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In September 2020, the Western United States experienced anomalously severe wildfires that resulted in carbon monoxide (CO) emissions almost three times the 2001–2019 average. In this study, we investigate the influence of wildfires on atmospheric carbon monoxide (CO) variability through a comparative analysis of observations from the Measurements of Pollution in the Troposphere (MOPITT), the Infrared Atmospheric Sounding Interferometer (IASI), and the Tropospheric Monitoring Instrument (TROPOMI). Our focus is on the North American domain, aiming to understand the differences among these products. In general, all instruments show excellent agreement under typical atmospheric CO conditions. However, notable discrepancies were observed in the CO data from the three sensors, particularly in regions with elevated CO total column (TC) values. IASI and TROPOMI consistently showed higher CO values over the western U.S. compared to MOPITT. During the fire episodes, we found that the IASI retrievals suggested higher CO abundances near the surface than the MOPITT thermal infrared retrievals that are probably the result of the differences in the covariance matrices used in IASI and MOPITT retrievals. We also found that the high IASI and TROPOMI CO observations over the western U.S. coincided with high values of the TROPOMI aerosol index (AI), suggesting the presence of absorbing aerosols. The analysis exhibited better agreement between TROPOMI and MOPITT CO TC when the AI values were low. Our results suggest that appropriate quality filtering should be employed when analyzing pollution events with these data. In particular, utilizing the AI for quality filtering may be useful when analyzing extreme pollution events with these satellite products. Plain Language Summary: In September 2020, wildfires in the Western U.S. caused large smoke plumes that spread across the continent, significantly increasing atmospheric carbon monoxide (CO) levels. Using data from the MOPITT, IASI, and TROPOMI satellite sensors, this study found strong CO enhancements from the fires. The sensors showed good agreement under moderate CO conditions but diverged in areas of high CO and heavy aerosol loads, suggesting aerosol interference in CO retrievals. TROPOMI's UV Aerosol Index (AI) and CALIPSO data were used to evaluate aerosol impacts, emphasizing the need for quality filtering when analyzing CO during intense pollution events. Key Points: All the three CO satellite instruments (Measurements of Pollution in the Troposphere, Infrared Atmospheric Sounding Interferometer (IASI), and Tropospheric Monitoring Instrument (TROPOMI)) show excellent agreement under typical atmospheric CO conditionsThe CO data from the three sensors indicated large discrepancies in regionsThe very high IASI and TROPOMI CO observations over the PNW coincide with the high TROPOMI aerosol index values [ABSTRACT FROM AUTHOR]

Satellite retrievals of carbon monoxide (CO) are routinely assimilated in atmospheric chemistry models to improve air quality forecasts, produce reanalyzes and to estimate emissions. This study applies the quantile‐conserving ensemble filter framework, a novel assimilation algorithm that can deal with non‐Gaussian and modestly nonlinear distributions. Instead of assuming normal distributions like the Ensemble Adjustments Kalman Filter (EAKF), we now apply a bounded normal rank histogram (BNRH) distribution for the prior. The goal is to efficiently estimate bounded quantities such as CO atmospheric mixing ratios and emission fluxes while maintaining the good performance achieved by the EAKF. We contrast assimilating meteorological and MOPITT (Measurement of Pollution in the Troposphere) observations for May 2018. We evaluate the results with the fourth deployment of the NASA Atmospheric Tomography Mission (ATom‐4) airborne field campaign. We also compare simulations with CO tropospheric columns from the network for the detection of atmospheric composition change and surface in‐situ observations from NOAA carbon cycle greenhouse gases. While the differences remain small, the BNRH approach clearly works better than the EAKF in comparison to all observation data sets. Plain Language Summary: The MOPITT instrument on the NASA/Terra satellite can detect carbon monoxide (CO) pollution in the lower and mid‐tropospheric atmosphere but cannot accurately differentiate small changes in the altitude of pollution plumes. Such satellite observations are assimilated in numerical model predictions to improve the spatial and temporal distribution of CO in the atmosphere and to estimate emission fluxes. We present a novel method that does not require assumptions about the model and the observations, leading to a more efficient and accurate assimilation of the satellite observations. Key Points: A novel non Gaussian and nonlinear ensemble data assimilation (DA) framework is applied to MOPITT joint state/flux optimizationThe new method performs better than the Ensemble Adjustment Kalman Filter in comparison to independent observationsMOPITT observations indicate that CAMS‐GLOB‐ANT_v5.3 emission fluxes are underestimated across the mid‐latitudes in May 2018 [ABSTRACT FROM AUTHOR]

