Ecosystem Response to Climatic Change: The Importance of the Cold Season

Winter climate and snow cover are the important drivers of plant community development in polar regions. However, the impacts of changing winter climate and associated changes in snow regime have received much less attention than changes during summer. Here, we synthesize the results from studies on the impacts of extreme winter weather events on polar heathland and lichen communities. Dwarf shrubs, mosses and soil arthropods were negatively impacted by extreme warming events while lichens showed variable responses to changes in extreme winter weather events. Snow mould formation underneath the snow may contribute to spatial heterogeneity in plant growth, arthropod communities and carbon cycling. Winter snow cover and depth will drive the reported impacts of winter climate change and add to spatial patterns in vegetation heterogeneity. The challenges ahead lie in obtaining better predictions on the snow patterns across the landscape and how these will be altered due to winter climate change.     

Ecosystem response to climatic change: the importance of the cold season

Winter climate and snow cover are the important drivers of plant community development in polar regions. However, the impacts of changing winter climate and associated changes in snow regime have received much less attention than changes during summer. Here, we synthesize the results from studies on the impacts of extreme winter weather events on polar heathland and lichen communities. Dwarf shrubs, mosses and soil arthropods were negatively impacted by extreme warming events while lichens showed variable responses to changes in extreme winter weather events. Snow mould formation underneath the snow may contribute to spatial heterogeneity in plant growth, arthropod communities and carbon cycling. Winter snow cover and depth will drive the reported impacts of winter climate change and add to spatial patterns in vegetation heterogeneity. The challenges ahead lie in obtaining better predictions on the snow patterns across the landscape and how these will be altered due to winter climate change.     

Changes in weather and climate extremes: State of knowledge relevant to air and water quality in the United States

Air and water quality are impacted by extreme weather and climate events on time scales ranging from minutes to many months. This review paper discusses the state of knowledge of how and why extreme events are changing and are projected to change in the future. These events include heat waves, cold waves, floods, droughts, hurricanes, strong extratropical cyclones such as nor'easters, heavy rain, and major snowfalls. Some of these events, such as heat waves, are projected to increase, while others, with cold waves being a good example, will decrease in intensity in our warming world. Each extreme's impact on air or water quality can be complex and can even vary over the course of the event.

Implications:

Because extreme weather and climate events impact air and water quality, understanding how the various extremes are changing and are projected to change in the future has ramifications on air and water quality management.     

Changes in extreme events and the potential impacts on human health

Extreme weather and climate-related events affect human health by causing death, injury, and illness, as well as having large socioeconomic impacts. Climate change has caused changes in extreme event frequency, intensity, and geographic distribution, and will continue to be a driver for change in the future. Some of these events include heat waves, droughts, wildfires, dust storms, flooding rains, coastal flooding, storm surges, and hurricanes. The pathways connecting extreme events to health outcomes and economic losses can be diverse and complex. The difficulty in predicting these relationships comes from the local societal and environmental factors that affect disease burden. More information is needed about the impacts of climate change on public health and economies to effectively plan for and adapt to climate change. This paper describes some of the ways extreme events are changing and provides examples of the potential impacts on human health and infrastructure. It also identifies key research gaps to be addressed to improve the resilience of public health to extreme events in the future.

Implications: Extreme weather and climate events affect human health by causing death, injury, and illness, as well as having large socioeconomic impacts. Climate change has caused changes in extreme event frequency, intensity, and geographic distribution, and will continue to be a driver for change in the future. Some of these events include heat waves, droughts, wildfires, flooding rains, coastal flooding, surges, and hurricanes. The pathways connecting extreme events to health outcomes and economic losses can be diverse and complex. The difficulty in predicting these relationships comes from the local societal and environmental factors that affect disease burden.     

Extending the Kolmogorov-Zurbenko filter: application to ozone, particulate matter, and meteorological trends

