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1.
Phytopathology ; 2020 Mar 31.
Artigo em Inglês | MEDLINE | ID: mdl-32228378

RESUMO

Nonribosomal peptide synthetases (NPS) are known for the biosynthesis of antibiotics, toxins, and siderophore production. They are also a virulence determinant in different phytopathogens. However, until now, the functional characterization of NPS in Verticillium dahliae has not been reported. Deletion of the NPS gene in V. dahliae led to the decrease of conidia, microsclerotia, and pathogenicity. ΔVdNPS strains were tolerant to H2O2, and the genes involved in H2O2 detoxification, iron/copper transport and cytoskeleton were differentially expressed in ΔVdNPS. Interestingly, ΔVdNPS strains exhibited hypersensitive to SA, and the genes involved in SA hydroxylation were up-regulated in ΔVdNPS compared with wild-type V. dahliae under SA stress. Additionally, during infection, ΔVdNPS induced more PR gene expression, higher ROS production, and stronger SA-meidated signaling transduction in host to overcome pathogen. Uncovering the function of VdNPS in pathogenicity could provide a reliable theoretical basis for the development of cultivars with durable resistance against V. dahliae associated diseases.

2.
Sci Total Environ ; 722: 137842, 2020 Jun 20.
Artigo em Inglês | MEDLINE | ID: mdl-32197160

RESUMO

Results from recent studies on associations between blood pressure (BP) and short-term exposure to fine particulate matter (PM2.5) have been inconsistent. Most studies have been evaluations of small geographic areas, with no national study in China. This study aimed to examine the acute BP responses to ambient PM2.5 among the general population of Chinese adults. During 2012-2015, systolic and diastolic BP levels were obtained from a large national representative sample, the China Hypertension Survey database (n = 479,842). Daily PM2.5 average exposures with a spatial resolution of 0.1° were estimated using a data assimilation that combines satellite measurements, air model simulations, and monitoring values. Overall, a 10-µg/m3 increase in daily PM2.5 was associated with a 0.035 (95% confidence interval: 0.020, 0.049) mmHg change in systolic BP and 0.001 (-0.008, 0.011) mmHg in diastolic BP after adjustments. Stratified by geographic regions, the systolic and diastolic BP levels varied from -0.050 (-0.109, 0.010) to 0.242 (0.176, 0.307) mmHg, and from -0.026 (-0.053, 0.001) to 0.051 (0.020, 0.082) mmHg, respectively. Statistically significant positive BP-PM2.5 associations were only found in South and North China for systolic levels and in Southwest China for diastolic levels. We further explored the regional study population characteristics and exposure-response curves, and found that the geographic variations in BP-PM2.5 associations were probably due to different population compositions or different PM2.5 exposure levels. Our study provided national-level evidence on the associations between ambient PM2.5 exposure and elevated BP levels. The magnitude of the estimated associations varied substantially by geographic location in China. CLINICAL TRIAL REGISTRATION: The Clinical trial registration name was Survey on prevalence of hypertension in China; the registration number was ChiCTR-ECS-14004641. http://www.chictr.org.cn/showproj.aspx?proj=4932.

3.
Org Biomol Chem ; 18(10): 1877-1880, 2020 03 14.
Artigo em Inglês | MEDLINE | ID: mdl-32100814

RESUMO

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.

4.
Proc Natl Acad Sci U S A ; 116(49): 24463-24469, 2019 Dec 03.
Artigo em Inglês | MEDLINE | ID: mdl-31740599

RESUMO

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.

5.
Proc Natl Acad Sci U S A ; 116(35): 17193-17200, 2019 Aug 27.
Artigo em Inglês | MEDLINE | ID: mdl-31405979

RESUMO

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.

6.
Nat Commun ; 10(1): 3609, 2019 Aug 06.
Artigo em Inglês | MEDLINE | ID: mdl-31383856

RESUMO

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

7.
Nature ; 572(7769): 373-377, 2019 08.
Artigo em Inglês | MEDLINE | ID: mdl-31261374

RESUMO

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.