• Vertical column density and column averaged dry air concentrations of GHGs were retrieved from FTIR using GFIT model. • Seasonal and interannual variations of GHGs were studied. • FTIR retrieved X CO 2 and X CO data were compared with satellite data. Solar absorption spectra collected using a ground-based Fourier Transform Infrared (FTIR) Spectrometer were used to retrieve the column-averaged concentrations (X) of CO 2 , CH 4 , CO, and N 2 O during the years 2016–2019 in the Suburban region of Shadnagar, Telangana, India. For the research period, the diurnal mean amplitudes of X CO 2 , X CH 4 , X CO, and X N 2 O are ∼ 13 ppmv, ∼50 ppbv, ∼13 ppbv, and ∼ 19 ppbv respectively. Strong seasonality at the study site is indicated by the seasonal variations of X CO 2 and X CO of 18.3 ppmv and 39.2 ppbv, respectively. Additionally, we compared FTIR data to X CO 2 detected by Orbiting Carbon Observatory-2 (OCO-2) and CO columns from Measurements of Pollution in the Troposphere (MOPITT). For the X CO 2 and CO columns, the comparison research shows a mean relative bias between FTIR data and satellite data of 0.92 % and 0.71 %, respectively. The FTIR and satellite data show a Pearson correlation coefficient (r) of 0.71 (X CO 2 , N = 26 co-located) and 0.60 (CO columns, N = 44), respectively. The findings demonstrate a good agreement between our data and satellite data. [ABSTRACT FROM AUTHOR]

Carbon monoxide (CO) is an indirect greenhouse gas that has a significant impact on atmospheric chemistry. This study investigates the spatial and temporal variation and trend in CO concentrations over Africa from 2000 to 2019 using data from the Measurements of Pollution In The Troposphere (MOPITT) satellite instrument. The study classifies Africa into eight subregions based on emission inventories: northern hemisphere (NH), southern hemisphere (SH), arid (A), semi-arid north (SAN), savannah NH (SNH), savannah SH (SSH), semi-arid south (SAS), and tropical rainforest (TRF). It is observed that the northern hemisphere contributes about 54.07% of CO over Africa, while the SH accounts for 45.93%. The research reveals that the annual mean columnar CO over Africa declined significantly, with most subregions exhibiting a significant decrease in columnar CO, particularly over the NH windows. The columnar CO over Africa also revealed a seasonal pattern with two peaks in DJF (December-February) and SON (September–November), reflecting affluence from both hemispheres. The seasonal maxima and minima differ among subregions. The study further demonstrates that the tropospheric CO's spatial and temporal variability in most subregions in Africa are sensitive to biomass burning, with MOPITT CO, MODIS fire count, and MODIS FRP being key parameters used to understand CO transport and fire emission across Africa. The study is relevant to climate researchers and policymakers seeking to understand the impact of CO on atmospheric chemistry, air quality, and climate change. [ABSTRACT FROM AUTHOR]

Top-down observational constraints on emissions flux estimates from satellite observations of chemical composition are subject to biases and errors stemming from transport, chemistry and prior emissions estimates. In this context, we developed an ensemble data assimilation system to optimize the initial conditions for carbon monoxide (CO) and aerosols, while also quantifying the respective emission fluxes with a distinct attribution of anthropogenic and wildfire sources. We present the separate assimilation of CO profile v9 retrievals from the Measurements of Pollution in the Troposphere (MOPITT) instrument and Aerosol Optical Depth (AOD), collection 6.1, from the Moderate Resolution Imaging Spectroradiometer (MODIS) instruments. This assimilation system is built on the Data Assimilation Research Testbed (DART) and includes a meteorological ensemble to assimilate weather observations within the online Community Atmosphere Model with Chemistry (CAM-chem). Inversions indicate an underestimation of CO emissions in CAMS-GLOB-ANT_v5.1 in China for 2015 and an overestimation of CO emissions in the Fire INventory from NCAR (FINN) version 2.2, especially in the tropics. These emissions increments are consistent between the MODIS AOD and the MOPITT CO-based inversions. Additional simulations and comparison with in situ observations from the NASA Atmospheric Tomography Mission (ATom) show that biases in hydroxyl radical (OH) chemistry dominate the CO errors. [ABSTRACT FROM AUTHOR]

