Dew condensation during a typical haze event in Changchun, China

2019 ◽  
Vol 11 (2) ◽  
pp. 568-576
Author(s):  
Yingying Xu ◽  
Zhaoqing Luan ◽  
Hui Zhu
Keyword(s):  
Particulate Matter ◽  
Water Vapor ◽  
Meteorological Factors ◽  
Environmental Problems ◽  
Underlying Surface ◽  
Removal Rates ◽  
Near Surface ◽  
Haze Event ◽  
Dew Amount ◽  
Mass Concentrations

Abstract Haze is one of the most serious environmental problems affecting China. This study monitored the changes in dew amount and quality during a haze event that occurred in 2016. Water vapor migrated continuously to the near surface during the haze event. The period of dew condensation increased because of meteorological factors, and the daily dew amount (0.178 mm) was higher during the haze event than in non-haze weather (0.0607 mm). The concentrations of all ions in the dew increased gradually during the haze event, peaking during the most serious period of the haze. The concentrations of SO42− and NH4+ reached 15,325.95 and 13,865.45 μeq/L, which were 2.24 and 10.83 times greater than those obtained before the haze event, respectively. During the haze event, the particulate matter (PM) concentrations within the dew increased, and the mass concentrations of PM2.5 and PM2.5-10 during the worst haze event were 65.3 and 166.1 mg/L, respectively. The dew mainly removed coarse PM; the average removal rates of PM2.5 and PM2.5-10 during the haze event were 13.6% and 16.9%, respectively. Dew can capture PM throughout a haze event, and its purifying effect on the underlying surface was obvious, especially during the beginning of the event.

scholarly journals Comparison of dry and wet deposition of particulate matter in near-surface waters during summer

PLoS ONE ◽  
2018 ◽  
Vol 13 (6) ◽  
pp. e0199241 ◽  
Author(s):  
Yanan Wu ◽  
Jiakai Liu ◽  
Jiexiu Zhai ◽  
Ling Cong ◽  
Yu Wang ◽  
...  
Keyword(s):  
Particulate Matter ◽  
Surface Waters ◽  
Wet Deposition ◽  
Near Surface ◽  
Dry And Wet Deposition

Extreme Surface Winds During Landfalling Atmospheric Rivers: The Modulating Role of Near-Surface Stability

2021 ◽  
Author(s):  
Terence J. Pagano ◽  
Duane E. Waliser ◽  
Bin Guan ◽  
Hengchun Ye ◽  
F. Martin Ralph ◽  
...  
Keyword(s):  
Water Vapor ◽  
Static Stability ◽  
Vapor Transport ◽  
Water Vapor Transport ◽  
Surface Winds ◽  
Near Surface ◽  
Extreme Surface ◽  
Atmospheric Rivers ◽  
Explained Variance

AbstractAtmospheric rivers (ARs) are long and narrow regions of strong horizontal water vapor transport. Upon landfall, ARs are typically associated with heavy precipitation and strong surface winds. A quantitative understanding of the atmospheric conditions that favor extreme surface winds during ARs has implications for anticipating and managing various impacts associated with these potentially hazardous events. Here, a global AR database (1999–2014) with relevant information from MERRA-2 reanalysis, QuikSCAT and AIRS satellite observations are used to better understand and quantify the role of near-surface static stability in modulating surface winds during landfalling ARs. The temperature difference between the surface and 1 km MSL (ΔT; used here as a proxy for near-surface static stability), and integrated water vapor transport (IVT) are analyzed to quantify their relationships to surface winds using bivariate linear regression. In four regions where AR landfalls are common, the MERRA-2-based results indicate that IVT accounts for 22-38% of the variance in surface wind speed. Combining ΔT with IVT increases the explained variance to 36-52%. Substitution of QuikSCAT surface winds and AIRS ΔT in place of the MERRA-2 data largely preserves this relationship (e.g., 44% compared to 52% explained variance for USA West Coast). Use of an alternate static stability measure–the bulk Richardson number–yields a similar explained variance (47%). Lastly, AR cases within the top and bottom 25% of near-surface static stability indicate that extreme surface winds (gale or higher) are more likely to occur in unstable conditions (5.3%/14.7% during weak/strong IVT) than in stable conditions (0.58%/6.15%).

scholarly journals Spaceborne differential absorption radar water vapor retrieval capabilities in tropical and subtropical boundary layer cloud regimes

