Search Results (134)

This study investigates the effects of key atmospheric features on mineral dust emissions and transport in the Sahara–Sahel region, focusing on the Bodélé Depression, during June 2006 and 2011. We use a combination of high-resolution atmospheric simulations (AROME model), satellite observations (MODIS), and reanalysis data (ERA5, ECMWF) to examine the roles of the low-level jet (LLJ), Saharan heat low (SHL), Intertropical Discontinuity (ITD), and African Easterly Jet (AEJ) in modulating dust activity. Our results reveal significant interannual variability in aerosol optical depth (AOD) between the two periods, with a marked decrease in June 2011 compared to June 2006. The LLJ emerges as a dominant factor in dust uplift over Bodélé, with its intensity strongly influenced by local topography, particularly the Tibesti Massif. The position and intensity of the SHL also play crucial roles, affecting the configuration of monsoon flow and Harmattan winds. Analysis of wind patterns shows a strong negative correlation between AOD and meridional wind in the Bodélé region, while zonal wind analysis emphasizes the importance of the AEJ and Tropical Easterly Jet (TEJ) in dust transport. Surprisingly, we observe no significant correlation between ITD position and AOD measurements, highlighting the complexity of dust emission processes. This study is the first to combine climatological context and case studies to demonstrate the effects of African monsoon variability on dust uplift at intra-seasonal timescales, associated with the modulation of ITD latitude position, SHL, LLJ, and AEJ. Our findings contribute to understanding the complex relationships between large-scale atmospheric features and dust dynamics in this key source region, with implications for improving dust forecasting and climate modeling efforts. Full article

The development of combustion experiments in a controlled environment is essential for comparing different fuels and quantifying the influence of different key parameters. It is fundamental to understand the transport phenomena at the particle level to obtain reliable results and information for further proper biomass combustion modeling of large-scale equipment. Hence, this paper presents a comprehensive analysis of the thermal decomposition and kinetic of eight samples of forest biomass fuels in terms of combustion behavior by using the thermogravimetric analysis (TGA) technique. The tests were carried out in an oxidizing atmosphere at a heating rate between 5 and 100 °C/min up to 900 °C. It was observed that, for all samples, fuel conversion follows a sequence of drying, devolatilization, and char combustion. Furthermore, differences in chemical and physical composition, as well as in structures and their thermal stability, justify the differences observed between the mass-loss curves of the different fuels. For this, the complexity of kinetic study is addressed in this paper by using different approaches: isoconversional and model-fitting methods. However, the use of isoconversional methods proved ineffective for determining reliable kinetic parameters, due to their sensitivity to particle conversion. A significant variation in activation energy was observed during the devolatilization stage, ranging from 47.92 to 101.30 kJ/mol. For the char oxidation stage, it ranged from 14.97 to 35.48 kJ/mol. These results highlight Eucalyptus as the most reactive species among those studied. Full article

A small-scale supersonic flight experiment vehicle is being developed at Muroran Institute of Technology as a flying testbed for verification of innovative technologies for high-speed atmospheric flights, which are essential to next-generation aerospace transportation systems. Its baseline configuration M2011 with a cranked-arrow main wing with an inboard and outboard leading edge sweepback angle of 66 and 61 degrees and horizontal and vertical tails has been proposed. Its aerodynamics caused by attitude motion are required to be clarified for six-degree-of-freedom flight capability prediction and autonomous guidance and control. This study concentrates on characterization of such aerodynamics caused by rolling rates in the subsonic regime. A mechanism for rolling a wind-tunnel test model at various rolling rates and arbitrary pitch angle is designed and fabricated using a programmable stepping motor and an equatorial mount. A series of subsonic wind-tunnel tests and preliminary CFD analysis are carried out. The resultant static derivatives have sufficiently small scatter and agree quite well with the static wind-tunnel tests in the case of a small pitch angle, whereas the static directional stability deteriorates in the case of large pitch angles and large nose lengths. In addition, the resultant dynamic derivatives agree well with the CFD analysis and the conventional theory in the case of zero pitch angle, whereas the roll damping deteriorates in the case of large pitch angles and proverse yaw takes place in the case of a large nose length. Full article

