Global Warming Targets Research Articles

Understanding Climate Change by Modeling the Earth's Atmosphere as a Well‐Stirred Tank

AbstractComing to terms with climate change by understanding climate processes and their policy implications is essential not only for climate scientists and policymakers, but also for the general public, for industrial practitioners, and for engineers, including process system engineers. We have developed a simplified linear climate model (SLCM) to enable non‐specialists to explore the essential physical and chemical processes caused by greenhouse gas emissions. Trading‐off simplicity and accuracy, achieved by calibrating model parameters using established simple climate models, the SLCM allows (i) determining the climate impact of given past and future emissions, (ii) determining the amounts of CO2 removal needed to compensate for any unavoidable emissions of CH4 and N2O from agriculture, and (iii) back‐calculating emission pathways to meet specified global warming targets.

Impacts of climate change on diarrhoeal disease hospitalisations: How does the global warming targets of 1.5-2°C affect Dhaka, Bangladesh?

Dhaka is one of the world's densely populated cities and faces significant public health challenges including high burden of diarrhoeal diseases. Climate change is intensifying existing environmental problems including urban heat island effect and poor water quality. While numerous epidemiological studies have linked meteorological factors to diarrhoeal diseases in Bangladesh, assessment of the impacts of future climate change on diarrhoeal diseases is scarce. We provide the assessment of climate change impacts on diarrhoeal disease in Dhaka and project future health risks under climate change scenarios. About 3 million acute diarrhoea cases presenting to the Dhaka Hospital of the International Centre for Diarrhoeal Disease Research Bangladesh (icddr,b) during 1981-2010 were linked to daily temperature, rainfall and humidity and association investigated using time series adapted negative binomial regression models employing constrained distributed lag linear models. The findings were applied to climate projections to estimate future risks of diarrhoea under various global warming scenarios. There was a significantly raised risk of diarrhoea hospitalisation in all ages with daily mean temperature (RR: 3.4, 95% CI: 3.0-3.7) after controlling for the confounding effects of heavy rainfall, humidity, autocorrelations, day of the week effect, long-term time, and seasonal trends. Using the incidence rate ratio (IRR) of 1.034, temperature increases based on the global warming targets of 1.5-2°C could result in an increase of diarrhoea hospitalisations by 4.5-7.4% in all age groups by the 2100s. These effects were more pronounced among <5 children where the predicted temperature increases could raise diarrhoea hospitalisation by 5.7% - 9.4%. Diarrhoea hospitalisation will increase significantly in Dhaka even if the global warming targets adopted by the Paris Agreement is reached. This underscores the importance of preparing the city for management and prevention of diarrhoeal diseases.

Resetting tropospheric OH and CH4 lifetime with ultraviolet H2O absorption.

The decay of methyl chloroform, a banned ozone-depleting substance, has provided a clear observational metric of mean tropospheric hydroxyl radical (OH) abundance. Almost all current global chemistry models calculate about 15% too much OH and thus too rapid methane loss. Methane is a short-lived climate forcer, critical to achieving global warming targets, and this error affects our model projections of climate change. New observations of water vapor absorption in the ultraviolet region (290 to 350 nanometers) imply reductions in sunlight with key photolysis rates decreasing by 8 to 12% in the near-surface tropical atmosphere. Incorporation of this new mechanism in a chemistry-transport model reduces OH and methane loss by only 4%, but combined with other proposed mechanisms, such as tropospheric halogen chemistry (7%), we may be able to resolve this conundrum.

Global wheat planting suitability under the 1.5°C and 2°C warming targets.

