Xin Qian

Mortality effects assessment of ambient PM2.5 pollution in the 74 leading cities of China.

BACKGROUNDnAmbient fine particulate matter (PM2.5) pollution is currently a most severe and worrisome environmental problem in China. However, current knowledge of the health effects of this pollution is insufficient.nnnOBJECTIVESnThis study aims to provide an overall understanding regarding the long-term mortality effects of current PM2.5 pollution in China and the potential health benefits of realizing the goals stipulated in the ongoing action plan of Air Pollution Prevention and Control (APPC) and the targets suggested by the WHO.nnnMETHODSnThree typical causes and all-cause of PM2.5-related mortality were considered. The log-linear exposure-response function was adopted, and a meta-analysis was used to determine the exposure-response coefficients, based on newly available data in China and abroad.nnnRESULTSnIn the 74 leading cities of China, approximately 32% of the reported deaths, with a mortality rate of 1.9‰, were associated with PM2.5 in 2013, in which deaths from cardiovascular, respiratory and lung-cancer causes accounted for 20% of the reported deaths, with a mortality rate of 1.2‰. The regional difference is remarkable for the mortalities and proportions of the different causes. If the PM2.5 concentration goals of the APPC plan, the first interim and the guideline targets of the WHO could be achieved, the PM2.5-related all-cause mortality would be reduced by 25%, 64% and 95%, respectively, compared with that of 2013.nnnCONCLUSIONSnPM2.5 pollution in China has incurred great health risks that are even worse than those of tobacco smoking. The health benefits of the APPC plan could be outstanding, although there is still great potential to improve future air quality.

Bioaccessibility, sources and health risk assessment of trace metals in urban park dust in Nanjing, Southeast China

Arsenic, Cd, Co, Cr, Cu, Mn, Ni, Pb, V, and Zn total concentrations and bioaccessibilities in 15 urban park dust samples were determined. The oral bioaccessibility measured by the Simple Bioaccessibility Extraction Test (SBET) decreased in the order of Pb>Cd>Zn>Mn>Cu>Co>V>Ni>As>Cr. The Tomlinson pollution load index (PLI) and geoaccumulation index (I(geo)) were calculated to evaluate the pollution extent to which the samples were contaminated. Sources were identified using principal component analysis and Pb isotope compositions. Most elements except Co and V were considered to mainly originate from anthropogenic sources. Non-carcinogenic and carcinogenic risks to humans through urban park dust exposure were assessed using the oral bioaccessibilities of the elements. Ingestion was the main pathway for non-carcinogenic risk. The hazard quotients were below the safe level (=1) for all elements, however, Pb (0.154) and As (0.184) posed potential higher risks to children than adults. The carcinogenic effects occurring were below the acceptable level (10(-4)) for As and <10(-6) for Cd, Co, Cr, and Ni.

Temporal and spatial variability of chlorophyll a concentration in Lake Taihu using MODIS time-series data

In order to predict the distribution of chlorophyll a synoptically in Lake Taihu from 2006 to 2008, a common empirical algorithm was developed to relate time series chlorophyll a concentrations in the lake to reflectance derived as a function of band 2 MODIS data (r2xa0=xa00.907, nxa0=xa0145) using time series from 2005. The empirical model was further validated with chlorophyll a data from a 2008 to 2009 dataset, with RMSExa0<xa07.48xa0μgxa0l−1 and r2xa0=xa00.978. The seasonal and inter-annual variability of the surface chlorophyll a concentration from 2006 to 2008 was then examined using Empirical Orthogonal Function (EOF) analysis. The results revealed that the first four modes were significant, explaining 54.0% of the total chlorophyll a variance, and indicated that during the summer, algal blooms always occur in the northern bays, Meiliang Bay and Gonghu Bay, while they occur along the southwestern lakeshore during early summer, fall, and even early winter. The inter-annual variance analysis showed that the duration of algal blooms was from April to December of 2007, which was different from the bloom periods in 2006 and 2008. The results of EOF analysis show its potential for long-term integrated lake monitoring, not only in Lake Taihu but also in other large lakes threatened by accelerating eutrophication.

Time-series MODIS Image-based Retrieval and Distribution Analysis of Total Suspended Matter Concentrations in Lake Taihu (China)

Although there has been considerable effort to use remotely sensed images to provide synoptic maps of total suspended matter (TSM), there are limited studies on universal TSM retrieval models. In this paper, we have developed a TSM retrieval model for Lake Taihu using TSM concentrations measured in situ and a time series of quasi-synchronous MODIS 250 m images from 2005. After simple geometric and atmospheric correction, we found a significant relationship (R = 0.8736, N = 166) between in situ measured TSM concentrations and MODIS band normalization difference of band 3 and band 1. From this, we retrieved TSM concentrations in eight regions of Lake Taihu in 2007 and analyzed the characteristic distribution and variation of TSM. Synoptic maps of model-estimated TSM of 2007 showed clear geographical and seasonal variations. TSM in Central Lake and Southern Lakeshore were consistently higher than in other regions, while TSM in East Taihu was generally the lowest among the regions throughout the year. Furthermore, a wide range of TSM concentrations appeared from winter to summer. TSM in winter could be several times that in summer.

