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The cement industry is among the top three polluters among all industries and the examination of the nonlinear and cointegration dynamics between cement production and CO 2 emissions has not been explored. Focusing on this research gap, the study employs a novel Markov-switching autoregressive distributed lag (MS-ARDL) model and its generalization to vector error correction, the MS-VARDL model, for regime-dependent causality testing. The new method allows the determination of nonlinear long-run and short-run relations, regime duration, and cement-induced-CO 2 emission cycles in the USA for a historically long dataset covering 1900-2021. Empirical findings point to nonlinearity in all series and nonlinear cointegration between cement production and cement-induced CO 2 emissions. The phases of regimes coincide closely with NBER's official economic cycles for the USA. The second regime, characterized by expansions, lasts twice as long relative to the first, the contractionary regime, which contains severe economic recessions, as well as economic crises, the 1929 Great Depression, the 1973 Oil Crisis, the 2009 Great Recession, and the COVID-19 Shutdown and Wars, including WWI and II. In both regimes, the adverse effects of cement production on CO 2 emissions cannot be rejected with varying degrees both in the long and the short run. Markov regime-switching vector autoregressive distributed lag (MS-VARDL) causality tests confirm unidirectional causality from cement production to CO 2 emissions in both regimes. The traditional Granger causality test produces an over-acceptance of causality in a discussed set of cases. Industry-level policy recommendations include investments to help with the shift to green kiln technologies and energy efficiency. National-level policies on renewable energy and carbon capture are also vital considering the energy consumption of cement production., (© 2024. The Author(s).)

Recently, countries have been making intensive efforts to alleviate the burden on the environment and to make environmental conditions sustainable. In this context, our study aims to investigate the long-term impact of renewable energy consumption (REC) and human capital (HC) by considering the load capacity factor (LCF). We also investigate the long-term impact of economic growth (Y) and non-renewable energy consumption (NREC) on the LCF. In this context, we analyze annual data for the U.S. for the period 1965-2018 using the newly developed augmented ARDL (AARDL) approach. The long-term empirical results show the following. i) Increases in Y negatively affect LCF and deteriorate environmental quality. ii) Increases in NREC negatively affect LCF and accelerate the deterioration of environmental quality. iii) REC has no significant impact on environmental quality. iv) Increases in HC support the improvement of environmental quality. The empirical results show that contrary to expectations, renewable energy consumption does not have a significant impact on environmental quality in the U.S., whereas human capital is an important factor in improving environmental quality. In this context, US policymakers should pave the way for more investment in eco-friendly renewable energy investments and human capital to establish sustainable environmental quality. Policymakers should also take steps to reduce the use of fossil fuels., (© 2024. The Author(s).)

By considering the existence of two separate analysis families and the usage of different data frequencies, this study aims to examine the effect of method choice, data frequency, and sector-based energy consumption on carbon dioxide (CO 2 ) emissions by performing machine learning (ML) algorithms and time series econometric (TS) models simultaneously. In this situation, the study examines the United States (USA), considers sector-based energy consumption indicators as explanatory variables, uses monthly and yearly data between January 1973 and December 2021, estimates CO 2 emissions, and compares the estimation performance of the models. The empirical findings reveal that (i) the ML algorithms outperform the TS models based on R 2 and goodness of fit criteria; (ii) the estimation performance of the models increases with the high-frequency (i.e., monthly) data; (iii) the ML algorithms perform much better in case of high-frequency usage; (iv) some thresholds identify the effects of the sector-based energy consumption indicators on the CO 2 emissions; (v) electric power and transportation sectors are the most important sectors in the estimation of the CO 2 emissions for monthly and yearly data, respectively. Hence, the study provides to help the understanding role of method choice, data frequency, and sector-based energy consumption for the estimation of CO 2 emissions. Based on the results, this study proposes that US policymakers should consider the ML algorithms, use higher-frequency data, and include sector-based energy consumption indicators to have a better estimation of CO 2 emissions., (© 2023. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

Photovoltaic is emerging as a cost-competitive source of energy generation and has experienced a decade of substantial cost decline. Recognizing that innovation in sustainable technologies can substantially contribute to the sustainable generation of energy, the federal government, universities, and industries in the USA have invested considerably in innovative solar technologies involving photovoltaic energy generation. However, the association between innovations in photovoltaic energy generation, distribution, or transmission-related technologies (IPVEGRT) and carbon dioxide emissions is unclear. The present study significantly contributes to energy economics by inspecting the nexus between IPVEGRT and carbon dioxide emissions, renewable energy consumption, the expansionary monetary policy, international collaboration in green technology development, gross domestic product per capita, and trade openness in the USA from 1990Q1 to 2018Q4. The results indicate that IPVEGRT helps reduce carbon dioxide emissions. International collaboration in green technology development and renewable energy consumption was negatively associated with carbon dioxide emissions, while expansionary monetary policy, gross domestic product per capita, and trade openness were positively associated with carbon dioxide emissions. The two-way causality between IPVEGRT and carbon dioxide emissions and between international collaboration in green technology development and carbon dioxide emissions was validated. Finally, a one-way causality between expansionary monetary policy, carbon dioxide emissions, gross domestic product per capita, and carbon dioxide emissions was validated., (© 2022. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

The economic complexity index, which indicates the level of knowledge and skills needed in the production of the exported goods, is a measure of economic development. Some researchers have investigated the validity of the environmental Kuznets curve (EKC) hypothesis by considering the effect of economic complexity on environmental pollution. This study, for the first time, examines the impact of economic complexity, globalization, and renewable and non-renewable energy consumption on both CO 2 emissions and ecological footprint within the framework of the EKC hypothesis in the USA. To this end, the combined cointegration test and three different estimators are utilized for the period from 1980 to 2016. The main finding of the study indicates that the inverted U-shaped EKC relationship between economic complexity and environmental pollution holds for the USA. In addition to this finding, globalization and renewable energy consumption play a dominant role in reducing environmental pollution, while non-renewable energy consumption contributing factor to environmental pressure. Overall, the outcomes indicate that increasing economic complexity helps to minimize environmental degradation after a threshold, and the US government can provide a better environment by using renewable energy sources and globalization. Graphical abstract.