Tropospheric ozone (O3) and particulate matter (PM) are pollutants of great concern to air quality managers. Federal standards for these pollutants have been promulgated in recent years because of the known adverse effects of the pollutants on human health, the environment, and visibility. Local meteorological conditions exert a strong influence over day-to-day variations in pollutant concentrations; therefore, the meteorological signal must be removed in order for air quality planners and managers to examine underlying emissions-related trends and make better air quality management decisions for the future. Although the Kolmogorov-Zurbenko (KZ) filter has been widely used for this type of trend separation in O3 studies in the eastern United States, this article aims to extend the method in three key ways. First, whereas the KZ filter is known as a useful tool for O3 analysis, this study also evaluates its effectiveness when applied to PM. Second, the method was applied to Tucson, AZ, a city in the semi-arid southwestern United States (Southwest), to evaluate the appropriateness of the method in a region with weaker synoptic weather controls on air quality than the eastern United States. Third, additional forms of output were developed and tailored to be more applicable to decision-makers' needs through a partnership between academic researchers and air quality planners and managers. Results of the study indicate that the KZ filter is a useful method for examining emissions-related PM trends, resulting in small, but potentially significant, differences after adjustment. For the Tucson situation with weaker synoptic controls, the KZ method identified mixing height as a more important variable than has been found in other cities.     

Development of risk-based air quality management strategies under impacts of climate change

Climate change is forecast to adversely affect air quality through perturbations in meteorological conditions, photochemical reactions, and precursor emissions. To protect the environment and human health from air pollution, there is an increasing recognition of the necessity of developing effective air quality management strategies under the impacts of climate change. This paper presents a framework for developing risk-based air quality management strategies that can help policy makers improve their decision-making processes in response to current and future climate change about 30-50 years from now. Development of air quality management strategies under the impacts of climate change is fundamentally a risk assessment and risk management process involving four steps: (1) assessment of the impacts of climate change and associated uncertainties; (2) determination of air quality targets; (3) selections of potential air quality management options; and (4) identification of preferred air quality management strategies that minimize control costs, maximize benefits, or limit the adverse effects of climate change on air quality when considering the scarcity of resources. The main challenge relates to the level of uncertainties associated with climate change forecasts and advancements in future control measures, since they will significantly affect the risk assessment results and development of effective air quality management plans. The concept presented in this paper can help decision makers make appropriate responses to climate change, since it provides an integrated approach for climate risk assessment and management when developing air quality management strategies. Implications: Development of climate-responsive air quality management strategies is fundamentally a risk assessment and risk management process. The risk assessment process includes quantification of climate change impacts on air quality and associated uncertainties. Risk management for air quality under the impacts of climate change includes determination of air quality targets, selections of potential management options, and identification of effective air quality management strategies through decision-making models. The risk-based decision-making framework can also be applied to develop climate-responsive management strategies for the other environmental dimensions and assess costs and benefits of future environmental management policies.     

Future Impacts of Distributed Power Generation on Ambient Ozone and Particulate Matter Concentrations in the San Joaquin Valley of California

ABSTRACT

Distributed power generation—electricity generation that is produced by many small stationary power generators distributed throughout an urban air basin—has the potential to supply a significant portion of electricity in future years. As a result, distributed generation may lead to increased pollutant emissions within an urban air basin, which could adversely affect air quality. However, the use of combined heating and power with distributed generation may reduce the energy consumption for space heating and air conditioning, resulting in a net decrease of pollutant and greenhouse gas emissions. This work used a systematic approach based on land-use geographical information system data to determine the spatial and temporal distribution of distributed generation emissions in the San Joaquin Valley Air Basin of California and simulated the potential air quality impacts using state-of-the-art three-dimensional computer models. The evaluation of the potential market penetration of distributed generation focuses on the year 2023. In general, the air quality impacts of distributed generation were found to be small due to the restrictive 2007 California Air Resources Board air emission standards applied to all distributed generation units and due to the use of combined heating and power. Results suggest that if distributed generation units were allowed to emit at the current Best Available Control Technology standards (which are less restrictive than the 2007 California Air Resources Board standards), air quality impacts of distributed generation could compromise compliance with the federal 8-hr average ozone standard in the region.

IMPLICATIONS The San Joaquin Valley is a fast growing region that demands increasing power generation to sustain the economic development, and at the same time it is one of the worst polluted areas in the United States. Hence, the region demands alternatives that minimize the air quality impacts of power generation. This paper addresses the air quality impacts of distributed generation of power, an alternative to central power generation that can potentially reduce greenhouse gas and pollutant emissions throughout the United States.     

