Ajith Kaduwela
California Air Resources Board
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Featured researches published by Ajith Kaduwela.
Journal of The Air & Waste Management Association | 2011
Chenxia Cai; James T. Kelly; Jeremy C. Avise; Ajith Kaduwela; William R. Stockwell
ABSTRACT An updated version of the Statewide Air Pollution Research Center (SAPRC) chemical mechanism (SAPRC07C) was implemented into the Community Multiscale Air Quality (CMAQ) version 4.6. CMAQ simulations using SAPRC07C and the previously released version, SAPRC99, were performed and compared for an episode during July– August, 2000. Ozone (O3) predictions of the SAPRC07C simulation are generally lower than those of the SAPRC99 simulation in the key areas of central and southern California, especially in areas where modeled concentrations are greater than the federal 8-hr O3 standard of 75 parts per billion (ppb) and/or when the volatile organic compound (VOC)/nitrogen oxides (NOx) ratio is less than 13. The relative changes of ozone production efficiency (OPE) against the VOC/NOx ratio at 46 sites indicate that the OPE is reduced in SAPRC07C compared with SAPRC99 at most sites by as much as approximately 22%. The SAPRC99 and SAPRC07C mechanisms respond similarly to 20% reductions in anthropogenic VOC emissions. The response of the mechanisms to 20% NOx emissions reductions can be grouped into three cases. In case 1, in which both mechanisms show a decrease in daily maximum 8-hr O3 concentration with decreasing NOx emissions, the O3 decrease in SAPRC07C is smaller. In case 2, in which both mechanisms show an increase in O3 with decreasing NOx emissions, the O3 increase is larger in SAPRC07C. In case 3, SAPRC07C simulates an increase in O3 in response to reduced NOx emissions whereas SAPRC99 simulates a decrease in O3 for the same region. As a result, the areas where NOx controls would be disbeneficial are spatially expanded in SAPRC07C. Although the results presented here are valuable for understanding differences in predictions and model response for SAPRC99 and SAPRC07C, the study did not evaluate the impact of mechanism differences in the context of the U.S. Environmental Protection Agencys guidance for using numerical models in demonstrating air quality attainment. Therefore, additional study is required to evaluate the full regulatory implications of upgrading air quality models to SAPRC07. IMPLICATIONS CMAQ simulations of gas-phase pollutants over California were conducted using the newly released SAPRC07C gas-phase chemical mechanism and the previous released version, SAPRC99. SAPRC07C predicted slightly lower concentrations of O3 and important radical species than did SAPRC99 in key polluted regions of California. In certain regions, SAPRC07C simulates an increase in O3 in response to 20% reductions in NOx emissions, whereas SAPRC99 simulates a decrease in O3. A consequence of this difference is that areas where NOx controls would be disbeneficial are spatially expanded for SAPRC07C compared with SAPRC99.
Aerosol Science and Technology | 2011
James T. Kelly; Jeremy C. Avise; Chenxia Cai; Ajith Kaduwela
Reliable simulations of particle mass size distributions by regional photochemical air quality models are needed in regulatory applications because the U.S. EPAs National Ambient Air Quality Standards specify limits on the mass concentration of particles in a specific size range (i.e., aerodynamic diameter <2.5 μm). Considering the associations between adverse health effects and exposure to ultrafine particles, air quality models may need to accurately simulate particle number size distributions in addition to mass size distributions in future applications. In this study, predictions of particle number and mass size distributions by the Community Multiscale Air Quality model with the standard and an updated emission size distribution are evaluated using wintertime observations in California. Differences in modeled lung deposition fraction for simulated and observed particle number size distributions are also evaluated. Simulated mass size distributions are generally broader and shifted to larger diameters than observations, and observed differences in inorganic and carbon (elemental and organic) distributions are not captured by the model. These model limitations can be reasonably accounted for in regulatory modeling applications. Simulated number size distributions are considerably less accurate than mass size distributions and are difficult to represent in air quality models due to large sub-grid-scale concentration gradients. However, modeled number size distributions are responsive to updates of the emission size distribution, and reasonable simulation of background number size distributions might be possible with an improved treatment of emission size distributions. Modeled lung deposition fractions for simulated number size distributions peak in the same lung region as those for number size distributions observed in the background. However, differences in modeled and observed total number concentrations generally suggest large differences in the total number of deposited particles. Future model development on simulating particle mass size distributions should focus on improving predictions of the mass fraction of particles <2.5 μm. Model development for particle number size distributions should focus on reducing differences in modeled lung deposition for modeled and observed distributions.
