A bottom-up emissions inventory is one of the most important data sets needed to understand air quality (AQ) and climate change (CC). Several emission inventories have been developed for Asia, including Transport and Chemical Evolution over the Pacific (TRACE-P), Regional Emission Inventory in Asia (REAS), and Inter-Continental Chemical Transport Experiment (INTEX) and, while these have been used successfully for many international studies, they have limitations including restricted amounts of information on pollutant types and low levels of transparency with respect to the polluting sectors or fuel types involved. To address these shortcomings, we developed: (1) a base-year, bottom-up anthropogenic emissions inventory for Asia, using the most current parameters and international frameworks (i.e., the Greenhouse gas—Air pollution INteractions and Synergies (GAINS) model); and (2) a base-year, natural emissions inventory for biogenic and biomass burning. For (1), we focused mainly on China, South Korea, and Japan; however, we also covered emission inventories for other regions in Asia using data covering recent energy/industry statistics, emission factors, and control technology penetration. The emissions inventory (Comprehensive Regional Emissions inventory for Atmospheric Transport Experiment (CREATE)) covers 54 fuel classes, 201 subsectors, and 13 pollutants, namely SO₂, NO_x, CO, non-methane volatile organic compounds (NMVOC), NH₃, OC, BC, PM₁₀, PM_2.5, CO₂, CH₄, N₂O, and Hg. For the base-year natural emissions inventory, the Model of Emissions of Gases and Aerosols from Nature (MEGAN) and BlueSky-Asia frameworks were used to estimate biogenic and biomass burning emissions, respectively. Since the CREATE emission inventory was designed/developed using international climate change/air quality (CC/AQ) assessment frameworks, such as GAINS, and has been fully connected with the most comprehensive emissions modeling systems—such as the US Environmental Protection Agency (EPA) Chemical Manufacturing Area Source (CMAS) system—it can be used to support various climate and AQ integrated modeling studies, both now and in the future.

Aged smoke from a prescribed fire (dominated by conifers) impacted Atlanta, GA on 28 February 2007 and dramatically increased hourly ambient concentrations of PM_2.5 and organic carbon (OC) up to 140 and 72 μg m⁻³, respectively. It was estimated that over 1 million residents were exposed to the smoky air lasting from the late afternoon to midnight. To better understand the processes impacting the aging of fire plumes, a detailed chemical speciation of carbonaceous aerosols was conducted by gas chromatography/mass spectrometry (GC/MS) analysis. Ambient concentrations of many organic species (levoglucosan, resin acids, retene, n-alkanes and n-alkanoic acids) associated with wood burning emission were significantly elevated on the event day. Levoglucosan increased by a factor of 10, while hopanes, steranes, cholesterol and major polycyclic aromatic hydrocarbons (PAHs) did not show obvious increases. Strong odd over even carbon number predominance was found for n-alkanes versus even over odd predominance for n-alkanoic acids. Alteration of resin acids during transport from burning sites to monitors is suggested by the observations. Our study also suggests that large quantities of biogenic volatile organic compounds (VOCs) and semivolatile organic compounds (SVOCs) were released both as products of combustion and unburned vegetation heated by the fire. Higher leaf temperature can stimulate biogenic VOC and SVOC emissions, which enhanced formation of secondary organic aerosols (SOA) in the atmosphere. This is supported by elevated ambient concentrations of secondary organic tracers (dicarboxylic acids, 2-methyltetrols, pinonic acid and pinic acid). An approximate source profile was built for the aged fire plume to help better understand evolution of wood smoke emission and for use in source impact assessment.

