ABSTRACT
To elucidate the characteristics of VOCs chemical components during heavy pollution episodes, hourly online VOCs data derived from 11 heavy pollution events in Tianjin from 2019 to 2020 were employed. The positive matrix factorization ï¼PMFï¼ and conditional bivariate probability function ï¼CBPFï¼ were employed to analyze the sources of VOCs during heavy pollution episodes. The results indicated that the average VOCs volume fraction during these episodes was recorded at 35.7×10-9. Furthermore, it was observed that during the winter emergency response period, there was a discernible increase in the volume fraction of VOCs when compared to that during the autumn season. Specifically, there was a notable upswing of 48% in the olefins category, whereas alkanes registered a 4% increase. Additionally, the VOCs component structure changed significantly during the heavy pollution episodes. During the orange warning period, the proportion of alkanes increased by 36%, and the proportion of acetylene decreased by 32%. During the yellow warning period, the proportion of alkanes increased by 14%, and the proportion of acetylene decreased by 5%. During the emergency response period, motor vehicle emission sources, natural gas evaporative sources, and solvent use sources were the main contributors of VOCs in environmental receptors, contributing 17.5%, 15.4%, and 15.2%, respectively. Compared with that during the period antecedent to the emergency response, the contribution of vehicle emission sources and diesel volatile sources to VOCs in environmental receptors decreased by 2.0% to 5.5% and 2.1% to 6.6%, respectively, and the contribution of solvent use sources decreased by 0.2% to 2.4% during the yellow warning period. During the orange warning period, the contribution of motor vehicle emission sources was reduced by 0.1% to 8.3%, and the contribution of solvent use sources was reduced by 0.5% to 6.2%.
Subject(s)
Air Pollutants , Environmental Monitoring , Vehicle Emissions , Volatile Organic Compounds , China , Environmental Monitoring/methods , Air Pollutants/analysis , Volatile Organic Compounds/analysis , Vehicle Emissions/analysis , Air Pollution/analysis , SeasonsABSTRACT
Dual isotopes of nitrogen and oxygen of NO3- are crucial tools for quantifying the formation pathways and precursor NOx sources contributing to atmospheric nitrate. However, further research is needed to reduce the uncertainty associated with NOx proportional contributions. The acquisition of nitrogen isotopic composition from NOx emission sources lacks regulation, and its impact on the accuracy of contribution results remains unexplored. This study identifies key influencing factors of source isotopic composition through statistical methods, based on a detailed summary of δ15N-NOx values from various sources. NOx emission sources are classified considering these factors, and representative means, standard deviations, and 95 % confidence intervals are determined using the bootstrap method. During the sampling period in Tianjin in 2022, the proportional nitrate formation pathways varied between sites. For suburban and coastal sites, the ranking was [Formula: see text] (NO2 + OH radical) > [Formula: see text] (N2O5 + H2O) > [Formula: see text] (NO3 + DMS/HC), while the rural site exhibited similar fractional contributions from all three formation pathways. Fossil fuel NOx sources consistently contributed more than non-fossil NOx sources in each season among three sites. The uncertainties in proportional contributions varied among different sources, with coal combustion and biogenic soil emission showing lower uncertainties, suggesting more stable proportional contributions than other sources. The sensitivity analysis clearly identifies that the isotopic composition of 15N-enriched and 15N-reduced sources significantly influences source contribution results, emphasizing the importance of accurately characterizing the localized and time-efficient nitrogen isotopic composition of NOx emission sources. In conclusion, this research sheds light on the importance of addressing uncertainties in NOx proportional contributions and emphasizes the need for further exploration of nitrogen isotopic composition from NOx emission sources for accurate atmospheric nitrate studies.
ABSTRACT
Civil airports are recognized as significant contributors to fine particulate matter, especially ultra-fine particulate matter (UFP). The pollutants from airport activities have a notable adverse impact on global climate, urban air quality, and public health. However, there is a lack of practical observational studies on the characterization of integrated pollutant emissions from large civil airports. This study aims to focus on the combined emission characteristics of particulate number concentration (PNC), size distribution, and components at a large civil airport, especially UFP. The findings reveal that airport activities significantly contribute to elevated PNC levels during aircraft activity in downwind conditions (four times higher than background levels) and upwind conditions (7.5 times higher). UFP dominates the PNC around the airport. The particle size distribution shows two peaks occurring around 10-30 nm and 60-80 nm. Notably, particles within the ranges of 17-29 nm and 57-101 nm account for 65.9 % and 12.0 % of the total PNC respectively. Aircraft landing has the greatest impact on particles sized between 6 and 17 nm while takeoff affects particles sized between 29 and 57 nm resulting in a respective increase in PNC by factors of approximately 3.27 and 35.4-fold increase compared to background levels. Different aircraft types exhibit varying effects on PNC with A320 and A321 showing more pronounced effects during takeoff and landing.The presence of airports leads to roughly five-fold rise in elemental component concentrations with Si being highest followed by OC, Ca, Al, Fe, Ca2+, EC, and Mg2+. The OC/EC ratio under high aircraft activity in downwind conditions falls within range of approximately 2.5-3.5. These characteristic components and ratio can be considered as identifying species for civil airports. PMF model show about 75 % of the particulate emissions at the airport boundary were related to airport activities.
