Peroxyacetyl nitrate (PAN) is the main tropospheric reservoir of NO x (NO + NO 2 ). Its lifetime can reach several months in the upper cold troposphere. This enables the long-range transport of NO x radicals, under the form of PAN, far from the regions of emission. The subsequent release of NO x through the PAN thermal decomposition leads to the efficient formation of tropospheric ozone (O 3 ), with important consequences for tropospheric oxidative capacity and air quality. The chemical properties of PAN have stimulated the progressive development of remote-sensing products by the satellite community, and recent additions open the prospect for the production of decadal and near-global time series. These products will provide new constraints on the distribution and evolution of this key trace gas in the Earth’s atmosphere, but they will also require reliable measurements for validation and characterization of performance. We present an approach that has been developed to retrieve PAN total columns from ground-based high-resolution solar absorption Fourier transform infrared (FTIR) spectra. This strategy is applied to observations recorded at remote FTIR stations of the Network for the Detection of Atmospheric Composition Change (NDACC). The resulting data sets are compared with total column time series derived from IASI (Infrared Atmospheric Sounding Interferometer) satellite observations and to a global chemical transport model. The results are discussed in terms of their overall consistency, mutual agreement, and seasonal cycles. Noticeable is the fact that the FTIR data point to substantial deficiencies in the global model simulation over high latitudes, a poorly sampled region, with an underestimation of the PAN columns during spring, at the peak of the seasonal cycle. Finally, we suggest avenues for development that should make it possible to limit intra- or intersite biases and extend the retrieval of PAN to other NDACC stations that are more affected by water vapor interferences.

In this study, the results from two passive air sampling campaigns (winter and summer) performed previously in 8 different urban sites allowed the inclusion of the volatile methyl siloxane (VMS) D5 in a chemistry transport model (WRF+CHIMERE modeling system) to assess its performance in describing the concentrations and seasonal distribution of this emergent contaminant in a domain covering the western Iberian Peninsula. The model estimations were evaluated using the available field-based data, and the WRF+CHIMERE approach showed, in general, errors under 50% for all sampling sites and seasons, with a slight tendency to underestimations of D5 concentrations when using the lowest emission factor among those selected from the literature and to very large overestimations when using the highest emission factor available. The greatest errors are found for remote sampling points (substantial overestimations of the models at Midões, by even a factor of 3) and for coastal ones (where population and therefore emissions exhibit strong seasonality). The results also indicate that the chemical sinks by OH degradation play a negligible role on the ground-level concentrations of D5 at the scale of the investigated domain, with average contributions under 0.5%. Despite the lack of data regarding D5 emissions in the area, which led to the assumption of emission rates taken from other countries (and a constant population in the domain), the results of this first study are excellent and highlight the skill of WRF+CHIMERE in reproducing D5 concentrations. Indeed, the nature of the proposed modeling tool is helpful for understanding the processes conditioning the present and future behavior of contaminants like D5. Moreover, the model is bound to allow the future inclusion of D5 (and other VMSs) in regulatory scenarios, since restrictions on the use of these chemicals have just started to be introduced.

PM 2.5 and its bound metals pose a serious threat to human health. Understanding their contamination characteristics and source could provide implication for controlling their spreading and ensuring air quality. In this article, 1,600 of PM 2.5 samples were collected from 5 urban sites in Lanzhou, China. The contamination characteristics of PM 2.5 , its relationship with meteorological factors, and the source of its bound metals were studied based on multiple linear regression analysis, enrichment factor (EF), principal component analysis and correlation analysis. The outcomes show that the PM 2.5 concentrations in winter (0.117 mg·m –3 ) and spring (0.083 mg·m –3 ) are higher than those in summer (0.043 mg·m –3 ) and autumn (0.048 mg·m –3 ). The influence degree of meteorological factors on PM 2.5 concentration is in the order of wind speed > atmospheric pressure > temperature > humidity. The major source of Fe and Cu in PM 2.5 is construction dust, Pb and As is industrial, and Hg is coal combustion. In addition, Cd, V, Co, and Mn are mainly derived from dust produced by weathering of soil or rock. In general, the spatiotemporal distribution of PM 2.5 and its bound metals are different, which is closely related to geographical location, source, and meteorological factors. The results in this article could provide support for the scientific formulation to prevent air pollution in Lanzhou.

