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Abstract Atmospheric transport and dispersion models (ATDMs) are widely used to study and forecast pollution events. In the frame of the “Effect of Megacities on the transport and transformation of pollutants on the regional to global scales” (EMeRGe) project, ATDM forecasts were carried out to identify potential airborne sampling areas of perfluorocarbons (PFCs) emanating from controlled PFC releases. The forecasts involved short-distance transport over small-scale topographic maxima (Manilla; Philippines), short-distance transport over large-scale topographic maxima (Taipei, Taiwan) and long-distance transport over mixed topography (Nanjing, China, sampled over Taiwan). In situ aircraft measurements of PFC mixing ratios down to a few parts per quadrillion (ppqv) provide us with a unique dataset to explore the added benefits of dynamical downscaling. Transport simulations were repeated using FLEXPART driven by ERA5 and IFS meteorological data and FLEXPART-WRF with dynamically downscaled IFS data down to 1.1 km and four PBL parametrisations. Of the three cases studied, dynamical downscaling led to significant differences for the Manilla and Taipei releases that can be interpreted through changes in the modelled orographic flow regimes. The choice of PBL scheme also significantly impacted accuracy, but there was no systematically better-performing option, highlighting the benefits of ensemble forecasting. Results show how convergence and divergence between ensemble members can be utilised to help decision-making during field campaigns. This study highlights the role that dynamical downscaling can play as an important component in campaign planning when dealing with observations over orographically complex areas.

In the present era, national borders frequently encounter the risk and threat of unidentified airspace objects such as airborne balloons; however, there is a lack of effective methods for predicting their trajectories. To address this gap, we examine the utilization of a Lagrangian diffusion model named FLEXPART for forecasting the movement of airborne balloons. The simulation results show that when taking into account the radius of the airborne balloon, there is a potential increase of up to 1.07 km and 1.45 km in the mean absolute error (MAE) and root mean square error (RMSE), respectively, in the horizontal direction. Similarly, considering the density of the airborne balloon can also result in an increase of 3.46 km (MAE) and 4.71 km (RMSE) horizontally. Therefore, simplifying them into mass points enables FLEXPART to predict their trajectories with higher accuracy. On this basis, we simulate and comparatively analyze the forward and backward trajectories of an airborne balloon observed in China in 2019 using the FLEXPART model. The results demonstrate that within 11 h, FLEXPART predicts the horizontal trajectory of the balloon, with both RMSE and MAE falling within 50 km. Moreover, when it comes to the vertical direction bias within the 11 h prediction, RMSE and MAE are both below 500 m. Furthermore, trajectory bias gradually diminishes as the forecast time increases. The combination of the sensitivity tests and the results of the actual balloon trajectory simulation confirm that the FLEXPART model is capable of predicting the airborne balloon trajectory. [ABSTRACT FROM AUTHOR]

Sources of moisture-feeding for the incipient tropical cyclones (TCs) over the Bay of Bengal (BoB) are least explored. Using a three-dimensional Lagrangian model running with NCEP-FNL data, the present work identified various source locations and major transport routes that contributed moisture to pre- and post-monsoon TCs genesis (TCG) over the BoB. The clustered mean trajectories identified using the k-means method demonstrated that moisture transport towards the TCG region during pre-monsoon is dominated by intense low-level westerly/south-westerly trajectories propagating across the North Indian Ocean covering the Somalia coast and the Arabian Sea. Meanwhile, during post-monsoon, north-easterly/easterly trajectories are more prevalent and bring moisture to the BoB TCG region from the South China Sea and North-West Pacific. Moreover, the study highlights the spatiotemporal variations of moisture uptake (MU) pattern and its contribution and demonstrates that robust MU with a contribution of 20–90% occurs locally before three days of TCG. Meanwhile, remote sources contribute a moisture amount of ≤ 20%. Furthermore, the composite analysis of different diagnostic parameters confirms that identified MU at the local scale is attributed to an evaporation process in association with a dynamic uplifting mechanism caused by an anomalous cyclonic circulation, which provides moisture for TCG, while the horizontal advection is the mechanism, which gradually builds moisture required for the TCG from the remote sources. [ABSTRACT FROM AUTHOR]

Atmospheric transport and dispersion models (ATDMs) are widely used to study and forecast pollution events. In the frame of the "Effect of Megacities on the transport and transformation of pollutants on the regional to global scales" (EMeRGe) project, ATDM forecasts were carried out to identify potential airborne sampling areas of perfluorocarbons (PFCs) emanating from controlled PFC releases. The forecasts involved short-distance transport over small-scale topographic maxima (Manilla; Philippines), short-distance transport over large-scale topographic maxima (Taipei, Taiwan) and long-distance transport over mixed topography (Nanjing, China, sampled over Taiwan). In situ aircraft measurements of PFC mixing ratios down to a few parts per quadrillion (ppqv) provide us with a unique dataset to explore the added benefits of dynamical downscaling. Transport simulations were repeated using FLEXPART driven by ERA5 and IFS meteorological data and FLEXPART-WRF with dynamically downscaled IFS data down to 1.1 km and four PBL parametrisations. Of the three cases studied, dynamical downscaling led to significant differences for the Manilla and Taipei releases that can be interpreted through changes in the modelled orographic flow regimes. The choice of PBL scheme also significantly impacted accuracy, but there was no systematically better-performing option, highlighting the benefits of ensemble forecasting. Results show how convergence and divergence between ensemble members can be utilised to help decision-making during field campaigns. This study highlights the role that dynamical downscaling can play as an important component in campaign planning when dealing with observations over orographically complex areas. [ABSTRACT FROM AUTHOR]

We integrated Enviro-HIRLAM (Environment-High Resolution Limited Area Model) meteorological output into FLEXPART (FLEXible PARTicle dispersion model). A FLEXPART simulation requires meteorological input from a numerical weather prediction (NWP) model. The publicly available version of FLEXPART can utilize either ECMWF (European Centre for Medium-range Weather Forecasts) Integrated Forecast System (IFS) forecast or reanalysis NWP data, or NCEP (U.S. National Center for Environmental Prediction) Global Forecast System (GFS) forecast or reanalysis NWP data. The primary benefits of using Enviro-HIRLAM are that it runs at a higher resolution and accounts for aerosol effects in meteorological fields. We compared backward trajectories generated with FLEXPART using Enviro-HIRLAM (both with and without aerosol effects) to trajectories generated using NCEP GFS and ECMWF IFS meteorological inputs, for a case study of a heavy haze event which occurred in Beijing, China in November 2018. We found that results from FLEXPART were considerably different when using different meteorological inputs. When aerosol effects were included in the NWP, there was a small but noticeable difference in calculated trajectories. Moreover, when looking at potential emission sensitivity instead of simply expressing trajectories as lines, additional information, which may have been missed when looking only at trajectories as lines, can be inferred.