Using multi-source precipitation datasets including NASA GPM (IMERG), GPCP, ECMWF ERA5, and station precipitation data from the China Meteorological Administration (CMA), along with ERA5 reanalysis fields for atmospheric circulation analysis, this study investigates the extreme precipitation events during the “Dragon-Boat Precipitation” period from 20 May to 21 June over South China in 2022 using the synoptic diagnostic method. The results indicate that the total precipitation during this period significantly exceeded the climatological average, with multiple large-scale extreme rainfall events characterized by high intensity, extensive coverage, and prolonged duration. The spatial distribution of precipitation exhibited a north-more-south-less pattern, with the maximum rainfall center located in the Nanling Mountains, particularly in the Shaoguan–Qingyuan–Heyuan region of Guangdong Province, where peak precipitation exceeded 1100 mm, and the mean precipitation was approximately 1.7 times the climatology from the GPM data. The average daily precipitation throughout the period was 17.5 mm/day, which was 6 mm/day higher than the climatological mean, while the heaviest rainfall on 13 June reached 39 mm/day above the average, exceeding two standard deviations. The extreme precipitation during the “Dragon-Boat Precipitation” period in 2022 was associated with an anomalous deep East Asian trough, an intensified South Asian High, a stronger-than-usual Western Pacific Subtropical High, an enhanced South Asian monsoon and South China Sea monsoon, and the dominance of a strong Southwesterly Low-Level Jet (SLLJ) over South China. Two major moisture transport pathways were established: one from the Bay of Bengal to South China and another from the South China Sea, with the latter contributing a little higher amount of water vapor transport than the former. The widespread extreme precipitation on 13 June 2022 was triggered by the anomalous atmospheric circulation conditions. In the upper levels, South China was located at the northwestern periphery of the slightly stronger-than-normal Western Pacific Subtropical High, intersecting with the base of a deep trough associated with an anomalous intense Northeast China Cold Vortex (NCCV). At lower levels, the region was positioned along a shear line formed by anomalous southwesterly and northerly winds, where exceptionally strong southwesterly moisture transport, significant moisture convergence, and intense vertical updraft led to the widespread extreme rainfall event on that day. Full article

Emerging evidence indicates that large-scale forest restoration exhibits dual hydrological effects: direct reduction of local water availability through elevated evapotranspiration (ET) and indirect augmentation of water resources via enhanced atmospheric moisture recycling. However, the quantitative assessment of these counteracting effects remains challenging due to the limited observational constraints on moisture transport. Here, we integrate the Budyko model with the Lagrangian-based UTrack moisture-tracking dataset to disentangle the direct (via ET) and indirect (via precipitation) large-scale hydrological impacts of China’s four-decade forest restoration campaign across eight major river basins. Multisource validation datasets, including gauged runoff records, hydrological reanalysis products, and satellite-derived forest cover maps, were systematically incorporated to verify the Budyko model at the nested spatial scales. Our scenario analyses reveal that during 1980–2015, extensive afforestation individually reduced China’s terrestrial water yield by −28 ± 25 mm yr⁻¹ through dominant ET increases. Crucially, atmospheric moisture recycling mechanisms attenuated this water loss by 12 ± 5 mm yr⁻¹ nationally, with marked spatial heterogeneity across the basins. In some moisture-limited watersheds in the Yellow River Basin, the negative ET effect was compensated for to a certain extent by precipitation recycling, demonstrating net positive hydrological outcomes. We conclude that China’s forest expansion imposes local water stress (direct effect) by elevating ET, while the concomitant strengthening of continental-scale moisture recycling generates compensatory water gains (indirect effect). These findings advance the mechanistic understanding of the vegetation-climate-water nexus, providing quantitative references for optimizing forestation strategies under atmospheric water connectivity constraints. Full article

