PM10 Aerosol Research Articles

Source identification and ambient trace element concentrations of PM10 using receptor modeling in an urban area of Chhattisgarh, India

This study investigated seasonal variation in PM10 aerosols and associated trace metal concentrations in an urban city Raipur, India. PM10 aerosols were monitored at Raipur for the year 2015 to 2019. Eighteen trace elements (Al, Ba, Ca, Cr, As, Mn, Sb, Se, Sr, Cu, Fe, Ga, Mg, Ni, Ti, V, Pb, Zn) and (EC and OC) were analyzed using atomic absorption spectroscopy and thermal optical transmittance technique. A receptor-based positive matrix factorization (PMF) model was used to identify the possible sources with qualitative analysis of crustal enrichment factor, back-trajectory analysis using concentration weighted trajectory (CWT) to predict potential locations of distant sources, and correlation between different species. The average PM10 aerosol mass concentration during the study period was found to be 184.91 ± 114 µg/m³. Seasonally, the average winter–time PM10 concentration (193.49 ± 129.18 µg/m³) was found higher as compared to summer time (176.32 ± 65.80 µg/m³) during the study period. Five sources were identified including the iron and steel industry (30%), biomass and waste combustion (28.7%), vehicular emissions (21%), heavy oil combustion (17.4%), and crustal dust (2.9%). The study provides information on major sources affecting air quality.

Insights into aerosol chemical composition and optical properties at Lulin Atmospheric Background Station (2862 m asl) during two contrasting seasons

Continental outflows from peninsular Southeast Asia and East Asia dominate the widespread dispersal of air pollutants over subtropical western North Pacific during spring and autumn, respectively. This study analyses the chemical composition and optical properties of PM10 aerosols during autumn and spring at a representative high-altitude site, viz., Lulin Atmospheric Background Station (23.47°N, 120.87°E; 2862 m a.s.l.), Taiwan. PM10 mass was reconstructed and the contributions of major chemical components were also delineated. Aerosol scattering (σsp) and absorption (σap) coefficients were regressed on mass densities of major chemical components by assuming external mixing between them, and the site-specific mass scattering efficiency (MSE) and mass absorption efficiency (MAE) of individual components for dry conditions were determined. NH4NO3 exhibited the highest MSE among all components during both seasons (8.40 and 12.58 m2 g−1 at 550 nm in autumn and spring, respectively). (NH4)2SO4 and organic matter (OM) accounted for the highest σsp during autumn (51%) and spring (50%), respectively. Mean MAE (mean contribution to σap) of elemental carbon (EC) at 550 nm was 2.51 m2 g−1 (36%) and 7.30 m2 g−1 (61%) in autumn and spring, respectively. Likewise, the mean MAE (mean contribution to σap) of organic carbon (OC) at 550 nm was 0.84 m2 g−1 (64%) and 0.83 m2 g−1 (39%) in autumn and spring, respectively. However, a classification matrix, based on scattering Ångström exponent, absorption Ångström exponent, and single scattering albedo (ω), demonstrated that the composite absorbing aerosols were EC-dominated (with weak absorption; ω = 0.91–0.95) in autumn and a combination of EC-dominated and EC/OC mixture (with moderate absorption; ω = 0.85–0.92) in spring. This study demonstrates a strong link between chemical composition and optical properties of aerosol and provides essential information for model simulations to assess the imbalance in regional radiation budget with better accuracy over the western North Pacific.