To achieve net-zero emissions by 2050, we need economic means of sequestering carbon dioxide (CO 2 ) and reducing greenhouse gas emissions (GHG). We analyze the sequestration potential of the Intermountain West (I-West) region, US, as a primary energy transition hub through analysis of wellbore retrofit potential and emission reduction in both fugitive gas abatement and flare gas. We selected the I-West region due to its abundant energy sources and oil and gas production legacy. Preliminary analysis hints that well retrofits can breathe new life into a well at a fraction of the cost of a new drill. With millions of potential candidates in the US, even a modest fraction (1% or less) suitable for retrofit could accelerate the shift to large-scale CO 2 sequestration. Fugitive gas, the unintentional release of wellbore gases such as methane, is a significant emissions source. Through conservative analysis, it is estimated that wellhead leakage alone may account for 5 million tonnes of carbon dioxide equivalent (CO 2 e) emissions. We conclude by assessing the CO 2 emissions from flaring, which is the burning of associated gas during well operations, conservative analysis indicates flaring contributes another 2 million tonnes of CO 2 emissions to the region. We find that with targeted retrofit and better controls on emissions sources, the I-West region can make a significant impact in the nation's push to become net-zero. This study outlines economic feasibility and actionable items to achieve the critical reductions in emissions and increases in sequestration necessary to attain net zero., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Published by Elsevier Ltd.)

Consistent with the increasing environmental interest, the clean energy transition is highly critical to achieving decarbonization targets. Also, energy security has become an important topic under the shadow of the energy crisis,. Accordingly, countries have been trying to stimulate clean energy use to preserve the environment and ensure energy security. So, considering the leading role of economic size and volume of energy use, the study examines the USA to define whether energy transition helps decrease energy security risk (ESR) and curb CO 2 emissions. So, the study applies a disaggregated level analysis by performing quantile-based models for the period from 2001/Q1 through 2022/Q4. The results demonstrate that (i) the energy transition index decreases environmental ESR at higher quantiles and reliability ESR at lower and middle quantiles, whereas it is not beneficial in declining economic and geopolitical ESR; (ii) energy transition curbs CO 2 emissions in building and transport sectors at lower quantiles, whereas it does not help decrease CO 2 emissions in industrial and power sectors; (iii) energy transition is mostly ineffective on ESR, whereas it is highly effective in curbing CO 2 emissions in all sectors except for transport across various quantiles as time passes; (iv) the results differ according to the aggregated and disaggregated levels; (v) the results are consistent across main and alternative models. Hence, the study highlights the dominant effect of energy transition in curbing sectoral CO 2 emissions rather than easing ESR. Accordingly, the study discusses various policy implications for the USA., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Ltd. All rights reserved.)

The article reports on the proposal publishing companies to becoming entirely carbon neutral and reduce its carbon emission in the U.S. Hearst Corp. plans to consider the implications for their magazines after the calculation on the amount of carbon dioxide emissions produced in the process of publishing. On the other hand, Time Inc. announced that it had asked their paper suppliers to reduce their greenhouse gas emissions by 20 percent by 2012.

Air-sea carbon dioxide (CO2) fluxes have recently been reported for the US South Atlantic Bight (SAB), a low-latitude shallow continental shelf bordered landward by abundant salt marshes and rivers. In this study, influences of terrestrial inputs on sea surface partial pressure of CO2 (pCO2) in the SAB are quantified. After re- moving pCO2 variations due to the annual temperature cycle and air-sea gas ex- change from the in situ pCO2, temperature and gas exchange corrected (TG-corrected) pCO2 is derived. Contributions from the river, marsh, and continental shelf to the TG-corrected pCO2 are then calculated. Findings show that CO2 contributions from the river [ΔpCO2 (river)] are highest close to the coast and decrease with distance off-shore. For example, ΔpCO2 (river) was up to 30 µatm on the inner shelf but averaged only 0--3 µatm on the outer shelf during January and March 2005. CO2 contributions from salt marshes [ΔpCO2 (marsh)] show similar spatial and seasonal distributions as ΔpCO2 (river), with the magnitude of ΔpCO2 (marsh) being about three times as high as that of ΔpCO2 (river). CO2 contributions from within the shelf [ΔpCO2 (shelf)] are highest among the three components. Compared to ΔpCO2 (river) and ΔpCO2 (marsh), ΔpCO2 (shelf) show the smallest onshore-offshore gradients. Despite large uncertainties, this study clearly demonstrates the importance of terrestrial impacts on coastal ocean CO2 distribution. [ABSTRACT FROM AUTHOR]

The aim of this study was to examine the effects of elevated carbon dioxide [CO2] and ozone [O3] and their interaction on wood chemistry and anatomy of five clones of 3-year-old trembling aspen (Populus tremuloides Michx.). Wood chemistry was studied also on paper birch (Betula papyrifera Marsh.) and sugar maple (Acer saccharum Marsh.) seedling-origin saplings of the same age. Material for the study was collected from the Aspen Free-Air CO2 Enrichment (FACE) experiment in Rhinelander, WI, USA, where the saplings had been exposed to four treatments: control (C; ambient CO2, ambient O3), elevated CO2 (560ppm during daylight hours), elevated O3 (1.5 × ambient during daylight hours) and their combination (CO2 + O3) for three growing seasons (1998–2000). Wood chemistry responses to the elevated CO2 and O3 treatments differed between species. Aspen was most responsive, while maple was the least responsive of the three tree species. Aspen genotype affected the responses of wood chemistry and, to some extent, wood structure to the treatments. The lignin concentration increased under elevated O3 in four clones of aspen and in birch. However, elevated CO2 ameliorated the effect. In two aspen clones, nitrogen in wood samples decreased under combined exposure to CO2 and O2. Soluble sugar concentration in one aspen clone and starch concentration in two clones were increased by elevated CO2. In aspen wood, α-cellulose concentration changed under elevated CO2, decreasing under ambient 03 and slightly increasing under elevated O3. Hemicellulose concentration in birch was decreased by elevated CO2 and increased by elevated O3. In aspen, elevated O3 induced statistically significant reductions in distance from the pith to the bark and vessel lumen diameter, as well as increased wall thickness and wall percentage, and in one clone, decreased fibre lumen diameter. Our results show that juvenile wood properties of broadleaves, depending on species and genotype, were altered by atmospheric gas concentrations predicted for the year 2050 and that CO2 ameliorates some adverse effects of elevated O3 on wood chemistry. [ABSTRACT FROM AUTHOR]

The article discusses a study on the use of SCIAMACHY WFM-DOAS XCO2 to determine errors related to reduction of scattering. The study develops a new version of the retrieval algorithm (WFMDv2.2) to enhance the quality of the SCIAMACHY XCO2 data product. It validates the new XCO2 data using ground-based observations from the Total Carbon Column Observing Network (TCCON). It also compares NOAA's global CO2 modelling and assimilation system CarbonTracker.

