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.

Influence of biomass burning on local air pollution in mainland Southeast Asia from 2001 to 2016

In this study, various remote sensing data, modeling data and emission inventories were integrated to analyze the tempo-spatial distribution of biomass burning in mainland Southeast Asia and its effects on the local ambient air quality from 2001 to 2016. Land cover changes have been considered in dividing the biomass burning into four types: forest fires, shrubland fires, crop residue burning and other fires. The results show that the monthly average number of fire spots peaked at 34,512 in March and that the monthly variation followed a seasonal pattern, which was closely related to precipitation and farming activities. The four types of biomass burning fires presented different tempo-spatial distributions. Moreover, the monthly Aerosol Optical Depth (AOD), concentration of particulate matter with a diameter less than 2.5 μm (PM_2.5) and carbon monoxide (CO) total column also peaked in March with values of 0.62, 45 μg/m³ and 3.25 × 10¹⁸ molecules/cm², respectively. There are significant correlations between the monthly means of AOD (r = 0.74, P < 0.001), PM_2.5 concentration (r = 0.88, P < 0.001), and CO total column (r = 0.82, P < 0.001) and the number of fire spots in the fire season. We used Positive Matrix Factorization (PMF) model to resolve the sources of PM_2.5 into 3 factors. The result indicated that the largest contribution (48%) to annual average concentration of PM_2.5 was from Factor 1 (dominated by biomass burning), followed by 27% from Factor 3 (dominated by anthropogenic emission), and 25% from Factor 2 (long-range transport/local nature source). The annually anthropogenic emission of CO and PM_2.5 from 2001 to 2012 and the monthly emission from the Emission Database for Global Atmosphere Research (EDGAR) were consistent with PMF analysis and further prove that biomass burning is the dominant cause of the variation in the local air quality in mainland Southeast Asia.

Modeling the effect of VOCs from biomass burning emissions on ozone pollution in upper Southeast Asia

We used a Weather Research and Forecasting Model with Chemistry (WRF-CHEM) model that includes anthropogenic emissions from EDGAR-HTAP, biomass burning from FINN, and biogenic emissions from MEGAN to investigate the main volatile organic compound (VOC) ozone precursors during high levels of biomass burning emissions in March 2014 over upper Southeast Asia. A comparison between the model and ground-based measurement data shows that the WRF-CHEM model simulates the precipitation and 2 m temperature reasonably well, with index of agreement (IOA) values ranging from 0.76 to 0.78. Further, the model predicts O3, NO2, and CO fairly well, with IOA values ranging from 0.50 to 0.57. However, the magnitude of the simulated NO2 concentration was generally underestimated compared to OMI satellite observations. The model result shows that CO and VOCs such as BIGENE play an important role in atmospheric oxidation to surface O3. In addition, biomass burning emissions are responsible for increasing surface O3 by ∼1 ppmv and increasing the reaction rate of CO and BIGENE by approximately 0.5 × 106 and 1 × 106 molecules/cm3/s, respectively, in upper Southeast Asia.

Spatio-Temporal Characteristics of Tropospheric Ozone and Its Precursors in Guangxi, South China

