Measurements Of Pollution In The Troposphere Research Articles

Discrepancy in assimilated atmospheric CO over East Asia in 2015–2020 by assimilating satellite and surface CO measurements

Abstract. Satellite and surface carbon monoxide (CO) observations have been widely used to investigate the sources and variabilities of atmospheric CO. However, comparative analyses to explore the effects of satellite and surface measurements on atmospheric CO assimilations are still lacking. Here we investigate the assimilated atmospheric CO over East Asia in 2015–2020, via assimilating CO measurements from the Measurement of Pollution in the Troposphere (MOPITT) instrument and Ministry of Ecology and Environment of China (MEE) monitoring network. We find noticeable inconsistencies in the assimilations: the adjusted CO columns (Xco) are about 162, 173 and 172 ppb by assimilating surface CO measurements, in contrast to 138–144, 149–155 and 144–151 ppb by assimilating MOPITT CO observations over East China, the North China Plain (NCP), and the Yangtze River Delta (YRD), respectively. These inconsistencies could be associated with possible representation errors due to differences between urban and regional CO backgrounds. Furthermore, the adjusted surface CO concentrations are about 631, 806, and 657 ppb by assimilating surface CO measurements, in contrast to 418–427, 627–639 and 500–509 ppb by assimilating MOPITT CO observations over East China, NCP, and YRD, respectively; assimilations of normalized surface CO measurements (to mitigate the influences of representation errors) indicate declines of CO columns by about 2.2, 2.1, and 1.8 ppb yr−1, in contrast to 0.63–0.86, 0.97–1.29, and 1.0–1.27 ppb yr−1 by assimilating MOPITT CO measurements over East China, South Korea, and Japan, respectively. These discrepancies reflect the different vertical sensitivities of satellite and surface observations in the lower and free troposphere. This work demonstrates the importance of integrating information from satellite and surface measurements to provide a more accurate evaluation of atmospheric CO changes.

The MOPITT Version 9 CO product: sampling enhancements and validation

Abstract. Characteristics of the Version 9 (V9) MOPITT (Measurements of Pollution in the Troposphere) satellite retrieval product for tropospheric carbon monoxide (CO) are described. The new V9 product includes many CO retrievals over land which, in previous MOPITT product versions, would have been discarded by the cloud detection algorithm. Globally, the number of daytime MOPITT retrievals over land has increased by 30 %–40 % relative to the Version 8 product, although the increase in retrieval coverage exhibits significant geographical variability. Areas benefiting from the improved cloud detection performance include (but are not limited to) source regions often characterized by high aerosol concentrations. The V9 MOPITT product also incorporates a modified calibration strategy for the MOPITT near-infrared (NIR) CO channels, resulting in greater temporal consistency for the NIR-only and thermal-infrared–near-infrared (TIR–NIR) retrieval variants. Validation results based on in situ CO profiles acquired from aircraft in a variety of contexts indicate that retrieval biases for V9 are typically within the range of ±5 % and are generally comparable to results for the V8 product.

Assessment of regional carbon monoxide simulations over Africa and insights into source attribution and regional transport

This study assesses the quality of carbon monoxide (CO) simulations from the Weather Research and Forecasting model coupled with Chemistry (WRF-Chem) and analyzes different processes controlling CO distribution in Africa. Sixteen CO tracers are implemented in WRF-Chem to track CO from different sources and regions. The model captures the seasonal cycles of surface temperature fairly well (r > 0.75 at most sites) and reproduces key features and variability of precipitation, wind speed, and planetary boundary layer height with errors typically seen in application of a regional model over such a large domain. The model also captures CO concentration hotspots and vertical gradients but underestimates the Measurements of Pollution in the Troposphere (MOPITT) retrieved total column with a larger underestimation in northern hemispheric Africa. The model also underestimates MOPITT and aircraft observed CO profiles throughout the troposphere. We discuss outdated anthropogenic emissions, low biomass burning emissions, and well-known low biases in global models of CO as potential contributors to the discrepancies between the regional model and MOPITT CO. Source contribution analysis of surface CO showed that all sources contribute to CO in Africa with anthropogenic emissions dominating in the urban regions, fire emissions dominating in central Africa, CO inflow from domain boundaries dominating in North Africa and the oceanic regions, and photochemical production dominance aligning with seasonal changes in sunlight. We also show that regional transport of CO emissions between African regions also play a very important role in controlling surface CO distribution in Africa. In some regions, more than 50% of the anthropogenic or biomass burning emitted CO comes from sources located outside those regions, highlighting the need for regional coordination and cooperation for air quality management in Africa.

