Long-range Transport Of Pollutants Research Articles

Source apportionment of PM2.5 using DN-PMF in three megacities in South Korea

AbstractPM2.5 pollution is problematic in megacities on the western coast in South Korea (Seoul, Incheon, and Gwangju). As these megacities are located downwind of China, their air quality is easily affected by local and long-range transport sources. PM2.5 samples collected in Seoul (n = 222), Incheon (n = 221), and Gwangju (n = 224) from September 2020 to March 2022, were chemically characterized. Dispersion normalized positive matrix factorization was applied to these PM2.5 speciated data to provide source apportionments. Nine common sources (including secondary nitrate, secondary sulfate, biomass burning, mobile, and waste incinerator) were identified at all sites. The conditional bivariate probability function helped to identify each site’s local sources. Joint potential source contribution function analysis identified northeast China and Inner Mongolia as potential source areas of long-range transport pollutants affecting all sites. Forced lifestyle changes due to the pandemic such as limited gatherings while increased recreational activities may have caused different patterns on the biomass burning source. The constraints on old vehicles during the policy implementation periods likely reduced the mobile source contributions in cities that adopted the policy. Secondary nitrate accounted for 40% of the PM2.5 mass at all sites, implying a significant impact from NOX sources. While the current policy focuses primarily on controlling primary emission sources, it should include secondary sources as well which may include precursor emissions control. Healthier air quality would be achieved if the policy effects are not limited to local, but also to foreign sources in regions upwind of Korea by intergovernmental collaboration.

Tethered balloon measurements reveal enhanced aerosol occurrence aloft interacting with Arctic low-level clouds

Low-level clouds in the Arctic affect the surface energy budget and vertical transport of heat and moisture. The limited availability of cloud-droplet-forming aerosol particles strongly impacts cloud properties and lifetime. Vertical particle distributions are required to study aerosol–cloud interaction over sea ice comprehensively. This article presents vertically resolved measurements of aerosol particle number concentrations and sizes using tethered balloons. The data were collected during the Multidisciplinary drifting Observatory for the Study of Arctic Climate expedition in the summer of 2020. Thirty-four profiles of aerosol particle number concentration were observed in 2 particle size ranges: 12–150 nm (N12−150) and above 150 nm (N>150). Concurrent balloon-borne meteorological measurements provided context for the continuous profiles through the cloudy atmospheric boundary layer. Radiosoundings, cloud remote sensing data, and 5-day back trajectories supplemented the analysis. The majority of aerosol profiles showed more particles above the lowest temperature inversion, on average, double the number concentration compared to below. Increased N12−150 up to 3,000 cm−3 were observed in the free troposphere above low-level clouds related to secondary particle formation. Long-range transport of pollution increased N>150 to 310 cm−3 in a warm, moist air mass. Droplet activation inside clouds caused reductions of N>150 by up to 100%, while the decrease in N12−150 was less than 50%. When low-level clouds were thermodynamically coupled with the surface, profiles showed 5 times higher values of N12−150 in the free troposphere than below the cloud-capping temperature inversion. Enhanced N12−150 and N>150 interacting with clouds were advected above the lowest inversion from beyond the sea ice edge when clouds were decoupled from the surface. Vertically discontinuous aerosol profiles below decoupled clouds suggest that particles emitted at the surface are not transported to clouds in these conditions. It is concluded that the cloud-surface coupling state and free tropospheric particle abundance are crucial when assessing the aerosol budget for Arctic low-level clouds over sea ice.

Source and variability of formaldehyde in the Fenwei Plain: An integrated multi-source satellite and emission inventory study

Formaldehyde (HCHO) is a high-yield product of the oxidation of volatile organic compounds (VOCs) released by anthropogenic activities, fires, and vegetations. Hence, we examined the spatiotemporal variation trends in HCHO columns observed using the Ozone Monitoring Instrument (OMI) during 2005–2021 across the Fenwei Plain (FWP) and analysed the source and variability of HCHO using multi-source data, such as thermal anomalies. The spatial distribution of the annual mean HCHO in the FWP increased from northwest to southeast during 2005–2021, and the high-value aggregation areas contracted and gradually clustered, forming a belt-shaped distribution area from Xi'an to Baoji, north of the Qinling Mountains. The annual mean HCHO concentration generally showed a two-step increase over the 17 years. Fires showed a single-peak trend in March and a double-peak M-shaped trend in March and October, whereas urban thermal anomalies (UTAs) showed an inverted U-shaped trend over 17 years, with peaks occurring in May. The HCHO peaks are mainly caused by the alternating contributions of fires and UTAs. The fires and UTAs (predominantly industrial heat sources) played a role in controlling the background level of HCHO in the FWP. Precipitation and temperature were also important influencing variables for seasonal variations, and the influence of plant sources on HCHO concentrations had significant regional characteristics and contributions. In addition, the FWP has poor dispersion conditions and is an aggregated area for the long-range transport of air pollutants.

