Deep-sequencing identification of the genomic targets of the cytidine deaminase AID and its cofactor RPA in B lymphocytes.

The cytidine deaminase AID hypermutates immunoglobulin genes but can also target oncogenes, leading to tumorigenesis. The extent of AID's promiscuity and its predilection for immunoglobulin genes are unknown. We report here that AID interacted broadly with promoter-proximal sequences associated with stalled polymerases and chromatin-activating marks. In contrast, genomic occupancy of replication protein A (RPA), an AID cofactor, was restricted to immunoglobulin genes. The recruitment of RPA to the immunoglobulin loci was facilitated by phosphorylation of AID at Ser38 and Thr140. We propose that stalled polymerases recruit AID, thereby resulting in low frequencies of hypermutation across the B cell genome. Efficient hypermutation and switch recombination required AID phosphorylation and correlated with recruitment of RPA. Our findings provide a rationale for the oncogenic role of AID in B cell malignancy.

Change in household fuels dominates the decrease in PM2.5 exposure and premature mortality in China in 2005-2015.

To tackle the severe fine particle (PM2.5) pollution in China, the government has implemented stringent control policies mainly on power plants, industry, and transportation since 2005, but estimates of the effectiveness of the policy and the temporal trends in health impacts are subject to large uncertainties. By adopting an integrated approach that combines chemical transport simulation, ambient/household exposure evaluation, and health-impact assessment, we find that the integrated population-weighted exposure to PM2.5 (IPWE) decreased by 47% (95% confidence interval, 37-55%) from 2005 [180 (146-219) µg/m3] to 2015 [96 (83-111) µg/m3]. Unexpectedly, 90% (86-93%) of such reduction is attributed to reduced household solid-fuel use, primarily resulting from rapid urbanization and improved incomes rather than specific control policies. The IPWE due to household fuels for both cooking and heating decreased, but the impact of cooking is significantly larger. The reduced household-related IPWE is estimated to avoid 0.40 (0.25-0.57) million premature deaths annually, accounting for 33% of the PM2.5-induced mortality in 2015. The IPWE would be further reduced by 63% (57-68%) if the remaining household solid fuels were replaced by clean fuels, which would avoid an additional 0.51 (0.40-0.64) million premature deaths. Such a transition to clean fuels, especially for heating, requires technology innovation and policy support to overcome the barriers of high cost of distribution systems, as is recently being attempted in the Beijing-Tianjin-Hebei area. We suggest that household-fuel use be more highly prioritized in national control policies, considering its effects on PM2.5 exposures.

Environmental impact of national and subnational carbon policies in China based on a multi-regional dynamic CGE model.

Carbon policies are important not only for mitigating global climate change, but also for controlling local and regional air pollution. The large regional disparities in economic development and air pollution across China calls for regionally differentiated policies. Previous studies have not systematically investigated the environmental impacts of regional carbon policies in China covering different spatial scales. This study constructs a multi-regional dynamic computable general equilibrium (CGE) model covering 30 provinces of China to assess the impacts of national and subnational carbon polices on CO2 emissions and co-emitted air pollutants from 2020 to 2050. We consider one national carbon policy which aims to achieve China's 2030 national CO2 abatement target, as well as three regional policies with the same policy stringency as the national one but only applied to eastern China (EP), the Jiangsu-Shanghai-Zhejiang area (JSZP), and the Beijing-Tianjin-Hebei area (BTHP), respectively. We find that regional policies (EP, JSZP, and BTHP) are as effective in reducing CO2 emissions in their targeted regions as the national policy. However, they lead to an increase in CO2 emissions in untargeted regions (the so-called "emissions leakage"). The CO2 leakage rates, which depend on the policy spatial coverage, are 4%, 13%, and 65% for EP, JSZP, and BTHP, respectively, in 2050. Compared with CO2, changes in air pollutant emissions, including sulfur dioxide (SO2), nitrogen oxides (NOx), volatile organic compounds (VOC), and fine particulate matter (PM2.5), exhibit a similar pattern under all policy scenarios, but the magnitude of change is significantly smaller. Transportation, thermal power, and some energy intensive industries are the three largest contributors to CO2 and air pollutant emission reductions. Our results suggest that regional carbon policy is effective in reducing CO2 and air pollutant emissions in the targeted regions, and extending the spatial coverage or increasing policy stringency can largely inhibit emissions leakage.

