Source Apportionment Analysis Research Articles

Unraveling Urban NOx Emission Sources in Polluted Arctic Wintertime Using NO2 Nitrogen Isotopes

AbstractNitrogen (N) isotopic fractionation during nitrogen oxides (NOx) cycling and conversion into atmospheric nitrate alters the original N isotopic composition (δ15N) of NOx emissions. Limited quantification of these isotopic effects in urban settings hampers the δ15N‐based identification and apportionment of NOx sources. δ15N of nitrogen dioxide (NO2) measured during winter in downtown Fairbanks, Alaska, displayed a large temporal variability, from −10.2 to 24.1‰. δ15N(NO2) records are found to be driven by equilibrium isotopic fractionation, at a rate in very close agreement with theoretical predictions. This result confirms that N isotopic partitioning between NO and NO2 can be accurately predicted over a wide range of conditions. This represents an important step for inferring NOx emission sources from isotopic composition measurement of reactive nitrogen species. After correcting our δ15N(NO2) measurements for N fractionation effects, a δ15N‐based source apportionment analysis identifies vehicle and space heating oil emissions as the dominant sources of breathing‐level NOx at this urban site. Despite their large NOx emissions, coal‐fired power plants with elevated chimney stacks (>26 m) appear to make a small contribution to surface NOx levels in downtown Fairbanks (likely less than 18% on average). The combined uncertainties of the δ15N of NOx from heating oil combustion and of the influence of low temperatures on the δ15N of NOx emitted by vehicle exhaust prevent a more detailed partitioning of surface NOx sources in Fairbanks.

Source apportionment of airborne volatile organic compounds near unconventional oil and gas development

Abstract Oil and natural gas (ONG) extraction activities have been associated with the release of volatile organic compounds (VOCs), including hazardous air pollutants (HAPs) that are known to have adverse health effects and other VOCs that contribute to ozone formation. This study investigated the impact of ONG operations on HAP and other VOC concentrations during the development of multi-well ONG pads in suburban Broomfield, Colorado. Weekly VOC measurements were collected at 18 sites across the community, including locations near the well pads, in adjacent neighborhoods, and at a regional background site. The measurements, from October 2018 to December 2020, encompassed different stages of well pad development, including well drilling, hydraulic fracturing, flowback, and production. Measured concentrations were analyzed using Positive Matrix Factorization (PMF) to characterize VOC sources. Six PMF source factors were identified, including factors associated with combustion, background/biogenic sources, light alkanes, complex alkanes, drilling activities, and ONG acetylene. The factors related to local ONG activities showed clear temporal and spatial correlations with Broomfield well development activities. A benzene source apportionment analysis revealed important source contribution gradients across the community, with ONG-related sources exhibiting the largest influence at locations near the well pads, especially during pre-production activities. Weekly average benzene concentration contributions from ONG-related sources ranged from 9% to 63% at a community background site and from 18% to 89% at a neighborhood site close to a well pad.

Atmospheric evolution of environmentally persistent free radicals in the rural North China Plain: effects on water solubility and PM2.5 oxidative potential

Abstract. Environmentally persistent free radicals (EPFRs) represent a novel class of hazardous substances, posing risks to human health and the environment. In this study, we investigated the EPFRs in ambient fine, coarse, and total suspended particles (PM2.5, PM10, and TSPs) in the rural North China Plain, where local primary emissions of EPFRs were limited. We observed that the majority of EPFRs occurred in PM2.5. Moreover, distinct seasonal patterns and higher g factors of EPFRs were found compared to those in urban environments, suggesting unique characteristics of EPFRs in rural areas. The source apportionment analyses revealed atmospheric oxidation as the largest contributor (33.6 %) to EPFRs. A large water-soluble fraction (35.2 %) of EPFRs was determined, potentially resulting from the formation of more oxidized EPFRs through atmospheric oxidation processes during long-range or regional transport. Additionally, significant positive correlations were observed between EPFRs and the oxidative potential of water-soluble PM2.5 measured by dithiothreitol-depletion and hydroxyl-generation assays, likely attributable to the water-soluble fractions of EPFRs. Overall, our findings reveal the prevalence of water-soluble EPFRs in rural areas and underscore the fact that atmospheric oxidation processes can modify their properties, such as increasing their water solubility. This evolution may alter their roles in contributing to the oxidative potential of PM2.5 and potentially also influence their impact on climate-related cloud chemistry.

