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Abstract Many insects utilise optical information in linearly polarised light for navigation, with the degree of linear polarisation (DoLP) determining whether the ‘visibility’ of such optical information is available to them. However, changes in degree of linear polarisation in response to increased atmospheric levels of fine particulate matter (PM2.5) are poorly understood. We present analyses based on both ground-based monitoring and particulate matter modelling, establishing a quantitative relationship between PM2.5 mass concentration and the DoLP. We apply this relationship to a global PM2.5 projection for 2050 and estimate the increase in number and spatial extent of low visibility days for honeybees. We find an increase by up to 20% in the geographical extent of low visibility days in 2050, with an augmented frequency of low visibility days across an area exceeding 0.75 million km2 in India and 2 million km2 in China. More frequent and widespread low visibility conditions can reduce the ability of insects to navigate, especially in hotspot regions.

Abstract Satellites provide global coverage for monitoring atmospheric greenhouse gases, crucial for understanding global climate dynamics. However, their temporal and spatial resolutions fall short in detecting urban‐scale variations. To enhance satellite reliability over urban areas, this study presents the first comprehensive analysis of long‐term observations of column‐averaged dry air mole fractions of CO2, CH4, and CO (XCO2, XCH4, XCO) using two ground‐based fourier transform infrared spectrometers, EM27/SUNs, in a megacity. With over 2 years of observations, our study shows that EM27/SUN measurements can effectively capture the daily and seasonal variability of XCO2, XCH4, and XCO over Seoul, a megacity with complex topography and various emission sources. In addition, we use the advantage of having multiple greenhouse gas satellites targeting Seoul to compare with the EM27/SUNs. Our study highlights the importance of EM27/SUN observations in Seoul to identify the need for improvements in satellites to monitor greenhouse gas behaviors and emissions in urban areas.

Abstract Marine heatwave (MHW), a prolonged period of anomalously warm seawater, has a catastrophic repercussion on marine ecosystems. With global warming, MHWs have become increasingly frequent, intense, and prolonged. To avoid irreversible damages from such extreme events, net‐zero carbon emissions by the 2050s, called carbon neutrality, were proposed. Here, we evaluate the impact of carbon neutrality on MHWs in the late 21st century using multi‐model projections from the Coupled Model Intercomparison Project Phase 6 (CMIP6) Shared Socioeconomic Pathway (SSP) 1–1.9 and SSP3‐7.0 scenarios. It is found that if the current regional rivalry over carbon emissions continues (i.e., SSP3‐7.0), the MHWs in the late 21st century will become stronger and longer than historical ones, especially in the western boundary current and equatorial current regions. Approximately 68% of the global ocean will be exposed to permanent MHWs, regionally 93% in the Indian Ocean, 76% in the Pacific Ocean, 68% in the Atlantic Ocean, 65% in the Coastal Ocean, and 48% in the Southern Ocean. Such MHWs can be significantly reduced by achieving carbon neutrality (i.e., SSP1‐1.9). In particular, the spatial proportion of the ocean exposed to permanent MHWs can be reduced to as low as 0.02%–0.07%, depending on the regions. This result underscores the critical importance of ongoing efforts to achieve net‐zero carbon emissions to reduce the potential ecological risks induced by extreme MHWs.

Abstract Climate extremes, such as hot temperature and heavy precipitation events, have devastating effects on human societies. As the planet gets warmer, they have become more intense and more frequent. To avoid irreversible damages from climate extremes, many countries have committed to achieving net‐zero anthropogenic carbon emissions, or carbon neutrality, by the 2050s. Here, we quantify the impact of carbon neutrality on population exposure to climate extremes using multi‐model projections from the Coupled Model Intercomparison Project Phase 6 (CMIP6) Shared Socioeconomic Pathway (SSP)1‐1.9 and SSP3‐7.0 scenarios. It is found that the increasing population exposure to hot‐temperature and heavy‐precipitation extremes under SSP3‐7.0 scenario can be substantially reduced by 87%–98% in the late 21st century by achieving the carbon neutrality based on SSP1‐1.9 scenario. The benefits of carbon neutrality are particularly pronounced in Africa and Asia. The potential benefits of carbon neutrality are also significant in North America, Europe, and Oceania, where a reduction in climate extremes is more than twice as important as population decline in reducing population exposure to climate extremes. These results provide important scientific support for ongoing efforts to achieve net‐zero carbon emissions by the 2050s to reduce potential climate risk and its inequity across continents.

