Environmental Emissions Research Articles

Modernizing load and emission factors for construction machinery based on real-world operation: Estimation of emission data in Korea.

The emissions inventory for non-road mobile machinery (NRMM) in Korea relies on laboratory engine tests, which do not accurately reflect the real-world emissions from construction machinery. Hence, standardized real-world test conditions suitable for the Korean environment were first designed based on the manufacturer's testing methods and previous research. Next, using portable emissions measurement systems (PEMS), data on exhaust emissions and load factor (LF) were collected and analyzed during real-world tests on three types of construction machinery (excavators, loaders, and forklifts) with high registration rates and emissions in Korean environment. The improved LFs, which reflect real-world tests, were significantly lower than the existing LF value (0.48), with values of 0.38-0.5 for excavators, 0.3-0.44 for loaders and 0.26 for forklifts. The emission factors (EFs) were higher than those currently used in Korea's emissions inventory, namely, the Clean Air Policy Support System (CAPSS). Based on the results, emissions were calculated and compared using an emission calculation formula. The relationship between LFs and EFs was also investigated to address the limitations of previous studies that focused solely on EF measurements. The combined improvements in EFs+LFs can lead to slightly higher emissions inventories. The improved LFs and EFs based on the results of real-world tests reported herein can enhance the accuracy of estimating emissions from construction machinery in Korea.

From policy to progress: Environmental taxation to mitigate air pollution in OECD countries.

Environmental taxes play a critical role in mitigating air pollution and fostering sustainability by internalizing the social costs of environmental damage. By imposing financial disincentives on polluters, these taxes encourage cleaner practices and technological innovation. Using panel ARDL models, this study examines the impact of environmental taxes on CO₂ emissions across 38 OECD countries, accounting for cross-sectional dependence, non-stationarity, and heterogeneity. Findings reveal a significant long-run negative relationship between environmental taxes and CO₂ emissions and support the Environmental Kuznets Curve (EKC) hypothesis in high-income nations. The analysis highlights that while environmental taxes effectively reduce emissions at moderate and high levels, their impact diminishes at lower emission levels. Moreover, disaggregated analysis of fossil fuel consumption demonstrates a substantial decline in coal and oil usage, whereas natural gas consumption exhibits a positive association with taxes, reflecting a shift toward less carbon-intensive energy sources. The study emphasizes the importance of well-designed environmental tax schemes to maximize policy effectiveness.

Heavy-duty vehicles dominate expressway tunnel environment analysis and emission factor determination

Vehicle emission factors (EFs) are important factors affecting tunnel environments. In this study, field tests were conducted in an expressway tunnel in southwest China. The percentage of heavy-duty vehicles (HDVs) was approximately 38 %. The NOx concentrations exceeded the safety thresholds. The average CO, NOx, and PM2.5 EFs of the mixed fleet were 1.25, 2.68, and 0.079 g/km veh−1, respectively. The NOx and PM2.5 EFs of the HDV were 31.3 and 14.7 times higher than those of the light-duty vehicle (LDV), respectively. HDVs contributed 61.5 % to CO, 94.8 % to NOx, and 89.3 % to PM2.5 emissions in this investigation. When compared to previous studies, a significant reduction in CO and PM was observed, but NOx remained at a high level. Stricter policies are needed to control the emissions of HDVs, and the ventilation of tunnels must consider the NOx concentration.

An Econometric Analysis of Egypt's Cereal Production and Environmental Emissions for Food Security

An Econometric Analysis of Egypt's Cereal Production and Environmental Emissions for Food Security

A Comprehensive Analysis of Environmental Emissions from Trenchless CIPP and Excavation Technologies for Sanitary Sewers

The renewal of underground infrastructure is an emerging challenge for most municipalities in the United States. As compared to trenchless cured-in-place pipes (CIPPs), excavation technologies (ETs) have adverse impacts on the environment. Due to its lower ecological impact, trenchless technology is preferred in comparison to conventional pipe replacement. The selection of the most appropriate method depends on factors such as the existing sewer network, traffic disruption, soil conditions, and environmental safety. Recent concerns pertaining to environmental impact have increased the demand for reduced carbon footprints. The objectives of this paper are the following: (1) to present a comprehensive review on the achievements achieved over the years in understanding the factors influencing environmental emissions from the use of CIPP and ETs and (2) to analyze and compare the environmental emissions produced from CIPPs and ETs for 8-inch-, 10-inch-, and 12-inch-diameter pipes. Published papers from 1990 through 2024 have been included, which reported emissions from both alternatives. A comparison of total environmental emissions produced from both the processes is presented. The literature review and analysis suggest that higher emissions are a result of higher fuel consumption, material use, and input allocation. The emissions of pipeline renewal methods were evaluated using USEPA’s TRACI 2.1 methodology within SimaPro software. The analysis showed that CIPP renewal greatly reduced carbon emissions when compared with ET. CIPPs exhibited approximately 70% less ecological impact, 75% less impact on human health, and 60% less depletion of resources. CIPPs reduced carbon emissions by 78–100% in comparison to ETs. The recycling materials used in CIPPs potentially reduce the environmental impact by 10%, making them highly sustainable. The installation phase should therefore be carefully analyzed for factors like the pipe material and the pipes’ external diameter in view of achieving the greatest sustainability of these methods, as these characteristics affect emissions. It can be inferred that the comparison of the emissions of both alternatives is extremely vital for sustainable underground infrastructure development.

