Interagency Monitoring Of Protected Visual Environments Research Articles

Long-term source apportionment of PM2.5 across the contiguous United States (2000-2019) using a multilinear engine model

Identifying PM2.5 sources is crucial for effective air quality management and public health. This research used the Multilinear Engine (ME-2) model to analyze PM2.5 from 515 EPA Chemical Speciation Network (CSN) and Interagency Monitoring of Protected Visual Environments (IMPROVE) sites across the U.S. from 2000 to 2019. The U.S. was divided into nine regions for detailed analysis. A total of seven source types (tracers) were resolved across the country: (1) Soil/Dust (Si, Al, Ca and Fe); (2) Vehicle emissions (EC, OC, Cu and Zn); (3) Biomass/wood burning (K); (4) Heavy oil/coal combustion (Ni, V, Cl and As); (5) Secondary sulfate (SO42-); (6) Secondary nitrate (NO3-) and (7) Sea salt (Mg, Na, Cl and SO42-). Furthermore, we extracted and calculated secondary organic aerosols (SOA) based on the secondary sulfate and nitrate factors. Notably, significant reductions in secondary sulfate, nitrate, and heavy oil/coal combustion emissions reflect recent cuts in fossil-fueled power sector emissions. A decline in SOA suggests effective mitigation of their formation conditions or precursors. Despite these improvements, vehicle emissions and biomass burning show no significant decrease, highlighting the need for focused control on these persistent pollution sources for future air quality management.

Implementation of the ISORROPIA-lite aerosol thermodynamics model into the EMAC chemistry climate model (based on MESSy v2.55): implications for aerosol composition and acidity

Abstract. This study explores the differences in performance and results by various versions of the ISORROPIA thermodynamic module implemented within the ECHAM/MESSy Atmospheric Chemistry (EMAC) model. Three different versions of the module were used, ISORROPIA II v1, ISORROPIA II v2.3, and ISORROPIA-lite. First, ISORROPIA II v2.3 replaced ISORROPIA II v1 in EMAC to improve pH predictions close to neutral conditions. The newly developed ISORROPIA-lite has been added to EMAC alongside ISORROPIA II v2.3. ISORROPIA-lite is more computationally efficient and assumes that atmospheric aerosols exist always as supersaturated aqueous (metastable) solutions, while ISORROPIA II includes the option to allow for the formation of solid salts at low RH conditions (stable state). The predictions of EMAC by employing all three aerosol thermodynamic models were compared to each other and evaluated against surface measurements from three regional observational networks in the polluted Northern Hemisphere (Interagency Monitoring of Protected Visual Environments (IMPROVE), European Monitoring and Evaluation Programme (EMEP), and Acid Deposition Monitoring Network of East Asia (EANET)). The differences between ISORROPIA II v2.3 and ISORROPIA-lite were minimal in all comparisons with the normalized mean absolute difference for the concentrations of all major aerosol components being less than 11 % even when different phase state assumptions were used. The most notable differences were lower aerosol concentrations predicted by ISORROPIA-lite in regions with relative humidity in the range of 20 % to 60 % compared to the predictions of ISORROPIA II v2.3 in stable mode. The comparison against observations yielded satisfactory agreement especially over the USA and Europe but higher deviations over East Asia, where the overprediction of EMAC for nitrate was as high as 4 µg m−3 (∼20 %). The mean annual aerosol pH predicted by ISORROPIA-lite was on average less than a unit lower than ISORROPIA II v2.3 in stable mode, mainly for coarse-mode aerosols over the Middle East. The use of ISORROPIA-lite accelerated EMAC by nearly 5 % compared to the use of ISORROPIA II v2.3 even if the aerosol thermodynamic calculations consume a relatively small fraction of the EMAC computational time. ISORROPIA-lite can therefore be a reliable and computationally efficient alternative to the previous thermodynamic module in EMAC.

