Jeffrey R. Pierce

Rethinking Organic Aerosols: Semivolatile Emissions and Photochemical Aging

Most primary organic-particulate emissions are semivolatile; thus, they partially evaporate with atmospheric dilution, creating substantial amounts of low-volatility gas-phase material. Laboratory experiments show that photo-oxidation of diesel emissions rapidly generates organic aerosol, greatly exceeding the contribution from known secondary organic-aerosol precursors. We attribute this unexplained secondary organic-aerosol production to the oxidation of low-volatility gas-phase species. Accounting for partitioning and photochemical processing of primary emissions creates a more regionally distributed aerosol and brings model predictions into better agreement with observations. Controlling organic particulate-matter concentrations will require substantial changes in the approaches that are currently used to measure and regulate emissions.

Large contribution of natural aerosols to uncertainty in indirect forcing.

The effect of anthropogenic aerosols on cloud droplet concentrations and radiative properties is the source of one of the largest uncertainties in the radiative forcing of climate over the industrial period. This uncertainty affects our ability to estimate how sensitive the climate is to greenhouse gas emissions. Here we perform a sensitivity analysis on a global model to quantify the uncertainty in cloud radiative forcing over the industrial period caused by uncertainties in aerosol emissions and processes. Our results show that 45 per cent of the variance of aerosol forcing since about 1750 arises from uncertainties in natural emissions of volcanic sulphur dioxide, marine dimethylsulphide, biogenic volatile organic carbon, biomass burning and sea spray. Only 34 per cent of the variance is associated with anthropogenic emissions. The results point to the importance of understanding pristine pre-industrial-like environments, with natural aerosols only, and suggest that improved measurements and evaluation of simulated aerosols in polluted present-day conditions will not necessarily result in commensurate reductions in the uncertainty of forcing estimates.

The magnitude and causes of uncertainty in global model simulations of cloud condensation nuclei

Abstract. Aerosol–cloud interaction effects are a major source of uncertainty in climate models so it is important to quantify the sources of uncertainty and thereby direct research efforts. However, the computational expense of global aerosol models has prevented a full statistical analysis of their outputs. Here we perform a variance-based analysis of a global 3-D aerosol microphysics model to quantify the magnitude and leading causes of parametric uncertainty in model-estimated present-day concentrations of cloud condensation nuclei (CCN). Twenty-eight model parameters covering essentially all important aerosol processes, emissions and representation of aerosol size distributions were defined based on expert elicitation. An uncertainty analysis was then performed based on a Monte Carlo-type sampling of an emulator built for each model grid cell. The standard deviation around the mean CCN varies globally between about ±30% over some marine regions to ±40–100% over most land areas and high latitudes, implying that aerosol processes and emissions are likely to be a significant source of uncertainty in model simulations of aerosol–cloud effects on climate. Among the most important contributors to CCN uncertainty are the sizes of emitted primary particles, including carbonaceous combustion particles from wildfires, biomass burning and fossil fuel use, as well as sulfate particles formed on sub-grid scales. Emissions of carbonaceous combustion particles affect CCN uncertainty more than sulfur emissions. Aerosol emission-related parameters dominate the uncertainty close to sources, while uncertainty in aerosol microphysical processes becomes increasingly important in remote regions, being dominated by deposition and aerosol sulfate formation during cloud-processing. The results lead to several recommendations for research that would result in improved modelling of cloud–active aerosol on a global scale.

Huddle: automatically generating interfaces for systems of multiple connected appliances

Systems of connected appliances, such as home theaters and presentation rooms, are becoming commonplace in our homes and workplaces. These systems are often difficult to use, in part because users must determine how to split the tasks they wish to perform into sub-tasks for each appliance and then find the particular functions of each appliance to complete their sub-tasks. This paper describes Huddle, a new system that automatically generates task-based interfaces for a system of multiple appliances based on models of the content flow within the multi-appliance system.

