Large contribution of biomass burning emissions to ozone throughout the global remote troposphere

Ozone is the third most important anthropogenic greenhouse gas after carbon dioxide and methane but has a larger uncertainty in its radiative forcing, in part because of uncertainty in the source characteristics of ozone precursors, nitrogen oxides, and volatile organic carbon that directly affect ozone formation chemistry. Tropospheric ozone also negatively affects human and ecosystem health. Biomass burning (BB) and urban emissions are significant but uncertain sources of ozone precursors. Here, we report global-scale, in situ airborne measurements of ozone and precursor source tracers from the NASA Atmospheric Tomography mission. Measurements from the remote troposphere showed that tropospheric ozone is regularly enhanced above background in polluted air masses in all regions of the globe. Ozone enhancements in air with high BB and urban emission tracers (2.1 to 23.8 ppbv [parts per billion by volume]) were generally similar to those in BB-influenced air (2.2 to 21.0 ppbv) but larger than those in urban-influenced air (−7.7 to 6.9 ppbv). Ozone attributed to BB was 2 to 10 times higher than that from urban sources in the Southern Hemisphere and the tropical Atlantic and roughly equal to that from urban sources in the Northern Hemisphere and the tropical Pacific. Three independent global chemical transport models systematically underpredict the observed influence of BB on tropospheric ozone. Potential reasons include uncertainties in modeled BB injection heights and emission inventories, export efficiency of BB emissions to the free troposphere, and chemical mechanisms of ozone production in smoke. Accurately accounting for intermittent but large and widespread BB emissions is required to understand the global tropospheric ozone burden.

Evaluation of regional simulation of surface ozone over Southeast Asia using ground-based observation at two existing Global Atmospheric Watch stations

High level of ground level ozone concentrations was found in most of Southeast Asian (SEA) large cities and often exceeded the national ambient air quality standard. Ozone and PM10 are among of the critical air quality parameters that cause the unhealthy air quality index. Effort to mitigate ozone pollution is greatly complicated due to the photochemistry processes therefore photochemical smog modelling has been widely used. Surface ozone simulation in SEA was done using CHIMERE and weather research forecast (WRF) model. Emission inventory of ozone precursors was done for three countries in the domain, i.e. Indonesia, Thailand and Cambodia. Modelling performance evaluation for meteorological parameters and ozone at the SEA big cities was done in another study. This paper focused on the model evaluation conducted at the two remote sites represented by 2 (two) global atmospheric watch (GAW) remote stations of Bukit Kototabang (BKT) and Danum Valley (DNV). Evaluation result showed an overestimation of observed ozone in BKT while a contradictive result was seen in DNV station which was due to the ozone chemistry and inaccurate estimation of emissions (both anthropogenic and biogenic emission). The evaluation conducted at the remote sites was not even better than that conducted previously at the urban areas. Statistically, only mean normalized gross error and unpaired peak accuracy values that satisfy the criteria for surface ozone modelling suggesting major improvement required for ozone precursors emission inventory data.

Study on Air Pollution Behavior of VOCs with Photochemical Monitoring Stations Using EGARCH Model in Southern Taiwan

This study adopted the exponential generalized autoregressive conditional heteroscedasticity (EGARCH) model to examine the 10 ozone precursors of the highest concentrations among the 54 that were assessed over a number of years at the four photochemical assessment monitoring stations (PAMSs) in the Kaohsiung–Pingtung Area in Taiwan. First, the 10 ozone precursors, which were all volatile organic compounds (VOCs), were analyzed using the factor analyses in multiple statistical analyses that had the most significant impact on the area’s ozone formation: mobile pollution factor, which included 1,2,4-Trimethylbenzene (C9H12), toluene (C7H8), and Isopropyl benzene (C9H12). Then, taking into consideration that the number sequences might be affected by standardized residuals, this study applied the vector autoregressive moving average-EGARCH (VARMA-EGARCH) model to analyze the correlation between the three VOCs under different polluting activities. The VARMA-EGARCH model in this research included dummy variables representing changing points of variance structures in the variance formula to predict the conditional variance. This process proved able to effectively estimate the relevant coefficients of the three VOCs’ dynamic conditions that changed with time. The model also helped to prevent errors from occurring when estimating the conditional variance. Based on the testing results, this study determined the VARMA(2,1)-EGARCH(1,0) as the most suitable model for exploring the correlation between the three VOCs and meteorological phenomena, as well as the interplay between them in regard to interaction and formation. With the most representative of the three, toluene (TU), as the dependent variable and 1,2,4-Trimethylbenzene (TB) and Isopropyl benzene (IB) as the independent variables, this study found it impossible to calculate the TU concentration with TB and IB concentrations in the same period; estimations of TB and IB concentrations with a period of lag time were required because TU was mainly contributed by automobiles and motorcycles in Kaohsiung. TB and IB resulted from other stationary pollution sources in the region besides cars and motorbikes. When TU was evenly distributed and stayed longer in the atmosphere, the TB and IB concentrations were lower, so distribution conditions and concentrations could not be used to effectively estimate the concentration of toluene. This study had to wait until the next period, or when stationary pollution sources started producing TB and IB of higher concentrations during the daytime, in order to estimate the TU concentrations in a better photochemical situation.

