Chemistry-driven changes strongly influence climate forcing from vegetation emissions.

Biogenic volatile organic compounds (BVOCs) affect climate via changes to aerosols, aerosol-cloud interactions (ACI), ozone and methane. BVOCs exhibit dependence on climate (causing a feedback) and land use but there remains uncertainty in their net climatic impact. One factor is the description of BVOC chemistry. Here, using the earth-system model UKESM1, we quantify chemistry's influence by comparing the response to doubling BVOC emissions in the pre-industrial with standard and state-of-science chemistry. The net forcing (feedback) is positive: ozone and methane increases and ACI changes outweigh enhanced aerosol scattering. Contrary to prior studies, the ACI response is driven by cloud droplet number concentration (CDNC) reductions from suppression of gas-phase SO2 oxidation. With state-of-science chemistry the feedback is 43% smaller as lower oxidant depletion yields smaller methane increases and CDNC decreases. This illustrates chemistry's significant influence on BVOC's climatic impact and the more complex pathways by which BVOCs influence climate than currently recognised.

Avoiding high ozone pollution in Delhi, India.

Surface ozone is a major pollutant threatening public health, agricultural production and natural ecosystems. While measures to improve air quality in megacities such as Delhi are typically aimed at reducing levels of particulate matter (PM), ozone could become a greater threat if these measures focus on PM alone, as some air pollution mitigation steps can actually lead to an increase in surface ozone. A better understanding of the factors controlling ozone production in Delhi and the impact that PM mitigation measures have on ozone is therefore critical for improving air quality. Here, we combine in situ observations and model analysis to investigate the impact of PM reduction on the non-linear relationship between volatile organic compounds (VOC), nitrogen oxides (NOx) and ozone. In situ measurements of NOx, VOC, and ozone were conducted in Delhi during the APHH-India programme in summer (June) and winter (November) 2018. We observed hourly averaged ozone concentrations in the city of up to 100 ppbv in both seasons. We performed sensitivity simulations with a chemical box model to explore the impacts of PM on the non-linear VOC-NOx-ozone relationship in each season through its effect on aerosol optical depth (AOD). We find that ozone production is limited by VOC in both seasons, and is particularly sensitive to solar radiation in winter. Reducing NOx alone increases ozone, such that a 50% reduction in NOx emissions leads to 10-50% increase in surface ozone. In contrast, reducing VOC emissions can reduce ozone efficiently, such that a 50% reduction in VOC emissions leads to ∼60% reduction in ozone. Reducing PM alone also increases ozone, especially in winter, by reducing its dimming effects on photolysis, such that a 50% reduction in AOD can increase ozone by 25% and it also enhances VOC-limitation. Our results highlight the importance of reducing VOC emissions alongside PM to limit ozone pollution, as well as benefitting control of PM pollution through reducing secondary organic aerosol. This will greatly benefit the health of citizens and the local ecosystem in Delhi, and could have broader application for other megacities characterized by severe PM pollution and VOC-limited ozone production.

Minimal Climate Impacts From Short-Lived Climate Forcers Following Emission Reductions Related to the COVID-19 Pandemic.

We present an assessment of the impacts on atmospheric composition and radiative forcing of short-lived pollutants following a worldwide decrease in anthropogenic activity and emissions comparable to what has occurred in response to the COVID-19 pandemic, using the global composition-climate model United Kingdom Chemistry and Aerosols Model (UKCA). Emission changes reduce tropospheric hydroxyl radical and ozone burdens, increasing methane lifetime. Reduced SO2 emissions and oxidizing capacity lead to a decrease in sulfate aerosol and increase in aerosol size, with accompanying reductions to cloud droplet concentration. However, large reductions in black carbon emissions increase aerosol albedo. Overall, the changes in ozone and aerosol direct effects (neglecting aerosol-cloud interactions which were statistically insignificant but whose response warrants future investigation) yield a radiative forcing of -33 to -78 mWm-2. Upon cessation of emission reductions, the short-lived climate forcers rapidly return to pre-COVID levels; meaning, these changes are unlikely to have lasting impacts on climate assuming emissions return to pre-intervention levels.

On the changes in surface ozone over the twenty-first century: sensitivity to changes in surface temperature and chemical mechanisms.

In this study, we show using a state-of-the-art Earth system model, UKESM1, that emissions and climate scenario depending, there could be large changes in surface ozone by the end of the twenty-first century, with unprecedentedly large increases over South and East Asia. We also show that statistical modelling of the trends in future ozone works well in reproducing the model output between 1900 and 2050. However, beyond 2050, and especially under large climate change scenarios, the statistical model results are in poorer agreement with the fully interactive Earth system model output. This suggests that additional processes occurring in the Earth system model such as changes in the production of ozone at higher temperatures or changes in the influx of ozone from the stratosphere, which are not captured by the statistical model, have a first order impact on the evolution of surface ozone over the twenty-first century. We show in a series of idealized box model simulations, with two different chemical schemes, that changes in temperature lead to diverging responses between the schemes. This points at the chemical mechanisms as being a source of uncertainty in the response of ozone to changes in temperature, and so climate, in the future. This underscores the need for more work to be performed to better understand the response of ozone to changes in temperature and constrain how well this relationship is simulated in models. This article is part of a discussion meeting issue 'Air quality, past present and future'.

Revisiting the mystery of recent stratospheric temperature trends.