Variability of Near-Surface Aerosol Composition in Moscow in 2020–2021: Episodes of Extreme Air Pollution of Different Genesis

During 2020–2021, a comprehensive experiment was conducted to study the composition of near-surface atmospheric aerosol in Moscow. The paper considers the experimental data together with synoptic and meteorological conditions. Attention is focused on six episodes of extremely high aerosol mass concentration values: in March and October 2020, as well in March, April, May and July 2021. In all these cases (and only in them), the average daily mass concentration of PM10 aerosol exceeded the Maximum Permissible Concentration (MPC) value (according to Russian standards, 60 μg/m3). The origin of the aerosol during these periods of extreme pollution is revealed, which is the main result of the work. It was shown that the July episode of 2021 was associated with a local intensive anthropogenic source that arose as a result of the active dismantling and demolition of multistory industrial buildings. The remaining spring and autumn episodes were caused by atmospheric transport of both smoke aerosol from various regions with strong biomass fires and dust aerosol from arid zones of the south of European territory of Russia (ETR) with dust wind storms. The cases of atmospheric pollution transport to Moscow region from the other regions are confirmed with the help of air mass transport trajectories (HYSPLIT 4 model) and MERRA-2 reanalysis data on black carbon and/or dust distribution in the atmosphere over ETR. Differences in the elemental composition of the near-surface aerosol of Moscow air during periods with extremely high aerosol concentrations are analyzed in comparison with each other and with unperturbed conditions for the season.

The influence of atmospheric blocking on regional PM10 aerosol transport to South Korea during February–March of 2019

The particulate matter (PM10) trend has decreased at a growing rate in South Korea, which is on the downwind side in the East Asian region over the last five-year period of 2014–2018. Nevertheless, nationwide, days of high PM10 levels and haze frequently occurred over the period of February–March in 2019. During the period of February–March 2019, two major atmospheric blockings were identified over the Alaskan region in the northeast Pacific over the periods of February 21-March 1 and March 18–29. Warm and stagnant synoptic meteorological conditions favorable for high-PM10 haze days in the East Asian region were accompanied 4–5 days later by the remote Alaskan atmospheric blockings. The Weather Research and Forecasting model coupled with Chemistry (WRF-Chem) was used, applying zero-out emission to analyze the regional PM10 contribution on severe haze days exceeding a daily average of 100 μg m−3 over South Korea during March 3–6, 2019. The daily average regional PM10 contribution indicated a rate of 57% compared to rates of 23% before and 29% after severe haze days. Furthermore, the major regional PM10 components were nitrates (49%), other inorganics (28%), and sulphates (9%) during the severe haze days. Among inorganic PM10 aerosols, other inorganics mainly composed of anthropogenic fine dust were not a major contribution component in the South Korean case due to fuel consumption changes in China. However, higher nitrate flux from sources in eastern China remained in South Korea, though in slightly reduced amounts. The contribution rate of NOX discharged from automobiles has gradually increased in China, and the level of SO2 remained on a low level through emission control technologies and regulatory options. The warm and stagnant atmosphere in the East Asian region caused the flux of relatively more nitrates were likely transported, with ammonium nitrate in the atmosphere and with lower sulphate levels.

Seasonal Variations of the Mercury Multiple Isotopic Compositions of Subrural and Urban Aerosols Highlight an Additional Atmospheric Hg0 Oxidation Pathway

The mechanisms triggering the large variations in the mercury (Hg) multiple isotopic compositions of atmospheric particle-bound Hg worldwide still remain unclear. The comparison of Hg isotopic compositions in aerosols collected in urban and rural areas may help distinguish the effects of natural processes from those of anthropogenic inputs. We thus investigated the Hg isotopic compositions of PM10 aerosols collected seasonally during 2015 at two monitoring stations on Montreal Island, one located downtown and the other in its westernmost subrural part, barely impacted by the city anthropogenic emissions. Our results show that, while Hg isotopic compositions present no seasonality at the urban station, possibly due to constant anthropogenic emissions, the subrural samples display clear seasonal variations, with higher Δ199Hg and Δ200Hg values (up to 0.77 and 0.12‰, respectively) during summer and close to 0‰ during the rest of the year, that cannot solely be explained by anthropogenic primary emissions. Besides, Δ200Hg measured in the subrural aerosols display a positive correlation with O3 suggesting the implication of secondary processes involving ozone. We propose that the significant summer shift in the multiple Hg isotopic compositions may reflect a transition in the corresponding Hg0 oxidation pathway, from halogens-triggered to ozone-dominated reactions. Still, this hypothesis needs to be further tested. Nevertheless, it demonstrates that Hg isotopes are effective at characterizing secondary processes that control its atmospheric budget, even at a local scale (i.e., urban vs subrural) and could thus be used to better constrain its atmospheric chemistry in various environments.

