Committed emissions from existing energy infrastructure jeopardize 1.5 °C climate target.

Net anthropogenic emissions of carbon dioxide (CO2) must approach zero by mid-century (2050) in order to stabilize the global mean temperature at the level targeted by international efforts1-5. Yet continued expansion of fossil-fuel-burning energy infrastructure implies already 'committed' future CO2 emissions6-13. Here we use detailed datasets of existing fossil-fuel energy infrastructure in 2018 to estimate regional and sectoral patterns of committed CO2 emissions, the sensitivity of such emissions to assumed operating lifetimes and schedules, and the economic value of the associated infrastructure. We estimate that, if operated as historically, existing infrastructure will cumulatively emit about 658 gigatonnes of CO2 (with a range of 226 to 1,479 gigatonnes CO2, depending on the lifetimes and utilization rates assumed). More than half of these emissions are predicted to come from the electricity sector; infrastructure in China, the USA and the 28 member states of the European Union represents approximately 41 per cent, 9 per cent and 7 per cent of the total, respectively. If built, proposed power plants (planned, permitted or under construction) would emit roughly an extra 188 (range 37-427) gigatonnes CO2. Committed emissions from existing and proposed energy infrastructure (about 846 gigatonnes CO2) thus represent more than the entire carbon budget that remains if mean warming is to be limited to 1.5 degrees Celsius (°C) with a probability of 66 to 50 per cent (420-580 gigatonnes CO2)5, and perhaps two-thirds of the remaining carbon budget if mean warming is to be limited to less than 2 °C (1,170-1,500 gigatonnes CO2)5. The remaining carbon budget estimates are varied and nuanced14,15, and depend on the climate target and the availability of large-scale negative emissions16. Nevertheless, our estimates suggest that little or no new CO2-emitting infrastructure can be commissioned, and that existing infrastructure may need to be retired early (or be retrofitted with carbon capture and storage technology) in order to meet the Paris Agreement climate goals17. Given the asset value per tonne of committed emissions, we suggest that the most cost-effective premature infrastructure retirements will be in the electricity and industry sectors, if non-emitting alternatives are available and affordable4,18.

The therapeutically actionable long non-coding RNA 'T-RECS' is essential to cancer cells' survival in NRAS/MAPK-driven melanoma.

Finding effective therapeutic targets to treat NRAS-mutated melanoma remains a challenge. Long non-coding RNAs (lncRNAs) recently emerged as essential regulators of tumorigenesis. Using a discovery approach combining experimental models and unbiased computational analysis complemented by validation in patient biospecimens, we identified a nuclear-enriched lncRNA (AC004540.4) that is upregulated in NRAS/MAPK-dependent melanoma, and that we named T-RECS. Considering potential innovative treatment strategies, we designed antisense oligonucleotides (ASOs) to target T-RECS. T-RECS ASOs reduced the growth of melanoma cells and induced apoptotic cell death, while having minimal impact on normal primary melanocytes. Mechanistically, treatment with T-RECS ASOs downregulated the activity of pro-survival kinases and reduced the protein stability of hnRNPA2/B1, a pro-oncogenic regulator of MAPK signaling. Using patient- and cell line- derived tumor xenograft mouse models, we demonstrated that systemic treatment with T-RECS ASOs significantly suppressed the growth of melanoma tumors, with no noticeable toxicity. ASO-mediated T-RECS inhibition represents a promising RNA-targeting approach to improve the outcome of MAPK pathway-activated melanoma.

Multiple-access ultrastable frequency dissemination based on optical frequency combs via a fiber link.

We demonstrate an optical fiber-based, multiple-access frequency transmission using two optical frequency combs. The experimental results using the Allan deviation analysis show that with the phase compensation technique, the frequency instabilities at the remote site are 8.7 × 10-15/1 s and 1.0 × 10-17/103 s, and at the accessing node along the fiber link, the frequency instabilities are 6.9 × 10-15/1 s and 1.1 × 10-17/103 s. Similarly, the power spectral density of phase noise was analyzed in the frequency domain. These experimental results demonstrate that the compensation scheme improved the performance by two to three orders of magnitude. Thus, the proposed frequency transmission technique has potential application for disseminating ultrastable frequency references in the optical fiber network.

Associations of visual, hearing, and dual sensory impairment with motoric cognitive risk syndrome: Observational and Mendelian randomization analyses.