In this case study analysis, we identified fungal traits that were associated with the responses of taxa to 4 global change factors: elevated CO 2 , warming and drying, increased precipitation, and nitrogen (N) enrichment. We developed a trait-based framework predicting that as global change increases limitation of a given nutrient, fungal taxa with traits that target that nutrient will represent a larger proportion of the community (and vice versa). In addition, we expected that warming and drying and N enrichment would generate environmental stress for fungi and may select for stress tolerance traits. We tested the framework by analyzing fungal community data from previously published field manipulations and linking taxa to functional gene traits from the MycoCosm Fungal Portal. Altogether, fungal genera tended to respond similarly to 3 elements of global change: increased precipitation, N enrichment, and warming and drying. The genera that proliferated under these changes also tended to possess functional genes for stress tolerance, which suggests that these global changes—even increases in precipitation—could have caused environmental stress that selected for certain taxa. In addition, these genera did not exhibit a strong capacity for C breakdown or P acquisition, so soil C turnover may slow down or remain unchanged following shifts in fungal community composition under global change. Since we did not find strong evidence that changes in nutrient limitation select for taxa with traits that target the more limiting nutrient, we revised our trait-based framework. The new framework sorts fungal taxa into Stress Tolerating versus C and P Targeting groups, with the global change elements of increased precipitation, warming and drying, and N enrichment selecting for the stress tolerators.

Large industrial facilities, such as petrochemical complexes, have decisive effects on regional air quality: directly due to their own hazardous volatile organic compounds (VOCs) emissions and indirectly due to their contribution to secondary air pollution. In South Korea, pronounced ozone and particulate matter issues have been reported in industrial areas. In this study, we develop a new top-down VOC emission rate estimation method using in situ airborne formaldehyde (HCHO) observations in the downwind plume of the Daesan Petrochemical Complex (DPC) in South Korea during the 2016 Korea–United States Air Quality (KORUS-AQ) mission. On May 22, we observed a peak HCHO mole fraction of 12 ppb after a transport time of 2.5 h (distance approximately 36 km) under conditions where the HCHO photochemical lifetime was 1.8 h. Box model calculations indicate that this elevated HCHO is mainly due to secondary production (more than 90% after 2 h of plume aging) from various VOC precursors including ethene, propene, and 1,3-butadiene. We estimate a lower limit for yearly DPC VOC emissions of 31 (±8.7) × 10 3 MT/year for HCHO precursors and 53 (±15) × 10 3 MT/year for all measured primary VOCs. These estimates are 1.5–2.5 times higher than the latest Korean emission inventories, KORUSv5. This method is beneficial not only by tracking the sources, sinks, and evolution of HCHO but also by validating existing emission inventories.

This article sets the near-surface meteorological conditions during the Multidisciplinary drifting Observatory for the Study of Arctic Climate expedition in the context of the interannual variability and extremes within the past 4 decades. Hourly ERA5 reanalysis data for the Polarstern trajectory for 1979–2020 are analyzed. The conditions were relatively normal given that they were mostly within the interquartile range of the preceding 4 decades. Nevertheless, some anomalous and even record-breaking conditions did occur, particularly during synoptic events. Extreme cases of warm, moist air transported from the northern North Atlantic or northwestern Siberia into the Arctic were identified from late fall until early spring. Daily temperature and total column water vapor were classified as being among the top-ranking warmest/wettest days or even record-breaking based on the full record. Associated with this, the longwave radiative fluxes at the surface were extremely anomalous for these winter cases. The winter and spring period was characterized by more frequent storm events and median cyclone intensity ranking in the top 25th percentile of the full record. During summer, near melting point conditions were more than a month longer than usual, and the July and August 2020 mean conditions were the all-time warmest and wettest. These record conditions near the Polarstern were embedded in large positive temperature and moisture anomalies over the whole central Arctic. In contrast, unusually cold conditions occurred during the beginning of November 2019 and in early March 2020, related to the Arctic Oscillation. In March, this was linked with anomalously strong and persistent northerly winds associated with frequent cyclone occurrence to the southeast of the Polarstern .

