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Jiao X.-G.,Heilongjiang University | Gao C.-S.,Chinese Academy of Sciences | Lu G.-H.,Shenyang Institute of Atmospheric Environment | Lu G.-H.,CAS Shenyang Institute of Applied Ecology | Sui Y.-Y.,Chinese Academy of Sciences
Agricultural Sciences in China | Year: 2011

Human activities have altered weather patterns by causing an increase in greenhouse gas. The effects of climate change have been studied, including effects on some ecosystems throughout the world. There are many studies on changes in the soil due to climate change, but much of them did not extend their research to soil enzyme that integrates information on soil microbial status and soil physical-chemical conditions. Meanwhile, there are lots of experimental fields established to study effects of long-term fertilization on soil enzyme activities, but many did not compare the difference of soil enzyme activities and did not analyze the effect of climatic factors on soil enzyme activities with long-term fertilization under different hydrothermal conditions. In this study, we compared soil enzyme activities of three long-fertilization stations which had different hydrothermal conditions in Northeast China, and analyzed the relationship of hydrothermal condition, soil chemical properties with soil enzyme activities. Hydrothermal conditions (annual temperature and total rainfall) decreased in order of Gongzhuling (Jilin Province, China) > Harbin (Heilongjiang Province, China) > Heihe (Heilongjiang Province, China) over the course of the long-term fertilization experiment. Sunshine hours showed the longest in Gongzhuling, the second in Heihe, and the last in Harbin. However, the order of soil enzymes was not in agreement with hydrothermal conditions. Overall, the order of soil enzymes for the same treatment among three stations was consistent in 2008 with in 2009. Correlation analysis demonstrated that different soil enzymes achieved the different affected levels by climatic factors under different fertilization treatments. Urease activity showed a significant relationship with sunshine hours in no fertilizer (CK) treatment (R=-0.91, P<0.01) and relative humidity in mineral fertilizers plus manure (MNPK) treatment (R=0.82, P<0.05). Phosphatase activity exhibited a negative correlation with annual mean temperature, annual mean maximum temperature and annual mean minimum temperature, and their correlation coefficients were separately -0.83, -0.79, and -0.83 at P<0.05 in CK treatment. Invertase activity was highly and positively correlated with sunshine hours in CK treatment (R=0.94, P<0.01). Catalase activity showed significant negative correlations with minimum relative humidity in CK treatment (R=-0.81, P<0.05), and positive correlations with sunshine hours in M treatment (R=0.83, P<0.05). There were no climatic factors which strongly affected on dehydrogenase in all treatments. Soil enzyme activities were closely related to the soil chemical properties. Soil urease activity was positively correlated with available P (P<0.05). With exception of correlation between invertase and total P at P<0.05, phosphase, invertase, catalase, and dehydrogenase showed significant positive correlations with soil chemical properties (P<0.01). It was a comprehensive process that biologic and abiotic factors were effect on soil enzyme activities under different fertilization treatments. To sum up, the variation of hydrothermal conditions in different climate zones and soil chemical properties affect integrally metabolic activity and metabolic finger print of microbial communities in black soil. © 2011 Chinese Academy of Agricultural Sciences. Source


Chen R.,Fudan University | Li Y.,Chinese Academy of Meteorological Sciences | Ma Y.,Shenyang Institute of Atmospheric Environment | Pan G.,U.S. Center for Disease Control and Prevention | And 4 more authors.
Science of the Total Environment | Year: 2011

Evidence concerning the health risks of coarse particles (PM 10-2.5) is limited. There have been no multi-city epidemiologic studies of PM 10-2.5 in developing Asian countries. We examine the short-term association between PM 10-2.5 and daily mortality in three Chinese cities: Beijing, Shanghai, and Shenyang. PM 10-2.5 concentrations were estimated by subtracting PM 2.5 from PM 10 measurements. Data were analyzed using the over-dispersed generalized linear Poisson models. The average daily concentrations of PM 10-2.5 were 101μg/m 3 for Beijing (2007-2008), 50μg/m 3 for Shanghai (2004-2008), and 49μg/m 3 for Shenyang (2006-2008). In the single-pollutant models, the three-city combined analysis showed significant associations between PM 10-2.5 and daily mortality from both total non-accidental causes and from cardiopulmonary diseases. A 10-μg/m 3 increase in 1-day lagged PM 10-2.5 was associated with a 0.25% (95% CI: 0.08 to 0.42) increase in total mortality, 0.25% (95% CI: 0.10 to 0.40) increase in cardiovascular mortality, and 0.48% (95% CI: 0.20 to 0.76) increase in respiratory mortality. However, these associations became statistically insignificant after adjustment for PM 2.5. PM 2.5 was significantly associated with mortality both before and after adjustment for PM 10-2.5. In conclusion, there were no statistically significant associations between PM 10-2.5 and daily mortality after adjustment for PM 2.5 in the three Chinese cities. © 2011 Elsevier B.V. Source


Ma Y.,Shenyang Institute of Atmospheric Environment | Chen R.,Fudan University | Pan G.,U.S. Center for Disease Control and Prevention | Xu X.,University of Florida | And 3 more authors.
Science of the Total Environment | Year: 2011

