One-year Simulation Research Articles

Optimizing Treatment of Schizophrenia: Clinical and Economical Potential for Patient Switching to Long‑Acting Injectables

INTRODUCTION: Long-acting injectable antipsychotics (LAIs), due to a lower frequency of administration, could address the well-established challenge of non-adherence to oral ones. We conducted a Network Meta-Analysis (NMA) to assess the relationship between administration frequency and effectiveness. The recent introduction of a semi-annual paliperidone palmitate formulation, along with the arrival of monthly paliperidone generics, could emphasize LAI’s advantages. Aim of this paper is to present the results derived from an updated version of our previous NMA. These results are used to fuel a budget impact model built to evaluate the economic implications of optimizing dosing intervals.METHODS: We compare the current distribution of patients among available LAI active substances and dosing frequencies with an optimized scenario. In this scenario, 20% of patients are switched to the next permitted regimen with a longer inter-dosing interval. Drug acquisition costs and relapse management costs are taken into account over a one-year simulation period; these last items are estimated by means of the event rates obtained from the updated meta-analysis. The optimized scenario incorporates the reduced cost resulting from the expiration of patents.RESULTS: Throughout the analysis, a total of 11,600 patients were able to switch from shorter to longer dosing intervals, leading to an overall optimization of quality of care. The greater expenditure incurred by the Italian National Health Service (NHS) in the acquisition of newer and longer-lasting drugs is offset by savings associated with the arrival of generics of monthly paliperidone palmitate and the shift toward less-relapsing regimens. The net impact on the NHS budget is a saving of more than 19 million Euros.CONCLUSION: This economic saving has the potential to initiate a virtuous process: it could be reinvested to fund a further shift from oral daily therapies, which are less expensive but marked by poor compliance, to LAIs. According to our simulation, nearly 40 thousand patients could undergo this transition, without additional expenses for the NHS.

Modelling of Sediment Transport and Deposition in Generating River-Mouth Closure: Oum-Errabia River, Morocco

River mouths are dynamic systems that can respond rapidly to both fluxes in fluvial water and sediment discharge and marine energy conditions, notably waves. On semi-arid wave-exposed coasts, the morphosedimentary behaviour of river mouths is particularly sensitive to variations in water discharge, which can be significantly influenced by climate variations, in addition to anthropogenic actions such as the construction of dams for water resource needs. In this climatic setting, an increasingly common consequence of decreasing river water discharge is the more or less prolonged closure of river mouths. Most studies have addressed river-mouth closure using analytical, parametric, numerical, or statistical models. The present study uses output from four numerical models to elucidate the hydrodynamic and sedimentary behaviour of the mouth of the Oum-Errabia River (catchment size: 35,000 km2), which debouches on the Atlantic coast of Morocco. The historical evolution of the river mouth and the impact of human interventions, such as the construction of dams, are discussed. The study also briefly discusses the impact of the recent closure of the river outlet, in response to particularly low water discharge, on the marine ecosystem and water quality. The modelling results covering a one-year simulation in this situation of closure indicate a deposition of 427,400 m3 of sediment in front of the mouth of the Oum-Errabia. Ensuring permanent river-mouth opening and tidal flushing and renewal of this river’s estuarine waters will necessitate costly regular dredging.

Is a fan coil unit (FCU) an efficient cooling system for net-zero energy buildings (NZEBs) in tropical regions? An experimental study on thermal comfort and energy performance of an FCU

In tropical regions, the selection of an efficient cooling system is a prerequisite for energy-efficient and net-zero energy buildings (NZEBs), while fan coil unit (FCU) systems are commonly used to provide thermal comfort (TC) of the interior environment throughout the entire year. In this study, to find a cooling solution for Malaysia's first net-zero building, the performance of a case study FCU-classroom was evaluated based on a one-month experimental assessment and a one-year simulation function. The precision of the measurements was computed using uncertainty analysis, and the simulation model was validated using measurement data. The impact of mechanical dehumidification on FCU performance was evaluated by analyzing the collected data in terms of cooling load allocation, cooling coil capacity, TC, and energy consumption. In order to guide the selection of a cooling system, a comparative analysis has been conducted between the performance of the FCU and two alternative systems, namely the redesigned FCU and the desiccant cooling system. This analysis was focused on evaluating the TC and energy use of these systems. The findings from the FCU performance analysis indicated that, in order to handle the cooling load in a classroom with an equal distribution of latent and sensible load (50:50 ratio), the FCU utilized 56 % of its total cooling coil capacity (13.06 kW) and 37 % of its energy consumption for the dehumidification process. The FCU utilized an average of 1360.3 kWh per month to maintain a comfortable room temperature of 24.3 °C and an uncomfortable relative humidity (RH) of 77.2 %. However, it was observed that the amount of moisture removal was insufficient to achieve a humidity comfort level in the room. Comparing alternative solutions to the FCU revealed that while a redesigned could provide TC, it consumed approximately 1.6 times more energy per month than the FCU. The desiccant cooling system provided TC with an average monthly energy savings of 37.8 % compared to the case study FCU.

