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Using satellite remote sensing, we show the distribution, dominant type, and amounts of marine debris off the northeast coast of Japan after the Great East Japan Earthquake on 11 March 2011 and subsequent tsunami. Extensive marine debris was found on March 12, with the maximal amount found on March 13. The debris was found to be mainly wood (possibly lumber wood), with an estimated 1.5 million metric tons in an elongated water area of 6800 km 2 (18 km E-W and 380 km N-S) near parallel to the coast between 36.75°N and 40.25°N. The amount decreased rapidly with time, with scattered debris patches captured in high-resolution satellite images up to April 6. These results provide new insights on the initial distribution of the Japanese Tsunami Marine Debris, which may be used to help find bottom deposition of debris and help refine numerical models to predict the debris trajectory and fate. SYNOPSIS: Marine debris induced by the 2011 Great East Japan Earthquake and Tsunami is found to be mainly composed of wood and possibly lumber wood from constructions, with maximum amount on 13 March 2011 distributed within a narrow band of ∼18 km near parallel to the northeast coast of Japan between 36.75°N and 40.25°N., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 The Authors. Published by Elsevier Ltd.. All rights reserved.)

Background: Achieving a net zero greenhouse gas United States (US) economy is likely to require both deep sectoral mitigation and additional carbon dioxide removals to offset hard-to-abate emissions. Enhancing the terrestrial carbon sink, through practices such as the adoption of no-till and cover cropping agricultural management, could provide a portion of these required offsets. Changing domestic agricultural practices to optimize carbon content, however, might reduce or shift US agricultural commodity outputs and exports, with potential implications on respective global markets and land use patterns. Here, we use an integrated energy-economy-land-climate model to comprehensively assess the global land, trade, and emissions impacts of an adoption of domestic no-till farming and cover cropping practices based on carbon pricing., Results: We find that the adoption of these practices varies depending on which aspects of terrestrial carbon are valued. Valuation of all terrestrial carbon resulted in afforestation at the expense of domestic agricultural production. In contrast, a policy valuing soil carbon in agricultural systems specifically indicates strong adoption of no-till and cover cropping for key crops., Conclusions: We conclude that under targeted terrestrial carbon incentives, adoption of no-till and cover cropping practices in the US could increase the terrestrial carbon sink with limited effects on crop availability for food and fodder markets. Future work should consider integrated assessment modeling of non-CO 2 greenhouse gas impacts, above ground carbon storage changes, and capital and operating cost considerations., (© 2024. Battelle Memorial Institute and Alliance for Sustainable Energy, LLC.)

Some key low-carbon technologies, ranging from wind turbines to electric vehicles, are underpinned by the strong rare-earth-based permanent magnets of the Nd, Pr (Dy)-Fe-Nb type (NdFeB). These NdFeB magnets, which are sensitive to demagnetization with temperature elevation (the Curie point), require the addition of variable amounts of dysprosium (Dy), where an elevation of the Curie point is needed to meet operational conditions. Given that China is the world's largest REE supplier with abundant REE reserves, the impact of an ambitious 1.5 °C climate target on China's Dy supply chain has sparked widespread concern. Here, we explore future trends and innovation strategies associated with the linkage between Dy and NdFeBs under various climate scenarios in China. We find China alone is expected to exhaust the global present Dy reserve within the next 2-3 decades to facilitate the 1.5 °C climate target. By implementing global available innovation strategies, such as material substitution, reduction, and recycling, it is possible to avoid 48%-68% of China's cumulative demand for Dy. Nevertheless, ongoing efforts in REE exploration and production are still required to meet China's growing Dy demand, which will face competition from the United States, European Union, and other countries with ambitious climate targets. Thus, our analysis urges China and those nations to form wider cooperation in REE supply chains as well as in NdFeB innovation for the realization of a global climate-safe future.

Hurricane Katrina (category 5 with maximum wind of 280 km/h when the eye is in the central Gulf of Mexico) made landfall near New Orleans on August 29, 2005, causing millions of cubic meters of disaster debris, severe flooding, and US$125 billion in damage. Yet, despite numerous reports on its environmental and economic impacts, little is known about how much debris has entered the marine environment. Here, using satellite images (MODIS, MERIS, and Landsat), airborne photographs, and imaging spectroscopy, we show the distribution, possible types, and amount of Katrina-induced debris in the northern Gulf of Mexico. Satellite images collected between August 30 and September 19 show elongated image features around the Mississippi River Delta in a region bounded by 92.5°W-87.5°W and 27.8°N-30.25°N. Image spectroscopy and color appearance of these image features indicate that they are likely dominated by driftwood (including construction lumber) and dead plants (e.g., uprooted marsh) and possibly mixed with plastics and other materials. The image sequence shows that if aggregated together to completely cover the water surface, the maximal debris area reached 21.7 km 2 on August 31 to the east of the delta, which drifted to the west following the ocean currents. When measured by area in satellite images, this perhaps represents a historical record of all previously reported floating debris due to natural disasters such as hurricanes, floodings, and tsunamis.

Rapid climate and socioeconomic changes are transforming Arctic human-earth systems. An integral part of these systems is mobility, which encompasses the transport of humans and goods into, out of, and between Arctic regions. Impacts of climate and socioeconomic drivers on Arctic mobility are heterogenous. Methodologies are needed to quantify these impacts in measures that can be linked with broader socioeconomic systems. This article reviews existing methods and organizes them into a conceptual framework to understand trends and gaps in the literature. We found methods quantifying impacts of a range of climate drivers on most transportation modes present in the Arctic, but few methods focused on socioeconomic drivers. In addition, underrepresented were methods explicitly considering adaptive capacity of transportation systems. We provide insight into the data and relationships relevant to understanding impacts of Arctic change on transportation systems, laying a foundation for future work that investigates how these impacts fit into broader human-arth systems., (© 2023. Battelle Memorial Institute and Rowland, under exclusive licence to Royal Swedish Academy of Sciences.)

Understanding the temperature sensitivity (Q 10 ) of soil respiration is critical for benchmarking the potential intensity of regional and global terrestrial soil carbon fluxes-climate feedbacks. Although field observations have demonstrated the strong spatial heterogeneity of Q 10 , a significant knowledge gap still exists regarding to the factors driving spatial and temporal variabilities of Q 10 at regional scales. Therefore, we used a machine learning approach to predict Q 10 from 1994 to 2016 with a spatial resolution of 1 km across China from 515 field observations at 5 cm soil depth using climate, soil and vegetation variables. Predicted Q 10 varied from 1.54 to 4.17, with an area-weighted average of 2.52. There was no significant temporal trend for Q10 (p = 0.32), but annual vegetation production (indicated by normalized difference vegetation index, NDVI) was positively correlated to it (p < 0.01). Spatially, soil organic carbon (SOC) was the most important driving factor in 62 % of the land area across China, and varied greatly, demonstrating soil controls on the spatial pattern of Q 10 . These findings highlighted different environmental controls on the spatial and temporal pattern of soil respiration Q 10 , which should be considered to improve global biogeochemical models used to predict the spatial and temporal patterns of soil carbon fluxes to ongoing climate change., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 Elsevier B.V. All rights reserved.)