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.

Chemical characterization of atmospheric aerosols at a high-altitude mountain site: a study of source apportionment

Abstract. The study of aerosols in high mountain regions is essential because particulate matter can play a role in altering the energy balance of high mountain regions, and aerosols can accelerate glacier melting in high mountain areas by darkening the ice surface, reducing its reflectivity (albedo). Studying aerosols in high mountain areas provides insights into long-range transport of pollutants, atmospheric dynamics, and climate change impacts. These regions can serve as valuable observatories for studying atmospheric processes. The main aim of this paper is to define the main sources of aerosols over an entire year of sampling at the Col Margherita Atmospheric Observatory (MRG; 46°22′0.059′′ N, 11°47′30.911′′ E; 2543 m a.s.l.), a high-altitude background site in the eastern Italian Alps. Here, we discuss the potential origins of more than 100 chemical markers (major ions, water-soluble organic compounds, trace elements, and rare earth elements) using different approaches. Some diagnostic ratios were applied, but source apportionment using positive matrix factorization (PMF) was used to define the main inputs of PM10 collected at this high-altitude site, resulting in the identification of four factors: (1) Saharan dust events, (2) long-range marine/anthropogenic influence, (3) biogenic sources, and (4) biomass-burning and anthropogenic emissions. It can be inferred that, despite the distant location of the Col Margherita site, both regional pollution and long-range anthropogenic pollution have discernible effects on this area.

Investigating sources and health risk assessment of n-alkanes in atmospheric wet deposition in Indo-Gangetic Plain

The present study determines the levels of n-alkanes in atmospheric wet deposition at an urban site in the Indo-Gangetic Plain, Delhi, during monsoon and non-monsoon periods in 2021. The n-alkane homologs (C10–C33) were determined in wet deposition, which included wet-only and bulk samples. The average total n-alkanes were found to be 56.0 ± 16.7 and 439.4 ± 150.8 μg/L in wet-only samples, whereas, 149.6 ± 46.4 and 454.9 ± 108.4 μg/L in bulk samples during monsoon and non-monsoon periods, respectively. The low molecular weight n-alkanes (C10–C25) exhibited no odd-even predominance in wet-only and bulk depositions during monsoon and non-monsoon periods. However, the high molecular weight n-alkanes (>C25) showed odd-even predominance during the non-monsoon period. The molecular distribution patterns of n-alkanes indicated possible emissions from bacteria, fossil-fuel combustion, direct volatilization of unburnt fuels, biogenic sources, and other anthropogenic activities. A health risk assessment for n-alkanes revealed the higher susceptibility of children via dermal and oral exposure. The Hazard Index for the exposure of n-alkanes through atmospheric wet deposition was <1, i.e., within the acceptable limit. The Carbon Preference Index (CPI) and wax n-alkanes (WNA)%, supported the prevalence of mixed emission sources with higher contributions from anthropogenic activities. Five sources of n-alkanes were identified using the positive matrix factorization (PMF) model, i.e., gasoline vehicles + fuel evaporation, biogenic, biogenic + diesel exhaust, road dust, and mixed, contributing ∼30 %, 11 %, 26 %, 17 %, and 16 % respectively. The Concentration Weighted Trajectory (CWT) analysis revealed that n-alkanes in wet-only and bulk samples were contributed by different local, regional, and long-range transport of air pollutants.