Top-down observational constraints on emissions flux estimates from satellite observations of chemical composition are subject to biases and errors stemming from transport, chemistry and prior emissions estimates. In this context, we developed an ensemble data assimilation system to optimize the initial conditions for carbon monoxide (CO) and aerosols, while also quantifying the respective emission fluxes with a distinct attribution of anthropogenic and wildfire sources. We present the separate assimilation of CO profile v9 retrievals from the Measurements of Pollution in the Troposphere (MOPITT) instrument and Aerosol Optical Depth (AOD), collection 6.1, from the Moderate Resolution Imaging Spectroradiometer (MODIS) instruments. This assimilation system is built on the Data Assimilation Research Testbed (DART) and includes a meteorological ensemble to assimilate weather observations within the online Community Atmosphere Model with Chemistry (CAM-chem). Inversions indicate an underestimation of CO emissions in CAMS-GLOB-ANT_v5.1 in China for 2015 and an overestimation of CO emissions in the Fire INventory from NCAR (FINN) version 2.2, especially in the tropics. These emissions increments are consistent between the MODIS AOD and the MOPITT CO-based inversions. Additional simulations and comparison with in situ observations from the NASA Atmospheric Tomography Mission (ATom) show that biases in hydroxyl radical (OH) chemistry dominate the CO errors.

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). [ABSTRACT FROM AUTHOR]

The 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. Key Points: Anomalously high carbon monoxide (CO) emitted during the 2015 Indonesian fire season was transported into the upper troposphere and lower stratosphereSatellite measurements of hydrogen cyanide (HCN) indicate that wildfires can have an impact on the HCN concentrations in the stratosphere for up to 2 yearsCommunity Atmosphere Model with Chemistry simulations reproduce increases in CO in October 2015 but underestimate the amount of CO compared to the measurements [ABSTRACT FROM AUTHOR]

Atmospheric 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. Plain Language Summary: Carbon monoxide (CO) is an atmospheric pollutant produced from combustion, such as wildfires and gasoline powered automobiles. We use a 16‐year satellite record to determine how atmospheric CO levels have been changing this century. Though sporadic, large wildfires happen somewhere every year which can affect trends in CO. We find trends for small regions (∼40 × 40 km) over the full 16 years and over 5‐year subsets. Trends vary significantly among regions and among the 5‐year subsets. We then examine how CO levels in cities change compared to their surrounding region. In most cases, CO trends in cities do not vary significantly from trends in the surrounding region. In some regions where we would expect a decrease (like Los Angeles and Mexico City), we find large intra‐annual variability. Key Points: Column CO (XCO) trends vary regionally by 4%–5% year‐1 on 5‐year scales with an overall global decreaseLarge CO emitting events can cause XCO anomalies of +20 ppb (∼20%) compared to other years over thousands of kilometerUrban trends are similar enough to regional trends that it is difficult to distinguish them with this system [ABSTRACT FROM AUTHOR]

