Income, Trade and Pollution in Central Asia, Russia and China: An Econometric Analysis

The study performs a panel estimation of the relationship between per capita income, trade, and airborne pollution in the five Central Asian nations, Russia and China between 1992 and 2008. First, this study uses an environmental Kuznets curve hypothesis (EKC)- an inverted-U relationship between the increase in income and the level of environmental degradation - to examine how income and pollution are related. Second, the study uses a gravity model to estimate the effect of a regional trade agreement (Shanghai Cooperation Organization: SCO) on incomes and carbon dioxide emissions in the region. Empirical analysis confirms the existence of the rising portion of the EKC curve in the region - a positive correlation between per capita income growth and carbon dioxide emissions- and that the volume of bilateral trade, and not the existence of a regional trade agreement, contributes to the increasing level of environmental pollution.

Income, Trade and Pollution in Central Asia, Russia and China: An Econometric Analysis

The study performs a panel estimation of the relationship between per capita income, trade, and airborne pollution in the five Central Asian nations, Russia and China between 1992 and 2008. First, this study uses an environmental Kuznets curve hypothesis (EKC)- an inverted-U relationship between the increase in income and the level of environmental degradation - to examine how income and pollution are related. Second, the study uses a gravity model to estimate the effect of a regional trade agreement (Shanghai Cooperation Organization: SCO) on incomes and carbon dioxide emissions in the region. Empirical analysis confirms the existence of the rising portion of the EKC curve in the region - a positive correlation between per capita income growth and carbon dioxide emissions- and that the volume of bilateral trade, and not the existence of a regional trade agreement, contributes to the increasing level of environmental pollution.

Monitoring Stormwater Redistribution Into Low Resistivity Soils Using Noninvasive Geophysical Techniques

Water held in the unsaturated zone is important for agriculture and construction and is replenished by infiltrating rainwater. Monitoring the soil water content of clay soils using ground-penetrating radar (GPR) has not been researched, as clay soils cause attenuation of GPR signal. In this study, GPR common-midpoint soundings (CMPs) are used in the clayey soils of the Miller Run floodplain to monitor changes in the soil water content (SWC) before and after rainfall events. GPR accomplishes this task because increases in water content will increase the dielectric constant of the subsurface material, and decrease the velocity of the GPR wave. Using an empirical relationship between dielectric constant and SWC, the Topp relation, we are able to calculate a SWC from these velocity measurements. Non-invasive electromagnetics, resistivity, and seismic were performed, and from these surveys, the layering at the field site was delineated. EM characterized the horizontal variation of the soil, allowing us to target the most clay rich area. At the CMP location, resistivity indicates the vertical structure of the subsurface consists of a 40 cm thick layer with a resistivity of 100 ohm*m. Between 40 cm and 1.5 m is a layer with a resistivity of 40 ohm*m. The thickness estimates were confirmed with invasive auger and trenching methods away from the CMP location. GPR CMPs were collected relative to a July 2013 and September 2013 storm. The velocity observations from the CMPs had a precision of +/- 0.001 m/ns as assessed by repeat analysis. In the case of both storms, the GPR data showed the expected relationship between the rainstorms and calculated SWC, with the SWC increasing sharply after the rainstorm and decreasing as time passed. We compared these data to auger core samples collected at the same time as the CMPs were taken, and the volumetric analysis of the cores confirmed the trend seen in the GPR, with SWC values between 3 and 5 percent lower than the GPR estimates. Our data shows that we can, with good precision, monitor changes in the SWC of conductive soils in response to rainfall events, despite the attenuation induced by the clay.