Biomass burning has shaped many of the ecosystems of the planet and for millennia humans have used it as a tool to manage the environment. When widespread fires occur, the health and daily lives of millions of people can be affected by the smoke, often at unhealthy to hazardous levels leading to a range of short-term and long-term health consequences such as respiratory issues, cardiovascular issues, and mortality. It is critical to adequately represent and include smoke and its consequences in atmospheric modeling systems to meet needs such as addressing the global climate carbon budget and informing and protecting the public during smoke episodes. Many scientific and technical challenges are associated with modeling the complex phenomenon of smoke. Variability in fire emissions estimates has an order of magnitude level of uncertainty, depending upon vegetation type, natural fuel heterogeneity, and fuel combustion processes. Quantifying fire emissions also vary from ground/vegetation-based methods to those based on remotely sensed fire radiative power data. These emission estimates are input into dispersion and air quality modeling systems, where their vertical allocation associated with plume rise, and temporal release parameterizations influence transport patterns, and, in turn affect chemical transformation and interaction with other sources. These processes lend another order of magnitude of variability to the downwind estimates of trace gases and aerosol concentrations. This chapter profiles many of the global and regional smoke prediction systems currently operational or quasi-operational in real time or near-real time. It is not an exhaustive list of systems, but rather is a profile of many of the systems in use to give examples of the creativity and complexity needed to simulate the phenomenon of smoke. This chapter, and the systems described, reflect the needs of different agencies and regions, where the various systems are tailored to the best available science to address challenges of a region. Smoke forecasting requirements range from warning and informing the public about potential smoke impacts to planning burn activities for hazard reduction or resource benefit. Different agencies also have different mandates, and the lines blur between the missions of quasi-operational organizations (e.g. research institutions) and agencies with operational mandates. The global smoke prediction systems are advanced, and many are self-organizing into a powerful ensemble, as discussed in section 2. Regional and national systems are being developed independently and are discussed in sections 3-5 for Europe (11 systems), North America (7 systems), and Australia (3 systems). Finally, the World Meteorological Organization (WMO) effort (section 6) is bringing together global and regional systems and building the Vegetation Fire and Smoke Pollution Advisory and Assessment Systems (VFSP-WAS) to support countries with smoke issues and who lack resources.
Water quality in rivers is influenced by natural factors and human activities that interact in complex and nonlinear ways, which make water quality modelling a challenging task. The concepts of complex networks (CN), a recent development in network theory, seem to provide new avenues to unravel the connections and dynamics of water quality phenomenon, including clandestine teleconnections. This study aims to explore the spatial patterns of water quality using the CN concepts, at both catchment scale and larger national scale. Three major water quality parameters, i.e. dissolved oxygen (DO), permanganate index (COD Mn), and ammonia nitrogen (NH 3-N) are considered for analysis. Weekly data over a period of 12 years (since 2006) from 91 monitoring stations across China are analysed. Degree centrality and clustering coefficient methods are employed. The results show that the degree centrality and clustering coefficients values for water quality indicators is DO > NH 3-N > COD Mn at both basin scale and national scale. Since COD Mn is more sensitive to the upstream point source pollution, as it depends upon the locality and human activities, it leads to a higher heterogeneity of CN indexes even among spatially closer stations. NH 3-N comes next due to the identical pollution level and degradation process in a certain spatial extension. Meanwhile, DO shows good regional connectivity in line with the strong diffusivity. However, the CN characteristic is relatively inconspicuous in large basins and nationwide scale, which indicates the regional impact on water quality fluctuation and CN analysis. These original findings boost a comprehensive understanding of water quality dynamics and enlighten novel methods for environment system analysis and watershed management.
Tethyan evolution is characterized by cyclical continent-transfer from Gondwana to the continents in the Northern Hemisphere, similar to a “one-way” train. Subduction has been viewed as the primary driver of transference. Therefore, it is crucial to understand the tectonic evolution of all past subduction zones that occurred along Eurasia’s southern margin. We studied the earliest known eclogite located at the Neo-Tethyan suture in the Iranian segment. A prograde-E-MORB-like eclogite reached a peak metamorphic condition of 2.2 GPa and 560°C, at 190 ± 11 Ma (1 rutile U-Pb ages), which constrains the youngest age for subduction initiation of the Neo-Tethyan slab. Combined with regional magmatic and structural data, the oldest age for Neo-Tethys subduction initiation is 210–192 Ma, which is younger than the Paleo-Tethyan closure time of 228–209 Ma. These data, used with previous numerical modeling, supports collision-induced subduction initiation. The collision-induced force, together with the Paleo-Tethyan subduction driven-mantle flow, is likely to have exploited weak inherited structures from earlier Neo-Tethyan rifting, resulting in a northward directed subduction zone along the southern margin of Central Iran Block.
