Reducing Soil-Emitted Nitrous Acid as a Feasible Strategy for Tackling Ozone Pollution

Severe ozone (O3) pollution has been a major air quality issue and affects environmental sustainability in China. Conventional mitigation strategies focusing on reducing volatile organic compounds and nitrogen oxides (NOx) remain complex and challenging. Here, through field flux measurements and laboratory simulations, we observe substantial nitrous acid (HONO) emissions (FHONO) enhanced by nitrogen fertilizer application at an agricultural site. The observed FHONO significantly improves model performance in predicting atmospheric HONO and leads to regional O3 increases by 37%. We also demonstrate the significant potential of nitrification inhibitors in reducing emissions of reactive nitrogen, including HONO and NOx, by as much as 90%, as well as greenhouse gases like nitrous oxide by up to 60%. Our findings introduce a feasible concept for mitigating O3 pollution: reducing soil HONO emissions. Hence, this study has important implications for policy decisions related to the control of O3 pollution and climate change.

Nitrogen Isotopes Reveal High NOx Emissions from Arid Agricultural Soils in the Salton Sea Air Basin

Air quality management commonly aims to mitigate emissions of oxides of nitrogen (NO x ) from combustion, reducing ozone and particulate matter pollution. Despite such efforts, regulations have recently proven ineffective in rural areas like the Salton Sea Air Basin of Southern California, which routinely violates air quality standards. With $2 billion in annual agricultural sales and low population density, air quality in the region is likely influenced by year-round farming. We conducted NO x source apportionment using nitrogen stable isotopes of ambient NO 2 , which indicate a substantial contribution of soil-emitted NO x . The soil source strength was estimated based on the mean δ 15 N-NO x from each emission category in the California Air Resources Board's NO x inventory. Our annual average soil emission estimate for the air basin was 11.4 ± 4 tons/d, representing ~ 30% of the extant NO x inventory, 10× larger than the state's inventory. Therefore, the impact of soil NO x in agricultural regions must be re-evaluated.

Atmospheric HONO emissions in China: Unraveling the spatiotemporal patterns and their key influencing factors

Nitrous acid (HONO) can be photolyzed to produce hydroxyl radicals (OH) in the atmosphere. OH plays a critical role in the formation of secondary pollutants like ozone (O3) and secondary organic aerosols (SOA) via various oxidation reactions. Despite the abundance of recent HONO studies, research on national HONO emissions in China remains relatively limited. Therefore, this study employed a "wetting-drying" model and bottom-up approach to develop a high-resolution gridded inventory of HONO emissions for mainland China using multiple data. We used the Monte Carlo method to estimate the uncertainty in HONO emissions. In addition, the primary sources of HONO emissions were identified and their spatiotemporal distribution and main influencing factors were studied. The results indicated that the total HONO emissions in mainland China in 2016 were 0.77 Tg N (R50: 0.28-1.42 Tg N), with soil (0.42 Tg N) and fertilization (0.26 Tg N) as the primary sources, jointly contributing to over 87% of the total. Notably, the North China Plain (NCP) had the highest HONO emission density (3.51 kg N/ha/yr). Seasonal HONO emissions followed the order: summer (0.38 kg N/ha) > spring (0.19 kg N/ha) > autumn (0.17 kg N/ha) > winter (0.06 kg N/ha). Moreover, HONO emissions were strongly correlated with fertilization, cropland, temperature, and precipitation. This study provides vital scientific groundwork for the atmospheric nitrogen cycle and the formation of secondary pollutants.

Changing Responses of PM2.5 and Ozone to Source Emissions in the Yangtze River Delta Using the Adjoint Model

China's industrial restructuring and pollution controls have altered the contributions of individual sources to varying air quality over the past decade. We used the GEOS-Chem adjoint model and investigated the changing sensitivities of PM2.5 and ozone (O3) to multiple species and sources from 2010 to 2020 in the central Yangtze River Delta (YRDC), the largest economic region in China. Controlling primary particles and SO2 from industrial and residential sectors dominated PM2.5 decline, and reducing CO from multiple sources and ≥C3 alkenes from vehicles restrained O3. The chemical regime of O3 formation became less VOC-limited, attributable to continuous NOX abatement for specific sources, including power plants, industrial combustion, cement production, and off-road traffic. Regional transport was found to be increasingly influential on PM2.5. To further improve air quality, management of agricultural activities to reduce NH3 is essential for alleviating PM2.5 pollution, while controlling aromatics, alkenes, and alkanes from industry and gasoline vehicles is effective for O3. Reducing the level of NOX from nearby industrial combustion and transportation is helpful for both species. Our findings reveal the complexity of coordinating control of PM2.5 and O3 pollution in a fast-developing region and support science-based policymaking for other regions with similar air pollution problems.

Coupled atmospheric chemistry, radiation, and dynamics of an exoplanet generate self-sustained oscillations

Nonlinearity in photochemical systems is known to allow self-sustained oscillations, but they have received little attention in studies of planetary atmospheres. Here, we present a unique, self-oscillatory solution for ozone chemistry of an exoplanet from a numerical simulation using a fully coupled, three-dimensional (3D) atmospheric chemistry-radiation-dynamics model. Forced with nonvarying stellar insolation and emission flux of nitric oxide (NO), atmospheric ozone abundance oscillates by a factor of thirty over a multidecadal timescale. As such self-oscillations can only occur with biological nitrogen fixation contributing to NO emission, we propose that they are a unique class of biosignature. The resulting temporal variability in the atmospheric spectrum is potentially observable. Our results underscore the importance of revisiting the spectra of exoplanets over multidecadal timescales to characterizing the atmospheric chemistry of exoplanets and searching for exoplanet biosignatures. There are also profound implications for comparative planetology and the evolution of the atmospheres of terrestrial planets in the solar system and beyond. Fully coupled, 3D atmospheric chemistry-radiation-dynamics models can reveal new phenomena that may not exist in one-dimensional models, and hence, they are powerful tools for future planetary atmospheric research.

Impacts of local soil and vehicle NOx emissions on ground-level NO2 concentrations on a university campus in the city of Shenyang, China

Nitrogen dioxide (NO2) is a ubiquitous atmospheric pollutant, and fossil fuel combustion is generally considered its predominant source in and around urban areas. As the total nitrogen deposition is high over here, soil NOx emissions from urban green space might also be an important local source of ground-level NO2. In this study, Willems badge samplers were employed to monitor the spatial and seasonal variations of 2-week mean atmospheric NO2 concentrations at a height of 1.7 m on an urban campus in Northeast China from November 2020 to December 2021. We found considerable small-scale spatial variations of ground-level NO2 concentrations on the campus during the growing season, with local soil NOx emissions as the main driver. According to its linear correlation with green space coverage, the increment in ground-level NO2 concentration was partitioned into two components, with one ascribed to the local soil source (referred to as NO2-Isoil) and the other the local vehicle source (NO2-Ivehicle). NO2-Isoil generally reached a maximum (as high as 25.6 μg/m3) during early spring, while its ratio to the background value generally reached a maximum (could be >1) during late spring and could reach 0.52 to 0.92 during summer. Therefore, soil NOx emissions were an important source of ground-level NO2 on the campus, with the contribution even higher than those of other anthropogenic sources during late spring. Even with light traffic on the campus, NO2-Ivehicle could reach 0.48 times the background value at a site with high frequencies of warm starts.

Summertime tropospheric ozone source apportionment study in the Madrid region (Spain)

The design of emission abatement measures to effectively reduce high ground-level ozone (O3) concentrations in urban areas is very complex. In addition to the strongly non-linear chemistry of this secondary pollutant, precursors can be released by a variety of sources in different regions, and locally produced O3 is mixed with that transported from the regional or continental scales. All of these processes depend also on the specific meteorological conditions and topography of the study area. Consequently, high-resolution comprehensive modeling tools are needed to understand the drivers of photochemical pollution and to assess the potential of local strategies to reduce adverse impacts from high tropospheric O3 levels. In this study, we apply the Integrated Source Apportionment Method (ISAM) implemented in the Community Multiscale Air Quality (CMAQ v5.3.2) model to investigate the origin of summertime O3 in the Madrid region (Spain). Consistent with previous studies, our results confirm that O3 levels are dominated by non-local contributions, representing around 70 % of mean values across the region. Nonetheless, precursors emitted by local sources, mainly road traffic, play a more important role during O3 peaks, with contributions as high as 25 ppb. The potential impact of local measures is higher under unfavorable meteorological conditions associated with regional accumulation patterns. These findings suggest that this modeling system may be used in the future to simulate the potential outcomes of specific emission abatement measures to prevent high-O3 episodes in the Madrid metropolitan area.