Predicting human-wildlife interaction in urban environments through agent-based models

Synurbic species adapt to global urbanization by increasingly inhabiting urban environments, where social and ecological factors, such as anthropogenic food resources and habitat alterations, promote close human-wildlife interactions. Ineffective management of these interactions can result in conflicts, altered animal population dynamics, and increased public and private expenditures. This study presents the Barcelona wild boar (BCNWB)-prototype model, a spatially explicit, incremental agent-based simulation that captures interactions between citizens and wild boar (Sus scrofa) agents in fine-scale GIS-based scenarios in Barcelona. Developed using GAMA software, the model's results were analyzed with QGIS and R software. The model aims to simulate the dynamics of the social-ecological system underlying the urban ecosystem use by synurbic wild boars and their interactions with humans in the (peri)urban area of Barcelona, Spain.The BCNWB-prototype model demonstrated high accuracy in predicting the magnitude and location of wild boar movements (multiple-resolution-goodness-of-fit = 0.73) compared to reported wild boar presences in Barcelona. The model also forecasted 115 attack events and 1,442 direct feeding events during a one-year simulation period, as compared to the actual 150 attacks and 1,858 feeding events reported annually. The model’s strong performance highlights its potential as a predictive tool for identifying priority areas for human-wild boar interactions and conflicts. Additionally, the model could be employed to assess the cost-effectiveness of management strategies and evaluate the spread, transmission risks, and public health implications of pathogens carried by wild boars.

Inter-firm exchanges, distributed renewable energy generation, and battery energy storage system integration via microgrids for energy symbiosis

Policymakers and entrepreneurs are aware that reducing energy waste and underutilization are mandatory to actually foster the green transition. Nevertheless, small–medium enterprises usually meet technical and overwhelming financial constraints. They are unable to make profits, become less energy-sensitive, and cut down on their emissions simultaneously. Industrial districts are a source of both wealth and GHG (greenhouse gas) emissions. Eco-industrial parks (EIPs) supply a suitable strategy to ease symbiotic exchanges among various organizations. Surplus electricity from larger, energy-autonomous companies will be a new input for more vulnerable ones. This type of district is challenging, and it can provide an unexplored opportunity to cooperate, invest in renewable energy sources, and form alliances. To better exploit underutilized energy in industrial districts, it is essential to explore energy symbiosis (ES), i.e., an energy-based perspective of industrial symbiosis. This study presents an original mixed-integer linear programming (MILP) optimization model that aims to identify possible inter-firm exchanges and introduce microgrid-based support for distributed renewable-energy generators (DREGs) and battery energy storage systems (BESS) over a one-year simulation period. The model simultaneously targets economic and ecological objectives. The paper compares two case studies, one with battery support and one without. The optimization model was tested using a case study and found to improve energy efficiency (with a 43.46% saving in energy costs) and reduce greenhouse gas emissions (with an 84.59% reduction in GHG) by facilitating symbiotic exchanges among SMEs in industrial districts. The inclusion of BESS support further enhanced the model's ability to utilize green and recovered energy. These findings have implications for policymakers, entrepreneurs, and SMEs seeking to transition to more sustainable energy practices. Future work could explore the applicability of the MILP optimization model in other contexts and the potential for scaling up the model to larger industrial districts.