The limited available evidence about effects of high CO2 and acidification of our oceans on fish suggests that effects will differ across fish species, be subtle, and interact with other stressors. An experimental framework was implemented that includes the use of (1) multiple marine fish species of relevance to the northeastern USA that differ in their ecologies including spawning season and habitat; (2) a wide yet realistic range of environmental conditions (i.e., concurrent manipulation of CO2 levels and water temperatures), and (3) a diverse set of response variables related to fish sensitivity to elevated CO2 levels, water temperatures, and their interactions. This report is on an array of early life-history responses of summer flounder (Paralichthys dentatus), an ecologically and economically important flatfish of this region, to a wide range of pH and CO2 levels. Survival of summer flounder embryos was reduced by 50% below local ambient conditions (7.8 pH, 775ppmpCO2) when maintained at the intermediate conditions (7.4 pH, 1860ppmpCO2), and by 75% below local ambient when maintained at the most acidic conditions tested (7.1 pH, 4715ppmpCO2). This pattern of reduced survival of embryos at higher CO2 levels was consistent among three females used as sources of embryos. Sizes and shapes of larvae were altered by elevated CO2 levels with longer larvae in more acidic waters. This pattern of longer larvae was evident at hatching (although longer hatchlings had less energy reserves) to midway through the larval period. Larvae from the most acidic conditions initiated metamorphosis at earlier ages and smaller sizes than those from more moderate and ambient conditions. Tissue damage was evident in older larvae (age 14 to 28 d post-hatching) from both elevated CO2 levels. Damage included liver sinusoid dilation, focal hyper-plasia on the epithelium, separation of the trunk muscle bundles, and dilation of the liver sinusoids and central veins. Cranial-facial features were affected by CO2 levels that changed with ages of larvae. Skeletal elements of larvae from ambient CO2 environments were comparable or smaller than those from elevated CO2 environments when younger (14d and 21 d post-hatching) but larger at older ages (28 d). The degree of impairment in the early life-stages of summer flounder due to elevated CO2 levels suggests that this species will be challenged by ocean acidification in the near future. Further experimental comparative studies on marine fish are warranted in order to identify the species, life-stages, ecologies, and responses that are most sensitive to increased levels of CO2 and acidity in near-future ocean waters, and a strategy is proposed for achieving these goals. [ABSTRACT FROM AUTHOR]

Wildfires are becoming more frequent due to the global climate change. Large amounts of greenhouse gases emitted by wildfires can lead to increases in extreme climate events. Accurately estimating the greenhouse gas carbon dioxide (CO2) emissions from wildfires is important for mitigation of climate change. In this paper, we develop a novel method to estimate wildfire CO2 emissions from the relationship between local CO2 emissions and XCO2 anomalies. Our method uses the WRF-Chem assimilation system from OCO-2 XCO2 retrievals which coupled with Data Assimilation Research Testbed (DART). To validate our results, we conducted three experiments evaluating the wildfire CO2 emissions over the conterminous United States. The four-month average wildfire emissions from July to October in 2015∼2018 were estimated at 4.408 Tg C, 1.784 Tg C, 1.514 Tg C and 2.873 Tg C, respectively. Compared to the average of established inventories CT2019B, FINNv1.5 and GFASv1.2 fire emissions, our estimates fall within one standard deviation, except for 2017 due to lacking of OCO-2 XCO2 retrievals. These results suggest that the regional carbon assimilation system, such as WRF-Chem/DART, using OCO-2 XCO2 retrievals has a great potential for accurately tracking regional wildfire emissions. [ABSTRACT FROM AUTHOR]

Extreme climate events including heat waves and droughts are projected to become more frequent under future climate change conditions. However, the mechanisms between soybean yields and climate factors, specifically involving variable rainfall and high heat episodes, are still unclear, particularly with respect to spatial trends in the United States (US) Midwest. A recently modified version of the model GLYCIM was used to evaluate rainfed soybean production across 12 states at a 10 km spatial resolution for three time periods (2011-2020, 2051-2060, 2091-2099) under Representative Concentration Pathway (RCP) scenarios 4.5 and 8.5. Results showed that except for the northernmost Midwest counties, most of the current rainfed cropping system in the Midwest would suffer a 24.6-47.4 % yield loss without considering the CO 2 fertility effect. Incorporating the effect of elevated CO 2 showed a smaller yield loss of 11.6-29.5 %. The increased frequency of extreme degree days (EDD) or accumulation of hourly temperatures above 30 °C associated with increased vapor pressure deficit (VPD) played a key role in contributing to water deficits and resultant crop losses under these future climate conditions. Although a relatively weak relationship between summer rainfall and crop yield was observed, decreased rainfall caused VPD to increase which induced crop water deficits. These findings suggest that it is crucial to consider VPD along with high temperature and low rainfall trends simultaneously for development of potential management or breeding-based adaptative strategies for soybean., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 Elsevier B.V. All rights reserved.)

This investigation explores whether sustainable finance and renewable energy could facilitate U.S. carbon neutrality. We perform the time-varying parameter-stochastic volatility-vector auto-regression (TVP-SV-VAR) model to obtain the changing relations among U.S. sustainable finance (SF), renewable energy (RE) and carbon dioxide emission (CO2). The empirical outcomes reveal a short-term negative effect from RE to CO2, indicating that renewable energy consumption could promote U.S. carbon neutrality. This effect is asymmetrical, and it could be observed that RE increase has a greater effect on CO2 than RE reduction. Also, the development of sustainable finance could facilitate U.S. carbon neutrality, and the direct impact is longer and more significant than RE, but the indirect effect of SF on CO2 by influencing RE is hysteretic. Besides, the asymmetric effect reveals that the negative direct impact of SF increase on CO2 is smaller than SF reduction, and the latter's indirect effect is more rapid than the former. Against the backdrop of global warming and frequent extreme weather, the above conclusions have meaningful practical applications for the U.S. to achieve carbon neutrality targets through developing sustainable finance and renewable energy., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2022 Elsevier Ltd. All rights reserved.)

This paper based on quantile stochastic frontier framework constructs quantile eco-efficiency measures. Using the estimates from the quantile stochastic frontier, the eco-performance of the U.S. states for nitrogen oxides (NO X ), carbon dioxide (CO 2 ), and sulfur dioxide (SO 2 ) emissions is evaluated. A decoupling analysis involving the evaluation of the nonsynchronous change among states' economic output and environmental degradation levels is also performed. The findings suggest that U.S. states have followed a decoupling process among their GDP and emission levels over the period 1990-2017. In addition, a quantile eco-productivity change estimator is presented alongside with its main components (i.e. quantile eco-technical change and quantile eco-efficiency change). Our findings suggest that over the examined period states' eco-productivity levels have been improved driven both from their eco-technical and eco-efficiency change levels., (Copyright © 2022 Elsevier Ltd. All rights reserved.)