Water vapour is a critical component of the hydrological cycle and plays a key role in climate systems and water resources on the Tibetan Plateau (TP). However, the effect of water vapour on extreme precipitation during the snow season over the TP, where snow cover is widespread, has not been determined. In this study, we investigated the water vapour contributions from extreme precipitation events during the snow season from 1980 to 2017 in four subregions of the TP using the flexible particle dispersion method. We divided the TP into four regions: the northeastern TP (NETP), northwestern TP (NWTP), southeastern TP (SETP) and southwestern TP (SWTP). The water vapour contributions from extreme precipitation among the four subregions were clearly different. The most important water vapour area that contributed the most water vapour to extreme precipitation over the NETP was from local contributions; nevertheless, Central Asia contributed the most water vapour to the NWTP. Water vapour from the Arabian Sea and Bay of Bengal (ASBB) dominantly controlled extreme precipitation in the SETP at a ratio of 45% and in the SWTP at a ratio of 72.9%. The water vapour contribution from the ASBB was significantly correlated with the extreme precipitation occurring in the TP subregions during the snow season in comparison to that of non‐extreme precipitation. These results could improve the understanding of water vapour cycle differences across the interior TP; additionally, our study provides a theoretical reference for the relationship between the snow distribution and water vapour sources in the TP. [ABSTRACT FROM AUTHOR]

A rare event of mixed biomass-burning and polluted dust aerosols was observed over Athens, Greece (37.9° N, 23.6° E), during 21–26 May 2014. This event was studied using a synergy of a 6-wavelength elastic-Raman-depolarization lidar measurements, a CIMEL sun photometer, and in situ instrumentation. The FLEXPART dispersion model was used to identify the aerosol sources and quantify the contribution of dust and black carbon particles to the mass concentration. The identified air masses were found to originate from Kazakhstan and Saharan deserts, under a rare atmospheric pressure system. The lidar ratio (LR) values retrieved from the Raman lidar ranged within 25–89 sr (355 nm) and 35–70 sr (532 nm). The particle linear depolarization ratio (δaer) ranged from 7 to 28% (532 nm), indicating mixing of dust with biomass-burning particles. The aerosol optical depth (AOD) values derived from the lidar ranged from 0.09–0.43 (355 nm) to 0.07–0.25 (532 nm). An inversion algorithm was used to derive the mean aerosol microphysical properties (mean effective radius (reff), single scattering albedo (SSA), and mean complex refractive index (m)) inside selected atmospheric layers. We found that reff was 0.12–0.51 (±0.04) µm, SSA was 0.94–0.98 (±0.19) (at 532 nm), while m ranged between 1.39 (±0.05) + 0.002 (±0.001)i and 1.63 (±0.05) + 0.008 (±0.004)i. The polarization lidar photometer networking (POLIPHON) algorithm was used to estimate the vertical profile of the mass concentration for the dust and non-dust components. A mean mass concentration of 15 ± 5 μg m−3 and 80 ± 29 μg m−3 for smoke and dust was estimated for selected days, respectively. Finally, the retrieved aerosol microphysical properties were compared with column-integrated sun photometer CIMEL data with good agreement. [ABSTRACT FROM AUTHOR]

The climate of Southwest China is wet all year round， but the frequent drought disasters in recent years have caused huge economic losses such as crop yield reduction and forest fire.In order to fully understand the anomalies of water vapor transport in drought years in Southwest China and provide reference for early warning of drought disasters in this area in the future， this study used TRMM and APHRODITE precipitation data to analyze the interannual variation of precipitation and the interannual variation of precipitation in various seasons in Southwest China from 1998 to 2019， selected the summer dry year （2011）， autumn dry year （2009） and 2008， which were relatively wet in summer and autumn.Using Lagrangian transport model FLEXPART， we tracked the paths of water vapor transport and water vapor sources in the two extreme dry seasons （the autumn of 2009 and the summer of 2011）， and compared with the summer and autumn of the wet year （2008）， respectively.The results showed that： （1） The paths of water vapor transport in dry and wet year are consistent， and the paths in southwest China in summer can be divided into three main paths： the southwest path， the southeast path and the northwest path， among which the most dominant is the southwest path， so the main water vapor source area are the Arabian Sea——the Bay of Bengal.In autumn， the main paths can be divided into two： the southeast path and the northwest path， of which the most important is the southeast path， so the main source of water vapor is South China Sea——the Pacific Northwest.（2） There are differences in the strength of water vapor transport between dry and wet years.The reason for the drought in Southwest China in summer is that the water vapor transported by the southwest route is weak， while the reason for the drought in Southwest China in autumn is that the water vapor transported by southeast route is weak.

In the present era, national borders frequently encounter the risk and threat of unidentified airspace objects such as airborne balloons; however, there is a lack of effective methods for predicting their trajectories. To address this gap, we examine the utilization of a Lagrangian diffusion model named FLEXPART for forecasting the movement of airborne balloons. The simulation results show that when taking into account the radius of the airborne balloon, there is a potential increase of up to 1.07 km and 1.45 km in the mean absolute error (MAE) and root mean square error (RMSE), respectively, in the horizontal direction. Similarly, considering the density of the airborne balloon can also result in an increase of 3.46 km (MAE) and 4.71 km (RMSE) horizontally. Therefore, simplifying them into mass points enables FLEXPART to predict their trajectories with higher accuracy. On this basis, we simulate and comparatively analyze the forward and backward trajectories of an airborne balloon observed in China in 2019 using the FLEXPART model. The results demonstrate that within 11 h, FLEXPART predicts the horizontal trajectory of the balloon, with both RMSE and MAE falling within 50 km. Moreover, when it comes to the vertical direction bias within the 11 h prediction, RMSE and MAE are both below 500 m. Furthermore, trajectory bias gradually diminishes as the forecast time increases. The combination of the sensitivity tests and the results of the actual balloon trajectory simulation confirm that the FLEXPART model is capable of predicting the airborne balloon trajectory.

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The impact of moisture transport and sources on precipitation stable isotopes (δ18O and d‐excess) in the central Himalayas are crucial to understanding the climatic archives. However, this is still unclear due to the lack of in‐situ observations. Here we present measurements of stable isotopes in precipitation at two stations (Yadong and Pali) in the central Himalayas during 2014–2015. Combined with simulations from the dispersion model FLEXPART, we investigate effects on precipitation stable isotopes related to changes in moisture sources and convections in the region, and possible influence by El Niño. Our results suggest that the moisture supplies related to evaporation over northeastern India and moisture losses related to convective activities over the Bay of Bengal (BoB) and Bangladesh region play important roles in changes in δ18O and d‐excess in precipitation in the Yadong Valley. Outgoing longwave radiation and moisture flux divergence analysis further confirm that the contribution from continental evaporation dominates the moisture supply in the central Himalayas with a lesser contribution from convection over the BoB during the 2015 monsoon season compared with 2014. A change in the altitude effect is observed in 2015, which is more significant than the temperature and precipitation amount effect during the observation period. These findings provide valuable insights into climatic interpretations of paleo‐isotopic archives with an isotopic response to changes in moisture transport to the central Himalayas. Plain Language Summary: Evaporation, convection, temperature, topography, large‐scale circulation (Indian summer monsoon and westerlies), and large‐scale modes (e.g., El Niño Southern Oscillation) all play roles in precipitation variability in the Himalayas. Influences of processes related to these factors are not well understood, and therefore difficult to interpret climatic signals in paleo‐climate records. Stable isotopes in precipitation are useful tools to trace different moisture sources and convective activities along the transport. Therefore, we present measurements of stable isotopes in precipitation at two stations in the central Himalayas during 2014 and 2015 to estimate changes in moisture sources and convection. To do so, we also use the dispersion model FLEXPART to diagnose changes in moisture supplies and losses along transports during 2015 compared to 2014. We found that there is less moisture supply from the Bay of Bengal in 2015, and more from the Indian continent with spatiotemporal variations. Key Points: Direct measurements of event‐based δ18O and d‐excess in precipitation in the central Himalayas in the 2015 monsoon season compared to 2014Combination of in‐situ isotopic measurements with simulations of evaporation minus precipitation using FLEXPARTIsotopic variations in precipitation are associated with changes in moisture supplies along the transport path [ABSTRACT FROM AUTHOR]