Regulation of microRNA expression and abundance during lymphopoiesis.

Although the cellular concentration of miRNAs is critical to their function, how miRNA expression and abundance are regulated during ontogeny is unclear. We applied miRNA-, mRNA-, and ChIP-Seq to characterize the microRNome during lymphopoiesis within the context of the transcriptome and epigenome. We show that lymphocyte-specific miRNAs are either tightly controlled by polycomb group-mediated H3K27me3 or maintained in a semi-activated epigenetic state prior to full expression. Because of miRNA biogenesis, the cellular concentration of mature miRNAs does not typically reflect transcriptional changes. However, we uncover a subset of miRNAs for which abundance is dictated by miRNA gene expression. We confirm that concentration of 5p and 3p miRNA strands depends largely on free energy properties of miRNA duplexes. Unexpectedly, we also find that miRNA strand accumulation can be developmentally regulated. Our data provide a comprehensive map of immunity's microRNome and reveal the underlying epigenetic and transcriptional forces that shape miRNA homeostasis.

Air Quality and Health Cobenefits of Different Deep Decarbonization Pathways in California.

As the world's fifth-largest economy, California has committed to reduce its greenhouse gas (GHG) emissions by 80% below 1990 levels by 2050. While previous studies have shown that GHG reductions could synergistically decrease air pollutant emissions and protect public health, limited research has been conducted to compare the health cobenefits of different technology pathways toward deep decarbonization. Using an integrated approach that combines energy and emission technology modeling, high-resolution chemical transport simulation, and health impact assessment, we find that achievement of the 80% GHG reduction target would bring substantial air quality and health cobenefits. The cobenefits, however, highly depend on the selected technology pathway largely because of California's relatively clean energy structure. Compared with the business-as-usual levels, a decarbonization pathway that focuses on electrification and clean renewable energy is estimated to reduce concentrations of fine particulate matter (PM2.5) by 18-37% in major metropolitan areas of California and subsequently avoid about 12 100 (9600-14 600) premature deaths. In contrast, only a quarter of such health cobenefits, i.e., 2800 (2300-3400) avoided deaths, can be achieved through a pathway focusing more on combustible renewable fuels. After subtracting the cost, the net monetized benefit of the electrification-focused pathway still exceeds that of the renewable fuel-focused pathway, indicating that a cleaner but more expensive decarbonization pathway may be more preferable in California.

Type-Dependent Responses of Ice Cloud Properties to Aerosols From Satellite Retrievals.

Aerosol-cloud interactions represent one of the largest uncertainties in external forcings on our climate system. Compared with liquid clouds, the observational evidence for the aerosol impact on ice clouds is much more limited and shows conflicting results, partly because the distinct features of different ice cloud and aerosol types were seldom considered. Using 9-year satellite retrievals, we find that, for convection-generated (anvil) ice clouds, cloud optical thickness, cloud thickness, and cloud fraction increase with small-to-moderate aerosol loadings (<0.3 aerosol optical depth) and decrease with further aerosol increase. For in situ formed ice clouds, however, these cloud properties increase monotonically and more sharply with aerosol loadings. An increase in loading of smoke aerosols generally reduces cloud optical thickness of convection-generated ice clouds, while the reverse is true for dust and anthropogenic pollution aerosols. These relationships between different cloud/aerosol types provide valuable constraints on the modeling assessment of aerosol-ice cloud radiative forcing.

The use of neural networks in identifying error sources in satellite-derived tropical SST estimates.

An neural network model of data mining is used to identify error sources in satellite-derived tropical sea surface temperature (SST) estimates from thermal infrared sensors onboard the Geostationary Operational Environmental Satellite (GOES). By using the Back Propagation Network (BPN) algorithm, it is found that air temperature, relative humidity, and wind speed variation are the major factors causing the errors of GOES SST products in the tropical Pacific. The accuracy of SST estimates is also improved by the model. The root mean square error (RMSE) for the daily SST estimate is reduced from 0.58 K to 0.38 K and mean absolute percentage error (MAPE) is 1.03%. For the hourly mean SST estimate, its RMSE is also reduced from 0.66 K to 0.44 K and the MAPE is 1.3%.

