Emission Rates Research Articles

Fluorotelomer Alcohol (FTOH) Emission Rates from New and Old Rain Jackets to Air Determined by Iodide High-Resolution Chemical Ionization Mass Spectrometry

Per- and polyfluoroalkyl substances (PFAS), which include fluorotelomer alcohols (FTOHs), are synthetic chemicals used in consumer products because of their water-, stain-, and grease-repellent properties; thus, PFAS are commonly found in functional clothing such as rain jackets. To date, emissions of PFAS from products to indoor air have not been well characterized, although many PFAS-containing products are used and stored indoors. We used a test chamber connected to a high-resolution time-of-flight chemical ionization mass spectrometer equipped with iodide as a reagent ion (I-HR-ToF-CIMS) to measure emission rates for four FTOHs from 10 rain jackets and one backpack cover. The materials were categorized as old/used, new, or “PFAS-free”, and they were tested under two different scenarios, i.e., immediately out of package and after airing out. We observed real-time FTOH emissions from all materials. Under the out-of-package scenario, emissions of 6:2, 8:2 and 10:2 FTOH showed characteristics that indicate mass transfer is limited by internal diffusion, with a high initial peak followed by a lower steady-state emission rate. Peak emission rates correlated well with material-phase concentrations determined by an offline extractive gas chromatography-mass spectrometry (GC-MS) method. Our results further suggest that the old, used jackets had, on average, higher peak emission rates and higher material-phase concentrations than the new jackets, largely driven by 8:2 FTOH. “PFAS-free” materials had the overall lowest emission rates and material-phase concentrations. After airing out, emission rates were on average an order of magnitude lower than peak emission rates. Our findings emphasize the importance of considering consumer products like rain jackets as sources of indoor exposure to PFAS.

Techno-enviro-economic assessment of hydropower-driven decarbonization pathways for Nepalese cement industry

This study presents a comparative techno-enviro-economic assessment of decarbonization measures for the Nepalese cement sector, focusing on post-combustion carbon capture (PCC), use of alternative fuels and oxy-combustion techniques. A typical Nepalese clinker plant is first modelled in Aspen Plus using industrial data, the results of which is then utilized to simulate various decarbonization pathways. Performance of the measures is evaluated based on four performance indicators. The combination of oxy-combustion with hydrogen as fuel (25% thermal substitution rate) is identified as a favorable pathway compared to PCC only and combination of refuse derived fuel and PCC pathways. However, this pathway is sensitive to hydrogen byproduct price. The levelized cost of clinker (LCOC), CO2 abatement cost (CAC), specific electricity consumption for avoided CO2 and carbon intensity for this pathway are 145 USD/tclinker, 98 USD/tCO2, 1.88 MWh/tCO2 and 100 kgCO2/tclinker respectively. The LCOC value for the reference clinker plant without decarbonization is 75 USD/tclinker. The electricity consumption increased by 2153.80%, and the emissions rate decreased by 88%, compared to the reference clinker plant. Capacity utilization rates above 80% are favorable for decarbonization. Sensitivity analysis showed that a 30% decrease in the hydroelectricity cost would lower the LCOC and CAC from base values by 21.160% and 42.379% respectively. Similarly, increasing the tariff rebate to 30% would lower the LCOC and CAC for this case by 12.447% and 24.928% respectively. The results highlight a synergistic relationship between cement industry decarbonization and hydroelectricity utilization, both key targets of Nepal for net zero pathway.

Innovative biogas energy system: Enhancing efficiency and sustainability through multigeneration integration

This research suggests using landfill gas, derived from landfilling operations, as a feasible alternative to fossil fuels. This study introduces a novel and all-encompassing method for utilizing landfill biogas. The proposed system utilizes a supercritical Brayton cycle with carbon dioxide as the working fluid, a transcritical CO2 cycle, two ammonia Rankine cycles, a single-effect desalination cycle, a proton exchange membrane electrolyzer, and an improved Kalina cycle. The system underwent evaluation using Aspen HYSYS software, enabling assessments in terms of energy, exergy, thermo-economic, and environmental variables. The examination of the findings indicates that the suggested solution has much higher energy efficiency compared to similar studies. The assessments determined the energy efficiency of the process in power generation, combined heat and power, combined cooling, heat and power, and multigeneration modes to be 23.62 %, 80.89%, 81.19%, and 82.72%, respectively. Furthermore, environmental research has revealed that the new process emits a total of 1743 kg/h of carbon dioxide and has an emission rate of 0.23 kg/kWh. The exergy analysis indicated that the fuel burner exhibited the greatest degree of irreversibility, accounting for 40%. Furthermore, a sensitivity analysis was performed on crucial parameters, including the temperature of the heat source in the single-effect desalination section and the rate at which water flows into the electrolyzer. The objective was to evaluate the influence of changes in these parameters on energy efficiency, exergy efficiency, carbon dioxide emission intensity, product production rate, and levelized energy cost. The economic analysis determined that the proposed scheme would have a total annual cost of 8,667,124 $ with a levelized energy cost of 0.17 $/kWh.

