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.

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.

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.

Key Points: • Machine learning (ML) helps model the interaction between clouds and climate using large datasets. • We review physics-guided/explainable ML applied to cloud-related processes in the climate system. • We also provide a guide to scientists who would like to get started with ML. Abstract: Machine learning (ML) algorithms are powerful tools to build models of clouds and climate that are more faithful to the rapidly-increasing volumes of Earth system data than commonly-used semiempirical models. Here, we review ML tools, including interpretable and physics-guided ML, and outline how they can be applied to cloud-related processes in the climate system, including radiation, microphysics, convection, and cloud detection , classification, emulation, and uncertainty quantification. We additionally provide a short guide to get started with ML and survey the frontiers of ML for clouds and climate .

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.

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.

This introductory chapter discusses the atmospheric subgrid processes ─ collectively called "fast 11 physics" or "fast processes", and their parameterizations in large scale atmospheric models. It 12 presents a brief historical progression of the parameterization of fast processes in numerical 13 models. Despite great efforts and notable advances in understanding, progress in improving fast 14 physics parameterizations has been frustratingly slow, the underlying reasons for which are 15 explored. To guide readers, this chapter describes the main objectives and scope of this book and 16 summarizes each chapter. 

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.

Preface Many physical processes that influence Earth's climate and weather occur on spatial (temporal) scales smaller (shorter) than typical grid sizes (time steps) of general circulation models, and thus must be parameterized. Computer models are essential tools for understanding atmospheric phenomena and for making accurate predictions of any changes in the Earth's climate, weather, and resources of renewable energy resulting from anthropogenic activities that generate greenhouse gases and particulates into the atmosphere. This book focuses on the atmospheric subgrid processes ─ collectively called fast physics ─by reviewing and synthesizing relevant physical understanding, parameterization developments, various measurement technologies, and model evaluation framework. The publication is divided into three parts, containing seventeen chapters (Chapters 2-17) to reflect and synthesize the multiple aspects involved. The first chapter briefly introduces the historical development of fast physics parameterizations and the involved complexities; the last chapter summarizes emerging challenges, new opportunities and future research directions. Part I deals with major subgrid processes, with eight chapters (Chapters 2-9) each covering different processes more or less in the conventional compartmentalized format with an emphasis on individual processes, including but, not limited to radiative transfer, aerosols, and aerosol direct & indirect effects, entrainment-mixing processes, their microphysical influences, convection & convective clouds, stratiform clouds such as stratus and stratocumulus clouds, planetary boundary layer processes, land surface and interactions with atmosphere, and gravity waves. On top of the conventional treatments, some promising ideas/approaches have recently emerged to unify the treatment of individual processes and thus allows for consideration of process interactions. Part II is devoted to such unifying efforts, with four chapters (Chapters 10-13) covering four different endeavors: the unifying parameterizations based on assumed probability density functions; the EDMF approach that combines the Eddy Diffusivity and Mass Flux approaches to unify turbulence and convection; application of machine learning techniques; and innovative top-down attempts that consider the involved totality by borrowing ideas from systems theory, statistical physics, and non-linear sciences. Part III (Chapters 14-17) is devoted to assessments, model evaluation, and model-measurement integration, with four chapters that focus on satellite and airborne remote sensing measurements, surface-based remote sensing measurements, in-situ and laboratory measurements, and model evaluation, and model-measurement integration, respectively.