Fractionation of airborne particulate-bound elements in haze-fog episode and associated health risks in a megacity of southeast China.

Haze caused by high particulate matter loadings is an important environmental issue. PM2.5 was collected in Nanjing, China, during a severe haze-fog event and clear periods. The particulate-bound elements were chemically fractionated using sequential extractions. The average PM2.5 concentration was 3.4 times higher during haze-fog (96-518 μg/m(3)) than non-haze fog periods (49-142 μg/m(3)). Nearly all elements showed significantly higher concentrations during haze-fog than non-haze fog periods. Zn, As, Pb, Cd, Mo and Cu were considered to have higher bioavailability and enrichment degree in the atmosphere. Highly bioavailable fractions of elements were associated with high temperatures. The integrated carcinogenic risk for two possible scenarios to individuals exposed to metals was higher than the accepted criterion of 10(-6), whereas noncarcinogenic risk was lower than the safe level of 1. Residents of a city burdened with haze will incur health risks caused by exposure to airborne metals.

Seasonal and Spatial Variations of Heavy Metals in Two Typical Chinese Rivers: Concentrations, Environmental Risks, and Possible Sources

Ten metals were analyzed in samples collected in three seasons (the dry season, the early rainy season, and the late rainy season) from two rivers in China. No observed toxic effect concentrations were used to estimate the risks. The possible sources of the metals in each season, and the dominant source(s) at each site, were assessed using principal components analysis. The metal concentrations in the area studied were found, using t-tests, to vary both seasonally and spatially (P = 0.05). The potential risks in different seasons decreased in the order: early rainy season > dry season > late rainy season, and Cd was the dominant contributor to the total risks associated with heavy metal pollution in the two rivers. The high population and industrial site densities in the Taihu basin have had negative influences on the two rivers. The river that is used as a source of drinking water (the Taipu River) had a low average level of risks caused by the metals. Metals accumulated in environmental media were the main possible sources in the dry season, and emissions from mechanical manufacturing enterprises were the main possible sources in the rainy season. The river in the industrial area (the Wusong River) had a moderate level of risk caused by the metals, and the main sources were industrial emissions. The seasonal and spatial distributions of the heavy metals mean that risk prevention and mitigation measures should be targeted taking these variations into account.

Heavy Metals in Atmospheric Particulate Matter: A Comprehensive Understanding Is Needed for Monitoring and Risk Mitigation

U atmospheric pollution is one of the most serious global environmental issues of the past decade. Atmospheric particulate matter (PM) is of great concern to the public and to government agencies because of the health effects and haze episodes associated with it. PM has the strong potential for adsorbing toxic metals, which may then enter the human body through inhalation and have adverse physiological effects. Exposure to PM has been linked to a wide range of diseases, including cardiovascular and respiratory diseases and lung cancer. There is growing evidence that heavy metals adsorbed to PM are crucial to the toxicity and adverse health effects of PM. Metal elements adsorbed to atmospheric PM can also be deposited to soils, water bodies, and plant leaves via wet and dry deposition. They may then accumulate in plants or animals through biochemical processes; and humans may then be exposed by consumption of contaminated plants or animals. In order to control the atmospheric heavy metal pollution, it is essential to conduct effective environmental risk management. Rapid evaluation models on spatiotemporal distributions of heavy metals and practical early warning programs could be developed by combining the monitoring data with interdisciplinary research, such as atmospheric pollutant diffusion models, epidemiological investigations, toxicological experiments, and geographical information systems. Recent scientific research on heavy metals in PM has been focused on the pollution levels, source analysis, temporal variations, spatial distributions, and health effects of heavy metals adsorbed to PM. However, heavy metals are important components of PM in the atmospheric environment and they have complex pollution feature. There are still several potentially important problems that require special attention and further study before we will have a comprehensive understanding of the occurrence and behavior of heavy metals in PM. First, when compared with coarse PM, fine particulate matter (PM2.5, particles with aerodynamic diameters ≤2.5 μm) has a greater surface area per unit mass, allowing PM2.5 to accumulate heavy metals more effectively; PM2.5 is also more hazardous than coarser PM because of its longer residence time in the atmosphere and deeper penetration into the lungs. The standards or reference values for atmospheric Pb, Cd, As, Ni, and Cr (VI) concentrations proposed by the European Union and the World Health Organization, as well as the newest Chinese “Ambient Air Quality Standards” (GB3095−2012) which were issued in 2012, are currently based on heavy metal concentrations in coarse PM. Atmospheric Hg concentrations are determined as elemental mercury vapor (Hg 0). Although monitoring data may be appropriate to meet safety standard requirements, ambient heavy metal concentrations and the extent of adverse effects caused by heavy metals in PM2.5 remain uncertain. It is necessary to conduct more surveys and analyses on heavy metals in fine PM or even ultrafine PM (PM0.1, particles with aerodynamic diameters ≤0.1 μm) to improve the usefulness of monitoring atmospheric heavy metals. Second, the total amount of heavy metals in the environment is usually used as the main or only evaluation criteria in assessing the pollution conditions. However, it is generally recognized that the chemical speciation of a heavy metal probably determines its bioavailability and the potential risks it poses to the environment and to human health. The heavy metal chemical speciation in a solid environmental sample can generally be determined by sequentially extracting the different species as the adsorbed−exchangeable carbonate phase, the reducible phase, the oxidizable phase, and the residual fraction. The first three of those species types, especially the adsorbed− exchangeable carbonate phase, are considered to be more mobile in the environment and more hazardous to organisms than is the resistant fraction. Attention should therefore be paid to the chemical speciation of heavy metals in PM. Third, PM can either be directly emitted into the air (primary PM), or it can be formed secondarily in the