Analysis of improvements in MOPITT observational coverage over Canada

Abstract. The Measurements of Pollution in the Troposphere (MOPITT) satellite instrument has been measuring global tropospheric carbon monoxide (CO) since March 2000, providing the longest nearly continuous record of CO from space. During its long mission, the data processing algorithms have been updated to improve the quality of CO retrievals and the sensitivity to the lower troposphere. Currently, MOPITT retrievals are only performed for clear-sky observations or over low clouds for ocean scenes. The cloud detection scheme was modified in the new V9 product, resulting in an improvement in observational coverage, especially over land. Comparison of the spatial and seasonal variations of the data coverage in V9 and V8 shows differences with significant geographical and temporal variability, with some regions such as Canada and the Amazon exhibiting a doubling of data in winter. Here we conducted an analysis of Moderate Resolution Imaging Spectroradiometer (MODIS) cloud heights and cloud mask products along with MOPITT retrieval cloud flag descriptors to understand the impact of cloud conditions on the MOPITT observational coverage, with a particular focus on observations over Canada. The MOPITT CO total column (TC) data were modified by turning off the cloud detection scheme to allow for a CO retrieval result, regardless of their cloud status. Analyses of the standard V8 CO TC product (cloud filtered) and non-standard product (non-cloud-masked) were conducted for selected days. Results showed some coherent structures that were observed frequently in the non-masked CO product that was not present in the V8 product and could potentially be actual CO features. Many times, these CO plumes were also seen in the Infrared Atmospheric Sounding Interferometer (IASI) CO TC product. The MODIS cloud height analysis revealed that a significant number of low-cloud CO retrievals were discarded in the V8 product. Most of the missed CO plumes in the V8 product are now detected in the new V9 product as a result of the dependence of the MOPITT radiance ratio (MRT) test over land. Comparisons of the MRT and MODIS cloud height data indicate a remarkable negative correlation. As a result of the modified V9 cloud detection algorithm, a significant portion of the low-cloud CO retrievals is now incorporated in the new V9 MOPITT product. Consequently, the observational coverage over Canada is significantly improved, which benefits analyses of regional CO variability, especially during extreme pollution events. We also conducted a comparison of MOPITT and IASI CO TC and found generally good agreement, with about a 5 %–10 % positive bias that is more pronounced in highly polluted scenes.

Diurnal, seasonal, and vertical distribution of carbon monoxide levels and their potential sources over a semi-arid region, India

The present study focuses on the investigation of both near-surface and vertical variability of carbon monoxide (CO) concentrations and their potential sources obtained from both in situ and satellite Measurements of Pollution in the Troposphere (MOPITT) over a semiarid region (Anantapur, India) from January 2016 to December 2017. The diurnal variation of CO shows sharp morning (07:00-09:00 LT) and evening (07:00-09:00 LT) peaks associated to local anthropogenic activities as well as the impact of the mixed layer height, and low concentrations during daytime (12:00-15:00 LT). The low levels during afternoon hours may be due to the increase of the mixed layer height and the decrease of anthropogenic sources. The seasonal mean CO showed no obvious variation, with highest levels observed in winter (329 ± 52 ppbv), followed by the pre-monsoon (327 ± 57 ppbv), post-monsoon (234 ± 36 ppbv) and monsoon (192 ± 22 ppbv). The high levels of CO during the winter are attributed to increased emissions from anthropogenic sources and a shallow mixed layer height. The vertical distribution of CO showed secondary peaks at high-pressure levels (300-200 hPa) during winter, pre-monsoon, and post-monsoon, which indicates CO transport from different source regions. These findings are reasonably confirmed through the air mass Concentrated Weighted Trajectory (CWT) analysis obtained from the Hybrid Single Particle Lagrangian Integrated Trajectory (HYSPLIT) model. This study suggests that except for the monsoon, air masses transported from Indo-Gangetic Basin region also contribute to the enhancement of CO concentrations at the receptor site

Spatial Analysis of the CO Emission from Nineveh Governorate Using Remote Sensing Techniques and GIS

Carbon Monoxide (CO) has a significant indirect effect on greenhouse gasses due to its ozone and carbon dioxide precursor, and its mechanism of degradation involving the hydroxyl radical (OH) which control the oxidizing ability of the tropospheric. To understand the effect of human activities on atmospheric composition, accurate estimates of the sources of atmospheric carbon monoxide (CO) are necessary. MOPITT (Measurements of Pollution in the Troposphere) is a NASA Terra satellite instrument designed to allow both Thermal-Infra-Red (TIR) and Near-Infra-Red (NIR) observations to be used to collect vertical CO profiles in the Troposphere via the concept of correlation spectroscopy. The objective of the current study is to analyze and map the monthly, seasonal and annual trend of CO concentration for year 2016 in Nineveh governorate using the retrieved CO Surface Mixing Ratio Day mode of level 3, version 7 dataset. The dataset was downloaded from the National Aeronautics and Space Administration (NASA) operated GIOVANNI portal. The results of dataset analysis in GIS software showed many sources of carbon monoxide in Nineveh Governorate, which change with months and seasons of the year. Generally, the observed CO concentration levels in the southern and western of the governorate were more than in the northern and eastern parts. The annually average CO ranges from (115.374 ppbv) to (132.452 ppbv). Also, CO emissions and concentrations were higher in winter (128.638-157.567 ppbv) than summer season (97.144-106.515 ppbv).

