Zhen Liu

The atmospheric water resources (AWR) in China have evident regional characteristics. In order to scientifically and rationally exploit the AWR in different regions of China, we divided China into seven regions based on the ERA‐5, the CloudSat data, and so on. Such characteristics as water vapour, cloud characteristics, cloud water resources (CWR), precipitation efficiency of hydrometeors (PEh), and the exploitation potential of CWR were studied in this article. Some results in summer are shown. (a) There were relatively more precipitation, richer water vapour, stronger water vapour transport and convergence, more cloud covers, and relatively larger zones of rich total column cloud water content in China. Therefore, it is of important significance to study AWR in summer in China. (b) In respect of single‐layer clouds, low clouds were in the majority over the Tibetan Plateau (TP) and the southwest China (SW), medium clouds were predominant over the northern regions, and high clouds existed more over the central region (CR) and the southeast China (SE). The liquid water content (LWC) at each height of cloud was less than 800 mg·m⁻³ and decreased gradually with the increase in height in China. The convective development heights, the LWC at each altitude, and the frequencies of less LWCs over the northern regions were lower than those over the southern regions. The ice water content (IWC) at each height of cloud was less than 250 mg·m⁻³, and more than 96% of them were less than 100 mg·m⁻³. (c) CWR over the northeast China (NE), north China (NC), and CR were relatively rich, but with relatively low PEh, so there was relatively higher exploitation potential of CWR in these regions, followed by the northwest China (NW) and TP, and there was still some exploitation potential of CWR in SE and SW.

Quantifying methane (CH₄) emissions from the oil and natural gas (O/NG) production sector is an important regulatory challenge in the United States. In this study, we conduct a set of inversion calculations using different methods to quantify lognormal distributed CH₄ surface fluxes in the Haynesville‐Bossier O/NG production basin in Texas and Louisiana, combining three statistical cost functions, four meteorological configurations, and two days of aircraft measurements from a 2013 field campaign. We aggregate our posterior flux estimates to derive our best estimate of the basin‐wide CH₄ emissions, 76 metric tons/hr, with a 95% highest density interval of 51–104 metric tons/hr, in agreement with previous estimates using mass balance and eddy covariance approaches with the same aircraft measurements. Our inversion estimate of basin‐wide CH₄ emissions is 133% (89%–182%, 95% highest density interval) of a gridded Environmental Protection Agency's inventory for 2012, and the largest discrepancies between our study and this inventory are located in the northeastern quadrant of the basin containing active unconventional O/NG wells. Our inversion approach provides a new spatiotemporal characterization of CH₄ emissions in this O/NG production region and shows the usefulness of inverse modeling for improving O/NG CH₄ emission estimates.

Intercontinental ozone (O₃) transport extends the geographic range of O₃ air pollution impacts and makes local air pollution management more difficult. Phase 3 of the Air Quality Modeling Evaluation International Initiative (AQMEII-3) is examining the contribution of intercontinental transport to regional air quality by applying regional-scale atmospheric models jointly with global models. We investigate methods for tracing O₃ from global models within regional models. The CAMx photochemical grid model was used to track contributions from boundary condition (BC) O₃ over a North American modeling domain for calendar year 2010 using a built-in tracer module called RTCMC. RTCMC can track BC contributions using chemically reactive tracers and also using inert tracers in which deposition is the only sink for O₃. Lack of O₃ destruction chemistry in the inert tracer approach leads to overestimation biases that can exceed 10 ppb. The flexibility of RTCMC also allows tracking O₃ contributions made by groups of vertical BC layers. The largest BC contributions to seasonal average daily maximum 8 h averages (MDA8) of O₃ over the US are found to be from the mid-troposphere (over 40 ppb) with small contributions (a few ppb) from the upper troposphere–lower stratosphere. Contributions from the lower troposphere are shown to not penetrate very far inland. Higher contributions in the western than the eastern US, reaching an average of 57 ppb in Denver for the 30 days with highest MDA8 O₃ in 2010, present a significant challenge to air quality management approaches based solely on local or US-wide emission reductions. The substantial BC contribution to MDA8 O₃ in the Intermountain West means regional models are particularly sensitive to any biases and errors in the BCs. A sensitivity simulation with reduced BC O₃ in response to 20 % lower emissions in Asia found a near-linear relationship between the BC O₃ changes and surface O₃ changes in the western US in all seasons and across the US in fall and winter. However, the surface O₃ decreases are small: below 1 ppb in spring and below 0.5 ppb in other seasons.