Chemical characterization and source apportionment of atmospheric fine particulate matter (PM2.5) at an urban site in Astana, Kazakhstan

PM2.5 is a significant air quality concern in urban areas globally. PM2.5 in Astana exceeded the US EPA standard for annual mean PM2.5 EPA with an average PM2.5 mass concentration of 23.43 ± 11.50 μg/m3 and a maximum daily value of 63.8 μg/m3 in January (heating season). The lowest 3.7 μg/m3 was observed in September (non-heating season). However, source apportionment in Kazakhstan has not been done because of a lack of PM2.5 composition measurements. This study presents the first analysis of chemical composition of PM2.5 and source apportionments in Kazakhstan. It comprehensively examined Astana's PM2.5 chemical characteristics and source apportionment over ∼ two years (November 2019 to August 2021). Using elements, water-soluble inorganic ions, black carbon (BC), and estimated unmeasured mass (UMM), source apportionment was obtained using Positive Matrix Factorization (PMF) supported by conditional bivariate probability function (CBPF) analyses. Average PM2.5 contributions of the eight sources were ‘Spark Ignition’ (30.3%), ‘Coal Flyash’ (17.1%), ‘Secondary Nitrate’ (15.1%), ‘Primary Sulfate-Fuel Combustion’ (9.9%), ‘Secondary Sulfate-Coal Combustion’ (8.5%), ‘Soil/Road Dust’ (7.9%), ‘Diesel’ (7.1%), and ‘Local Power Plant(s)’ (4.2%). Local power plants burn high-ash coal and fuel oil year-round. The major contributions of heating/power plants, private residential heating systems, autonomous boilers, vehicles, asphalt pavement mixing facilities, and local construction activities. This study's source apportionment analysis provides critical insights for developing targeted air quality management strategies in Kazakhstan. Findings highlight the need for improved controls on vehicular emissions and heat/power generation sources and for the implementation of measures by local governments to effectively reduce PM2.5.

Seasonal variation and origins of C1–C5 alkyl nitrates: A year-long study at a Hong Kong coastal site

Alkyl nitrates (RONO₂) are key reactive nitrogen compounds with significant impacts on local and regional air quality. The concentrations of alkyl nitrates can vary significantly across different regions, especially in areas with varying levels of human activity. Long-term observation of alkyl nitrates is necessary to assess the intensity of photochemical reactions and the contributions from different sources. In this study, we present the first continuous year-long monitoring results of eight alkyl nitrates via whole air sample collection and GC-MSD/ECD analysis at a coastal site in Hong Kong. Source apportionment analysis via positive matrix factorization (PMF) revealed distinctive seasonal variations in the source contributions for the eight alkyl nitrate species. Furthermore, increased contributions from biomass combustion were found in autumn and winter, while marine emissions primarily influenced methyl nitrate levels during summer. Our study highlights the significant impact of biomass burning from inland areas on photochemical pollutants in Hong Kong. Cross-regional cooperation in the Greater Bay Area (GBA) is necessary for more comprehensive management of secondary photochemical pollution.

Characterizing and tracing the heavy metals' spatial distribution in karst surface river affected by acid mine drainage

