Journal of Environmental Management最新文献

Most environmental policy studies focus on the technical pathway effect but ignore the non-technical pathway. This paper analyzes the synergistic governance effects of three types of environmental policies on the technical and non-technical pathways. The super-efficient slacks-based measure-data envelopment analysis (SBM-DEA) assesses the green total factor productivity, while the Malmquist index decomposes into pure technical efficiency. The findings indicate that: (1) command-and-control policy has the ‘too-little-of-a-good-thing’ effect, but the policy intensity in most Chinese provinces is strong enough to reduce air pollution, while market-based incentive policy may be ‘too-much-of-a-good-thing’, but Chinese provinces have not reached the inflection point; (2) there are considerable differences in the environmental effects of different policies through technical and non-technical pathways; (3) different policies have various focuses. Command-and-control policy focuses on the non-technical pathway, whereas market-based incentive policy can induce technological progress.

Fossil and mineral raw materials cause unintended and detrimental environmental and social impacts via extraction, production and combustion processes. In this study, we analyse how consumer demand in the European Union (EU) drives environmental and social impacts in mining sectors worldwide. We employ multi-regional input-output analysis to quantify positive (i.e., income, female and male employment) and negative (greenhouse gas emissions, accidents at work, and modern slavery) impacts of raw materials. We trace these environmental and social impacts across the EU's trading partners to identify sectoral and regional hotspots of international spillovers embodied in the EU's consumer demand. We estimate that the EU's consumption is associated with significant spillover impacts primarily in Central Asia, Asia Pacific, and Africa. We contextualise these results within a three-pillar framework to highlight the importance of a comprehensive and partnership-based approach to curbing environmental and social spillovers embodied in the EU's consumption of raw materials. Specifically, we highlight three potential practical policy strategies: leveraging EU domestic instruments and regulations, strengthening the Green Deal and SDG diplomacy and financing, and promoting responsible consumption, recycling and innovation. Our results underline the need for further reforms in mining industries and trade policies to reduce adverse social and environmental impacts.

Cold climates have an adverse effect on the nitrogen-removal capacity of bioretention cells, especially during freeze-thaw cycles (FTCs). To explore the effects of FTCs on the nitrogen removal performance of bioretention cells, this research compared the effects of FTCs on the pore structure and microbial community composition of the filler, and analyzed the nitrogen removal performance of the bioretention cell before (RT), during (FTC) and after (RRT) FTCs. The results demonstrated that RRT filler had a much greater number of pores with equivalent diameter <500 μm than RT filler, and that RRT had a higher pore volume and pore density than RT. Microbial community analysis revealed that the diversity and richness of the microbial community in FTC were lower than in RT, and the relative abundance of Lacunisphaera, Pseudomonas, and Dokdonella decreased significantly. There was no significant difference in microbial community richness between RRT and RT, however RRT diversity was lower. RRT has a higher relative abundance of nitrifying bacteria (Subgroup_10, Bryobacter, etc.) than RT, but a lower relative abundance of denitrifying bacteria (Pseudomonas, Dokdonella, Arenimonas, etc.). The nitrogen removal efficiency of FTC was inhibited, resulting in a decrease of 13.0 ± 4.86%, 19.7 ± 9.17%, and 26.6 ± 1.74% in the removal rates of ammonia nitrogen(NH₄⁺-N), nitrate nitrogen(NO₃⁻-N), and total nitrogen(TN) when compared to RT, respectively. RRT improved nitrification and increased NH₄⁺-N removal rate by 10.3 ± 2.69% compared to RT. However, because of denitrification inhibition, the nitrogen removal performance of RRT was not able to reach RT levels, and its NO₃⁻-N and TN removal rates decreased by 100 ± 4.70% and 58.3 ± 3.71%, respectively. This study has demonstrated that FTCs can permanently harm the bioretention cell's filler structure and microbial community, resulting in a significant decrease in the nitrogen removal performance of the bioretention cell designed according to warm climate conditions after experiencing FTCs.

This research investigates the intricate relationships between economic variables and how they affect South Asian nation's ability to develop sustainably. Given the growing concerns about climate change and global warming brought on by emissions of greenhouse gases, this study looks into the connection between emissions of CO₂, green energy, industrialization, foreign direct investment, economic globalization, and financial development from 1995 to 2022. Second-generation panel techniques were employed in this study to look at the relationship between variables because of the potential of residual cross-sectional dependency and heterogeneity. The empirical outcomes display that green energy, economic globalization, and financial development reduce CO₂ emissions by 1.839%, 1.223%, and 3.902% respectively. Industrialization and foreign direct investment degrade the environment by 4.302% and 1.893% respectively. A bidirectional causality link between green energy, industrialization, economic globalization, and CO₂ emissions was found by Dumitrescu and Hurlin (D-H). Based on our findings, we recommend legislative support for renewable energy, cleaner technologies, and strict environmental regulations, aligning with the Sustainable Development Goals (SDGs). Encouraging FDI, sustainable practices, and financial development can drive economic growth while preserving the environment. As we approach COP28, this holistic approach to sustainable development becomes increasingly vital for South Asian countries to achieve their SDG targets and combat climate change.