Inland waters (rivers, lakes, and reservoirs) have been recognized as hotspots of methane (CH 4 ) emissions. However, the magnitude and spatiotemporal pattern of CH 4 emissions and their underlying mechanisms remain largely unknown due to a lack of process-based quantification of CH 4 production, consumption, and evasion within the aquatic ecosystem. Here we developed a process-based aquatic CH 4 module within the framework of the Dynamic Land Ecosystem Model (DLEM) to explicitly simulate inland water carbon fluxes and the associated CH 4 processes. We further applied this model to assess the inland-water CH 4 emissions across the conterminous United States (CONUS) as affected by the climate variability, land use, fertilizer nitrogen (N) application, atmospheric N deposition, and rising atmospheric CO 2 concentration during 1860-2019. The inland water CH 4 emissions across the CONUS had doubled from the 1860s (1.65±0.18 Tg CH 4 -C∙yr -1 ) to the 2010s (3.73±0.36 Tg CH 4 -C∙yr -1 ). In the 2000s, inland water accounts for 8% of the regional CH 4 budget that offsets 11∼14% of the terrestrial C uptake across the CONUS. Our study showed that the small headwater streams (1 st -3 rd order) account for 49% of the diffusive CH 4 , and reservoirs constitute 50% of the ebullitive CH 4 emissions during the 2010s. Climate change and variability played a dominant role in the increased CH 4 emissions from rivers and lakes. This study implies that effective mitigation strategies to reduce CH4 emissions should pay much attention to global climate change and headwater stream management., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2022 Elsevier Ltd. All rights reserved.)

This paper investigates carbon emission peak in China based on a comparative analysis of energy transition in China and the United States (US). The LMDI model is adopted to decompose carbon emissions into several driving factors in 2000-2018 for China and the US. Gray forecasting and NAR neural network are combined to predict peak time and identify optimal transition paths. The factor decomposition indicates that energy intensity is the main inhibitory factor for increased carbon emissions, while economic growth and population size are contributors for increased carbon emissions. There are significant differences in the impact of structure effect on carbon emissions in the two countries. The industry decomposition indicates that industry development is a critical inhibitor for increased carbon emissions after 2014 in China. The growth of transport and agriculture are basically contributing to increase carbon emissions in China and the US. The forecast results illustrate that China could complete carbon emission peak by 2030 under the baseline scenario, with a peak volume of 11354.72Mt CO 2 . Under the industrial structure adjustment scenario, the carbon peak year may be advanced to 2028. While adjusting industrial structure and energy consumption structure at the same time, China could achieve carbon emission peak at 9918.21Mt CO 2 in 2025., (© 2022. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

Over the last half century in the United States, the per-hectare volume of wood in trees has increased, but it is not clear whether this increase has been driven by forest management, forest recovery from past land uses, such as agriculture, or other environmental factors such as elevated carbon dioxide, nitrogen deposition, or climate change. This paper uses empirical analysis to estimate the effect of elevated carbon dioxide on aboveground wood volume in temperate forests of the United States. To accomplish this, we employ matching techniques that allow us to disentangle the effects of elevated carbon dioxide from other environmental factors affecting wood volume and to estimate the effects separately for planted and natural stands. We show that elevated carbon dioxide has had a strong and consistently positive effect on wood volume while other environmental factors yielded a mix of both positive and negative effects. This study, by enabling a better understanding of how elevated carbon dioxide and other anthropogenic factors are influencing forest stocks, can help policymakers and other stakeholders better account for the role of forests in Nationally Determined Contributions and global mitigation pathways to achieve a 1.5 degree Celsius target., (© 2022. This is a U.S. Government work and not under copyright protection in the US; foreign copyright protection may apply.)

The visual analysis of carbon neutrality research can help better understand the development of the research field and explore the difficulties and hot spots in the research, thus making contributions to "carbon emission reduction," environmental protection and human health. This paper makes a visual quantitative analysis of 2,819 research papers published in top international journals from 2008 to 2021 in the WOS core database. It is found that China, the United States, Britain, and Germany are leading the way in carbon neutrality research. The research hotspots are mainly divided into three dimensions: (1) biomass energy and the negative effects it might bring; (2) ways and methods of electrochemical reduction of carbon dioxide; (3) catalysts and catalytic environment. The research mainly went through the conceptual period of 1997-2007, the exploration period of bioenergy from 2008 to 2021, the criticized period of bioenergy sources from 2011 to 2013, and the carbon dioxide electroreduction period from 2013 to the present. In the future, the research direction of biomass energy is to find one kind of biomass energy source which can be stored in a low-carbon way, produced in large quantities at a low cost, and will not occupy forestland. The electrolysis of water to produce hydrogen and the synthesis of fuel with CO 2 are two major research directions at present, whose aims are to find the suitable catalyst and environment for the reaction. Besides, more research can be done on "carbon neutrality" policies so as to reduce carbon dioxide emissions from the source, develop a low-carbon economy and protect human health., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2022 Mao, Zhu, Ju, Bao and Xu.)

The present paper endeavours to analyse and provide fresh insights from the dynamic association between tourist arrivals, transportation services, growth and carbon dioxide emanation in the United States. The analysis employs a unique Morlet's Wavelet method. Precisely, this paper implements Partial and Multiple Wavelet Coherence techniques to the monthly dataset spanning from 2001 to 2017. From the frequency perspective, this research finds remarkable wavelet coherence and vigorous lead and lag associations. The analysis discovers significant progress in variables over frequency and time. The variables display strong but inconsistent associations between them. There exist a strong co-movement among the variables considered, which is not equal across the time scales. The study may help the policymakers and regulars to devise strategies and formulate policies pertaining to tourism development, which can contribute towards environmentally sustainable economic growth. [ABSTRACT FROM AUTHOR]

The development of globalization has separated the production and consumption of products spatially, and the international trade of products has become a carrier of embodied carbon trade. This paper adopted the perspective of value-added trade to calculate the amount of embodied carbon trade of China from 2006 to 2015 and perform a structural decomposition analysis of the changes in China's embodied carbon trade. This study found that: (1) China's embodied carbon exports are much larger than its embodied carbon imports, and there are differences between countries. China imported the largest amount of embodied carbon from South Korea, and it exported the largest amount of embodied carbon to the United States. (2) The structural decomposition analysis shows that changes in the value-added carbon emission coefficient during the study period would have caused China's embodied carbon trade to decrease, and changes in value-added trade would have caused China's embodied carbon trade to increase. Therefore, countries trading with China need to strengthen their cooperation with China in energy conservation, emission reduction, and product trade. In order to accurately reflect China's embodied carbon trade, it is necessary to calculate embodied carbon trade from the perspective of value-added trade., Competing Interests: The authors have declared that no competing interests exist.

