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Atmosphere, Volume 13, Issue 6 (June 2022) – 145 articles

Cover Story (view full-size image): Mineral dust emissions in atmospheric models are usually based on static erodibility maps. In this study, we present the development of a physically based dust source map for driving GOCART-AFWA dust emissions in a WRF-Chem model. The new parameterization is constrained by MODIS-NDVI observations, and the erodibility map is updated every 15 days. The new methodology is applied over a large area covering Africa, the Mediterranean, the Middle East, and Europe during a highly active dust period (March to May 2017). The new module describes the dust sources at finer detail, also including their evolution in time. Comparison with AERONET AOD measurements indicates an overall improvement in model performance, especially for stronger dust episodes. View this paper
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13 pages, 2081 KiB  
Article
Impacts of Different Land Use Scenarios on Future Global and Regional Climate Extremes
by Tao Hong, Junjie Wu, Xianbiao Kang, Min Yuan and Lian Duan
Atmosphere 2022, 13(6), 995; https://doi.org/10.3390/atmos13060995 - 20 Jun 2022
Cited by 8 | Viewed by 2260
Abstract
Land use and land cover change (LULCC) alters the character of the land surface and directly impacts the climate. The impacts of LULCC on historical and future climate have been largely investigated, mostly using simulations with or without land use change. However, it [...] Read more.
Land use and land cover change (LULCC) alters the character of the land surface and directly impacts the climate. The impacts of LULCC on historical and future climate have been largely investigated, mostly using simulations with or without land use change. However, it is still not clear to what extent the projections of future climate change depend on the choice of land use scenario, which can provide important guidance on using land use and land management as a tool for regional climate mitigation. Here, using ten Earth system models participating in future land use policy sensitivity experiments in Land Use Model Intercomparison Project (LUMIP), we assessed the impact of two different land use scenarios (SSP1-2.6 and SSP3-7.0) on extreme climate. The results demonstrate that the use of different land use change scenarios has a substantial effect on the projections of regional climate extreme changes. Our study also reveals that, compared with other anthropogenic forcings, land use change has a considerable contribution to regional temperature extreme changes, with the contribution ranging from −14.0% to 10.3%, and the contribution to regional precipitation extreme change is larger, with a range of −118.4~138.8%. The global climate effects of land use change are smaller in magnitude than regional effects, with a small (5%) contribution to temperature extreme change. We also found a large spread in the model’s responses to LULCC, especially for precipitation extremes, suggesting that observation-based studies on reducing models’ uncertainties are needed to obtain more robust future projections of regional climate change. Our study highlights the essential role of land use and land management strategies in future regional climate mitigation. Full article
(This article belongs to the Section Climatology)
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15 pages, 2241 KiB  
Article
Long-Term Variations of Meteorological and Precursor Influences on Ground Ozone Concentrations in Jinan, North China Plain, from 2010 to 2020
by Jing Sun, Shixin Duan, Baolin Wang, Lei Sun, Chuanyong Zhu, Guolan Fan, Xiaoyan Sun, Zhiyong Xia, Bo Lv, Jiaying Yang and Chen Wang
Atmosphere 2022, 13(6), 994; https://doi.org/10.3390/atmos13060994 - 20 Jun 2022
Cited by 3 | Viewed by 1945
Abstract
Ground-level ozone (O3) pollution in the North China Plain has become a serious environmental problem over the last few decades. The influence of anthropogenic emissions and meteorological conditions on ozone trends have become the focus of widespread research. We studied the [...] Read more.
Ground-level ozone (O3) pollution in the North China Plain has become a serious environmental problem over the last few decades. The influence of anthropogenic emissions and meteorological conditions on ozone trends have become the focus of widespread research. We studied the long-term ozone trends at urban and suburban sites in a typical city in North China and quantified the contributions of anthropogenic and meteorological factors. The results show that urban O3 increased and suburban O3 decreased from 2010 to 2020. The annual 90th percentile of the maximum daily 8-h average of ozone in urban areas increased by 3.01 μgm−3year−1 and, in suburban areas, it decreased by 3.74 μgm−3year−1. In contrast to the meteorological contributions, anthropogenic impacts are the decisive reason for the different ozone trends in urban and suburban areas. The rapid decline in nitrogen oxides (NOX) in urban and suburban areas has had various effects. In urban areas, this leads to a weaker titration of NOX and enhanced O3 formation, while in suburban areas, this weakens the photochemical production of O3. Sensitivity analysis shows that the O3 formation regime is in a transition state in both the urban and suburban areas. However, this tends to be limited to volatile organic compounds (VOCs) in urban areas and to NOX in suburban areas. One reasonable approach to controlling ozone pollution should be to reduce nitrogen oxide emissions while strengthening the control of VOCs. Full article
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19 pages, 2126 KiB  
Article
Analytical Four-Dimensional Ensemble Variational Data Assimilation for Joint State and Parameter Estimation
by Kangzhuang Liang, Wei Li, Guijun Han, Yantian Gong and Siyuan Liu
Atmosphere 2022, 13(6), 993; https://doi.org/10.3390/atmos13060993 - 20 Jun 2022
Cited by 3 | Viewed by 1637
Abstract
The joint state and parameter estimation problem is an important issue in data assimilation. An adjoint free data assimilation method, namely analytical four-dimensional ensemble variational (A-4DEnVar) data assimilation method, was developed to provide a solution for the joint estimation problem. In the algorithm, [...] Read more.
The joint state and parameter estimation problem is an important issue in data assimilation. An adjoint free data assimilation method, namely analytical four-dimensional ensemble variational (A-4DEnVar) data assimilation method, was developed to provide a solution for the joint estimation problem. In the algorithm, to estimate the adjoint model reasonably, the ensemble initial conditions and parameters are generated by Gaussian noise whose covariance is constructed by multiplying a very small factor by their background error covariance. The ensemble perturbations are calculated with respect to background states rather than the ensemble mean. Next, the usage of temporal cross covariances makes it possible to avoid the adjoint model and estimate the gradient in 4DVar. Furthermore, we update the solution iteratively with a linear search process to improve the stability and ensure the convergence of the algorithm. The method is tested using the three-variable Lorenz model (Lorenz-1963) to illustrate its efficiency. It is shown that A-4DEnVar results in similar performance with 4DVar. Sensitivity experiments show that A-4DEnVar is able to assimilate observations successfully with different settings. The proposed method is able to work as well as 4DVar and avoid adjoint models for the joint state and parameter estimation. Full article
(This article belongs to the Section Atmospheric Techniques, Instruments, and Modeling)
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18 pages, 6482 KiB  
Article
Variations in Aerosol Optical Properties over East Asian Dust Storm Source Regions and Their Climatic Factors during 2000–2021
by Saichun Tan, Bin Chen, Hong Wang, Huizheng Che, Huaying Yu and Guangyu Shi
Atmosphere 2022, 13(6), 992; https://doi.org/10.3390/atmos13060992 - 20 Jun 2022
Cited by 4 | Viewed by 1939
Abstract
The East Asian dust storms occur in western and northern China, and southern Mongolia every year, particularly in spring. In this study, we use satellite aerosol products to demonstrate the spatial and temporal variation in aerosol optical depth (AOD) from MODIS, and the [...] Read more.
