HYSPLIT Model Research Articles

Abundance and Seasonal Migration Patterns of Green Lacewings (Neuroptera: Chrysopidae) across the Bohai Strait in Eastern Asia.

Many insects, including green lacewings, migrate seasonally to exploit suitable breeding and winter habitats. Green lacewings are important natural enemies of insect pests worldwide. Here, four dominant green lacewing species, Chrysoperla nipponensis (Okamoto), Chrysopa pallens (Rambur), Chrysoperla furcifera (Okamoto), and Chrysopa formosa Brauer, were investigated for their ability to migrate between northern and northeastern China across the Bohai Strait from late May to late October each year. Furthermore, there were significant interannual and seasonal differences in the number of migratory green lacewings collected. The number of green lacewings in spring was significantly lower than that in summer and autumn, and the highest average number of green lacewings occurred in June. In addition, there were differences in the sex ratio of migrating green lacewings between months, with a greater proportion of females than males. Finally, the seasonal migration trajectories simulated by the HYSPLIT model revealed that the green lacewings captured on Beihuang Island primarily originated from Shandong Province. Accordingly, these findings contribute to our understanding of green lacewing migration in eastern Asia and aid its incorporation within integrated pest management (IPM) packages for several crop pests. Furthermore, long-term tracking of migrant insect populations can reveal ecosystem services and trophic dynamic processes at the macroscale.

Chemical composition and trajectories of atmospheric particles at the Machu Picchu Peruvian Antarctic scientific station (62.09º S, 58.47º W)

Antarctica is a remote and relatively pristine region, but the regional transport of aerosols may be a source of pollution, especially in the Antarctic Peninsula. Few studies have characterized atmospheric aerosols and evaluated the contribution of their emission sources. The Peruvian Antarctic research station Machu Pichu (ECAMP, by its Spanish acronym) is located on King George Island in the Antarctic Peninsula. During February 2020, atmospheric particulate mass (PM10 and PM2.5) was sampled and analyzed to characterize its elemental composition and was supplemented by measurements of equivalent black carbon and aerosol size distributions. Chemical elements were analyzed by inductively coupled plasma mass spectrometry (ICP-MS), multivariate techniques, and enrichment factors. The most abundant elements in PM10 and PM2.5 were Na, Fe, Mg, and Si, with the most important local sources being marine (Na, Mg, Mn, Ca) and crustal (Fe, Al, P). Sources of weathering (Ba and Si) from glacial thawing and sources of combustion linked to the use of oil (V) and emission of black carbon were recorded. Air mass back-trajectory analysis using the HYSPLIT model helped identify external sources of particulate matter in the air masses reaching the ECAMP site. Overall, this study supports the growing evidence of the anthropogenic impact of distant and local sources on the white continent.

A Hybrid Modeling Approach for Estimating the Exposure to Organophosphate Pesticide Drift in Sangamon County, Illinois

According to estimates from the World Health Organization (WHO), organophosphate pesticides are responsible for approximately 300,000 deaths worldwide. In the United States, documented cases of organophosphate pesticide exposure number around 8000, with a small number of fatalities occurring annually. The health risks associated with these pesticides affect those living in agricultural areas, as well as farmers and pesticide applicators. Despite the intervention of government agencies in Illinois to regulate pesticide application, studies have shown that these pesticides remain present in the soil, crops, water, and air. Urban-agricultural interface communities around Sangamon County exhibit significant levels of air pollution due to pesticide spray drift, although the lack of reliable pesticide data poses a challenge in estimating the extent of the problem. Therefore, developing novel strategies to reduce the impact of pesticides on environmental health is a critical and effective research area. Currently, new, dependable models and methods are being developed to calculate spray drift and mitigate its effects. The primary objective of this study was to investigate whether and to what extent organophosphate pesticide spray drifts into urban-agricultural interface communities in Sangamon County, Illinois. To achieve this, the current study employed an integrated approach that combined the capabilities of the HYSPLIT and AgDRIFT models to evaluate organophosphate pesticide spray drifting at both the field- and county-level scales. In the absence of precise pesticide quantity data, this novel approach allowed for field simulations within identified exposure drift zones. The preliminary findings indicate that all residential areas close to agricultural areas are at risk of pesticide drift, as buffer zones do not exceed 25 m. Furthermore, of the 34 water bodies (rivers, lakes, streams, and drains) in the 30,200-acre study region, 12 are within the high-drift zone for pesticide spray drift from corn and soybean fields. Finally, the potential for organophosphate pesticide drift was present in approximately 106 buildings, covering an area of 10,300 km2.