Long-term carbon monoxide (CO) total columns were retrieved from the MOPITT satellite to investigate long-term trends and seasonal variability of CO loads in the atmosphere of Thailand during 2001-2015. The results showed significantly high levels of CO total columns over the upper part of Thailand, especially in the northern region during March. Long range transport of CO plumes during biomass burning period can also be detected by the satellite. The comparisons between MOPITT CO total columns and surface CO emissions (from anthropogenic and biomass burning activities) were performed for five regions including the central, eastern, northern, northeastern, and southeastern parts of Thailand. The outputs presented similar seasonal patterns of MOPITT data and surface emissions with higher levels of CO during dry months and lower levels during wet months. Ground monitoring concentrations of CO were also comparably analyzed with MOPITT CO total columns in the central, eastern, and northern regions. The results gave relatively good consistency between these two datasets with the correlation coefficients (r) of 0.68-0.73. The analysis of the annual trends of CO total columns (2001-2015) and CO emissions (2001-2008) revealed slightly decreasing trends for most of the regions, except for the northern region, which showed the increase of CO emissions due to the intensive biomass burning in 2007. MOPITT observations were useful for tracking pollutant plumes and for monitoring CO loads in the atmosphere, particularly where there are limited data due to a lack of ground monitoring stations.

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. [ABSTRACT FROM AUTHOR]

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.

Carbon monoxide (CO) and formaldehyde (CH2O) are air pollutants playing an important role in the formation of tropospheric ozone (O3), which in turn have an influence on climate change. This study investigated the levels of CO and CH2O in Thailand during the periods of 2007 to 2017 (11 years). The observed data of CO were collected from the MOPITT satellite. For CH2O, the observed data were collected from the OMI satellite. Overall, during the study period, CO were detected at high levels from October to April and at low levels from May to September. For CH2O, the higher levels were detected from February to May while the lower levels were detected from June to September. Moreover, ground monitoring data of CO and CH2O were also obtained from the Pollution Control Department (PCD) from all over Thailand to compare with the satellite observed data. The results showed well correlated between satellite and ground CO levels in term of monthly pattern. However, the correlation between satellite and ground CH2O was relatively low. The results in this study showed that satellite observations of CO are useful to support ground measurements, particularly when ground monitoring stations are limited. [ABSTRACT FROM AUTHOR]

• We found sublinear scaling relationships between CO concentration and urban population. • Larger cities emit less CO per capita than smaller cities. • Satellite CO data resulted in a smaller scaling coefficient than the NEI data. • Discrepancies may be due in part to measurement differences. As the world's population is projected to reach 9.7 billion by 2050, large and small cities will continue to expand. There are few studies investigating how the size of cities affects air pollution. Carbon monoxide (CO), a precursor of ozone and a by-product of incomplete combustion, is a common air pollutant. The major sources of CO in the US urban areas are motor vehicles. Here we examined the scaling relation of CO concentrations over major US metropolitan statistical areas (MSAs) using Measurement Of Pollution in The Troposphere (MOPITT) surface CO retrievals and National Emissions Inventory (NEI) data. We found significant power-law scaling relationships between CO and population (r2 of 0.30 for MOPITT average CO concentration and r2 of 0.71 for NEI total CO emission). We found decreasing CO trends from 2000 to 2015 using MOPITT and EPA CO ground measurements. Sublinear scaling relationships (scaling coefficient β < 1) suggest that larger MSAs are more combustion-efficient in terms of CO emissions. We found a weaker scaling relation and smaller scaling coefficient from MOPITT CO concentrations than from NEI total CO emission data. This pattern may be attributed to the differences between the two CO datasets: annual average of monthly MOPITT CO concentration at 1° by 1° spatial resolution versus the NEI annual CO emissions compiled from emission inventories and estimated from mobile source emissions models. Future research is needed to investigate the capability of using satellite observations to study scaling relations between air pollutants and population. [ABSTRACT FROM AUTHOR]

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.