BACKGROUND: Dementia is associated with individual vision impairment (VI) and hearing impairment (HI). However, little is known about their associations with motoric cognitive risk syndrome (MCR), a pre-dementia stage. We investigated the association of VI, HI, and dual sensory impairment (DSI) with MCR and to further evaluate causal relationships using Mendelian randomization (MR) approach. METHODS: First, an observational study was conducted in the China Health and Retirement Longitudinal Study (CHARLS). Evaluate the cross-sectional and longitudinal associations of VI, HI, and DSI with MCR using the logistic regression models and Cox proportional hazard models, respectively. Second, evaluate the causal association between VI and HI with MCR using MR analysis. The GWAS data was used for genetic instruments, including 88,250 of European ancestry (43,877 cases and 44,373 controls) and 504,307 with "white British" ancestry (100,234 cases and 404,073 controls), respectively; MCR information was obtained from the GWAS with 22,593 individuals. Inverse variance weighted was the primary method and sensitivity analysis was used to evaluate the robustness of MR methods. RESULTS: In the observational study, VI (HR: 1.767, 95%CI: 1.331-2.346; p < 0.001), HI (HR: 1.461, 95%CI: 1.196-1.783; p < 0.001), and DSI (HR: 1.507, 95%CI: 1.245-1.823; p < 0.001) were significantly associated with increased risk of MCR. For the MR, no causal relationship between VI (OR: 0.902, 95% CI: 0.593-1.372; p = 0.631) and HI (OR: 1.016, 95% CI: 0.989-1.043; p = 0.248) with MCR risk, which is consistent with the sensitivity analysis. CONCLUSION: VI, HI, and DSI were significantly associated with MCR, but MR analysis failed to provide evidence of their causal relationship. Emphasized the importance of sensory impairment screening in identifying high-risk populations for dementia.

Co-drivers of Air Pollutant and CO2 Emissions from On-Road Transportation in China 2010-2020.

Co-controlling the emissions of air pollutants and CO2 from automobiles is crucial for addressing the intertwined challenges of air pollution and climate change in China. Here, we analyze the synergetic characteristics of air pollutant and CO2 emissions from China's on-road transportation and identify the co-drivers influencing these trends. Using detailed emission inventories and employing index decomposition analysis, we found that despite notable progress in pollution control, minimizing on-road CO2 emissions remains a formidable task. Over 2010-2020, the estimated sectoral emissions of VOCs, NOx, PM2.5, and CO declined by 49.9%, 25.9%, 75.2%, and 63.5%, respectively, while CO2 emissions increased by 46.1%. Light-duty passenger vehicles and heavy-duty trucks have been identified as the primary contributors to carbon-pollution co-emissions, highlighting the need for tailored policies. The driver analysis indicates that socioeconomic changes are primary drivers of emission growth, while policy controls, particularly advances in emission efficiency, can facilitate co-reductions. Regional disparities emphasize the need for policy refinement, including reducing dependency on fuel vehicles in the passenger subsector and prioritizing co-reduction strategies in high-emission provinces in the freight subsector. Overall, our study confirms the effectiveness of China's on-road control policies and provides valuable insights for future policy makers in China and other similarly positioned developing countries.

Health Impacts of Long-Term NO2 Exposure and Inequalities among the Chinese Population from 2013 to 2020.

Nitrogen dioxide (NO2) is associated with mortality and many other adverse health outcomes. In 2021, the World Health Organization established a new NO2 air quality guideline (AQG) (annual average <10 µg/m3). However, the burden of diseases attributable to long-term NO2 exposure above the AQG is unknown in China. Nitrogen oxide is a major air pollutant in populous cities, which are disproportionately impacted by NO2; this represents a form of environmental inequality. We conducted a nationwide risk assessment of premature deaths attributable to long-term NO2 exposure from 2013 to 2020 based on the exposure-response relationship, high-resolution annual NO2 concentrations, and gridded population data (considering sex, age, and residence [urban vs rural]). We calculated health metrics including attributable deaths, years of life lost (YLL), and loss of life expectancy (LLE). Inequality in the distribution of attributable deaths and YLLs was evaluated by the Lorenz curve and Gini index. According to the health impact assessments, in 2013, long-term NO2 exposure contributed to 315,847 (95% confidence interval [CI]: 306,709-319,269) premature deaths, 7.90 (7.68-7.99) million YLLs, and an LLE of 0.51 (0.50-0.52) years. The high-risk subgroup (top 20%) accounted for 85.7% of all NO2-related deaths and 85.2% of YLLs, resulting in Gini index values of 0.81 and 0.67, respectively. From 2013 to 2020, the estimated health impact from NO2 exposure was significantly reduced, but inequality displayed a slightly increasing trend. Our study revealed a considerable burden of NO2-related deaths in China, which were disproportionally frequent in a small high-risk subgroup. Future clean air initiatives should focus not only on reducing the average level of NO2 exposure but also minimizing inequality.

