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In 2016, air pollution from oil & gas (O&G) production in the U.S. resulted in 7,500 (95% CI: 4,500 - 12,000) excess deaths among many other health impacts, valued at $77 billion ($2016 USD) (95% CI: $27 billion - $170 billion). An ambitious methane reduction policy in 2028 would result in 1,400 (820 - 2,300) deaths compared to 2028 business as usual, while other policies would have modest effects. Regions without O&G activity experienced impact from the sector and benefits from emissions reductions. On a per ton basis, the health co-benefits per methane reduction from each policy were ~5x lower than health co-impacts from the whole production sector, since policies only apply to specific O&G production processes. We show that there are still substantial health co-benefits to policies that reduce methane emissions, however the health co-benefits can be enhanced if emissions reduction policies cover more components of O&G production.

Methane emission fluxes were estimated for 71 oil and gas well pads in the western Permian Basin (Delaware Basin), using a mobile laboratory and an inverse Gaussian dispersion method (OTM 33A). Sites with emissions that were below detection limit (BDL) for OTM 33A were recorded and included in the sample. Average emission rate per site was estimated by bootstrapping and by maximum likelihood best log-normal fit. Sites had to be split into "complex" (sites with liquid storage tanks and/or compressors) and "simple" (sites with only wellheads/pump jacks/separators) categories to achieve acceptable log-normal fits. For complex sites, the log-normal fit depends heavily on the number of BDL sites included. As more BDL sites are included, the log-normal distribution fit to the data is falsely widened, overestimating the mean, highlighting the importance of correctly characterizing low end emissions when using log-normal fits. Basin-wide methane emission rates were estimated for the production sector of the New Mexico portion of the Permian and range from ∼520 000 tons per year, TPY (bootstrapping, 95% CI: 300 000-790 000) to ∼610 000 TPY (log-normal fit method, 95% CI: 330 000-1 000 000). These estimates are a factor of 5.5-9.0 times greater than EPA National Emission Inventory (NEI) estimates for the region.

Isoprene carries approximately half of the flux of non-methane volatile organic carbon emitted to the atmosphere by the biosphere. Accurate representation of its oxidation rate and products is essential for quantifying its influence on the abundance of the hydroxyl radical (OH), nitrogen oxide free radicals (NO_x), ozone (O_3), and, via the formation of highly oxygenated compounds, aerosol. We present a review of recent laboratory and theoretical studies of the oxidation pathways of isoprene initiated by addition of OH, O_3, the nitrate radical (NO_3), and the chlorine atom. From this review, a recommendation for a nearly complete gas-phase oxidation mechanism of isoprene and its major products is developed. The mechanism is compiled with the aims of providing an accurate representation of the flow of carbon while allowing quantification of the impact of isoprene emissions on HO_x and NO_x free radical concentrations and of the yields of products known to be involved in condensed-phase processes. Finally, a simplified (reduced) mechanism is developed for use in chemical transport models that retains the essential chemistry required to accurately simulate isoprene oxidation under conditions where it occurs in the atmosphere—above forested regions remote from large NO_x emissions.

Sulfate and secondary organic aerosol (cloud aqSOA) can be chemically formed in cloud water. Model implementation of these processes represents a computational burden due to the large number of microphysical and chemical parameters. Chemical mechanisms have been condensed by reducing the number of chemical parameters. Here, an alternative is presented to reduce the number of microphysical parameters (number of cloud-droplet-size classes). In-cloud mass formation is surface- and volume-dependent due to surface-limited oxidant uptake and/or size-dependent pH. Box and parcel model simulations show that using the effective cloud droplet diameter (proportional to total volume-to-surface ratio) reproduces sulfate and aqSOA formation rates within ≤ 30% as compared to full droplet distributions; other single diameters lead to much greater deviations. This single-class approach reduces computing time significantly and can be included in models when total liquid water content and effective diameter are available.