Predicted and observed changes in summertime biogenic and total organic aerosol in the southeast United States from 2001 to 2010

Biogenic secondary organic aerosol (bSOA) is a major component of atmospheric particulate matter (PM2.5) in the southeast United States especially during the summer, when emissions of biogenic volatile organic compound (VOCs) are high and emissions from anthropogenic sources enhance the formation of secondary particulate matter. In this work we test the hypothesis whether a chemical transport model (PMCAMx) that includes a detailed description of gas-phase chemistry, secondary organic aerosol (SOA) formation based on the volatility basis set (VBS), and interactions among compounds based on partitioning theory can predict organic aerosol (OA) concentrations that are consistent with the observed changes in OA in response to significant changes in anthropogenic emissions during the summers of 2001 and 2010. The model had good performance for OA for both periods and its predictions were consistent with the observed changes in both the urban and rural areas. The fractional error of OA predictions remained practically the same (0.41 and 0.44 at Chemical Speciation Network (CSN) sites and 0.40 to 0.41 at Interagency Monitoring of Protected Visual Environments (IMPROVE) sites in the summers of 2001 and 2010 respectively) in the two examined periods. The fractional bias of OA predictions increased from 0.10 to 0.22 at CSN sites and decreased from 0 to −0.09 at IMPROVE sites between the two periods. Average predicted bSOA concentrations in the southeast US did not change appreciably from the summer of 2001 to the summer of 2010, while the anthropogenic SOA decreased by 45%. As a result, the biogenic fraction of predicted total OA increased from 0.46 in 2001 to 0.63 in 2010. Partitioning effects due to reduced anthropogenic OA from 2001 resulted in 0.4 μg m−3 less biogenic OA on average in the southeast US in the summer of 2010. This was offset by biogenic SOA increases due to higher biogenic vapor emissions in the warmer 2010 summer. Removing the NOx-dependence of SOA formation yields resulted in higher fractional error and fractional bias at both CSN and IMPROVE sites in both summer periods, demonstrating the efficacy of the current formulation of SOA yields. The results of the analysis support the conclusion that a CTM that simulates NOx-dependent SOA chemistry and semivolatile partitioning of SOA material can consistently predict the observed changes in a region rich in biogenic VOCs and SOA.

Evaluating IMPROVE PM2.5 element measurements

ABSTRACT The Interagency Monitoring of PROtected Visual Environments (IMPROVE) network has collected airborne particulate matter (PM) samples at locations throughout the United States since 1988 and provided chemical speciation measurements on the samples using several techniques including X-ray fluorescence (XRF). New XRF instruments for measuring PM elemental content of IMPROVE samples were introduced in 2011. To evaluate the performance of these new instruments relative to the old instruments, archived sample from three IMPROVE monitoring sites were retrieved and analyzed on the new instruments. The agreement between the two instruments varied by element. Comparisons of the results were very good (slopes within 10% of unity) for most elements regularly measured well above the detection limits (sulfur, chlorine, potassium, titanium, vanadium, manganese, iron, copper, zinc, selenium, lead). Different particle compositions at the three sites highlighted different measurement interferences. High sea salt concentrations at the coastal site emphasized corrections applied in the old systems to light elements – sodium and magnesium – and resulted in poor agreement for these elements. Comparisons of the XRF measurements with collocated sulfate measurements by ion chromatography suggest that sulfur measurements from the new instruments are more precise but slight underestimates. Comparing elemental ratios to expected ratios for soil-derived PM demonstrate the new instruments are better at resolving the aluminum and silicon peaks. Implications: The presented work represents a comprehensive analysis of the method change enacted within the Interagency Monitoring of PROtected Visual Environments (IMPROVE) air monitoring network. This work describes the implications of the last change in elemental quantification methodology. The most important point for data users performing longitudinal analyses is that light elements (e.g., sodium – sulfur) were affected; the old instrumentation overestimated these elements while the current measurements are slightly underestimated. The authors recommend these results to be taken into consideration when interpreting sea salt and crustal sources of atmospheric dust.

Stability assessment of organic sulfur and organosulfate compounds in filter samples for quantification by Fourier- transform infrared spectroscopy