Near-real time observations of aerosol properties could have a potential to improve the accuracy of XCO2 retrieval algorithm in operational satellite missions. In this study, we developed a retrieval algorithm of XCO2 (Yonsei Retrieval Algorithm; YCAR) based on the Optimal Estimation (OE) method that used aerosol information at the location of the Orbiting Carbon Observatory-2 (OCO-2) measurement from co-located measurement of the Afternoon constellation (A-train) such as the Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) onboard the Cloud-Aerosol Lidar and Infrared Pathfinder Observation (CALIPSO) and the MODerate-resolution Imaging Spectrometer (MODIS) onboard the Aqua. Specifically, we used optical depth, vertical profile, and optical properties of aerosol from MODIS and CALIOP data. We validated retrieval results to the Total Carbon Column Observing Network (TCCON) ground-based measurements and found general consistency. The impact of observed aerosol information and its constraint was examined by retrieval tests using different settings. The effect of using additional aerosol information was analyzed in connection with the bias correction process of the operational retrieval algorithm. YCAR using a priori aerosol loading parameters from co-located satellite measurements and less constraint of aerosol optical properties made comparable results with operational data with the bias correction process in three of the four cases subject to this study. Our work provides evidence supporting the bias correction process of operational algorithms and quantitatively presents the effectiveness of synergic use of multiple satellites (e.g. A-train) and better treatment of aerosol information.

Abstract Projections of future carbon sinks and stocks are important because they show how the world's ecosystems will respond to elevated CO2 and changes in climate. Moreover, they are crucial to inform policy decisions around emissions reductions to stay within the global warming levels identified by the Paris Agreement. However, Earth System Models from the 6th Coupled Model Intercomparison Project (CMIP6) show substantial spread in future projections—especially of the terrestrial carbon cycle, leading to a large uncertainty in our knowledge of any remaining carbon budget (RCB). Here we evaluate the global terrestrial carbon cycle projections on a region‐by‐region basis and compare the global models with regional assessments made by the REgional Carbon Cycle Assessment and Processes, Phase 2 activity. Results show that for each region, the CMIP6 multi‐model mean is generally consistent with the regional assessment, but substantial cross‐model spread exists. Nonetheless, all models perform well in some regions and no region is without some well performing models. This gives confidence that the CMIP6 models can be used to look at future changes in carbon stocks on a regional basis with appropriate model assessment and benchmarking. We find that most regions of the world remain cumulative net sources of CO2 between now and 2100 when considering the balance of fossil‐fuels and natural sinks, even under aggressive mitigation scenarios. This paper identifies strengths and weaknesses for each model in terms of its performance over a particular region including how process representation might impact those results and sets the agenda for applying stricter constraints at regional scales to reduce the uncertainty in global projections.

The seasonal greening of Northern Hemisphere ecosystems due to extended growing periods and enhanced photosynthetic activity is, via experiments, shown to modify near-surface warming by perturbing land-atmosphere energy exchanges.

Abstract Background Cities are a major source of atmospheric CO2; however, understanding the surface CO2 exchange processes that determine the net CO2 flux emitted from each city is challenging owing to the high heterogeneity of urban land use. Therefore, this study investigates the spatiotemporal variations of urban CO2 flux over the Seoul Capital Area, South Korea from 2017 to 2018, using CO2 flux measurements at nine sites with different urban land-use types (baseline, residential, old town residential, commercial, and vegetation areas). Results Annual CO2 flux significantly varied from 1.09 kg C m− 2 year− 1 at the baseline site to 16.28 kg C m− 2 year− 1 at the old town residential site in the Seoul Capital Area. Monthly CO2 flux variations were closely correlated with the vegetation activity (r = − 0.61) at all sites; however, its correlation with building energy usage differed for each land-use type (r = 0.72 at residential sites and r = 0.34 at commercial sites). Diurnal CO2 flux variations were mostly correlated with traffic volume at all sites (r = 0.8); however, its correlation with the floating population was the opposite at residential (r = − 0.44) and commercial (r = 0.80) sites. Additionally, the hourly CO2 flux was highly related to temperature. At the vegetation site, as the temperature exceeded 24 ℃, the sensitivity of CO2 absorption to temperature increased 7.44-fold than that at the previous temperature. Conversely, the CO2 flux of non-vegetation sites increased when the temperature was less than or exceeded the 18 ℃ baseline, being three-times more sensitive to cold temperatures than hot ones. On average, non-vegetation urban sites emitted 0.45 g C m− 2 h− 1 of CO2 throughout the year, regardless of the temperature. Conclusions Our results demonstrated that most urban areas acted as CO2 emission sources in all time zones; however, the CO2 flux characteristics varied extensively based on urban land-use types, even within cities. Therefore, multiple observations from various land-use types are essential for identifying the comprehensive CO2 cycle of each city to develop effective urban CO2 reduction policies.