Finding optimum balances between conflicting interests in multipurpose reservoirs often represents an important challenge for decision makers. This study assesses the use of different computational tools to obtain optimal reservoir operations applied to the Hatillo dam in the Dominican Republic. A multiobjective optimization approach is used, in which non-dominated sorting genetic algorithm II (NSGAII) and multi-objective evolutionary algorithm based on decomposition (MOEA/D) optimizers are applied to models that simulate reservoir operations. Three different Machine Learning (ML) models, namely, the multilayer perceptron (MLP), the radial basis network (RBN) and the linear function (LF), are employed to learn the current operation of the system. Subsequently, a general model is proposed to simulate daily reservoir operations (2009-2019), integrating water balances, physical constraints of the dam components and the ML models, the latter defining daily controlled discharges. In the optimization process, the ML parameters are the decision variables, while the objectives evaluated are irrigation, hydropower generation and flood control. The results are compared with the actual operation of the reservoir. Three dimensional Pareto fronts are obtained, from which, the wide variety of operations can be evidenced. The flood control objective was found to have a wide room for improvement over the current operation of the reservoir, and several of the solutions found improve the current operation for the three proposed objectives. The MLP models tend to generate the best results for this case study and the NSGAII optimizer generates the best optimization results.
Skillful forecasts of weather phenomena in numerical models begin with the most accurate set of initial conditions achievable from observational datasets. The process of combining observations with numerical model predictions is called data assimilation. This chapter describes the types of observations available for data assimilation in models that predict the transport, fate, and impacts of smoke pollution. Observation properties needed for effective data assimilation are identified based on experiences with a variety of observation types in data assimilation experiments, compiled from the published literature. The second half of the chapter surveys the data assimilation methodologies that have been applied to smoke aerosols, and describes specific problems associated with the smoke observations that require innovative techniques in data assimilation. The chapter concludes by providing an outlook for future research and development in data assimilation for smoke prediction models. Data assimilation for prediction of smoke is an emerging area of development that promises to greatly improve forecast skill as new datasets and techniques are applied.
This chapter discusses the sounds emitted by gas bubbles when they are generated underwater. Here we define bubbles to be volumes of gas, surrounded by liquid (here, taken to be water), having surface tension forces (the so-called Laplace pressure) generated by a single wall, and so are distinguished from the soap bubbles familiar in children’s games, where the volume of gas is surrounded by two gas/liquid boundaries1. In comparison with other acoustic sources, such as marine mammals, ships and tectonic events, a single bubble may seem insignificant. Indeed, without ideal conditions it can be difficult to observe the sound of a single bubble from a distance of more than a few tens of centimetres. However, natural processes rarely produce single bubbles, and in fact can generate them in their millions at which point the sound generation is significant. With the formation of bubbles as a result of gas seeps, rainfall and breaking waves being a major component of ambient noise in the marine environment and can even alter the propagation of sound waves from other sources. This chapter focuses on the passive emissions of bubbles as they are formed, released, or injected into water, and here the volume pulsations are linear. In this chapter we will discuss the mechanics behind an individual bubble’s acoustic signature, in particular the Minnaert equation and other relevant properties, before discussing the formation of bubbles from subsurface gas migration, rainfall and wave action, characterizing the acoustic nature of each process. The primary focus will be on the sound resulting from bubble generation from each of these sources. A number of different units are used to define each acoustic source, while this may appear confusing and make direct comparison difficult, this is done to be consistent with the literature. The topics covered here are broad, so the approach taken is to summarise the key principles and state of the field, while providing substantial linkage to the literature.
With wildfires increasing in activity in the Western United States and around the world, there is an immediate need to understand the toxic effects of the smoke. This chapter will provide a background of toxicology and apply principle concepts such as dose, duration and frequency to help define the potential effects of smoke exposure. Characteristics that influence toxicity will be discussed, which include particle size, source and temperature and the mixture of chemical constituents. An overview of the routes of exposure, mechanisms of action, toxicokinetics and the role of the immune system will all be covered. The importance and mutual benefits of in vitro, ex vivo and in vivo studies will be discussed. Finally, the chapter concludes by outlining knowledge gaps and research needs.
This chapter discusses efforts to measure surface observations of air pollution at the country-scale. The countries with the most comprehensive regulatory systems to monitor air pollution are the older industrial nations such as countries in the United Kingdom and the United States. Recent proliferation of low-cost air quality monitors (LCAQM) are making near-real-time air pollution monitoring more prevalent across the globe. While unique challenges exist between regulatory and LCAQM data access and usability, there are common challenges in using these data for decision support and research applications. This chapter discusses common statistical methods for estimating air pollution including spatial interpolation methods, statistical regression methods, machine learning, and chemical transport modeling.