Constraining Particle Evolution from Wall Losses, Coagulation, and Condensation-Evaporation in Smog-Chamber Experiments: Optimal Estimation Based on Size Distribution Measurements

A goal of secondary organic aerosol (SOA) experiments performed in smog chambers is to determine the condensation of SOA onto suspended particles. Complicating the calculation of the condensation rate are uncertainties in particle wall-loss rates. Wall-loss rates generally depend on particle size, turbulence in the bag, the size and shape of the bag, and particle charge. In analyzing smog-chamber data, some or all of the following assumptions are commonly made regarding the first-order wall-loss rate constant: (a) that it is constant during an experiment; (b) that it is constant between experiments; and (c) that it is not a strong function of particle size for the relatively narrow size distributions in smog chamber experiments. Each of these assumptions may not be justified in some circumstances. We present the development and evaluation of the Aerosol Parameter Estimation (APE) model. APE is an inverse model that solves the aerosol general dynamic equation to determine best estimates for the size-dependent condensation rate and size-dependent wall-loss rate as a function of time. Size distribution measurements from a Scanning Mobility Particle Sizer (SMPS) provide time boundary conditions that constrain the general dynamic equation. The APE model is tested using data from a smog chamber experiment with dry ammonium sulfate particles in which no condensation occurred. Finally, we assess the variability in predicted SOA production between different wall-loss correction methods for relatively-fast-chemistry limonene-ozonolysis experiments and relatively-slow-chemistry toluene-oxidation experiments. In the fast limonene experiments, wall-loss correction methods agree within 10% for SOA production, and in the slow toluene experiments, wall-loss correction methods disagree up to a factor of 2.

Recent advances in understanding secondary organic aerosol: Implications for global climate forcing

Anthropogenic emissions and land use changes have modified atmospheric aerosol concentrations and size distributions over time. Understanding preindustrial conditions and changes in organic aerosol due to anthropogenic activities is important because these features (1) influence estimates of aerosol radiative forcing and (2) can confound estimates of the historical response of climate to increases in greenhouse gases. Secondary organic aerosol (SOA), formed in the atmosphere by oxidation of organic gases, represents a major fraction of global submicron-sized atmospheric organic aerosol. Over the past decade, significant advances in understanding SOA properties and formation mechanisms have occurred through measurements, yet current climate models typically do not comprehensively include all important processes. This review summarizes some of the important developments during the past decade in understanding SOA formation. We highlight the importance of some processes that influence the growth of SOA particles to sizes relevant for clouds and radiative forcing, including formation of extremely low volatility organics in the gas phase, acid-catalyzed multiphase chemistry of isoprene epoxydiols, particle-phase oligomerization, and physical properties such as volatility and viscosity. Several SOA processes highlighted in this review are complex and interdependent and have nonlinear effects on the properties, formation, and evolution of SOA. Current global models neglect this complexity and nonlinearity and thus are less likely to accurately predict the climate forcing of SOA and project future climate sensitivity to greenhouse gases. Efforts are also needed to rank the most influential processes and nonlinear process-related interactions, so that these processes can be accurately represented in atmospheric chemistry-climate models.

A Computationally Efficient Aerosol Nucleation/ Condensation Method: Pseudo-Steady-State Sulfuric Acid

In order to model accurately the size and number of atmospheric particles, it is necessary to predict aerosol nucleation rates. However, the explicit prediction of the sulfuric acid vapor concentration may become computationally intensive when nucleation and condensation are simultaneously occurring. In this article, we develop and test a computationally efficient solution to the problem of solving for the sulfuric acid vapor concentration. Rather than explicitly solving the differential equation for the temporal profile of sulfuric acid vapor, we assume that the sulfuric acid vapor is at the concentration in steady state with its source (oxidation of SO2) and sinks (condensation and nucleation); this is known as the Pseudo-Steady-State Approximation (PSSA). Two versions of a box model with online size-resolved aerosol microphysics were developed to test the PSSA; (1) a “benchmark model” that solves explicitly for the sulfuric acid vapor concentration, and (2) a “PSSA model” that uses the PSSA. A wide array of atmospheric conditions was used to compare the benchmark and PSSA models. The mean difference in the total number of particles in the two models with diameters larger than 10 nm was only 1.8% and 1.1% in lower troposphere simulations after 2 and 6 hours, and 3.8% and 2.3% in the upper troposphere simulations after 2 and 6 h. The PSSA model was faster in 97% of the tests, more than ten times faster in 91% of the points, and more than 100 times faster in 69% of the tests.