This study analyzed the sensitivities of carbon cycle to surface air temperature using the CO _2 flux data collected from June to September for six years (2014–2019) over a moist tundra site in Council, Alaska. The tundra ecosystem was a strong sink of carbon in June and July, a weak sink in August with rapidly decreasing photosynthesis, and a carbon source in September. The ecosystem respiration (Re) and gross primary production (GPP) were obtained from the net ecosystem exchange (NEE) of eddy-covariance system. Both the Re and GPP increased with temperature, enhancing carbon emission and uptake during observation period. Notably, Re showed higher sensitivity to temperature than GPP did. This result means that as global warming continues, the increase in carbon release is greater than the increase in carbon uptake. In other words, the tundra ecosystem is expected to become a weaker carbon sink in June and July and a stronger source of carbon in September. Possible mechanism of different temperature sensitivities of Re and GPP as well as temporal variations of temperature sensitivities are suggested. Present results highlight the importance of understanding the temperature sensitivities of Re and GPP in various tundra ecosystems to accurately understand changes in the carbon cycle in the Arctic region.

Anomalous warming in the Arctic region of the Barents-Kara Sea is associated with cold damage and reduced springtime vegetation activity in East Asian forests, according to a correlation analysis of Arctic warming and leaf area anomalies in East Asia.

Abstract Background Understanding a carbon budget from a national perspective is essential for establishing effective plans to reduce atmospheric CO2 growth. The national characteristics of carbon budgets are reflected in atmospheric CO2 variations; however, separating regional influences on atmospheric signals is challenging owing to atmospheric CO2 transport. Therefore, in this study, we examined the characteristics of atmospheric CO2 variations over South and North Korea during 2000–2016 and unveiled the causes of their regional differences in the increasing rate of atmospheric CO2 concentrations by utilizing atmospheric transport modeling. Results The atmospheric CO2 concentration in South Korea is rising by 2.32 ppm year− 1, which is more than the globally-averaged increase rate of 2.05 ppm year− 1. Atmospheric transport modeling indicates that the increase in domestic fossil energy supply to support manufacturing export-led economic growth leads to an increase of 0.12 ppm year− 1 in atmospheric CO2 in South Korea. Although enhancements of terrestrial carbon uptake estimated from both inverse modeling and process-based models have decreased atmospheric CO2 by up to 0.02 ppm year− 1, this decrease is insufficient to offset anthropogenic CO2 increases. Meanwhile, atmospheric CO2 in North Korea is also increasing by 2.23 ppm year− 1, despite a decrease in national CO2 emissions close to carbon neutrality. The great increases estimated in both South Korea and North Korea are associated with changes in atmospheric transport, including increasing emitted and transported CO2 from China, which have increased the national atmospheric CO2 concentrations by 2.23 ppm year− 1 and 2.27 ppm year− 1, respectively. Conclusions This study discovered that economic activity is the determinant of regional differences in increasing atmospheric CO2 in the Korea Peninsula. However, from a global perspective, changes in transported CO2 are a major driver of rising atmospheric CO2 over this region, yielding an increase rate higher than the global mean value. Our findings suggest that accurately separating the contributions of atmospheric transport and regional sources to the increasing atmospheric CO2 concentrations is important for developing effective strategies to achieve carbon neutrality at the national level.