As relative rates of sea level rise accelerate in the Mid-Atlantic region of the United States, the frequency of flooding and saltwater intrusion on coastal lands also increases, prompting ecological transformation which can conflict with existing coastal land use such as agriculture. We performed an exploratory study of coastal farmers and woodlot managers in Maryland and Virginia to understand how these producers make land management decisions within the context of sea level rise. Specifically, we used a mixed-methods approach to identify and understand 1) the producer-observed impacts of sea level rise and flooding on coastal lands; 2) the range of actions producers may take in response to sea level rise and flooding; 3) producers' intentions for managing their land in the short- and long-term; 4) producers' motivations for selecting a particular response; and 5) the additional support coastal producers need to successfully adapt to sea level rise. We used the Resist-Accept-Direct framework as an analytical tool to understand how producers' actions and motivations align with 1) prevention or removal of impacts from flooding and saltwater intrusion, 2) accommodation for wetter or saltier conditions as they naturally occur, or 3) facilitation of specific changes toward a new desired outcome. We found that while most producers in our study plan to resist or accept changes over the next five years, over the longer term a majority of participating producers plan to transition land to a use that is compatible with increased saltwater intrusion and flooding. Most producers in our study would prefer to continue farming yet face a lack of effective and/or affordable management options to resist ecological changes. Flexible mechanisms that support producers in resisting sea level rise impacts in the short term, while supporting them in directing the transition of their land to another productive use in the long term, are needed to support coastal farmers as they adapt to a changing climate., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 The Authors. Published by Elsevier Ltd.. All rights reserved.)

Since the early 2000s, sea ice has experienced an increased rate of decline in thickness, extent and age. This new regime, coined the 'New Arctic', is accompanied by a reshuffling of energy flows at the surface. Understanding of the magnitude and nature of this reshuffling and the feedbacks therein remains limited. A novel database is presented that combines satellite observations, model output, and reanalysis data with sea ice parcel drift tracks in a Lagrangian framework. This dataset consists of daily time series of sea ice parcel locations, sea ice and snow conditions, and atmospheric states, including remotely sensed surface energy budget terms. Additionally, flags indicate when sea ice parcels travel within cyclones, recording cyclone intensity and distance from the cyclone center. The quality of the ice parcel database was evaluated by comparison with sea ice mass balance buoys and correlations are high, which highlights the reliability of this database in capturing the seasonal changes and evolution of sea ice. This database has multiple applications for the scientific community; it can be used to study the processes that influence individual sea ice parcel time series, or to explore generalized summary statistics and trends across the Arctic., (© 2023. This is a U.S. Government work and not under copyright protection in the US; foreign copyright protection may apply.)

The terrestrial carbon cycle is a major source of uncertainty in climate projections. Its dominant fluxes, gross primary productivity (GPP), and respiration (in particular soil respiration, R S ), are typically estimated from independent satellite-driven models and upscaled in situ measurements, respectively. We combine carbon-cycle flux estimates and partitioning coefficients to show that historical estimates of global GPP and R S are irreconcilable. When we estimate GPP based on R S measurements and some assumptions about R S :GPP ratios, we found the resulted global GPP values (bootstrap mean [Formula: see text] Pg C yr -1 ) are significantly higher than most GPP estimates reported in the literature ([Formula: see text] Pg C yr -1 ). Similarly, historical GPP estimates imply a soil respiration flux (Rs GPP , bootstrap mean of [Formula: see text] Pg C yr -1 ) statistically inconsistent with most published R S values ([Formula: see text] Pg C yr -1 ), although recent, higher, GPP estimates are narrowing this gap. Furthermore, global R S :GPP ratios are inconsistent with spatial averages of this ratio calculated from individual sites as well as CMIP6 model results. This discrepancy has implications for our understanding of carbon turnover times and the terrestrial sensitivity to climate change. Future efforts should reconcile the discrepancies associated with calculations for GPP and Rs to improve estimates of the global carbon budget., (© 2022. The Author(s).)

We analyze airborne measurements of atmospheric CO concentration from 70 flights conducted over six years (2015-2020) using an inverse model to quantify the CO emissions from the Washington, DC, and Baltimore metropolitan areas. We found that CO emissions have been declining in the area at a rate of ≈-4.5 % a -1 since 2015 or ≈-3.1 % a -1 since 2016. In addition, we found that CO emissions show a "Sunday" effect, with emissions being lower, on average, than for the rest of the week and that the seasonal cycle is no larger than 16 %. Our results also show that the trend derived from the NEI agrees well with the observed trend, but that NEI daytime-adjusted emissions are ≈50 % larger than our estimated emissions. In 2020, measurements collected during the shutdown in activity related to the COVID-19 pandemic indicate a significant drop in CO emissions of 16 % relative to the expected emissions trend from the previous years, or 23 % relative to the mean of 2016 to February 2020. Our results also indicate a larger reduction in April than in May. Last, we show that this reduction in CO emissions was driven mainly by a reduction in traffic.

Background: Over 3 million people die every year from diseases caused by exposure to outdoor PM 2·5 air pollution, and more than a quarter of these premature deaths occur in China. In addition to clean-air policies that target pollution emissions, climate policies aimed at reducing fossil-fuel CO 2 emissions (eg, to avoid 1·5°C of warming) might also greatly improve air quality and public health. However, no comprehensive accounting of public health outcomes has been done under different energy pathways and local clean-air management decisions in China. We aimed to develop an integrated method for quantifying the health co-benefits from different climate, energy, and clean-air policy scenarios and to assess the relationship between climate and clean-air policies and future health burdens in China, where an ageing population will further exacerbate the effects of air pollution., Methods: For this modelling study, we used a China-focused integrated assessment model and a dynamic emission projection model to project future Chinese air quality in scenarios spanning a range of global climate targets (1·5°C, 2°C, national determined contributions [NDC], unambitious, baseline, and 4·5°C) and national clean-air actions (termed 2015-pollution, current-pollution, and ambitious-pollution). We then evaluated the health effects of PM 2·5 air pollution in the scenario matrix using the air quality model and the latest epidemiological concentration-response functions from the 2019 Global Burden of Diseases, Injuries, and Risk Factors Study., Findings: We found that, without ambitious climate mitigation (eg, under current NDC pledge), Chinese deaths related to PM 2·5 air pollution might not always decrease-and might often grow-by 2050 compared with the base year of 2015, regardless of clean-air policies and air quality improvements. For example, in the scenario that tracks China's current NDC pledge and uses the best available pollution control technologies (the ambitious-pollution and NDC goals scenario), PM 2·5 -related deaths in China would decrease slightly by 2030 to 1·23 million per year (95% CI 0·95-1·51) from 1·25 million (1·04-1·46) in 2015, but would not decrease further by 2050 (1·21 million, 0·86-1·60) despite substantial and continuous improvements in population-weighted air quality (from 27·2 μg/m 3 in 2030 to 16·0 μg/m 3 in 2050). The contrary trends of improving air quality and increasing PM 2·5 -related deaths in many of our scenarios revealed the extent to which extra efforts are needed to compensate for the increasing age of China's population in the future. With the scenarios that included ambitious clean-air policies and met international climate goals to avoid 1·5°C and 2°C of warming (the ambitious-pollution-2°C goals scenario and the ambitious-pollution-1·5°C goals scenario), we observed substantial decreases in China's PM 2·5 -related deaths of 0·32-0·55 million deaths compared with NDC goals in 2050, and age-standardised death rates decreased by 10·2-14·2 deaths per 100 000 population per year., Interpretation: Our results show that ambitious climate policies (ie, limiting global average temperature rise to well below 2°C) and low-carbon energy transitions coupled with stringent clean-air policies are necessary to substantially reduce the human health effects from air pollution in China, regardless of socioeconomic assumptions. Our findings could help policy makers understand the crucial links between climate policy and public health., Funding: The National Natural Science Foundation of China., Competing Interests: Declaration of interests We declare no competing interests., (Copyright © 2022 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY-NC-ND 4.0 license. Published by Elsevier Ltd.. All rights reserved.)