The potential distribution of crops will be impacted by climate change, but there is limited research on potential wheat distributions under specific global warming targets. This study employed the Maxent model to predict the potential distribution of wheat under the 1.5°C and 2°C warming targets based on data from the Inter-Sectoral Impact Model Intercomparison Project (ISI-MIP) multimodel ensemble, and the effect of global warming on wheat planting suitability was analyzed. Our results indicated global warming would significantly change wheat planting suitability. Over half of the areas experienced changes in wheat planting suitability under two warming targets, and the effect became more pronounced with increasing temperatures. Additionally, global warming might promote wheat planting in more regions. The area with an increase in wheat planting suitability was observed to be 9% higher than those experiencing a decrease on average. Moreover, global warming could exacerbate the disparity between global wheat supply and demand in countries/regions. Traditional wheat-producing countries/regions are poised to benefit from the warming effects of climate change, while less developed and wheat import-dependent countries/regions may face greater challenges in achieving wheat self-sufficiency. To address this potential challenge, the promotion and inter-regional exchange of agronomic technologies, and the development of more rational trade standards are urgently needed. Since socioeconomic factors have a significant impact on wheat cultivation, further investigation is required to determine how the wheat planting distribution may change in the future under the combined impact of climate change, supply-demand relationship, and policy.

Valorizing inherent resources from waste streams for in-situ CO2 capture and sequestration in the steel industry

The imperative need for decarbonization within the energy-intensive steel industry, a pivotal sector for meeting global warming mitigation targets, underscores the significance of deploying cost-effective CO2 capture and sequestration (CCS) measures. The substantial external costs and resource consumption associated with traditional CCS methods present practical challenges. Here, we proposed a pragmatic strategy to integrate CCS into the steel industry through recycling inherent resources from steelmaking waste streams for in-situ CCS (ICCS). The composites prepared from blast furnace slag (BFS) and steel slag (SS) demonstrated the capacity to capture a maximum of 2.77 mol/kg of CO2 from the simulated flowing flue gas at 75 °C, and the energy required could be sourced from steelmaking waste heat. Comprehensive characterizations revealed the evolution of phase compositions and pore structures in different BFS/SS-incorporated composites, providing insights into accelerating the carbonation by elevating temperatures and SS dosages. Notably, ICCS strategy was validated to offer significant potential in CO2 emission reduction (up to −570.0 kg CO2e/t) normalized by compressive strength of the conventional construction materials. Overall, ICCS strategy can minimize the external resource consumption and additional units for implementing collaborative waste recycling in the steel industry with significant environmental benefits.

An environmental evaluation of potentially optimal regions for solar plant construction in China

Owing to the huge environmental costs and socioeconomic losses caused by burning fossil fuels, renewable energy has become a heated topic for researchers to investigate on. Accordingly, solar energy (e.g., photovoltaic energy or PV energy), renowned for being an eco-friendly power source, emerges as a crucial subject for investigation, particularly within the context of global warming and net-zero carbon economy targets. To expedite the production of PV power in China, this study aims to assess the environmental suitability of potential regions optimal for the construction of solar plants within the country. By collecting data in different regions of China based on various factors (including environmental and socioeconomic factors), innovative evaluation metrics are developed, which produce a score for each regions suitableness for constructing solar power plants. According to the evaluation framework for solar plant construction, each region can be ranked easily according to those scores. The results suggest that Tibet is the optimal province for PV power production, with Gar identified as the most favorable area within Tibet; meanwhile, Chongqing exhibits the lowest potential for solar plant construction among all evaluated regions. The insights derived from this study can provide a vital reference for corporations and government entities in making informed decisions on the location for the development of large-scale solar power installations.

Projected changes in Köppen‒Trewartha climate zones under 1.5–4 °C global warming targets over mid-high latitudes of Northern Asia using an ensemble of RegCM4 simulations

Mid-high latitude Northern Asia is one of the most vulnerable and sensitive areas to global warming, but relatively less studied previously. We used an ensemble of a regional climate model (RegCM4) projections to assess future changes in surface air temperature, precipitation and Köppen‒Trewartha (K‒T) climate types in Northern Asia under the 1.5–4 °C global warming targets. RegCM4 is driven by five CMIP5 global models over an East Asia domain at a grid spacing of 25 km. Validation of the present day (1986–2005) simulations shows that the ensembles of RegCM4 (ensR) and driving GCMs (ensG) reproduce the major characters of the observed temperature, precipitation and K‒T climate zones reasonably well. Greater and more realistic spatial detail is found in RegCM4 compared to the driving GCMs. A general warming and overall increases in precipitation are projected over the region, with these changes being more pronounced at higher warming levels. The projected warming by ensR shows different spatial patterns, and is in general lower, compared to ensG in most months of the year, while the percentage increases of precipitation are maximum during the cold months. The future changes in K‒T climate zones are characterized by a substantial expansion of Dc (temperature oceanic) and retreat of Ec (sub-arctic continental) over the region, reaching ∼20% under the 4 °C warming level. The most notable change in climate types in ensR is found over Japan (∼60%), followed by Southern Siberia, Mongolia, and the Korean Peninsula (∼40%). The largest change in the K‒T climate types is found when increasing from 2 to 3 °C. The results will help to better assess the impacts of climate change and in implementation of appropriate adaptation measures over the region.