Trans-Boundary Dust Transport of Dust Storms in Northern China: A Study Utilizing Ground-Based Lidar Network and CALIPSO Satellite

During 14–16 March 2021, a large-scale dust storm event occurred in the northern region of China, and it was considered the most intense event in the past decade. This study employs observation data for PM2.5 and PM10 from the air quality monitoring station, the HYSPLIT model, ground-based polarized Lidar networks, AGRI payload data from Fengyun satellites and CALIPSO satellite Lidar data to jointly explore and scrutinize the three-dimensional spatial and temporal characteristics of aerosol transport. Firstly, by integrating meteorological data for PM2.5 and PM10, the air quality is assessed across six stations within the Lidar network during the dust storm. Secondly, employing a backward trajectory tracking model, the study elucidates sources of dust at the Lidar network sites. Thirdly, deploying a newly devised portable infrared 1064 nm Lidar and a pulsed 532 nm Lidar, a ground-based Lidar observation network is established for vertical probing of transboundary dust transport within the observed region. Finally, by incorporating cloud imagery from Fengyun satellites and CALIPSO satellite Lidar data, this study revealed the classification of dust and the height distribution of dust layers at pertinent sites within the Lidar observation network. The findings affirm that the eastward movement and southward compression of the intensifying Mongolian cyclone led to severe dust storm weather in western and southern Mongolia, as well as Inner Mongolia, further transporting dust into northern, northwestern, and northeastern parts of China. This dust event wielded a substantial impact on a broad expanse in northern China, manifesting in localized dust storms in Inner Mongolia, Beijing, Gansu, and surrounding areas. In essence, the dust emanated from the deserts in Mongolia and northwest China, encompassing both deserts and the Gobi region. The amalgamation of ground-based and spaceborne Lidar observations conclusively establishes that the distribution height of dust in the source region ranged from 3 to 5 km. Influenced by high-pressure systems, the protracted transport of dust over extensive distances prompted a gradual reduction in its distribution height owing to sedimentation. The comprehensive analysis of pertinent research data and information collectively affirms the precision and efficacy of the three-dimensional aerosol monitoring conducted by the ground-based Lidar network within the region.

Modelling the effect of shape on atmospheric microplastic transport

Microplastics are particles less than 5 mm in size and are a growing scientific concern, given the potential harm caused across ecosystems as a result of the global use of plastics. Most microplastics are non-spherical in shape, however, most atmospheric modelling studies to date treat microplastics as simple spheres when assessing transport. To further understand the effects of shape and size on atmospheric microplastic transport, the HYSPLIT model was utilized to identify potential differences. It was shown that the extent of microplastic transport and deposition varied significantly by shape for particles larger than 6 μm, but for particles smaller than 6 μm, the differences were not significant. Long fibres deposited over a 32% greater area than spherical particles at the largest equivalent size of 23.5 μm. The maximum deposition area occurred for particles with an equivalent size of 4.5 μm, varying in deposition area by less than 0.25% by the shapes considered. As particles smaller than 10 μm have a large potential to cause adverse health effects and shape affects transport in the 6 μm–10 μm size range, accurately modelling the shape of atmospheric microplastic transport is crucial to determining the range and amount of deposition globally.

Assessment of particulate matter and particle path trajectory analysis using a HYSPLIT model over Dire Dawa, Ethiopia

This work deals with the assessment of particulate matter (PM1, PM2.5, and PM10) over Dire Dawa during the month of May 2021. In the study, purple sensor (PS) and gravimetric methods (GM) were used. The purple sensor was to provide real-time measurements of PM1.0, PM2.5, and PM10 particulates. The GM instruments were constructed using wood with 1 m height (distance to ground), with flat board on top of which filter papers were placed to collect particulate matter. The difference in filter paper weight before and after sampling was used to calculate the particle masses. By dividing the weight gain of the filter by the amount of air measured, the concentrations of suspended particulate matter in the defined size range were estimated. The mean value of PM10 indicated a good status whereas the mean value of PM2.5 revealed a moderate condition as far as pollution is concerned. The purple sensor detected relatively higher values for PM10 measurement as compared to GM method during the study period. According to the calculated results of the ratio of mass concentration of PM1.0 to PM10, coarse particles were dominant whereas in the ratio of PM2.5 to PM10 both coarse and fine mode particles were equally present during the sampling period. The spatial distribution showed variations depending on the locations where the sampling filter papers were placed. The HYSPLIT backward trajectory analysis indicated various air masses and transport channels during different seasons. The predominant pathways were from both urban and desert origins.