Convergent orogens are typically linear with laterally continuous, orogen-parallel folds and thrusts. Over the years, geoscience research has revealed evidence for important orthogonal/cross structures as well as lateral heterogeneity in deformation style, igneous activity, metamorphic grade, geomorphology, and seismic activity. To assess the occurrence, causal mechanisms, and implications of these lateral heterogeneities, a selection of convergent orogens, with different tectonic settings and history are reviewed. The Appalachians, the North American Cordillera, the Alps, the Himalayas, the Zagros, the Andes, and several other belts all exhibit a degree of lateral heterogeneity. Major factors driving the lateral heterogeneity and/or cross structures include the pre-existing deformational history of the cratonic blocks involved, lateral change in lithology of crustal rocks, variations in crustal/lithospheric rheologic properties, or changes in plate kinematics. The Appalachian orogenic front mimics the Iapetan rift margin. Pre-existing basement structures have control on pre- and syn-orogenic sedimentation, which subsequently impacts how an orogenic wedge evolves. A thicker sedimentary column generally evolves into a salient (as opposed to a recess), which is further enhanced by the presence of weak horizons as seen in the Zagros and the Cordillera. Lateral variation in sedimentary facies also creates changes in thrust-ramp geometry. During orogenic contraction, inherited basement structures can be preferentially reactivated based on their orientation. Several cross faults in the Himalayas spatially coincide with orogen-perpendicular, lower plate, basement structures. In a similar way, oceanic subducting plate physiography can also influence deformation in the overriding plate. Along-strike variations in subduction dynamics have been reflected in the Andean deformation. Orogenic extension in the Alps has been accompanied by a system of orogen-parallel strike slip faults and extensional cross faults. It is evident that lateral heterogeneities can form crucial control on the evolution of orogenic belts and can influence seismic rupture patterns, resource occurrence, and landslide-related natural hazards.

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.

Compressional and contractional tectonics are of interest to various researchers, from rock mechanics and engineering to those studying the hazards, dynamics, and evolution of plate boundaries. We summarize here the terminology regarding deformation associated with compressional and contractional tectonics. We describe the now largely discarded geosyncline theory, which has its roots in contraction. Today, plate tectonics is the primary theory for explaining the processes shaping the Earth, including earthquakes, volcanoes, and mountain ranges. We emphasize the importance of subduction zones, the most extensive recycling system on the planet, and suture zones, complex boundaries marking the collision zone between two plates. The effects and hazards associated with convergent and collisional plate boundaries are felt far afield and for long distances.

Magmas readily react with their surroundings, which may be other magmas or solid rocks. Such reactions are important in the chemical and physical evolution of magmatic systems and the crust, for example, in inducing volcanic eruptions and in the formation of ore deposits. In this contribution, we conceptually distinguish assimilation from other modes of magmatic interaction and discuss and review a range of geochemical (+/- thermodynamical) models used to model assimilation. We define assimilation in its simplest form as an end-member mode of magmatic interaction in which an initial state (t0) that includes a system of melt and solid wallrock evolves to a later state (tn) where the two entities have been homogenized. In complex natural systems, assimilation can refer more broadly to a process where a mass of magma wholly or partially homogenizes with materials derived from wallrock that initially behaves as a solid. The first geochemical models of assimilation used binary mixing equations and then evolved to incorporate mass balance between a constant-composition assimilant and magma undergoing simultaneous fractional crystallization. More recent tools incorporate energy and mass conservation in order to simulate changing magma composition as wallrock undergoes partial melting. For example, the Magma Chamber Simulator utilizes thermodynamic constraints to document the phase equilibria and major element, trace element, and isotopic evolution of an assimilating and crystallizing magma body. Such thermodynamic considerations are prerequisite for understanding the importance and thermochemical consequences of assimilation in nature, and confirm that bulk assimilation of large amounts of solid wallrock is limited by the enthalpy available from the crystallizing resident magma. Nevertheless, the geochemical signatures of magmatic systems-although dominated for some elements (particularly major elements) by crystallization processes-may be influenced by simultaneous assimilation of partial melts of compositionally distinct wallrock.

In its three-dimensional (3-D) characterization, drought is approached as an event whose spatial extent changes over time. Each drought event has an onset and end time, a location, a magnitude, and a spatial trajectory. These characteristics help to analyze and describe how drought develops in space and time, i.e., drought dynamics. Methodologies for 3-D characterization of drought include a 3-D clustering technique to extract the drought events from the hydrometeorological data. The application of the clustering method yields small ‘artifact’ droughts. These small clusters are removed from the analysis with the use of a cluster size filter. However, according to the literature, the filter parameters are usually set arbitrarily, so this study concentrated on a method to calculate the optimal cluster size filter for the 3-D characterization of drought. The effect of different drought indicator thresholds to calculate drought is also analyzed. The approach was tested in South America with data from the Latin American Flood and Drought Monitor (LAFDM) for 1950–2017. Analysis of the spatial trajectories and characteristics of the most extreme droughts is also included. Calculated droughts are compared with information reported at a country scale and a reasonably good match is found.

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.