An adaptive charge control strategy for participation of neighbourhood battery energy storage systems in frequency stability

Neighbourhood Battery Energy Storage System (N-BESS) is a new scale of energy storage that is expected to have a potential role in modern power systems stability. In the literature, there is a lack of studies that proposed a smart engagement of N-BESS in the frequency stability. In this paper, an adaptive charge control strategy for the N-BESS has been proposed to enhance the frequency stability while maintaining a fair State-of-Charge (SOC) levels for N-BESS. Also, a collaborative framework for large-scale Battery Energy Storage System (L-BESS) with N-BESS has been introduced, in which the N-BESS play an auxiliary role in frequency stability. In this study, a number of system uncertainties, including N-BESS SOC, load consumption, wind farm generation, and contingency size and location, have been considered. The simulation has been carried out in the Simplified 14-Generator Model of the South East Australian Power System over one-year simulation using DIgSILENT/PowerFactory software and Python interface. The results have demonstrated that a higher SOC levels of N-BESS under the proposed strategy have been maintained compared to that of the conventional strategy. Moreover, when the L-BESS collaborated with the N-BESS under the proposed framework, the best frequency stability with highest SOC levels of N-BESS have been obtained; at the same time less discharged power by the L-BESS was noted compared to that when the L-BESS participated individually which indicated that a smaller L-BESS size would be required if it collaborated with N-BESS in frequency stability service.

Energy analysis of novel hybrid solar and natural gas combined cycle plants

The integration of renewable energy sources into standard energy systems is a fundamental step in the energy transition. The purpose of the paper is to investigate the integration of solar energy into a traditional natural gas-fired combined cycle power plant, while also evaluating the impact of intercooling, in terms of energy efficiency and CO2 emissions. Solar energy is integrated into the gas turbine topping cycle through parabolic trough collectors, with the aim of preheating the air leaving the compressor. Two additional configurations have been compared, based on one- and two-stage intercooled compression. The goal is to find the optimal hybrid configuration. To this purpose, a thermodynamic analysis of the overall plant has been performed, and a numerical model has been specifically developed to simulate the solar field. The model has been integrated into Thermoflex™ to simulate the overall combined cycle. Solar-to-electric conversion efficiency, based on solar energy input alone, has received specific attention to make relevant comparisons with conventional concentrated solar based power plants. Furthermore, net electric efficiency, electrical power share due to solar energy integration, natural gas savings, and CO2 emissions have been investigated. The solar-to-electric conversion efficiency has been shown to increase with the compression ratio while the net electric efficiency decreases. To achieve a trade-off between the need for high net electric efficiency and high solar integration, an optimization based on the Pareto front was carried out. The selected configuration consists of one intercooling stage and a compression ratio of 17.9, resulting in a solar conversion efficiency of 33%, which is much better than traditional solar-only power plants. Additionally, the net electric efficiency is 69.5%. To test this configuration under actual operating conditions, a one-year simulation was carried out in two cities with different climates: Messina and Torino. An average annual solar-to-electric efficiency of around 32% can be achieved in both cities, with natural gas savings of 7.7% and 5.8% per year for Messina and Torino, respectively.

Exploring the benefits of molten salt reactors: An analysis of flexibility and safety features using dynamic simulation

There has been a growing interest in Molten Salt Reactors (MSRs) in recent years due to the significant potential for increasing flexibility, security, and reliability of the grid, as well as the inherent passive safety features when compared to traditional pressurized water reactors (PWRs). MSRs can help meet many future nuclear energy goals, such as improved sustainability, high security, high efficiency, and high safety passive features, and help reduce nuclear waste. In this study, to investigate MSRs’ passive safety features, a dynamic model of 9 graphite nodes and 18 fuel salt nodes are simulated in 7 safety scenarios. These simulation results are compared with a traditional PWR dynamic simulation. The simulation shows the stability of MSR operations during these 7 safety scenarios, showing that the coolant and graphite temperature within the system stay within the safety limits of operation. The negative feedback coefficient of the fuel salt within MSR cores plays a significant role in stabilizing the power response inside the core, keeping the power from significant excursions. A one-year simulation is also conducted to test the load-following capabilities of MSRs in comparison with traditional PWRs. It is found that MSRs increase the flexibility, reliability, and security of the grid by operating in load-following mode without the need to change the position of the control rods. MSR's increased efficiency also leads to a reduction in backup fossil-fuel based electricity generation by 82% when compared to traditional PWRs operating in load-following mode.