Impacts of Saharan Mineral Dust on Air-Sea Interaction over North Atlantic Ocean Using a Fully Coupled Regional Model.

This study examines the modifications of air-sea coupling processes by dust-radiation-cloud interactions over the North Atlantic Ocean using a high-resolution coupled atmosphere-wave-ocean-dust (AWOD) regional model. The dust-induced mechanisms that are responsible for changes of sea surface temperature (SST) and latent and sensible heat fluxes (LHF/SHF) are also examined. Two 3-month numerical experiments are conducted, and they differ only in the activation and deactivation of dust-radiation-cloud interactions. Model results show that the dust significantly reduces surface downward radiation fluxes (SDRF) over the ocean with the maximum change of 20-30 W m-2. Over the dust plume region, the dust effect creates a low-pressure anomaly and a cyclonic circulation anomaly, which drives a positive wind stress curl anomaly, thereby reducing sea surface height and mixed layer depth. However, the SST change by dust, ranging from -0.5 to 0.5 K, has a great spatial variation which differs from the dust plume shape. Dust cools SST around the West African coast, except under the maximum dust plume ridge, and extends westward asymmetrically along the northern and southern edges of the dust plume. Dust unexpectedly warms SST over a large area of the western tropical North Atlantic and north of the dust plume. These SST changes are controlled by different mechanisms. Unlike the SST change pattern, the LHF and SHF changes are mostly reduced underneath the dust plume region, though they are different in detail due to different dominant factors, and increased south of the dust plume over the tropic.

Phase matrix for light scattering by concentrically stratified spheres: comparison of geometric optics and the "exact" theory.

We have developed a hit-and-miss Monte Carlo geometric ray-tracing program to compute the scattering phase matrix for concentrically stratified spheres. Using typical refractive indices for water and aerosols in the calculations, numerous rainbow features appear in the phase matrix that deviate from the results calculated from homogeneous spheres. In the context of geometric ray tracing, rainbows and glory are identified by means of their ray paths, which provide physical explanation for the features produced by the "exact" Lorenz-Mie theory. The computed results for the phase matrix, the single-scattering albedo, and the asymmetry factor for a size parameter of approximately 600 compared closely with those evaluated from the "exact" theory.

Combining In Situ and Satellite Observations to Understand the Vertical Structure of Tropical Anvil Cloud Microphysical Properties During the TC4 Experiment.

Tropical anvil clouds have a profound impact on Earth's weather and climate. Their role in Earth's energy balance and hydrologic cycle is heavily modulated by the vertical structure of the microphysical properties for various hydrometeors in these clouds and their dependence on the ambient environmental conditions. Accurate representations of the variability and covariability of such vertical structures are key to both the satellite remote sensing of cloud and precipitation and numerical modeling of weather and climate, which remain a challenge. This study presents a new method to combine vertically resolved observations from CloudSat radar reflectivity and Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation cloud masks with probability distributions of cloud microphysical properties and the ambient atmospheric conditions from detailed in situ measurements on tropical anvils sampled during the National Aeronautics and Space Administration TC4 (Tropical Composition, Cloud and Climate Coupling) mission. We focus on the microphysical properties of the vertical distribution of ice water content, particle size distributions, and effective sizes for different hydrometeors, including ice particles and supercooled liquid droplets. Results from this method are compared with those from in situ data alone and various CloudSat/Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation cloud retrievals. The sampling limitation of the field experiment and algorithm limitations in the current retrievals is highlighted, especially for the liquid cloud particles, while a generally good agreement with ice cloud microphysical properties is seen from different methods. While the method presented in this study is applied to tropical anvil clouds observed during TC4, it can be readily employed to study a broad range of ice clouds sampled by various field campaigns.

Satellite remote sensing of dust aerosol indirect effects on ice cloud formation.