Compound dry–hot events refer to climate phenomena where drought and high temperatures occur simultaneously. Compared to single extreme events, compound dry–hot events may have greater adverse impacts. This study uses high-spatial-resolution observational data (i.e., temperature, precipitation, and climate water balance) to cluster and identify spring compound dry–hot events in the Pearl River Basin over the past nearly 50 years. It further investigates the associated large-scale atmospheric circulation conditions during compound dry–hot events. Using three clustering methods and twenty-six evaluation criteria, six events are identified. These events primarily exhibit negative anomalies in precipitation and climate water balance and positive anomalies in temperature. The spatial distribution results show that moisture deficits during compound events are mainly concentrated in the eastern Pearl River Basin, especially in the Pearl River Delta region. An atmospheric circulation analysis indicates that spring compound dry–hot events in the Pearl River Basin are commonly accompanied by persistent abnormal high-pressure systems, relatively weak westerly transport from subtropical regions such as the Indian Ocean and the Bay of Bengal (20–25 °N), and limited moisture input from the western Pacific region. The results of this study can help to better understand and analyze the risk changes of extreme events in the context of global warming. Full article

Palm kernel shells, an abundant agro-industrial residue in countries like Ecuador, can be valorized through their conversion into activated carbon for industrial applications. This study investigates the physical activation of carbonized palm kernel shells using both a Nichols furnace at the pilot scale and a rotary kiln at the industrial scale. The progressive conversion model was used to explain how the activation process works and to calculate the reaction rate constants for CO₂ (kr_CO2) and H₂O (kr_H2O). The experimental results demonstrated that activation in an H₂O-rich atmosphere significantly enhanced porosity development and iodine index compared to CO₂ alone. Additionally, the study confirmed that activation kinetics are primarily controlled by the chemical reaction rather than mass transport limitations, as indicated by the negligible effect of particle size on gasification rates. At 850 °C, the reaction rate constants were calculated to be kr_CO2 = 0.75 (mol·cm⁻³·s)⁻¹ and kr_H2O = 8.91 (mol·cm⁻³·s)⁻¹. The model’s predictions closely matched the experimental data, validating its applicability for process optimization at both the pilot and industrial scales. These findings provide valuable insights for improving the efficiency of activated carbon production from palm kernel shells in large-scale operations. Full article

Mercury, a global pollutant with high biotoxicity, is widely distributed in soils, water bodies, and the atmosphere. Anthropogenic activities such as industrial emissions and coal combustion release large quantities of mercury into the environment, posing health risks to human populations. Strict implementation of the Minamata Convention and innovative remediation technologies can mitigate escalating environmental and public health risks. This study investigated the spatiotemporal dynamics of mercury in soils and atmosphere across four spatial scales (central city, county, township, and village) within the Changchun urban agglomeration, China. During spring, summer, and autumn of 2023, surface soil and atmospheric mercury concentrations (at 0 cm and 100 cm) were measured using LUMEX RA-915+ at 361 sites. Soil mercury exhibited seasonal variability, with a mean concentration of 46.2 µg/kg, showing peak values in spring and troughs in summer; concentrations decreased by 29.40% from spring to summer, followed by a 27.85% rebound in autumn. Spatially, soil mercury concentrations exhibited a core–periphery decreasing gradient (central city > county > township > village). Average concentrations at county, township, and village levels were 9.92%, 35.07%, and 42.11% lower, respectively, than those in the central city. Atmospheric mercury displayed seasonal variations; mean concentrations at 0 cm and 100 cm heights were 6.13 ng/m³ and 6.75 ng/m³, respectively, both peaking in summer. At 0 cm, summer concentrations increased by 35.61% compared to spring, then declined by 35.96% in autumn; at 100 cm, summer concentrations rose by 49.39% from spring and decreased by 31.08% in autumn. Atmospheric mercury at both heights decreased from the central city to the peripheries, with reductions of approximately 40% at 0 cm and 37–39% at 100 cm. Atmospheric mercury dynamics were significantly correlated with meteorological parameters such as temperature and humidity. Spatial autocorrelation analysis revealed scale-dependent clustering patterns: soil mercury Moran’s I ranked central city > county > village > township, while atmospheric mercury followed township > village > county > central city. Structural equation modeling demonstrated that different spatial scales had a significant negative effect on soil mercury concentrations, atmospheric mercury concentrations at 0 cm and 100 cm, and mercury and its compounds emissions. Organic matter content had a significant positive effect on soil mercury content. Temperature and humidity positively influenced near-surface atmospheric mercury. This multi-scale approach elucidates urban agglomeration mercury dynamics, highlighting core–periphery pollution gradients and seasonal patterns, thereby providing empirical evidence for regional mercury transport studies and providing a scientific foundation for future heavy metal management strategies. Full article