A series of pollution problems have been caused by the drainage of closed coal mines. This study focuses on the XZ River in Guizhou Province, employing a comprehensive approach involving hydrochemical analysis, mathematical statistics, and one-dimensional water quality modeling to investigate the spatial evolution and source apportionment of heavy metals in karst surface rivers affected by AMD. The average pH, EC, and Eh values of groundwater and surface water in the XZ river basin were 6.27, 331 <i>μ</i>s/cm, 230 mV and 3.86, 1671.57 <i>μ</i>s/cm, 412.71 mV, respectively, indicating severe pollution of surface water by AMD. The study reveals that groundwater in the XZ River Basin is predominantly of the HCO<sub>3</sub>-Ca-Mg type, shifting to HCO<sub>3</sub>-SO<sub>4</sub>-Ca-Mg type with the influx of acid mine wastewater. Utilizing statistical methods for source apportionment analysis indicated that downstream concentrations of Fe, Mn, Zn, Cu, As, and Sr most likely originate from tributaries. Further analysis through one-dimensional water quality simulation confirmed that downstream concentrations of Fe, Mn, Zn, Cu, As, and Sr are attributed to tributaries. This suggests that XZ River is affected by pollution from different coal mines, primarily from coal mine M4, followed by coal mine M1.

New magnetic proxies to reveal source and bioavailability of heavy metals in contaminated soils

Environmental magnetism plays an important role in monitoring heavy metal pollution, but most studies are confined to indicating only the levels of heavy metals using magnetic parameters. This study established new magnetic proxies for accurately depicting the sources and bioavailability of heavy metals in contaminated soils. We observed different relationships between χ and SIRM in the soils contaminated by non-ferrous metal smelting compared to those polluted by coal combustion and steel smelting. Furthermore, we found that the soft magnetic components (IRMsoft) in the soils were mainly controlled by the non-ferrous metal smelting activities, while the hard magnetic components (HIRM) might be affected by the iron erosion. These new magnetic proxies enriched the source composition spectrum and improved the accuracy of the source apportionment analyses (principal component analysis and positive matrix factorization), yielding a result that was comparable to that by Pb isotope fingerprinting. We also found strong relationships between magnetic parameters (especially IRMsoft) and bioavailable fractions of heavy metals, indicating that magnetic measurement may be a powerful tool for monitoring the bioavailability of heavy metals. This study expands the application fields of magnetism in environmental science research.

International airport emissions and their impact on local air quality: chemical speciation of ambient aerosols at Madrid–Barajas Airport during the AVIATOR campaign

Abstract. Madrid–Barajas Airport (MAD) is the fourth-busiest airport in Europe. The aerosol chemical composition and the concentrations of other key pollutants were measured at the airport perimeter during October 2021 to assess the impact of airport emissions on local air quality. A high-fidelity ambient instrumentation system was deployed at Madrid–Barajas Airport to measure the following: concentrations of organic aerosols (with their composition), black carbon (eBC), carbon dioxide (CO2), carbon monoxide (CO), nitrogen dioxide (NOx), sulfur dioxide (SO2), particulate matter (PM2.5, PM10), total hydrocarbon (THC), and total particle number. The average concentrations of eBC, NOx, SO2, PM2.5, PM10, CO, and THC at the airport for the entire campaign were 1.07 µg m−3, 22.7 µg m−3, 4.10 µg m−3, 9.35 µg m−3, 16.43 µg m−3, 0.23 mg m−3, and 2.30 mg m−3, respectively. The source apportionment analysis of the non-refractory organic aerosol (OA) using positive matrix factorisation (PMF) allowed us to discriminate between different sources of pollution, namely less oxidised oxygenated organic aerosol (LO-OOA), alkane organic aerosol (AlkOA), and more oxidised oxygenated organic aerosol (MO-OOA). The results showed that LO-OOA and MO-OOA account for more than 80 % of the total organic particle mass measured near the runway. Trace gases correlate better with the AlkOA factor than LO-OOA and MO-OOA, indicating that AlkOA is mainly related to primary combustion emissions. Bivariate polar plots were used for pollutant source identification. Significantly higher concentrations of the obtained factors were observed at low wind speeds (<3 m s−1) from the southwest, where two of the runways and all terminals are located. Higher SO2/NOx and CO/eBC ratios were observed when the winds originated from the northeast, where the two northern runways are located. These elevated ratios are attributed to the aircraft activity being the major pollutant source in the northeast area.