Efficient Thermal Integration Model based on a Biogas-fired Gas Turbine Cycle (GTC) for Electricity and Desalination Applications; Thermo-Economic and GA-based Optimization

As the global energy demand continues to rise, there is an urgent need to improve the efficiency and sustainability of power generation systems. This study integrated a modified supercritical carbon dioxide (S-CO2) and multi-effect desalination (MED) units to recover residual heat from a gas turbine cycle (GTC) in two stages, significantly enhancing electricity production while reducing the environmental footprint of the GTC. The significance of this study lies in its comprehensive approach, combining thermodynamic, environmental, and thermoeconomic analyses alongside thorough sensitivity evaluations. A triple optimization framework was implemented to optimize the system's performance, focusing on key metrics such as exergy efficiency, CO2 reduction rates, and levelized energy cost, utilizing the NSGA-II and the TOPSIS decision-making method in MATLAB software. Economic viability was assessed through a net present value (NPV) analysis, demonstrating substantial profitability. Finally, a comparison study of the devised system CO2 emissions rate was performed for different renewable energy sources. A specific application of the devised system is its capacity to generate 1.415 m³/h of distilled water while generating 1441 kW of electricity. Sensitivity analysis identified the combustion chamber temperature as the most critical design parameter, with a sensitivity index of 0.328. The optimum economic indicators showed marked improvement, with the NPV increasing from 2.371 M$ to 10.75 M$ and the payback period decreasing from 13.28 years to 7.18 years.

Evaluation of wood coating performance and volatile organic compounds

The aim of this study was to evaluate the environment-performance relationship of surface coating applications on data obtained by measuring the emission rates of volatile organic compounds in polyurethane and water-based varnishes. For this purpose, polyurethane and water-based varnishes from five different companies were applied to the test samples of Entandrophragma cylindricum (sapele) and Piptadeniastrum africanum (dabema), both widely used in the production of urban furniture. Volatile organic compound, hardness and adhesion strength were measured during application. When evaluated in terms of performance, polyurethane varnishes showed superior hardness, while water-based varnishes demonstrated better adhesion after the UV test. The hardness values of polyurethane varnishes before and after the UV aging test were 15,9 s and 79,403 s, respectively, while forwater-based varnishes were , the values were 114,92 s and 75,406 s. The adhesion values of water-based varnishes were 2,885 MPa and 1,18 MPa before and after the UV aging test, and for polyurethane varnishes 3,13 MPa and 1,05 MPa for. When the environment-oriented results were evaluated, the ; emission values of volatile organic compounds in polyurethane varnish applications were found to be significantly higher than those in in water-based varnishes applications. While the total emission rate of volatile organic compounds detected in polyurethane varnishes was 53,63 mg/Nm3, while only one brand of water-based varnishes showed a measurable emission value, recorded at 0,0057 mg/Nm3. The volatile organic compounds emission values of other water-based varnishes were below the device detection limit (<0,0035 mg/Nm3), and therefore could not be measured.

Development of seasonal ozone maximum reactivity scales for Beijing, China.