Seasonal Variation, Source Contribution, and Impact Factors of Biogenic Organic Aerosols in Pm2.5 in Nanjing, China

Seasonal Variation, Source Contribution, and Impact Factors of Biogenic Organic Aerosols in Pm2.5 in Nanjing, China

Pm10 Aerosol Enhancement in the Anticyclonic Anomalies Caused by the East Asian Spring Warming of 2021

Pm10 Aerosol Enhancement in the Anticyclonic Anomalies Caused by the East Asian Spring Warming of 2021

Impact of Anomalous Meteorological Variables on Pm10 Aerosol Formation During Regional Transport in the East Asian Region in March of 2021

Impact of Anomalous Meteorological Variables on Pm10 Aerosol Formation During Regional Transport in the East Asian Region in March of 2021

Аномальное аэрозольное загрязнение воздуха в Москве вблизи локального антропогенного источника в июле 2021 года

The paper analyzes the composition of surface aerosol close to the local intense anthropogenic source of pollution associated with the active phase of demolition of multistorey buildings in the center of Moscow. An abnormal increase in the daytime PM10 aerosol particle concentration to 5 MPC for daily values and to 14 MPC for maximum single values was reinforced by unfavorable meteorological conditions in the middle of July 2021. Preliminary estimation of the power of the dust aerosol source and its effect on the aerosol air pollution in nearby areas of the city is performed. The extreme and background values of the aerosol mass concentration, its elemental composition and particle size distribution during this period are determined. It is necessary to take into account such point pollutant sources in estimating and forecasting environmental conditions in a densely populated city. Keywords: surface aerosol, local anthropogenic source, Moscow, aerosol mass concentration, elemental composition, meteorological conditions

Аномальное аэрозольное загрязнение воздуха в Москве вблизи локального антропогенного источника в июле 2021 года

The paper analyzes the composition of surface aerosol close to the local intense anthropogenic source of pollution associated with the active phase of demolition of multistorey buildings in the center of Moscow. An abnormal increase in the daytime PM10 aerosol particle concentration to 5 MPC for daily values and to 14 MPC for maximum single values was reinforced by unfavorable meteorological conditions in the middle of July 2021. Preliminary estimation of the power of the dust aerosol source and its effect on the aerosol air pollution in nearby areas of the city is performed. The extreme and background values of the aerosol mass concentration, its elemental composition and particle size distribution during this period are determined. It is necessary to take into account such point pollutant sources in estimating and forecasting environmental conditions in a densely populated city. Keywords: surface aerosol, local anthropogenic source, Moscow, aerosol mass concentration, elemental composition, meteorological conditions

Source apportionment of sulphate in the High Arctic by a 10 yr-long record from Gruvebadet Observatory (Ny-Ålesund, Svalbard Islands)

A long-term study of the chemical composition of Arctic aerosol has been carried out at the Gruvebadet Observatory located in Ny-Ålesund since 2010. The PM10 aerosol has been collected continuously every year on a daily/2-day basis, each covering at least the spring and summer months, and the ionic content was evaluated using simultaneously three IC-systems. In order to determine the contribution of different sources (sea spray, crustal, biogenic and anthropogenic) to the total sulphate budget, specific markers and characteristic marker-to-sulphate ratios were used (Na+, Ca2+ and methanesulphonate). The obtained data set was then compared with the one from the Zeppelin Observatory, also located in Ny-Ålesund. The anthropogenic fraction resulted to be the major component, reaching the highest value in March and April during the Haze period, followed by the sea salt, biogenic and crustal ones. The comparison between the two datasets confirms the seasonal trend of these fractions even though some differences in magnitude were observed, likely due to discrepancies in the timing and resolution of sampling campaigns. The temporal profile of the anthropogenic fraction, evaluated in both sites, showed no evident continuous trend from 2010 to 2019, although the 2017–19 period revealed higher concentration with respect to the previous years. Focusing on single months, two opposite trends in the sulphate budget along 10 years were observed for March against April and September. Whereas a decrease was observed in March, April and September showed an increase in the monthly mean concentration values. Finally, the correlation between the non-sea salt non-crustal sulphate fraction and ammonium was evaluated. An increase in the ammonia neutralizing effect, resulting in a decrease in aerosol acidity, was observed at GVB, from the 2010 to 2017, then stabilized. Conversely, a decrease in the concentration of ammonia was found in ZEP since 2015, leading to an increase of the nssSO42−/NH4+ ratio in the same period.

