Individual and Structural Determinants of Underemployment: A Comparative Study between Colombia and the Atlantic Coast

US coastal cities are regularly subjected to destruction by tropical cyclones. The risk of tropical cyclone winds varies along the length of the coastline. We analyze landfalling North Atlantic basin tropical cyclones whose intensities are considered extreme relative to their landfall location. To be considered extreme, a tropical cyclone’s wind speed must exceed the 50-year return level for a given city. Of interest is the spatial and temporal patterns of these extreme hurricane wind events for fifteen coastal cities, which are organized into four coastal regions: Northeast Atlantic, Southeast Atlantic, Florida, and Gulf. Findings suggest that extreme hurricanes along the Florida and Atlantic coasts cluster in time, specifically decades, while there is no temporal clustering detected along the Gulf. Atlantic coast hurricane clusters are in part due to the likelihood of one intense hurricane impacting multiple coastal cities, which is unlikely to happen along the Gulf due to the alignment of the coast. It is also unlikely for an intense hurricane to impact multiple Florida cities as an extreme hurricane, suggesting a physical mechanism enables the temporal clustering seen here. The results of this work advocate for annual and decadal hurricane risk to include: (1) the likelihood of temporal clusters of extreme hurricanes along the Atlantic and Florida coasts and (2) extreme hurricanes impacting multiple cities along the Atlantic coast.

One of the major concerns engendered by a warming climate are changing sea levels and their lasting effects on coastal populations, infrastructures, and natural habitats. Sea levels are now monitored by satellites, but long‐term records are only available at discrete locations along the coasts. Sea levels and sea‐level processes must be better understood at the local level to best inform real‐world adaptation decisions. We propose a statistical model that facilitates the characterization of known sea‐level processes, which jointly govern the observed sea level along the United States Atlantic Coast. Our model not only incorporates long‐term sea level rise and seasonal cycles but also accurately accounts for residual spatiotemporal processes. By combining a spatially varying coefficient modeling approach with spatiotemporal factor analysis methods in a Bayesian framework, the method represents the contribution of each of these processes and accounts for corresponding dependencies and uncertainties in a coherent way. Additionally, the model provides a consistent way to estimate these processes and sea level values at unmonitored locations along the coast. We show the outcome of the proposed model using thirty years of sea level data from 38 stations along the Atlantic (east) Coast of the United States. Among other results, our method estimates the rate of sea level rise to range from roughly 1 mm/year in the northern and southern regions of the Atlantic coast to 5.4 mm/year in the middle region.

In this study, relationships between temperature, precipitation, and the percentage of C4 grasses in local grass floras from the Atlantic and Pacific coastal regions of North America were examined. The proportion of C4 species in a local grass flora increased as latitude decreased on both coasts. At a given latitude, the C4 percentage on the Atlantic coast was higher than the Pacific coast. This difference was related to the Atlantic coast having greater July minimum temperatures than Pacific coast locations of similar latitude. Linear regression analysis showed that the proportion of C4 species in a local flora was positively associated with July minimum temperature on both coasts. The regression line between July minimum temperature and C4 representation was similar for each coast, indicating growth-season temperature has a similar control over C4 presence on the two coasts. Proportionally more of the annual precipitation fell in midsummer on the Atlantic than the Pacific coast, but this difference in the seasonal occurrence of precipitation did not alter the relationship between July minimum temperature and the contribution of C4 grass species to local floras. The Atlantic coast locations with the most precipitation had the highest C4 grass occurrence, indicating aridity alone did not increase the C4 representation in a grass flora. On both coasts, the proportion of NADP-malic enzyme C4 species in local C4 grass floras was positively correlated with mean annual precipitation; however, at equivalent percentages of NADP-malic enzyme subtype occurrence, precipitation levels were substantially lower on the Pacific than Atlantic coast. The trend between latitude and the percentage of C4 species in exotic grass floras was similar to the trend between latitude and the percentage of all C4 grasses in an entire grass flora. Thus, the C4 pathway appears to play no obvious role in enhancing the invasibility of exotic grasses in North America.Key words: bioinvasions, biogeography, C4 photosynthesis, C4 subtype, Poaceae, photosynthesis.

