HCOOH measurements from space: TES retrieval algorithm and observed global distribution

Presented is a detailed description of the TES (Tropospheric Emission Spectrometer)-Aura satellite formic acid (HCOOH) retrieval algorithm and initial results quantifying the global distribution of tropospheric HCOOH. The retrieval strategy, including the optimal estimation methodology, spectral microwindows, a priori constraints, and initial guess information, are provided. A comprehensive error and sensitivity analysis is performed in order to characterize the retrieval performance, degrees of freedom for signal, vertical resolution, and limits of detection. These results show that the TES HCOOH retrievals (i) typically provide at best 1.0 pieces of information; (ii) have the most vertical sensitivity in the range from 900 to 600 hPa with ~ 2 km vertical resolution; (iii) require at least 0.5 ppbv (parts per billion by volume) of HCOOH for detection if thermal contrast is greater than 5 K, and higher concentrations as thermal contrast decreases; and (iv) based on an ensemble of simulated retrievals, are unbiased with a standard deviation of ±0.4 ppbv. The relative spatial distribution of tropospheric HCOOH derived from TES and its associated seasonality are broadly correlated with predictions from a state-of-the-science chemical transport model (GEOS-Chem CTM). However, TES HCOOH is generally higher than is predicted by GEOS-Chem, and this is in agreement with recent work pointing to a large missing source of atmospheric HCOOH. The model bias is especially pronounced in summertime and over biomass burning regions, implicating biogenic emissions and fires as key sources of the missing atmospheric HCOOH in the model

Source influence on emission pathways and ambient PM2.5 pollution over India (2015–2050)

India currently experiences degraded air quality, with future economic development leading to challenges for air quality management. Scenarios of sectoral emissions of fine particulate matter and its precursors were developed and evaluated for 2015–2050, under specific pathways of diffusion of cleaner and more energy efficiency technologies. The impacts of individual source-sectors on PM2.5 concentrations were assessed through GEOS-Chem model simulations of spatially and temporally resolved particulate matter concentrations, followed by population-weighted aggregation to national and state levels. PM2.5 pollution is a pan-India problem, with a regional character, not limited to urban areas or megacities. Under present-day emissions, levels in most states exceeded the national PM2.5 standard (40 µg/m3). Future evolution of emissions under current regulation or under promulgated or proposed regulation, yield deterioration in future air-quality in 2030 and 2050. Only under a scenario where more ambitious measures are introduced, promoting a total shift away from traditional biomass technologies and a very large shift (80–85 %) to non-fossil electricity generation was an overall reduction in PM2.5 concentrations below 2015 levels achieved. In this scenario, concentrations in 20 states and six union territories would fall below the national standard. However, even under this ambitious scenario, 10 states (including Delhi) would fail to comply with the national standard through to 2050. Under present day (2015) emissions, residential biomass fuel use for cooking and heating is the largest single sector influencing outdoor air pollution across most of India. Agricultural residue burning is the next most important source, especially in north-west and north India, while in eastern and peninsular India, coal burning in thermal power plants and industry are important contributors. The relative influence of anthropogenic dust and total dust is projected to increase in all future scenarios, largely from decreases in the influence of other PM2.5 sources. Overall, the findings suggest a large regional background of PM2.5 pollution (from residential biomass, agricultural residue burning and power plant and industrial coal), underlying that from local sources (transportation, brick kiln, distributed diesel) in highly polluted areas

Photo-tautomerization of acetaldehyde as a photochemical source of formic acid in the troposphere

