Industrial Emissions Research Articles

Drying-Wetting Correlation Analysis of Chloride Transport Behavior and Mechanism in Calcium Sulphoaluminate Cement Concrete.

In response to rising CO2 emissions in the cement industry and the growing demand for durable offshore engineering materials, calcium sulphoaluminate (CSA) cement concrete, known for its lower carbon footprint and enhanced corrosion resistance compared to Ordinary Portland Cement (OPC), is increasingly important. However, the chloride transport behavior of CSA concrete in both laboratory and marine environments remains underexplored and controversial. Accordingly, the chloride ion transport behaviors and mechanisms of CSA concrete in laboratory-accelerated drying-wetting cyclic environments using NaCl solution and seawater, as well as in marine tidal environments, were characterized using the rapid chloride test (RCT), X-ray diffraction (XRD), mercury infiltration porosimetry (MIP), and thermogravimetric analysis (TGA). The results reveal that CSA concrete accumulates more chloride ions in NaCl solution than in seawater, with concentrations 2-3.5 times higher at the same water-cement ratio. Microscopic analysis indicates that calcium and sulfate ions present in seawater facilitate the regeneration of ettringite, thereby increasing the density of the surface pore structure. The hydration and repair mechanisms of CSA concrete under laboratory conditions closely resemble those in marine tidal conditions when exposed to seawater. Additionally, this study found that lower chloride ion concentrations and pH levels inhibit the formation of Friedel's salt. Therefore, laboratory experiments with seawater can effectively simulate CSA concrete's chloride transport properties in marine tidal environments, whereas NaCl solution does not accurately reflect actual marine conditions.

Status and prospects of energy efficiency in the glass industry: Measuring, assessing and improving energy performance

The significant share of energy-related emissions in the glass industry necessitates robust energy efficiency strategies. This paper evaluates the status and prospects of energy efficiency by integrating the measurement, assessment, and improvement of energy performance through energy data and modelling. Measurement and assessment are crucial for effective energy management in hard-to-abate industrial sectors, providing insight into the existence and extent of potential energy efficiency gains. The use of appropriate performance indicators allows for comparison across production contexts and the monitoring of improvements achieved through interventions. The benchmarking of a representative sample of container glass furnaces reveals a current potential for improvement of around 10% based on alignment with best practices. Energy modelling is used to map energy flows along the various systems involved in production, thereby identifying major energy losses. Energy efficiency options can then be categorised based on their contribution to improving energy performance, facilitating the identification of solutions that address current bottlenecks. The study discusses promising opportunities arising from improved batch compositions and outlines the role of renewable penetration on the viability of hydrogen use and furnace electrification. The proposed approach can be transferred to other hard-to-abate industrial sectors to drive progress in decarbonisation.

Ecological and Geochemical Assessment of the State of Soils in the City of Baikalsk According to the Content of Polycyclic Aromatic Hydrocarbons

The pollution of the topsoils of the city of Baikalsk (Irkutsk region) under the influence of industrial emissions and wastes of the Baikal Pulp and Paper Mill (BPPM) was studied. The content of 16 individual PAH structures in samples of urban and background soils taken during the soil geochemical survey in the summer of 2019 was analyzed. Relatively low levels of PAH content were found in the lignin sludge from the BPPM and СHP ash. The concentration of total PAHs in CHP ash reaches 46 mg/ kg with a predominance of low molecular weight compounds (the proportion of naphthalene and its homologues is 24% and 34% of the total PAHs, respectively), among high molecular weight PAHs, 5-nuclear benzo(b)fluoranthene dominates (16%). In lignin sludge, the amount of PAHs is 7.16 mg/kg with the predominance of benzo(b)fluoranthene (83%). In the soils of Baikalsk, the average total content of PAHs (38.4 mg/kg) is 5 times higher than the background content. In urban soils, 4–5-nuclear fluoranthene (61.1%) and benzo(b)fluoranthene (29.4%) prevail. This makes it possible to attribute soil pollution to the fluoranthene type. The soils of the motor transport (total PAH 105 mg/kg) and industrial (59.5 mg/ kg) zones are the most polluted, where the most contrasting PAH anomalies were formed. In descending order of the amount of PAHs, the land use zones of the city form a series: motor transport industrial residential one-storey railway transport residential multi-storey recreational zone. Several local anomalies in the amount of PAHs are distinguished, forming two large pollution halos in the western and eastern parts of the city. The leading factors in the accumulation of high molecular weight PAHs in soils are acid-alkaline conditions and soil organic matter, while the accumulation of low molecular weight polyarenes is mainly controlled by pH. The environmental hazard of pollution of Baikalsk soils with polyarenes is due to benzo(b)fluoranthene, its contribution is 83.5%.