The Horn of Africa drylands (HAD) are among the most vulnerable regions to hydroclimatic extremes. The two rainfall seasons—long and short rains—exhibit high intraseasonal and interannual variability. Accurately simulating the long and short rains has proven to be a significant challenge for the current generation of weather and climate models, revealing key gaps in our understanding of the drivers of rainfall in the region. In contrast to existing climate modeling and observation‐based studies, here we analyze the HAD rainfall from an observationally‐constrained Lagrangian perspective. We quantify and map the region's major oceanic and terrestrial sources of moisture. Specifically, our results show that the Arabian Sea (through its influence on the northeast monsoon circulation) and the southern Indian Ocean (via the Somali low‐level jet) contribute ∼80% of the HAD rainfall. We see that moisture contributions from land sources are very low at the beginning of each season, but supply up to ∼20% from the second month onwards, that is, when the oceanic‐origin rainfall has already increased water availability over land. Further, our findings suggest that the interannual variability in the long and short rains is driven by changes in circulation patterns and regional thermodynamic processes rather than changes in ocean evaporation. Our results can be used to better evaluate, and potentially improve, numerical weather prediction and climate models, and have important implications for (sub‐)seasonal forecasts and long‐term projections of the HAD rainfall. Plain Language Summary: The drylands in the Horn of Africa (HAD) have suffered a series of droughts in recent years with the consecutive failure of both the major rainfall seasons. So far, the rainfall in this region has been studied using observations and outputs from global climate models. In contrast, here, we employ a moisture tracking model, which traces individual parcels of moisture‐carrying air parcels from their destination (the HAD region) to their sources (land areas within and outside the HAD, and the oceans). We find that the majority of the moisture which causes rainfall in the HAD region comes from the oceans. However, in recent years, we see that land contributions are gaining importance in affecting water availability in the region. Key Points: Indian Ocean contributes majority of the moisture to rainfall in the Horn of Africa drylandsThe role of vegetation and land contribution to rainfall during the short rains is increasingMoisture contributions are driven more by atmospheric circulation changes rather than increased evaporation from source regions [ABSTRACT FROM AUTHOR]

As two of the most important products of the combustion process, carbon dioxide (CO _2 ) and carbon monoxide (CO) are commonly used as tracers for combustion source assignment. Their relationship will help to better understand the regional carbon cycle and assess climate forcing effects. In this study, mixing ratios of CO _2 and CO were continuously measured using a Picarro gas concentration analyzer at the Atmospheric Boundary Layer Eco-Environmental Shanghuang Observatory, Chinese Academy of Sciences (ABLECAS) throughout 2022–2023. The variability of the mixing ratio of CO to CO _2 (ΔCO/ΔCO _2 ) in a 1 h time interval was calculated based on linear slope analysis after background values were determined and subtracted. The results showed that the mixing ratio of CO had a clear seasonal variability with a moderate increase in the spring (249.1 ± 59.6 part per billion (ppb)) and winter (257.8 ± 90.3 ppb), mostly due to more frequent transport from north of the Yangtze River. ΔCO/ΔCO _2 at the ABLECAS varied with air mass origin, with a linear slope 0%–1% on a 1 h basis. Relatively high ΔCO/ΔCO _2 values for an air mass from the north in the winter indicate that the emission sources had lower combustion efficiency. In summer, the ΔCO/ΔCO _2 ratio mostly reflected the background conditions for air masses from marine areas. The potential source regions and contribution assignments were evaluatedat the ABLECAS according to source–receptor relationship analysis using the FLEXPART model with CO as a pollutant tracer from 2015 to 2023. We found that the footprint of an air mass had a clear transition period between 2018 and 2019, and a synoptic anomaly, related to Arctic Oscillation strength and west Pacific subtropical high position, plays a key role in influencing the pollutant transport patterns. This study provides a scientific basis for the formulation of air quality regulation policy, and helps to implement the national carbon neutralization strategy.

In this article, we focus on studying the nexus between moisture transport deficit and drought occurrence in nine key regions across the world where the magnitude of meteorological drought is projected to increase from 1850 to 2100 under a high anthropogenic emission scenario. These regions are central America, southwestern South America, northern Brazil, the Amazon, northeastern Brazil, the western Mediterranean, southern Africa, the eastern Mediterranean, and southwestern Australia. Using the Lagrangian particle dispersion model FLEXPART, we identify the specific moisture sources of the regions (the own region, the nearby continental source and the oceanic sources) and obtain their contributions to the precipitation in the regions for the period 1980–2018. For each region and specific moisture source, the conditional probability of meteorological drought occurrence given an equivalent contribution deficit from the source is estimated using copula models, a statistical methodology that allows us to capture complex relationships between variables. We identify the dominant moisture source in each region, which is the source for which the contribution deficit maximises drought probability. A variety of cases are found: in three regions, the dominant source is the region itself, in one region, it is the nearby terrestrial source, and in five regions, it is an oceanic source. In general, contribution deficits from specific moisture sources are associated with only slightly greater drought probabilities than those from major global moisture sources. We also reveal that the source that contributes the most to precipitation in a given region is not necessarily the dominant source of drought in the region. These results highlight the importance of understanding the role of dominant moisture sources and moisture transport deficits on meteorological drought occurrence at a regional scale.

