Search

Modeling atmospheric chemistry at fine resolution globally is computationally expensive; the capability to focus on specific geographic regions using a multiscale grid is desirable. Here, we develop, validate, and demonstrate stretched grids in the GEOS-Chem atmospheric chemistry model in its high-performance implementation (GCHP). These multiscale grids are specified at runtime by four parameters that offer users nimble control of the region that is refined and the resolution of the refinement. We validate the stretched-grid simulation versus global cubed-sphere simulations. We demonstrate the operation and flexibility of stretched-grid simulations with two case studies that compare simulated tropospheric NO 2 column densities from stretched-grid and cubed-sphere simulations to retrieved column densities from the TROPOspheric Monitoring Instrument (TROPOMI). The first case study uses a stretched grid with a broad refinement covering the contiguous US to produce simulated columns that perform similarly to a C180 (∼ 50 km) cubed-sphere simulation at less than one-ninth the computational expense. The second case study experiments with a large stretch factor for a global stretched-grid simulation with a highly localized refinement with ∼ 10 km resolution for California. We find that the refinement improves spatial agreement with TROPOMI columns compared to a C90 cubed-sphere simulation of comparable computational demands. Overall, we find that stretched grids in GEOS-Chem are a practical tool for fine-resolution regional- or continental-scale simulations of atmospheric chemistry. Stretched grids are available in GEOS-Chem version 13.0.0. [ABSTRACT FROM AUTHOR]

We present a new divergence method to estimated methane (CH4) emissions from satellite observed mean mixing ratio of methane (XCH4) by deriving the regional enhancement of XCH4 in the Planetary Boundary Layer (PBL). The applicability is proven by comparing the estimated emissions with its known emission inventory from a 3‐month GEOS‐Chem simulation. When applied to TROPOspheric Monitoring Instrument observations, sources from well‐known oil/gas production areas, livestock farms and wetlands in Texas become clearly visible in the emission maps. The calculated yearly averaged total CH4 emission over the Permian Basin is 3.06 (2.82, 3.78) Tg a−1 for 2019, which is consistent with previous studies and double that of EDGAR v4.3.2 for 2012. Sensitivity tests on PBL heights, on the derived regional background and on wind speeds suggest our divergence method is quite robust. It is also a fast and simple method to estimate the CH4 emissions globally. Plain Language Summary: Methane (CH4) is an important greenhouse gas in the atmosphere and plays a crucial role in the global climate change. It kept increasing over the last decades. About 70% of CH4 comes from human activities like oil/gas productions or livestock farms. The recently launched TROPOspheric Monitoring Instrument provides an opportunity to estimate the emissions of CH4 on a regional scale. This work presents a new method to fastly derive CH4 emissions at a fairly high spatial resolution without a priori knowledge of sources. Key Points: A new divergence method is developed to estimate methane emissions based on satellite observations, requiring no a priori emissionsThe applicability of this method in identifying and quantifying sources is proven by a GEOS‐Chem simulation with known emission inventoryThe estimated emissions over Texas (United States) based on TROPOspheric Monitoring Instrument observations are evaluated and are found to be robust [ABSTRACT FROM AUTHOR]

We present a new product with explicit aerosol corrections, POMINO-TROPOMI, for tropospheric nitrogen dioxide (NO2) vertical column densities (VCDs) over East Asia, based on the newly launched TROPOspheric Monitoring Instrument with an unprecedented high horizontal resolution. Compared to the official TM5-MP-DOMINO (OFFLINE) product, POMINO-TROPOMI shows stronger concentration gradients near emission source locations and better agrees with MAX-DOAS measurements (R2=0.75 ; NMB=0.8 % versus R2=0.68 , NMB=-41.9 %). Sensitivity tests suggest that implicit aerosol corrections, as in TM5-MP-DOMINO, lead to underestimations of NO2 columns by about 25 % over the polluted northern East China region. Reducing the horizontal resolution of a priori NO2 profiles would underestimate the retrieved NO2 columns over isolated city clusters in western China by 35 % but with overestimates of more than 50 % over many offshore coastal areas. The effect of a priori NO2 profiles is more important under calm conditions. [ABSTRACT FROM AUTHOR]

Seven scenarios were designed to study the national environmental benefits of ULE in coal-fired power plants (CPPs), ULE in industrial coal burning (ICB) and NH3 emission reduction by using the GEOS-Chem model. The results showed that although the CPPs have achieved the ULE transformation target, the PM2.5 concentration across the country has decreased by 4.8% (1.4 μg/m3). Due to the complex non-linear chemical competition mechanism among nitrate and sulfate, the average concentration of nitrate in the country has increased by 1.5% (0.1 μg/m3), which has reduced the environmental benefits of the power plant emission reduction. If the ULE technology is applied to the ICB to further reduce NOx and SO2, although the PM2.5 concentration can be reduced by 10.1% (2.9 μg/m3), the concentration of nitrate will increase by 2.7% (0.2 μg/m3). Based on the CPPs-ULE, NH3 emissions reduced by 30% and 50% can significantly reduce the concentration of ammonium and nitrate, so that the PM2.5 concentration is decreased by 11.5% (3.3 μg/m3) and 16.5% (4.7 μg/m3). Similarly, based on the CPPs-ICB-ULE, NH3 emissions can be reduced by 30% and 50% and the PM2.5 concentration reduced by 15.6% (4.4 μg/m3) and 20.3% (5.8 μg/m3). The CPPs and ICB use the ULE technology to reduce NOx and SO2, thereby reducing the concentration of ammonium and sulfate, causing the PM2.5 concentration to decline, and NH3 reduction is mainly achieved through reducing the concentration of ammonium and nitrate to reduce the concentration of PM2.5. In order to better reduce the concentration of PM2.5, NOx, SO2 and NH3 emission reduction control measures should be comprehensively considered in different regions of China. By comprehensively considering the economic cost and environmental benefits of ULE in ICB and NH3 emission reduction, an optimal haze control scheme can be determined. [ABSTRACT FROM AUTHOR]