Data-driven estimation of nitric oxide emissions from global soils based on dominant vegetation covers

Soils are a major source of global nitric oxide (NO) emissions. However, estimates of soil NO emissions have large uncertainties due to limited observations and multifactorial impacts. Here, we mapped global soil NO emissions, integrating 1356 in-situ NO observations from globally distributed sites with high-resolution climate, soil, and management practice data. We then calculated global and national total NO budgets and revealed the contributions of cropland, grassland, and forest to global soil NO emissions at the national level. The results showed that soil NO emissions were explained mainly by N input, water input and soil pH. Total above-soil NO emissions of the three vegetation cover types were 9.4 Tg N year-1 in 2014, including 5.9 Tg N year-1 (1.04, 95% confidence interval [95% CI]: 0.09-1.99 kg N ha-1  year-1 ) emitted from forest, 1.7 Tg N year-1 (0.68, 95% CI: 0.10-1.26 kg N ha-1  year-1 ) from grassland, and 1.8 Tg N year-1 (0.98, 95% CI: 0.42-1.53 kg N ha-1  year-1 ) from cropland. Soil NO emissions in approximately 57% of 213 countries surveyed were dominated by forests. Our results provide updated inventories of global and national soil NO emissions based on robust data-driven models. These estimates are critical to guiding the mitigation of soil NO emissions and can be used in combination with biogeochemical models.

Soil Emissions of Reactive Nitrogen Accelerate Summertime Surface Ozone Increases in the North China Plain

Summertime surface ozone in China has been increasing since 2013 despite the policy-driven reduction in fuel combustion emissions of nitrogen oxides (NOx). Here we examine the role of soil reactive nitrogen (Nr, including NOx and nitrous acid (HONO)) emissions in the 2013-2019 ozone increase over the North China Plain (NCP), using GEOS-Chem chemical transport model simulations. We update soil NOx emissions and add soil HONO emissions in GEOS-Chem based on observation-constrained parametrization schemes. The model estimates significant daily maximum 8 h average (MDA8) ozone enhancement from soil Nr emissions of 8.0 ppbv over the NCP and 5.5 ppbv over China in June-July 2019. We identify a strong competing effect between combustion and soil Nr sources on ozone production in the NCP region. We find that soil Nr emissions accelerate the 2013-2019 June-July ozone increase over the NCP by 3.0 ppbv. The increase in soil Nr ozone contribution, however, is not primarily driven by weather-induced increases in soil Nr emissions, but by the concurrent decreases in fuel combustion NOx emissions, which enhance ozone production efficiency from soil by pushing ozone production toward a more NOx-sensitive regime. Our results reveal an important indirect effect from fuel combustion NOx emission reduction on ozone trends by increasing ozone production from soil Nr emissions, highlighting the necessity to consider the interaction between anthropogenic and biogenic sources in ozone mitigation in the North China Plain.

The worldwide COVID-19 lockdown impacts on global secondary inorganic aerosols and radiative budget

Global lockdown measures to prevent the spread of the coronavirus disease 2019 (COVID-19) led to air pollutant emission reductions. While the COVID-19 lockdown impacts on both trace gas and total particulate pollutants have been widely investigated, secondary aerosol formation from trace gases remains unclear. To that end, we quantify the COVID-19 lockdown impacts on NOx and SO2 emissions and sulfate-nitrate-ammonium aerosols using multiconstituent satellite data assimilation and model simulations. We find that anthropogenic emissions over major polluted regions were reduced by 19 to 25% for NOx and 14 to 20% for SO2 during April 2020. These emission reductions led to 8 to 21% decreases in sulfate and nitrate aerosols over highly polluted areas, corresponding to >34% of the observed aerosol optical depth declines and a global aerosol radiative forcing of +0.14 watts per square meter relative to business-as-usual scenario. These results point to the critical importance of secondary aerosol pollutants in quantifying climate impacts of future mitigation measures.

Validating HONO as an Intermediate Tracer of the External Cycling of Reactive Nitrogen in the Background Atmosphere

In the urban atmosphere, nitrogen oxide (NO_x═NO + NO₂)-related reactions dominate the formation of nitrous acid (HONO). Here, we validated an external cycling route of HONO and NO_x, i.e., formation of HONO resulting from precursors other than NO_x, in the background atmosphere. A chemical budget closure experiment of HONO and NO_x was conducted at a background site on the Tibetan Plateau and provided direct evidence of the external cycling. An external daytime HONO source of 100 pptv h^-1 was determined. Both soil emissions and photolysis of nitrate on ambient surfaces constituted likely candidate mechanisms characterizing this external source. The external source dominated the chemical production of NO_x with HONO as an intermediate tracer. The OH production was doubled as a result of the external cycling. A high HONO/NO_x ratio (0.31 ± 0.06) during the daytime was deduced as a sufficient condition for the external cycling. Literature review suggested the prevalence of high HONO/NO_x ratios in various background environments, e.g., polar regions, pristine mountains, and forests. Our analysis validates the prevalence of external cycling in general background atmosphere and highlights the promotional role of external cycling regarding the atmospheric oxidative capacity.

Characterizing variations in ambient PM2.5 concentrations at the U.S. Embassy in Dhaka, Bangladesh using observations and the CMAQ modeling system

We analyze hourly PM2.5 (particles with an aerodynamic diameter of ≤ 2.5 μm) concentrations measured at the U.S. Embassy in Dhaka over the 2016 - 2021 time period and find that concentrations are seasonally dependent with the highest occurring in winter and the lowest in monsoon seasons. Mean winter PM2.5 concentrations reached ~165-175 μg/m3 while monsoon concentrations remained ~30-35 μg/m3. Annual mean PM2.5 concentration reached ~5-6 times greater than the Bangladesh annual PM2.5 standard of 15 μg/m3. The number of days exceeding the daily PM2.5 standard of 65 μg/m3 in a year approached nearly 50%. Daily-mean PM2.5 concentrations remained elevated (>65 μg/m3) for more than 80 consecutive days. Night-time concentrations were greater than daytime concentrations. The comparison of results obtained from the Community Multiscale Air Quality (CMAQ) model simulations over the Northern Hemisphere using 108-km horizontal grids with observed data suggests that the model can reproduce the seasonal variation of observed data but underpredicts observed PM2.5 in winter months with a normalized mean bias of 13-32%. In the model, organic aerosol is the largest component of PM2.5, of which secondary organic aerosol plays a dominant role. Transboundary pollution has a large impact on the PM2.5 concentration in Dhaka, with an annual mean contribution of ~40 μg/m3.

Urgency of controlling agricultural nitrogen sources to alleviate summertime air pollution in the North China Plain

Agricultural nitrogen sources (ANS) have played an increasingly important role in the air quality since ANS emission controls are much weaker than those for fossil fuel combustion sources due to the increasing food demand. However, ANS emissions are highly uncertain due to stochastic agricultural management activities and limited field measurements, and impacts of ANS on the air quality remain elusive. In the study, the WRF-Chem model has been used to investigate ANS shares in near surface air pollutant concentrations during a growing season in the North China Plain (NCP), with ANS emissions constrained by satellite retrievals. Soil NOX and agricultural NH3 emissions are about 36% and 92% of their total emissions during the growing season. Sensitivity studies demonstrate that ANS count 16.9 μg m-3 (9.9%) of the mean maximum daily average 8-h ozone concentrations (MDA8 [O3]) and 8.9 μg m-3 (31.7%) of fine particulate matter concentrations ([PM2.5]) on average in the NCP. Additionally, the contributions of ANS to MDA8 [O3] and [PM2.5] increase with the deterioration of air pollution in cities. A 50% emission reduction in ANS decreases MDA8 [O3] ([PM2.5]) from 4.2% to 8.4% (from 19.7% to 31.9%) when the air quality changes from being lightly to heavily polluted in terms of MDA8 [O3] (hourly [PM2.5]). Without fossil fuel combustion emissions, the simulated average MDA8 [O3] and [PM2.5] are 111.7 and 8.2 μg m-3 in cities of the NCP, respectively, exceeding the new standards from the World Health Organization. Our study highlights important contributions of ANS to air quality and the urgency of ANS emission abatement for air pollution alleviation during summertime in the NCP.

Separating emissions and meteorological impacts on peak ozone concentrations in Southern California using generalized additive modeling

Ozone levels have been declining in the Los Angeles, CA, USA area for the last four decades, but there was a recent uptick in the 4th highest daily maximum 8-h (MDA8) ozone concentrations from 2014 to 2018 despite continued reductions in the estimated precursor emissions. In this study, we assess the emissions and meteorological impacts on the 4th highest MDA8 ozone concentrations to better understand the factors affecting the observed MDA8 ozone using a two-step generalized additive model (GAM)/least squares approach applied to the South Coast Air Basin (SoCAB) for the 1990 to 2019 period. The GAM model includes emissions, meteorological factors, large-scale climate variables, date, and the interactions between meteorology and emissions. A least squares method was applied to the GAM output to better capture the 4th highest MDA8 ozone. The resulting two-step model had an R² of 0.98 and a slope of 1 between the observed and predicted 4th highest MDA8 ozone. Emissions and the interactions between the maximum temperature and emissions explain most of the variation in the peak MDA8 ozone concentrations. Declining emissions have lowered the 4th highest MDA8 ozone concentration. Meteorology explains the higher than expected 4th-high, ozone levels observed in 2014-2018, indicating that meteorology was a stronger forcer than the continued reductions in emissions during that time period. The model was applied to estimate future ozone levels. Meteorology developed from climate modeling of the representative concentration pathway (RCP) scenarios, and two sets of emissions were used in the application. The modeling results indicated climate trends will push ozone levels slightly higher if no further emissions reductions are realized and that of two emissions trajectories modeled, the more stringent is required to reliably meet the federal ozone standard given annual meteorological variability.

