三峡库区主要森林植被类型土壤有机碳贮量研究

根据全国森林资源清查资料,按主要优势树种和分布面积将三峡库区主要森林植被划分为马尾松针叶林、栎类混交林、灌木林等11种主要森林植被类型。基于196个土壤剖面数据,分析了11种主要森林植被类型下土壤有机碳含量、碳密度大小和分配特征。研究发现,三峡库区主要森林植被类型下土壤有机碳含量和碳密度均存在较大差异,二者总体上都随土层加深而降低。11种主要森林植被类型中以杉木针叶林土壤有机碳密度最大,达16.0 kg/m2,温性松林下土壤碳密度最小,仅为7.9 kg/m2。不同植被类型下土壤有机碳贮量在土层中的分配比例也不同,以灌木林和柏木林土壤碳贮量在土层间的差异最大。11种主要森林植被类型土壤平均厚度为56.3～98.5 cm,其中杉木针叶林土壤最厚,达98.5 cm,灌丛土壤最薄,平均厚度仅56.3 cm。三峡库区11种主要森林植被类型总面积为3 313 251 hm2,土壤总有机碳贮量为 366.36 t,其中0～10、10～20、20～40和＞40 cm土层分别占22.90%、18.36%、28.33%和30.41%。     

Toward sustainable use of natural resources: Nexus between resource rents,affluence, energy intensity and carbon emissions in developing and transition economies

Sustainable use of natural resources would entail ensuring that derived economic benefits today do not undermine the welfare of generations to come. On this basis, this study examines the nexus between natural resource rents and carbon dioxide (CO₂) emissions disaggregated into production and consumption-based (i.e., trade-adjusted) CO₂ emissions for a selected panel of 45 developing and transition economies over the period 1995–2017. The empirical model also incorporates the impacts of population, affluence, and energy intensity. The results show that affluence increases production-based CO₂ emissions by 1.407%, with the EKC's predicted inverted U-shaped curve only explaining consumption-based CO₂ emissions. Economic reliance on natural resource rents and energy intensification contribute 0.022% and 0.766%, respectively, to CO₂ emissions embedded in territorial production inventories and 0.035% and 0.583%, respectively, to CO₂ emissions embedded in consumption inventories. The bootstrap non-causality test shows that historical data on each variable has significant predictive power for future CO₂ emissions from both sources. The historical information about natural resource rents has significant predictive power over the future levels of affluence and energy intensity. Clearly, the results show that the environmental impact of natural resource rents is stronger when CO₂ emissions are adjusted for trade and varies among the countries, with Bangladesh, Guinea, India, Malaysia, Mexico, Nigeria, Pakistan, Saudi Arabia, Vietnam, and Zimbabwe among the most affected countries. Overall, this study provides motivation for policies to keep the use of natural resources within sustainable limits.     

A discussion to promote global sustainability techniques for motivating plastic waste to minimize carbon footprints

This paper emphasizes the significant challenges facing the sustainable environment, including managing and handling plastic waste and reducing carbon footprints. To tackle these challenges, it is essential to identify people's awareness levels of waste handling techniques and their pro-environmental behaviors. The study focuses on Guwahati, one of the most important cities in Northeast India, which generates increasing plastic waste daily. The paper aims to identify the factors contributing to the reduction of carbon footprints resulting from plastic waste management activities. The data collected from 1326 respondents was analyzed using factor analysis, and the reliability of the dataset was confirmed using Cronbach's alpha (0.84 for the awareness level of waste management techniques and 0.780 for the prevalent mode of plastic waste management techniques). KMO (0.796), Bartlett's test of sphericity (p < 0.001), and determinant score (0.019) were used to assess the data adequacy and factorability of the dataset, and the results were found to be satisfactory. Principal component analysis, exploratory factor analysis, and varimax orthogonal rotation method were used to identify high-loaded factors by reducing the number of variables. The results showed that two highly loaded components, namely awareness level of waste management techniques (AWMT) and prevalent mode of plastic waste management techniques (PWMT), explained 27.53% and 24.34% of the total variance, respectively, with eigenvalues of 3.35 and 2.88. The regression model confirmed the statistical significance of these factors (p < 0.001) and their relationship with the dependent variable, greenhouse reduction (GHGR). The study proposes that minimizing carbon footprints in the environment can be achieved by focusing on a limited number of controllable factors such as AWMT and PWMT. This study provides valuable insights to the authorities in controlling waste generation and achieving a pollution-free environment.     

