Agricultural production is the largest contributor of nitrogen and phosphorus pollution in lakes, rivers, and streams in the United States. The effectiveness of agricultural conservation programs that encourage farmers to adopt certain practices to reduce this water pollution, once implemented, is an open question. We develop a unique data set combining the spatial structure of the watershed river system, the timing of federal conservation contracts, water quality measurements, land use, land cover, and weather data to study the effect of conservation contracts on nitrogen and phosphorus levels in the Wabash River watershed, which drains Indiana and Illinois. We develop econometric models that generate a causal understanding of the effectiveness of these conservation contracts for reducing nitrogen and phosphorus levels in the surface water system. We find that at current treatment levels, these programs reduce surface water pollution only during relatively dry periods. The efficacy of these programs in the study area is highly sensitive to precipitation to the extent that average precipitation can eliminate the nutrient loss reduction benefits of conservation program installations at current treatment levels. Therefore, we find weak evidence to support ambient downstream water quality improvements resulting from program investment levels to date. We anticipate this work will motivate further inquiry into the manner in which these conservation programs have or have not been effective.

We propose spatial difference-in-differences (DID) models that are able to incorporate treatment effect spillovers through modeling spatial interactions in the response and spatial correlations in treatment status among individuals. We first explore the ways in which combinations of spatial interaction and spatial correlation bias the conventional DID estimator, and then we develop spatial DID models, estimators, and specification tests that allow for a flexible order of local spatial structures. We consider both simultaneous and dynamic treatment. The local spatial DID models with a flexible order of spatial structure allow for different types of heterogeneity in the treatment effects. Monte Carlo simulations support our discussions of the bias in the conventional DID model under spatial interaction and correlation, and demonstrate the finite sample performance of our proposed models, estimators, and tests.

With deteriorating air pollution and climate change, generating power with cleaner technologies to meet energy demand of economic development has become a crucial policy consideration globally. Biomass power generation, despite being cleaner than coal power generation, still emits certain air pollutants that can impact ambient air quality. On the other hand, biomass power plants might mitigate air pollution by reducing open-field crop burning. With this counteracting in play, it is unclear which effect is dominant and how biomass power generation affects ambient air quality eventually. We build a unique spatially high-resolution dataset for 20-km-radius circles, considering both regions with biomass power plants and those without, to explore the impacts of biomass power generation on air quality in nearby regions. By applying panel and canonical difference-in-differences models with various model specifications and estimation strategies, we demonstrate that biomass power generation in China significantly reduces ambient annual concentrations of PM2.5, PM10, SO2, and CO. The impacts on NO2 reduction could only be observed in summer, when open-field burnings decreased substantially. The impacts on PM2.5 could be observed in both summer and fall. No seasonal pattern is observed for the reductions in PM10, SO2, and CO concentrations.

New energy vehicles (NEVs) have emerged as a promising solution to reduce carbon emissions and address environmental concerns in the transportation sector. In order to effectively accelerate market acceptance, it is crucial to prioritize the heterogeneity of consumer preferences for NEV attributes. This study employs the multinomial logit model (MNL) and latent class model (LCM) to investigate both observed and unobserved preference heterogeneity based on stated preferences obtained from a discrete choice experiment conducted across seven cities in China. Results from the MNL model indicate that all attributes significantly influence alternative utility. In particular, there are differences in the willingness to pay (WTP) for attributes of battery electric vehicles (BEVs) and plug-in hybrid electric vehicles (PHEVs). Analysis of MNL subgroups reveals observed heterogeneity in WTP for identical attributes among consumers from regions with different latitudes and markets with different NEV penetration rates. Furthermore, the LCM model uncovers unobserved preference heterogeneity by classifying respondents into four distinct classes and identifies specific socioeconomic variables associated with each class. The recognition of heterogeneous WTP for NEV attributes across vehicle types, regions, markets, and consumer classes provides important implications for formulating targeted policies that promote the sustainable development of the NEV industry.