The East Asian dust storms occur in western and northern China, and southern Mongolia every year, particularly in spring. In this study, we use satellite aerosol products to demonstrate the spatial and temporal variation in aerosol optical depth (AOD) from MODIS, and the absorbing aerosol index (AAI) from TOMS and OMI, over the main dust storm source regions (MDSR), and to investigate their relationship to vegetation coverage (NDVI), soil properties (surface soil moisture content and soil temperature 0–10 cm underground), and climatic factors (surface wind speed, air temperature at 2 m above the ground, and precipitation) in spring for the period of 2000–2021. Compared with dust storm occurrence frequency (DSF) observed at surface stations, MODIS AOD, TOMS AAI, and OMI AAI showed consistent spatial distributions and seasonal variations with DSF in the MDSR, with correlation coefficients of 0.88, 0.55, and 0.88, respectively. The results showed that AOD and AAI over the MDSR decreased during 2000–2005, 2006–2017, and 2000–2021, but increased during 2017–2021.The improvements in vegetation coverage and soil moisture together with favorable climatic factors (the increase in temperature and precipitation and the decrease in surface wind speed) resulted in the decreasing trend of AOD and AAI during 2000–2005, 2006–2017, and the entire period of 2000–2021. Conversely, the increase in surface wind speed, the decrease in temperature and the low soil moisture in 2018 and 2020 were the reasons for the increases in AOD and AAI over the MDSR during 2017–2021. The combination effects of surface wind, temperature, soil moisture, and vegetation coverage would determine DSF, AOD, and AAI, in the end, under global climate change. Full article
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16 pages, 3000 KiB  
Article
Characterizing Atmospheric Brown Carbon and Its Emission Sources during Wintertime in Shanghai, China
by Linyuan Zhang, Jung Hyun Son, Zhe Bai, Wei Zhang, Ling Li, Lina Wang and Jianmin Chen
Atmosphere 2022, 13(6), 991; https://doi.org/10.3390/atmos13060991 - 20 Jun 2022
Cited by 7 | Viewed by 1856
Abstract
Atmospheric brown carbon (BrC) is a kind of organic aerosol that efficiently absorbs ultraviolet-visible light and has an impact on climate forcing. We conducted an in-depth field study on ambient aerosols at a monitoring point in Shanghai, China, aiming to investigate the potential [...] Read more.
Atmospheric brown carbon (BrC) is a kind of organic aerosol that efficiently absorbs ultraviolet-visible light and has an impact on climate forcing. We conducted an in-depth field study on ambient aerosols at a monitoring point in Shanghai, China, aiming to investigate the potential emission sources, molecular structures, and the contributions to light absorptions of ambient BrC chromophores. The results indicated that nine molecules were identified as nitroaromatic compounds, five of which (4-nitrophenol, 4-nitrocatechol, 2-nitro-1-naphthol, 3-methyl-4-nitrocatechol, and 2-methyl-4-nitrophenol) usually came from biomass burning or were produced from the photo-oxidation of anthropogenic volatile organic compounds (e.g., toluene, benzene) under high-NOx conditions. 4-nitrophenol was the strongest BrC chromophore and accounted for 13% of the total aerosol light absorption at λ = 365 nm. The estimated light absorption of black carbon was approximately three times the value of methanol-soluble BrC at λ = 365 nm. The ratios of K+/OC and K+/EC, and the correlations with WSOC, OC, HULIS-C and K+, and MAE values of methanol extracts also indicated that the primary emissions from biomass burning contributed more aerosol light absorption compared to the secondary formation during the wintertime in Shanghai. Therefore, biomass burning control is still the most urgent strategy for reducing BrC in Shanghai. Full article
(This article belongs to the Special Issue Chemical Composition and Sources of Particles in the Atmosphere)
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16 pages, 12064 KiB  
Article
Spatiotemporal Variation in Air Pollution Characteristics and Influencing Factors in Ulaanbaatar from 2016 to 2019
by Suriya, Narantsogt Natsagdorj, Aorigele, Haijun Zhou and Sachurila
Atmosphere 2022, 13(6), 990; https://doi.org/10.3390/atmos13060990 - 20 Jun 2022
Cited by 4 | Viewed by 2196
Abstract
Ambient air pollution is a global environmental issue that affects human health. Ulaanbaatar (UB), the capital of Mongolia, is one of the most polluted cities in the world, and it is of great importance to study the temporal and spatial changes in air [...] Read more.
Ambient air pollution is a global environmental issue that affects human health. Ulaanbaatar (UB), the capital of Mongolia, is one of the most polluted cities in the world, and it is of great importance to study the temporal and spatial changes in air pollution in this city, along with their influencing factors. To understand the characteristics of atmospheric pollutants in UB, the contents of PM10, PM2.5, SO2, NO2, CO, and O3, as well as their influencing factors, were analyzed from data obtained from automatic air quality monitoring stations. These analyses yielded six major findings: (1) From 2016 to 2019, there was a total of 883 pollution days, and PM2.5 and PM10 were the primary pollutants on 553 and 351 of these days, respectively. The air pollution was dominated by PM10 in spring and summer, affected by both PM2.5 and PM10 in autumn, and dominated by PM2.5 in winter. (2) Compared with 2016, the number of days with good air quality in UB in 2019 increased by 45%, and the number of days with unhealthy or worse levels of pollution decreased by 56%, indicating that the air quality improved year by year. (3) From 2016 to 2019, the annual average PM2.5/PM10 ratio dropped from 0.55 to 0.45, and the proportion of PM2.5 in particulate matter decreased year by year. The PM concentration and PM2.5/PM10 ratio were highest in winter and lowest in summer. When comparing the four-season averages, the average PM2.5 concentration decreased by 89% from its highest level, and the PM10 concentration decreased by 67%, indicating stronger seasonal differences in PM2.5 than in PM10. (4) The hourly changes in PM concentration showed a bimodal pattern, exhibiting a decrease during the day and a slight increase in the afternoon due to temperature inversion, so the PM2.5/PM10 ratio increased at night in all four seasons. The PM concentration during the heating season was significantly higher than that in the non-heating season, indicating that coal-fired heating was the main cause of air pollution in UB. (5) Sand dust and soot were the two main types of pollution in UB. (6) Correlation analysis and linear fitting analysis showed that PM2.5 and PM10 caused by coal-firing had an important impact on air quality in UB. Coal combustion and vehicle emissions with SO2, NO2, and CO as factors made large contributions to PM2.5. Full article
(This article belongs to the Special Issue Advances in Air Quality Monitoring)
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16 pages, 1015 KiB  
Article
Multitask Learning Based on Improved Uncertainty Weighted Loss for Multi-Parameter Meteorological Data Prediction
by Junkai Wang, Lianlei Lin, Zaiming Teng and Yu Zhang
Atmosphere 2022, 13(6), 989; https://doi.org/10.3390/atmos13060989 - 20 Jun 2022
Viewed by 1739
Abstract
With the exponential growth in the amount of available data, traditional meteorological data processing algorithms have become overwhelmed. The application of artificial intelligence in simultaneous prediction of multi-parameter meteorological data has attracted much attention. However, existing single-task network models are generally limited by [...] Read more.
With the exponential growth in the amount of available data, traditional meteorological data processing algorithms have become overwhelmed. The application of artificial intelligence in simultaneous prediction of multi-parameter meteorological data has attracted much attention. However, existing single-task network models are generally limited by the data correlation dependence problem. In this paper, we use a priori knowledge for network design and propose a multitask model based on an asymmetric sharing mechanism, which effectively solves the correlation dependence problem in multi-parameter meteorological data prediction and achieves simultaneous prediction of multiple meteorological parameters with complex correlations for the first time. The performance of the multitask model depends largely on the relative weights among the task losses, and manually adjusting these weights is a difficult and expensive process, which makes it difficult for multitask learning to achieve the expected results in practice. In this paper, we propose an improved multitask loss processing method based on the assumptions of homoscedasticity uncertainty and the Laplace loss distribution and validate it using the German Jena dataset. The results show that the method can automatically balance the losses of each subtask and has better performance and robustness. Full article
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25 pages, 11748 KiB  
Article
Precipitable Water Content Climatology over Poland
by Hanna Ojrzyńska, Marek Błaś and Maciej Kryza
Atmosphere 2022, 13(6), 988; https://doi.org/10.3390/atmos13060988 - 19 Jun 2022
Cited by 2 | Viewed by 1638
Abstract
In this work, the high-resolution spatial and temporal variability of precipitable water (PW) over Poland is presented. PW is one of the key parameters of the atmosphere taken into account in thermodynamic and radiation models. The daily PW values from years 2001–2010, calculated [...] Read more.