Land-free bioenergy from circular agroecology—a diverse option space and trade-offs

Bioenergy from energy crops is a source of negative emissions and carbon-neutral fuels in many 1.5/2 ∘C IPCC pathways. This may compete with other land uses. In contrast, ancillary biomass like by-products and waste is not primarily grown for energy and thus without land/food/feed competition. Here, we examine the availability and environmental impacts of ancillary bioenergy from agricultural sources under 190 circular agroecological strategies using the global food-system model SOLm for the year 2050. We find that there is a diverse option space for the future food and energy system to meet both global warming targets (1.5 ∘C) and food system sustainability (medium to highly organic) – a similar range of ancillary bioenergy global potential (55–65 EJ)from very different food systems (50%–75% organic agriculture and various levels of waste and concentrate feeding reduction). We find three trade-offs between food system sustainability and ancillary bioenergy provision. First, there is a clear trade-off between nutrient recycling and negative emissions potential. 1.4–2.6 GTCO2eq of negative emissions supplied through ancillary bioenergy with carbon capture and storage comes at the cost of nutrient deficits and resulting incompatibility with even a medium degree of organic farming. Second, reducing feed from croplands increases the ancillary bioenergy production with low shares of organic agriculture and reduces it for high shares. Third, food waste reduction reduces ancillary bioenergy provision. Hence, the sustainable transformation of the food system towards a less animal-based diet and waste reduction may conflict with a higher ancillary bioenergy provision, especially when the organic share is high as well. The policy implication of our results is that ancillary bioenergy can provide a similar range of future bioenergy as foreseen in IPCC AR6 illustrative pathways (±10% ) without additional land use or compromising food availability. However, higher ancillary bioenergy provision or additional negative emissions compete with food system sustainability; hence, we recommend policymakers consider aligning energy system planning with the compatibility of sustainable food systems simultaneously.

Impact of anthropogenic warming on emergence of extreme precipitation over global land monsoon area

Human activities have led to a global temperature increase, and the primary objective of the Paris Agreement is to limit this rise to 1.5 °C of warming level. Understanding the impact of global warming beyond preindustrial conditions on precipitation intensity is crucial for devising effective adaptation and mitigation strategies, particularly in densely populated global land monsoon (GLM) regions. However, the time of emergence (ToE) of extreme summer monsoon precipitation and its dependency on global warming targets has rarely been investigated. Using large ensemble simulations forced by the SSP3–7.0 scenario, we reveal that the impacts of anthropogenic forcing on extreme precipitation intensity become evident in GLM regions before 2050, accompanied by a sudden expansion in areas where the ToE of extreme precipitation occurs. Furthermore, our study demonstrates that achieving the Paris Agreement goal at 1.5 °C of global warming level can prevent the ToE of extreme precipitation in Asian and African monsoon regions. This, in turn, has the potential to halve the number (over one billion) of individuals exposed to extreme precipitation. These findings highlight the urgent need for action to mitigate the risk associated with anthropogenic warming induced climate change.