As electricity from coal declines, co-firing coal plants with biomass has been proposed to extend coal unit life, increase production, and reduce carbon emissions. Previous studies reach conflicting conclusions on whether coal biomass co-firing would result in a net increase or decrease in carbon emissions. We explore whether biomass co-firing would decrease emissions using a novel framework that includes two critical features of electricity markets: strategic adoption decisions by firms and intertemporal constraints on power plant operations. We apply this framework to a case study based on the Midwestern U.S. electricity market and show that profit maximizing firms will retrofit mid-efficiency coal units, rather than the most or least efficient units. We demonstrate that, contrary to expectations, this strategy leads to a net increase in system-wide carbon emissions under high carbon prices because of the other generators displaced by co-firing units.

This paper analyzes the abatement costs associated with greenhouse gas reductions achievable by co-firing corn stover with coal at 71 coal-fired, utility-scale power plants in the Midwestern USA. The cost per metric ton of abated CO2-equivalents is estimated using facility-specific supply functions for corn stover assuming best carbon management practices, county-level corn production data, a life cycle inventory tool for calculating biomass feedstock emissions, and simplified cost models for coal and co-fired capital and operating costs. Abatement costs vary substantially across the power plants modeled: mean costs were $123.71 per metric ton CO2-eq at a 5% co-firing rate, $64.43 for 10% co-firing, and $49.20 for 20% co-firing, with coefficients of variation of 26%, 38%, and 48%, respectively. Lower abatement costs are primarily associated with high co-firing rates and high estimated unit costs for coal. The local corn yield and collection radius do not appear to have a substantial impact on estimated abatement costs. This advances our understanding of the abatement costs associated with co-firing biomass and coal, and the drivers of variability in abatement costs, by modeling feasible production scenarios using actual power plant and corn production data instead of idealized scenarios.

As scientists seek to better understand the linkages between energy, water, and land systems, they confront a critical question of scale for their analysis. Many studies exploring this nexus restrict themselves to a small area in order to capture fine-scale processes, whereas other studies focus on interactions between energy, water, and land over broader domains but apply coarse resolution methods. Detailed studies of a narrow domain can be misleading if the policy intervention considered is broad-based and has impacts on energy, land, and agricultural markets. Regional studies with aggregate low-resolution representations may miss critical feedbacks driven by the dynamic interactions between subsystems. This study applies a novel, gridded energy-land-water modeling system to analyze the local environmental impacts of biomass cofiring of coal power plants across the upper MISO region. We use this framework to examine the impacts of a hypothetical biomass cofiring technology mandate of coal-fired power plants using corn residues. We find that this scenario has a significant impact on land allocation, fertilizer applications, and nitrogen leaching. The effects also impact regions not involved in cofiring through agricultural markets. Further, some MISO coal-fired plants would cease generation because the competition for biomass increases the cost of this feedstock and because the higher operating costs of cofiring renders them uncompetitive with other generation sources. These factors are not captured by analyses undertaken at the level of an individual power plant. We also show that a region-wide analysis of this cofiring mandate would have registered only a modest increase in nitrate leaching (just +5% across the upper MISO region). Such aggregate analyses would have obscured the extremely large increases in leaching at particular locations, as much as +60%. Many of these locations are already pollution hotspots. Fine-scale analysis, nested within a broader framework, is necessary to capture these critical environmental interactions within the energy, land, and water nexus.

We estimate the effect of gasoline-electric hybrid vehicle ownership on household annual miles traveled. We focus on two types of rebound effects associated with hybrid adoption. The first is a social status driven rebound effect arising out of the signaling value associated with visually distinct hybrid vehicles. The second is the total rebound effect: in addition to any social status effects, the higher fuel efficiency of gasoline-electric vehicles leads to a lower cost per mile. We recover causal effects using a matching strategy to account for observable and unobservable factors that influence both hybrid adoption and miles traveled. While we do not find evidence of a significant social status rebound effect, we estimate an overall hybrid rebound of about 3 percent of the (average) annual miles traveled. This rebound effect is not sufficient to offset the reduction in fuel consumption associated with the higher fuel efficiency of the hybrid and we find that hybrid adoption reduces fuel consumption by 34-46 percent per year compared to conventional gasoline powered vehicles. (C) 2019 Elsevier B.V. All rights reserved.