Abstract. Organic sulfur and sulfate compounds, which are tracers for sources and atmospheric processes, are not currently measured in national monitoring networks such as the Interagency Monitoring of Protected Visual Environments (IMPROVE). The goal of this paper is to begin to assess the stability of organic sulfur and sulfate-containing compounds on polytetrafluoroethylene (PTFE) filters and the suitability of Fourier-transform infrared (FT-IR) spectroscopy to measure these compounds. Stability assessment is needed because PTFE samples collected by IMPROVE are typically stored 6–9 months prior to analysis. For this study, two organosulfur compounds, methanesulfonic acid (MSA) and hydroxymethanesulfonate ion (HMS), and two organosulfate compounds, methyl sulfate (MS) and 2-methyltetrol sulfate (2-MTS), are collected individually on PTFE filters. Gravimetric mass measurements are used to assess mass stability over time. FT-IR spectra are evaluated to assess the capability of measuring the compound from PTFE filters by assessing the compound stability or chemical changes over time. Ion chromatography (IC) and inductively coupled plasma optical emission spectroscopy (ICP-OES) are used as additional tools to assess stability or chemical changes over time. MS has the highest potential to be measured by FT-IR in IMPROVE samples. For MS, a simple organosulfate, the mass changes are within measurement uncertainty and FT-IR spectra indicate no compositional change over a 4-month period, suggesting that MS can be measured using FT-IR. IC and ICP-OES support the conclusion that MS is stable on the filter. However, for 2-MTS, the other organosulfate measured in this study, spectral changes after a month on the filter suggest that it decomposes into other organosulfates or an inorganic sulfate. MSA in IMPROVE samples can be measured, but only as a lower bound, due to volatility off the filter as indicated by FT-IR and gravimetry. FT-IR and IC both show that MSA does not chemically change over the course of the study. Measurements by all methods indicate that HMS is unstable on the PTFE filter, and IC and FT-IR indicate that it likely converts to inorganic sulfate. Future work includes the evaluation of these compounds in an ambient aerosol sample matrix to determine any differences in stability, identifying interference that could limit quantification, and developing calibrations to measure the compounds or functional groups in ambient samples.

Regional Sources and Sinks of Atmospheric Particulate Selenium in the United States Based on Seasonality Profiles.

Selenium (Se) is an essential nutrient for humans and enters our food chain through bioavailable Se in soil. Atmospheric deposition is a major source of Se to soils, driving the need to investigate the sources and sinks of atmospheric Se. Here, we used Se concentrations from PM2.5 data at 82 sites from 1988 to 2010 from the Interagency Monitoring of Protected Visual Environments (IMPROVE) network in the US to identify the sources and sinks of particulate Se. We identified 6 distinct seasonal profiles of atmospheric Se, grouped by geographical location: West, Southwest, Midwest, Southeast, Northeast, and North Northeast. Across most of the regions, coal combustion is the largest Se source, with a terrestrial source dominating in the West. We also found evidence for gas-to-particle partitioning in the wintertime in the Northeast. Wet deposition is an important sink of particulate Se, as determined by Se/PM2.5 ratios. The Se concentrations from the IMPROVE network compare well to modeled output from a global chemistry-climate model, SOCOL-AER, except in the Southeast US. Our analysis constrains the sources and sinks of atmospheric Se, thereby improving the predictions of Se distribution under climate change.

Public health applications of historical smoke forecasts: An evaluation of archived BlueSky data for the coterminous United States, 2015–2018

BackgroundWildfires are increasing in magnitude, frequency, and severity. Populations in the wildland-urban interface and in downwind communities are at increased risk of exposure to elevated concentrations of fine particulate matter (PM2.5) and other harmful components of wildfire smoke. We conducted this analysis to evaluate the use of modeled predictions of wildfire smoke to create county-level measures of smoke exposure for public health research and surveillance. MethodsWe evaluated four years (2015–2018) of grid-based North American Mesoscale (NAM)-derived PM2.5 forecasts from the U.S. Forest Service BlueSky modeling framework with monitoring data from the Environmental Protection Agency Air Quality System (AQS), the Interagency Monitoring of Protected Visual Environments (IMPROVE), the Western Regional Climate Center (WRCC), and the Interagency Real Time Smoke Monitoring (AIRSIS) programs. To assess relationships between model-derived estimates and monitor-based observations, we assessed Spearman's correlations by spatial (i.e., county, level of urbanization, states in the western United States impacted by major wildfires, and climate regions) and temporal (i.e., month and wildfire activity periods) characteristics. We then generated county-level smoke estimates and examined spatial and temporal patterns in total and person-days of smoke exposure. ResultsAcross all counties in the coterminous United States and for all days, the correlation between county-level model- and monitor-derived PM2.5 estimates was 0.14 (p < 0.001). Correlations were stronger using data from temporary monitors and for areas and days impacted by high wildfire smoke, especially in the western United States. Correlations between county-level model- and monitor-derived estimates in non-metropolitan counties, and at higher concentrations ranged from 0.25 to 0.54 (p < 0.001). ConclusionsIn general, public health practitioners and health researchers need to consider the pros and cons associated with modeled data products for conducting health analyses. Our results support the use of model-derived smoke estimates to identify communities impacted by heavy smoke events, especially during emergency response and for communities located near wildfire episodes.