In this work, the high-resolution spatial and temporal variability of precipitable water (PW) over Poland is presented. PW is one of the key parameters of the atmosphere taken into account in thermodynamic and radiation models. The daily PW values from years 2001–2010, calculated with the use of the WRF model, were compared with PW from soundings. The WRF modeled PW is in close agreement with measurements for the whole column of the troposphere and for individual levels: below 1.5 km, 1.5–3 km, 3–6 km and 6–10 km. The best agreement is observed in the lower part of the troposphere, especially for winter months. At the levels of 1.5 km to 10 km, the WRF model overestimates the PW values throughout the year, whereas up to 1.5 km PW is underestimated. The study shows an increasing trend of PW annual values between 1983 and 2010, but the trend is statistically insignificant. A significant positive trend with a high Sen’s slope is observed for the summer season up to 3 km in the troposphere, along with a significant negative tendency for spring. The trends in PW over Poland and Central Europe identified in this study contribute to the ongoing discussion on the observed climate changes. Full article
(This article belongs to the Section Climatology)
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22 pages, 7097 KiB  
Article
Data Assimilation of Doppler Wind Lidar for the Extreme Rainfall Event Prediction over Northern Taiwan: A Case Study
by Chih-Ying Chen, Nan-Ching Yeh and Chuan-Yao Lin
Atmosphere 2022, 13(6), 987; https://doi.org/10.3390/atmos13060987 - 18 Jun 2022
Cited by 2 | Viewed by 2453
Abstract
On 4 June 2021, short-duration extreme precipitation occurred in Taipei. Within 2 h, over 200 mm of rainfall accumulated in the Xinyi district. In this study, advanced data assimilation technology (e.g., hybrid data and 3D variations) was incorporated to develop a high-resolution, small-scale [...] Read more.
On 4 June 2021, short-duration extreme precipitation occurred in Taipei. Within 2 h, over 200 mm of rainfall accumulated in the Xinyi district. In this study, advanced data assimilation technology (e.g., hybrid data and 3D variations) was incorporated to develop a high-resolution, small-scale (e.g., northern Taiwan) data assimilation forecast system, namely the weather research and forecast-grid statistical interpolation (WRF-GSI) model. The 3D wind field data recorded by the Doppler wind lidar system of Taipei Songshan Airport were assimilated for effective simulation of the extreme precipitation. The results revealed that the extreme rainfall was caused by the interaction between the northeast wind incurred by a front to the north of Taiwan, a humid southerly wind generated by Typhoon Choi-wan, and the regional sea–land breeze circulation. For the Xinyi district, the WRF-GSI_lidar model reported accumulated rainfall 30 mm higher than that in the non-assimilated experiment (WRF-GSI_noDA), indicating that the WRF-GSI model with lidar observation was improved 15% more than the nonassimilated run. Full article
(This article belongs to the Special Issue The Impact of Data Assimilation on Severe Weather Forecast)
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13 pages, 1673 KiB  
Article
Spatiotemporal Variations in the Air Pollutant NO2 in Some Regions of Pakistan, India, China, and Korea, before and after COVID-19, Based on Ozone Monitoring Instrument Data
by Wardah Naeem, Jaemin Kim and Yun Gon Lee
Atmosphere 2022, 13(6), 986; https://doi.org/10.3390/atmos13060986 - 18 Jun 2022
Cited by 9 | Viewed by 2097
Abstract
In 2020, COVID-19 was proclaimed a pandemic by the World Health Organization, prompting several nations throughout the world to block their borders and impose a countrywide lockdown, halting all major manmade activities and thus leaving a beneficial impact on the natural environment. We [...] Read more.
In 2020, COVID-19 was proclaimed a pandemic by the World Health Organization, prompting several nations throughout the world to block their borders and impose a countrywide lockdown, halting all major manmade activities and thus leaving a beneficial impact on the natural environment. We investigated the influence of a sudden cessation of human activity on tropospheric NO2 concentrations to understand the resulting changes in emissions, particularly from the power-generating sector, before (2010–2019) and during the pandemic (2020). NO2 was chosen because of its short lifespan in the Earth’s atmosphere. Using daily tropospheric NO2 column concentrations from the Ozone Monitoring Instrument, the geographic and temporal characteristics of tropospheric NO2 column were investigated across 12 regions in India, Pakistan, China, and South Korea (2010–2020). We analyzed weekly, monthly, and annual trends and found that the NO2 concentrations were decreased in 2020 (COVID-19 period) in the locations investigated. Reduced anthropogenic activities, including changes in energy production and a reduction in fossil fuel consumption before and during the COVID-19 pandemic, as well as reduced traffic and industrial activity in 2020, can explain the lower tropospheric NO2 concentrations. The findings of this study provide a better understanding of the process of tropospheric NO2 emissions over four nations before and after the coronavirus pandemic for improving air quality modeling and management approaches. Full article
(This article belongs to the Section Air Quality)
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31 pages, 11065 KiB  
Article
Evaluation of the Performance of the WRF Model in a Hyper-Arid Environment: A Sensitivity Study
by Rachid Abida, Yacine Addad, Diana Francis, Marouane Temimi, Narendra Nelli, Ricardo Fonseca, Oleksandr Nesterov and Emmanuel Bosc
Atmosphere 2022, 13(6), 985; https://doi.org/10.3390/atmos13060985 - 18 Jun 2022
Cited by 5 | Viewed by 1941
Abstract
Accurate simulation of boundary layer surface meteorological parameters is essential to achieve good forecasting of weather and atmospheric dispersion. This paper is devoted to a model sensitivity study over a coastal hyper-arid region in the western desert of the United Arab Emirates. This [...] Read more.
Accurate simulation of boundary layer surface meteorological parameters is essential to achieve good forecasting of weather and atmospheric dispersion. This paper is devoted to a model sensitivity study over a coastal hyper-arid region in the western desert of the United Arab Emirates. This region hosts the Barakah Nuclear Power Plant (BNPP), making it vital to correctly simulate local weather conditions for emergency response in case of an accidental release. We conducted a series of high-resolution WRF model simulations using different combinations of physical schemes for the months January 2019 and June 2019. The simulated results were verified against in-situ meteorological surface measurements available offshore, nearshore, and inland at 12 stations. Several statistical metrics were calculated to rank the performance of the different simulations and a near-to-optimal set of physics options that enhance the performance of a WRF model over different locations in this region has been selected. Additionally, we found that the WRF model performed better in inland locations compared to offshore or nearshore locations, suggesting the important role of dynamical SSTs in mesoscale models. Moreover, morning periods were better simulated than evening ones. The impact of nudging towards station observations resulted in an overall reduction in model errors by 5–15%, which was more marked at offshore and nearshore locations. The sensitivity to grid cell resolution indicated that a spatial resolution of 1 km led to better performance compared to coarser spatial resolutions, highlighting the advantage of high-resolution simulations in which the mesoscale coastal circulation is better resolved. Full article
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11 pages, 3099 KiB  
Article
Ambient Size-Segregated Particulate Matter Characterization from a Port in Upstate New York
by Omosehin D. Moyebi, Brian P. Frank, Shida Tang, Gil LaDuke, David O. Carpenter and Haider A. Khwaja
Atmosphere 2022, 13(6), 984; https://doi.org/10.3390/atmos13060984 - 18 Jun 2022
Cited by 1 | Viewed by 1886
Abstract
Air pollution impacts human health and the environment, especially in urban cities with substantial industrial activities and vehicular traffic emissions. Despite increasingly strict regulations put in place by regulatory agencies, air pollution is still a significant environmental problem in cities across the world. [...] Read more.
