Neil J. M. Wheeler

Bio: Neil J. M. Wheeler is an academic researcher from North Carolina State University. The author has contributed to research in topics: Air quality index & Decision support system. The author has an hindex of 8, co-authored 22 publications receiving 673 citations.

Emission inventory development and processing for the Seasonal Model for Regional Air Quality (SMRAQ) project

Abstract: This paper describes the experiences and insights gained from inventory preparation and emissions processing for the Seasonal Model for Regional Air Quality (SMRAQ) project. The emission inventory was derived from the 1990 and 1995 Ozone Transport Assessment Group (OTAG) inventories. Here we outline the emissions processing strategy used for the May-to-September simulation, summarize the inventory characteristics and corrections made on the OTAG inventories, and describe the quality assurance steps taken as part of the processing. We then provide spatial maps and daily total time series charts of the hourly, gridded emissions of nitrogen oxides (NOx), reactive organic gases (ROG), and carbon monoxide (CO). Large peaks from electric utility point sources and urban mobile sources characterize the NOx emissions, and the NOx emissions in nonpeak regions are primarily mobile-source emissions. ROG emissions are dominated by biogenic isoprene production in the southern United States, and they have a strong seasonal variability. CO emissions are characterized by less variability, with area and mobile sources dominating the inventory. We compare ratios of season-average nonmethane organic gases to NOx between the emission inventory and the Photochemical Assessment Monitoring Stations (PAMS) data, and these comparisons show poor correlation between the inventory and ambient ratios.

Toward Effective Source Apportionment Using Positive Matrix Factorization: Experiments with Simulated PM2.5 Data

Abstract: To elucidate the relationship between factors resolved by the positive matrix factorization (PMF) receptor model and actual emission sources and to refine the PMF modeling strategy, speciated PM2.5 (particulate matter with aerodynamic diameter 0.95). Retaining more factors in the model does not help resolve minor sources, unless temporal resolution of the data is increased, thus allowing more information to be used by the model. If guided with a priori knowledge of source markers and/or special events, rotation of factors leads to more interpretable PMF factors. The choice of uncertainty weighting coefficients greatly influences the PMF modeling results, but it cannot usually be determined for simulated or real-world data. A simple test is recommended to check whether the weighting coefficients are suitable. However, uncertainties in the data divert PMF solutions even when the optimal weighting coefficients and number of factors are in place.

An Evaluation of Modeled Plume Injection Height with Satellite-Derived Observed Plume Height

Abstract: Plume injection height influences plume transport characteristics, such as range and potential for dilution. We evaluateplume injection height from a predictive wildland d fire smoke transport model over the contiguous United States (U.S.) from 2006 to 2008 using satellite-derived information, including plume top heights from the Multiangle -Imaging SpectroRadiometer (MISR) Plume Height Climatology Project and aerosol vertical profiles from the Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP). While significant geographic variability was found in the comparison between modeled plumes and satellite-detected plumes, modeled plume heights were lower overall. In the eastern U.S., satellite-detected and modeled plume heights were similar (median height 671 and 660 m respectively). Both satellite-derived and modeled plume injection heights were higher in the western .S. U(2345 and 1172 m, respectively). Comparisons of modeled plume injection 2height to satellite-derived plume height at the fire location (

Analyses of BlueSky Gateway PM2.5 predictions during the 2007 southern and 2008 northern California fires

Abstract: [1] We evaluated predictions of hourly PM2.5surface concentrations produced by the experimental BlueSky Gateway air quality modeling system during two wildfire episodes in southern California (Case 1) and northern California (Case 2). In southern California, the prediction performance was dominated by the prevailing synoptic weather patterns, which differentiated the smoke plumes into two types: narrow and highly concentrated during an offshore flow, and diluted and well-mixed during a light onshore flow. For the northern California fires, the prediction performance was dominated by terrain and the limitations of predicting concentrations in a narrow valley, rather than by the synoptic pattern, which did not differ much throughout the wildfire episode. There was an over-prediction bias for the maximum values during this episode. When the predicted values were compared to observed values, the best performance results were for the onshore flow during the southern California fires, indicating that the coarse grid used by BlueSky Gateway appropriately represented these well-mixed conditions. Overall, the southern California fire predictions were biased low and the model did not reproduce the high hourly concentrations (>240μg/m3) observed by the monitors. The predicted results performed well against the observations for the northern California fires, with a large number of predicted values within acceptable range of the observed values.

Numerical study of convection observed during the Winter Monsoon Experiment using a mesoscale two-dimensional model [presentation]

Abstract: Abstract A two-dimensional version of the Pennsylvania State University mesoscale model has been applied to Winter Monsoon Experiment data in order to simulate the diurnally occurring convection observed over the South China Sea. The domain includes a representation of part of Borneo as well as the sea so that the model can simulate the initiation of convection. Also included in the model are parameterizations of mesoscale ice phase and moisture processes and longwave and shortwave radiation with a diurnal cycle. This allows use of the model to test the relative importance of various heating mechanisms to the stratiform cloud deck, which typically occupies several hundred kilometers of the domain. Frank and Cohen's cumulus parameterization scheme is employed to represent vital unresolved vertical transports in the convective area. The major conclusions are: Ice phase processes are important in determining the level of maximum large-scale heating and vertical motion because there is a strong anvil componen...