This paper provides a review and comparison of strategies to increase forest carbon, and reduce species losses for climate change mitigation and adaptation in the United States. It compares forest management strategies and actions that are taking place or being proposed to reduce wildfire risk and to increase carbon storage with recent research findings. International agreements state that safeguarding biodiversity and ecosystems is fundamental to climate resilience with respect to climate change impacts on them, and their roles in adaptation and mitigation. The recent Intergovernmental Panel on Climate Change report on impacts, mitigation, and adaptation found, and member countries agreed, that maintaining the resilience of biodiversity and ecosystem services at a global scale is "fundamental" for climate mitigation and adaptation, and requires "effective and equitable conservation of approximately 30 to 50% of Earth's land, freshwater and ocean areas, including current near-natural ecosystems." Our key message is that many of the current and proposed forest management actions in the United States are not consistent with climate goals, and that preserving 30 to 50% of lands for their carbon, biodiversity and water is feasible, effective, and necessary for achieving them. [ABSTRACT FROM AUTHOR]

Introduction: Over the past 20 years, there has been a tripling in the consumption of small cigars and cigarillos, with further increases expected because cigar products are not subject to Food and Drug Administration regulations. Acute toxin exposure from cigar smoking is difficult to assess because unlike cigarettes, cigars vary widely in size, design, composition, and in the smoking behavior of their consumers. For example, a recent practice among urban youth is to remove the paper liner (i.e., “freaking”) of a small cigar in the belief that it is this paper liner that leads to addiction and cancer. Methods: We examined acute exposure (CO and nicotine boosts) and puffing behavior in 12 participants (10 men) who smoked (ad lib) their usual conventional cigarette, a Black & Mild cigar (B&M) and a B&M without the paper liner (i.e., “freaked” [B&Mf]). Results: All products (cigarettes, B&M, and B&Mf) significantly increased heart rate and CO with a trend for plasma nicotine. Nicotine boost was significantly higher after cigarette smoking than both B&M and B&Mf, while CO boost was significantly greater after B&M and B&Mf than cigarettes. The CO boost after B&M was larger than after B&Mf. Conclusions: These findings suggest that small cigar smoking is associated with smoke inhalation that leads to significant exposure to nicotine, CO, and presumably other components of tobacco smoke and that removing the inner liner does not substantially reduce toxin exposure. [ABSTRACT FROM PUBLISHER]

A critical reason for China-United States trade friction is that China has a huge trade balance, especially the trade balance of goods. However, this huge trade balance is based on the results of official statistics and does not reflect the real economic benefits and environmental costs embodied in China-US trade, where both refer to trade in value-added and embodied CO 2 emission costs, respectively. This paper calculates the trade in value-added and carbon emission transfer between China and the United States based on the World Input-Output Database. Results demonstrate that: (1) Gross trade statistics seriously overestimate China's benefits in China-US trade. The China-US trade surplus, based on gross trade statistics, is 20% higher than when based on trade in value-added accounting. (2) In China-US bilateral trade, China mainly adopts the trade model of importing intermediate products and exporting final products，whereas the United States mainly adopts the trade model of importing final products and exporting intermediate products. China's exports to the United States contain many of value-added in Korea, Taiwan, and Japan. (3) From 2000 through 2014, China maintained a large surplus of CO 2 emissions exports to the United States, and China paid a huge environmental cost in its trade with the United States. (4) In China-US trade, China's environmental costs per unit value-added is 3.02 times that of the United States., (Copyright © 2020 Elsevier Ltd. All rights reserved.)

In this paper, we analyze how carbon emissions affect the selection of transportation modes and social welfare by using a two-stage Stackelberg gaming model. Based on this model, the government’s optimal carbon-emission tax scheme and the company’s optimal transportation mode and production decisions are explored. We find that: 1) whether or not the transport carbon-emission tax can increase social welfare depends on the relationships among the social cost of carbon (SCC), the transportation mode shifting threshold (TMST), and the biggest carbon-emission tax that a company can afford (BCRA); 2) a greater SCC implies a higher probability of improving social welfare via imposing transportation carbon-emission tax; and 3) a smaller TMST or BCRA yields a higher probability of improving social welfare when a carbon-emission tax is imposed. Further study shows that imposing a carbon-emission tax on the product with a higher production cost, a bigger product volume, or a bigger product density can increase the probability of improving social welfare. [ABSTRACT FROM PUBLISHER]

Johnson grass (Sorghum halepense (L.) Pers.) is rapidly spreading throughout the continental United States (U.S.). Thus, determining magnitudes and seasonal dynamics of carbon dioxide (CO 2 ) and water vapor (H 2 O) fluxes in Johnson grass is crucial to understand regional changes in hydrology and carbon balance. Using eddy covariance (EC), CO 2 and H 2 O fluxes were measured from June 2017 to October 2019 over a rainfed Johnson grass field in central Oklahoma. Hay was harvested from late May to early July each year, with biomass yield ~7.5 t ha -1 . Weekly averaged daily integrated net ecosystem CO 2 exchange (NEE), gross primary production (GPP), and evapotranspiration (ET) reached -8.28 ± 0.76 g C m -2 , 20.02 ± 1.62 g C m -2 , and 5.42 ± 0.26 mm, respectively. Ecosystem water use efficiency (EWUE) and ecosystem light use efficiency (ELUE) ranged from 3.22 to 3.93 g C mm -1 ET and 0.34 to 0.41 g C mol -1 PAR (photosynthetically active radiation), respectively, during peak growths. Based on aggregated fluxes for each month over the three years (2017-2019), cumulative annual NEE was -434 ± 112 g C m -2 , indicating a carbon gain by the Johnson grass field. Cumulative annual ET (858 ± 72 mm) was ~86% of the average annual rainfall (996 ± 100 mm). Results showed Johnson grass could be a carbon sink from May to September in the U.S. Southern Great Plains. Both NEE and ET did not decline up to air temperature (T a ) of ~33 °C and vapor pressure deficit (VPD) of ~2 kPa, suggesting optimum T a of ≥33 °C and VPD of ≥2 kPa for the fluxes. Results indicated that Johnson grass might be well suited for dryland production in the region. Additionally, these findings provide initial baseline information on CO 2 fluxes and ET for Johnson grass relative to other forage species in the region., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Published by Elsevier B.V.)