Identifying source apportionment of atmospheric particulate matter and gaseous pollutants using receptor models : A case study of Bengaluru, India

The data of Particulate matter PMs (PM2.5, PM10) and Gaseous Pollutants such as carbon monoxide (CO), methane (CH4), oxides of nitrogen (NOx: NO and NO2), non-methane hydrocarbons (NMHCs), sulfur dioxide (SO2), along with ammonia (NH3) at five different locations across Bengaluru from 1st January, 2017 to 20th March, 2018 were collected. The primary objective of this research work is to identify the sources of atmospheric particulate matter and gaseous pollutants using receptor models in Bengaluru, India. To execute this, receptor models, namely Conditional Bivariate Probability Function (CBPF) and Concentrated Weighted Trajectory (CWT) Analysis, are applied. Conditional Bivariate Probability Function (CBPF) shows that, annually, the maximum concentrations of PMs over receptor sites were detected during low wind speed (&lt; 2 knots) along the north-east direction specifying that the long-range transport does not play an essential role in the transportation of higher concentrations of PM and their primary source region may be localized. Concentrated Weighted Trajectory (CWT) analysis shows that, seasonally, the highest air mass contribution of about 37% was noticed in summer, whereas the lowest was in the post-monsoon season (13%). The significant contribution of PM2.5 transported from long distances was during monsoon, and in the case of PM10, it was in summer. The study suggests that the long-range transport of PMs and gaseous Pollutants was not vital and was observed to be localized.

Prediction of the Concentration and Source Contributions of PM2.5 and Gas-Phase Pollutants in an Urban Area with the SmartAQ Forecasting System

The SmartAQ (Smart Air Quality) forecasting system produces high-resolution (1 × 1 km2) air quality predictions in an urban area for the next three days using advanced chemical transport modeling. In this study, we evaluated the SmartAQ performance for the urban area of Patras, Greece, for four months (July 2021, September 2021, December 2021, and March 2022), covering all seasons. In this work, we assess the system’s ability to forecast PM2.5 levels and the major gas-phase pollutants during periods with different meteorological conditions and local emissions, but also in areas of the city with different characteristics (urban, suburban, and background sites). We take advantage of this SmartAQ application to also quantify the main sources of the pollutants at each site. During the summertime, PM2.5 model performance was excellent (Fbias &lt; 15%, Ferror &lt; 30%) for all sites both in the city center and suburbs. For the city center, the model reproduced well (MB = −0.9 μg m−3, ME = 2.5 μg m−3) the overall measured PM2.5 behavior and the high nighttime peaks due to cooking activity, as well as the transported PM pollution in the suburbs. During the fall, the SmartAQ PM2.5 performance was good (Fbias &lt; 42%, Ferror &lt; 45%) for the city center and the suburban core, while it was average (Fbias &lt; 50%, Ferror &lt; 54%, MB, ME &lt; 3.3 μg m−3) for the suburbs because the model overpredicted the long-range transport of pollution. For wintertime, the system reproduced well (MB = −2 μg m−3, ME = 6.5 μg m−3) the PM2.5 concentration in the high-biomass-burning emission area with an excellent model performance (Fbias = −4%, Ferror = 33%) and reproduced well (MB &lt; 1.1 μg m−3, ME &lt; 3 μg m−3) the background PM2.5 levels. SmartAQ reproduced well the PM2.5 concentrations in the urban and suburban core during the spring (Fbias &lt; 40%, Ferror &lt; 50%, MB &lt; 8.5 μg m−3, ME &lt; 10 μg m−3), while it tended to slightly overestimate the regional pollution. The main local source of fine PM during summer and autumn was cooking, but most of the PM was transported to the city. Residential biomass burning was the dominant particle source of pollution during winter and early spring. For gas-phase pollutants, the system reproduced well the daily nitrogen oxides (NOx) concentrations during the summertime. Predicted NOx concentrations during the winter were consistent with measurements at night but underestimated the observations during the rest of the day. SmartAQ achieved the US EPA modeling goals for hourly O3 concentrations indicating good model performance.

Comparison of inorganic nitrogen concentrations in airborne particles at inshore and offshore sites in the Yellow Sea (2017–2019): Long-range transport and potential impact on marine productivity

Atmospheric deposition of nitrogen is one of the most important external nutrient sources. We investigated the concentrations of NO3− and NH4+ in airborne particles at both an offshore and an inshore site in the Yellow Sea. At the offshore site, devoid of local sources and located downwind from the highly developed areas of Korea and China, the concentrations of atmospheric particulate NO3− and NH4+ were ∼88 ± 101 nmol m−3 and ∼102 ± 102 nmol m−3, respectively, likely due to the transboundary long-range transport of pollutants. The inshore site showed a concentration ∼2 times higher than the offshore site. Considering not only dry inorganic nitrogen deposition but also wet and organic material deposition, the total atmospheric nitrogen deposition was estimated to contribute roughly 10 % to the new production in the Yellow Sea.

