76 research outputs found
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Using synthetic tracers as a proxy for summertime PM2.5 air quality over the Northeastern United States in physical climate models
Fine particulate matter (PM2.5) is a criteria pollutant. Its sensitivity to meteorology implies its distribution will likely change with climate shifts. Limited availability of global climate models with full chemistry complicates efforts to assess rigorously the uncertainties in the PM2.5 response to a warming climate. We evaluate the potential for PM2.5 distributions in a chemistry-climate model under current-day and warmer climate conditions over the Northeastern United States to be represented by a Synthetic Aerosol tracer (SAt). The SAt implemented into the Geophysical Fluid Dynamics Laboratory chemistry-climate model (AM3) follows the protocol of a recent multimodel community effort (HTAP), with CO emissions, 25-day chemical lifetime, and wet deposition rate of sulfate. Over the Northeastern United States, the summer daily time series of SAt correlates strongly with that of PM2.5, with similar cumulative density functions under both present and future climate conditions. With a linear regression model derived from PM2.5 and SAt in the current-day simulation, we reconstruct both the current-day and future PM2.5 daily time series from the simulated SAt. This reconstruction captures the summer mean PM2.5, the incidence of days above the 24-h mean PM2.5 NAAQS, and PM2.5 responses to climate change. This reconstruction also works over other polluted Northern Hemispheric regions and in spring. Our proof-of-concept study demonstrates that simple tracers can be developed to mimic PM2.5, including its response to climate change, as an easy-to-implement and low-cost addition to physical climate models that should help air quality managers to reap the benefits of climate models that have no chemistry
Climate variability modulates western US ozone air quality in spring via deep stratospheric intrusions
Evidence suggests deep stratospheric intrusions can elevate western US surface ozone to unhealthy levels during spring. These intrusions can be classified as ‘exceptional events’, which are not counted towards non-attainment determinations. Understanding the factors driving the year-to-year variability of these intrusions is thus relevant for effective implementation of the US ozone air quality standard. Here we use observations and model simulations to link these events to modes of climate variability. We show more frequent late spring stratospheric intrusions when the polar jet meanders towards the western United States, such as occurs following strong La Niña winters (Niño3.4<−1.0 °C). While El Niño leads to enhancements of upper tropospheric ozone, we find this influence does not reach surface air. Fewer and weaker intrusion events follow in the two springs after the 1991 volcanic eruption of Mt. Pinatubo. The linkage between La Niña and western US stratospheric intrusions can be exploited to provide a few months of lead time during which preparations could be made to deploy targeted measurements aimed at identifying these exceptional events
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Assessment of source contributions to seasonal vegetative exposure to ozone in the U.S.
W126 is a cumulative ozone exposure index based on sigmoidally weighted daytime ozone concentrations used to evaluate the impacts of ozone on vegetation. We quantify W126 in the U.S. in the absence of North American anthropogenic emissions (North American background or “NAB”) using three regional or global chemical transport models for May–July 2010. All models overestimate W126 in the eastern U.S. due to a persistent bias in daytime ozone, while the models are relatively unbiased in California and the Intermountain West. Substantial difference in the magnitude and spatial and temporal variability of the estimates of W126 NAB between models supports the need for a multimodel approach. While the average NAB contribution to daytime ozone in the Intermountain West is 64–78%, the average W126 NAB is only 9–27% of current levels, owing to the weight given to high O3 concentrations in W126. Based on a three-model mean, NAB explains ~30% of the daily variability in the W126 daily index in the Intermountain West. Adjoint sensitivity analysis shows that nationwide W126 is influenced most by NOx emissions from anthropogenic (58% of the total sensitivity) and natural (25%) sources followed by nonmethane volatile organic compounds (10%) and CO (7%). Most of the influence of anthropogenic NOx comes from the U.S. (80%), followed by Canada (9%), Mexico (4%), and China (3%). Thus, long-range transport of pollution has a relatively small impact on W126 in the U.S., and domestic emissions control should be effective for reducing W126 levels
Springtime high surface ozone events over the western United States: Quantifying the role of stratospheric intrusions