Snow Contamination by Metals and Metalloids in a Polar Town: A Case Study of Nadym, Russia.

Snow composition depends on the long-range transport of pollutants. This article examines aspects of snow composition in the town of Nadym in Western Siberia. During fieldwork conducted in 2021 and 2022, we determined dust load, concentrations and ratio of dissolved and suspended forms of metals and metalloids (MMs). Moreover, we analyzed air mass trajectories using the HYSPLIT model, and the results showed that industrial regions of the southern Urals, southeastern Siberia, and Kazakhstan were the sources of MMs. Content of the insoluble fraction was increased by 23-fold in Nadym. The dust load in Nadym was higher than that in urban communities situated in the temperate zone, even though this town is relatively small in population and has little industrial infrastructure. This significant increase in dust load led to a ten- to 100-fold increase in the content MMs. Local soils (Fe, Al), vehicles (W), building dust (Mg, Ca), and anti-icing agents (Na) were found to be the sources of pollution. We found that the high dust load is caused by meteorological factors, such as temperature inversion and a large number of calm days, which reduce the dispersion of pollution. This case study demonstrates that winter air quality in polar settlements can be worse than that in urban areas in the temperate zone, even with few local sources of pollution. Furthermore, the trend toward an increase in the number of windless days, such as observed in Siberia as a result of global climate change, increases the risk of anthropogenic pollution of the atmosphere of polar cities.

Characteristics of PM2.5 in Long Binh Industry Park, Bien Hoa City, Vietnam: Mass Concentrations, Chemical Composition, Source Apportionment, and Health Risk Assessment

This study aimed to assess the concentration, source, chemical properties, and health risks associated with PM2.5 in Long Binh ward, Bien Hoa city, Dong Nai province, where there is a large distribution of industrial zones. PM2.5 samples were collected using a high-volume sampler during both the dry and rainy seasons. The mass concentration of PM2.5 was determined by Mettler Toledo XS205, and the chemical properties of eleven heavy metal elements were analyzed using inductively coupled plasma mass spectrometry (ICP-MS; iCAP-RQ, Thermo Science, US). The migration trajectory of PM2.5 was determined using the HYSPLIT model. The results showed that the PM2.5 concentration exceeded the WHO recommended value, while only the PM2.5 concentration in the dry season exceeded the national standard gia (QCVN 05:2013/BTNMT). Industry, road and non-road transportation activities were identified as the main sources of PM2.5. The heavy metal element Cr was found to be the most significant contributor to the chemical composition of fine particles. The health risk assessment revealed that the HI values were lower than 1 in both seasons, indicating a low risk of chronic adverse health effects. However, the TRC values exceeded the recommended threshold for cancer risk in both the rainy season (10-4 ± 6,6 x 10-5) and dry seasons (7,9 x 10-4 ± 5,6 x 10-4).

Characteristics and impacts of fine particulates from the largest power plant plume in Taiwan

In this study, the impact of the coal-fired Taichung Power Plant (TPP) plume in Taiwan during an observation experiment from Oct. 31 to Nov. 22, 2021, is simulated. We used the WRF/CMAQ and HYSPLIT models to analyze the changes in the PM2.5 concentration and the contribution percentage of major PM2.5 species along the forward trajectory of the TPP plume. Twenty trajectories with high PM2.5 concentrations above the chimney are divided into three types: transport to inland (TI), northeast monsoon transport southward (NMTS), and transport to sea (TS). The first kind, which exhibits mostly windy cases, is more harmful to people. Moreover, the largest proportion of the plume when it first exits the stack is SO42− (sulfate), which slightly decreases over time. The proportions of OM (organic matter) and NO3− (nitrate) slightly increased, and the proportion of NH4+ (ammonium ions) increased but not significantly. With the generation of low volatility/semi-volatile SOA (secondary organic aerosol), the proportion of OM significantly increases along the trajectory. Daytime photochemical reactions increase the radical concentrations, leading to an increase in the generation of low volatility/semi-volatile SOA and thus an increase in the proportion of OM. However, the proportion of NO3− in the smoke plume is smaller than that in other major PM2.5 species. Near the chimney, ANO3 (nitrate) accounts for a larger proportion of NO3− than HNO3 (nitrate acid). Furthermore, a sensitivity test shows that the height of the TPP that is reduced from 250 m to 150 m can have less effect on the environment.

