Size-resolved global emission inventory of primary particulate matter from energy-related combustion sources

Abstract

h i g h l i g h t sMass-based size distribution of emissions of energy-related combustion sources. Method to estimate the size distribution of components of the combustion sector. Global PM 10 emissions showing single-mode size distribution with peak around 700 nm. Discussion of uncertainties in global size distribution emission estimation. Investigation of mass size distribution changes with emission reduction scenarios. a b s t r a c t Current emission inventories provide information about the mass emissions of different chemical species from different emitting sources without information concerning the size distribution of primary particulate matter (PM). The size distribution information, however, is an important input into chemical transport models that determine the fate of PM and its impacts on climate and public health. At present, models usually make rather rudimentary assumptions about the size distribution of primary PM emissions in their model inputs. In this study, we develop a global and regional, size-resolved, mass emission inventory of primary PM emissions from source-specific combustion components of the residential, industrial, power, and transportation sectors for the year 2010. Uncertainties in the emission profiles are also provided. The global size-resolved PM emissions show a distribution with a single peak and the majority of the mass of particles in size ranges smaller than 1 mm. The PM size distributions for different sectors and world regions vary considerably, due to the different combustion characteristics. Typically, the sizes of particles decrease in the order: power sector > industrial sector > residential sector > transportation sector. Three emission scenarios are applied to the baseline distributions to study the likely changes in size distribution of emissions as clean technologies are implemented.

Ambient Particulate Matter Size Distributions Drive Regional and Global Variability in Particle Deposition in the Respiratory Tract

“…Different emission sources may emit particles at different sizes. For instance, combustion processes tend to emit particle mass in the 100-to 300-nm diameter range (Ban-Weiss et al, 2010;Janhäll et al, 2010;Sakamoto et al, 2015;Winijkul et al, 2015), while dust (fugitive and windblown) and sea-spray emissions tend emit aerosol mass in ranges above 1 μm (Jaeglé et al, 2011;Kok, 2011;Mahowald et al, 2014). This results in urban regions having a strong contribution of accumulation-mode mass to PM 2.5 concentration, and desert regions having a substantial contribution to coarse-mode mass.…”

Understanding and improving model representation of aerosol optical properties for a Chinese haze event measured during KORUS-AQ

“…Further increasing the refractive indices and hygroscopicity parameters (as noted above) provided overall better representation of optical properties. Future work needs to assess if the simulated size distributions can be improved by including primary aerosol emissions in the model using size-resolved and source-specific observational datasets (Winijkul et al, 2015;Lu et al, 2015).…”

“…For primary and secondary organic aerosols, there is a large range of values found in the literature (e.g., Moise et al, 2015;Lu et al, 2015). Aldhaif et al (2018) derived OA real refractive index from field deployments by air mass type, finding a mean value of 1.54 with 1.52-1.55 as the 25-75 th percentile range for urban air masses.…”

“…We chose the value of 1.55 as it is in the 25-75 th percentile range and because it is a typical value used in past studies (Zhang et al, 1994;Hand and Kreidenweis, 2002;Hodzic et al, 2004). This value also corresponds to the mean real refractive index reported by Lu et al (2015) for primary organic aerosol based on a literature review. The Closure 4 case includes these updates (summary of updated parameters in Table 2) showing an increase in the efficiencies which improves the model representation (Figure 9a,b).…”

Understanding and improving model representation of aerosol optical properties for a Chinese haze event measured during KORUS-AQ

“…We first used the same configuration as the forecast, which we labeled MOSAIC4b. To explore the model sensitivity to increasing the resolution of the aerosol size bins, we performed simulations using the MOSAIC eight-bin configuration coupled to the Carbon Bond Mechanism version Z (CBM-Z) chemical scheme (Zaveri and Peters, 1999) and labeled it MOSAIC8b. Some caveats of this sensitivity simulation are that it uses a different gas-phase chemistry scheme and does not include secondary organic aerosol formation; thus, this needs to be considered in the analysis when comparing it to the base configuration.…”