Biomass-burning sources control ambient particulate matter, but traffic and industrial sources control volatile organic compound (VOC) emissions and secondary-pollutant formation during extreme pollution events in Delhi

Abstract. Volatile organic compounds (VOCs) and particulate matter (PM) are major constituents of smog. Delhi experiences severe smog during the post-monsoon season, but a quantitative understanding of VOCs and PM sources is still lacking. Here, we conduct a source apportionment study for VOCs and PM using a recent (2022), high-quality dataset of 111 VOCs, PM2.5, and PM10 in a positive matrix factorization (PMF) model. Contrasts between clean monsoon air and polluted post-monsoon air, VOC source fingerprints, and molecular tracers enabled us to differentiate paddy residue burning from other biomass-burning sources, which had previously been impossible. Burning of fresh paddy residue, as well as residential heating and waste burning, contributed the most to observed PM10 levels (25 % and 23 %, respectively) and PM2.5 levels (23 % and 24 %, respectively), followed by heavy-duty vehicles fuelled by compressed natural gas (CNG), with a PM10 contribution of 15 % and a PM2.5 contribution of 11 %. For ambient VOCs, ozone formation potential, and secondary-organic-aerosol (SOA) formation potential, the top sources were petrol four-wheelers (20 %, 25 %, and 30 %, respectively), petrol two-wheelers (14 %, 12 %, and 20 %, respectively), industrial emissions (12 %, 14 %, and 15 %, respectively), solid-fuel-based cooking (10 %, 10 %, and 8 %, respectively), and road construction (8 %, 6 %, and 9 %, respectively). Emission inventories tended to overestimate residential biofuel emissions at least by a factor of 2 relative to the PMF output. The major source of PM pollution was regional biomass burning, while traffic and industries governed VOC emissions and secondary-pollutant formation. Our novel source apportionment method even quantitatively resolved similar biomass and fossil fuel sources, offering insights into both VOC and PM sources affecting extreme pollution events. This approach represents a notable advancement compared to current source apportionment approaches, and it could be of great relevance for future studies in other polluted cities and regions of the world with complex source mixtures.

Volatile organic compounds in typical coal chemical industrial park in China and their environmental and health impacts

The coal chemical industry produces a large amount of volatile organic compounds (VOCs), and the emission characteristics and associated impact on the environment and health of the residents are still unclear. This study determined the VOC concentrations and compositions in the Jinjie Coal Chemical Industry Park which is located in northern China. The average concentrations of total measured VOCs (TVOCs) in the industrial areas in summer and winter were 231.5 and 103.2 μg/m3, which were higher than those in the residential areas (123.7 and 70.3 μg/m3), respectively. Aromatics, Oxygenated volatile organic compounds (OVOCs), and alkanes were the dominant VOC classes in the industrial areas, while halocarbons, OVOCs, and alkenes had higher compositions in the residential areas where were not only affected by industrial emissions and also other anthropogenic sources. OVOCs contributed over 43% of ozone formation potential (OFP), while aromatics contributed over 61% of secondary organic aerosol (SOA) formation in the Park in both seasons. Using the source apportionment method, biogenic emission and anthropogenic source (gasoline production, coking emission, fuel combustion, solvent coating, and vehicle exhaust) were major contributors to VOCs in residential areas. The industrial-related emissions were the main components of anthropogenic source, accounting for 53.5%–58.7% of the overall VOCs. With reliable estimations of the health aspects, exposures to acrolein (HQ: 7.4–126.6) and formaldehyde (ILCR: 5.5 × 10−3-5.7 × 10−2) posed the highest non-carcinogenic and carcinogenic risks, accounting for 94.3%–98.6% and 55.8%–93.8% of the total HQ and ILCR, respectively. The results demonstrated that substantial environmental and health co-benefits to the residents could be achieved by reducing the industrial emissions from gasoline production, coking process, and diesel-fueled vehicles in the Jinjie Coal Chemical Industry Park. Prioritizing the establishment of efficient air pollution measures and tightening industrial emission standards, especially for hazardous VOCs, are recommended according to the findings of the valuable work.