Air pollution impacts human health and the environment, especially in urban cities with substantial industrial activities and vehicular traffic emissions. Despite increasingly strict regulations put in place by regulatory agencies, air pollution is still a significant environmental problem in cities across the world. The objective of this study was to evaluate the environmental pollution from stationary and mobile sources using real-time monitoring and sampling techniques to characterize size-segregated particulate matter (PM), black carbon (BC), and ozone (O3) at the Port of Albany, NY. Air pollution monitoring was carried out for 3 consecutive weeks under a 24-hour cycle in 2018 at the New York State Department of Environmental Conservation (NYSDEC) site within the Port. Sampling was done with an AEROCET 531, optical particle sizer (OPS), ozone monitor, and MicroAeth AE51. Higher mass and number concentrations of size-segregated particles were observed during the daytime. PM2.5 and PM10 concentrations ranged from 1 to 271 micrograms per cubic meter (µg/m3) and 1 to 344 µg/m3, respectively. While these values do not exceed the level of the USEPA 24-hour standards, frequent sharp peaks were observed at higher concentrations. Size-segregated PM at sizes 0.3 µm and 0.374 µm recorded maximum concentrations of 101,631 particle number per cubic centimeter (#/cm3) and 43,432 #/cm3, respectively. Wide variations were observed in the particle number concentrations for 0.3 µm, 0.374 µm, and 0.465 µm sizes, which ranged from 1521 to 101,631 #/cm3; 656 to 43,432 #/cm3; and 311 to 29,271 #/cm3, respectively. BC concentration increased during morning and evening rush hours with the maximum concentration of 11,971 ng/m3 recorded at 8:00 AM. This suggests that mobile sources are the primary contributor to anthropogenic sources of BC within the Port. Episodic elevations in the concentrations of size-segregated PM and BC confirmed the contribution of industrial and vehicular activities around the Port of Albany. This study underscores the importance of measuring particles on a size-segregated basis in order to more fully understand the contributions of the multiple sources present within and surrounding a port environment. Full article
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19 pages, 6465 KiB  
Article
Landfill Emissions of Methane Inferred from Unmanned Aerial Vehicle and Mobile Ground Measurements
by Eduardo P. Olaguer, Shelley Jeltema, Thomas Gauthier, Dustin Jermalowicz, Arthur Ostaszewski, Stuart Batterman, Tian Xia, Julia Raneses, Michael Kovalchick, Scott Miller, Jorge Acevedo, Jonathan Lamb, Jeff Benya, April Wendling and Joyce Zhu
Atmosphere 2022, 13(6), 983; https://doi.org/10.3390/atmos13060983 - 18 Jun 2022
Cited by 6 | Viewed by 3651
Abstract
Municipal solid waste landfills are significant sources of atmospheric methane, the second most important greenhouse gas after carbon dioxide. Large emissions of methane from landfills contribute not only to global climate change, but also to local ozone formation due to the enhancement of [...] Read more.
Municipal solid waste landfills are significant sources of atmospheric methane, the second most important greenhouse gas after carbon dioxide. Large emissions of methane from landfills contribute not only to global climate change, but also to local ozone formation due to the enhancement of radical chain lengths in atmospheric reactions of volatile organic compounds and nitrogen oxides. Several advanced techniques were deployed to measure methane emissions from two landfills in the Southeast Michigan ozone nonattainment area during the Michigan–Ontario Ozone Source Experiment (MOOSE). These techniques included mobile infrared cavity ringdown spectrometry, drone-mounted meteorological sensors and tunable diode laser spectrometry, estimation of total landfill emissions of methane based on flux plane measurements, and Gaussian plume inverse modeling of distributed methane emissions in the presence of complex landfill terrain. The total methane emissions measured at the two landfills were of the order of 500 kg/h, with an uncertainty of around 50%. The results indicate that both landfill active faces and leaking gas collection systems are important sources of methane emissions. Full article
(This article belongs to the Special Issue The Michigan-Ontario Ozone Source Experiment (MOOSE))
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20 pages, 3977 KiB  
Article
Vertical Eddy Diffusivity in the Tropical Cyclone Boundary Layer during Landfall
by Chen Chen
Atmosphere 2022, 13(6), 982; https://doi.org/10.3390/atmos13060982 - 17 Jun 2022
Cited by 1 | Viewed by 1802
Abstract
This study investigated surface layer turbulence characteristics and parameters using 20 Hz eddy covariance data collected from five heights with winds up to 42.27 m s−1 when Super Typhoon Maria (2018) made landfall. The dependence of these parameters including eddy diffusivities for [...] Read more.
This study investigated surface layer turbulence characteristics and parameters using 20 Hz eddy covariance data collected from five heights with winds up to 42.27 m s−1 when Super Typhoon Maria (2018) made landfall. The dependence of these parameters including eddy diffusivities for momentum (Km) and heat (Kt), vertical mixing length (Lm), and strain rate (S) on wind speed (un), height, and radii was examined. The results show that momentum fluxes (τ), turbulent kinetic energy (TKE), and Km had a parabolic dependence on un at all five heights outside three times the RMW, the maximum of Km and S increased from the surface to a maximum value at a height of 50 m, and then decreased with greater heights. However, Km and S were nearly constant with wind and height within two to three times the RMW from the TC center before landfall. Our results also found the |τ|, TKE, and Km were larger than over oceanic areas at any given wind, and Km was about one to two orders of magnitude bigger than Kt. The turbulence characteristic and parameters’ change with height and radii from the TC center should be accounted for in sub-grid scale physical processes of momentum fluxes in numerical TC models. Full article
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28 pages, 40490 KiB  
Article
Large-Scale Saharan Dust Episode in April 2019: Study of Desert Aerosol Loads over Sofia, Bulgaria, Using Remote Sensing, In Situ, and Modeling Resources
by Zahari Peshev, Atanaska Deleva, Liliya Vulkova and Tanja Dreischuh
Atmosphere 2022, 13(6), 981; https://doi.org/10.3390/atmos13060981 - 17 Jun 2022
Cited by 7 | Viewed by 1946
Abstract
Emissions of immense amounts of desert dust into the atmosphere, spreading over vast geographical areas, are in direct feedback relation with ongoing global climate changes. An extreme large-scale Saharan dust episode occurred over Mediterranean and Europe in April 2019, driven by a dynamic [...] Read more.
Emissions of immense amounts of desert dust into the atmosphere, spreading over vast geographical areas, are in direct feedback relation with ongoing global climate changes. An extreme large-scale Saharan dust episode occurred over Mediterranean and Europe in April 2019, driven by a dynamic blocking synoptic pattern (omega block) creating conditions for a powerful northeastward circulation of air masses rich in dust and moisture. Here, we study and characterize the effects of related dust intrusion over Sofia, Bulgaria, using lidar remote sensing combined with in situ measurements, satellite imagery, and modeling data. Optical and microphysical parameters of the desert aerosols were obtained and vertically profiled, namely, backscatter coefficients and backscatter-related Ångström exponents, as well as statistical distributions of the latter as qualitative analogs of the actual particle size distributions. Dynamical and topological features of the dust-dominated aerosol layers were determined. Height profiles of the aerosol/dust mass concentration were obtained by synergistic combining and calibrating lidar and in situ data. The comparison of the retrieved mass concentration profiles with the dust modeling ones shows a satisfactory compliance. The local meteorological conditions and the aerosol composition and structure of the troposphere above Sofia during the dust event were seriously affected by the desert air masses. Full article
(This article belongs to the Special Issue Atmospheric Composition and Regional Climate Studies in Bulgaria)
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12 pages, 1701 KiB  
Article
Characteristics of Fine Particulate Matter (PM2.5)-Bound n-Alkanes and Polycyclic Aromatic Hydrocarbons (PAHs) in a Hong Kong Suburban Area
by Yuan Gao, Zhenhao Ling, Zhuozhi Zhang and Shuncheng Lee
Atmosphere 2022, 13(6), 980; https://doi.org/10.3390/atmos13060980 - 17 Jun 2022
Cited by 3 | Viewed by 1885
Abstract
PM2.5 samples were collected at Tung Chung (TC), Hong Kong, during four nonconsecutive months in 2011/2012 to determine the concentrations, seasonal variations, and potential sources of polycyclic aromatic hydrocarbons (PAHs) and n-alkanes (n-C15-n-C35). Samples [...] Read more.