Analysis of hydrodynamics and thermal dispersion by numerical modelling in Sele Strait, West Papua

Indonesian standard for wastewater quality regulates 40°C for the maximum outfall temperature. Meanwhile, the seawater temperature below 30°C is utilized for the cooling facility which the intake area is close to the outfall source. This research examine the hydrodynamics and thermal dispersion condition in PT Kilang Pertamina Internasional Kasim process plant in Sele Strait, West Papua. This study uses a two-dimensional numerical model Mike21 for a one-year simulation. Considering the limited field data, the ERA5 reanalysis satellite was utilized for the model input boundary. It also finds the discharge from the river with a temperature assumption of 26.5°C also in the boundary. The model validated with tidal field data with an R-squared number is 0.86. The hydrodynamics model shows the current speed in the intake area varied between 0-0.5 m/s. Two-scenario thermal simulation model (outfall condition 37°C & 40°C) shows that the frequency of 27°C water temperature is 81.5% and 85.8% respectively. Both scenarios give less than 10% for the temperature above 30°C. It concludes that the intake and outfall design planned is proper in the Kasim process plant.

Evaluation of advanced control strategies for building energy systems

Advanced building control strategies like model predictive control and reinforcement learning can consider forecasts for weather, occupancy, and energy prices. Combined with system and domain knowledge, this makes them a promising approach to reduce buildings’ energy consumption and CO2 emissions. For this reason, model predictive control and reinforcement learning have recently gained more popularity in the scientific literature. Nevertheless, publications often lack comparability among different control algorithms. The studies in the literature mainly focus on the comparison of an advanced algorithm with a conventional alternative. At the same time, use cases and key performance indicators vary strongly. This paper extensively evaluates six advanced control algorithms based on quantitative and qualitative key performance indicators. The considered control algorithms are a state-of-the-art model-free reinforcement learning algorithm (Soft-Actor-Critic), three model predictive controllers based on white-box, gray-box, and black-box modeling, approximate model predictive control, and a well-designed rule-based controller for fair benchmarking. The controllers are applied to an exemplary multi–input–multi–output building energy system and evaluated using a one-year simulation to cover seasonal effects. The considered building energy system is an office room supplied with heat and cold by an air handling unit and a concrete core activation.We consider the violation of air temperature constraints as thermal discomfort, the yearly energy consumption, and the computational effort as quantitative key performance indicators. Compared to the well-tuned rule-based controller, all advanced controllers decrease thermal discomfort. The black-box model predictive controller achieves the highest energy savings with 8.4%, followed by the white-box model predictive controller with 7.4% and the gray-box controller with 7.2%. The reinforcement learning algorithm reduces energy consumption by 7.1% and the approximate model predictive controller by 4.8%. Next to these quantitative key performance indicators, we introduce qualitative criteria like adaptability, interpretability, and required know-how. Furthermore, we discuss the shortcomings and potential improvements of each controller.

Hydromorphological management of a lengthy coastal strip in the presence of natural coral reefs flocs in the red sea

Further than the influential role that coral reefs perform in promoting the sustainable development of several diverse aquatic organism species, they may also play a crucially significant environmental role in controlling the hydrodynamic forces and managing the action of sediment movement along wide coastal stretches. This study presents an applied example of a comprehensive hydromorphological investigation focused on the management of sediment transport in the presence of natural coral reefs based on the creation of a numerical model using the Delft3D. A series of model calibrations and verifications demonstrated that the model is capable of replicating the hydrodynamic and sediment transport processes, it is precisely applied to the study of the morphological alteration of the Western Coast of Saudi Arabia, AlWajh & Umluj, Red Sea. Within the model, the natural coral reef flocs were characterized as porous and rough cohesive soil to obtain the maximum possible simulation accuracy and minimize uncertainty. According to the findings, the impacts of remote wind and waves in the midst of coral reefs should be taken into consideration to acquire correct results for monitoring erosion and accretion regions. The results also highlighted how the natural coral reefs effectively inhibit hydrodynamic forces such as waves and ocean currents, which in turn lowered sediment transport activity and led to slight variations in sedimentary stock throughout the one-year simulation.

