Table of contents

The low-lying Senegalese sandy coast is extremely vulnerable to marine flooding and erosion. Using climate and wave reanalysis, we establish the remote connections between Atlantic climate modes and coastal wave variability in Senegal. We show that impacting swells come from the North Atlantic in boreal winter but also from the South and Tropical Atlantic in boreal summer. Near shore-normal tropical cyclones swells have a large impact on the sea level contribution at the coast but a limited influence on the longshore sediment transport. In contrast, boreal summer south swells have a large destabilizing coastal impact due to a reversal of the climatological southward sediment drift. They also induce large sea level anomalies on the southern Senegalese coast, the most exposed to flooding. This study emphasizes the importance of quantifying the influence of both the regional and remote climate variability on wave activity to better understand the drivers of coastal evolution and vulnerability.

Coal-fired power plants with carbon capture and sequestration (CCS), natural-gas-fired power plants with CCS, and Small Modular Reactors (SMR) are potentially important emerging energy technologies that could help mitigate climate change and contribute to a low-carbon future. Public opinion and preferences towards these technologies will affect their adoption when they are technologically ready to be implemented. This study examines the nature and stability of public preferences among these options. We find that participants have internally consistent preferences, when tested in several ways. Overall, they prefer SMRs to natural gas with CCS to coal with CCS. On a group level, these preferences depend on the choice alternatives, but not on how fully the technologies are described nor how far away a hypothetical power plant would be sited. On the individual level, preferences are related to participants' perceptions of the technology and their political ideology. Our findings suggest that presenting the three technologies together will produce the most balanced, informed judgment, with the least influence of political ideology.

In the last century, about 50,000 dams have been constructed all around the world, and regulated rivers are now pervasive throughout the Earth's landscapes. Damming has produced global-scale alterations of the hydrologic cycle, inducing severe consequences on the ecological and morphological equilibrium of streams. However, a recognizable link between specific uses of reservoirs and their impact on flow regimes has not been disclosed yet. Here, extensive hydrological data are integrated with a physically-based model to investigate hydrological alterations downstream of 47 isolated dams in the Central Eastern U.S. Our results reveal a strong connection between the anthropogenic use and the hydrological impact of dams. Flood control reduces the temporal variability and spatial heterogeneity of river flows proportionally to the specific capacity allocated to mitigate floods (i.e., capacity scaled to the average inflow). Conversely, water supply increases the relative variability and regional heterogeneity of streamflows proportionally to the relative amount of withdrawn inflow. Accordingly, downstream of our multipurpose reservoirs the impact of regulation on streamflow variability is smoothed due to the compensating effect of flood control and water supply. Nevertheless, reservoirs with high storage capacity and overlapping uses produce regulated hydrographs that increase their unpredictability for larger aggregation periods and, thus, resemble an autocorrelated red noise. These findings suggest that the increase of freshwater demand could redefine the cumulative effects of dams at regional scale, reshaping the trajectories of eco-morphological alteration of dammed rivers.

Regional reanalyses constitute valuable new data sources for climatological applications by providing consistent meteorological parameter fields commonly requested, e.g., wind speed, solar radiation, temperature and precipitation. Within the European project Uncertainties in Ensembles of Regional ReAnalyses (UERRA) three different numerical weather prediction (NWP) models have been employed to generate different European regional reanalyses and subsequent surface reanalysis products. The uncertainties of the individual reanalysis products and of the combined UERRA multi-model ensemble are investigated by comparing against observations. Here, we provide guidance on the meteorological parameters and spatial-temporal scales where regional reanalyses add value to global reanalyses. The reanalysis fields are compared to station measurements and derived gridded fields, as well as satellite data. In general, reanalyses are especially valuable in data sparse areas, where the NWP models are superior in transporting information compared to the traditional gridding procedures based on station observations. For wind speed at heights relevant for wind energy, where little conventional observations exist, regional reanalyses can provide higher resolution horizontally, vertically, and in time, adding value to global reanalyses. Solar radiation fields capture the variability in general, however, they are prone to model-dependent biases. Temperature fields were generally found to be in good agreement with station observations, with biases for the (moderately) extreme values causing potential pitfalls for threshold applications such as climate indices. Comparisons of the precipitation fields in different areas of Europe demonstrate that various reanalyses excel in different regions. The multi-model ensemble of regional reanalyses was found to provide better uncertainty estimates than an ensemble realisation from one reanalysis system alone. The freely available regional reanalyses provide a new, high resolution data source, which might be attractive for many applications, especially when conventional data are sparse or restricted by data policies.

To investigate the origins, other than fossil fuel combustion and biomass burning, of urban carbonaceosus aerosols, we studied the fine (PM_2.5) aerosols collected in Guiyang, Southwest China in winter (December 10–23) 2012 for organic carbon (OC), elemental carbon (EC) and water-soluble diacids, oxoacids, α-dicarbonyls and fatty acids as well as inorganic ions. Oxalic acid (C₂) found to be the most abundant diacid species followed by succinic (C₄) and terephthalic (t-Ph) acids, respectively. Even-carbon numbered fatty acids showed high abundances with a peak at C₁₆. OC, EC and most of diacids and related compounds, but not inorganic ions, showed a similar temporal pattern with a drastic rise in December 15 day- and night-time samples during the campaign. Based on molecular distributions of diacids and fatty acids, and linear relations of OC and EC with selected marker ions and diacid species, we found that the organics and EC in PM_2.5 are mainly derived from higher plant/cooking and municipal waste burning emissions in Guiyang. This study implies that municipal waste burning largely contributes to carbonaceous aerosols and warrants a need of further research on its role in aerosol loading and air quality in the urban atmosphere.