The Potential Ozone Impacts of Landfills

Landfill gas produces ozone precursors such as nitrogen oxides and formaldehyde when combusted in flares or stationary engines. Solid waste landfills are also the third largest anthropogenic source of methane in the United States. Methane is both a greenhouse gas and a tropospheric ozone precursor. Despite its low photochemical reactivity, methane may noticeably affect urban ozone if released in large quantities along with other organic compounds in landfill gas. A fine-scale 3D Eulerian chemical transport model was used to demonstrate that, under meteorological and background chemical conditions conducive to high ozone concentrations, typical emissions of ozone precursors from a single hypothetical landfill may result in persistent daytime additions to ozone of over 1 part per billion (ppb) by volume tens of kilometers downwind. Large leaks of landfill gas can enhance this ozone pollution by over a tenth of a ppb, and external sources of non-methane ozone precursors may further exacerbate this impact. In addition, landfill gas combustion may increase near-source exposure to toxic formaldehyde by well over half a ppb. In Southeast Michigan, the combined influence of several landfills upwind of key monitoring sites may contribute significantly to observed exceedances of the U.S. ozone standard.

Emissions Reduction of Greenhouse Gases, Ozone Precursors, Aerosols and Acidifying Gases from Road Transportation during the COVID-19 Lockdown in Colombia

The aim of this work was to analyze the changes in the emissions from the transport sector during the COVID-19 lockdown in Colombia. We compared estimated emissions from road transportation of four groups of pollutants, namely, greenhouse gases (CO2, CH4, N2O), ozone precursor gases (CO, NMVOC, NOx), aerosols (BC, PM2.5, PM10), and acidifying gases (NH3, SO2), during the first half of 2020 with values obtained in the same period of 2018. The estimate of emissions from road transportation was determined using a standardized methodology consistent with the 2006 Intergovernmental Panel on Climate Change (IPCC) Guidelines for National Greenhouse Gas Inventories and the European Environment Agency/European Monitoring and Evaluation Program. We found a substantial reduction in GHG emissions for CH4, N2O, and CO2 by 17%, 21%, and 28%, respectively. The ozone precursors CO and NMVOC presented a decrease of 21% and 22%, respectively, while NOx emissions were reduced up to 15% for the study period. In addition, BC decreased 15%, and there was a reduction of 17% for both PM10 and PM2.5 emissions. Finally, acidifying gases presented negative variations of 19% for SO2 and 23% for NH3 emissions. Furthermore, these results were consistent with the Ozone Monitoring Instrument (OMI) satellite observations and measurements at air quality stations. Our results suggest that the largest decreases were due to the reduction in the burning of gasoline and diesel oil from the transport sector during the COVID-19 lockdown. These results can serve decision makers in adopting strategies to improve air quality related to the analyzed sector.

Characterization and sources of volatile organic compounds (VOCs) during ozone pollution events in Chengdu plain, Southwest China

<p>Since 2015, the annual average ozone (O<sub>3</sub>) concentration in Chengdu has shown significant positive trends and reached a maximum of 55.2 ppb in 2018. By 2019, the annual average O<sub>3</sub> value has slightly decreased to 52.9 ppb, but it is still at the highest level in the Sichuan Basin. In order to illuminate VOCs characteristics, identify critical ozone precursors and explore potential sources during ozone pollution events in Chengdu plain, we performed a comprehensive field observation campaign from 9 August to 14 September 2019. During the campaign, the averaged O<sub>3</sub> concentration was 29.1 ppb, and mean values of ozone precursors NOx and TVOC were 14.9 ppb and 31.3 ppb, respectively. Two severe ozone pollution events occurred in Chengdu during the observation period. In ozone pollution event 1, the ratios of the average O<sub>3</sub>, NOx, NMHCs, and OVOCs concentration on the polluted days relative to the clean days were 4.1, 0.3, 0.6, and 1.4, respectively. In ozone pollution event 2, the ratios of the average O<sub>3</sub>, NOx, NMHCs, and OVOCs concentration on the polluted days relative to the clean days were 3.4, 0.4, 0.6 and 2.1, respectively. The difference of the ratios indicates that there are secondary conversions of NMHCs and NOx and secondary formation of O<sub>3</sub> and OVOCs during the pollution period. Isoprene, Acetaldehyde, Methyl Vinyl Ketone, m/p-Xylene and 1-Butene constitute a large fraction of the L<sub>OH</sub> during polluted days.  In this study, air mass cluster analysis, the potential source contribution function (PSCF), and positive matrix factorization (PMF) receptor models were used in combination to analyze the sources and potential source areas of VOCs during O3 pollution events.</p>