The Importance of Cumulus Parameterization and Resolution in Simulating Rainfall over Peninsular Malaysia

In this study, five simulations were conducted using the weather research and forecasting (WRF) model with different cumulus parameterizations schemes (CPSs) for the period from 2013 until 2018. A one-year simulation of 2013 with three different horizontal resolutions of 25, 5, and 1.6 km was also performed. The CPSs used were Kain–Fritsch (KF), Grell–Devenyi (GR), Betts–Miller–Janjic (BM), and a non-parameterized scheme (NC). In assessments of model resolutions, both the 25 and 5 km resolutions depicted a strong negative bias in the northeastern part of Peninsular Malaysia during December–January–February (DJF), with marginal differences between the two simulations. Among all 5 km experiments, the best performing scheme was the BM scheme for almost all seasons. Furthermore, the 5 km simulation did not exhibit significant differences relative to the 25 km of the diurnal cycle. The 1.6 km simulation showed significant added value as it was the only simulation that was able to simulate the high precipitation intensity in the morning and a precipitation peak during the evening. The 1.6 km resolution was also the only resolution capable of picking up the precipitation signals in the R4 region (South Peninsular Malaysia) compared to the other two resolutions. While both CPSs and resolutions are important for accurate predictions, the role of CPSs became less significant in a higher resolution simulation.

Utilization of Animal Solid Waste for Electricity Generation in the Northwest of Iran 3E Analysis for One-Year Simulation

Today, the use of renewable energy is increasing day by day. The most susceptible to renewable energy is biomass energy because it depends directly on the size of the population and does not have the problems of other renewable energies such as lack of access day and night and constant change throughout the year. For this reason, animal solid waste has been used in the research to supply electrical energy to the study area. In this regard, the amount of animal waste is considered as a source of biomass input energy. HOMER software was used to simulate the system under study. To better compare the competitiveness of this energy, photovoltaic systems and wind turbines have been used as different scenarios of electrical energy production in the study area. The results of scenario analysis showed that in all designed systems, the highest amount of energy production was in July and was related to the hottest season of the year. Among hybrid systems, the biomass system has a higher priority than other systems due to the minimum cost of energy production and total net present cost (NPC). The amount of exhaust gas from the biomass system reached 53.5 kg/yr and the biomass-wind and biomass-wind-solar systems reached 52.5 kg/yr and 52.2 kg/yr, respectively. The surplus generated electricity also increases from 2.91% to 6.65% from the biomass-wind system to the biomass-with-solar system.

The SVOM/ECLAIRs image trigger with wavelet-based background correction optimised with a one-year simulation of observations

Context. The Space-based multi-band astronomical Variable Objects Monitor (SVOM) mission under development will carry four instruments, and in particular the coded-mask telescope named ECLAIRs, with a large field of view of about 2 sr, operating in the 4–150 keV energy band. The trigger software on board ECLAIRs will search for high-energy transients such as gamma-ray bursts and peculiar behaviour (e.g. strong outbursts) from known X-ray sources, in order to repoint the satellite to perform follow-up observations with the onboard narrow field of view instruments. Aims. The image trigger, one of the two algorithms implemented in the software on board ECLAIRs, produces images over periods of exposure ranging from 20 s to 20 min during which the Earth can cross the field of view. The Cosmic X-ray Background and contributions from known X-ray sources are expected to dominate the ECLAIRs astrophysical and instrumental background and must be taken into account and corrected prior to coded-mask image deconvolution in order to optimise the sensitivity to faint transients. Methods. To correct these background components, we implemented and studied a traditional fitting method and a new method based on wavelet decomposition of the detector image. In order to study and to assess the performance of these methods, we performed a 1-yr simulation of the image trigger on board ECLAIRs. From the images produced during this realistic observation scenario of the SVOM mission, we also defined a way to analyse the sky images to search for new sources. Results. We present the algorithms behind the image trigger on board SVOM/ECLAIRs. We show that the wavelet method we implemented provides similar results in terms of cleaning performance compared to the traditional fitting method, and has the benefit of not requiring any assumption on the shape of the background on the detector. We also calibrate the detection threshold to be adaptive and based on the quality of the reconstructed sky image.

Improvement of the vertical mixing in chemistry transport modeling based on a 1.5-order turbulence kinetic energy-based eddy diffusivity closure scheme