Belowground autotrophic respiration (RA soil ) depends on carbohydrates from photosynthesis flowing to roots and rhizospheres, and is one of the most important but least understood components in forest carbon cycling. Carbon allocation plays an important role in forest carbon cycling and reflects forest adaptation to changing environmental conditions. However, carbon allocation to RA soil has not been fully examined at the global scale. To fill this knowledge gap, we first used a Random Forest algorithm to predict the spatio-temporal patterns of RA soil from 1981 to 2017 based on the most updated Global Soil Respiration Database (v5) with global environmental variables; calculated carbon allocation from photosynthesis to RA soil (CA B ) as a fraction of gross primary production; and assessed its temporal and spatial patterns in global forest ecosystems. Globally, mean RA soil from forests was 8.9 ± 0.08 Pg C yr -1 (mean ± standard deviation) from 1981 to 2017 and increased significantly at a rate of 0.006 Pg C yr -2 , paralleling broader soil respiration changes and suggesting increasing carbon respired by roots. Mean CA B was 0.243 ± 0.016 and decreased over time. The temporal trend of CA B varied greatly in space, reflecting uneven responses of CA B to environmental changes. Combined with carbon use efficiency, our CA B results offer a completely independent approach to quantify global aboveground autotropic respiration spatially and temporally, and could provide crucial insights into carbon flux partitioning and global carbon cycling under climate change., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2021 Elsevier B.V. All rights reserved.)

Many secondary deciduous forests of eastern North America are approaching a transition in which mature early-successional trees are declining, resulting in an uncertain future for this century-long carbon (C) sink. We initiated the Forest Accelerated Succession Experiment (FASET) at the University of Michigan Biological Station to examine the patterns and mechanisms underlying forest C cycling following the stem girdling-induced mortality of >6,700 early-successional Populus spp. (aspen) and Betula papyrifera (paper birch). Meteorological flux tower-based C cycling observations from the 33-ha treatment forest have been paired with those from a nearby unmanipulated forest since 2008. Following over a decade of observations, we revisit our core hypothesis: that net ecosystem production (NEP) would increase following the transition to mid-late-successional species dominance due to increased canopy structural complexity. Supporting our hypothesis, NEP was stable, briefly declined, and then increased relative to the control in the decade following disturbance; however, increasing NEP was not associated with rising structural complexity but rather with a rapid 1-yr recovery of total leaf area index as mid-late-successional Acer, Quercus, and Pinus assumed canopy dominance. The transition to mid-late-successional species dominance improved carbon-use efficiency (CUE = NEP/gross primary production) as ecosystem respiration declined. Similar soil respiration rates in control and treatment forests, along with species differences in leaf physiology and the rising relative growth rates of mid-late-successional species in the treatment forest, suggest changes in aboveground plant respiration and growth were primarily responsible for increases in NEP. We conclude that deciduous forests transitioning from early to middle succession are capable of sustained or increased NEP, even when experiencing extensive tree mortality. This adds to mounting evidence that aging deciduous forests in the region will function as C sinks for decades to come., (© 2021 by the Ecological Society of America.)

Understanding potential health risks associated with biofuel production is critical to sustainably combating energy insecurity and climate change. However, the specific health impacts associated with biorefinery-related emissions are not yet well characterized. We evaluated the relationship between respiratory emergency department (ED) visits (2011-2015) and residential exposure to biorefineries by comparing 15 biorefinery sites to 15 control areas across New York (NY) State. We further examined these associations by biorefinery types (e.g., corn, wood, or soybean), seasons, and lower respiratory disease subtypes. We measured biorefinery exposure using residential proximity in a cross-sectional study and estimation of biorefinery emission via AERMOD-simulated modeling. After controlling for multiple confounders, we consistently found that respiratory ED visit rates among residents living within 10 km of biorefineries were significantly higher (rate ratios (RRs) range from 1.03 to 3.64) than those in control areas across our two types of exposure indices. This relationship held across biorefinery types (higher in corn and soybean biorefineries), seasons (higher in spring and winter), air pollutant types (highest for NO 2 ), and respiratory subtypes (highest for emphysema). Further research is needed to confirm our findings.

Clean air policies in China have substantially reduced particulate matter (PM 2.5 ) air pollution in recent years, primarily by curbing end-of-pipe emissions. However, reaching the level of the World Health Organization (WHO) guidelines may instead depend upon the air quality co-benefits of ambitious climate action. Here, we assess pathways of Chinese PM 2.5 air quality from 2015 to 2060 under a combination of scenarios that link global and Chinese climate mitigation pathways (i.e. global 2°C- and 1.5°C-pathways, National Determined Contributions (NDC) pledges and carbon neutrality goals) to local clean air policies. We find that China can achieve both its near-term climate goals (peak emissions) and PM 2.5 air quality annual standard (35 μg/m 3 ) by 2030 by fulfilling its NDC pledges and continuing air pollution control policies. However, the benefits of end-of-pipe control reductions are mostly exhausted by 2030, and reducing PM 2.5 exposure of the majority of the Chinese population to below 10 μg/m 3 by 2060 will likely require more ambitious climate mitigation efforts such as China's carbon neutrality goals and global 1.5°C-pathways. Our results thus highlight that China's carbon neutrality goals will play a critical role in reducing air pollution exposure to the level of the WHO guidelines and protecting public health., (© The Author(s) 2021. Published by Oxford University Press on behalf of China Science Publishing & Media Ltd.)