Tracking Daily Concentrations of PM2.5 Chemical Composition in China since 2000.

PM2.5 chemical components play significant roles in the climate, air quality, and public health, and the roles vary due to their different physicochemical properties. Obtaining accurate and timely updated information on China's PM2.5 chemical composition is the basis for research and environmental management. Here, we developed a full-coverage near-real-time PM2.5 chemical composition data set at 10 km spatial resolution since 2000, combining the Weather Research and Forecasting-Community Multiscale Air Quality modeling system, ground observations, a machine learning algorithm, and multisource-fusion PM2.5 data. PM2.5 chemical components in our data set are in good agreement with the available observations (correlation coefficients range from 0.64 to 0.75 at a monthly scale from 2000 to 2020 and from 0.67 to 0.80 at a daily scale from 2013 to 2020; most normalized mean biases within ±20%). Our data set reveals the long-term trends in PM2.5 chemical composition in China, especially the rapid decreases after 2013 for sulfate, nitrate, ammonium, organic matter, and black carbon, at the rate of -9.0, -7.2, -8.1, -8.4, and -9.2% per year, respectively. The day-to-day variability is also well captured, including evolutions in spatial distribution and shares of PM2.5 components. As part of Tracking Air Pollution in China (http://tapdata.org.cn), this daily-updated data set provides large opportunities for health and climate research as well as policy-making in China.

Mitigating China's Ozone Pollution with More Balanced Health Benefits.

China is confronting the challenge of opposite health benefits (OHBs) during ambient ozone (O3) mitigation because the same reduction scheme might yield opposite impacts on O3 levels and associated public health across different regions. Here, we used a combination of chemical transport modeling, health benefit assessments, and machine learning to capture such OHBs and optimize O3 mitigation pathways based on 121 control scenarios. We revealed that, for the China mainland, Beijing-Tianjin-Hebei and its surroundings ("2 + 26" cities), Yangtze River Delta, and Pearl River Delta, there could be at most 2897, 920, 1247, and 896 additional O3-related deaths in urban areas, respectively, accompanying 21,512, 3442, 5614, and 642 avoided O3-related deaths in rural areas, respectively, at the same control stage. Additionally, potential disbenefits during O3 mitigation were "pro-wealthy", that is, residents in developed regions are more likely to afford additional health risks. In order to avoid OHBs during O3 abatement, we proposed a two-phase control strategy, whereby the reduction ratio of NOX (nitrogen oxide) to VOCs (volatile organic compounds) was adjusted according to health benefit distribution patterns. Our study provided novel insights into China's O3 attainment and references for other countries facing the dual challenges of environmental pollution and associated inequality issues.

Impacts of climate change on future air quality and human health in China.

In recent years, air pollution has caused more than 1 million deaths per year in China, making it a major focus of public health efforts. However, future climate change may exacerbate such human health impacts by increasing the frequency and duration of weather conditions that enhance air pollution exposure. Here, we use a combination of climate, air quality, and epidemiological models to assess future air pollution deaths in a changing climate under Representative Concentration Pathway 4.5 (RCP4.5). We find that, assuming pollution emissions and population are held constant at current levels, climate change would adversely affect future air quality for >85% of China's population (∼55% of land area) by the middle of the century, and would increase by 3% and 4% the population-weighted average concentrations of fine particulate matter (PM2.5) and ozone, respectively. As a result, we estimate an additional 12,100 and 8,900 Chinese (95% confidence interval: 10,300 to 13,800 and 2,300 to 14,700, respectively) will die per year from PM2.5 and ozone exposure, respectively. The important underlying climate mechanisms are changes in extreme conditions such as atmospheric stagnation and heat waves (contributing 39% and 6%, respectively, to the increase in mortality). Additionally, greater vulnerability of China's aging population will further increase the estimated deaths from PM2.5 and ozone in 2050 by factors of 1 and 3, respectively. Our results indicate that climate change and more intense extremes are likely to increase the risk of severe pollution events in China. Managing air quality in China in a changing climate will thus become more challenging.