Mitigation of microfibers in laundry effluent: Investigation of luffa fibers as an eco-friendly filtration system.

Domestic laundry wastewater is a major contributor to microfiber emissions in the aquatic environment. Among several mitigation measures, the use of external filters to capture microfibers from wastewater is one of the most efficient and commercially viable methods. This study attempted to develop an eco-friendly filtration medium to filter microfibers in laundry wastewater using luffa cylindrica fibers. Sourced luffa fibers were made into tight rolls and stacked in a filtration column to filter the effluent. The analysis showed that the alkali-treated luffa fiber rolls were more effective in filtering the microfibers than untreated luffa fibers. Hence, the alkali treatment process was optimized for better performance; an alkali concentration of 5.8%, treatment time of 5h, and 37°C temperature provide better performance. The characterization of alkali-treated luffa fibers showed significant changes in the morphology and removal of lignin and hemicellulose components, enhancing the physical adsorption of microfibers on the surface. The experimental filtration results showed that the developed filter can effectively remove up to 93% of microfibers from laundry effluent, and the efficiency remained superior for up to 15 filtrations. Furthermore, an increase in filtration leads to the accumulation of detergents in the luffa net-like vascular structure and reduced effectiveness. The use of the developed product in a real-time washing machine outlet was found to be effective with an efficiency of 98%. The developed product is a versatile and cost-effective solution, suitable for use in domestic washing machines. Its simplicity and ease of integration make it an effective and eco-friendly alternative for filtering microfibers from laundry effluent. The future direction of the study also suggests a sustainable disposal method for luffa fibers using it as a matrix material in red soil-based thermal or sound insulation panels and restricting the reach of microfibers into the environment.

Identifying influencing physical and environmental parameters on fate and characterization factors for microplastic emissions in the marine environment

Identifying influencing physical and environmental parameters on fate and characterization factors for microplastic emissions in the marine environment

Environmental antibiotic emissions and their residual impact on livestock farming

Environmental antibiotic emissions and their residual impact on livestock farming

Microbial community structure and water quality performance in local scrubber reclaim system for water reclamation of the semiconductor industry: A case study of a semiconductor plant in Beijing.

The local scrubber reclaim (LSR) system plays a critical role in water reclamation and in reducing environmental pollution emissions in semiconductor factories. This study monitored the changes in water quality and assessed the key stages of pollutant removal, with a primary focus on evaluating microbial growth and the shifts in microbial community structure and function in the LSR system. The results showed that activated carbon filtration (ACF) effectively removed total organic carbon (TOC) with a removal rate of 59.35%, while ion exchange (IEX) was essential for reducing conductivity, with a removal rate of 87.33%. Furthermore, severe bacterial growth was observed (more than 1000CFU/ml) in the system. Bacteria numbers in the MMF and ACF stages grew dramatically, at least four times higher than that in the influent tank. After chlorination in the storage tank, microbial numbers sharply dropped, yet microbial diversity increased. The dominant microbial group in the LSR system was Patescibacteria (average relative abundance was 32.37%), considered part of the "microbial dark matter" and also known as Candidate Phyla Radiation (CPR). Following the effluent from the storage tank, the biofilm-forming potential of bacteria significantly increased (relative abundance rose from 7.19% to 15.20%), along with a varying increase in the abundance of genes related to metabolism. Measures should be implemented to prevent pipeline blockage and improve water reclamation efficiency.

