Dataset Information

Inferring Changes in Summertime Surface Ozone-NO_x-VOC Chemistry over U.S. Urban Areas from Two Decades of Satellite and Ground-Based Observations.

ABSTRACT: Urban ozone (O₃) formation can be limited by NO_x, VOCs, or both, complicating the design of effective O₃ abatement plans. A satellite-retrieved ratio of formaldehyde to NO₂ (HCHO/NO₂), developed from theory and modeling, has previously been used to indicate O₃ formation chemistry. Here, we connect this space-based indicator to spatiotemporal variations in O₃ recorded by on-the-ground monitors over major U.S. cities. High-O₃ events vary nonlinearly with OMI HCHO and NO₂, and the transition from VOC-limited to NO_x-limited O₃ formation regimes occurs at higher HCHO/NO₂ value (3 to 4) than previously determined from models, with slight intercity variations. To extend satellite records back to 1996, we develop an approach to harmonize observations from GOME and SCIAMACHY that accounts for differences in spatial resolution and overpass time. Two-decade (1996-2016) multisatellite HCHO/NO₂ captures the timing and location of the transition from VOC-limited to NO_x-limited O₃ production regimes in major U.S. cities, which aligns with the observed long-term changes in urban-rural gradient of O₃ and the reversal of O₃ weekend effect. Our findings suggest promise for applying space-based HCHO/NO₂ to interpret local O₃ chemistry, particularly with the new-generation satellite instruments that offer finer spatial and temporal resolution.

SUBMITTER: Jin X

PROVIDER: S-EPMC7996126 | biostudies-literature |

REPOSITORIES: biostudies-literature

ACCESS DATA

Similar Datasets

Project description:The World Health Organization (WHO) declared the coronavirus disease of 2019 (COVID-19) as a pandemic due to its widespread global infection. This has resulted in lockdown under different phases in many nations, including India, around the globe. In the present study, we report the impact of aerosols on surface ozone in the context of pre-lockdown (01st - 24th March 2020 (PLD)), lockdown phase1 (25th March to 14th April 2020 (LDP1)), and lockdown phase 2 (15th April to 03rd May 2020 (LDP2)) on clear days at a semi-arid site, Anantapur in southern India using both in situ observations and model simulations. Collocated measurements of surface ozone (O3), aerosol optical depth (AOD), black carbon mass concentration (BC), total columnar ozone (TCO), solar radiation (SR), and ultraviolet radiation (UV-A) data were collected using an Ozone analyzer, MICROTOPS sunphotometer, Ozonometer, Aethalometer, and net radiometer during the study period. The diurnal variations of O3 and BC exhibited an opposite trend during three phases. The concentrations of ozone were ~10.7% higher during LDP1 (44.8 ± 5.2 ppbv) than the PLD (40.5 ± 6.0 ppbv), which mainly due to an unprecedented reduction in NOx emissions leading to a lower O3 titration by NO. The prominent increase in the surface zone during LDP1 is reasonably consistent with the observed photolysis frequencies (j (O1D)) through Tropospheric Ultraviolet and Visible (TUV) model. The results show that a pronounced spectral and temporal variability in the AOD during three lockdown phases is mainly due to distinct aerosol sources. The increase in AOD during LDP2 due to long-range transport can bring large amounts of mineral dust and smoke aerosols from the west Asian region and central India, and which is reasonably consistent with the Hybrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT) air mass back trajectories and Moderate Resolution Imaging Spectroradiometer (MODIS) fire counts analysis over the measurement location. Overall, a drastic reduction in BC concentration (~8.4%) and AOD (10.8%) were observed in the semi-arid area during LDP1 with correspondence to PLD. The columnar aerosol size distributions retrieved from the spectral AODs followed power-law plus unimodal during three phases. The absorption angstrom exponent (AAE) analysis reveals a predominant contribution to the BC from biomass burning activities during the lockdown period over the measurement location.

Project description:Wildland fires are a major source of fine particulate matter (PM2.5), one of the most harmful ambient pollutants for human health globally. To represent the influence of wildland fire emissions on atmospheric composition, regional and global chemical transport models rely on emission inventories developed from estimates of burned area (i.e. fire size and location). While different methods of estimating annual burned area agree reasonably well in the western U.S. (within 20-30% for most years during 2002-2014), estimates for the southern U.S. can vary by more than a factor of 5. These differences in burned area lead to significant variability in the spatial and temporal allocation of emissions across fire emission inventory platforms. In this work, we implement wildland fire emission estimates for 2011 from three different products - the USEPA National Emission Inventory (NEI), the Fire Inventory of NCAR (FINN), and the Global Fire Emission Database (GFED4s) - into the Community Multiscale Air Quality (CMAQ) model to quantify and characterize differences in simulated PM and ozone concentrations across the contiguous U.S. (CONUS) due to the fire emission inventory used. The NEI is developed specifically for the U.S., while both FINN and GFED4s are available globally. We find that NEI emissions lead to the largest increases in modeled annual average PM2.5 (0.85 μg m-3) and April-September maximum daily 8-h ozone (0.28 ppb) nationally compared to a "no fire" baseline, followed by FINN (0.33 μg m-3 and 0.22 ppb) and GFED4s (0.12 μg m-3 and 0.17 ppb). Annual mean enhancements in wildland fire pollution are highest in the southern U.S. across all three inventories (over 4 μg m-3 and 2 ppb in some areas), but show considerable spatial variability within these regions. We also examine the representation of five individual fire events during 2011 and find that of the two global inventories, FINN reproduces more of the acute changes in pollutant concentrations modeled with NEI and shown in surface observations during each of the episodes investigated compared to GFED4s. Understanding the sensitivity of modeling fire-related PM2.5 and ozone in the U.S. to burned area estimation approaches will inform future efforts to assess the implications of present and future fire activity for air quality and human health at national and global scales.

Dataset Information

Inferring Changes in Summertime Surface Ozone-NO_x-VOC Chemistry over U.S. Urban Areas from Two Decades of Satellite and Ground-Based Observations.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets

Dataset Information

Inferring Changes in Summertime Surface Ozone-NOx-VOC Chemistry over U.S. Urban Areas from Two Decades of Satellite and Ground-Based Observations.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets

Inferring Changes in Summertime Surface Ozone-NO_x-VOC Chemistry over U.S. Urban Areas from Two Decades of Satellite and Ground-Based Observations.