Adjusting elemental carbon emissions in Northeast Asia using observed surface concentrations of downwind area and simulated contributions

In this study, we developed a practical approach to augment elemental carbon (EC) emissions to improve the reproducibility of the most recent air quality with photochemical grid modeling in support of source-receptor relationship analysis. We demonstrated the usefulness of this approach with a series of simulations for EC concentrations over Northeast Asia during the 2016 Korea-United States Air Quality study. Considering the difficulty of acquiring EC observational data in foreign countries, our approach takes two steps: (1) augmenting upwind EC emissions based on simulated upwind contributions and observational data at a downwind EC monitor considered as the most representative monitor for upwind influences and (2) adjusting downwind EC emissions based on simulated downwind contributions, including the effects of updated upwind emissions from the first step and observational data at the downwind EC monitors. The emission adjustment approach resulted in EC emissions 2.5 times higher than the original emissions in the modeling domain. The EC concentration in the downwind area was observed to be 1.0 μg m-3 during the study period, while the simulated EC concentration was 0.5 μg m-3 before the emission adjustment. After the adjustment, the normalized mean error of the daily mean EC concentration decreased from 48 % to 22 % at ground monitor locations. We found that the EC simulation results were improved at high altitudes, and the contribution of the upwind areas was greater than that of the downwind areas for EC concentrations downwind with or without emission adjustment. This implies that collaborating with upwind regions is essential to alleviate high EC concentrations in downwind areas. The developed emission adjustment approach can be used for any upwind or downwind area when transboundary air pollution mitigation is needed because it provides better reproducibility of the most recent air quality through modeling with improved emission data.

How have Divergent Global Emission Trends Influenced Long-range Transported Ozone to North America?

Several locations across the United States in non-compliance with the national standard for ground-level ozone (O3) are thought to have sizeable influences from distant extra-regional emission sources or natural stratospheric O3, which complicates design of local emission control measures. To quantify the amount of long-range transported O3 (LRT O3), its origin, and change over time, we conduct and analyze detailed sensitivity calculations characterizing the response of O3 to emissions from different source regions across the Northern Hemisphere in conjunction with multi-decadal simulations of tropospheric O3 distributions and changes. Model calculations show that the amount of O3 at any location attributable to sources outside North America varies both spatially and seasonally. On a seasonal-mean basis, during 1990-2010, LRT O3 attributable to international sources steadily increased by 0.06-0.2 ppb yr-1 at locations across the United States and arose from superposition of unequal and contrasting trends in individual source-region contributions, which help inform attribution of the trend evident in O3 measurements. Contributions of emissions from Europe steadily declined through 2010, while those from Asian emissions increased and remained dominant. Steadily rising NOx emissions from international shipping resulted in increasing contributions to LRT O3, comparable to those from Asian emissions in recent years. Central American emissions contribute a significant fraction of LRT O3 in southwestern United States. In addition to the LRT O3 attributable to emissions outside of North America, background O3 across the continental United States is comprised of a sizeable and spatially variable fraction that is of stratospheric origin (29-78%).

Evaluating the Impact of Chemical Complexity and Horizontal Resolution on Tropospheric Ozone Over the Conterminous US With a Global Variable Resolution Chemistry Model

A new configuration of the Community Earth System Model (CESM)/Community Atmosphere Model with full chemistry (CAM-chem) supporting the capability of horizontal mesh refinement through the use of the spectral element (SE) dynamical core is developed and called CESM/CAM-chem-SE. Horizontal mesh refinement in CESM/CAM-chem-SE is unique and novel in that pollutants such as ozone are accurately represented at human exposure relevant scales while also directly including global feedbacks. CESM/CAM-chem-SE with mesh refinement down to ∼14 km over the conterminous US (CONUS) is the beginning of the Multi-Scale Infrastructure for Chemistry and Aerosols (MUSICAv0). Here, MUSICAv0 is evaluated and used to better understand how horizontal resolution and chemical complexity impact ozone and ozone precursors over CONUS as compared to measurements from five aircraft campaigns, which occurred in 2013. This field campaign analysis demonstrates the importance of using finer horizontal resolution to accurately simulate ozone precursors such as nitrogen oxides and carbon monoxide. In general, the impact of using more complex chemistry on ozone and other oxidation products is more pronounced when using finer horizontal resolution where a larger number of chemical regimes are resolved. Large model biases for ozone near the surface remain in the Southeast US as compared to the aircraft observations even with updated chemistry and finer horizontal resolution. This suggests a need for adding the capability of replacing sections of global emission inventories with regional inventories, increasing the vertical resolution in the planetary boundary layer, and reducing model biases in meteorological variables such as temperature and clouds.

Rural vehicle emission as an important driver for the variations of summertime tropospheric ozone in the Beijing-Tianjin-Hebei region during 2014-2019

Tropospheric ozone (O₃) pollution is increasing in the Beijing-Tianjin-Hebei (BTH) region despite a significant decline in atmospheric fine aerosol particles (PM_2.5) in recent years. However, the intrinsic reason for the elevation of the regional O₃ is still unclear. In this study, we analyzed the spatio-temporal variations of tropospheric O₃ and relevant pollutants (PM_2.5, NO₂, and CO) in the BTH region based on monitoring data from the China Ministry of Ecology and Environment during the period of 2014-2019. The results showed that summertime O₃ concentrations were constant in Beijing (BJ, 0.06 µg/(m³•year)) but increased significantly in Tianjin (TJ, 9.09 µg/(m³•year)) and Hebei (HB, 6.06 µg/(m³•year)). Distinct O₃ trends between Beijing and other cities in BTH could not be attributed to the significant decrease in PM_2.5 (from -5.08 to -6.32 µg/(m³•year)) and CO (from -0.053 to -0.090 mg/(m³•year)) because their decreasing rates were approximately the same in all the cities. The relatively stable O₃ concentrations during the investigating period in BJ may be attributed to a faster decreasing rate of NO₂ (BJ: -2.55 µg/(m³•year); TJ: -1.16 µg/(m³•year); HB: -1.34 µg/(m³•year)), indicating that the continued reduction of NO_x will be an effective mitigation strategy for reducing regional O₃ pollution. Significant positive correlations were found between daily maximum 8 hr average (MDA8) O₃ concentrations and vehicle population and highway freight transportation in HB. Therefore, we speculate that the increase in rural NO_x emissions due to the increase in vehicle emissions in the vast rural areas around HB greatly accelerates regional O₃ formation, accounting for the significant increasing trends of O₃ in HB.

Statistical and machine learning methods for evaluating trends in air quality under changing meteorological conditions

Evaluating the influence of anthropogenic-emission changes on air quality requires accounting for the influence of meteorological variability. Statistical methods such as multiple linear regression (MLR) models with basic meteorological variables are often used to remove meteorological variability and estimate trends in measured pollutant concentrations attributable to emission changes. However, the ability of these widely used statistical approaches to correct for meteorological variability remains unknown, limiting their usefulness in the real-world policy evaluations. Here, we quantify the performance of MLR and other quantitative methods using simulations from a chemical transport model, GEOS-Chem, as a synthetic dataset. Focusing on the impacts of anthropogenic-emission changes in the US (2011 to 2017) and China (2013 to 2017) on PM_2.5 and O₃, we show that widely used regression methods do not perform well in correcting for meteorological variability and identifying long-term trends in ambient pollution related to changes in emissions. The estimation errors, characterized as the differences between meteorology-corrected trends and emission-driven trends under constant meteorology scenarios, can be reduced by 30%-42% using a random forest model that incorporates both local- and regional-scale meteorological features. We further design a correction method based on GEOS-Chem simulations with constant-emission input and quantify the degree to which anthropogenic emissions and meteorological influences are inseparable, due to their process-based interactions. We conclude by providing recommendations for evaluating the impacts of anthropogenic-emission changes on air quality using statistical approaches.

Statistical and machine learning methods for evaluating trends in air quality under changing meteorological conditions

Evaluating the influence of anthropogenic-emission changes on air quality requires accounting for the influence of meteorological variability. Statistical methods such as multiple linear regression (MLR) models with basic meteorological variables are often used to remove meteorological variability and estimate trends in measured pollutant concentrations attributable to emission changes. However, the ability of these widely used statistical approaches to correct for meteorological variability remains unknown, limiting their usefulness in the real-world policy evaluations. Here, we quantify the performance of MLR and other quantitative methods using simulations from a chemical transport model, GEOS-Chem, as a synthetic dataset. Focusing on the impacts of anthropogenic-emission changes in the US (2011 to 2017) and China (2013 to 2017) on PM_2.5 and O₃, we show that widely used regression methods do not perform well in correcting for meteorological variability and identifying long-term trends in ambient pollution related to changes in emissions. The estimation errors, characterized as the differences between meteorology-corrected trends and emission-driven trends under constant meteorology scenarios, can be reduced by 30%-42% using a random forest model that incorporates both local- and regional-scale meteorological features. We further design a correction method based on GEOS-Chem simulations with constant-emission input and quantify the degree to which anthropogenic emissions and meteorological influences are inseparable, due to their process-based interactions. We conclude by providing recommendations for evaluating the impacts of anthropogenic-emission changes on air quality using statistical approaches.