PM2.5 samples were collected at Tung Chung (TC), Hong Kong, during four nonconsecutive months in 2011/2012 to determine the concentrations, seasonal variations, and potential sources of polycyclic aromatic hydrocarbons (PAHs) and n-alkanes (n-C15-n-C35). Samples were analyzed using the thermal desorption gas chromatography/mass spectrometry (TD-GC/MS) method. The concentrations of particulate PAHs ranged from 1.26–13.93 ng/m3 with a mean value of 2.57 ng/m3, dominated by 4-ring species. Phenanthrene (Phe) and fluoranthene (Flu) were the two most abundant species, accounting for 13% and 18%, respectively. The dominant sources of PAHs were coal and biomass burning. The inhalation cancer risk value in our study exceeded 1 × 10−6 but was below 1 × 10−4, implying that the inhalation cancer risk of PAHs at the TC site is acceptable. The average concertation of n-alkanes was 103.21 ng/m3 (ranging from 38.58 to 191.44 ng/m3), and C25 was the most abundant species. Both PAHs and n-alkanes showed higher concentrations in autumn and winter whilst these values were lowest in summer. The carbon preference index (CPI) and percent contribution of wax n-alkanes showed that biogenic sources were the major sources. The annual average contributions of higher plant wax to n-alkanes at TC were over 40%. Full article
(This article belongs to the Special Issue Advances in Light-Absorbing Carbonaceous Aerosols Research)
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11 pages, 1907 KiB  
Article
A Study of the Vertical Distribution and Sub-Peaks of Ozone below 12 km over Wuyishan Region Based on Ozone Sounding in Winter
by Yulan Zheng, Huiying Deng, Huabiao You, Yiming Qiu, Tianfu Zhu, Xugeng Cheng and Hong Wang
Atmosphere 2022, 13(6), 979; https://doi.org/10.3390/atmos13060979 - 17 Jun 2022
Cited by 2 | Viewed by 1685
Abstract
An understanding of the vertical distribution of ozone is critical to assessing the ozone variabilities both in the stratosphere and the troposphere. We collected the profiles of atmospheric ozone partial pressure and ozone volume mixing ratio (VMR) by a sounding system at the [...] Read more.
An understanding of the vertical distribution of ozone is critical to assessing the ozone variabilities both in the stratosphere and the troposphere. We collected the profiles of atmospheric ozone partial pressure and ozone volume mixing ratio (VMR) by a sounding system at the Wuyi Mountain National Meteorological Observation Station (Shaowu sounding station 58725) from November 2021 to February 2022. In this study, the vertical distribution and sub-peak phenomenon of tropospheric ozone below 12 km are investigated using mathematical statistics and synthetic analysis. The results show that the ozone partial pressure decreased from the ground to the tropopause, which is consistent with the temperature profile. However, 66.7% of cases first showed an increasing trend from the ground to about 3 km, while there were one or more temperature inversions in the corresponding temperature profiles and the atmosphere was stable and the relative humidity was high; then, in the stratosphere, the ozone partial pressure began to increase significantly, The ozone partial pressure reaches its maximum at an average height of 24.9 km, and the maximum value was 14 mPa. The ozone VMR in troposphere is the fluctuating increase from the ground to the tropopause, and 83.3% of the cases begin to rise rapidly at about 2–5 km away from the tropopause, and the ozone surge height is 2.9 km lower than the tropopause on average. Some of these tropopause ozone VMR have shown the characteristics of stratospheric ozone. The sub-peaks of tropospheric ozone below 12 km has four cases. All the sub-peaks occur between 6.7 km and 11.5 km vertically, and peak ozone VMR is 1.6–1.9 times larger than that of the average state at the same height. The maximum stratospheric ozone VMR is 8649 ppb on average, occurring at an average height of 31.3 km, and this average height of the maximum stratospheric ozone VMR is 6.4 km higher than that for the ozone partial pressure. The total ozone in the boundary layer (0–1.5 km) is 4.3 DU on average, accounting for 1.5% in total ozone column. The total ozone in the troposphere is 39.5 DU, accounting for 13.1% in total ozone column, and the total ozone in the stratosphere is 262.4 DU, accounting for 86.9% in total ozone column. Full article
(This article belongs to the Special Issue Remote Sensing and Multiple Observations of Air Quality in China)
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17 pages, 2473 KiB  
Article
Phenological Response of Flood Plain Forest Ecosystem Species to Climate Change during 1961–2021
by Lenka Bartošová, Petra Dížkova, Jana Bauerová, Lenka Hájková, Milan Fischer, Jan Balek, Monika Bláhová, Martin Možný, Pavel Zahradníček, Petr Štěpánek, Zdeněk Žalud and Miroslav Trnka
Atmosphere 2022, 13(6), 978; https://doi.org/10.3390/atmos13060978 - 17 Jun 2022
Cited by 4 | Viewed by 1976
Abstract
The present study analyses 61 years of phenological observations (1961–2021) of five herb, five shrub, four tree, and one bird species representing the prevalent spring species of floodplain forest ecosystems in the Czech Republic, central Europe. The in situ observations were conducted at [...] Read more.
The present study analyses 61 years of phenological observations (1961–2021) of five herb, five shrub, four tree, and one bird species representing the prevalent spring species of floodplain forest ecosystems in the Czech Republic, central Europe. The in situ observations were conducted at the Vranovice site (48°48′ N, 16°46′ E, 170 m above mean sea level) representing the Plaček’ forest National Reserve. The observed plants and bird species showed statistically significant (p < 0.05) shifts in phenological terms to an earlier date of the year, but the rate of the shift among the observed species differed. The most progressive shifts were detected for the herbs (14 days), followed by the shrubs (13 days), trees (9 days), and finally by the bird species (8 days). All the phenophases were significantly correlated with the daily maximum temperature (r = 0.72–0.91). The results also showed a decline in the correlation for species among the phenophases of the herbs and trees. The phenophases that were highly correlated in the past were less correlated and had higher variability in the last decades. We conclude that the phenological response of the ecosystem to warming in the spring resulted in higher variability and a lower correlation among the observed phenophases mainly caused by the most expressive phenological shifts of the early herbs. Full article
(This article belongs to the Section Biometeorology)
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33 pages, 18274 KiB  
Article
Evapotranspiration of an Abandoned Grassland in the Italian Alps: Influence of Local Topography, Intra- and Inter-Annual Variability and Environmental Drivers
by Davide Gisolo, Ivan Bevilacqua, Justus van Ramshorst, Alexander Knohl, Lukas Siebicke, Maurizio Previati, Davide Canone and Stefano Ferraris
Atmosphere 2022, 13(6), 977; https://doi.org/10.3390/atmos13060977 - 16 Jun 2022
Cited by 3 | Viewed by 2121
Abstract
Evapotranspiration is a key variable of the hydrological cycle but poorly studied in Alpine ecosystems. The current study aimed to characterise the impact of topography and temporal variability on actual evapotranspiration (ETa) and its environmental drivers at an Alpine abandoned grassland encroached by [...] Read more.