We quantify methane (CH₄) emissions in California's San Joaquin Valley (SJV) by using 4 days of aircraft measurements from a field campaign during May–June 2010 together with a Bayesian inversion method and a mass balance approach. For the inversion estimates, we use the FLEXible PARTicle dispersion model (FLEXPART) to establish the source‐receptor relationship between sampled atmospheric concentrations and surface fluxes. Our prior CH₄ emission estimates are from the California Greenhouse Gas Emissions Measurements (CALGEM) inventory. We use three meteorological configurations to drive FLEXPART and subsequently construct three inversions to analyze the final optimized estimates and their uncertainty (one standard deviation). We conduct May and June inversions independently and derive similar total CH₄ emission estimates for the SJV: 135 ± 28 Mg/h in May and 135 ± 19 Mg/h in June. The inversion result is 1.7 times higher than the prior estimate from CALGEM. We also use an independent mass balance approach to estimate CH₄ emissions in the northern SJV for one flight when meteorological conditions allowed. The mass balance estimate provides a confirmation of our inversion results, and these two independent estimates of the total CH₄ emissions in the SJV are consistent with previous studies. In this study, we provide optimized CH₄ emissions estimates at 0.1° horizontal resolution. Using independent spatial information on major CH₄ sources, we estimate that livestock contribute 75–77% and oil/gas production contributes 15–18% of the total CH₄ emissions in the SJV. Livestock explain most of the discrepancies between the prior and the optimized emissions from our inversion.

Photochemical grid models are addressing an increasing variety of air quality related issues, yet procedures and metrics used to evaluate their performance remain inconsistent. This impacts the ability to place results in quantitative context relative to other models and applications, and to inform the user and affected community of model uncertainties and weaknesses. More consistent evaluations can serve to drive improvements in the modeling process as major weaknesses are identified and addressed. The large number of North American photochemical modeling studies published in the peer-reviewed literature over the past decade affords a rich data set from which to update previously established quantitative performance “benchmarks” for ozone and particulate matter (PM) concentrations. Here we exploit this information to develop new ozone and PM benchmarks (goals and criteria) for three well-established statistical metrics over spatial scales ranging from urban to regional and over temporal scales ranging from episodic to seasonal. We also recommend additional evaluation procedures, statistical metrics, and graphical methods for good practice. While we primarily address modeling and regulatory settings in the United States, these recommendations are relevant to any such applications of state-of-the-science photochemical models. Our primary objective is to promote quantitatively consistent evaluations across different applications, scales, models, model inputs, and configurations. The purpose of benchmarks is to understand how good or poor the results are relative to historical model applications of similar nature and to guide model performance improvements prior to using results for policy assessments. To that end, it also remains critical to evaluate all aspects of the model via diagnostic and dynamic methods. A second objective is to establish a means to assess model performance changes in the future. Statistical metrics and benchmarks need to be revisited periodically as model performance and the characteristics of air quality change in the future. Implications: We address inconsistent procedures and metrics used to evaluate photochemical model performance, recommend a specific set of statistical metrics, and develop updated quantitative performance benchmarks for those metrics. We promote quantitatively consistent evaluations across different applications, scales, models, inputs, and configurations, thereby (1) improving the user’s ability to quantitatively place results in context and guide model improvements, and (2) better informing users, regulators, and stakeholders of model uncertainties and weaknesses prior to using results for policy assessments. While we primarily address U.S. modeling and regulatory settings, these recommendations are relevant to any such applications of state-of-the-science photochemical models.

Radiocarbon in CO₂ (¹⁴CO₂) measurements can aid in discriminating between fast (5–10 years) cycling of C between the atmosphere and the terrestrial biosphere due to the ¹⁴C disequilibrium between atmospheric and terrestrial C. However, ¹⁴CO₂ in the atmosphere is typically much more strongly impacted by fossil fuel emissions of CO₂, and, thus, observations often provide little additional constraints on respiratory flux estimates at regional scales. Here we describe a data set of ¹⁴CO₂ observations from a tall tower in northern Wisconsin (USA) where fossil fuel influence is far enough removed that during the summer months, the biospheric component of the ¹⁴CO₂ budget dominates. We find that the terrestrial biosphere is responsible for a significant contribution to ¹⁴CO₂ that is 2–3 times higher than predicted by the Carnegie‐Ames‐Stanford approach terrestrial ecosystem model for observations made in 2010. This likely includes a substantial contribution from the North American boreal ecoregion, but transported biospheric emissions from outside the model domain cannot be ruled out. The ¹⁴CO₂ enhancement also appears somewhat decreased in observations made over subsequent years, suggesting that 2010 may be anomalous. With these caveats acknowledged, we discuss the implications of the observation/model comparison in terms of possible systematic biases in the model versus short‐term anomalies in the observations. Going forward, this isotopic signal could be exploited as an important indicator to better constrain both the long‐term carbon balance of terrestrial ecosystems and the short‐term impact of disturbance‐based loss of carbon to the atmosphere.