Evaluating Carbon Monoxide and Aerosol Optical Depth Simulations from CAM-Chem Using Satellite Observations

The scope of this work was to evaluate simulated carbon monoxide (CO) and aerosol optical depth (AOD) from the CAM-chem model against observed satellite data and additionally explore the empirical relationship of CO, AOD and fire radiative power (FRP). The simulated seasonal global concentrations of CO and AOD were compared, respectively, with the Measurements of Pollution in the Troposphere (MOPITT) and the Moderate-Resolution Imaging Spectroradiometer (MODIS) satellite products for the period 2010–2014. The CAM-chem simulations were performed with two configurations: (A) tropospheric-only; and (B) tropospheric with stratospheric chemistry. Our results show that the spatial and seasonal distributions of CO and AOD were reasonably reproduced in both model configurations, except over central China, central Africa and equatorial regions of the Atlantic and Western Pacific, where CO was overestimated by 10–50 ppb. In configuration B, the positive CO bias was significantly reduced due to the inclusion of dry deposition, which was not present in the model configuration A. There was greater CO loss due to the chemical reactions, and shorter lifetime of the species with stratospheric chemistry. In summary, the model has difficulty in capturing the exact location of the maxima of the seasonal AOD distributions in both configurations. The AOD was overestimated by 0.1 to 0.25 over desert regions of Africa, the Middle East and Asia in both configurations, but the positive bias was even higher in the version with added stratospheric chemistry. By contrast, the AOD was underestimated over regions associated with anthropogenic activity, such as eastern China and northern India. Concerning the correlations between CO, AOD and FRP, high CO is found during March–April–May (MAM) in the Northern Hemisphere, mainly in China. In the Southern Hemisphere, high CO, AOD, and FRP values were found during August–September–October (ASO) due to fires, mostly in South America and South Africa. In South America, high AOD levels were observed over subtropical Brazil, Paraguay and Bolivia. Sparsely urbanized regions showed higher correlations between CO and FRP (0.7–0.9), particularly in tropical areas, such as the western Amazon region. There was a high correlation between CO and aerosols from biomass burning at the transition between the forest and savanna environments over eastern and central Africa. It was also possible to observe the transport of these pollutants from the African continent to the Brazilian coast. High correlations between CO and AOD were found over southeastern Asian countries, and correlations between FRP and AOD (0.5–0.8) were found over higher latitude regions such as Canada and Siberia as well as in tropical areas. Higher correlations between CO and FRP are observed in Savanna and Tropical forests (South America, Central America, Africa, Australia, and Southeast Asia) than FRP x AOD. In contrast, boreal forests in Russia, particularly in Siberia, show a higher FRP x AOD correlation than FRP x CO. In tropical forests, CO production is likely favored over aerosol, while in temperate forests, aerosol production is more than CO compared to tropical forests. On the east coast of the United States, the eastern border of the USA with Canada, eastern China, on the border between China, Russia, and Mongolia, and the border between North India and China, there is a high correlation of CO x AOD and a low correlation between FRP with both CO and AOD. Therefore, such emissions in these regions are not generated by forest fires but by industries and vehicular emissions since these are densely populated regions.

Impacts of MOPITT cloud detection revisions on observation frequency and mapping of highly polluted scenes

Measurements made by the MOPITT (“Measurements of Pollution in the Troposphere”) instrument on the NASA Terra polar-orbiting platform enable the retrieval of tropospheric carbon monoxide (CO) concentrations. As determined by the Terra orbit and MOPITT swath width, the frequency of MOPITT observations at a specific location, or measurement sampling frequency, is typically about once every three to four days. However, because the MOPITT retrieval algorithm is only applicable to clear-sky scenes, MOPITT retrieval sampling frequency strongly depends on regional cloudiness and can be much smaller than the measurement sampling frequency. Moreover, highly polluted scenes, characterized by high aerosol optical depths, can be confused with cloudy scenes and thus be discarded unnecessarily by the MOPITT cloud detection algorithm. Herein are described revisions to this algorithm which substantially increase retrieval sampling over land in varying pollution conditions. The performance of the revised cloud detection algorithm is evaluated through validation, case studies, and continental-scale maps of retrieval sampling frequency. Presented case studies illustrate (1) why the current operational MOPITT cloud detection algorithm excludes extended areas of potentially valuable cloud-free MOPITT observations and (2) how, for the same scenes, improved retrieval coverage benefits analyses of regional CO variability. Maps of retrieval sampling frequency for South America and Asia exhibit well-defined improvements, especially in regions with poor sampling frequency in the current product.