Ambient Aerosol Is Physically Larger on Cloudy Days in Bondville, Illinois.

Particle chemical composition affects aerosol optical and physical properties in ways important for the fate, transport, and impact of atmospheric particulate matter. For example, hygroscopic constituents take up water to increase the physical size of a particle, which can alter the extinction properties and atmospheric lifetime. At the collocated AERosol RObotic NETwork (AERONET) and Interagency Monitoring of PROtected Visual Environments (IMPROVE) network monitoring stations in rural Bondville, Illinois, we employ a novel cloudiness determination method to compare measured aerosol physicochemical properties on predominantly cloudy and clear sky days from 2010 to 2019. On cloudy days, aerosol optical depth (AOD) is significantly higher than on clear sky days in all seasons. Measured Ångström exponents are significantly smaller on cloudy days, indicating physically larger average particle size for the sampled populations in all seasons except winter. Mass concentrations of fine particulate matter that include estimates of aerosol liquid water (ALW) are higher on cloudy days in all seasons but winter. More ALW on cloudy days is consistent with larger particle sizes inferred from Ångström exponent measurements. Aerosol chemical composition that affects hygroscopicity plays a determining impact on cloudy versus clear sky differences in AOD, Ångström exponents, and ALW. This work highlights the need for simultaneous collocated, high-time-resolution measurements of both aerosol chemical and physical properties, in particular at cloudy times when quantitative understanding of tropospheric composition is most uncertain.

A Global-Scale Mineral Dust Equation.

A robust method to estimate mineral dust mass in ambient particulate matter (PM) is essential, as the dust fraction cannot be directly measured but is needed to understand dust impacts on the environment and human health. In this study, a global-scale dust equation is developed that builds on the widely used Interagency Monitoring of Protected Visual Environments (IMPROVE) network's "soil" formula that is based on five measured elements (Al, Si, Ca, Fe, and Ti). We incorporate K, Mg, and Na into the equation using the mineral-to-aluminum (MAL) mass ratio of (K2O+MgO+Na2O)/Al2O3 and apply a correction factor (CF) to account for other missing compounds. We obtain region-specific MAL ratios and CFs by investigating the variation in dust composition across desert regions. To calculate reference dust mass for equation evaluation, we use total-mineral-mass (summing all oxides of crustal elements) and residual-mass (subtracting non-dust species from total PM) approaches. For desert dust in source regions, the normalized mean bias (NMB) of the global equation (within ±1%) is significantly smaller than the NMB of the IMPROVE equation (-6% to 10%). For PM2.5 with high dust content measured by the IMPROVE network, the global equation estimates dust mass well (NMB within ±5%) at most sites. For desert dust transported to non-source regions, the global equation still performs well (NMB within ±2%). The global equation can also represent paved road, unpaved road, and agricultural soil dust (NMB within ±5%). This global equation provides a promising approach for calculating dust mass based on elemental analysis of dust.

The relationship between PM&amp;lt;sub&amp;gt;2.5&amp;lt;/sub&amp;gt; and anticyclonic wave activity during summer over the United States

