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Factor Separation in the Atmosphere : Applications and Future Prospects
\"Modeling atmospheric processes in order to forecast the weather or future climate change is an extremely complex and computationally intensive undertaking. One of the main difficulties is that there are a huge number of factors that need to be taken into account, some of which are still poorly understood. The Factor Separation (FS) method is a computational procedure that helps deal with these nonlinear factors. In recent years many scientists have applied FS methodology to a range of modeling problems, including paleoclimatology, limnology, regional climate change, rainfall analysis, cloud modeling, pollution, crop growth, and other forecasting applications. This book is the first to describe the fundamentals of the method, and to bring together its many applications in the atmospheric sciences. The main audience is researchers and graduate students using the FS method, but it is also of interest to advanced students, researchers, and professionals across the atmospheric sciences\"-- Provided by publisher.
Book
Application and Improvement of the Particle Swarm Optimization Algorithm in Source-Term Estimations for Hazardous Release
Hazardous gas release can pose severe hazards to the ecological environment and public safety. The source-term estimation of hazardous gas leakage serves a crucial role in emergency response and safety management practices. Nevertheless, the precision of a forward diffusion model and atmospheric diffusion conditions have a significant impact on the performance of the method for estimating source terms. This work proposes the particle swarm optimization (PSO) algorithm coupled with the Gaussian dispersion model for estimating leakage source parameters. The method is validated using experimental cases of the prairie grass field dispersion experiment with various atmospheric stability classes. The results prove the effectiveness of this method. The effects of atmospheric diffusion conditions on estimation outcomes are also investigated. The estimated effect in extreme atmospheric diffusion conditions is not as good as in other diffusion conditions. Accordingly, the Gaussian dispersion model is improved by adding linear and polynomial correction coefficients to it for its inapplicability under extreme diffusion conditions. Finally, the PSO method coupled with improved models is adapted for the source-term parameter estimation. The findings demonstrate that the estimation performance of the PSO method coupled with improved models is significantly improved. It was also found that estimated performances of source parameters of two correction models were significantly distinct under various atmospheric stability classes. There is no single optimal model; however, the model can be selected according to practical diffusion conditions to enhance the estimated precision of source-term parameters.
Journal Article
Remote Sensing of Planetary Boundary Layer Thermodynamic and Material Structures over a Large Steel Plant, China
Air pollutants emitted by industries can significantly affect local air quality and jeopardize human health, and the study of the boundary layer thermodynamic structure and diffusion capacity over industrial plants can be beneficial for the improvement of corporate air pollution control measures. The continuous high temporal and spatial resolution monitoring of the boundary layer structure (thermal, dynamic, and material) by advanced remote sensing instruments over a single strong industrial source (steel plant) in Shanxi Province, China, from May to June 2021 revealed the boundary layer characteristics under the influence of a single strong local anthropogenic influence. Strong nocturnal temperature inversions and grounded temperature inversions were prone to occur over industrial sources. The local wind field was characterized by significant daily variations, with the whole-layer airflow during the daytime dominated by southwesterly winds. At night, under the influence of radiation, topography, and surface, the airflow was dominated by easterly winds with low speeds (less than 2 m/s) in the low altitude range of 100 m, while the wind direction was still dominated by southwesterly winds with higher speeds in the altitude of 100 m. In addition, the average atmospheric diffusion capacity increased significantly with height in the 500 m altitude range, with an increase in rate of about 2~3 times/50 m, and continued to show a discontinuous increasing trend above 500 m. Combined with the wind direction and wind speed contours, it can be seen that the pollutants can be effectively dispersed at a height of 100 m. The thermal and turbulent boundary layer heights were highly consistent, and the material boundary layer height was significantly higher than the thermal and turbulent boundary layer heights during the daytime when convection was strong.
Journal Article
Impact of Large Cooling Tower on Atmospheric Dispersion of Effluent from Coastal Nuclear Power Plant
Wang, X.; Wei, G.; Wang, S.; Yang, Y.; Du, F., and Wang, B., 2020. Impact of large cooling tower on atmospheric dispersion of effluent from coastal nuclear power plant. In: Yang, Y.; Mi, C.; Zhao, L., and Lam, S. (eds.), Global Topics and New Trends in Coastal Research: Port, Coastal and Ocean Engineering. Journal of Coastal Research, Special Issue No. 103, pp. 474–478. Coconut Creek (Florida), ISSN 0749-0208. In order to improve the simulation quality of atmospheric dispersion on coastal nuclear power plant, computational fluid dynamics (CFD) method was used to simulate the impact of large cooling tower on the diffusion of gaseous effluent from coastal nuclear power plant. The simulation results show that when the release point is directly in front of the cooling tower, with considering the natural ventilation effect of the cooling tower, the axis concentration of the effluent is significantly reduced by about 1 to 2 orders of magnitude. Compared with different ambient wind speeds, the cooling tower has a more significant effect on the diffusion under low wind speed. For the ground release, atmospheric stability conditions have little effect on the concentration distribution. On this basis, a correction of the Gaussian model for the cooling tower effect is proposed. The atmospheric diffusion parameters in the Gaussian plume model can be given by three distance segments, which are 0-240 m, 240-270 m and above.