Evapotranspiration is a key variable of the hydrological cycle but poorly studied in Alpine ecosystems. The current study aimed to characterise the impact of topography and temporal variability on actual evapotranspiration (ETa) and its environmental drivers at an Alpine abandoned grassland encroached by shrubs on a steep slope. Eddy covariance, meteorological, hydrological and soil data were analysed over four growing seasons, of which two had wet and two dry conditions. The topography caused a systematic morning inflexion of ETa in all growing seasons, reflecting the valley wind system. Inter-annual differences of ETa exceeded 100 mm, and ETa means and cumulative values were significantly different between wet and dry growing seasons in the four years. Besides, ETa had a larger temporal variability in wet growing seasons. A bimodality of ETa was found in all years, caused by the onset of plant activity in the morning hours. Energy- and water-limited ETa periods were identified by comparing ETa to potential evapotranspiration (ETo). Periods of fifteen days revealed the main intra- and inter-annual differences of the environmental variables (air temperature, vapour pressure deficit—VPD, precipitation and ETa). The fixed effects of a linear mixed model based on ETa drivers explained 56% of ETa variance. The most important ETa drivers were net radiation and VPD, followed by wind speed. In growing seasons characterised by dry conditions, air temperature and the ground heat flux at the surface (either both or one of them) influenced ETa as well. The current study contributed to the understanding of topographical and temporal effects on evapotranspiration and other micrometeorological variables in an Alpine ecosystem still rarely studied. Full article
(This article belongs to the Section Biosphere/Hydrosphere/Land–Atmosphere Interactions)
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10 pages, 1815 KiB  
Article
Effects of Chemical Reactions on the Oxidative Potential of Humic Acid, a Model Compound of Atmospheric Humic-like Substances
by Yohei Koike and Takayuki Kameda
Atmosphere 2022, 13(6), 976; https://doi.org/10.3390/atmos13060976 - 16 Jun 2022
Cited by 1 | Viewed by 1857
Abstract
Atmospheric particulate matter (PM) contains various chemicals, some of which generate in vivo reactive oxygen species (ROS). Owing to their high reactivity and oxidation ability, ROS can cause various diseases. To understand how atmospheric PM affects human health, we must clarify the PM [...] Read more.
Atmospheric particulate matter (PM) contains various chemicals, some of which generate in vivo reactive oxygen species (ROS). Owing to their high reactivity and oxidation ability, ROS can cause various diseases. To understand how atmospheric PM affects human health, we must clarify the PM components having oxidative potential (OP) leading to ROS production. According to previous studies, OP is exhibited by humic-like substances (HULIS) in atmospheric PM. However, the OP-dependence of the chemical structures of HULIS has not been clarified. Therefore, in this study, humic acid (HA, a model HULIS material) was exposed to ozone and ultraviolet (UV) irradiation, and its OP and structures were evaluated before and after the reactions using dithiothreitol (DTT) assay and Fourier transform infrared (FT-IR), respectively. The OP of HA was more significantly increased by UV irradiation than by ozone exposure. FT-IR analysis showed an increased intensity of the C=O peak in the HA structure after UV irradiation, suggesting that the OP of HA was increased by a chemical change to a more quinone-like structure after irradiation. Full article
(This article belongs to the Special Issue Student-Led Research in Atmospheric Science)
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12 pages, 3578 KiB  
Article
Development of an Engine Power Binning Method for Characterizing PM2.5 and NOx Emissions for Off-Road Construction Equipment with DPF and SCR
by Qi Yao, Seungju Yoon, Yi Tan, Liang Liu, Jorn Herner, George Scora, Robert Russell, Hanwei Zhu and Tom Durbin
Atmosphere 2022, 13(6), 975; https://doi.org/10.3390/atmos13060975 - 16 Jun 2022
Cited by 2 | Viewed by 1547
Abstract
Aftertreatment technologies in Tier 4 off-road engines have resulted in significant emission reductions compared to older tier engines without aftertreatments. The appropriate characterization of Tier 4 engine emissions in consideration of aftertreatment operation is important for projecting emissions and developing mitigation strategies. The [...] Read more.
Aftertreatment technologies in Tier 4 off-road engines have resulted in significant emission reductions compared to older tier engines without aftertreatments. The appropriate characterization of Tier 4 engine emissions in consideration of aftertreatment operation is important for projecting emissions and developing mitigation strategies. The current method of aggregating emissions over an entire duty cycle and averaging them by engine load has a limitation in developing emission profiles over various duty cycles of Tier 4 engines, especially at low-load operations, where aftertreatment control for NOx may not be effective. In this study, an engine power binning method was developed to characterize emissions for Tier 4 construction equipment with aftertreatment systems, especially at low-power operating conditions. This binning method was applied to real-time emissions and activity data for four different types of Tier 4 construction equipment. Results show that low-power operations (<20% engine power) are responsible for 38–60% NOx and 11–51% of PM2.5 emissions depending on the equipment types. These results underscore the need for controlling NOx emissions during low-power operations. PM2.5 EFs for non-DPF backhoes were one to two orders of magnitude greater than all the other equipment due to the lack of a DPF, despite being certified to the same PM2.5 standard. This shows the benefits of DPFs on construction equipment and that they are substantial in reducing PM2.5 emissions. Estimated emission differences between using the binning and the averaging methods were 49–86% and 16–82% for NOx and PM2.5, respectively. These differences may change once the binning method is applied to larger emission datasets obtained from real-world vocational activities. Full article
(This article belongs to the Special Issue Air Quality Impacts of Vehicle Emissions)
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13 pages, 5052 KiB  
Article
Black Sea Freezing and Relation to the Winter Conditions in 2006–2021
by Mirna Matov, Elisaveta Peneva and Vasko Galabov
Atmosphere 2022, 13(6), 974; https://doi.org/10.3390/atmos13060974 - 16 Jun 2022
Cited by 1 | Viewed by 4681
Abstract
Black Sea freezing in winter is observed regularly in its northern parts and near the Kerch Strait. The reason for this is the relatively shallow northwestern shelf part and the river inflow of the three major European rivers Danube, Dnieper, and Dniester, as [...] Read more.
Black Sea freezing in winter is observed regularly in its northern parts and near the Kerch Strait. The reason for this is the relatively shallow northwestern shelf part and the river inflow of the three major European rivers Danube, Dnieper, and Dniester, as well as Don through the Azov Sea, carrying a large amount of fresh water to this part of the Black Sea. The global warming that has been observed in recent decades has made these episodes less intense; nevertheless, they exist and impact people who live n the area. The aim of this study is to analyze the extent of sea-ice variability in the last 15 years, observed by satellite observations, and to describe the weather conditions favorable for freezing to occur. It is found that, in 2006, 2012 and 2017, sea ice extended unusually southward, which is related to the unusually cold winter and weather conditions in these years. The weather patterns associated with the periods of maximal sea ice in the Black Sea are discussed. In addition, we analyze how the winter conditions change in the period 1926–2021 by combining different data sources. The winter is classified as cold, moderate or mild through the Winter Severity Index following a previously published methodology. The findings in our paper could help to monitor and predict these events and to inform the interested end-users. Full article
(This article belongs to the Special Issue Atmospheric Composition and Regional Climate Studies in Bulgaria)
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12 pages, 6383 KiB  
Article
Topographical and Thermal Forcing in Favorable Circulation Pattern to Early Spring Precipitation over the Southeastern Tibetan Plateau
by Yaoxian Yang, Zeyong Hu, Maoshan Li, Haipeng Yu, Weiqiang Ma and Weiwei Fan
Atmosphere 2022, 13(6), 973; https://doi.org/10.3390/atmos13060973 - 15 Jun 2022
Viewed by 1756
Abstract
During the boreal spring (March–May), the precipitation that occurs from March over the southeastern Tibetan Plateau (TP) can account for 20–40% of the total annual amount. The origin of this phenomenon has not been clearly understood from a climatological perspective. In this study, [...] Read more.