In the Himalayan regions of complex terrains, such as Himachal Pradesh, the occurrence of extreme rainfall events (EREs) has been increasing, triggering landslides and flash floods. Investigating the dynamics and precipitation characteristics and improving the prediction of such events are crucial and could play a vital role in contributing to sustainable development in the region. This study employs a high-resolution numerical weather prediction framework, the weather research and forecasting (WRF) model, to deeply investigate an ERE which occurred between 8 July and 13 July 2023. This ERE caused catastrophic floods in the Mandi and Kullu districts of Himachal Pradesh. The WRF model was configured with nested domains of 12 km and 4 km horizontal grid resolutions, and the results were compared with global high-resolution precipitation products and the fifth-generation European Centre for Medium-Range Weather Forecasts atmospheric reanalysis dataset. The selected case study was amplified by the synoptic scale features associated with the position and intensity of the monsoon trough, including mesoscale processes like orographic lifting. The presence of a western disturbance and the heavy moisture transported from the Arabian Sea and the Bay of Bengal both intensified this event. The model has effectively captured the spatial distribution and large-scale dynamics of the phenomenon, demonstrating the importance of high-resolution numerical modeling in accurately simulating localized EREs. Statistical evaluation revealed that the WRF model overestimated extreme rainfall intensity, with the root mean square error reaching 17.33 mm, particularly during the convective peak phase. The findings shed light on the value of high-resolution modeling in capturing localized EREs and offer suggestions for enhancing disaster management and flood forecasting. Full article

The Antarctic sea ice concentration (SIC) plays a crucial role in global climate dynamics by influencing atmospheric and oceanic circulation. This study examines SIC variability and its relationship with major climate modes, including the El Niño-Southern Oscillation (ENSO), Pacific-South American (PSA) pattern, Southern Annular Mode (SAM), and Antarctic Dipole (ADP). Using NSIDC satellite-derived sea ice data and ERA5 reanalysis from 1980 to 2022, we analyzed SIC anomalies in the Weddell, Ross, and Bellingshausen and Amundsen (B&A) Seas, assessing their response to climatic forcings across different timescales. Our findings reveal strong linkages between SIC variability and large-scale atmospheric circulation. ENSO-related teleconnections drive a dipolar SIC response, with warming in the Pacific sector and cooling in the Atlantic during El Niño, and the opposite pattern during La Niña. PSA and ADP further modulate this response by altering Rossby wave propagation and heat fluxes, leading to significant SIC fluctuations. The ADP emerges as a dominant driver of interannual SIC anomalies, showing an out-of-phase relationship between the Atlantic and Pacific sectors of the Southern Ocean. Regional SIC trends exhibit contrasting patterns: the Ross Sea shows a significant positive SIC trend, while the B&A and Weddell Seas experience persistent negative anomalies due to enhanced meridional heat transport and stronger westerly winds. SAM strongly influences SIC, particularly in the Atlantic sector, with delayed responses of up to six months, likely due to ice-albedo feedbacks and ocean memory effects. These results enhance our understanding of Antarctic sea ice variability and its sensitivity to large-scale climate oscillations. Given the observed trends and ongoing climate change, further research is needed to assess how these processes will evolve under future warming scenarios. This study highlights the importance of continuous satellite observations and high-resolution climate modeling for improving projections of Antarctic sea ice behavior and its implications for the global climate system. Full article

