Prediction of the Response of a Photoionization Detector to a Complex Gaseous Mixture of Volatile Organic Compounds Produced by α-Pinene Oxidation.

Photoionization detectors (PIDs) are lightweight and respond in real time to the concentrations of volatile organic compounds (VOCs), making them suitable for environmental measurements on many platforms. However, the nonselective sensing mechanism of PIDs challenges data interpretation, particularly when exposed to the complex VOC mixtures prevalent in the Earth's atmosphere. Herein, two approaches to this challenge are investigated. In the first, quantum-chemistry calculations are used to estimate photoionization cross sections and ionization potentials of individual species. In the second, machine learning models are trained on these calculated values, as well as empirical PID response factors, and then used for prediction. For both approaches, the resulting information for individual species is used to model the overall PID response to a complex VOC mixture. In complement, laboratory experiments in the Harvard Environmental Chamber are carried out to measure the PID response to the complex molecular mixture produced by α-pinene oxidation under various conditions. The observations show that the measured PID response is 15% to 30% smaller than the PID response modeled by quantum-chemistry calculations of the photoionization cross section for the photo-oxidation experiments and 15% to 20% for the ozonolysis experiments. By comparison, the measured PID response is captured within a 95% confidence interval by the use of machine learning to model the PID response based on the empirical response factor in all experiments. Taken together, the results of this study demonstrate the application of machine learning to augment the performance of a nonselective chemical sensor. The approach can be generalized to other reactive species, oxidants, and reaction mechanisms, thus enhancing the utility and interpretability of PID measurements for studying atmospheric VOCs.

Accounting for Cloud Nucleation Activation Mechanism of Secondary Organic Matter from α-Pinene Oxidation Using Experimentally Retrieved Water Solubility Distributions.

Activation of cloud droplets of aerosol particles from biogenic precursors plays a critical role in Earth's climate system. However, the molecular-level understanding of the cloud condensation nuclei (CCN) activation process for secondary organic matter (SOM) is still lacking. Here, we reduced the gap by segregating SOM from α-pinene based on water solubility. The chemical composition and CCN activity of the solubility-segregated fractions of SOM were measured. The results demonstrated for the first time by laboratory experiment that highly oxygenated compounds such as hydroperoxides and highly oxygenated organic molecules are important contributors for the CCN activity of α-pinene SOM. Meanwhile, relatively less water-soluble species were also abundant. Analysis based on the Köhler theory demonstrated that less water-soluble compounds in SOM remain undissolved during the cloud activation process, suggesting that the traditional single-parameter parameterization for CCN activation would not be sufficient for representing the process. In combination with the recent developments in SOM formation chemistry, the present study helps in understanding the interactions between the biosphere and climate.

Machine Learning for Ionization Potentials and Photoionization Cross Sections of Volatile Organic Compounds.

Molecular ionization potentials (IP) and photoionization cross sections (σ) can affect the sensitivity of photoionization detectors (PIDs) and other sensors for gaseous species. This study employs several methods of machine learning (ML) to predict IP and σ values at 10.6 eV (117 nm) for a dataset of 1251 gaseous organic species. The explicitness of the treatment of the species electronic structure progressively increases among the methods. The study compares the ML predictions of the IP and σ values to those obtained by quantum chemical calculations. The ML predictions are comparable in performance to those of the quantum calculations when evaluated against measurements. Pretraining further reduces the mean absolute errors (ε) compared to the measurements. The graph-based attentive fingerprint model was most accurate, for which εIP = 0.23 ± 0.01 eV and εσ = 2.8 ± 0.2 Mb compared to measurements and computed cross sections, respectively. The ML predictions for IP correlate well with both the measured IPs (R 2 = 0.88) and with IPs computed at the level of M06-2X/aug-cc-pVTZ (R 2 = 0.82). The ML predictions for σ correlated reasonably well with computed cross sections (R 2 = 0.66). The developed ML methods for IP and σ values, representing the properties of a generalizable set of volatile organic compounds (VOCs) relevant to industrial applications and atmospheric chemistry, can be used to quantitatively describe the species-dependent sensitivity of chemical sensors that use ionizing radiation as part of the sensing mechanism, such as photoionization detectors.

