A Designing of the Manufacturing Facility for Disposing of Greenhouse Gases

Grass attack

Four key decades

Addressing Climate Change Without Legislation - Volume 1: DOI

Spectres of the Anthropocene.

The recent publication of the summary for policy makers by Working Group I of the Intergovernmental Panel on Climate Change (IPCC) [1] has injected a renewed sense of urgency to address climate change. It is therefore timely to review the notion of preventing 'dangerous anthropogenic interference with the climate system' as put forward in the United Nations Framework Convention on Climate Change (UNFCCC). The article by Danny Harvey in this issue [2] offers a fresh perspective by rephrasing the concept of 'dangerous interference' as a problem of risk assessment. As Harvey points out, identification of 'dangerous interference' does not require us to know with certainty that future climate change will be dangerous—an impossible task given that our knowledge about future climate change includes uncertainty. Rather, it requires the assertion that interference would lead to a significant probability of dangerous climate change beyond some risk tolerance, and therefore would pose an unacceptable risk.

Between Scylla and Charybdis: energy, carbon dioxide, and indoor environmental quality

There is an increasing concern over climate change and its environmental impacts. Effective greenhouse gases (GHG) monitoring and control strategies are of pivotal importance. Models such as STILT (Stochastic Time-Inverted Lagrangian Transport), statistical techniques, and experimental data analysis provide valuable tools for quantifying emissions and identifying greenhouse gas (GHG) tendencies. The Mediterranean basin is considered a global hotspot for air-quality and climate change: here, we combine experimental datasets of atmospheric methane (CH 4 ) and carbon dioxide (CO 2 ) with atmospheric transport models to present an atmospherically-based framework for monitoring GHG emissions. We applied methodologies, i.e., the Smoothed Minima (SM) and STILT, to extract background concentration data from the time series of atmospheric gases and identify measurements deemed representative of atmospheric background (GRD) levels. At the Lamezia Terme (Global Atmosphere Watch, GAW code: LMT), Capo Granitola (GAW code: CGR), and Lampedusa (GAW code: LMP) observation sites, GHG measurements were performed with specific calibration routines carried out using primary standards of calibration from the National Oceanic and Atmospheric Administration – Global Monitoring Laboratory (NOAA–GML), with secondary standards used to evaluate possible drifts and calibration factors stability. The first two are coastal stations and the third is an island station. At these sites, atmospheric CH 4 and CO 2 mole fractions can be evaluated at local and continental scales, in locations with specific Mediterranean climatic characteristics. This paper presents the variability of CH 4 and CO 2 in the central Mediterranean basin by analyzing hourly GHG concentrations over a 9-year period (2015–2023) for LMT, a 8-year period (2015–2022) for CGR, and a 19-year period (2006–2024) for CO 2 and 5-year period (2020–2024) for CH 4 at LMP. STILT provides 3-hourly results for methane and carbon dioxide concentrations that correlate well with surface measurements at LMT, CGR, and LMP. These analyses are aimed at relevant long-term datasets of GHG over southern Italy. This work would provide a useful contribution to comparing the observed concentrations of gases measured at three sites in the central Mediterranean with those predicted by models such as STILT. The results indicate good agreement between in situ measurements and modeling, and underline the importance of synergies between different institutions and methodologies. Compared to the CGR and LMP site, LMT has recorded higher levels of anthropogenic emissions in the area. Graphical Abstract Framework shows the variability of methane and carbon dioxide in the Mediterranean basin at three permanent World Meteorological Organization/Global Atmosphere Watch (WMO/GAW) stations in southern Italy: Lamezia Terme (GAW code: LMT), Capo Granitola (GAW code: CGR) and Lampedusa (GAW code: LMP). Accurate modeling of atmospheric transport is essential to address environmental concerns and to establish a quantitative link between observed gas distributions and surface emissions. In the present work, we used the Stochastic Time Inverted Lagrangian Transport (STILT) and the Smoothed Minima (SM) models. STILT simulates transport by following the time evolution of a particle ensemble, interpolating meteorological fields to the subgrid location of each particle. Both methods were used to extract background concentration data from the time series of atmospheric gases representative of the atmospheric background levels. The paper is an important contribution to the comparison between the observed and predicted by models concentrations of methane and carbon dioxide at three sites in the central Mediterranean. The STILT model datasets, validated at the three sites, show satisfactory results, with the exception of an overall underestimation in all comparisons (background and no-background). They demonstrate that the model can accurately estimate the CH 4 and CO 2 concentrations in the Mediterranean basin. Similar results are also obtained when comparing the SM and STILT background datasets. This last comparison indicates a good identification of the concentrations of the background gases by the models.