A variety of smoke model frameworks are used to simulate smoke for research and forecast applications. Here, a comprehensive summary is provided which covers the many different smoke models that are available, while simultaneously highlighting some of the strengths and weaknesses of each model, along with the uncertainties surrounding each of these frameworks. This review also provides an in-depth discussion on coupled wildfire-atmosphere models, which is a relatively newer smoke modeling tool not previously discussed in other review papers. Key processes related to smoke transport and dispersion, such as the wildfire plume rise, are also discussed in length. This review wraps up with a discussion of future smoke modeling needs and potential new research directions for smoke transport and dispersion models.
The Gulf of Mexico is a prolific petroleum basin with more than a century-long exploration history. Tectonic models proposed for the basin vary dramatically in many aspects, ranging from the pre-rift locations of the crustal blocks, the timing of the break-up to even the order of tectonic events. The reason for these disagreements is in a thick and complex overburden that obscures seismic imaging of crustal structures. To overcome that, we integrated seismic data with gravity and magnetic fields to determine the crustal architecture in different parts of the basin, as well as to map the location of the key tectonic features. The subsequent spatial analysis of potential fields allowed us to trace the tectonic structures outside of seismic coverage. As a result, a set of new geological constraints was derived including the Triassic rifts, regions of Seaward Dipping Reflectors (SDR), and Jurassic pre-salt sedimentary basins in the eastern Gulf of Mexico and along the Yucatan margin, and two distinct crustal zones in the oceanic domain. We ensure the pre-breakup alignment of the crustal blocks based on the mapped geological features on the conjugate margins. Our tectonic reconstruction takes into account an apparent temporal variability of the magmatic regime during basin formation that ranged from CAMP (~200 Ma) to an ultra-slow amagmatic spreading during the initial stage of the GoM opening (~ 165 Ma). Our reconstruction also includes a major ridge reorganization (~ 152 Ma) associated with increased magmatic supply. This second phase of oceanic spreading ceased at early Cretaceous (~ 135 Ma) based on published correlation analysis of seismic and well data. Overall, the tectonic reconstruction presented here takes into account previously known and newly derived geological constraints and integrates various geophysical datasets, namely seismic, gravity, and magnetics.
Given the increasing global demand for rare earth elements (REE), prospects for REE recovery from both traditional and non-traditional sources have been a focus of intense interest. Many have noted the need for ecologically sustainable alternatives to conventional pyrometallurgical and hydrometallurgical methods to recover REE. Among the newer approaches that have garnered recent interest are those that rely on microbiological processes or microbiologically produced reagents to recover the rare earths. Biological approaches can often avoid many of the environmental and or safety hazards associated with the corrosive (e.g., strong acids) or toxic chemicals (e.g., organic solvents) often used in hydrometallurgy as well as costs related to the high energy, reagent and capital requirements and potential air emissions associated with pyrometallurgy. Microbial processes are considered environmentally friendly because they are “natural”, although opportunities also exist to improve on native capabilities by the application of synthetic biology. In this chapter we will focus on some important factors that have not been as widely discussed but which should be considered in planning actual deployment of biological approaches for recovery and purification of rare earths, drawing on some of our own experience for examples. In particular we will focus on geochemical and biogeochemical constraints posed by the feedstocks from which REE may be extracted, for both bioleaching and biosorption, and point out the importance of aqueous equilibrium modeling as a tool for interpreting results and supporting design of biological recovery methods. We will also discuss some important cost factors for REE recovery that are specific to biological processes.
Coal fly ash has long been considered a potential resource for recovery of valuable elements, such as rare earth elements (REE), which are retained and concentrated upon combustion of coal feedstocks. Understanding REE occurrence within fly ash is a key to developing possible recovery methods. Recent results using modern analytical approaches shed light on the distribution REE in fly ash and the approaches required for their recovery. Some of the highest REE contents occur in fly ash derived from U.S. Appalachian Basin coals, and among these, coals influenced by input volcanic ash (Fire Clay coal, Kentucky) are especially enriched. Leaching studies of bulk fly ash show that, as a proportion of the total REE present, samples from eastern U.S. coals are generally less readily extractible than fly ash derived from western U.S. coals having lower REE contents. Direct determinations by ion microprobe show that REE in a range of fly ash samples are partitioned into aluminosilicate glasses formed during melting at boiler temperatures. These glasses comprise the largest mass fraction of coal fly ash. REE-enriched domains are present locally in fly ash at the nanometer scale (as shown by TEM), and these REE coexist with the glass phase. To enable systematic study of these REE, Ce has been proposed as a proxy for the trivalent lanthanides, as supported by speciation determinations demonstrating that Ce occurs in the trivalent form in fly ash. Despite a decreasing proportion of coal use for electric power generation in the U.S. and elsewhere, annual fly ash production, combined with coal ash already in storage, make up a large resource for potential recovery of rare earths and associated critical elements. Further developments in extraction technologies are needed to overcome difficulties in REE concentration and purification to produce REE materials of saleable purity derived from coal ash.