Accuracy and applicability of ship's fuel consumption prediction models: A comprehensive comparative analysis

The available extensive ship activity data enables employing a complex data-driven resistance-based power model to estimate ship's instantaneous power, and thus the ship's fuel consumption. The Ship Traffic Emissions Assessment Model emerges as a prominent example of such models. However, the performance of the Ship Traffic Emissions Assessment Model in ship's fuel consumption estimation is rarely verified by real fuel consumption data. Hence, this study aims to validate the accuracy of the Ship Traffic Emissions Assessment Model using real fuel consumption data and evaluates its applicability in terms of input features. Situations where the Ship Traffic Emissions Assessment Model shows large errors are identified to analyze its applicability. Furthermore, the Ship Traffic Emissions Assessment Model is compared with other popular fuel consumption prediction models, including the propeller law, the gradient-boosted regression tree model, and two grey box models. A systematical analysis is conducted to evaluate the applicability of various fuel consumption prediction models in different sailing scenarios, providing insights in selecting appropriate models for accurate ship's fuel consumption estimation. The findings contribute to optimizing the ship energy efficiency and facilitating the transition to alternative energy options, ultimately leading to a reduction in greenhouse gas emissions of the maritime industry.

Regulation techniques and applications of distributed load resources in urban power grids based on internet of things

The power consumption of urban power systems is increasing rapidly with two typical trends: the first one is that the daily peak-valley difference of loads is more significant, and the power supply is tight during peak hours, which threatens the system’s safe and stable operation; the second one is that the load energy efficiency in urban power systems is not high, which is the primary source of carbon emission in the power industry. Therefore, reducing the peak power and improving the system’s energy efficiency are urgent tasks for enhancing the system’s security and achieving the carbon emission goals. The rapid development of the Internet of Things (IoTs) ushers new opportunities for regulating demand-side loads. By analyzing the technical characteristics of load control based on IoTs, this paper investigates the modeling methods of load resources. On this basis, different control and optimization methods of load resources are analyzed and compared thoroughly. Besides, considering that load control is not only related to technical methods but also impacted by incentive strategies, the load control mechanisms under the mature and immature market environments are analyzed. Finally, the research gap and prospect of load regulation are proposed.

Evolutionary Game Analysis of Collaborative Prefabricated Buildings Development Behavior in China under Carbon Emissions Trading Schemes

Prefabricated buildings (PBs) are considered a green way to reduce energy consumption and carbon emissions in the construction industry due to their environmental and social benefits. However, PBs have obstacles such as high construction costs, immature technology, and insufficient policy incentives, and developers’ willingness to develop them needs to be higher. Therefore, it is necessary to explore how to motivate more developers to develop PBs. In this paper, we first discuss the impact of the carbon emissions trading scheme (ETS) on the construction industry and then consider the heterogeneity of construction developers, introduce a collaborative mechanism to establish a three-party evolutionary game model between the government and the heterogeneous developers, and explore the evolution of the three-party dynamic strategies through numerical simulation. The results show that developers’ initial development probability affects the system’s evolutionary trend, and the developer who obtains more low-carbon benefits plays a dominant role. Further analyses show that critical factors such as market profitability, synergistic benefits, and carbon tax price positively influence the development of PBs, and the influence of synergistic cooperation mechanisms should be especially emphasized. This study provides practical insights into the sustainable development of the construction industry and the government’s development of a suitable carbon portfolio policy for it. Including the construction industry in the ETS is recommended when carbon prices reach 110 RMB/t. At this point, the government can remove the subsidy for PBs, but the behaviors of the developers who participate in the ETS still need to be supervised.

Integrated CO2 capture and dynamic catalysis for CO2 recycling in a microbrewery

In this study, we used fermentation off-gases from a brewery for integrated CO2 capture and utilisation in order to produce CH4 with a dual-function material (DFM) containing NiRu as catalyst and dispersed CaO as adsorbent. CH4 was produced from captured CO2 via 2 pathways (fast and slow), proceeding through formyl intermediates according to the operando DRIFTS-MS results. The NiRuCa DFM showed a stable CH4 capacity over 8 cycles (105 μmol/gDFM) with fermentation off-gases being used as a CO2 capture feed. H2O and O2, which were present in small amounts in the emissions feed, resulted in the passivation of Ni in the form of a NiO layer and hence, the DFM did not undergo excessive oxidation and deactivation. This work constitutes a first in terms of validating the use of DFMs with real industrial emissions, and it directly correlates the DFM activity performance with its reaction mechanism and intermediate species.