Journal Article
Modeling Impacts of Urbanization on Winter Boundary Layer Meteorology and Aerosol Pollution in the Central Liaoning City Cluster, China
The influence of urbanization on the frequent winter aerosol pollution events in Northeast China is not fully understood. The Weather Research and Forecasting Model with Chemistry (WRF–Chem) coupled with urban canopy (UC) models was used to simulate the impact of urbanization on an aerosol pollution process in the Central Liaoning city cluster (CLCC), China. To investigate the main mechanisms of urban expansion and UC on the winter atmospheric environment and the atmospheric diffusion capacity (ADC) in the CLCC, three simulation cases were designed using land-use datasets from different periods and different UC schemes. A comparative analysis of the simulation results showed that the land-use change (LU) and both LU and UC (LUUC) effects lead to higher surface temperature and lower relative humidity and wind speed in the CLCC by decreasing surface albedo, increasing sensible heat flux, and increasing surface roughness, with a spatial distribution similar to the distribution of LU. The thermal effect leads to an increase in atmospheric instability, an increase in boundary layer height and diffusion coefficient, and an increase in the ADC. The LU and LUUC effects lead to a significant decrease in near-surface PM2.5 concentrations in the CLCC due to changes in meteorological conditions and ADC within the boundary layer. The reduction in surface PM2.5 concentrations due to the LU effect is stronger at night than during daytime, while the LUUC effect leads to a greater reduction in surface PM2.5 concentrations during the day, mainly due to stronger diffusion and dilution caused by the effect of urban turbulence within different levels caused by the more complex UC scheme. In this study, the LU and LUUC effects result in greater thermal than dynamic effects, and both have a negative impact on surface PM2.5 concentrations, but redistribute pollutants from the lower urban troposphere to higher altitudes.
Journal Article
Challenges and Opportunities in Numerical Weather Prediction
NOAA’s National Centers for Environmental Prediction (NCEP) Production Suite (NPS) currently includes over 20 operational weather forecast systems, providing forecasts from the mesoscale to global seasonal outlooks. In an effort to optimize resources, the NPS is being simplified to far fewer systems within the Unified Forecast System (UFS) framework that nevertheless span NOAA’s weather prediction mission: short-range regional and atmospheric composition (RRFS, WoF), medium-range subseasonal (GEFS) to seasonal (SFS), marine and coastal (GFS, GEFS, NWPS, GLWU), hurricanes (HAFS), on-demand atmospheric dispersion (HySPLIT), hydrology (NWM), and space weather (WAM/IPE) (see appendix for a full list of abbreviation definitions). An international constellation of low-Earth-orbit and geosynchronous-equatorial-orbit satellites are expanding our Earth intelligence; for example, polar-orbiting satellites now provide 85% of the data used in global weather models. In addition to the advancement of DA research, the Joint Effort for Data assimilation Integration (JEDI), operated by the UCAR Joint Center for Satellite Data Assimilation (JCSDA), provides a common software infrastructure for full community engagement in the testing, research, and development of new observations and DA methods.
Journal Article
Effects of atmospheric circulations on the interannual variation in PM2.5 concentrations over the Beijing–Tianjin–Hebei region in 2013–2018
The Chinese government has made many efforts to mitigate fine particulate matter pollution in recent years by taking strict measures on air pollutant reduction, which has generated the nationwide improvements in air quality since 2013. However, under the stringent air pollution controls, how the wintertime PM2.5 concentration (i.e., the mass concentration of atmospheric particles with diameters less than 2.5 µm) varies and how much the meteorological conditions contribute to the interannual variations in PM2.5 concentrations are still unclear, and these very important for the local government to assess the emission reduction of the previous year and adjust mitigation strategies for the next year. The effects of atmospheric circulation on the interannual variation in wintertime PM2.5 concentrations over the Beijing–Tianjin–Hebei (BTH) region in the period of 2013–2018 are evaluated in this study. Generally, the transport of clean and dry air masses and an unstable boundary layer in combination with the effective near-surface horizontal divergence or pumping action at the top of the boundary layer benefits the horizontal or vertical diffusion of surface air pollutants. Instead, the co-occurrence of a stable boundary layer, frequent air stagnation, positive water vapor advection and deep near-surface horizontal convergence exacerbate the wintertime air pollution. Favorable circulation conditions lasting for 2–4 d are beneficial for the diffusion of air pollutants, and 3–7 d of unfavorable circulation events exacerbates the accumulation of air pollutants. The occurrence frequency of favorable circulation events is consistent with the interannual variation in seasonal mean PM2.5 concentrations. There is better diffusion ability in the winters of 2014 and 2017 than in other years. A 59.9 % observed decrease in PM2.5 concentrations in 2017 over the BTH region could be attributed to the improvement in atmospheric diffusion conditions. It is essential to exclude the contribution of meteorological conditions to the variation in interannual air pollutants when making a quantitative evaluation of emission reduction measurements.