In this study, we characterize atmospheric ozone over the tropical Andes in the boundary layer, the free troposphere, and the stratosphere; we quantify each contribution to total column ozone, and we evaluate the performance of the multi-sensor reanalysis (MSR2) in the region. Thus, we present data taken in Ecuador and Peru (2014–2019). The contribution from the surface was determined by integrating ozone concentrations measured in Quito and Cuenca (Ecuador) up to boundary layer height. In addition, tropospheric and stratospheric column ozone were quantified from ozone soundings (38) launched from Quito during the study time period. Profiles were compared against soundings at Natal (SHADOZ network) for being the closest observational reference with sufficient data in 2014–2019. Data were also compared against stratospheric mixing ratios from the Aura Microwave Limb Sounder (Aura MLS). Findings demonstrate that the stratospheric component of total column ozone over the Andes (225.2 ± 8.9 Dobson Units [DU]) is at similar levels as those observed at Natal (223.3 ± 8.6 DU), and observations are comparable to Aura MLS data. In contrast, the tropospheric contribution is lower over the Andes (20.2 ± 4.3 DU) when compared to Natal (35.4 ± 6.4 DU) due to a less deep and cleaner troposphere. From sounding extrapolation of Quito profiles down to sea level, we determined that altitude deducts about 5–7 DU from the total column, which coincides with a 3%–4% overestimation of the MSR2 over Quito and Marcapomacocha (Peru). In addition, when MSR2 data are compared along a transect that crosses from the Amazon over Quito, the Ecuadorian coast side, and into the Pacific, observations are not significantly different among the three first locations. Results point to coarse reanalysis resolution not being suitable to resolve the formidable altitude transition imposed by the Andes mountain chain. This work advances our knowledge of atmospheric ozone over the study region and provides a robust time series of upper air measurements for future evaluations of satellite and reanalysis products.

COVID-19 has quickly spread throughout the world, infecting and killing millions of people. In an effort to contain the spread of the virus, many governments implemented stringent lockdown measures. These lockdown restrictions, coupled with social distancing, severely curtailed transportation and industrial activities, which are the primary drivers of nitrogen oxides emissions. This study investigates whether lockdown orders in the United States have impacted tropospheric nitrogen dioxide (NO 2 ) levels by evaluating 12 major counties with a total population of 38 million. For each county, Sentinel-5P satellite data were obtained and analyzed to determine NO 2 column concentrations during the pre-lockdown, peak lockdown, and loosening lockdown periods in 2020. Then, NO 2 levels were compared during these three periods to the same time frame in 2019. Our results show that the lockdowns in the 12 major U.S. counties analyzed led to a significant decline in NO 2 levels, with an average reduction of 28.7% (±14.6%) and 17.6% (±10.9%) during peak lockdown and loosening lockdown periods, respectively.

From 2008 to mid-2016, there was more than a 7-fold increase in oil production and nearly a tripling of natural gas production in the Colorado Denver–Julesburg Basin (DJB). This study utilized air samples collected at the Boulder Atmospheric Observatory (BAO) tower in southwestern Weld County in the DJB to investigate atmospheric mole fraction trends of methane and volatile organic compounds (VOCs). Elevated methane and propane mole fractions and low values (<1) in the ratio of i-pentane to n-pentane at BAO were found to be associated with flow patterns that transport air from the northeast (NE) to east (E) sector to the site, the direction where the primary locations of oil and natural gas (O&NG) extraction and processing activities are located. Median mole fractions of the O&NG tracer propane at BAO were 10 times higher than background values when winds came from the NE quadrant. This contrasts with lower mole fractions of O&NG-related constituents in air parcels arriving at BAO from the south, the direction of the major urban area of Denver. None of O&NG tracers, for example, methane and propane, show statistically significant trends in mole fraction (relative to the background) over the study period in air transported from the DJB. Also, longer term acetylene mole fraction changes were not seen in NE quadrant or south sector samples. A significant decline in the mole fraction ratio of i-pentane to n-pentane in the NE sector data provides evidence of an increasing influence of O&NG on the overall composition of VOCs measured at BAO, a change not seen in measurements from the south (urban) sector. These results suggest that O&NG emissions and resulting atmospheric mole fractions have remained relatively constant over 2008–2016. The behavior in the observations is in contrast to the most recent VOC emissions inventory. While the inventory projects O&NG total VOC emission reductions between 2011 and 2020, of –6.5% per year despite the large production increases, the best estimate of the propane emission rate of change for the DJB-filtered data during 2008–2016 is much smaller, that is, –1.5% per year.

