Why is the Indo-Gangetic Plain the region with the largest NH&amp;lt;sub&amp;gt;3&amp;lt;/sub&amp;gt; column in the globe during pre-monsoon and monsoon seasons?

Wang, Tiantian; Song, Yu; Xu, Zhenying; Liu, Mingxu; Xu, Tingting; Liao, Wenling; Yin, Longfei; Cai, Xuhui; Kang, Ling; Zhang, Hongsheng; Zhu, Tong

doi:10.5194/acp-20-8727-2020

Cited by 13 publications

(20 citation statements)

References 43 publications

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“…Seasonal enhancements come from intense agricultural fires along the Indo-Gangetic Plain (IGP) north of Delhi, frequent firework festivals, and dust storms originating from the Thar Desert and Arabian Peninsula (Ghosh et al, 2014;Parkhi et al, 2016;Yadav et al, 2017;Liu et al, 2018). Like the UK, the agricultural sector is not directly regulated, and intense agricultural activity in the IGP contributes to the largest global NH 3 hotspot (Warner et al, 2017;Van Damme et al, 2018;T. Wang et al, 2020).…”

Section: Introductionmentioning

confidence: 99%

Long-term trends in air quality in major cities in the UK and India: a view from space

et al. 2021

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Abstract. Air quality networks in cities can be costly and inconsistent and typically monitor a few pollutants. Space-based instruments provide global coverage spanning more than a decade to determine trends in air quality, augmenting surface networks. Here we target cities in the UK (London and Birmingham) and India (Delhi and Kanpur) and use observations of nitrogen dioxide (NO2) from the Ozone Monitoring Instrument (OMI), ammonia (NH3) from the Infrared Atmospheric Sounding Interferometer (IASI), formaldehyde (HCHO) from OMI as a proxy for non-methane volatile organic compounds (NMVOCs), and aerosol optical depth (AOD) from the Moderate Resolution Imaging Spectroradiometer (MODIS) for PM2.5. We assess the skill of these products at reproducing monthly variability in surface concentrations of air pollutants where available. We find temporal consistency between column and surface NO2 in cities in the UK and India (R = 0.5–0.7) and NH3 at two of three rural sites in the UK (R = 0.5–0.7) but not between AOD and surface PM2.5 (R < 0.4). MODIS AOD is consistent with AERONET at sites in the UK and India (R ≥ 0.8) and reproduces a significant decline in surface PM2.5 in London (2.7 % a−1) and Birmingham (3.7 % a−1) since 2009. We derive long-term trends in the four cities for 2005–2018 from OMI and MODIS and for 2008–2018 from IASI. Trends of all pollutants are positive in Delhi, suggesting no air quality improvements there, despite the roll-out of controls on industrial and transport sectors. Kanpur, identified by the WHO as the most polluted city in the world in 2018, experiences a significant and substantial (3.1 % a−1) increase in PM2.5. The decline of NO2, NH3, and PM2.5 in London and Birmingham is likely due in large part to emissions controls on vehicles. Trends are significant only for NO2 and PM2.5. Reactive NMVOCs decline in Birmingham, but the trend is not significant. There is a recent (2012–2018) steep (> 9 % a−1) increase in reactive NMVOCs in London. The cause for this rapid increase is uncertain but may reflect the increased contribution of oxygenated volatile organic compounds (VOCs) from household products, the food and beverage industry, and domestic wood burning, with implications for the formation of ozone in a VOC-limited city.

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Section: Introductionmentioning

confidence: 99%

Long-term trends in air quality in major cities in the UK and India: a view from space

et al. 2021

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“…MOZART-4 includes 157 gas-phase reactions, 85 gas-phase species, 39 photolysis compounds and 12 bulk aerosol compounds (Emmons et al, 2010). Dry deposition of gases and aerosols was calculated online according to the parameterisation of Wesely (1989), and wet deposition of soluble gases was calculated as described by the method of Emmons et al (2010). Land use cover (LUC) maps used in MOZART-4 are based on the Advanced Very High Resolution Radiometer (AVHRR) and Moderate Resolution Imaging Spectroradiometer (MODIS) data based on the NCAR Community Land Model (CLM) (Oleson et al, 2010).…”

Section: Mozart-4 Modelmentioning

confidence: 99%

“…The application of any equilibrium model (EQM) in global atmospheric studies is associated with considerable uncertainties. In MOZART-4 chemistry, the ammonium nitrate distribution is determined from NH 3 emissions and the parameterisation of gas-aerosol par- (Jena et al, 2015b;Wang et al, 2020), which can introduce additional uncertainty in NH 3 / NH + 4 gas-aerosol partitioning. In MOZART-4 chemistry, uncertainty can also be associated with the dry and wet deposition scheme, which can result in overestimation (Emmons et al, 2010).…”

Section: Annual Mean Nh 3 Total Columns Over South Asiamentioning

confidence: 99%

“…Han et al (2020) suggested that an updated emission inventory as per the source activity is essential for South Asia to reduce the uncertainties in simulated NH 3 over this region. A recent study by Wang et al (2020) examined the NH 3 column observed over the IGP during summer using a regional model driven with the MIX emission inventory. The study suggested that high agriculture activity and high summer temperature contribute to high NH 3 emission fluxes over the IGP, which lead to large total columns.…”