Integrated Modeling of U.S. Agricultural Soil Emissions of Reactive Nitrogen and Associated Impacts on Air Pollution, Health, and Climate

Agricultural soils are leading sources of reactive nitrogen (Nr) species including nitrogen oxides (NO_x), ammonia (NH₃), and nitrous oxide (N₂O). The propensity of NO_x and NH₃ to generate ozone and fine particulate matter and associated impacts on health are highly variable, whereas the climate impacts of long-lived N₂O are independent of emission timing and location. However, these impacts have rarely been compared on a spatially resolved monetized basis. In this study, we update the nitrogen scheme in an agroecosystem model to simulate the Nr emissions from fertilized soils across the contiguous United States. We then apply a reduced-form air pollution health effect model to assess air quality impacts from NO_x and NH₃ and a social cost of N₂O to assess the climate impacts. Assuming an $8.2 million value of a statistical life and a $13,100/ton social cost of N₂O, the air quality impacts are a factor of ∼7 to 15 times as large as the climate impacts in heavily populated coastal regions, whereas the ratios are closer to 2.5 in sparsely populated regions. Our results show that air pollution, health, and climate should be considered jointly in future assessments of how farming practices affect Nr emissions.

A synthesis of nitric oxide emissions across global fertilized croplands from crop-specific emission factors

Nitrogen (N) fertilizer application to agricultural soils results in substantial emissions of nitric oxide (NO), a key substance in tropospheric chemistry involved in climate forcing and air pollution. However, the estimates of global cropland NO emissions remain uncertain due to a lack of information on direct NO emission factors (EF_d s) of applied N for various cropping systems at seasonal or annual scales. Here we quantified the crop-specific seasonal and annual-scale NO EF_d s through synthesizing 1094 measurements from 125 field-based studies worldwide. The global mean crop-specific seasonal EF_d was 0.53%, with the highest for vegetables (0.75%). Among cereal crops, the EF_d of maize (0.45%) or wheat (0.47%) was about three times higher than for rice (0.12%). At annual scale, the mean EF_d across all cropping systems was 0.58%, with tea plantations having the highest (1.54%). For other cropping systems, the annual-scale EF_d s ranged from 0.02% to 1.07%. Besides crop type, also soil organic carbon, total N, and pH as well as N fertilizer type were the main factors explaining the variations of NO EF_d s. Based on obtained specific EF_d s for each crop type, we estimated that NO emissions due to the use of synthetic fertilizers from global croplands are about 0.42-0.62 Tg N year^-1 . Our budgets are relatively lower if compared to estimates derived by the use of IPCC defaults for NO emissions (0.72-1.66 Tg N year^-1 ) or reported elsewhere (0.67-1.04 Tg N year^-1 ). In our estimates, cash crops (vegetable, tea and orchard), which cover only 9% of the world cropland area, contributed about 31% to total NO emissions from global fertilized croplands. Overall, our meta-analysis provides improved crop-specific NO EF_d s reflecting current stage of knowledge. The work also highlights the relative importance of cash crop production as sources for atmospheric NO, that is, agricultural systems on which mitigation efforts may focus.

Synergistic effects of biogenic volatile organic compounds and soil nitric oxide emissions on summertime ozone formation in China

Natural emissions play a key role in modulating the formation of ground-level ozone (O₃), especially emissions of biogenic volatile organic compounds (BVOCs) and soil nitric oxide (SNO), and their individual effects on O₃ formation have been previously quantified and evaluated. However, their synergistic effects remain unclear and have not yet been well assessed. By applying the Weather Research and Forecasting (WRF) model coupled with the Chemistry-Model of Emissions of Gases and Aerosols from Nature (WRF/Chem-MEGAN) model, this study reveals that in the presence of sufficient BVOC emissions, which act as a fuel, SNO emissions act as a fuel additive and promote the chemical reactions of BVOCs and the subsequent production of O₃. Consequently, the synergistic effects of BVOC and SNO emissions on summertime O₃ production surpassed the sum of their individual effects by as much as 10-20 μg m^-3 in eastern China in 2014. In order to reduce O₃ concentration to a level corresponding to no natural emissions of BVOC or SNO (i.e., the BASE scenario), the anthropogenic volatile organic compound (AVOC) emissions in the scenario considers BVOC and SNO emissions must be reduced by 1.76 times that of the BASE scenario. This study demonstrates that the synergistic effects of BVOC and SNO emissions can impede ground-level O₃ regulation and can subsequently impose stricter requirements on anthropogenic precursor emission control in China. The results of this study can also inform efforts in other regions that are still combating ground-level O₃ pollution.

Exploring the environmental impact of crop production in China using a comprehensive footprint approach

The carbon-nutrient-water cycles of farmland ecosystem not only provides support for crop production, but also has an impact on the environment. Comprehensively quantifying the impact of crop production on the environment can provide a basis for crop sustainable production. A series of environmental footprint approaches, including carbon footprint (CF), nitrogen footprint (NF) and water footprint (WF), were optimized to evaluate greenhouse gas (GHG) emissions, reactive nitrogen (Nr) loss and water resource consumption in crop production, and a comprehensive footprint method based on Endpoint modeling was proposed to evaluate the overall environmental impact of crop production in China. The CF, NF and WF of 28 forms of crop production varied from 1206.29 kg CO₂ equivalent (CO₂-eq) ha^-1 of oil crops to 7326.37 kg CO₂-eq ha^-1 of fiber crops, 16.07 kg Nr-eq ha^-1 of oil crops to 60.70 kg Nr-eq ha^-1 of sugar crops, and 4032.04 m³ ha^-1 oil crops to 12,476.28 m³ ha^-1 of sugar crops, respectively. The contribution of each component to footprints varied greatly among different crops, and fertilizer manufacture, NH₃ volatilization and green WF were generally the main contributors of CF, NF and WF, respectively. The total GHG emissions, Nr loss and water consumption were estimated to be 670.11 Tg CO₂-eq, 5.50 Tg Nr-eq and 837.06 G m³ for all crop production of China. The greenhouse vegetable with the highest area-scaled comprehensive footprint was 4.5 times that of the oil crops which had the lowest one. The contribution of crop production to the corresponding environmental impact in China was as low as 3.7%, of which NH₃ volatilization contributed 48% and grain production contributed 72%. Mineral N fertilization was the main driver of the variation of comprehensive footprint between provinces, with reduction of N fertilizer application as an important way to reduce the environmental impact of crop production.

Combining Machine Learning and Satellite Observations to Predict Spatial and Temporal Variation of near Surface OH in North American Cities

The hydroxyl radical (OH) is the primary cleansing agent in the atmosphere. The abundance of OH in cities initiates the removal of local pollutants; therefore, it serves as the key species describing the urban chemical environment. We propose a machine learning (ML) approach as an efficient alternative to OH simulation using a computationally expensive chemical transport model. The ML model is trained on the parameters simulated from the WRF-Chem model, and it suggests that six predictive parameters are capable of explaining 76% of the OH variability. The parameters are the tropospheric NO₂ column, the tropospheric HCHO column, J(O¹D), H₂O, temperature, and pressure. We then use observations of the tropospheric NO₂ column and HCHO column from OMI as input to the ML model to enable measurement-based prediction of daily near surface OH at 1:30 pm local time across 49 North American cities over the course of 10 years between 2005 and 2014. The result is validated by comparing the OH predictions to measurements of isoprene, which has a source that is uncorrelated with OH and is removed rapidly and almost exclusively by OH in the daytime. We demonstrate that the predicted OH is, as expected, anticorrelated with isoprene. We also show that this ML model is consistent with our understanding of OH chemistry given the solely data-driven nature.