In this article, we examine atmospheric and river discharge conditions within the Hudson Bay Complex for the BaySys 2016–2018 field program time frame. Investigated in particular is a subset of European Centre for Medium-Range Weather Forecasts (ECMWF) Re-Analysis - Interim (ERA-Interim) atmospheric forcing variables, namely 2-m surface temperature, 10-m surface winds, precipitation, and sea-level pressure, in addition to river discharge. Results from this assessment show that 2016 was characterized by unusually warm conditions (terrestrial and marine) throughout the annual cycle; 2017 by strong cyclone activity in March and high precipitation in January, October, and November; and 2018 by cold and windy conditions throughout the annual cycle. Evaluation of terrestrial conditions showed higher than normal land surface temperatures (the Hudson Bay physical watershed) for all of the 2016–2018 period (excluding a colder than normal spell August–November 2018), particularly in January (2016 and 2017), higher than normal precipitation in October (2016 and 2017), and higher than normal terrestrial discharge to the Hudson Bay Complex in March (2016 and 2017), with drier than average June through October (2016–2018).

Advanced leak detection (ALD) to survey local natural gas distribution systems has reached a point in technological maturity where new federal regulations will require its use in compliance surveys. Because most of these deployments are conducted by commercial providers, there has been little publicly available data documenting characteristics of the underlying methane (CH 4 ) plumes that are the core features measured in ALD surveys. Here, we document key features of CH 4 plumes measured in ALD surveys of 15 U.S. metropolitan areas where we had deployed high-sensitivity CH 4 analyzers on Google Street View cars. Our analysis reveals that CH 4 concentration enhancements from CH 4 sources exhibit high temporal variability, often differing by more than 10-fold among repeated observations. This variability introduces challenges for estimating source emission rates because the same source can appear to be large on one drive-by and small on the next. Additionally, the frequency distribution of CH 4 enhancements from a given source generally has a strong positive skew that can lead to overestimation of leak size. The magnitude of CH 4 enhancements from a source measured with a mobile sensor can also change quickly over time, as indicated by decreasing temporal correlation between mobile measurements longer than an approximately hourly time scale. To manage the uncertainty, we demonstrate how additional survey effort can help overcome this variability and instability to allow discrimination among the wide range of leak sizes. We quantify the probability of source detection, finding that it increases with estimated leak size. Combining these results, we develop a simulation that demonstrates the potential for ALD to detect leaks and quantify emissions as a function of sampling (driving) effort. Our results suggest that five to eight drives of each roadway in a target area would detect >90% of leaks and provide adequate emissions quantification for repair/replacement prioritization.

Methane is a powerful greenhouse gas and a key player in atmospheric chemistry. Important uncertainties remain in the global atmospheric methane budget, with natural geologic emissions being one of the particularly uncertain terms. In recent bottom-up studies, geologic emissions have been estimated to comprise up to 10% of the global budget (40–60 Teragrams of methane per year, Tg CH 4 yr –1 ). In contrast, top-down constraints from 14 C of methane in preindustrial air extracted from ice cores indicate that the geologic methane source is approximately an order of magnitude lower. Recent bottom-up inventories propose microseepage (diffuse low-level flux of methane through soils over large areas) as the largest single component of the geologic methane flux. In this study, we present new measurements of methane microseepage from the Appalachian Basin (Western New York State) and compare these with prior microseepage measurements from other regions and with predicted values from the most recent bottom-up inventory. Our results show lower microseepage values than most prior data sets and indicate that positive microseepage fluxes in this region are not as widespread as previously assumed. A statistical analysis of our results indicates that mean microseepage flux in this region has very likely been overestimated by the bottom-up inventory, even though our measurements more likely than not underestimate the true mean flux. However, this is a small data set from a single region and as such cannot be used to evaluate the validity of the microseepage emissions inventory as a whole. Instead, the results demonstrate the need for a more extensive network of direct geologic emission measurements in support of improved bottom-up inventories.

