Dataset associated with "Beyond SOx reductions from shipping: Assessing the impact of NOx and carbonaceous-particle controls on human health and climate" Kelsey R. Bilsback (1)*, Deanna Kerry (2), Betty Croft (2), Bonne Ford (1), Shantanu H. Jathar (3), Ellison Carter (4), Randall V. Martin (5,2), Jeffrey R. Pierce (1) (1) Department of Atmospheric Science, Colorado State University, Fort Collins, CO, United States (2) Department of Physics and Atmospheric Science, Dalhousie University, Halifax, NS, Canada (3) Department of Mechanical Engineering, Colorado State University, Fort Collins, CO, United States (4) Department of Civil and Environmental Engineering, Colorado State University, Fort Collins, CO, United States (5) Department of Energy, Environmental & Chemical Engineering, Washington University, St. Louis, MO, United States *Please contact Kelsey Bilsback (kelsey.bilsback@colostate.edu) or Jeffrey Pierce (jeffrey.pierce@colostate.edu) regarding this dataset. Abstract: Historically, cargo ships have been powered by low-grade fossil fuels, which emit particles and particle-precursor vapors that impact human health and climate. We used a global chemical-transport model with online aerosol microphysics (GEOS-Chem-TOMAS) to estimate the aerosol health and climate impacts of four emission-control policies: (1) 85% reduction in sulfur oxide (SOx) emissions (Sulf); (2) 85% reduction in SOx and black carbon (BC) emissions (Sulf-BC); (3) 85% reduction in SOx, BC, and organic aerosol (OA) emissions (Sulf-BC-OA); and (4) 85% reduction in SOx, BC, OA, and nitrogen oxide (NOx) emissions (Sulf-BC-OA-NOx). The SOx reductions reflect the 0.5% fuel-sulfur cap implemented by the International Maritime Organization (IMO) on January 1st, 2020. The other reductions represent realistic estimates of future emission-control policies. We estimate that these policies could reduce fine particulate matter (PM2.5)-attributable mortalities by 13,200 (Sulf) to 38,600 (Sulf-BC-OA-NOx) mortalities per year. These changes represent 0.3% and 0.8%, respectively, of annual PM2.5-attributable mortalities from anthropogenic sources. Comparing simulations, we estimate that adding the NOx cap has the greatest health benefit. In contrast to the health benefits, all scenarios lead to a simulated climate warming tendency. The combined aerosol direct radiative effect (DRE) and cloud-albedo indirect effects (AIE) are between 27 mW m-2 (Sulf) and 41 mW m-2 (Sulf-BC-OA-NOx). These changes are about 2.1% (Sulf) to 3.2% (Sulf-BC-OA-NOx) of the total anthropogenic aerosol radiative forcing. The emission control policies examined here yield larger relative changes in the aerosol radiative forcing (2.1-3.2%) than in health effects (0.3-0.8%), because most shipping emissions are distant from populated regions. Valuation of the impacts suggests that these emissions reductions could produce much larger marginal health benefits ($128-$374 billion annually) than the marginal climate costs ($12-$17 billion annually). These data are analyzed results of five GEOS-Chem v12.6.0 simulations that were run to investigate the aerosol health and radiative impacts of four shipping-industry emission-control scenarios (see associated manuscript for details). The simulation was run for the globe in the year 2013 and the data were created in 2019 at Colorado State University in Fort Collins, Colorado, USA. The dataset includes two files. File 1 includes the radiative forcing estimates and the changes in aerosol composition under each of the emission-control scenarios, by latitude and longitude. File 2 is the estimates of averted mortality under each emission-control scenario, by country. Variable names and units are listed below. Recommended citation: Bilsback, K. Kerry, D., Croft, B., Ford, B., Jathar, S.H., Carter, E., Martin, R.V., & Pierce, J.R. (2020). Dataset