Chemical Signatures of Seasonally Unique Anthropogenic Influences on Organic Aerosol Composition in the Central Amazon.

Urbanization and fires perturb the quantities and composition of fine organic aerosol in the central Amazon, with ramifications for radiative forcing and public health. These disturbances include not only direct emissions of particulates and secondary organic aerosol (SOA) precursors but also changes in the pathways through which biogenic precursors form SOA. The composition of ambient organic aerosol is complex and incompletely characterized, encompassing millions of potential structures relatively few of which have been synthesized and characterized. Through analysis of submicron aerosol samples from the Green Ocean Amazon (GoAmazon2014/5) field campaign by two-dimensional gas chromatography coupled with machine learning, ∼1300 unique compounds were traced and characterized over two seasons. Fires and urban emissions produced chemically and interseasonally distinct impacts on product signatures, with only ∼50% of compounds observed in both seasons. Seasonally unique populations point to the importance of aqueous processing in Amazonian aerosol aging, but further mechanistic insights are impeded by limited product identity knowledge. Less than 10% of compounds were identifiable at an isomer-specific level. Overall, the findings (i) provide compositional characterization of anthropogenic influence on submicron organic aerosol in the Amazon, (ii) identify key season-to-season differences in chemical signatures, and (iii) highlight high-priority knowledge gaps in current speciated knowledge.

The feedback effects of aerosols from different sources on the urban boundary layer in Beijing China.

The interaction of aerosols and the planetary boundary layer (PBL) plays an important role in deteriorating urban air quality. Aerosols from different sources may have different effects on regulating PBL structures owing to their distinctive dominant compositions and vertical distributions. To characterize the complex feedback of aerosols on PBL over the Beijing megacity, multiple approaches, including in situ observations in the autumn and winter of 2016-2019, backward trajectory clusters, and large-eddy simulations, were adopted. The results revealed notable distinctions in aerosol properties, vertical distributions and thermal stratifications among three types of air masses from the West Siberian Plain (Type-1), Central Siberian Plateau (Type-2) and Mongolian Plateau (Type-3). Low loadings of 0.28 ± 0.26 and 0.15 ± 0.08 of aerosol optical depth (AOD) appeared in the Type-1 and Type-2, accompanied by cool and less stable stratification, with a large part (80%) of aerosols concentrated below 1500 m. For Type-3, the AOD and single scattering albedo (SSA) were as high as 0.75 ± 0.54 and 0.91 ± 0.05, demonstrating severe pollution levels of abundant scattering aerosols. Eighty percent of the aerosols were constrained within a lower height of 1150 m owing to the warmer and more stable environment. Large-eddy simulations revealed that aerosols consistently suppressed the daytime convective boundary layer regardless of their origins, with the PBL height (PBLH) decreasing from 1120 m (Type-1), 1160 m (Type-2) and 820 m (Type-3) in the ideal clean scenarios to 980 m, 1100 m and 600 m, respectively, under polluted conditions. Therefore, the promotion of absorbing aerosols below the residual layer on PBL could be greatly hindered by the suppression effects generated by both absorbing aerosols in the upper temperature inversion layer and scattering aerosols. Moreover, the results indicated the possible complexities of aerosol-PBL interactions under future emission-reduction scenarios and in other urban regions.

Size Dependence of Liquid-Liquid Phase Separation by in Situ Study of Flowing Submicron Aerosol Particles.