Houston, Texas, with its large-scale industrial activities, serves as a national hub for petrochemical processing and chemical feedstock production, making it a unique emission region for volatile organic compounds (VOCs) and production-related emissions. These emissions can be associated with industrial activities, including solvent usage and production to manufacture consumer products such as volatile chemical products. To support the Houston-based Dept. of Energy’s Atmospheric Measurement Radiation program-led Tracking Aerosol Convection ExpeRiment (TRACER) projects, VOCs were measured at the San Jacinto Battleground State Historic Site during September 2021 and 2022. The observed VOC mixing ratios reveal unique emission signatures for select VOCs, including benzene, toluene, acetone, and isoprene. Routine nighttime enhancements of these compounds exceeded the urban background, with mixing ratios increasing by up to 20 ppbv per hour and persisting for up to 6 h, suggesting that emissions from local industrial activities near the Houston Ship Channel (HSC) are impacting the site. For example, mixing ratios exceeding 15 ppbv for at least one VOC were observed on 58% of nights (n = 32 nights), with 19 nights (~35%) having two or more VOCs with mixing ratios above 15 ppbv. For select peak emission events, the NOAA dispersion model estimated plume transport across parts of the urban system, suggesting that VOCs from the HSC may impact local air quality. This study highlights the importance of VOC-related emissions from industrial production and supply chains in contributing to total VOC emissions in urban areas like Houston, Texas. Full article

The frequent launches of reusable launch vehicles are currently the primary approach to support large-scale space transportation, necessitating high reliability in recovery flights. This paper proposes a mission re-planning scheme to address throttling faults, which significantly affect the feasibility of powered landing. To quantify the influence of throttling capability, the concept of “controllable set (CS)” is introduced. The CS is defined as the collection of all feasible initial states that can achieve a successful powered landing and is computed using polyhedron approximation and convex optimization. Based on the CS, the physical feasibility of a power landing problem under deviations from the nominal conditions can be evaluated probabilistically. Besides, a deep neural network (DNN) is constructed to enhance the computational efficiency of the CS analysis, thereby meeting the requirements for online applications. Finally, an effective re-planning scheme is proposed to deal with throttling faults in recovery flight. This is achieved by adjusting the designed angle of attack during the endo-atmosphere unpowered descent phase and selecting the associated optimal handover conditions to initiate the powered landing. The optimal re-planning parameters are determined through a comprehensive investigation of the design space, leveraging probability-based CS analysis and computationally efficient DNN predictions. Simulations verify the accuracy of the CS computation algorithm and the effectiveness of the re-planning scheme under different fault conditions. The results indicate high feasibility probabilities of 99.97%, 98.12%, and 78.52% for maximum throttling capabilities at 65%, 75%, and 85% of nominal thrust magnitude, respectively. Full article

Greenhouse gases such as methane will be generated from the landfilling of municipal waste. The emissions of noxious gas from landfills and other waste disposal areas can present a significant hazard to the environment and to the health of the population if not properly controlled. In order to have the harmful gas controlled and mitigate the environmental pollution, the extent to which the gas will be transported into the air at some time in the future must be estimated. The emission estimates (inventories) are combined with atmospheric observations and modeling techniques. In this work, large eddy simulation (LES) is used to determine the dispersion of methane in the atmosphere at large distances from the landfill. The methane is modeled as an active scalar, which diffuses from the landfill with a given mass flux. The Boussinesq approximation has been used to embed the effect of the buoyancy in the momentum equation. A logarithmic velocity profile has been used to model the wind velocity. The results in the far field show that the mean concentration and concentration rms of methane, appropriately scaled, are self-similar functions of a certain combination of the coordinates. Furthermore, the LES results are used to fit the parameters of the Gaussian plume model. This result can be used to optimize the placement of the atmospheric receptors and reduce their numbers in the far-field region, to improve emissions estimates and reduce the costs. Full article