Atmospheric Carbone monoxide (CO) volume mixing ratios (VMR) retrieved by the Measurement of Pollution in the Troposphere (MOPITT) and Atmospheric Infrared Sounder (AIRS) instruments were used to monitor local emissions and compared over Iraq during the winter and spring of 2012. A comparison and cross reference are necessary to understand the impacts of these two data sets to the scientific conclusions developed from them, due to their simultaneous measurements of CO. The monthly CO VMR from MOPITT surface and AIRS 800 hpa are compared between the two instruments over Iraq for both direct comparison and the comparison using the same a priori profile for the period from 1 January to 31 December 2012. The CO VMR examination of the fluctuated, related to the mean CO background measured by each instrument, shows large-scale serendipitous spatial properties develop along the year. The regional CO VMR differences between two instruments were 5-35 ppbv and it's large for higher CO plumes and smaller for clean pristine desert environment. Both instruments observed enhancements of CO over the mountains and agreed with low CO over the southern region. Also, the time series of the monthly CO anomalies reveal a seasonal cycle signal, with high in winter and low in summer, due to meteorological condition, geographic nature of the regions and characteristic of the lower and upper troposphere to which MOPITT and AIRS are respectively sensitive to. This comparison demonstrates that there is a general consistency when considering the different vertical sensitivities of the instruments. The satellites observation efficiently shows the spatial and temporal variations of CO for the considered study area. [ABSTRACT FROM AUTHOR]

Biomass burning and urbanization are both significant sources of CO emissions and atmospheric loadings in the real environment. The sources of CO are due to incomplete combustion, on one hand of biomass from agriculture or forest clearing, and on the other hand from coal, oil, gas, and other similar materials. However, the spatial and temporal underlying properties and patterns are quite different between these two types of source regions, with urban regions having a relatively constant source of CO emissions, with only short term concentration fluctuations due to local meteorology. On the other hand, in biomass burning regions, the emissions themselves tend to be highly concentrated over a short burning period, and very low otherwise. We hence present a new technique to classify and quantify biomass burning regions and urban regions based on an objective analysis of the CO total column measurements from the MOPITT satellite. By using all of the data from2000-2016, in connection with averages and standard deviation cutoffs, we successfully determine these regions. By performing a sensitivity analysis, in connection with additional ground-based measurements, we determine that the ideal cutoffs for the mean column loading and standard deviation of the column loading 28×1017 mol/cm2 and 6×1017 mol/cm2 respectively. These results are capable of representing known urban regions and biomass burning regions well throughout China, Southeast Asia, and South Asia, specifically including Beijing, Hebei, Shandong, Jiangsu, Anhui, Hunan, Guangdong, and Bangkok on one hand, and Northeastern India, Myanmar, Laos, Northern Thailand, and Vietnam on the other hand. A detailed analysis of the time series over the different classified regions show that while the urban areas have a much higher annual value, and a relatively long peak time, that their maximum is never as high as the peaks in the biomass burning regions, and that these peaks in the biomass burning regions are extremely short in duration, although they occur annually or bi-annually. Finally, we have not been able to obtain a statistically relevant decreasing trend, as others have found, making CO possibly an interesting species for future studies. [ABSTRACT FROM AUTHOR]

A comparative study was carried out to explore carbon monoxide total columnar amount (CO TC) in background and polluted atmosphere, including the stations of ZSS (Zvenigorod), ZOTTO (Central Siberia), Peterhof, Beijing, and Moscow, during 1998-2014, on the basis of ground- and satellite-based spectroscopic measurements. Interannual variations of CO TC in different regions of Eurasia were obtained from ground-based spectroscopic observations, combined with satellite data from the sensors MOPITT (2001-14), AIRS (2003-14), and IASI MetOp-A (2010-13). A decreasing trend in CO TC (1998-2014) was found at the urban site of Beijing, where CO TC decreased by 1.14%±0.87% yr−1. Meanwhile, at the Moscow site, CO TC decreased remarkably by 3.73%±0.39% yr−1. In the background regions (ZSS, ZOTTO, Peterhof), the reduction was 0.9%-1.7% yr−1 during the same period. Based on the AIRSv6 satellite data for the period 2003-14, a slight decrease (0.4%-0.6% yr−1) of CO TC was detected over the midlatitudes of Eurasia, while a reduction of 0.9%-1.2% yr−1 was found in Southeast Asia. The degree of correlation between the CO TC derived from satellite products (MOPITTv6 Joint, AIRSv6 and IASI MetOp-A) and ground-based measurements was calculated, revealing significant correlation in unpolluted regions. While in polluted areas, IASI MetOp-A and AIRSv6 data underestimated CO TC by a factor of 1.5-2.8. On average, the correlation coefficient between ground- and satellite-based data increased significantly for cases with PBL heights greater than 500 m. [ABSTRACT FROM AUTHOR]