Soil labile organic carbon (LOC) responds rapidly to environmental changes and plays an important role in carbon cycle. In this study, the seasonal fluctuations in LOC, the activities of carbon-cycle related enzymes, and the bacterial and fungal communities were analyzed for soils collected from two forests, namely Betula albosinensis (Ba) and Picea asperata Mast. (Pa), in the Qinling Mountains of China. Results revealed that the seasonal average contents of microbial biomass carbon (MBC), easily oxidized organic carbon (EOC), and dissolved organic carbon (DOC) of Pa forest soil were 13.5%, 30.0% and 15.7% less than those in Ba soil. The seasonal average enzyme activities of β-1,4-glucosidase (βG), and β-1,4-xylosidase (βX) of Ba forest soils were 30.0% and 32.3% higher than those of Pa soil while the enzyme activity of cellobiohydrolase (CBH) was 19.7% lower. Furthermore, the relative abundance of Acidobacteria was significantly higher in summer than in winter, whereas the relative abundance of Bacteroidetes was higher in winter. Regarding the fungal communities, the relative abundance of Basidiomycota was lowest in winter, whereas Ascomycota predominated in the same season. In addition, the soil LOC was significantly positively correlated with the CBH, βG and βX activities. Changes in LOC were significantly correlated with Acidobacteria, Bacteroidetes and Basidiomycota. We conclude that the seasonal fluctuations in forest soil LOC fractions relied on carbon cycle-associated enzymatic activities and microorganisms, which in turn were affected by climatic conditions.

Although the transition to renewable energies will intensify the global competition for land, the potential impacts driven by solar energy remain unexplored. In this work, the potential solar land requirements and related land use change emissions are computed for the EU, India, Japan and South Korea. A novel method is developed within an integrated assessment model which links socioeconomic, energy, land and climate systems. At 25-80% penetration in the electricity mix of those regions by 2050, we find that solar energy may occupy 0.5-5% of total land. The resulting land cover changes, including indirect effects, will likely cause a net release of carbon ranging from 0 to 50 gCO 2 /kWh, depending on the region, scale of expansion, solar technology efficiency and land management practices in solar parks. Hence, a coordinated planning and regulation of new solar energy infrastructures should be enforced to avoid a significant increase in their life cycle emissions through terrestrial carbon losses.

Achievement of the 1.5 °C limit for global temperature increase relies on the large-scale deployment of carbon dioxide removal (CDR) technologies. In this article, we explore two CDR technologies: soil carbon sequestration (SCS), and carbon capture and storage (CCS) integrated with cellulosic biofuel production. These CDR technologies are applied as part of decentralized biorefinery systems processing corn stover and unfertilized switchgrass grown in riparian zones in the Midwestern United States. Cover crops grown on corn-producing lands are chosen from the SCS approach, and biogenic CO 2 in biorefineries is captured, transported by pipeline, and injected into saline aquifers. The decentralized biorefinery system using SCS, CCS, or both can produce carbon-negative cellulosic biofuels (≤-22.2 gCO 2 MJ -1 ). Meanwhile, biofuel selling prices increase by 15-45% due to CDR costs. Economic incentives (e.g., cover crop incentives and/or a CO 2 tax credit) can mitigate price increases caused by CDR technologies. A combination of different CDR technologies in decentralized biorefinery systems is the most efficient method for greenhouse gas (GHG) mitigation, and its total GHG mitigation potential in the Midwest is 0.16 GtCO 2 year -1 .

Many countries have implemented national climate policies to accomplish pledged Nationally Determined Contributions and to contribute to the temperature objectives of the Paris Agreement on climate change. In 2023, the global stocktake will assess the combined effort of countries. Here, based on a public policy database and a multi-model scenario analysis, we show that implementation of current policies leaves a median emission gap of 22.4 to 28.2 GtCO 2 eq by 2030 with the optimal pathways to implement the well below 2 °C and 1.5 °C Paris goals. If Nationally Determined Contributions would be fully implemented, this gap would be reduced by a third. Interestingly, the countries evaluated were found to not achieve their pledged contributions with implemented policies (implementation gap), or to have an ambition gap with optimal pathways towards well below 2 °C. This shows that all countries would need to accelerate the implementation of policies for renewable technologies, while efficiency improvements are especially important in emerging countries and fossil-fuel-dependent countries.

Understanding spatially and temporally explicit life cycle environmental impacts is critical for designing sustainable supply chains for biofuel and animal sectors. However, annual life cycle environmental impacts of crop production at county scale across mutiple years are lacking. To address this knowledge gap, this study used a combination of Environmental Policy Integrated Climate and process-based life cycle assessment models to quantify life cycle global warming (GWP), eutrophication (EU) and acidification (AD) impacts of soybean production in nearly 1000 Midwest counties yr -1 over 9 years. Sequentially, a machine learning approach was applied to identify the top influential factors among soil, climate, and farming practices, which drive the spatial and temporal heterogeneity of life cycle environmental impacts. The results indicated that significant variations existed in life cycle GWP, EU, and AD among counties and across years. Life cycle GWP impacts ranged from -11.4 to 22.0 kg CO 2 -eq kg soybean -1 , whereas life cycle EU and AD impacts varied by factors of 302 and 44, respectively. Nitrogen application rates, temperature in March and soil texture were the top influencing factors for life cycle GWP impacts. In contrast, soil organic content and nitrogen application rate were the top influencing factors for life cycle EU and AD impacts.

Climate change is exacerbating environmental pollution from crop production. Spatially and temporally explicit estimates of life-cycle environmental impacts are therefore needed for suggesting location and time relevant environmental mitigations strategies. Emission factors and process-based mechanism models are popular approaches used to estimate life-cycle environmental impacts. However, emission factors are often incapable of describing spatial and temporal heterogeneity of agricultural emissions, whereas process-based mechanistic models, capable of capturing the heterogeneity, tend to be very complicated and time-consuming. Efficient prediction of life-cycle environmental impacts from agricultural production is lacking. This study develops a rapid predictive model to quantify life-cycle global warming (GW) and eutrophication (EU) impacts of corn production using a novel machine learning approach. We used the boosted regression tree (BRT) model to estimate future life-cycle environmental impacts of corn production in U.S. Midwest counties under four emissions scenarios for years 2022-2100. Results from BRT models indicate that the cross-validation (R 2 ) for predicting life cycle GW and EU impacts ranged from 0.78 to 0.82, respectively. Furthermore, results show that future life-cycle GW and EU impacts of corn production will increase in magnitude under all four emissions scenarios, with the highest environmental impacts shown under the high-emissions scenario. Moreover, this study found that changes in precipitation and temperature played a significant role in influencing the spatial heterogeneity in all life-cycle impacts across Midwest counties. The BRT model results indicate that machine learning can be a useful tool for predicting spatially and temporally explicit future life-cycle environmental impacts associated with corn production under different climate scenarios., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2020 Elsevier B.V. All rights reserved.)