Liquid-liquid phase separation (LLPS) of atmospheric particles impacts a range of atmospheric processes. Driven by thermodynamics, LLPS occurs in mixed organic-inorganic particles when high inorganic salt concentrations exclude organic compounds, which develop into a separate phase. The effect of particle size on the thermodynamic and kinetic drivers of LLPS, however, remains incompletely understood. Here, the size dependence was studied for the separation relative humidity (SRH) of LLPS. Submicron organic-inorganic aerosol particles of ammonium sulfate mixed with 1,2,6-hexanetriol and polyethylene glycol (PEG) were studied. In a flow configuration, upstream size selection was coupled to a downstream fluorescence aerosol flow tube (F-AFT) at 293 ± 1 K. For both mixed particle types, the SRH values for submicron particle diameters of 260-410 nm agreed with previous measurements reported in the literature for supermicron particles. For smaller particles, the SRH values decreased by approximately 5% RH for diameters of 130-260 nm for PEG-sulfate particles and of 70-190 nm for hexanetriol-sulfate particles. From these observations, the nucleation rate in the hexanetriol-sulfate system was constrained, implying an activation barrier to nucleation of +1.4 to +2.0 × 10-19 J at 70% RH and 293 K. Quantifying the activation barrier is an approach for predicting size-dependent LLPS in the atmosphere.

River Winds and Transport of Forest Volatiles in the Amazonian Riparian Ecoregion.

Volatile organic compounds (VOCs) emitted from forests are important chemical components that affect ecosystem functioning, atmospheric chemistry, and regional climate. Temperature differences between a forest and an adjacent river can induce winds that influence VOC fate and transport. Quantitative observations and scientific understanding, however, remain lacking. Herein, daytime VOC datasets were collected from the surface up to 500 m over the "Rio Negro" river in Amazonia. During time periods of river winds, isoprene, α-pinene, and ß-pinene concentrations increased by 50, 60, and 80% over the river, respectively. The concentrations at 500 m were up to 80% greater compared to those at 100 m because of the transport path of river winds. By comparison, the concentration of methacrolein, a VOC oxidation product, did not depend on river winds or height. The differing observations for primary emissions and oxidation products can be explained by the coupling of timescales among emission, reaction, and transport. This behavior was captured in large-eddy simulations with a coupled chemistry model. The observed and simulated roles of river winds in VOC fate and transport highlight the need for improved representation of these processes in regional models of air quality and chemistry-climate coupling.

Partitioning of Organonitrates in the Production of Secondary Organic Aerosols from α-Pinene Photo-Oxidation.

The chemical pathways for the production of secondary organic aerosols (SOA) are influenced by the concentration of nitrogen oxides (NOx), including the production of organonitrates (ON). Herein, a series of experiments conducted in an environmental chamber investigated the production and partitioning of total organonitrates from α-pinene photo-oxidation from <1 to 24 ppb NOx. Gas-phase and particle-phase organonitrates (gON and pON, respectively) were measured by laser-induced fluorescence (LIF). The composition of the particle phase and the particle mass concentration were simultaneously characterized by online aerosol mass spectrometry. The LIF and MS measurements of pON concentrations had a Pearson correlation coefficient of 0.91 from 0.3 to 1.1 µg m-3. For 1-6 ppb NOx, the yield of SOA particle mass concentration increased from 0.02 to 0.044 with NOx concentration. For >6 ppb NOx, the yield steadily dropped, reaching 0.034 at 24 ppb NOx. By comparison, the yield of pON steadily increased from 0.002 to 0.022 across the range of investigated NOx concentrations. The yield of gON likewise increased from 0.005 to 0.148. The gas-to-particle partitioning ratio (pON/(pON + gON)) depended strongly on the NOx concentration, changing from 0.27 to 0.13 as the NOx increased from <1 to 24 ppb. In the atmosphere, there is typically a cross-over point between clean and polluted conditions that strongly affects SOA production, and the results herein quantitatively identify 6 ppb NOx as that point for α-pinene photo-oxidation under these study conditions, including the production and partitioning of organonitrates. The trends in SOA yield and partitioning ratio as a function of NOx occur because of the changes in pON volatility.

Phase Behavior of Internal Mixtures of Hydrocarbon-like Primary Organic Aerosol and Secondary Aerosol Based on Their Differences in Oxygen-to-Carbon Ratios.

