The Haze Nightmare Following the Economic Boom in China: Dilemma and Tradeoffs

This study aims to expand on a deeper understanding of the relationship between rapid economic development and ensuing air pollution in China. The database includes the gross domestic product (GDP), the value added of a secondary industry, the per capita GDP (PGDP), greenhouse gases emissions, and PM2.5 concentrations. The results indicate that China's PGDP has continued to rise over the past decade, and the rate of PGDP slowed down from 1980 to 2004 (slope = 5672.81, R-2 = 0.99, p < 0.001) but was significantly lower than that from the year 2004 to 2013 (slope = 46,911.08, R-2 > 0.99, p < 0.001). Unfortunately, we found that total coal consumption, annual steel production, and SO2 emission had been continually growing as the overall economy expands at temporal scale, with the coefficient of determinations greater than 0.98 (p < 0.001). Considering the spatial pattern aspect, we also found a significant relationship between GDP and greenhouse gases. Meanwhile, severe air pollution has negatively impacted the environment and human health, particularly in some highlighted regions. The variation explained by both total SO2 emission and total smoke and dust emission were 33% (p < 0.001) and 24% (p < 0.01) for the rate of total pertussis at temporal scale, respectively. Furthermore, at the spatial scale, pulmonary tuberculosis rates and pertussis mainly occurred in area with serious air pollution (economically developed region). It can be summarized that the extensive mode of economic growth has brought a number of serious environment and human health problems. Thus, a new policy framework has been proposed to meet the goals of maintaining a healthy economy without harming natural environment, which may prove integral, especially when coupled with long-term national strategic development plans

Variability in crop yields associated with climate anomalies in China over the past three decades

We used simple and explicit methods, as well as improved datasets for climate, crop phenology and yields, to address the association between variability in crop yields and climate anomalies in China from 1980 to 2008. We identified the most favourable and unfavourable climate conditions and the optimum temperatures for crop productivity in different regions of China. We found that the simultaneous occurrence of high temperatures, low precipitation and high solar radiation was unfavourable for wheat, maize and soybean productivity in large portions of northern, northwestern and northeastern China; this was because of droughts induced by warming or an increase in solar radiation. These climate anomalies could cause yield losses of up to 50 % for wheat, maize and soybeans in the arid and semi-arid regions of China. High precipitation and low solar radiation were unfavourable for crop productivity throughout southeastern China and could cause yield losses of approximately 20 % for rice and 50 % for wheat and maize. High temperatures were unfavourable for rice productivity in southwestern China because they induced heat stress, which could cause rice yield losses of approximately 20 %. In contrast, high temperatures and low precipitation were favourable for rice productivity in northeastern and eastern China. We found that the optimum temperatures for high yields were crop specific and had an explicit spatial pattern. These findings improve our understanding of the impacts of extreme climate events on agricultural production in different regions of China

SOC storage and potential of grasslands from 2000 to 2012 in central and eastern Inner Mongolia, China

Grassland ecosystem is an important component of the terrestrial carbon cycle system. Clear comprehension of soil organic carbon (SOC) storage and potential of grasslands is very important for the effective management of grassland ecosystems. Grasslands in Inner Mongolia have undergone evident impacts from human activities and natural factors in recent decades. To explore the changes of carbon sequestration capacity of grasslands from 2000 to 2012, we carried out studies on the estimation of SOC storage and potential of grasslands in central and eastern Inner Mongolia, China based on field investigations and MODIS image data. First, we calculated vegetation cover using the dimidiate pixel model based on MODIS-EVI images. Following field investigations of aboveground biomass and plant height, we used a grassland quality evaluation model to get the grassland evaluation index, which is typically used to represent grassland quality. Second, a correlation regression model was established between grassland evaluation index and SOC density. Finally, by this regression model, we calculated the SOC storage and potential of the studied grasslands. Results indicated that SOC storage increased with fluctuations in the study area, and the annual changes varied among different sub-regions. The SOC storage of grasslands in 2012 increased by 0.51x10(12) kg C compared to that in 2000. The average carbon sequestration rate was 0.04x10(12) kg C/a. The slope of the values of SOC storage showed that SOC storage exhibited an overall increase since 2000, particularly for the grasslands of Hulun Buir city and Xilin Gol League, where the typical grassland type was mainly distributed. Taking the SOC storage under the best grassland quality between 2000 and 2012 as a reference, this study predicted that the SOC potential of grasslands in central and eastern Inner Mongolia in 2012 is 1.38x10(12) kg C. This study will contribute to researches on related methods and fundamental database, as well as provide a reference for the protection of grassland ecosystems and the formulation of local policies on sustainable grassland development

Unchanged carbon balance driven by equivalent responses of production and respiration to climate change in a mixed-grass prairie