Sunlight can oxidize dissolved organic carbon (DOC) to dissolved inorganic carbon (DIC) in freshwaters. The importance of complete photooxidation, or photomineralization, as a sink for DOC remains unclear in temperate rivers, as most estimates are restricted to lakes, high latitude rivers, and coastal river plumes. In this study, we construct a model representing over 75,000 river reaches in the Connecticut River Watershed (CRW), USA, to calculate spectrally resolved photomineralization. We test the hypothesis that photomineralization is a negligible DOC sink across all reaches and flow conditions relative to DOC fluxes. Our model quantifies reaction rates and transport drivers within the river reaches for the ranges of flow conditions, incoming solar irradiance, and canopy cover shading observed throughout the year. Our model predicts average daily areal photomineralization rates ranging from 1.16 mg‐C m−2 day−1 in low flow river reaches in the winter, to 18.33 mg‐C m−2 day−1 in high flow river reaches during the summer. Even for high photomineralization fluxes, corresponding photomineralization uptake velocities are typically at least an order of magnitude smaller than those reported for other instream processes. We calculate DOC elimination by photomineralization relative to DOC fluxes through individual stream reaches as well as the entire riverine portion of the CRW. We find that relative photomineralization fluxes are highest in summer drought conditions in low order streams. In median flows and mean light intensities, for an average watershed travel distance, 3%–5% of the DOC fluxes are eliminated, indicating that photomineralization is a minor DOC sink in temperate rivers. Plain Language Summary: Rivers are an important part of the carbon cycle, moving carbon compounds from land to the ocean. Within rivers, dissolved organic carbon molecules can be broken down into inorganic carbon molecules, including the greenhouse gas carbon dioxide. Sunlight shining into rivers can cause these organic molecules to break down in a process called photomineralization, but it is not clear if this process is important compared to the total amount of organic carbon that travels through rivers every day. In this paper, we build a model for the river sections of temperate Connecticut River Watershed, which calculates photomineralization for possible river flow conditions, dissolved organic carbon concentrations, and seasons, and compares the size of the sunlight‐driven breakdown of dissolved organic carbon to the amount of dissolved organic carbon in the river. This is the first model that puts photomineralization rates in the context of a flowing temperate river network. We show that compared with the dissolved organic carbon amounts present in the river at any time of the year or any flow conditions, photomineralization is essentially an unimportant process, removing on average 3%–5% of the dissolved organic carbon through an average watershed river route. Key Points: We build a model calculating reaction and transport drivers for photomineralization in 75,000 temperate river reachesPhotomineralization is a negligible dissolved organic carbon (DOC) sink relative to DOC fluxesDOC elimination by photomineralization in temperate rivers is limited by short water residence times and canopy cover [ABSTRACT FROM AUTHOR]

The prevailing political atmosphere and partisanship in the United States depict the degree of polarization between the two major political parties of the country. Evidently, the polarization between the Democratic Party (DP) and the Republican Party will expectedly drive the partisan conflict to the higher levels. Considering this motivation, this paper examined the role of partisan conflict in the pollutant emissions in the case of the United States. For sound empirical analysis, the impacts of other environmental quality determinants are being examined over the period 1960-2015. In order to present a decent argument that is viable for policy implementation, the study adopts the combined methodologies of Johansen cointegration; the autoregressive distributed lag (ARDL) of Pesaran et al. J Am Stat Assoc 94(446):621-634 (1999); and the Toda and Yamamoto J Econ 66(1-2):225-250 (1995) Granger causality. Empirical outcomes show (i) the kg oil equivalent per capita energy consumed exercise positive and significant impacts on metric tons of per capita CO 2 emissions, and it is the principal determinant of environmental degradation in both the short-run and the long-run (ii) renewable energy consumption and economic growth also exercise negative and significant impacts on metric tons of per capita CO 2 emissions. Based on our empirical findings, we conclude that partisan conflict indirectly plays a significant role in environmental sustainability targets of the United States. Thus, we are of the opinion that the government should avoid heightened partisan conflict among the political parties in order to promote sustainable environmental policies that would enhance sound and clean environment for both the immediate and the future generation.

The goals of this paper are to examine whether the environmental Kuznets curve (EKC) holds and to investigate whether renewable energy consumption can decrease CO 2 emissions in the USA using monthly data spanning the period 2000:M01-2018:M07. For these purposes, the paper employs a cointegration test with a regime shift and observes the long-run coefficients before and after the regime shift. The findings support the presence of the EKC. The findings also indicate that renewable energy consumption has negative effects on CO 2 emissions, while these effects are greater when the share of renewable energy consumption in total energy consumption is higher in the USA. Theoretical and practical implications for these findings are discussed.

Estimates of the marginal value of carbon dioxide-the social cost of carbon (SCC)-were recently adopted by both the U.S. and U.K. Governments in order to satisfy requirements to value estimated greenhouse gas (GHG) changes of new federal regulations. However, the development and use of SCC estimates comes with significant challenges and controversial decisions. This paper summarizes the key issues and then derives guidance for developing, selecting, and applying the estimates that follows from the fundamental scientific nature and economic principles associated with GHGs and climate change, as well as an understanding of the state of the art for estimating the SCC. The paper evaluates recent estimates in light of the guidance and finds the estimates inconsistent with the guidance in a number of significant areas. The paper also differentiates SCC policy applications in terms of policies with incremental versus nonincremental implications for global GHGs, and identifies serious issues for application of the SCC in setting and evaluating climate policy targets. WIREs Clim Change 2012, 3:163-195. doi: 10.1002/wcc.163 For further resources related to this article, please visit the . [ABSTRACT FROM AUTHOR]

Purpose – The purpose of this paper is to forecast the performance and adoption of residential energy management technology (REMT).Design/methodology/approach – The paper integrates scenarios, analogy and Bass diffusion model.Findings – Four different scenarios were identified. Bass curve parameters were extracted through many different existing devices, and then fit into each scenario subjectively to produce four different kinds of diffusion curves.Originality/value – The approach and the model provide decision and policy makers to evaluate how they should position new energy management innovations based on the desired type of diffusion. [ABSTRACT FROM AUTHOR]

With heightened concerns on carbon dioxide (CO2) emissions from coal power plants, there has been a major emphasis in recent years on development of safe and economical geological carbon sequestration (GCS) technology. However, the detailed multiphase fluid dynamics and processes of GCS are not fully understood because various CO2 trapping mechanisms in geological formations have large variations in both spatial and temporal scales. As a result, there remain many uncertainties in determining the sequestration capacity of the reservoir and the safety of sequestered CO2 due to leakage. Furthermore, the sequestration efficiency is highly dependent on the CO2 injection strategy, which includes injection rate, injection pressure, and type of injection well, and its orientation, etc. The goal of GCS is to maximize the sequestration capacity and minimize the plume migration by optimizing the GCS operation. In this paper, first the basic fluid dynamics and trapping mechanisms for CO2 sequestration are briefly discussed. They are followed by a brief summary of current GCS projects worldwide with special emphasis on those in the United States. Majority of the paper is devoted to the numerical modeling, simulation, and optimization of CO2 sequestration in saline aquifers at macro spatial scales of a few to hundreds of kilometers and macro temporal scales of a few to hundreds of years. Examples of numerical simulations of a few large industrial scale projects are presented. The optimization studies include the investigation of various injection and well placement strategies to determine the optimal approach for maximizing the storage and minimizing the plume migration. [ABSTRACT FROM AUTHOR]