Air quality modeling to inform pollution mitigation strategies in a Latin American megacity

Poor air quality disproportionally impacts cities in low- and middle-income countries. In Bogotá, Colombia, a metropolitan area with over 10 million inhabitants, fine particulate matter (PM_2.5) levels regularly exceed air quality guidelines, leading to detrimental effects on health. Although there is public interest to improve the city's air quality, the main sources of PM_2.5 pollution have not been clearly identified and the use of modeling for policy development in Bogotá has been limited. Here, we apply a modeling framework based on the Community Multiscale Air Quality Modeling System (CMAQ) to conduct seasonal simulations of air pollution in Bogotá and reveal the emissions sectors with the largest contributions to PM_2.5. Based on these results, we project and compare the air quality benefits of potential pollution mitigation strategies focused on these sources. The analysis finds that resuspended dust from unpaved roads is the largest local source of PM_2.5 and can contribute over 30% of seasonally-averaged concentration across the city. Vehicles, industrial activity, and unpaved road dust combined are responsible for over 60% of PM_2.5 pollution in Bogotá. A scenario analysis shows that paving roads can lead to PM_2.5 decreases of nearly 10 μg/m³ by 2030 in some areas of the city, but air quality will deteriorate significantly over others in the absence of additional emissions control measures. Mitigation strategies designed to target the sectors with the largest contributions to PM_2.5, including road cleaning systems, controls for industrial point sources, cleaner transportation fuels, and updated vehicle fleets, can largely avert projected increases in concentrations, although the impacts of different approaches vary throughout the city. This study is the first to use a comprehensive model to determine sector contributions to air pollution and inform potential emissions control policies in Bogotá, demonstrating an approach to guide pollution management in developing cities facing comparable challenges.

Air Pollution Health Risk Assessment (AP-HRA), Principles and Applications

Air pollution is a major public health problem. A significant number of epidemiological studies have found a correlation between air quality and a wide variety of adverse health impacts emphasizing a considerable role of air pollution in the disease burden in the general population ranging from subclinical effects to premature death. Health risk assessment of air quality can play a key role at individual and global health promotion and disease prevention levels. The Air Pollution Health Risk Assessment (AP-HRA) forecasts the expected health effect of policies impacting air quality under the various policy, environmental and socio-economic circumstances, making it a key tool for guiding public policy decisions. This paper presents the concept of AP-HRA and offers an outline for the proper conducting of AP-HRA for different scenarios, explaining in broad terms how the health hazards of air emissions and their origins are measured and how air pollution-related impacts are quantified. In this paper, seven widely used AP-HRA tools will be deeply explored, taking into account their spatial resolution, technological factors, pollutants addressed, geographical scale, quantified health effects, method of classification, and operational characteristics. Finally, a comparative analysis of the proposed tools will be conducted, using the SWOT (strengths, weaknesses, opportunities, and threats) method.

Modelling grass pollen levels in Belgium

Biogenic aerosols such as airborne grass pollen affect the public health badly by putting additional distress on people already suffering from cardiovascular and respiratory diseases. In Belgium, daily airborne pollen concentrations are monitored offline at a few sites only, hampering the timely coverage of the country and short-term forecasts. Here we apply the Chemistry Transport Model SILAM to the Belgian territory to model the spatio-temporal airborne grass pollen levels near the surface based on bottom-up inventories of grass pollen emissions updated with the Copernicus land monitoring Service grassland map of 2015. Transport of aerosols in SILAM is driven by ECMWF ERA5 meteorological data. The emitted grass pollen amounts in SILAM are computed by the multiplication of the grass pollen source map with the release rate determined by the seasonal shape production curve during the grass flowering period. The onset and offset of this period follow a location-dependent prescribed calendar days. Here we optimize the grass pollen seasonal start and end in SILAM by comparing a 2008-2018 time series of daily airborne grass pollen concentrations from the Belgian aerobiological surveillance network with the simulations. The effect of the spatial distribution of grass pollen sources is quantified by constructing pollen source-receptor relations using model simulations with varying grass pollen emissions in five areas of the model domain as input. Up to 33% of the airborne grass pollen in one area was transport from others areas inside Belgium. Adjusting the start and end of the grass pollen season improved the model performance substantially by almost doubling the correlation with local observations. By introducing the temporal scaling of the inter-seasonal pollen amounts in the model, an additional R² increase up to 22% was obtained. Further improvements can be made by including more detailed grass pollen sources and more dynamic start and end dates of the pollen season.

Lower air pollution during COVID-19 lock-down: improving models and methods estimating ozone impacts on crops

We suggest that the unprecedented and unintended decrease of emissions of air pollutants during the COVID-19 lock-down in 2020 could lead to declining seasonal ozone concentrations and positive impacts on crop yields. An initial assessment of the potential effects of COVID-19 emission reductions was made using a set of six scenarios that variously assumed annual European and global emission reductions of 30% and 50% for the energy, industry, road transport and international shipping sectors, and 80% for the aviation sector. The greatest ozone reductions during the growing season reached up to 12  ppb over crop growing regions in Asia and up to 6 ppb in North America and Europe for the 50% global reduction scenario. In Europe, ozone responses are more sensitive to emission declines in other continents, international shipping and aviation than to emissions changes within Europe. We demonstrate that for wheat the overall magnitude of ozone precursor emission changes could lead to yield improvements between 2% and 8%. The expected magnitude of ozone precursor emission reductions during the Northern Hemisphere growing season in 2020 presents an opportunity to test and improve crop models and experimentally based exposure response relationships of ozone impacts on crops, under real-world conditions. This article is part of a discussion meeting issue 'Air quality, past present and future'.

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.

Constraining remote oxidation capacity with ATom observations

The global oxidation capacity, defined as the tropospheric mean concentration of the hydroxyl radical (OH), controls the lifetime of reactive trace gases in the atmosphere such as methane and carbon monoxide (CO). Models tend to underestimate the methane lifetime and CO concentrations throughout the troposphere, which is consistent with excessive OH. Approximately half of the oxidation of methane and non-methane volatile organic compounds (VOCs) is thought to occur over the oceans where oxidant chemistry has received little validation due to a lack of observational constraints. We use observations from the first two deployments of the NASA ATom aircraft campaign during July-August 2016 and January-February 2017 to evaluate the oxidation capacity over the remote oceans and its representation by the GEOS-Chem chemical transport model. The model successfully simulates the magnitude and vertical profile of remote OH within the measurement uncertainties. Comparisons against the drivers of OH production (water vapor, ozone, and NO y concentrations, ozone photolysis frequencies) also show minimal bias, with the exception of wintertime NO y . The severe model overestimate of NO y during this period may indicate insufficient wet scavenging and/or missing loss on sea-salt aerosols. Large uncertainties in these processes require further study to improve simulated NO y partitioning and removal in the troposphere, but preliminary tests suggest that their overall impact could marginally reduce the model bias in tropospheric OH. During the ATom-1 deployment, OH reactivity (OHR) below 3 km is significantly enhanced, and this is not captured by the sum of its measured components (cOHRobs) or by the model (cOHRmod). This enhancement could suggest missing reactive VOCs but cannot be explained by a comprehensive simulation of both biotic and abiotic ocean sources of VOCs. Additional sources of VOC reactivity in this region are difficult to reconcile with the full suite of ATom measurement constraints. The model generally reproduces the magnitude and seasonality of cOHRobs but underestimates the contribution of oxygenated VOCs, mainly acetaldehyde, which is severely underestimated throughout the troposphere despite its calculated lifetime of less than a day. Missing model acetaldehyde in previous studies was attributed to measurement uncertainties that have been largely resolved. Observations of peroxyacetic acid (PAA) provide new support for remote levels of acetaldehyde. The underestimate in both model acetaldehyde and PAA is present throughout the year in both hemispheres and peaks during Northern Hemisphere summer. The addition of ocean sources of VOCs in the model increases cOHRmod by 3% to 9% and improves model-measurement agreement for acetaldehyde, particularly in winter, but cannot resolve the model summertime bias. Doing so would require 100 Tg yr-1 of a long-lived unknown precursor throughout the year with significant additional emissions in the Northern Hemisphere summer. Improving the model bias for remote acetaldehyde and PAA is unlikely to fully resolve previously reported model global biases in OH and methane lifetime, suggesting that future work should examine the sources and sinks of OH over land.

Premature mortality related to United States cross-state air pollution

Outdoor air pollution adversely affects human health and is estimated to be responsible for five to ten per cent of the total annual premature mortality in the contiguous United States^1-3. Combustion emissions from a variety of sources, such as power generation or road traffic, make a large contribution to harmful air pollutants such as ozone and fine particulate matter (PM_2.5)⁴. Efforts to mitigate air pollution have focused mainly on the relationship between local emission sources and local air quality². Air quality can also be affected by distant emission sources, however, including emissions from neighbouring federal states^5,6. This cross-state exchange of pollution poses additional regulatory challenges. Here we quantify the exchange of air pollution among the contiguous United States, and assess its impact on premature mortality that is linked to increased human exposure to PM_2.5 and ozone from seven emission sectors for 2005 to 2018. On average, we find that 41 to 53 per cent of air-quality-related premature mortality resulting from a state's emissions occurs outside that state. We also find variations in the cross-state contributions of different emission sectors and chemical species to premature mortality, and changes in these variations over time. Emissions from electric power generation have the greatest cross-state impacts as a fraction of their total impacts, whereas commercial/residential emissions have the smallest. However, reductions in emissions from electric power generation since 2005 have meant that, by 2018, cross-state premature mortality associated with the commercial/residential sector was twice that associated with power generation. In terms of the chemical species emitted, nitrogen oxides and sulfur dioxide emissions caused the most cross-state premature deaths in 2005, but by 2018 primary PM_2.5 emissions led to cross-state premature deaths equal to three times those associated with sulfur dioxide emissions. These reported shifts in emission sectors and emission species that contribute to premature mortality may help to guide improvements to air quality in the contiguous United States.