Drivers of improved PM2.5 air quality in China from 2013 to 2017.

From 2013 to 2017, with the implementation of the toughest-ever clean air policy in China, significant declines in fine particle (PM2.5) concentrations occurred nationwide. Here we estimate the drivers of the improved PM2.5 air quality and the associated health benefits in China from 2013 to 2017 based on a measure-specific integrated evaluation approach, which combines a bottom-up emission inventory, a chemical transport model, and epidemiological exposure-response functions. The estimated national population-weighted annual mean PM2.5 concentrations decreased from 61.8 (95%CI: 53.3-70.0) to 42.0 µg/m3 (95% CI: 35.7-48.6) in 5 y, with dominant contributions from anthropogenic emission abatements. Although interannual meteorological variations could significantly alter PM2.5 concentrations, the corresponding effects on the 5-y trends were relatively small. The measure-by-measure evaluation indicated that strengthening industrial emission standards (power plants and emission-intensive industrial sectors), upgrades on industrial boilers, phasing out outdated industrial capacities, and promoting clean fuels in the residential sector were major effective measures in reducing PM2.5 pollution and health burdens. These measures were estimated to contribute to 6.6- (95% CI: 5.9-7.1), 4.4- (95% CI: 3.8-4.9), 2.8- (95% CI: 2.5-3.0), and 2.2- (95% CI: 2.0-2.5) µg/m3 declines in the national PM2.5 concentration in 2017, respectively, and further reduced PM2.5-attributable excess deaths by 0.37 million (95% CI: 0.35-0.39), or 92% of the total avoided deaths. Our study confirms the effectiveness of China's recent clean air actions, and the measure-by-measure evaluation provides insights into future clean air policy making in China and in other developing and polluting countries.

First report of Atractylodes lancea leaf spot caused by Fusarium acuminatum in China.

Atractylodes lancea Thunb. DC (cangzhu) is a traditional Chinese medicinal plant (Cai et al., 2020). In June 2020, leaf spots were observed in A. lancea plants at the Chongqing Institute of Medicinal Plant Cultivation located in Nanchuan District, Chongqing, China (29°8'26.46″ N, 107°13'23'21″ E). Approximately 75% of the plants displayed leaf spot, partial leaf wilting, and stunted growth, and some plants died. To determine the cause of this disease, five typical leaf spots were cut into small pieces. The pieces were successively surface-disinfected with 0.5% NaClO for 1 min and 75% ethanol for 30 s, washed thrice with sterile water, and placed on potato dextrose agar (PDA) to incubate at 25 ℃. These isolates initially formed abundant white aerial mycelium, then gradually developed a rose pigmentation with a brownish color in the center and grayish rose at the periphery of the colony (Li et al. 2019). Mycelial tips were picked and placed on carnation leaf agar (CLA) and inoculated for 7 days. The macroconidia of the isolates were slender, distinctively curved in the bottom half of the apical cell, and sickle-shaped, with 3-4 septa. They ranged in size from 16.68-26.49 × 1.48-2.34 µm (n=50). The microconidia were fusiform with or without one septum. Their size ranged from 6.19-11.02 × 1.25-1.43 µm (n=50) (Li et al. 2019). The morphological characteristics of the isolates were consistent with those of Fusarium spp. PCR amplification and DNA sequencing of the internal transcribed spacer (ITS) region and ß-tubulin (TUB2) gene were performed using the primers ITS1/ITS4 (White et al. 1990) and Bt-2a/Bt-2b (Robideau et al. 2011), respectively. BLASTn analysis revealed that the ITS sequences of the isolates were 100% identical to those of the F. acuminatum isolates from the Fusarium MLST database (http://isolate.fusariumdb.org/guide.php). Further analysis revealed that the TUB2 sequences were 99.14% identical to those of the F. acuminatum strain S16 isolates (MF662644) from the GeneBank database of the NCBI server. Based on the morphology and sequence analyses, the isolates were identified as F. acuminatum. Pathogenicity tests were conducted on 1.5-year-old A. lancea plants by inoculating spore suspensions under greenhouse conditions (25°C). For this, wound were made on leaves by piercing with sterilized toothpicks. 30 µl of spore suspension containing 2 × 106 conidia/ml was placed on each wound. Wounds on the leaves of control plants were inoculated with 10 µl of sterile distilled water. There were three plants for each treatment. After incubation at 25 °C for 5 days in a greenhouse, the leaves of the treated plants all showed partial wilting, consistent with the field observations. No symptoms were observed in controlled plants. The fungi were again isolated from the symptomatic tissues and were identical to the original isolate. The experiment was repeated twice with similar results. Pathogenicity symptoms were similar to what was first observed in the field and the isolated fungi were verified based on morphological characteristics, thus fulfilling Koch's postulate. To the best of our knowledge, this is the first time that A. lancea leaf spot caused by F. acuminatum has been discovered in China. The leaf spot caused by F. acuminatum on A. lancea has serious yield loss, and proper control measures should be applied.