Despite much effort made in studying human health associated with fine particulate matter (PM 2.5), our knowledge about PM 2.5 and human health from a long-term perspective is still limited by inadequately long data. Here, we presented a novel method to retrieve surface PM 2.5 mass concentrations using surface visibility measurements and GEOS-Chem model simulations. First, we used visibility measurements and the ratio of PM 2.5 and aerosol extinction coefficient (AEC) in GEOS-Chem to calculate visibility-inferred PM 2.5 at individual stations (SC-PM 2.5). Then we merged SC-PM 2.5 with the spatial pattern of GEOS-Chem modeled PM 2.5 to obtain a gridded PM 2.5 dataset (GC-PM 2.5). We validated the GC-PM 2.5 data over the North China Plain on a 0.3125° longitude x 0.25° latitude grid in January, April, July and October 2014, using ground-based PM 2.5 measurements. The spatial patterns of temporally averaged PM 2.5 mass concentrations are consistent between GC-PM 2.5 and measured data with a correlation coefficient of 0.79 and a linear regression slope of 0.8. The spatial average GC-PM 2.5 data reproduce the day-to-day variation of observed PM 2.5 concentrations with a correlation coefficient of 0.96 and a slope of 1.0. The mean bias is less than 12 μg/m3 (<14%). Future research will validate the proposed method using multi-year data, for purpose of studying long-term PM 2.5 variations and their health impacts since 1980. • We integrate visibility data and GEOS-Chem simulations to estimate PM 2.5 concentrations in 2014 over North China. • Visibility converted PM 2.5 are spatiotemporally consistent with PM 2.5 measurements. • Our method provides a novel, plausible way to retrieve long-term variation of PM 2.5. [ABSTRACT FROM AUTHOR]

Ambient near-surface ozone pollution threatens public health. Over the past decades, the world has seen complex ozone changes across the globe, with important implications for public health. Previous studies have estimated premature mortality attributable to ozone exposure in more recent years, yet a historical assessment of the health impacts of ozone is largely lacking. Contrary to controlling many other air pollutants endangering public health, reducing ozone pollution is complicated by its nonlinear chemistry and complex relationship with precursor emissions. A historical evaluation is crucial to understanding the long-term changes in surface ozone concentration, driving factors, and health implications. This study uses chemical transport model simulations, ground measurements, and pollution-health response models to estimate the ozone changes over the past few decades, their health impacts, and the effectiveness of precursor emission control. Our results will help improve the ozone mitigation strategies on the global scale. [ABSTRACT FROM AUTHOR]

Emission datasets of nitrogen oxides (NOx) at high horizontal resolutions (e.g., 0.05°×0.05°) are crucial for understanding human influences at fine scales, air quality studies, and pollution control. Yet high-resolution emission data are often lacking or contain large uncertainties especially for the developing regions. Taking advantage of long-term satellite measurements of nitrogen dioxide (NO2), here we develop a computationally efficient method to inverting NOx emissions in major urban areas at the 0.05°×0.05° resolution. The inversion accounts for the nonlinear effects of horizontal transport, chemical loss, and deposition. We construct a 2-dimensional Peking University High-resolution Lifetime-Emission-Transport (PHLET) model, its adjoint model (PHLET-A), and a Satellite Conversion Metrix approach to relate emissions, simulated NO2, and satellite NO2 data. The inversion method is applied to summer months of 2012–2016 in the Yangtze River Delta area (YRD, 118°E-123°E, 29°N-34°N), a major polluted region of China, using the POMINO NO2 vertical column density product retrieved from the Ozone Monitoring Instrument. A systematic analysis of inversion errors is performed, including using an Observing System Simulation Experiment-like test. Across the YRD area, the inverted summer average emission ranges from 0 to 12.0 kg km-2 h-1, and the lifetime (due to chemical loss and deposition) from 1.4 to 3.6 h. Our inverted emission dataset reveals fine-scale spatial information tied to nighttime light, population density, road network, and maritime shipping. Many of the inverted fine-scale emission features are not well represented or not included in the widely used Multi-scale Emissions Inventory of China. Our inversion method can be applied to other regions and other satellite sensors such as the TROPOspheric Monitoring Instrument. [ABSTRACT FROM AUTHOR]