Techno-economic assessment of integrated NH3-power co-production with CCS and energy storage in an LNG regasification terminal

Energy efficiency and carbon capture and storage (CCS) are two key levers to attain global warming targets. Integration of various industrial and energy processes as well as complementary use of fuels with low carbon intensity such as natural gas with renewable sources will enable to mitigate environmental impacts in a cost competitive manner. This study proposes one such opportunity through integration of LNG cold exergy utilization for liquid N2 energy storage during regasification coupled to a novel NH3-electricity co-production scheme with CCS. A techno-economic benchmarking between standalone NH3 production process with net electricity imports (Case A), an integrated co-production solution (Case B) and non-integrated co-production plant with a standard combined cycle for power generation (Case C) is performed. Base economic assumptions are a natural gas price of 6.5 €/ton, CO2 tax of 100 €/ton, NH3 selling price of 400 €/ton and electricity average price of 80 €/MWh. At varying power generation capacity factors CFEl ranging from 30 to 50%, the electricity price premium required by the co-production schemes to break even with Case A is 2.5–9.9 €/MWh lower for Case B compared to Case C, with a premium as low as 12.9 €/MWh at 50% CFEl for the former when 2 days' worth of energy storage capacity is constructed. Thus, integration improves economic competitiveness for short storage times, applicable to regions with reliable year-round solar resources. However, the competitive advantage disappears when storage periods longer than one week are considered, such as power systems with high wind shares or seasonal solar availability.

Differences of East Asian Summer Monsoon Precipitation Responses between Transient and Stabilization Simulations

The differences between the two global warming targets of the Paris Agreement, 1.5 °C and 2 °C above pre-industrial levels, have drawn much attention from the scientific community. However, there is a remaining gap to distinguish regional climate responses in these two most typical pathways, i.e., transient and stabilization simulations, toward specific warming levels. In this study, we discern the East Asia summer monsoon (EASM) responses between these two types of simulations at low-warming targets, based on the fully coupled community Earth system model (CESM). The two types of responses display a similar increase pattern in the EASM precipitation. However, the quantitative differences between these two types of responses are as large as those between the 1.5 °C and 2 °C warming scenarios. The moist budget analysis reveals that the EASM precipitation differences are mainly caused by the thermodynamic, dynamic, and transient eddy effects. Specifically, the thermodynamic effect contributes to the precipitation increment in the coastal area of East Asia in both types of responses, with the enhanced low-level specific humidity. The dynamic contribution shows tripolar and bipolar patterns in East Asia in the transient and stabilization responses, respectively. Remarkably, the transient eddy effect contribution emerges only in the stabilization responses. Further, we reveal the dominant role of the East Asian subtropical jet (EASJ) in determining the contributions from dynamic and transient eddy effects. The changes in the EASJ’s position and intensity are greatly regulated by the temperature change patterns at the mid-high levels in response to different greenhouse gas emission pathways. Our study highlights the differences between transient and stabilization climate states on a regional scale.

Constraining the Nineteenth-Century Temperature Baseline for Global Warming

Abstract Since the Paris Agreement, climate policy has focused on 1.5° and 2°C maximum global warming targets. However, the agreement lacks a formal definition of the nineteenth-century “pre-industrial” temperature baseline for these targets. If global warming is estimated with respect to the 1850–1900 mean, as in the latest IPCC reports, uncertainty in early instrumental temperatures affects the quantification of total warming. Here, we analyze gridded datasets of instrumental observations together with large-scale climate reconstructions from tree rings to evaluate nineteenth-century baseline temperatures. From 1851 to 1900 warm season temperatures of the Northern Hemisphere extratropical landmasses were 0.20°C cooler than the twentieth-century mean, with a range of 0.14°–0.26°C among three instrumental datasets. At the same time, proxy-based temperature reconstructions show on average 0.39°C colder conditions with a range of 0.19°–0.55°C among six records. We show that anomalously low reconstructed temperatures at high latitudes are underrepresented in the instrumental fields, likely due to the lack of station records in these remote regions. The nineteenth-century offset between warmer instrumental and colder reconstructed temperatures is reduced by one-third if spatial coverage is reduced to those grid cells that overlap between the different temperature fields. The instrumental dataset from Berkeley Earth shows the smallest offset to the reconstructions indicating that additional stations included in this product, due to more liberal data selection, lead to cooler baseline temperatures. The limited early instrumental records and comparison with reconstructions suggest an overestimation of nineteenth-century temperatures, which in turn further reduces the probability of achieving the Paris targets. Significance Statement The warming targets formulated in the Paris Agreement use a “pre-industrial” temperature baseline that is affected by significant uncertainty in the instrumental temperature record. During the second half of the nineteenth century, much of the continental landmasses were not yet covered by the observational station network and existing records were often subject to inhomogeneities and biases, thus resulting in uncertainty regarding the large-scale mean temperature estimate. By analyzing summer temperature reconstructions from tree-rings for the Northern Hemisphere extratropical land areas, we examine an independent climate archive with a typically broader and more continuous spatial extent during the “pre-industrial” period. Despite the additional uncertainty when using climate reconstructions instead of direct observations, there is evidence for an overestimation of land temperature during the summer season in early instrumental data. Colder early instrumental temperatures would reduce the probability of reaching the Paris targets.