Most states in the MISO region have created State Renewable Portfolio Standards that require electric utilities to generate a certain portion of their power from renewable and clean energy sources. Accordingly, power plants need to modify their practices to meet requirement. For coal-fired power plants, biomass co-firing is considered to be a promising and efficient way to enhance the renewable portfolio, but at a lower cost and higher efficiency compared to power plants fully dedicated to biomass (IRENA 2012). Due to the high transportation cost associated with biomass feedstock, the potential for co-firing at a given coal-fired power plant depends on the local availability of biomass. In the MISO region, there are many coal power plants which are candidates for co-firing with biomass. For most of these plants, corn residue is the most available and cost-effective biomass resource. However, if there is a significant shift to co-firing with corn residue, this could have important implications for agriculture in the region, as it will increase the returns to corn production relative to other crops. This, in turn is expected to have important implications for land and water quality, as corn is relative intensive in nitrogen fertilizer use – and in some locations it is an important user of irrigation. Nitrate leaching is, in turn, a significant source of water quality degradation in the region, as well as downstream – as far away as the Gulf of Mexico (Goolsby et al. 1999). The main objective of this study is to explore the potential for biomass co-firing and the associated impacts on land and water resources in the MISO region.

There is a lot of policy emphasis on increasing the environmental sustainability of agricultural production, particularly in the Midwest where production of corn and soybeans is a major contributor of nitrogen and phosphorus pollution in surface water bodies throughout the Midwest and into the Gulf of Mexico. As a result, agricultural conservation programs have been developed as a means of encouraging farmers to adopt various conservation practices aimed at improving the environmental sustainability of agricultural production. In this paper, we develop a unique, spatially explicit dataset including the adoption of conservation practices, water quality, watershed networks, land use, and weather data. With strategically spatially matched dataset, we estimate the effect of these practice adoptions on nitrogen and phosphorus levels within surface water bodies in the Wabash River watershed. Despite a variety of model specifications and robustness checks, we find that these conservation practices have, so far, be unable to effect surface water body quality.

Electricity generation in coal-fired power plants results in one quarter of US GHG emissions and is the single largest sources of GHG emissions in the United States (US EPA GHG Inventory 2014). Co-firing biomass in the existing coal-fired power plants has been considered as an effective and efficient way to reduce emissions (McGlynn et al. 2014); many policies are also implemented or proposed to stimulate biomass co-firing both in the U.S. and in other countries, especially Europe. Due to the high transportation cost associated with biomass feedstock, the potential for co-firing at a given coal-fired power plant depends very much on the local availability of biomass. For large-scale co-firing, a stable supply of biomass is required, and for this, the planting of dedicated energy crops is essential (Evans et al. 2010, IRENA 2013). This, in turn results in land use change, which itself can have undesirable emissions impacts and causes concern in term of food security throughout the world. The main objective of this study is to explore the potential for co-firing and associated land use changes in the United States. Specifically, we investigate: (1) the total potential of co-firing and the associated land use changes in the United States; (2) heterogeneity in the potential for co-firing across different existing power plants and heterogeneity in the induced land use changes in different areas; (3) the co-firing threshold that requires dedicated energy crops involved as feedstock beyond residues from forest and agriculture; and (4) heterogeneity in these thresholds for different power plants in different areas.

Groundwater depletion is a serious problem in Mexico. Several policy alternatives are currently being considered in order to improve the efficiency of irrigation water use so that extraction of groundwater is diminished. An understanding and quantification of different sources of inefficiency in groundwater extraction is critical for policy design. Survey data from a geographically extensive sample of irrigators is used to gauge the importance of common pool problems on input-specific irrigation inefficiency. Results show that mechanisms of electricity cost sharing implemented in many wells have a sizable impact on inefficiency of irrigation application. Moreover, irrigation is very inelastic to its own unitary cost. Therefore, results suggest that policies aimed at eliminating electricity cost-sharing mechanisms would be significantly more effective than electricity price-based policies in reducing irrigation application. Results also show that well sharing does not affect groundwater pumping significantly, suggesting either a limited effect of individual pumping on water level or absence of strategic pumping by farmers sharing the wells.

