JP

Abstract: Agricultural soils play a dual role in regulating the Earth's climate by releasing or sequestering carbon dioxide (CO2) in soil organic carbon (SOC) and emitting non-CO2 greenhouse gases (GHGs) such as nitrous oxide (N2O) and methane (CH4). To understand how agricultural soils can play a role in climate solutions requires a comprehensive assessment of net soil GHG balance (i.e., sum of SOC-sequestered CO2 and non-CO2 GHG emissions) and the underlying controls. Herein, we used a model-data integration approach to understand and quantify how natural and anthropogenic factors have affected the magnitude and spatiotemporal variations of the net soil GHG balance in U.S. croplands during 1960–2018. Specifically, we used the dynamic land ecosystem model for regional simulations and used field observations of SOC sequestration rates and N2O and CH4 emissions to calibrate, validate, and corroborate model simulations.

Results show that U.S. agricultural soils sequestered 13.2 ± 1.16 Tg CO2-C year−1 in SOC (at a depth of 3.5 m) during 1960–2018 and emitted 0.39 ± 0.02 Tg N2O-N year−1 and 0.21 ± 0.01 Tg CH4-C year−1, respectively. Based on the GWP100 metric (global warming potential on a 100-year time horizon), the estimated national net GHG emission rate from agricultural soils was 122.3 ± 11.46 Tg CO₂-eq year−¹, with the largest contribution from N₂O emissions. The sequestered SOC offset ~28% of the climate-warming effects resulting from non-CO₂ GHG emissions, and this off- setting effect increased over time. Increased nitrogen fertilizer use was the dominant factor contributing to the increase in net GHG emissions during 1960–2018, explaining ~47% of total changes. In contrast, reduced cropland area, the adoption of agricultural conservation practices (e.g., reduced tillage), and rising atmospheric CO₂ levels attenuated net GHG emissions from U.S. croplands.

Improving management practices to mitigate N₂O emissions represents the biggest opportunity for achieving net-zero emissions in U.S. croplands. Our study highlights the importance of concurrently quantifying SOC-sequestered CO₂ and non-CO₂ GHG emissions for developing effective agricultural climate change mitigation measures.

Abstract: The open-source fully-automated Surface Energy Balance Algorithm for Land-Improved (SEBALI) Google Earth Engine (SEBALIGEE) estimates 30-m actual evapotranspiration (ET) at a monthly rate, a much needed parameter in many hydrological and agricultural applications. An improved version of the basin-based SEBALIGEE v1 is proposed in this paper.

The improvement of SEBALIGEE v1, named v2, focuses primarily on adding advanced machine learning approaches which have enabled us to implement SEBALIGEE over any scale application and enhance its performance. More particularly, an evaluation of the monthly ET estimated from the new algorithm across several fluxnet sites in the US, China, Italy, Belgium, Germany, and France, yielded a Mean Absolute Error (MAE) of 12.22 mm/month versus 14.54 mm/month in the original SEBALIGEE v1. Furthermore, we used the new any-scale capability to implement SEBALIGEE v2 over the contiguous United States (CONUS) while emphasizing on the three main crops, including corn, soybeans and winter wheat.

Our analysis indicated that all three crops presented similar ET seasonal cycles with peaks occurring in late spring to the summer (May-Aug) and between October and January, corresponding well to the key stages of crop life cycle. Moreover, corn and soybeans exhibited similar magnitudes of ET (36 ~ 168 mm/month) and higher than winter wheat (33 ~ 122 mm/month), with large standard deviations were observed in the ET estimates of all the crops. On interannual comparisons, the corn and soybeans ET and aKc showed higher values than winter wheat, with the highest and lowest years identified and discussed. Following an exploratory analysis against some of the most common interfering variables such as air temperature, dewpoint temperature, surface net solar radiation, wind speed, SPEI drought index calculated on 14 days and 30-days, it was noted that the surface net solar radiation had the most influencing factor on ET in corn and soybeans plantations with R2 values of ~0.72. The SPEI-30 stands out for winter wheat, showing a water scarcity tolerance up to a month in most of its developing stages. Different management practices are then recommended in each of these two crops’ categories (corn and soybeans vs. winter wheat).

 

Abstract: With companies, states, and countries targeting net-zero emissions around midcentury, there are questions about how these targets alter household welfare and finances, including distributional effects across income groups. This paper examines the distributional dimensions of technology transitions and net-zero policies with a focus on welfare impacts across household incomes. The analysis uses a model intercomparison with a range of energy-economy models using harmonized policy scenarios reaching economy-wide, net-zero CO2 emissions across the United States in 2050. We employ a novel linking approach that connects output from detailed energy system models with survey microdata on energy expenditures across income classes to provide distributional analysis of net-zero policies.

Although there are differences in model structure and input assumptions, we find broad agreement in qualitative trends in policy incidence and energy burdens across income groups. Models generally agree that direct energy expenditures for many households will likely decline over time with reference and net-zero policies. However, there is variation in the extent of changes relative to current levels, energy burdens relative to reference levels, and electricity expenditures. Policy design, primarily how climate policy revenues are used, has first-order impacts on distributional outcomes. Net-zero policy costs, in both absolute and relative terms, are unevenly distributed across households, and relative increases in energy expenditures are higher for lowest-income households. However, we also find that recycled revenues from climate policies have countervailing effects when rebated on a per-capita basis, offsetting higher energy burdens and potentially even leading to net progressive outcomes. Model results also show carbon Laffer curves, where revenues from net-zero policies increase but then decline with higher stringencies, which can diminish the progressive effects of climate policies. We also illustrate how using annual income deciles for distributional analysis instead of expenditure deciles can overstate the progressivity of emissions policies by overweighting revenue impacts on the lowest-income deciles.

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