In times of demographic change, better job quality is needed to promote health and thereby extend employment participation among older workers. Past research has focussed on the investigation of single job quality characteristics, but neglected their combined effects on health and employment. To address this limitation, we have built upon an established typology based on nine job quality characteristics and representing five profiles of overall poor or good job quality constellations among manual and non-manual older workers, respectively. It was investigated how constant and changing job quality affects non-employment and how mental and physical health mediate this association. Analyses were based on representative data from N = 2,952 employees born in 1959 or 1965, who participated in all current waves (in the years 2011, 2014 and 2018) of the German lidA cohort study. Job quality was measured in 2011 and 2014 according to profile assignment per wave, composite mental and physical health scores from 2014 were used as mediators and non-employment (vs. employment) in 2018 represented the outcome. Two separate mediation models were calculated, one for manuals and one for non-manuals. Among manuals with constantly poor job quality, the risk of non-employment was increased through both poor mental and physical health. Deteriorating job quality increased this risk through poor mental health, while changing from manual to non-manual work reduced this risk through better physical health. Among non-manuals, poor job quality was not related to the risk of non-employment and no health effects were found to significantly mediate such a risk. In conclusion, the health risks of poor later-life job quality demand critical consideration to maintain employability, particularly of manual workers in poor quality jobs. Timely workplace improvements for certain groups are needed to increase employment participation in good health, thereby increasing efficiency and fairness of measures promoting longer working lives.

Wind power generates a significant percentage of electricity and is used by a great many countries, including the largest producers worldwide: China, the United States, Germany and Spain.Colombia has a wind energy potential of an estimated 21 GW on its Atlantic coast alone, and yet in the nation as a whole only 19.5 MW are currently generated, coming from the Jeripachi wind farm in La Guajira. The utilization of this type of energy in other geographical locations is still undeveloped, sparking a need to evaluate its utility and profitability, such as in urban generation and consumption.In this paper we present the preliminary results of a study on the estimation of wind power in 4 cities, where weather stations have been set up at University Antonio Nariño installations. We measured variables such as wind speed, wind direction and environmental temperature.As a result, we statistically characterized wind speed in each location by fitting the data to a Weibull distribution. We also estimated the percentage of energy coverage that could be exploited in an average home using a domestic urban wind turbine. The study also presents a prefeasibility analysis of what could be expected from investment in self-generated electricity using such technology in the studied locations.

Monitoring Colombia's Children Wellbeing

BackgroundThere is little evidence on whether becoming re-employed in poor quality work is better for health and well-being than remaining unemployed. We examined associations of job transition with health and chronic stress-related biomarkers among a population-representative cohort of unemployed British adults.MethodsA prospective cohort of 1116 eligible participants aged 35 to 75 years, who were unemployed at wave 1 (2009/10) of the UK Household Longitudinal Study, were followed up at waves 2 (2010/11) and 3 (2011/12) for allostatic load biomarkers and self-reported health. Negative binomial and multiple regression models estimated the association between job adversity and these outcomes.ResultsCompared with adults who remained unemployed, formerly unemployed adults who transitioned into poor quality jobs had higher levels of overall allostatic load (0.51, 0.32–0.71), log HbA1c (0.06, <0.001–0.12), log triglycerides (0.39, 0.22–0.56), log C-reactive protein (0.45, 0.16–0.75), log fibrinogen (0.09, 0.01–0.17) and total cholesterol to high-density lipoprotein (HDL) ratio (1.38, 0.88–1.88). Moreover, physically healthier respondents at wave 1 were more likely to transition into good quality and poor quality jobs after 1 year than those who remained unemployed.ConclusionsFormerly unemployed adults who transitioned into poor quality work had greater adverse levels of biomarkers compared with their peers who remained unemployed. The selection of healthier unemployed adults into these poor quality or stressful jobs was unlikely to explain their elevated levels of chronic stress-related biomarkers. Job quality cannot be disregarded from the employment success of the unemployed, and may have important implications for their health and well-being.

This report describes a large-area model that relates temperature and precipitation data to changes in southern pine beetle outbreak intensity. The model first transforms monthly mean temperature and total precipitation data with principal component analysis, and then uses the resultant linear combinations to predict a percent coverage indicator in ten climatic districts in Atlantic Coastal and Piedmont regions. While the model usually correctly estimates the sign of the coverage change from the previous year, it usually underestimates the magnitude. However, the analysis indicates that substantial changes were estimated 1972, 1974, and 1977, the three years in which coverage figures change the most from the previous year. The principal components were calculated from a very reliable 48-year record, and then were statistically related to a county coverage record from 1960 through 1980. The resultant model is applicable to a larger region than is previously published work. Forest Sci. 30:143-156.