Extending the Kolmogorov–Zurbenko Filter: Application to Ozone,Particulate Matter,and Meteorological Trends

Abstract

Tropospheric ozone (O₃) and particulate matter (PM) are pollutants of great concern to air quality managers. Federal standards for these pollutants have been promulgated in recent years because of the known adverse effects of the pollutants on human health, the environment, and visibility. Local meteorological conditions exert a strong influence over day‐to‐day variations in pollutant concentrations; therefore, the meteorological signal must be removed in order for air quality planners and managers to examine underlying emissions-related trends and make better air quality management decisions for the future. Although the Kolmogorov–Zurbenko (KZ) filter has been widely used for this type of trend separation in O₃ studies in the eastern United States, this article aims to extend the method in three key ways. First, whereas the KZ filter is known as a useful tool for O₃ analysis, this study also evaluates its effectiveness when applied to PM. Second, the method was applied to Tucson, AZ, a city in the semi‐arid southwestern United States (Southwest), to evaluate the appropriateness of the method in a region with weaker synoptic weather controls on air quality than the eastern United States. Third, additional forms of output were developed and tailored to be more applicable to decision-makers’ needs through a partnership between academic researchers and air quality planners and managers. Results of the study indicate that the KZ filter is a useful method for examining emissions‐related PM trends, resulting in small, but potentially significant, differences after adjustment. For the Tucson situation with weaker synoptic controls, the KZ method identified mixing height as a more important variable than has been found in other cities.     

Climate forcing by the on-road transportation and power generation sectors

The on-road transportation (ORT) and power generation (PG) sectors are major contributors to carbon dioxide (CO₂) emissions and a host of short-lived radiatively-active air pollutants, including tropospheric ozone and fine aerosol particles, that exert complex influences on global climate. Effective mitigation of global climate change necessitates action in these sectors for which technology change options exist or are being developed. Most assessments of possible energy change options to date have neglected non-CO₂ air pollutant impacts on radiative forcing (RF). In a multi-pollutant approach, we apply a global atmospheric composition-climate model to quantify the total RF from the global and United States (U.S.) ORT and PG sectors. We assess the RF for 2 time horizons: 20- and 100-year that are relevant for understanding near-term and longer-term impacts of climate change, respectively. ORT is a key target sector to mitigate global climate change because the net non-CO₂ RF is positive and acts to enhance considerably the CO₂ warming impacts. We perform further sensitivity studies to assess the RF impacts of a potential major technology shift that would reduce ORT emissions by 50% with the replacement energy supplied either by a clean zero-emissions source (S1) or by the PG sector, which results in an estimated 20% penalty increase in emissions from this sector (S2). We examine cases where the technology shift is applied globally and in the U.S. only. The resultant RF relative to the present day control is negative (cooling) in all cases for both S1 and S2 scenarios, global and U.S. emissions, and 20- and 100-year time horizons. The net non-CO₂ RF is always important relative to the CO₂ RF and outweighs the CO₂ RF response in the S2 scenario for both time horizons. Assessment of the full impacts of technology and policy strategies designed to mitigate global climate change must consider the climate effects of ozone and fine aerosol particles.     

Siberian environmental change: Synthesis of recent studies and opportunities for networking

A recent multidisciplinary compilation of studies on changes in the Siberian environment details how climate is changing faster than most places on Earth with exceptional warming in the north and increased aridity in the south. Impacts of these changes are rapid permafrost thaw and melt of glaciers, increased flooding, extreme weather events leading to sudden changes in biodiversity, increased forest fires, more insect pest outbreaks, and increased emissions of CO₂ and methane. These trends interact with sociological changes leading to land-use change, globalisation of diets, impaired health of Arctic Peoples, and challenges for transport. Local mitigation and adaptation measures are likely to be limited by a range of public perceptions of climate change that vary according to personal background. However, Siberia has the possibility through land surface feedbacks to amplify or suppress climate change impacts at potentially global levels. Based on the diverse studies presented in this Ambio Special Issue, we suggest ways forward for more sustainable environmental research and management.Supplementary InformationThe online version contains supplementary material available at 10.1007/s13280-021-01626-7.     

Enhanced science–stakeholder communication to improve ecosystem model performances for climate change impact assessments

In recent years, climate impact assessments of relevance to the agricultural and forestry sectors have received considerable attention. Current ecosystem models commonly capture the effect of a warmer climate on biomass production, but they rarely sufficiently capture potential losses caused by pests, pathogens and extreme weather events. In addition, alternative management regimes may not be integrated in the models. A way to improve the quality of climate impact assessments is to increase the science–stakeholder collaboration, and in a two-way dialog link empirical experience and impact modelling with policy and strategies for sustainable management. In this paper we give a brief overview of different ecosystem modelling methods, discuss how to include ecological and management aspects, and highlight the importance of science–stakeholder communication. By this, we hope to stimulate a discussion among the science–stakeholder communities on how to quantify the potential for climate change adaptation by improving the realism in the models.     