Abstract. To better understand the role of atmospheric dynamics in modulating surface concentrations of fine particulate matter (PM2.5), we relate the anticyclonic wave activity (AWA) metric and PM2.5 data from the Interagency Monitoring of Protected Visual Environment (IMPROVE) data for the period of 1988–2014 over the US. The observational results are compared with hindcast simulations over the past 2 decades using the National Center for Atmospheric Research–Community Earth System Model (NCAR CESM). We find that PM2.5 is positively correlated (up to R=0.65) with AWA changes close to the observing sites using regression analysis. The composite AWA for high-aerosol days (all daily PM2.5 above the 90th percentile) shows a similarly strong correlation between PM2.5 and AWA. The most prominent correlation occurs in the Midwestern US. Furthermore, the higher quantiles of PM2.5 levels are more sensitive to the changes in AWA. For example, we find that the averaged sensitivity of the 90th-percentile PM2.5 to changes in AWA is approximately 3 times as strong as the sensitivity of 10th-percentile PM2.5 at one site (Arendtsville, Pennsylvania; 39.92∘ N, 77.31∘ W). The higher values of the 90th percentile compared to the 50th percentile in quantile regression slopes are most prominent over the northeastern US. In addition, future changes in US PM2.5 based only on changes in climate are estimated to increase PM2.5 concentrations due to increased AWA in summer over areas where PM2.5 variations are dominated by meteorological changes, especially over the western US. Changes between current and future climates in AWA can explain up to 75 % of PM2.5 variability using a linear regression model. Our analysis indicates that higher PM2.5 concentrations occur when a positive AWA anomaly is prominent, which could be critical for understanding how pollutants respond to changing atmospheric circulation as well as for developing robust pollution projections.

Significant reduction in atmospheric organic and elemental carbon in PM2.5 in 2+26 cities in northern China

To better understand the change characteristics and reduction in organic carbon (OC) and elemental carbon (EC) in particulate matter (PM) with a diameter of ≤2.5 μm (PM2.5) driven by the most stringent clean air policies and pandemic-related lockdown measures in China, a comprehensive field campaign was performed to measure the carbonaceous components in PM2.5 on an hourly basis via harmonized analytical methods in the Beijing-Tianjin-Hebei and its surrounding region (including 2 + 26 cities) from January 1 to December 31, 2020. The results indicated that the annual average concentrations of OC and EC reached as low as 6.6 ± 5.7 and 1.8 ± 1.9 μg/m3, respectively, lower than those obtained in previous studies, which could be attributed to the effectiveness of the Clean Air Action Plan and the impact of the COVID-19-related lockdown measures implemented in China. Marked seasonal and diurnal variations in OC and EC were observed in the 2 + 26 cities. Significant correlations (p < 0.001) between OC and EC were found. The annual average secondary OC levels level ranged from 1.8–5.4 μg/m3, accounting for 37.7–73.0% of the OC concentration in the 2 + 26 cities estimated with the minimum R squared method. Based on Interagency Monitoring of Protected Visual Environments (IMPROVE) algorithms, the light extinction contribution of carbonaceous PM to the total amount reached 21.1% and 26.0% on average, suggesting that carbonaceous PM played a less important role in visibility impairment than did the other chemical components in PM2.5. This study is expected to provide an important real-time dataset and in-depth analysis of the significant reduction in OC and EC in PM2.5 driven by both the Clean Air Action Plan and COVID-19-related lockdown policies over the past few years, which could represent an insightful comparative case study for other developing countries/regions facing similar carbonaceous PM pollution.

Evaluation of Extinction Effect of PM2.5 and Its Chemical Components during Heating Period in an Urban Area in Beijing–Tianjin–Hebei Region

PM2.5 pollution and visibility impairment has attracted wild public attention in urban China during the past decade. Field observation was carried out in Tianjin, China, during heating (HP) and non-heating periods (NHP). The IMPROVE (Interagency Monitoring of Protected Visual Environments) method was localized to better understand the quantitative impact of PM2.5 composition on extinction coefficient (Bext). Bext of organic mass (OM) was classified into that of primary organic aerosol (POA) and secondary organic aerosol (SOA). Bext of Rayleigh scattering was calculated based on observation data directly, instead of a fixed value in the original IMPROVE method. The mass extinction efficiency (MEE) of EC was also updated based on literature research. The estimation bias of reconstructed Bext was reduced from 4.8 Mm−1 to 0.8 Mm−1 with the localized algorithm. It was found that the secondary components contribute more than 40% of Bext, and ammonium sulfate (AS) and ammonium nitrate (AN) are the dominant components. The different formation pathway leads to significant difference in secondary inorganic components during HP and NHP. Based on the positive matrix factorization (PMF) model and localized IMPROVE method, secondary aerosols were identified as the main source contributing to both PM2.5 concentration (48.2%) and Bext (44.3%) during HP, followed by vehicular emission and coal combustion, biomass burning with municipal incinerators, fugitive dust, and steel processing.