Since greenhouse gas mitigation efforts are mostly being implemented in cities, the ability to quantify emission trends for urban environments is of paramount importance. However, previous aircraft work has indicated large daily variability in the results. Here we use measurements of CO 2 , CH 4 , and CO from aircraft over 5 days within an inverse model to estimate emissions from the DC-Baltimore region. Results show good agreement with previous estimates in the area for all three gases. However, aliasing caused by irregular spatiotemporal sampling of emissions is shown to significantly impact both the emissions estimates and their variability. Extensive sensitivity tests allow us to quantify the contributions of different sources of variability and indicate that daily variability in posterior emissions estimates is larger than the uncertainty attributed to the method itself (i.e., 17% for CO 2 , 24% for CH 4 , and 13% for CO). Analysis of hourly reported emissions from power plants and traffic counts shows that 97% of the daily variability in posterior emissions estimates is explained by accounting for the sampling in time and space of sources that have large hourly variability and, thus, caution must be taken in properly interpreting variability that is caused by irregular spatiotemporal sampling conditions.

This study assesses the reductions in air pollution emissions and subsequent beneficial health effects from different global mitigation pathways consistent with the 2 °C stabilization objective of the Paris Agreement. We use an integrated modelling framework, demonstrating the need for models with an appropriate level of technology detail for an accurate co-benefit assessment. The framework combines an integrated assessment model (GCAM) with an air quality model (TM5-FASST) to obtain estimates of premature mortality and then assesses their economic cost. The results show that significant co-benefits can be found for a range of technological options, such as introducing a limitation on bioenergy, carbon capture and storage (CCS) or nuclear power. Cumulative premature mortality may be reduced by 17-23% by 2020-2050 compared to the baseline, depending on the scenarios. However, the ratio of health co-benefits to mitigation costs varies substantially, ranging from 1.45 when a bioenergy limitation is set to 2.19 when all technologies are available. As for regional disaggregation, some regions, such as India and China, obtain far greater co-benefits than others., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Published by Elsevier Ltd.)

Exposure to fine particulate matter (PM 2.5 ) from fuel combustion significantly contributes to global and US mortality. Traditional control strategies typically reduce emissions for specific air pollutants and sectors to maintain pollutant concentrations below standards. Here we directly set national PM 2.5 mortality cost reduction targets within a global human-earth system model with US state-level energy systems, in scenarios to 2050, to identify endogenously the control actions, sectors, and locations that most cost-effectively reduce PM 2.5 mortality. We show that substantial health benefits can be cost-effectively achieved by electrifying sources with high primary PM 2.5 emission intensities, including industrial coal, building biomass, and industrial liquids. More stringent PM 2.5 reduction targets expedite the phaseout of high emission intensity sources, leading to larger declines in major pollutant emissions, but very limited co-benefits in reducing CO 2 emissions. Control strategies limiting health damages achieve the greatest emission reductions in the East North Central and Middle Atlantic states.

Field studies have been performed for decades to analyze effects of different management practices on agricultural soils and crop yields, but these data have never been combined together in a way that can inform current and future cropland management. Here, we collected, extracted, and integrated a database of soil health measurements conducted in the field from sites across the globe. The database, named SoilHealthDB, currently focuses on four main conservation management methods: cover crops, no-tillage, agro-forestry systems, and organic farming. These studies represent 354 geographic sites (i.e., locations with unique latitudes and longitudes) in 42 countries around the world. The SoilHealthDB includes 42 soil health indicators and 46 background indicators that describe factors such as climate, elevation, and soil type. A primary goal of this effort is to enable the research community to perform comprehensive analyses, e.g., meta-analyses, of soil health changes related to cropland conservation management. The database also provides a common framework for sharing soil health, and the scientific research community is encouraged to contribute their own measurements.

Some researchers have suggested that corals living in deeper reefs may escape heat stress experienced by shallow corals. We evaluated the potential of deep coral reef refugia from bleaching stress by leveraging a long record of satellite-derived sea surface temperature data with a temporal, spatial, and depth precision of in situ temperature records. We calculated an in situ stress metric using a depth bias-adjusted threshold for 457 coral reef sites among 49 islands in the western and central Pacific Ocean over the period 2001-2017. Analysis of 1,453 heating events found no meaningful depth refuge from heat stress down to 38 m, and no significant association between depth and subsurface heat stress. Further, the surface metric underestimated subsurface stress by an average of 39.3%, across all depths. Combining satellite and in situ temperature data can provide bleaching-relevant heat stress results to avoid misrepresentation of heat stress exposure at shallow reefs.

Identifying the mechanisms controlling the timing and magnitude of snow accumulation on sea ice is crucial for understanding snow's net effect on the surface energy budget and sea-ice mass balance. Here, we analyze the role of cyclone activity on the seasonal buildup of snow on Arctic sea ice using model, satellite, and in situ data over 1979-2016. On average, 44% of the variability in monthly snow accumulation was controlled by cyclone snowfall and 29% by sea-ice freeze-up. However, there were strong spatio-temporal differences. Cyclone snowfall comprised ~50% of total snowfall in the Pacific compared to 83% in the Atlantic. While cyclones are stronger in the Atlantic, Pacific snow accumulation is more sensitive to cyclone strength. These findings highlight the heterogeneity in atmosphere-snow-ice interactions across the Arctic, and emphasize the need to scrutinize mechanisms governing cyclone activity to better understand their effects on the Arctic snow-ice system with anthropogenic warming.

A rapid and deep decarbonization of power supply worldwide is required to limit global warming to well below 2 °C. Beyond greenhouse gas emissions, the power sector is also responsible for numerous other environmental impacts. Here we combine scenarios from integrated assessment models with a forward-looking life-cycle assessment to explore how alternative technology choices in power sector decarbonization pathways compare in terms of non-climate environmental impacts at the system level. While all decarbonization pathways yield major environmental co-benefits, we find that the scale of co-benefits as well as profiles of adverse side-effects depend strongly on technology choice. Mitigation scenarios focusing on wind and solar power are more effective in reducing human health impacts compared to those with low renewable energy, while inducing a more pronounced shift away from fossil and toward mineral resource depletion. Conversely, non-climate ecosystem damages are highly uncertain but tend to increase, chiefly due to land requirements for bioenergy.

A rapid transition away from unabated coal use is essential to fulfilling the Paris climate goals. However, many countries are actively building and operating coal power plants. Here we use plant-level data to specify alternative trajectories for coal technologies in an integrated assessment model. We then quantify cost-effective retirement pathways for global and country-level coal fleets to limit long-term temperature change. We present our results using a decision-relevant metric: the operational lifetime limit. Even if no new plants are built, the lifetimes of existing units are reduced to approximately 35 years in a well-below 2 °C scenario or 20 years in a 1.5 °C scenario. The risk of continued coal expansion, including the near-term growth permitted in some Nationally Determined Contributions (NDCs), is large. The lifetime limits for both 2 °C and 1.5 °C are reduced by 5 years if plants under construction come online and 10 years if all proposed projects are built.

Land use is at the core of various sustainable development goals. Long-term climate foresight studies have structured their recent analyses around five socio-economic pathways (SSPs), with consistent storylines of future macroeconomic and societal developments; however, model quantification of these scenarios shows substantial heterogeneity in land-use projections. Here we build on a recently developed sensitivity approach to identify how future land use depends on six distinct socio-economic drivers (population, wealth, consumption preferences, agricultural productivity, land-use regulation, and trade) and their interactions. Spread across models arises mostly from diverging sensitivities to long-term drivers and from various representations of land-use regulation and trade, calling for reconciliation efforts and more empirical research. Most influential determinants for future cropland and pasture extent are population and agricultural efficiency. Furthermore, land-use regulation and consumption changes can play a key role in reducing both land use and food-security risks, and need to be central elements in sustainable development strategies.