Identification of regional pattern of climate change risk in China under different global warming targets

Identification of regional pattern of climate change risk in China under different global warming targets

Change in Temperature Extremes over India Under 1.5 °C and 2 °C Global Warming Targets

Change in Temperature Extremes over India Under 1.5 °C and 2 °C Global Warming Targets

Modeling forest above-ground biomass using freely available satellite and multisource datasets

Achieving the 2 °C global warming target will require all stakeholders, from local to global, to accelerate carbon reduction plans. To properly estimate carbon amounts sequestered and stored by forests, these stakeholders need accurate maps of forest above-ground biomass (AGB). However, AGB maps are developed solely by researchers using methodologies that are typically difficult for non-researchers to understand. To ensure that non-researchers can prepare such maps, freely available open-source datasets are needed along with a simple AGB estimation method. Remote sensing data have become widely used, and some satellite images are provided as open-source data. However, few AGB estimation studies have relied exclusively on freely available datasets. This study, therefore, examined the capability of using open-source satellite and multisource datasets to estimate AGB for two contrasting test sites in Hokkaido, Japan, and for the two sites combined (the unified sites). Test site 1 contained three forest types on a hilly terrain, while test site 2 contained one dominant forest type on a flat terrain. The datasets used were L-band backscatter, a canopy height model, slope, aspect, annual mean temperature, annual precipitation, and forest type. Three machine-learning algorithms and one parametric algorithm were compared. The results showed that the machine-learning models outperformed the parametric model in all instances, reproducing low and high AGB values properly with reduced saturation issues. A variable importance analysis revealed that in the best-performing machine-learning models, forest type and annual precipitation were the two most important variables for test site 1 and the unified sites, and another climatic factor, annual mean temperature, rose in rank for the unified sites. These variables had relatively large intra-variability and inter-variability in common, both of which appear to have offered advantages in modeling AGB for the sites where AGB variability was large. In contrast, the synthetic aperture radar (SAR)-based variables (the backscatter and the canopy height model) ranked lower in relative importance. This may reflect the negative influence of hilly terrain of test site 1 (and the unified sites) on the precision of SAR-based datasets. For test site 2, with its flat terrain, these SAR-based variables were the two dominant variables. Our results show the promise of freely available satellite and multisource datasets for modeling AGB and the important roles that non-SAR-based variables may play in large-scale AGB mapping that includes varied terrain.

Challenge of Sustainability: Turning Science into Art

&#x0D; &#x0D; &#x0D; This paper addresses the critical question of how to turn climate concern into climate action as we move forward towards the 1.5 degree Celsius global warming target adopted by COP 26 in 2021 and reaffirmed by COP 27 in 2022. It argues that it has taken scientists more than a Century to accept, first: that climate change is real and second: that it is anthropogenic. Scientists still continue to debate the precise effects of greenhouse gases on weather, fires, floods and food security. Climate optimists continue to rely on the search for new miracle technologies, such as fusion energy or carbon capture. This is all very good. But this is the easy part. What is more critical is to motivate people towards collective action in pursuit of a zero-emission target. This requires harnessing the art of fostering humanist, economically just, collective action rooted in local commitment and transparency. The real challenge of sustainability today is to turn science into art. We do not have over a century and half, as the scientists did to practice this art. Repeatedly, pointing to climate change apocalypse will not be enough.&#x0D; &#x0D; &#x0D;