Air Pollution Modeling of UNI-DEM Model by using Innovative Stochastic Approaches

In this paper we develop advanced multidimensional sensitivity analysis, based on some innovative stochastic approaches for performing air pollution modelling on a large-scale model of long-range transport of air pollutants. The Unified Danish Eulerian Model (UNI-DEM) is a very important mathematical model, and can be applied in many different studies related to damaging effects caused by high air pollution levels. We shall use it in this paper to get a reliable answer to a some very important questions regrading environmental protection. We develop some advanced Monte Carlo and quasi-Monte Carlo methods, based on special lattice and digital sequences. In this paper we will improve the digital ecosystem modeling by improving the existence stochastic approaches. The computational efficiency (in terms of relative error and computational time) of the advanced Monte Carlo algorithms for multidimensional numerical integration has been studied to analyze the sensitivity of UNI-DEM model output to variation of input emissions of the anthropogenic pollutants and of rates of several chemical reactions. The algorithms will be applied to compute global Sobol sensitivity measures corresponding to the influence of several input parameters on the concentrations of important air pollutants. The study will be done for the areas of several European cities with different geographical locations.

Systematic Literature Review on Ozone Dispersion Correlated with Diurnal Concentration Pattern in Urban and Rural Areas

&#x0D; &#x0D; &#x0D; Ground level ozone is known to exhibit a strong daily variation of concentration leading to long-range transport of air pollutants from urban to rural areas. Moreover, the characteristics of O3 relationship between urban, suburban, and rural sites can be explained by O3 photochemical chemistry and meteorological dispersions as indicated by the different result of O3 diurnal pattern. However, little is known about the global phenomenon of diurnal concentration of ozone, meteorological dispersion such as long-range transport, and their correlation with ozone precursors, especially in urban and rural areas. This paper attempt to compare the difference between daily ozone fluctuations in both sites and assess some factors that cause long-range ozone transport from urban and rural areas both in subtropical and tropical areas for global scale. Using systematic literature review analysis with the PRISMA method, it examined 43 peer-reviewed articles published between 2010 and 2022 globally meeting the inclusion criteria. The result showed that the fluctuation patterns of daytime ozone in urban and rural areas are different to those in tropical and subtropical regions, depending on latitude. This was primarily due to the influence of solar radiation and the presence of precursors. Conversely, a slight decrease in ozone rate at night occurs because the precursor was accumulated by the shutdown of photochemical ozone production. Some precursors of ozone from other regions can be transported and accumulated from the long-range transport process in other locations. This paper serves as an initial guideline to analysing the pattern of ozone concentration in urban and rural areas and the factors that influence it.&#x0D; &#x0D; &#x0D;

Systematic Literature Review on Ozone Dispersion Correlated with Diurnal Concentration Pattern in Urban and Rural Areas

&#x0D; &#x0D; &#x0D; Ground level ozone is known to exhibit a strong daily variation of concentration leading to long-range transport of air pollutants from urban to rural areas. Moreover, the characteristics of O3 relationship between urban, suburban, and rural sites can be explained by O3 photochemical chemistry and meteorological dispersions as indicated by the different result of O3 diurnal pattern. However, little is known about the global phenomenon of diurnal concentration of ozone, meteorological dispersion such as long-range transport, and their correlation with ozone precursors, especially in urban and rural areas. This paper attempt to compare the difference between daily ozone fluctuations in both sites and assess some factors that cause long-range ozone transport from urban and rural areas both in subtropical and tropical areas for global scale. Using systematic literature review analysis with the PRISMA method, it examined 43 peer-reviewed articles published between 2010 and 2022 globally meeting the inclusion criteria. The result showed that the fluctuation patterns of daytime ozone in urban and rural areas are different to those in tropical and subtropical regions, depending on latitude. This was primarily due to the influence of solar radiation and the presence of precursors. Conversely, a slight decrease in ozone rate at night occurs because the precursor was accumulated by the shutdown of photochemical ozone production. Some precursors of ozone from other regions can be transported and accumulated from the long-range transport process in other locations. This paper serves as an initial guideline to analysing the pattern of ozone concentration in urban and rural areas and the factors that influence it.&#x0D; &#x0D; &#x0D;