Adaptation to coastal flood risk is hampered by high uncertainty in the rate and magnitude of sea-level rise. Subsequently, adaptation decisions carry strong risks of under- or over-investment, and could lead to costly retrofitting or unnecessary high margins. To better allocate resources timely and effectively, and achieve long-term sustainability, planners could utilise adaptation pathways, revealing the path-dependencies of adaptation options. This helps to identify low-regret short-term decisions that preserve options in an uncertain future, while monitoring to detect signals to adapt. A major barrier to the application of adaptation pathways is limited experience. To facilitate this, here we generalize this pathways approach for six common coastal archetypes, resulting in generic pathways suitable to be adjusted to local conditions. This provides a much richer analysis of coastal adaptation than provided by any previous analysis, by assessing the solution space and options over time for a variety of coastal regions. Based on this analysis, we find that the number of adaptation options declines while sea-level rises. For some archetypes, it becomes clear that long-term thinking is needed now, about if, how and when to move to transformative options, such as planned retreat, which may presently not be considered or acceptable. Our analysis further shows that coastal adaptation needs to start earlier than anticipated, especially given time required for local debate and choice and to implement measures.

The US Department of Agriculture-Agricultural Research Service (USDA-ARS) worked together with the University of Maryland, College Park and BMT Designers and Planners (Consultant) to design a biowall to remediate the groundwater of a Superfund site located in Beltsville, MD. The US Environmental Protection Agency (US EPA) oversaw the remediation plan as per the regulations of the Comprehensive Environmental Response, Compensation, and Liability Act (CERCLA) program. A hybrid adaptive management strategy was employed to to guarantee the use of a science-based approach to the remediation efforts, to ensure that new information could be incorporated into the remediation plan, and to avoid the shortcomings of other remediation efforts elsewhere. Laboratory experiments and a historic-data assessment were conducted in conjunction with the monitoring plan to provide the Consultant and USDA with comprehensive feedback, to strengthen and to modify the monitoring and biowall construction plans as the requirements of the site changed. This feedback mechanism was repeated multiple times to make certain that the highest quality and most effective methods were used. The scope of the project also grew to include investigations of the soil microbial community for future structural biostimulation and bioaugmentation activities. While the biowall has reduced the concentration of trichloroethylene (TCE) to levels at or below its Maximum Contaminant Level, work is on-going to improve the functionality of the biowall and to address emerging challenges.

The National Weather Service of the United States uses the heat index—a combined measure of temperature and relative humidity—to define risk thresholds warranting the issuance of public heat alerts. We use statistically downscaled climate models to project the frequency of and population exposure to days exceeding these thresholds in the contiguous US for the 21st century with two emissions and three population change scenarios. We also identify how often conditions exceed the range of the current heat index formulation. These 'no analog' conditions have historically affected less than 1% of the US by area. By mid-21st century (2036–2065) under both emissions scenarios, the annual numbers of days with heat indices exceeding 37.8 °C (100 °F) and 40.6 °C (105 °F) are projected to double and triple, respectively, compared to a 1971–2000 baseline. In this timeframe, more than 25% of the US by area would experience no analog conditions an average of once or more annually and the mean duration of the longest extreme heat index event in an average year would be approximately double that of the historical baseline. By late century (2070–2099) with a high emissions scenario, there are four-fold and eight-fold increases from late 20th century conditions in the annual numbers of days with heat indices exceeding 37.8 °C and 40.6 °C, respectively; 63% of the country would experience no analog conditions once or more annually; and extreme heat index events exceeding 37.8 °C would nearly triple in length. These changes amount to four- to 20-fold increases in population exposure from 107 million person-days per year with a heat index above 37.8 °C historically to as high as 2 billion by late century. The frequency of and population exposure to these extreme heat index conditions with the high emissions scenario is roughly twice that of the lower emissions scenario by late century.

The United States is the largest supplier of dairy products globally, making it an important focus for environmental, economic, and societal outcomes. Increasingly greenhouse gases (GHGs) have become an area of focus for the industry, as industry groups have set their own goals to improve environmental impacts. A significant portion of dairy GHG emissions come from manure management, which can vary considerably by farm and region. Here we explore how the adoption and use of six common manure management strategies (MMS) have changed over a recent 12-year period, and how this relates to milk production, climate, and manure GHGs. Using data from the United States Department of Agriculture, the Environmental Protection Agency, and the National Oceanic and Atmospheric Administration across all fifty states, we find that overall US dairy manure management GHG emission intensity (CO₂e per kg of milk produced) has increased 18% between 2003 and 2014, which is associated with an increase in adoption of liquid and anaerobic MMS. However, we also find that these systems are positively associated with higher productivity: nationally, total milk production grew by 21.0%, while the cow herd inventory grew by just 1.9%, an increase of 18.7% in per-cow milk production over the study period. We find clear regional adoption of certain kinds of MMS, which relate in many cases to temperature and rainfall. We discuss why these shifts may have occurred as a result of economic and policy drivers, including the shift towards these MMS for compliance with new water quality policies in the past decade, highlighting the tradeoffs that exist in on-farm decision-making. We provide some potential strategies to reduce GHG emissions in these systems while simultaneously considering water quality and other potential tradeoffs. We suggest that transitioning to some of these strategies requires additional research to better understand farmer decision-making as it relates to MMS, a currently understudied topic.