Phase distribution and probabilistic risk assessment of polycyclic aromatic hydrocarbons in indoor air of coffee shops at Zahedan, Iran

Polycyclic aromatic hydrocarbons (PAHs) are a class of hydrocarbons, some of which are established human carcinogens. Human exposure to these chemicals is complex and originates from both indoor and outdoor sources. This study measured the concentration of PAHs in the gaseous and particulate phases during the cold months of 2022 using XAD-2 sorbent tubes and Polytetrafluoroethylene (PTFE) filters in the indoor air of coffee shops in Zahedan, Iran (n = 23). The average concentrations of particulate-bound PAHs and gaseous PAHs were 13,411.86 ± 6517.24 ng/m³ and 6432.76 ± 4311.72 ng/m³, respectively. Source apportionment analyses indicated that the primary sources of PAHs in coffee shops were fossil fuel combustion and environmental tobacco smoke (ETS), commonly referred to as second and third-hand smoke. The lifetime cancer risk (LTCR) of inhaled PAHs was calculated using the Monte Carlo simulation method. The mean LTCR for adults and children from inhaling these substances were 9.43 × 10-6 ± 5.06 × 10-6 and 5.34 × 10-6 ± 2.87 × 10-6, respectively. The hazard quotient (HQ) of PAHs exceeded 1. These findings highlight the need to reduce PAHs exposure in public spaces through proper health warning labels and regulated indoor smoking policies.

Anthropogenic and biogenic pollutants in a forested environment: SPRUCE-22 campaign overview

The SPRUCE-22 field campaign was conducted during July 2022 on a remote mountainous forested site in Greece to assess interactions of biogenic and anthropogenic pollutants in the Eastern Mediterranean. Particle chemical composition and size distributions along with concentrations of organic and inorganic gases were measured at high temporal resolution, while samples were collected and analyzed off-line. PM1 had a surprisingly high average concentration of 13 μg m−3 consisting primarily of organics (57%), followed by sulfate (30%), ammonium (9%), and black carbon (2%). Nitrates (both inorganic and organic) were less than 1% of the PM1 despite the relatively high NOx emissions in the Balkans. The PM2.5 concentrations at this remote site were similar and even higher than those in major cities across Greece including Athens, indicating the importance of regional transport for summertime pollution in the Eastern Mediterranean. The relatively constant average diurnal profiles of major anthropogenic pollutants are consistent with only minimal effects from local sources. Sulfates are not any more the dominant component of fine PM in Greece due to the reduction of SO2 emissions of coal-burning powerplants. The organic aerosol (OA) was quite oxidized with an average oxygen to carbon ratio (O:C) equal to 0.83. The average concentration of isoprene was 0.6 ppb, of monoterpenes 0.5 ppb, while the biogenic secondary organic aerosol factor (obtained through source apportionment analysis) was estimated to contribute 22% of the OA. Additional biogenic secondary organic aerosol (SOA) may be part of the two oxygenated OA (OOA) factors that were also identified. Radiocarbon analysis indicated that the non-fossil carbon was approximately equal to the sum of the biogenic and the more oxidized oxygenated OA, implying that the less oxidized OOA in this study was mostly associated to anthropogenic fossil fuel combustion. The biogenic SOA was quite aged (O:C equal to 0.63) and was also mostly transported to the site. Nearby new particle formation events occurred during 20 % of the days, with an average SO2 concentration of 0.3 ppb. The oxidative potential of the PM per unit of mass was quite high. The source attribution of the fine PM and the interactions among its anthropogenic and biogenic components are also discussed.

Estimation of Particulate Matter (PM10) Over Middle Indo-Gangetic Plain (Patna) of India: Seasonal Variation and Source Apportionment

Despite extensive research on particulate matter (PM) pollution in India’s Indo-Gangetic Plain (IGP), source apportionment remains challenging. This study investigates the effect of particulate matter (PM10)-associated water soluble inorganic ions (WSIIs) on ambient air concentration across the middle IGP from January to December 2018. Moreover, the seasonal fluctuation and chemical characterization of PM10 were assessed for the year 2018. The results revealed a high concentration of PM10 (156 µg/m3), exceeding the WHO and National Ambient Air Quality Standard (NAAQS) limits. The highest PM10 levels were observed during autumn, winter, summer, and the rainy season. The study identified SO42− and NH4+ as the most common WSIIs, constituting 46% and 23% of the total WSIIs. Source apportionment analysis indicated that street dust, biomass burning, and vehicle and industrial emissions together with secondary formation significantly contributed to IGP’s PM pollution. Additionally, the investigation of air mass back trajectory suggests that air quality in IGP is largely influenced by eastern and western Maritime air masses originated from the Arabian Sea, the Bay of Bengal, Gujarat, Afghanistan, Pakistan, and Bangladesh.