The first rainy season (April–May–June) extreme precipitation events over South China tend to frequently occur in specific hotspots, resulting in a great threat to local society and economy. Abundant moisture supply is essential to precipitation formation. In this study, we employ the FLEXPART model to investigate the geographical moisture sources for extreme precipitation events in three hotspots of Guangdong from west to east (termed as Area‐A, B, and C). During both the periods before and after the onset of the South China Sea Summer Monsoon (hereafter SCSSM), the moisture contributions of ocean regions are larger than that of land regions for all the hotspots, but the main moisture source regions are different. Before the onset of SCSSM, the main source regions are South China Sea and Southeastern Asia, which contribute 36.50 and 31.79% to Area‐A, 35.85 and 27.83% to Area‐B, while 42.27 and 23.81% to Area‐C, respectively. After the onset of SCSSM, the contribution of moisture from Indian Ocean increases a lot. Thus, the main source regions are Indian Ocean, Southeastern Asia and South China Sea, which contribute 31.52, 24.58 and 18.13% to Area‐A, 29.21, 21.82 and 14.99% to Area‐B, 26.62, 20.70%, and 28.19% to Area‐C, respectively. Among the three hotspots, the contribution of ocean regions for Area‐C is the largest. Southeastern Asia is the main land contributor before and after the onset of SCSSM for all the hotspots. This study implies the important role of both ocean and land moisture sources on extreme precipitation variations over South China. [ABSTRACT FROM AUTHOR]

New Nuclear Power Plant (NPP), which is under construction in El Dabaa, Egypt, is expected to start working within few years. Such project should be associated with several scientific research works. The suitability of the NPP location as well as the assessment of the impact of its routine work and accidental failure is among the points that should be addressed. In this work, the contamination risks due to uniform accidental leakage of the radioactive aerosol C 137 s that continues for eight hours is studied. FLEXPART version 10.4 at high resolution (55 km) is applied using six-hour NCEP FNL (1° × 1°) gridded data to simulate the dispersion and deposition of C 137 s for the subsequent five days. This process is repeated each day for the period of 2008 to 2018. It is shown that high concentration and total deposition are observed particularly during the summer season. In addition, the consideration of different emission scenarios indicates that Egypt is expected to be strongly affected. Moreover, dispersion and concentration of the radioactive materials is notably influenced by near-surface winds. In conclusion, FLEXPART is considered as a promising tool to explore the possible nuclear hazards under a variety of meteorological conditions. Further, a future study will consider the influence of the horizontal grid spacing and lateral boundary condition using the coupled Weather Research and Forecasting (WRF)-FLEXPART system. [ABSTRACT FROM AUTHOR]

Atmospheric ozone (O3) concentration is impacted by a number of factors, such as the amount of solar radiation, the composition of nitrogen oxides (NOx) and hydrocarbons, the transport of pollutants and the amount of particulate matter in the atmosphere. The oxidative potential of the atmosphere and the formation of secondary organic aerosols (SOAs) as a result of atmospheric oxidation are influenced by the prevalent O3 concentration. The formation of secondary aerosols from O3 depends on several meteorological, environmental and chemical factors. The relationship between PM2.5 and O3 in different urban environmental regimes of India is investigated in this study during the summer and winter seasons. A relationship between PM2.5 and O3 has been established for many meteorological and chemical variables, such as RH, WS, T and NOx, for the selected study locations. During the winter season, the correlation between PM2.5 and O3 was found to be negative for Delhi and Bengaluru, whereas it was positive in Ahmedabad. The city of Bengaluru was seen to have a positive correlation between PM2.5 and O3 during summer, coinciding with the transport of marine air masses with high RH and low wind speed (as evident from FLEXPART simulations), leading to the formation of SOAs. Further, O3 concentrations are predicted using a Recurrent Neural Network (RNN) model based on the relation obtained between PM2.5 and O3 for the summer season using NOx, T, RH, WS and PM2.5 as inputs. [ABSTRACT FROM AUTHOR]

As the "water tower of Asia"， it’s of great significance to study the precipitation sources of the Qinghai-Xizang Plateau for China's water security and water resources utilization.Using the methods of diagnostic analysis and Lagrangian model simulation， a heavy rainfall in Naqu caused by the plateau vortex was analyzed and studied， the source of water vapor in the Naqu area was determined and the contribution of the water vapor source area to the summer precipitation in the study area was further quantified.The results show that there is a strong upward movement over Naqu and has good water vapor conditions.Many strong convective cloud clusters have been formed successively， forming short-term heavy precipitation.The majority of target air blocks that affect precipitation come from the relatively low atmosphere south of the target area and can be traced back to the Bay of Bengal， Arabian Sea and Indian Ocean.In addition， a small part of the target gas block in the western path of the Qinghai-Xizang Plateau comes from the middle and lower atmospheres.High-level water vapor is mainly transported by high-pressure anticyclones in South Asia.A few blocks of gas come from eastern China and the South China Sea.The transportation of water vapor along the western and southern borders is the main source of heavy precipitation in Naqu.The main sources of water vapor are the Indian Ocean， Arabian Sea， India， the Bay of Bengal， Xinjiang， and Central Asia.The water vapor from the Indian Ocean and the Arabian Sea plays a key water vapor contribution to the precipitation area， and the local water vapor contribution is negligible.

As the source of the three major rivers of Yangtze River， Yellow River and Lancang River in China， Sanjiangyuan （SJY） and its water vapor source and transportation have an important impact on the weather and climate in the downstream area.According to the summer precipitation data in the Sanjiangyuan area from 1994 to 2019， the precipitation in July showed multiple positive and negative anomaly exchange characteristics.The strongest positive anomaly was in 2012 （+1290 mm）， and the strongest negative anomaly is 2015 （-802 mm）.In this study， the FLEXPART model based on the Lagrangian method was used to simulate this abnormal precipitation period.All the air parcels that reached the source area of the target area during the study period were traced backward， focusing on the analysis of the water vapor transport characteristics and potential source of water vapor of SJY.Besides， the contribution of different water vapor sources to the precipitation of SJY was also evaluated.The results show that the water vapor transmission channels of SJY were mainly divided into the north and the south paths.During the period of positive anomalous precipitation， air parcels mainly transported from the north， west and south of the Qinghai-Xizang Plateau into SJY through the south path.While during the period of negative precipitation anomaly， air parcels mainly transported from the north side of the Qinghai-Xizang Plateau to SJY through the northern path.When the precipitation of SJY was smaller， the southern branch's transport was weaker and the northern path's transport was stronger.Among the potential water vapor sources of SJY， the most important contribution to the precipitation in SJY was on the northern side of the Qinghai-Xizang Plateau， followed by the western side of the Qinghai-Xizang Plateau and the local area， as well as the southern side of the Qinghai-Xizang Plateau， the Arabian Sea and the Bay of Bengal.The contribution of the northern side of the Qinghai-Xizang Plateau to the precipitation of SJY increased during the negative anomaly of precipitation in SJY， while the contribution rate of other water vapor sources decreased.

Water vapor sources and related transport processes are fundamental to the understanding of precipitation mechanisms. This study focuses on a typical Northeast Cold Vortex (NECV) rainstorm on July 25, 2016, which brought floods and huge economic losses to Northeast China. Using the Lagrangian flexible particle dispersion model (FLEXPART) and the areal source–receptor attribution method, the moisture sources and transport characteristics during this event were analyzed. The results show that this NECV rainstorm occurred under a favorable atmospheric circulation background, and particles in the rainstorm area mainly came from the Indo‐China Peninsula, South China Sea, Bay of Bengal, and central China at relatively low levels. The largest water vapor uptake and release were found in central China, which was the primary moisture source of this NECV precipitation. Although the Indian Subcontinent–Bay of Bengal–Indo‐China Peninsula had a higher moisture intake than the South China Sea–the Philippines, a considerable amount of moisture in the former was released during transport, making the moisture contributions of the two equivalents. Furthermore, the Northeast rainstorm area had a non‐negligible precipitation recycling process. All examined sources contributed more than 90% of the moisture in the rainstorm area. [ABSTRACT FROM AUTHOR]