We designed scenarios based on urban emissions to develop a Maximum Incremental Reactivity (MIR) scale for 41 conventional volatile organic compounds (VOCs) in Beijing and quantitatively analyzed the various factors affecting MIR in urban areas. We explored the effects of updating the representative urban atmosphere used for ozone reactivity calculations by incorporating updated meteorological data, emission rates, initial condition concentrations, and VOC profile compositions. A box model equipped with the Master Chemical Mechanism (MCM) was used to localize the MIR scale for Beijing based on urban emission model inputs, and this was compared with scenarios in the United States. The MIR differences for most VOC species were minimal; however, Beijing exhibited higher MIR values for aromatic hydrocarbons in the summer, attributed to the higher emission intensity of aromatics in the city. Due to differences in meteorological conditions and emission scenarios, the MIR showed significant seasonal characteristics across different months. It is necessary to calculate independent MIR scales for different urban agglomerations under specific ozone pollution seasons and emission conditions. This study provides recommendations for the application of the MIR scale and can serve as a reference for VOC control strategies in China and other countries facing ozone pollution.

Nitrogen Addition Increased the Greenhouse Gas Emissions of Permafrost Peatland Due to the Abundance of Soil Microbial Functional Genes Increasing in the Great Khingan Mountains, Northeast China

Permafrost peatlands are sensitive to changes in nitrogen levels because they are largely nitrogen-limited ecosystems. However, the microbial mechanisms by which the addition of nitrogen increases the emission of greenhouse gasses from permafrost peatlands remain unclear. This study was conducted to decipher the relationship between greenhouse gas emissions and soil microorganisms under nitrogen addition. Here, we performed a 154-day experimental investigation in order to assess the release of greenhouse gasses such as CO2, CH4, and N2O from the soils. Additionally, we examined the correlation between the rates of these gas emissions and the presence of crucial microbial functional genes in the soil. The results showed that the addition of low (0.01 g kg−1), medium (0.02 g kg−1), and high (0.04 g kg−1) levels of nitrogen increased the cumulative CO2 emissions by 2.35%–90.42%, respectively. The cumulative emissions of CH4 increased by 17.29%, 25.55% and 21.77%, respectively. The cumulative emissions of N2O increased 2.97, 7.49 and 7.72-fold. The addition of nitrogen increased the abundance of functional genes in the bacteria, fungi, methanogens, denitrifying bacteria, and nitrogen-fixing bacteria in soil by modifying abiotic soil variables and providing sufficient substrates for microorganisms. The results indicated that the addition of nitrogen can significantly promote the emission of greenhouse gasses by increasing the abundance of functional microbial genes in the soil of permafrost peatlands. These findings highlight the importance of considering nitrogen deposition and the nitrogen released from thawing permafrost when predicting the future greenhouse gasses emitted from permafrost peatlands.

Production Simulation of Stimulated Reservoir Volume in Gas Hydrate Formation with Three-Dimensional Embedded Discrete Fracture Model

Natural gas hydrates (NGHs) in the Shenhu area of the South China Sea are deposited in low-permeability clayey silt sediments. As a renewable energy source with such a low carbon emission, the exploitation and recovery rate of NGH make it difficult to meet industrial requirements using existing development strategies. Research into an economically rewarding method of gas hydrate development is important for sustainable energy development. Hydraulic fracturing is an effective stimulation technique to improve the fluid conductivity. In this paper, an efficient three-dimensional embedded discrete fracture model is developed to investigate the production simulation of hydraulically fractured gas hydrate reservoirs considering the stimulated reservoir volume (SRV). The proposed model is applied to a hydraulically fractured production evaluation of vertical wells, horizontal wells, and complex structural wells. To verify the feasibility of the method, three test cases are established for different well types as well as different fractures. The effects of fracture position, fracture conductivity, fracture half-length, and stimulated reservoir volume size on gas production are presented. The results show that the production enhancement in multi-stage fractured horizontal wells is obvious compared to that of vertical wells, while spiral multilateral wells are less sensitive to fractures due to the distribution of wellbore branches and perforation points. Appropriate stimulated reservoir volume size can obtain high gas production and production efficiency.

Corner Reflector Plasmonic Nanoantennas for Enhanced Single-Photon Emission

The emission rate of atom-like photon sources can be significantly improved by coupling them to plasmonic resonant nanostructures. These arrangements function as nanoantennas, serving the dual purpose of enhancing light–matter interactions and decoupling the emitted photons. However, there is a contradiction between the requirements for these two tasks. A small resonator volume is necessary for maximizing interaction efficiency, while a large antenna mode volume is essential to achieve high emission directivity. In this work, we analyze a hybrid structure composed of a noble metal plasmonic resonant nanoparticle coupled to the atom-like emitter, which is designed to enhance the emission rate, alongside a corner reflector aimed at optimizing the angular distribution of the emitted photons. A comprehensive numerical study of silver and gold corner reflector nanoantennas, employing the finite difference time domain method, is presented. The results demonstrate that a well-designed corner reflector can significantly enhance photon emission directivity while also substantially boosting the emission rate.

