New Analytical Paradigm to Determine Concentration of Brown Carbon and Its Sample-by-Sample Mass Absorption Efficiency.

Brown carbon (BrC) has a substantial direct radiative effect, but current estimates of its impact on radiative balance are highly uncertain due to a lack of measurements of its light-absorbing properties, such as mass absorption efficiency (MAE). Here, we present a new analytical paradigm based on a Bayesian inference (BI) model that takes multiwavelength aethalometer measurements and total carbon data to resolve the concentrations of black carbon and BrC, and MAEs of BrC on a sample-by-sample basis. Hourly MAEs, unattainable in previous studies, can now be calculated, enabling the first-time observation of the darkening-bleaching dynamics of BrC in response to photochemical transformation.

Contributions of non-tailpipe emissions to near-road PM and PM: A chemical mass balance study.

As the importance of non-tailpipe particles (NTP) over tailpipe emissions from urban traffic has been increasing, there is a need to evaluate NTP contributions to ambient particulate matter (PM) using representative source profiles. The Brake and Tire Wear Study conducted in Los Angeles, California in the winter of 2020 collected 64 PM and 64 PM samples from 32 pairs of downwind-upwind measurements at two near-road locations (I-5 in Anaheim and I-710 in Long Beach). These samples were characterized for inorganic and organic markers and, along with locally-developed brake wear, tire wear, and road dust source profiles, subject to source apportionment using the effective-variance chemical mass balance (EV-CMB) model.

Evidence of non-tailpipe emission contributions to PM and PM near southern California highways.

Particulate Matter (PM) concentrations near highways are influenced by vehicle tailpipe and non-tailpipe emissions, other emission sources, and urban background aerosols. This study collected PM and PM filter samples near two southern California highways (I-5 and I-710) over two weeks in winter 2020. Samples were analyzed for chemical source markers.

Spatial and temporal variability of brown carbon in United States: implications for direct radiative effects.

A newly developed dataset from the Interagency Monitoring of PROtected Visual Environments (IMPROVE) observation network, combined with a 3-D chemical transport model, is used to evaluate the spatial and temporal variability of brown carbon (BrC) in the United States. The model with BrC emitted from biomass burning and biofuel emissions agrees with the seasonal and spatial variability of BrC planetary boundary layer (PBL) absorption aerosol optical depth (AAOD) observations within a factor of 2. The model without whitening, the tendency for absorption to decrease with aerosol aging, overestimates the observed BrC PBL AAOD, and does not reflect the measured BrC PBL AAOD spatial variability.

Lagged meteorological impacts on COVID-19 incidence among high-risk counties in the United States-a spatiotemporal analysis.

Background: The associations between meteorological factors and coronavirus disease 2019 (COVID-19) have been discussed globally; however, because of short study periods, the lack of considering lagged effects, and different study areas, results from the literature were diverse and even contradictory.

Objective: The primary purpose of this study is to conduct more reliable research to evaluate the lagged meteorological impacts on COVID-19 incidence by considering a relatively long study period and diversified high-risk areas in the United States.

Methods: This study adopted the distributed lagged nonlinear model with a spatial function to analyze COVID-19 incidence predicted by multiple meteorological measures from March to October of 2020 across 203 high-risk counties in the United States.

Nonuniform impacts of COVID-19 lockdown on air quality over the United States.

Most of the state governments in United States (U.S.) issued lockdown or business restrictions amid the COVID-19 pandemic in March 2020, which created a unique opportunity to evaluate the air quality response to reduced economic activities.

Health Benefits from Upgrading Public Buses for Cleaner Air: A Case Study of Clark County, Nevada and the United States.

Public transit buses, which move more than 5 billion passengers annually in the United States (U.S.), can contribute substantially to the environmental health burden through emitted air pollutants.

Separation of brown carbon from black carbon for IMPROVE and Chemical Speciation Network PM samples.