The phase behavior, the number and type of phases, in atmospheric particles containing mixtures of hydrocarbon-like organic aerosol (HOA) and secondary organic aerosol (SOA) is important for predicting their impacts on air pollution, human health, and climate. Using a solvatochromic dye and fluorescence microscopy, we determined the phase behavior of 11 HOA proxies (O/C = 0-0.29) each mixed with 7 different SOA materials generated in environmental chambers (O/C 0.4-1.08), where O/C represents the average oxygen-to-carbon atomic ratio. Out of the 77 different HOA + SOA mixtures studied, we observed two phases in 88% of the cases. The phase behavior was independent of relative humidity over the range between 90% and <5%. A clear trend was observed between the number of phases and the difference between the average O/C ratios of the HOA and SOA components (ΔO/C). Using a threshold ΔO/C of 0.265, we were able to predict the phase behavior of 92% of the HOA + SOA mixtures studied here, with one-phase particles predicted for ΔO/C < 0.265 and two-phase particles predicted for ΔO/C ≥ 0.265. The threshold ΔO/C value provides a relatively simple and computationally inexpensive framework for predicting the number of phases in internal SOA and HOA mixtures in atmospheric models.

Rapid growth of anthropogenic organic nanoparticles greatly alters cloud life cycle in the Amazon rainforest.

Aerosol-cloud interactions remain uncertain in assessing climate change. While anthropogenic activities produce copious aerosol nanoparticles smaller than 10 nanometers, they are too small to act as efficient cloud condensation nuclei (CCN). The mechanisms responsible for particle growth to CCN-relevant sizes are poorly understood. Here, we present aircraft observations of rapid growth of anthropogenic nanoparticles downwind of an isolated metropolis in the Amazon rainforest. Model analysis reveals that the sustained particle growth to CCN sizes is predominantly caused by particle-phase diffusion-limited partitioning of semivolatile oxidation products of biogenic hydrocarbons. Cloud-resolving numerical simulations show that the enhanced CCN concentrations in the urban plume substantially alter the formation of shallow convective clouds, suppress precipitation, and enhance the transition to deep convective clouds. The proposed nanoparticle growth mechanism, expressly enabled by the abundantly formed semivolatile organics, suggests an appreciable impact of anthropogenic aerosols on cloud life cycle in previously unpolluted forests of the world.

How do aerosols above the residual layer affect the planetary boundary layer height?

We revealed that the absorption aerosol lying below or above the morning residual layer (MRL) promotes (stove effect, heating the MRL layer) or strongly inhibits (dome effect, heating the temperature inversion layer) the development of planetary boundary layer (PBL) after sunrise, while scattering aerosol exhibits similar suppression (surface or aloft umbrella effect) on the PBL regardless of its vertical location. However, the role of different type of aerosols (i.e., strong absorption aerosol and purely scattering aerosol) present from MRL to upper atmosphere remains lacking and therefore, needs to be further explored. Utilizing a large-eddy simulation model constrained by the in-situ observations in urban Beijing, we observed that the dome inhibition of absorption aerosols on PBL development becomes weaker as elevating the aerosol layer, and the effect (virtual dome effect) remains no change beyond a certain height, which is defined as the dome effective height z. This height z is highly related to the surface sensible heat flux. By comparison, the altitude of light-scattering aerosols relative to the MRL was less important. The scattering aerosols exhibit similar inhibition from MRL to upper atmosphere (aloft umbrella effect), but to a weaker extent than the virtual dome effect. The virtual dome effect and aloft umbrella effect play a leading role during some extremely polluted scenarios with deep aerosol layer, such as sandstorms and volcanic eruptions. Aerosol dome, virtual dome, and aloft umbrella effects, together with aerosol stove and surface umbrella effects, further advance the understanding on aerosol-PBL interactions, which is, more broadly, applied to interpret the impact of aerosol on PBL over other ecosystems as well as exoplanet atmospheres.

Humidity Dependence of the Condensational Growth of α-Pinene Secondary Organic Aerosol Particles.