The urgent need for transition to renewable energy is underscored by a nearly 50 % increase in atmospheric carbon dioxide levels over the past century. The combustion of fossil fuels for energy production, transportation, and industrial activities are the main contributors to carbon dioxide emissions in the anthroposphere. Present approaches to reducing carbon emissions are proving inefficient, thereby accentuating the relevance of carbon dioxide photocatalysis in combating climate change — one of the critical issues of public concern. This process uses sunlight to convert carbon dioxide into valuable products, e.g., clean fuels, effectively reducing the carbon footprint and offering a sustainable use of carbon dioxide. In this context, plasmonic nanoparticles such as gold, silver, and copper play a pivotal role due to their proficiency in absorbing a wide range of light spectra, thereby effectively generating the necessary electrons and holes for the degradation of pollutants and surpassing the capabilities of traditional semiconductor catalysts. This review meticulously examines the latest advancements in plasmon-based carbon dioxide photocatalysis, scrutinizing the methodologies, characterizations, and experimental outcomes. The critical evaluation extends to exploring adjustments in the dimensional and morphological aspects of plasmonic nanoparticles, complemented by the incorporation of stabilizing agents, which may offer additional benefits. Furthermore, the review includes a thorough analysis of production rates and quantum yields based on different plasmonic materials and nanoparticle shapes and sizes, enriching the ongoing discourse on effective solutions in the field. Thus, our work emphasizes the pivotal role of plasmon-based photocatalysts in reducing carbon dioxide, investigating both the merits and challenges associated with integrating this emerging technology into climate change mitigation efforts.

Effects of fuel and forest conservation on future levels of atmospheric carbon dioxide

Transport currently represents approximately 19% of the global energy demand and accounts for about 23% of the global carbon dioxide emissions (IEA 2009). As the demand for mobility is expected to continue to increase in the coming decades, the stabilization of atmospheric carbon dioxide levels will require the evolution of transport, along with power generation, building design and manufacturing. The continued development of these sectors will need to include changes in energy sources, energy delivery, materials, infrastructure and human behavior. Pathways to reducing carbon from the transport sector have unique challenges and opportunities that are inherent to the human choices and behavioral patterns that mold the transportation systems and the associated energy needs. Technology, government investment, and regulatory policies have a significant impact on the formulation of transportation infrastructure; however, the role of human behavior and public acceptance on the efficiency and effectiveness of transport systems should not be underestimated.

’s (2012) conclusion that observed climate change is comparableto projections, and in some cases exceeds projections, allows further inferences ifwe can quantify changing climate forcings and compare those with projections.The largest climate forcing is caused by well-mixed long-lived greenhouse gases.Here we illustrate trends of these gases and their climate forcings, and we discussimplications. We focus on quantities that are accurately measured, and we includecomparison with fixed scenarios, which helps reduce common misimpressionsabout how climate forcings are changing.Annual fossil fuel CO

گرمایش جهانی و به‌تبع آن تغییر اقلیم، موضوع مهمی است که در دهه‌های اخیر توسط محققین در سرتاسر دنیا موردمطالعه قرارگرفته است. در این مطالعات تغییرات پارامترهای اقلیمی موردبررسی قرار می‌گیرد. با توجه به عدم قطعیت فراوان دخیل در برآورد این پارامترها، بهتر است شیوه‌ای اتخاذ گردد تا تحلیل‌ها با بررسی باند ناشی از منابع مختلف عدم قطعیت، صورت پذیرد. بدین منظور در این مطالعه تلاش شد با بررسی باند عدم قطعیت ناشی از 15 مدل AOGCM تحت تأثیر سه سناریو انتشار A1B، A2 و B1 به بررسی تغییرات پارامترهای حداقل دما، حداکثر دما و بارندگی در ایستگاه سینوپتیک مشهد واقع در حوضه قره قوم پرداخته شود. از مدل LARS-WG به منظور ریزمقیاس نمایی استفاده گردید. توانایی بالای مدل LARS-WG در شبیه‌سازی پارامترهای اقلیمی در دوره پایه تأیید شد؛ به‌طوری‌که مقادیر مدل نسبت به مقادیر مشاهده‌شده در تمامی ماه‌ها دقت خوبی را دارا بوده است. نتایج حاکی از وجود بیشترین باند عدم قطعیت در برآوردهای مربوط به سناریو A1B بود، ولی در مورد کمترین باند عدم قطعیت در مورد پارامترهای مختلف نتایج متفاوتی به دست آمد که برای حداقل دما و بارندگی سناریو B1 و برای حداکثر دما سناریو A2 معرفی گردید.

Effects of fuel and forest conservation on future levels of atmospheric carbon dioxide

Tree restoration is seen as a nature-based solution to climate change, because trees remove carbon from the atmosphere. However, tree cover can influence surface temperatures in other ways, for example by changing albedo and enhancing evapotranspiration. These impacts may, in turn, be affected by increasing atmospheric carbon dioxide concentrations. Here, we present simulations with a coupled atmosphere-land-slab-ocean model to investigate how doubled atmospheric carbon dioxide levels affect warming in a high-end scenario where afforestation covers a land area 35% larger than the USA. Changes in albedo, changes in evapotranspiration, and forest biogenic volatile organic compound emissions combined result in reduced warming by 0.06+/-0.04 K in the afforestation scenario with doubled carbon dioxide scenario, compared with afforestation in a baseline scenario with present-day carbon dioxide levels. This reduced warming is largely due to less snow in the Northern Hemisphere and thus less surface darkening. Similarly, tree carbon sequestration enhances cooling by 0.20 K in the afforestation/doubled carbon dioxide scenario, compared to an afforestation/present-day carbon dioxide scenario . We conclude that in a world with doubled atmospheric carbon dioxide concentrations, the climate mitigation potential of tree restoration is only minimally affected.

Limits to Paris compatibility of CO2 capture and utilization