Air quality challenges in Central Asian urban areas: a PM2.5 source apportionment analysis in Dushanbe, Tajikistan.

This work presents the first comprehensive assessment of PM pollution sources in Dushanbe, Tajikistan. A total of 138 PM2.5 samples were collected during 2015-2016 and 2018-2019 and were analyzed through gravimetric, ED-XRF, and multi-wavelength absorption techniques. The results show that PM2.5 concentrations were substantially higher than the European annual limit value and WHO Air Quality Guidelines annual average value, with an average of 90.9 ± 68.5μgm-3. The PMF application identified eight sources of pollution that influenced PM2.5 concentration levels in the area. Coal burning (21.3%) and biomass burning (22.3%) were the dominant sources during the winter, while vehicular traffic (7.7%) contributed more during the warm season. Power plant emissions (17.5%) showed enhanced contributions during the warm months, likely due to high energy demand. Cement industry emissions (6.9%) exhibited significant contribution during the cold period of 2018-2019, while soil dust (11.3%) and secondary sulphates (11.5%) displayed increased contribution during the warm and cold months, respectively. Finally, waste burning (1.5%) displayed the lowest contribution, with no significant temporal variation. Our results highlight the significant impact of anthropogenic activities, and especially the use of coal burning for energy production (both in power plants and for residential heating), and the significant contribution of biomass burning during both warm and cold seasons.

Sources of acellular oxidative potential of water-soluble fine ambient particulate matter in the midwestern United States

Ambient fine particulate matter (PM2.5) is associated with numerous health complications, yet the specific PM2.5 chemical components and their emission sources contributing to these health outcomes are understudied. Our study analyzes the chemical composition of PM2.5 collected from five distinct locations at urban, roadside and rural environments in midwestern region of the United States, and associates them with five acellular oxidative potential (OP) endpoints of water-soluble PM2.5. Redox-active metals (i.e., Cu, Fe, and Mn) and carbonaceous species were correlated with most OP endpoints, suggesting their significant role in OP. We conducted a source apportionment analysis using positive matrix factorization (PMF) and found a strong disparity in the contribution of various emission sources to PM2.5 mass vs. OP. Regional secondary sources and combustion-related aerosols contributed significantly (> 75 % in total) to PM2.5 mass, but showed weaker contribution (43–69 %) to OP. Local sources such as parking emissions, industrial emissions, and agricultural activities, though accounting marginally to PM2.5 mass (< 10 % for each), significantly contributed to various OP endpoints (10–50 %). Our results demonstrate that the sources contributing to PM2.5 mass and health effects are not necessarily same, emphasizing the need for an improved air quality management strategy utilizing more health-relevant PM2.5 indicators.

Uncovering sources, distribution, and seasonal patterns of trace element deposition: the elemental puzzle of the western Himalayas.