Representing Organic Compound Oxidation in Chemical Mechanisms for Policy-Relevant Air Quality Models under Background Troposphere Conditions

This intercomparison has taken thirteen chemical mechanisms and compared how they treat VOC oxidation and degradation and its relationship to the photochemical formation of ozone and hydroxyl radicals. Here, we have looked in some detail at the incremental responses of hydroxyl radicals to incremental additions of a range of organic compounds under conditions appropriate to the background atmosphere. Most of the time, with most organic compounds and most chemical mechanisms, incremental additions of an organic compound led to depletion of hydroxyl radical concentrations. The chemical mechanisms studied demonstrated increasingly negative incremental hydroxyl radical reactivities with increasing carbon numbers for the alkanes ethane, propane and n-butane. Hydroxyl radical incremental reactivities for the simple alkenes, ethylene and propylene, were reasonably consistent across the chemical mechanisms studied. However, this consistent representation did not extend to trans but-2-ene, where reactivity estimates spanned a range of a factor of five. Incremental reactivities were reasonably well-defined for isoprene which was encouraging in view of its importance to background tropospheric chemistry. The most serious discrepancies emerging from this study were found with the aromatics toluene and o-xylene, and with the Master Chemical Mechanism and these are discussed in some detail.

Multifractal Detrended Cross-Correlation Analysis of Global Methane and Temperature

Multifractal Detrended Cross-Correlation Analysis (MF-DCCA) was applied to time series of global methane concentrations and remotely-sensed temperature anomalies of the global lower and mid-troposphere, with the purpose of investigating the multifractal characteristics of their cross-correlated time series and examining their interaction in terms of nonlinear analysis. The findings revealed the multifractal nature of the cross-correlated time series and the existence of positive persistence. It was also found that the cross-correlation in the lower troposphere displayed more abundant multifractal characteristics when compared to the mid-troposphere. The source of multifractality in both cases was found to be mainly the dependence of long-range correlations on different fluctuation magnitudes. Multifractal Detrended Fluctuation Analysis (MF-DFA) was also applied to the time series of global methane and global lower and mid-tropospheric temperature anomalies to separately study their multifractal properties. From the results, it was found that the cross-correlated time series exhibit similar multifractal characteristics to the component time series. This could be another sign of the dynamic interaction between the two climate variables.

Mapping ozone source-receptor relationship and apportioning the health impact in the Pearl River Delta region using adjoint sensitivity analysis

While fine particulate matters are decreasing in the Pearl River Delta (PRD) region, the regional ozone (O₃) shows an increasing trend that affects human health, leading to an urgent need for scientific understanding of source-receptor relationship between O₃ and its precursor emissions given the changing background composition. We advanced and applied an adjoint air quality model to map contributions of individual O₃ precursor emission sources [nitrogen oxides (NO_x) and volatile organic compound (VOC)] at each location to annual regional O₃ concentrations and to identify the possible dominant influential pathways of emission sources to O₃ at different spatiotemporal scales. Additionally, we introduced the novel adjoint sensitivity approach to assess the relationship between precursor emissions and O₃-induced premature mortality. Adjoint results show that Shenzhen was a major source contributor to regional O₃ throughout all seasons, of which 49.4% (3.8%) were from its NO_x (VOC) emissions. Local emissions (within PRD) contributed to 83% of the regional O₃ whereas only ~54% of the estimated ~4000 regional O₃-induced premature mortalities. The discrepancy between these two contributions was because O₃-induced mortalities are dependent on not only O₃ concentration, but incident rate and population density. We also found that a city with low O₃-induced mortalities could have significant emission contributions to health impact in the region since the transport pathways could be through transport of local O₃ or through transport of O₃ precursors that form regional O₃ thereafter. It is therefore necessary to formulate emission control policies from both air quality and public health perspectives, and it is also critical to have better understanding of influential pathways of emission sources to O₃.

Spatio-temporal evolution of ozone pollution and its influencing factors in the Beijing-Tianjin-Hebei Urban Agglomeration

Ozone has become a major atmospheric pollutant in China as the pattern of urban energy usage has changed and the number of motor vehicles has grown rapidly. The Beijing-Tianjin-Hebei Urban Agglomeration, also known as the Jing-Jin-Ji Urban Agglomeration (hereafter, JJJUA), with a precarious balance between protecting the ecological environment and sustaining economic development, is challenged by high levels of ozone pollution. Based on ozone observation data from 13 cities in the JJJUA from 2014 to 2017, the spatio-temporal trends in the evolution of ozone pollution and its associated influencing factors were analyzed using Moran's I Index, hot-spot analysis, and Geodetector using ArcGIS and SPSS software. Five key results were obtained. 1) There was an increase in the annual average ozone concentration, for the period 2014-2017. Comparing the 13 prefecture-level cities, ozone pollution in Chengde and Hengshui decreased, while it worsened in the remaining 11 cities. 2) Ozone pollution was worse in spring and summer than in autumn and winter; the peak ozone pollution season was from May to September; the average ozone concentration on workdays was higher than that on non-workdays, showing a counter-weekend effect. 3) Annual average concentrations were high in the central and southern parts of the study region but low in the north. 4) Prominent positive spatial correlations were observed in ozone concentration, with the best correlations shown in summer and autumn; concentrations were high in Baoding and Xingtai but low in Beijing and Chengde. 5) Concentrations of PM₁₀, NO₂, CO, SO₂, and PM_2.5, as well as average wind speed, sunshine duration, evaporation, precipitation, and temperature, all had significant effects on ozone pollution, and interactions between these influencing factors increased it.

Differences in Model Performance and Source Sensitivities for Sulfate Aerosol Resulting from Updates of the Aqueous- and Gas-Phase Oxidation Pathways for a Winter Pollution Episode in Tokyo, Japan

During the Japanese intercomparison study, Japan’s Study for Reference Air Quality Modeling (J-STREAM), it was found that wintertime SO42– concentrations were underestimated over Japan with the Community Multiscale Air Quality (CMAQ) modeling system. Previously, following two development phases, model performance was improved by refining the Fe- and Mn-catalyzed oxidation pathways and by including an additional aqueous-phase pathway via NO2 oxidation. In a third phase, we examined a winter haze period in December 2016, involving a gas-phase oxidation pathway whereby three stabilized Criegee intermediates (SCI) were incorporated into the model. We also included options for a kinetic mass transfer aqueous-phase calculation. According to statistical analysis, simulations compared well with hourly SO42– observations in Tokyo. Source sensitivities for four domestic emission sources (transportation, stationary combustion, fugitive VOC, and agricultural NH3) were investigated. During the haze period, contributions from other sources (overseas and volcanic emissions) dominated, while domestic sources, including transportation and fuel combustion, played a role in enhancing SO42– concentrations around Tokyo Bay. Updating the aqueous phase metal catalyzed and NO2 oxidation pathways lead to increase contribution from other sources, and the additional gas phase SCI chemistry provided a link between fugitive VOC emission and SO42– concentration via changes in O3 concentration.

Global tropospheric effects of aromatic chemistry with the SAPRC-11 mechanism implemented in GEOS-Chem version 9-02

The Goddard Earth Observing System with chemistry (GEOS-Chem) model has been updated with the Statewide Air Pollution Research Center version 11 (SAPRC-11) aromatics chemical mechanism, with the purpose of evaluating global and regional effects of the most abundant aromatics (benzene, toluene, xylenes) on the chemical species important for tropospheric oxidation capacity. The model evaluation based on surface and aircraft observations indicates good agreement for aromatics and ozone. A comparison between scenarios in GEOS-Chem with simplified aromatic chemistry (as in the standard setup, with no ozone formation from related peroxy radicals or recycling of NOx) and with the SAPRC-11 scheme reveals relatively slight changes in ozone, the hydroxyl radical, and nitrogen oxides on a global mean basis (1 %-4 %), although remarkable regional differences (5 %-20 %) exist near the source regions. NO x decreases over the source regions and increases in the remote troposphere, due mainly to more efficient transport of peroxyacetyl nitrate (PAN), which is increased with the SAPRC aromatic chemistry. Model ozone mixing ratios with the updated aromatic chemistry increase by up to 5 ppb (more than 10 %), especially in industrially polluted regions. The ozone change is partly due to the direct influence of aromatic oxidation products on ozone production rates, and in part to the altered spatial distribution of NOx that enhances the tropospheric ozone production efficiency. Improved representation of aromatics is important to simulate the tropospheric oxidation.