In the present study, surface ozone (O3), nitrogen oxides (NOx), and carbon monoxide (CO) levels were measured at two sites downwind of fire active region in the Indo-Gangetic Plain (IGP): Agra (27.16° N, 78.08° E) and Delhi (28.37° N, 77.12° E) to study the impact of post-harvest crop-residue fires. The study period was classified into two groups: Pre-harvest period and Post-harvest period. During the post-harvest period, an enhancement of 17.3 and 31.7 ppb in hourly averaged O3 mixing ratios was observed at Agra and Delhi, respectively, under similar meteorological conditions. The rate of change of O3 was also higher in the post-harvest period by 56.2% in Agra and 39.5% in Delhi. Relatively higher O3 episodic days were observed in the post-harvest period. Fire hotspots detected by Moderate Resolution Imaging Spectroradiometer (MODIS) along with backward air-mass trajectory analysis suggested that the enhanced O3 and CO levels at the study sites during the post-harvest period could be attributed to crop-residue burning over the North-West IGP (NW-IGP). Satellite observations of surface CO mixing ratios and tropospheric formaldehyde (HCHO) column also showed higher levels during the post-harvest period.Graphical abstract [ABSTRACT FROM AUTHOR]

Abstract: The “Measurements of Pollution in the Troposphere” (MOPITT) satellite record is applied to study the geographical and temporal variability of carbon monoxide (CO) from biomass burning in the Amazon Basin. The presented analysis demonstrates the use of satellite observations for interpreting the effects of deforestation and climate on past and future emissions of CO. The study exploits the MOPITT “multispectral” retrieval product which effectively resolves tropospheric CO into two independently measured layers. New validation results based on in situ measurements during the ACRIDICON‐CHUVA aircraft campaign in 2014 are used for bias correction. Contrasting CO monthly climatologies are presented for the Amazon Basin for the lower and upper troposphere (“LT” and “UT”) with an emphasis on the Amazonian dry season. Climatologically, spatial patterns of UT CO over the Amazon Basin appear to be related to both deep convection and anticyclonic flow. Strongly enhanced LT basin‐mean CO concentrations are observed for the dry season months in 2005, 2007, 2010, and 2015, while the record also indicates a decreasing long‐term trend. These observations are consistent with the expected effects of falling deforestation rates since 2004, punctuated by CO spikes in drought years due to large‐scale wildfires. [ABSTRACT FROM AUTHOR]

Long-term carbon monoxide (CO) total columns were retrieved from the MOPITT satellite to investigate long-term trends and seasonal variability of CO loads in the atmosphere of Thailand during 2001-2015. The results showed significantly high levels of CO total columns over the upper part of Thailand, especially in the northern region during March. Long range transport of CO plumes during biomass burning period can also be detected by the satellite. The comparisons between MOPITT CO total columns and surface CO emissions (from anthropogenic and biomass burning activities) were performed for five regions including the central, eastern, northern, northeastern, and southeastern parts of Thailand. The outputs presented similar seasonal patterns of MOPITT data and surface emissions with higher levels of CO during dry months and lower levels during wet months. Ground monitoring concentrations of CO were also comparably analyzed with MOPITT CO total columns in the central, eastern, and northern regions. The results gave relatively good consistency between these two datasets with the correlation coefficients (r) of 0.68-0.73. The analysis of the annual trends of CO total columns (2001-2015) and CO emissions (2001-2008) revealed slightly decreasing trends for most of the regions, except for the northern region, which showed the increase of CO emissions due to the intensive biomass burning in 2007. MOPITT observations were useful for tracking pollutant plumes and for monitoring CO loads in the atmosphere, particularly where there are limited data due to a lack of ground monitoring stations. [ABSTRACT FROM AUTHOR]