Fate of Pollution Emitted During the 2015 Indonesian Fire Season

AbstractThe El Niño‐driven fire season in Indonesia in September–October 2015 produced the largest fire emissions on record since NASA's EOS satellites started making observations of tropospheric pollutants from space. In this study, measurements of carbon monoxide (CO) from the Measurement of Pollution in the Troposphere (MOPITT) on Terra and the Microwave Limb Sounder are used to characterize the anomalously high CO emitted during the 2015 Indonesian fire season transported into the tropical upper troposphere and stratosphere. The satellite measurements indicate that CO emitted from wildfires was transported into the upper troposphere with time lags up to ∼2 months and continued to be transported into the stratosphere, which resulted in higher concentrations of CO extending up to ∼20 hPa by the end of 2016. Hydrogen cyanide (HCN) measured by the Atmospheric Chemistry Experiment Fourier Transform Spectrometer (ACE‐FTS) confirms that anomalously high HCN emitted from the same wildfires was also transported into the tropical stratosphere and persisted throughout 2017. Simulations of CO from the Community Atmosphere Model with Chemistry (CAM‐chem) show a significant increase in CO concentrations in the troposphere in October 2015. However, comparisons between CAM‐chem and MOPITT CO suggest that the model underestimates the amount of CO even with doubled emissions of CO in October 2015. Both the satellite measurements and the model simulations show that the pollution emitted from the wildfires over Indonesia was transported to and persisted in the tropical stratosphere much longer than the previous El‐Niño driven fire events due to unprecedented amount of the fire emissions.

Regional and Urban Column CO Trends and Anomalies as Observed by MOPITT Over 16 Years

AbstractAtmospheric carbon monoxide (CO) concentrations have decreased since the beginning of the century, and the rate of decrease depends on the region. Depending on how regions are chosen, their boundaries may not always align with where there are differences in trends. To address this, we calculate trends within 0.4° × 0.4° grid cells independently throughout the globe using satellite CO retrievals from the Measurements Of Pollution In The Troposphere (MOPITT) satellite instrument from 2002 to 2017. These trends are found with the caveat that there are large singular biomass burning events somewhere nearly every year, and we include examples of large column CO anomalies during sporadic but large burning events in the North American and Eurasian boreal forests, the Amazon, Africa, and Indonesia. CO trends behave similarly within regions that span about a few thousand kilometers. Using TransCom region definitions, we find average trends between −0.9 and 0.1 ppb year−1 (about −0.9 to 0.1% year−1) for 2002–2017. Over 5‐year subsets, trends in TransCom regions vary between −3.6 and 1.8 ppb year−1. This substantial spatial and temporal variability in trends is in agreement with other studies. With an understanding of regional trends, we compare with trends from urban areas. Generally, CO trends within urban areas are indistinguishable from regional trends. This may be because of a combination of noise in the data, the large footprint for MOPITT, or because anthropogenic CO reduction measures were implemented before the MOPITT record began. We provide case studies for a few cities, such as Los Angeles, and find long‐term variation in the rate of change of column CO.

Air pollution trends measured from Terra: CO and AOD over industrial, fire-prone, and background regions

Following past studies to quantify decadal trends in global carbon monoxide (CO) using satellite observations, we update estimates and find a CO trend in column amounts of about −0.50 % per year between 2002 to 2018, which is a deceleration compared to analyses performed on shorter records that found −1 % per year. Aerosols are co-emitted with CO from both fires and anthropogenic sources but with a shorter lifetime than CO. A combined trend analysis of CO and aerosol optical depth (AOD) measurements from space helps to diagnose the drivers of regional differences in the CO trend. We use the long-term records of CO from the Measurements of Pollution in the Troposphere (MOPITT) and AOD from the Moderate Resolution Imaging Spectroradiometer (MODIS) instrument. Other satellite instruments measuring CO in the thermal infrared, AIRS, TES, IASI, and CrIS, show consistent hemispheric CO variability and corroborate results from the trend analysis performed with MOPITT CO. Trends are examined by hemisphere and in regions for 2002 to 2018, with uncertainties quantified. The CO and AOD records are split into two sub-periods (2002 to 2010 and 2010 to 2018) in order to assess trend changes over the 16 years. We focus on four major population centers: Northeast China, North India, Europe, and Eastern USA, as well as fire-prone regions in both hemispheres. In general, CO declines faster in the first half of the record compared to the second half, while AOD trends show more variability across regions. We find evidence of the atmospheric impact of air quality management policies. The large decline in CO found over Northeast China is initially associated with an improvement in combustion efficiency, with subsequent additional air quality improvements from 2010 onwards. Industrial regions with minimal emission control measures such as North India become more globally relevant as the global CO trend weakens. We also examine the CO trends in monthly percentile values to understand seasonal implications and find that local changes in biomass burning are sufficiently strong to counteract the global downward trend in atmospheric CO, particularly in late summer.