Panax notoginseng saponins alleviate damage to the intestinal barrier and regulate levels of intestinal microbes in a rat model of chronic kidney disease.

OBJECTIVES: Chronic kidney disease (CKD) is a long-term condition characterized by poor prognosis and a high mortality rate. Panax notoginseng saponins (PNS) are the main active ingredient of the traditional Chinese herb Panaxnotoginseng(Burk.)F.H.Chen, which has been widely reported to have various pharmacological effects. Here, we examined the effect of PNS on renal function and the modulation of intestinal flora and intestinal barrier in a rat model of adenine-induced CKD. METHODS: Adenine was used to establish a rat model of CKD, biochemical testing, histopathologic examination, ELISA, immunohistochemical assay, western blot assay, and fecal microbiota 16s rRNA analysis was used to test the effect of PNS on CKD rats. RESULTS: Adenine induced a significant decrease in glomerular filtration rate, an increase in urinary protein excretion rate, and pathological damage to renal tissue in CKD rats. TNF-α, MCP-1, IL-1ß, IL-18, TMAO, and endotoxin levels were increased in the blood of the model rats. Application of PNS countered the effects of adenine, restoring the above parameters to the level observed in healthy rats. In addition, activation of the inflammatory proteins NF-κB (p65) and NLRP3 and the fibrosis-associated proteins α-SMA and smad3 were inhibited in the kidneys of CKD rats. Furthermore, PNS promoted the expression of the tight junction proteins Occludin and ZO-1, increased SIgA levels, strengthened intestinal immunity, reduced mechanical damage to the intestine, was reduced levels of DAO and D-LA. Our data suggest PNS may delay CKD by restoring gut microbiota, and through the subsequent generation of a microbial barrier and modulation of microbiota metabolites. CONCLUSIONS: In conclusion, PNS may inhibit the development of inflammation and fibrosis in the kidney tissue through regulation of intestinal microorganisms and inhibition of the activation of pro-inflammatory and pro-fibrotic proteins in the kidney.

The Role of School Connectedness and Friend Contact in Adolescent Loneliness, and Implications for Physical Health.

The current study investigated how adolescents' loneliness relates to school connectedness, classmate support, teacher support, and offline and online communication with friends. We also examined the association between loneliness, physical health, and sleep. Data came from the Scottish Health Behavior in School-aged Children (HBSC). The total sample was 2983 adolescents (F = 1479 [49.6%]) aged 14-17 years (M = 15.66, SD = 0.39) from 117 secondary schools in Scotland. Results showed that (1) higher teacher support, classmate support, and offline contact with friends predicted lower levels of loneliness, (2) online friendship engagement predicted higher levels of loneliness, and (3) poor health and sleep were positively associated with loneliness. The study offers new findings, highlighting the role played by classmates/peers and teachers in reducing loneliness. Supporting previous research, we also found associations between loneliness, poor sleep, and worse physical health.

Production of Atosiban's Key Intermediate Pentapeptide: Synthetic Approaches to the Development of a Peptide Synthesis with Less Racemization and Simplifier Purification Process.

The key intermediate NH2-Ile-Thr(Bzl)-Asn-Cys(Bzl)-Pro-COOH of Atosiban was prepared from N-Boc-S-Bzl-cysteine by the stepwise lengthening of the chain according to the repetitive N,O-bis(trimethylsilyl)acetamide/N-hydroxysuccinimide ester (BSA/NHS) strategy. This synthetic route required no chromatography purification and can be readily performed, yielding a highly pure pentapeptide compound.