The published literature debates the extent to which naturally occurring stratospheric ozone intrusions reach the surface and contribute to exceedances of the U.S. National Ambient Air Quality Standard (NAAQS) for ground-level ozone (75 ppbv implemented in 2008). Analysis of ozonesondes, lidar, and surface measurements over the western U.S. from April to June 2010 show that a global high-resolution (∼50 × 50 km2) chemistry-climate model (GFDL AM3) captures the observed layered features and sharp ozone gradients of deep stratospheric intrusions, representing a major improvement over previous chemical transport models. Thirteen intrusions enhanced total daily maximum 8-h average (MDA8) ozone to ∼70–86 ppbv at surface sites. With a stratospheric ozone tracer defined relative to a dynamically varying tropopause, we find that stratospheric intrusions can episodically increase surface MDA8 ozone by 20–40 ppbv (all model estimates are bias corrected), including on days when observed ozone exceeds the NAAQS threshold. These stratospheric intrusions elevated background ozone concentrations (estimated by turning off North American anthropogenic emissions in the model) to MDA8 values of 60–75 ppbv. At high-elevation western U.S. sites, the 25th–75th percentile of the stratospheric contribution is 15–25 ppbv when observed MDA8 ozone is 60–70 ppbv, and increases to ∼17–40 ppbv for the 70–85 ppbv range. These estimates, up to 2–3 times greater than previously reported, indicate a major role for stratospheric intrusions in contributing to springtime high-O3events over the high-altitude western U.S., posing a challenge for staying below the ozone NAAQS threshold, particularly if a value in the 60–70 ppbv range were to be adopted
Physics-informed Deep Diffusion MRI Reconstruction with Synthetic Data: Break Training Data Bottleneck in Artificial Intelligence
Diffusion magnetic resonance imaging (MRI) is the only imaging modality for
non-invasive movement detection of in vivo water molecules, with significant
clinical and research applications. Diffusion MRI (DWI) acquired by multi-shot
techniques can achieve higher resolution, better signal-to-noise ratio, and
lower geometric distortion than single-shot, but suffers from inter-shot
motion-induced artifacts. These artifacts cannot be removed prospectively,
leading to the absence of artifact-free training labels. Thus, the potential of
deep learning in multi-shot DWI reconstruction remains largely untapped. To
break the training data bottleneck, here, we propose a Physics-Informed Deep
DWI reconstruction method (PIDD) to synthesize high-quality paired training
data by leveraging the physical diffusion model (magnitude synthesis) and
inter-shot motion-induced phase model (motion phase synthesis). The network is
trained only once with 100,000 synthetic samples, achieving encouraging results
on multiple realistic in vivo data reconstructions. Advantages over
conventional methods include: (a) Better motion artifact suppression and
reconstruction stability; (b) Outstanding generalization to multi-scenario
reconstructions, including multi-resolution, multi-b-value,
multi-undersampling, multi-vendor, and multi-center; (c) Excellent clinical
adaptability to patients with verifications by seven experienced doctors
(p<0.001). In conclusion, PIDD presents a novel deep learning framework by
exploiting the power of MRI physics, providing a cost-effective and explainable
way to break the data bottleneck in deep learning medical imaging.Comment: 23 pages, 16 figure
Transport of Asian ozone pollution into surface air over the western United States in spring
Many prior studies clearly document episodic Asian pollution in the western U.S. free troposphere. Here, we examine the mechanisms involved in the transport of Asian pollution plumes into western U.S. surface air through an integrated analysis of in situ and satellite measurements in May–June 2010 with a new global high-resolution (∼50 × 50 km2) chemistry-climate model (GFDL AM3). We find that AM3 with full stratosphere-troposphere chemistry nudged to reanalysis winds successfully reproduces observed sharp ozone gradients above California, including the interleaving and mixing of Asian pollution and stratospheric air associated with complex interactions of midlatitude cyclone air streams. Asian pollution descends isentropically behind cold fronts; at ∼800 hPa a maximum enhancement to ozone occurs over the southwestern U.S., including the densely populated Los Angeles Basin. During strong episodes, Asian emissions can contribute 8–15 ppbv ozone in the model on days when observed daily maximum 8-h average ozone (MDA8 O3) exceeds 60 ppbv. We find that in the absence of Asian anthropogenic emissions, 20% of MDA8 O3 exceedances of 60 ppbv in the model would not have occurred in the southwestern USA. For a 75 ppbv threshold, that statistic increases to 53%. Our analysis indicates the potential for Asian emissions to contribute to high-O3 episodes over the high-elevation western USA, with implications for attaining more stringent ozone standards in this region. We further demonstrate a proof-of-concept approach using satellite CO column measurements as a qualitative early warning indicator to forecast Asian ozone pollution events in the western U.S. with lead times of 1–3 days
Tropospheric Ozone Assessment Report: Tropospheric ozone from 1877 to 2016, observed levels, trends and uncertainties
From the earliest observations of ozone in the lower atmosphere in the 19th century, both measurement methods and the portion of the globe observed have evolved and changed. These methods have different uncertainties and biases, and the data records differ with respect to coverage (space and time), information content, and representativeness. In this study, various ozone measurement methods and ozone datasets are reviewed and selected for inclusion in the historical record of background ozone levels, based on relationship of the measurement technique to the modern UV absorption standard, absence of interfering pollutants, representativeness of the well-mixed boundary layer and expert judgement of their credibility. There are significant uncertainties with the 19th and early 20th-century measurements related to interference of other gases. Spectroscopic methods applied before 1960 have likely underestimated ozone by as much as 11% at the surface and by about 24% in the free troposphere, due to the use of differing ozone absorption coefficients.