Simulating lightning NO production in CMAQv5.2: performance evaluations

This study assesses the impact of the lightning nitric oxide (LNO) production schemes in the Community Multiscale Air Quality (CMAQ) model on ground-level air quality as well as aloft atmospheric chemistry through detailed evaluation of model predictions of nitrogen oxides (NO x ) and ozone (O3) with corresponding observations for the US. For ground-level evaluations, hourly O3 and NO x values from the U.S. EPA Air Quality System (AQS) monitoring network are used to assess the impact of different LNO schemes on model prediction of these species in time and space. Vertical evaluations are performed using ozonesonde and P-3B aircraft measurements during the Deriving Information on Surface Conditions from Column and Vertically Resolved Observations Relevant to Air Quality (DISCOVER-AQ) campaign conducted in the Baltimore- Washington region during July 2011. The impact on wet deposition of nitrate is assessed using measurements from the National Atmospheric Deposition Program's National Trends Network (NADP NTN). Compared with the Base model (without LNO), the impact of LNO on surface O3 varies from region to region depending on the Base model conditions. Overall statistics suggest that for regions where surface O3 mixing ratios are already overestimated, the incorporation of additional NO from lightning generally increased model overestimation of mean daily maximum 8 h (DM8HR) O3 by 1-2 ppb. In regions where surface O3 is underestimated by the Base model, LNO can significantly reduce the underestimation and bring model predictions close to observations. Analysis of vertical profiles reveals that LNO can significantly improve the vertical structure of modeled O3 distributions by reducing underestimation aloft and to a lesser degree decreasing overestimation near the surface. Since the Base model underestimates the wet deposition of nitrate in most regions across the modeling domain with the exception of the Pacific Coast, the inclusion of LNO leads to reduction in biases and errors and an increase in correlation coefficients at almost all the NADP NTN sites. Among the three LNO schemes described in Kang et al. (2019), the hNLDN scheme, which is implemented using hourly observed lightning flash data from National Lightning Detection Network (NLDN), performs best for comparisons with ground-level values, vertical profiles, and wet deposition of nitrate; the mNLDN scheme (the monthly NLDN-based scheme) performed slightly better. However, when observed lightning flash data are not available, the linear regression-based parameterization scheme, pNLDN, provides an improved estimate for nitrate wet deposition compared to the base simulation that does not include LNO.

Modeling regional pollution transport events during KORUS-AQ: Progress and challenges in improving representation of land-atmosphere feedbacks

This study evaluates the impact of assimilating soil moisture data from NASA's Soil Moisture Active Passive (SMAP) on short-term regional weather and air quality modeling in East Asia during the Korea-US Air Quality Study (KORUS-AQ) airborne campaign. SMAP data are assimilated into the Noah land surface model using an ensemble Kalman filter approach in the Land Information System framework, which is semi-coupled with the NASA-Unified Weather Research and Forecasting model with online chemistry (NUWRF-Chem). With SMAP assimilation included, water vapor and carbon monoxide (CO) transport from northern-central China transitional climate zones to South Korea is better represented in NUWRF-Chem during two studied pollution events. Influenced by different synoptic conditions and emission patterns, impact of SMAP assimilation on modeled CO in South Korea is intense (>30 ppbv) during one event and less significant (<8 ppbv) during the other. SMAP assimilation impact on air quality modeling skill is complicated by other error sources such as the chemical initial and boundary conditions (IC/LBC) and emission inputs of NUWRF-Chem. Using a satellite-observation-constrained chemical IC/LBC instead of a free-running, coarser-resolution chemical IC/LBC reduces modeled CO by up to 80 ppbv over South Korea. Consequently, CO performance is improved in the middle-upper troposphere whereas degraded in the lower troposphere. Remaining negative CO biases result largely from the emissions inputs. The advancements in land surface modeling and chemical IC/LBC presented here are expected to benefit future investigations on constraining emissions using observations, which can in turn enable more accurate assessments of SMAP assimilation and chemical IC/LBC impacts.

Ground ozone concentrations over Beijing from 2004 to 2015: Variation patterns, indicative precursors and effects of emission-reduction

Based on ozone observation data from urban stations and the Dingling (DL) background station, we investigated the trend of ozone concentrations in Beijing during 2004-2015. For urban stations, both O₃_1 h and O₃_8 h increased stably with a clear and significant linear pattern and the increase rate was notably higher during the period of May to Sep. Meanwhile, the variation of O₃_1 h and O₃_8 h for the DL station did not demonstrate a regular pattern. During this period, the differences between the diurnal peak of ozone concentrations at the DL background station and urban stations decreased significantly due to the rapid urbanization of Beijing. Furthermore, we examined simultaneous variations of ozone and its precursors during 2015 Grand Military Parade and 2014 APEC meeting and evaluated the performances of different emission-reduction measures during the two specific events. For 2015 Grand Military Parade, emission-reduction measures were implemented 14 days in advance, which led to a notable decrease of ozone concentrations during the Parade period. For 2014 APEC meeting, emission-reduction measures were not implemented in advance, which led to incomplete VOCs reduction and high VOCs/NO_x values, and thus a significant increase of ozone concentrations during the APEC period. The emission-reduction measures during APEC and PARADE periods both slowed down the accumulation and cut down the concentration peaks of ozone. We also analyzed simultaneous concentration variations of ozone and its precursors in long time-series. The results proved that compared with other precursors, NO₂/NO was an effective indicator for ozone concentration in Beijing, especially in urban areas. The findings from this research provide useful reference for better monitoring and managing ozone concentrations in Beijing and other cities through properly designed and implemented emission-reduction measures.

Southeast Atmosphere Studies: learning from model-observation syntheses

Concentrations of atmospheric trace species in the United States have changed dramatically over the past several decades in response to pollution control strategies, shifts in domestic energy policy and economics, and economic development (and resulting emission changes) elsewhere in the world. Reliable projections of the future atmosphere require models to not only accurately describe current atmospheric concentrations, but to do so by representing chemical, physical and biological processes with conceptual and quantitative fidelity. Only through incorporation of the processes controlling emissions and chemical mechanisms that represent the key transformations among reactive molecules can models reliably project the impacts of future policy, energy and climate scenarios. Efforts to properly identify and implement the fundamental and controlling mechanisms in atmospheric models benefit from intensive observation periods, during which collocated measurements of diverse, speciated chemicals in both the gas and condensed phases are obtained. The Southeast Atmosphere Studies (SAS, including SENEX, SOAS, NOMADSS and SEAC4RS) conducted during the summer of 2013 provided an unprecedented opportunity for the atmospheric modeling community to come together to evaluate, diagnose and improve the representation of fundamental climate and air quality processes in models of varying temporal and spatial scales. This paper is aimed at discussing progress in evaluating, diagnosing and improving air quality and climate modeling using comparisons to SAS observations as a guide to thinking about improvements to mechanisms and parameterizations in models. The effort focused primarily on model representation of fundamental atmospheric processes that are essential to the formation of ozone, secondary organic aerosol (SOA) and other trace species in the troposphere, with the ultimate goal of understanding the radiative impacts of these species in the southeast and elsewhere. Here we address questions surrounding four key themes: gas-phase chemistry, aerosol chemistry, regional climate and chemistry interactions, and natural and anthropogenic emissions. We expect this review to serve as a guidance for future modeling efforts.

Two-scale multi-model ensemble: is a hybrid ensemble of opportunity telling us more?

In this study we introduce a hybrid ensemble consisting of air quality models operating at both the global and regional scale. The work is motivated by the fact that these different types of models treat specific portions of the atmospheric spectrum with different levels of detail, and it is hypothesized that their combination can generate an ensemble that performs better than mono-scale ensembles. A detailed analysis of the hybrid ensemble is carried out in the attempt to investigate this hypothesis and determine the real benefit it produces compared to ensembles constructed from only global-scale or only regional-scale models. The study utilizes 13 regional and 7 global models participating in the Hemispheric Transport of Air Pollutants phase 2 (HTAP2)-Air Quality Model Evaluation International Initiative phase 3 (AQMEII3) activity and focuses on surface ozone concentrations over Europe for the year 2010. Observations from 405 monitoring rural stations are used for the evaluation of the ensemble performance. The analysis first compares the modelled and measured power spectra of all models and then assesses the properties of the mono-scale ensembles, particularly their level of redundancy, in order to inform the process of constructing the hybrid ensemble. This study has been conducted in the attempt to identify that the improvements obtained by the hybrid ensemble relative to the mono-scale ensembles can be attributed to its hybrid nature. The improvements are visible in a slight increase of the diversity (4 % for the hourly time series, 10 % for the daily maximum time series) and a smaller improvement of the accuracy compared to diversity. Root mean square error (RMSE) improved by 13-16 % compared to G and by 2-3 % compared to R. Probability of detection (POD) and false-alarm rate (FAR) show a remarkable improvement, with a steep increase in the largest POD values and smallest values of FAR across the concentration ranges. The results show that the optimal set is constructed from an equal number of global and regional models at only 15 % of the stations. This implies that for the majority of the cases the regional-scale set of models governs the ensemble. However given the high degree of redundancy that characterizes the regional-scale models, no further improvement could be expected in the ensemble performance by adding yet more regional models to it. Therefore the improvement obtained with the hybrid set can confidently be attributed to the different nature of the global models. The study strongly reaffirms the importance of an in-depth inspection of any ensemble of opportunity in order to extract the maximum amount of information and to have full control over the data used in the construction of the ensemble.

