Ground and satellite observations show that air pollution regulations in the United States (US) have resulted in substantial reductions in emissions and corresponding improvements in air quality over ...the last several decades. However, large uncertainties remain in evaluating how recent regulations affect different emission sectors and pollutant trends. Here we show a significant slowdown in decreasing US emissions of nitrogen oxides (NOₓ) and carbon monoxide (CO) for 2011–2015 using satellite and surface measurements. This observed slowdown in emission reductions is significantly different from the trend expected using US Environmental Protection Agency (EPA) bottom-up inventories and impedes compliance with local and federal agency air-quality goals. We find that the difference between observations and EPA’s NOₓ emission estimates could be explained by: (i) growing relative contributions of industrial, area, and off-road sources, (ii) decreasing relative contributions of on-road gasoline, and (iii) slower than expected decreases in on-road diesel emissions.
Full text
Available for:
BFBNIB, NMLJ, NUK, PNG, SAZU, UL, UM, UPUK
During the 1997 to 1998 El Niño, drought conditions triggered widespread increases in fire activity, releasing CH4and CO2to the atmosphere. We evaluated the contribution of fires from different ...continents to variability in these greenhouse gases from 1997 to 2001, using satellite-based estimates of fire activity, biogeochemical modeling, and an inverse analysis of atmospheric CO anomalies. During the 1997 to 1998 El Niño, the fire emissions anomaly was$2.1 \pm 0.8$petagrams of carbon, or$66 \pm 24%$of the CO2growth rate anomaly. The main contributors were Southeast Asia (60%), Central and South America (30%), and boreal regions of Eurasia and North America (10%).
Full text
Available for:
BFBNIB, NMLJ, NUK, PNG, SAZU, UL, UM, UPUK
Long-term measurements from satellites and surface stations have demonstrated a decreasing trend of tropospheric carbon monoxide (CO) in the Northern Hemisphere over the past decade. Likely ...explanations for this decrease include changes in anthropogenic, fires, and/or biogenic emissions or changes in the primary chemical sink hydroxyl radical (OH). Using remotely sensed CO measurements from the Measurement of Pollution in the Troposphere (MOPITT) satellite instrument, in situ methyl chloroform (MCF) measurements from the World Data Centre for Greenhouse Gases (WDCGG) and the adjoint of the GEOS-Chem model, we estimate the change in global CO emissions from 2001 to 2015. We show that the loss rate of MCF varied by 0.2 % in the past 15 years, indicating that changes in global OH distributions do not explain the recent decrease in CO. Our two-step inversion approach for estimating CO emissions is intended to mitigate the effect of bias errors in the MOPITT data as well as model errors in transport and chemistry, which are the primary factors contributing to the uncertainties when quantifying CO emissions using these remotely sensed data. Our results confirm that the decreasing trend of tropospheric CO in the Northern Hemisphere is due to decreasing CO emissions from anthropogenic and biomass burning sources. In particular, we find decreasing CO emissions from the United States and China in the past 15 years, and unchanged anthropogenic CO emissions from Europe since 2008. We find decreasing trends of biomass burning CO emissions from boreal North America, boreal Asia and South America, but little change over Africa. In contrast to prior results, we find that a positive trend in CO emissions is likely for India and southeast Asia.