The influence of relative humidity (RH) on the condensational growth of organic aerosol particles remains incompletely understood. Herein, the RH dependence was investigated via a series of experiments for α-pinene ozonolysis in a continuously mixed flow chamber in which recurring cycles of particle growth occurred every 7 to 8 h at a given RH. In 5 h, the mean increase in the particle mode diameter was 15 nm at 0% RH and 110 nm at 75% RH. The corresponding particle growth coefficients, representing a combination of the thermodynamic driving force and the kinetic resistance to mass transfer, increased from 0.35 to 2.3 nm2 s-1. The chemical composition, characterized by O:C and H:C atomic ratios of 0.52 and 1.48, respectively, and determined by mass spectrometry, did not depend on RH. The Model for Simulating Aerosol Interactions and Chemistry (MOSAIC) was applied to reproduce the observed size- and RH-dependent particle growth by optimizing the diffusivities Db within the particles of the condensing molecules. The Db values increased from 5 α-1 × 10-16 at 0% RH to 2 α-1 × 10-12 cm-2 s-1 at 75% RH for mass accommodation coefficients α of 0.1 to 1.0, highlighting the importance of particle-phase properties in modeling the growth of atmospheric aerosol particles.

Aqueous production of secondary organic aerosol from fossil-fuel emissions in winter Beijing haze.

Secondary organic aerosol (SOA) produced by atmospheric oxidation of primary emitted precursors is a major contributor to fine particulate matter (PM2.5) air pollution worldwide. Observations during winter haze pollution episodes in urban China show that most of this SOA originates from fossil-fuel combustion but the chemical mechanisms involved are unclear. Here we report field observations in a Beijing winter haze event that reveal fast aqueous-phase conversion of fossil-fuel primary organic aerosol (POA) to SOA at high relative humidity. Analyses of aerosol mass spectra and elemental ratios indicate that ring-breaking oxidation of POA aromatic species, leading to functionalization as carbonyls and carboxylic acids, may serve as the dominant mechanism for this SOA formation. A POA origin for SOA could explain why SOA has been decreasing over the 2013-2018 period in response to POA emission controls even as emissions of volatile organic compounds (VOCs) have remained flat.

Synergistic Uptake by Acidic Sulfate Particles of Gaseous Mixtures of Glyoxal and Pinanediol.

The uptake of gaseous organic species by atmospheric particles can be affected by the reactive interactions among multiple co-condensing species, yet the underlying mechanisms remain poorly understand. Here, the uptake of unary and binary mixtures of glyoxal and pinanediol by neutral and acidic sulfate particles is investigated. These species are important products from the oxidation of volatile organic compounds (VOCs) under atmospheric conditions. The uptake to acidic aerosol particles greatly increased for a binary mixture of glyoxal and pinanediol compared to the unary counterparts. The strength of the synergism depended on the particle acidity and water content (i.e., relative humidity). The greater uptake was up to 2.5× to 8× at 10% relative humidity (RH) for glyoxal and pinanediol, respectively. At 50% RH, it was 2× and 1.2× for the two species. Possible mechanisms of acid-catalyzed cross reactions between the species are proposed to explain the synergistic uptake. The proposed mechanisms are applicable to a broader extent across atmospheric species having carbonyl and hydroxyl functionalities. The results thus suggest that synergistic uptake reactions can be expected to significantly influence the gas-particle partitioning of VOC oxidation products under atmospheric conditions and thus greatly affect their atmospheric transport and lifetime.

Fast sulfate formation from oxidation of SO2 by NO2 and HONO observed in Beijing haze.

Severe events of wintertime particulate air pollution in Beijing (winter haze) are associated with high relative humidity (RH) and fast production of particulate sulfate from the oxidation of sulfur dioxide (SO2) emitted by coal combustion. There has been considerable debate regarding the mechanism for SO2 oxidation. Here we show evidence from field observations of a haze event that rapid oxidation of SO2 by nitrogen dioxide (NO2) and nitrous acid (HONO) takes place, the latter producing nitrous oxide (N2O). Sulfate shifts to larger particle sizes during the event, indicative of fog/cloud processing. Fog and cloud readily form under winter haze conditions, leading to high liquid water contents with high pH (>5.5) from elevated ammonia. Such conditions enable fast aqueous-phase oxidation of SO2 by NO2, producing HONO which can in turn oxidize SO2 to yield N2O.This mechanism could provide an explanation for sulfate formation under some winter haze conditions.