Impacts of different characterizations of large-scale background on simulated regional-scale ozone over the continental United States

This study analyzes simulated regional-scale ozone burdens both near the surface and aloft, estimates process contributions to these burdens, and calculates the sensitivity of the simulated regional-scale ozone burden to several key model inputs with a particular emphasis on boundary conditions derived from hemispheric or global-scale models. The Community Multiscale Air Quality (CMAQ) model simulations supporting this analysis were performed over the continental US for the year 2010 within the context of the Air Quality Model Evaluation International Initiative (AQMEII) and Task Force on Hemispheric Transport of Air Pollution (TF-HTAP) activities. CMAQ process analysis (PA) results highlight the dominant role of horizontal and vertical advection on the ozone burden in the mid-to-upper troposphere and lower stratosphere. Vertical mixing, including mixing by convective clouds, couples fluctuations in free-tropospheric ozone to ozone in lower layers. Hypothetical bounding scenarios were performed to quantify the effects of emissions, boundary conditions, and ozone dry deposition on the simulated ozone burden. Analysis of these simulations confirms that the characterization of ozone outside the regional-scale modeling domain can have a profound impact on simulated regional-scale ozone. This was further investigated by using data from four hemispheric or global modeling systems (Chemistry - Integrated Forecasting Model (C-IFS), CMAQ extended for hemispheric applications (H-CMAQ), the Goddard Earth Observing System model coupled to chemistry (GEOS-Chem), and AM3) to derive alternate boundary conditions for the regional-scale CMAQ simulations. The regional-scale CMAQ simulations using these four different boundary conditions showed that the largest ozone abundance in the upper layers was simulated when using boundary conditions from GEOS-Chem, followed by the simulations using C-IFS, AM3, and H-CMAQ boundary conditions, consistent with the analysis of the ozone fields from the global models along the CMAQ boundaries. Using boundary conditions from AM3 yielded higher springtime ozone columns burdens in the middle and lower troposphere compared to boundary conditions from the other models. For surface ozone, the differences between the AM3-driven CMAQ simulations and the CMAQ simulations driven by other large-scale models are especially pronounced during spring and winter where they can reach more than 10 ppb for seasonal mean ozone mixing ratios and as much as 15 ppb for domain-averaged daily maximum 8 h average ozone on individual days. In contrast, the differences between the C-IFS-, GEOS-Chem-, and H-CMAQ-driven regional-scale CMAQ simulations are typically smaller. Comparing simulated sur face ozone mixing ratios to observations and computing seasonal and regional model performance statistics revealed that boundary conditions can have a substantial impact on model performance. Further analysis showed that boundary conditions can affect model performance across the entire range of the observed distribution, although the impacts tend to be lower during summer and for the very highest observed percentiles. The results are discussed in the context of future model development and analysis opportunities.

Tropospheric ozone assessment report: Global ozone metrics for climate change, human health, and crop/ecosystem research

Assessment of spatial and temporal variation in the impacts of ozone on human health, vegetation, and climate requires appropriate metrics. A key component of the Tropospheric Ozone Assessment Report (TOAR) is the consistent calculation of these metrics at thousands of monitoring sites globally. Investigating temporal trends in these metrics required that the same statistical methods be applied across these ozone monitoring sites. The nonparametric Mann-Kendall test (for significant trends) and the Theil-Sen estimator (for estimating the magnitude of trend) were selected to provide robust methods across all sites. This paper provides the scientific underpinnings necessary to better understand the implications of and rationale for selecting a specific TOAR metric for assessing spatial and temporal variation in ozone for a particular impact. The rationale and underlying research evidence that influence the derivation of specific metrics are given. The form of 25 metrics (4 for model-measurement comparison, 5 for characterization of ozone in the free troposphere, 11 for human health impacts, and 5 for vegetation impacts) are described. Finally, this study categorizes health and vegetation exposure metrics based on the extent to which they are determined only by the highest hourly ozone levels, or by a wider range of values. The magnitude of the metrics is influenced by both the distribution of hourly average ozone concentrations at a site location, and the extent to which a particular metric is determined by relatively low, moderate, and high hourly ozone levels. Hence, for the same ozone time series, changes in the distribution of ozone concentrations can result in different changes in the magnitude and direction of trends for different metrics. Thus, dissimilar conclusions about the effect of changes in the drivers of ozone variability (e.g., precursor emissions) on health and vegetation exposure can result from the selection of different metrics.

HTAP2 multi-model estimates of premature human mortality due to intercontinental transport of air pollution and emission sectors

Ambient air pollution from ozone and fine particulate matter is associated with premature mortality. As emissions from one continent influence air quality over others, changes in emissions can also influence human health on other continents. We estimate global air pollution-related premature mortality from exposure to PM_2.5 and ozone, and the avoided deaths from 20% anthropogenic emission reductions from six source regions, North America (NAM), Europe (EUR), South Asia (SAS), East Asia (EAS), Russia/Belarus/Ukraine (RBU) and the Middle East (MDE), three global emission sectors, Power and Industry (PIN), Ground Transportation (TRN) and Residential (RES) and one global domain (GLO), using an ensemble of global chemical transport model simulations coordinated by the second phase of the Task Force on Hemispheric Transport of Air Pollution (TF-HTAP2), and epidemiologically-derived concentration-response functions. We build on results from previous studies of the TF-HTAP by using improved atmospheric models driven by new estimates of 2010 anthropogenic emissions (excluding methane), with more source and receptor regions, new consideration of source sector impacts, and new epidemiological mortality functions. We estimate 290,000 (95% CI: 30,000, 600,000) premature O₃-related deaths and 2.8 million (0.5 million, 4.6 million) PM_2.5-related premature deaths globally for the baseline year 2010. While 20% emission reductions from one region generally lead to more avoided deaths within the source region than outside, reducing emissions from MDE and RBU can avoid more O₃-related deaths outside of these regions than within, and reducing MDE emissions also avoids more PM_2.5-related deaths outside of MDE than within. Our findings that most avoided O₃-related deaths from emission reductions in NAM and EUR occur outside of those regions contrast with those of previous studies, while estimates of PM_2.5-related deaths from NAM, EUR, SAS and EAS emission reductions agree well. In addition, EUR, MDE and RBU have more avoided O₃-related deaths from reducing foreign emissions than from domestic reductions. For six regional emission reductions, the total avoided extra-regional mortality is estimated as 6,000 (-3,400, 15,500) deaths/year and 25,100 (8,200, 35,800) deaths/year through changes in O₃ and PM_2.5, respectively. Interregional transport of air pollutants leads to more deaths through changes in PM_2.5 than in O₃, even though O₃ is transported more on interregional scales, since PM_2.5 has a stronger influence on mortality. For NAM and EUR, our estimates of avoided mortality from regional and extra-regional emission reductions are comparable to those estimated by regional models for these same experiments. In sectoral emission reductions, TRN emissions account for the greatest fraction (26-53% of global emission reduction) of O₃-related premature deaths in most regions, in agreement with previous studies, except for EAS (58%) and RBU (38%) where PIN emissions dominate. In contrast, PIN emission reductions have the greatest fraction (38-78% of global emission reduction) of PM_2.5-related deaths in most regions, except for SAS (45%) where RES emission dominates, which differs with previous studies in which RES emissions dominate global health impacts. The spread of air pollutant concentration changes across models contributes most to the overall uncertainty in estimated avoided deaths, highlighting the uncertainty in results based on a single model. Despite uncertainties, the health benefits of reduced intercontinental air pollution transport suggest that international cooperation may be desirable to mitigate pollution transported over long distances.