The Penn State climate scientist who helped author the “hockey stick” global warming temperature graph describes the campaign to discredit him following the theft of emails, including some he wrote, from servers at England’s University of East Anglia. Climate-change denial groups said the emails showed unethical conduct, but scientific organizations and academic panels said this was not the case, defending Mann and the credibility of climate science. Mann believes the widespread media coverage contributed to the failure of the US Senate to take action on carbon dioxide emission controls this summer. But he cites polls showing that the matter may not have compromised public belief in climate science and expresses optimism that policymakers will force emissions reductions in time to avert truly catastrophic changes to Earth’s climate. [ABSTRACT FROM PUBLISHER]

As economic integration in the world continues to advance, energy consumption and carbon emissions in various regions have also become increasingly interdependent. In order to better understand the regional interaction of carbon emissions, this paper employs a three-region input-output approach to explore the linkage of CO 2 emissions among China, EU, and USA. Based on the world input-output table and environment account of World Input-Output Database (WIOD) in 2009, we calculate the carbon emission multiplier effect, spillover effect, and feedback effect and carry out the analysis from the regional and sectoral levels. The results show that, first of all, the carbon emission multiplier effect of each region is larger than the spillover and feedback effects. Second, EU and USA have higher carbon emission spillover effect on China than China's carbon emission spillover effect on them. Finally, the carbon multiplier effects in different sectors have different characteristics.

The climate change is one of the leading problems in the today's world. The rise of the renewable energy meets the sustainable growth objectives since it can decelerate the climate change. For this purpose, this paper investigates the relationship between the renewable energy consumption and the economic growth in the United States (USA). Theoretically, the paper constructs the growth model that captures the effects of the economic complexity indicator as a measure of capabilities and productivity for exporting the "complex" (high value-added) products. Empirically, the paper uses the Autoregressive Distributed Lag (ARDL) estimations and observes that both the economic complexity and the renewable energy consumption lead to a higher rate of economic growth in the USA for the period from 1965 to 2016. The paper also discusses the potential policy implications of the results for achieving the sustainable growth objectives.

The accurate forecast of carbon dioxide emissions is critical for policy makers to take proper measures to establish a low carbon society. This paper discusses a hybrid of the mixed data sampling (MIDAS) regression model and BP (back propagation) neural network (MIDAS-BP model) to forecast carbon dioxide emissions. Such analysis uses mixed frequency data to study the effects of quarterly economic growth on annual carbon dioxide emissions. The forecasting ability of MIDAS-BP is remarkably better than MIDAS, ordinary least square (OLS), polynomial distributed lags (PDL), autoregressive distributed lags (ADL), and auto-regressive moving average (ARMA) models. The MIDAS-BP model is suitable for forecasting carbon dioxide emissions for both the short and longer term. This research is expected to influence the methodology for forecasting carbon dioxide emissions by improving the forecast accuracy. Empirical results show that economic growth has both negative and positive effects on carbon dioxide emissions that last 15 quarters. Carbon dioxide emissions are also affected by their own change within 3 years. Therefore, there is a need for policy makers to explore an alternative way to develop the economy, especially applying new energy policies to establish a low carbon society.

The U.S. Clean Power Plan stipulates a state-specific performance-based CO2 emission standard, delegating states with considerable flexibility for using either a tradable performance-based or a mass-based permit program. This paper analyzes these two standards under imperfect competitive. We limit our attention to (1) short-run analyses and (2) a situation in which all states are subject to the same type of standard. We show that while the cross-subsidy inherent in the performance- based standard might effectively reduce power prices, it could also inflate energy consumption. A dominant firm with a relatively clean endowment under the performance-based standard would be able to manipulate the electricity market as well as to elevate permit prices, which might worsen market outcomes compared to its mass-based counterpart. On the other hand, the "cross-subsidy" could be the dominant force leading to a higher social welfare if the leader has a relatively dirty endowment. [ABSTRACT FROM AUTHOR]

Methane (CH4) is a powerful greenhouse gas with a global warming potential 84 times higher than carbon dioxide (CO2) over 20 years. CH4 is produced from many natural and anthropogenic sources which can be further classified as biogenic or thermogenic in origin. The largest biogenic sources result from anaerobic decay such as wetlands, melting permafrost, or the breakdown of organic matter in the guts of ruminant animals. Thermogenic CH4 is generated during the breakdown of organic matter at high temperatures and pressure within the Earth's crust, a process which also produces more complex trace hydrocarbons such as ethane (C2H6) and propane (C3H8). Emissions of thermogenic CH4 are dominated by the fossil fuel energy sector, and the presence of elevated C2H6 along with CH4 can be used to distinguish oil and gas emissions from biogenic sources. This work outlines the development and deployment of an Unmanned Aerial System (UAS) outfitted with a fast (1 Hz) and sensitive (1–2 ppb s-1) CH4 & C2H6 sensor and ultrasonic anemometer. The UAV platform is a vertical-takeoff, hexarotor vehicle capable of vertical profiling to 120 m altitude and plume sampling across scales up to 1 km. This system has been used for direct quantification of point sources, as well as distributed emitters such as landfills, with source rates as low as 0.04 kg h-1 and up to 1500 kg h-1. Simultaneous measurements of CH4 and C2H6 mixing ratios, vector winds, and positional data allows for source classification (biogenic versus thermogenic), differentiation, and emission rates without the need for modeling or a priori assumptions about winds, vertical mixing, or other environmental conditions. The UAS has been deployed throughout the Southwest United States for system validation and targeted quantification of various sources emitting at or below the detection limits of other aircraft and satellite systems. This system offers a direct, repeatable method of horizontal and vertical profiling of emission plumes at scales that provide complementary information for regional aerial surveys as well as local ground-based monitoring. [ABSTRACT FROM AUTHOR]

In 2009, the National Research Council issued Electricity from Renewables: Status, Prospects, and Impediments the study report of the Panel on Electricity from Renewable Sources. As part of the larger America's Energy Future study undertaken by the National Academies, the panel was asked to examine the technical potential for development and deployment of renewable electricity technologies. This paper summarizes the report by this panel. The panel noted that renewable electricity generation technologies represent a tremendous opportunity to provide low net carbon dioxide (CO2)-emitting electricity generation from domestic resources and to generate new economic opportunities for the United States. The panel found that there are sufficient domestic renewable resources and technologies to allow renewable electricity to play a significant role in future electricity generation. However, although wind and solar electricity in particular have exhibited very large growth rates, non-hydropower renewables still provide a small percentage of total US electricity generation. The study considered the size and distribution of the resource base; the status of renewable electricity technologies; the economics of renewable electricity in light of various policy options; the environmental impacts of electricity from renewable resources; and the issues related to scaling up deployment. The panel concluded that an aggressive but achievable future for renewables could have non-hydroelectric renewables contributing 10% of the nation's electricity generation by 2020 and 20% or more by 2035. To reach these levels, significant and sustained actions, involving a combination and coordination of policy, technology, and capital, will be essential. The panel emphasizes policy, technology, and capital equally because the scale of the effort required to reach such levels brings significant challenges beyond simple resource availability or technical capabilities. [ABSTRACT FROM AUTHOR]

