities and livestock farming， but also a key policy for promoting the synergistic reduction of pollution and carbon emissions. Based on the EU's revision and release of IED 2.0， this study reviews the background and main amendments of the directive， summarizes its requirements and features regarding the synergistic control of pollution and carbon reduction， and analyzes its implications for China in light of its actual conditions. IED 2.0 emphasizes achieving high-quality protection of the “overall environment” with many provisions aimed at promoting the synergistic reduction of pollution and carbon emissions. Key features include： 1）Using assessment results as an important basis for the revision of IED 2.0； 2）Integrating pollutant reduction and decarbonization into emission reduction targets； 3）Utilizing permits and environmental management systems as key tools； 4）Ensuring the maximization of benefits from selected and implemented emission reduction technologies； 5）Emphasizing the enhancement of synergies between environmental and climate policies； 6）Focusing on the multiple benefits of reducing non-CO2 greenhouse gas emissions； 7）Promoting corporate emission reduction and industrial transformation through technological innovation. Implications for China include： 1）Promote the synergistic reduction of pollution and carbon emissions in key sectors through legal and regulatory frameworks； 2）Strengthen the evaluation of the effectiveness of policies and actions related to synergistic pollution and carbon reduction； 3）Incorporate greenhouse gas emission reduction requirements into the management of stationary source emission permits； 4）Develop best available technology guidelines for synergistic pollution and carbon reduction in key industries； 5）Require energy-intensive industries to establish management systems for synergistic pollution and carbon reduction； 6）Emphasize the synergistic reduction of non-CO2 greenhouse gases （such as methane） and pollutants； 7）Encourage stakeholders to participate in decision-making for synergistic pollution and carbon reduction.
2026, 44(9): 245-254.
doi: 10.13205/j.hjgc.202609026
Abstract:
To support the ecological protection， high-quality development， and the achievement of the Dual Carbon Goals in the Yellow River Basin， this study systematically investigated the spatiotemporal variations and regional disparityies of carbon emissions in the basin. Drawing on carbon emission data from 69 prefecture-level cities in the Yellow River Basin for the period 1997 to 2020， this study employed methods including the Theil index， kernel density estimation， standard deviational ellipse， and Moran's I index. The results indicated that the total carbon emissions in the Yellow River Basin exhibited an overall upward trend from 1997 to 2020， but the growth rate reduced significantly after 2011. Notable regional disparities existed but gradually narrowed： carbon emissions in the upper reaches grew the fastest， followed by those in the middle reaches， while those in the lower reaches remained relatively stable. In terms of spatial distribution， the center of carbon emissions shifted westward， and the distribution pattern transitioned from agglomeration to dispersion， with the spatial agglomeration effect weakening over time. Moran's I index revealed a significant positive spatial autocorrelation of carbon emissions， although this agglomeration effect also showed a weakening trend. Based on these findings， this study proposed formulating differentiated emission reduction policies for the upper， middle， and lower reaches of the basin and strengthening regional collaborative governance， thereby providing a scientific reference for promoting the green and low-carbon transformation of the Yellow River Basin.
To support the ecological protection， high-quality development， and the achievement of the Dual Carbon Goals in the Yellow River Basin， this study systematically investigated the spatiotemporal variations and regional disparityies of carbon emissions in the basin. Drawing on carbon emission data from 69 prefecture-level cities in the Yellow River Basin for the period 1997 to 2020， this study employed methods including the Theil index， kernel density estimation， standard deviational ellipse， and Moran's I index. The results indicated that the total carbon emissions in the Yellow River Basin exhibited an overall upward trend from 1997 to 2020， but the growth rate reduced significantly after 2011. Notable regional disparities existed but gradually narrowed： carbon emissions in the upper reaches grew the fastest， followed by those in the middle reaches， while those in the lower reaches remained relatively stable. In terms of spatial distribution， the center of carbon emissions shifted westward， and the distribution pattern transitioned from agglomeration to dispersion， with the spatial agglomeration effect weakening over time. Moran's I index revealed a significant positive spatial autocorrelation of carbon emissions， although this agglomeration effect also showed a weakening trend. Based on these findings， this study proposed formulating differentiated emission reduction policies for the upper， middle， and lower reaches of the basin and strengthening regional collaborative governance， thereby providing a scientific reference for promoting the green and low-carbon transformation of the Yellow River Basin.