Influence of anthropogenic emissions and boundary conditions on multi-model simulations of major air pollutants over Europe and North America in the framework of AQMEII3

In the framework of the third phase of the Air Quality Model Evaluation International Initiative (AQMEII3), and as contribution to the second phase of the Hemispheric Transport of Air Pollution (HTAP2) activities for Europe and North America, the impacts of a 20 % decrease of global and regional anthropogenic emissions on surface air pollutant levels in 2010 are simulated by an international community of regional-scale air quality modeling groups, using different state-of-the-art chemistry and transport models (CTMs). The emission perturbations at the global level, as well as over the HTAP2-defined regions of Europe, North America and East Asia, are first simulated by the global Composition Integrated Forecasting System (C-IFS) model from European Centre for Medium-Range Weather Forecasts (ECMWF), which provides boundary conditions to the various regional CTMs participating in AQMEII3. On top of the perturbed boundary conditions, the regional CTMs used the same set of perturbed emissions within the regional domain for the different perturbation scenarios that introduce a 20 % reduction of anthropogenic emissions globally as well as over the HTAP2-defined regions of Europe, North America and East Asia. Results show that the largest impacts over both domains are simulated in response to the global emission perturbation, mainly due to the impact of domestic emission reductions. The responses of NO2, SO2 and PM concentrations to a 20 % anthropogenic emission reduction are almost linear (~ 20 % decrease) within the global perturbation scenario with, however, large differences in the geographical distribution of the effect. NO2, CO and SO2 levels are strongly affected over the emission hot spots. O3 levels generally decrease in all scenarios by up to ~ 1 % over Europe, with increases over the hot spot regions, in particular in the Benelux region, by an increase up to ~ 6 % due to the reduced effect of NOx titration. O3 daily maximum of 8 h running average decreases in all scenarios over Europe, by up to ~ 1 %. Over the North American domain, the central-to-eastern part and the western coast of the US experience the largest response to emission perturbations. Similar but slightly smaller responses are found when domestic emissions are reduced. The impact of intercontinental transport is relatively small over both domains, however, still noticeable particularly close to the boundaries. The impact is noticeable up to a few percent, for the western parts of the North American domain in response to the emission reductions over East Asia. O3 daily maximum of 8 h running average decreases in all scenarios over north Europe by up to ~ 5 %. Much larger reductions are calculated over North America compared to Europe. In addition, values of the Response to Extra-Regional Emission Reductions (RERER) metric have been calculated in order to quantify the differences in the strengths of nonlocal source contributions to different species among the different models. We found large RERER values for O3 (~ 0.8) over both Europe and North America, indicating a large contribution from non-local sources, while for other pollutants including particles, low RERER values reflect a predominant control by local sources. A distinct seasonal variation in the local vs. non-local contributions has been found for both O3 and PM2.5, particularly reflecting the springtime long-range transport to both continents.

Scientific assessment of background ozone over the U.S.: Implications for air quality management

Ozone (O3) is a key air pollutant that is produced from precursor emissions and has adverse impacts on human health and ecosystems. In the U.S., the Clean Air Act (CAA) regulates O3 levels to protect public health and welfare, but unraveling the origins of surface O3 is complicated by the presence of contributions from multiple sources including background sources like stratospheric transport, wildfies, biogenic precursors, and international anthropogenic pollution, in addition to U.S. anthropogenic sources. In this report, we consider more than 100 published studies and assess current knowledge on the spatial and temporal distribution, trends, and sources of background O3 over the continental U.S., and evaluate how it inflattainment of the air quality standards. We conclude that spring and summer seasonal mean U.S. background O3 (USB O3), or O3 formed from natural sources plus anthropogenic sources in countries outside the U.S., is greatest at high elevation locations in the western U.S., with monthly mean maximum daily 8-hour average (MDA8) mole fractions approaching 50 parts per billion (ppb) and annual 4th highest MDA8s exceeding 60 ppb, at some locations. At lower elevation sites, e.g., along the West and East Coasts, seasonal mean MDA8 USB O3 is in the range of 20-40 ppb, with generally smaller contributions on the highest O3 days. The uncertainty in U.S. background O3 is around ±10 ppb for seasonal mean values and higher for individual days. Noncontrollable O3 sources, such as stratospheric intrusions or precursors from wildfires, can make significant contributions to O3 on some days, but it is challenging to quantify accurately these contributions. We recommend enhanced routine observations, focused fi studies, process-oriented modeling studies, and greater emphasis on the complex photochemistry in smoke plumes as key steps to reduce the uncertainty associated with background O3 in the U.S.

Volatile organic compounds (VOCs) source profiles of on-road vehicle emissions in China

Volatile Organic Compounds (VOCs) source profiles of on-road vehicles were widely studied as their critical roles in VOCs source apportionment and abatement measures in megacities. Studies of VOCs source profiles from on-road motor vehicles from 2001 to 2016 were summarized in this study, with a focus on the comparisons among different studies and the potential impact of different factors. Generally, non-methane hydrocarbons dominated the source profile of on-road vehicle emissions. Carbonyls, potential important components of vehicle emission, were seldom considered in VOCs emissions of vehicles in the past and should be paid more attention to in further study. VOCs source profiles showed some variations among different studies, and 6 factors were extracted and studied due to their impact to VOCs source profile of on-road vehicles. Vehicle types, being dependent on engine types, and fuel types were two dominant factors impacting VOCs sources profiles of vehicles. In comparison, impacts of ignitions, driving conditions and accumulated mileage were mainly due to their influence on the combustion efficiency. An opening and interactive database of VOCs from vehicle emissions was critically essential in future, and mechanisms of sharing and inputting relative research results should be formed to encourage researchers join the database establishment. Correspondingly, detailed quality assurance and quality control procedures were also very important, which included the information of test vehicles and test methods as detailed as possible. Based on the community above, a better uncertainty analysis could be carried out for the VOCs emissions profiles, which was critically important to understand the VOCs emission characteristics of the vehicle emissions.

Strong Dependence of U.S. Summertime Air Quality on the Decadal Variability of Atlantic Sea Surface Temperatures

We find that summertime air quality in the eastern U.S. displays strong dependence on North Atlantic sea surface temperatures, resulting from large-scale ocean-atmosphere interactions. Using observations, reanalysis data sets, and climate model simulations, we further identify a multidecadal variability in surface air quality driven by the Atlantic Multidecadal Oscillation (AMO). In one-half cycle (~35 years) of the AMO from cold to warm phase, summertime maximum daily 8 h ozone concentrations increase by 1-4 ppbv and PM2.5 concentrations increase by 0.3-1.0 μg m-3 over much of the east. These air quality changes are related to warmer, drier, and more stagnant weather in the AMO warm phase, together with anomalous circulation patterns at the surface and aloft. If the AMO shifts to the cold phase in future years, it could partly offset the climate penalty on U.S. air quality brought by global warming, an effect which should be considered in long-term air quality planning.

Chemical Mechanisms and Their Applications in the Goddard Earth Observing System (GEOS) Earth System Model

NASA's Goddard Earth Observing System (GEOS) Earth System Model (ESM) is a modular, general circulation model (GCM), and data assimilation system (DAS) that is used to simulate and study the coupled dynamics, physics, chemistry, and biology of our planet. GEOS is developed by the Global Modeling and Assimilation Office (GMAO) at NASA Goddard Space Flight Center. It generates near-real-time analyzed data products, reanalyses, and weather and seasonal forecasts to support research targeted to understanding interactions among Earth System processes. For chemistry, our efforts are focused on ozone and its influence on the state of the atmosphere and oceans, and on trace gas data assimilation and global forecasting at mesoscale discretization. Several chemistry and aerosol modules are coupled to the GCM, which enables GEOS to address topics pertinent to NASA's Earth Science Mission. This paper describes the atmospheric chemistry components of GEOS and provides an overview of its Earth System Modeling Framework (ESMF)-based software infrastructure, which promotes a rich spectrum of feedbacks that influence circulation and climate, and impact human and ecosystem health. We detail how GEOS allows model users to select chemical mechanisms and emission scenarios at run time, establish the extent to which the aerosol and chemical components communicate, and decide whether either or both influence the radiative transfer calculations. A variety of resolutions facilitates research on spatial and temporal scales relevant to problems ranging from hourly changes in air quality to trace gas trends in a changing climate. Samples of recent GEOS chemistry applications are provided.

The effects of forest canopy shading and turbulence on boundary layer ozone

The chemistry of the Earth's atmosphere close to the surface is known to be strongly influenced by vegetation. However, two critical aspects of the forest environment have been neglected in the description of the large-scale influence of forests on air pollution: the reduction of photolysis reaction rates and the modification of vertical transport due to the presence of foliage. Here we show that foliage shading and foliage-modified vertical diffusion have a profound influence on atmospheric chemistry, both at the Earth's surface and extending throughout the atmospheric boundary layer. The absence of these processes in three-dimensional models may account for 59–72% of the positive bias in North American surface ozone forecasts, and up to 97% of the bias in forested regions within the continent. These processes are shown to have similar or greater influence on surface ozone levels as climate change and current emissions policy scenario simulations.

Fully quantifying the influence of vegetation on atmospheric chemistry remains challenging. Here, the authors show that forest canopy shading and turbulence significantly modify air pollution throughout the atmospheric boundary layer, and must be taken into account in models of the atmosphere.