The Renewable Fuel Standard (RFS) program specifies a greenhouse gas (GHG) reduction threshold for cellulosic biofuels, while the Low Carbon Fuel Standard (LCFS) program in California does not. Here, we investigate the effects of the GHG threshold under the RFS on projected GHG savings from two corn stover-based biofuel supply chain systems in the United States Midwest. The analysis is based on a techno-economic framework that minimizes ethanol selling price. The GHG threshold lowers the lifecycle GHG of ethanol: 34.39 ± 4.92 gCO 2 MJ -1 in the RFS-compliant system and 46.30 ± 10.05 gCO 2 MJ -1 in the non RFS-compliant system. However, hypothetical biorefinery systems complying with the RFS will not process the more GHG-intensive corn stover, and thus much less biofuel will be produced compared to the non RFS-compliant system. Thus, taken as a whole, the non RFS-compliant system would achieve more GHG savings than an RFS-compliant system: 10.7 TgCO 2 year -1 in the non RFS-compliant system compared with 4.4 TgCO 2 year -1 in the RFS-compliant system. These results suggest that the current RFS GHG reduction threshold may not be the most efficient way to carry out the purposes of the Energy Security and Independence Act in the corn stover-based biofuel system: relaxing the threshold could actually increase the overall GHG savings from corn stover-based biofuels. Therefore, the LCFS-type regulatory approach is recommended for the corn stover-based cellulosic biofuel system under the RFS program. In addition, our calculation of the GHG balance for stover-based biofuel accounts for SOC losses, while the current RFS estimates do not include effects on SOC.

Excessive nitrogen runoff leads to degraded water quality, harming human and ecosystem health. We examine the impact of changes in land use and land management for six combinations of socioeconomic pathways and climate outcomes, and find that societal choices will substantially impact riverine total nitrogen loading (+54% to -7%) for the continental United States by the end of the century. Regional impacts will be even larger. Increased loading is possible for both high emission and low emission pathways, due to increased food and biofuel demand, respectively. Some pathways, however, suggest that limiting climate change and eutrophication can be achieved concurrently. Precipitation changes will further exacerbate loading, resulting in a net increase of 1 to 68%. Globally, increases in cropland area and agricultural intensification will likely impact vast portions of Asia. Societal and climate trends must therefore both be considered in designing strategies for managing inland and coastal water quality.

The replacement of forest areas with human-dominated landscapes usually leads to fragmentation, altering the structure and function of the forest. Here we studied the dynamics of forest patch sizes at a global level, examining signals of a critical transition from an unfragmented to a fragmented state, using the MODIS vegetation continuous field. We defined wide regions of connected forest across continents and big islands, and combined five criteria, including the distribution of patch sizes and the fluctuations of the largest patch over the last sixteen years, to evaluate the closeness of each region to a fragmentation threshold. Regions with the highest deforestation rates-South America, Southeast Asia, Africa-all met these criteria and may thus be near a critical fragmentation threshold. This implies that if current forest loss rates are maintained, wide continental areas could suddenly fragment, triggering extensive species loss and degradation of ecosystems services.

[This corrects the article DOI: 10.1016/j.heliyon.2018.e00603.].

U.S. President John F. Kennedy was assassinated while riding in an open motorcade by a sniper in Dallas, Texas on 22 November 1963. A civilian bystander, Mr. Abraham Zapruder, filmed the motorcade with a 8-mm home movie camera as it drove through Dealey Plaza, inadvertently recording an ≈8 second sequence of events that included a fatal gunshot wound to the President in the head. The accompanying backward motion of the President's head after impact appeared to support later "conspiracy theories" because it was claimed that this was proof of a shot from the front (in addition to one from behind). In this paper, simple one-dimensional dynamical models are uniquely applied to study in detail the fatal shot and the motion of the President's head observed in the film. Using known parameters from the crime scene, explicit force calculations are carried out for determining the projectile's retardation during tissue passage along with the resulting transfer of momentum and kinetic energy (KE). The computed instantaneous KE transfer within the soft tissue is found to be consistent with the formation of a temporary cavity associated with the observed explosion of the head, and subsequent quantitative examination of this phenomenon reveals two delayed forces at play in the backward motion of the President following impact. It is therefore found that the observed motions of President Kennedy in the film are physically consistent with a high-speed projectile impact from the rear of the motorcade, these resulting from an instantaneous forward impulse force, followed by delayed rearward recoil and neuromuscular forces.

The sensitivity of the sea-surface temperature (SST) prediction skill to the atmospheric internal variability (weather noise) in the North Pacific (20 ∘ -60 ∘ N;120 ∘ E-80 ∘ W) on decadal timescales is examined using state-of-the-art Climate Forecasting System model version 2 (CFS) and a variation of CFS in an Interactive Ensemble approach (CFSIE), wherein six copies of atmospheric components with different perturbed initial states of CFS are coupled with the same ocean model by exchanging heat, momentum and fresh water fluxes dynamically at the air-sea interface throughout the model integrations. The CFSIE experiments are designed to reduce weather noise and using a few ten-year long forecasts this study shows that reduction in weather noise leads to lower SST forecast skill. To understand the pathways that cause the reduced SST prediction skill, two twenty-year long forecasts produced with CFS and CFSIE for 1980-2000 are analyzed for the ocean subsurface characteristics that influence SST due to the reduction in weather noise in the North Pacific. The heat budget analysis in the oceanic mixed layer across the North Pacific reveals that weather noise significantly impacts the heat transport in the oceanic mixed layer. In the CFSIE forecasts, the reduced weather noise leads to increased variations in heat content due to shallower mixed layer, diminished heat storage and enhanced horizontal heat advection. The enhancement of the heat advection spans from the active Kuroshio regions of the east coast of Japan to the west coast of continental United States and significantly diffuses the basin-wide SST anomaly (SSTA) contrasts and leads to reduction in the SST prediction skill in decadal forecasts.