Modeling SO2 dispersion from future eruptions in the Auckland Volcanic Field, New Zealand

Auckland city (pop. 1.7 M) is Aotearoa New Zealand’s largest city and an important economic hub. The city is built upon the active intraplate basaltic Auckland Volcanic Field (AVF). An AVF eruption would cause considerable impacts. An important component of volcanic risk management is assessing the likely volcanic hazards to help inform emergency planning and other preparedness activities. Previous volcanic hazard assessments for the AVF, particularly those for emergency planning scenarios, have modeled multiple volcanic hazards including lava flows, pyroclastic density currents, ballistic projectiles and tephra fall. Despite volcanic gas being an important and impactful hazard from intraplate basaltic field eruptions, there has been limited consideration of volcanic gas in AVF hazard assessment to date. This project is one of the first to quantitatively assess potential volcanic gas hazards for an explosive eruption scenario. For basaltic volcanism, sulfur dioxide (SO2) gas is typically the most consequential volcanic gas emitted. The aim of this exploratory study was to model SO2 dispersion from a high impact eruption during weather conditions conducive to high ground level pollutant concentrations. Since ground level SO2 concentrations are influenced by complex wind patterns resulting from interactions of locally driven flow circulations and topographically influenced weather, we modeled SO2 dispersion using the HYSPLIT model, a state-of-the art hybrid Eulerian and Lagrangian dispersion model widely used for volcanic gases, using high-resolution meteorological forcing fields given by the Weather Research and Forecasting (WRF) model.Modeled air parcel trajectories and ground level SO2 concentrations illustrate the effect of the converging sea breeze winds on SO2 dispersion. Under worst-case dispersion conditions, extensive areas of up to hundreds of square kilometers to the north and northwest of the eruption location would exceed New Zealand short-term (24 h) air quality standards and guidelines for SO2, indicating heightened health risks to downwind communities. Using this numerical modeling approach, this work presents a methodology for future applications to other AVF eruption scenarios, with a wider range of meteorological conditions that can help in exploring consequences for health services such as anticipated emergency department respiratory admissions.

Characterization of microplastics in outdoor and indoor air in Ranchi, Jharkhand, India: First insights from the region

The study focused on detecting and characterizing microplastics in outdoor and indoor air in Ranchi, Jharkhand, India during post-monsoon (2022) and winter (2023). Stereo microscopic analysis showed that plastic fibres had a dominant presence, fragments were less abundant, whereas fewer films could be detected in indoor and outdoor air. The atmospheric deposition of microplastics outdoors observed 465 ± 27 particles/m2/day in PM10 and 12104 ± 665 and 13833 ± 1152 particles/m2/day in PM2.5 in quartz and PTFE, respectively during the post-monsoon months. During winter, microplastic deposition rates in PM10 samples were found to be 689 ± 52 particles/m2/day and 19789 ± 2957 and 30087 ± 13402 in quartz and PTFE particles/m2/day respectively in PM2.5. The mean deposition rate in indoor environment during post-monsoon was 8.3 × 104 and 1.03 × 105 particles/m2/day in winter. During the post-monsoon period in PM10, there were fibres from 7.7 to 40 μm and fragments from 2.3 μm to 8.6 μm. Indoor atmospheric microplastics, fibres ranged from 1.2 to 47 μm and fragments from 0.9 to 16 μm present respectively during the post-monsoon season. Fibres and fragment sizes witnessed during winter were 3.6–6.9 μm and 2.3–34 μm, respectively. Indoor air films measured in the range of 4.1–9.6 μm. Fourier transform infrared analysis showed that outdoor air contained polyethylene, polypropylene, Polystyrene, whereas indoor air had polyvinyl chloride. Polyethylene mainly was present in outdoor air, with lesser polypropylene and polystyrene than indoors, where polyvinyl chloride and polyethylene were in dominant proportions. Elemental mapping of outdoor and indoor air samples showed the presence of elements on the microplastics. The HYSPLIT models suggest that the particles predominantly were coming from North-West during the post-monsoon season. Principal component analysis indicated wind speed and direction influencing the abundance of microplastics. Microplastics concentration showed strong seasonal influence and potential to act as reservoir of contaminants.