A variance-maximization approach based on 19 years of weekly measurements of pollution in the troposphere carbon monoxide (CO) measurements quantifies the spatial-temporal distribution of global biomass burning. Seven regions consistent with existing datasets are discovered and shown to burn for longer, over a more widespread area. Each region has a unique and recurring burning season, with three dominated by inter- and intra-annual variation. The CO is primarily lofted to the free troposphere from where it spreads downwind at 800 to 700 mb with three exceptions: The Maritime Continent and South America where there is spread at 300 mb consistent with deep- and pyro-convection; and Southern Africa which reaches to 600 mb. The total mass of CO lofted into the free troposphere ranges from 46% over Central Africa to 92% over Australia. The global, annual emissions made using two different techniques lead to an increase of biomass burning CO emissions of 47TgCO/year and 99TgCO/year respectively. The larger increase is mainly due to two factors: first, a large amount of the emissions is lofted rapidly upwards over the biomass burning region and subsequently transported downwind, therefore not appearing near the biomass source in space and time and second, an increase in inter-annual variability. Consistently, there is an increase in variability year-to-year and during peak events, from which 35% to more than 80% of the total emissions is lofted into the free troposphere. The results demonstrate a significantly higher CO emission from biomass burning, a larger impact on the global atmospheric composition, and likely impacts on atmospheric chemistry and climate change.

This study examines the spatio-temporal trends obtained from decade long (Jan 2003–Dec 2014) satellite observational data of Atmospheric Infrared Sounder (AIRS) and Measurements of Pollution in the Troposphere (MOPITT) on carbon monoxide (CO) concentration over the Indo-Gangetic Plains (IGP) region. The time sequence plots of columnar CO levels over the western, central and eastern IGP regions reveal marked seasonal behaviour, with lowest CO levels occurring during the monsoon months and the highest CO levels occurring during the pre-monsoon period. A negative correlation between CO levels and rainfall is observed. CO vertical profiles show relatively high values in the upper troposphere at ∼200 hPa level during the monsoon months, thus suggesting the role of convective transport and advection in addition to washout behind the decreased CO levels during this period. MOPITT and AIRS observations show a decreasing trend of 9.6 × 10 15 and 1.5 × 10 16 molecules cm −2 yr −1 , respectively, in columnar CO levels over the IGP region. The results show the existence of a spatial gradient in CO from the eastern (higher levels) to western IGP region (lower levels). Data from the Census of India on the number of households using various cooking fuels in the IGP region shows the prevalence of biomass-fuel (i.e. firewood, crop residue, cowdung etc.) use over the eastern and central IGP regions and that of liquefied petroleum gas over the western IGP region. CO emission estimates from cooking activity over the three IGP regions are found to be in the order east > central > west, which support the existence of the spatial gradient in CO from eastern to the western IGP region. Our results support the intervention of present Indian government on limiting the use of biomass-fuels in domestic cooking to achieve the benefits in terms of the better air quality, household health and regional/global climate change mitigation. [ABSTRACT FROM AUTHOR]

In the present study, MOZART-4 (Model for Ozone and Related chemical Tracers-Version-4) simulation has been made from 2003 to 2007 and compared with satellite and in-situ observations with a specific focus on Indian subcontinent to illustrate the capabilities of MOZART-4 model. The model simulated CO have been compared with latest version (version-6) of MOPITT (Measurement Of Pollution In The Troposphere) carbon monoxide (CO) retrievals at 900, 800 and 700 hPa. Model reproduces major features present in satellite observations. However model significantly overestimates CO over the entire Indian region at 900 hPa and moderately overestimates at 800 hPa and 700 hPa. The frequency distribution of all simulated data points with respect to MOZART error shows maximum in the error range of 10–20% at all pressure levels. Over total Indian landmass, the percentage of gridded CO data that are being overestimated in the range of 0–30% at 900 hPa, 800 hPa and 700 hPa are 58%, 62% and 66% respectively. The study reflects very good correlation between two datasets over Central India (CI) and Southern India (SI). The coefficient of determination (r 2 ) is found to be 0.68–0.78 and 0.70–0.78 over the CI and SI respectively. The weak correlation is evident over Northern India (NI) with r 2 values of 0.1–0.3. Over Eastern India (EI), Good correlation at 800 hPa (r 2 = 0.72) and 700 hPa (r 2 = 0.66) whereas moderately weak correlation at 900 hPa (r 2 = 0.48) has been observed. In contrast, Over Western India (WI), strong correlation is evident at 900 hPa (r 2 = 0.64) and moderately weak association is found to be present at 800 hPa and 700 hPa. Model fairly reproduces seasonal cycle of CO in the lower troposphere over most of the Indian regions. However, during June to December, model shows overestimation over NI. The magnitude of overestimation is increasing linearly from 900 hPa to 700 hPa level. During April–June months, model results are coinciding with observed CO concentrations over SI region at 900 hPa. Model simulation has been compared with surface in-situ observations over ten Indian locations. Model performance is found to be moderate to good over various observational locations. However, over highly polluted megacities, model underestimates observed CO concentration by up to 3500 ppbv. A case study over the forest fire prone area reveals the clear increase of modeled and retrieved CO in February–March and a decrease in May which is coinciding with biomass burning emissions and fire counts. Model performance is found to be relatively poor over this region with r 2 of 0.29 and slope of 0.56. [ABSTRACT FROM AUTHOR]