Assessment of pre-industrial to present-day anthropogenic climate forcing in UKESM1

Quantifying forcings from anthropogenic perturbations to the Earth System (ES) is important for understanding changes in climate since the pre-industrial period. In this paper, we quantify and analyse a wide range of present-day (PD) anthropogenic climate forcings with the UK's Earth System Model (ESM), UKESM1, following the protocols defined by the Radiative Forcing Model Intercomparison Project (RFMIP) and the Aerosol and Chemistry Model Intercomparison Project (AerChemMIP). In particular, by quantifying effective radiative forcings (ERFs) that include rapid adjustments within a full ESM, it enables the role of various climate-chemistry-aerosol-cloud feedbacks to be quantified. Global mean ERFs are 1.83, 0.13, −0.33, and 0.93 W m−2 at the PD (Year 2014) relative to the pre-industrial (PI; Year 1850) for carbon dioxide, nitrous oxide, ozone-depleting substances, and methane, respectively. The PD total greenhouse gas ERF is 2.89 W m−2, larger than the sum of the individual GHG ERFs. UKESM1 has an aerosol forcing of −1.13 W m−2. A relatively strong negative forcing from aerosol-cloud interactions and a small negative instantaneous forcing from aerosol-radiation interactions are partially offset by a substantial forcing from black carbon absorption. Internal mixing and chemical interactions mean that neither the forcing from aerosol-radiation interactions nor aerosol-cloud interactions are linear, making the total aerosol ERF less than the sum of the individual speciated aerosol ERFs. Tropospheric ozone precursors, in addition to exerting a positive forcing due to ozone, lead to oxidant changes which in turn cause an indirect aerosol ERF, altering the sign of the net ERF from nitrogen oxide emissions. Together, aerosol and tropospheric ozone precursors (near-term climate forcers, NTCFs) exert a global mean ERF of −1.12 W m−2, mainly due to changes in the cloud radiative effect. There is also a negative PD ERF from land use (−0.32 W m−2). It is outside the range of previous estimates, and is most likely due to too strong an albedo response. In combination, the net anthropogenic ERF is potentially biased low (1.61 W m−2) relative to other estimates, due to the inclusion of non-linear feedbacks and ES interactions. By including feedbacks between greenhouse gases, stratospheric and tropospheric ozone, aerosols, and clouds, some of which act non-linearly, this work demonstrates the importance of ES interactions when quantifying climate forcing. It also suggests that rapid adjustments need to include chemical as well as physical adjustments to fully account for complex ES interactions.

Characteristics of Ground-Level Ozone from 2015 to 2018 in BTH Area, China

With the ground-level ozone pollution problem increasingly prominent in recent years in China, it is particularly important in basic researches on ozone contamination characteristics. In this study, 13 cities in Beijing-Tianjin-Hebei (BTH) area were examined to determine the characteristics of surface ozone (O3) from 2015 to 2018. Due to the photochemical oxidation of ozone precursors (such as nitrogen oxides and carbon monoxide) along with the presence of sunlight and characteristics of local emission sources, the O3 and oxidant (OX) concentrations showed obvious seasonal variation and daily variation. It implicated that the O3 concentrations reached the maximum during summer. The concentrations of O3 were higher at daytime than those measured at nighttime. The ozone weekend effect was estimated by the difference and deviation, which exhibited that the difference between weekday and weekend were related to the concentrations of ozone precursors and PM, vehicle emissions, and solar radiation. Moreover, the O3 concentrations decreased with the increase of other air pollutants by correlation analysis. The ozone pollution was easily formed at light and moderate polluted periods when compared to other air quality levels.

Investigate Wildfire Impacts on Ozone Production by Vertical Observations and Photochemical Modeling

In troposphere, ozone is a toxic secondary pollutant produced when its precursors react in sunlight. An important source of ozone precursors is biomass burning. Here we investigate the impacts of 2016 Southeast U.S. Wildfires on ozone production by integrating vertical resolved ozone profiles and photochemical modeling. The results show that wildfires contributed to ozone lamina at the top of boundary layer and enhanced surface ozone up to about 10ppbv in Southeast U.S.. Ozone lidar observed a lower ozone change with respect to a fast growth of aerosol plume, of which the reason is also investigated. Current results indicate an effective integration of vertical observations and modeling for us to understand the ozone production from fires in troposphere.