Mechanisms of isotopic control of precipitation in the Yellow River source region

AbstractThe study of water vapour sources and water cycle patterns in the Yellow River source region is of great significance for ensuring water resource security in the arid and semi‐arid regions of northern China. We established a precipitation stable isotope observation system in the Yellow River source region for three consecutive years (2020–2022), systematically analysed the spatial and temporal distribution characteristics of precipitation stable isotopes 2H and 18O in the Yellow River source region and their interrelationships with environmental factors and topography, and explored the regional water vapour transport pathways by using the HYSPLIT model and combining with the global reanalysis data. The results show that: (1) the δ18O and δ2H values of precipitation in the Yellow River source region follow the seasonal pattern, with the first half of the year being richer than the second half of the year; (2) the spatial variations of δ18O of precipitation in the Yellow River source region show a low in the southwest and a high in the northeast; (3) the water vapour source in the source area is basically stable, and the complex transport paths and the cross‐effects of the local factors determine the stable isotope characteristics of the water, and the stable isotope characteristics of the water are determined by the cross‐effects of the local factors, because the source of the water vapour and the local factors such as the height will not change significantly in the short term. Since the source of water vapour and local elevation factors will not change significantly in the short term, the precipitation pattern in the source area of the Yellow River can be considered to be basically stable.

Particulate matter pollution over artisanal crude oil refining areas of Niger-Delta Nigeria: Spatiotemporal analysis, transport modelling and risk assessment

The increasing rate of particulate matter pollution in Niger-Delta region of Nigeria due to artisanal crude oil refining and other unregulated emission activities is of great concern. This research work therefore quantify particulate matter (PM2.5) level over the Niger-Delta region of Nigeria. Also, backward trajectory and dispersion pattern of PM2.5 over six selected municipal areas within the region were simulated and health risks of PM2.5 exposure were assessed. IQAir satellite-based sensor was used to quantify PM2.5 (hourly) for 61 days (1st November 2022 to 31st December 2022) over the selected areas during the dreadful environmental and health challenged harmattan period. HYSPLIT model i.e Hybrid single-particle Lagrangian integrated trajectory model was used to simulate the trajectory, dispersion pattern and the dispered particulate matter position over the region. Air quality index (AQI) via the updated World Health Organization (WHO) standard was used to evaluate risks associted with PM2.5 exposure in the region. The result showed that the levels of PM2.5 quantified on daily average basis for the region were above the WHO standard. The trajectory models revealed the movement of the similar sourced PM2.5 pollutant and the dispersion model showed that it takes more than 24 hr for any released particulate matter to be fully dispersed. Also, majority of the dispersed particles were located between 0 m and 500 m. Finally, the AQI levels for the period considered ranged from unhealthy for sensitive groups (145.50 μg/m3) to hazardous (425.23 μg/m3) air quality. It can therefore be deduced that the inhabitants of the Niger-Delta region of Nigeria are liable to hazardous health effects over a prolong exposure to the high level PM2.5 in the region. Hence, more robust measures should be put in place to ensure an improved air quality and also to achieve a sustainable future for the Niger-Delta region, where economic growth can coexist with a healthy and pollution-free environment.

Analysis of O3 Pollution Affected by a Succession of Three Landfall Typhoons in 2020 in Eastern China