The transport and deposition of atmospheric pollutants in the Himalayas have a adverse impact on the climate, cryosphere, ecosystem, and monsoon patterns. Unfortunately, there is a insufficiency of data on trace element concentrations and behaviors in the high-altitude Himalayan region, leading to limited research in this area. This study presents a comprehensive and detailed comprehension of trace element deposition, its spatial distribution, seasonal variations, and anthropogenic signals in the high-altitude Kashmir region of the Western Himalayas. Our investigation involved the analysis of 10 trace elements (Al, Cr, Mn, Fe, Co, Ni, Cu, Zn, Cd, and Pb) in glacier ice, snow pits, surface snow, and rainwater collected at various sites including Kolahoi, Thajwas, Pahalgam (Greater Himalayan ranges), and Kongdori and Shopian (Pir Panjal Ranges) during 2021.The study reveals distinct ranges of concentrations for the trace elements at different sampling sites. Our analysis of trace element concentration depth profiles in snow pits reveals seasonal fluctuations during the deposition year. The highest concentrations were found in the autumn(below 20cm) and summer (top layer), compared to the winter concentration (10-20cm). The high enrichment factors (EFs) suggest the severity of human-induced trace metal deposition in the western Himalayan region, relative to surrounding regions. Surprisingly, the concentrations and EFs of trace elements showed seasonal contradictions, with lower concentration values and higher EFs during the non-monsoon season and vice versa. A source apportionment analysis using the positive matrix factorization (PMF) technique identified five sources of trace element deposition in the region, including crustal sources (32.33%), coal combustion (15.62%), biomass burning (17.63%), traffic emission (18.8%), and industrial sources (15.6%). Additionally, the study incorporated backward trajectories coupled with δ18O using the NOAA HYSPLIT model to estimate moisture sources in the region, which suggests atmospheric pollutants predominately deposited from the large-scale atmospheric circulation from westerlies (75%) during non-monsoon season. These findings underscore the urgent need for enhanced monitoring and research efforts in the future.

Oxidative potential apportionment of atmospheric PM1: a new approach combining high-sensitive online analysers for chemical composition and offline OP measurement technique

Abstract. Source apportionment models were widely used to successfully assign highly time-resolved aerosol data to specific emissions and/or atmospheric chemical processes. These techniques are necessary for targeting the sources affecting air quality and for designing effective mitigation strategies. Moreover, evaluation of the toxicity of airborne particulate matter is important since the classically measured particulate matter (PM) concentrations appear insufficient for characterizing the impact on human health. Oxidative potential (OP) measurement has recently been developed to quantify the capability of PM to induce an oxidative imbalance in the lungs. As a result, this measurement unit could be a better proxy than PM mass concentration to represent PM toxicity. In the present study, two source apportionment analyses were performed using positive matrix factorization (PMF) from organic aerosol (OA) mass spectra measured at a 15 min time resolution using a time-of-flight aerosol chemical speciation monitor (ToF-ACSM) and from 19 trace elements measured on an hourly basis using an online metal analyser (Xact 625i). The field measurements were carried out in summer 2018. While it is common to perform PMF studies individually on ACSMs and more recently on Xact datasets, here we used a two-step methodology leading to a complete PM1 source apportionment. The outputs from both OA PMF and Xact PMF, the inorganic species concentrations from the ACSM, and the black carbon (BC) fractions (fossil fuel and wood burning) measured using an Aethalometer (AE33) were gathered into a single dataset and subjected to a combined PMF analysis. Overall, eight factors were identified, each of them corresponding to a more precise source than performing single PMF analyses. The results show that besides the high contribution of secondary ammonium sulfate (28 %) and organic nitrate (19 %), about 50 % of PM1 originated from distinct combustion sources, including emissions from traffic, shipping, industrial activities, cooking, and biomass burning. Simultaneously, PM1 filters were collected during the experimental period on a 4 h sampling basis. On these filters, two acellular OP assays were performed (dithiothreitol; OPDTT and ascorbic acid; OPAA) and an inversion method was applied on factors issued from all PMFs to assess the contribution of the PM sources to the OP. This work highlights the sensitivity of OPAA to industrial and dust resuspension sources and those of OPDTT to secondary ammonium sulfate, shipping, and biomass burning.