Fine particulatematter (PM2.5) is not a criteria pollutant in China, and few studies were conducted in the country to investigate the health impact of PM2.5. In this study,we did a time-stratified case-crossover analysis to examine the association between PM2.5 and daily mortality in Shenyang, an industrial center in northeast China. Daily mortality, air pollution andweather data from August 1, 2006 to December 31, 2008 in Shenyangwere collected. Atime-stratified case-crossover approachwas used to estimate the association of PM2.5 with both total and cause-specific mortality. Controls were selected as matched days of the week in the same month. Potential effect modifiers, such as age, gender, and season,were also examined.Wefound significant associations between PM2.5 and daily mortality in Shenyang. A 10 μg/m3 increment in the 2-day moving average (lag 01) concentrations of PM2.5 corresponded to 0.49% (95% CI: 0.19%, 0.79%), 0.53% (95% CI: 0.09%, 0.97%), and 0.97% (95% CI: 0.01%, 1.94%) increase of total, cardiovascular, and respiratory mortality, respectively. The associations appeared to be stronger in older people (aged≥75 years), in females and during the warm season. To our knowledge, this is the longest PM2.5 health study in time duration in China. Our findings provide newinformation on the adverse health effects of PM2.5, and may have implications for environmental policy making and standard setting in China. © 2011 Elsevier B.V. All rights reserved. Source


Zhang H.,Nanjing University of Information Science and Technology | Zhang H.,CAS Beijing Institute of Geographic Sciences and Nature Resources Research | Shen S.,Nanjing University of Information Science and Technology | Wen X.,CAS Beijing Institute of Geographic Sciences and Nature Resources Research | And 2 more authors.
Shengtai Xuebao/ Acta Ecologica Sinica | Year: 2012

The eddy covariance technique is a micrometeorological method to directly measure the exchanges of carbon, water and energy between the vegetation and atmosphere. The spatial resolution of meteorological observation of fluxes can expand from tens of meters to kilometers. The eddy covariance method is most accurate when the contributing area of the fluxes is topographically flat, and vegetation extends uniformly within the footprint area. Currently there are more than 100 eddy covariance flux observation sites in China. Most of them are established in non-ideal conditions such as forest, undulating surface, patchy canopy area. Therefore, it is important to accurately interpret the ecological representativeness of flux data by evaluation of the spatial representativeness of its footprint in China. This paper reviews basic theories of the footprint, along with progress and applications about footprint functions. It discusses the research focus and difficulties when considering the development of footprint. The footprint of a measurement point is the influence of the properties of the upwind source area weighted by the footprint function. The major effects on the dimensions of the flux footprint are measurement height, surface roughness length, and atmospheric stability. Increase in measurement height, decrease in surface roughness, and change in atmospheric stability from unstable to stable would enlarge the footprint size and move the peak contribution away from the instrument point. The opposite is also true. Footprint functions can be classified into four categories: Analytical model, Lagrangian stochastic model, Large eddy simulation, and Closure model. The footprint result can be applied to experimental design and to evaluate the quality of CO2 flux data, the variation of CO2 flux in urban areas, surface energy balance closure and gross primary productivity of landscape scales or regional scales combined with remote sensing. The latest research shows that there is a negative footprint zone in the convective boundary layer and that the location of the footprint peak is closer to the tower for convergent surface flow than for horizontally homogeneous flow. This is reversed for divergent surface flow. Atmospheric advection and non-Gaussian diffusion should be taken into account when building footprint functions. It is necessary for footprint functions within forested areas to consider spatial heterogeneity, clumpiness of vegetation, and instationarity of canopy layer turbulence. Analogical experiments should be implemented in complex terrain, based on the tracer release experiment in ideal conditions. Source


Meng X.,Fudan University | Ma Y.,Shenyang Institute of Atmospheric Environment | Chen R.,Fudan University | Zhou Z.,Fudan University | And 2 more authors.
Environmental Health Perspectives | Year: 2013

Background: Associations between airborne particles and health outcomes have been documented worldwide; however, there is limited information regarding health effects associated with different particle sizes. Objectives: We explored the association between size-fractionated particle number concentrations (PNCs) and daily mortality in Shenyang, China. Methods: We collected daily data on cause-specific mortality and PNCs for particles measuring 0.25-10 μm in diameter between 1 December 2006 and 30 November 2008. We used quasi-Poisson regression generalized additive models to estimate associations between PNCs and mortality, and we used natural spline smoothing functions to adjust for time-varying covariates and long-term and seasonal trends. Results: Mean numbers of daily deaths were 67, 32, and 7 for all natural causes, cardiovascular diseases, and respiratory diseases, respectively. Interquartile range (IQR) increases in PNCs for particles measuring 0.25-0.50 μm were significantly associated with total and cardiovascular mortality, but not respiratory mortality. Effect estimates were larger for PNCs during the warm season than the cool season, and increased with decreasing particle size. IQR increases in PNCs of 0.25-0.28 μm, 0.35-0.40 μm, and 0.45-0.50 μm particles were associated with 2.41% (95% CI: 1.23, 3.58%), 1.31% (95% CI: 0.52, 2.09%), and 0.45% (95% CI: 0.04, 0.87%) higher total mortality, respectively. Associations were generally stable after adjustment for mass concentrations of ambient particles and gaseous pollutants. Conclusions: Our findings suggest that particles < 0.5 μm in diameter may be most responsible for adverse health effects of particulate air pollution and that adverse health effects may increase with decreasing particle size. Source

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