Dynamic relationships between environment-related technologies, agricultural value added, transport infrastructure and environmental emissions in the five most populous countries

Densely populated countries have higher demand for agricultural products and greater use of fuel and vehicles, resulting in higher environmental emissions, so this study considers transportation infrastructure and the agricultural sector as the two major drivers of environmental degradation in the top five densely populated countries. In a baseline regression, this study first unveils the impact of investments in transportation infrastructure, agricultural value addition, and environment-related technologies on per capita CO2 emissions using CS-ARDL approach from 1990 to 2021 in the five most populous countries. Besides, this study also reveals the typical moderating effect of environment-related technologies in the link between transport infrastructure, agricultural value added and environmental hazards. The results of the baseline model indicate that transport infrastructure and agricultural value added can substantially contribute to per capita carbon emissions in both the short and long term. However, environment-related technologies significantly reduce environmental emissions in both the short and long term. Per capita GDP extensively promotes per capita carbon dioxide emissions, while per capita GDP2 substantially reduces per capita carbon dioxide emissions in the long term rather than the short term, thus authenticating the inverted U-shaped EKC hypothesis for the top five countries with the highest population density. The moderating effect of environment-related technologies shows that the application of environment-related technologies in both transportation and agriculture can alleviate environmental pollution. Finally, the threshold level of environment-related technologies shows that as environment-related technologies move from lower threshold levels (≤ − 1.05) to higher threshold levels (> -1.05), agricultural value added and transportation infrastructure investment significantly improve the reduction of environmental contamination. The goal of environmental sustainability can be ensured by the adoption of environment-related technologies in agriculture and transportation sectors.

Eco-Drive: Leveraging Gamification and Community Engagement for Carbon Footprint Reduction through Smart Mobility Solutions

This research is based on the Eco-Drive app application that integrates automatic travel detection, gamification, and social engagement as a mobile platform to reduce individual and community-level carbon footprints. The application encourages sustainable commuting behaviours. An engaging interface with advanced analytics aligns with global sustainability goals through vehicular emission reduction. Preliminary results indicate that the app can contribute considerably toward increasing environmental awareness and action. This is just one of the major challenge’s environmental experts face: vehicle emissions and air quality, and this is what the Eco-Drive project is for. It's an automated carbon footprint tracking within a gamified incentive program with community involvement to empower the users to make responsible decisions that lead to commuting sustainably. Using smartphone sensors and frameworks, it identifies the mode of travel and travel time to show live information with a nudge to carpool, bicycle, or travel by public transport. Gamification supports behaviour change through friendly competitions and virtual rewards. This awareness and sense of community responsibility make Eco Drive work for the global sustainability goal through a scalable and user-centered approach to reducing emissions in the urban environment. Keywords—Carbon FootPrint,gamification,sustainability,carpooling,community engagement

Valorization of Maize Processing Industrial Waste as Activated Magnetic Biochar Catalyst through Pyrolysis for Biodiesel Production: Detailed Investigations on Economic Profitability and Environmental Emissions

Valorization of Maize Processing Industrial Waste as Activated Magnetic Biochar Catalyst through Pyrolysis for Biodiesel Production: Detailed Investigations on Economic Profitability and Environmental Emissions

A scenario-based modelling for the long-term energy planning based on efficient energy Use, economic and environmental emission reduction on national scale: A case study Iran

A scenario-based modelling for the long-term energy planning based on efficient energy Use, economic and environmental emission reduction on national scale: A case study Iran

Integration of Fuzzy 0/1 Knapsack Dynamic Programming and PROMETHEE Method for Vehicle Exhaust Emission Parametric Optimization and Selection in the Packing Industry

Packaging industries fabricate and transport products in wrapped, sealed, and cushioned containers and boxes on roads, often through fossil-fuelled vehicles that emit carbons. Thus, decarbonization and net zero emission drive are compelling for these vehicles. This paper proposes a robust green logistics interaction model for monitoring and reducing exhaust pipe emissions in an uncertain environment. It uses a hybrid method known as fuzzy-0/1-KDP-PROMETHEE (Fuzzy-0/1 Knapsack dynamic programming-Preference Ranking Organization Method for Enrichment Evaluation) approach to concurrently reduce uncertainty, optimize the capacity of the knapsack and establish the preferred option among the parameters of green logistic. Both PROMETHEE I and II were introduced and tested using logistics data from an Indian environment based on secondary data. The method works by first reducing the effect of uncertainty on the model outcomes. This was achieved by establishing the output space as the fuzzy state, creating fuzzy rules, and mapping degrees to rules. Then, the degrees are used to maximize, ensuring that the weighted sum is not greater than the capacity of the Knapsack. The outcome is then regarded as the element of the green logistics exhaust emission process. The results obtained from the analysis, using the replacement of fuzzy expert (triangular) with fuzzy extent (trapezoidal), fuzzy geometric mean (triangular), and fuzzy geometric mean (trapezoidal) reveal that the fuzzy-0/1-KDP-PROMETHEE method adequately represents the score obtained using the data set from the exhaust emissions.