8.
Sci Total Environ ; 692: 361-370, 2019 Nov 20.
Artigo em Inglês | MEDLINE | ID: mdl-31351280

RESUMO

In 2013, the Chinese government announced its first air quality standard for PM2.5 (particulate matter with a diameter < 2.5 µm) which requires annual mean PM2.5 concentration to achieve the World Health Organization (WHO) interim target 1 of 35 µg/m3 nationwide including the most polluted region of Beijing-Tianjin-Hebei (BTH). Here, we explore the future mitigation pathways for the BTH region to investigate the possibility of air quality attainment by 2030 in that region, by developing two energy scenarios (i.e., baseline energy scenario and enhanced energy scenario) and two end-of-pipe scenarios (i.e., business as usual scenario and best available technology scenario) and simulating future air quality for different scenarios using the WRF/CMAQ model. Results showed that without stringent energy and industrial structure adjustment, even the most advanced end-of-pipe technologies did not allow the BTH region to attain the 35 µg/m3 target. Under the most stringent scenario that coupled the enhanced structure adjustment measures and the best available end-of-pipe measures, the emissions of SO2, NOx, PM2.5 and NMVOCs (nonmethane volatile organic compounds) were estimated to be reduced by 85%, 74%, 82% and 72%, respectively, in 2030 over the BTH region. As a result, the simulated annual mean PM2.5 concentrations in Beijing, Tianjin and Hebei could decline to 23, 28 and 28 µg/m3, respectively, all of which achieved the 35 µg/m3 target by 2030. Our study identified a feasible pathway to achieve the 2030 target and highlighted the importance of reshaping the energy and industrial structure of the BTH region for future air pollution mitigation.

9.
Environ Int ; 129: 430-437, 2019 08.
Artigo em Inglês | MEDLINE | ID: mdl-31154145

RESUMO

Long-term exposure to ambient fine particulate matter (PM2.5) has been identified as a major contributor to disease burden in many countries, including China. The effects of long-term PM2.5 exposure have been evaluated by risk assessment studies, which are based on an exposure-response function (ERF) derived from a specific epidemiological study or multiple studies. To explore whether generalization from the pre-established ERFs (including the integrated exposure-response [IER] model and the global exposure mortality model [GEMM]) introduces biases into risk assessment of a specific local population, we conducted the first census-based epidemiological study of PM2.5, aimed at the entire population of mainland China. Using a difference-in-difference analysis at the county level, we associated mortality changes from 2000 to 2010 to corresponding PM2.5 changes, with adjustments made for multiple socioeconomic factors. Based on the epidemiological linkage between PM2.5 and total mortality, we calculated the change in PM2.5-attributed deaths and compared this value with the results derived from the pre-established models (IER and GEMM). According to the epidemiological model, a 10-µg/m3 increment in PM2.5 was associated with a 4.3% (95% confidence interval [CI]: 1.9%-6.7%) increment in total mortality, and the change in PM2.5-attributed deaths from 2000 to 2010 was estimated as 561,000 (95% CI: 539,000-581,000). The census-based estimation was in better agreement with the GEMM results (545,000-612,000) than was the IER result (354,000 [95% CI: 286,000-421,000]). In sensitivity analyses of the epidemiological model, the association between PM2.5 exposure and mortality was stronger among younger adults, consistent with the pre-established models. Due to the potential limitations of our findings, we cannot conclusively state that GEMM is more reliable than IER in China. Future studies are warranted to confirm or refute our findings.


Assuntos
Poluentes Atmosféricos/toxicidade , Poluição do Ar/efeitos adversos , Mortalidade/tendências , Vigilância da População , Adulto , China , Exposição Ambiental/análise , Feminino , Humanos , Masculino , Material Particulado/análise , Medição de Risco , Fatores Socioeconômicos
10.
Nat Commun ; 10(1): 2165, 2019 05 15.
Artigo em Inglês | MEDLINE | ID: mdl-31092825

RESUMO

Mental disorders have been associated with various aspects of anthropogenic change to the environment, but the relative effects of different drivers are uncertain. Here we estimate associations between multiple environmental factors (air quality, residential greenness, mean temperature, and temperature variability) and self-assessed mental health scores for over 20,000 Chinese residents. Mental health scores were surveyed in 2010 and 2014, allowing us to link changes in mental health to the changes in environmental variables. Increases in air pollution and temperature variability are associated with higher probabilities of declined mental health. Mental health is statistically unrelated to mean temperature in this study, and the effect of greenness on mental health depends on model settings, suggesting a need for further study. Our findings suggest that the environmental policies to reduce emissions of air pollution or greenhouse gases can improve mental health of the public in China.