Impact of intercontinental pollution transport on North American ozone air pollution: an HTAP phase 2 multi-model study

The recent update on the US National Ambient Air Quality Standards (NAAQS) of the ground-level ozone (O₃/ can benefit from a better understanding of its source contributions in different US regions during recent years. In the Hemispheric Transport of Air Pollution experiment phase 1 (HTAP1), various global models were used to determine the O₃ source-receptor (SR) relationships among three continents in the Northern Hemisphere in 2001. In support of the HTAP phase 2 (HTAP2) experiment that studies more recent years and involves higher-resolution global models and regional models' participation, we conduct a number of regional-scale Sulfur Transport and dEposition Model (STEM) air quality base and sensitivity simulations over North America during May-June 2010. STEM's top and lateral chemical boundary conditions were downscaled from three global chemical transport models' (i.e., GEOS-Chem, RAQMS, and ECMWF C-IFS) base and sensitivity simulations in which the East Asian (EAS) anthropogenic emissions were reduced by 20 %. The mean differences between STEM surface O₃ sensitivities to the emission changes and its corresponding boundary condition model's are smaller than those among its boundary condition models, in terms of the regional/period-mean (<10 %) and the spatial distributions. An additional STEM simulation was performed in which the boundary conditions were downscaled from a RAQMS (Realtime Air Quality Modeling System) simulation without EAS anthropogenic emissions. The scalability of O₃ sensitivities to the size of the emission perturbation is spatially varying, and the full (i.e., based on a 100% emission reduction) source contribution obtained from linearly scaling the North American mean O₃ sensitivities to a 20% reduction in the EAS anthropogenic emissions may be underestimated by at least 10 %. The three boundary condition models' mean O₃ sensitivities to the 20% EAS emission perturbations are ~8% (May-June 2010)/~11% (2010 annual) lower than those estimated by eight global models, and the multi-model ensemble estimates are higher than the HTAP1 reported 2001 conditions. GEOS-Chem sensitivities indicate that the EAS anthropogenic NO _x emissions matter more than the other EAS O₃ precursors to the North American O₃, qualitatively consistent with previous adjoint sensitivity calculations. In addition to the analyses on large spatial-temporal scales relative to the HTAP1, we also show results on subcontinental and event scales that are more relevant to the US air quality management. The EAS pollution impacts are weaker during observed O₃ exceedances than on all days in most US regions except over some high-terrain western US rural/remote areas. Satellite O₃ (TES, JPL-IASI, and AIRS) and carbon monoxide (TES and AIRS) products, along with surface measurements and model calculations, show that during certain episodes stratospheric O₃ intrusions and the transported EAS pollution influenced O₃ in the western and the eastern US differently. Free-running (i.e., without chemical data assimilation) global models underpredicted the transported background O₃ during these episodes, posing difficulties for STEM to accurately simulate the surface O₃ and its source contribution. Although we effectively improved the modeled O₃ by incorporating satellite O₃ (OMI and MLS) and evaluated the quality of the HTAP2 emission inventory with the Royal Netherlands Meteorological Institute-Ozone Monitoring Instrument (KNMI-OMI) nitrogen dioxide, using observations to evaluate and improve O₃ source attribution still remains to be further explored.

Long-Lived Species Enhance Summertime Attribution of North American Ozone to Upwind Sources

Ground-level ozone (O₃), harmful to most living things, is produced from both domestic and foreign emissions of anthropogenic precursors. Previous estimates of the linkage from distant sources rely on the sensitivity approach (i.e., modeling the change of ozone concentrations that result from modifying precursor emissions) as well as the tagging approach (i.e., tracking ozone produced from specific O₃ precursors emitted from one region). Here, for the first time, we tag all O₃ precursors (i.e., nitrogen oxides (NO_x), carbon monoxide (CO), and volatile organic compounds (VOCs)) from East Asia and explicitly track their physicochemical evolution without perturbing the nonlinear O₃ chemistry. We show that, even in summer, when intercontinental influence on ozone has typically been found to be weakest, nearly 3 parts per billion by volume (ppbv) seasonal average surface O₃ over North America can be attributed to East Asian anthropogenic emissions, compared with 0.7 ppbv using the sensitivity approach and 0.5 ppbv by tagging reactive nitrogen oxides. Considering the acute effects of O₃ exposure, approximately 670 cardiovascular and 300 respiratory premature mortalities within North America could be attributed to East Asia. CO and longer-lived VOCs, largely overlooked in previous studies, extend the influence of regional ozone precursors emissions and, thus, greatly enhance O₃ attribution to source region.

Air Pollution and Climate Change Effects on Allergies in the Anthropocene: Abundance, Interaction, and Modification of Allergens and Adjuvants

Air pollution and climate change are potential drivers for the increasing burden of allergic diseases. The molecular mechanisms by which air pollutants and climate parameters may influence allergic diseases, however, are complex and elusive. This article provides an overview of physical, chemical and biological interactions between air pollution, climate change, allergens, adjuvants and the immune system, addressing how these interactions may promote the development of allergies. We reviewed and synthesized key findings from atmospheric, climate, and biomedical research. The current state of knowledge, open questions, and future research perspectives are outlined and discussed. The Anthropocene, as the present era of globally pervasive anthropogenic influence on planet Earth and, thus, on the human environment, is characterized by a strong increase of carbon dioxide, ozone, nitrogen oxides, and combustion- or traffic-related particulate matter in the atmosphere. These environmental factors can enhance the abundance and induce chemical modifications of allergens, increase oxidative stress in the human body, and skew the immune system toward allergic reactions. In particular, air pollutants can act as adjuvants and alter the immunogenicity of allergenic proteins, while climate change affects the atmospheric abundance and human exposure to bioaerosols and aeroallergens. To fully understand and effectively mitigate the adverse effects of air pollution and climate change on allergic diseases, several challenges remain to be resolved. Among these are the identification and quantification of immunochemical reaction pathways involving allergens and adjuvants under relevant environmental and physiological conditions.

Burden of Disease from Rising Coal-Fired Power Plant Emissions in Southeast Asia

Southeast Asia has a very high population density and is on a fast track to economic development, with most of the growth in electricity demand currently projected to be met by coal. From a detailed analysis of coal-fired power plants presently planned or under construction in Southeast Asia, we project in a business-as-usual scenario that emissions from coal in the region will triple to 2.6 Tg a^-1 SO₂ and 2.6 Tg a^-1 NO_x by 2030, with the largest increases occurring in Indonesia and Vietnam. Simulations with the GEOS-Chem chemical transport model show large resulting increases in surface air pollution, up to 11 μg m^-3 for annual mean fine particulate matter (PM_2.5) in northern Vietnam and up to 15 ppb for seasonal maximum 1 h ozone in Indonesia. We estimate 19 880 (11 400-28 400) excess deaths per year from Southeast Asian coal emissions at present, increasing to 69 660 (40 080-126 710) by 2030. 9000 of these excess deaths in 2030 are in China. As Chinese emissions from coal decline in coming decades, transboundary pollution influence from rising coal emissions in Southeast Asia may become an increasing issue.

Extending the Community Multiscale Air Quality (CMAQ) Modeling System to Hemispheric Scales: Overview of Process Considerations and Initial Applications

The Community Multiscale Air Quality (CMAQ) modeling system is extended to simulate ozone, particulate matter, and related precursor distributions throughout the Northern Hemisphere. Modelled processes were examined and enhanced to suitably represent the extended space and time scales for such applications. Hemispheric scale simulations with CMAQ and the Weather Research and Forecasting (WRF) model are performed for multiple years. Model capabilities for a range of applications including episodic long-range pollutant transport, long-term trends in air pollution across the Northern Hemisphere, and air pollution-climate interactions are evaluated through detailed comparison with available surface, aloft, and remotely sensed observations. The expansion of CMAQ to simulate the hemispheric scales provides a framework to examine interactions between atmospheric processes occurring at various spatial and temporal scales with physical, chemical, and dynamical consistency.

Regional and Hemispheric Influences on Temporal Variability in Baseline Carbon Monoxide and Ozone over the Northeast US

Interannual variability in baseline carbon monoxide (CO) and ozone (O3), defined as mixing ratios under minimal influence of recent and local emissions, was studied for seven rural sites in the Northeast US over 2001 - 2010. Annual baseline CO exhibited statistically significant decreasing trends (-4.3 - -2.3 ppbv yr-1), while baseline O3 did not display trends at any site. In examining the data by season, wintertime and springtime baseline CO at the two highest sites (1.5 km and 2 km asl) did not experience significant trends. Decadal increasing trends (~2.55 ppbv yr-1) were found in springtime and wintertime baseline O3 in southern New Hampshire, which was associated with anthropogenic NOx emission reductions from the urban corridor. Biomass burning emissions impacted summertime baseline CO with ~38% variability from wildfire emissions in Russia and ~22% from Canada at five sites and impacted baseline O3 at the two high elevation sites only with ~27% variability from wildfires in both Russia and Canada. The Arctic Oscillation was negatively correlated with summertime baseline O3, while the North Atlantic Oscillation was positively correlated with springtime baseline O3. This study suggested that anthropogenic and biomass burning emissions, and meteorological conditions were important factors working together to determine baseline O3 and CO in the Northeast U.S. during the 2000s.

Nitrate radicals and biogenic volatile organic compounds: oxidation, mechanisms, and organic aerosol

Oxidation of biogenic volatile organic compounds (BVOC) by the nitrate radical (NO₃) represents one of the important interactions between anthropogenic emissions related to combustion and natural emissions from the biosphere. This interaction has been recognized for more than 3 decades, during which time a large body of research has emerged from laboratory, field, and modeling studies. NO₃-BVOC reactions influence air quality, climate and visibility through regional and global budgets for reactive nitrogen (particularly organic nitrates), ozone, and organic aerosol. Despite its long history of research and the significance of this topic in atmospheric chemistry, a number of important uncertainties remain. These include an incomplete understanding of the rates, mechanisms, and organic aerosol yields for NO₃-BVOC reactions, lack of constraints on the role of heterogeneous oxidative processes associated with the NO₃ radical, the difficulty of characterizing the spatial distributions of BVOC and NO₃ within the poorly mixed nocturnal atmosphere, and the challenge of constructing appropriate boundary layer schemes and non-photochemical mechanisms for use in state-of-the-art chemical transport and chemistry-climate models. This review is the result of a workshop of the same title held at the Georgia Institute of Technology in June 2015. The first half of the review summarizes the current literature on NO₃-BVOC chemistry, with a particular focus on recent advances in instrumentation and models, and in organic nitrate and secondary organic aerosol (SOA) formation chemistry. Building on this current understanding, the second half of the review outlines impacts of NO₃-BVOC chemistry on air quality and climate, and suggests critical research needs to better constrain this interaction to improve the predictive capabilities of atmospheric models.