The attainment of suitable ambient air quality standards is a matter of great concern for successfully hosting the XXIV Olympic Winter Games (OWG). Transport patterns and potential sources of pollutants in Zhangjiakou (ZJK) were investigated using pollutant monitoring datasets and a dispersion model. The PM2.5 concentration during February in ZJK has increased slightly (28%) from 2018 to 2021, mostly owing to the shift of main potential source regions of west-central Inner Mongolia and Mongolian areas (2015–18) to the North China Plain and northern Shanxi Province (NCPS) after 2018. Using CO as an indicator, the relative contributions of the different regions to the receptor site (ZJK) were evaluated based on the source-receptor-relationship method (SRR) and an emission inventory. We found that the relative contribution of pollutants from NCPS increased from 33% to 68% during 2019–21. Central Inner Mongolia (CIM) also has an important impact on ZJK under unfavorable weather conditions. This study demonstrated that the effect of pollution control measures in the NCPS and CIM should be strengthened to ensure that the air quality meets the standard during the XXIV OWG. [ABSTRACT FROM AUTHOR]

Lidar measurements of 11 smoke layers recorded at Măgurele, Romania, in 2014, 2016, and 2017 are analyzed in conjunction with the vegetation type of the burned biomass area. For the identified aerosol pollution layers, the mean optical properties and the intensive parameters in the layers are computed. The origination of the smoke is estimated by the means of the HYSPLIT dispersion model, taking into account the location of the fires and the injection height for each fire. Consequently, for each fire location, the associated land cover type is acquired by satellite-derived land cover products. We explore the relationship between the measured intensive parameters of the smoke layers and the respective land cover of the burned area. The vegetation type for the cases we analyzed was either broadleaf crops or grasses/cereals. Overall, the intensive parameters are similar for the two types, which can be associated with the fact that both types belong to the broader group of agricultural crops. For the cases analyzed, the smoke travel time corresponding to the effective predominant vegetation type is up to 2.4 days. [ABSTRACT FROM AUTHOR]

Abstract Water vapor sources and related transport processes are fundamental to the understanding of precipitation mechanisms. This study focuses on a typical Northeast Cold Vortex (NECV) rainstorm on July 25, 2016, which brought floods and huge economic losses to Northeast China. Using the Lagrangian flexible particle dispersion model (FLEXPART) and the areal source–receptor attribution method, the moisture sources and transport characteristics during this event were analyzed. The results show that this NECV rainstorm occurred under a favorable atmospheric circulation background, and particles in the rainstorm area mainly came from the Indo‐China Peninsula, South China Sea, Bay of Bengal, and central China at relatively low levels. The largest water vapor uptake and release were found in central China, which was the primary moisture source of this NECV precipitation. Although the Indian Subcontinent–Bay of Bengal–Indo‐China Peninsula had a higher moisture intake than the South China Sea–the Philippines, a considerable amount of moisture in the former was released during transport, making the moisture contributions of the two equivalents. Furthermore, the Northeast rainstorm area had a non‐negligible precipitation recycling process. All examined sources contributed more than 90% of the moisture in the rainstorm area.

The TRansport Of water VApor (TROVA) software, developed in Python and Fortran for the study of moisture sources and sinks, is presented here. TROVA includes the main Lagrangian methodologies established in the literature, using outputs from the global FLEXible PARTicle dispersion model and the regional FLEXPART-WRF model at different spatial resolutions. TROVA will benefit users investigating the physics of the atmosphere and fields associated with this branch in the study of current and future changes in source–sink moisture relationships and their link with mean and extreme precipitation.

An increase in the frequency of wildfire occurrence is predicted in all climate model estimates, implying significant health impacts, due to the emission of combustion products. Application of pollutant dispersion models at strategic and operational levels is imperative for safety reasons and for compliance with European Civil Protection Mechanism policies. Here, we describe the dispersion of smoke from the forest fire of Penteli-Attica (Greece) on 19 July 2022, which burnt a total area of 2781.7 hectares. High-resolution dispersion simulations, air-quality measurements, and remote sensing observations are used to describe the transport of smoke and facilitate effective smoke control in areas where air quality impacts are likely to be significant.

Moisture transport, associated with moisture sources and synoptic‐scale weather conditions, is a key dynamic process of precipitation events. Using the K‐means clustering method and the FLEXPART Lagrangian particle dispersion model, this paper investigates moisture contributions from different source regions to extreme precipitation in the first rainy season (hereafter FRS) over South China. In average, land regions contribute more to the FRS extreme precipitation over South China than the ocean regions. The main source regions are Southeast Asia (22.7%), South China (17.2%), the South China Sea (14.3%), and the Bay of Bengal (8.3%). Extreme precipitation events are classified into three types by the K‐means clustering based on 850 hPa geopotential height, which are all characterized by an anomalous low‐pressure system over South China with varying intensity and locations. The distribution of geopotential height anomaly for Type I (30.3%) is characterized the low trough extending from Japan to South China, while Type II (42.5%) and Type III (27.2%) are characterized by "west negative–east positive" and "north positive–south negative" patterns over East Asia with anomalous cyclone over South China, respectively. The much larger contribution of land sources than ocean regions are mainly concentrated in Type I and Type III, of which the contribution from each source region is similar. Ocean sources play a more important role in Type II and are mainly from the Indian Ocean (16.2%) associated with the onset of South China Sea summer monsoon. [ABSTRACT FROM AUTHOR]

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Copyright of Plateau Meteorology is the property of Plateau Meteorology Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

New Nuclear Power Plant (NPP), which is under construction in El Dabaa, Egypt, is expected to start working within few years. Such project should be associated with several scientific research works. The suitability of the NPP location as well as the assessment of the impact of its routine work and accidental failure is among the points that should be addressed. In this work, the contamination risks due to uniform accidental leakage of the radioactive aerosol C137s that continues for eight hours is studied. FLEXPART version 10.4 at high resolution (55 km) is applied using six-hour NCEP FNL (1° × 1°) gridded data to simulate the dispersion and deposition of C137s for the subsequent five days. This process is repeated each day for the period of 2008 to 2018. It is shown that high concentration and total deposition are observed particularly during the summer season. In addition, the consideration of different emission scenarios indicates that Egypt is expected to be strongly affected. Moreover, dispersion and concentration of the radioactive materials is notably influenced by near-surface winds. In conclusion, FLEXPART is considered as a promising tool to explore the possible nuclear hazards under a variety of meteorological conditions. Further, a future study will consider the influence of the horizontal grid spacing and lateral boundary condition using the coupled Weather Research and Forecasting (WRF)-FLEXPART system.