Assuntos
Poluição do Ar/efeitos adversos , Transtornos Mentais/epidemiologia , Saúde Mental/tendências , Adolescente , Adulto , Idoso , Poluição do Ar/prevenção & controle , China/epidemiologia , Política Ambiental , Feminino , Efeito Estufa/prevenção & controle , Gases de Efeito Estufa/efeitos adversos , Humanos , Masculino , Transtornos Mentais/etiologia , Saúde Mental/estatística & dados numéricos , Pessoa de Meia-Idade , Estações do Ano , Autoavaliação , Temperatura , Adulto Jovem
11.
Sci Total Environ ; 654: 135-143, 2019 Mar 01.
Artigo em Inglês | MEDLINE | ID: mdl-30439690

RESUMO

Evidence suggesting an association between ozone exposure and stroke risk remains inconsistent; variations in the distributions of susceptibilities of the study populations may explain some of it. We examined the hypothesis in a general Chinese population. During 2013-2015, 1356 first-ever stroke events were selected from a large representative sample, the China National Stroke Screening Survey (CNSSS) database; daily maximal 8-hour ozone concentrations were obtained from spatiotemporally interpolated estimates of in-situ observations over China. We conducted a time-stratified case-crossover design to assess associations between stroke risk and ambient ozone exposure. Next, potential effect modifiers were identified using interaction analyses. Final, a well-established approach was applied to estimate individual-level susceptibility (i.e., the individual-specific effect given a certain combination of multiple effect-modifiers) and its probability distribution among all the CNSSS participants (n = 1,292,010). With adjustments for temperature, relative humidity and ambient fine particulate matter exposure, a 10-µg/m3 increment in mean ozone levels 2-3 day prior to symptom onset was associated with a 3.0% change in stroke risk (95% confidence interval: -1.2%, 7.3%). This association was statistically significantly enhanced by male gender, rural residence and low vegetable and fruit consumption. The subgroup results suggested that a fraction of the population might be considerably affected by ozone, regardless of the insignificant association in average level. The analysis of susceptibility distribution further indicated that the ozone-stroke association was statistically significantly positive in 14% of the general population. Susceptibility to ozone-related stroke significantly varied among Chinese adults. Characterizing individual-level susceptibility reveals the complexity underlying the weak average effect of ozone, and supports to plan subpopulation-specific interventions to mitigate the stroke risk.


Assuntos
Poluentes Atmosféricos/análise , Ozônio/análise , Material Particulado/análise , Acidente Vascular Cerebral/epidemiologia , Idoso , China/epidemiologia , Estudos Cross-Over , Suscetibilidade a Doenças/epidemiologia , Feminino , Humanos , Masculino , Pessoa de Meia-Idade , Fatores de Risco , Estações do Ano
12.
Environ Int ; 123: 345-357, 2019 02.
Artigo em Inglês | MEDLINE | ID: mdl-30562706

RESUMO

Ambient exposure to fine particulate matter (PM2.5) is known to harm public health in China. Satellite remote sensing measurements of aerosol optical depth (AOD) were statistically associated with in-situ observations after 2013 to predict PM2.5 concentrations nationwide, while the lack of surface monitoring data before 2013 have created difficulties in historical PM2.5 exposure estimates. Hindcast approaches using statistical models or chemical transport models (CTMs) were developed to overcome this limitation, while those approaches still suffer from incomplete daily coverage due to missing AOD data or limited accuracy due to uncertainties of CTMs. Here we developed a new machine learning (ML) model with high-dimensional expansion (HD-expansion) of numerous predictors (including AOD and other satellite covariates, meteorological variables and CTM simulations). Through comprehensive characterization of the nonlinear effects of, and interactions among different predictors, the HD-expansion parameterized the association between PM2.5 and AOD as a nonlinear function of space and time covariates (e.g., planetary boundary layer height and relative humidity). In this way, the PM2.5-AOD association can vary spatiotemporally. We trained the model with data from 2013 to 2016 and evaluated its performance using annually-iterated cross-validation, which iteratively held out the in-situ observations for a whole calendar year (as testing data) to examine the predictions from a model trained by the rest of the observations. Our estimates were found to be in good agreement with in-situ observations, with correlation coefficients (R2) of 0.61, 0.68, and 0.75 for daily, monthly and annual averages, respectively. To interpolate the missing predictions due to incomplete AOD data, we incorporated a generalized additive model into the ML model. The two-stage estimates of PM2.5 sacrificed the prediction accuracy on a daily timescale (R2 = 0.55), but achieved complete spatiotemporal coverage and improved the accuracy of monthly (R2 = 0.71) and annual (R2 = 0.77) averages. The model was then used to predict daily PM2.5 concentrations during 2000-2016 across China and estimate long-term trends in PM2.5 for the period. We found that population-weighted concentrations of PM2.5 significantly increased, by 2.10 (95% confidence interval (CI): 1.74, 2.46) µg/m3/year during 2000-2007, and rapidly decreased by 4.51 (3.12, 5.90) µg/m3/year during 2013-2016. In this study, we produced AOD-based estimates of historical PM2.5 with complete spatiotemporal coverage, which were evidenced as accurate, particularly in middle and long term. The products could support large-scale epidemiological studies and risk assessments of ambient PM2.5 in China and can be accessed via the website (http://www.meicmodel.org/dataset-phd.html).