Artificial Neural Network-Based Route Optimization of a Wind-Assisted Ship

The International Maritime Organization aims for net-zero carbon emissions in the maritime industry by 2050. Among various alternatives, route optimization holds an important place as it does not require any additional component-related costs. Especially for wind-assisted ships, the effectiveness of different sailing systems can be improved significantly through route optimization. However, finding the ship’s optimal route is computationally expensive when the totality of possible weather conditions is taken into consideration. To determine the optimal route that minimizes energy consumption, an energy model based on the environmental conditions, ship route and ship speed was built using artificial neural networks. The energy consumed for given input data was calculated using a ship dynamics model and a database was generated to train the artificial neural networks, which predict how much energy is consumed depending on the route followed in given environmental conditions. Then, such networks were exploited to derive the optimal routes for all the relevant operational conditions. It was found that route optimization can reduce the overall ship energy consumption depending on the weather conditions of the environment by up to 9.7% without any increase in voyage time and by up to 35% with a 10% delay in voyage time. The proposed methodology can be applied to any ship by training real weather conditions and provides a framework for reducing energy consumption and greenhouse gas emissions during the service life of ships.

New perspective, more rational decoupling: A case study of China

Scholars usually unconsciously employ the Tapio decoupling model with a static perspective and results-oriented philosophy, which often leads to errors. Therefore, we propose an improved Tapio decoupling model that adopts a dynamic perspective and process-oriented philosophy. Taking China, the world's largest carbon emitter, as a case study, we investigate the decoupling of its provincial industrial carbon emissions (ICE) from industrial value-added (IVA) during 2005–2020 using both the conventional and improved decoupling model, followed by a comparative analysis of their results. Our findings are as follows: (1) Both China's ICE and IVA exhibited a general upward trend during the study period, with non-linear annual ICE and IVA variations observed across all provinces. (2) Overall, China's provincial IVA increasingly decoupled from ICE, with some provinces achieving a strong decoupling state during 2015–2020; however, from the long-term perspective spanning the entire study period, most provinces remained in a weak decoupling state. (3) The conventional decoupling model tends to yield overly optimistic results in empirical study of China, with the decoupling indices during the periods of 2005–2010 and 2005–2020 determined by the conventional model even had significant statistical difference between those determined by the improved model. (4) To ensure equity, differentiated carbon reduction policies should be tailored to each province, considering factors such as absolute carbon emissions, short-term decoupling states, and long-term decoupling states. The improved Tapio decoupling model is proposed as a valuable framework for researchers engaged in related studies.

The chemical characteristics and sources of formaldehyde on O3 and non-O3 polluted days in Wuhan, central China

In August 2023, a detailed investigation of formaldehyde (HCHO) chemical characteristics on ozone (O3) polluted days and non-O3 polluted days in Wuhan was undertaken. The mean value of HCHO on O3 polluted days (3.02 ± 1.15 ppbv) was 122% higher than that on non-O3 polluted days (1.35 ± 0.41 ppbv). Utilizing Positive Matrix Factorization (PMF) model revealed secondary formation as the dominant HCHO source (58.3% on non-O3 polluted days and 66.2% on O3 polluted days). On O3 polluted days, the contribution of liquefied petroleum gas (LPG)/solvent usage and industrial emissions to HCHO were 13.7% and 8.2%, respectively, whereas on non-O3 polluted days, LPG/solvent use and diesel exhaust contributed 15.4% and 14.7%, respectively. The top ten species, with the highest Relative Incremental Reactivity (RIR) to HCHO, were mainly alkenes and aromatics, which remained consistent on both O3 and non-O3 polluted days. It is noteworthy that the RIR of isobutane to HCHO is significant in this study. Further reapportionment of secondary HCHO by a photochemical box model indicated that LPG/solvent usage (33.2%) contributed the most to HCHO on O3 polluted days, while diesel exhaust (31.9%) dominated on non-O3 polluted days. This research enhances understanding of HCHO in Wuhan, providing a theoretical basis for targeted pollution reduction and supporting efforts to improve air quality and public health.