&lt;em&gt;Abstract.&lt;/em&gt;—Because of their tendency to accumulate in estuaries and coastal regions, organochlorine (OC) contaminants such as pesticides and polychlorinated biphenyls (PCBs) represent potential threats to the quality of essential fish habitat for many shark species. These compounds pose special risks to immature sharks in particular because of their ability to impair growth and sexual maturation in juvenile fish at environmentally relevant levels of exposure. In order to assess the extent of these risks in shark populations on the East Coast of the United States, the present study examined concentrations of 30 OC pesticides/pesticide metabolites and total PCBs in juvenile sandbar &lt;em&gt;Carcharhinus plumbeus &lt;/em&gt;and blacktip &lt;em&gt;C. limbatus &lt;/em&gt;sharks from seven major nursery areas in the western Atlantic Ocean and eastern Gulf of Mexico. Quantifiable levels of PCBs and 13 OC pesticides/ pesticide metabolites were detected via gas chromatography and mass spectrometry in liver of 25 young-of-the-year blacktip sharks from the southeastern U.S. Atlantic coast and three regions on Florida’s gulf coast: Cedar Key, Tampa Bay, and Charlotte Harbor. Similarly, quantifiable levels of PCBs and 14 OC pesticides/metabolites were detected in 23 juvenile &lt;em&gt;C. plumbeus &lt;/em&gt;from three sites on the northeastern U.S. coast: middle Delaware Bay, lower Chesapeake Bay, and Virginia’s eastern shore. Liver OC concentrations in Atlantic sandbar and blacktip sharks were higher than expected and, in some cases, comparable with elevated levels observed in deep-sea and pelagic sharks. Although significantly lower than those observed in Atlantic sharks, pesticide and PCB levels in Florida blacktip sharks were similar to, if not greater than, OC concentrations reported in adults of other coastal shark species. Based on these data, OC contamination appears to pose significant threats to habitat quality in sandbar and blacktip shark nursery areas on the U.S. Atlantic coast.

Coastal erosion poses a significant challenge along Africa’s Atlantic coast, with flooding ranking as the second most pressing threat after erosion. This issue is particularly acute in Cameroon, especially along the Kribian coast and the Wouri estuary, where Cape Cameroon is undergoing severe erosional processes. The central research question of this study examines whether the erosion in the Wouri estuary is due to local factors or part of a broader dynamic affecting the entire Atlantic African shoreline. The study aims to achieve three main objectives: (i) to map shoreline dynamics in the Wouri estuary from 1975 to 2019, identifying and quantifying eroding segments; (ii) to analyze factors contributing to erosion in the Wouri estuary and those common to other Atlantic African coasts; and (iii) to contextualize these findings within current scientific literature. Utilizing Hilhorst’s theory of “reciprocity” or “complexity”, the study recognizes that coastal areas are shaped by both physical and human factors influencing natural hazards like erosion and flooding. To investigate the causes of coastal erosion, a smaller-scale map (1:5000) derived from Landsat images (30-m resolution) and a larger-scale map (1:1500) based on Pleiades and Google Earth images (0.5-m resolution) were employed, focusing on Cape Cameroon. The imagery covers various years: Landsat (1975, 1986, 2000, 2016, 2024), Pleiades (2013, 2018), and Google Earth (2000, 2016). Shoreline extraction utilized both automatic (unsupervised classification) and semi-automatic (digitization) methods, especially in cloud-obscured areas. The Digital Shoreline Analysis System (DSAS) within ArcGIS 10.7.1 quantified shoreline retreat rates using the End Point Rate (EPR) method while meticulously calculating sources of error and uncertainty. Analysis of Landsat imagery revealed that over 75% of the Wouri estuary’s shoreline is eroding, with average retreat rates ranging from − 3 m/year to − 11 m/year between 1975 and 2020. Hotspots for erosion include Cape Cameroon, the coastal spit around Manoka Island, and the vicinity of the APD. The northern tip of Cape Cameroon retreats at an estimated rate of − 15 m/year, with a maximum retreat at 53 m. Conversely, an annual accretion rate of + 5 m/year was noted at Toubé from 1975 to 2024. These findings highlight the dynamic nature of the coastal region, which may reflect broader trends across West African coasts experiencing intense erosion. This study lays a foundation for comprehensive coastal research and management, providing insights applicable to other African coastlines to mitigate the impacts of coastal erosion.