Global coupled chemistry-climate models underestimate carbon monoxide (CO) in the Northern Hemisphere, exhibiting a pervasive negative bias against measurements peaking in late winter and early ...spring. While this bias has been commonly attributed to underestimation of direct anthropogenic and biomass burning emissions, chemical production and loss via OH reaction from emissions of anthropogenic and biogenic volatile organic compounds (VOCs) play an important role. Here we investigate the reasons for this underestimation using aircraft measurements taken in May and June 2016 from the Korea-United States Air Quality (KORUS-AQ) experiment in South Korea and the Air Chemistry Research in Asia (ARIAs) in the North China Plain (NCP). For reference, multispectral CO retrievals (V8J) from the Measurements of Pollution in the Troposphere (MOPITT) are jointly assimilated with meteorological observations using an ensemble adjustment Kalman filter (EAKF) within the global Community Atmosphere Model with Chemistry (CAM-Chem) and the Data Assimilation Research Testbed (DART). With regard to KORUS-AQ data, CO is underestimated by 42% in the control run and by 12% with the MOPITT assimilation run. The inversion suggests an underestimation of anthropogenic CO sources in many regions, by up to 80% for northern China, with large increments over the Liaoning Province and the North China Plain (NCP). Yet, an often-overlooked aspect of these inversions is that correcting the underestimation in anthropogenic CO emissions also improves the comparison with observational O
datasets and observationally constrained box model simulations of OH and HO
. Running a CAM-Chem simulation with the updated emissions of anthropogenic CO reduces the bias by 29% for CO, 18% for ozone, 11% for HO
, and 27% for OH. Longer-lived anthropogenic VOCs whose model errors are correlated with CO are also improved, while short-lived VOCs, including formaldehyde, are difficult to constrain solely by assimilating satellite retrievals of CO. During an anticyclonic episode, better simulation of O
, with an average underestimation of 5.5 ppbv, and a reduction in the bias of surface formaldehyde and oxygenated VOCs can be achieved by separately increasing by a factor of 2 the modeled biogenic emissions for the plant functional types found in Korea. Results also suggest that controlling VOC and CO emissions, in addition to widespread NO
controls, can improve ozone pollution over East Asia.
While meteorology and aerosols are identified as key drivers of snow cover (SC) variability in High Mountain Asia, complex non‐linear interactions between them are not adequately quantified. Here, we ...attempt to unravel these interactions through a simple relative importance (RI) analysis of meteorological and aerosol variables from ERA5/CAMS‐EAC4 reanalysis against satellite‐derived SC from Moderate Resolution Imaging Spectroradiometer across 2003–2018. Our results show a statistically significant 7% rise in the RI of aerosol‐meteorology interactions (AMI) in modulating SC during late snowmelt season (June and July), notably over low snow‐covered (LSC) regions. Sensitivity tests further reveal that the importance of meteorological interactions with individual aerosol species are more prominent than total aerosols over LSC regions. We find that the RI of AMI for LSC regions is clearly dominated by carbonaceous aerosols, on top of the expected importance of dynamic meteorology. These findings clearly highlight the need to consider AMI in hydrometeorological monitoring, modeling, and reanalyses.
Plain Language Summary
Understanding the changes in snow cover (SC) over glaciers in High Mountain Asia (HMA) is important yet challenging. Despite its impact on water resources, physical processes that drive these changes are complex. In particular, large‐scale weather patterns, together with aerosol pollution hotspots in the vicinity, and its steep elevation strongly interact with each other. We use a statistical approach to assess the relevance of these interactions using geophysical data from present day reanalysis and observed SC extent from satellite products for two decades. We find that during the late snowmelt period from June to July, interactions between aerosols and meteorology are significant, specifically in low SC regions. Interactions of individual aerosol species, especially carbonaceous aerosols like black carbon are more important than total aerosol concentration. This approach in quantifying the interactions of these processes can help improve the monitoring and modeling of snow hydrology. Representing these relevant interactions in current models and reanalysis of hydrometeorology can lead to more accurate predictions of the state of snow for critical regions like HMA.
Key Points
Interactions between aerosols and meteorology are significant during late snowmelt (June and July) over low snow‐covered regions in High Mountain Asia
Species related interactions drive the seasonal variability of the overall relative importance
Carbonaceous aerosols are more relevant than mineral dust during late snowmelt
Full text
Available for:
FZAB, GIS, IJS, KILJ, NLZOH, NUK, OILJ, SAZU, SBCE, SBMB, UL, UM, UPUK
A ratio-based method is used to characterize anthropogenic elemental carbon (ECa) using in situ measurements and emissions of carbon monoxide (CO) and nitrogen oxides (NO x ). We use long-term ...records of ground-based measurements from the U.S. Environmental Protection Agency (EPA) Air Quality System and Interagency Monitoring of Protected Visual Environments to assess the patterns in anthropogenic combustion ratios (ΔECa/ΔCO and ΔECa/ΔNO x ) across the U.S. Petroleum Administration for Defense Districts (PADD) regions for the years 2000–2015. We investigate the change in these ratios between the periods 2000–2007 and 2008–2015. Overall, ΔECa/ΔCO ratios increase by 0.7–82% and ΔECa/ΔNO x by 6.8–104% across the East and West PADD regions. The urban West showed the largest increase relative to other regions. This is mainly attributed to a 13–23% increase in ΔECa during the winter and fall seasons and significant reductions in urban ΔNO x (except in winter). We also find that emission ratios derived from the EPA’s National Emission Inventory (NEI) overestimate (underestimate) the increase in the observed enhancement ratios in the East (West). Analyses of changes in NEI emissions in the West reveal (a) smaller reductions in NEI emissions for NO x from the off-road sector and (b) an increase in PM2.5 (particulate matter 2.5 μm or less in diameter) emissions from commercial/residential combustion and smaller reductions in nonroad emissions.