Measurement report: Long-term variations in carbon monoxide at a background station in China's Yangtze River Delta region

Abstract. This study analyzed the long-term variations in carbon monoxide (CO) mixing ratios from January 2006 to December 2017 at the Lin'an regional atmospheric background station (LAN; 30.3∘ N, 119.73∘ E, 138 m a.s.l.) in China's Yangtze River Delta (YRD) region. The CO mixing ratios were at their highest (0.69 ± 0.08 ppm) and lowest (0.54 ± 0.06 ppm) in winter and summer, respectively. The average daily variation in CO exhibited a double-peaked pattern, with peaks in the morning and evening and a valley in the afternoon. A significant downward trend of −11.3 ppb yr−1 of CO was observed from 2006 to 2017 at the LAN station, which was in accordance with the negative trends of the average CO mixing ratios and total column retrieved from the satellite data (Measurements of Pollution in the Troposphere, MOPITT) over the YRD region during the same period. The average annual CO mixing ratio at the LAN station in 2017 was 0.51 ± 0.04 ppm, which was significantly lower than that (0.71 ± 0.12 ppm) in 2006. The decrease in CO levels was largest in autumn (−15.7 ppb yr−1), followed by summer (−11.1 ppb yr−1), spring (−10.8 ppb yr−1), and winter (−9.7 ppb yr−1). Moreover, the CO levels under relatively polluted conditions (the annual 95th percentiles) declined even more rapidly (−22.4 ppb yr−1, r=-0.68, p<0.05) from 2006 (0.91 ppm) to 2017 (0.58 ppm), and the CO levels under clean conditions (the annual 5th percentiles) showed decreasing evidence but not statistically significant (r=-0.41, p=0.19) throughout the years. The long-term decline and short-term variations in the CO mixing ratios at the LAN station were mainly attributed to the implementation of the anthropogenic pollution control measures in the YRD region and to events like the Shanghai Expo in 2010 and Hangzhou G20 in 2016. The decreased CO level may influence atmospheric chemistry over the region. The average OH reactivity of CO at the LAN station is estimated to significantly drop from 4.1 ± 0.7 s−1 in 2006 to 3.0 ± 0.3 s−1 in 2017.

Correcting model biases of CO in East Asia: impact on oxidant distributions during KORUS-AQ

Global coupled chemistry-climate models underestimate carbon monoxide (CO) in the Northern Hemisphere, exhibiting a pervasive negative bias against measurements peaking in late winter and early spring. While this bias has been commonly attributed to underestimation of direct anthropogenic and biomass burning emissions, chemical production and loss via OH reaction from emissions of anthropogenic and biogenic volatile organic compounds (VOCs) play an important role. Here we investigate the reasons for this underestimation using aircraft measurements taken in May and June 2016 from the Korea-United States Air Quality (KORUS-AQ) experiment in South Korea and the Air Chemistry Research in Asia (ARIAs) in the North China Plain (NCP). For reference, multispectral CO retrievals (V8J) from the Measurements of Pollution in the Troposphere (MOPITT) are jointly assimilated with meteorological observations using an ensemble adjustment Kalman filter (EAKF) within the global Community Atmosphere Model with Chemistry (CAM-Chem) and the Data Assimilation Research Testbed (DART). With regard to KORUS-AQ data, CO is underestimated by 42% in the control run and by 12% with the MOPITT assimilation run. The inversion suggests an underestimation of anthropogenic CO sources in many regions, by up to 80% for northern China, with large increments over the Liaoning Province and the North China Plain (NCP). Yet, an often-overlooked aspect of these inversions is that correcting the underestimation in anthropogenic CO emissions also improves the comparison with observational O3 datasets and observationally constrained box model simulations of OH and HO2. Running a CAM-Chem simulation with the updated emissions of anthropogenic CO reduces the bias by 29% for CO, 18% for ozone, 11% for HO2, and 27% for OH. Longer-lived anthropogenic VOCs whose model errors are correlated with CO are also improved, while short-lived VOCs, including formaldehyde, are difficult to constrain solely by assimilating satellite retrievals of CO. During an anticyclonic episode, better simulation of O3, with an average underestimation of 5.5 ppbv, and a reduction in the bias of surface formaldehyde and oxygenated VOCs can be achieved by separately increasing by a factor of 2 the modeled biogenic emissions for the plant functional types found in Korea. Results also suggest that controlling VOC and CO emissions, in addition to widespread NO x controls, can improve ozone pollution over East Asia.