Based on air quality monitoring, surface meteorological data, wind profile radar observation, and the HYSPLIT model, the characteristics and causes of O3 pollution in eastern China during the period of the typhoons BAVI, MAYSAK, and HAISHEN from August 26 to September 8, 2020 were analyzed. The results showed that during the succession of the three landfall typhoons, the O3 pollution sites in Beijing Tianjin Hebei and its surrounding areas (BTHS) and the Yangtze River Delta (YRD) exceeded 50%. During the HAISHEN period, O3 pollution days in the two regions reached 2.22 d and 2.97 d, respectively, with significant persistence characteristics. The location of the typhoon had an obvious influence on O3 concentration. When the typhoons were located within the 24h warning line, the O3 concentrations in BTHS and YRD were relatively low. When the typhoons were located between the 24 h and 48 h warning lines, the O3 concentration in BTHS was the highest. When the typhoons moved north of 34°N, the YRD was most prone to regional O3 pollution. O3 pollution in Shanghai mainly occurred under the control of the northward air flow to the west side of the typhoons, and the regional transport from the upstream area had a significant impact on the increase in O3 and its precursor concentrations. The downdraft below 1 000 m maintained O3 at a high concentration at night. In Jinan, O3 pollution mainly occurred under the control of the subtropical high and typhoon periphery. The downdraft prevailed in the middle and lower levels during the O3 pollution. From August 28 to 30, under the control of the subtropical high, the pollutants were mainly accumulated locally, and some of them were transmitted within the province, showing a "double high" phenomenon of O3 and PM2.5. From September 5 to 8, under the influence of HAISHEN peripheral circulation, the regional transport was obvious, and the O3 concentration increased earlier than that of PM2.5.

Investigation of atmospheric particles in Urmia Lake region using a hand-held sun-photometer

Urmia Lake is a hypersaline lake in Northwest Iran. Regions inside its water catchment area experience frequent dust events. We are reporting the results of a two-year measurement campaign using a Calitoo sunphotometer, alongside synoptic measurements, satellite data, and atmospheric models. The monthly mean aerosol optical thickness (AOT) demonstrates a seasonal pattern, with fine particles prevailing in the winter and coarse particles being dominant during the summer months. Approximately 69% and 10% of the measurements indicate urban-industrial pollution and dust as the primary atmospheric particle types in the region, respectively. On the remaining days, a combination of the aforementioned aerosol types prevails as the dominant atmospheric particle composition. An in-depth analysis of a specific dust event unveiled a 24-hour delay between the peak AOT and the subsequent increase in particulate matter. Furthermore, the HYSPLIT model’s backward trajectory analysis depicted the transport of a dust plume from Mesopotamia to Urmia Lake, inducing alterations in AOT, mass concentrations, and visibility.

Emissions and trajectories of atmospheric pollutants from mobile sources in a Colombian intermediate city

In this study, the emissions of criteria pollutants and greenhouse gases from mobile sources in the main streets of the city of Valledupar were estimated. A vehicular characterization of the streets studied was carried out, and the IVE model was implemented to estimate the emissions generated by automobiles; subsequently, scenarios of atmospheric transport routes of pollutants were analyzed with the HYSPLIT model. The results showed that in the case of pollutant criteria, motorcycles emitted the highest amount of CO and PM10, and private cars the highest SOx and NOx emissions. For GHGs, private cars emitted the highest amount of CO2 and N2O, while motorcycles emitted the highest amount of CH4. The trajectory scenarios for the days of the study were carried out during the peak hours of vehicular circulation, implementing meteorological data from the WRF model. The trajectories were evaluated in rainy periods of 2021 and 2022 and in the dry period of 2022. In the rainy period, it was observed that the transport routes of the pollutants were directed in a greater proportion towards the NE direction and the dry period towards the SE direction. With this, it was possible to determine which areas of the city could be the most affected by vehicle emissions from the roads studied.

Spatio-temporal assessment of aerosol and cloud properties using MODIS satellite data and a HYSPLIT model: Implications for climate and agricultural systems

Understanding the spatiotemporal dynamics of aerosol optical characteristics is crucial for assessing their impact on the climate system. This study focuses on Aerosol Optical Depth (AOD) at 550 nm, measured by the Moderate-resolution Imaging Spectroradiometer (MODIS) aboard the Terra satellite, over a decade (2011–2021) in ten major cities across Pakistan. Our primary objectives were to investigate AOD variability, assess its correlation with cloud parameters, examine the source and trajectory of aerosol-laden air masses, and analyze the relationship between AOD and the Angstrom exponent. We employed the Hybrid single-particle Lagrangian Integrated Trajectory (HYSPLIT) model to trace air mass origins and paths. AOD exhibited its highest values in low-latitude urban areas, reflecting significant human activity. Conversely, high-altitude and mountainous regions displayed the lowest AOD levels. In summer (June–August), AOD peaked at 1.19, while in winter (December–February), it dropped to 0.24. The negative correlation between AOD and the Angstrom exponent, particularly in southern and western Pakistan, highlighted aerosol particle size variations. We further explored the relationships between AOD and five cloud parameters: water vapor (WV), cloud fraction (CF), cloud optical thickness (COT), cloud top temperature (CTT), and cloud top pressure (CTP). These relationships were found to be weather-dependent. This study provides valuable insights into the spatio-temporal dynamics of AOD in Pakistan, contributing to a better understanding of its impact on climate. This information is essential for climate scientists, meteorologists, and environmental departments, facilitating informed decision-making and climate modeling in the region.