Material Cycles, Environmental Emissions, and Ecological Risks of Bisphenol A (BPA) in China and Implications for Sustainable Plastic Management.

Bisphenol A (BPA) is a high-production-volume plastic chemical, with ∼98% of its usage in China allocated to producing polycarbonate and epoxy resin, and its fugitive release threatens ecosystems. However, knowledge of its anthropogenic cycles, environmental emissions, and ecological risks remains incomplete, hindering effective plastic lifecycle management. Herein, material flow analysis, multimedia environmental modeling, and ecological risk assessment were integrated to comprehensively map BPA dynamics in China. Results reveal a ∼ 90-fold increase in BPA consumption between 1992 and 2022 and major applications shifted from optics and packaging to automotive, construction, and electronics. China held ∼34 Mt of in-use BPA stock in 2022 (∼24 kg per capita), with no indication of reaching saturation. BPA release occurred throughout its lifecycle, and soil and water were primary sinks. Aquatic BPA concentrations exceeded the limit in national pollutant emission standards in ∼8.4% of Chinese mainland areas in 2022, and ∼4.5% of areas suffered very high chronic ecological risks to aquatic organisms. Scenario analysis indicates that a 90% reduction in BPA emission factors would be required to avoid BPA contamination in all areas of focus. Our findings contribute as a scientific basis for sustainable plastic management and highlight the need for updated techniques, intensified monitoring, and standardized regulations.

The Mechanism and Effects of the Digital Economy on Urban Resilience: An Empirical Test Based on 110 Cities in the Yangtze River Economic Belt

Cities encounter increasing risks and challenges under new development patterns, and digital economy (DE) can drive cities’ improved resilience to natural and social uncertainties. Based on data collected on the Yangtze River Economic Belt from 2011 to 2021, the development situation of the regional DE and urban resilience (UR) was measured, and the impact mechanisms of the DE on UR were analysed theoretically and empirically using a benchmark regression model. The findings are as follows: The benchmark test revealed that the DE development contributed significantly to UR in the region. The mediating effect test revealed that the DE improved UR through two pathways: industrial structure upgradation and energy restructuring. The moderating effect test suggested that environmental pollutant emissions had a negative moderating effect between the impact mechanisms of the DE, industrial structure, and energy structure and between the effects of industrial structure, energy structure, and UR, whereas CO2 emissions had a positive moderating effect between the impact mechanisms of DE and industrial structure. Heterogeneity analysis indicated that the DE contributed positively to the UR except in the upstream region, where the coefficient of the DE was insignificant. Overall, this study highlights the crucial role of the DE in improving UR and elucidates the theoretical impact mechanisms of environmental pollution control and carbon reduction measures on UR.

Exploring the emission reduction and economic impacts of environmental regulation from a dynamic endogenous perspective: evidence based on the PVAR and threshold models

How to effectively reduce pollution emissions and achieve high-quality economic development (HQED) is an important challenge currently facing China. On the basis of China’s provincial panel data from 2008 to 2020, this paper constructs a panel vector autoregression (PVAR) model, to clarify the dynamic interactive relationships among environmental regulation, pollution emissions and HQED from an endogenous perspective. On this basis, the threshold model was used to test the threshold effect of environmental regulation and pollution emission intensity. The results indicate the following: (1) A bidirectional Granger causality relationship exists between environmental regulation and pollution emission, and between pollution emission and HQED, with environmental regulation being a one-way Granger cause of HQED. (2) Environmental regulation can significantly promote HQED in the long term. Pollution emission intensity and HQED have a mutual inhibitory effect, with the inhibitory effect of pollution emission intensity showing a lag, and a long-term “inverted M” pattern. Pollution emission intensity has a positive promoting effect on environmental regulation intensity in the long term, whereas the reverse relationship is inhibitory, following an inverted U-shaped trend. (3) Variance decomposition reveals that, in addition to the variables themselves, pollution emissions contribute the most to the intensity of environmental regulation. Environmental regulation contributes the most to the other two variables. (4) The threshold regression model indicates that when the intensity of environmental regulation crosses the threshold value of 0.8430, pollution emission intensity has a significant negative impact on HQED. When pollution emission intensity crosses the second threshold value of 0.4870, the intensity of environmental regulation begins to show a positive promoting effect. This article not only effectively supplements the EKC hypothesis from a theoretical level, but also clarifies the dynamic interactive relationship between environmental regulation, pollution emissions and HQED from a practical level, providing a reference for the government to improve environmental regulation policies and facilitate HQED in China.

