Record high levels of atmospheric ammonia over India: Spatial and temporal analyses

Atmospheric ammonia (NH₃) is an alkaline gas and a prominent constituent of the nitrogen cycle that adversely affects ecosystems at higher concentrations. It is a pollutant, which influences all three spheres such as haze formation in the atmosphere, soil acidification in the lithosphere, and eutrophication in water bodies. Atmospheric NH₃ reacts with sulfur (SO_x) and nitrogen (NO_x) oxides to form aerosols, which eventually affect human health and climate. Here, we present the seasonal and inter-annual variability of atmospheric NH₃ over India in 2008-2016 using the IASI (Infrared Atmospheric Sounding Interferometer) satellite observations. We find that Indo-Gangetic Plains (IGP) is one of the largest and rapidly growing NH₃ hotspots of the world, with a growth rate of +1.2% yr^-1 in summer (June-August: Kharif season), due to intense agricultural activities and presence of many fertilizer industries there. However, our analyses show insignificant decreasing trends in annual NH₃ of about -0.8% yr^-1 in all India, about -0.4% yr^-1 in IGP, and -1.0% yr^-1 in the rest of India. Ammonia is positively correlated with total fertilizer consumption (r = 0.75) and temperature (r = 0.5) since high temperature favors volatilization, and is anti-correlated with total precipitation (r = from -0.2, but -0.8 in the Rabi season: October-February) as wet deposition helps removal of atmospheric NH₃. This study, henceforth, suggests the need for better fertilization practices and viable strategies to curb emissions, to alleviate the adverse health effects and negative impacts on the ecosystem in the region. On the other hand, the overall decreasing trend in atmospheric NH₃ over India shows the positive actions, and commitment to the national missions and action plans to reduce atmospheric pollution and changes in climate.

Using satellite-based measurements to explore spatiotemporal scales and variability of drivers of new particle formation

New particle formation (NPF) can potentially alter regional climate by increasing aerosol particle (hereafter particle) number concentrations and ultimately cloud condensation nuclei. The large scales on which NPF is manifest indicate potential to use satellite-based (inherently spatially averaged) measurements of atmospheric conditions to diagnose the occurrence of NPF and NPF characteristics. We demonstrate the potential for using satellite-based measurements of insolation (UV), trace gas concentrations (sulfur dioxide (SO₂), nitrogen dioxide (NO₂), ammonia (NH₃), formaldehyde (HCHO), and ozone (O₃)), aerosol optical properties (aerosol optical depth (AOD) and Ångström exponent (AE)), and a proxy of biogenic volatile organic compound emissions (leaf area index (LAI) and temperature (T)) as predictors for NPF characteristics: formation rates, growth rates, survival probabilities, and ultrafine particle (UFP) concentrations at five locations across North America. NPF at all sites is most frequent in spring, exhibits a one-day autocorrelation, and is associated with low condensational sink (AOD × AE) and HCHO concentrations, and high UV. However, there are important site-to-site variations in NPF frequency and characteristics, and in which of the predictor variables (particularly gas concentrations) significantly contribute to the explanatory power of regression models built to predict those characteristics. This finding may provide a partial explanation for the reported spatial variability in skill of simple generalized nucleation schemes in reproducing observed NPF. In contrast to more simple proxies developed in prior studies (e.g., based on AOD, AE, SO₂, and UV), use of additional predictors (NO₂, NH₃, HCHO, LAI, T, and O₃) increases the explained temporal variance of UFP concentrations at all sites.

Tropospheric methanol observations from space: retrieval evaluation and constraints on the seasonality of biogenic emissions

Methanol retrievals from nadir-viewing space-based sensors offer powerful new information for quantifying methanol emissions on a global scale. Here we apply an ensemble of aircraft observations over North America to evaluate new methanol measurements from the Tropospheric Emission Spectrometer (TES) on the Aura satellite, and combine the TES data with observations from the Infrared Atmospheric Sounding Interferometer (IASI) on the MetOp-A satellite to investigate the seasonality of methanol emissions from northern midlatitude ecosystems. Using the GEOS-Chem chemical transport model as an intercomparison platform, we find that the TES retrieval performs well when the degrees of freedom for signal (DOFS) are above 0.5, in which case the model:TES regressions are generally consistent with the model:aircraft comparisons. Including retrievals with DOFS below 0.5 degrades the comparisons, as these are excessively influenced by the a priori. The comparisons suggest DOFS >0.5 as a minimum threshold for interpreting retrievals of trace gases with a weak tropospheric signal. We analyze one full year of satellite observations and find that GEOS-Chem, driven with MEGANv2.1 biogenic emissions, underestimates observed methanol concentrations throughout the midlatitudes in springtime, with the timing of the seasonal peak in model emissions 1-2 months too late. We attribute this discrepancy to an underestimate of emissions from new leaves in MEGAN, and apply the satellite data to better quantify the seasonal change in methanol emissions for midlatitude ecosystems. The derived parameters (relative emission factors of 11.0, 0.26, 0.12 and 3.0 for new, growing, mature, and old leaves, respectively, plus a leaf area index activity factor of 0.5 for expanding canopies with leaf area index <1.2) provide a more realistic simulation of seasonal methanol concentrations in midlatitudes on the basis of both the IASI and TES measurements.