Allelopathic effect of Microcystis aeruginosa on Microcystis wesenbergii: microcystin-LR as a potential allelochemical

Microcystis aeruginosa and Microcystis wesenbergii are two cyanobacteria commonly found in eutrophic shallow lakes. Previous studies reported that microcystin-producing M. aeruginosa could have an increased competitive potential on other algae and aquatic plants, and microcystin-LR (MC-LR) was regarded as an allelochemical. Based on this hypothesis, the allelopathic interaction between these two cyanobacteria was studied for the first time under laboratory conditions, and potential allelochemicals were screened. Cyanobacteria biomass and microcystin-LR (MC-LR) concentration were monitored under different culture conditions. The potential allelochemicals from M. aeruginosa were investigated by extract fractionation and GC(LC)/MS analysis. The growth of M. wesenbergii was inhibited by the addition of cell-free filtrates of M. aeruginosa whereas M. aeruginosa was promoted by the addition of cell-free filtrates of M. wesenbergii. The higher polarity the extract of M. aeruginosa is, the stronger the inhibition effect of the extract on M. wesenbergii will be. According to our results, M. aeruginosa has a significant allelopathic inhibition effect on M. wesenbergii. Allelopathic compounds from M. aeruginosa have synergistic effects on inhibition of M. wesenbergii. Besides microcystin, there may be other allelopathic compounds in M. aeruginosa.

Spatial Multicriteria Decision Analysis of Flood Risks in Aging-Dam Management in China: A Framework and Case Study

Approximately 30,000 dams in China are aging and are considered to be high-level risks. Developing a framework for analyzing spatial multicriteria flood risk is crucial to ranking management scenarios for these dams, especially in densely populated areas. Based on the theories of spatial multicriteria decision analysis, this report generalizes a framework consisting of scenario definition, problem structuring, criteria construction, spatial quantification of criteria, criteria weighting, decision rules, sensitivity analyses, and scenario appraisal. The framework is presented in detail by using a case study to rank dam rehabilitation, decommissioning and existing-condition scenarios. The results show that there was a serious inundation, and that a dam rehabilitation scenario could reduce the multicriteria flood risk by 0.25 in the most affected areas; this indicates a mean risk decrease of less than 23%. Although increased risk (<0.20) was found for some residential and commercial buildings, if the dam were to be decommissioned, the mean risk would not be greater than the current existing risk, indicating that the dam rehabilitation scenario had a higher rank for decreasing the flood risk than the decommissioning scenario, but that dam rehabilitation alone might be of little help in abating flood risk. With adjustments and improvement to the specific methods (according to the circumstances and available data) this framework may be applied to other sites.

Prediction of size-fractionated airborne particle-bound metals using MLR, BP-ANN and SVM analyses.

Size-fractionated heavy metal concentrations were observed in airborne particulate matter (PM) samples collected from 2014 to 2015 (spanning all four seasons) from suburban (Xianlin) and industrial (Pukou) areas in Nanjing, a megacity of southeast China. Rapid prediction models of size-fractionated metals were established based on multiple linear regression (MLR), back propagation artificial neural network (BP-ANN) and support vector machine (SVM) by using meteorological factors and PM concentrations as input parameters. About 38% and 77% of PM2.5 concentrations in Xianlin and Pukou, respectively, were beyond the Chinese National Ambient Air Quality Standard limit of 75xa0μg/m3. Nearly all elements had higher concentrations in industrial areas, and in winter among the four seasons. Anthropogenic elements such as Pb, Zn, Cd and Cu showed larger percentages in the fine fraction (ø≤2.5xa0μm), whereas the crustal elements including Al, Ba, Fe, Ni, Sr and Ti showed larger percentages in the coarse fraction (ø > 2.5xa0μm). SVM showed a higher training correlation coefficient (R), and lower mean absolute error (MAE) as well as lower root mean square error (RMSE), than MLR and BP-ANN for most metals. All the three methods showed better prediction results for Ni, Al, V, Cd and As, whereas relatively poor for Cr and Fe. The daily airborne metal concentrations in 2015 were then predicted by the fully trained SVM models and the results showed the heaviest pollution of airborne heavy metals occurred in December and January, whereas the lightest pollution occurred in June and July.