There is no unambiguous evidence in the measurement record back to 1896 that typical mid-latitude background surface ozone values were below about 20 nmol mol–1, but there is robust evidence for increases in the temperate and polar regions of the northern hemisphere of 30–70%, with large uncertainty, between the period of historic observations, 1896–1975, and the modern period (1990–2014). Independent historical observations from balloons and aircraft indicate similar changes in the free troposphere. Changes in the southern hemisphere are much less. Regional representativeness of the available observations remains a potential source of large errors, which are difficult to quantify
Estimates of ozone return dates from Chemistry-Climate Model Initiative simulations
We analyse simulations performed for the Chemistry-Climate Model Initiative (CCMI) to estimate the return dates of the stratospheric ozone layer from depletion caused by anthropogenic stratospheric chlorine and bromine. We consider a total of 155 simulations from 20 models, including a range of sensitivity studies which examine the impact of climate change on ozone recovery. For the control simulations (unconstrained by nudging towards analysed meteorology) there is a large spread (±20DU in the global average) in the predictions of the absolute ozone column. Therefore, the model results need to be adjusted for biases against historical data. Also, the interannual variability in the model results need to be smoothed in order to provide a reasonably narrow estimate of the range of ozone return dates. Consistent with previous studies, but here for a Representative Concentration Pathway (RCP) of 6.0, these new CCMI simulations project that global total column ozone will return to 1980 values in 2049 (with a 1σ uncertainty of 2043–2055). At Southern Hemisphere mid-latitudes column ozone is projected to return to 1980 values in 2045 (2039–2050), and at Northern Hemisphere mid-latitudes in 2032 (2020–2044). In the polar regions, the return dates are 2060 (2055–2066) in the Antarctic in October and 2034 (2025–2043) in the Arctic in March. The earlier return dates in the Northern Hemisphere reflect the larger sensitivity to dynamical changes. Our estimates of return dates are later than those presented in the 2014 Ozone Assessment by approximately 5–17 years, depending on the region, with the previous best estimates often falling outside of our uncertainty range. In the tropics only around half the models predict a return of ozone to 1980 values, around 2040, while the other half do not reach the 1980 value. All models show a negative trend in tropical total column ozone towards the end of the 21st century. The CCMI models generally agree in their simulation of the time evolution of stratospheric chlorine and bromine, which are the main drivers of ozone loss and recovery. However, there are a few outliers which show that the multi-model mean results for ozone recovery are not as tightly constrained as possible. Throughout the stratosphere the spread of ozone return dates to 1980 values between models tends to correlate with the spread of the return of inorganic chlorine to 1980 values. In the upper stratosphere, greenhouse gas-induced cooling speeds up the return by about 10–20 years. In the lower stratosphere, and for the column, there is a more direct link in the timing of the return dates of ozone and chlorine, especially for the large Antarctic depletion. Comparisons of total column ozone between the models is affected by different predictions of the evolution of tropospheric ozone within the same scenario, presumably due to differing treatment of tropospheric chemistry. Therefore, for many scenarios, clear conclusions can only be drawn for stratospheric ozone columns rather than the total column. As noted by previous studies, the timing of ozone recovery is affected by the evolution of N2O and CH4. However, quantifying the effect in the simulations analysed here is limited by the few realisations available for these experiments compared to internal model variability. The large increase in N2O given in RCP 6.0 extends the ozone return globally by ∼15 years relative to N2O fixed at 1960 abundances, mainly because it allows tropical column ozone to be depleted. The effect in extratropical latitudes is much smaller. The large increase in CH4 given in the RCP 8.5 scenario compared to RCP 6.0 also lengthens ozone return by ∼15 years, again mainly through its impact in the tropics. Overall, our estimates of ozone return dates are uncertain