The Copernicus Atmosphere Monitoring Service (CAMS) is operationally providing forecast and reanalysis products of air quality and atmospheric composition. In this article, we present an extended evaluation of the CAMS global reanalysis data set of four reactive gases, namely, ozone (O 3 ), carbon monoxide (CO), nitrogen dioxide (NO 2 ), and formaldehyde (HCHO), using multiple independent observations. Our results show that the CAMS model system mostly provides a stable and accurate representation of the global distribution of reactive gases over time. Our findings highlight the crucial impact of satellite data assimilation and emissions, investigated through comparison with a model run without assimilated data. Stratospheric and tropospheric O 3 are mostly well constrained by the data assimilation, except over Antarctica after 2012/2013 due to changes in the assimilated data. Challenges remain for O 3 in the Tropics and high-latitude regions during winter and spring. At the surface and for short-lived species (NO 2 ), data assimilation is less effective. Total column CO in the CAMS reanalysis is well constrained by the assimilated satellite data. The control run, however, shows large overestimations of total column CO in the Southern Hemisphere and larger year-to-year variability in all regions. Concerning the long-term stability of the CAMS model, we note drifts in the time series of biases for surface O 3 and CO in the Northern midlatitudes and Tropics and for NO 2 over East Asia, which point to biased emissions. Compared to the previous Monitoring Atmospheric Composition and Climate reanalysis, changes in the CAMS chemistry module and assimilation system helped to reduce biases and enhance the long-term temporal consistency of model results for the CAMS reanalysis.

Summertime ozone in the Western United States presents a unique public health challenge. Changes in population, background ozone, wildland fire, and local precursor emissions combined with terrain-induced meteorology can affect surface ozone levels and compliance with the National Ambient Air Quality Standards (NAAQS). While there is considerable research on ozone in the Northern Front Range Metropolitan Area of Colorado, United States, less is known about the Southern Front Range. In Colorado Springs, approximately 100 km south of Denver, summertime maximum daily 8-h average (MDA8) ozone shows no significant ( p < .05) trend at the 5th, 50th, or 95th percentile over the past 20 years. However, the region is at risk of nonattainment with the NAAQS based on observations from 2018 to 2020. From June through September 2018, the Colorado Department of Public Health and Environment measured hourly ozone at eight sites to characterize the spatial distribution of ozone in Colorado Springs. Mean ozone (±1σ) ranged from 34 ± 19 to 60 ± 9 ppb. The 95th percentile of hourly ozone increased approximately 1.1 ppb per 100 m of elevation, while the amplitudes of mean diurnal profiles decreased with elevation and distance from the interstate. MDA8 ozone was also highly correlated across all sites, and there is little evidence of local photochemical production or ozone transport from Denver. Further, results from generalized additive modeling show that summertime MDA8 in this region is strongly influenced by regional background air and wildfire, with smoke contributing an average of 4–5 ppb to the MDA8. Enhanced MDA8 values due to wildfires were especially pronounced in 2018 and 2020. Lastly, we find that the permanent monitoring sites represent the lower end of observed ozone in the region, suggesting that additional long-term monitoring for public health may be warranted in populated, higher elevation areas.

The Korea–United States Air Quality (KORUS-AQ) field study was conducted during May–June 2016. The effort was jointly sponsored by the National Institute of Environmental Research of South Korea and the National Aeronautics and Space Administration of the United States. KORUS-AQ offered an unprecedented, multi-perspective view of air quality conditions in South Korea by employing observations from three aircraft, an extensive ground-based network, and three ships along with an array of air quality forecast models. Information gathered during the study is contributing to an improved understanding of the factors controlling air quality in South Korea. The study also provided a valuable test bed for future air quality–observing strategies involving geostationary satellite instruments being launched by both countries to examine air quality throughout the day over Asia and North America. This article presents details on the KORUS-AQ observational assets, study execution, data products, and air quality conditions observed during the study. High-level findings from companion papers in this special issue are also summarized and discussed in relation to the factors controlling fine particle and ozone pollution, current emissions and source apportionment, and expectations for the role of satellite observations in the future. Resulting policy recommendations and advice regarding plans going forward are summarized. These results provide an important update to early feedback previously provided in a Rapid Science Synthesis Report produced for South Korean policy makers in 2017 and form the basis for the Final Science Synthesis Report delivered in 2020.