Journal Article
PM2.5 POLLUTION IN CHINA AND HOW IT HAS BEEN EXACERBATED BY TERRAIN AND METEOROLOGICAL CONDITIONS
The recent severe and frequent PM2.5 (i.e., fine particles smaller than 2.5 μm) pollution in China has aroused unprecedented public concern. The first two years of PM2.5 measurements in China are reported and compared with those of Europe and the United States. The average PM2.5 concentration in China is approximately 5 times that over Europe and America. The contribution of atmospheric dispersion to such air quality is evaluated in this study. Air stagnation or its absence is a good indicator of the atmosphere’s capability to disperse its pollutants, but the NOAA definition of an air stagnation event is found to not be applicable to China since it depends on vertical mixing that is weakened in China by the effects of terrain. To address this deficiency, a new threshold for air stagnation events is proposed that depends on the 10-m wind speed, boundary layer height, and occurrence of precipitation. This newly defined air stagnation closely tracks the day-to-day variation of PM2.5 concentrations. Such events are more frequent over China than over Europe and the United States during autumn and winter, especially over the Sichuan basin and Jing-Jin-Ji region of China. If China had the same frequency of air stagnation as the United States or Europe, 67% and 82% of its stations would improve their current air quality during autumn and winter (e.g., an average of 12% decrease in PM2.5 concentrations for the Jing-Jin-Ji region in wintertime). Its severe pollution and frequent air stagnation conditions make controls on emission less effective in China than elsewhere.
Journal Article
Air dispersion modeling
A single reference to all aspects of contemporary air dispersion modeling The practice of air dispersion modeling has changed dramatically in recent years, in large part due to new EPA regulations. Current with the EPA's 40 CFR Part 51, this book serves as a complete reference to both the science and contemporary practice of air dispersion modeling. Throughout the book, author Alex De Visscher guides readers through complex calculations, equation by equation, helping them understand precisely how air dispersion models work, including such popular models as the EPA's AERMOD and CALPUFF. Air Dispersion Modeling begins with a primer that enables readers to quickly grasp basic principles by developing their own air dispersion model. Next, the book offers everything readers need to work with air dispersion models and accurately interpret their results, including: Full chapter dedicated to the meteorological basis of air dispersion Examples throughout the book illustrating how theory translates into practice Extensive discussions of Gaussian, Lagrangian, and Eulerian air dispersion modeling Detailed descriptions of the AERMOD and CALPUFF model formulations This book also includes access to a website with Microsoft Excel and MATLAB files that contain examples of air dispersion model calculations. Readers can work with these examples to perform their own calculations. With its comprehensive and up-to-date coverage, Air Dispersion Modeling is recommended for environmental engineers and meteorologists who need to perform and evaluate environmental impact assessments. The book's many examples and step-by-step instructions also make it ideal as a textbook for students in the fields of environmental engineering, meteorology, chemical engineering, and environmental sciences.
eBook
Amplified positive effects on air quality, health, and renewable energy under China’s carbon neutral target
China pledged to achieve carbon neutrality by 2060 to combat global climate change, yet the resulting multi-aspect domestic impacts are not fully analysed due to an incomplete understanding of the underlying anthropogenic–natural interactions. Building an integrated cross-disciplinary modelling framework that can capture the feedbacks of changing aerosols on meteorology, here we highlight the amplified air quality, human health and renewable energy self-reinforcing synergies of China’s carbon neutral target in comparison to the baseline in 2015 and 2060. We find that owing to emissions reduction and more favourable meteorological conditions caused by less aerosol, achieving China’s carbon neutrality target in 2060 reduces national population-weighted PM
2.5
concentrations and associated premature deaths by ~39 μg m
−
3
and 1.13 (95% confidence interval: 0.97–1.29) million while boosting provincial solar (wind) power performance by up to ~10% (~6%) with mostly decreased resource variability in comparison to the 2060 baseline. Enhanced renewable performance along with low-carbon energy transition may provide additional opportunities to address the remaining air pollution and associated human health damages upon achieving carbon neutrality. Our results highlight that global developing and polluting countries’ pledge for carbon neutrality can produce important positive feedbacks between aerosols mitigation, air quality improvement and enhanced renewable energy, which can be amplified via weakened aerosol–meteorology interactions and better atmospheric dispersion.
The interaction between aerosol and meteorology amplifies the positive effects on air quality, health and renewable energy under China’s carbon neutrality target for 2060, according to an integrated modelling analysis.
Journal Article