Identifying the pathways of extreme rainfall in South Africa using storm trajectory analysis and unsupervised machine learning techniques

Abstract This study has utilised National Oceanic and Atmospheric Administration (NOAA) NCEP/NCAR Reanalysis 1 project meteorological data and the HYSPLIT model to extract the air parcel trajectories for selected historical extreme rainfall events in South Africa. The k-means unsupervised machine learning algorithm has been used to cluster the resulting trajectories, and from this, the spatial origin of moisture for each of the rainfall events has been determined. It has been demonstrated that rainfall events on the east coast with moisture originating from the Indian Ocean have distinctly larger average maximum daily rainfall magnitudes (279 mm) compared to those that occur on the west coast with Atlantic Ocean influences (149 mm) and those events occurring in the central plateau (150 mm) where moisture has been continentally recirculated. Further, this study has suggested new metrics by which the HYSPLIT trajectories may be assessed and demonstrated the applicability of trajectory clustering in a region not previously studied. This insight may in future facilitate improved early warning systems based on monitoring of atmospheric systems, and an understanding of rainfall magnitudes and origins can be used to improve the prediction of design floods for infrastructure design.

Source Apportionment of PM2.5 and PM2.5-Bound Trace Elements in Pretoria, South Africa

Outdoor PM2.5 samples were collected for 34 months in Pretoria, South Africa from 18 April 2017 to 28 February 2020. The average total PM2.5 concentration was 23.2 ± 17.3 µg.m3 (0.69–139 µg.m−3), with the highest mean recorded during winter and the lowest during summer (p < 0.05). The sources were determined by means of cross referencing the US EPA PMF 5.0 program and the NOAA HYsplit model. The sources of the total PM2.5 were mining (33%), resuspended dust (24%), industry (15%), general exhaust (12%), vehicular emissions (12%) and biomass burning (4%). Sources of air pollutants are both ubiquitous and seasonal.

Pollution status and source resolution of atmospheric mercury in the intersectional region of Northern Philippines, southern Taiwan, and northern South China Sea

A four-season sampling of speciated atmospheric mercury (SAM) was employed in East Asia. Three mercury species including gaseous elemental mercury (GEM), gaseous oxidized mercury (GOM), and particulate mercury (PHg) were measured at three background sites. This study explored the temporal variation, spatial distribution, gas-solid partition, transport routes, and source resolution of SAM. The yearly average concentrations of GEM, GOM, and PHg were 2.76 ± 0.36 ng/m3, 23.14 ± 8.67 pg/m3, and 0.23 ± 0.058 ng/m3. The highest GEM and PHg concentrations occurred at Laoag (northern Philippines) in spring, while that of GOM was observed at Laoag but in summer. The lowest GEM and PHg concentrations always occurred at Dongsha Islands (northern South China Sea) in summer, while that of GOM was also observed at Dongsha Islands but in fall. SAM was partition as showed 92.64–96.72% of total gas-phase mercury (TGM) and 3.28–7.36% of solid phase mercury. Eight clustered transport routes were resolved by a HYSPLIT model with polluted air parcels originating from Central/North China. Routes from Indochina Peninsula and South China showed the highest GEM concentration. Moreover, air parcels transported from West Pacific Ocean and South China Sea (SCS) had the lowest concentration of GEM. High concentrations of SAM in the region were mainly attributed to long-range transport (LRT) from Asian continental outflows (ACOs). We further revealed that GEM was positively correlated to SO2, CO, NOx, and PM2.5, but negatively correlated to O3. GOM was positively correlated to SO2, O3, NOx, and PM2.5, but negatively correlated to CO, While, PHg was positively correlated to SO2, CO, O3, NOx, and PM2.5.