Organic acids play a key role in the troposphere, contributing to atmospheric aqueous-phase chemistry, aerosol formation, and precipitation acidity. Atmospheric models currently account for less than half the observed, globally averaged formic acid loading. Here we report that acetaldehyde photo-tautomerizes to vinyl alcohol under atmospherically relevant pressures of nitrogen, in the actinic wavelength range, λ = 300–330 nm, with measured quantum yields of 2–25%. Recent theoretical kinetics studies show hydroxyl-initiated oxidation of vinyl alcohol produces formic acid. Adding these pathways to an atmospheric chemistry box model (Master Chemical Mechanism) demonstrates increased formic acid concentrations by a factor of ~1.7 in the polluted troposphere and a factor of ~3 under pristine conditions. Incorporating this mechanism into the GEOS-Chem 3D global chemical transport model reveals an estimated 7% contribution to worldwide formic acid production, with up to 60% of the total modeled formic acid production over oceans arising from photo-tautomerization

Aerosol Optical Depth Over India

Tropospheric aerosol optical depth (AOD) over India was simulated by Goddard Earth Observing System (GEOS)-Chem, a global 3-D chemical-transport model, using SMOG (Speciated Multi-pOllutant Generator from Indian Institute of Technology Bombay) and GEOS-Chem (GC) (current inventories used in the GEOS-Chem model) inventories for 2012. The simulated AODs were similar to 80% (SMOG) and 60% (GC) of those measured by the satellites (Moderate Resolution Imaging Spectroradiometer and Multi-angle Imaging SpectroRadiometer). There is no strong seasonal variation in AOD over India. The peak AOD values are observed/simulated during summer. The simulated AOD using SMOG inventory has particulate black and organic carbon AOD higher by a factor similar to 5 and 3, respectively, compared to GC inventory. The model underpredicted coarse-mode AOD but agreed for fine-mode AOD with Aerosol Robotic Network data. It captured dust only over Western India, which is a desert, and not elsewhere, probably due to inaccurate dust transport and/or noninclusion of other dust sources. The calculated AOD, after dust correction, showed the general features in its observed spatial variation. Highest AOD values were observed over the Indo-Gangetic Plain followed by Central and Southern India with lowest values in Northern India. Transport of aerosols from Indo-Gangetic Plain and Central India into Eastern India, where emissions are low, is significant. The major contributors to total AOD over India are inorganic aerosol (41-64%), organic carbon (14-26%), and dust (7-32%). AOD over most regions of India is a factor of 5 or higher than over the United States. Plain Language Summary Overhead amounts of particulate matter, their chemical make up, and their variations over India, a highly polluted and fast developing country, were calculated using a global model. It shows that the particulate pollution levels over the Indo-Gangetic Plain is more than 5 times higher than over the United States. The use of the most recent available emission inventory shows that there is more black carbon, from incomplete combustion, than estimated using the existing regional inventory. The calculations also show that the cleanest part is the very Northern India and that pollution over Eastern India is significantly influenced by what happens over the Indo-Gangetic Plain

HCOOH measurements from space: TES retrieval algorithm and observed global distribution

Ces trois livres ont en commun de participer à l’émergence d’un intérêt dans la photographie couleur qui n’existait guère dans l’histoire de la photographie il y a une dizaine d’années. On exhume des archives datant d’une époque où l’image couleur – autochromes, diapositives ou procédés plus exotiques– était rare. Le public découvre à cette occasion un « monde » qu’il ne connaissait qu’à travers sa traduction en noir et blanc. On pense à la Seconde Guerre mondiale, voire à la Première, et, bi..

A Large Underestimate of Formic Acid from Tropical Fires: Constraints from Space-Borne Measurements

Formic acid (HCOOH) is one of the most abundant carboxylic acids and a dominant source of atmospheric acidity. Recent work indicates a major gap in the HCOOH budget, with atmospheric concentrations much larger than expected from known sources. Here, we employ recent space-based observations from the Tropospheric Emission Spectrometer with the GEOS-Chem atmospheric model to better quantify the HCOOH source from biomass burning, and assess whether fire emissions can help close the large budget gap for this species. The space-based data reveal a severe model HCOOH underestimate most prominent over tropical burning regions, suggesting a major missing source of organic acids from fires. We develop an approach for inferring the fractional fire contribution to ambient HCOOH and find, based on measurements over Africa, that pyrogenic HCOOH:CO enhancement ratios are much higher than expected from direct emissions alone, revealing substantial secondary organic acid production in fire plumes. Current models strongly underestimate (by 10 ± 5 times) the total primary and secondary HCOOH source from African fires. If a 10-fold bias were to extend to fires in other regions, biomass burning could produce 14 Tg/a of HCOOH in the tropics or 16 Tg/a worldwide. However, even such an increase would only represent 15–20% of the total required HCOOH source, implying the existence of other larger missing sources