Isotopic constraints confirm the significant role of microbial nitrogen oxides emissions from the land and ocean environment

Nitrogen oxides (NO_x, the sum of nitric oxide (NO) and N dioxide (NO₂)) emissions and deposition have increased markedly over the past several decades, resulting in many adverse outcomes in both terrestrial and oceanic environments. However, because the microbial NO_x emissions have been substantially underestimated on the land and unconstrained in the ocean, the global microbial NO_x emissions and their importance relative to the known fossil-fuel NO_x emissions remain unclear. Here we complied data on stable N isotopes of nitrate in atmospheric particulates over the land and ocean to ground-truth estimates of NO_x emissions worldwide. By considering the N isotope effect of NO_x transformations to particulate nitrate combined with dominant NO_x emissions in the land (coal combustion, oil combustion, biomass burning and microbial N cycle) and ocean (oil combustion, microbial N cycle), we demonstrated that microbial NO_x emissions account for 24 ± 4%, 58 ± 3% and 31 ± 12% in the land, ocean and global environment, respectively. Corresponding amounts of microbial NO_x emissions in the land (13.6 ± 4.7 Tg N yr⁻¹), ocean (8.8 ± 1.5 Tg N yr⁻¹) and globe (22.5 ± 4.7 Tg N yr⁻¹) are about 0.5, 1.4 and 0.6 times on average those of fossil-fuel NO_x emissions in these sectors. Our findings provide empirical constraints on model predictions, revealing significant contributions of the microbial N cycle to regional NO_x emissions into the atmospheric system, which is critical information for mitigating strategies, budgeting N deposition and evaluating the effects of atmospheric NO_x loading on the world.

Cropland nitrogen dioxide emissions and effects on the ozone pollution in the North China plain

Soil nitrogen dioxide (NO_X = NO₂ + NO) emissions have been measured and estimated to be the second most significant contributor to the NO_X burden following the fossil fuel combustion source globally. NO_X emissions from croplands are subject to being underestimated or overlooked in air pollution simulations of regional atmospheric chemistry models. With constraints of ground and space observations of NO₂, the WRF-Chem model is used to investigate the cropland NO_X emission and its contribution to the near-surface ozone (O₃) pollution in North China Plain (NCP) during a growing season as a case study. Model simulations have revealed that the cropland NO_X emissions are underestimated by around 80% without constraints of satellite measured NO₂ column densities. The biogenic NO_X source is estimated to account for half of the anthropogenic NO_X emissions in the NCP during the growing season. Additionally, the cropland NO_X source contributes around 5.0% of the maximum daily average 8h O₃ concentration and 27.7% of NO₂ concentration in the NCP. Our results suggest the agriculture NO_X emission exerts non-negligible impacts on the summertime air quality and needs to be considered when designing emission abatement strategies.

Unraveling pathways of elevated ozone induced by the 2020 lockdown in Europe by an observationally constrained regional model using TROPOMI

Questions about how emissions are changing during the COVID-19 lockdown periods cannot be answered by observations of atmospheric trace gas concentrations alone, in part due to simultaneous changes in atmospheric transport, emissions, dynamics, photochemistry, and chemical feedback. A chemical transport model simulation benefiting from a multi-species inversion framework using well-characterized observations should differentiate those influences enabling to closely examine changes in emissions. Accordingly, we jointly constrain NO _x and VOC emissions using well-characterized TROPOspheric Monitoring Instrument (TROPOMI) HCHO and NO₂ columns during the months of March, April, and May 2020 (lockdown) and 2019 (baseline). We observe a noticeable decline in the magnitude of NO _x emissions in March 2020 (14 %-31 %) in several major cities including Paris, London, Madrid, and Milan, expanding further to Rome, Brussels, Frankfurt, Warsaw, Belgrade, Kyiv, and Moscow (34 %-51 %) in April. However, NO _x emissions remain at somewhat similar values or even higher in some portions of the UK, Poland, and Moscow in March 2020 compared to the baseline, possibly due to the timeline of restrictions. Comparisons against surface monitoring stations indicate that the constrained model underrepresents the reduction in surface NO₂. This underrepresentation correlates with the TROPOMI frequency impacted by cloudiness. During the month of April, when ample TROPOMI samples are present, the surface NO₂ reductions occurring in polluted areas are described fairly well by the model (model: -21 ± 17 %, observation: -29 ± 21 %). The observational constraint on VOC emissions is found to be generally weak except for lower latitudes. Results support an increase in surface ozone during the lockdown. In April, the constrained model features a reasonable agreement with maximum daily 8 h average (MDA8) ozone changes observed at the surface (r = 0.43), specifically over central Europe where ozone enhancements prevail (model: +3.73 ± 3.94 %, + 1.79 ppbv, observation: +7.35 ± 11.27 %, +3.76 ppbv). The model suggests that physical processes (dry deposition, advection, and diffusion) decrease MDA8 surface ozone in the same month on average by -4.83 ppbv, while ozone production rates dampened by largely negative J NO 2 [ NO 2 ] - k NO + O 3 [ NO ] [ O 3 ] become less negative, leading ozone to increase by +5.89 ppbv. Experiments involving fixed anthropogenic emissions suggest that meteorology contributes to 42 % enhancement in MDA8 surface ozone over the same region with the remaining part (58 %) coming from changes in anthropogenic emissions. Results illustrate the capability of satellite data of major ozone precursors to help atmospheric models capture ozone changes induced by abrupt emission anomalies.

Predicting Spatial Variations in Multiple Measures of Oxidative Burden for Outdoor Fine Particulate Air Pollution across Canada

Fine particulate air pollution (PM_2.5) is a leading contributor to the overall global burden of disease. Traditionally, outdoor PM_2.5 has been characterized using mass concentrations which treat all particles as equally harmful. Oxidative potential (OP) (per μg) and oxidative burden (OB) (per m³) are complementary metrics that estimate the ability of PM_2.5 to cause oxidative stress, which is an important mechanism in air pollution health effects. Here, we provide the first national estimates of spatial variations in multiple measures (glutathione, ascorbate, and dithiothreitol depletion) of annual median outdoor PM_2.5 OB across Canada. To do this, we combined a large database of ground-level OB measurements collected monthly prospectively across Canada for 2 years (2016-2018) with PM_2.5 components estimated using a chemical transport model (GEOS-Chem) and satellite aerosol observations. Our predicted ground-level OB values of all three methods were consistent with ground-level observations (cross-validation R² = 0.63-0.74). We found that forested regions and urban areas had the highest OB, predicted primarily by black carbon and organic carbon from wildfires and transportation sources. Importantly, the dominant components associated with OB were different than those contributing to PM_2.5 mass concentrations (secondary inorganic aerosol); thus, OB metrics may better indicate harmful components and sources on health than the bulk PM_2.5 mass, reinforcing that OB estimates can complement the existing PM_2.5 data in future national-level epidemiological studies.

Impacts of Soil NOx Emission on O3 Air Quality in Rural California

Nitrogen oxides (NO_x) are a key precursor in O₃ formation. Although stringent anthropogenic NO_x emission controls have been implemented since the early 2000s in the United States, several rural regions of California still suffer from O₃ pollution. Previous findings suggest that soils are a dominant source of NO_x emissions in California; however, a statewide assessment of the impacts of soil NO_x emission (SNO_x) on air quality is still lacking. Here we quantified the contribution of SNO_x to the NO_x budget and the effects of SNO_x on surface O₃ in California during summer by using WRF-Chem with an updated SNO_x scheme, the Berkeley Dalhousie Iowa Soil NO Parameterization (BDISNP). The model with BDISNP shows a better agreement with TROPOMI NO₂ columns, giving confidence in the SNO_x estimates. We estimate that 40.1% of the state's total NO_x emissions in July 2018 are from soils, and SNO_x could exceed anthropogenic sources over croplands, which accounts for 50.7% of NO_x emissions. Such considerable amounts of SNO_x enhance the monthly mean NO₂ columns by 34.7% (53.3%) and surface NO₂ concentrations by 176.5% (114.0%), leading to an additional 23.0% (23.2%) of surface O₃ concentration in California (cropland). Our results highlight the cobenefits of limiting SNO_x to help improve air quality and human health in rural California.

Sensitivities of Ozone Air Pollution in the Beijing-Tianjin-Hebei Area to Local and Upwind Precursor Emissions Using Adjoint Modeling

Effective mitigation of surface ozone pollution entails detailed knowledge of the contributing precursors' sources. We use the GEOS-Chem adjoint model to analyze the precursors contributing to surface ozone in the Beijing-Tianjin-Hebei area (BTH) of China on days of different ozone pollution severities in June 2019. We find that BTH ozone on heavily polluted days is sensitive to local emissions, as well as to precursors emitted from the provinces south of BTH (Shandong, Henan, and Jiangsu, collectively the SHJ area). Heavy ozone pollution in BTH can be mitigated effectively by reducing NO_x (from industrial processes and transportation), ≥C₃ alkenes (from on-road gasoline vehicles and industrial processes), and xylenes (from paint use) emitted from both BTH and SHJ, as well as by reducing CO (from industrial processes, transportation, and power generation) and ≥C₄ alkanes (from industrial processes, paint and solvent use, and on-road gasoline vehicles) emissions from SHJ. In addition, reduction of NO_x, xylene, and ≥C₃ alkene emissions within BTH would effectively decrease the number of BTH ozone-exceedance days. Our analysis pinpoint the key areas and activities for locally and regionally coordinated emission control efforts to improve surface ozone air quality in BTH.