Abstract Increased concentration of airborne particulate matter (PM) in the atmosphere alters the degree of polarization of skylight which is used by honeybees for navigation during their foraging trips. However, little has empirically shown whether poor air quality indeed affects foraging performance (foraging trip duration) of honeybee. Here, we show apparent increases in the average duration of honeybee foraging during and after a heavy air pollution event compared with that of the pre‐event period. The average foraging duration of honeybees during the event increased by 32 min compared with the pre‐event conditions, indicating that 71% more time was spent on foraging. Moreover, the average foraging duration measured after the event did not recover to its pre‐event level. We further investigated whether an optical property (Depolarization Ratio, DR) of dominant PM in the atmosphere and level of air pollution (fine PM mass concentration) affect foraging trip duration. The result demonstrates the DR and fine PM mass concentration have significant effects on honeybee foraging trip duration. Foraging trip duration increases with decreasing DR while it increases with increasing fine PM mass concentration. In addition, the effects of fine PM mass concentration are synergistic with overcast skies. Our study implies that poor air quality could pose a new threat to bee foraging.

There are big uncertainties in the contribution of irrigation to crop yields. Here, the authors use Bayesian model averaging to combine statistical and process-based models and quantify the contribution of irrigation for wheat and maize yields, finding that irrigation alone cannot close yield gaps for a large fraction of global rainfed agriculture.

Abstract Population aging, an increasing share of the elderly to the total population, can exacerbate heat vulnerability to intensified heat hazards. However, the aging impacts on increases in exposure of the elderly to unprecedented hot summers (UHSs) could be variable in the warming climate. Here, we present considerable contribution of age structure changes to increases in the elders' exposure to intensified UHSs in countries with a high percentage of youth population, namely, China, India, and Brazil, by analyzing combined scenarios of climate change with population structure. In the aforementioned regions, increases in exposure to stronger UHSs relevant to rapid aging will exceed at least half of the warming impact, which primarily causes frequent occurrence of stronger UHSs. Conversely, the United States and Europe, which have already entered an aged society, show a negligible aging impact. These results suggest that the future evolution of a society's age structure is an important constraint for projecting population exposure to strengthened summer heat.

Recent studies have reported a 9% decrease in global carbon emissions during the COVID-19 lockdown period; however, its impact on the variation of atmospheric CO _2 level remains under question. Using atmospheric CO _2 observed at Anmyeondo station (AMY) in South Korea, downstream of China, this study examines whether the decrease in China’s emissions due to COVID-19 can be detected from the enhancement of CO _2 mole fraction (ΔCO _2 ) relative to the background value. The Weather Research and Forecasting–Stochastic Time-Inverted Lagrangian Transport model was applied to determine when the observed mole fractions at AMY were affected by air parcels from China. Atmospheric observations at AMY showed up to a −20% (−1.92 ppm) decrease in ΔCO _2 between February and March 2020 compared to the same period in 2018 and 2019, particularly with a −34% (−3.61 ppm) decrease in March. ΔCO, which was analyzed to explore the short-term effect of emission reductions, had a decrease of −43% (−80.66 ppb) during the lockdown in China. Particularly in East China, where emissions are more concentrated than in Northeast China, ΔCO _2 and ΔCO decreased by −44% and −65%, respectively. The ΔCO/ΔCO _2 ratio (24.8 ppb ppm ^−1 ), which is the indicator of emission characteristics, did not show a significant difference before and after the COVID-19 lockdown period ( α = 0.05), suggesting that this decrease in ΔCO _2 and ΔCO was associated with emission reductions rather than changes in emission sources or combustion efficiency in China. Reduced carbon emissions due to limited human activity resulted in a decrease in the short-term regional enhancement to the observed atmospheric CO _2 .