Unexpectedly strong heat stress induction of monoterpene, methylbutenol, and other volatile emissions for conifers in the cypress family (Cupressaceae)

We investigated the biogenic volatile organic compound (BVOC) emission rates and composition of Cupressaceae species and how the emissions change in response to moderate warming and more severe heat stress. A total of 8 species from 7 distinct Cupressaceae genera were targeted in this study and exposed to laboratory-simulated heatwaves. Each plant was enclosed in a temperature-controlled glass chamber and allowed to equilibrate at 30 °C for 24 h. The temperature was then increased stepwise from 33 °C to 43 °C in 2 °C increments, with each step lasting 2 h, and was finally kept at 45 °C for 12 h. The BVOC emissions were measured periodically using an automated air sampler coupled to a gas chromatograph.Most of the sampled Cupressaceae species (6 out of 8) were low BVOC emitters (<0.3 μgC g−1 h−1) at 30 °C. However, the BVOC emissions of all 8 species increased strongly with temperature, and in most species (5 out of 8), the emissions continued to increase with longer exposure times to heat stress. The largest increase was observed in Thuja occidentalis and Chamaecyparis thyoides, which reached maximum emissions of 350 and 190 μgC g−1 h−1, respectively. Of the different BVOCs, monoterpenes responded most strongly to heat stress, with Q10 temperature coefficients typically ranging between 7.6 and 22, which were significantly greater than the model-predicted value of 2.7. Other BVOCs including sesquiterpenes, C9 aromatics (only detected in Calocedrus decurrens), methylbutenols, and other C5 oxygenates were also induced by heat stress, but generally at a lower magnitude than monoterpenes.Our results indicate that Cupressaceae are a large but typically dormant source of reactive volatile hydrocarbons (mostly monoterpenes) whose emissions can be activated by heat stress. This phenomenon could have important implications for ozone and aerosol formation, air quality, and human health, particularly in urban areas that are prone to heatwaves.

Environmental and Cost Assessments of Marine Alternative Fuels for Fully Autonomous Short-Sea Shipping Vessels Based on the Global Warming Potential Approach

This research paper presents an effective approach to reducing marine pollution and costs by determining the optimal marine alternative fuels framework for short-sea shipping vessels, with a focus on energy efficiency. Employing mathematical models in a Python environment, the analyses are tailored specifically for conventional and fully autonomous high-speed passenger ferries (HSPFs) and tugboats, utilizing bottom-up methodologies, ship operating phases, and the global warming potential approach. The study aims to identify the optimal marine fuel that offers the highest Net Present Value (NPV) and minimal emissions, aligning with International Maritime Organization (IMO) regulations and environmental objectives. Data from the ship’s Automatic Identification System (AIS), along with specifications and port information, were integrated to assess power, energy, and fuel consumption, incorporating parameters of proposed marine alternative fuels. This study examines key performance indicators (KPIs) for marine alternative fuels used in both conventional and autonomous vessels, specifically analyzing total mass emission rate (TMER), total global warming potential (TGWP), total environmental impact (TEI), total environmental damage cost (TEDC), and NPV. The results show that hydrogen (H2-Ren, H2-F) fuels and electric options produce zero emissions, while traditional fuels like HFO and MDO exhibit the highest TMER. Sensitivity and stochastic analyses identify critical input variables affecting NPV, such as fuel costs, emission costs, and vessel speed. Findings indicate that LNG consistently yields the highest NPV, particularly for autonomous vessels, suggesting economic advantages and reduced emissions. These insights are crucial for optimizing fuel selection and operational strategies in marine transportation and offer valuable guidance for decision-making and investment in the marine sector, ensuring regulatory compliance and environmental sustainability.