An integrated monitoring system (IMS) for air quality: Observations of a unique ozone-exceedance event in Maryland

Ozone (O3) exceedance events in the mid-Atlantic states of the U.S. are typically observed during the summer months. They frequently result from local diurnal emissions of NO2 and VOCs where photochemical production of O3 is most prevalent. Occasionally, summertime O3-exceedances in the region are driven by long-range transport of pollutants or regional nocturnal dynamics. Discussed herein is the use of multiple observation platforms as an integrated monitoring system (IMS) to characterize the spatiotemporal confluence of long-range transport and nocturnal low-level jet induced O3-exceedances impacting air quality in the mid-Atlantic region. The IMS discussed is comprised of enhanced monitoring of vertically resolved observations of O3, atmospheric backscatter, winds, and state variables (e.g., temperature and relative humidity). This is in combination with surface-O3 observations, satellite-retrieved aerosol optical depth (by the moderate resolution imaging spectroradiometer (MODIS)), and simulations of air mass transport by NOAA's hybrid single-particle Lagrangian trajectory (HYSPLIT) model. Here we discuss an exceedance event that impacted the Mid-Atlantic region on May 20, 2021, where seven air monitoring sites in Maryland were driven by the combination of nocturnal low-level jet downmixing of pollutants and long-range transport of biomass-burning pollutants/O3-precursors. The most notable features of this case are this event's deviation from decadal O3-exceedance seasonality trends, the large spatial context of high surface-O3 impacting traditionally non-exceedance sites (sites that have not exceeded in years), the arrival of a well-mixed polluted air mass into the region, and nocturnal increases in surface-O3 induced by NLLJ.

Integrated ground and vertical measurement techniques to characterize overhead atmosphere: Case studies of local versus transboundary pollution

Much attention has been found to the long-range transport (LRT) of air pollutants and their adverse effects on downwind air qualities resulting from the Chinese haze, which frequently occurs in association with winter monsoon. This study integrates ground-based measurements, unmanned aerial vehicles (UAVs), and model simulations to characterize the meteorological, chemical, and particulate matter (PM) properties comprehensively for the events that were LRT or local pollution (LP) dominated in northern Taiwan during the wintertime of 2017. During the two types of episodes, various approaches were made to investigate the vertical mixing conditions and PM properties with UAV flights. A confined and PM accumulated feature near ground level with a temperature inversion was found during the LP event. In contrast, a vertically homogeneous atmospheric structure with strong winds was suggested during the LRT event. Independent measurements of criteria air pollutants, meteorological variables, volatile organic compounds (VOCs), and micropulse lidar (MPL) made at the ground level were closely supported by the vertical measurements. When synchronizing all these observational and numerical tools in a three-dimensional manner, the characterization of air masses and possible origins of pollution, such as LP vs. LRT, has now become more versatile and capable of gaining a complete picture of atmospheric conditions that define air quality.

Do heat waves worsen air quality? A 21-year observational study in Seoul, South Korea

Heat waves are generally known to deteriorate air quality. However, the impacts of heat waves on air quality can substantially vary depending on the characteristics of heat waves. In this study, we examine air quality changes in Seoul during heat waves and their associations with large-scale atmospheric patterns. For this, air quality data from 25 stations and meteorological data from 23 weather stations and reanalysis datasets during July and August of 2001–2021 are used. Under heat waves, the mean daily PM10, NO2, and CO concentrations decrease by 7.9 %, 6.1 %, and 4.6 %, respectively, whereas the mean daily PM2.5, O3, and SO2 concentrations increase by 4.1 %, 17.2 %, and 2.9 %, respectively. The atmospheric circulation under heat waves is less favorable for long-range transport of air pollutants to Seoul. The PM2.5/PM10 ratio increases under heat waves, indicating that the secondary formation of aerosols becomes more important under heat waves. 37 % of the heat wave days are accompanied by severe O3 pollution exceeding the O3 concentration standard in South Korea. There is a significant variability of air quality in Seoul within heat waves. The heat wave days with higher concentrations of PM2.5, PM10, O3, NO2, and CO than their non-heat wave means exhibit a prominent difference in large-scale atmospheric pattern from the heat wave days with lower concentrations. This difference is characterized by a zonal wave-like pattern of geopotential height, which is similar to the circumglobal teleconnection pattern known as one of the major patterns for heat waves in South Korea. This zonal wave-like pattern produces more stagnant conditions over Seoul.