This paper undertakes a quantitative analysis of the socioeconomic and environmental impacts of different trade agreements for Chile. A dynamic general equilibrium model is used to compare the consequences of unilateral liberalization and trade agreements with the European Union (EU) and the United States (USA). The results show that economic gains under the trade agreements are only significant if foreign investment increases or value added taxes are modified. Winners and losers depend on the agreement; however, unskilled labor-intensive sectors always progress. Consequently, these agreements seem to be good for the poorest groups. Some natural resource intensive sectors significantly increase their production with the EU and the US agreements, also increasing the environmental pressures. CO2 and PM-10 emissions are not very different under these agreements as compared to business as usual – under which environmental pressures increase significantly. The results show the importance of economy-wide analysis of trade agreements in developing contexts. [ABSTRACT FROM AUTHOR]

This paper provides comparisons of a variety of time-series methods for short-run forecasts of the main greenhouse gas, carbon dioxide, for the United States, using a recently released state-level data set from 1960–2001. We test the out-of-sample performance of univariate and multivariate forecasting models by aggregating state-level forecasts versus forecasting the aggregate directly. We find evidence that forecasting the disaggregate series and accounting for spatial effects drastically improves forecasting performance under root mean squared forecast error loss. Based on the in-sample observations we attempt to explain the emergence of voluntary efforts by states to reduce greenhouse gas emissions. We find evidence that states with decreasing per capita emissions and a “greener” median voter are more likely to push toward voluntary cutbacks in emissions. [ABSTRACT FROM AUTHOR]

Abstract As carbon dioxide and other greenhouse gases accumulate in the atmosphere and contribute to rising global temperatures, it is important to examine how derivative changes in climate may affect natural and managed ecosystems. In this series of papers, we study the impacts of climate change on agriculture, water resources and natural ecosystems in the conterminous United States using twelve scenarios derived from General Circulation Model (GCM) projections to drive biophysical impact models. These scenarios are described in this paper. The scenarios are first put into the context of recent work on climate-change by the IPCC for the 21st century and span two levels of global-mean temperature change and three sets of spatial patterns of change derived from GCM results. In addition, the effect of either the presence or absence of a CO2 fertilization effect on vegetation is examined by using two levels of atmospheric CO2 concentration as a proxy variable. Results from three GCM experiments were used to produce different regional patterns of climate change. The three regional patterns for the conterminous United States range from: an increase in temperature above the global-mean level along with a significant decline in precipitation; temperature increases in line with the global-mean with an average increase in precipitation; and, with a sulfate aerosol effect added to in the same model, temperature increases that are lower than the global-mean. The resulting set of scenarios span a wide range of potential climate changes and allows examination of the relative importance of global-mean temperature change, regional climate patterns, aerosol cooling, and CO2 fertilization effects. [ABSTRACT FROM AUTHOR]

Abstract As carbon dioxide and other greenhouse gasses accumulate in the atmosphere and contribute to rising global temperatures, it is important to examine how a changing climate may affect natural and managed ecosystems. In this series of papers, we study the impacts of climate change on agriculture, water resources and natural ecosystems in the General Circulation Model (GCM)-derived climate change projections, described in Part 1, to drive the crop production and water resource models EPIC (Erosion Productivity Impact Calculator) and HUMUS (Hydrologic Unit Model of the United States). These models are described and validated in this paper using historical crop yields and streamflow data in the conterminous United States in order to establish their ability to accurately simulate historical crop and water conditions and their capability to simulate crop and water response to the extreme climate conditions predicted by GCMs. EPIC simulated grain and forage crop yields are compared with historical crop yields from the US Department of Agriculture (USDA) and with yields from agricultural experiments. EPIC crop yields correspond more closely with USDA historical county yields than with the higher yields from intensively managed agricultural experiments. The HUMUS model was validated by comparing the simulated water yield from each hydrologic basin with estimates of natural streamflow made by the US Geological Survey. This comparison shows that the model is able to reproduce significant observed relationships and capture major trends in water resources timing and distribution across the country. [ABSTRACT FROM AUTHOR]

Objective: This paper examines the relationship between obesity and greenhouse gas (GHG) emissions while accounting for the environmental impact of growth in transportation output and in crop and animal farming. Study Design: The study makes use of US state-level longitudinal data over the 1997--2011 period. Methods: Random effects and fixed effects estimators are employed within a multiple regression analysis framework. Results: After controlling for other sources of emissions, there is evidence that the effect of transportation output on CO2 emissions worsens at obesity rates exceeding 33.7% and the effect on N2O emissions worsens at obesity rates exceeding 22.5%. In addition, the impact of crop and animal farming on N2O emissions worsens at obesity rates exceeding 20.2%. Conclusion: This paper provides significant and new insight about the causal link between obesity and environmental emissions and highlights the importance of addressing the obesity epidemic on public health and environmental grounds. Thus, mitigating GHG emissions connected to obesity requires joint effort between policymakers, public health officials, and parties from concerned economic sectors in pursuing remedial actions to reverse the current obesity trend. Various policy measures are discussed. [ABSTRACT FROM AUTHOR]

The quantification of fossil-fuel-related emissions of carbon dioxide to the atmosphere is necessary in order to accurately represent carbon cycle fluxes and to understand and project the details of the global carbon cycle. In addition, the monitoring, reporting, and verification (MRV) of carbon dioxide emissions is necessary for the success of international agreements to reduce emissions. However, existing fossil-fuel carbon dioxide (FFCO) emissions inventories vary in terms of the data and methods used to estimate and distribute FFCO. This paper compares how the approaches used to create spatially explicit FFCO emissions inventories affect the spatial distribution of emissions estimates and the magnitude of emissions estimates in specific locales. Five spatially explicit FFCO emission inventories were compared: Carbon Dioxide Information and Analysis Center (CDIAC), Emission Database for Global Atmospheric Research (EDGAR), Fossil Fuel Data Assimilation System (FFDAS), Open-source Data Inventory for Anthropogenic CO (ODIAC), and Vulcan. The effects of using specific data and approaches in the creation of spatially explicit FFCO emissions inventories, and the effect of resolution on data representation are analyzed using graphical, numerical, and cartographic approaches. We examined the effect of using top-down versus bottom-up approaches, nightlights versus population proxies, and the inclusion of large point sources. The results indicate that the approach used to distribute emissions in space creates distinct patterns in the distribution of emissions estimates and hence in the estimates of emissions in specific locations. The different datasets serve different purposes but collectively show the key role of large point sources and urban centers and the strong relationship between scale and uncertainty. [ABSTRACT FROM AUTHOR]