Section: Introductionmentioning

confidence: 99%

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Analysis of atmospheric ammonia over South and East Asia based on the MOZART-4 model and its comparison with satellite and surface observations

et al. 2021

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Abstract. Limited availability of atmospheric ammonia (NH3) observations limits our understanding of controls on its spatial and temporal variability and its interactions with the ecosystem. Here we used the Model for Ozone and Related chemical Tracers version 4 (MOZART-4) global chemistry transport model and the Hemispheric Transport of Air Pollution version 2 (HTAP-v2) emission inventory to simulate global NH3 distribution for the year 2010. We presented a first comparison of the model with monthly averaged satellite distributions and limited ground-based observations available across South Asia. The MOZART-4 simulations over South Asia and East Asia were evaluated with the NH3 retrievals obtained from the Infrared Atmospheric Sounding Interferometer (IASI) satellite and 69 ground-based monitoring stations for air quality across South Asia and 32 ground-based monitoring stations from the Nationwide Nitrogen Deposition Monitoring Network (NNDMN) of China. We identified the northern region of India (Indo-Gangetic Plain, IGP) as a hotspot for NH3 in Asia, both using the model and satellite observations. In general, a close agreement was found between yearly averaged NH3 total columns simulated by the model and IASI satellite measurements over the IGP, South Asia (r=0.81), and the North China Plain (NCP), East Asia (r=0.90). However, the MOZART-4-simulated NH3 column was substantially higher over South Asia than East Asia, as compared with the IASI retrievals, which show smaller differences. Model-simulated surface NH3 concentrations indicated smaller concentrations in all seasons than surface NH3 measured by the ground-based observations over South and East Asia, although uncertainties remain in the available surface NH3 measurements. Overall, the comparison of East Asia and South Asia using both MOZART-4 model and satellite observations showed smaller NH3 columns in East Asia compared with South Asia for comparable emissions, indicating rapid dissipation of NH3 due to secondary aerosol formation, which can be explained by larger emissions of acidic precursor gases in East Asia.

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“…Emissions from land transportation, particularly in cities, also represent a significant contribution to anthropogenic emissions (Begum et al, 2013;Mallik and Lal, 2014). Intense agriculture over the IGP is associated with large emissions of ammonia, an aerosol precursor, from urea fertiliser application, as well as from post-harvest burning as described above (Kuttippurath et al, 2020;Wang et al, 2020). Vegetation cover over the IGP consists mainly of croplands (Stibig et al, 2007;Gumma et al, 2019), which have lower isoprene emissions than trees (Hardacre et al, 2013).…”

Section: Introductionmentioning

confidence: 99%

Seasonal distribution and drivers of surface fine particulate matter and organic aerosol over the Indo-Gangetic Plain

et al. 2021

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Abstract. The Indo-Gangetic Plain (IGP) is home to 9 % of the global population and is responsible for a large fraction of agricultural crop production in Pakistan, India, and Bangladesh. Levels of fine particulate matter (mean diameter <2.5 µm, PM2.5) across the IGP often exceed human health recommendations, making cities across the IGP among the most polluted in the world. Seasonal changes in the physical environment over the IGP are dominated by the large-scale south Asian monsoon system that dictates the timing of agricultural planting and harvesting. We use the WRF-Chem model to study the seasonal anthropogenic, pyrogenic, and biogenic influences on fine particulate matter and its constituent organic aerosol (OA) over the IGP that straddles Pakistan, India, and Bangladesh during 2017–2018. We find that surface air quality during pre-monsoon (March–May) and monsoon (June–September) seasons is better than during post-monsoon (October–December) and winter (January–February) seasons, but all seasonal mean values of PM2.5 still exceed the recommended levels, so that air pollution is a year-round problem. Anthropogenic emissions influence the magnitude and distribution of PM2.5 and OA throughout the year, especially over urban sites, while pyrogenic emissions result in localised contributions over the central and upper parts of IGP in all non-monsoonal seasons, with the highest impact during post-monsoon seasons that correspond to the post-harvest season in the agricultural calendar. Biogenic emissions play an important role in the magnitude and distribution of PM2.5 and OA during the monsoon season, and they show a substantial contribution to secondary OA (SOA), particularly over the lower IGP. We find that the OA contribution to PM2.5 is significant in all four seasons (17 %–30 %), with primary OA generally representing the larger fractional contribution. We find that the volatility distribution of SOA is driven mainly by the mean total OA loading and the washout of aerosols and gas-phase aerosol precursors that result in SOA being less volatile during the pre-monsoon and monsoon season than during the post-monsoon and winter seasons.

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Why is the Indo-Gangetic Plain the region with the largest NH<sub>3</sub> column in the globe during pre-monsoon and monsoon seasons?

Cited by 13 publications

References 43 publications

Long-term trends in air quality in major cities in the UK and India: a view from space

Long-term trends in air quality in major cities in the UK and India: a view from space

Analysis of atmospheric ammonia over South and East Asia based on the MOZART-4 model and its comparison with satellite and surface observations

Seasonal distribution and drivers of surface fine particulate matter and organic aerosol over the Indo-Gangetic Plain

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