Leaf isoprene and monoterpene emission distribution across hyperdominant tree genera in the Amazon basin.

Tropical forests are acknowledged to be the largest global source of isoprene (C5H8) and monoterpenes (C10H16) emissions, with current synthesis studies suggesting few tropical species emit isoprenoids (20-38%) and do so with highly variable emission capacities, including within the same genera. This apparent lack of a clear phylogenetic thread has created difficulties both in linking isoprenoid function with evolution and for the development of accurate biosphere-atmosphere models. Here, we present a systematic emission study of "hyperdominant" tree species in the Amazon Basin. Across 162 individuals, distributed among 25 botanical families and 113 species, isoprenoid emissions were widespread among both early and late successional species (isoprene: 61.9% of the species; monoterpenes: 15.0%; both isoprene and monoterpenes: 9.7%). The hyperdominant species (69) across the top five most abundant genera, which make up about 50% of all individuals in the Basin, had a similar abundance of isoprenoid emitters (isoprene: 63.8%; monoterpenes: 17.4%; both 11.6%). Among the abundant genera, only Pouteria had a low frequency of isoprene emitting species (15.8% of 19 species). In contrast, Protium, Licania, Inga, and Eschweilera were rich in isoprene emitting species (83.3% of 12 species, 61.1% of 18 species, 100% of 8 species, and 100% of 12 species, respectively). Light response curves of individuals in each of the five genera showed light-dependent, photosynthesis-linked emission rates of isoprene and monoterpenes. Importantly, in every genus, we observed species with light-dependent isoprene emissions together with monoterpenes including ß-ocimene. These observations support the emerging view of the evolution of isoprene synthases from ß-ocimene synthases. Our results have important implications for understanding isoprenoid function-evolution relationships and the development of more accurate Earth System Models.

Natural and Anthropogenically Influenced Isoprene Oxidation in Southeastern United States and Central Amazon.

Anthropogenic emissions alter secondary organic aerosol (SOA) formation chemistry from naturally emitted isoprene. We use correlations of tracers and tracer ratios to provide new perspectives on sulfate, NOx, and particle acidity influencing isoprene-derived SOA in two isoprene-rich forested environments representing clean to polluted conditions-wet and dry seasons in central Amazonia and Southeastern U.S. summer. We used a semivolatile thermal desorption aerosol gas chromatograph (SV-TAG) and filter samplers to measure SOA tracers indicative of isoprene/HO2 (2-methyltetrols, C5-alkene triols, 2-methyltetrol organosulfates) and isoprene/NOx (2-methylglyceric acid, 2-methylglyceric acid organosulfate) pathways. Summed concentrations of these tracers correlated with particulate sulfate spanning three orders of magnitude, suggesting that 1 µg m-3 reduction in sulfate corresponds with at least ∼0.5 µg m-3 reduction in isoprene-derived SOA. We also find that isoprene/NOx pathway SOA mass primarily comprises organosulfates, ∼97% in the Amazon and ∼55% in Southeastern United States. We infer under natural conditions in high isoprene emission regions that preindustrial aerosol sulfate was almost exclusively isoprene-derived organosulfates, which are traditionally thought of as representative of an anthropogenic influence. We further report the first field observations showing that particle acidity correlates positively with 2-methylglyceric acid partitioning to the gas phase and negatively with the ratio of 2-methyltetrols to C5-alkene triols.

Unified Description of Diffusion Coefficients from Small to Large Molecules in Organic-Water Mixtures.