Source influence on emission pathways and ambient PM_2.5 pollution over India (2015–2050)

India is currently experiencing degraded air quality, and future economic development will lead to challenges for air quality management. Scenarios of sectoral emissions of fine particulate matter and its precursors were developed and evaluated for 2015–2050, under specific pathways of diffusion of cleaner and more energy-efficient technologies. The impacts of individual source sectors on PM2.5 concentrations were assessed through systematic simulations of spatially and temporally resolved particulate matter concentrations, using the GEOS-Chem model, followed by population-weighted aggregation to national and state levels. We find that PM2.5 pollution is a pan-India problem, with a regional character, and is not limited to urban areas or megacities. Under present-day emissions, levels in most states exceeded the national PM2.5 annual standard (40 µg m−3). Sources related to human activities were responsible for the largest proportion of the present-day population exposure to PM2.5 in India. About 60 % of India's mean population-weighted PM2.5 concentrations come from anthropogenic source sectors, while the remainder are from other sources, windblown dust and extra-regional sources. Leading contributors are residential biomass combustion, power plant and industrial coal combustion and anthropogenic dust (including coal fly ash, fugitive road dust and waste burning). Transportation, brick production and distributed diesel were other contributors to PM2.5. Future evolution of emissions under regulations set at current levels and promulgated levels caused further deterioration of air quality in 2030 and 2050. Under an ambitious prospective policy scenario, promoting very large shifts away from traditional biomass technologies and coal-based electricity generation, significant reductions in PM2.5 levels are achievable in 2030 and 2050. Effective mitigation of future air pollution in India requires adoption of aggressive prospective regulation, currently not formulated, for a three-pronged switch away from (i) biomass-fuelled traditional technologies, (ii) industrial coal-burning and (iii) open burning of agricultural residue. Future air pollution is dominated by industrial process emissions, reflecting larger expansion in industrial, rather than residential energy demand. However, even under the most active reductions envisioned, the 2050 mean exposure, excluding any impact from windblown mineral dust, is estimated to be nearly 3 times higher than the WHO Air Quality Guideline

Simulation of atmospheric N₂O with GEOS-Chem and its adjoint:Evaluation of observational constraints