To evaluate the potential of an upcoming large-swath satellite for estimating surface methane (CH₄) fluxes at a weekly scale, we report the results from a series of observing system simulation experiments (OSSEs) that use an established modeling framework that includes the GEOS-Chem 3D atmospheric transport model and an ensemble Kalman filter. These experiments focus on the sensitivity of CH₄ flux estimates to systematic errors ($\mu$) and random errors ($\sigma$) in the column average methane (XCH₄) measurements. Our control test (INV_CTL) demonstrates that with median errors ($\mu$ = 1.0 ± 0.9 ppb and $\sigma$ = 6.9 ± 1.6 ppb) in XCH₄ measurements over a 1000 km swath, global CH₄ fluxes can be estimated with an accuracy of 5.1 ± 1.7%, with regional accuracies ranging from 3.8% to 21.6% across TransCom sub-continental regions. The northern hemisphere mid-latitudes show greater reliability and consistency across varying $\mu$ and $\sigma$ levels, while tropical and boreal regions exhibit higher sensitivity due to limited high-quality observations. In $\sigma$-sensitive regions, such as the North American boreal zone, expanding the swath width from 1000 km to 3000 km significantly reduces discrepancies, while such adjustments provide limited improvements for $\mu$-sensitive regions like North Africa. For TanSat-2 mission, with its elliptical medium Earth orbit and 1500 km swath width, the global total estimates achieved an accuracy of 3.1 ± 2.2%. Enhancing the swath width or implementing a dual-satellite configuration is proposed to further improve TanSat-2 inversion performance. Full article

The North China Plain is a crucial agricultural region in China, but irregular precipitation patterns have led to significant water shortages. To address this, analyzing the high-resolution dynamics of root-zone soil moisture transport is essential for optimizing irrigation strategies and improving water resource efficiency. The Richards equation is a robust model for describing soil moisture transport dynamics across multiple soil layers, yet its application at large spatial scales is hindered by its sensitivity to boundary conditions and model parameters. This study introduces a novel approach that, for the first time, employs a continuous time series of near-surface soil moisture as the upper boundary condition in the Richards equation to estimate high-resolution root-zone soil moisture in the North China Plain, thus enabling its large-scale application. Singular spectrum analysis (SSA) was first applied to reconstruct site-specific time series, filling in missing and singular values. Leveraging observational data from 617 monitoring sites across the North China Plain and multiple spatial covariates, we developed a machine learning model to estimate near-surface soil moisture at a 1 km resolution. This high-resolution, continuous near-surface soil moisture series then served as the upper boundary condition for the Richards equation, facilitating the estimation of root-zone soil moisture across the region. The results indicated that the machine learning model achieved a correlation coefficient (R) of 0.92 for estimating spatial near-surface soil moisture. Analysis of spatial covariates showed that atmospheric forcing factors, particularly temperature and evaporation, had the most substantial impact on model performance, followed by static factors such as latitude, longitude, and soil texture. With a continuous time series of near-surface soil moisture, the Richards equation method accurately predicted multi-layer soil moisture and demonstrated its applicability for large-scale spatial use. The model yielded R values of 0.97, 0.78, 0.618, and 0.43, with RMSEs of 0.024, 0.06, 0.08, and 0.11, respectively, for soil layers at depths of 10 cm, 20 cm, 40 cm, and 100 cm across the North China Plain. Full article