Survey of Ambient Air Pollution Health Risk Assessment Tools

Designing air quality policies that improve public health can benefit from information about air pollution health risks and impacts, which include respiratory and cardiovascular diseases and premature death. Several computer-based tools help automate air pollution health impact assessments and are being used for a variety of contexts. Expanding information gathered for a May 2014 World Health Organization expert meeting, we survey 12 multinational air pollution health impact assessment tools, categorize them according to key technical and operational characteristics, and identify limitations and challenges. Key characteristics include spatial resolution, pollutants and health effect outcomes evaluated, and method for characterizing population exposure, as well as tool format, accessibility, complexity, and degree of peer review and application in policy contexts. While many of the tools use common data sources for concentration-response associations, population, and baseline mortality rates, they vary in the exposure information source, format, and degree of technical complexity. We find that there is an important tradeoff between technical refinement and accessibility for a broad range of applications. Analysts should apply tools that provide the appropriate geographic scope, resolution, and maximum degree of technical rigor for the intended assessment, within resources constraints. A systematic intercomparison of the tools' inputs, assumptions, calculations, and results would be helpful to determine the appropriateness of each for different types of assessment. Future work would benefit from accounting for multiple uncertainty sources and integrating ambient air pollution health impact assessment tools with those addressing other related health risks (e.g., smoking, indoor pollution, climate change, vehicle accidents, physical activity).

Impact of increasing heat waves on U.S. ozone episodes in the 2050s: Results from a multimodel analysis using extreme value theory

We develop a statistical model using extreme value theory to estimate the 2000-2050 changes in ozone episodes across the United States. We model the relationships between daily maximum temperature (Tmax) and maximum daily 8-hour average (MDA8) ozone in May-September over 2003-2012 using a Point Process (PP) model. At ~20% of the sites, a marked decrease in the ozone-temperature slope occurs at high temperatures, defined as ozone suppression. The PP model sometimes fails to capture ozone-Tmax relationships, and so we refit the ozone-Tmax slope using logistic regression and a Generalized Pareto Distribution model. We then apply the resulting hybrid-EVT model to projections of Tmax from an ensemble of downscaled climate models. Assuming constant anthropogenic emissions at the present level, we find an average increase of 2.3 days a-1 in ozone episodes (> 75 ppbv) across the United States by the 2050s, with a change of +3-9 days a-1 at many sites.

China's air pollution reduction efforts may result in an increase in surface ozone levels in highly polluted areas

China, as a fast growing fossil-fuel-based economy, experiences increasing levels of air pollution. To tackle air pollution, China has taken the first steps by setting emission-reduction targets for nitrogen oxides (NO x ) and sulphur dioxide (SO2) in the 11th and 12th Five Year Plans. This paper uses two models-the Energy-Environment-Economy Model at the Global level (E3MG) and the global Chemistry Transport Model pTOMCAT-to test the effects of these policies. If the policy targets are met, then the maximum values of 32 % and 45 % reductions below 'business as usual' in the monthly mean NO x and SO2 concentrations, respectively, will be achieved in 2015. However, a decrease in NO x concentrations in some highly polluted areas of East, North-East and South-East China can lead to up to a 10% increase in the monthly mean concentrations in surface ozone in 2015. Our study demonstrates an urgent need for the more detailed analysis of the impacts and designs of air pollution reduction guidelines for China.

Photochemical Aging of α-pinene and β-pinene Secondary Organic Aerosol formed from Nitrate Radical Oxidation

The nitrate radical (NO3) is the dominant nighttime oxidant in most urban and rural environments and reacts rapidly with biogenic volatile organic compounds to form secondary organic aerosol (SOA) and organic nitrates (ON). Here, we study the formation of SOA and ON from the NO3 oxidation of two monoterpenes (α-pinene and β-pinene) and investigate how they evolve during photochemical aging. High SOA mass loadings are produced in the NO3+β-pinene reaction, during which we detected 41 highly oxygenated gas- and particle-phase ON possessing 4 to 9 oxygen atoms. The fraction of particle-phase ON in the β-pinene SOA remains fairly constant during photochemical aging. In contrast to the NO3+β-pinene reaction, low SOA mass loadings are produced during the NO3+α-pinene reaction, during which only 5 highly oxygenated gas- and particle-phase ON are detected. The majority of the particle-phase ON evaporates from the α-pinene SOA during photochemical aging, thus exhibiting a drastically different behavior from that of β-pinene SOA. Our results indicate that nighttime ON formed by NO3+monoterpene chemistry can serve as either permanent or temporary NOx sinks depending on the monoterpene precursor.

Why do Models Overestimate Surface Ozone in the Southeastern United States?

Ozone pollution in the Southeast US involves complex chemistry driven by emissions of anthropogenic nitrogen oxide radicals (NO_x ≡ NO + NO₂) and biogenic isoprene. Model estimates of surface ozone concentrations tend to be biased high in the region and this is of concern for designing effective emission control strategies to meet air quality standards. We use detailed chemical observations from the SEAC⁴RS aircraft campaign in August and September 2013, interpreted with the GEOS-Chem chemical transport model at 0.25°×0.3125° horizontal resolution, to better understand the factors controlling surface ozone in the Southeast US. We find that the National Emission Inventory (NEI) for NO_x from the US Environmental Protection Agency (EPA) is too high. This finding is based on SEAC⁴RS observations of NO_x and its oxidation products, surface network observations of nitrate wet deposition fluxes, and OMI satellite observations of tropospheric NO₂ columns. Our results indicate that NEI NO_x emissions from mobile and industrial sources must be reduced by 30-60%, dependent on the assumption of the contribution by soil NO_x emissions. Upper tropospheric NO₂ from lightning makes a large contribution to satellite observations of tropospheric NO₂ that must be accounted for when using these data to estimate surface NO_x emissions. We find that only half of isoprene oxidation proceeds by the high-NO_x pathway to produce ozone; this fraction is only moderately sensitive to changes in NO_x emissions because isoprene and NO_x emissions are spatially segregated. GEOS-Chem with reduced NO_x emissions provides an unbiased simulation of ozone observations from the aircraft, and reproduces the observed ozone production efficiency in the boundary layer as derived from a regression of ozone and NO_x oxidation products. However, the model is still biased high by 8±13 ppb relative to observed surface ozone in the Southeast US. Ozonesondes launched during midday hours show a 7 ppb ozone decrease from 1.5 km to the surface that GEOS-Chem does not capture. This bias may reflect a combination of excessive vertical mixing and net ozone production in the model boundary layer.

Atmospheric transport of ozone between Southern and Eastern Asia

This study describes the effect of pollution transport between East Asia and South Asia on tropospheric ozone (O3) using model results from the Task Force on Hemispheric Transport of Air Pollution (TF HTAP). Ensemble mean O3 concentrations are evaluated against satellite-data and ground observations of surface O3 at four stations in India. Although modeled surface O3 concentrations are 1020ppb higher than those observed, the relative magnitude of the seasonal cycle of O3 is reproduced well. Using 20% reductions in regional anthropogenic emissions, we quantify the seasonal variations in pollution transport between East Asia and South Asia. While there is only a difference of 0.05 to 0.1ppb in the magnitudes of the regional contributions from one region to the other, O3 from East Asian sources affects the most densely populated parts of South Asia while Southern Asian sources only partly affect the populated parts of East Asia. We show that emission changes over East Asia between 2000 and 2010 had a larger impact on populated parts of South Asia than vice versa. This study will help inform future decisions on emission control policy over these regions.

Impact of Biofuel Poplar Cultivation on Ground-Level Ozone and Premature Human Mortality Depends on Cultivar Selection and Planting Location

Isoprene and other volatile organic compounds emitted from vegetation play a key role in governing the formation of ground-level ozone. Emission rates of such compounds depend critically on the plant species. The cultivation of biofuel feedstocks will contribute to future land use change, altering the distribution of plant species and hence the magnitude and distribution of emissions. Here we use relationships between biomass yield and isoprene emissions derived from experimental data for 29 commercially available poplar hybrids to assess the impact that the large-scale cultivation of poplar for use as a biofuel feedstock will have on air quality, specifically ground-level ozone concentrations, in Europe. We show that the increases in ground-level ozone across Europe will increase the number of premature deaths attributable to ozone pollution each year by up to 6%. Substantial crop losses (up to ∼9 Mt y(-1) of wheat and maize) are also projected. We further demonstrate that these impacts are strongly dependent on the location of the poplar plantations, due to the prevailing meteorology, the population density, and the dominant crop type of the region. Our findings indicate the need for a concerted and centralized decision-making process that considers all aspects of future land use change in Europe, and not just the effect on greenhouse gas emissions.