The Inequities of National Adaptation to Climate Change

With global efforts to mitigate climate change lagging behind what is necessary to achieve Paris Agreement global warming targets, global mean temperatures are increasing, and weather extremes are becoming more frequent and more severe. When mitigation falters, adaptation to current and anticipated future climate conditions becomes increasingly urgent. This study provides a novel collection of adaptive capacity and adaptation readiness indicators, which it aggregates into a composite adaptation index to assess the relative adaptation performance of nations. Adaptation performance is assessed using two complementary techniques, a distance to frontier analysis and a dominance analysis. Developed countries perform relatively well and developing countries perform relatively poorly in both exercises. Adaptation performance is found to be closely and positively related to both national income per capita and greenhouse gas emissions per capita, highlighting the inequities of global adaptation performance. These adaptation inequities are consistent with the IPCC assessment that nations most affected by climate change are those that are least able to adapt and contribute least to the problem, creating a need for assistance from developed countries.

Adaptive emission reduction approach to reach any global warming target

Adaptive emission reduction approach to reach any global warming target

Potential impacts of climate extremes on snow under global warming conditions in the Mongolian Plateau

PurposeThe paper aims to investigate the possible changes in mean temperature in the Mongolian Plateau associated with the 1.5 and 2°C global warming targets and how snow changes in the Mongolian Plateau when the mean global warming is well below 2°C or limited to 1.5°C.Design/methodology/approachIn total, 30 model simulations of consecutive temperature and precipitation days from Coupled Model Inter-comparison Project Phase 5 (CMIP5) are assessed in comparison with the 111 meteorological monitoring stations from 1961–2005. Multi-model ensemble and model relative error were used to evaluate the performance of CMIP5 models. Slope and the Mann–Kendall test were used to analyze the magnitude of the trends and evaluate the significance of trends of snow depth (SD) from 1981 to 2014 in the Mongolian Plateau.FindingsSome models perform well, even better than the majority (80%) of the models over the Mongolian Plateau, particularly HadGEM2-CC, CMCC-CM, BNU-ESM and GFDL-ESM2M, which simulate best in consecutive dry days (CDD), consecutive wet days (CWD), cold spell duration indicator (CSDI) and warm spell duration indicator (WSDI), respectively. Emphasis zones of WSDI on SD were deeply analysed in the 1.5 and 2 °C global warming period above pre-industrial conditions, because it alone has a significant negative relation with SD among the four indices. It is warmer than before in the Mongolian Plateau, particularly in the southern part of the Mongolian Plateau, indicating less SD.Originality/valueProviding climate extremes and SD data sets with different spatial-temporal scales over the Mongolian Plateau. Zoning SD potential risk areas and proposing adaptations to promote regional sustainable development.

CORDEX-EA Phase 2 다중 지역기후모델 앙상블을 이용한 전지구 온난화 제한 목표(1.5, 2.0℃)하에서의 한반도 미래 기온 전망

This study presents a future projection of temperature over the Korean Peninsula (KP) under the global warming targets of 1.5℃ and 2.0℃ set in the 2015 Paris Agreement. For projection, simulation data from the multi-Regional Climate Model (RCM) ensemble in Coordinated Regional Climate Downscaling Experiment (CORDEX)-East Asia (EA) Phase 2 are used. Under the 2.0℃ (1.5℃) global warming condition, mean temperature over KP would increase 2.13℃ (1.51℃) compared to the present period (1985 ~ 2005 years). Extreme minimum and maximum temperature intensity indices (TNn and TXx) would also increase 2.61℃ (1.91℃) and 2.38℃ (1.58℃). In addition, changes in probabilities of extreme temperature events that occurs once in 20 years during the present period are investigated. Extreme cold events would occur once in 28.9 years (22.6 years) and warm events once in 5.9 years (7.2 years). Meanwhile, there are several noteworthy points about the future projection. The temperature over KP would increase more over the northern KP than the southern KP and this feature is more distinct in TNn. The uncertainties of the projection are higher for the 1.5℃ warming condition than the 2.0℃ warming condition and for extreme temperature versus mean temperature. The spatial pattern of change in extreme temperature frequency is different from that of intensity. In other words, a smaller increase in the frequency of extreme cold events is expected over the inland KP.