Unlabelled: The replacement of the Desert Research Institute (DRI) model 2001 with model 2015 thermal/optical analyzers (TOAs) results in continuity of the long-term organic carbon (OC) and elemental carbon (EC) database, and it adds optical information with no additional carbon analysis effort. The value of multiwavelength light attenuation is that light absorption due to black carbon (BC) can be separated from that of brown carbon (BrC), with subsequent attribution to known sources such as biomass burning and secondary organic aerosols. There is evidence of filter loading effects for the 25% of all samples with the highest EC concentrations based on the ratio of light attenuation to EC.

Atmospheric deposition of particles at a sensitive alpine lake: Size-segregated daily and annual fluxes from passive sampling techniques.

Lake Tahoe, a North American alpine lake long appreciated for its clear water and geographic setting, has experienced a trend of declining water clarity due to increasing nutrient and particle inputs. Contributions from atmospheric deposition of particulate matter (PM) could be important, yet they are inadequately quantified. This study established a yearlong deposition monitoring network in the northern Lake Tahoe Basin.

Inter-annual variability of wintertime PM2.5 chemical composition in Xi'an, China: Evidences of changing source emissions.

Chemical characteristics of PM2.5 in Xi'an in wintertime of 2006, 2008, and 2010 were investigated. Markers of OC2, EC1, and NO3(-)/SO4(2-) ratio were calculated to investigate the changes in PM2.

Mass reconstruction methods for PM: a review.

Major components of suspended particulate matter (PM) are inorganic ions, organic matter (OM), elemental carbon (EC), geological minerals, salt, non-mineral elements, and water. Since oxygen (O) and hydrogen (H) are not directly measured in chemical speciation networks, more than ten weighting equations have been applied to account for their presence, thereby approximating gravimetric mass. Assumptions for these weights are not the same under all circumstances.

Long-term trends in visibility and at Chengdu, China.

Long-term (1973 to 2010) trends in visibility at Chengdu, China were investigated using meteorological data from the U.S. National Climatic Data Center.

Fine particulate matter and visibility in the Lake Tahoe Basin: chemical characterization, trends, and source apportionment.

Speciated PM2.5 (particulate matter with an aerodynamic diameter View Article and Find Full Text PDF

PM source apportionment: reconciling receptor models for U.S. nonurban and urban long-term networks.

Chemical mass balance (CMB) and trajectory receptor models were applied to speciated particulate matter with aerodynamic diameter < or =2.5 microm (PM2.5) measurements from Speciation Trends Network (STN; part of the Chemical Speciation Network [CSN]) and Interagency Monitoring of Protected Visual Environments (IMPROVE) monitoring network across the state of Minnesota as part of the Minnesota PM2.

Regional source identification using Lagrangian stochastic particle dispersion and HYSPLIT backward-trajectory models.

The main objective of this study was to investigate the capabilities of the receptor-oriented inverse mode Lagrangian Stochastic Particle Dispersion Model (LSPDM) with the 12-km resolution Mesoscale Model 5 (MM5) wind field input for the assessment of source identification from seven regions impacting two receptors located in the eastern United States. The LSPDM analysis was compared with a standard version of the Hybrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT) single-particle backward-trajectory analysis using inputs from MM5 and the Eta Data Assimilation System (EDAS) with horizontal grid resolutions of 12 and 80 km, respectively. The analysis included four 7-day summertime events in 2002; residence times in the modeling domain were computed from the inverse LSPDM runs and HYPSLIT-simulated backward trajectories started from receptor-source heights of 100, 500, 1000, 1500, and 3000 m.

Quality assurance and quality control for thermal/optical analysis of aerosol samples for organic and elemental carbon.

Accurate, precise, and valid organic and elemental carbon (OC and EC, respectively) measurements require more effort than the routine analysis of ambient aerosol and source samples. This paper documents the quality assurance (QA) and quality control (QC) procedures that should be implemented to ensure consistency of OC and EC measurements. Prior to field sampling, the appropriate filter substrate must be selected and tested for sampling effectiveness.