Carbon monoxide (CO) total columns over European Russia (ER) and western Siberia (WS) have been analyzed using MOPITT (V5, TIR/NIR, L3) IR-radiometer data obtained in 2000-2014. High CO contents are revealed over large urban and industrial agglomerations and over regions of oil-and-gas production. A stable local CO maximum is observed over the Moscow agglomeration. Statistical characteristics of CO total columns observed in the atmosphere over ER and WS in 2000-2014 are presented. An analysis of long-term changes in CO content reveals nonlinear changes in the CO total column over northern Eurasia in 2000-2014. Results of a comparative analysis of annual variations in atmospheric CO contents over ER and WS are given. Based on Fourier analysis, empirical models of annual variations in total CO contents over ER and WS are proposed. Relations between regional CO contents and fire characteristics and between spatial CO distributions and features of large-scale atmospheric dynamics under conditions of weather and climate anomalies in the summers of 2010 in ER and 2012 in WS are analyzed. Data on total CO contents measured with a MOPITT satellite radiometer and a ground-based spectrometer operating at the Zvenigorod Scientific Station of the Obukhov Institute of Atmospheric Physics are compared. [ABSTRACT FROM AUTHOR]

The Measurements of Pollution in the Troposphere (MOPITT) instrument on the NASA Terra platform has now acquired over thirteen years of global tropospheric carbon monoxide (CO) observations, forming the longest satellite record for an important pollutant. [...]

In this study, for the first time, the influence of springtime (MAM) biomass burning in South Asia on regional ozone (O 3 ) distribution has been evaluated using a regional chemical transport model (WRF-Chem) and the Fire Inventory from NCAR (FINNv1). Model results are compared with satellite retrievals of tropospheric column amounts of carbon monoxide (CO) from MOPITT and nitrogen dioxide (NO 2 ) from OMI. With daily varying emissions, the model captures reasonably well the satellite-derived temporal variations in CO and NO 2 (index of agreement ( R ) for CO is 0.83 and for NO 2 is 0.76), indicating the effectiveness of the model in estimating the overall fire impact on a regional scale. Simulated tropospheric NO 2 concentration shows better agreement with the magnitude of observed NO 2 when FINNv1 NO x emissions are reduced by a factor of 2.2 over the model domain. A clear increase in CO and NO 2 levels over Burma (35–60%), Central India (15–30%), the Indo-Gangetic (15–25%) region and the Bay of Bengal (15–40%) are simulated with fire emissions. The model results are also used to quantify the net O 3 production from fires. Calculated O 3 productions are up to 4 ppb h − 1 over inland and up to 0.1 ppb h − 1 over marine regions respectively. Our model-based analysis yields average enhancement ratios ΔO 3 /ΔCO of 0.12 ppbv/ppbv and a total O 3 production of about 3.5 Tg from South Asia during the spring season. The findings demonstrate that the springtime fire emissions in South Asia have a noticeable impact on the O 3 in this region. [ABSTRACT FROM AUTHOR]