2021 ◽  
Vol 14 (10) ◽  
pp. 6443-6468
Author(s):  
Richard J. Roy ◽  
Matthew Lebsock ◽  
Marcin J. Kurowski
Keyword(s):  
Boundary Layer ◽  
Water Vapor ◽  
Trade Wind ◽  
Retrieval Algorithm ◽  
Line Center ◽  
Vertical Resolution ◽  
Horizontal Integration ◽  
Differential Absorption ◽  
Near Surface ◽  
Cloud Regimes

Abstract. Differential absorption radar (DAR) near the 183 GHz water vapor absorption line is an emerging measurement technique for humidity profiling inside of clouds and precipitation with high vertical resolution, as well as for measuring integrated water vapor (IWV) in clear-air regions. For radar transmit frequencies on the water line flank away from the highly attenuating line center, the DAR system becomes most sensitive to water vapor in the planetary boundary layer (PBL), which is a region of the atmosphere that is poorly resolved in the vertical by existing spaceborne humidity and temperature profiling instruments. In this work, we present a high-fidelity, end-to-end simulation framework for notional spaceborne DAR instruments that feature realistically achievable radar performance metrics and apply this simulator to assess DAR's PBL humidity observation capabilities. Both the assumed instrument parameters and radar retrieval algorithm leverage recent technology and algorithm development for an existing airborne DAR instrument. To showcase the capabilities of DAR for humidity observations in a variety of relevant PBL settings, we implement the instrument simulator in the context of large eddy simulations (LESs) of five different cloud regimes throughout the trade-wind subtropical-to-tropical cloud transition. Three distinct DAR humidity observations are investigated: IWV between the top of the atmosphere and the first detected cloud bin or Earth's surface; in-cloud water vapor profiles with 200 meter vertical resolution; and IWV between the last detected cloud bin and the Earth's surface, which can provide a precise measurement of the sub-cloud humidity. We provide a thorough assessment of the systematic and random errors for all three measurement products for each LES case and analyze the humidity precision scaling with along-track measurement integration. While retrieval performance depends greatly on the specific cloud regime, we find generally that for a radar with cross-track scanning capability, in-cloud profiles with 200 m vertical resolution and 10 %–20 % uncertainty can be retrieved for horizontal integration distances of 100–200 km. Furthermore, column IWV can be retrieved with 10 % uncertainty for 10–20 km of horizontal integration. Finally, we provide some example science applications of the simulated DAR observations, including estimating near-surface relative humidity using the cloud-to-surface column IWV and inferring in-cloud temperature profiles from the DAR water vapor profiles by assuming a fully saturated environment.

scholarly journals Effect of the uncertainty in meteorology on air quality model predictions

Időjárás ◽  
2021 ◽  
Vol 125 (4) ◽  
pp. 625-646
Author(s):  
Zita Ferenczi ◽  
Emese Homolya ◽  
Krisztina Lázár ◽  
Anita Tóth
Keyword(s):  
Air Pollution ◽  
Particulate Matter ◽  
Air Quality ◽  
Weather Prediction ◽  
Horizontal Resolution ◽  
Model System ◽  
Air Quality Model ◽  
Quality Model ◽  
Near Surface ◽  
The Impact

An operational air quality forecasting model system has been developed and provides daily forecasts of ozone, nitrogen oxides, and particulate matter for the area of Hungary and three big cites of the country (Budapest, Miskolc, and Pécs). The core of the model system is the CHIMERE off-line chemical transport model. The AROME numerical weather prediction model provides the gridded meteorological inputs for the chemical model calculations. The horizontal resolution of the AROME meteorological fields is consistent with the CHIMERE horizontal resolution. The individual forecasted concentrations for the following 2 days are displayed on a public website of the Hungarian Meteorological Service. It is essential to have a quantitative understanding of the uncertainty in model output arising from uncertainties in the input meteorological fields. The main aim of this research is to probe the response of an air quality model to its uncertain meteorological inputs. Ensembles are one method to explore how uncertainty in meteorology affects air pollution concentrations. During the past decades, meteorological ensemble modeling has received extensive research and operational interest because of its ability to better characterize forecast uncertainty. One such ensemble forecast system is the one of the AROME model, which has an 11-member ensemble where each member is perturbed by initial and lateral boundary conditions. In this work we focus on wintertime particulate matter concentrations, since this pollutant is extremely sensitive to near-surface mixing processes. Selecting a number of extreme air pollution situations we will show what the impact of the meteorological uncertainty is on the simulated concentration fields using AROME ensemble members.