Evaporation process dominates vehicular NMVOC emissions in China with enlarged contribution from 1990 to 2016

Non-methane volatile organic compounds (NMVOC) are important precursors of ozone and secondary organic aerosols in PM2.5 (particulate matter with aerodynamic diameters smaller than 2.5 μm), both of which cause severe climate, ecosystem, and human health damages. As one of the major anthropogenic sources, onroad vehicles are subject to relatively large errors and uncertainties in the estimation of NMVOC emissions due to complicated methods and parameters involved and a lack of comprehensive evaluation of influencing factors. Here, based on our previous work with necessary improvement, we estimate China’s vehicular NMVOC emissions by county and by month during 1990–2016 with a consideration of meteorological influence on the spatial-temporal dynamics of emission factors. Our estimate suggests that vehicular NMVOC emissions in China have peaked around 2008 and then declined up to 2016 with an enlarged contribution of the evaporative process to vehicular NMVOC emissions. Vehicular NMVOC emissions have been dominated by the evaporative process at present. Meteorological factors alter spatial-temporal distributions of NMVOC emissions, especially evaporative emissions, which are enhanced in South China and in summer. Emissions and ozone formation potential of the major chemical groups (i.e. Alkenes, Aromatics, and Alkanes) also increase substantially due to meteorological influences. Our analysis suggests that mitigation strategies for vehicle pollutions should be designed based on a sophisticated emission inventory accounting for the meteorological impact on emission factors to correct the potential underestimation of NMVOC emissions, especially those from the evaporative process.

Precursors and Pathways Leading to Enhanced Secondary Organic Aerosol Formation during Severe Haze Episodes.

Molecular analyses help to investigate the key precursors and chemical processes of secondary organic aerosol (SOA) formation. We obtained the sources and molecular compositions of organic aerosol in PM2.5 in winter in Beijing by online and offline mass spectrometer measurements. Photochemical and aqueous processing were both involved in producing SOA during the haze events. Aromatics, isoprene, long-chain alkanes or alkenes, and carbonyls such as glyoxal and methylglyoxal were all important precursors. The enhanced SOA formation during the severe haze event was predominantly contributed by aqueous processing that was promoted by elevated amounts of aerosol water for which multifunctional organic nitrates contributed the most followed by organic compounds having four oxygen atoms in their formulae. The latter included dicarboxylic acids and various oxidation products from isoprene and aromatics as well as products or oligomers from methylglyoxal aqueous uptake. Nitrated phenols, organosulfates, and methanesulfonic acid were also important SOA products but their contributions to the elevated SOA mass during the severe haze event were minor. Our results highlight the importance of reducing nitrogen oxides and nitrate for future SOA control. Additionally, the formation of highly oxygenated long-chain molecules with a low degree of unsaturation in polluted urban environments requires further research.