We describe a new 4D-Var inversion framework for nitrous oxide (N2O) based on the GEOS-Chem chemical transport model and its adjoint, and apply it in a series of observing system simulation experiments to assess how well N2O sources and sinks can be constrained by the current global observing network. The employed measurement ensemble includes approximately weekly and quasicontinuous N2O measurements (hourly averages used) from several long-term monitoring networks, N2O measurements collected from discrete air samples onboard a commercial aircraft (Civil Aircraft for the Regular Investigation of the atmosphere Based on an Instrument Container; CARIBIC), and quasi-continuous measurements from the airborne HIAPER Pole-to-Pole Observations (HIPPO) campaigns. For a 2-year inversion, we find that the surface and HIPPO observations can accurately resolve a uniform bias in emissions during the first year; CARIBIC data provide a somewhat weaker constraint. Variable emission errors are much more difficult to resolve given the long lifetime of N2O, and major parts of the world lack significant constraints on the seasonal cycle of fluxes. Current observations can largely correct a global bias in the stratospheric sink of N2O if emissions are known, but do not provide information on the temporal and spatial distribution of the sink. However, for the more realistic scenario where source and sink are both uncertain, we find that simultaneously optimizing both would require unrealistically small errors in model transport. Regardless, a bias in the magnitude of the N2O sink would not affect the a posteriori N2O emissions for the 2-year timescale used here, given realistic initial conditions, due to the timescale required for stratosphere-troposphere exchange (STE). The same does not apply to model errors in the rate of STE itself, which we show exerts a larger influence on the tropospheric burden of N2O than does the chemical loss rate over short (< 3 year) timescales. We use a stochastic estimate of the inverse Hessian for the inversion to evaluate the spatial resolution of emission constraints provided by the observations, and find that significant, spatially explicit constraints can be achieved in locations near and immediately upwind of surface measurements and the HIPPO flight tracks; however, these are mostly confined to North America, Europe, and Australia. None of the current observing networks are able to provide significant spatial information on tropical N2O emissions. There, averaging kernels (describing the sensitivity of the inversion to emissions in each grid square) are highly smeared spatially and extend even to the midlatitudes, so that tropical emissions risk being conflated with those elsewhere. For global inversions, therefore, the current lack of constraints on the tropics also places an important limit on our ability to understand extratropical emissions. Based on the error reduction statistics from the inverse Hessian, we characterize the atmospheric distribution of unconstrained N2O, and identify regions in and downwind of South America, central Africa, and Southeast Asia where new surface or profile measurements would have the most value for reducing present uncertainty in the global N2O budget

Evaluation of the MindOut Programme in Youthreach Centres

This report describes the evaluation of the MindOut programme that was implemented in Youthreach Centres in the HSE West (Galway, Mayo and Roscommon). The MindOut programme was originally developed as a resource to promote mental health in Irish secondary schools. Since then it has been adapted to suit the out-of-school setting. The programme aims to provide an opportunity for trainees in Youthreach Centres to develop an awareness of mental health issues and to acquire skills in relation to dealing with stress, emotions, relationships and being a support to others

Tropospheric Emission Spectrometer (TES) satellite observations of ammonia, methanol, formic acid, and carbon monoxide over the Canadian oil sands: Validation and model evaluation

The wealth of air quality information provided by satellite infrared observations of ammonia (NH3), carbon monoxide (CO), formic acid (HCOOH), and methanol (CH3OH) is currently being explored and used for a number of applications, especially at regional or global scales. These applications include air quality monitoring, trend analysis, emissions, and model evaluation. This study provides one of the first direct validations of Tropospheric Emission Spectrometer (TES) satellite-retrieved profiles of NH3, CH3OH, and HCOOH through comparisons with coincident aircraft profiles. The comparisons are performed over the Canadian oil sands region during the intensive field campaign (August-September, 2013) in support of the Joint Canada-Alberta Implementation Plan for Oil Sands Monitoring (JOSM). The satellite/aircraft comparisons over this region during this period produced errors of (i) +0.08 \ub1 0.25 ppbv for NH3, (ii) +7.5 \ub1 23 ppbv for CO, (iii) +0.19 \ub1 0.46 ppbv for HCOOH, and (iv) -1.1 \ub1 0.39 ppbv for CH3OH. These values mostly agree with previously estimated retrieval errors; however, the relatively large negative bias in CH3OH and the significantly greater positive bias for larger HCOOH and CO values observed during this study warrant further investigation. Satellite and aircraft ammonia observations during the field campaign are also used in an initial effort to perform preliminary evaluations of Environment Canada's Global Environmental Multi-scale - Modelling Air quality and CHemistry (GEM-MACH) air quality modelling system at high resolution (2.5 7 2.5 km2). These initial results indicate a model underprediction of 3c 0.6 ppbv ( 3c 60 %) for NH3, during the field campaign period. The TES/model CO comparison differences are 3c +20 ppbv ( 3c +20 %), but given that under these conditions the TES/aircraft comparisons also show a small positive TES CO bias indicates that the overall model underprediction of CO is closer to 3c 10 % at 681 hPa ( 3c 3 km) during this period.Peer reviewed: YesNRC publication: Ye