Societal shifts due to COVID-19 reveal large-scale complexities and feedbacks between atmospheric chemistry and climate change.

The COVID-19 global pandemic and associated government lockdowns dramatically altered human activity, providing a window into how changes in individual behavior, enacted en masse, impact atmospheric composition. The resulting reductions in anthropogenic activity represent an unprecedented event that yields a glimpse into a future where emissions to the atmosphere are reduced. Furthermore, the abrupt reduction in emissions during the lockdown periods led to clearly observable changes in atmospheric composition, which provide direct insight into feedbacks between the Earth system and human activity. While air pollutants and greenhouse gases share many common anthropogenic sources, there is a sharp difference in the response of their atmospheric concentrations to COVID-19 emissions changes, due in large part to their different lifetimes. Here, we discuss several key takeaways from modeling and observational studies. First, despite dramatic declines in mobility and associated vehicular emissions, the atmospheric growth rates of greenhouse gases were not slowed, in part due to decreased ocean uptake of CO2 and a likely increase in CH4 lifetime from reduced NO x emissions. Second, the response of O3 to decreased NO x emissions showed significant spatial and temporal variability, due to differing chemical regimes around the world. Finally, the overall response of atmospheric composition to emissions changes is heavily modulated by factors including carbon-cycle feedbacks to CH4 and CO2, background pollutant levels, the timing and location of emissions changes, and climate feedbacks on air quality, such as wildfires and the ozone climate penalty.

A Multiplatform Inversion Estimation of Statewide and Regional Methane Emissions in California during 2014-2016.

California methane (CH4) emissions are quantified for three years from two tower networks and one aircraft campaign. We used backward trajectory simulations and a mesoscale Bayesian inverse model, initialized by three inventories, to achieve the emission quantification. Results show total statewide CH4 emissions of 2.05 ± 0.26 (at 95% confidence) Tg/yr, which is 1.14 to 1.47 times greater than the anthropogenic emission estimates by California Air Resource Board (CARB). Some of differences could be biogenic emissions, superemitter point sources, and other episodic emissions which may not be completely included in the CARB inventory. San Joaquin Valley (SJV) has the largest CH4 emissions (0.94 ± 0.18 Tg/yr), followed by the South Coast Air Basin, the Sacramento Valley, and the San Francisco Bay Area at 0.39 ± 0.18, 0.21 ± 0.04, and 0.16 ± 0.05 Tg/yr, respectively. The dairy and oil/gas production sources in the SJV contribute 0.44 ± 0.36 and 0.22 ± 0.23 Tg CH4/yr, respectively. This study has important policy implications for regulatory programs, as it provides a thorough multiyear evaluation of the emissions inventory using independent atmospheric measurements and investigates the utility of a complementary multiplatform approach in understanding the spatial and temporal patterns of CH4 emissions in the state and identifies opportunities for the expansion and applications of the monitoring network.

Evaluating the effects of climate change on summertime ozone using a relative response factor approach for policymakers.

UNLABELLED: The impact of climate change on surface-level ozone is examined through a multiscale modeling effort that linked global and regional climate models to drive air quality model simulations. Results are quantified in terms of the relative response factor (RRF(E)), which estimates the relative change in peak ozone concentration for a given change in pollutant emissions (the subscript E is added to RRF to remind the reader that the RRF is due to emission changes only). A matrix of model simulations was conducted to examine the individual and combined effects offuture anthropogenic emissions, biogenic emissions, and climate on the RRF(E). For each member in the matrix of simulations the warmest and coolest summers were modeled for the present-day (1995-2004) and future (2045-2054) decades. A climate adjustment factor (CAF(C) or CAF(CB) when biogenic emissions are allowed to change with the future climate) was defined as the ratio of the average daily maximum 8-hr ozone simulated under a future climate to that simulated under the present-day climate, and a climate-adjusted RRF(EC) was calculated (RRF(EC) = RRF(E) x CAF(C)). In general, RRF(EC) > RRF(E), which suggests additional emission controls will be required to achieve the same reduction in ozone that would have been achieved in the absence of climate change. Changes in biogenic emissions generally have a smaller impact on the RRF(E) than does future climate change itself The direction of the biogenic effect appears closely linked to organic-nitrate chemistry and whether ozone formation is limited by volatile organic compounds (VOC) or oxides of nitrogen (NO(x) = NO + NO2). Regions that are generally NO(x) limited show a decrease in ozone and RRF(EC), while VOC-limited regions show an increase in ozone and RRF(EC). Comparing results to a previous study using different climate assumptions and models showed large variability in the CAF(CB). IMPLICATIONS: We present a methodology for adjusting the RRF to account for the influence of climate change on ozone. The findings of this work suggest that in some geographic regions, climate change has the potential to negate decreases in surface ozone concentrations that would otherwise be achieved through ozone mitigation strategies. In regions of high biogenic VOC emissions relative to anthropogenic NO(x) emissions, the impact of climate change is somewhat reduced, while the opposite is true in regions of high anthropogenic NO(x) emissions relative to biogenic VOC emissions. Further, different future climate realizations are shown to impact ozone in different ways.

Photochemical modeling in California with two chemical mechanisms: model intercomparison and response to emission reductions.

An updated version of the Statewide Air Pollution Research Center (SAPRC) chemical mechanism (SAPRC07C) was implemented into the Community Multiscale Air Quality (CMAQ) version 4.6. CMAQ simulations using SAPRC07C and the previously released version, SAPRC99, were performed and compared for an episode during July-August, 2000. Ozone (O3) predictions of the SAPRC07C simulation are generally lower than those of the SAPRC99 simulation in the key areas of central and southern California, especially in areas where modeled concentrations are greater than the federal 8-hr O3 standard of 75 parts per billion (ppb) and/or when the volatile organic compound (VOC)/nitrogen oxides (NOx) ratio is less than 13. The relative changes of ozone production efficiency (OPE) against the VOC/NOx ratio at 46 sites indicate that the OPE is reduced in SAPRC07C compared with SAPRC99 at most sites by as much as approximately 22%. The SAPRC99 and SAPRC07C mechanisms respond similarly to 20% reductions in anthropogenic VOC emissions. The response of the mechanisms to 20% NOx emissions reductions can be grouped into three cases. In case 1, in which both mechanisms show a decrease in daily maximum 8-hr O3 concentration with decreasing NOx emissions, the O3 decrease in SAPRC07C is smaller. In case 2, in which both mechanisms show an increase in O3 with decreasing NOx emissions, the O3 increase is larger in SAPRC07C. In case 3, SAPRC07C simulates an increase in O3 in response to reduced NOx emissions whereas SAPRC99 simulates a decrease in O3 for the same region. As a result, the areas where NOx controls would be disbeneficial are spatially expanded in SAPRC07C. Although the results presented here are valuable for understanding differences in predictions and model response for SAPRC99 and SAPRC07C, the study did not evaluate the impact of mechanism differences in the context of the U.S. Environmental Protection Agency's guidance for using numerical models in demonstrating air quality attainment. Therefore, additional study is required to evaluate the full regulatory implications of upgrading air quality models to SAPRC07.