Agricultural ammonia (NH₃) emissions are highly uncertain, with high spatiotemporal variability and a lack of widespread in situ measurements. Regional NH₃ emission estimates using mass balance or emission ratio approaches are uncertain due to variable NH₃ sources and sinks as well as unknown plume correlations with other dairy source tracers. We characterize the spatial distributions of NH₃ and methane (CH₄) dairy plumes using in situ surface and airborne measurements in the Tulare dairy feedlot region of the San Joaquin Valley, California, during the NASA Deriving Information on Surface conditions from Column and Vertically Resolved Observations Relevant to Air Quality 2013 field campaign. Surface NH₃ and CH₄ mixing ratios exhibit large variability with maxima localized downwind of individual dairy feedlots. The geometric mean NH₃:CH₄ enhancement ratio derived from surface measurements is 0.15 ± 0.03 ppmv ppmv⁻¹. Individual dairy feedlots with spatially distinct NH₃ and CH₄ source pathways led to statistically significant correlations between NH₃ and CH₄ in 68% of the 69 downwind plumes sampled. At longer sampling distances, the NH₃:CH₄ enhancement ratio decreases 20–30%, suggesting the potential for NH₃ deposition as a loss term for plumes within a few kilometers downwind of feedlots. Aircraft boundary layer transect measurements directly above surface mobile measurements in the dairy region show comparable gradients and geometric mean enhancement ratios within measurement uncertainties, even when including NH₃ partitioning to submicron particles. Individual NH₃ and CH₄ plumes sampled at close proximity where losses are minimal are not necessarily correlated due to lack of mixing and distinct source pathways. Our analyses have important implications for constraining NH₃ sink and plume variability influences on regional NH₃ emission estimates and for improving NH₃ emission inventory spatial allocations.

Methane (CH₄) is the primary component of natural gas and has a larger global warming potential than CO₂. Recent top‐down studies based on observations showed CH₄ emissions in California's South Coast Air Basin (SoCAB) were greater than those expected from population‐apportioned bottom‐up state inventories. In this study, we quantify CH₄ emissions with an advanced mesoscale inverse modeling system at a resolution of 8 km × 8 km, using aircraft measurements in the SoCAB during the 2010 Nexus of Air Quality and Climate Change campaign to constrain the inversion. To simulate atmospheric transport, we use the FLEXible PARTicle‐Weather Research and Forecasting (FLEXPART‐WRF) Lagrangian particle dispersion model driven by three configurations of the Weather Research and Forecasting (WRF) mesoscale model. We determine surface fluxes of CH₄ using a Bayesian least squares method in a four‐dimensional inversion. Simulated CH₄ concentrations with the posterior emission inventory achieve much better correlations with the measurements (R² = 0.7) than using the prior inventory (U.S. Environmental Protection Agency's National Emission Inventory 2005, R² = 0.5). The emission estimates for CH₄ in the posterior, 46.3 ± 9.2 Mg CH₄/h, are consistent with published observation‐based estimates. Changes in the spatial distribution of CH₄ emissions in the SoCAB between the prior and posterior inventories are discussed. Missing or underestimated emissions from dairies, the oil/gas system, and landfills in the SoCAB seem to explain the differences between the prior and posterior inventories. We estimate that dairies contributed 5.9 ± 1.7 Mg CH₄/h and the two sectors of oil and gas industries (production and downstream) and landfills together contributed 39.6 ± 8.1 Mg CH₄/h in the SoCAB.

Current knowledge of daytime HONO sources remains incomplete. A large missing daytime HONO source has been found in many places around the world, including polluted regions in China. Conventional understanding and recent studies attributed this missing source mainly to ground surface processes or gas-phase chemistry, while assuming aerosols to be an insignificant media for HONO production. We analyze in situ observations of HONO and its precursors at an urban site in Beijing, China, and report an apparent dependence of the missing HONO source strength on aerosol surface area and solar ultraviolet radiation. Based on extensive correlation analysis and process-modeling, we propose that the rapid daytime HONO production in Beijing can be explained by enhanced hydrolytic disproportionation of NO₂ on aqueous aerosol surfaces due to catalysis by dicarboxylic acid anions. The combination of high abundance of NO₂, aromatic hydrocarbons, and aerosols over broad regions in China likely leads to elevated HONO levels, rapid OH production, and enhanced oxidizing capacity on a regional basis. Our findings call for attention to aerosols as a media for daytime heterogeneous HONO production in polluted regions like Beijing. This study also highlights the complex and uncertain heterogeneous chemistry in China, which merits future efforts of reconciling regional modeling and laboratory experiments, in order to understand and mitigate the regional particulate and O₃ pollutions over China.