Modeling to Evaluate Contribution of Oil and Gas Emissions to Air Pollution

Oil and gas production in the Western United States has increased considerably over the past 10 years. While many of the still limited oil and gas impact assessments have focused on potential human health impacts, the typically remote locations of production in the Intermountain West suggests that the impacts of oil and gas production on national parks and wilderness areas (Class I and II areas) could also be important. To evaluate this, we utilize the Comprehensive Air quality Model with Extensions (CAMx) with a year-long modeling episode representing the best available representation of 2011 meteorology and emissions for the Western United States. The model inputs for the 2011 episodes were generated as part of the Three State Air Quality Study (3SAQS). The study includes a detailed assessment of oil and gas (O&G) emissions in Western States. The year-long modeling episode was run both with and without emissions from O&G production. The difference between these two runs provides an estimate of the contribution of the O&G production to air quality. These data were used to assess the contribution of O&G to the 8 hour average ozone concentrations, daily and annual fine particulate concentrations, annual nitrogen deposition totals and visibility in the modeling domain. We present the results for the Class I and II areas in the Western United States. Modeling results suggest that emissions from O&G activity are having a negative impact on air quality and ecosystem health in our National Parks and Class I areas.

Implications: In this research, we use a modeling framework developed for oil and gas evaluation in the western United States to determine the modeled impacts of emissions associated with oil and gas production on air pollution metrics. We show that oil and gas production may have a significant negative impact on air quality and ecosystem health in some national parks and other Class I areas in the western United States. Our findings are of particular interest to federal land managers as well as regulators in states heavy in oil and gas production as they consider control strategies to reduce the impact of development.     

Application of satellite remote-sensing data for source analysis of fine particulate matter transport events

Satellite sensors have provided new datasets for monitoring regional and urban air quality. Satellite sensors provide comprehensive geospatial information on air quality with both qualitative imagery and quantitative data, such as aerosol optical depth. Yet there has been limited application of these new datasets in the study of air pollutant sources relevant to public policy. One promising approach to more directly link satellite sensor data to air quality policy is to integrate satellite sensor data with air quality parameters and models. This paper presents a visualization technique to integrate satellite sensor data, ground-based data, and back trajectory analysis relevant to a new rule concerning the transport of particulate matter across state boundaries. Overlaying satellite aerosol optical depth data and back trajectories in the days leading up to a known fine particulate matter with an aerodynamic diameter of <2.5 microm (PM2.5) event may indicate whether transport or local sources appear to be most responsible for high PM2.5 levels in a certain location at a certain time. Events in five cities in the United States are presented as case studies. This type of analysis can be used to help understand the source locations of pollutants during specific events and to support regulatory compliance decisions in cases of long distance transport.     

Air quality and its possible impacts on the terrestrial ecosystems of the North American Great Plains: an overview

Over the past several decades, numerous studies have been conducted on the impacts of air pollutants (air quality) on terrestrial ecosystems (crops and forests). Although ambient air is always composed of pollutant mixtures, in determining the relative air quality and its ecosystem impacts at a given geographic location and time, a predominant number of studies have shown that at the present time surface-level O(3) is the most important phytotoxic air pollutant. Within the North American Great Plains, the precursors for surface-level O(3) are mainly anthropogenic NO(x) and VOCs (volatile organic compounds). Texas and Alberta are the top regions of such emissions in the United States and Canada, respectively. This appears to be due mainly to the prevalence of natural gas and/or oil industry in the two regions and the consequent urbanization. Nevertheless, the total emissions of NO(x) and VOCs within the North American Great Plains represent only about 25-36% of the corresponding total emissions within the contiguous United States and the whole of Canada. Within the Great Plains many major crop and tree species are known to be sensitive to O(3). This sensitivity assessment, however, is based mainly on our knowledge from univariate (O(3) only) exposure-plant response studies. In the context of global climate change, in almost all similar univariate studies, elevated CO(2) concentrations have produced increases in plant biomass (both crop and tree species). The question remains as to whether this stimulation will offset any adverse effects of elevated surface O(3) concentrations. Future research must address this important issue both for the Great Plains and for all other geographic locations, taking into consideration spatial and temporal variabilities in the ambient concentrations of the two trace gases.     

