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Computable general equilibrium (CGE) models provide valuable insights into economy-wide impacts of anticipated future structural changes in the transportation sector, yet few CGE models offer detailed transportation representations. We use an enhanced Applied Dynamic Analysis of the Global Economy (ADAGE) CGE model to incorporate disaggregated transportation modes and technologies in on-road passenger and freight transportation. We assess the impacts of these inclusions on U.S. transportation patterns, energy consumption and greenhouse gas emissions. Simulating illustrative global oil price cases with and without transportation detail, we find subsector mode disaggregation and technology additions in a CGE model significantly alter the impacts of oil prices on global trade and freight patterns, energy consumption, and GHG emissions. We find that: (1) alternative technologies are essential for capturing transportation sector impacts, (2) electrification may reduce emissions with electricity decarbonization, and (3) higher oil prices may hasten electrification.

The Forestry and Agriculture Sector Optimization Model with Greenhouse Gases (FASOMGHG) has historically relied on regional average costs of land conversion to simulate land use change across cropland, pasture, rangeland, and forestry. This assumption limits the accuracy of the land conversion estimates by not recognizing spatial heterogeneity in land quality and conversion costs. Using data from Nielsen et al. (2014), we obtained the afforestation cost per county, then estimated nonparametric regional marginal cost functions for land converting to forestry. These afforestation costs were then incorporated into FASOMGHG. Three different assumptions for land moving into the forest sector (constant average conversion cost, static rising marginal costs, and dynamic rising marginal cost) were run in order to assess the implications of alternative land conversion cost assumptions on key outcomes, such as projected forest area and cropland use, carbon sequestration, and forest product output.

Maintaining and improving future food and energy security poses key challenges globally, especially in the face of climate change and climate mitigation. a computable general equilibrium (CGE) model -- the Applied Dynamic Analysis of the Global Economy model focusing on agriculture and land use (ADAGE-ALU), is used to examine how the global economy, especially energy, agriculture and land use, responds when facing these challenges. Despite continued increases in land productivity and energy efficiency in future decades, the effects of population and economic growth would dominate, leading to global increases in agricultural production, but also rising food and energy prices as well as continually growing GHG emissions in the BAU scenario. Comparing the climate change scenario with the BAU scenario, there are substantial reductions in global crop production and significant further increases in food prices, but little change in fossil fuel and biofuel production and energy prices, and only mild increases in CO2 emissions due to land-use changes. Relative to the BAU case, the implementation of a carbon tax on emissions other than those from land use change leads to the expansion of global biofuel production and a shift in the mix of crops produced towards those used as biofuels feedstocks, raises food prices, and reduces oil consumption and price slightly. Meanwhile, GHG emissions are slightly reduced as a result of lower oil consumption. In the REDD scenario, some cropland is afforested to store carbon, leading to a moderate rise in food and energy prices and significant GHG emission reductions. When climate change, REDD scenarios are implemented together, we see even higher reductions in global crop production and larger food price increases, along with greater reduction in GHG emissions compared with the CC scenario.

Efforts to satisfy global energy demand and improve food security while simultaneously taking action to mitigate climate change pose many key challenges for the world. In this study, the Applied Dynamic Analysis of the Global Economy (ADAGE), a computable general equilibrium (CGE) model, is applied to examine the impact of oil price on biofuel expansion, and subsequently, on food supply/price, land use change and climate mitigation potential, when both first and second generation biofuel feedstocks are considered. The results indicate despite a continued increase in land productivity and energy efficiency, increases in population and economic growth lead to a global increase in agriculture production, rising food, agriculture, biofuels, and energy prices, and land conversion from the other four land types to cropland in the REF scenario from 2010 to 2040. Oil price plays an important role in biofuel expansion. Globally, higher oil price leads to the expansion of biofuel production, increasing its share in total liquid fuel consumption in the private transportation sector. Consequently, more land is allocated for biofuel production, reducing global agriculture output and increasing agricultural consumption prices. Although emissions from land-use change increase, the overall emissions including fossil fuel emissions decreases. Regions display different patterns on biofuel expansions, land-use change, prices for food/agriculture and energy/biofuels, and GHG emissions.