Landfill is a significant source of atmospheric CH₄ and CO₂ emissions. In this study, four landfill reactor systems were constructed to investigate the effects of different ventilation methods, including continuous aeration (20 h d⁻¹) and intermittent aeration (continuous aeration for 4 h d⁻¹ and 2 h of aeration every 12 h, twice a day), on properties of landfilled waste and emissions of CH₄ and CO₂, in comparison to a traditional landfill. Compared with continuous aeration, intermittent aeration could reduce the potential global warming effect of the CH₄ and CO₂ emissions, especially multiple intermittent aeration. The CH₄ and CO₂ emissions could be predicted by the multiple linear regression model based on the contents of carbon, sulfur and/or pH during landfill stabilization. Both intermittent and continuous aeration could enhance the methane oxidation activity of landfilled waste. The aerobic methane oxidation activity of landfilled waste reached the maximums of 50.77–73.78 μg g⁻¹ h⁻¹ after aeration for 5 or 15 d, which was higher than the anaerobic methane oxidation activity (0.45–1.27 μg g⁻¹ h⁻¹). CO₂ was the predominant form of organic carbon loss in the bioreactor landfills. Candidatus Methylomirabilis, Methylobacter, Methylomonas and Crenothrix were the main methane-oxidating microorganisms (MOM) in the landfills. Total, NO₂⁻-N, pH and Fe³⁺ were the main environmental variables influencing the MOM community, among which NO₂⁻-N and pH had the significant impact on the MOM community. Partial least squares path modelling indicated that aeration modes mainly influenced the emissions of CH₄ and CO₂ by affecting the degradation of landfilled waste, environmental variables and microbial activities. The results would be helpful for designing aeration systems to reduce the emissions of CH₄ and CO₂, and the cost during landfill stabilization.

With the e-waste growing rapidly all over the globe due to growing demand of electronics, smartphones, etc., coming up with an efficient and sustainable recycling process is the need of the hour. The present work reports a novel and sustainable process of manufacturing Ni alloy by bringing together three major waste streams such as waste Ni-MH batteries, e-waste plastics, and waste glass. The chosen temperature (1550 °C) favours the reduction of nickel-oxide by e-waste plastic as the reductant and sends rare earth elements present in the waste Ni-MH battery as oxide mixture to the slag phase. Waste glass powder used in this process functions as the fluxing agent, hence not requiring any additional flux. The reduction mechanism is gas-based, controlled mainly by hydrogen and carbon monoxide gases released as a result of decomposition of e-waste plastic as reaction commenced from cold zone (∼300 °C) to hot zone (1550 °C) in the horizontal tubular furnace. Formation of nickel alloy and enrichment of slag with mixture of rare earth oxides were confirmed by XRD, SEM-EDS, and Rietveld refining analysis performed on the XRD spectra of slag phase. ICP-OES (Inductively coupled plasma optical emission spectroscopy) and LIBS (laser induced breakdown spectrometer KT-100S) confirmed the high metal content in the alloy, thereby emphasizing the purity (∼98%) which is close to the composition of nickel super alloy. A maximum of 61% by weight REO enrichment was achieved in the slag phase, having La₂O₃:44.6%, Pr₂O₃:14.8%, and Nd₂O₃: 1.6% under optimised experimental conditions (1550 °C, 15 min, and 20% waste glass powder). This scientific investigation evinces a promising route for efficient utilisation of waste streams emanating from e-waste, thereby devising a sustainable recycling technique and protecting the environment, too.

Phosphorus (P) pollution in aquatic environments poses significant environmental challenges, necessitating the development of effective remediation strategies, and biochar has emerged as a promising adsorbent for P removal at the cost of extensive research resources worldwide. In this study, a machine learning approach was proposed to simulate and predict the performance of biochar in removing P from water. A dataset consisting of 190 types of biochar was compiled from literature, encompassing various variables including biochar characteristics, water quality parameters, and operating conditions. Subsequently, the random forest and CatBoost algorithms were fine-tuned to establish a predictive model for P adsorption capacity. The results demonstrated that the optimized CatBoost model exhibited high prediction accuracy with an R² value of 0.9573, and biochar dosage, initial P concentration in water, and C content in biochar were identified as the predominant factors. Furthermore, partial dependence analysis was employed to examine the impact of individual variables and interactions between two features, providing valuable insights for adsorbent design and operating condition optimization. This work presented a comprehensive framework for applying a machine learning approach to address environmental issues and provided a valuable tool for advancing the design and implementation of biochar-based water treatment systems.