Transport of pollution into pristine wilderness areas is of concern for both federal and state agencies. Assessing such transport in complex terrain is a challenge when relying solely on data from standard federal or state air quality monitoring networks because of the sparsity of network monitors beyond urban areas. During the Front Range air quality study, conducted in the summer of 2008 in the vicinity of Denver, CO, research-grade surface air quality data, vertical wind profiles and mixing heights obtained by radar wind profilers, and ozone profile data obtained by an airborne ozone differential absorption lidar augmented the local regulatory monitoring networks. Measurements from this study were taken on 2 successive days at the end of July 2008. On the first day, the prevailing winds were downslope westerly, advecting pollution to the east of the Front Range metropolitan areas. On this day, chemistry measurements at the mountain and foothills surface stations showed seasonal background ozone levels of approximately 55–68 ppbv (nmol mol –1 by volume). The next day, upslope winds prevailed, advecting pollution from the Plains into the Rocky Mountains and across the Continental Divide. Mountain stations measured ozone values greater than 90 ppbv, comparable to, or greater than, nearby urban measurements. The measurements show the progression of the ozone-enriched air into the mountains and tie the westward intrusion into high-elevation mountain sites to the growth of the afternoon boundary layer. Thus, under deep upslope flow conditions, ozone-enriched air can be advected into wilderness areas of the Rocky Mountains. Our findings highlight a process that is likely to be an important ozone transport mechanism in mountainous terrain adjacent to ozone source areas when the right circumstances come together, namely a deep layer of light winds toward a mountain barrier coincident with a deep regional boundary layer.

Atmospheric nitrogen oxide and nitrogen dioxide (NO + NO 2 , together termed as NO X ) estimates from annual photochemical simulations for years 2002–2016 are compared to surface network measurements of NO X and total gas-phase-oxidized reactive nitrogen (NO Y ) to evaluate the Community Multiscale Air Quality (CMAQ) modeling system performance by U.S. region, season, and time of day. In addition, aircraft measurements from 2011 Deriving Information on Surface Conditions from Column and Vertically Resolved Observations Relevant to Air Quality are used to evaluate how emissions, chemical mechanism, and measurement uncertainty each contribute to the overall model performance. We show distinct seasonal and time-of-day patterns in NO X performance. Summertime NO X is overpredicted with bimodal peaks in bias during early morning and evening hours and persisting overnight. The summertime morning NO X bias dropped from between 28% and 57% for earlier years (2002–2012) to between –2% and 7% for later years (2013–2016). Summer daytime NO X tends to be unbiased or underpredicted. In winter, the evening NO X overpredictions remain, but NO X is unbiased or underpredicted overnight, in the morning, and during the day. NO X overpredictions are most pronounced in the Midwestern and Southern United States with Western regions having more of a tendency toward model underpredictions of NO X . Modeled NO X performance has improved substantially over time, reflecting updates to the emission inputs and the CMAQ air quality model. Model performance improvements are largest for years simulated with CMAQv5.1 or later and for emission inventory years 2014 and later, coinciding with reduced onroad NO X emissions from vehicles with newer emission control technologies and improved treatment of chemistry, deposition, and vertical mixing in CMAQ. Our findings suggest that emissions temporalization of specific mobile source sectors have a small impact on model performance, while chemistry updates improve predictions of NO Y but do not improve summertime NO X bias in the Baltimore/DC area. Sensitivity runs performed for different locations across the country suggest that the improvement in summer NO X performance can be attributed to updates in vertical mixing incorporated in CMAQv5.1.