Global production of biofuels has been expanding with the enduring concerns on climate change and energy security. The U.S. Congress has established a renewable fuel standard 2 (RFS2) rule that mandates annual combined production of 36 billion gallons (bg) biofuels by 2022 (USEPA, 2010). Large scale production of biofuels results in far-reaching intended and unintended consequences on the economy and environment. In this study, a computable general equilibrium model (CGE) - Applied Dynamic Analysis of Global Economy -- ADAGE-Biofuel is developed to examine the global implications of the U.S. RFS2 policy. This model is built upon a dynamic version of ADAGE model (Ross, 2009) by introducing eight crop categories, one livestock and one forestry sectors, seven first generation biofuels, three second generation biofuels and five land categories and explicitly model land-use changes. We find out that despite of continued increase in land productivity and energy efficiency, increase in population and economic growth leads to a global-wide increase in agriculture production, rise in price of food, agriculture, biofuel and energy and land conversion from the other four land types to cropland from 2010 to 2025 when RFS2 is not implemented and biofuel consumption remain at the base year (2010) level in all the regions until 2025 (BAU scenario). The implementation of RFS2 policy would require 36.3 million ha (mha) of land for switchgrass production by 2025, where 34.8 mha from existing cropland, 0.9 mha from pasture, and 0.6 mha from managed forest land. Compared with the BAU scenario, price is projected to increase by around 5~7% for eight crops, 1.6% for livestock and 1.6% for forestry as a result of reducing production. Globally, due to reduction in agriculture exports from U.S. as a result of the RFS2 policy, all other regions would allocate slightly more land for crop and food production, leading to gentle loss of natural grassland and natural forestland, especially in Africa, which would lose 0.5 million ha of natural grassland for crop and livestock production. The RFS2 policy would bring environmental benefits too. The accumulated carbon saving from 2010 to 2025 would be arround 392 mmt c globally with 207 mmt c from fossile fuel and 185 mmt from land. Among it, U.S. alone would contribute 300 mmt c with 208 mmt c from fossile fuel and 92 mmt c from land.

Panel models with random effects are used to estimate how climate influences in-stream surface water supply, municipal water demand, crop yields and irrigation water use. The results are added into TEXRIVERSIM, a state wide economic, hydrological, environmental and inter-basin water transfer (IBTs) investment model, through the objective function and hydrological constraints. A climate change related scenario analysis from the Global Circulation Models (GCMs)--Hadley, Canadian, BCCR and NCAR with SRES scenarios A1B, B1, and A2 indicates that inter-basin water transfers not only greatly relax water scarcity problems for major cities and industrial counties, but also create growth opportunity for Houston. However, while destination basins receive the benefits, source basins will experience dramatic reduction in in-stream flow and water flows to bays and estuaries. Climate change requires accelerated water development with more IBTs proving economically feasible depending on the GCMs and SRES scenarios.

Self protection and altruism are crucial behavioral factors in determining the effectiveness of public policies aimed to improve human health from environmental hazards. This paper examined people’s arsenic mortality risk perception in the drinking water for themselves and their children using the Bayesian learning framework. A two-stage structural model within the random utility framework was developed to model the household’s risk averting behavior with respect to arsenic-related mortality risk. The empirical results indicate that parents engage in a form of mixed altruism. Parents are willing to spend more to make a trade-off between their risk and their children’s risk.

Using state-level data from the Behavioral Risk Factor Surveillance System, we investigate the effects of household food-away-from-home and food-at-home expenditures on overweight rates, obesity rates, and combined rates. Our random effects model estimates suggest that food-away-from-home expenditures are positively related to obesity and combined rates, while food-at-home expenditures are negatively related to obesity and combined rates. However, the magnitudes of these effects, while statistically significant, are relatively small. Both food-at-home and food-away-from-home expenditures do not significantly influence overweight rates.

Climate change will alter ecosystem metabolism and may lead to a redistribution of vegetation and changes in fire regimes in Northern Eurasia over the 21st century. Land management decisions will interact with these climate-driven changes to reshape the region's landscape. Here we present an assessment of the potential consequences of climate change on land use and associated land carbon sink activity for Northern Eurasia in the context of climate-induced vegetation shifts. Under a 'business-as-usual' scenario, climate-induced vegetation shifts allow expansion of areas devoted to food crop production (15%) and pastures (39%) over the 21st century. Under a climate stabilization scenario, climate-induced vegetation shifts permit expansion of areas devoted to cellulosic biofuel production (25%) and pastures (21%), but reduce the expansion of areas devoted to food crop production by 10%. In both climate scenarios, vegetation shifts further reduce the areas devoted to timber production by 6–8% over this same time period. Fire associated with climate-induced vegetation shifts causes the region to become more of a carbon source than if no vegetation shifts occur. Consideration of the interactions between climate-induced vegetation shifts and human activities through a modeling framework has provided clues to how humans may be able to adapt to a changing world and identified the trade-offs, including unintended consequences, associated with proposed climate/energy policies., United States. National Aeronautics and Space Administration (Land-Cover and Land-Use Change program NASA-NNX09A126G)