Perfluorooctanoic acid (PFOA) as emerging pollutants was largely produced and stable in nature environment. Its fate and effect to the wasted sludge digestion process and corresponding microbial mechanism was rarely reported. This study investigated the different dose of PFOA to the wasted sludge digestion process, where the methane yield and microbial mechanism was illustrated. The PFOA added before digestion were 0–10000 μg/L, no significant variation in daily and accumulated methane production between each group. The 9th day methane yield was significantly higher than other days (p < 0.05). The soluble protein was significantly decreased after 76 days digestion (p < 0.001). The total PFOA in sludge (R² = 0.8817) and liquid (R² = 0.9083) phase after digestion was exponentially correlated with PFOA dosed. The PFOA in liquid phase was occupied 54.10 ± 18.38% of the total PFOA in all reactors. The dewatering rate was keep decreasing with the increase of PFOA added (R² = 0.7748, p < 0.001). The mcrA abundance was significantly correlated with the pH value and organic matter concentration in the reactors. Chloroflexi was the predominant phyla, Aminicenantales, Bellilinea and Candidatus_Cloacimonas were predominant genera in all reactors. Candidatus_Methanofastidiosum and Methanolinea were predominant archaea in all reactors. The function prediction by FAPROTAX and Tax4fun implied that various PFOA dosage resulted in significant function variation. The fermentation and anaerobic chemoheterotrophy function were improved with the PFOA dose. Co-occurrence network implied the potent cooperation among the organic matter degradation and methanogenic microbe in the digestion system. PFOA has little impact to the methane generation while affect the microbe function significantly, its remaining in the digested sludge should be concerned to reduce its potential environmental risks.

Green roof systems have been developed to improve the environmental, economic, and social aspects of sustainability. Selecting the appropriate version of the green roof composition plays an important role in the life cycle assessment of a green roof. In this study, 10 compositions of an intensive green roof for moderate zone and 4 green roof compositions for different climatic conditions were designed and comprehensively assessed in terms of their environmental and economic impacts within the “Cradle-to-Cradle” system boundary. The assessment was carried out over a 50-year period for a moderate climate zone. The results showed that asphalt strips and concrete slab produced the highest total emissions. It was found that most greenhouse gases emissions were released in the operational energy consumption phase and in the production phase. The energy consumption phase (48.78%) for automatic irrigation and maintenance caused the highest Global Warming Potential (GWP) value (758.39 kg CO_2e) in the worst variant, which also caused the highest life cycle cost (878.47€). On the contrary, in the best variant, planting more vegetation and lower maintenance and irrigation requirements led to a reduction in GWP (445.0 kg CO_2e), but in terms of cost (506.6€) this composition didn't represent the best variant. The Global Warming Potential Biogenic (GWP-bio) compared to the Global Warming Potential Total (GWP-total) represents a proportion ranging from 0.8% to 78% depending on the proposed vegetation. Overall higher biogenic carbon values (up to 1525 kg CO_2e) were observed for the proposed tall vegetation of Magnolia, Red Mulberry, Hawthorne, Cherry, and Crab-apple Tree. Based on the results of the multicriteria analysis, which included core environmental & economic parameters, biogenic carbon emission levels, the outcome of this paper proposed optimal green roof composition. Optimal intensive green roof composition was subjected to a sensitivity analysis to determine the impact of changing climatic conditions on CO₂ emissions and life cycle costs. The results of the sensitivity analysis show that the optimal variant of the green roof can be implemented in the cold and subtropical zone with regard to CO₂ emissions, but not with regard to life cycle costs.

Antimicrobial resistance (AMR) is a significant threat that demands surveillance to identify and analyze trends of the emerging antibiotic resistance genes (ARGs) and potential microbial carriers. The influent of the wastewater treatment plants (WWTPs) reflects the microbes derived from the population and effluent being the source of dissemination of potential pathogenic microbes and AMR. The present study aimed to monitor microbial communities and antibiotic resistance genes in WWTPs employing a whole metagenome shotgun sequencing approach. The samples were collected from a sewage treatment plant (STP) and a common effluent treatment plant (CETP) in Delhi, India. The results showed the influent of STP to be rich in Bifidobacterium, Bacteroides, Escherichia, Arcobacter, and Pseudomonas residents of gut microbiota and known to cause diseases in humans and animals; whereas the CETP sample was abundant in Aeromonas, Escherichia, and Shewanella known to be involved in the degradation of different compounds. Interestingly, the effluent samples from both STPs and CETP were rich in microbial diversity, comprising organic and xenobiotic compound degrading and disease-causing bacteria, indicating the effluent being the source of dissemination of concerning bacteria to the environment. The functional profile at both sites displayed similarity with an abundance of housekeeping function genes as analyzed by Clusters of Orthologous Genes (COG), KEGG Orthology (KO), and subsystem databases. Resistome profiling by MEGARes showed the dominance of ARGs corresponding to beta-lactams having relative abundance ranging from 16% to 34% in all the metagenome datasets, followed by tetracycline (8%–16%), aminoglycosides (7%–9%), multi-drug (5%–9%), and rifampin (3%–9%). Also, AMR genes oxa, ant3-DPRIME, and rpoB, which are of clinical importance were predominantly and most prevalently present in all the samples. The presence of AMR in effluents from both types of treatment plants indicates that wastewater from both sources contributes to the spread of pathogenic bacteria and resistance genes, increasing the environmental AMR burden and therefore requires tertiary treatment before discharge. This work will facilitate further research towards the identification of suitable biomarkers for monitoring antibiotic resistance.