Life cycle environmental trade-off of decarbonising UK industrial clusters — A cradle to gate approach

The industrial sector is a major source of greenhouse gas (GHG) emissions due to process emissions and a heavy reliance on fossil fuels for heat and power. Methods exist to produce low carbon versions of products made in industrial clusters, including hydrogen, carbon capture and storage and alternative production methods, but these could increase burdens to other areas of the environment, such as resource depletion and water scarcity. This study compares different decarbonisation pathways for ammonia, cement, methanol and steel produced in the UK, to determine whether decarbonising could result in unintended environmental consequences. To determine this, life cycle assessment was applied to compare 267 different pathways to the conventional (fossil fuel) baseline. We find that most pathways lead to GHG emission reductions (43 to 78 % on average) but would increase impacts to other areas of the environment, including metal resources and ecotoxicity (8 % to 5-fold and 19 % to 24-fold, on average respectively). This study is the first to assess decarbonisation pathways for unintended environmental impacts and is of interest to industry, policy makers and anyone modelling industrial lifecycle emissions.

The microbiome of bioreactors containing mass-cultivated marine diatoms for industrial carbon capture and utilization

Marine microalgae are a promising innovation platform for carbon capture and utilization (CCU) biotechnologies to mitigate industrial greenhouse gas emissions. However, industrial-scale cultivation of algal mono-cultures is challenging and often unscalable. Non-axenic microalgae in large semi-open photobioreactors lead to the co-cultivation of diverse microbial communities. There is limited knowledge about the “bioreactor ecology” involving microalgae interacting with the microbiome and its subsequent impact on process stability and productivity. In this study, we describe the semi-continuous industrial mass cultivation of the cold-adapted marine diatom, Porosira glacialis UiT201, by investigating the prokaryotic and microeukaryotic (phytoplankton and heterotrophic protist) communities. Data were collected in two consecutive time series experiments, representing the initiation and operation of an industrial-scale CCU photobioreactor (300,000 L). The first experiment experienced a culture “crash” of the focal strain after 39 days, while the second culture remained stable and “healthy” for 60 days. The results highlight that this mass cultivation system represents a unique industrial marine microbial ecosystem. The succession of the prokaryotic community was primarily driven by species replacement, indicating turnover due to selective bioreactor conditions and/or biological interactions. Nonetheless, the bioreactor consistently harbors a recurring and abundant core microbiome, suggesting that the closely associated bacterial community is influenced by microalgae-specific properties and can endure a dynamic and variable environment. The observed culture collapse of P. glacialis coincided with changes in the core microbiome structure and different environmental growth conditions compared to the stable and “healthy” experiment. These findings imply that cohabiting microbial taxa within industrial microalgae cultivation likely play a critical role in stabilizing the conversion of industrial CO2 into marine biomass, and changes in community structure serve as an indicator of process stability.

Increasing the efficiency of coagulation in resonant gaps due to acoustic flow formation

Relevance. The urgent need to eliminate environmental pollution from industrial emissions of various solid particles. At the same time, maximum attention is paid to cleaning exhaust gases from particles of 2.5 microns in size or less. One of the most promising ways to increase the efficiency of existing gas purification equipment in capturing such particles is their coagulation by exposing the gas flow to high-intensity acoustic vibrations of ultrasonic frequency. However, at low concentrations, even at the maximum permissible sound pressure level, the coagulation efficiency of particles smaller than 2.5 microns is insufficient to increase the recovery rate of gas cleaning equipment. Therefore, there is an urgent need to find new ways to further improve the efficiency of ultrasonic coagulation of particles smaller than 2.5 μm. Aim. To determine the conditions for the formation of vortex flows in ultrasonic fields with the maximum ultrasonic influence in terms of sound pressure level. Conducting comparative studies of the coagulation of particles with a size of 2.5 microns with and without vortex flows. This will make it possible to determine the real values of increasing the efficiency of ultrasonic coagulation during turbulization of a gas-dispersed flow by acoustic flows in comparison with coagulation in a uniform ultrasonic field and without it. Objects. Coagulation of particles under the influence of homogeneous and inhomogeneous ultrasonic fields. Methods. Computer modeling of the formed ultrasonic field by the finite element method using harmonic acoustic analysis. The paper considers the experimental method for studying the process of combining particles under the influence of ultrasonic vibrations. To determine the characteristics of an aerosol during experimental studies, a TIPAS-1 meter based on the small-angle scattering method and the spectral transparency method was used. Results. The paper introduces the results of studies of coagulation of particles with a size of 2.5 microns or less in an ultrasonic field formed in resonant gaps by oscillating disk emitters. The authors proposed to increase the efficiency of coagulation in resonant gaps through the use of ultrasonic disk emitters capable of forming alternating zones of maximum and minimum amplitude oscillations in the resonant gaps. The creation of such zones ensured the formation of vortex-type acoustic flows capable of moving particles within the nodal regions of a standing wave and between them. The involvement of small particles in the formed flows made it possible to increase the probability of their collision. It was established that more effective ultrasonic coagulation provides an increase in the degree of inertial capture for particles of 2.5 microns in size by 6% – from 89 to 95%, for particles of 1.5 microns in size by 7% – from 85 to 92%, and for particles of 0.5 microns by 9% – from 76 to 85%.