Earth system models (ESMs) are widely used in scientific research to understand the responses of various components of Earth systems to natural and anthropogenic forcings. ESMs embody terrestrial ecosystems on the basis of the leaf area index (LAI) to formulate various interactions between the land surface and atmosphere. Here, we evaluated the LAI seasonality of deciduous forests simulated by 14 ESMs participating in the Coupled Model Intercomparison Project Phase 5 (CMIP5) and CMIP6 to understand the efficacy of recent ESMs in describing leaf dynamics in the northern extratropics from 1982 to 2014. We examined three indicators of LAI seasonality (annual mean, amplitude, and phase) and three phenological dates (start (SOS), end (EOS), and length of growing season (LOS)) of the models in comparison to the third-generation LAI of Global Inventory Modeling and Mapping Studies (GIMMS LAI _3g ) and the Climate Research Unit gridded time series dataset. CMIP6 models tend to simulate larger annual means (1.7 m ^2 m ^−2 ), weaker amplitudes (0.9 m ^2 m ^−2 ), and delayed phases (226 DOY) compared to the GIMMS LAI _3g (1.2 m ^2 m ^−2 , 1.2 m ^2 m ^−2 , and 212 DOY, respectively), yet are similar to the CMIP5 models (2.2 m ^2 m ^−2 , 1.0 m ^2 m ^−2 , and 225 DOY). The later phase is attributed to a systematic positive bias in EOS of the CMIP5 and CMIP6 models (later by 22 and 18 d, respectively) compared to the GIMMS LAI _3g (261 DOY). Further tests on phenological responses to seasonal temperature revealed that the majority of CMIP5 and CMIP6 ESMs inaccurately describe the sensitivities of SOS and EOS to seasonal temperature and the recent changes in mean SOS and EOS distributions (2005–2014 minus 1982–1991). This study suggests that phenology schemes of deciduous forests, especially for autumn leaf senescence, should be revisited to achieve an accurate representation of terrestrial ecosystems and their interactions.

In 2019, an unusually strong positive Indian Ocean Dipole spawned hot and dry weather in southeastern Australia, which promoted devastating wildfires in the period from September 2019 to February 2020. The fires produced large plumes of biomass burning aerosols that prevented sunlight from reaching the Earth’s surface, and in this way elicited regional radiative cooling. We estimated the direct aerosol radiative forcing (ARF) resulting from these wildfires, based on Moderate Resolution Imaging Spectroradiometer space-based data and an empirical relationship from AErosol RObotic NETwork ground-based data collected in biomass-burning regions. The wildfire-derived air pollution was associated with an aerosol optical thickness of >0.3 in Victoria and a strongly negative ARF of between −14.8 and −17.7 W m ^−2 , which decreased the surface air temperature by about 3.7 °C–4.4 °C. This is of the same order of magnitude as the radiative cooling from volcanic eruptions. Although the atmospheric lifetime of biomass-burning aerosols is relatively short (about a week), the Australian wildfire pollution plumes extended across the Pacific Ocean to South America. Since climate change is expected to lead to more frequent and increasingly intense fires in many regions worldwide, the consequent biomass burning aerosols may become a significant radiative forcing factor, which will need to be accounted for in climate model projections for the future.

The production of tea ( Camellia sinensis (L.) Kuntze), the world’s second most consumed beverage, is susceptible to extreme weather events. However, our understanding about the impacts of extreme temperatures and climate change on tea yields remains fairly limited. Here we quantify the historical and predict future fluctuations in tea yield caused by extreme temperatures in China, the largest tea producing country. We found that both heat and cold extremes were associated with significantly reduced tea yields. In the present climate, dominating cold extremes influence more than half of China’s tea production, with a maximum of 56.3% reduced annual production. In the near future, we predict positive net impacts of climate change on tea yield in all study regions at both the 1.5 °C and 2.0 °C global warming levels. Climate warming may diminish the negative impacts of cold extremes to 14%, especially at the current most affected northern tea growing regions (>28° N). However, new areas of yield reduction by intensified heat extremes will emerge, up to 14%–26% yield losses estimated at the Yangtze River (∼30° N) and southern China (