Particulate emission factors for mobile fossil fuel and biomass combustion sources.

PM emission factors (EFs) for gasoline- and diesel-fueled vehicles and biomass combustion were measured in several recent studies. In the Gas/Diesel Split Study (GD-Split), PM(2.5) EFs for heavy-duty diesel vehicles (HDDV) ranged from 0.

Toward effective source apportionment using positive matrix factorization: experiments with simulated PM2.5 data.

To elucidate the relationship between factors resolved by the positive matrix factorization (PMF) receptor model and actual emission sources and to refine the PMF modeling strategy, speciated PM2.5 (particulate matter with aerodynamic diameter < 2.5 microm) data generated from a state-of-the-art chemical transport model for two rural sites in the eastern United States are subjected to PMF analysis.

Evaluation of regional-scale receptor modeling.

The ability of receptor models to estimate regional contributions to fine particulate matter (PM2.5) was assessed with synthetic, speciated datasets at Brigantine National Wildlife Refuge (BRIG) in New Jersey and Great Smoky Mountains National Park (GRSM) in Tennessee. Synthetic PM2.

Toward Effective Source Apportionment Using Positive Matrix Factorization: Experiments with Simulated PM Data.

To elucidate the relationship between factors resolved by the positive matrix factorization (PMF) receptor model and actual emission sources and to refine the PMF modeling strategy, speciated PM (particulate matter with aerodynamic diameter <2.5 μm) data generated from a state-of-the-art chemical transport model for two rural sites in the eastern United States are subjected to PMF analysis. In addition to χ- and R used to infer the quality of fitting, the interpretability of PMF factors with respect to known primary and secondary sources is evaluated using a root mean square difference analysis.

Evaluation of Regional-Scale Receptor Modeling.

The ability of receptor models to estimate regional contributions to fine particulate matter (PM) was assessed with synthetic, speciated datasets at Brigantine National Wildlife Refuge (BRIG) in New Jersey and Great Smoky Mountains National Park (GRSM) in Tennessee. Synthetic PM chemical concentrations were generated for the summer of 2002 using the Community Multiscale Air Quality (CMAQ) model and chemically speciated PM source profiles from the U.S.

Methods to assess carbonaceous aerosol sampling artifacts for IMPROVE and other long-term networks.

Volatile organic compounds (VOCs) and semi-volatile organic compounds (SVOCs) adsorb to quartz fiber filters during fine and coarse particulate matter (PM2.5 and PM10, respectively) sampling for thermal/optical carbon analysis that measures organic carbon (OC) and elemental carbon (EC). Particulate SVOCs can evaporate after collection, with a small portion adsorbed within the filter.

Particulate-phase and gaseous elemental mercury emissions during biomass combustion: controlling factors and correlation with particulate matter emissions.

Mercury emissions from wildfires are significant natural sources of atmospheric mercury, but little is known about what controls speciation of emissions important to mercury deposition processes. The goal of this study was to quantify gaseous elemental mercury (GEM) and particulate-phase mercury (PHg) emissions from biomass combustion to identify key factors controlling the speciation. Emissions were characterized in an exhaust stack 17 m above fires using a gaseous mercury analyzer and quartz-fiber filters.

Source apportionment: findings from the U.S. Supersites Program.

Receptor models are used to identify and quantify source contributions to particulate matter and volatile organic compounds based on measurements of many chemical components at receptor sites. These components are selected based on their consistent appearance in some source types and their absence in others. UNMIX, positive matrix factorization (PMF), and effective variance are different solutions to the chemical mass balance (CMB) receptor model equations and are implemented on available software.

Advances in integrated and continuous measurements for particle mass and chemical composition.

Recent improvements in integrated and continuous PM2.5 mass and chemical measurements from the Supersite program and related studies in the past decade are summarized. Analytical capabilities of the measurement methods, including accuracy, precision, interferences, minimum detectable levels, comparability, and data completeness are documented.