Evaluating Drought Responses of Surface Ozone Precursor Proxies: Variations With Land Cover Type, Precipitation, and Temperature

Prior work suggests drought exacerbates US air quality by increasing surface ozone concentrations. We analyze 2005-2015 tropospheric column concentrations of two trace gases that serve as proxies for surface ozone precursors retrieved from the OMI/Aura satellite: Nitrogen dioxide (ΩNO_2; NO_x proxy) and formaldehyde (ΩHCHO; VOC proxy). We find 3.5% and 7.7% summer drought enhancements (classified by SPEI) for ΩNO₂ and ΩHCHO, respectively, corroborating signals previously extracted from ground-level observations. When we subset by land cover type, the strongest ΩHCHO drought enhancement (10%) occurs in the woody savannas of the Southeast US. By isolating the influences of precipitation and temperature, we infer that enhanced biogenic VOC emissions in this region increase ΩHCHO independently with both high temperature and low precipitation during drought. The strongest ΩNO₂ drought enhancement (6.0%) occurs over Midwest US croplands and grasslands, which we infer to reflect the sensitivity of soil NO_x emissions to temperature.

Nitrogen in Life Cycle Assessment (LCA) of agricultural crop production systems: Comparative analysis of regionalization approaches

Assessing reactive nitrogen (N_r) flows resulting from agricultural crop production systems (ACPS) with LCA requires regionalization. However, methodological approaches for regionalized LCA of ACPS may not necessarily reflect a comprehensive picture of N_r compounds and their complex interaction with the environment. This study presents a comprehensive analysis of the consideration of N_r in methodological approaches for regionalized LCA applied to ACPS. We conducted a review comprehending scientific literature on regionalization approaches applied to ACPS and compared these with general requirements of LCA and the scientific background of the N-cycle following the LCA framework. Special focus was placed on the analysis of process-based models (PBM) and life cycle impact assessment (LCIA) methods. We derived key factors relevant for a regional assessment of N flows in LCA and compared these to 23 regionalization approaches applied to ACPS. Main obstacles identified to conduct a regionalized LCA for ACPS involved the consideration of different regional scales and thus a missing common regionalization approach suitable for ACPS. Although, N related key-factors were mainly considered by the analyzed approaches in the different LCA phases, critical points involved the consideration of N field emissions and N impact assessment. Based on these findings, practical recommendations were given. Our comprehensive review provides relevant requirements for an improved regional N assessment in regionalized LCA of ACPS and aims to present a realistic picture when comparing different alternatives considering N specific regional impacts.

Impact of the COVID-19 outbreak on air pollution levels in East Asia

This study leverages satellite remote sensing to investigate the impact of the coronavirus outbreak and the resulting lockdown of public venues on air pollution levels in East Asia. We analyze data from the Sentinel-5P and the Himawari-8 satellites to examine concentrations of NO₂, HCHO, SO₂, and CO, and the aerosol optical depth (AOD) over the BTH, Wuhan, Seoul, and Tokyo regions in February 2019 and February 2020. Results show that most of the concentrations of pollutants are lower than those of February 2019. Compared to other pollutants, NO₂ experienced the most significant reductions by almost 54%, 83%, 33%, and 19% decrease in BTH, Wuhan, Seoul, and Tokyo, respectively. The greatest reductions in pollutants occurred in Wuhan, with a decrease of almost 83%, 11%, 71%, and 4% in the column densities of NO₂, HCHO, SO₂, and CO, respectively, and a decrease of about 62% in the AOD. Although NO₂, CO, and formaldehyde concentrations decreased in the Seoul and Tokyo metropolitan areas compared to the previous year, concentrations of SO₂ showed an increase in these two regions due to the effect of transport from polluted upwind regions. We also show that meteorological factors were not the main reason for the dramatic reductions of pollutants in the atmosphere. Moreover, an investigation of the HCHO/NO₂ ratio shows that in many regions of East China, particularly in Wuhan, ozone production in February 2020 is less NO_X saturated during the daytime than it was in February 2019. With large reductions in the concentrations of NO₂ during lockdown situations, we find that significant increases in surface ozone in East China from February 2019 to February 2020 are likely the result of less reaction of NO and O₃ caused by significantly reduced NO_X concentrations and less NO_X saturation in East China during the daytime.

Short-Term Responses of Air Quality to Changes in Emissions under the Representative Concentration Pathway 4.5 Scenario over Brazil

Brazil, one of the world's fastest-growing economies, is the fifth most populous country and is experiencing accelerated urbanization. This combination of factors causes an increase in urban population that is exposed to poor air quality, leading to public health burdens. In this work, the Weather Research and Forecasting Model with Chemistry is applied to simulate air quality over Brazil for a short time period under three future emission scenarios, including current legislation (CLE), mitigation scenario (MIT), and maximum feasible reduction (MFR) under the Representative Concentration Pathway 4.5 (RCP4.5), which is a climate change scenario under which radiative forcing of greenhouse gases (GHGs) reach 4.5 W m-2 by 2100. The main objective of this study is to determine the sensitivity of the concentrations of ozone (O3) and particulate matter with aerodynamic diameter 2.5 µm or less (PM2.5) to changes in emissions under these emission scenarios and to determine the signal and spatial patterns of these changes for Brazil. The model is evaluated with observations and shows reasonably good agreement. The MFR scenario leads to a reduction of 3% and 75% for O3 and PM2.5 respectively, considering the average of grid cells within Brazil, whereas the CLE scenario leads to an increase of 1% and 11% for O3 and PM2.5 respectively, concentrated near urban centers. These results indicate that of the three emission control scenarios, the CLE leads to poor air quality, while the MFR scenario leads to the maximum improvement in air quality. To the best of our knowledge, this work is the first to investigate the responses of air quality to changes in emissions under these emission scenarios for Brazil. The results shed light on the linkage between changes of emissions and air quality.

Unprecedented Temporary Reduction in Global Air Pollution Associated with COVID-19 Forced Confinement: A Continental and City Scale Analysis

Shortly after the outbreak of the novel infectious disease (COVID-19) started at the end of 2019, it turned into a global pandemic, which caused the lockdown of many countries across the world. Various strict measures were adopted to reduce anthropogenic activities in order to prevent further spread and infection of the disease. In this study, we utilized continental scale remotely sensed data along with city scale in situ air quality observations for 2020 as well as data from the baseline period (2015–2019) to provide an early insight on air pollution changes in response to the COVID-19 pandemic lockdown, by combining both continental and city scales. For the continental scale analysis, data of NO2, SO2, and O3 were acquired from the ozone monitoring instrument (OMI) and data of aerosol optical depth (AOD) were collected from the moderate resolution imaging spectroradiometer (MODIS). For city scale analysis, data of NO2, CO, PM2.5, O3, and SO2 were derived from ground-based air quality observations. Results from satellite observations at the continental scale showed that concentrations of NO2, SO2, and AOD substantially dropped in 2020 during the lockdown period compared to their averages for the baseline period over all continents, with a maximum reduction of ~33% for NO2 in East Asia, ~41% for SO2 in East Asia, and ~37% for AOD in South Asia. In the case of O3, the maximum overall reduction was observed as ~11% in Europe, followed by ~10% in North America, while a slight increase was found in other study regions. These findings align with ground-based air quality observations, which showed that pollutants such as NO2, CO, PM2.5, and SO2 during the 2020 lockdown period decreased significantly except that O3 had varying patterns in different cities. Specifically, a maximum reduction of ~49% in NO2 was found in London, ~43% in CO in Wuhan, ~38% in PM2.5 in Chennai, and ~48% in SO2 in Beijing. In the case of urban O3, a maximum reduction of ~43% was found in Wuhan, but a significant increase of ~47% was observed in Chennai. It is obvious that restricted human activities during the lockdown have reduced the anthropogenic emissions and subsequently improved air quality, especially across the metropolitan cities.

Global high-resolution emissions of soil NOx, sea salt aerosols, and biogenic volatile organic compounds

Natural emissions of air pollutants from the surface play major roles in air quality and climate change. In particular, nitrogen oxides (NOx) emitted from soils contribute ~15% of global NOx emissions, sea salt aerosols are a major player in the climate and chemistry of the marine atmosphere, and biogenic emissions are the dominant source of non-methane volatile organic compounds at the global scale. These natural emissions are often estimated using nonlinear parameterizations, which are sensitive to the horizontal resolutions of inputted meteorological and ancillary data. Here we use the HEMCO model to compute these emissions worldwide at horizontal resolutions of 0.5° lat. × 0.625° lon. for 1980-2017 and 0.25° lat. × 0.3125° lon. for 2014-2017. We further offer the respective emissions at lower resolutions, which can be used to evaluate the impacts of resolution on estimated global and regional emissions. Our long-term high-resolution emission datasets offer useful information to study natural pollution sources and their impacts on air quality, climate, and the carbon cycle.

