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This paper investigates the relationship between the income growth and the trend in industrial wastewater discharge in China during the period 1981-2007. For the data encompassing all the provinces over the entire period considered, both an inverted U-shaped EKC and an N-shaped EKC are statistically significant. An analysis dividing provinces into rich and poor groups reveals that the EKC relations are mainly governed by the rich province group. The EKC relations for the poor province group are either not found or are statistically weak. A further analysis based on dividing the data into before and after the year 2000 is in favour of the quadratic EKC model. The results of this study show that the relationships between a given pollutant and income are temporal and spatial specific depending on the driving forces behind. This implies that results derived from one study for certain regions/countries and for a specific time period may not be generalized for other regions/countries and extrapolated to other periods., Consilience, No 4 (2010): Issue Four: 2010

Crop yields exhibit known responses to droughts. However, quantifying crop drought vulnerability is often not straightforward, because components of vulnerability are not defined in a standardized and spatially comparable quantity in most cases and it must be defined on a fine spatial resolution. This study aims to develop a physical crop drought vulnerability index through linking the drought exposure index (DEI) with the crop sensitivity index (CSI) in sub-Saharan Africa. Two different DEIs were compared. One was derived from the cumulative distribution functions fitted to precipitation and the other from the difference between precipitation and potential evapotranspiration. DEIs were calculated for one, three, six, nine, and twelve-month time scales. Similarly, CSI was calculated by fitting a cumulative distribution function to maize yield simulated using the Environmental Policy Integrated Climate model. Using a power function, curves were fitted to CSI and DEI relations resulting in different shapes explaining the severity of vulnerability. The results indicated that the highest correlation was found between CSI and DEI obtained from the difference between precipitation and potential evapotranspiration in one, three, and six-month time scales. Our findings show that southern African countries and some regions of the Sahelian strip are highly vulnerable to drought due to experiencing more water stress, whereas vulnerability in Central African countries pertains to temperature stresses. The proposed methodology provides complementary information on quantifying different degrees of vulnerabilities and the underlying reasons. The methodology can be applied to different regions and spatial scales., Environmental Research Letters, 13 (7), ISSN:1748-9326, ISSN:1748-9318

A large number of local and global databases for soil, land use, crops, and climate are now available from different sources, which often differ, even when addressing the same spatial and temporal resolutions. As the correct database is unknown, their impact on estimating water resource components (WRC) has mostly been ignored. Here, we study the uncertainty stemming from the use of multiple databases and their impacts on WRC estimates such as blue water and soil water for the Karkheh River Basin (KRB) in Iran. Four climate databases and two land use maps were used to build multiple configurations of the KRB model using the soil and water assessment tool (SWAT), which were similarly calibrated against monthly river discharges. We classified the configurations based on their calibration performances and estimated WRC for each one. The results showed significant differences in WRC estimates, even in models of the same class i.e., with similar performance after calibration. We concluded that a non-negligible level of uncertainty stems from the availability of different sources of input data. As the use of any one database among several produces questionable outputs, it is prudent for modelers to pay more attention to the selection of input data., Water, 9 (9), ISSN:2073-4441