associated with "Beyond SOx reductions from shipping: Assessing the impact of NOx and carbonaceous-particle controls on human health and climate." Colorado State University. Libraries. http://dx.doi.org/10.25675/10217/208319 File 1: radiative_forcing_and_aerosols.csv 1. Row number 2. Latitude 3. Longitude Radiative Forcing Estimates: 4. Sulf AIE (mW m-2) 5. Sulf-BC AIE (mW m-2) 6. Sulf-BC-OA AIE (mW m-2) 7. Sulf-BC-OA-NOx AIE (mW m-2) 8. Sulf Core-shell DRE (mW m-2) 9. Sulf-BC Core-shell DRE (mW m-2) 10. Sulf-BC-OA Core-shell DRE (mW m-2) 11. Sulf-BC-OA-NOx Core-shell DRE (mW m-2) 12. Sulf External DRE (mW m-2) 13. Sulf-BC External DRE (mW m-2) 14. Sulf-BC-OA External DRE (mW m-2) 15. Sulf-BC-OA-NOx External DRE (mW m-2) Particle Number Concentrations: 16. Sulf Change in N10 at 900 hPa (%) 17. Sulf Change in N80 at 900 hPa (%) 18. Sulf-BC Change in N10 at 900 hPa (%) 19. Sulf-BC Change in N80 at 900 hPa (%) 20. Sulf-BC-OA Change in N10 at 900 hPa (%) 21. Sulf-BC-OA Change in N80 at 900 hPa (%) 22. Sulf-BC-OA-NOx Change in N10 at 900 hPa (%) 23. Sulf-BC-OA-NOx Change in N80 at 900 hPa (%) Aerosol Mass Concentrations: 24. Sulf Change in column black carbon (%) 25. Sulf Change in column organic aerosol (%) 26. Sulf Change in column nitrate (%) 27. Sulf Change in column sulfate (%) 28. Sulf Change in column ammonium (%) 29. Sulf Change in column ozone (%) 30. Sulf-BC Change in column black carbon (%) 31. Sulf-BC Change in column organic aerosol (%) 32. Sulf-BC Change in column nitrate (%) 33. Sulf-BC Change in column sulfate (%) 34. Sulf-BC Change in column ammonium (%) 35. Sulf-BC Change in column ozone (%) 36. Sulf-BC-OA Change in column black carbon (%) 37. Sulf-BC-OA Change in column organic aerosol (%) 38. Sulf-BC-OA Change in column nitrate (%) 39. Sulf-BC-OA Change in column sulfate (%) 40. Sulf-BC-OA Change in column ammonium (%) 41. Sulf-BC-OA Change in column ozone (%) 42. Sulf-BC-OA-NOx Change in column black carbon (%) 43. Sulf-BC-OA-NOx Change in column organic aerosol (%) 44. Sulf-BC-OA-NOx Change in column nitrate (%) 45. Sulf-BC-OA-NOx Change in column sulfate (%) 46. Sulf-BC-OA-NOx Change in column ammonium (%) 47. Sulf-BC-OA-NOx Change in column ozone (%) 48. Sulf Change in surface PM2.5 (%) 49. Sulf Change in surface black carbon (%) 50. Sulf Change in surface organic aerosol (%) 51. Sulf Change in surface nitrate (%) 52. Sulf Change in surface sulfate (%) 53. Sulf Change in surface ammonium (%) 54. Sulf Change in surface ozone (%) 55. Sulf-BC Change in surface PM2.5 (%) 56. Sulf-BC Change in surface black carbon (%) 57. Sulf-BC Change in surface organic aerosol (%) 58. Sulf-BC Change in surface nitrate (%) 59. Sulf-BC Change in surface sulfate (%) 60. Sulf-BC Change in surface ammonium (%) 61. Sulf-BC Change in surface ozone (%) 62. Sulf-BC-OA Change in surface PM2.5 (%) 63. Sulf-BC-OA Change in surface black carbon (%) 64. Sulf-BC-OA Change in surface organic aerosol (%) 65. Sulf-BC-OA Change in surface nitrate (%) 66. Sulf-BC-OA Change in surface sulfate (%) 67. Sulf-BC-OA Change in surface ammonium (%) 68. Sulf-BC-OA Change in surface ozone (%) 69. Sulf-BC-OA-NOx Change in surface PM2.5 (%) 70. Sulf-BC-OA-NOx Change in surface black carbon (%) 71. Sulf-BC-OA-NOx Change in surface organic aerosol (%) 72. Sulf-BC-OA-NOx Change in surface nitrate (%) 73. Sulf-BC-OA-NOx Change in surface sulfate (%) 74. Sulf-BC-OA-NOx Change in surface ammonium (%) 75. Sulf-BC-OA-NOx Change in surface ozone (%) 76. Sulf Change in surface PM2.5 (ug m-3) 77. Sulf-BC Change in surface PM2.5 (ug m-3) 78. Sulf-BC-OA Change in surface PM2.5 (ug m-3) 79. Sulf-BC-OA-NOx Change in surface PM2.5 (ug m-3) File 2: mortalities.csv 1. Row number 2. Country 3. Sulf Mortalities averted (year-1) 4. Sulf-BC Mortalities averted (year-1) 5. Sulf-BC-OA Mortalities averted (year-1) 6. Sulf-BC-OA-NOx Mortalities averted (year-1)