Hydroxyl radical (OH) oxidation of toluene produces ring-retaining products: cresol and benzaldehyde, and ring-opening products: bicyclic intermediate compounds and epoxides. Here, first- and later-generation OH oxidation products from cresol and benzaldehyde are identified in laboratory chamber experiments. For benzaldehyde, first-generation ring-retaining products are identified, but later-generation products are not detected. For cresol, low-volatility (saturation mass concentration, C* ∼ 3.5 × 104 − 7.7 × 10−3 µg m−3), first- and later-generation ring-retaining products are identified. Subsequent OH addition to the aromatic ring of o-cresol leads to compounds such as hydroxy, dihydroxy, and trihydroxy methyl benzoquinones and dihydroxy, trihydroxy, tetrahydroxy, and pentahydroxy toluenes. These products are detected in the gas phase by chemical ionization mass spectrometry (CIMS) and in the particle phase using offline direct analysis in real-time mass spectrometry (DART-MS). Our data suggest that the yield of trihydroxy toluene from dihydroxy toluene is substantial. While an exact yield cannot be reported as authentic standards are unavailable, we find that a yield for trihydroxy toluene from dihydroxy toluene of ∼ 0.7 (equal to the reported yield of dihydroxy toluene from o-cresol; Olariu et al., 2002) is consistent with experimental results for o-cresol oxidation under low-NO conditions. These results suggest that even though the cresol pathway accounts for only ∼ 20 % of the oxidation products of toluene, it is the source of a significant fraction (∼ 20–40 %) of toluene secondary organic aerosol (SOA) due to the formation of low-volatility products.

Laboratory chambers, invaluable in atmospheric chemistry and aerosol formation studies, are subject to particle and vapor wall deposition, processes that need to be accounted for in order to accurately determine secondary organic aerosol (SOA) mass yields. Although particle wall deposition is reasonably well understood and usually accounted for, vapor wall deposition is less so. The effects of vapor wall deposition on SOA mass yields in chamber experiments can be constrained experimentally by increasing the seed aerosol surface area to promote the preferential condensation of SOA-forming vapors onto seed aerosol. Here, we study the influence of seed aerosol surface area and oxidation rate on SOA formation in α-pinene ozonolysis. The observations are analyzed using a coupled vapor–particle dynamics model to interpret the roles of gas–particle partitioning (quasi-equilibrium vs. kinetically limited SOA growth) and α-pinene oxidation rate in influencing vapor wall deposition. We find that the SOA growth rate and mass yields are independent of seed surface area within the range of seed surface area concentrations used in this study. This behavior arises when the condensation of SOA-forming vapors is dominated by quasi-equilibrium growth. Faster α-pinene oxidation rates and higher SOA mass yields are observed at increasing O3 concentrations for the same initial α-pinene concentration. When the α-pinene oxidation rate increases relative to vapor wall deposition, rapidly produced SOA-forming oxidation products condense more readily onto seed aerosol particles, resulting in higher SOA mass yields. Our results indicate that the extent to which vapor wall deposition affects SOA mass yields depends on the particular volatility organic compound system and can be mitigated through the use of excess oxidant concentrations.

International audience; Abstract. Chemical mechanisms play an important role in simulating the atmospheric chemistry of volatile organic compound oxidation. Comparison of mechanism simulations with laboratory chamber data tests our level of understanding of the prevailing chemistry as well as the dynamic processes occurring in the chamber itself. α-Pinene photooxidation is a well-studied system experimentally, for which detailed chemical mechanisms have been formulated. Here, we present the results of simulating low-NO α-pinene photooxidation experiments conducted in the Caltech chamber with the Generator for Explicit Chemistry and Kinetics of Organics in the Atmosphere (GECKO-A) under varying concentrations of seed particles and OH levels. Unexpectedly, experiments conducted at low and high OH levels yield the same secondary organic aerosol (SOA) growth, whereas GECKO-A predicts greater SOA growth under high OH levels. SOA formation in the chamber is a result of a competition among the rates of gas-phase oxidation to low-volatility products, wall deposition of these products, and condensation into the aerosol phase. Various processes – such as photolysis of condensed-phase products, particle-phase dimerization, and peroxy radical autoxidation – are explored to rationalize the observations. In order to explain the observed similar SOA growth at different OH levels, we conclude that vapor wall loss in the Caltech chamber is likely of order 10−5 s−1, consistent with previous experimental measurements in that chamber. We find that GECKO-A tends to overpredict the contribution to SOA of later-generation oxidation products under high-OH conditions. Moreover, we propose that autoxidation may alternatively resolve some or all of the measurement–model discrepancy, but this hypothesis cannot be confirmed until more explicit mechanisms are established for α-pinene autoxidation. The key role of the interplay among oxidation rate, product volatility, and vapor–wall deposition in chamber experiments is illustrated.