due to both uncertainties in future scenarios, in particular those of greenhouse gases, and uncertainties in models. The scenario uncertainty is small in the short term but increases with time, and becomes large by the end of the century. There are still some model–model differences related to well-known processes which affect ozone recovery. Efforts need to continue to ensure that models used for assessment purposes accurately represent stratospheric chemistry and the prescribed scenarios of ozone-depleting substances, and only those models are used to calculate return dates. For future assessments of single forcing or combined effects of CO2, CH4, and N2O on the stratospheric column ozone return dates, this work suggests that it is more important to have multi-member (at least three) ensembles for each scenario from every established participating model, rather than a large number of individual models
Nanomaterial-Assisted Signal Enhancement of Hybridization for DNA Biosensors: A Review
Detection of DNA sequences has received broad attention due to its potential applications in a variety of fields. As sensitivity of DNA biosensors is determined by signal variation of hybridization events, the signal enhancement is of great significance for improving the sensitivity in DNA detection, which still remains a great challenge. Nanomaterials, which possess some unique chemical and physical properties caused by nanoscale effects, provide a new opportunity for developing novel nanomaterial-based signal-enhancers for DNA biosensors. In this review, recent progress concerning this field, including some newly-developed signal enhancement approaches using quantum-dots, carbon nanotubes and their composites reported by our group and other researchers are comprehensively summarized. Reports on signal enhancement of DNA biosensors by non-nanomaterials, such as enzymes and polymer reagents, are also reviewed for comparison. Furthermore, the prospects for developing DNA biosensors using nanomaterials as signal-enhancers in future are also indicated
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Characterizing sources of high surface ozone events in the southwestern US with intensive field measurements and two global models
The detection and attribution of high background ozone (O3) events in the southwestern US is challenging but relevant to the effective implementation of the lowered National Ambient Air Quality Standard (NAAQS; 70 ppbv). Here we leverage intensive field measurements from the Fires, Asian, and Stratospheric Transport−Las Vegas Ozone Study (FAST-LVOS) in May–June 2017, alongside high-resolution simulations with two global models (GFDL-AM4 and GEOS-Chem), to study the sources of O3 during high-O3 events. We show possible stratospheric influence on 4 out of the 10 events with daily maximum 8 h average (MDA8) surface O3 above 65 ppbv in the greater Las Vegas region. While O3 produced from regional anthropogenic emissions dominates pollution events in the Las Vegas Valley, stratospheric intrusions can mix with regional pollution to push surface O3 above 70 ppbv. GFDL-AM4 captures the key characteristics of deep stratospheric intrusions consistent with ozonesondes, lidar profiles, and co-located measurements of O3, CO, and water vapor at Angel Peak, whereas GEOS-Chem has difficulty simulating the observed features and underestimates observed O3 by ∼20 ppbv at the surface. On days when observed MDA8 O3 exceeds 65 ppbv and the AM4 stratospheric ozone tracer shows 20–40 ppbv enhancements, GEOS-Chem simulates ∼15 ppbv lower US background O3 than GFDL-AM4. The two models also differ substantially during a wildfire event, with GEOS-Chem estimating ∼15 ppbv greater O3, in better agreement with lidar observations. At the surface, the two models bracket the observed MDA8 O3 values during the wildfire event. Both models capture the large-scale transport of Asian pollution, but neither resolves some fine-scale pollution plumes, as evidenced by aerosol backscatter, aircraft, and satellite measurements. US background O3 estimates from the two models differ by 5 ppbv on average (greater in GFDL-AM4) and up to 15 ppbv episodically. Uncertainties remain in the quantitative attribution of each event. Nevertheless, our multi-model approach tied closely to observational analysis yields some process insights, suggesting that elevated background O3 may pose challenges to achieving a potentially lower NAAQS level (e.g., 65 ppbv) in the southwestern US.
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