Questioning complacency: climate change impacts, vulnerability, and adaptation in Norway

Most European assessments of climate change impacts have been carried out on sectors and ecosystems, providing a narrow understanding of what climate change really means for society. Furthermore, the main focus has been on technological adaptations, with less attention paid to the process of climate change adaptation. In this article, we present and analyze findings from recent studies on climate change impacts, vulnerability, and adaptation in Norway, with the aim of identifying the wider social impacts of climate change. Three main lessons can be drawn. First, the potential thresholds and indirect effects may be more important than the direct, sectoral effects. Second, highly sensitive sectors, regions, and communities combine with differential social vulnerability to create both winners and losers. Third, high national levels of adaptive capacity mask the barriers and constraints to adaptation, particularly among those who are most vulnerable to climate change. Based on these results, we question complacency in Norway and other European countries regarding climate change impacts and adaptation. We argue that greater attention needs to be placed on the social context of climate change impacts and on the processes shaping vulnerability and adaptation.     

Megacities and atmospheric pollution

About half of the world's population now lives in urban areas because of the opportunity for a better quality of life. Many of these urban centers are expanding rapidly, leading to the growth of megacities, which are defined as metropolitan areas with populations exceeding 10 million inhabitants. These concentrations of people and activity are exerting increasing stress on the natural environment, with impacts at urban, regional and global levels. In recent decades, air pollution has become one of the most important problems of megacities. Initially, the main air pollutants of concern were sulfur compounds, which were generated mostly by burning coal. Today, photochemical smog--induced primarily from traffic, but also from industrial activities, power generation, and solvents--has become the main source of concern for air quality, while sulfur is still a major problem in many cities of the developing world. Air pollution has serious impacts on public health, causes urban and regional haze, and has the potential to contribute significantly to climate change. Yet, with appropriate planning, megacities can efficiently address their air quality problems through measures such as application of new emission control technologies and development of mass transit systems. This review is focused on nine urban centers, chosen as case studies to assess air quality from distinct perspectives: from cities in the industrialized nations to cities in the developing world. While each city--its problems, resources, and outlook--is unique, the need for a holistic approach to the complex environmental problems is the same. There is no single strategy in reducing air pollution in megacities; a mix of policy measures will be needed to improve air quality. Experience shows that strong political will coupled with public dialog is essential to effectively implement the regulations required to address air quality problems.     

Assessment of the emissions and air quality impacts of biomass and biogas use in California

It is estimated that there is sufficient in-state “technically” recoverable biomass to support nearly 4000 MW of bioelectricity generation capacity. This study assesses the emissions of greenhouse gases and air pollutants and resulting air quality impacts of new and existing bioenergy capacity throughout the state of California, focusing on feedstocks and advanced technologies utilizing biomass resources predominant in each region. The options for bioresources include the production of bioelectricity and renewable natural gas (NG). Emissions of criteria pollutants and greenhouse gases are quantified for a set of scenarios that span the emission factors for power generation and the use of renewable natural gas for vehicle fueling. Emissions are input to the Community Multiscale Air Quality (CMAQ) model to predict regional and statewide temporal air quality impacts from the biopower scenarios. With current technology and at the emission levels of current installations, maximum bioelectricity production could increase nitrogen oxide (NO_x) emissions by 10% in 2020, which would cause increases in ozone and particulate matter concentrations in large areas of California. Technology upgrades would achieve the lowest criteria pollutant emissions. Conversion of biomass to compressed NG (CNG) for vehicles would achieve comparable emission reductions of criteria pollutants and minimize emissions of greenhouse gases (GHG). Air quality modeling of biomass scenarios suggest that applying technological changes and emission controls would minimize the air quality impacts of bioelectricity generation. And a shift from bioelectricity production to CNG production for vehicles would reduce air quality impacts further. From a co-benefits standpoint, CNG production for vehicles appears to provide the best benefits in terms of GHG emissions and air quality.

Implications:?This investigation provides a consistent analysis of air quality impacts and greenhouse gas emissions for scenarios examining increased biomass use. Further work involving economic assessment, seasonal or annual emissions and air quality modeling, and potential exposure analysis would help inform policy makers and industry with respect to further development and direction of biomass policy and bioenergy technology alternatives needed to meet energy and environmental goals in California.     