中国铜产业体系演化的碳中和实现机制研究

本文研究了我国铜产业采选、冶炼、加工和再生等环节的演化趋势,构建了铜产业直接碳排放-能源间接排放-其他间接排放相结合的多层级碳排放核算模型,分析了我国铜产业各环节碳排放演变规律及碳中和实现机制。结果表明：①1980-2020年我国铜精矿、精炼铜、铜加工材、再生铜产品分别增长了6.6倍、 25.1倍、 88.5倍、 37.1倍,受碳中和目标实现对电力需求量增加的影响,预计2060年铜资源消费总量将较2020年提升62.3%,铜资源社会存量将达到3.9亿t,再生铜将于2030年超过原生铜成为主导资源类型。②2020年铜产业的碳排放总量达到2968.2万tCO₂e,其中,采选环节的吨铜碳排放量最高,达到了3.4tCO₂e,是第二位冶炼的2.3倍;冶炼环节的碳排放总量最大,达到铜产业的39.3%;再生环节的降碳效果突出,相较原生采选冶炼环节减少1251.2万tCO₂e;进出口贸易则进一步降低了该产业43.7%的碳排放总量。③预计2060年铜产业碳排放总量将达到1499.8万tCO₂e,通过促进国际贸易、循环经济、技术创新及环境市场建设等举措,可大幅降低产业的碳排放总量,其中国际贸易及循环经济情景的碳减排效果在2030年前均较显著、随后逐渐下降,技术创新及环境市场建设是该产业碳中和目标实现的根本,在2060年的减排潜力分别达到535.9万t及607.9万t。为了更好地促进该产业可持续发展及“双碳”目标实现,建议依托国内国际双循环格局合理调控铜产业结构,秉持全生命周期理念加快构建铜产业绿色供应链,紧随碳中和发展趋势促进资源循环减污降碳协同增效。     

碳标签对低碳购买意愿的作用路径研究——基于亲社会行为调节的中介效应

降低消费阶段的碳排放量对实现国家“双碳”战略目标具有重要意义。在此背景下,本研究从碳标签出发,引入“亲社会行为”这一变量,提出研究假设并构建了消费者低碳购买意愿的模型,利用调查问卷和结构方程模型进行数据分析,探究碳标签对消费者低碳购买意愿的影响,并分析亲社会行为在其中的调节作用。研究结果显示,碳标签认知、碳标签宣传均直接影响消费者的低碳购买意愿,碳标签公信力对低碳购买意愿没有直接影响;感知价值和购买态度在碳标签相关因素与低碳购买意愿之间起到完全或部分中介作用;亲社会行为在感知价值和购买态度对低碳购买意愿产生中介效应的链路上具有调节作用。基于研究结果,本文从提高消费者碳标签的认知水平、增强碳标签的宣传效果、提升碳标签的公信力、倡导亲社会的低碳行为等方面提出对策建议,以期通过政府、企业和消费者的多方努力,促进消费者积极参与低碳消费,实现消费领域的低碳变革。     

底泥与衰亡植物营养释放及细菌群落演替差异的比较分析

为揭示两种"湖泛"因素对水质影响及细菌群落演替差异,对泸沽湖草海底泥和衰亡植物营养释放过程进行对比研究,并通过冗余分析阐明影响细菌群落不同阶段变化的主要环境因子.结果表明,前期是衰亡植物与底泥营养释放及细菌演替差异显著的主要阶段.植物腐解过程中,细菌前期厌氧发酵更剧烈,水体迅速处于低pH、低DO和低ORP(Oxidat...     

基于多行业DSGE模型的中国碳减排政策效应

碳达峰和碳中和目标的提出,标志着中国低碳减排进入新的阶段,从国家层面的宏观政策包括各个行业的行业政策都在推行各种低碳减排政策,从行业异质性视角动态分析碳减排政策的效应具有重要的学术和实践意义。为此,构建一个包含环境外部性和碳减排政策的多行业动态随机一般均衡模型,研究许可证交易和碳税两种政策情景下,行业技术冲击、税收政策和减排政策调整冲击对宏观经济、环境和行业排放的动态效应。模拟发现:许可证交易政策情景下,行业技术冲击具有明显的结构性效应,覆盖行业企业减排率上升,排放下降,而未覆盖行业排放随产出上升而上升,而在碳税政策情景下,这种差异并不明显。政府采用盯住总排放波动的碳减排政策能够有效地减少冲击带来的福利损失,提高对维持排放水平的关注程度能够减少相应的福利损失。建议政府有效地权衡经济增长和改善环境二者之间的关系,在不造成大的负面经济影响的前提下,加大减排政策力度,推广和扩大碳交易试点范围,尽快在全国建立统一的碳市场。制定碳减排政策时,考虑碳减排政策收入的返还机制,配以减税的财政政策以刺激经济,缓和减排政策的负面影响。政府应根据排放水平顺周期地动态调整碳减排政策的强度,适当提高对维持排放水平的关注程度。     