Diffusion coefficients in mixtures of organic molecules and water are needed for many applications, ranging from the environmental modeling of pollutant transport, air quality, and climate, to improving the stability of foods, biomolecules, and pharmaceutical agents for longer use and storage. The Stokes-Einstein relation has been successful for predicting diffusion coefficients of large molecules in organic-water mixtures from viscosity, yet it routinely underpredicts, by orders of magnitude, the diffusion coefficients of small molecules in organic-water mixtures. Herein, a unified description of diffusion coefficients of large and small molecules in organic-water mixtures, based on the fractional Stokes-Einstein relation, is presented. A fractional Stokes-Einstein relation is able to describe 98% of the observed diffusion coefficients from small to large molecules, roughly within the uncertainties of the measurements. The data set used in the analysis includes a wide range of radii of diffusing molecules, viscosities, and intermolecular interactions. As a case study, we show that the degradation of polycyclic aromatic hydrocarbons (PAHs) by O3 within organic-water particles in the planetary boundary layer is relatively short (≲1 day) when the viscosity of the particle is ≲102 Pa s. We also show that the degradation times predicted using the Stokes-Einstein relation and the fractional Stokes-Einstein relation can differ by up to a factor of 10 in this region of the atmosphere.

Impact of biomass burning on a metropolitan area in the Amazon during the 2015 El Niño: The enhancement of carbon monoxide and levoglucosan concentrations.

Extreme droughts associated with changes in the climate have occurred every 5 years in the Amazon during the 21st century, with the most severe being in 2015. The increase in biomass burning (BB) events that occurred during the 2015 drought had several negative socioeconomic and environmental impacts, one of which was a decrease in the air quality. This study is an investigation into the air quality in the Manaus Metropolitan Region (MMR) (central Amazon, Brazil) during the dry (September to October) and wet (April to May) seasons of 2015 and 2016. A strong El Niño event began during the wet season of 2015 and ended during the wet season of 2016. Particulate matter samples were collected in the MMR during 2015 and 2016, and analyses of the satellite-estimated total carbon monoxide (CO) column and observed levoglucosan concentrations were carried out. Levoglucosan has been shown to be significantly correlated with regional fires and is a well-established chemical tracer for the atmospheric particulates emitted by BB, and CO can be treated as a gaseous-phase tracer for BB. The number of BB events increased significantly during the El Niño period when compared to the average number during 2003-2016. Consequently, the total CO column and levoglucosan concentration values in the MMR increased by 15% and 500%, respectively, when compared to the normal conditions. These results indicate that during the period that was analyzed, the impacts of BB were exacerbated during the strong El Niño event as compared to the non-El Niño period. In this study, we provided evidence that the air quality in the MMR will degrade in the future if droughts and BB occurrences continue to increase.

Vertical profiling of fine particulate matter and black carbon by using unmanned aerial vehicle in Macau, China.

An unmanned aerial vehicle (UAV) equipped with miniature monitors was used to study the vertical profiles of PM2.5 (particulate matter with a ≤2.5-µm diameter) and black carbon (BC) in Macau, China, from the surface to 500 m above ground level (AGL). Twelve- and 11-day measurements were conducted during February and March 2018, respectively. In total, 46 flights were conducted between 05:00 and 06:00 AM Local Time (LT). The average concentrations of PM2.5 and BC were significantly lower in March (40.1 ± 17.9 and 2.3 ± 2.0 µg m-3, respectively) when easterly winds prevailed, compared with those in February (69.8 ± 35.7 and 3.6 ± 2.0 µg m-3, respectively) when northerly winds dominated. In general, PM2.5 concentrations decreased with height, with a vertical decrement of 0.2 µg m-3 per 10 m. BC concentrations exhibited diverse vertical profiles with an overall vertical decrement of 0.1 µg m-3 per 10 m. Meteorological analyses including back-trajectory analysis and atmospheric stability categorization revealed that both advection and convection transports may have notable influences on the vertical profiles of PM pollutants. The concentration of PM pollutants above the boundary layer was lower than that within the layer, thus exhibiting a sigmoid profile in some cases. In addition, the lighting of firecrackers and fireworks on February 16 (first day of the Chinese New Year) resulted in the elevated concentrations of PM2.5 and BC within 150 m AGL. The takeoff of a civil flight on February 10 may have resulted in a substantial increase in the PM2.5 concentrations from 80.8 (±2.1) µg m-3 at the ground level to 119.2 (±9.3) µg m-3 at a height of 330 m. Although the results are confined to a height of 500 m AGL, the current study provides a useful dataset for PM vertical distributions, complementing the spatiotemporal variations by ground-based measurements.