Recent studies have shown the unique value of satellite-observed land surface thermal infrared (TIR) information (e.g., skin temperature) and the feasibility of assimilating land surface temperature (LST) into land surface models (LSMs) to improve the simulation of land-atmosphere water and energy exchanges. In this study, two different types of LST assimilation techniques are implemented and the benefits from the techniques are compared. One of the techniques is to directly assimilate LST using ensemble Kalman filter (EnKF) data assimilation (DA) utilities. The other is to use the Atmosphere-Land Exchange Inversion model (ALEXI) as an "observation operator" that converts LST retrievals into the soil moisture (SM) proxy based on the ratio of actual to potential evapotranspiration (fPET), which is then assimilated into an LSM. While most current studies have shown some success in both directly the assimilating LST and assimilating ALEXI SM proxy into offline LSMs, the potential impact of the assimilation of TIR information through coupled numerical weather prediction (NWP) models is unclear. In this study, a semi-coupled Land Information System (LIS) and Weather Research and Forecast (WRF) system is employed to assess the impact of the two different techniques for assimilating the TIR observations from NOAA GOES satellites on WRF model forecasts. The NASA LIS, equipped with a variety of LSMs and advanced data assimilation tools (e.g., the ensemble Kalman Filter (EnKF)), takes atmospheric forcing data from the WRF model run, generates updated initial land surface conditions with the assimilation of either LST- or TIR-based SM and returns them to WRF for initializing the forecasts. The WRF forecasts using the daily updated initializations with the TIR data assimilation are evaluated against ground weather observations and re-analysis products. It is found that WRF forecasts with the LST-based SM assimilation have better agreement with the ground weather observations than those with the direct LST assimilation or without the land TIR data assimilation., Competing Interests: Conflicts of Interest: The authors declare that there is no conflict of interest regarding the publication of this paper.

Droughts and other extreme precipitation events are predicted to increase in intensity, duration, and extent, with uncertain implications for terrestrial carbon (C) sequestration. Soil wetting from above (precipitation) results in a characteristically different pattern of pore-filling than wetting from below (groundwater), with larger, well-connected pores filling before finer pore spaces, unlike groundwater rise in which capillary forces saturate the finest pores first. Here we demonstrate that pore-scale wetting patterns interact with antecedent soil moisture conditions to alter pore-scale, core-scale, and field-scale C dynamics. Drought legacy and wetting direction are perhaps more important determinants of short-term C mineralization than current soil moisture content in these soils. Our results highlight that microbial access to C is not solely limited by physical protection, but also by drought or wetting-induced shifts in hydrologic connectivity. We argue that models should treat soil moisture within a three-dimensional framework emphasizing hydrologic conduits for C and resource diffusion.

Background: Livestock play an important role in carbon cycling through consumption of biomass and emissions of methane. Recent research suggests that existing bottom-up inventories of livestock methane emissions in the US, such as those made using 2006 IPCC Tier 1 livestock emissions factors, are too low. This may be due to outdated information used to develop these emissions factors. In this study, we update information for cattle and swine by region, based on reported recent changes in animal body mass, feed quality and quantity, milk productivity, and management of animals and manure. We then use this updated information to calculate new livestock methane emissions factors for enteric fermentation in cattle, and for manure management in cattle and swine., Results: Using the new emissions factors, we estimate global livestock emissions of 119.1 ± 18.2 Tg methane in 2011; this quantity is 11% greater than that obtained using the IPCC 2006 emissions factors, encompassing an 8.4% increase in enteric fermentation methane, a 36.7% increase in manure management methane, and notable variability among regions and sources. For example, revised manure management methane emissions for 2011 in the US increased by 71.8%. For years through 2013, we present (a) annual livestock methane emissions, (b) complete annual livestock carbon budgets, including carbon dioxide emissions, and (c) spatial distributions of livestock methane and other carbon fluxes, downscaled to 0.05 × 0.05 degree resolution., Conclusions: Our revised bottom-up estimates of global livestock methane emissions are comparable to recently reported top-down global estimates for recent years, and account for a significant part of the increase in annual methane emissions since 2007. Our results suggest that livestock methane emissions, while not the dominant overall source of global methane emissions, may be a major contributor to the observed annual emissions increases over the 2000s to 2010s. Differences at regional and local scales may help distinguish livestock methane emissions from those of other sectors in future top-down studies. The revised estimates allow improved reconciliation of top-down and bottom-up estimates of methane emissions, will facilitate the development and evaluation of Earth system models, and provide consistent regional and global Tier 1 estimates for environmental assessments.

Snow cover dynamics are considered to play a key role on spring phenological shifts in the high-latitude, so investigating responses of spring phenology to snow cover dynamics is becoming an increasingly important way to identify and predict global ecosystem dynamics. In this study, we quantified the temporal trends and spatial variations of spring phenology and snow cover across the Tibetan Plateau by calibrating and analyzing time series of the NOAA AVHRR-derived normalized difference vegetation index (NDVI) during 1983-2012. We also examined how snow cover dynamics affect the spatio-temporal pattern of spring alpine vegetation phenology over the plateau. Our results indicated that 52.21% of the plateau experienced a significant advancing trend in the beginning of vegetation growing season (BGS) and 34.30% exhibited a delaying trend. Accordingly, the snow cover duration days (SCD) and snow cover melt date (SCM) showed similar patterns with a decreasing trend in the west and an increasing trend in the southeast, but the start date of snow cover (SCS) showed an opposite pattern. Meanwhile, the spatial patterns of the BGS, SCD, SCS and SCM varied in accordance with the gradients of temperature, precipitation and topography across the plateau. The response relationship of spring phenology to snow cover dynamics varied within different climate, terrain and alpine plant community zones, and the spatio-temporal response patterns were primarily controlled by the long-term local heat-water conditions and topographic conditions. Moreover, temperature and precipitation played a profound impact on diverse responses of spring phenology to snow cover dynamics., (Copyright © 2017 Elsevier B.V. All rights reserved.)

Phosphorus (P) fate and transport plays a crucial role in the ecology of rivers and reservoirs in which eutrophication is limited by P. A key uncertainty in models used to help manage P in such systems is the partitioning of P to suspended and bed sediments. By analyzing data from field and laboratory experiments, we stochastically characterize the variability of the partition coefficient (K d ) and derive spatio-temporal solutions for P transport in the Three Gorges Reservoir (TGR). We formulate a set of stochastic partial different equations (SPDEs) to simulate P transport by randomly sampling K d from the measured distributions, to obtain statistical descriptions of the P concentration and retention in the TGR. The correspondence between predicted and observed P concentrations and P retention in the TGR combined with the ability to effectively characterize uncertainty suggests that a model that incorporates the observed variability can better describe P dynamics and more effectively serve as a tool for P management in the system. This study highlights the importance of considering parametric uncertainty in estimating uncertainty/variability associated with simulated P transport., (Copyright © 2017 Elsevier B.V. All rights reserved.)