Prescriptions (Rx) for Prevention: Clinical Tools for Integrating Environmental Health into Pediatric Clinical Care

The integration of environmental health (EH) into routine clinical care for children is in its early stages. The vision of pediatric EH is that all clinicians caring for children are aware of and able to help connect families to needed resources to reduce harmful environmental exposures and increase health-enhancing ones. Environmental exposures include air pollution, substandard housing, lead, mercury, pesticides, consumer products chemicals, drinking water contaminants, industrial facility emissions and, increasingly, climate change-related extreme weather and heat events. An identified need is to simultaneously educate clinicians while connecting families to evidence-based EH interventions. Here, we describe a multi-decadal effort to create, refine, and disseminate a clinical tool called Prescriptions (Rxs) for Prevention that responds to that identified need. These tools are modeled on a risk communication framework and use a format that support clinicians when they screen their patients for EH concerns, to then counsel on those topics, and refer to EH resources if needed. Rxs for Prevention—tailored with local resources—are now in use at more than a dozen sites in multiple regions of the U.S. supporting the promotion of healthy homes, communities, and the broader environment for children. These Rxs are reducing barriers to EH integration by educating clinicians, linking families to community resources, and strengthening clinic and community connections. On-going evaluation can help further the implementation of the Rxs for Prevention to help achieve the long-term vision of integrating EH into routine clinical care.

Alcohols as Biofuel for a Diesel Engine with Blend Mode—A Review

In the era of decarbonization driven by environmental concerns and stimulated by legislative measures such as Fit for 55, the industry and transportation sectors are increasingly replacing petroleum-based fuels with those derived from renewable sources. For many years, the share of these fuels in blends used to power compression ignition engines has been growing. The primary advantage of this fuel technology is the reduction of GHG emissions while maintaining comparable engine performance. However, these fuel blends also have drawbacks, including limited ability to form stable mixtures or the requirement for chemical stabilizers. The stability of these mixtures varies depending on the type of alcohol used, which limits the applicability of such fuels. This study focuses on evaluating the impact of eight types of alcohol fuels, including short-chain (methanol, ethanol, propanol) and long-chain alcohols (butanol, pentanol, hexanol, heptanol, and octanol), on the most critical operational parameters of an industrial engine and exhaust emissions. The engines being compared operated at a constant speed and under a constant load, either maximum or close to maximum. The study also evaluated the effect of alcohol content in the mixture on combustion process parameters such as peak cylinder pressure and heat release, which are the basis for parameterizing the engine’s combustion process. Determining ignition delay and combustion duration is fundamental for optimizing the engine’s thermal cycle. As the research results show, both the type of alcohol and its concentration in the mixture influence these parameters. Another parameter important from a usability perspective is engine stability, which was also considered. Engine performance evaluation also includes assessing emissions, particularly the impact of alcohol content on NOx and soot emissions. Based on the analysis, it can be concluded that adding alcohol fuel to diesel in a CI engine increases ignition delay (up to 57%), pmax (by approximately 15–20%), HRRmax (by approximately 80%), and PPRmax (by approximately 70%). Most studies indicate a reduction in combustion duration with increasing alcohol content (by up to 50%). For simple alcohols, an increase in thermal efficiency (by approximately 15%) was observed, whereas for complex alcohols, a decrease (by approximately 10%) was noted. The addition of alcohol to diesel slightly worsens the stability of the CI engine. Most studies pointed to the positive impact of adding alcohol fuel to diesel on NOx emissions from the compression ignition engine, with the most significant reductions reaching approximately 50%. Increasing the alcohol fuel content in the diesel blend significantly reduced soot emissions from the CI engine (by up to approximately 90%).