1.5 years of TROPOMI CO measurements: comparisons to MOPITT and ATom

Abstract. We have analyzed TROPOspheric Monitoring Instrument (TROPOMI) carbon monoxide (CO) data acquired between November 2017 and March 2019 with respect to other satellite (MOPITT, Measurement Of Pollution In The Troposphere) and airborne (ATom, Atmospheric Tomography mission) datasets to better understand TROPOMI's contribution to the global tropospheric CO record (2000 to present). MOPITT and TROPOMI are two of only a few satellite instruments to ever derive CO from solar-reflected radiances. Therefore, it is particularly important to understand how these two datasets compare. Our results indicate that TROPOMI CO retrievals over land show excellent agreement with respect to MOPITT: relative biases and their SD (i.e., accuracy and precision) are on average -3.73%±11.51%, -2.24%±12.38%, and -3.22%±11.13% compared to the MOPITT TIR (thermal infrared), NIR (near infrared), and TIR + NIR (multispectral) products, respectively. TROPOMI and MOPITT data also show good agreement in terms of temporal and spatial patterns. Despite depending on solar-reflected radiances for its measurements, TROPOMI can also retrieve CO over bodies of water if clouds are present by approximating partial columns under cloud tops using scaled, model-based reference CO profiles. We quantify the bias of TROPOMI total column retrievals over bodies of water with respect to colocated in situ ATom CO profiles after smoothing the latter with the TROPOMI column averaging kernels (AKs), which account for signal attenuation under clouds (relative bias and its SD =3.25%±11.46 %). In addition, we quantify enull (the null-space error), which accounts for differences between the shape of the TROPOMI reference profile and that of the ATom true profile (enull=2.16%±2.23 %). For comparisons of TROPOMI and MOPITT retrievals over open water we compare TROPOMI total CO columns to their colocated MOPITT TIR counterparts. Relative bias and its SD are 2.98 %±15.71 % on average. We investigate the impact of discrepancies between the a priori and reference CO profiles (used by MOPITT and TROPOMI, respectively) on CO retrieval biases by applying a null-space adjustment (based on the MOPITT a priori) to the TROPOMI total column values. The effect of this adjustment on MOPITT and TROPOMI biases is minor, typically 1–2 percentage points.

Satellite measurements of aerosol optical depth and carbon monoxide and comparison with ground data.

Satellite data of aerosol optical depths (AODs) from the moderate resolution imaging spectroradiometer (MODIS) and carbon monoxide (CO) columns from the measurements of pollution in the troposphere (MOPITT) were collected for the study in Northern Thailand. Comparative analyses were conducted of MODIS (Terra and Aqua) AODs with ground particulate matter with diameter below 10 microns (PM10) concentrations and MOPITT CO surface/total columns with ground CO concentrations for 2014-2017. Temporal variations in both the satellite and ground datasets were in good agreement. High levels of air pollutants were common during March-April. The annual analysis of both satellite and ground datasets revealed the highest levels of air pollutants in 2016 and the lowest levels in 2017. The AODs and PM10 concentrations were at higher levels in the morning than in the afternoon. The comparison between satellite products showed that AODs correlated better with the CO total columns than the CO surface columns. The regression analysis presented better performance of Aqua AODs-PM10 than Terra AODs-PM10 with correlation coefficients (r) of 0.72-0.83 and 0.57-0.79, respectively. Ground CO concentrations correlated better with MOPITT CO surface columns (r = 0.65-0.73) than with CO total columns (r = 0.56-0.72). The r values of satellite and ground datasets were greatest when the analysis was restricted to November-March (dry weather periods with possible low mixing height (MH)). Overall, the results suggested that the relationships between satellite and ground data can be used to develop predictive models for ground PM10 and CO in northern Thailand, particularly during air pollution episodes located where ground monitoring stations are limited.

O3 and CO in the South Asian outflow over the Bay of Bengal: Impact of monsoonal dynamics and chemistry

Abstract Monsoonal dynamics strongly impacts the composition over the South Asian region, however, in situ measurements remain limited mostly to the continental region. Whereas, remote oceanic regions of the Bay of Bengal (BoB) remain largely unexplored where shipping emissions can infuse into the South Asian outflow. In this direction, we performed ship-based measurements of ozone (O3) and carbon monoxide (CO) over the BoB during July‒August 2018 and corroborated the analyses with model results and satellite retrievals. Surface level mixing ratios of O3 and CO varied in the range of 14–45 and 50–164 ppbv, respectively during the expedition. Elevated O3 and CO levels were observed in coastal region downwind of a tropical megacity (Chennai), referred to as the Chennai-plume. Analysis of the Copernicus Atmosphere Monitoring Service (CAMS) model simulations suggests volatile organic compound (VOC)-limited O3 production in morning over most of the plume and east coast followed by gradual shift to NOx-limited regime over the BoB in afternoon. While the southern BoB (7–10° N) received generally pristine airmasses from the equatorial Indian Ocean, impacts of shipping emissions near 6° N are observed. Consequently, higher values of CO (as much as 120 ppbv) and net O3 production by 1.1–1.3 ppbv h−1 with a diurnal amplitude of 4–8 ppbv are observed over the southern BoB. Satellite-based observations from the Measurements of Pollution in the Troposphere (MOPITT) and results from CAMS model show decreasing trend (4.1–5.2 ± 1 ppbv decade−1) of surface CO, as also inferred from in situ measurements. Zonal fluxes of CO across the east coast show the outflow over the BoB with higher values (2–3 × 1019 molecules m−2 s−1) over the northern BoB. Positive vertical fluxes (~2 × 1016 molecules m−2 s−1) show the transport of CO from marine boundary layer to the free-troposphere. Due to strong updrafts, CO levels in upper and lower troposphere are seen to be comparable during monsoon. These findings in conjunction with higher methane and nitrogen dioxide in the upper-troposphere manifest the influences of monsoonal convection and trapping of trace gases in the anticyclone.

