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Soil emissions of nitrogen compounds, including NO and HONO, play a significant role in the atmospheric nitrogen budget. However, HONO has been overlooked in previous research on soil reactive nitrogen (Nr) emissions and their impacts on air quality in China. This study estimates soil NOx and soil HONO emissions (SNO x and SHONO) in North China during July 2018 using an updated soil Nr emissions scheme in a chemical transport model, Unified Inputs (initial and boundary conditions) for Weather Research and Forecasting coupled with Chemistry (UI-WRF-Chem). The effects of soil Nr emissions on O3 pollution, air quality and temperature rise are also studied, with a focus on two key regions, Beijing–Tianjin–Hebei (BTH) and the Fenwei Plain (FWP), known for high soil Nr and anthropogenic emissions. We find that the flux of SNO x is nearly double that of SHONO. The monthly contributions of SNO x and SHONO account, respectively, for 37.3 % and 13.5 % of anthropogenic NOx emissions in BTH and for 29.2 % and 19.2 % in the FWP during July 2018. Soil Nr emissions have a significant impact on surface O3 and nitrate, exceeding SNO x or SHONO effects alone. On average, soil Nr emissions increase maximum daily 8 h (MDA8) O3 by 16.9 % and nitrate concentrations by 42.4 % in BTH, and they increase MDA8 O3 by 17.2 % and nitrate concentrations by 42.7 % in the FWP. Reducing anthropogenic NOx emissions leads to a more substantial suppressive effect of soil Nr emissions on O3 mitigation, particularly in BTH. Soil Nr emissions, through their role as precursors for secondary inorganic aerosols, can result in a slower increase rate of surface air temperature in future emissions reduction scenarios. This study suggests that mitigating O3 pollution and addressing climate change in China should consider the role of soil Nr emissions and their regional differences. [ABSTRACT FROM AUTHOR]

Space-borne formaldehyde (HCHO) column measurements from the Ozone Monitoring Instrument (OMI), with 13 × 24 km2 nadir footprint and daily global coverage, provide new constraints on the spatial distribution of biogenic isoprene emission from North America. OMI HCHO columns for June-August 2006 are consistent with measurements from the earlier GOME satellite sensor (1996-2001) but OMI is 2-14% lower. The spatial distribution of OMI HCHO columns follows that of isoprene emission; anthropogenic hydrocarbon emissions are undetectable except in Houston. We develop updated relationships between HCHO columns and isoprene emission from a chemical transport model (GEOS-Chem), and use these to infer top-down constraints on isoprene emissions from the OMI data. We compare the OMI-derived emissions to a state-of-science bottom-up isoprene emission inventory (MEGAN) driven by two land cover databases, and use the results to optimize the MEGAN emission factors (EFs) for broadleaf trees (the main isoprene source). The OMI-derived isoprene emissions in North America (June-August 2006) with 1° × 1° resolution are spatially consistent with MEGAN (R2 = 0.48-0.68) but are lower (by 4-25% on average). MEGAN overestimates emissions in the Ozarks and the Upper South. A better fit to OMI (R2 = 0.73) is obtained in MEGAN by using a uniform isoprene EF from broadleaf trees rather than variable EFs. Thus MEGAN may overestimate emissions in areas where it specifies particularly high EFs. Within-canopy isoprene oxidation may also lead to significant differences between the effective isoprene emission to the atmosphere seen by OMI and the actual isoprene emission determined by MEGAN. Copyright 2008 by the American Geophysical Union.

Soil emissions of nitrogen compounds, including NO and HONO, play a significant role in atmospheric nitrogen budget. However, HONO has been overlooked in previous research on soil reactive nitrogen (Nr) emissions and their impacts on air quality in China. This study estimates both soil NOx and HONO emissions (SNOx and SHONO) in North China with an updated soil Nr emissions scheme in a chemical transport model, the Unified Inputs for WRF-Chem (UI-WRF-Chem). The effects of soil Nr emissions on O3 pollution, air quality and temperature rise are also studied, with a focus on two key regions, Beijing-Tianjin-Hebei (BTH) and Fenwei Plain (FWP), known for high soil Nr and anthropogenic emissions. We find that the flux of SNOx is nearly doubled those of SHONO; the monthly contributions of SNOx and SHONO account for 37.3% and 13.5% of anthropogenic NOx emissions in the BTH, and 29.2% and 19.2% in the FWP during July 2018, respectively. Soil Nr emissions have a significant impact on surface O3 and nitrate, exceeding SNOx or SHONO effects alone. On average, soil Nr emissions increase MDA8 O3 by 16.9% and nitrate concentrations by 42.4% in the BTH, 17.2% for MDA8 O3 and 42.7% for nitrate in the FWP. Reducing anthropogenic NOx emissions leads to a more substantial suppressive effect of soil Nr emissions on O3 mitigation, particularly in BTH. Soil Nr emissions, via their role as precursors for secondary inorganic aerosols, can result in a slower increase rate of surface air temperature. This study suggests that mitigating O3 pollution and addressing climate change in China should consider the role of soil Nr emission, and their regional differences. [ABSTRACT FROM AUTHOR]