Validating Aerosol Optical Depth Estimation Methods Using the National Institute of Environmental Research Operational Numerical Forecast Model

Currently, significant efforts are being made to enhance the performance of the National Institute of Environmental Research (NIER) operational model. However, the model performance concerning Aerosol Optical Depth (AOD) estimation remains uninvestigated. In this study, three different estimation methods for AOD were implemented using the NIER operational model and validated with satellite and ground observations. In the widely used Interagency Monitoring of Protected Visual Environments (IMPROVE) method, AOD exponentially increases with relative humidity owing to a hygroscopic growth factor. However, alternative methods show better performance, since AOD estimation considers the size dependency of aerosol particles and is not sensitive to high relative humidity, which reduces the high AOD in areas with large cloud fractions. Although some R values are significantly low, especially for a single observational comparison and small numerical domain analysis, one of the alternative estimation methods achieves the best performance for diagnosing AOD in the East Asia region.

Extreme Aerosol Events at Mesa Verde, Colorado: Implications for Air Quality Management

A significant concern for public health and visibility is airborne particulate matter, especially during extreme events. Of most relevance for health, air quality, and climate is the role of fine aerosol particles, specifically particulate matter with aerodynamic diameters less than or equal to 2.5 micrometers (PM2.5). The purpose of this study was to examine PM2.5 extreme events between 1989 and 2018 at Mesa Verde, Colorado using Interagency Monitoring of Protected Visual Environments (IMPROVE) monitoring data. Extreme events were identified as those with PM2.5 on a given day exceeding the 90th percentile value for that given month. We examine the weekly, monthly, and interannual trends in the number of extreme events at Mesa Verde, in addition to identifying the sources of the extreme events with the aid of the Navy Aerosol Analysis and Prediction (NAAPS) aerosol model. Four sources were used in the classification scheme: Asian dust, non-Asian dust, smoke, and “other”. Our results show that extreme PM2.5 events in the spring are driven mostly by the dust categories, whereas summertime events are influenced largely by smoke. The colder winter months have more influence from “other” sources that are thought to be largely anthropogenic in nature. No weekly cycle was observed for the number of events due to each source; however, interannual analysis shows that the relative amount of dust and smoke events compared to “other” events have increased in the last decade, especially smoke since 2008. The results of this work indicate that, to minimize and mitigate the effects of extreme PM2.5 events in the southwestern Colorado area, it is important to focus mainly on smoke and dust forecasting in the spring and summer months. Wintertime extreme events may be easier to regulate as they derive more from anthropogenic pollutants accumulating in shallow boundary layers in stagnant conditions.

Contributions of aerosol chemical composition and sources to light extinction during haze and non-haze days in Taiyuan, China

To better understand the causes of visibility degradation in Taiyuan, the concentrations of PM1.5 and main chemical compositions were analyzed during the period from July 28, 2014 to April 26, 2015. The average concentration of PM1.5 during the sampling period was 107.6 ± 51.0 μg/m3. The concentrations of secondary inorganic water-soluble ions (SIA, the sum of SO42−, NO3− and NH4+), OC and EC were 31.0 μg/m3, 14.6 μg/m3 and 6.0 μg/m3, accounting for 28.8%, 13.5% and 5.6% of PM1.5, respectively. Light extinction coefficients (bext) were estimated by the revised US Interagency Monitoring of Protected Visual Environments (IMPROVE) equation. (NH4)2SO4 (48.7%) was the largest contributor to bext in summer, while the contribution of organic matter (OM) to bext was the highest in spring (25.0%) and winter (42.0%). Compared with non-haze days in summer and winter, the contributions of (NH4)2SO4 and NH4NO3 to bext during haze days increased, while the contributions of OM, EC, fine soil and coarse matter (PM1.5-10) decreased. Air masses from the southern areas had the largest bext and contribution of (NH4)2SO4 in summer and winter. The results of source apportionment by positive matrix factorization model found that secondary sulfate, secondary nitrate, coal combustion, vehicle emission, fugitive dust, biomass burning were the main sources to bext in Taiyuan. Secondary sulfate (81.7%) and coal combustion (43.1%) were the largest contributors to the bext in summer and winter during haze days, respectively. The results of our study could improve the understanding of the major sources that affect visibility degradation in Taiyuan.