Isotopic evidence that recent agriculture overprints climate variability in nitrogen deposition to the Tibetan Plateau

The stable isotopes of nitrogen in nitrate archived in polar ice have been interpreted as reflecting a shift in reactive nitrogen sources or changes in atmospheric chemical reactivity. Here, we present a novel concentration and isotopic record of nitrate (δ¹⁵N-NO₃^-) from a central Tibetan Plateau ice core over the last ~200 years. We find that nitrate concentration increased from 6.0 ± 2.3 μeq/L (mean ± 1σ) in the preindustrial period (prior to 1900s) to 7.3 ± 2.7 μeq/L in post-1950. Over the same time period, the δ¹⁵N-NO₃^- decreased from 8.7 ± 3.7‰ to 4.2 ± 3.1‰, with much larger interannual variation in δ¹⁵N-NO₃^- during the preindustrial period. We present a useful framework for quantifying the sensitivity of the isotopic composition of atmospheric nitrate to changes in both sources and chemistry (gas and aerosol phase). After 1950, nitrogen deposition is primarily driven by fertilizer use, leading to significant increases in concentration and decreases in δ¹⁵N-NO₃^-. The large interannual variability of ice core δ¹⁵N-NO₃^- in the preindustrial reflects natural processes, namely the El Niño Southern Oscillation (ENSO) and dust events. Our results highlight a new connection between the nitrogen cycle and ENSO, and the overprinting of natural climate signals by recent anthropogenic increases in reactive nitrogen release.

Temporal Analysis of OMI-Observed Tropospheric NO2 Columns over East Asia during 2006–2015

The study analyzed temporal variations of Ozone Monitoring Instrument (OMI)-observed NO2 columns, interregional correlation, and comparison between NO2 columns and NOx emissions during the period from 2006 to 2015. Regarding the trend of the NO2 columns, the linear lines were classified into four groups: (1) ‘upward and downward’ over six defined geographic regions in central-east Asia; (2) ‘downward’ over Guangzhou, Japan, and Taiwan; (3) ‘stagnant’ over South Korea; and (4) ‘upward’ over North Korea, Mongolia, Qinghai, and Northwestern Pacific ocean. In particular, the levels of NO2 columns in 2015 returned to those in 2006 over most of the polluted regions in China. Quantitatively, their relative changes in 2015 compared to 2006 were approximately 10%. From the interregional correlation analysis, it was found that unlike positive relationships between the polluted areas, the different variations of monthly NO2 columns led to negative relationships in Mongolia and Qinghai. Regarding the comparison between NO2 columns and NOx emission, the NOx emissions from the Copernicus Atmosphere Monitoring Service (CAMS) and Clean Air Policy Support System (CAPSS) inventories did not follow the year-to-year variations of NO2 columns over the polluted regions. In addition, the weekly effect was only clearly shown in South Korea, Japan, and Taiwan, indicating that the amounts of NOx emissions are significantly contributed to by the transportation sector.

Simulation of airborne trace metals in fine particulate matter over North America

Trace metal distributions are of relevance to understand sources of fine particulate matter (PM2.5), PM2.5-related health effects, and atmospheric chemistry. However, knowledge of trace metal distributions is lacking due to limited ground-based measurements and model simulations. This study develops a simulation of 12 trace metal concentrations (Si, Ca, Al, Fe, Ti, Mn, K, Mg, As, Cd, Ni and Pb) over continental North America for 2013 using the GEOS-Chem chemical transport model. Evaluation of modeled trace metal concentrations with observations indicates a spatial consistency within a factor of 2, an improvement over previous studies that were within a factor of 3-6. The spatial distribution of trace metal concentrations reflects their primary emission sources. Crustal element (Si, Ca, Al, Fe, Ti, Mn, K) concentrations are enhanced over the central US from anthropogenic fugitive dust and over the southwestern U.S. due to natural mineral dust. Heavy metal (As, Cd, Ni and Pb) concentrations are high over the eastern U.S. from industry. K is abundance in the southeast from biomass burning and high concentrations of Mg is observed along the coast from sea spray. The spatial pattern of PM2.5 mass is most strongly correlated with Pb, Ni, As and K due to their signature emission sources. Challenges remain in accurately simulating observed trace metal concentrations. Halving anthropogenic fugitive dust emissions in the 2011 National Air Toxic Assessment (NATA) inventory and doubling natural dust emissions in the default GEOS-Chem simulation was necessary to reduce biases in crustal element concentrations. A fivefold increase of anthropogenic emissions of As and Pb was necessary in the NATA inventory to reduce the national-scale bias versus observations by more than 80 %, potentially reflecting missing sources.

The Spatial–Temporal Variation of Tropospheric NO2 over China during 2005 to 2018

In recent years, new and strict air quality regulations have been implemented in China. Therefore, it is of great significance to evaluate the current air pollution situation and effectiveness of actions. In this study, Ozone Monitoring Instrument (OMI) satellite data were used to detect the spatiotemporal characteristics of tropospheric NO2 columns over China from 2005 to 2018, including spatial distribution, seasonal cycles and long-term trends. The averaged NO2 pollution is higher in southeastern China and lower in the northwest, which are well delineated by the Heihe–Tengchong line. Furthermore, the NO2 loadings are highest in the North China Plain, with vertical column density (VCD) exceeding 13 × 1015 molec cm−2. Regarding the seasonal cycle, the NO2 loadings in eastern China is highest in winter and lowest in summer, while the western region shows the opposite feature. The amplitude of annual range increase gradually from the south to the north. If the entire period of 2005–2018 is taken into account, China has experienced little change in NO2. In fact, however, there appears to be significant trends of an increase followed by a downward tendency, with the turning point in the year 2012. In the former episode of 2005–2012, increasing trends overwhelm nearly the whole nation, especially in the Jing–Jin–Tang region, Shandong Province, and Northern Henan and Southern Hebei combined regions, where the rising rates were as high as 1.0–1.8 × 1015 molec cm−2 year−1. In contrast, the latter episode of 2013–2018 features remarkable declines in NO2 columns over China. Particularly, the regions where the decreased degree was remarkable in 2013–2018 were consistent with the regions where the upward trend was obvious in 2005–2012. Overall, this upward–downward pattern is true for most parts of China. However, some of the largest metropolises, such as Beijing, Shanghai and Guangzhou, witnessed a continuous decrease in the NO2 amounts, indicating earlier and more stringent measures adopted in these areas. Finally, it can be concluded that China’s recent efforts to cut NO2 pollution are successful, especially in mega cities.

Hybrid Mass Balance/4D-Var Joint Inversion of NO x and SO2 Emissions in East Asia

Accurate estimates of NO x and SO2 emissions are important for air quality modeling and management. To incorporate chemical interactions of the two species in emission estimates, we develop a joint hybrid inversion framework to estimate their emissions in China and India (2005-2012). Pseudo observation tests and posterior evaluation with surface measurements demonstrate that joint assimilation of SO2 and NO2 can provide more accurate constraints on emissions than single-species inversions. This occurs through synergistic change of O3 and OH concentrations, particularly in conditions where satellite retrievals of the species being optimized have large uncertainties. The percentage changes of joint posterior emissions from the single-species posterior emissions go up to 242% at grid scales, although the national average of monthly emissions, seasonality, and interannual variations are similar. In China and India, the annual budget of joint posterior SO2 emissions is lower, but joint NO x posterior emissions are higher, because NO x emissions increase to increase SO2 concentration and better match Ozone Monitoring Instrument SO2 observations in high-NO x regions. Joint SO2 posterior emissions decrease by 16.5% from 2008 to 2012, while NO x posterior emissions increase by 24.9% from 2005 to 2011 in China-trends which are consistent with the MEIC inventory. Joint NO x and SO2 posterior emissions in India increase by 15.9% and 19.2% from 2005 to 2012, smaller than the 59.9% and 76.2% growth rate using anthropogenic emissions from EDGARv4.3.2. This work shows the benefit and limitation of joint assimilation in emission estimates and provides an efficient framework to perform the inversion.

Urban pollution greatly enhances formation of natural aerosols over the Amazon rainforest

One of the least understood aspects in atmospheric chemistry is how urban emissions influence the formation of natural organic aerosols, which affect Earth's energy budget. The Amazon rainforest, during its wet season, is one of the few remaining places on Earth where atmospheric chemistry transitions between preindustrial and urban-influenced conditions. Here, we integrate insights from several laboratory measurements and simulate the formation of secondary organic aerosols (SOA) in the Amazon using a high-resolution chemical transport model. Simulations show that emissions of nitrogen-oxides from Manaus, a city of ~2 million people, greatly enhance production of biogenic SOA by 60-200% on average with peak enhancements of 400%, through the increased oxidation of gas-phase organic carbon emitted by the forests. Simulated enhancements agree with aircraft measurements, and are much larger than those reported over other locations. The implication is that increasing anthropogenic emissions in the future might substantially enhance biogenic SOA in pristine locations like the Amazon.