Full text
Available for:
IJS, KILJ, NUK, PNG, UL, UM
While pesticide vapor and particles from agricultural spray drift have been reported to pose a risk to public health, limited baseline ambient measurements exist to warrant an accurate assessment of ...their impacts at community-to-county-wide scale. Here, we present an initial modeling investigation of the transport and deposition of applied pesticides in an agricultural county in Arizona (Yuma County), to provide initial estimates on the corresponding enhancements in ambient levels of these spray drifts downwind of application sites. With a 50 × 50 km domain, we use the dispersion model CALPUFF with meteorology from the Weather Research and Forecasting (WRF) to investigate the spatiotemporal distribution of pesticide abundance due to spray drift from a representative sample of nine application sites. Data records for nine application days in September and October 2011, which are the peak months of pesticide application, were retroactively simulated for 48-h for all nine application sites using an active ingredient lambda-cyhalothrin, which is a commonly-used pesticide in the county. Twenty-one WRF/CALPUFF simulations were conducted with varying emissions, chemical lifetime, deposition rate, application height, and meteorology inputs, allowing for an ensemble-based analysis on the possible ranges in modeled abundance. Our results show that dispersion of vapors released at time of application heavily depends on prevailing meteorology, particularly wind speed and direction. Dispersion is limited to thin plumes that are easily transported out of the domain. The ensemble-mean vapor concentrations of the 48-h average (> 90 percentile domain-wide) range from 0.2 nanograms (ng)/m
to 200 ng/m
, and the peak can be as high as 1000 ng/m
near the application sites. Pesticide particles are mainly deposited within 1-2 km from the application sites at an average rate of 10
ng/km
/h but vary with particle mean diameter and standard deviation. While these findings are generally consistent with reported ambient levels in the literature, the associated ensemble-spread on these estimates are in the same order of magnitude as their ensemble-mean. At the two nearby communities downwind of these sites, we find that peak vapor concentrations are less than 50 ng/m
with exposure times of less than an hour, as approximately 99.4% of the vapors are advected out and 99.5% of the particles deposit within the domain. Results of this study indicate pesticide spray drift from a sample of application sites and representative days in Fall may have a limited impact on neighboring communities. However, we strongly suggest that field measurements should be collected for model validation and more rigorous investigation of the actual scale of these impacts when the bulk of pesticide applications across the county, variation in active pesticide ingredients, and potential resuspension of deposited particles are considered.
Full text
Available for:
GEOZS, IJS, IMTLJ, KILJ, KISLJ, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UL, UM, UPCLJ, UPUK
A statistical analysis of data from the Interagency Monitoring of Protected Visual Environments (IMPROVE) network of aerosol samplers has been used to study the spatial and temporal concentration ...trends in airborne particulate metals and metalloids for southern Arizona. The study region is a rapidly growing area in southwestern North America characterized by high fine soil concentrations (among the highest in the United States), anthropogenic emissions from an area within the fastest growing region in the United States, and a high density of active and abandoned mining sites. Crustal tracers in the region are most abundant in the summer (April–June) followed by fall (October–November) as a result of dry meteorological conditions which favor dust emissions from natural and anthropogenic activity. A distinct day-of-week cycle is evident for crustal tracer mass concentrations, with the greatest amplitude evident in urban areas. There have been significant reductions since 1988 in the concentrations of toxic species that are typically associated with smelting and mining. Periods with high fine soil concentrations coincide with higher concentrations of metals and metalloids in the atmosphere, with the enhancement being higher at urban sites.