Nitrogen dioxide (NO2) and formaldehyde (HCHO) play vital roles in atmospheric photochemical processes. Their tropospheric vertical column density (TVCD) distributions have been monitored by satellite instruments. Evaluation of these observations is essential for applying these observations to study photochemistry. Assessing satellite products using observations at rural sites, where local emissions are minimal, is particularly useful due in part to the spatial homogeneity of trace gases. In this study, we evaluate OMI and TROPOMI NO2 and HCHO TVCDs using multi‐axis differential optical absorption spectroscopy (MAX‐DOAS) measurements at a rural site in the east coast of the Shandong province, China in spring 2018 during the Ozone Photochemistry and Export from China Experiment (OPECE) measurement campaign. On days not affected by local burning, we found generally good agreement of NO2 data after using consistent a priori profiles in satellite and MAX‐DOAS retrievals and accounting for low biases in scattering weights in one of the OMI products. In comparison, satellite HCHO products exhibited weaker correlations with MAX‐DOAS data, in contrast to satellite NO2 products. However, TROPOMI HCHO products showed significantly better agreement with MAX‐DOAS measurements compared to OMI data. Furthermore, case studies of the vertical profiles measured by MAX‐DOAS on burning days revealed large enhancements of nitrous acid (HONO), NO2, and HCHO in the upper boundary layer, accompanied with considerable variability, particularly in HONO enhancements. Plain Language Summary: We compared satellite NO2 and HCHO tropospheric vertical columns (TVCDs), that is, the integrated column concentrations from the surface to the top of the troposphere, from OMI and TROPOMI instruments with ground‐based MAX‐DOAS measurements in spring 2018 at a rural coastal site in China. Our results on non‐burning days indicate good agreement between satellite products and MAX‐DOAS measurements for NO2 TVCDs, albeit with some biases in one of the products. Potential factors contributing to the biases in that satellite product are investigated. Satellite HCHO products, however, did not compare as well with MAX‐DOAS data as satellite NO2 products, although TROPOMI HCHO products showed better agreement with MAX‐DOAS data than OMI HCHO products. We further analyzed MAX‐DOAS observations of HONO and HCHO on days with nearby agricultural burning activities. We found that HONO, NO2, and HCHO can be significantly enhanced by burning, but the increase due to nearby fires, especially for HONO, is highly variable. Key Points: Satellite NO2 products are in much better agreement with MAX‐DOAS measurements than HCHO productsTROPOMI HCHO products have a significantly lower RMSE and better correlation with MAX‐DOAS data than OMI HCHO productsAgricultural burning can significantly enhance HONO, NO2, and HCHO in the upper boundary layer, but enhancements due to fires, particularly of HONO, are highly variable [ABSTRACT FROM AUTHOR]

A new method is presented for estimating urban hydroxyl radical (OH) concentrations using the downwind decay of the ratio of nitrogen dioxide over carbon monoxide column-mixing ratios (XNO2/XCO) retrieved from the Tropospheric Monitoring Instrument (TROPOMI). The method makes use of plumes simulated by the Weather Research and Forecast model (WRF-Chem) using passive-tracer transport, instead of the encoded chemistry, in combination with auxiliary input variables such as Copernicus Atmospheric Monitoring Service (CAMS) OH, Emission Database for Global Atmospheric Research v4.3.2 (EDGAR) NO x and CO emissions, and National Center for Environmental Protection (NCEP)-based meteorological data. NO 2 and CO mixing ratios from the CAMS reanalysis are used as initial and lateral boundary conditions. WRF overestimates NO 2 plumes close to the center of the city by 15 % to 30 % in summer and 40 % to 50 % in winter compared to TROPOMI observations over Riyadh. WRF-simulated CO plumes differ by 10 % with TROPOMI in both seasons. The differences between WRF and TROPOMI are used to optimize the OH concentration, NO x , CO emissions and their backgrounds using an iterative least-squares method. To estimate OH, WRF is optimized using (a) TROPOMI XNO2/XCO and (b) TROPOMI-derived XNO 2 only. For summer, both the NO2/CO ratio optimization and the XNO 2 optimization increase the prior OH from CAMS by 32 ± 5.3 % and 28.3 ± 3.9 %, respectively. EDGAR NO x and CO emissions over Riyadh are increased by 42.1 ± 8.4 % and 101 ± 21 %, respectively, in summer. In winter, the optimization method doubles the CO emissions while increasing OH by ∼ 52 ± 14 % and reducing NO x emissions by 15.5 ± 4.1 %. TROPOMI-derived OH concentrations and the pre-existing exponentially modified Gaussian function fit (EMG) method differ by 10 % in summer and winter, confirming that urban OH concentrations can be reliably estimated using the TROPOMI-observed NO2/CO ratio. Additionally, our method can be applied to a single TROPOMI overpass, allowing one to analyze day-to-day variability in OH, NO x and CO emission. [ABSTRACT FROM AUTHOR]