Tropospheric carbon monoxide over the northern Indian Ocean during winter: influence of inter-continental transport

South Asian outflow over the adjoining marine regions is most pronounced during winter season, whereas the prevalence of strong winds aloft can transport the influences from inter-continental sources. Here, we investigate the tropospheric carbon monoxide (CO) distribution over the northern Indian Ocean (IO) combining shipborne measurements carried out during the Integrated Campaign for Aerosols, gases, and Radiation Budget (ICARB) campaign (January–February 2018), retrievals from Measurements of Pollution in the Troposphere (MOPITT), and Copernicus Atmosphere Monitoring Service (CAMS) model. Surface CO varied from ~ 50 to 365 ppbv (179 ± 67 ppbv) with higher levels over the coastal region of southeast Arabian Sea and lower levels over the equatorial IO. We observed lower CO levels (200 ± 43 ppbv) than those during the Indian Ocean Experiment-1999 (229 ± 40 ppbv) supporting the reported decreasing trend of tropospheric CO. In situ CO observations are found to be in a good agreement with the satellite retrievals (MOPITT-version 8) as well as the CAMS model results (r2 = 0.60‒0.65). The upper-tropospheric CO (300‒200 hPa) over the equatorial IO is observed to be higher by up to 30% during February-2018 as compared to the decadal mean, coinciding with anomalous westerlies resulting from a disturbed Walker cell over the equatorial IO and deeper penetration of the sub-tropical jet. The influences of African forest fires are suggested to have enhanced the upper-tropospheric CO over the IO during February-2018. Our study highlights the importance of strong large-scale dynamics and global biomass-burning emissions in the wintertime pollution loading over the IO, besides the South Asian outflow.

Assessing Measurements of Pollution in the Troposphere (MOPITT) carbon monoxide retrievals over urban versus non-urban regions

Abstract. The Measurements of Pollution in the Troposphere (MOPITT) retrievals over urban regions have not been validated systematically, even though MOPITT observations are widely used to study CO over urban regions. Here we compare MOPITT products over urban and non-urban regions with aircraft measurements from the Deriving Information on Surface conditions from Column and Vertically Resolved Observations Relevant to Air Quality (DISCOVER-AQ – 2011–2014), Studies of Emissions and Atmospheric Composition, Clouds, and Climate Coupling by Regional Surveys (SEAC4RS – 2013), Air Chemistry Research In Asia (ARIAs – 2016), A-FORCE (2009, 2013), and Korea United States Air Quality (KORUS-AQ – 2016) campaigns. In general, MOPITT agrees reasonably well with the in situ profiles, over both urban and non-urban regions. Version 8 multispectral product (V8J) biases vary from −0.7 % to 0.0 % and version 8 thermal-infrared product (TIR) biases vary from 2.0 % to 3.5 %. The evaluation statistics of MOPITT V8J and V8T over non-urban regions are better than those over urban regions with smaller biases and higher correlation coefficients. We find that the agreement of MOPITT V8J and V8T with aircraft measurements at high CO concentrations is not as good as that at low CO concentrations, although CO variability may tend to exaggerate retrieval biases in heavily polluted scenes. We test the sensitivities of the agreements between MOPITT and in situ profiles to assumptions and data filters applied during the comparisons of MOPITT retrievals and in situ profiles. The results at the surface layer are insensitive to the model-based profile extension (required due to aircraft altitude limitations), whereas the results at levels with limited aircraft observations (e.g., the 600 hPa layer) are more sensitive to the model-based profile extension. The results are insensitive to the maximum allowed time difference criterion for co-location (12, 6, 3, and 1 h) and are generally insensitive to the radius for co-location, except for the case where the radius is small (25 km), and hence few MOPITT retrievals are included in the comparison. Daytime MOPITT products have smaller overall biases than nighttime MOPITT products when comparing both MOPITT daytime and nighttime retrievals to the daytime aircraft observations. However, it would be premature to draw conclusions on the performance of MOPITT nighttime retrievals without nighttime aircraft observations. Applying signal-to-noise ratio (SNR) filters does not necessarily improve the overall agreement between MOPITT retrievals and in situ profiles, likely due to the reduced number of MOPITT retrievals for comparison. Comparisons of MOPITT retrievals and in situ profiles over complex urban or polluted regimes are inherently challenging due to spatial and temporal variabilities of CO within MOPITT retrieval pixels (i.e., footprints). We demonstrate that some of the errors are due to CO representativeness with these sensitivity tests, but further quantification of representativeness errors due to CO variability within the MOPITT footprint will require future work.