We undertook a new approach to investigate the aerosol indirect effect of the first kind on ice cloud formation by using available data products from the Moderate-Resolution Imaging Spectrometer (MODIS) and obtained physical understanding about the interaction between aerosols and ice clouds. Our analysis focused on the examination of the variability in the correlation between ice cloud parameters (optical depth, effective particle size, cloud water path, and cloud particle number concentration) and aerosol optical depth and number concentration that were inferred from available satellite cloud and aerosol data products. Correlation results for a number of selected scenes containing dust and ice clouds are presented, and dust aerosol indirect effects on ice clouds are directly demonstrated from satellite observations.

An Algorithm for Cold Patch Detection in the Sea off Northeast Taiwan Using Multi-Sensor Data.

Multi-sensor data from different satellites are used to identify an upwelling area in the sea off northeast Taiwan. Sea surface temperature (SST) data derived from infrared and microwave, as well as sea surface height anomaly (SSHA) data derived from satellite altimeters are used for this study. An integration filtering algorithm based on SST data is developed for detecting the cold patch induced by the upwelling. The center of the cold patch is identified by the maximum negative deviation relative to the spatial mean of a SST image within the study area and its climatological mean of each pixel. The boundary of the cold patch is found by the largest SST gradient. The along track SSHA data derived from satellite altimeters are then used to verify the detected cold patch. Applying the detecting algorithm, spatial and temporal characteristics and variations of the cold patch are revealed. The cold patch has an average area of 1.92 × 10(4) km(2). Its occurrence frequencies are high from June to October and reach a peak in July. The mean SST of the cold patch is 23.8 °C. In addition to the annual and the intraseasonal fluctuation with main peak centered at 60 days, the cold patch also has a variation period of about 4.7 years in the interannual timescale. This implies that the Kuroshio variations and long-term and large scale processes playing roles in modifying the cold patch occurrence frequency.

On the Convergence of Numerical Computations for Both Exact and Approximate Solutions for Electromagnetic Scattering by Nonspherical Dielectric Particles.

We summarize the size parameter range of the applicability of four light-scattering computational methods for nonspherical dielectric particles. These methods include two exact methods - the extended boundary condition method (EBCM) and the invariant imbedding T-matrix method (II-TM) and two approximate approaches - the physical-geometric optics method (PGOM) and the improved geometric optics method (IGOM). For spheroids, the single-scattering properties computed by EBCM and II-TM agree for size parameters up to 150, and the comparison gives us confidence in using IITM as a benchmark for size parameters up to 150 for other geometries (e.g., hexagonal columns) because the applicability of II-TM with respect to particle shape is generic, as demonstrated in our previous studies involving a complex aggregate. This study demonstrates the convergence of the exact II-TM and approximate PGOM solutions for the complete set of single-scattering properties of a nonspherical shape other than spheroids and circular cylinders with particle sizes of ~ 48λ(size parameter ~150), specifically a hexagonal column with a length size parameter of kL = 300 where k = 2π/λ and L is the column length. IGOM is also quite accurate except near the exact 180°backscattering direction. This study demonstrates that a synergetic combination of the numerically-exact II-TM and the approximate PGOM can seamlessly cover the entire size parameter range of practical interest. To demonstrate the applicability of the approach, we compute the optical properties of dust particles and demonstrate a downstream application to the retrieval of dust aerosol optical thickness and effective particle size from satellite polarimetric observations.

Mortality burdens in California due to air pollution attributable to local and nonlocal emissions.

Limited research has been conducted on the contributions of local and nonlocal emission sources to ambient fine particulate matter (PM2.5) and ozone (O3) and their associated mortality. In this study, we estimated the total mortality resulting from long-term PM2.5 and O3 exposures in California in 2012 using multiple concentration response functions (CRFs) and attributed the estimated mortality to different emission groups. The point estimates of PM2.5-associated mortality in California ranged from 12,700 to 26,700, of which 53% were attributable to in-state anthropogenic emissions. Based on new epidemiological evidence, we estimated that O3 could be associated with up to 13,700 deaths from diseases of both the respiratory and cardiovascular systems in California. In addition, 75% of the ambient O3 in California was due to distant emissions outside the western United States, leading to 92% of the O3-associated mortality. Overall, distant emissions lead to greater mortality burdens of air pollution in California than local anthropogenic emissions.

Ice nucleation by aerosols from anthropogenic pollution.