A procedure to design a Permeable Adsorptive Barrier (PAB) for contaminated groundwater remediation

A procedure to optimize the design of a Permeable Adsorptive Barrier (PAB) for the remediation of a contaminated aquifer is presented in this paper. A computer code, including different routines that describe the groundwater contaminant transport and the pollutant capture by adsorption in unsteady conditions over the barrier solid surface, has been developed. The complete characterization of the chemical–physical interactions between adsorbing solids and the contaminated water, required by the computer code, has been obtained by experimental measurements. A case study in which the procedure developed has been applied to a tetrachloroethylene (PCE)-contaminated aquifer near a solid waste landfill, in the district of Napoli (Italy), is also presented and the main dimensions of the barrier (length and width) have been evaluated. Model results show that PAB is effective for the remediation of a PCE-contaminated aquifer, since the concentration of PCE flowing out of the barrier is everywhere always lower than the concentration limit provided for in the Italian regulations on groundwater quality.     

基于DNDC模型评估水位变化对滨海湿地净生态系统CO2交换的影响

水位是影响滨海湿地生态系统蓝碳功能的重要因素。气候变化引起的海平面上升以及极端气候事件的频发,可能加快水位的变化,从而改变生态系统碳交换的过程。然而,滨海湿地碳汇功能响应水位变化的机制尚不清楚。为了评估水位对滨海湿地净生态系统CO₂交换(NEE)特征的影响,以及验证DNDC(denitrification-decomposition)模型对模拟预测滨海湿地生态系统碳交换的适用性,该研究设计了野外水位控制试验(自然水位,地下20 cm水位、地表10 cm水位),并利用DNDC模型模拟和预测水位变化对滨海湿地NEE的影响。结果表明:(1)不同水位处理之间NEE差异显著,地表10 cm水位处理促进CO₂吸收,地下20 cm水位则抑制CO₂吸收;(2)经过校准和验证的DNDC模型可以准确模拟水位变化对黄河三角洲湿地NEE的影响,NEE模拟值的日动态与田间观测结果显著相关(R²>0.6);(3)通过改变气候、土壤和田间管理等输入参数对DNDC模型进行灵敏度检验,生态系统碳交换过程对日均温、降雨和水位改变的响应最为显著,其中,水位对NEE的影响主要作用于土壤呼吸(Rs)。未来气候情境下,不同水位变化下的生态系统碳交换过程随年份增长呈现不同的规律,因此未来的模拟研究应关注DNDC中水文模块和植被演替过程的完善。该研究可为预测水文变化情境下滨海湿地碳汇功能的未来发展以及政策制定提供参考。     

Catalytic fast pyrolysis of walnut shell for alkylphenols production with nitrogen-doped activated carbon catalyst

• N-doped activated carbon was prepared for catalytic pyrolysis of walnut shell. • Alkylphenols were selectively produced from catalytic pyrolysis process. • The alkylphenols yield increased by 8.5 times under the optimal conditions. • Formation mechanism of alkylphenols was proposed. Alkylphenols are a group of valuable phenolic compounds that can be derived from lignocellulosic biomass. In this study, three activated carbons (ACs) were prepared for catalytic fast pyrolysis (CFP) of walnut shell to produce alkylphenols, including nitrogen-doped walnut shell-derived activated carbon (N/WSAC), nitrogen-doped rice husk-derived activated carbon (N/RHAC) and walnut shell-derived activated carbon (WSAC). Pyrolysis-gas chromatography/mass spectrometry (Py-GC/MS) experiments were carried out to reveal the influences of AC type, pyrolytic temperature, and AC-to-walnut shell (AC-to-WS) ratio on the product distributions. Results showed that with nitrogen doping, the N/WSAC possessed stronger capability than WSAC toward the alkylphenols production, and moreover, the N/WSAC also exhibited better effects than N/RHAC to prepare alkylphenols. Under the catalysis of N/WSAC, yields of alkylphenols were significantly increased, especially phenol, cresol and 4-ethylphenol. As the increase of pyrolytic temperature, the alkylphenols yield first increased and then decreased, while high selectivity could be obtained at low pyrolytic temperatures. Such a trend was also observed as the AC-to-WS ratio continuously increased. The alkylphenols production achieved a maximal yield of 44.19 mg/g with the corresponding selectivity of 34.7% at the pyrolytic temperature of 400°C and AC-to-WS ratio of 3, compared with those of only 4.67 mg/g and 6.1% without catalyst. In addition, the possible formation mechanism of alkylphenols was also proposed with the catalysis of N/WSAC.