Disposable compressed gas aerosols have been a ubiquitous part of life since the mid-1950s. The signing of the Montreal Protocol in 1987 led to aerosol propellants changing from halocarbons to less damaging replacements; around 93% of current aerosol emissions by mass are volatile organic compounds (VOCs), with small contributions from compressed air (6.6%) and fluorocarbons (0.4%). The global consumption of aerosol units has increased significantly since the signing of the Montreal Protocol, increasing by an order of magnitude in some countries. In high-income countries, annual consumption increased through the 1990s and 2000s, typically reaching a plateau of approximately 10 ± 3 units person –1 year –1 dependant on product preferences. The largest contributors of both units and mass emissions are personal care products (PCPs). Consumption of aerosols in lower- and upper-middle income countries are growing rapidly, for example, Brazil, Mexico, China, Thailand, all tripling reported consumption since 2006. Based on evidence drawn from national production estimates, product specifications and formulations, and interpolation of usage between countries of similar economic status, we estimate global emissions of VOC from aerosol propellants were approximately 1.3 ± 0.23 Tg year –1 in 2018. The fraction of anthropogenic VOC emissions accounted for by aerosols has in some countries increased significantly as emissions from vehicles and fuels have declined. For example, in the UK, 6.1% of anthropogenic VOC emissions were from aerosols in 2017, more than were released from gasoline passenger cars. Should low- and middle-income economies grow consumption per capita in line with recent trends, then we project global aerosol consumption may reach approximately 4.4 ± 0.96 × 10 10 units year –1 in 2050. Should existing national and international policies on aerosol product formulation remain unchanged, and VOCs remain the dominant propellant, compressed aerosols could account for a global emission of approximately 2.2 ± 0.48 Tg year –1 in 2050.

Nonmethane volatile organic compounds (NMVOCs) result in ozone and aerosol production that adversely affects the environment and human health. For modeling purposes, anthropogenic NMVOC emissions have been typically compiled using the “bottom-up” approach. To minimize uncertainties of the bottom-up emission inventory, “top-down” NMVOC emissions can be estimated using formaldehyde (HCHO) observations. In this study, HCHO vertical column densities (VCDs) obtained from the Geostationary Trace gas and Aerosol Sensor Optimization spectrometer during the Korea–United States Air Quality campaign were used to constrain anthropogenic volatile organic compound (AVOC) emissions in South Korea. Estimated top-down AVOC emissions differed from those of the up-to-date bottom-up inventory over major anthropogenic source regions by factors of 1.0 ± 0.4 to 6.9 ± 3.9. Our evaluation using a 3D chemical transport model indicates that simulated HCHO mixing ratios using the top-down estimates were in better agreement with observations onboard the DC-8 aircraft during the campaign relative to those with the bottom-up emission, showing a decrease in model bias from –25% to –13%. The top-down analysis used in this study, however, has some limitations related to the use of HCHO yields, background HCHO columns, and AVOC speciation in the bottom-up inventory, resulting in uncertainties in the AVOC emission estimates. Our attempt to constrain diurnal variations of the AVOC emissions using the aircraft HCHO VCDs was compromised by infrequent aircraft observations over the same source regions. These limitations can be overcome with geostationary satellite observations by providing hourly HCHO VCDs.

Single particle aerosol mass spectrometers (SPAMS) have created significant interest among atmospheric scientists by virtue of their ability to provide real-time size-resolved information on the chemical composition of aerosols. The objective of this study is to evaluate the newly developed single particle analysis technique in terms of chemical characterization and source apportionment of ambient aerosols by comparing it with traditional filter-based methods. In this study, an air quality monitoring campaign was conducted over a period of 25 days at an urban area in Yulin city, southern China, by employing both SPAMS and traditional filter-based measurements to establish the performance of SPAMS. It was observed that the chemical characterization of particles based on SPAMS did not agree well with the filter-based analysis. Based on the filter analysis, sulfate was the most abundant component in PM 2.5 (23.5%), followed by OC (18.1%), while for single particle analysis (number concentration), EC-containing particles showed the largest contribution to PM 2.5 (>40%), followed by OC (15.7%). In terms of source apportionment via positive matrix factorization, six sources were identified by each of the two approaches. Both the approaches showed relatively good agreements for secondary species, traffic, and dust sources; however, discrepancies were noted for industry, fossil fuel, and biomass burning sources. Finally, investigation of diurnal profiles and two specific emission episodes monitored during the Chinese New Year and traffic activities demonstrated the relative advantage of single particle analysis over filter-based methods. Overall, single particle analysis can provide source apportionment with a high time resolution, which is helpful for policy makers to analyze and implement emergency control strategies during air pollution episodes. However, SPAMS performs quantification of number concentration rather than mass concentration and is limited to particles larger than 200 nm, which leads to discrepancies between the two methods. SPAMS measurements can therefore not simply replace traditional filter-based analyses, which needs to be carefully considered in the selection of the monitoring implementation.