Spatial and temporal heterogeneity of air pollution in East Africa

East Africa's air pollution levels are deteriorating due to anthropogenic and biomass burning emissions and unfavorable weather conditions. This study investigates the changes and influencing factors of air pollution in East Africa from 2001 to 2021. The study found that air pollution in the region is heterogeneous, with increasing trends observed in pollution hot spots (PHS) while it decreased in pollution cold spots (PCS). The analysis identified four major pollution periods: High Pollution period 1, Low Pollution period 1, High Pollution period 2, and Low Pollution period 2, which occur during Feb-Mar, Apr-May, Jun-Aug and Oct-Nov, respectively. The study also revealed that long range transport of pollutants to the study area is primarily influenced by distant sources from the eastern, western, southern, and northern part of the continent. The seasonal meteorological conditions, such as high sea level pressure in the upper latitudes, cold air masses from the northern hemisphere, dry vegetation, and a dry and less humid atmosphere from boreal winter, further impact the transport of pollutants. The concentrations of pollutants were found to be influenced by climate factors, such as temperature, precipitation, and wind patterns. The study identified different pollution patterns in different seasons, with some areas having minimal anthropogenic pollution due to high vegetation vigor and moderate precipitation. Using Ordinary Least Square (OLS) regression and Detrended Fluctuation Analysis (DFA), the study quantified the magnitude of spatial variation in air pollution. The OLS trends indicated that 66 % of pixels exhibited decreasing trends while 34 % showed increasing trends, and DFA results indicating that 36 %, 15 %, and 49 % of pixels exhibited anti-persistence, random, and persistence in air pollution, respectively. Areas in the region experiencing increasing or decreasing trends in air pollution, which can be used to prioritize interventions and resources for improving air quality, were also highlighted. It also identifies the driving forces behind air pollution trends, such as anthropogenic or biomass burning, which can inform policy decisions aimed at reducing air pollution emissions from these sources. The findings on the persistence, reversibility, and variability of air pollution can inform the development of long-term policies for improving air quality and protecting public health.

Source apportionment of PM2.5 and the impact of future PM2.5 changes on human health in the monsoon-influenced humid subtropical climate

Local emission sources and long-range transport of air pollutants are the main causes of PM2.5 pollution in developing metropolises. A modeling system was used to determine the main contributors of PM2.5 and future changes in PM2.5 concentrations in Hanoi, one of the fast-growing and most polluted capital cities in the world. Additionally, BenMAP was used to estimate the number of premature deaths caused or avoided due to PM2.5 concentration changes. October and December 2017 as well as April and June 2018 were selected for analysis. The source apportionment approach revealed that the boundary conditions (BCON), were the primary source of PM2.5, accounting for 24–59.7%. Agriculture was a substantial contributor of PM2.5 within Hanoi in June and October, accounting for 27.8 and 18.8%, respectively. Projected emissions for 2030 from our previous work, which were estimated based on the action plans and scenarios proposed by the government, were used as input into the air quality modeling system to analyze changes in the concentrations of the total PM2.5 and its major components owing to emissions changes. It is shown that, the concentrations of PM2.5 can increase by 0.5 and 1.6 μg/m3 in April and December, and decrease by 3.2 and 1.5 μg/m3 in June and October, respectively. Using BenMAP , it is estimated that these changes can cause 45 and 95 premature deaths in April and December, but prevent 198 and 88 premature deaths in June and October respectively, in Hanoi.