Meaningfully confronting the climate crisis requires, among many other things, a transition from an economy driven by the burning of fossil fuels to one driven by renewable energy. Development of offshore wind energy is an important aspect of the effort to decarbonize the energy sector because wind farms with large generating capacities can be constructed in the abundant offshore areas near densely populated coastal regions with high energy demand. In the United States, the offshore wind industry lags behind that of countries in Europe and Asia, but growth is on the horizon: the Atlantic Coast is projected to host thousands of offshore wind turbines (OWTs) with a cumulative capacity in the tens of gigawatts in the coming decades. It is likely that many or even most of the OWTs along the U.S. Atlantic Coast will be supported by monopiles. Monopiles support nearly three quarters of global offshore wind capacity and the U.S. Atlantic Coast has nearshore depths that are shallow enough for monopiles to be a viable foundation type. The scale of these offshore infrastructure installations will be dictated by trends in OWT capacity. Currently, the largest installed OWTs have capacities of 8 MW and monopile diameters of 7.5m, but with next-generation OWTs projected to have capacities in the 12-15 MW range, monopiles with diameters of 10m and greater are considered feasible and even necessary for future development. Structural engineers have an important role to play in this development. Assessing the risk to the offshore renewable energy infrastructure planned for the U.S. Atlantic Coast will rely in large part on the ability of structural engineers to accurately predict wave loads on large diameter monopiles. Structural engineers face a modeling problem and a computational problem: many uncertainties in the wave loading of monopile-supported OWTs persist because the offshore environment is so complex, but high-fidelity simulations that accurately model that complexity are computationally expensive and difficult to implement with confidence in a practical setting. As a result, comprehensive analysis and risk assessment for the total number of OWTs along the Atlantic Coast is challenging. Engineering methods of wave load prediction based on simple wave mechanics and hydrodynamics models offer a means to circumvent the computational limits imposed by high-fidelity simulations. If used judiciously, such engineering methods can expedite comprehensive analysis of many scenarios of practical interest. The goal of this dissertation research is to assess the conditions for which these methods for the prediction of wave loads on large diameter monopiles can preserve a minimum level of accuracy that is necessary to make useful design recommendations and risk predictions. This assessment is made by comparing predictions of wave loads yielded by the engineering methods with simulated wave loads and with measurements of wave loads from wave flume experiments. Such comparisons can also demonstrate which site, environmental, and structural characteristics are most important for the accurate prediction of wave loads. In this way, the work provides further insight into the physics governing the response of monopile-supported OWTs to wave loading. --Author's abstract

The origin of the tidal marshes and the development of their vegetative cover have received the attention of several American investigators. Shaler (1885) and Knight (1934) ascribed the origin of marginal marshes that are protected from the direct action of waves by bars or by their location along the borders of estuaries to the silting up of quiet bodies of water to a little above the low-tide level. Such deposition permits the invasion and ecesis of the salt marsh grasses. The first marsh grass to colonize an aggraded substratum along the Atlantic and Gulf coasts is usually Spartina glabra alternifora2, occuring in nearly pure stand. Conard (1935) named this association the Spartinetum glabrae, a more precise designation than the sedge association, or Spartinetum of Ganong (1903). This association has been recognized or described floristically from Nova Scotia, southward along the Atlantic coast, to North Carolina (Kearney 1900-1901, Ganong 1903, Davis 1910, Shreve et al. 1910, Harshberger 1909-1916, Johnson and York 1915, Nichols 1920, Wells 1928, Knight 1934, Conard 1935, Chapman 1940). It is known in the Gulf Coast region from the work of Penfound and O'Neil (1934) and Penfound and Hathaway (1938).