Simulated stratospheric temperatures over the period 1979-2016 in models from the Chemistry-Climate Model Initiative (CCMI) are compared with recently updated and extended satellite observations. The multi-model mean global temperature trends over 1979- 2005 are -0.88 ± 0.23, -0.70 ± 0.16, and -0.50 ± 0.12 K decade-1 for the Stratospheric Sounding Unit (SSU) channels 3 (~40-50 km), 2 (~35-45 km), and 1 (~25-35 km), respectively. These are within the uncertainty bounds of the observed temperature trends from two reprocessed satellite datasets. In the lower stratosphere, the multi-model mean trend in global temperature for the Microwave Sounding Unit channel 4 (~13-22 km) is -0.25 ± 0.12 K decade-1 over 1979-2005, consistent with estimates from three versions of this satellite record. The simulated stratospheric temperature trends in CCMI models over 1979-2005 agree with the previous generation of chemistry-climate models. The models and an extended satellite dataset of SSU with the Advanced Microwave Sounding Unit-A show weaker global stratospheric cooling over 1998-2016 compared to the period of intensive ozone depletion (1979-1997). This is due to the reduction in ozone-induced cooling from the slow-down of ozone trends and the onset of ozone recovery since the late 1990s. In summary, the results show much better consistency between simulated and satellite observed stratospheric temperature trends than was reported by Thompson et al. (2012) for the previous versions of the SSU record and chemistry-climate models. The improved agreement mainly comes from updates to the satellite records; the range of simulated trends is comparable to the previous generation of models.

Structure-activity relationship (SAR) for the prediction of gas-phase ozonolysis rate coefficients: an extension towards heteroatomic unsaturated species.

Heteroatomic unsaturated volatile organic compounds (HUVOCs) are common trace components of the atmosphere, yet their diverse chemical behaviour presents difficulties for predicting their oxidation kinetics using structure-activity relationships (SARs). An existing SAR is adapted to help meet this challenge, enabling the prediction of ozonolysis rates with unprecedented accuracy. The new SAR index, x(H), correlates strongly with available literature measurements of ozonolysis rate coefficients (R(2) = 0.87), a database representing 110 species. It was found that capturing the inductive effect rather than the steric effect is of primary importance in predicting the reactivity of these species, which is to be anticipated since HUVOCs can possess a variety of functional groups with a range of electron-withdrawing and donating tendencies. New experimental measurements of ozonolysis rate coefficients were conducted for 1-penten-3-ol, 3-methyl; ethene, 1,1-dimethoxy; E-2-pentenoic acid; E-1,2-dichloroethene; Z-1,2-dichloroethene; trichloroethene; tetrachloroethene; 1-butene, 3-chloro and 2-chloropropene, and were determined to be 5.15 × 10(-18), 4.82 × 10(-16), 3.07 × 10(-18), 8.05 × 10(-20), 4.88 × 10(-21), 6.04 × 10(-22), 1.56 × 10(-24), 2.26 × 10(-18) and 1.13 × 10(-19) cm(3) molecule(-1) s(-1), respectively. The index of the inductive effect, i(H), is compared with other indices of the electron-withdrawing capacity of a substitution, notably the Taft σ* constants and the rate of reaction of a given species with the hydroxyl radical, both of which are expected to be unaffected by steric factors. i(H) correlates strongly in both cases and suggests a universal response by olefinic species towards electrophilic addition.

Structure-activity relationship (SAR) for the gas-phase ozonolysis of aliphatic alkenes and dialkenes.

The configuration of alkyl substituents about carbon-carbon unsaturated bonds exerts a controlling influence on the rate of the ozonolysis reaction. Alkyl substituents can increase (via the inductive effect) and decrease (via the steric effect) the activity of unsaturated bonds, and an accurate description of this information ought to correlate with the ozonolysis rate coefficient. A strong linear relationship is observed (R2 = 0.94), providing the basis of our SAR method. SAR estimates were tested against literature measurements of ozonolysis rate coefficients for 48 aliphatic alkenes and dialkenes, and were found to be accurate to within a factor of 2.3 of the measured value for the entire dataset. This represents a significant improvement over methods reported in the literature, where quoted predictions are at best accurate to within a factor of 6.5. Rates of gas-phase ozonolysis of alkenes and dialkenes can now be predicted with unprecedented accuracy using a simple SAR. The SAR was then validated against new experimental data. Absolute rate coefficients for the gas-phase reaction of ozone with a series of alkenes were determined in a simulation chamber at 295 +/- 2 K and atmospheric pressure by monitoring the loss of ozone in the presence of excess alkene. The rate coefficients (in units of 1 x 10(-18) cm3 molecule(-1) s(-1)) are: 5.12 +/- 0.93 for 1-pentene, 2,3-dimethyl; 406 +/- 49 for 2-pentene, 2-methyl; 151 +/- 5 for (E)-2-hexene, 14.5 +/- 1.0 for 1,5-hexadiene and 20.7 +/- 3.1 for 1,5-hexadiene, 2-methyl. There is good agreement between the experimental and predicted values and the adjustable parameters of the SAR are shown to be insensitive to the inclusion of the new data. The use of the SAR in atmospheric chemical modelling is investigated. Ozonolysis and OH radical rate coefficients are estimated for each alkene and dialkene present in the MCM v3.1. The effects of error within predicted rate coefficients upon modelled concentrations of a number of key species, including O3, OH, HO2, NO and NO2 were rather small and is not in itself a major cause of uncertainty in modelled concentrations.