A world avoided: impacts of changes in anthropogenic emissions on the burden and effects of air pollutants in Europe and North America

Emissions from anthropogenic activity are known to have deleterious impacts on human and ecosystem health and as such a significant amount of time, effort and money has been spent developing legislation to minimise their effects. Here we use a state of the art coupled chemistry-climate model HadGEM2-ES, with extended tropospheric chemistry, to assess the impacts that changes in emissions from anthropogenic activity have had on the burden and impacts of air pollutants over the last three decades. We use HadGEM2-ES to assess an alternative trajectory in air pollutant emissions to that which we have seen, with a regional focus on the contiguous United States and areas of Western Europe. This alternative trajectory can be considered to reflect a world avoided. In this world avoided, the significant levels of air pollution legislation imposed over the last three decades are simulated to not have come into effect in the contiguous United States and Western Europe. Rather a business as usual emission scenario is followed from 1970 to the present day. By combining the results of simulations of the world avoided with a base case present day atmosphere our model runs demonstrate that as a result of air pollution legislation, over 500 000 early mortalities a year have been mitigated owing to extensive reduction in sulfate aerosol and up to 8000 early mortalities a year have been mitigated as a result of improvements in ozone and nitrogen dioxide pollution. These results highlight the important role of legislation in reducing air pollution related mortality in these areas of the globe and highlight a compelling case for developing regions to follow.

Hot Summers: Effect of Extreme Temperatures on Ozone in Sydney, Australia

Poor air quality is often associated with hot weather, but the quantitative attribution of high temperatures on air quality remains unclear. In this study, the effect of elevated temperatures on air quality is investigated in Greater Sydney using January 2013, a period of extreme heat during which temperatures at times exceeded 40 ∘ C, as a case study. Using observations from 17 measurement sites and the Weather Research and Forecasting Chemistry (WRF-Chem) model, we analyse the effect of elevated temperatures on ozone in Sydney by running a number of sensitivity studies in which: (1) the model is run with biogenic emissions generated by MEGAN and separately run with monthly average Model of Emissions of Gases and Aerosols from Nature ( MEGAN) biogenic emissions (for January 2013); (2) the model results from the standard run are compared with those in which average temperatures (for January 2013) are only applied to the chemistry; (3) the model is run using both averaged biogenic emissions and temperatures; and (4 and 5) the model is run with half and zero biogenic emissions. The results show that the impact on simulated ozone through the effect of temperature on reaction rates is similar to the impact via the effect of temperature on biogenic emissions and the relative impacts are largely additive when compared to the run in which both are averaged. When averaged across 17 sites in Greater Sydney, the differences between ozone simulated under standard and averaged model conditions are as high as 16 ppbv. Removing biogenic emissions in the model has the effect of removing all simulated ozone episodes during extreme heat periods, highlighting the important role of biogenic emissions in Australia, where Eucalypts are a key biogenic source.

Emission of formic and acetic acids from two Colorado soils

A 'missing source' of atmospheric formic acid is consistently observed during model-measurement comparisons, and evidence from multiple environments suggests a near-surface source. Soil emissions are considered to be a small formic acid source, but estimates are based on a single study from a tropical site. Here, we investigate soil emissions of organic acids from two soils - a ponderosa pine forest (Manitou Experimental Forest Observatory), and a managed lawn (Colorado State University) using a laboratory chamber. Both soils are a source of formic and acetic acids. Under ambient conditions, formic acid emissions are 0.11 (pine forest) and 0.15 (lawn) nmol m-2 s-1, and acetic acid emissions are 0.05 (pine forest) and 0.71 (lawn) nmol m-2 s-1. Only acetic acid emissions from the forest site correlate with CO2 fluxes, but all formic and acetic acid emissions increase exponentially with temperature. Increasing soil moisture only enhances acetic acid emissions from the forest. Considering this temperature and moisture dependence, we hypothesize that while equilibrium partitioning may contribute to the forest emissions, organic acid emissions from the lawn are likely driven by microbial activity. Lactic acid was emitted from both soils, but not quantified. The observed formic acid emissions are higher than previous measurements, but still low enough that soils are unlikely the 'missing source' of atmospheric organic acids, although the variability in the soil source is substantial. We contrast observations to previous parameterizations used in models, and present recommendations for modified parameterizations for formic and acetic acid emission.

Modeling emissions for three-dimensional atmospheric chemistry transport models

Poor air quality is still a threat for human health in many parts of the world. In order to assess measures for emission reductions and improved air quality, three-dimensional atmospheric chemistry transport modeling systems are used in numerous research institutions and public authorities. These models need accurate emission data in appropriate spatial and temporal resolution as input. This paper reviews the most widely used emission inventories on global and regional scales and looks into the methods used to make the inventory data model ready. Shortcomings of using standard temporal profiles for each emission sector are discussed, and new methods to improve the spatiotemporal distribution of the emissions are presented. These methods are often neither top-down nor bottom-up approaches but can be seen as hybrid methods that use detailed information about the emission process to derive spatially varying temporal emission profiles. These profiles are subsequently used to distribute bulk emissions such as national totals on appropriate grids. The wide area of natural emissions is also summarized, and the calculation methods are described. Almost all types of natural emissions depend on meteorological information, which is why they are highly variable in time and space and frequently calculated within the chemistry transport models themselves. The paper closes with an outlook for new ways to improve model ready emission data, for example, by using external databases about road traffic flow or satellite data to determine actual land use or leaf area. In a world where emission patterns change rapidly, it seems appropriate to use new types of statistical and observational data to create detailed emission data sets and keep emission inventories up-to-date.

IMPLICATIONS

Emission data are probably the most important input for chemistry transport model (CTM) systems. They need to be provided in high spatial and temporal resolution and on a grid that is in agreement with the CTM grid. Simple methods to distribute the emissions in time and space need to be replaced by sophisticated emission models in order to improve the CTM results. New methods, e.g., for ammonia emissions, provide grid cell-dependent temporal profiles. In the future, large data fields from traffic observations or satellite observations could be used for more detailed emission data.

Air-quality-related health impacts from climate change and from adaptation of cooling demand for buildings in the eastern United States: An interdisciplinary modeling study

BACKGROUND

Climate change negatively impacts human health through heat stress and exposure to worsened air pollution, amongst other pathways. Indoor use of air conditioning can be an effective strategy to reduce heat exposure. However, increased air conditioning use increases emissions of air pollutants from power plants, in turn worsening air quality and human health impacts. We used an interdisciplinary linked model system to quantify the impacts of heat-driven adaptation through building cooling demand on air-quality-related health outcomes in a representative mid-century climate scenario.

METHODS AND FINDINGS

We used a modeling system that included downscaling historical and future climate data with the Weather Research and Forecasting (WRF) model, simulating building electricity demand using the Regional Building Energy Simulation System (RBESS), simulating power sector production and emissions using MyPower, simulating ambient air quality using the Community Multiscale Air Quality (CMAQ) model, and calculating the incidence of adverse health outcomes using the Environmental Benefits Mapping and Analysis Program (BenMAP). We performed simulations for a representative present-day climate scenario and 2 representative mid-century climate scenarios, with and without exacerbated power sector emissions from adaptation in building energy use. We find that by mid-century, climate change alone can increase fine particulate matter (PM2.5) concentrations by 58.6% (2.50 μg/m3) and ozone (O3) by 14.9% (8.06 parts per billion by volume [ppbv]) for the month of July. A larger change is found when comparing the present day to the combined impact of climate change and increased building energy use, where PM2.5 increases 61.1% (2.60 μg/m3) and O3 increases 15.9% (8.64 ppbv). Therefore, 3.8% of the total increase in PM2.5 and 6.7% of the total increase in O3 is attributable to adaptive behavior (extra air conditioning use). Health impacts assessment finds that for a mid-century climate change scenario (with adaptation), annual PM2.5-related adult mortality increases by 13,547 deaths (14 concentration-response functions with mean incidence range of 1,320 to 26,481, approximately US$126 billion cost) and annual O3-related adult mortality increases by 3,514 deaths (3 functions with mean incidence range of 2,175 to 4,920, approximately US$32.5 billion cost), calculated as a 3-month summer estimate based on July modeling. Air conditioning adaptation accounts for 654 (range of 87 to 1,245) of the PM2.5-related deaths (approximately US$6 billion cost, a 4.8% increase above climate change impacts alone) and 315 (range of 198 to 438) of the O3-related deaths (approximately US$3 billion cost, an 8.7% increase above climate change impacts alone). Limitations of this study include modeling only a single month, based on 1 model-year of future climate simulations. As a result, we do not project the future, but rather describe the potential damages from interactions arising between climate, energy use, and air quality.

CONCLUSIONS

This study examines the contribution of future air-pollution-related health damages that are caused by the power sector through heat-driven air conditioning adaptation in buildings. Results show that without intervention, approximately 5%-9% of exacerbated air-pollution-related mortality will be due to increases in power sector emissions from heat-driven building electricity demand. This analysis highlights the need for cleaner energy sources, energy efficiency, and energy conservation to meet our growing dependence on building cooling systems and simultaneously mitigate climate change.