Dry deposition is an important ozone sink that impacts ecosystem carbon and water cycling. Ozone dry deposition in forests is regulated by vertical transport, stomatal uptake, and non‐stomatal processes including chemical removal. However, accurate descriptions of these processes in deposition parameterizations are hindered by sparse observational constraints on individual sink terms. Here we quantify the contribution of canopy‐atmosphere turbulent exchange and chemical ozone removal by soil‐emitted nitric oxide (NO) to ozone deposition in a North‐Italian broadleaf deciduous forest. We apply a multi‐layer canopy exchange model to interpret campaign observations of nitrogen oxides (NOx = NO + NO2) and ozone exchange above and inside the forest canopy. Two state‐of‐science parameterizations of in‐canopy vertical diffusivity, based on above‐canopy wind speed or stability, do not reproduce the observed exchange suppressed by canopy‐top radiative heating, resulting in overestimated dry deposition velocities of 10%–19% during daytime. Applying observation‐derived vertical diffusivities in our simulations largely resolves this overestimation. Soil emissions are an important NOx source despite the observed high background NOx levels. Soil NOx emissions decrease the gradient between canopy and surface layer NOx mixing ratios, which suppresses simulated NOx deposition by 80% compared to a sensitivity simulation without soil emissions. However, a sensitivity analysis shows that the enhanced chemical ozone sink by reaction with soil‐emitted NO is offset by increased vertical ozone transport from aloft and suppressed dry deposition. Our results highlight the need for targeted observations of non‐stomatal ozone removal and turbulence‐resolving deposition simulations to improve quantification and model representation of forest ozone deposition. Plain Language Summary: Ozone is a harmful air pollutant that impacts human and ecosystem health. Ozone can be removed by forest ecosystems as a result of air transport into forests followed by plant ozone uptake or chemical removal, but quantifying these individual processes is difficult. We combine model simulations and treetop measurements to study the role of vertical forest‐atmosphere air transport and chemical ozone removal inside the forest. We find that our model can only reproduce surface ozone removal if we account for suppressed transport as derived from observations. The soil is a substantial source of nitric oxide (NO) that reacts with ozone. According to our analysis, the presence of a soil NO source does not lead to increased ozone removal because other ozone sinks are reduced. Our results suggest that individual ozone removal processes in forests can best be studied using targeted observations and models that better resolve forest‐atmosphere exchange. Key Points: We use a multi‐layer canopy‐atmosphere exchange model to interpret ozone flux observations inside and above a North‐Italian forestTwo state‐of‐science vertical exchange parameterizations do not capture in‐canopy stable stratification suppressing ozone depositionSoil nitric oxide emissions do not increase ozone deposition due to compensating effects by deposition and transport [ABSTRACT FROM AUTHOR]

Quantification and control of NOx and CO2 emissions are important across the world to limit adverse climate change. We present a new top-down method, an improved superposition column model to estimate day-to-day NOx and CO2 emissions from the large city of Wuhan, China, located in a polluted background. The lasted released version 2.3.1 TROPOMI NO2 columns and the version 10r of the OCO-2 observed CO2 mixing ratio are employed. Our estimated NOx and CO2 emissions from Wuhan are verified against bottom-up inventories with small deviations (< 3 %). Based on the estimated CO2 emissions, we also predicted daily CO2 column mixing ratio enhancements, which match well with OCO-2 observations (< 5 % bias, within ±0.3 ppm). We capture the day-to-day variation of NOx and CO2 emissions from Wuhan in 2019-2020, which does not reveal a substantial 'weekend reduction' but does show a clear 'holiday reduction' in the NOx and CO2 emissions. Our method also quantifies the abrupt decrease and slow rebound of NOx and CO2 emissions due to the Wuhan lockdown in early 2020. This work demonstrates the improved superposition model to be a promising new tool for the quantification of city NOx and CO2 emissions, allowing policy makers to gain real-time information into spatial-temporal emission patterns and the effectiveness of carbon and nitrogen regulation in urban environments. [ABSTRACT FROM AUTHOR]