Our study evaluated the effectiveness of using eight pathways in combination for a complete to transition from fossil fuels to renewable energy by 2050. These pathways included renewable energy development; improving energy efficiency; increasing energy conservation; carbon taxes; more equitable balancing of human wellbeing and per capita energy use; cap and trade systems; carbon capture, utilization, and storage; and nuclear power development. We used the annual ‘British Petroleum statistical review of world energy 2021’ report as our primary database. Globally, fossil fuels, renewable (primarily hydro, wind and solar), nuclear energy accounted for 83%, 12.6%, and 6.3% of the total energy consumption in 2020. To achieve zero fossil fuel use by 2050, we found that renewable energy production will need to be increased by up to 6-fold or 8-fold if energy demand is held constant at, or increased 50% from, the 2020 energy demand level. Constraining 2050 world energy demand to a 25% increase over the 2020 level, improves the probability of achieving independence from fossil fuels. Improvements in energy efficiency need to accelerate beyond the current rate of ~1.5% per year. Aggressive application of energy conservation policies involving land use and taxation could potentially reduce world energy use by 10% or more by 2050. Our meta-analysis shows that the minimum level of per capita energy consumption that would allow 8 billion people to have a ‘Decent Living Standard’ is on average ~70 GJ per capita per year, which is 93% of the 2020 global average. Developed countries in temperate climates with high vehicle-dependency needed ~120 GJ per capita year−1, whereas equatorial countries with low vehicle-dependency needed 30 GJ per capita year−1. Our meta-analyses indicated replacement of fossil fuels with renewable energy by 2050 may be possible but will require aggressive application of all eight pathways, major lifestyle changes in developed countries, and close cooperation among all countries.

Abstract. Thermal and multispectral remote sensing data from low-altitude aircraft can provide high spatial resolution necessary for sub-field ( ≤ 10 m) and plant canopy (≤ 1 m) scale evapotranspiration (ET) monitoring. In this study, highresolution (sub-meter-scale) thermal infrared and multispectral shortwave data from aircraft are used to map ET over vineyards in central California with the two-source energy balance (TSEB) model and with a simple model having operational immediate capabilities called DATTUTDUT (Deriving Atmosphere Turbulent Transport Useful To Dummies Using Temperature). The latter uses contextual information within the image to scale between radiometric land surface temperature (T R ) values representing hydrologic limits of potential ET and a non-evaporative surface. Imagery from 5 days throughout the growing season is used for mapping ET at the sub-field scale. The performance of the two models is evaluated using tower-based measurements of sensible (H ) and latent heat (LE) flux or ET. The comparison indicates that TSEB was able to derive reasonable ET estimates under varying conditions, likely due to the physically based treatment of the energy and the surface temperature partitioning between the soil/cover crop inter-row and vine canopy elements. On the other hand, DATTUTDUT performance was somewhat degraded presumably because the simple scaling scheme does not consider differences in the two sources (vine and inter-row) of heat and temperature contributions or the effect of surface roughness on the efficiency of heat exchange. Maps of the evaporative fraction (EF = LE/(H + LE)) from the two models had similar spatial patterns but different magnitudes in some areas within the fields on certain days. Large EF discrepancies between the models were found on 2 of the 5 days (DOY 162 and 219) when there were significant differences with the tower-based ET measurements, particularly using the DATTUTDUT model. These differences in EF between the models translate to significant variations in daily water use estimates for these 2 days for the vineyards. Model sensitivity analysis demonstrated the high degree of sensitivity of the TSEB model to the accuracy of the T R data, while the DATTUTDUT model was insensitive to systematic errors in T R as is the case with contextual-based models. However, it is shown that the study domain and spatial resolution will significantly influence the ET estimation from the DATTUTDUT model. Future work is planned for developing a hybrid approach that leverages the strengths of both modeling schemes and is simple enough to be used operationally with high-resolution imagery.

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Accelerated climate change is a global challenge that is increasingly putting pressure on the sustainability of livestock production systems that heavily depend on rangeland ecosystems. Rangeland management practices have low potential to sequester greenhouse gases. However, mismanagement of rangelands and their conversion into ex-urban, urban, and industrial landscapes can significantly exacerbate the climate change process. Under conditions of more droughts, heat waves, and other extreme weather events, management of risks (climate, biological, financial, political) will probably be more important to the sustainability of ranching than capability to expand output of livestock products in response to rising demand due to population growth. Replacing traditional domestic livestock with a combination of highly adapted livestock and game animals valued for both hunting and meat may be the best strategy on many arid rangelands. Eventually, traditional ranching could become financially unsound across large areas if climate change is not adequately addressed. Rangeland policy, management, and research will need to be heavily focused on the climate change problem.

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The estimation of sensible heat flux, H, using large aperture scintillometer (LAS) under varying surface heterogeneity conditions was investigated. Surface roughness features characterized by variable topography and vegetation height were represented using data derived from the highly accurate light detection and range (lidar) techniques as well as from traditional vegetation survey and topographic map methods. The study was conducted at the Cibola National Wildlife Refuge, Southern California, over a riparian zone covered with natural vegetation dominated by tamarisk trees interspersed with bare soil in a region characterized by arid to semiarid climatic conditions. Estimates of H were obtained using different representations of surface roughness features derived from both traditional and lidar methods to estimate LAS beam height [z(u)] at each increment u along its path, vegetation height (h c ), displacement height (d), and roughness length (z 0 ) combined with the LAS weighing function, W(u), along the path. The effect of the LAS 3D footprint was examined to account for the contribution from the individual patches in the upwind direction, hence on the estimates of H. The results showed better agreement between LAS and Bowen ratio sensible heat fluxes when lidar-derived surface roughness was used, especially when considering the LAS 3D footprint effects. It was also found that, under certain conditions, the LAS path weighted h c and d obtained using the LAS weighting function W(u) is a good approximation of the 3D weighted footprint values.

In support of Food-Energy-Water Systems (FEWS) analysis to enhance its sustainability for New Mexico (NM), this study evaluated observed trends in beef cattle population in response to environmental and economic changes. The specific goal was to provide an improved understanding of the behavior of NM’s beef cattle production systems relative to precipitation, temperature, rangeland conditions, production of hay and crude oil, and prices of hay and crude oil. Historical data of all variables were available for the 1973–2017 period. The analysis was conducted using generalized autoregressive conditional heteroscedasticity models. The results indicated declining trends in beef cattle population and prices. The most important predictors of beef cattle population variation were hay production, mean annual hay prices, and mean annual temperature, whereas mean annual temperature, cattle feed sold, and crude oil production were the most important predictors for calf population that weigh under 500 lb. Prices of beef cattle showed a strong positive relationship with crude oil production, mean annual hay prices, rangeland conditions, and mean annual precipitation. However, mean annual temperature had a negative relationship with mean annual beef prices. Variation in mean annual calf prices was explained by hay production, mean annual temperature, and crude oil production. This analysis suggested that NM’s beef cattle production systems were affected mainly and directly by mean annual temperature and crude oil production, and to a lesser extent by other factors studied in this research.