Spatio-temporal assessment and seasonal variation of tropospheric ozone in Pakistan during the last decade

This study uses the tropospheric ozone data derived from combined observations of Ozone Monitoring Instrument/Microwave Limb Sounder instruments by using the tropospheric ozone residual method. The main objective was to study the spatial distribution and temporal evolution in the troposphere ozone columns over Pakistan during the time period of 2004 to 2014. Results showed an overall increase of 3.2 ± 1.1 DU in tropospheric ozone columns over Pakistan. Spatial distribution showed enhanced ozone columns in the Punjab and southern Sindh consistent to high population, urbanization, and extensive anthropogenic activities, and exhibited statistically significant temporal increase. Seasonal variations in tropospheric ozone columns are driven by various factors such as seasonality in UV-B fluxes, seasonality in ozone precursor gases such as NO_x and volatile organic compounds (caused by temperature dependent biogenic emission) and agricultural fire activities in Pakistan. A strong correlation of 96% (r = 0.96) was found between fire events and tropospheric ozone columns in Pakistan.

Agriculture is a major source of NO x pollution in California

Nitrogen oxides (NO _x = NO + NO₂) are a primary component of air pollution-a leading cause of premature death in humans and biodiversity declines worldwide. Although regulatory policies in California have successfully limited transportation sources of NO _x pollution, several of the United States' worst-air quality districts remain in rural regions of the state. Site-based findings suggest that NO _x emissions from California's agricultural soils could contribute to air quality issues; however, a statewide estimate is hitherto lacking. We show that agricultural soils are a dominant source of NO _x pollution in California, with especially high soil NO _x emissions from the state's Central Valley region. We base our conclusion on two independent approaches: (i) a bottom-up spatial model of soil NO _x emissions and (ii) top-down airborne observations of atmospheric NO _x concentrations over the San Joaquin Valley. These approaches point to a large, overlooked NO _x source from cropland soil, which is estimated to increase the NO _x budget by 20 to 51%. These estimates are consistent with previous studies of point-scale measurements of NO _x emissions from the soil. Our results highlight opportunities to limit NO _x emissions from agriculture by investing in management practices that will bring co-benefits to the economy, ecosystems, and human health in rural areas of California.

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.

Nonlinear response of nitric oxide fluxes to fertilizer inputs and the impacts of agricultural intensification on tropospheric ozone pollution in Kenya

Crop yields in sub-Saharan Africa remain stagnant at 1 ton ha^-1 , and 260 million people lack access to adequate food resources. Order-of-magnitude increases in fertilizer use are seen as a critical step in attaining food security. This increase represents an unprecedented input of nitrogen (N) to African ecosystems and will likely be accompanied by increased soil emissions of nitric oxide (NO). NO is a precursor to tropospheric ozone, an air pollutant and greenhouse gas. Emissions of NO from soils occur primarily during denitrification and nitrification, and N input rates are a key determinant of emission rates. We established experimental maize plots in western Kenya to allow us to quantify the response function relating NO flux to N input rate during the main 2011 and 2012 growing seasons. NO emissions followed a sigmoid response to fertilizer inputs and have emission factors under 1% for the roughly two-month measurement period in each year, although linear and step relationships could not be excluded in 2011. At fertilization rates above 100 kg N ha^-1 , NO emissions increased without a concomitant increase in yields. We used the geos-chem chemical transport model to evaluate local impacts of increased NO emissions on tropospheric ozone concentrations. Mean 4-hour afternoon tropospheric ozone concentrations in Western Kenya increased by up to roughly 2.63 ppbv under fertilization rates of 150 kg N ha^-1 or higher. Using AOT40, a metric for assessing crop damage from ozone, we find that the increased ozone concentrations result in an increase in AOT40 exposure of approximately 110 ppbh for inputs of 150 kg N ha^-1 during the March-April-May crop growing season, compared with unfertilized simulations, with negligible impacts on crop productivity. Our results suggest that it may be possible to manage Kenyan agricultural systems for high yields while avoiding substantial impacts on air quality.

USEEIO: a New and Transparent United States Environmentally-Extended Input-Output Model

National-scope environmental life cycle models of goods and services may be used for many purposes, not limited to quantifying impacts of production and consumption of nations, assessing organization-wide impacts, identifying purchasing hotspots, analyzing environmental impacts of policies, and performing streamlined life cycle assessment. USEEIO is a new environmentally-extended input-output model of the United States fit for such purposes and other sustainable materials management applications. USEEIO melds data on economic transactions between 389 industry sectors with environmental data for these sectors covering land, water, energy and mineral usage and emissions of greenhouse gases, criteria air pollutants, nutrients and toxics, to build a life cycle model of 385 US goods and services. In comparison with existing US models, USEEIO is more current with most data representing year 2013, more extensive in its coverage of resources and emissions, more deliberate and detailed in its interpretation and combination of data sources, and includes formal data quality evaluation and description. USEEIO is assembled with a new Python module called the IO Model Builder capable of assembling and calculating results of user-defined input-output models and exporting the models into LCA software. The model and data quality evaluation capabilities are demonstrated with an analysis of the environmental performance of an average hospital in the US. All USEEIO files are publicly available bringing a new level of transparency for environmentally-extended input-output models.

Novel Method for Nitrogen Isotopic Analysis of Soil-Emitted Nitric Oxide

The global inventory of NO_x (NO_x = NO + NO₂) emissions is poorly constrained, with a large portion of the uncertainty attributed to soil NO emissions that result from soil abiotic and microbial processes. While natural abundance stable N isotopes (δ¹⁵N) in various soil N-containing compounds have proven to be a robust tracer of soil N cycling, soil δ¹⁵N-NO is rarely quantified due to the measurement difficulties. Here, we present a new method that collects soil-emitted NO through NO conversion to NO₂ in excess ozone (O₃) and subsequent NO₂ collection in a 20% triethanolamine (TEA) solution as nitrite and nitrate for δ¹⁵N analysis using the denitrifier method. The precision and accuracy of the method were quantified through repeated collection of an analytical NO tank and intercalibration with a modified EPA NO_x collection method. The results show that the efficiency of NO conversion to NO₂ and subsequent NO₂ collection in the TEA solution is >98% under a variety of controlled conditions. The method precision (1σ) and accuracy across the entire analytical procedure are ±1.1‰. We report the first analyses of soil δ¹⁵N-NO (-59.8‰ to -23.4‰) from wetting-induced NO pulses at both laboratory and field scales that have important implications for understanding soil NO dynamics.

Response of Power Plant Emissions to Ambient Temperature in the Eastern United States

Past studies have established strong connections between meteorology and air quality, via chemistry, transport, and natural emissions. A less understood linkage between weather and air quality is the temperature-dependence of emissions from electricity generating units (EGUs), associated with high electricity demand to support building cooling on hot days. This study quantifies the relationship between ambient surface temperatures and EGU air emissions (CO₂, SO₂, and NO_X) using historical data. We find that EGUs in the Eastern U.S. region from 2007 to 2012 exhibited a 3.87% ± 0.41% increase in electricity generation per °C increase during summer months. This is associated with a 3.35%/°C ± 0.50%/°C increase in SO₂ emissions, a 3.60%/°C ± 0.49%/°C increase in NO_X emissions, and a 3.32%/°C ± 0.36%/°C increase in CO₂ emissions. Sensitivities vary by year and by pollutant, with SO₂ both the highest sensitivity (5.04% in 2012) and lowest sensitivity (2.19% in 2007) in terms of a regional average. Texas displays 2007-2012 sensitivities of 2.34%/°C ± 0.28%/°C for generation, 0.91%/°C ± 0.25%/°C for SO₂ emissions, 2.15%/°C ± 0.29%/°C for NO_X emissions, and 1.78%/°C ± 0.22%/°C for CO₂ emissions. These results suggest demand-side and supply side technological improvements and fuel choice could play an important role in cost-effective reduction of carbon emissions and air pollution.

Understanding the glacial methane cycle

Atmospheric methane (CH₄) varied with climate during the Quaternary, rising from a concentration of 375 p.p.b.v. during the last glacial maximum (LGM) 21,000 years ago, to 680 p.p.b.v. at the beginning of the industrial revolution. However, the causes of this increase remain unclear; proposed hypotheses rely on fluctuations in either the magnitude of CH₄ sources or CH₄ atmospheric lifetime, or both. Here we use an Earth System model to provide a comprehensive assessment of these competing hypotheses, including estimates of uncertainty. We show that in this model, the global LGM CH₄ source was reduced by 28–46%, and the lifetime increased by 2–8%, with a best-estimate LGM CH₄ concentration of 463–480 p.p.b.v. Simulating the observed LGM concentration requires a 46–49% reduction in sources, indicating that we cannot reconcile the observed amplitude. This highlights the need for better understanding of the effects of low CO₂ and cooler climate on wetlands and other natural CH₄ sources.

The cause of the increase in atmospheric methane from 375 p.p.b.v. during the last ice age to 680 p.p.b.v. at the onset of Industrialization remains uncertain. Here, using an Earth system model, the authors show that we cannot reconcile this rise based on our current understanding of natural methane sources.