The relationship between geographic distance to environmental protection agencies and industrial pollution emissions

ABSTRACT The distance between governments and firms is associated with firms’ economic activities, while the association of geographic proximity to environmental agencies with industrial pollution emissions is unclear. To explore the effects of geographic distance on firms’ pollution emissions, we use the fixed-effect models with data from the China Industrial Enterprise Database. Our results show that the firms located further away from environmental agencies release more SO2 (β = 0.102, p < 0.01) than those close to those environmental agencies. Subsequent investigations reveal that geographic distance has a positive correlation with the short-term performance of firms (total production value and fixed investment) but a negative correlation with firms’ long-term performance (green innovation, technological updates and clean energy use). Heterogeneous checks show that the influence of geographic distance on SO2 emissions is mainly found in non-local firms, suggesting a possibility of collusion between proximate firms and local government. This study highlights how the firm-agency distance relation affects pollution emissions and suggests that policymakers should consider more efficient instruments for environmental management.

Effects of the Interaction of Salinity and Rare Earth Elements on the Health of Mytilus galloprovincialis: The Case of Praseodymium and Europium.

The growing use of products containing rare earth elements (REEs) may lead to higher environmental emissions of these elements, which can potentially enter aquatic systems. Praseodymium (Pr) and europium (Eu) are widely used REEs with various applications. However, their ecotoxicological impacts remain largely unexplored, with poorly understood risks to wildlife. Moreover, organisms also face environmental stressors like salinity fluctuations, and the nature of the interaction between salinity variations and contaminants is not yet clear. Therefore, this study aimed to evaluate the influence of salinity shifts on the impacts of Pr and Eu on adult mussels and the sperm of the species Mytilus galloprovincialis after 28 days and 30 min of exposure, respectively. To do so, biochemical and histopathological alterations were evaluated in adults, while biochemical and physiological changes were analysed in sperm. Additionally, the Integrated Biological Index (IBR) was calculated to understand the overall impact of each treatment. The results showed that adult mussels were most affected when exposed to the combination of high salinity and each element, which altered the behaviour of defence mechanisms causing redox imbalance and cellular damage. On the other hand, sperm demonstrated sensitivity to specific REE-salinity combinations, particularly Pr at lower salinity and Eu at higher salinity. These specific treatments elicited changes in sperm motility and velocity: Pr 20 led to a higher production of O2- and a decrease in velocity, while Eu 40 resulted in reduced motility and an increase in irregular movement. At both lower and higher salinity levels, exposure to Eu caused similar sensitivities in adults and sperm, reflected by comparable IBR scores. In contrast, Pr exposure induced greater alterations in sperm than in adult mussels at lower salinity, whereas the reverse was observed at higher salinity. These findings suggest that reproductive success and population dynamics could be modulated by interactions between salinity levels and REE pollution, highlighting the need for further investigation into how REEs and environmental factors interact. This study offers valuable insights to inform policymakers about the potential risks of REE contamination, emphasising the importance of implementing environmental regulations and developing strategies to mitigate the impact of these pollutants.

Proposing a new integrated MEREC‐NDEA algorithm for assessing and selecting the optimal sustainable suppliers: a case study

AbstractIn recent decades, choosing sustainable suppliers (SS) within a supply chain (SC) has posed a significant challenge for management. The evaluation and selection of the optimal SS from a pool of suppliers in the SC stands as a pivotal factor in maintaining competitiveness in the market. Hence, decision‐makers must seek the most effective method to identify key selection criteria for SS. This study aims to introduce a novel hybrid algorithm for the selection and assessment of the best SSs, encompassing varied criteria such as economic, environmental, sustainability, and human health considerations. The innovative algorithm combines the MEthod based on the Removal Effects of Criteria (MEREC) technique with network data envelopment analysis (NDEA). The enhanced NDEA model incorporates undesirable outputs and environmental emissions like CO2. Initially, leveraging the MEREC approach, criteria weights are determined in two distinct groups: cost and benefit. Subsequently, inputs, intermediate products, and outputs are defined based on these weights, with NDEA models devised accordingly. The NDEA models effectively identify top suppliers based on efficiency. An efficient supplier is considered the best choice. The NDEA model highlights areas for improvement for inefficient suppliers while also leveraging insights from efficient ones. This leads to a comprehensive ranking of all suppliers, from which the best are selected. A case study at Shahriar Plast Company involving 10 suppliers and 11 criteria demonstrates the methodology's effectiveness. Results indicate that this hybrid algorithm is a reliable solution for supplier selection across various SCs. A comparative analysis with existing models further confirms the stability and reliability of the proposed algorithm, yielding consistent outcomes.