The temporal and spatial distributions of tropospheric ozone and its precursors (NO2, CO, HCHO) are analyzed over Guangxi (GX) in South China. We used tropospheric column ozone (TCO) from the Ozone Monitoring Instrument (OMI) and Microwave Limb Sounder (MLS) onboard the Aura satellite (OMI/MLS), NO2 and HCHO from OMI and CO from the Measurements of Pollution in the Troposphere (MOPITT) instrument in the period 2005–2016. The TCO shows strong seasonality, with the highest value in spring and the lowest value observed in the monsoon season. The seasonal variation of HCHO is similar to that of TCO, while NO2 and CO show slightly different patterns with higher values in spring and winter compared to lower values in autumn and summer. The surface ozone, NO2 and CO observed by national air quality monitoring network sites are also compared with satellite-observed TCO, NO2 and CO, showing good agreement for NO2 and CO but a different seasonal pattern for ozone. Unlike TCO, surface ozone has the highest value in autumn and the lowest value in winter. To reveal the difference, the vertical profiles of ozone and CO from the measurement of ozone and water vapor by airbus in-service aircraft (MOZAIC) observations over South China are also examined. The seasonal averaged vertical profiles of ozone and CO show obvious enhancements at 2–6 km altitudes in spring. Furthermore, we investigate the dependence of TCO and surface ozone on meteorology and transport in detail along with the ECMWF reanalysis data, Tropical Rainfall Measuring Mission (TRMM) 3BV42 dataset, OMI ultraviolet index (UV index) dataset, MODIS Fire Radiative Power (FRP) and back trajectory. Our results show that the wind pattern at 800 hPa plays a significant role in determining the seasonality of TCO over GX, especially for the highest value in spring. Trajectory analysis, combined with MODIS FRP suggests that the air masses that passed through the biomass burning (BB) region of Southeast Asia (SEA) induced the enhancement of TCO and CO in the upper-middle troposphere in spring. However, the seasonal cycle of surface ozone is associated with wind patterns at 950 hPa, and the contribution of the photochemical effect is offset by the strong summer monsoon, which results in the maximum surface ozone concentration in post-monsoon September. The variations in the meteorological conditions at different levels and the influence of transport from SEA can account for the vertical distribution of ozone and CO. We conclude that the seasonal distribution of TCO results from the combined impact of meteorology and long-term transport.

Influence of El Niño on atmospheric CO2 over the tropical Pacific Ocean: Findings from NASA's OCO-2 mission

Spaceborne observations of carbon dioxide (CO₂) from the Orbiting Carbon Observatory-2 are used to characterize the response of tropical atmospheric CO₂ concentrations to the strong El Niño event of 2015-2016. Although correlations between the growth rate of atmospheric CO₂ concentrations and the El Niño-Southern Oscillation are well known, the magnitude of the correlation and the timing of the responses of oceanic and terrestrial carbon cycle remain poorly constrained in space and time. We used space-based CO₂ observations to confirm that the tropical Pacific Ocean does play an early and important role in modulating the changes in atmospheric CO₂ concentrations during El Niño events-a phenomenon inferred but not previously observed because of insufficient high-density, broad-scale CO₂ observations over the tropics.

Three-dimensional investigation of ozone pollution in the lower troposphere using an unmanned aerial vehicle platform

Potential utilities of instrumented lightweight unmanned aerial vehicles (UAVs) to quickly characterize tropospheric ozone pollution and meteorological factors including air temperature and relative humidity at three-dimensional scales are highlighted in this study. Both vertical and horizontal variations of ozone within the 1000 m lower troposphere at a local area of 4 × 4 km² are investigated during summer and autumn times. Results from field measurements show that the UAV platform has a sufficient reliability and precision in capturing spatiotemporal variations of ozone and meteorological factors. The results also reveal that ozone vertical variation is mainly linked to the vertical distribution patterns of air temperature and the horizontal transport of air masses from other regions. In addition, significant horizontal variations of ozone are also observed at different levels. Without major exhaust sources, ozone horizontal variation has a strong correlation with the vertical convection intensity of air masses within the lower troposphere. Higher air temperatures are usually related to lower ozone horizontal variations at the localized area, whereas underlying surface diversity has a week influence. Three-dimensional ozone maps are obtained using an interpolation method based on UAV collected samples, which are capable of clearly demonstrating the diurnal evolution processes of ozone within the 1000 m lower troposphere.

Analysis of carbon monoxide budget in North China

A global chemical transport model (MOZART-2; model of ozone and related tracers, version 2) was used to assess physical and chemical processes that control the budget of tropospheric carbon monoxide (CO) in North China. Satellite observations of CO from the measurements of pollution in the troposphere (MOPITT) instrument are combined with model results for the analysis. The comparison between the model simulations and the satellite observations of total column CO (TCO) shows that the model can reproduce the spatial and temporal distributions. However, the model results underestimate TCO by 23% in North China. This underestimation of TCO may be caused by the uncertainties of emissions. The tropospheric CO budget analysis suggests that in North China, surface emission is the largest source of tropospheric CO. The main sinks of tropospheric CO in this region are chemical reaction and stratosphere_and_troposphere exchange. The analysis also shows that most of inflow CO to Pacific regions comes from the upwind regions of North China. This transport of CO is significant during Winter and Spring time.