In this study, firstly, three first-order local closure vertical diffusion schemes used in multiple mesoscale chemical transport models (CTM) were embedded in the CHIMERE CTM model and tested over a one-year simulation covering the whole France. Three model configurations present a fair reproduction of pollutant concentrations both in urban and rural areas, indicating it is an effective way to reproduce the dispersion of pollutants in chemistry transport modeling. However, it cannot be expected to significantly improve the vertical mixing under the first-order closure scheme. Secondly, a 1.5-order turbulence kinetic energy-based eddy diffusivity closure scheme called as the new eddy diffusion (NED) is implemented in CHIMERE to describe more realistic diffusion processes near the surface. A fifteen-day simulation encompassing a winter pollution episode was performed for three major cities with horizontal resolution of 1.67 km and the first layer height at 12 m, respectively. The NED scheme improved NO2 simulations at most urban sites compared to the initial Kz diffusion scheme (IKD). Taking the root mean square error as evaluation criteria, the average improvements are 18.8%, 24.5% and 9.5% for NO2 simualtion in Paris, Lyon and Bordeaux respectively. For the model performance of PM2.5 and PM10 simulations in the urban areas of Paris, the improvements are 13.5% and 19.1%, respectively. Overall, preliminary outcomes of this study are encouraging. The simulation with more sophisticated and realistic eddy viscosities are better than for IKD that is widely used in CTMs, but we need to realize that this is only a fifteen-day simulation for three cities, for further research, longer periods are needed with a greater variety of meteorological situations to prove the universality of the NED scheme.

Thermal Model Validation Process for Building Environment Simulation: A Case Study for Single-Family House

Currently, more and more emphasis is being placed on reducing energy consumption in buildings to reduce greenhouse gases in the atmosphere. Building performance simulation is very useful to predict energy demand and indoor environment quality. An indispensable element of the simulation is the validation and calibration of the model, which is an arduous process. The aim of the study was to present a four-level validation (using measurement results) and calibration of a thermal model of a naturally ventilated single-family house. Numerical calculations using co-simulation between EnergyPlus and Contam were performed. The results of the one-year simulation measurements of the indoor temperature and ventilation airflows were compared. After the calibration was performed, a high convergence of the results was found. The normalized mean bias error for hourly and monthly values did not exceed 1% and the coefficient of variation of the root mean squared error was a maximum of 7% with a simultaneous high correlation of the results in the range from 0.85 to 0.89. It was found that the final results were significantly influenced by the appropriate modeling of air exchange in the building, including the opening of windows.

One-year Simulation of Air Pollution in Central China, Characteristics, Distribution, Inner Region Cross-transmission, and Pathway Research in 18 Cities

Air pollution in Henan province is serious and is significantly impacted by pollution transmission and interactions with surrounding areas. The emission sources in 18 cities in Henan province were labeled and applied to the WRF-CMAQ traceability model for simulation in January, April, July, and October of 2017. The pollutant distribution results showed that due to the combined influence of emissions and meteorology, the concentrations of PM2.5, NO2, and SO2 in Henan province were the highest in winter and the lowest in summer. The seasonal variation in O3-8h concentration was the highest in summer, followed by spring, and the lowest in winter. There was a large difference in pollutant concentrations between different seasons. The average concentrations of PM2.5, NO2, and SO2 in winter in Henan province were 4.17, 4.12, and 6.24 times those in summer, respectively, whereas the concentration of O3-8h in summer was 2.24 times that in winter. Since PM2.5, NO2, and SO2 are closely related to primary emissions and have a certain homology, the distributions of high values of these three pollutants were higher in the north and lower in the south, and the seasonal trends were more consistent. The seasonal distribution of O3-8h varied widely, with high O3-8h values mainly distributed in the northeastern region of Henan province in summer, when meteorological conditions contributed to O3 production; in winter, spring, and autumn, high O3-8h values were mainly distributed in the southern part of Henan province due to the suppression of meteorological conditions and NOx consumption. The results of the study on the transport of pollutants showed that extra-provincial transport and natural sources contributed the most to the concentrations of PM2.5, O3-8h, NO2, and SO2 in winter, with 36.20%-72.32%, 77.96%-96.08%, 49.45%-78.80%, and 59.05%-88.85%, respectively. When considering only local emissions and intra-provincial transmission, the contributions of emissions to local concentrations of the four pollutants in summer were the highest in all cities of Henan province. The contributions of intra-provincial transmission to PM2.5 and O3-8h in spring were the largest, with 25.63%-74.69% and 30.21%-80.01%, respectively, and the contributions of intra-provincial transmission to NO2 and SO2 in winter were larger, with 26.02%-76.96% and 20.30%-82.34%. The transmission paths of PM2.5, NO2, and SO2 were more similar in Henan province, with more transmission from north to south in winter, from west to east and southwest to northeast in spring, from southwest to northeast in summer, and from north to south in autumn; however, the transmission of PM2.5 was more complicated. The O3-8h transport path was more different from the others, especially in autumn when pollutants were mostly transported from north to south, but the O3-8h transport path from southwest to northeast was obvious.