Atmospheric ozone (O3) concentration is impacted by a number of factors, such as the amount of solar radiation, the composition of nitrogen oxides (NOx) and hydrocarbons, the transport of pollutants and the amount of particulate matter in the atmosphere. The oxidative potential of the atmosphere and the formation of secondary organic aerosols (SOAs) as a result of atmospheric oxidation are influenced by the prevalent O3 concentration. The formation of secondary aerosols from O3 depends on several meteorological, environmental and chemical factors. The relationship between PM2.5 and O3 in different urban environmental regimes of India is investigated in this study during the summer and winter seasons. A relationship between PM2.5 and O3 has been established for many meteorological and chemical variables, such as RH, WS, T and NOx, for the selected study locations. During the winter season, the correlation between PM2.5 and O3 was found to be negative for Delhi and Bengaluru, whereas it was positive in Ahmedabad. The city of Bengaluru was seen to have a positive correlation between PM2.5 and O3 during summer, coinciding with the transport of marine air masses with high RH and low wind speed (as evident from FLEXPART simulations), leading to the formation of SOAs. Further, O3 concentrations are predicted using a Recurrent Neural Network (RNN) model based on the relation obtained between PM2.5 and O3 for the summer season using NOx, T, RH, WS and PM2.5 as inputs.

The Chernobyl Nuclear Power Plant (NPP) catastrophe of 1986 has been a milestone in the use of nuclear power for energy generation. After the accident, various topics have been discussed to evaluate the details of occurrence of the event and to understand its impacts on human, animal and plant life. One of the most controversial topics is the release height and homogeneity of radionuclides at release point in the atmosphere. Currently, there exists no definitive decision on the release height and vertical distribution pattern of radionuclides released from the Chernobyl accident. Based on this premise, this study focuses on the analysis of various possible release patterns along the vertical dimension and the potential influences on the atmospheric dispersion and total deposition with particular reference to 137Cs. For this purpose, some release pattern functions following uniform, Dirac delta, exponential, log-Pearson type III, and cumulative distribution functions along the z-axis were used to simulate the dispersion of 137Cs released from the accident site. A total of 22 release patterns are produced using different maximum release heights (2000, 3000, and 4000 m). A Lagrangian particle dispersion model, FLEXPART, was then used to conduct simulations for these conditions to assess most coherent dispersion and deposition patterns. Model results from each release function were plotted, compared with each other and verified with measured data. In the functions where the release predominantly existed at lower levels, more extreme values were observed in the close vicinity of the source. Consequently, Dirac delta, log-Pearson type III (1), and exponential functions can be used as worst-case conditions at local scale. On the other hand, simulations also revealed that contamination spread to wider areas in cases where the release occurred from higher levels of the atmosphere. Therefore, log-Pearson type III (2) and cumulative distribution function can be considered more significant concerning a wider distribution of affected areas. [ABSTRACT FROM AUTHOR]

The boreal biome plays an important role in the global carbon cycle. However, current estimates of its sink‐source strength and responses to changes in climate are primarily derived from models and thus remain uncertain. A major challenge is the validation of these models at a regional scale since empirical flux estimates are typically confined to ecosystem or continental scales. The Integrated Carbon Observation System (ICOS)‐Svartberget atmospheric station (SVB) provides observations including tall tower eddy covariance (EC) and atmospheric concentration measurements that can contribute to such validation in Northern Sweden. Thus, the overall aim of this study was to quantify the carbon balance in Northern Sweden region by integrating land‐atmosphere fluxes and atmospheric carbon dioxide (CO2) concentrations. There were three specific objectives. First, to compare flux estimates from four models (VPRM, LPJ‐GUESS, ORCHIDEE, and SiBCASA) to tall tower EC measurements at SVB during the years 2016–2018. Second to assess the fluxes' impact on atmospheric CO2 concentrations using a regional transport model. Third, to assess the impact of the drought in 2018. The comparison of estimated concentrations with ICOS observations helped the evaluation of the models' regional scale performance. Both the simulations and observations indicate there were similar reductions in the net CO2 uptake during drought. All the models (except for SiBCASA) and observations indicated the region was a net carbon sink during the 3‐year study period. Our study highlights a need to improve vegetation models through comparisons with empirical data and demonstrate the ICOS network's potential utility for constraining CO2 fluxes in the region. Plain Language Summary: As the largest global carbon sink, the boreal region can play an important role in climate mitigation strategies. Thus, it is important to estimate the region's sink strength properly. However, due to limitations in measurement techniques at the regional scale, the sink strength estimates are often obtained from models, which require robust validation. Therefore, we combined flux and atmospheric concentration data from one of the stations in Northern Europe to validate estimates generated using four vegetation models. We also used a transport model to connect the fluxes to atmospheric concentration dynamics, then compared the modeled CO2 concentration patterns with observations to provide a regional scale validation of the vegetation models. These observed and modeled fluxes and concentrations are also used to investigate the impact of the 2018 drought over Nordic vegetation. We find that the 2018 European drought had only limited impact on the carbon fluxes over Northern Sweden. Both the modeling and measurements show that the study region was a carbon sink during the study period (2016–2018), with some variation in estimates from the four models. Key Points: Northern Sweden region was a carbon sink in the years 2016–2018 according to vegetation model estimates and observationsBoth concentration and flux measurements suggest 2018 drought had limited impact on the Nordic carbon balanceEmpirical measurements can improve vegetation models by integrating them into model simulations at site and regional scaleHowever, annual net ecosystem exchange values generated by the models varied between −275 and −25 gC m−2 year−1 [ABSTRACT FROM AUTHOR]

The summer of 2020 recorded a record-breaking flood due to excessive mei-yu rain falling over the Yangtze River Valley (YRV). Using the Lagrangian model FLEXPART, this paper investigates moisture sources and transport processes behind this extreme event. Based on climate data from 1979 to 2019, the air-particle (an infinitesimally small air parcel) trajectories reaching the YRV show sectors that correspond to five main moisture sources: the Indian monsoon region (IND, 27.5% of the total rainfall), the local evaporation (27.4%), the Western Pacific Ocean (WPO, 21.3%), the Eurasian continent (8.5%) and Northeast Asia (4.4%). In the 2020 mei-yu season, moisture from all source regions was above normal except that from Northeast Asia. A record-breaking moisture source from the IND and WPO dominated this extreme mei-yu flood in 2020, which was 1.5 and 1.6 times greater than the climate mean, respectively. This study reveals a significant relationship between the moisture source with three moisture transport processes, i.e., trajectory density, moisture content, and moisture uptake of air-particles. A broad anomalous anticyclonic circulation over the Indo-Northwestern Pacific (Indo-NWP) provides a favorable environment to enhance the moisture transport from the IND and WPO into the YRV. In the 2020 mei-yu season, a record-breaking Indo-NWP anomalous anticyclonic circulation contributed to a higher trajectory density as well as higher moisture content and moisture uptake of air-particles from the IND and WPO regions. This collectively resulted in unprecedented moisture transport from source origins, thus contributing to the mei-yu flood over the YRV in 2020. [ABSTRACT FROM AUTHOR]

Based on the output data from the Lagrangian flexible particle dispersion model (FLEXPART), we analyze the pathways of moisture to identify the moisture source areas for extreme precipitation in the summer half-year (April–September) over northern and southern Xinjiang, respectively. For both northern and southern Xinjiang, the local evaporation plays a decisive role for extreme precipitation in the summer half-year, of which contribution ratio accounts for 24.5% to northern Xinjiang and 30.2% to southern Xinjiang of all identified source areas. In addition, central Asia and northwestern Asia are the major moisture source areas as well and contribute similarly to extreme precipitation relative to local evaporation. For northern Xinjiang, central Asia surpasses northwestern Asia, and each of them contributes 24.1 and 18.8%, whereas northwestern Asia is somewhat more crucial than central Asia for southern Xinjiang, accounting 22.1 and 19.1%, respectively. Note that the three top-ranked moisture source areas make up a large proportion of total sources. Regarding the remaining source areas that also provide moisture, the contributions are entirely different for southern and northern Xinjiang. Originating from the North Atlantic Ocean, Europe, and the Mediterranean Sea, some water vapor enters northern Xinjiang and converge to precipitate, while this process is barely detectable for extreme precipitation over southern Xinjiang, which is affected by the westerly flow. On the contrary, the Arabian Sea, the Arabian Peninsula, and the Indian Peninsula contribute, even though slightly, to extreme precipitation over southern Xinjiang, which indicates that the meridional transport pathways from the Arabian Sea can carry moisture to this inland region.