Assuntos
Poluentes Atmosféricos/análise , Monitoramento Ambiental/métodos , Aprendizado de Máquina , Material Particulado/análise , Aerossóis/análise , China , Humanos , Modelos Químicos , Modelos Estatísticos , Saúde Pública , Medição de Risco , Comunicações Via Satélite
13.
Environ Sci Technol ; 52(21): 12905-12914, 2018 11 06.
Artigo em Inglês | MEDLINE | ID: mdl-30249091

RESUMO

As the largest energy infrastructure in China, the power sector consumed approximately half of China's coal over the past decade and threatened air quality and greenhouse gas (GHG) abatement targets. In this work, we assessed the evolution of coal-fired power plants and associated emissions in China during 2010-2030 by using a unit-based emission projection model, which integrated the historical power plant information, turnover of the future power plant fleet, and evolution of end-of-pipe control technologies. We found that, driven by stringent environmental legislation, SO2, NO x, and PM2.5 (particulate matter less than 2.5 µm in diameter) emissions from coal-fired power plants decreased by 49%, 45%, and 24%, respectively, during 2010-2015, compared to 15% increase in CO2 emissions. In contrast to ever-increasing CO2 emissions until 2030 under current energy development planning, we found that aggressive energy development planning could curb CO2 emissions from the peak before 2030. Owing to the implementation of a "near zero" emission control policy, we projected emissions of air pollutants will significantly decrease during 2016-2030. Early retirement of small and low-efficiency power plants would further reduce air pollutants and CO2 emissions. Our study explored various mitigation pathways for China's coal-fired power plants, which could reduce coal consumption, air pollutants, and CO2 emissions and improve energy efficiency.


Assuntos
Poluentes Atmosféricos , Poluição do Ar , China , Carvão Mineral , Centrais Elétricas
15.
Lancet Planet Health ; 2(4): e151-e161, 2018 04.
Artigo em Inglês | MEDLINE | ID: mdl-29615216

RESUMO

BACKGROUND: Except for comparing the implementation costs of the Paris Agreement with potential health benefits at the national levels, previous studies have not explored the health impacts of the nationally determined contributions (NDCs) by countries and in regional details. In this Lancet Countdown study, we aimed to estimate and monetise the health benefits of China's NDCs in the electric power generation sector, and then compare them with the implementation costs, both at the national and regional levels. METHODS: In this modelling study, we linked the Multi-regional model for Energy Supply system and their Environmental ImpaCts, the Multi-resolution Emission Inventory for China model, the offline-coupled Weather Research and Forecasting model, the Community Multiscale Air Quality model, and the Integrated Health Impact Assessment model with a time scope from 2010 to 2050. We calculated the PM2·5 concentrations and compared the health impacts and implementation costs between two scenarios that reflect CO2 and air pollutant emissions-the reference (REF) scenario (no climate policy) and the NDC scenario (100% realisation of NDC targets: CO2 emission intensity needs to be about 40% below 2010 emissions by 2030 [roughly 35% below 2030 emissions in REF], and about 90% below 2010 emissions by 2050 [roughly 96% below 2050 emissions in REF]). FINDINGS: Under a comparatively optimistic health benefits valuation condition, at the national level, 18-62% of implementation costs could be covered by the health benefits in 2030. In 2050, the overall health benefits would substantially increase to 3-9 times of the implementation costs. However, northwest China would require the highest implementation costs and will also have more premature deaths because of a more carbon-intensive energy structure than business as usual. By 2030, people in northwest China (especially in Gansu, Shaanxi, and Xinjiang provinces) would need to bear worse air quality, and 10 083 (95% CI 3419-16 138) more premature deaths annually. This undesirable situation would diminish by about 2050. A solution that assumes no growth in air pollutant emissions in 2030 at the regional level is technically feasible, but would not be cost-effective. INTERPRETATION: Our results suggest that cost-benefit analysis of climate policy that omits regional air pollution could greatly underestimate benefits. A compensation mechanism for inter-regional interests (including financial, technological, and knowledge support) should be established for regions that give up their human health benefits for the sake of the whole nation to realise the climate change targets. FUNDING: National Natural Science Foundation of China and Cyrus Tang Foundation.