ABSTRACT
Air pollution over the oceans has received less attention compared to densely populated urban areas of continents. The Bohai Sea, a semi-enclosed sea in northern China, is surrounded by thirteen industrial cities that have experienced significant improvements in air quality over the past decade. However, the changes in air pollution over the Bohai Sea and its impacts on surrounding cities remain poorly understood. To address this, this study investigated the evolution of air pollution and its chemical composition in the Bohai Sea over four decades, utilizing satellite remote sensing data, reanalysis datasets, emissions inventories, and statistical modeling. Historically, the region has suffered from severe air pollution, resulting from a combination of continental emissions and marine inputs (e.g., sea salt, ports and maritime vessel activities). The aerosol optical depth (AOD) over the sea was higher than the mean levels observed in its surrounding coastal cities. Statistically, 45% of the air masses reaching the Bohai Sea are associated with natural sources (dust- and marine-rich), while the remainder carry anthropogenic pollutants from continental regions. With the exception of Cangzhou city, these coastal cities suffer from air pollutants originating from the Bohai Sea. Cities in the northern region of the sea, spanning from Tianjin to Yingkou, are particularly impacted. The majority of the surrounding cities are affected by a large proportion of anthropogenic aerosol types transported through air masses from the Bohai Sea, including those from biomass burning and industrial activities. These findings emphasize the considerable influence of human-induced sources in the Bohai Sea on neighboring urban areas. Furthermore, being a maritime region, natural sources like sea salt and dust from the sea may also exert a discernible impact on the neighboring environment.
Subject(s)
Air Pollutants , Air Pollution , Humans , Cities , Air Pollutants/analysis , Dust/analysis , Air Pollution/analysis , China , Aerosols/analysis , Environmental Monitoring/methodsABSTRACT
The role of chloride in atmospheric chemistry received increased attention over recent years. Given the primary and chemical-active nature of PM2.5-bound chlorine (p-Cl-), it makes sense to get to know the sources and processes of p-Cl-. The temporal behavior of observed p-Cl- concentration based on 1-h high resolution exhibited seasonal variation of high in winter, low in summer and diurnal variation of high in the morning, low in afternoon. Meteorological normalization technique based on random forest was used to disentangle the effects of emission changes which affected the seasonal variation and meteorology which was related to diurnal variation on p-Cl-. Generalized additive model (GAM) identified RH and temperature as the key meteorological factors of p-Cl- generation, and p-Cl- pollution was serious under the condition of low temperature and high RH. Dispersion-normalized positive matrix factorization (DN-PMF) was used to apportion the p-Cl- to its sources, finding that coal combustion was the main source of p-Cl-, followed by biomass burning and industrial process emissions. Our results will provide the basis for further analysis the causes of p-Cl- pollution and composite air pollution control strategies.
Subject(s)
Air Pollutants , Air Pollution , Air Pollutants/analysis , Air Pollution/analysis , China , Chlorides , Chlorine/analysis , Coal/analysis , Environmental Monitoring , Meteorology , Particulate Matter/analysis , Seasons , Vehicle Emissions/analysisABSTRACT
Sand and dust storms (SDS) frequently hit northern China and adversely impact both environment and health. The carbonaceous components, inorganic elements, water-soluble ions, and meteorological parameters of several severe SDS episodes have been measured in a supersite in Tianjin, which is a big and representative city located in SDS transmission pathway in northern China. Six SDS episodes were identified in Spring, 2021. The maximum PM10 mass concentration was 2684 and 1664 µg/m3 in SDS1 and SDS3, respectively. North and northwest wind was dominant and significant differences were found in wind speed and RH between the SDS and non-SDS episodes. North dust from Inner Mongolia and Mongolia was determined by back trajectory analysis as the probable source region. The mass concentration of SO42-, NO3-, and NH4+ decreased in PM2.5. Increase of Na+ and K+ and low SO42-SDS/ SO42-non-SDS indicate dust source for short length SDS transmission in northern China. The ratio of elements could also be used to distinguish SDS and non-SDS episodes identify north and northwest source for the SDS episodes. Pb/Al, Zn/Al, and Si/Al could be regarded as indicators for SDS and non-SDS episodes, Ca/Al and Ca/Si can help to indicate SDS source direction. This study provides a variety of evidences for the dust source identification and reveals the characteristics of the most severe SDS episodes of the decade in Tianjin during Spring 2021.
Subject(s)
Air Pollutants , Particulate Matter , Aerosols/analysis , Air Pollutants/analysis , China , Dust/analysis , Environmental Monitoring , Ions/analysis , Particulate Matter/analysis , Sand , SeasonsABSTRACT
Conventional factor analyses can present problems in cases with changing numbers of sources and/or time-dependent source compositions. There is also lack of a reliable method to estimate uncertainties in the source contributions derived by positive matrix factorization (PMF). Applying a moving window evolving PMF to hourly PM2.5 composition dataset from a field campaign in Tianjin China that included the Spring and Lantern Festivals and the start of COVID-19 pandemic has substantially improved the apportionment compared to a conventional analysis using the entire data. Festival-related sources (e.g., fireworks and residential burning here) have been clearly identified and estimated during both the Spring and Lantern Festivals. During this period, the sources changed because the time period overlaps with the outbreak of COVID-19 and related reductions in activity during the lockdown that began on Lunar New Year. Multiple PMF runs providing source contribution estimates made it possible to estimate the uncertainties in these values. Our results show that winds-dependent sources like dust and distant point sources have larger uncertainties than the other sources. Compared with conventional PMF analyses, the current method may better reflect the actual emissions as well as being able to estimate uncertainties. Thus, this approach appears to be an improvement if the appropriate data are available.