Integrated Fertilizers for Sustainable Wheat Production to Improve Food Security—A Comprehensive Review

ABSTRACTWheat is a key cereal crop that is substantial to global food security. Fertilizers are crucial in wheat production and significantly impact the yield. This review aims to evaluate the effectiveness of inorganic, organic, and integrated fertilizers in terms of sustainable wheat production and economic and environmental benefits. For this review, we thoroughly examined 133 previous research findings. The results indicate that inorganic fertilizers play a vital role in improving wheat yield. However, continuous use of inorganic fertilizers pollutes the environment, affects beneficial microorganisms in the soil, and increases the emissions of greenhouse gases, consequently decreasing crop yield. Organic fertilizers enhance soil quality, which is critical for crop growth and development. However, a high concentration of methane (CH4), nitrous oxide (N2O), and carbon dioxide (CO2) are emitted from organic fertilizers, but the CO2 emission rate is less than the sequestration rate. Integrated fertilizers trade off the drawbacks of both inorganic and organic fertilizers. Integrated fertilizers decrease nitrous oxide (N2O) and ammonia (NH3) emissions and carbon loss by 11%–24%, 13%–27%, and 18%, respectively, compared to the sole use of fertilizers. From the review analysis, the highest grain yield (4855 kg ha−1) and net benefit ($2836.66) are achieved by using a combination of 75% organic and 25% inorganic fertilizers at a rate of 120 kg N ha−1. Therefore, this combination is recommended for the users. Furthermore, a site‐specific approach research is needed on integrated fertilizers that simultaneously focus on economic and environmental profits. Also, there must be a policy that supports the farmers in teaching, training, and subsidizing them to adopt integrated fertilizers for sustainable wheat production and improving food security.

Spontaneous photon emission by shaped quantum electron wavepackets and the QED origin of bunched electron beam superradiance.

It has been shown that the spontaneous emission rate of photons by free electrons, unlike stimulated emission, is independent of the shape or modulation of the quantum electron wavefunction (QEW). Nevertheless, here we show that the quantum state of the emitted photons is non-classical and does depend on the QEW shape. This non-classicality originates from the shape dependent off-diagonal terms of the photon density matrix. This is manifested in the Wigner distribution function and would be observable experimentally through homodyne detection techniques as a squeezing effect. Considering a scheme of electrons interaction with a single microcavity mode, we present a QED formulation of spontaneous emission by multiple modulated QEWs through a build-up process. Our findings indicate that in the case of a density modulated QEWs beam, the phase of the off-diagonal terms of the photon state emitted by the modulated QEWs is the harbinger of bunched beam superradiance, where the spontaneous emission is proportional to N_e^2 . This observation offers a potential for enhancement of other quantum electron interactions with quantum systems by a modulated QEWs beam carrying coherence and quantum properties of the modulation.

Research on single-point fast three-dimensional concentration reconstruction of a smoke plume based on the static interference infrared imaging spectroscopy system

To meet the requirements of real-time and effectiveness of three-dimensional concentration telemetry of gas clouds and address the difficulty of fast three-dimensional concentration reconstruction of single instrument smoke plumes, the paper proposes a single-point fast three-dimensional concentration reconstruction of the smoke plume based on a static interference infrared Fourier transform imaging spectrometer (ISIFTS) by using the advantages of high throughput, large field of view, high stability, and rapid detection. Based on the scanning field switching characteristics of ISIFTS, a single instrument quickly scans the dual-field map data to obtain the three-dimensional point cloud of the target scene. Combined with the three-dimensional spatial parameters of the scene, a multi-dimensional re-projection algorithm is constructed based on the Gaussian plume continuous diffusion model to simulate the concentration-path-length product (CL) image, and the measured CL image is solved by analyzing the smoke plume image spectra data. The normalized cross-correlation fitting algorithm is used to perform the optimal matching of simulated-measured CL images, and then the three-dimensional concentration distribution of the plume scene is reconstructed based on the dimension mapping relationship. The field smoke plume telemetry experiment was designed and carried out, and the three-dimensional concentration distribution of plume gas at three emission points in the scene was obtained. The CO2 emission rates were calculated to be 13.572 kg / s, 12.225 kg / s, and 14.114 kg / s, respectively. The data are consistent with the emission rate of the coal-fired thermal power plant, which verifies the effectiveness of the single-point fast three-dimensional concentration reconstruction of the smoke plume method based on the ISIFTS system.