For decades, the increase of nutrient enrichment has threatened the ecological integrity and economic sustainability of many rivers, lakes, and coastal waters, including Lake Okeechobee, the second largest freshwater lake in the contiguous United States. Water quality trading programs have been an area of active development to both, reduce nutrient pollution and minimize abatement costs. The objective of this study was to apply a comprehensive modeling framework, integrating a hydrologic-water quality model with an economic model, to assess and compare the cost-effectiveness of a water quality trading program over a command-and-control approach in order to reduce phosphorus loadings to Lake Okeechobee. The Upper Kissimmee (UK) and Taylor Creek/Nubbin Slough (TCNS) sub-watersheds, identified as major sources of total phosphorus (TP) loadings to the lake, were selected for this analysis. The effect of different caps on the market potential was assessed while considering four factors: the least-cost abatement solutions, credit prices, potential cost savings, and credit supply and demand. Hypothetical trading scenarios were also developed, using the optimal caps selected for the two sub-watersheds. In both sub-watersheds, a phosphorus credit trading program was less expensive than the conventional command-and-control approach. While attaining cost-effectiveness, keeping optimal credit prices, and fostering market competition, phosphorus reduction targets of 46% and 32% were selected as the most appropriate caps in the UK and TCNS sub-watersheds, respectively. Wastewater treatment facilities and urban areas in the UK, and concentrated animal feeding operations in the TCNS sub-watershed were identified as potential credit buyers, whereas improved pastures were identified as the major credit sellers in both sub-watersheds. The estimated net cost savings resulting from implementing a phosphorus trading program in the UK and TCNS sub-watersheds were 76% ($ 34.9 million per year) and 45% ($ 3.2 million per year), respectively. It is important to note that the realization of the environmental and economic benefits of this market-based alternative is also contingent on other important factors, such as the market structure, the specific program rules, the risk perception, and the education and outreach to develop trusted relationships among regulatory agencies, the public sector, and other stakeholders. Nevertheless, this research provided the foundation for stakeholders to better understand whether water quality trading has the potential to work in the Lake Okeechobee watershed and to facilitate the development of a pilot program., (Copyright © 2017 Elsevier Ltd. All rights reserved.)

The possible factors associated with the shortening of lead time between ocean warm water volume (WWV) variability along the equatorial Pacific and El Niño-Southern Oscillation (ENSO) variability after 2000 are documented. It is shown that the shortening of lead time is due to frequency increases of both WWV and ENSO. During 1979-99 the dominant frequencies were 1.5-3.5 years for both the Niño3.4 and WWV indices. In contrast, during 2000-16, both indices had a relatively flatter spectrum and were closer to a white noise process with a relative maximum at 1.5-2.0 years for the Niño3.4 index and 0.8-1.3 years for the WWV index. The frequency change of ENSO and WWV were linked to a westward shift of the Bjerknes feedback region. The results here are consistent with previous argument that the westward shift of the air-sea coupling region will cause an increase of ENSO frequency, as the corresponding zonal advection feedback reduces the period and growth of coupled instability, thus favoring more frequent and weak El Niño events.

The freight sector's role is examined using the Global Change Assessment Model (GCAM) for a range of climate change mitigation scenarios and future freight demand assumptions. Energy usage and CO 2 emissions from freight have historically grown with a correlation to GDP, and there is limited evidence of near-term global decoupling of freight demand from GDP. Over the 21 st century, greenhouse gas (GHG) emissions from freight are projected to grow faster than passenger transportation or other major end-use sectors, with the magnitude of growth dependent on the assumed extent of long-term decoupling. In climate change mitigation scenarios that apply a price to GHG emissions, mitigation of freight emissions (including the effects of demand elasticity, mode and technology shifting, and fuel substitution) is more limited than for other demand sectors. In such scenarios, shifting to less-emitting transportation modes and technologies is projected to play a relatively small role in reducing freight emissions in GCAM. By contrast, changes in the supply chain of liquid fuels that reduce the fuel carbon intensity, especially deriving from large-scale use of biofuels coupled to carbon capture and storage technologies, are responsible for the majority of freight emissions mitigation, followed by price-induced reduction in freight demand services.

Despite significant effort to quantify the interdependence of the water and energy sectors, global requirements of energy for water (E4W) are still poorly understood, which may result in biases in projections and consequently in water and energy management and policy. This study estimates water-related energy consumption by water source, sector, and process for 14 global regions from 1973 to 2012. Globally, E4W amounted to 10.2 EJ of primary energy consumption in 2010, accounting for 1.7%-2.7% of total global primary energy consumption, of which 58% pertains to fresh surface water, 30% to fresh groundwater, and 12% to nonfresh water, assuming median energy intensity levels. The sectoral E4W allocation includes municipal (45%), industrial (30%), and agricultural (25%), and main process-level contributions are from source/conveyance (39%), water purification (27%), water distribution (12%), and wastewater treatment (18%). While the United States was the largest E4W consumer from the 1970s until the 2000s, the largest consumers at present are the Middle East, India, and China, driven by rapid growth in desalination, groundwater-based irrigation, and industrial and municipal water use, respectively. The improved understanding of global E4W will enable enhanced consistency of both water and energy representations in integrated assessment models.

Starting in 2006, a new source of intense salt dust storms developed in Mar Chiquita (Córdoba, Argentina), the largest saline lake in South America. Storms originate from vast mudflats left by a 30-year expansion-retreat cycle of the lake due to changes in the regional rainfall regime. The annual frequency of salt dust storms correlated with the size of the salt mudflats. Events were restricted to the coldest months, and reached up to 800 km from the source. Occurrence of dust storms was associated with specific surface colors and textures easily identifiable in satellite images. High-emission surfaces were characterized by the presence of sodium sulfate hydrous/anhydrous crystals (mirabilite and thenardite), and a superficial and variable water table, which may result in the periodic development of a characteristic "fluffy" surface derived from salt precipitation-dissolution processes. HYSPLIT model simulation estimates a deposition maximum near the sources (of about 2.5 kg/ha/yr), and a decreasing trend from the emission area outwards, except for the relative secondary maximum modeled over the mountain ranges in southern Bolivia and northern Argentina due to an orographic effect. The 2009 total deposition of salt dust generated in Mar Chiquita was estimated at 6.5 million tons.

Carbon cycling in inland waters has been identified as an important, but poorly constrained component of the global carbon cycle. In this study, we compile and analyze particulate organic carbon (POC) concentration data from 1145 U.S. Geological Survey (USGS) gauge stations to investigate the spatial variability and environmental controls of POC concentration. We observe substantial spatial variability in POC concentration (1.43 ± 2.56 mg C/L, mean ± one standard deviation), with the Upper Mississippi River basin and the Piedmont region in the eastern U.S. having the highest POC concentration. Further, we employ generalized linear models (GLMs) to analyze the impacts of sediment transport and algae growth as well as twenty-one other environmental factors on the POC variability. Suspended sediment and chlorophyll-a explain 26% and 17% of the variability in POC concentration, respectively. At the national level, the twenty-one environmental factors combined can explain ca. 40% of the spatial variance in POC concentration. At the national scale, urban area and soil clay content show significant negative correlations with POC concentration, whereas soil water content and soil bulk density correlate positively with POC. In addition, total phosphorus concentration and dam density correlate positively with POC concentration. Furthermore, regional scale analyses reveal substantial variation in environmental controls of POC concentration across eighteen major water resource regions in the U.S. The POC concentration and associated environmental controls also vary non-monotonically from headwaters to large rivers. These findings indicate complex interactions among multiple factors in regulating POC concentration over different spatial scales and across various sections of the river networks. This complexity, together with the large unexplained uncertainty, highlights the need for considering non-linear interplays of multiple environmental factors and developing appropriate methodologies to track the transformation and transport of POC along the terrestrial-aquatic interfaces., (Copyright © 2016 Elsevier B.V. All rights reserved.)