During the boreal spring (March–May), the precipitation that occurs from March over the southeastern Tibetan Plateau (TP) can account for 20–40% of the total annual amount. The origin of this phenomenon has not been clearly understood from a climatological perspective. In this study, the role of topographical and thermal forcing on the precipitation over the southeastern TP in early spring (March) was investigated through sensitivity numerical simulations based on general circulation model. The simulated results show the favorable circulation and static stability to early spring precipitation over the southeastern TP when the model is simultaneously forced by realistic topography, zonal symmetric radiative equilibrium temperature, and diabatic heating over the TP and its surrounding areas. The quasi-stationary wave pattern over the Eurasian continent forced by realistic and TP topographical forcing leads to prolonged low pressure and intensified zonal winds over the southeastern TP due to quasi-steady wave activities. Thermal forcing experiments reveals that sensible heating over the southeastern TP not only strengthens the cyclonic circulation, ascending motion and statically unstable over the southeastern TP through thermal adaptation and the Sverdrup balance, but also triggers an anticyclone at upper tropospheric level extending from north of the Bay of Bengal to the eastern TP, which further favors precipitation over the southeastern TP. This work will provide useful background information for spring climate prediction over the TP. Full article
(This article belongs to the Special Issue Land-Atmosphere Interaction on the Tibetan Plateau)
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13 pages, 5430 KiB  
Article
Dynamics of Precipitation Anomalies in Tropical South America
by Mario Córdova, Rolando Célleri and Aarnout van Delden
Atmosphere 2022, 13(6), 972; https://doi.org/10.3390/atmos13060972 - 15 Jun 2022
Cited by 5 | Viewed by 2322
Abstract
In this study, precipitation in Tropical South America in the 1931–2016 period is investigated by means of Principal Component Analysis and composite analysis of circulation fields. The associated dynamics are analyzed using the 20th century ERA-20C reanalysis. It is found that the main [...] Read more.
In this study, precipitation in Tropical South America in the 1931–2016 period is investigated by means of Principal Component Analysis and composite analysis of circulation fields. The associated dynamics are analyzed using the 20th century ERA-20C reanalysis. It is found that the main climatic processes related to precipitation anomalies in Tropical South America are: (1) the intensity and position of the South Atlantic Convergence Zone (SACZ); (2) El Niño Southern Oscillation (ENSO); (3) the meridional position of the Intertropical Convergence Zone (ITCZ), which is found to be related to Atlantic Sea Surface Temperature (SST) anomalies; and (4) anomalies in the strength of the South American Monsoon System, especially the South American Low-Level Jet (SALLJ). Interestingly, all of the analyzed anomalies are related to processes that operate from the Atlantic Ocean, except for ENSO. Results from the present study are in agreement with the state of the art literature about precipitation anomalies in the region. However, the added strength of the longer dataset and the larger study area improves the knowledge and gives new insights into how climate variability and the resulting dynamics are related to precipitation in Tropical South America. Full article
(This article belongs to the Section Climatology)
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20 pages, 4110 KiB  
Article
Genetic Algorithm-Optimized Extreme Learning Machine Model for Estimating Daily Reference Evapotranspiration in Southwest China
by Quanshan Liu, Zongjun Wu, Ningbo Cui, Wenjiang Zhang, Yaosheng Wang, Xiaotao Hu, Daozhi Gong and Shunsheng Zheng
Atmosphere 2022, 13(6), 971; https://doi.org/10.3390/atmos13060971 - 15 Jun 2022
Cited by 8 | Viewed by 1880
Abstract
Reference evapotranspiration (ET0) is an essential component in hydrological and ecological processes. The Penman–Monteith (PM) model of Food and Agriculture Organization of the United Nations (FAO) model requires a number of meteorological parameters; it is urgent to develop high-precision and computationally [...] Read more.
Reference evapotranspiration (ET0) is an essential component in hydrological and ecological processes. The Penman–Monteith (PM) model of Food and Agriculture Organization of the United Nations (FAO) model requires a number of meteorological parameters; it is urgent to develop high-precision and computationally efficient ET0 models with fewer parameter inputs. This study proposed the genetic algorithm (GA) to optimize extreme learning machine (ELM), and evaluated the performances of ELM, GA-ELM, and empirical models for estimating daily ET0 in Southwest China. Daily meteorological data including maximum temperature (Tmax), minimum temperature (Tmin), wind speed (u2), relative humidity (RH), net radiation (Rn), and global solar radiation (Rs) during 1992–2016 from meteorological stations were used for model training and testing. The results from the FAO-56 Penman–Monteith formula were used as a control group. The results showed that GA-ELM models (with R2 ranging 0.71–0.99, RMSE ranging 0.036–0.77 mm·d−1) outperformed the standalone ELM models (with R2 ranging 0.716–0.99, RMSE ranging 0.08–0.77 mm·d−1) during training and testing, both of which were superior to empirical models (with R2 ranging 0.36–0.91, RMSE ranging 0.69–2.64 mm·d−1). ET0 prediction accuracy varies with different input combination models. The machine learning models using Tmax, Tmin, u2, RH, and Rn/Rs (GA-ELM5/GA-ELM4 and ELM5/ELM4) obtained the best ET0 estimates, with R2 ranging 0.98–0.99, RMSE ranging 0.03–0.21 mm·d−1, followed by models with Tmax, Tmin, and Rn/Rs (GA-ELM3/GA-ELM2 and ELM3/ELM2) as inputs. The machine learning models involved with Rn outperformed those with Rs when the quantity of input parameters was the same. Overall, GA-ELM5 (Tmax, Tmin, u2, RH and Rn as inputs) outperformed the other models during training and testing, and was thus recommended for daily ET0 estimation. With the estimation accuracy, computational costs, and availability of input parameters accounted, GA-ELM2 (Tmax, Tmin, and Rs as inputs) was determined to be the most effective model for estimating daily ET0 with limited meteorological data in Southwest China. Full article
(This article belongs to the Section Biosphere/Hydrosphere/Land–Atmosphere Interactions)
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19 pages, 5006 KiB  
Article
Characterization of Imidazole Compounds in Aqueous Secondary Organic Aerosol Generated from Evaporation of Droplets Containing Pyruvaldehyde and Inorganic Ammonium
by Xin Lin, Mingqiang Huang, Tingting Lu, Weixiong Zhao, Changjin Hu, Xuejun Gu and Weijun Zhang
Atmosphere 2022, 13(6), 970; https://doi.org/10.3390/atmos13060970 - 15 Jun 2022
Cited by 10 | Viewed by 2836
Abstract
Imidazole compounds are important constituents of atmospheric brown carbon. The imidazole components of aqueous secondary organic aerosol (aqSOA) that are generated from the evaporation of droplets containing pyruvaldehyde and inorganic ammonium are on-line characterized by an aerosol laser time-of-flight mass spectrometer (ALTOFMS) and [...] Read more.
