Investigation of surface energy and BVOC fluxes in the western United States during ENSO phases using the community land model

Interactions between the biosphere and the atmosphere play a fundamental role in determining pollutant transport and fate. Surface energy fluxes directly affect boundary layer dynamics and pollutant mixing, while biogenic volatile organic (BVOC) emissions influence atmospheric chemistry. The important driving factors for exchange processes include: net radiation, cloud cover, landcover, surface albedo, soil moisture, precipitation, and ambient temperature. Changes in the atmosphere, such as the El Nino Southern Oscillation (ENSO), can directly affect these factors and the associated surface exchange processes. The Community Land Model (CLM) simulates biosphere/atmosphere interactions and provides a way to investigate the effects of ENSO on surface energy fluxes and BVOC emissions. In this research, the overall goal was to improve our understanding of biosphere/atmosphere interactions across the western US. The specific objectives were 1) to evaluate CLM against observed sensible heat fluxes (SHF) and latent heat fluxes (LHF) using eddy covariance flux data from 38 sites for the period 2010-2017, and 2) to assess the effects of ENSO on surface energy fluxes and BVOC emissions with particular focus on 2011 (a strong La Niña) and 2015 (a very strong El Niño). We ran CLM4.5 over the western US (12 km x 12 km grids) with atmospheric data from the North American Land Data Assimilation System. Overall, CLM performed well for SHF and LHF across all landuse types with fractional bias and error less than 15% and 25%, respectively. However, the CLM evaluation indicates a potential issue for simulating the complexities of forest canopies as well as correct cropland management activities (i.e., harvest). The simulated ENSO patterns were generally consistent with expected ENSO cycles. The overall departures of temperature and SHF due to ENSO are correlated. Similarly, the departures of precipitation and LHF are correlated. The Northwest and South climate regions had the largest contrasting behavior for SHF/LHF and BVOCs emissions during summer and spring and for SHF and BVOCs emissions during winter. The fluxes from specific land types are predominately affected by the climate zone

The Survey of NOX Distribution Using Dispersion Models AERMOD and CALPUFF at a Gas Refinery

Background & Objectives: Nowadays, air pollution is one of the major challenges in the world, therefore, in the present study, according to the importance of the fourth refinery gas as the largest gas refinery in the region, the amount of emissions from stacks has been initially determined and then the distribution has been identified in the region. Methods: In this research, AERMOD and CALPUFF models have been used as the tools for the analysis of NOX emissions of stacks of 4th South Pars gas refinery located in Assaluyeh. First, NOX emissions from refinery stacks have been obtained by field measurements. Then, the distribution of these emissions has been examined using dispersion models AERMOD and CALPUFF in an area of 50 × 50 km in each direction x and y in the one-year period of 2013 to the average time of 1, 3, 8, and 24 and the amounts resulting from the implementation of the models have been compared to the results of field measurements at 9 receiving stations as a separate receptors in the model. Results: Review of charts and statistical parameters has shown that, according to the evaluation of predictions made, the CALPUFF model was better than AERMOD model, in the studied area. Conclusion: It could be concluded that performance of both models to predict the concentration of pollutants in the region can be generally considered acceptable

Dispersion Modeling of CO with AERMOD in South Pars fourth Gas Refinery

Background: Air quality modeling can be considered as a useful tool to predict air quality in future and determine the control strategies of emissions abatement. In this study, AERMOD dispersion model has been applied as a tool for the analysis of the values of CO emissions from the stacks and flares of South Pars fourth Gas Refinery located in Asaluyeh. Methods: First, the values of CO  emissions from the refinery's stacks and flares were investigated by measurement and using the emission factors in four seasons of 2013. Then, dispersion of pollutants was predicted by using the AERMOD model in the region with area of 10×10 km2  in each direction of x and y, in average times of 1, 3, 8, 24-hours and for the annual statistical period. Then the predicted and field measurement values in 9 receptors have been compared. Results: Statistical evaluation showed that the correlation coefficient values for CO were 0.85 in spring, 0.89 in summer, 0.96 in fall, and 0.95 in winter. The maximum concentration of CO was occurred in local scale of 10×10 km2. Conclusion: Comparison of maximum 1-hour and 8-hour concentrations of the predicted results with the national and international standards showed that CO concentration is higher than standard values. In total, according to the evaluation of the predictions made, the performance of AERMOD model was acceptable in prediction of CO concentrations in the study area