Effects of climate change and water management on West Florida Shelf's dynamics

In the present study we evaluated, in a high-resolution simulation (1.5 km), the separate and combined effects of freshwater discharge management and climate warming by 1 °C on the Loop Current (LC) intrusions on the West Florida Shelf (WFS) and its dynamics in the subtropical western Atlantic. Based on a one-year simulation in which an LC and its eddy intruded on the WFS, either the increase of freshwater discharge or the climate warming led to a change in the stratification properties of the WFS significant enough to affect the type of LC intrusions. Increased freshwater discharge contributed to the intensification of shelf water mixing that favors surface intrusion of LC waters. On the contrary, 1 °C warming led to increased shelf waters stratification that favors bottom intrusions. Either type of intrusion leads to a different oceanographic regime on the shelf to which the ecosystem might respond differently. Our study suggests, however, that increased freshwater discharge could mitigate the effect of climate warming on the WFS by reducing shelf waters stratification. The WFS response to cold air outbreaks that are common in the fall and winter months was also analyzed. It showed that under a warmer climate, the increased stratification due to the freshwater discharge at the end of the boreal summer wet season is cancelled by the warmer climate and reduces the available potential energy on the shelf, limiting coastal upwelling, instabilities, and shelf convection.

Coastal-urban meteorology: A sensitivity study using the WRF-urban model

The air quality of a city can be assessed by applying a computational modelling approach. However, one of the most critical issues faced while running air quality models is based on the meteorological model setup, which can significantly affect simulations over a coastal urban area with complex terrain. Thus, this study evaluates the performance of the Weather Research and Forecasting (WRF) model using urban canopy model schemes considering three different model heights (4, 10, and 20 m), and updated land use and cover data (ESA-CCI). The one-year simulation results, based on the observed surface parameters (wind speed and direction, temperature, humidity, and precipitation) over the Metropolitan Region of Vitória (MRV), Southeast of Brazil, showed that the WRF model systematically overpredicted temperature and wind speed, and underestimated humidity, especially during the autumn and winter seasons. However, a significant improvement was obtained using the building effect parameterisation (BEP) formulation to emulate meteorological variables over urban surfaces, especially for wind speed. For temperature and relative humidity, the use of BEP did not show appreciable improvement because the BULK scheme (the control experiment) had a similar performance. The land-use dataset changes showed minimal impact on the representation of urban surfaces; however, significant differences were observed in natural/vegetated areas. The different land covers impacted the surface meteorological parameters, such as temperature and precipitation. However, due to the low coverage of monitoring stations in the countryside area, it was insufficient to determine whether the performance of the WRF model is favoured by the land-use update.

Spatial and Temporal Variations in the Atmospheric Age Distribution of Primary and Secondary Inorganic Aerosols in China

The aging timescale of particles is a key parameter in determining their impacts on air quality, human health, and climate. In this study, a one-year simulation of the age distributions of the primary and secondary inorganic fine particulate matter (PM2.5) components was conducted over China using an age-resolved Community Multiscale Air Quality (CMAQ) model. The results indicate that primary PM2.5 (PPM) and ammonium mainly originate from fresh local emissions, with approximately 60%–80% concentrated in 0–24 h age bins in most of China throughout the year. The average age is about 15–25 h in most regions in summer, but increases to 40–50 h in southern region of China and the Sichuan Basin (SCB) in winter. Sulfate is more aged than PPM, indicating an enhanced contribution from regional transport. Aged sulfate with atmospheric age > 48 h account for 30%–50% of total sulfate in most regions and seasons, and the concentrations in the > 96 h age bin can reach up to 15 µg·m−3 in SCB during winter. Dramatic seasonal variations occur in the Yangtze River Delta, Pearl River Delta, and SCB, with highest average age of 60–70 h in winter and lowest of 40–45 h in summer. The average age of nitrate is 20–30 h in summer and increases to 40–50 h in winter. The enhanced deposition rate of nitric acid vapor combined with the faster chemical reaction rate of nitrogen oxides leads to a lower atmospheric age in summer. Additionally, on pollution days, the contributions of old age bins (> 24 h) increase notably for both PPM and secondary inorganic aerosols in most cities and seasons, suggesting that regional transport plays a vital role during haze events. The age information of PM2.5, provided by the age-resolved CMAQ model, can help policymakers design effective emergent emission control measures to eliminate severe haze episodes.