Secondary organic aerosol (SOA) constitutes a major fraction of submicrometer atmospheric particulate matter. Quantitative simulation of SOA within air-quality and climate models--and its resulting impacts--depends on the translation of SOA formation observed in laboratory chambers into robust parameterizations. Worldwide data have been accumulating indicating that model predictions of SOA are substantially lower than ambient observations. Although possible explanations for this mismatch have been advanced, none has addressed the laboratory chamber data themselves. Losses of particles to the walls of chambers are routinely accounted for, but there has been little evaluation of the effects on SOA formation of losses of semivolatile vapors to chamber walls. Here, we experimentally demonstrate that such vapor losses can lead to substantially underestimated SOA formation, by factors as much as 4. Accounting for such losses has the clear potential to bring model predictions and observations of organic aerosol levels into much closer agreement.

Hydroxyl radical (OH) oxidation of toluene produces the ring-retaining products cresol and benzaldehyde, and the ring-opening products bicyclic intermediate compounds and epoxides. Here, first- and later-generation OH oxidation products from cresol and benzaldehyde are identified in laboratory chamber experiments. For benzaldehyde, first-generation ring-retaining products are identified, but later-generation products are not detected. For cresol, low-volatility (saturation mass concentration, C* ~ 3.5 × 104–7.7 × 10−3 μg m−3) first- and later-generation ring-retaining products are identified. Subsequent OH addition to the aromatic ring of o-cresol leads to compounds such as hydroxy, dihydroxy, and trihydroxy methyl benzoquinones and dihydroxy, trihydroxy, tetrahydroxy, and pentahydroxy toluenes. These products are detected in the gas phase by chemical ionization mass spectrometry (CIMS) and in the particle phase using offline direct analysis in real time mass spectrometry (DART-MS). Our data suggest that the yield of trihydroxy toluene from dihydroxy toluene is substantial. While an exact yield cannot be reported as authentic standards are unavailable, we find that a yield for trihydroxy toluene from dihydroxy toluene of ~ 0.7 (equal to the yield of dihydroxy toluene from o-cresol) is consistent with experimental results for o-cresol oxidation under low-NO conditions. These results suggest that even though the cresol pathway accounts for only ~ 20 % of the oxidation products of toluene, it is the source of a significant fraction (~ 20–40 %) of toluene secondary organic aerosol (SOA) due to the formation of low-volatility products.

In order to constrain the effects of vapor–wall deposition on measured secondary organic aerosol (SOA) yields in laboratory chambers, researchers recently varied the seed aerosol surface area in toluene oxidation and observed a clear increase in the SOA yield with increasing seed surface area (Zhang, X.; et al. Proc. Natl. Acad. Sci. U.S.A. 2014, 111, 5802). Using a coupled vapor–particle dynamics model, we examine the extent to which this increase is the result of vapor–wall deposition versus kinetic limitations arising from imperfect accommodation of organic species into the particle phase. We show that a seed surface area dependence of the SOA yield is present only when condensation of vapors onto particles is kinetically limited. The existence of kinetic limitation can be predicted by comparing the characteristic time scales of gas-phase reaction, vapor–wall deposition, and gas–particle equilibration. The gas–particle equilibration time scale depends on the gas–particle accommodation coefficient α_p. Regardless of the extent of kinetic limitation, vapor–wall deposition depresses the SOA yield from that in its absence since vapor molecules that might otherwise condense on particles deposit on the walls. To accurately extrapolate chamber-derived yields to atmospheric conditions, both vapor–wall deposition and kinetic limitations must be taken into account.