Changes in precipitation extremes remain a key uncertainty as the climate warms. Improved understanding of their evolution is crucial for effective water management. A number of studies have demonstrated various scaling relationships between precipitation extremes and several different environmental variables. In this chapter, we review recent important advances in two of these relationships primarily based on observations: The scaling of precipitation extremes with surface temperature (both air temperature and dew point temperature) and convective available potential energy (CAPE). Two up-to-date global daily datasets are also used to provide a further check on the generality of earlier findings. Known scaling relationships are used to quantify the impacts of these two factors on precipitation extremes. Results show that both of them play important roles, but their impacts vary over different regions on various time scales, highlighting the challenges of constructing global relationships to explain the changing nature of precipitation extremes.
Health outcomes attributable to wildfire smoke pollution exposure are an increasingly important global health issue especially as wildfires are increasing in frequency and intensity with climate change. In this chapter, we present an up-to-date overview of the literature regarding the health consequences of wildfire smoke pollution exposure experienced by adults, identify research gaps, and propose possible areas for future epidemiological studies. We also discuss existing interventions to reduce the negative health outcomes associated with wildfire smoke pollution exposure.
Fragments of former oceans are commonly observed in mountain belts: blueschists and eclogites, on the one hand, and ophiolites, on the other hand, are all that remains of ancient oceanic lithosphere. Though volumetrically subordinate, they provide essential insights into past geodynamics and into the processes involved in the formation and destruction of oceanic lithosphere. This contribution apprehends these two types of oceanic fragments jointly and shows the advantage of doing so for understanding the dynamics of oceanic convergence, i.e. subduction and obduction. We examine the intimate relationships between blueschists/eclogites and ophiolites, as well as the similarities and differences in the mechanisms leading to their preservation. While the extensive, unmetamorphosed true ophiolites markedly differ from fragments of oceanic lithosphere offscraped from the slab during subduction, at shallow or great depths, both types record the mechanical behavior and ‘hiccups’ of the subduction plate boundary. Their preservation also highlights the importance of the evolution of the subduction regime through time, from the onset of intra-oceanic subduction to the cessation of continental subduction.
The tectonic development of the Southeast Anatolian Orogenic Belt (SAOB) is closely related to the demise of the NeoTethys Ocean, which was located between the Arabian and Eurasian plates from the late Cretaceous to Late Miocene. The ocean contained several continental slivers and intra-oceanic magmatic arcs. The continental slivers represent narrow tectonic belts rifted off and drifted away from the Arabian Plate while the NeoTethyan Ocean and the back-arc basins were opened. Later they collided with one another during the branches of the oceans were eliminated. In these periods, the continental slivers were involved in the subduction zone and turned into metamorphic massifs. During the Late Cretaceous, the first collision occurred when an accretionary complex was thrust over the Arabian Plate’s leading edge. Despite the collision, the ocean survived in the North and Its northward subduction generated a new intra oceanic arc, which collided later with the northerly located continental slivers. In this period, the metamorphic massifs and the intra-oceanic arc front migrated to the South. The new magmatic arc collided with the southerly transported nappe package during the Late Eocene. The amalgamated nappe pile eventually obducted onto the Arabian Plate during the Late Miocene. The collision produced escape structures during the Neotectonic period.
The East Anatolian High Plateau, part of the Alpine-Himalayan orogen, is a 200 km wide, approximately E-W trending belt surrounded by two peripheral mountains of the Anatolian Peninsula. The plateau is covered by a thick, interbedded Neogene volcanic and sedimentary rocks. Outcrops of the underlying rocks are rare. Therefore, contrasting views were proposed on the nature of the basement rocks. New geological and geophysical data suggest the presence of an ophiolitic mélange-accretionary complex under cover rocks of Eastern Anatolia. The cover units began to be deposited during the closure of the NeoTethyan Ocean that was located between the Pontide arc to the north, and the continental slivers drifted away from the Arabian Plate to the south. The surrounding orogenic belts experienced different orogenic evolution. The Eastern Anatolian orogen was formed during the later stages of the development of the surrounding orogenic belts. In this period, the melange-accretionary prism that occupied a large terrain behaved like a wide and thick cushion, which did not allow a head-on collision of the bordering continents. NeoTethyan oceanic lithosphere was eliminated from entire eastern Turkey by the Late Eocene. The eastern Anatolia began to rise when the northern advance of the Arabian Plate continued after the total demise of the oceanic lithosphere. The present stage of the elevation of the East Anatolian Plateau as a coherent block started during the Late Miocene.