scholarly journals Spatial and Seasonal Variations of PM Concentration and Size Distribution in Manure-Belt Poultry Layer Houses

2019 ◽  
Vol 62 (2) ◽  
pp. 415-427 ◽  
Author(s):  
Reyna M. Knight ◽  
Xinjie Tong ◽  
Zhenyu Liu ◽  
Sewoon Hong ◽  
Lingying Zhao
Keyword(s):  
Particle Size ◽  
Particulate Matter ◽  
Size Distribution ◽  
Seasonal Variations ◽  
Size Distributions ◽  
Particle Size Distributions ◽  
Potential Health ◽  
Significant Difference ◽  
Autumn And Winter ◽  
Mass Concentrations

Abstract. Poultry layer houses are a significant source of particulate matter (PM) emissions, which potentially affect worker and animal health. Particulate matter characteristics, such as concentration and size distribution inside layer houses, are critical information for assessment of the potential health risks and development of effective PM mitigation technologies. However, this information and its spatial and seasonal variations are lacking for typical layer facilities. In this study, two TSI DustTrak monitors (DRX 8533) and an Aerodynamic Particle Sizer (APS 3321) were used to measure PM mass concentrations and number-weighted particle size distributions in two typical manure-belt poultry layer houses in Ohio in three seasons: summer, autumn, and winter. Bimodal particle size distributions were consistently observed. The average count median diameters (mean ±SD) were 1.68 ±0.25, 2.16 ±0.31, and 1.87 ±0.07 µm in summer, autumn, and winter, respectively. The average geometric standard deviations of particle size were 2.16 ±0.23, 2.16 ±0.18, and 1.74 ±0.17 in the three seasons, respectively. The average mass concentrations were 67.4 ±54.9, 289.9 ±216.2, and 428.1 ±269.9 µg m-3 for PM2.5; 73.6 ±59.5, 314.6 ±228.9, and 480.8 ±306.5 µg m-3 for PM4; and 118.8 ±99.6, 532.5 ±353.0, and 686.2 ±417.7 µg m-3 for PM10 in the three seasons, respectively. Both statistically significant (p < 0.05) and practically significant (difference of means >20% of smaller value) seasonal variations were observed. Spatial variations were only practically significant for autumn mass concentrations, likely due to external dust infiltration from nearby agricultural activities. The OSHA-mandated permissible exposure limit for respirable PM was not exceeded in any season. Keywords: Air quality, Particulate matter, Poultry housing, Seasonal variation, Spatial variation.

scholarly journals The snow storm of 8 March 2010 in Catalonia (Spain): a paradigmatic wet-snow event with a high societal impact

2014 ◽  
Vol 14 (2) ◽  
pp. 427-441 ◽  
Author(s):  
M. C. Llasat ◽  
M. Turco ◽  
P. Quintana-Seguí ◽  
M. Llasat-Botija
Keyword(s):  
Meteorological Factors ◽  
Coastal Region ◽  
Heavy Precipitation ◽  
Precipitation Event ◽  
Societal Impact ◽  
Strong Wind ◽  
Near Surface ◽  
Wet Snow ◽  
Snow Storm ◽  
Meteorological Features

Abstract. A heavy precipitation event swept over Catalonia (NE Spain) on 8 March 2010, with a total amount that exceeded 100 mm locally and snowfall of more than 60 cm near the coast. Unusual for this region and at this time of the year, this snowfall event affected mainly the coastal region and was accompanied by thunderstorms and strong wind gusts in some areas. Most of the damage was due to "wet snow", a kind of snow that favours accretion on power lines and causes line-breaking and subsequent interruption of the electricity supply. This paper conducts an interdisciplinary analysis of the event to show its great societal impact and the role played by the recently developed social networks (it has been called the first "Snowfall 2.0"), as well to analyse the meteorological factors associated with the major damage, and to propose an indicator that could summarise them. With this aim, the paper introduces the event and its societal impact and compares it with other important snowfalls that have affected the Catalan coast, using the PRESSGAMA database. The second part of the paper shows the event's main meteorological features and analyses the near-surface atmospheric variables responsible for the major damage through the application of the SAFRAN (Système d'analyse fournissant des renseignements atmosphériques à la neige) mesoscale analysis, which, together with the proposed "wind, wet-snow index" (WWSI), allows to estimate the severity of the event. This snow storm provides further evidence of our vulnerability to natural hazards and highlights the importance of a multidisciplinary approach in analysing societal impact and the meteorological factors responsible for this kind of event.

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