In this study, the accuracy of biogenic isoprene emission fluxes over East Asia during two summer months (July and August) was examined by comparing two tropospheric HCHO columns (ΩHCHO) obtained from the SCIAMACHY sensor and the Community Multi-scale Air Quality (CMAQ v4.7.1) model simulations, using three available biogenic isoprene emission inventories over East Asia: i) GEIA, ii) MEGAN and iii) MOHYCAN. From this comparative analysis, the tropospheric HCHO columns from the CMAQ model simulations, using the MEGAN and MOHYCAN emission inventories (Ω(CMAQ, MEGAN) and Ω(CMAQ, MOHYCAN)), were found to agree well with the tropospheric HCHO columns from the SCIAMACHY observations (Ω(SCIA)). Secondly, the propagation of such uncertainties in the biogenic isoprene emission fluxes to the levels of atmospheric oxidants (e.g., OH and HO2) and other atmospheric gaseous/particulate species over East Asia during the two summer months was also investigated. As the biogenic isoprene emission fluxes decreased from the GEIA to the MEGAN emission inventories, the levels of OH radicals increased by factors of 1.39 and 1.75 over Central East China (CEC) and South China, respectively. Such increases in the OH radical mixing ratios subsequently influence the partitioning of HO(y) species. For example, the HO2/OH ratios from the CMAQ model simulations with GEIA isoprene emissions were 2.7 times larger than those from the CMAQ model simulations based on MEGAN isoprene emissions. The large HO2/OH ratios from the CMAQ model simulations with the GEIA biogenic emission were possibly due to the overestimation of GEIA biogenic isoprene emissions over East Asia. It was also shown that such large changes in HO(x) radicals created large differences on other tropospheric compounds (e.g., NO(y) chemistry) over East Asia during the summer months.

Plant functional type (PFT) distributions affect the results of biogenic emission modeling as well as O3 and particulate matter (PM) simulations using chemistry-transport models (CTMs). This paper analyzes the variations of both surface biogenic volatile organic compound (BVOC) emissions and O3 concentrations due to changes in the PFT distributions in the Seoul Metropolitan Areas, Korea. The Fifth-Generation NCAR/Pennsylvania State Meso-scale Model (MM5)/the Model of Emissions of Gases and Aerosols from Nature (MEGAN)/the Sparse Matrix Operator Kernel Emissions (SMOKE)/the Community Multiscale Air Quality (CMAQ) model simulations were implemented over the Seoul Metropolitan Areas in Korea to predict surface O3 concentrations for the period of 1 May to 31 June 2008. Starting from a performance check of CTM predictions, we consecutively assessed the effects of PFT area deviations on the MEGAN BVOC and CTM O3 predictions, and we further considered the basis of geospatial and statistical analyses. The three PFT data sets considered were (1) the Korean PFT, developed with Korea-specific vegetation database; (2) the CDP PFT, adopted from the community data portal (CDP) of US National Center for Atmospheric Research in the United States (NCAR); (3) MODIS PFT, reclassified from the NASA Terra and Aqua combined land cover products. Although the CMAQ performance check reveals that all of the three different PFT data sets are applicable choices for regulatory modeling practice, noticeable primary data (i.e., PFT and Leaf Area Index (LAI)) was observed to be missing in many geographic locations. Based on the assessed effect of such missing data on CMAQ O3 predictions, we found that this missing data can cause spatially increased bias in CMAQ O3. Thus, it must be resolved in the near future to obtain more accurate biogenic emission and chemistry transport modeling results. Comparisons of MEGAN biogenic emission results with the three different PFT data showed that broadleaf trees (BTs) are the most significant contributor, followed by needleleaf trees (NTs), shrub (SB), and herbaceous plants (HBs) to the total BVOCs. In addition, isoprene from BTs and terpene from NTs were recognized as significant primary and secondary BVOC species in terms of BVOC emissions distributions and O3-forming potentials in the study domain. A geographically weighted regression analysis with locally compensated ridge (LCR-GWR) with the different PFT data (δO3 vs. δPFTs) suggests that addition of BT, SB, and NT areas can contribute to O3 increase, whereas addition of an HB area contributes to O3 decrease in the domain. Assessment results of the simulated spatial and temporal changes of O3 distributions with the different PFT scenarios reveal that hourly and local impacts from the different PFT distributions on occasional inter-deviations of O3 are quite noticeable, reaching up to 13 ppb. The simulated maximum 1 h O3 inter-deviations between different PFT scenarios have an asymmetric diurnal distribution pattern (low in the early morning, rising during the day, peaking at 05:00 p.m., and decreasing during the night) in the study domain. Exponentially diverging hourly BVOC emissions and O3 concentrations with increasing ambient temperature suggest that the use of different PFT distribution data requires much caution when modeling (or forecasting) O3 air quality in complicated urban atmospheric conditions in terms of whether uncertainties in O3 prediction results are expected to be mild or severe.