Source apportionment of carbon monoxide over India: a quantitative analysis using MOZART-4

MOZART-4 chemistry transport model has been used to examine the contribution of carbon monoxide (CO) from different source regions/types by tagging their emissions in model simulations. These simulations are made using tagged tracer approach to estimate the relative contribution of different geographical regions and different emission sources, such as anthropogenic or biomass burning to the CO concentration at the surface, in the planetary boundary layer (PBL), and in the free troposphere (FT) over the Indian sub-continent. The CO budget analyses highlight the significant contribution of the Indian emissions on surface CO and influence of chemical production on the free tropospheric CO concentration. The total CO mixing ratio is estimated as 263 ± 139 parts per billion by volume (ppbv) for surface, 177 ± 71 ppbv for PBL, and 112 ± 14 ppbv for FT. The percentage contributions of primary sources are found to be 80%, 68%, and 53% at the surface, in the PBL, and in the FT, respectively. The sub-regional analysis of India shows that anthropogenic and photochemical processes contribute 41-75% and 15-46% CO, respectively, at the surface. Maximum percentage contribution of anthropogenic CO is observed over Indo-Gangetic Plain and Eastern India (75%). CO contribution from local anthropogenic and biomass burning emissions and transported from other global source regions are analyzed over the Indian region at the surface, in the PBL, and in the FT. The local anthropogenic sources contribute largest to the surface CO over India with 108 ppbv, followed by China with 98 ppbv, Europe with 55 ppbv, North America (NA) with 46 ppbv, and South-east Asia (SEA) and Middle East (ME) with 23 ppbv each. India's PBL (FT) CO is mostly influenced by China's anthropogenic emissions with 12 ppbv (8 ppbv) followed by SEA with 7 ppbv (6 ppbv). Surface biomass burning CO over India (6 ppbv) is much lower than in other regions such as SEA (32 ppbv), Africa (24 ppbv), and South America (11 ppbv). In the PBL (FT), SEA and Africa's BB emissions show major impact on CO over India with 6 ppbv (5 ppbv) and 5 ppbv (4 ppbv), respectively.

Modeling regional pollution transport events during KORUS-AQ: Progress and challenges in improving representation of land-atmosphere feedbacks

This study evaluates the impact of assimilating soil moisture data from NASA's Soil Moisture Active Passive (SMAP) on short-term regional weather and air quality modeling in East Asia during the Korea-US Air Quality Study (KORUS-AQ) airborne campaign. SMAP data are assimilated into the Noah land surface model using an ensemble Kalman filter approach in the Land Information System framework, which is semi-coupled with the NASA-Unified Weather Research and Forecasting model with online chemistry (NUWRF-Chem). With SMAP assimilation included, water vapor and carbon monoxide (CO) transport from northern-central China transitional climate zones to South Korea is better represented in NUWRF-Chem during two studied pollution events. Influenced by different synoptic conditions and emission patterns, impact of SMAP assimilation on modeled CO in South Korea is intense (>30 ppbv) during one event and less significant (<8 ppbv) during the other. SMAP assimilation impact on air quality modeling skill is complicated by other error sources such as the chemical initial and boundary conditions (IC/LBC) and emission inputs of NUWRF-Chem. Using a satellite-observation-constrained chemical IC/LBC instead of a free-running, coarser-resolution chemical IC/LBC reduces modeled CO by up to 80 ppbv over South Korea. Consequently, CO performance is improved in the middle-upper troposphere whereas degraded in the lower troposphere. Remaining negative CO biases result largely from the emissions inputs. The advancements in land surface modeling and chemical IC/LBC presented here are expected to benefit future investigations on constraining emissions using observations, which can in turn enable more accurate assessments of SMAP assimilation and chemical IC/LBC impacts.

Impact of wildfires on ozone exceptional events in the Western u.s

Wildfires generate substantial emissions of nitrogen oxides (NOx) and volatile organic compounds (VOCs). As such, wildfires contribute to elevated ozone (O3) in the atmosphere. However, there is a large amount of variability in the emissions of O3 precursors and the amount of O3 produced between fires. There is also significant interannual variability as seen in median O3, organic carbon and satellite derived carbon monoxide mixing ratios in the western U.S. To better understand O3 produced from wildfires, we developed a statistical model that estimates the maximum daily 8 h average (MDA8) O3 as a function of several meteorological and temporal variables for three urban areas in the western U.S.: Salt Lake City, UT; Boise, ID; and Reno, NV. The model is developed using data from June-September 2000-2012. For these three locations, the statistical model can explain 60, 52, and 27% of the variability in daily MDA8. The Statistical Model Residual (SMR) can give information on additional sources of O3 that are not explained by the usual meteorological pattern. Several possible O3 sources can explain high SMR values on any given day. We examine several cases with high SMR that are due to wildfire influence. The first case considered is for Reno in June 2008 when the MDA8 reached 82 ppbv. The wildfire influence for this episode is supported by PM concentrations, the known location of wildfires at the time and simulations with the Weather and Research Forecasting Model with Chemistry (WRF-Chem) which indicates transport to Reno from large fires burning in California. The contribution to the MDA8 in Reno from the California wildfires is estimated to be 26 ppbv, based on the SMR, and 60 ppbv, based on WRF-Chem. The WRF-Chem model also indicates an important role for peroxyacetyl nitrate (PAN) in producing O3 during transport from the California wildfires. We hypothesize that enhancements in PAN due to wildfire emissions may lead to regional enhancements in O3 during high fire years. The second case is for the Salt Lake City (SLC) region for August 2012. During this period the MDA8 reached 83 ppbv and the SMR suggests a wildfire contribution of 19 ppbv to the MDA8. The wildfire influence is supported by PM2.5 data, the known location of wildfires at the time, HYSPLIT dispersion modeling that indicates transport from fires in Idaho, and results from the CMAQ model that confirm the fire impacts. Concentrations of PM2.5 and O3 are enhanced during this period, but overall there is a poor relationship between them, which is consistent with the complexities in the secondary production of O3. A third case looks at high MDA8 in Boise, ID, during July 2012 and reaches similar conclusions. These results support the use of statistical modeling as a tool to quantify the influence from wildfires on urban O3 concentrations.