Influence of stubble burning on air quality of Northern India: a case study of Indo-Gangetic plains of India

Stubble burning is an emerging environmental issue in Northern India, which has severe implications for the air quality of the region. Although stubble burning occurs twice during a year, first during April-May and again in October-November due to paddy burning, the effects are severe during October-November months. This is exacerbated by the role of meteorological parameters and presence of inversion conditions in the atmosphere. The deterioration in the atmospheric quality can be attributed to the emissions from stubble burning which can be perceived from the changes observed in land use land cover (LULC) pattern, fire events, and sources of aerosol and gaseous pollutants. In addition, wind speed and wind direction also play a role in changing the concentration of pollutants and particulate matter over a specified area. The present study has been carried out for the states of Punjab, Haryana, Delhi, and western Uttar Pradesh to study the influence of stubble burning on the aerosol load of this region of Indo-Gangetic Plains (IGP). In this study, the aerosol level, smoke plume characteristics, long-range transport of pollutants, and affected areas during October-November from year 2016 to 2020 were examined over the Indo-Gangetic Plains (Northern India) region by the satellite observations. By MODIS-FIRMS (Moderate Resolution Imaging Spectroradiometer-Fire Information for Resource Management System) observations, it was revealed that there was an increase in stubble burning events with the highest number of events being observed during the year 2016 and then a decrease in the number of events in subsequent years from 2017 to 2020. MODIS observations revealed a strong AOD gradient from west to east. The prevailing north-westerly winds assist the spread of smoke plumes over Northern India during the peak burning season of October to November. The findings of this study might be used to expand on the atmospheric processes that occur over northern India during the post-monsoon season. The pollutant, smoke plume features, and impacted regions of biomass-burning aerosols in this region are critical for weather and climate research, especially given the rising trend in agricultural burning over the previous two decades.

The effects of meteorology and biomass burning on urban air quality: The case of Bangkok

Bangkok, one of the biggest metropolitan cities in Asia, has been experiencing poor (PM10 > 50 μg/m3 annual average) air quality for decades. Major sources of air pollution are traffic emissions, biomass burning, and non-combustible sources. In this study, the impact of meteorology and biomass burning on the concentration of particulate matter was assessed. Data from three monitoring stations and remotely sensed fire count between 2017 and 2020 was used to investigate the association. Moreover, the spatiotemporal pattern of aerosol optical depth (AOD) and fire count derived from remotely sensed data were investigated to observe their association. This study found that temperature, relative humidity, rainfall, wind speed, and wind direction have a significant negative relationship with particulate matter concentration. In contrast, atmospheric pressure and fire count have a significant positive correlation with particulate matter concentration. Moreover, the pollution rose diagram for particulate matter indicated that the northeasterly wind is the prevailing wind direction that carries the most pollutants. Furthermore, the Hybrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT) model and AOD indicated that biomass burning in neighboring regions significantly (p < 0.05) affected the particulate matter concentration in Bangkok. Multiple linear regression (MLR) analysis established that atmospheric pressure has the highest negative impact on the city air quality, followed by biomass burning, while heavy rainstorms were the most substantial parameter that reduced particulate matter concentration. Taken together, these findings highlight the importance of meteorological factors in understanding air pollution mechanisms in Bangkok. Equally important, the insights gained from this study may assist in addressing the long-range transport of air pollutants from biomass burning, which requires a coordinated engagement with neighboring countries.

Diagnosing domestic and transboundary sources of fine particulate matter (PM2.5) in UK cities using GEOS-Chem

The UK is set to impose a stricter ambient annual mean fine particulate matter (PM2.5) standard than was first adopted fourteen years ago. This necessitates strengthened knowledge of the magnitude and sources that influence urban PM2.5 in UK cities to ensure compliance and improve public health. Here, we use a regional-scale chemical transport model (GEOS-Chem), validated with national ground-based observations, to quantify the influence of specific sources within and transported to the mid-sized UK city Leicester. Of the sources targeted, we find that agricultural emissions of ammonia (NH3) make the largest contribution (3.7 μg m−3 or 38 % of PM2.5) to annual mean PM2.5 in Leicester. Another important contributor is long-range transport of pollution from continental Europe accounting for 1.8 μg m−3 or 19 % of total annual mean PM2.5. City sources are a much smaller portion (0.2 μg m−3; 2 %). We also apply GEOS-Chem to the much larger cities Birmingham and London to find that agricultural emissions of NH3 have a greater influence than city sources for Birmingham (32 % agriculture, 19 % city) and London (25 % agriculture, 13 % city). The portion from continental Europe is 16 % for Birmingham and 28 % for London. Action plans aimed at national agricultural sources of NH3 and strengthened supranational agreements would be most effective at alleviating PM2.5 in most UK cities.