Input- and output-based economic policies designed to reduce water pollution from fertilizer runoff by adjusting management practices are theoretically justified and well-understood. Yet, in practice, adjustment in fertilizer application or land allocation may be sluggish. We provide practical guidance for policymakers regarding the relative magnitude and speed of adjustment of input- and output-based policies. Through a dynamic dual model of corn production that takes fertilizer as one of several production inputs, we measure the short- and long-term effects of policies that affect the relative prices of inputs and outputs through the short- and long-term price elasticities of fertilizer application, and also the total time required for different policies to affect fertilizer application through the adjustment rates of capital and land. These estimates allow us to compare input- and output-based policies based on their relative cost-effectiveness. Using data from Indiana and Illinois, we find that input-based policies are more cost-effective than their output-based counterparts in achieving a target reduction in fertilizer application. We show that input- and output-based policies yield adjustment in fertilizer application at the same speed, and that most of the adjustment takes place in the short-term.

Groundwater depletion is a serious problem in Mexico. Several policy alternatives are currently being considered in order to improve the efficiency of irrigation water use so that extraction of groundwater is diminished. An understanding and quantification of different sources of inefficiency in groundwater extraction is critical for policy design. Survey data from a geographically extensive sample of irrigators is used to gauge the importance of common pool problems on input-specific irrigation inefficiency. Results show that mechanisms of electricity cost sharing implemented in many wells have a sizable impact on inefficiency of irrigation application. Moreover, irrigation is very inelastic to its own unitary cost. Therefore, results suggest that policies aimed at eliminating electricity cost-sharing mechanisms would be significantly more effective than electricity price-based policies in reducing irrigation application. Results also show that well sharing does not affect groundwater pumping significantly, suggesting either a limited effect of individual pumping on water level or absence of strategic pumping by farmers sharing the wells.

Policies that aim to mitigate water pollution from fertilizer use in agriculture include input-based and output-based policies. Both cost-effectiveness and the speed for policies to take effect are important for policy assessment. In this study, we found that fertilizer price policies cannot decrease fertilizer use significantly due to the insignificant effect of fertilizer price on fertilizer use. Contrarily, the fertilizer use is elastic to output price, and policies that impose tax on corn production or subsidize soybean production or both are able to mitigate water pollution form fertilizer use significantly. Policies that can increase labor supply in planting season may also have strong effect on mitigation of water pollution. The slow adjustment rate of land allocation suggests that policies that affect fertilizer use through motivating farmers’ land allocation adjustment from fertilizer-intensive crop to fertilizer-saving crop may be time costly.

In Mexico, farmers only pay the cost of electricity used to pump groundwater from wells for groundwater consumption and also receive electricity subsidy from government. It causes the fact that farmers consume groundwater under the situation that private marginal cost is lower than social marginal cost. Furthermore, in Mexico, different wells function under different institutional arrangements. Some wells are privately owned while others are shared by multiple farmers. In some shared wells, farmers pay for their own electricity consumption but in other shared wells farmers distribute total electricity cost based on a pre-specified rule. Both the jointly ownership and pre-specified payment rule may cause further distortion of groundwater pumping cost. By estimating the frontier demand function and technical efficiency of groundwater, we calculate the own-price elasticity of groundwater and test the effect of joint ownership and pre-specified electricity payment rule on the groundwater use efficiency. It is found that the groundwater has a negative and large (-0.5) own-price elasticity and that the number of farmers owning one well and the pre-specified payment rules do not affect the efficiency level significantly. The elimination of electricity subsidy may be the most effective policy to alleviate groundwater depletion in Mexico.