Responses of grassland carbon (C) cycling to climate change and land use remain a major uncertainty in model prediction of future climate. To explore the impacts of global change on ecosystem C fluxes and the consequent changes in C storage, we have conducted a field experiment with warming (+3 degrees C), altered precipitation (doubled and halved), and annual clipping at the end of growing seasons in a mixed-grass prairie in Oklahoma, USA, from 2009 to 2013. Results showed that although ecosystem respiration (ER) and gross primary production (GPP) negatively responded to warming, net ecosystem exchange of CO2 (NEE) did not significantly change under warming. Doubled precipitation stimulated and halved precipitation suppressed ER and GPP equivalently, with the net outcome being unchanged in NEE. These results indicate that warming and altered precipitation do not necessarily have profound impacts on ecosystem C storage. In addition, we found that clipping enhanced NEE due to a stronger positive response of GPP compared to ER, indicating that clipping could potentially be an effective land practice that could increase C storage. No significant interactions between warming, altered precipitation, and clipping were observed. Meanwhile, we found that belowground net primary production (BNPP) in general was sensitive to climate change and land use though no significant changes were found in NPP across treatments. Moreover, negative correlations of the ER/GPP ratio with soil temperature and moisture did not differ across treatments, highlighting the roles of abiotic factors in mediating ecosystem C fluxes in this grassland. Importantly, our results suggest that belowground C cycling (e.g., BNPP) could respond to climate change with no alterations in ecosystem C storage in the same period

Assessing changes in wind erosion climatic erosivity in China's dryland region during 1961-2012

China's dryland region has serious wind erosion problem and is sensitive to climate change due to its fragile ecological condition. Wind erosion climatic erosivity is a measure of climatic factors influencing wind erosion, therefore, evaluation of its intensity and response to recent climate changes can contribute to the understanding of climate change effect on wind erosion risk. Using the FAO equation, GIS and statistical analysis tools, this study quantified the climatic erosivity, analyzed its spatiotemporal variations, and detected the trend and sensitivity to climate factors during 1961-2012. The results indicate that mean annual climatic erosivity was 2-166 at 292 stations and 237-471 at 6 stations, with the spatial distribution highly in accordance with wind speed ( R-2 = 0.94). The climatic erosivity varied greatly over time with the annual variation ( CV) of 14.7%-108.9% and monthly variation ( concentration degree) of 0.10-0.71 in the region. Meanwhile, annual erosivity showed a significant downward trend at an annual decreasing rate mostly above 1.0%. This significantly decreasing trend was mainly attributed to the obvious decline of wind speed during the period. The results suggest that the recent climate changes were highly possible to induce a decrease of wind erosion risk in China's dryland region

Discussion on the Choice of Decomposition Level for Wavelet Based Hydrological Time Series Modeling

The combination of wavelet analysis methods with data-driven models is a prevalent approach to conducting hydrological time series forecasting, but the results are affected by the accuracy of the wavelet decomposition of the series. The choice of decomposition level is one of the key factors for the wavelet decomposition. In this paper, the data of daily precipitation and streamflow time series measured in the upper reach of the Heihe River Basin in Northwest China were used as an example, and the influence of the decomposition level on wavelet-based hydrological time series forecasting was investigated. The true components of the precipitation series were identified, and the modeling results using 10 decomposition levels and two decomposition types were compared. The results affirmed that the wavelet-based modeling performance is sensitive to the choice of decomposition level, which is determined by the time series analyzed, but has no relation with the decomposition type used. The essence of the choice of decomposition level is to reveal the complex variability of hydrological time series under multi-temporal scales, and first knowing the true components of series could guide the choice of decomposition level. Through this study, the relationship among original series' characteristics, the choice of decomposition level, and the accuracy of wavelet-based hydrological time series forecasting can be more clearly understood, and it can be an improvement for wavelet-based data-driven modeling

Mapping soil organic matter concentration at different scales using a mixed geographically weighted regression method

The present regression models in digital soil mapping usually assume that relationships between soil properties and environmental variables are always fixed (as in MLR) or varying (as in GWR) in geographical space. In reality, some of the environmental variables may be fixed in affecting soil property variation and some are local varying. In this study, a mixed geographically weighted regression (MGWR) method which can deal with fixed and varying spatial relationships between a target variable and its environmental variables were proposed and used to predict topsoil soil organic matter (SOM) concentration in two study areas (Heshan, Heilongjiang province and Xuancheng, Anhui province, China) at two scales. Three groups of sample sets were created based on the total samples in the study areas to evaluate the robustness and stability of the model. Multiple linear regression (MLR), geographically weighted regression (GWR), GWR-kriging (GWRK), local regression-kriging (LRK), kriging with an external drift (KED), and ordinary kriging (OK) were used for comparison with MGWR. The validation results showed that the use of MGWR reduced the RMSE of GWR by 10.5% and 7.6% on average, reduced the RMSE of MLR by 12.8% and 9.9% on average for Heshan and Xuancheng study areas respectively. MGWR also showed a good competitiveness when compared with GWRK, LRK, ICED and OK In Heshan study area, the influence of flow length, relative position index, foot slope and distance to the nearest drainage were constant, whereas the elevation, topographic wetness index and valley index showed different influence in different regions. In Xuancheng study area, the fixed environmental variables were profile curvature, topographic wetness index and slope, whereas the varying environmental variables were precipitation, temperature, elevation, and limestone. The results indicate that the accuracy of predictions can be improved by adaptive coefficient according to the variation of environmental variables as implemented in MGWR compared with others considering only the local or global relationships. It was concluded that mixed geographically weighted regression model could be a potential method for digital soil mapping. (C) 2016 Elsevier B.V. All rights reserved