New measurements reveal a large contribution of nitrogenous molecules to ambient organic aerosol

AbstractNitrogen is a significant element that constitutes ambient organic aerosol. Individual N-containing organic molecules are known to have both natural and anthropogenic sources and implicated in a wide-ranging health and environmental effects. Yet, unlike carbon (C), the total quantity of aerosol organic nitrogen (ON) remains largely unquantified, hindering a quantitative understanding of their major sources and impacts. Here, aerosol ON is quantitatively surveyed in hundreds of aerosol filter samples collected from sites of varying urban influence in China using our recently developed method that permits simple, and yet sensitive, simultaneous detection of inorganic and organic nitrogen. Annual average ON concentration was in the range of 0.4–1.4 μg N m−3, representing 17–31% of aerosol total nitrogen. Monte Carlo simulations constrained by paired ON and OC measurements suggest N-containing organic molecules contributed typically 37–50%, with a 95% confidence interval of [12%, 94%], to ambient organic aerosols. Source apportionment analysis reveals that biomass burning and secondary formation are dominant ON sources, accounting for 21–24% and ~ 30% of ON, respectively. Primary biological aerosol is also a significant source of ON (7–18%), with its contribution more prominent in non-urban atmospheres. The results provide the quantitative data for the extent of presence of organic nitrogenous aerosol and the origin of their major sources. Such data, we anticipate, would bring forth a breakthrough in our ability to describe and model organic aerosols and to assess their environmental impacts, such as atmospheric nitrogen nutrient inputs to ecosystems.

Isotopic insights and integrated analysis for heavy metal levels, ecological risks, and source apportionment in river sediments of the Qinghai-Tibet Plateau

The research was carried out to examine the pollution characteristics, ecological risk, and origins of seven heavy metals (Hg, As, Pb, Cu, Cd, Zn, and Ni) in 51 sediment samples gathered from 8 rivers located on the Qinghai-Tibet Plateau (QTP) in China. The contents of Hg and Cd were 5.0 and 1.1 times higher than their background values, respectively. The mean levels of other measured heavy metals were below those found naturally in the local soil. The enrichment factor showed that the study area exhibited significantly enriched Hg with 70.6% sampling sites. The Cd contents at 19.6% of sampling sites were moderately enriched. The other sampling sites were at a less enriched level. The sediments of all the rivers had a medium level of potential ecological risk. Hg was the major ecological risk factor in all sampling sites, followed by Cd. The findings from the positive matrix factorization (PMF) analysis shown agricultural activities, industrial activities, traffic emissions, and parent material were the major sources. The upper, middle, and low reaches of the Quanji river had different Hg isotope compositions, while sediments near the middle reaches were similar to the δ202Hg of the industrial source. At the upstream sampling sites, the Hg isotope content was very close to the background level. The results of this research can establish a strong scientific sound to improve the safety of the natural circumstances of rivers on the QTP.

Positive matrix factorization of seasonally resolved organic aerosol at three different central European background sites based on nuclear magnetic resonance Aerosolomics data

Concentration data derived from 1H NMR analysis of the water-soluble organic compounds from fine aerosol (PM2.5) at three Central European background stations, Košetice, Frýdlant (both in the Czech Republic), and Melpitz (Germany), were used for detailed source apportionment analysis. Two winter and two summer episodes (year 2021) with higher organic concentrations and similar wind directions were selected for NMR analyses. The concentration profiles of 61 water-soluble organic compounds were determined by NMR Aerosolomics and a principal component analysis (PCA) was performed on this dataset. Based on the PCA results, 23 compounds were selected for positive matrix factorization (PMF) analysis in order to identify dominant aerosol sources at rural background sites in Central Europe. Both the PCA and the subsequent PMF analyses clearly distinguished the characteristics of winter and summer aerosol particles.In summer, four factors were identified from PMF and were associated with biogenic aerosol (61–78 %), background aerosol (9–15 %), industrial biomass combustion (7–13 %), and residential heating (5–13 %). In winter, only 3 factors were identified - industrial biomass combustion (33–49 %), residential heating (37–45 %) and a background aerosol (8–30 %). The main difference was observed in the winter season with a stronger contribution of emissions from industrial biomass burning at the Czech stations Košetice and Frýdlant (47–49 %) compared to the Melpitz station (33 %). However, in general, there were negligible differences in identified sources between stations in the given seasons, indicating a certain homogeneity in PM2.5 composition within Central Europe at least during the sampling periods.