Nitrogenous and carbonaceous aerosols in PM2.5 and TSP during pre-monsoon: Characteristics and sources in the highly polluted mountain valley

This study reports for the first time a comprehensive analysis of nitrogenous and carbonaceous aerosols in simultaneously collected PM2.5 and TSP during pre-monsoon (March–May 2018) from a highly polluted urban Kathmandu Valley (KV) of the Himalayan foothills. The mean mass concentration of PM2.5 (129.8 µg/m3) was only ~25% of TSP mass (558.7 µg/ m3) indicating the dominance of coarser mode aerosols. However, the mean concentration as well as fractional contributions of water-soluble total nitrogen (WSTN) and carbonaceous species reveal their predominance in find-mode aerosols. The mean mass concentration of WSTN was 17.43±4.70 µg/m3 (14%) in PM2.5 and 24.64±8.07 µg/m3 (5%) in TSP. Moreover, the fractional contribution of total carbonaceous aerosols (TCA) is much higher in PM2.5 (~34%) than that in TSP (~20%). The relatively low OC/EC ratio in PM2.5 (3.03 ± 1.47) and TSP (4.64 ± 1.73) suggests fossil fuel combustion as the major sources of carbonaceous aerosols with contributions from secondary organic aerosols. Five-day air mass back trajectories simulated with the HYSPLIT model, together with MODIS fire counts indicate the influence of local emissions as well as transported pollutants from the Indo-Gangetic Plain region to the south of the Himalayan foothills. Principal component analysis (PCA) also suggests a mixed contribution from other local anthropogenic, biomass burning, and crustal sources. Our results highlight that it is necessary to control local emissions as well as regional transport while designing mitigation measures to reduce the KV's air pollution.

The Dynamics Of The Atmospheric Pollutants During The Covid-19 Pandemic 2020 And Their Relationship With Meteorological Conditions In Moscow

The relationship between the dynamics of the atmospheric pollutants and meteorological conditions has been analyzed during the COVID-19 pandemic in Moscow in spring, 2020. The decrease in traffic emissions during the lockdown periods from March 30th until June 8th played an important role in the decrease (up to 70%) of many gaseous species and aerosol PM10 concentrations and in the increase of surface ozone (up to 18%). The analysis of the pollutant concentrations during the lockdown showed much smoother diurnal cycle for most of the species due to the reduced intensity of traffic, especially during rush hours, compared with that before and after the lockdown. The specific meteorological conditions with low temperatures during the lockdown periods as well as the observed smoke air advection have made a considerable contribution to the air quality. After removing the cases with smoke air advection the decrease in concentration of many pollutants was observed, especially in NOx and PM10. The analysis of Pearson partial correlation coefficients with fixed temperature factor has revealed a statistically significant negative correlation between the Yandex self-isolation indices (SII), which can be used as a proxy of traffic intensity, and daily concentrations of all pollutants, except surface ozone, which has a statistically significant positive correlation with SII caused by specific photochemical reactions. In situations with SII>2.5 more favorable conditions for surface ozone generation were observed due to smaller NOx and the higher O3 /NOx ratios at the same ratio of VOC/NOx. In addition, this may also happen, since during the Arctic air advection, which was often observed during the lockdown period, the growth of ozone could be observed due to the downward flux of the ozone-rich air from the higher layers of the atmosphere.

Temporal trends of the concentration and sources of secondary organic aerosols in PM2.5 in Shanghai during 2012 and 2018

Based on the concentrations of the carbonaceous components and the typical organic tracers in 682 p.m.2.5 samples collected in Shanghai from 2012 to 2018, the temporal trends of the concentrations and potential sources of the secondary organic aerosols in PM2.5 in Shanghai were investigated. The annual average concentrations of organic carbon (OC), elemental carbon (EC) and water-soluble organic carbon (WSOC) all showed a decreasing trend along with the PM2.5 concentration. The annual concentration of total carbon (TC) in 2018 (4.3 μg m−3) was about 34% of that in 2012. Compared with that in 2013, the concentrations of isoprene and sesquiterpene SOA tracers in 2018 decreased by 48% and 43%. Meanwhile, the concentration of monoterpene SOA tracers kept stable in 2 ng m−3 to 3 ng m−3, and the concentration of toluene SOA tracer decreased slightly from 1.3 ng m−3 in 2013 to 1.0 ng m−3 in 2018. Correlation analysis with levoglucosan suggested that biomass burning should be an important source of sesquitertene in Shanghai. It was found that the 2-MGA/2-MTLs ratio of the isoprene tracers was more strongly affected by the ambient temperature but not NOx in Shanghai. The concentration of secondary organic carbon (SOC) estimated with OC/EC-based, WSOC-based and tracer-based methods showed a decreasing trend during the study period, but the contribution of SOC to OC was increasing. Anthropogenic aromatic volatile organic compounds was the increasingly important contributor to the SOC in PM2.5, and should be the key pollutants to be controlled to further improve the air quality in Shanghai.