Novel 2D photocatalyst of copper-doped carbon quantum dot CD(Cu) loaded with ultrathin Ni-MOL for degradation of tetracycline.

Broadening the light absorption range and suppressing the carrier complexation are the two keys to enhance the photocatalytic activity. In this work, a novel two-dimensional (2D) photocatalyst was successfully prepared by modified hydrothermal method and applied in tetracycline (TC) degradation. The degradation rate of CD(Cu)-Ni-MOL for TC reached 93.5% within 60 min under the visible light condition. The improved photocatalytic performance of CD(Cu)-Ni-MOL was attributed to the constructed 2D layered structure and the special properties of CD(Cu). The doped Cu in carbon dots (CDs) exhibited excellent photocatalytic performance among the elements of Cu, Zn, Ni, Co and Fe. The order of photocatalytic performance improvement was Cu > Zn > Ni > Co > Fe. In addition, a possible degradation pathway for TC was proposed. This work confirms the great potential of CD(Cu)-Ni-MOL as a highly efficient photocatalyst in removing tetracycline pollutants in water.

Clean air actions in China, PM2.5 exposure, and household medical expenditures: A quasi-experimental study.

BACKGROUND: Exposure to air pollution, a leading contributor to the global burden of disease, can cause economic losses. Driven by clean air policies, the air quality in China, one of the most polluted countries, has improved rapidly since 2013. This has enabled a unique, quasi-experiment to assess the economic impact of air pollution empirically. METHODS AND FINDINGS: Using a series of nation-scale longitudinal surveys in 2011, 2013, and 2015, we first examined the questionnaire-based medical expenditure changes before and after the policy intervention for air pollution. Using a state-of-the-art estimator of the historical concentration of particulate matters with diameter less than 2.5 µm (particulate matter (PM)2.5), we further quantified the association between household medical expenditure and PM2.5 using mixed-effect models of the repeated measurements from 26,511 households in 126 cities. Regression models suggest a robust linear association between reduced PM2.5 and saved medical expenditures, since the association did not vary significantly across models with different covariate adjustments, subregions, or subpopulations. Each 10 µg/m3 reduction in PM2.5 was associated with a saving of 251.6 (95% CI: 30.8, 472.3; p-value = 0.026) Yuan in per capita annual medical expenditure. However, due to limitations in data quality (e.g., self-reported expenditures), and imperfect control for unmeasured confounders or impact from concurrent healthcare reform in China, the causality underlying our findings should be further confirmed or refuted. CONCLUSION: In this study, we observed that compared with the PM2.5 reduction in 2013, the PM2.5 reduction in 2017 was associated with a saving of 552 (95% CI: 68, 1036) Yuan / (person × year), or approximately 736 billion Yuan (equivalent to 111 billion US dollar) per year nationally, which is equivalent to approximately 1% of the national gross domestic product of China.

A component-specific exposure-mortality model for ambient PM2.5 in China: findings from nationwide epidemiology based on outputs from a chemical transport model.

Long-term exposure to ambient fine particles (PM2.5) has been evidenced to be a leading contributor to premature mortality in China and many other countries. Previous studies assess the health risk using an exposure-response function, such as an exposure-mortality model (EMM) based on total concentration of PM2.5. However, the risk assessment method can be problematic as it ignores the unequal toxicity between the different chemical components of PM2.5. To derive a components-specific EMM (CS-EMM), we conducted a whole-population-based epidemiology study in China, using the Chinese Population Census data in 2000 and 2010. Concentrations of ambient PM2.5 and its components were assessed by satellite-based concentrations of PM2.5 and composition fractions simulated by a chemical transport model. We used a difference-in-difference approach to associate county-level changes of census-based total mortality with changes of PM2.5 and its components between 2010 and 2000. The chemical components of PM2.5 simulated by the model included sulfate (SO42-), nitrate (NO3-), ammonium (NH4+), organic carbon (OC), and black carbon (BC). We further compared CS-EMM with EMM based on a single pollutant of PM2.5 (PM2.5-EMM) or black carbon (BC-EMM), by evaluating their performance in a risk assessment. Using census-based total mortality and cross validation we evaluated the performance of the mortality prediction of an EMM, and found that the CS-EMM outperformed PM2.5-EMM or BC-EMM. For instance, CS-EMM, PM2.5-EMM, and BC-EMM all overestimated the average number of county-level deaths by 117, 142, and 149, respectively; hence CS-EMM overestimated by the lowest amount. Moreover, CS-EMM had the advantage of interpreting the toxicity of PM2.5 mixture in its entirety. From 2000 to 2010, CS-EMM attributed a 205 496 increase in PM2.5-associated mortality across China to the joint contribution of the growth of total concentration and the reduction of PM2.5 toxicity. Among the components, BC contributed 6.4% of PM2.5 concentration growth, but corresponded to a 46.7% increment in PM2.5-associated deaths. This study developed a framework to establish and validate an exposure-response function based on PM2.5 components, and illustrated its advantages in terms of risk prediction and result interpretation in China. Our approach can be utilized to evaluate how chemical composition modified the health impact of PM2.5, and should help policy-makers target the toxic sources of air pollution.