A hybrid metaheuristic and simulation approach towards green project scheduling

AbstractThis research tackles the environmental concern of greenhouse gas emissions in the execution of projects, with a focus on multi-site projects where the transportation of resources is a major source of emissions. Despite growing consciousness among consumers and stakeholders about sustainability, the domain of project scheduling has often overlooked the environmental impact. This paper seeks to bridge this oversight by exploring how to reduce greenhouse gas emissions during both project activities and resource transportation. A novel approach is proposed, combining a simulation model with an improved non-dominated sorted genetic algorithm. The simulation model incorporates the stochastic nature of emission rates and costs. This method is further refined with innovative techniques such as magnet-based crossover and mode reassignment. The former is a genetic algorithm operation inspired by magnetic attraction, which allows for a more diverse and effective exploration of solutions by aligning similar ’genes’ from parent solutions. The latter is a strategy for reallocating resources during project execution to optimize efficiency and reduce emissions. The efficacy of the proposed method is validated through testing on 2810 scenarios from established benchmark libraries, 100 additional scenarios adhering to the conventional multi-site problems, and a case study. The Best-Worst Method (BWM) is applied for identifying the best solution. The findings indicate substantial enhancements compared to traditional methods with a 12.7% decrease in project duration, 11.4% in costs, and a remarkable 13.6% reduction in greenhouse gas emissions.

Quantum sensing with optically accessible spin defects in van der Waals layered materials

Quantum sensing has emerged as a powerful technique to detect and measure physical and chemical parameters with exceptional precision. One of the methods is to use optically active spin defects within solid-state materials. These defects act as sensors and have made significant progress in recent years, particularly in the realm of two-dimensional (2D) spin defects. In this article, we focus on the latest trends in quantum sensing that use spin defects in van der Waals (vdW) materials. We discuss the benefits of combining optically addressable spin defects with 2D vdW materials while highlighting the challenges and opportunities to use these defects. To make quantum sensing practical and applicable, the article identifies some areas worth further exploration. These include identifying spin defects with properties suitable for quantum sensing, generating quantum defects on demand with control of their spatial localization, understanding the impact of layer thickness and interface on quantum sensing, and integrating spin defects with photonic structures for new functionalities and higher emission rates. The article explores the potential applications of quantum sensing in several fields, such as superconductivity, ferromagnetism, 2D nanoelectronics, and biology. For instance, combining nanoscale microfluidic technology with nanopore and quantum sensing may lead to a new platform for DNA sequencing. As materials technology continues to evolve, and with the advancement of defect engineering techniques, 2D spin defects are expected to play a vital role in quantum sensing.

COF-5/Pebax mixed-matrix membranes with enhanced CO2 removal ability for ECCO2R system

Extracorporeal CO2 removal (ECCO2R) is a type of extracorporeal life support (ECLS) technology. It aims to remove carbon dioxide (CO2) from small flow of the blood and correct hypercapnia and related acidosis. The ECCO2R system removes CO2 retained in the patient’s body through the gas-blood exchange membranes, which in use, blood flows on the outside of the membrane, and the inside of the membrane is for gas flow. Existing ECCO2R system generally improves the emission rate of CO2 by the increase of the gas flow rate. However, there is a problem that O2 is simultaneously taken out, which will reduce the blood O2 concentration. Therefore, the gas-blood exchange membranes should not only increase the CO2 removal rate by the improvement of CO2/O2 selectivity, but also retain more O2 in the blood and then maintain the oxygen saturation of the blood. In present work, a method was proposed to fabricate COF-5/Pebax mixed matrix membranes (MMMs) on the PMP surface for enhancing CO2/O2 selectivity, which was increased from 0.96 to 5.57. The CO2 removal ability of COF-5/Pebax MMM was tested by blood circulation, and it was found that the CO2 removal effect was increased 10.9% than that of the pristine membranes. The O2 concentration was maintained at a higher level, about 1.69 times that of the pristine membranes. In contrast to the pristine PMP membrane, blood compatibility of COF-5/Pebax MMMs was improved because protein adhesion decreased by 44.75%. The results of cytotoxicity test and rabbit pyrogen test exhibited that the prepared COF-5/Pebax MMM presented great biosafety. Overall, the proposed COF-5/Pebax MMM has good performance in ECCO2R system and attractive potential for medical application.