Proceedings of SPIE | 2006
Rebecca Rosen; Allen Chu; James J. Szykman; Russell J. DeYoung; Jay Al-Saadi; Ajith Kaduwela; Carol Bohnenkamp
High resolution (5x5 km2 horizontal resolution) retrievals of aerosol optical depth (AOD) from the MODerate Resolution Imaging Spectroradiometer (MODIS) instruments aboard NASAs Aqua and Terra satellite platforms have been examined. These data products have been compared to coincident, hourly measurements of ground-based PM-2.5 routinely obtained by the San Joaquin Valley Air Pollution Control District (SJV APCD) and California Air Resources Board (CARB) and to airborne light detection and ranging (lidar) aerosol scattering measurements obtained by NASA in July 2003 in San Joaquin Valley (SJV). Comparison of MODIS AOD to ground based PM-2.5 measurement shows significant improvement for the higher resolution MODIS AOD. Lidar aerosol scattering measurements correspond well to MODIS AOD during a variety of atmospheric conditions, and throughout the SJV. Future lidar measurements are proposed to establish a high resolution vertical link between satellite and ground-based measurements during the winter. With the data from these two episodes, we plan to characterize the horizontal, vertical, and temporal distribution of PM-2.5 in SJV and evaluate the need for future intensive ground-based measurement and modeling studies in SJV.
Journal of The Air & Waste Management Association | 2014
Sarika Kulkarni; Ajith Kaduwela; Jeremy C. Avise; John DaMassa; Daniel Chau
With the promulgation of the National Ambient Air Quality Standards (NAAQS or standard) for 8-hr ozone (O3), the U.S. Environmental Protection Agency (EPA) issued modeling guidance that advocated the use of results from photochemical air quality models in a relative sense. In doing so, the EPA provided guidance on how to calculate relative response factors (RRFs) that can project current design value (DV) mixing ratios into the future for the purpose of determining the attainment status with respect to the O3 standard. The RRFs recommended by the EPA represent the average response of the photochemical model over a broad range of O3 mixing ratios above a specified cutoff threshold. However, it is known that O3 response to emission reductions of limiting precursors (i.e., NOx and/or VOC) is greater on days with higher O3 mixing ratios compared to days with lower mixing ratios. In this study, we present a segmented RRF concept termed band-RRF, which takes into account the different model responses at different O3 mixing ratios. The new band-RRF concept is demonstrated in the San Joaquin Valley (SJV) region of California for the 1-hr and 8-hr O3 standards. The 1-hr O3 analysis is relevant to work done in support of the SJV O3 State Implementation Plan (SIP) submitted to the EPA in 2013. The 8-hr example for the future year of 2019 is presented for illustrative purposes only. Further work will be conducted with attainment deadline of 2032 as part of upcoming SIPs for the 0.075 parts per million (ppm) 8-hr O3 standard. The applicability of the band-RRF concept to the particulate matter (PM2.5) standards is also discussed. Implications: Results of photochemical models are used in regulatory applications in a relative sense using relative response factors (RRFs), which represent the impacts of emissions reductions over a wide range of ozone (O3) values. It is possible to extend the concept of RRFs to account for the fact that higher O3 mixing ratios (both 1-hr and 8-hr) respond more to emissions controls of limiting precursors than do lower O3 mixing ratios. We demonstrate this extended concept, termed band-RRF, for the 1-hr and 8-hr O3 National Ambient Air Quality Standard (NAAQS or standard) in the San Joaquin Valley of California. This extension can also be made applicable to the 24-hr PM2.5 and annual PM2.5 standards.
Atmospheric Environment | 2010
Hanwant B. Singh; Bruce E. Anderson; William H. Brune; C. Cai; R. C. Cohen; J. H. Crawford; Michael J. Cubison; E. Czech; Louisa Kent Emmons; Henry E. Fuelberg; Greg Huey; Daniel J. Jacob; Jose L. Jimenez; Ajith Kaduwela; Yutaka Kondo; Jingqiu Mao; J. R. Olson; G. W. Sachse; S. A. Vay; Andrew J. Weinheimer; Paul O. Wennberg; Armin Wisthaler
Atmospheric Chemistry and Physics | 2010
M. Huang; G. R. Carmichael; Bhupesh Adhikary; Sarika Kulkarni; Yafang Cheng; Chao Wei; Youhua Tang; D. D. Parrish; Samuel J. Oltmans; A. D'Allura; Ajith Kaduwela; Chenxia Cai; Andrew J. Weinheimer; M. Wong; R. B. Pierce; Jassim A. Al-Saadi; David G. Streets; Qiang Zhang
Atmospheric Environment | 2004
Tony Held; Qi Ying; Ajith Kaduwela; Michael J. Kleeman
Atmospheric Environment | 2012
Hanwant B. Singh; Chenxia Cai; Ajith Kaduwela; Andrew J. Weinheimer; Armin Wisthaler
Atmospheric Environment | 2008
Qi Ying; Jin Lu; Paul Allen; Paul Livingstone; Ajith Kaduwela; Michael J. Kleeman
Atmospheric Environment | 2008
Qi Ying; Jin Lu; Ajith Kaduwela; Michael J. Kleeman