WRF-Chem simulated surface ozone over south Asia during the pre-monsoon: effects of emission inventories and chemical mechanisms

Sharma, Amit; Ojha, Narendra; Pozzer, Andrea; Mar, Kathleen A.; Beig, Gufran; Lelieveld, Jos; Gunthe, Sachin S.

doi:10.5194/acp-17-14393-2017

Cited by 72 publications

(54 citation statements)

References 93 publications

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“…Although there is no perfect source apportionment technique for nonlinear systems, a reasonable method that tracks mass contributions and accounts for chemical nonlinearity can provide additional information in terms of the design of control strategies (Yarwood et al, 2007). In the tagging method, the photochemical indicator HCHO / NO y with a threshold of 0.28 (Sillman, 1995) was used to determine NO x -or VOC-limited conditions, which can also result in uncertainties in the results. Several other indicators have been proposed to indicate photochemical sensitivity, including O 3 / NO x and O 3 / NO y .…”

Section: Discussion and Summarymentioning

confidence: 99%

“…Both O 3 and its precursors from different source regions are tracked as independent variables. The ratio of formaldehyde to reactive nitrogen oxides (HCHO / NO y ) was used as proposed by Sillman (1995) to decide whether the grid cell is under NO x or VOC-limited conditions, and then different equations for these two conditions were selected to calculate total O 3 chemical production. A detailed description of the technique is provided in Gao et al (2017a).…”

Section: Ozone Tagging Methods and Setting Of Source Regionsmentioning

confidence: 99%

“…tumn (fewer biogenic emissions of VOCs in these seasons; Fu et al, 2012). The ratio of formaldehyde to reactive nitrogen (HCHO / NO y ) is widely used to determine the O 3 production sensitivity with a critical value of 0.28 (Sillman, 1995;Zhao et al, 2009). Figure S8 indicates that east China is VOC-limited in winter, spring, and autumn.…”

Section: O 3 Sensitivity To Emissions From Individual Source Sectorsmentioning

confidence: 99%

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Ozone pollution over China and India: seasonality and sources

et al. 2020

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A regional fully coupled meteorology-chemistry model, Weather Research and Forecasting model with Chemistry (WRF-Chem), was employed to study the seasonality of ozone (O 3 ) pollution and its sources in both China and India. Observations and model results suggest that O 3 in the North China Plain (NCP), Yangtze River Delta (YRD), Pearl River Delta (PRD), and India exhibit distinctive seasonal features, which are linked to the influence of summer monsoons. Through a factor separation approach, we examined the sensitivity of O 3 to individual anthropogenic, biogenic, and biomass burning emissions. We found that summer O 3 formation in China is more sensitive to industrial and biogenic sources than to other source sectors, while the transportation and biogenic sources are more important in all seasons for India. Tagged simulations suggest that local sources play an important role in the formation of the summer O 3 peak in the NCP, but sources from Northwest China should not be neglected to control summer O 3 in the NCP. For the YRD region, prevailing winds and cleaner air from the ocean in summer lead to reduced transport from polluted regions, and the major source region in addition to local sources is Southeast China. For the PRD region, the upwind region is replaced by contributions from polluted PRD as autumn approaches, leading to an autumn peak. The major upwind regions in autumn for the PRD are YRD (11 %) and Southeast China (10 %). For India, sources in North India are more important than sources in the south. These analyses emphasize the relative importance of source sectors and regions as they change with seasons, providing important implications for O 3 control strategies.

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Section: Discussion and Summarymentioning

confidence: 99%

Section: Ozone Tagging Methods and Setting Of Source Regionsmentioning

confidence: 99%

Section: O 3 Sensitivity To Emissions From Individual Source Sectorsmentioning

confidence: 99%

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Ozone pollution over China and India: seasonality and sources

et al. 2020

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“…Li et al () also pointed out that substantial uncertainties exist in the estimated emissions, especially for regions experiencing rapid changes in the economy such as China and India. For instance, a comparison of different anthropogenic emission inventories using WRF‐Chem over Southeast and South Asia has been performed in Amnuaylojaroen et al () and Sharma et al (). Amnuaylojaroen et al () showed that the uncertainties of carbon monoxide surface mixing ratios in simulations with different anthropogenic emission inventories reach 30%.…”