Estimating mean molecular weight, carbon number, and OM∕OC with mid-infrared spectroscopy in organic particulate matter samples from a monitoring network

Abstract. Organic matter (OM) is a major constituent of fine particulate matter, which contributes significantly to degradation of visibility and radiative forcing, and causes adverse health effects. However, due to its sheer compositional complexity, OM is difficult to characterize in its entirety. Mid-infrared spectroscopy has previously proven useful in the study of OM by providing extensive information about functional group composition with high mass recovery. Herein, we introduce a new method for obtaining additional characteristics such as mean carbon number and molecular weight of these complex organic mixtures using the aliphatic C−H absorbance profile in the mid-infrared spectrum. We apply this technique to spectra acquired non-destructively from Teflon filters used for fine particulate matter quantification at selected sites of the Inter-agency Monitoring of PROtected Visual Environments (IMPROVE) network. Since carbon number and molecular weight are important characteristics used by recent conceptual models to describe evolution in OM composition, this technique can provide semi-quantitative, observational constraints of these variables at the scale of the network. For this task, multivariate statistical models are trained on calibration spectra prepared from atmospherically relevant laboratory standards and are applied to ambient samples. Then, the physical basis linking the absorbance profile of this relatively narrow region in the mid-infrared spectrum to the molecular structure is investigated using a classification approach. The multivariate statistical models predict mean carbon number and molecular weight that are consistent with previous values of organic-mass-to-organic-carbon (OM/OC) ratios estimated for the network using different approaches. The results are also consistent with temporal and spatial variations in these quantities associated with aging processes and different source classes (anthropogenic, biogenic, and burning sources). For instance, the statistical models estimate higher mean carbon number for urban samples and smaller, more fragmented molecules for samples in which substantial aging is anticipated.

Brownness of Organic Aerosol over the United States: Evidence for Seasonal Biomass Burning and Photobleaching Effects.

Light-absorptivity of organic aerosol may play an important role in visibility and climate forcing, but it has not been assessed as extensively as black carbon (BC) aerosol. Based on multiwavelength thermal/optical analysis and spectral mass balance, this study quantifies BC for the U.S. Interagency Monitoring of Protected Visual Environments (IMPROVE) network while developing a brownness index (γBr) for non-BC organic carbon (OC*) to illustrate the spatiotemporal trends of light-absorbing brown carbon (BrC) content. OC* light absorption efficiencies range from 0 to 3.1 m2 gC-1 at 405 nm, corresponding to the lowest and highest BrC content of 0 and 100%, respectively. BC, OC*, and γBr explain >97% of the variability of measured spectral light absorption (405-980 nm) across 158 IMPROVE sites. Network-average OC* light absorptions at 405 nm are 50 and 28% those for BC over rural and urban areas, respectively. Larger organic fractions of light absorption occur in winter, partially due to higher organic brownness. Winter γBr exhibits a dramatic regional/urban-rural contrast consistent with anthropogenic BrC emissions from residential wood combustion. The spatial differences diminish to uniformly low γBr in summer, suggesting effective BrC photobleaching over the midlatitudes. An empirical relationship between BC, ambient temperature, and γBr is established, which can facilitate the incorporation of organic aerosol absorptivity into climate and visibility models that currently assume either zero or static organic light absorption efficiencies.

Study of aerosol characteristics and sources using MAX-DOAS measurement during haze at an urban site in the Fenwei Plain

Atmospheric aerosols have effects on atmospheric radiation assessments, global climate change, local air quality and visibility. In particular, aerosols are more likely transformed and accumulated in winter. In this paper, we used the Multi-Axis Differential Optical Absorption Spectroscopy (MAX-DOAS) instrument to study the characteristics of aerosol type and contributions of PM2.5 chemical components to aerosol extinction (AE), vertical distribution of aerosols, and source. From December 30, 2018 to January 27, 2019, we conducted MAX-DOAS observations on Sanmenxia. The proportion of PM2.5 to PM10 was 69.48%–95.39%, indicating that the aerosol particles were mainly fine particles. By analyzing the ion data and modifying Interagency Monitoring of Protected Visual Environments (IMPROVE) method, we found that nitrate was the largest contributor to AE, accounting for 31.51%, 28.98%, and 27.95% of AE on heavily polluted, polluted, and clean days, respectively. NH4+, OC, and SO42− were also major contributors to AE. The near-surface aerosol extinction retrieved from MAX-DOAS measurement the PM2.5 and PM10 concentrations measured by an Unmanned Aerial Vehicle (UAV) have the same trend in vertical distribution. AE increased about 3 times from surface to 500 m. With the backward trajectory of the air mass during the haze, we also found that the continuous heavy pollution was mainly caused by transport of polluted air from the northeast, then followed by local industrial emissions and other sources of emissions under continuous and steady weather conditions.