In September 2017, numerous measurement stations recorded large surface concentrations of Ru 106 in Europe. This event was well recorded by various monitoring stations worldwide and offer a valuable framework to compare the modelling strategies deployed to quickly evaluate where the plume goes and with what concentrations. In general, the source and its intensity are not known and hypotheses have to be done. Models have to be fast and accurate: Lagrangian and Eulerian are often used but rarely compared. In this study, the FLEXPART Lagrangian model and the WRF-CHIMERE Eulerian models are used to simulate the emissions, transport and deposition of this source of Ru 106. First, it is shown that the hypothesis of location, timing and intensity of the source is realistic, by comparison to surface measurements. Second, sensitivity analysis performed with the Eulerian model and several transport scheme showed that this model may provide better results than the Lagrangian one. It opens the door to further development, including chemistry and mixing with other pollutants during these specific events. • Long range atmospheric transport in CHIMERE and FLEXPART models yield similar behaviors. • Numerous worldwide measurements allowed the comparison of CHIMERE and FLEXPART at various ranges. • Confusion matrices indicate that CHIMERE performs overall better than FLEXPART on this case. • Numerical diffusion in CHIMERE can be reduced with newly implemented numerical transport schemes. • Conjoint use of both CHIMERE and FLEXPART could be beneficial in future work. [ABSTRACT FROM AUTHOR]

Evidence indicates that the densely cultivated region of northeastern China acts as a source for the wind-borne agent of Kawasaki disease (KD). KD is an acute, coronary artery vasculitis of young children, and still a medical mystery after more than 40 y. We used residence times from simulations with the flexible particle dispersion model to pinpoint the source region for KD. Simulations were generated from locations spanning Japan from days with either high or low KD incidence. The postepidemic interval (1987-2010) and the extreme epidemics (1979, 1982, and 1986) pointed to the same source region. Results suggest a very short incubation period (

Soil dusts are an important source of aerosol in agricultural regions and can affect the Earth's radiation budget through the modification of cloud properties, and in particular, through their ability to act as ice nucleating particles. In order to impact cloud properties, agricultural soil dusts need to be transported from the point of emission to cloud‐relevant altitudes. Vertical transport within the planetary boundary layer is strongly controlled by turbulence and is challenging to represent accurately in regional and global models. Large‐eddy simulations (LES) are run at resolutions capable of resolving most of the turbulent energy directly and can thus better simulate vertical transport. In this study, we leverage the LES ARM Symbiotic Simulation and Observation (LASSO) large‐eddy simulations to simulate vertical transport of agricultural dust within the turbulent boundary layer using a modified version of the stochastic dispersion model FLEXPART‐WRF. We find that the modified model is better capable of simulating particle transport due to turbulence, and that particle size was the greatest factor in determining particle lifetime. Individual meteorology and particle density had intermediate effects upon particle transport, while release height had little effect upon simulation results. Finally, we utilize a quasi‐single column model (QSCM) approach to determine how our results compare to a parameterized treatment of turbulence. The QSCM simulations led to greater tracer transport out of the boundary layer, with ramifications for any studies utilizing a Lagrangian stochastic model to understand tracer dispersion. These results highlight the importance of accurately simulating turbulence for understanding particle transport. Key Points: FLEXPART‐WRF is modified in order to better simulate turbulence and vertical transport of tracers using large eddy simulationsSensitivity studies show that size is the greatest factor affecting particulate vertical transportParameterized representations of turbulence may overestimate particle transport and lifetime compared to resolved simulations [ABSTRACT FROM AUTHOR]

Using the Lagrangian model FLEXPART and the quantitative method WaterSip, moisture sources of summer (June–July–August) precipitation over eastern China are investigated for the period 1979–2009 in this study. It is found that the Indochinese Peninsula plus southern China, the South China Sea, the northwestern Pacific Ocean, the Asian continent, and the Bay of Bengal are the major moisture sources in our results, and the moisture from eastern China, the Arabian Sea, and the Indian subcontinent also has minor contributions. Note that the contribution of the oceanic sources substantially surpasses that of the continental sources, and the contributions of sources exhibit interannual variations during 1979–2009, especially in the Indochinese Peninsula plus southern China, the South China Sea, the northwestern Pacific Ocean, the Asian continent, and the Bay of Bengal. Moreover, moisture sources have evident monthly variations and seasonal cycle features, which are responsible for supplying moisture to precipitating over eastern China in the different monsoonal periods. In addition, the major moisture sources for different intensities of precipitation over eastern China vary considerably; for light and moderate precipitation, a great amount of moisture originates from the local and northwestern continental regions and eastern oceanic regions adjacent to eastern China, while more moisture comes from southwestern oceanic sources and the surrounding continental regions of them for heavy precipitation. [ABSTRACT FROM AUTHOR]

In this study, the Flexible Particle Dispersion Model (FLEXPART) is employed to simulate the trajectories of global air parcels from March 1979 to February 2018 to analyse the moisture sources of precipitation over Xinjiang in China. The results show that more than 90% of the moisture can be tracked when the backtracking time is set to 10 days. There are three similar moisture transport paths in winter and summer, namely, the Mediterranean–Caspian Sea–Balkhash Lake path, the Eastern European Plain–Western Siberian Plain–Balkhash Lake path, and the Arabian Peninsula–Iranian Plateau–Pamir Plateau path. Besides, there is one more path in summer: the Indian Ocean–Indian Peninsula–Pamir Plateau. The paths of moisture transport in spring (autumn) are similar to those in winter (summer). In summer, the contribution rate of Xinjiang itself and Central Asia accounts for more than 80%, among which the local contributions account for 52%. In the other three seasons, Xinjiang, Central Asia, North Africa–Arabian Peninsula, and South Asia are the main sources of moisture. The contribution rates of moisture uptake in the source regions other than Central Asia vary greatly with the seasons. The interannual variation of contribution rate to precipitation of each source region is limited. Regionally, the moisture source distribution for southern Xinjiang resembles those of the whole Xinjiang; for the northern Xinjiang, the contribution of Central Asia becomes more important. [ABSTRACT FROM AUTHOR]