Realistic representation of monthly sea level anomalies in coastal regions has been a challenge for global ocean reanalyses. This is especially the case in coastal regions where sea levels are influenced by western boundary currents such as near the U.S. Atlantic Coast and the Gulf of Mexico. For these regions, most ocean reanalyses compare poorly to observations. Problems in reanalyses include errors in data assimilation and horizontal resolutions that are too coarse to simulate energetic currents like the Gulf Stream and Loop Current System. However, model capabilities are advancing with improved data assimilation and higher resolution. Here, we show that some current-generation ocean reanalyses produce monthly sea level anomalies with improved skill when compared to satellite altimetry observations of sea surface heights. Using tide gauge observations for coastal verification, we find the highest skill associated with the GLORYS12 and HYCOM ocean reanalyses. Both systems assimilate altimetry observations and have eddy-resolving horizontal resolutions (1/12°). We found less skill in three other ocean reanalyses (ACCESS-S2, ORAS5, and ORAP6) with coarser, though still eddy-permitting, resolutions (1/4°). The operational reanalysis from ECMWF (ORAS5) and their pilot reanalysis (ORAP6) provide an interesting comparison because the latter assimilates altimetry globally and with more weight, as well as assimilating ocean observations over continental shelves. We find these attributes associated with improved skill near many tide gauges. We also assessed an older reanalysis (CFSR), which has the lowest skill likely due to its lower resolution (1/2°) and lack of altimetry assimilation. ACCESS-S2 likewise does not assimilate altimetry, although its skill is much better than CFSR and only somewhat lower than ORAS5. Since coastal flooding is influenced by sea level anomalies, the recent development of skilful ocean reanalyses on monthly timescales may be useful for better understanding the physical processes associated with flood risks.

Summary form only given. This study addresses the consistency of the surface friction velocity derived from the scatterometer normalized radar cross section (NRCS) measurements and the directional properties of the NRCS (SIGMA-O) measurements in near coastal regions. NSCAT data (Level 1.7) colocated with numerous NDBC buoys is being analyzed to determine the variability of the directional properties of the colocated fore and aft beam measurements. These orthogonal measurements of the NRCS (25 km resolution, and converted to linear power units) by the fore and aft beams are used to calculate the Fourier series coefficients of the azimuthal model: AO and A2. The spatial variability of A2/AO, as an indication of how the azimuthal modulation varies, is being examined in the vicinity of buoys off the U.S. Atlantic coast, in the Gulf of Mexico and along the coast of California. Preliminary results show excellent agreement between the satellite derived friction velocity (u*) using the FASINEX/Weissman Ku-band model function and buoy measurements. An alternate method of estimating u* using the satellite (Level 2.0) wind speeds and a drag coefficient produce results with a wider scatter about the buoy-derived estimates of u*. Other results show some cases in which the A2/AO term is relatively constant for the 12-to-19 SIGMA-O cells that lie within the 10 square region centered about each buoy, and other situations in which the A2/AO values vary randomly and considerably even though the winds appear to be uniform. These latter situations are of strong interest, and are being studied to determine the possible causes of this variability. Under consideration are the long wave systems, atmospheric stability and surface material properties.

This study presents a comprehensive techno-economic assessment of offshore wind projects in the Colombian Caribbean, emphasizing the impact of site-specific parameters on development costs and performance. Wind resource conditions were evaluated in four coastal regions (La Guajira, Magdalena, Atlántico, and Bolívar) using hourly meteorological data from 2015 to 2024, adjusted to 100 m above ground level through logarithmic and power law wind profile models. The analysis included wind speed, bathymetry, distance to shore, distance to substation, foundation type, wind power density (WPD), and capacity factor (Cf). Based on these parameters, annual energy generation was estimated, and both capital expenditures (CAPEX) and operational expenditures (OPEX) were calculated, considering the technical and cost differences between fixed and floating foundations. Results show that La Guajira combines excellent wind conditions (WPD of 796 W/m2 and Cf of 61.5%) with favorable construction feasibility (bathymetry of −32 m), resulting in the lowest CAPEX among the studied regions. In contrast, Magdalena and Atlántico, with bathymetries exceeding 200 m, require floating foundations that more than double the investment costs. Bolívar presents an intermediate profile, offering solid wind potential and fixed foundation feasibility at a moderate cost. The findings confirm that offshore wind project viability depends not only on wind resource quality but also on physical site constraints, which directly influence the cost structure and energy yield. This integrated approach supports more accurate project prioritization and contributes to strategic planning for the sustainable deployment of offshore wind energy in Colombia.