Satellite-Observed Variations and Trends in Carbon Monoxide over Asia and Their Sensitivities to Biomass Burning

As the carbon monoxide (CO) total column over Asia is among the highest in the world, it is important to characterize its variations in space and time. Using Measurements of Pollution in the Troposphere (MOPITT) and Atmospheric InfraRed Sounder (AIRS) satellite data, the variations and trends in CO total column over Asia and its seven subregions during 2003–2017 are investigated in this study. The CO total column in Asia is higher in spring and winter than in summer and autumn. The seasonal maximum and minimum are in spring and summer respectively in the regional mean over Asia, varying between land and oceans, as well as among the subregions. The CO total column in Asia shows strong interannual variation, with a regional mean coefficient of variation of 5.8% in MOPITT data. From 2003 to 2017, the annual mean of CO total column over Asia decreased significantly at a rate of (0.58 ± 0.15)% per year (or −(0.11 ± 0.03) × 1017 molecules cm−2 per year) in MOPITT data, resulting from significant CO decreases in winter, summer, and spring. In most of the subregions, significant decreasing trends in CO total column are also observed, more obviously over areas with high CO total column, including eastern regions of China and the Sichuan Basin. The regional decreasing trends in these areas are over 1% per year. Over the entire Asia, and in fire-prone subregions including South Siberia, Indo-China Peninsula, and Indonesia, we found significant correlations between the MOPITT CO total column and the fire counts from the Moderate Resolution Imaging Spectroradiometer (MODIS). The variations in MODIS fire counts may explain 58%, 60%, 36%, and 71% of the interannual variation in CO total column in Asia and these three subregions, respectively. Over different land cover types, the variations in biomass burning may explain 62%, 52%, and 31% of the interannual variation in CO total column, respectively, over the forest, grassland, and shrubland in Asia. Extremes in CO total column in Asia can be largely explained by the extreme fire events, such as the fires over Siberia in 2003 and 2012 and over Indonesia in 2006 and 2015. The significant decreasing trends in MODIS fire counts inside and outside Asia suggest that global biomass burning may be a driver for the decreasing trend in CO total column in Asia, especially in spring. In general, the variations and trends in CO total column over Asia detected by AIRS are similar to but smaller than those by MOPITT. The two datasets show similar spatial and temporal variations in CO total column over Asia, with correlation coefficients of 0.86–0.98 in the annual means. This study shows that the interannual variation in atmospheric CO in Asia is sensitive to biomass burning, while the decreasing trend in atmospheric CO over Asia coincides with the decreasing trend in MODIS fire counts from 2003 to 2017.

Analysis of the atmospheric dust in Africa: The breathable dust's fine particulate matter PM2.5 in correlation with carbon monoxide

The dust has direct effects on people's health and climate change; so, this research studied the remotely sensed dust deposition in Africa from 1980 to 2018, and the dust's particulate matter of 2.5 μm size (or PM2.5), in particular, which pollutes the breathable air. PM2.5 is studied in comparison with multispectral carbon monoxide (CO), an abundant atmospheric air pollutant in central Africa. CO is an atmospheric gaseous pollutant for which the smoke, a gaseous aerosol from incomplete combustion processes, is the biggest source. The literature clarifies that both the particulate matter and the CO endanger human health while breathed in. The dust from the desert of Sahara is windblown all over the world. CO, in Africa, is from the anthropogenic fire and volcanic eruptions' smoke; these are two good reasons to have focused on Africa. Due to the big size of Africa, five sub-regions are set; these are the western, central, northern, eastern and southern sub-regions. The Goddard interactive online visualization and analysis infrastructure (GIOVANNI) has been a bridge to the collected remote sensing data, in this research. The data was collected online, from the measurement of pollution in the troposphere (MOPITT) as well as a second version of the modern era retrospective analysis for research and applications (MERRA-2); the analysis was done by a joint of the software tools, worth noting is the Arc GIS. As the amount of African dust dramatically increased by 2000; the heaviest in 2004, results are based on the selected dust deposition over 2000–2018: time-averaged maps, correlations, and quantitative estimations are reported in this research. The heaviest annual dust deposition reached 25.3 t/km2 over the year 2004, in Liberia, a focal point of study for the western sub-region. An important finding: the dust's PM2.5 positively correlated with multispectral CO from November to May; the positively high correlation coefficient was 0.86 in April 2018. The negative correlation between the two measurements started from June to October; the negatively high correlation was −0.68 in October 2015; this research discussed the possible reasons. This research recommends some onsite studies about the real figures and facts about the dust's effects on health, in all the seasons; thus, an alert to policymakers who would set some strategies to mitigate the dust hazards on the health of African inhabitants, neighbors, and visitors.