Secondary Organic Aerosols in PM2.5 in Bengbu, a Typical City in Central China: Concentration, Seasonal Variation and Sources

To investigate the concentration, seasonal variation, and sources of secondary organic aerosols (SOAs) in the inland areas of central China, 244 seasonal PM2.5 samples were collected from January to October 2019 at one urban site and one suburban site simultaneously in Bengbu of Anhui Province. Concentrations of organic carbon (OC), elemental carbon (EC), water-soluble organic carbon (WSOC), and typical organic tracers, including saccharides, tracers of SOAs from isoprene, terpenes, and toluene, were measured. Results showed that Bengbu has high pollution levels of organic aerosols, with annual average OC concentrations of about 9.5 μg m−3. About 60% of the OC in PM2.5 in Bengbu was water soluble. Different seasonal trends were found for the SOA tracers of isoprene, monoterpene, seisquiterpene, and toluene. The highest seasonal average concentration of the isoprene SOA tracers was observed in summer and of the monoterpene and seisquiterpene SOA tracers in autumn. A stronger correlation was found between the 2-methylglyceric acid-to-2-methyltetrol ratio (MGA/MTL) and ambient temperature than that between MGA/MTLs and NOX concentration, suggesting that temperature has an important impact on the MGA/MTL ratio besides NOX concentration. The OC/EC-based method, WSOC-based method, tracer yield method, and positive matrix factorization (PMF)-based method were used to estimate the concentration and sources of secondary organic carbon (SOC), and the PMF-based method was believed to be able to give reasonable results. SOC was the main contributor of WSOC in PM2.5 in Bengbu, while biomass burning made an important contribution to WSOC in autumn and winter (~40%). SOC was mainly associated with SOA tracers in summer and mainly associated with secondary ions in spring and winter, suggesting different formation mechanisms in different seasons.

Radiocarbon in the atmospheric gases and PM10 aerosol around the Paks Nuclear Power Plant, Hungary

Our study shows a one-year-long, monthly integrated continuous monitoring campaign of gaseous radiocarbon emission and ambient air compared with 4 event-like, weekly (168 h) atmospheric aerosol radiocarbon data in every season of 2019, at 4 locations (n = 16 aerosol sample) around the Paks Nuclear Power Plant, Hungary. The study shows the first aerosol radiocarbon results around a nuclear power plant measured by accelerator mass spectrometry in Hungary. There was no dominant contribution detected in the atmospheric CO2 gas fraction, but we could detect excess radiocarbon in the total gaseous carbon fraction at almost every sampling point around the Paks Nuclear Power Plant. The highest Δ14C value in the total gaseous carbon form was 157.9 ± 4.6‰ in November and the highest Δ 14C value in the CO2 fraction was 86.1 ± 4.0‰ in December during 2019. Observed 14C activity excess is not higher than previously published values around the Paks Nuclear Power plant at the same sampling points (Molnár et al., 2007; Varga et al., 2020). Our aerosol radiocarbon measurements show that there is no significant contribution from the nuclear power plant to the atmospheric PM10 fraction. We could not detect a Δ 14C value higher than 0‰ in any season. The results show that the simple aerosol sampling, without pre-treatment of the filters, is appropriate for the measurement of excess radiocarbon at the vicinity of nuclear power plants. The applied preparation and measurement method can be applicable for detection of hot (14C) particles and early identification of radiocarbon emission from nuclear power plants in the PM10 fraction.