Short-term source apportionment of fine particulate matter with time-dependent profiles using SoFi Pro: exploring the reliability of rolling positive matrix factorization (PMF) applied to bihourly molecular and elemental tracer data

Abstract. Positive matrix factorization (PMF) has been widely used to apportion the sources of fine particulate matter (PM2.5) by utilizing PM chemical speciation data measured at the receptor site(s). Traditional PMF, which typically relies on long-term observational datasets of daily or lower time resolution to meet the required sample size, has its reliability undermined by changes in source profiles; thus, it is inherently ill-suited for apportioning sporadic sources or ephemeral pollution events. In this study, we explored short-term source apportionment of PM2.5 using a set of bihourly chemical speciation data over a period of 37 d in the winter of 2019–2020. PMF run with campaign-wide data as input (PMFref) was initially conducted to obtain reference profiles for the primary source factors. Subsequently, short-term PMF analysis was performed using the Source Finder Professional (SoFi Pro). The analysis sets a window length of 18 d and constrained the primary source profiles using the a-value approach embedded in SoFi Pro software. Rolling PMF was then conducted with a fixed window length of 18 d and a step of 1 d using the remaining dataset. By applying the a-value constraints to the primary sources, the rolling PMF effectively reproduced the individual primary sources, as evidenced by the slope values close to unity (i.e., 0.9–1.0). However, the estimation for the firework emission factor in the rolling PMF was lower compared with PMFref (slope: 0.8). These results suggest the unique advantage of short-term PMF analysis in accurately apportioning sporadic sources. Although the total secondary sources were well modeled (slope: 1.0), larger biases were observed for individual secondary sources. The variation in source profiles indicated higher variabilities for the secondary sources, with average relative differences ranging from 42 % to 173 %, while the primary source profiles exhibited much smaller variabilities (relative differences of 8 %–26 %). This study suggests that short-term PMF analysis with the a-value constraints in SoFi Pro can be utilized to apportion primary sources accurately, while future efforts are needed to improve the prediction of individual secondary sources. Additionally, future rapid source apportionment analysis can benefit from utilizing a library of source profiles derived from existing measurement data, thereby significantly reducing the time lag associated with receptor modeling source apportionment techniques.

Unveiling vertical ozone variation with UAV-Based monitoring and modeling: A new challenge for city-level ozone pollution control in the pearl river delta region

Ozone distribution and variation within the Planetary Boundary Layer (PBL) present challenges for air quality management. UAV-based ozone profile measurements offer advantages in terms of high vertical resolution throughout the PBL and flexibility. However, previous studies on vertical variation in the Pearl River Delta (PRD) region have rarely focused on measuring the vertical ozone variation during ozone pollution episodes. In this study, we integrated UAV-based monitoring, ground monitoring, and numerical modeling to investigate ozone variation, driving processes, and source regions of pollution episodic period. UAV-based observations during a 2021 ozone episode at rural areas in the PRD region revealed three ozone profiles: increasing, well-mixed, and decreasing with height. Morning profiles showed multiple layers influenced by meteorology, while peak ozone hours exhibited a well-mixed pattern. By integrating the validated numerical model, we found that chemical processes (CHEM) contributed positively to ozone episodes in both rural and urban scenarios, especially at the middle and upper PBL. Horizontal advection (HADV) significantly contributes to the episode in rural cases, while urban cases were significantly affected by vertical diffusion (VDIF). Backward trajectory and source apportionment analyses categorized PRD cities into upwind/non-upwind/local categories, showing ozone pollution originating from both upwind and non-upwind cities at different vertical levels. It is because wind shear influenced diverse source regions, and the transport channel for city-level ozone pollution exhibited daily and vertical changes. Moreover, it could also be contributed by the formed regional mixing ozone layer (ROM Layer) throughout the PBL during persistent ozone episodes, triggered by enhanced CHEM and significantly contributed by the VDIF. The ROM Layer at center cities, influencing ground-level ozone downwind through horizontal transport and vertical exchange. Considering the complex three-dimensional transport of ozone and the ROM Layer phenomenon, city-level management or regional co-control based on simple transport channels may be insufficient. Emissions control measures should cover all cities or target significant emitters to address regional ozone pollution.