The formation of ice particles in the atmosphere strongly affects cloud properties and the climate. While mineral dust is known to be an effective ice nucleating particle, the role of aerosols from anthropogenic pollution in ice nucleation is still under debate. Here we probe the ice nucleation ability of different aerosol types by combining 11-year observations from multiple satellites and cloud-resolving model simulations. We find that, for strong convective systems, ice particle effective radius near cloud top decreases with increasing loading of polluted continental aerosols, because the ice formation is dominated by homogeneous freezing of cloud droplets that are smaller under more polluted conditions. In contrast, an increase in ice particle effective radius with polluted continental aerosols is found for moderate convection. Our model simulations suggest that this positive correlation is explained by enhanced heterogeneous ice nucleation and prolonged ice particle growth at larger aerosol loading, indicating that polluted continental aerosols contain a significant fraction of ice nucleating particles. Similar aerosol-ice relationships are observed for dust aerosols, further corroborating the ice nucleation ability of polluted continental aerosols. By catalyzing ice formation, aerosols from anthropogenic pollution could have profound impacts on cloud lifetime and radiative effect as well as precipitation efficiency.

Modeling Study of the Air Quality Impact of Record-Breaking Southern California Wildfires in December 2017.

We investigate the air quality impact of record-breaking wildfires in Southern California during 5-18 December 2017 using the Weather Research and Forecasting model with Chemistry in combination with satellite and surface observations. This wildfire event was driven by dry and strong offshore Santa Ana winds, which played a critical role in fire formation and air pollutant transport. By utilizing fire emissions derived from the high-resolution (375 × 375 m2) Visible Infrared Imaging Radiometer Suite active fire detections, the simulated magnitude and temporal evolution of fine particulate matter (PM2.5) concentrations agree reasonably well with surface observations (normalized mean bias = 4.0%). Meanwhile, the model could generally capture the spatial pattern of aerosol optical depth from satellite observations. Sensitivity tests reveal that using a high spatial resolution for fire emissions and a reasonable treatment of plume rise (a fair split between emissions injected at surface and those lifted to upper levels) is important for achieving decent PM2.5 simulation results. Biases in PM2.5 simulation are relatively large (about 50%) during the period with the strongest Santa Ana wind, due to a possible underestimation of burning area and uncertainty in wind field variation. The 2017 December fire event increases the 14-day averaged PM2.5 concentrations by up to 231.2 µg/m3 over the downwind regions, which substantially exceeds the U.S. air quality standards, potentially leading to adverse health impacts. The human exposure to fire-induced PM2.5 accounts for 14-42% of the annual total PM2.5 exposure in areas impacted by the fire plumes.

Validation and Variation of Upper Layer Thickness in South China Sea from Satellite Altimeter Data.

Satellite altimeter data from 1993 to 2005 has been used to analyze the seasonal variation and the interannual variability of upper layer thickness (ULT) in the South China Sea (SCS). Base on in-situ measurements, the ULT is defined as the thickness from the sea surface to the depth of 16°C isotherm which is used to validate the result derived from satellite altimeter data. In comparison with altimeter and in-situ derived ULTs yields a correlation coefficient of 0.92 with a slope of 0.95 and an intercept of 6 m. The basin averaged ULT derived from altimeter is 160 m in winter and 171 m in summer which is similar to the in-situ measurements of 159 m in winter and 175 m in summer. Both results also show similar spatial patterns. It suggests that the sea surface height data derived from satellite sensors are usable for study the variation of ULT in the semi-closed SCS. Furthermore, we also use satellite derived ULT to detect the development of eddy. Interannual variability of two meso-scale cyclonic eddies and one anticyclonic eddy are strongly influenced by El Niño events. In most cases, there are highly positive correlations between ULT and sea surface temperature except the periods of El Niño. During the onset of El Niño event, ULT is deeper when sea surface temperature is lower.

Intra-annual variations of regional aerosol optical depth, vertical distribution, and particle types from multiple satellite and ground-based observational datasets.