Improved estimation of PM2.5 brown carbon contributions to filter light attenuation

Multiwavelength light attenuation measurements have been acquired as part of thermal/optical carbon analysis in the U.S. Chemical Speciation Network (CSN) and the Interagency Monitoring of PROtected Visual Environments (IMPROVE) network beginning in 2016. These are used to estimate PM2.5 brown carbon (BrC) contributions to light absorption at various wavelengths, a useful method for separating biomass burning contributions from other sources. Attenuation of light transmitted through the filter deviates from Beers Law as the mass of light absorbing materials increase. This study estimates the effects of these deviations with empirical adjustment factors applied to samples for CSN from 2016 to 2017 and for IMPROVE from 2016 to 2019. Accounting for the filter loading effect results in an annual average increase of ∼6–7% BrC contribution to light attenuation: from 3.6% to 10.7% for the urban, more heavily loaded CSN samples; and from 23.7% to 29.5% for the non-urban IMPROVE samples. An alternative method is examined for BrC and black carbon (BC) adjustments by calculating the Absorption Ångström Exponent (AAE) for BC (i.e., AAEBC) based on the ratios of 635nm/780nm light attenuation rather than assuming AAEBC of unity. These paired-wavelength calculations result in a median AAEBC of 0.76 for CSN and 0.8 for IMPROVE, with the majority of samples (i.e., 91% of CSN and 70% of IMPROVE) showing AAEBC<1. By assuming negligible contributions from BrC to AAE at longer wavelengths, the amount of light attenuation at shorter wavelengths (e.g., 405nm) where BrC is dominant can be calculated. The paired-wavelength method applied to the filter loading adjusted data has a greater effect on urban (fresh) than on non-urban (aged) aerosols, resulting in a factor of two increase in annual averaged BrC light attenuation (from 10.7% to 21.6%) for CSN and by a factor of 1.11 (from 29.5% to 32.7%) for IMPROVE samples. This result demonstrates the importance of particle loading and AAE correction on quantifying BrC light attenuation from multi-wavelength thermal/optical analysis.

Long-term Measurements of Carbonaceous Aerosol at Cape Hedo, Okinawa, Japan: Effects of Changes in Emissions in East Asia

ABSTRACT We investigated the changes in the carbonaceous-aerosol sources and their effects on the long-term elemental carbon (EC) and organic carbon (OC) concentration trends at the Cape Hedo Atmosphere and Aerosol Monitoring Station (CHAAMS) in Okinawa, Japan, during the period 2004–2013. We obtained the EC and OC concentrations by conducting semi-real-time measurements using a carbon monitor, and performing an offline thermal/optical filter analysis according to the Interagency Monitoring of Protected Visual Environments (IMPROVE) protocol. The annual average concentration of the EC remained constant between 2004 and 2013, but that of the OC decreased at a rate of 0.11 µg C m–3 y–1 (α > 0.05). The secondary OC (SOC)/OC ratio showed an increasing trend from 2004 till 2011, which may have been caused by a reduction in primary emissions of OC and compositional changes in the organic compounds originating in China, from which air pollutants were frequently transported during spring and winter. Although the EC concentration did not change appreciably in either season, the OC concentration decreased at rates of 0.10 µg C m–3 y–1 and 0.11 µg C m–3 y–1 during spring and winter, respectively. We estimated the contributions from the various sources of carbonaceous aerosol, viz., biomass burning, fossil-fuel combustion, and air-pollutant transport from China, based on the OC/EC ratio, which decreased from 5.7 to 2.4 in terms of the annual average. The growing share from fossil-fuel combustion is responsible for the decline in biofuel-burning OC emissions transported from China to CHAAMS.