Environmental controls on storm intensity and charge structure in multiple regions of the continental United States

A database consisting of approximately 4000 storm observations has been objectively analyzed to determine environmental characteristics that produce high radar reflectivities above the freezing level, large total lightning flash rates on the order of 10 flashes per minute, and anomalous vertical charge structures (most notably, dominant midlevel positive charge). The storm database is drawn from four regions of the United States featuring distinct environments, each with coinciding Lightning Mapping Array (LMA) network data. LMAs are able to infer total lightning flash rates using flash clustering algorithms, such as the one implemented in this study. Results show that anomalous charge structures inferred from LMA data, significant lightning flash rates, and increased radar reflectivities above the freezing level tend to be associated with environments that have high cloud base heights (approximately 3 km above ground level) and large atmospheric instability, quantified by normalized convective available potential energy (NCAPE) near 0.2 m s−2. Additionally, we infer that aerosols may affect storm intensity. Maximum flash rates were observed in storms with attributed aerosol concentrations near 1000 cm−3, while total flash rates decrease when aerosol concentrations exceed 1500 cm−3, consistent with previous studies. However, this effect is more pronounced in regions where the NCAPE and cloud base height are low. The dearth of storms with estimated aerosol concentrations less than 700 cm−3 (approximately 1% of total sample) does not provide a complete depiction of aerosol invigoration.

Contribution of Arctic seabird-colony ammonia to atmospheric particles and cloud-albedo radiative effect

The Arctic region is vulnerable to climate change and able to affect global climate. The summertime Arctic atmosphere is pristine and strongly influenced by natural regional emissions, which have poorly understood climate impacts related to atmospheric particles and clouds. Here we show that ammonia from seabird-colony guano is a key factor contributing to bursts of newly formed particles, which are observed every summer in the near-surface atmosphere at Alert, Nunavut, Canada. Our chemical-transport model simulations indicate that the pan-Arctic seabird-influenced particles can grow by sulfuric acid and organic vapour condensation to diameters sufficiently large to promote pan-Arctic cloud-droplet formation in the clean Arctic summertime. We calculate that the resultant cooling tendencies could be large (about −0.5 W m−2 pan-Arctic-mean cooling), exceeding −1 W m−2 near the largest seabird colonies due to the effects of seabird-influenced particles on cloud albedo. These coupled ecological–chemical processes may be susceptible to Arctic warming and industrialization.

Simultaneous influences of thermodynamics and aerosols on deep convection and lightning in the tropics

Convective features (CFs) observed by the Tropical Rainfall Measuring Mission satellite between 2004 and 2011 are analyzed to determine the relative roles of thermodynamics and aerosols as they modulate radar reflectivity and lightning. We studied the simultaneous impacts of normalized convective available potential energy (NCAPE) and warm cloud depth (WCD) as well as cloud condensation nuclei concentrations (D ≥ 40 nm; N40) on total lightning density (TLD), average height of 30 dBZ echoes (AVGHT30), and vertical profiles of radar reflectivity (VPRR) within individual CFs. The results show that TLD increases by up to 600% and AVGHT30 increases by up to 2–3 km with increasing NCAPE and N40 for fixed WCD. The partial sensitivities of TLD/AVGHT30 to NCAPE and N40 separately were comparable in magnitude but account for a fraction of the total range of variability (i.e., when the influences of NCAPE and N40 are considered simultaneously). Both TLD and AVGHT30 vary inversely with WCD such that maxima of TLD and AVGHT30 are found for the combination of high NCAPE, high N40, and shallower WCD. The relationship between lightning and radar reflectivity was shown to vary as a function of N40 for a fixed thermodynamic environment. Analysis of VPRRs shows that reflectivity in the mixed phase region is up to 5.0–5.6 dB greater for CFs in polluted environments compared to CFs in pristine environments (holding thermodynamics fixed). This analysis favors a merged hypothesis for the simultaneous roles of thermodynamics and aerosols as they influence deep convective clouds in the Tropics.