The climatic and health effects of aerosols are strongly dependent on the intra-annual variations in their loading and properties. While the seasonal variations of regional aerosol optical depth (AOD) have been extensively studied, understanding the temporal variations in aerosol vertical distribution and particle types is also important for an accurate estimate of aerosol climatic effects. In this paper, we combine the observations from four satellite-borne sensors and several ground-based networks to investigate the seasonal variations of aerosol column loading, vertical distribution, and particle types over three populous regions: the Eastern United States (EUS), Western Europe (WEU), and Eastern and Central China (ECC). In all three regions, column AOD, as well as AOD at heights above 800 m, peaks in summer/spring, probably due to accelerated formation of secondary aerosols and hygroscopic growth. In contrast, AOD below 800m peaks in winter over WEU and ECC regions because more aerosols are confined to lower heights due to the weaker vertical mixing. In the EUS region, AOD below 800m shows two maximums, one in summer and the other in winter. The temporal trends in low-level AOD are consistent with those in surface fine particle (PM2.5) concentrations. AOD due to fine particles (< 0.7 µm diameter) is much larger in spring/summer than in winter over all three regions. However, the coarse mode AOD (> 1.4 µm diameter), generally shows small variability, except that a peak occurs in spring in the ECC region due to the prevalence of airborne dust during this season. When aerosols are classified according to sources, the dominant type is associated with anthropogenic air pollution, which has a similar seasonal pattern as total AOD. Dust and sea-spray aerosols in the WEU region peak in summer and winter, respectively, but do not show an obvious seasonal pattern in the EUS region. Smoke aerosols, as well as absorbing aerosols, present an obvious unimodal distribution with a maximum occurring in summer over the EUS and WEU regions, whereas they follow a bimodal distribution with peaks in August and March (due to crop residue burning) over the ECC region.

Impact of aerosols on ice crystal size.

The interactions between aerosols and ice clouds represent one of the largest uncertainties in global radiative forcing from pre-industrial time to the present. In particular, the impact of aerosols on ice crystal effective radius (R ei), which is a key parameter determining ice clouds' net radiative effect, is highly uncertain due to limited and conflicting observational evidence. Here we investigate the effects of aerosols on R ei under different meteorological conditions using 9-year satellite observations. We find that the responses of R ei to aerosol loadings are modulated by water vapor amount in conjunction with several other meteorological parameters. While there is a significant negative correlation between R ei and aerosol loading in moist conditions, consistent with the "Twomey effect" for liquid clouds, a strong positive correlation between the two occurs in dry conditions. Simulations based on a cloud parcel model suggest that water vapor modulates the relative importance of different ice nucleation modes, leading to the opposite aerosol impacts between moist and dry conditions. When ice clouds are decomposed into those generated from deep convection and formed in situ, the water vapor modulation remains in effect for both ice cloud types, although the sensitivities of R ei to aerosols differ noticeably between them due to distinct formation mechanisms. The water vapor modulation can largely explain the difference in the responses of R ei to aerosol loadings in various seasons. A proper representation of the water vapor modulation is essential for an accurate estimate of aerosol-cloud radiative forcing produced by ice clouds.

Enhanced PM2.5 pollution in China due to aerosol-cloud interactions.

Aerosol-cloud interactions (aerosol indirect effects) play an important role in regional meteorological variations, which could further induce feedback on regional air quality. While the impact of aerosol-cloud interactions on meteorology and climate has been extensively studied, their feedback on air quality remains unclear. Using a fully coupled meteorology-chemistry model, we find that increased aerosol loading due to anthropogenic activities in China substantially increases column cloud droplet number concentration and liquid water path (LWP), which further leads to a reduction in the downward shortwave radiation at surface, surface air temperature and planetary boundary layer (PBL) height. The shallower PBL and accelerated cloud chemistry due to larger LWP in turn enhance the concentrations of particulate matter with diameter less than 2.5 µm (PM2.5) by up to 33.2 µg m-3 (25.1%) and 11.0 µg m-3 (12.5%) in January and July, respectively. Such a positive feedback amplifies the changes in PM2.5 concentrations, indicating an additional air quality benefit under effective pollution control policies but a penalty for a region with a deterioration in PM2.5 pollution. Additionally, we show that the cloud processing of aerosols, including wet scavenging and cloud chemistry, could also have substantial effects on PM2.5 concentrations.