Assuntos
Poluentes Atmosféricos/análise , Poluição do Ar/prevenção & controle , Dióxido de Carbono/análise , Mudança Climática , Recuperação e Remediação Ambiental/métodos , Material Particulado/análise , Centrais Elétricas , China , Humanos , Modelos Teóricos , Tamanho da Partícula
16.
Am J Epidemiol ; 187(5): 1001-1009, 2018 05 01.
Artigo em Inglês | MEDLINE | ID: mdl-29351572

RESUMO

Different populations may respond differently to exposure to ambient fine particulate matter, defined as particulate matter with an aerodynamic diameter less than or equal to 2.5 µm (PM2.5); however, less is known about the distribution of susceptible individuals among the entire population. We conducted a time-stratified case-crossover study to assess associations between stroke risk and exposure to PM2.5. During 2013-2015, 1,356 first-ever stroke events were derived from a large representative sample, the China National Stroke Screening Survey (CNSSS) database. Daily PM2.5 average exposures with a spatial resolution of 0.1° were estimated using a data assimilation approach combining satellite measurements, air model simulations, and monitoring values. The distribution of susceptibility was derived according to individual-specific associations with PM2.5 modified by different combinations of individual-level characteristics and their joint frequencies among all of the CNSSS participants (n = 1,292,010). We found that first-ever stroke was statistically significantly associated with PM2.5 (per 10-µg/m3 increment of exposure, odds ratio = 1.049, 95% confidence interval (CI): 1.038, 1.061). This association was modified by demographic (e.g., sex), lifestyle (e.g., overweight/obesity), and medical history (e.g., diabetes) variables. The combined association with PM2.5 varied from 0.966 (95% CI: 0.920, 1.013) to 1.145 (95% CI: 1.080, 1.215) per 10-µg/m3 increment in different subpopulations. We found that most of the CNSSS participants were at increased risk of PM2.5-related stroke, while only a small proportion were highly susceptible.


Assuntos
Poluentes Atmosféricos/efeitos adversos , Poluição do Ar/efeitos adversos , Exposição Ambiental/efeitos adversos , Material Particulado/efeitos adversos , Acidente Vascular Cerebral/etiologia , Adulto , Idoso , Poluentes Atmosféricos/análise , Poluição do Ar/análise , China/epidemiologia , Estudos Cross-Over , Demografia , Suscetibilidade a Doenças/etiologia , Exposição Ambiental/análise , Feminino , Inquéritos Epidemiológicos , Humanos , Masculino , Pessoa de Meia-Idade , Razão de Chances , Material Particulado/análise , Risco , Acidente Vascular Cerebral/epidemiologia
17.
Huan Jing Ke Xue ; 39(12): 5289-5295, 2018 Dec 08.
Artigo em Chinês | MEDLINE | ID: mdl-30628371

RESUMO

Based on the high-resolution coal-fired power plant emission database, GEOS-Chem Adjoint, a global-regional nested atmospheric chemistry model and its adjoint were applied to analyze PM2.5-related premature deaths caused by the power sector in six grid regions of China due to air pollutant emissions and subsequent pollution. The results show that power sector-related PM2.5 pollution caused 106000 (95% CI:68000-132000) premature deaths in 2010, accounting for 9.8% of China's anthropogenic PM2.5-related premature deaths. The health loss intensity (defined as number of premature deaths caused by a unit of power generation) of small and old units is significantly higher than that of large and new units:units with a capacity below 100 MW reach 62 people·(TW·h)-1, 2.8 times that of units with a capacity above 600 MW. Similarly, the health loss intensity of units older than thirty years is 58 people·(TW·h)-1, 2.1 times that of new units. From the perspective of regional grids, the health impact index of Central China is relatively large, reaching 77 people·(TW·h)-1. Further analysis reveals that transregional power transmission led to a net increase of 680 premature deaths compared with the scenario without transmission in 2010. Our study implies that China should accelerate the pace of phasing out small and old units and optimize the power transmission distribution between grid regions to reduce the overall level of pollution and health losses.