Navigating urban risks for sustainability: A comprehensive evaluation of urban vulnerability based on a pressure–sensitivity–resilience framework

Cities are important symbols of civilization in human society. The vulnerability to cities caused by human activities and natural disasters has become increasingly evident. How to reduce the vulnerability of cities is an important topic in the research of urban public safety and sustainable development. In this study, a comprehensive evaluation of urban vulnerability is conducted on the basis of the pressure–sensitivity–resilience framework from a complex systems perspective, integrating three subsystems—the resource–environment, economic, and social subsystems. On the basis of data from 18 cities in Sichuan Province, China, from 2006 to 2021, this study analyzes vulnerability in terms of its scores, spatial and temporal evolution, and obstacles. The results reveal that the overall vulnerability of the Sichuan Basin has shown a fluctuating downward trend over the past sixteen years, and the spatial distribution has evolved into a large “low-vulnerability” agglomeration. The obstacles affecting urban vulnerability are also changing dynamically and include factors such as the harmless treatment rate of household waste and industrial smoke dust emissions. Drawing from these insights, this study enables the identification and diagnosis of urban vulnerability and, further, provides city managers with tailored recommendations for crafting policies that aim to mitigate risks and promote sustainable development.

County-Level Spatiotemporal Dynamics and Driving Mechanisms of Carbon Emissions in the Pearl River Delta Urban Agglomeration, China

Encouraging cities to take the lead in achieving carbon peak and carbon neutrality holds significant global implications for addressing climate change. However, existing studies primarily focus on the urban scale, lacking more comprehensive county-level analyses, which hampers the effective implementation of differentiated carbon mitigation policies. Therefore, this study focused on the Pearl River Delta urban agglomeration in China, adopting nighttime light data and socio-economic spatial data to estimate carbon emissions at the county level. Furthermore, trend analysis, spatial autocorrelation analysis, and Geodetector were adopted to elucidate the spatiotemporal patterns and influencing factors of county-level carbon emissions. Carbon emissions were predominantly concentrated in the counties on the eastern bank of the Pearl River Estuary. Since 2010, there has been a deceleration in the growth rate of carbon emissions in the region around the Pearl River Estuary, with some counties exhibiting declining trends. Throughout the study period, construction land expansion consistently emerged as a predominant factor driving carbon emission growth. Additionally, foreign direct investment, urbanization, and fixed asset investment each significantly contributed to the increased carbon emissions during different development periods.

Optimal performance design of bat algorithm: An adaptive multi‐stage structure

AbstractThe bat algorithm (BA) is a metaheuristic algorithm for global optimisation that simulates the echolocation behaviour of bats with varying pulse rates of emission and loudness, which can be used to find the globally optimal solutions for various optimisation problems. Knowing the recent criticises of the originality of equations, the principle of BA is concise and easy to implement, and its mathematical structure can be seen as a hybrid particle swarm with simulated annealing. In this research, the authors focus on the performance optimisation of BA as a solver rather than discussing its originality issues. In terms of operation effect, BA has an acceptable convergence speed. However, due to the low proportion of time used to explore the search space, it is easy to converge prematurely and fall into the local optima. The authors propose an adaptive multi‐stage bat algorithm (AMSBA). By tuning the algorithm's focus at three different stages of the search process, AMSBA can achieve a better balance between exploration and exploitation and improve its exploration ability by enhancing its performance in escaping local optima as well as maintaining a certain convergence speed. Therefore, AMSBA can achieve solutions with better quality. A convergence analysis was conducted to demonstrate the global convergence of AMSBA. The authors also perform simulation experiments on 30 benchmark functions from IEEE CEC 2017 as the objective functions and compare AMSBA with some original and improved swarm‐based algorithms. The results verify the effectiveness and superiority of AMSBA. AMSBA is also compared with eight representative optimisation algorithms on 10 benchmark functions derived from IEEE CEC 2020, while this experiment is carried out on five different dimensions of the objective functions respectively. A balance and diversity analysis was performed on AMSBA to demonstrate its improvement over the original BA in terms of balance. AMSBA was also applied to the multi‐threshold image segmentation of Citrus Macular disease, which is a bacterial infection that causes lesions on citrus trees. The segmentation results were analysed by comparing each comparative algorithm's peak signal‐to‐noise ratio, structural similarity index and feature similarity index. The results show that the proposed BA‐based algorithm has apparent advantages, and it can effectively segment the disease spots from citrus leaves when the segmentation threshold is at a low level. Based on a comprehensive study, the authors think the proposed optimiser has mitigated the main drawbacks of the BA, and it can be utilised as an effective optimisation tool.