PM 2.5 pollution in a megacity of southwest China: source apportionment and implication

Abstract: . Daily PM2.5 (aerosol particles with an aerodynamic diameter of less than 2.5 μm) samples were collected at an urban site in Chengdu, an inland megacity in southwest China, during four 1-month periods in 2011, with each period in a different season. Samples were subject to chemical analysis for various chemical components ranging from major water-soluble ions, organic carbon (OC), element carbon (EC), trace elements to biomass burning tracers, anhydrosugar levoglucosan (LG), and mannosan (MN). Two models, the ISORROPIA II thermodynamic equilibrium model and the positive matrix factorization (PMF) model, were applied to explore the likely chemical forms of ionic constituents and to apportion sources for PM2.5. Distinctive seasonal patterns of PM2.5 and associated main chemical components were identified and could be explained by varying emission sources and meteorological conditions. PM2.5 showed a typical seasonality of waxing in winter and waning in summer, with an annual mean of 119 μg m−3. Mineral soil concentrations increased in spring, whereas biomass burning species elevated in autumn and winter. Six major source factors were identified to have contributed to PM2.5 using the PMF model. These were secondary inorganic aerosols, coal combustion, biomass burning, iron and steel manufacturing, Mo-related industries, and soil dust, and they contributed 37 ± 18, 20 ± 12, 11 ± 10, 11 ± 9, 11 ± 9, and 10 ± 12%, respectively, to PM2.5 masses on annual average, while exhibiting large seasonal variability. On annual average, the unknown emission sources that were not identified by the PMF model contributed 1 ± 11% to the measured PM2.5 mass. Various chemical tracers were used for validating PMF performance. Antimony (Sb) was suggested to be a suitable tracer of coal combustion in Chengdu. Results of LG and MN helped constrain the biomass burning sources, with wood burning dominating in winter and agricultural waste burning dominating in autumn. Excessive Fe (Ex-Fe), defined as the excessive portion in measured Fe that cannot be sustained by mineral dust, is corroborated to be a straightforward useful tracer of iron and steel manufacturing pollution. In Chengdu, Mo / Ni mass ratios were persistently higher than unity, and considerably distinct from those usually observed in ambient airs. V / Ni ratios averaged only 0.7. Results revealed that heavy oil fuel combustion should not be a vital anthropogenic source, and additional anthropogenic sources for Mo are yet to be identified. Overall, the emission sources identified in Chengdu could be dominated by local sources located in the vicinity of Sichuan, a result different from those found in Beijing and Shanghai, wherein cross-boundary transport is significant in contributing pronounced PM2.5. These results provided implications for PM2.5 control strategies.

Climate change, ambient ozone, and health in 50 US cities

Abstract: We investigated how climate change could affect ambient ozone concentrations and the subsequent human health impacts. Hourly concentrations were estimated for 50 eastern US cities for five representative summers each in the 1990s and 2050s, reflecting current and projected future climates, respectively. Estimates of future concentrations were based on the IPCC A2 scenario using global climate, regional climate, and regional air quality models. This work does not explore the effects of future changes in anthropogenic emissions, but isolates the impact of altered climate on ozone and health. The cities’ ozone levels are estimated to increase under predicted future climatic conditions, with the largest increases in cities with present-day high pollution. On average across the 50 cities, the summertime daily 1-h maximum increased 4.8 ppb, with the largest increase at 9.6 ppb. The average number of days/summer exceeding the 8-h regulatory standard increased 68%. Elevated ozone levels correspond to approximately a 0.11% to 0.27% increase in daily total mortality. While actual future ozone concentrations depend on climate and other influences such as changes in emissions of anthropogenic precursors, the results presented here indicate that with other factors constant, climate change could detrimentally affect air quality and thereby harm human health.

Emission inventory development and processing for the Seasonal Model for Regional Air Quality (SMRAQ) project

Abstract: This paper describes the experiences and insights gained from inventory preparation and emissions processing for the Seasonal Model for Regional Air Quality (SMRAQ) project. The emission inventory was derived from the 1990 and 1995 Ozone Transport Assessment Group (OTAG) inventories. Here we outline the emissions processing strategy used for the May-to-September simulation, summarize the inventory characteristics and corrections made on the OTAG inventories, and describe the quality assurance steps taken as part of the processing. We then provide spatial maps and daily total time series charts of the hourly, gridded emissions of nitrogen oxides (NOx), reactive organic gases (ROG), and carbon monoxide (CO). Large peaks from electric utility point sources and urban mobile sources characterize the NOx emissions, and the NOx emissions in nonpeak regions are primarily mobile-source emissions. ROG emissions are dominated by biogenic isoprene production in the southern United States, and they have a strong seasonal variability. CO emissions are characterized by less variability, with area and mobile sources dominating the inventory. We compare ratios of season-average nonmethane organic gases to NOx between the emission inventory and the Photochemical Assessment Monitoring Stations (PAMS) data, and these comparisons show poor correlation between the inventory and ambient ratios.