Pollution Characteristics and Source Apportionment of Heavy Metals in Topsoil of Counties Along the Shandong Section of the Yellow River

The 25 counties along the Shandong section of the Yellow River are the core areas for promoting the ecological protection and high-quality development of the Yellow River in Shandong Province. Moreover, it is of great significance to study the current situation, sources, and potential risks of heavy metal pollution in the topsoil in this region. In this study, 103 soil samples were collected from the 25 counties along the Shandong section of the Yellow River, and the contents of eight heavy metals （As, Cu, Pb, Cr, Zn, Ni, Cd, and Hg） were determined. The pollution characteristics of heavy metals were analyzed and evaluated using the geological accumulation index and potential ecological risk index. Correlation analysis and the positive matrix factorization （PMF） model were used to analyze the sources of heavy metals. The results showed that the average contents of Cu and Cr were lower than that of the background values of soils, whereas the average contents of As, Pb, Zn, Ni, Cd, and Hg were 1.16, 1.42, 1.05, 1.14, 2.29, and 1.85 times higher than that of the background values, respectively, and the average contents of all eight elements were lower than the screening value of soil pollution risk in agricultural land. In terms of different heavy metal variations, the coefficient of variation （CV） of Cu and Cd was higher than 0.500, indicating high variations, whereas As, Pb, Cr, Zn, Ni, and Hg showed moderate variation. Cd and Hg were slightly polluted, whereas the other six elements were not polluted. Cd and Hg had a moderate potential ecological risk level, whereas the other six elements were at a low level. Correlation analysis and PMF model showed that the sources of heavy metals in the study area were influenced by four factors, i.e., agricultural activities, natural sources, industrial emissions, and atmospheric dust from coal combustion and vehicle exhaust emissions, and the relative contribution rates were 32.4%, 34.9%, 16.5%, and 16.2%, respectively.

Spatiotemporal Differentiation of Carbon Emissions from Logistics Industry at Provincial Scale in China Under the Background of High-quality Economic Development

Since 2010, the Chinese economy has transitioned from a high-speed growth model to a high-quality development model. During this period, the logistics industry has witnessed rapid growth, leading to significant carbon emissions and posing severe threats to the ecological environment. To investigate the spatiotemporal variations in carbon emissions in China's logistics industry, we conducted a correlation analysis using Moran's I index and a bivariate spatial autocorrelation model from 2010 to 2021. Additionally, we employed a geographically and temporally weighted regression model （GTWR） to examine the spatial heterogeneity of factors influencing provincial-level logistics-related carbon emissions. The results indicated that over the study period, there was a shift from insignificant spatial relationships to significant positive spatial correlations among provincial-level logistics carbon emissions in China. Furthermore, varying degrees of spatial clustering were observed. The findings regarding factor heterogeneity revealed that freight turnover volume, per capita GDP of the logistics industry, and infrastructure level exhibited positive spatial correlations with logistics-related carbon emissions, whereas energy intensity showed negative spatial correlations with such emissions. Comparing the results from the geographically weighted regression （GWR） and ordinary least squares regression （OLS）, it was evident that the adjusted R-squared values for the OLS, GWR, and GTWR models were 0.541, 0.567, and 0.838, respectively. This suggests that our adopted GTWR model provided a superior fit and offered better explanations for spatiotemporal heterogeneity between various influencing factors and logistics-related carbon emissions. These research findings can serve as valuable references for formulating province-specific strategies to reduce carbon emissions within China's economy under its high-quality development context.

Government relocation and air pollution: Evidence from China

In the pursuit of sustainable economic development, many cities have initiated the relocation of government offices as a strategy to optimize resource allocation. This study examines the environmental impacts of local government relocations in China between 1999 and 2016, with a focus on PM2.5 concentration data in the areas surrounding the relocation sites. Utilizing a difference-in-differences estimation approach, our findings indicate that (1) relocating local government offices significantly reduces pollution levels in nearby areas, with more pronounced effects closer to the relocation site; (2) environmental quality improvements intensify over time before stabilizing; (3) the relocation reform enhances the overall environmental quality of the entire city; and (4) government site relocations ultimately lead to regional environmental quality improvements by fostering the development of clean industries and reducing industrial pollution emissions. These results underscore the policy significance of green development principles and the spatial optimization of public resources.