Population ageing, an increase in the older age group’s portion of the total population, worsens the heat tolerance of a society. However, impacts of ageing on the social exposure to projected unprecedented hot summers (UHSs) are uncertain. We show that a shifting of the population distribution towards older ages amplifies the vulnerability of a country to the increasing frequency of UHSs as a result of warming during 2040–2070, especially in most populated regions such as China, India, and sub-Saharan countries. The warming scenarios from Representative Concentration Pathway (RCP) 8.5 are combined with population scenarios from three Shared Socio-economic Pathways (SSPs) SSP2, SSP3, and SSP5 together to estimate the exposure to UHSs. The ageing-driven increase in the exposure of elderly to UHSs ranges 51–198, 91–261, and 47–156 million in China, India, and sub-Saharan countries, respectively, between population scenarios. In China, with decreasing total population, the exposure to UHSs will be increased by rapid population ageing. In India and sub-Saharan countries, the potential of ageing to raise the exposure to UHSs will be even larger than that of warming. In contrast, in aged societies with slow ageing trend, e.g. United States and Europe, the warming mainly increases the exposure to UHSs. Our results suggest the changing age structure could exacerbate a country’s heat vulnerability despite limiting warming to a certain level in the future.

Declining soil moisture related to climate change can greatly affect social, economic, environmental, and hydrological processes, as well as extreme weather events. Hence, it is imperative to understand the timing of significant soil moisture drying under future climate change. Compared to spatial variations in soil moisture drying, however, our understanding of temporal variations remain unclear. In the present study, the timing of significant soil moisture depletion (SSD) is predicted using the soil moisture projection (0–50 cm depth) from the 30 Inter-Sectoral Impact Model Intercomparison Project fast-track outputs under the representative concentration pathways (RCPs) 2.6 and 8.5. Under both RCP scenarios, the ensemble medians of the projections show the emergence of the timing of SSD in Western Europe, Eastern United States, South America, Sub-Saharan Africa, Australia, and Southern China over 40 years (

Wind stilling has been observed in many regions across the Northern Hemisphere; however, the related mechanisms are not well understood. Analyses of the wind speed variations in South Korea during 1993–2015 in this study reveal that the annual-mean surface wind speeds at rural stations have increased by up to 0.41 m s ^−1 decade ^−1 , while those at urban stations have decreased by up to −0.63 m s ^−1 decade ^−1 . The local wind speed variations are found to be negatively correlated with the population density at the corresponding observation sites. Gustiness analyses show the increase in local surface roughness due to urbanization can explain the observed negative wind speed trends at urban stations as the urbanization effect overwhelms the positive wind speed trend due to climate change. The observed negative wind speed trend in urban areas are not found in the regional climate model simulations in the Coordinated Regional Climate Downscaling Experiment—East Asia (CORDEX-EA) as these models do not take into account the impact of urbanization on wind variations during the period. This study suggests that urbanization can play an important role in the recent wind stilling in rapidly developing regions such as South Korea. Our results suggest that future climate projections in CORDEX-EA may overestimate wind speeds in urban areas, and that future regional climate projections need to consider the effects of urbanization for a more accurate projection of wind speeds.

Degradation in air quality could be a potential factor for decreasing solar photovoltaic (PV) power generation. However, our understandings of the potential of airborne particulate matter (PM) to reduce actual solar PV power generation remain unclear. This study quantifies attenuation impacts of airborne PM on solar PV power generation on cloudless days at Yeongam and Eunpyeong-gu power plants installed in the Republic of Korea. The reduction rate of solar PV power generation according to the substantial amount of PM is calculated by constructing multiple regression models based on actual solar PV power generation record, observed meteorological parameters, and measured PM2.5 and PM10 concentrations for 2015–2017. At both power plants, PM2.5 and PM10 commonly reduce solar PV power generation by more than 10% of the maximum capacity under the conditions of ‘normal’ air quality, 35 μ g m ^−3 and 80 μ g m ^−3 for PM2.5 and PM10, respectively. Moreover, the reduction rate of solar PV power generation exceeds 20% of the maximum capacity under ‘bad’ air quality, 75 μ g m ^−3 and 150 μ g m ^−3 for PM2.5 and PM10, respectively. Results show that the negative impacts of PM on solar PV power generation should be considered in the process of policymaking on target solar power generation in Korea, as well as in countries with high PM emissions.

The article presents a study which revisited the trends of amplitude (AMP), especially those in the Southern Hemisphere (SH), by reanalyzing atmospheric records from 49 surface stations across all the latitudes during the period 1980-2018. Topics discussed include changes in surface carbon dioxide fluxes, attributions of changes in the seasonal amplitude of atmospheric carbon dioxide, and processes driving the changes in the seasonality of air-sea carbon dioxide influx in the Southern Ocean.