Increasing the Use of Earth Science Data and Models in Air Quality Management

In 2010, the U.S. National Aeronautics and Space Administration (NASA) initiated the Air Quality Applied Science Team (AQAST) as a 5-year, $17.5-million award with 19 principal investigators. AQAST aims to increase the use of Earth science products in air quality-related research and to help meet air quality managers’ information needs. We conducted a Web-based survey and a limited number of follow-up interviews to investigate federal, state, tribal, and local air quality managers’ perspectives on usefulness of Earth science data and models, and on the impact AQAST has had. The air quality managers we surveyed identified meeting the National Ambient Air Quality Standards for ozone and particulate matter, emissions from mobile sources, and interstate air pollution transport as top challenges in need of improved information. Most survey respondents viewed inadequate coverage or frequency of satellite observations, data uncertainty, and lack of staff time or resources as barriers to increased use of satellite data by their organizations. Managers who have been involved with AQAST indicated that the program has helped build awareness of NASA Earth science products, and assisted their organizations with retrieval and interpretation of satellite data and with application of global chemistry and climate models. AQAST has also helped build a network between researchers and air quality managers with potential for further collaborations.

Implications: NASA’s Air Quality Applied Science Team (AQAST) aims to increase the use of satellite data and global chemistry and climate models for air quality management purposes, by supporting research and tool development projects of interest to both groups. Our survey and interviews of air quality managers indicate they found value in many AQAST projects and particularly appreciated the connections to the research community that the program facilitated. Managers expressed interest in receiving continued support for their organizations’ use of satellite data, including assistance in retrieving and interpreting data from future geostationary platforms meant to provide more frequent coverage for air quality and other applications.     

Application of Satellite Remote-Sensing Data for Source Analysis of Fine Particulate Matter Transport Events

Abstract

Satellite sensors have provided new datasets for monitoring regional and urban air quality. Satellite sensors provide comprehensive geospatial information on air quality with both qualitative imagery and quantitative data, such as aerosol optical depth. Yet there has been limited application of these new datasets in the study of air pollutant sources relevant to public policy. One promising approach to more directly link satellite sensor data to air quality policy is to integrate satellite sensor data with air quality parameters and models. This paper presents a visualization technique to integrate satellite sensor data, ground-based data, and back trajectory analysis relevant to a new rule concerning the transport of particulate matter across state boundaries. Overlaying satellite aerosol optical depth data and back trajectories in the days leading up to a known fine particulate matter with an aerodynamic diameter of <2.5 μm (PM_2.5) event may indicate whether transport or local sources appear to be most responsible for high PM_2.5 levels in a certain location at a certain time. Events in five cities in the United States are presented as case studies. This type of analysis can be used to help understand the source locations of pollutants during specific events and to support regulatory compliance decisions in cases of long distance transport.     

Emissions from oil and gas operations in the United States and their air quality implications

The energy supply infrastructure in the United States has been changing dramatically over the past decade. Increased production of oil and natural gas, particularly from shale resources using horizontal drilling and hydraulic fracturing, made the United States the world’s largest producer of oil and natural gas in 2014. This review examines air quality impacts, specifically, changes in greenhouse gas, criteria air pollutant, and air toxics emissions from oil and gas production activities that are a result of these changes in energy supplies and use. National emission inventories indicate that volatile organic compound (VOC) and nitrogen oxide (NO_x) emissions from oil and gas supply chains in the United States have been increasing significantly, whereas emission inventories for greenhouse gases have seen slight declines over the past decade. These emission inventories are based on counts of equipment and operational activities (activity factors), multiplied by average emission factors, and therefore are subject to uncertainties in these factors. Although uncertainties associated with activity data and missing emission source types can be significant, multiple recent measurement studies indicate that the greatest uncertainties are associated with emission factors. In many source categories, small groups of devices or sites, referred to as super-emitters, contribute a large fraction of emissions. When super-emitters are accounted for, multiple measurement approaches, at multiple scales, produce similar results for estimated emissions. Challenges moving forward include identifying super-emitters and reducing their emission magnitudes. Work done to date suggests that both equipment malfunction and operational practices can be important. Finally, although most of this review focuses on emissions from energy supply infrastructures, the regional air quality implications of some coupled energy production and use scenarios are examined. These case studies suggest that both energy production and use should be considered in assessing air quality implications of changes in energy infrastructures, and that impacts are likely to vary among regions.

Implications: The energy supply infrastructure in the United States has been changing dramatically over the past decade, leading to changes in emissions from oil and natural gas supply chain sources. In many source categories along these supply chains, small groups of devices or sites, referred to as super-emitters, contribute a large fraction of emissions. Effective emission reductions will require technologies for both identifying super-emitters and reducing their emission magnitudes.