Formation and Prevention of Secondary Nitrate in PM2.5 in Tianjin

To study the formation and approaches to controlling secondary nitrate in PM2.5, the ionic compositions of PM2.5, pH of aerosols, variations in NH3-NH4+ and HNO3-NO3- concentrations, and the joint NH3/HNO3 sensitivity regime map of ammonium nitrate were investigated based on high-resolution online monitoring data for an urban site in central Tianjin from 2018 to 2019. The results showed that the average concentration of PM2.5 was 58μg·m-3, and the main ionic compositions of PM2.5 were nitrate (NO3-), ammonium (NH4+), sulfate (SO42-), Cl-, and K+ with corresponding mass percentages of 18.4%, 11.6%, 10.3%, 3.3%, and 2.6%, respectively. Concentrations of PM2.5 and the main components were relatively high during the heating season and relatively low during the non-heating season. The aerosols were weakly acidity with an average pH of 5.21; pH was higher in spring and winter and lower in summer and autumn, and diurnal variations pH were lower in the morning (00:00-08:00) and slightly higher at other times. The concentrations of NH3(g) (gas NH3) and HNO3(g) (gas HNO3) were 16.7μg·m-3and 1.2μg·m-3, respectively. The concentrations of NH3(g) were relatively higher from April to September and lower from October to February of the following year. HNO3(g) concentrations did not show any clear monthly pattern. Except during the summer, NH3(g) concentrations were higher in the morning and evening, and HNO3(g) concentrations were higher during the day. No clear linear relationships were observed between the concentrations of NH3(g) and NH4+ nor the concentrations of HNO3(g) and NO3- at different pH levels. Higher concentrations of NO3- and NH4+ were observed in the morning and evening, while no linear relationships were observed between the pH and concentrations of NH3(g)-NH4+ and HNO3(g)-NO3-. The joint NH3/HNO3 sensitivity regime map showed that most of the points were located in the HNO3 sensitive region with some in the NH3 & HNO3 sensitive region. In spring, autumn, and winter, most of the points were located in the HNO3 sensitive region while in summer, a significant quantity of the points were located in the NH3 & HNO3 sensitive region. Therefore, the precursors of HNO3 (such as NOx) should be controlled in the spring, autumn, and winter, and attention should be given to the control of the precursors of HNO3 (NOx) and NH3 in the summer to effectively control nitrate and ammonium aerosols in PM2.5 in Tianjin.

Machine learning models to quantify the influence of PM10 aerosol concentration on global solar radiation prediction in South Africa

Solar prediction models are essential in developing countries such as South Africa as most meteorological stations are unable to consistently measure this quantity. Quantification of solar radiation is of great significance for the adoption and application of renewable energy systems. Machine learning models are infamous for their high prediction capacity and low input requirements. This study's foremost intention was to investigate the efficacy of using the most widespread machine learning techniques for solar radiation estimation across South Africa, by introducing PM10 air pollutant concentration to generalized, readily available meteorological datasets. While assessing the performance of various input parameter configurations, the techniques which were evaluated include; Artificial Neural Network (ANN), Support Vector Regression (SVR), General Regression Neural Network (GRNN), and Random Forest (RF), of which ANNs proved the most appropriate for predicting global solar radiation as indicated by the high correlation coefficients (R2 = 0.99852) and low prediction errors (RMSE = 0.22627). The results described in this work indicate that machine learning models performed excellently for hybrid models as opposed to empirical models established in South Africa. ANN models which include PM10 concentration data profoundly improved the performance of relative humidity models and reduced overall error measures for models of various input parameter configurations. In addition, a poor correlation between PM10 concentration and air temperature was observed. This work suggests that the use of generalized, hybrid ANN models to predict solar radiation across South Africa are more functional than empirical modeling and this is indicated by the high prediction accuracy and low computational effort. The suggested model suffices as an accurate prediction model which will allow for a holistic understanding of the solar capacity available across this country while encouraging the implementation and investigation of sustainable, renewable energy technologies.