Imidazole compounds are important constituents of atmospheric brown carbon. The imidazole components of aqueous secondary organic aerosol (aqSOA) that are generated from the evaporation of droplets containing pyruvaldehyde and inorganic ammonium are on-line characterized by an aerosol laser time-of-flight mass spectrometer (ALTOFMS) and off-line detected by optical spectrometry in this study. The results demonstrated that the laser desorption/ionization mass spectra of aqSOA particles that were detected by ALTOFMS contained the characteristic mass peaks of imidazoles at m/z = 28 (CH2N+), m/z = 41 (C2H3N+) and m/z = 67 (C3H4N2+). Meanwhile, the extraction solution of the aqSOA particles that were measured by off-line techniques showed that the characteristic absorption peaks at 217 nm and 282 nm appeared in the UV-Vis spectrum, and the stretching vibration peaks of C-N bond and C=N bond emerged in the infrared spectrum. Based on these spectral information, 4-methyl-imidazole and 4-methyl-imidazole-2-carboxaldehyde are identified as the main products of the reaction between pyruvaldehyde and ammonium ions. The water evaporation accelerates the formation of imidazoles inside the droplets, possibly owing to the highly concentrated environment. Anions, such as F, CO32, NO3, SO42 and Cl in the aqueous phase promote the reaction of pyruvaldehyde and ammonium ions to produce imidazole products, resulting in the averaged mass absorption coefficient (<MAC>) in the range of 200–600 nm of aqSOA increases, and the order of promotion is: F > CO32 > SO42 ≈ NO3 ≈ Cl. These results will help to analyze the constituents and optics of imidazoles and provide a useful basis for evaluating the formation process and radiative forcing of aqSOA particles. Full article
(This article belongs to the Special Issue New Insights into Secondary Organic Aerosol Formation)
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7 pages, 592 KiB  
Article
Study on the Source Profile Characteristics of Carbon Plant
by Sen Li, Danni Liang and Jianhui Wu
Atmosphere 2022, 13(6), 969; https://doi.org/10.3390/atmos13060969 - 15 Jun 2022
Viewed by 1333
Abstract
In the background of carbon neutrality, carbon emissions are basked in the attention. As a significant source of carbon emissions, the emission characteristics of carbon plant should be known. Particulate matter in flue gas was collected in a carbon plant in Tongliao. The [...] Read more.
In the background of carbon neutrality, carbon emissions are basked in the attention. As a significant source of carbon emissions, the emission characteristics of carbon plant should be known. Particulate matter in flue gas was collected in a carbon plant in Tongliao. The chemical components in PM10 and PM2.5 were analyzed, and source profile of carbon plant was established. The results showed that the mass fractions of EC, Ca, Ca2+, S, Al, Si and Fe were higher in particles than other components. The chemical marker of carbon plant was EC, and the trace carbonaceous components of carbon plant were EC1 and EC2, which were very different from other carbon emission sources. In the absence of other chemical composition information, eight carbonaceous components can be used to identify the sources of particle. Full article
(This article belongs to the Section Air Quality)
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18 pages, 7238 KiB  
Article
Hygroscopic Ground-Based Generator Cloud Seeding Design; A Case Study from the 2020 Weather Modification in Larona Basin Indonesia
by Findy Renggono, Mahally Kudsy, Krisna Adhitya, Purwadi Purwadi, Halda Aditya Belgaman, Saraswati Dewi, Rahmawati Syahdiza, Erwin Mulyana, Edvin Aldrian and Jon Arifian
Atmosphere 2022, 13(6), 968; https://doi.org/10.3390/atmos13060968 - 15 Jun 2022
Cited by 1 | Viewed by 3463
Abstract
Cloud seeding activities have been carried out in the form of experiments and operation activities as part of water resource management in some parts of the world. Recently, a new method of cloud seeding using a ground-based generator (GBG) was introduced in Indonesia. [...] Read more.
Cloud seeding activities have been carried out in the form of experiments and operation activities as part of water resource management in some parts of the world. Recently, a new method of cloud seeding using a ground-based generator (GBG) was introduced in Indonesia. This method is used to seed orographic clouds with the aid of a 50 m GBG tower located in a mountainous area. By taking advantage of the topography and local circulation, the GBG tower will introduce hygroscopic seeding materials into orographic clouds to accelerate the collision and coalescence process within the clouds, increasing the cloud’s rainfall amount. The hygroscopic ground-based cloud seeding was conducted over the Larona Basin in Sulawesi, Indonesia, from December 2019 to April 2020. There were five towers installed around Larona Basin, located over 500 m above sea level. The results show that there was an increase in monthly rainfall amount from the GBG operation period in January, February, and March compared to its long-term average of as much as 79%, 17%, and 46%, respectively. Meanwhile, despite an increase of 0.4% in Lake Towuti water level, it is still not concluded that the GBG cloud seeding operation was involved in the lake water level raise. Therefore, more studies need to be performed in the future to answer whether the cloud seeding affected the lake water level. Full article
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19 pages, 1311 KiB  
Review
An Evaluation of Risk Ratios on Physical and Mental Health Correlations due to Increases in Ambient Nitrogen Oxide (NOx) Concentrations
by Stephanie Shaw and Bill Van Heyst
Atmosphere 2022, 13(6), 967; https://doi.org/10.3390/atmos13060967 - 14 Jun 2022
Cited by 11 | Viewed by 2518
Abstract
Nitrogen oxides (NOx) are gaseous pollutants contributing to pollution in their primary form and are also involved in reactions forming ground-level ozone and fine particulate matter. Thus, NOx is of great interest for targeted pollution reduction because of this cascade [...] Read more.
Nitrogen oxides (NOx) are gaseous pollutants contributing to pollution in their primary form and are also involved in reactions forming ground-level ozone and fine particulate matter. Thus, NOx is of great interest for targeted pollution reduction because of this cascade effect. Primary emissions originate from fossil fuel combustion making NOx a common outdoor and indoor air pollutant. Numerous studies documenting the observed physical health impacts of NOx were reviewed and, where available, were summarized using risk ratios. More recently, the literature has shifted to focus on the mental health implications of NOx exposure, and a review of the current literature found five main categories of mental health-related conditions with respect to NOx exposure: common mental health disorders, sleep, anxiety, depression, and suicide. All the physical and mental health effects with available risk ratios were organized in order of increasing risk. Mental health concerns emerged as those most influenced by NOx exposure, with physical health impacts, such as asthma, only beginning to surface as the fourth highest risk. Mental health conditions occupied seven of the top ten highest risk health ailments. The results summarized in this narrative review show that there are clear positive correlations between NOx and negative physical and mental health manifestations, thus strengthening the argument in support of the reduction in ambient NOx levels. Full article
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29 pages, 5803 KiB  
Article
Impact of Collaborative Agglomeration of Manufacturing and Producer Services on Air Quality: Evidence from the Emission Reduction of PM2.5, NOx and SO2 in China
by Penghao Ye, Jin Li, Wenjing Ma and Huarong Zhang
Atmosphere 2022, 13(6), 966; https://doi.org/10.3390/atmos13060966 - 14 Jun 2022
Cited by 11 | Viewed by 2229
Abstract
Industrial agglomeration is a major source of regional economic development and the main pattern enterprises employ after having developed to a certain stage. Industrial agglomeration also affects the emissions of air pollutants in production. Based on provincial panel data for China from 2006 [...] Read more.
Industrial agglomeration is a major source of regional economic development and the main pattern enterprises employ after having developed to a certain stage. Industrial agglomeration also affects the emissions of air pollutants in production. Based on provincial panel data for China from 2006 to 2019, this paper introduces the full generalized least squares (FGLS) panel econometrics model. By considering spatial correlation, the potential endogenous problem has been controlled using the instrumental variable and the effects of the co-agglomeration of manufacturing and producer services on three major air pollutants, i.e., SO2, PM2.5, and NOx, have been empirically estimated. The empirical results show that: (1) The agglomeration of manufacturing increases the emission of PM2.5 in the air, while the agglomeration of producer services and the co-agglomeration of manufacturing and producer services reduce it. Moran correlation index test showed that SO2 and NOx had no significant spatial correlation. (2) The agglomeration of manufacturing, the agglomeration of producer services, and co-agglomeration exert the most significant effects on PM2.5 in the air in central and western China. This is probably because of the availability of basic natural resources in these areas. (3) The energy consumption structure mediates the effect of the agglomeration of manufacturing on PM2.5, and human capital mediates the effect of the agglomeration of producer services on PM2.5 emissions. Based on the results, policy suggestions to improve the atmospheric environment during the process of industrial agglomeration are proposed. Full article
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