In this article, we formulate Monin–Obukhov similarity theory (MOST)-based relationships, for normalized standard deviations of wind velocity components under the local scaling framework, and investigate their applicability under stable and highly stable atmospheric conditions. We used the fast response data collected using an ultrasonic anemometer over a flat terrain of Kalpakkam in India and a complex hilly terrain at Cadarache, France, for arriving at these formulations. The study shows that after filtering of the submesoscale motions from the sonic anemometer data, the turbulence diffusion relationships follow local scaling, under stable conditions. The study further indicates that these relationships follow similar behavior for the sites taken for this study. At neutral conditions, the values of the scaled standard deviations are found to be 1.9 ± 0.07, 1.8 ± 0.06 and 1.3 ± 0.02, for longitudinal, crosswind and vertical component, respectively, for the complex terrain and 1.8 ± 0.03, 1.9 ± 0.06 and 1.1 ± 0.04, respectively, for the flat terrain. The research also investigates the effect of the new diffusion relationships in simulating atmospheric dispersion, using the Lagrangian particle dispersion model FLEXPART-WRF. Simulations using these new diffusion relationships show a higher dose estimate relative to the model default Hanna's method, in the case of radioactivity dispersion. Detailed comparisons of the simulated dose rate estimates against measurements using Environmental Radiation Monitors (ERM) indicate that the new relationships give better correlation (r2 = 0.62) under stable conditions over model default relationships (r2 = 0.50). [ABSTRACT FROM AUTHOR]

Sulphur dioxide is a toxic pollutant in the atmosphere emitted from natural sources and human activities. Normally, SO2 has a life-time of about 2 days in the atmosphere and is not transported to long distances from its source region. However, under favourable circumstances such as low humidity or high wind speed, it can travel intercontinental distances from the point of emission. In this article, we have analysed the surface mixing-ratio of SO2 measured over the time period from January 2010 to April 2012 at a rural region in south India. It is found that SO2 mixing-ratio is very low over this region with an annual mean value in the range of 0.21–0.24 ppbv. OMI satellite estimates an annual mean value of 0.5 Dobson Units (DU) over the same location and period. However, during January to May relatively higher concentrations of SO2 are observed, mainly coming from power plants located in southern and eastern India as indicated by higher SO2/NO2 ratios of greater than 0.5. In one instance, on June 20th, 2011, it is found that the OMI SO2 value was a factor of 13 higher than 2011 annual mean at Gadanki. Using the FLEXible PARTicle dispersion model (FLEXPART) and satellite data, it is found that the observed higher SO2 value on 20th June was due to intercontinental transport of SO2 from Nabro volcanic eruption. Using the FLEXPART model with ECLIPSE-v5 emission inventory, the observed seasonal variation of SO2 could be well reproduced; however, the mixing ratios are found to be overestimated. CAMS (Copernicus Atmosphere Monitoring Service) SO2 reanalysis values available through its implementation in the ECMWF Integrated Forecasting System are a factor of 7.8 higher than observations, possibly due to incorrect vertical profile used in the model. [ABSTRACT FROM AUTHOR]

Fine particulate matter (PM2.5) has a serious impact on human health. Forecasting PM2.5 levels and analyzing the pollution sources of PM2.5 are of great significance. In this study, the Lagrangian particle dispersion (LPD) model was developed by combining the FLEXPART model and the Bayesian inventory optimization method. The LPD model has the capacity for real-time forecasting and determination of pollution sources of PM2.5, which refers to the contribution ratio and spatial distribution of each type of pollution (industry, power, residential, and transportation). In this study, we applied the LPD model to the Beijing-Tianjin-Hebei (BTH) region to optimize the a priori PM2.5 emission inventory estimates during 15–20 March 2018. The results show that (1) the a priori estimates have a certain degree of overestimation compared with the a posteriori flux of PM2.5 for most areas of BTH; (2) after optimization, the correlation coefficient (R) between the forecasted and observed PM2.5 concentration increased by an average of approximately 10%, the root mean square error (RMSE) decreased by 30%, and the IOA (index of agreement) index increased by 16% at four observation sites (Aotizhongxin_Beijing, Beichenkejiyuanqu_Tianjin, Dahuoquan_Xintai, and Renmingongyuan_Zhangjiakou); and (3) the main sources of pollution at the four sites mainly originated from industrial and residential emissions, while power factory and transportation pollution accounted for only a small proportion. The concentration of PM2.5 forecasts and pollution sources in each type of analysis can be used as corresponding reference information for environmental governance and protection of public health.

In the event of an accidental or intentional hazardous material release in the atmosphere, researchers often run physics-based atmospheric transport and dispersion models to predict the extent and variation of the contaminant spread. These predictions are imperfect due to propagated uncertainty from atmospheric model physics (or parameterizations) and weather data initial conditions. Ensembles of simulations can be used to estimate uncertainty, but running large ensembles is often very time consuming and resource intensive, even using large supercomputers. In this paper, we present a machine-learning-based method which can be used to quickly emulate spatial deposition patterns from a multi-physics ensemble of dispersion simulations. We use a hybrid linear and logistic regression method that can predict deposition in more than 100,000 grid cells with as few as fifty training examples. Logistic regression provides probabilistic predictions of the presence or absence of hazardous materials, while linear regression predicts the quantity of hazardous materials. The coefficients of the linear regressions also open avenues of exploration regarding interpretability—the presented model can be used to find which physics schemes are most important over different spatial areas. A single regression prediction is on the order of 10,000 times faster than running a weather and dispersion simulation. However, considering the number of weather and dispersion simulations needed to train the regressions, the speed-up achieved when considering the whole ensemble is about 24 times. Ultimately, this work will allow atmospheric researchers to produce potential contamination scenarios with uncertainty estimates faster than previously possible, aiding public servants and first responders.

The richly forested Indian state of Uttarakhand experienced widespread forest fires in April to May 2016. The current study examines dispersion of carbon monoxide (CO) from the source regions of forest fire to distant places, using the Lagrangian particle dispersion model, FLEXPART. Atmospheric Infrared Sounder (AIRS) observations revealed that CO columnar concentrations had increased by almost 28 percentage during 24 April to 02 May 2016 with respect to the previous non-burning period of April 2016 at Uttarakhand. It is also seen that there is considerable enhancement of 45 percentage in average columnar concentration of CO during the burning period, compared to that in the previous 5 years as observed by AIRS. In the present study, concentrations of CO at different pressure levels and columnar CO over Uttarakhand during the forest fire event have been simulated using FLEXPART. The area averaged profile of model derived CO has been compared with the profile from AIRS onboard Aqua. Comparison between model derived columnar CO and satellite observations shows good agreement with coefficient of correlation (r) approximately 0.91 over the burnt areas. Further analysis using FLEXPART reveals that the transport of pollutants is towards north-eastern and eastern regions from the locations of forest fire events. Model derived vertical distribution of CO over Tibet, which is situated at the north-east of Uttarakhand, shows significant increase of CO concentration at higher altitudes around 3 km from the mean sea level during the fire event. FLEXPART results show that the emissions from the Uttarakhand fires were transported to Tibet during the study period.

Copyright of Revista de la Academia Colombiana de Ciencias Exactas, Físicas y Naturales is the property of Academia Colombiana de Ciencias Exactas, Fisicas y Naturales and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)