Section: Introductionmentioning

confidence: 99%

“…Amnuaylojaroen et al () showed that the uncertainties of carbon monoxide surface mixing ratios in simulations with different anthropogenic emission inventories reach 30%. Sharma et al () showed that the modeled ozone mixing ratios during noontime are sensitive to the choice of an emission inventory.…”

Section: Introductionmentioning

confidence: 99%

Study of SO Pollution in the Middle East Using MERRA‐2, CAMS Data Assimilation Products, and High‐Resolution WRF‐Chem Simulations

et al. 2020

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Oil recovery, power generation, water desalination, gas flaring, and traffic are the main contributors to SO2 emissions in the Middle East (ME). Satellite observations suggest that the traditional emission inventories do not account for multiple SO2 emission sources in the ME. This study aims to evaluate the most frequently used SO2 emission data sets over the ME by comparing high‐resolution regional model simulations and meteorology/chemistry assimilation products, MERRA‐2 and CAMS, with satellite and available ground‐based air‐quality observations. Here, we employ the WRF‐Chem‐3.7.1 regional meteorology‐chemistry model and conduct simulations for the period 2015–2016 with 10 km grid spacing using HTAP‐2.2 emission data sets and the new OMI‐HTAP data, which is based on the combination of the near‐surface SO2 emissions taken from the HTAP‐2.2 inventory with strong (>30 kt/year) SO2 point sources obtained from the satellite Ozone Monitoring Instrument (OMI) observations. We find that conventional emission inventories (EDGAR‐4.2, MACCity, and HTAP‐2.2) have uncertainties in the location and magnitude of SO2 sources in the ME and significantly underestimate SO2 emissions in the Arabian Gulf. The WRF‐Chem, run in conjunction with the new OMI‐HTAP emissions, improves comparisons between the satellite and ground‐based SO2 observations. Our simulations show that SO2 surface concentrations in Jeddah and Riyadh frequently exceed European air‐quality limits. The ME generates about 10% of global anthropogenic SO2 emissions, on par with India. Therefore, the development of effective emission controls and improvement of air‐quality monitoring in the ME are urgently needed.

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Elucidating the Impacts of COVID-19 Lockdown on Air Quality and Ozone Chemical Characteristics in India

Roozitalab

Carmichael

Guttikunda³

et al. 2021

Preprint

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India implemented stay-at-home order (i.e. lockdown) on 24 March 2020 to decrease the spread of novel COVID-19, which reduced air pollutant emissions in different sectors. The Weather Research and Forecasting model with Chemistry (WRF-Chem) was used to study the changes in air pollutants during the lockdown period in 2020 compared with similar period in 2019. We found that both meteorology and lockdown emissions contributed to daytime PM 2.5 (-6% and -11%, respectively) and ozone (-6% and -8%, respectively) reduction averaged in April 2020 in the Indo-Gangetic Plain. However, the ozone concentration response to reductions in its precursors (i.e. NO 2 and VOCs) due to the lockdown emissions was not constant over the domain.While ozone concentration decreased in most parts of the domain, it slightly increased in major cities like Delhi and in regions with many power plants. We utilized the reaction rates information in WRF-Chem to study the ozone chemistry. We found carbon monoxide, formaldehyde, isoprene, acetaldehyde, and ethylene as the major VOCs that contribute to the ozone formation in India. We used the ratio of chemical loss of radicals with radicals and NOx, and its corresponding formaldehyde to NO 2 ratio (FNR) to find the ozone chemical regimes. Using the upper limit of FNR transition region (1.3), we found that most parts of India are within NOx-limited regime while urban regions and the regions with many power plants are in a VOC-limited regime.As a result, policy makers should study the characteristics of a region before implementing mitigation strategies.

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WRF-Chem simulated surface ozone over south Asia during the pre-monsoon: effects of emission inventories and chemical mechanisms

Cited by 72 publications

References 93 publications

Ozone pollution over China and India: seasonality and sources

Ozone pollution over China and India: seasonality and sources

Study of SO Pollution in the Middle East Using MERRA‐2, CAMS Data Assimilation Products, and High‐Resolution WRF‐Chem Simulations

Elucidating the Impacts of COVID-19 Lockdown on Air Quality and Ozone Chemical Characteristics in India

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