Tracking Air Pollution in China: Near Real-Time PM2.5 Retrievals from Multisource Data Fusion.

Air pollution has altered the Earth's radiation balance, disturbed the ecosystem, and increased human morbidity and mortality. Accordingly, a full-coverage high-resolution air pollutant data set with timely updates and historical long-term records is essential to support both research and environmental management. Here, for the first time, we develop a near real-time air pollutant database known as Tracking Air Pollution in China (TAP, http://tapdata.org.cn/) that combines information from multiple data sources, including ground observations, satellite aerosol optical depth (AOD), operational chemical transport model simulations, and other ancillary data such as meteorological fields, land use data, population, and elevation. Daily full-coverage PM2.5 data at a spatial resolution of 10 km is our first near real-time product. The TAP PM2.5 is estimated based on a two-stage machine learning model coupled with the synthetic minority oversampling technique and a tree-based gap-filling method. Our model has an averaged out-of-bag cross-validation R2 of 0.83 for different years, which is comparable to those of other studies, but improves its performance at high pollution levels and fills the gaps in missing AOD on daily scale. The full coverage and near real-time updates of the daily PM2.5 data allow us to track the day-to-day variations in PM2.5 concentrations over China in a timely manner. The long-term records of PM2.5 data since 2000 will also support policy assessments and health impact studies. The TAP PM2.5 data are publicly available through our website for sharing with the research and policy communities.

Toward the total synthesis of grayanane diterpene mollanol A by a Prins [3 + 2] strategy.

Toward the total synthesis of a novel grayanoid, mollanol A, we developed a concise convergent strategy based on a formal [3 + 2] cyclization initiated by the Prins reaction. In this key intermolecular reaction between an unprotected hydroxyaldehyde and activating-group-free olefins, two chiral carbons and one densely substituted tetrahydrofuran ring were constructed stereoselectively.

Estimating Spatiotemporal Variation in Ambient Ozone Exposure during 2013-2017 Using a Data-Fusion Model.

Since 2013, clean-air actions in China have reduced ambient concentrations of PM2.5. However, recent studies suggest that ground surface O3 concentrations increased over the same period. To understand the shift in air pollutants and to comprehensively evaluate their impacts on health, a spatiotemporal model for O3 is required for exposure assessment. This study presents a data-fusion algorithm for O3 estimation that combines in situ observations, satellite remote sensing measurements, and model results from the community multiscale air quality model. Performance of the algorithm for O3 estimation was evaluated by five-fold cross-validation. The estimates are highly correlated with the in situ observations of the maximum daily 8 h averaged O3 (R2 = 0.70). The mean modeling error (measured using the root-mean-squared error) is 26 µg/m3, which accounts for 29% of the mean level. We also found that satellite O3 played a key role to improve model performance, particularly during warm months. The estimates were further used to illustrate spatiotemporal variation in O3 during 2013-2017 for the whole country. In contrast to the reduced trend of PM2.5, we found that the population-weighted O3 mean increased from 86 µg/m3 in 2013 to 95 µg/m3 in 2017, with a rate of 2.07 (95% CI: 1.65, 2.48) µg/m3 per year at the national level. This increased trend in O3 suggests that it is becoming an important contributor to the burden of diseases attributable to air pollutants in China. The developed method and the results generated from this study can be used to support future health-related studies in China.