•Spatiotemporal analysis of PM2.5 elemental composition in southern Arizona.•Concentrations of crustal elements exhibit a distinct day-of-week pattern.•There have been significant reductions in toxic species concentrations since 1988.•Toxic element concentrations are enhanced during ‘dust events’ in urban areas.•Phoenix has the highest concentrations of airborne Cu, Zn, and crustal elements.
Full text
Available for:
GEOZS, IJS, IMTLJ, KILJ, KISLJ, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UL, UM, UPCLJ, UPUK
We demonstrate the feasibility of using observing system simulation experiment (OSSE) studies to help define quantitative trace gas measurement requirements for satellite missions and to evaluate the ...expected performance of proposed observing strategies. The 2007 U.S. National Research Council Decadal Survey calls for a geostationary (GEO) satellite mission for atmospheric composition and air quality applications (Geostationary Coastal and Air Pollution Events Mission (GEO‐CAPE)). The requirement includes a multispectral (near‐infrared and thermal infrared) measurement of carbon monoxide (CO) at high spatiotemporal resolution with information on lowermost troposphere concentration. We present an OSSE to assess the improvement in surface CO characterization that would result from the addition of a GEO‐CAPE CO measurement to current low Earth orbit (LEO) thermal infrared‐only measurements. We construct instrument simulators for these two measurement scenarios and study the case of July 2004 when wildfires in Alaska and Canada led to significant CO pollution over the contiguous United States. Compared to a control experiment, an ensemble‐based data assimilation of simulated satellite observations in a global model leads to improvements in both the surface CO distributions and the time evolution of CO profiles at locations affected by wildfire plumes and by urban emissions. In all cases, an experiment with the GEO‐CAPE CO measurement scenario (overall model skill of 0.84) performed considerably better than the experiment with the current LEO/thermal infrared measurement (skill of 0.58) and the control (skill of 0.07). This demonstrates the advantages of increased sampling from GEO and enhanced measurement sensitivity to the lowermost troposphere with a multispectral retrieval.
This paper introduces the Weather Research and Forecasting Model with chemistry/Data Assimilation Research Testbed (WRF-Chem/DART) chemical transport forecasting/data assimilation system together ...with the assimilation of compact phase space retrievals of satellite-derived atmospheric composition products. WRF-Chem is a state-of-the-art chemical transport model. DART is a flexible software environment for researching ensemble data assimilation with different assimilation and forecast model options. DART's primary assimilation tool is the ensemble adjustment Kalman filter. WRF-Chem/DART is applied to the assimilation of Terra/Measurement of Pollution in the Troposphere (MOPITT) carbon monoxide (CO) trace gas retrieval profiles. Those CO observations are first assimilated as quasi-optimal retrievals (QORs). Our results show that assimilation of the CO retrievals (i) reduced WRF-Chem's CO bias in retrieval and state space, and (ii) improved the CO forecast skill by reducing the Root Mean Square Error (RMSE) and increasing the Coefficient of Determination (R2). Those CO forecast improvements were significant at the 95 % level. Trace gas retrieval data sets contain (i) large amounts of data with limited information content per observation, (ii) error covariance cross-correlations, and (iii) contributions from the retrieval prior profile that should be removed before assimilation. Those characteristics present challenges to the assimilation of retrievals. This paper addresses those challenges by introducing the assimilation of compact phase space retrievals (CPSRs). CPSRs are obtained by preprocessing retrieval data sets with an algorithm that (i) compresses the retrieval data, (ii) diagonalizes the error covariance, and (iii) removes the retrieval prior profile contribution. Most modern ensemble assimilation algorithms can efficiently assimilate CPSRs. Our results show that assimilation of MOPITT CO CPSRs reduced the number of observations (and assimilation computation costs) by ∼ 35 %, while providing CO forecast improvements comparable to or better than with the assimilation of MOPITT CO QORs.
Full text
Available for:
IZUM, KILJ, NUK, PILJ, PNG, SAZU, UL, UM, UPUK
PDF