Assuntos
Poluição do Ar/efeitos adversos , Carvão Mineral , Mortalidade , Centrais Elétricas , Poluentes Atmosféricos , China , Humanos , Material Particulado/efeitos adversos
18.
Environ Pollut ; 227: 296-305, 2017 Aug.
Artigo em Inglês | MEDLINE | ID: mdl-28477554

RESUMO

Four haze episodes (EPs) were observed in October 2014 in Beijing, China. For better understanding of the characteristics and the formation mechanisms of PM2.5 (particulate matter with an aerodynamic diameter ≤ 2.5 µm), especially secondary water-soluble inorganic species in these haze events, hourly concentrations of PM2.5, sulfate, nitrate, and ammonium (SNA) were measured in this study. Concentrations of gaseous pollutants and meteorological parameters were also measured. The average concentration of PM2.5 was 106.6 ± 83.5 µg m-3, which accounted for around 53% of PM10 (particulate matter with an aerodynamic diameter ≤ 10 µm) mass. Nitrogen dioxide (NO2) concentration was much higher than that of sulfur dioxide (SO2) since October is a non-heating month. SNA is the most abundant secondary water-soluble inorganic species and contributed to 33% of PM2.5 mass concentration. Sulfur oxidation ratio (SOR) was much higher than nitrogen oxidation ratio (NOR). NOR and SOR increased with elevated PM2.5 levels and heterogeneous processes seemed to be the most plausible explanation of this increase. Relative humidity (RH), which is of great influence on aerosol liquid water content (ALWC), played a considerable role in the formation of secondary inorganic aerosols, accelerated the secondary transformation of gaseous precursors, and further aggravated haze pollution. The positive feedback loop associated with high aerosol levels and low planetary boundary layer (PBL) height led to the evolution and exacerbation of heavy haze pollution. Fire maps and 48-h air mass backward trajectories supported the significant impact of biomass burning activities and regional transport on haze formation over Beijing in October 2014.


Assuntos
Poluentes Atmosféricos/análise , Monitoramento Ambiental , Material Particulado/análise , Aerossóis/análise , Pequim , China , Meteorologia , Nitratos/análise , Dióxido de Nitrogênio , Estações do Ano , Solubilidade , Sulfatos/análise , Dióxido de Enxofre , Água
19.
Environ Pollut ; 226: 143-153, 2017 Jul.
Artigo em Inglês | MEDLINE | ID: mdl-28419921

RESUMO

High resolution pollution maps are critical to understand the exposure and health effect of local residents to air pollution. Currently, none of the single technologies used to measure or estimate concentrations of pollutants can provide sufficient resolved exposure data. Land use regression (LUR) models were developed to combine ground-based measurements, satellite remote sensing (SRS) and air quality model (AQM), together with geographic and local source related spatial inputs, to generate high resolution pollution maps for both PM2.5 and NO2 in Pearl River Delta (PRD), China. Four sets of LUR models (LUR without SRS or AQM, with SRS only, with AQM only, and with both SRS and AQM), all including local traffic emissions and land use variables, were compared to evaluate the contribution of SRS and AQM data to the performance of LUR models in PRD region. For NO2, the annual model with SRS estimate performed best, explaining 60.5% of the spatial variation. For PM2.5, the annual model with traditional predictor variables without SRS or AQM estimates showed the best performance, explaining 88.4% of the spatial variation. Pollution surfaces at 200 m*200 m resolution were generated according to the best performed models.


Assuntos
Poluentes Atmosféricos/análise , Monitoramento Ambiental/métodos , Modelos Químicos , Dióxido de Nitrogênio/análise , Material Particulado/análise , Poluição do Ar/análise , China , Humanos , Tecnologia de Sensoriamento Remoto , Rios , Imagens de Satélites
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