Natural Climate Solutions for China:The Last Mile to Carbon Neutrality

“I call on all leaders worldwide to declare a State of Climate Emergency in their own countries until carbon neutrality is reached.”–António GUTERRES(United Nations Secretary General),12 December,2020 There is no shortcut to a carbon neutral society;solutions are urgently required from both energy&industrial sectors and global ecosystems.While the former is often held accountable and emphasized in terms of its emissions reduction capability,the latter(recently termed natural climate solutions)should also be assessed for potential and limitations by the scientific community,the public,and policy makers.

Offshore wind power in China:A potential solution to electricity transformation and carbon neutrality

China is likely to lead global offshore wind power development,in the hope of transforming the coal-based electricity system and reducing greenhouse gas emissions.However,the potential of power generation and emissions mitigation is largely unknown,and the contribution of offshore wind utilization to regional carbon neutrality needs to be further clarified.Here,we reveal that offshore wind energy resources are abundant in China,with an estimated power generation potential of about 17.5 PWh,more than doubling the current power consumption nationwide.Although current utilization of offshore wind energy in China accounts for 21%of global overall capacity,the total share is still limited,supplying just 0.4%of national electricity needs(2019).With the increasing use of offshore wind,by 2050,the planned installation along China coast would be nearly five times as much as current(2019)global capacity,or 25 times of current national offshore wind power generation.The total CO_(2)emissions reduction in 2050 due to the decrease in coal use is projected to be 294.3 Tg CO_(2)-eq yr^(-1),equivalent to 20%of current emissions from coal-fired power in the coastal region.The size of reduced emissions is higher than current CO_(2)emissions in about 90%of countries.Our results highlight the important role of offshore wind power in upgrading the energy system and achieving carbon neutrality.Future studies are encouraged to further explore technological,economic and institutional challenges facing offshore wind energy deployment and low-carbon energy system development.

Large potential of strengthening the land carbon sink in China through anthropogenic interventions

The terrestrial ecosystem in China mitigates 21%-45%of the national contemporary fossil fuel CO_(2) emissions every year.Maintaining and strengthening the land carbon sink is essential for reaching China’s target of carbon neutrality.However,this sink is subject to large uncertainties due to the joint impacts of climate change,air pollution,and human activities.Here,we explore the potential of strengthening land carbon sink in China through anthropogenic interventions,including forestation,ozone reduction,and litter removal,taking advantage of a well-validated dynamic vegetation model and meteorological forcings from 16 climate models.Without anthropogenic interventions,considering Shared Socioeconomic Pathways(SSP)scenarios,the land sink is projected to be 0.26-0.56 Pg C a^(-1) at 2060,to which climate change contributes 0.06-0.13 Pg C a^(-1) and CO_(2) fertilization contributes 0.08-0.44 Pg C a^(-1) with the stronger effects for higher emission scenarios.With anthropogenic interventions,under a close-to-neutral emission scenario(SSP1-2.6),the land sink becomes 0.47-0.57 Pg C a^(-1) at 2060,including the contributions of 0.12 Pg C a^(-1) by conservative forestation,0.07 Pg C a^(-1) by ozone pollution control,and 0.06-0.16 Pg C a^(-1) by 20%litter removal over planted forest.This sink can mitigate 90%-110% of the residue anthropogenic carbon emissions in 2060,providing a solid foundation for the carbon neutrality in China.

A long-term Global LAnd Surface Satellite(GLASS)data-set for environmental studies

Recently,five Global LAnd Surface Satellite(GLASS)products have been released:leaf area index(LAI),shortwave broadband albedo,longwave broadband emissivity,incident short radiation,and photosynthetically active radiation(PAR).The first three products cover the years 19822012(LAI)and 19812010(albedo and emissivity)at 15 km and 8-day resolutions,and the last two radiation products span the period 20082010 at 5 km and 3-h resolutions.These products have been evaluated and validated,and the preliminary results indicate that they are of higher quality and accuracy than the existing products.In particular,the first three products have much longer time series,and are therefore highly suitable for various environmental studies.This paper outlines the algorithms,product characteristics,preliminary validation results,potential applications and some examples of initial analysis of these products.

Influence of the carbon cycle on the attribution of responsibility for climate change

The carbon cycle is one of the fundamental climate change issues.Its long-term evolution largely affects the amplitude and trend of human-induced climate change,as well as the formulation and implementation of emission reduction policy and technology for stabilizing the atmospheric CO2concentration.Two earth system models incorporating the global carbon cycle,the Community Earth System Model and the Beijing Normal University-Earth System Model,were used to investigate the effect of the carbon cycle on the attribution of the historical responsibility for climate change.The simulations show that when compared with the criterion based on cumulative emissions,the developed(developing)countries’responsibility is reduced(increased)by 6%–10%using atmospheric CO2concentration as the criterion.This discrepancy is attributed to the fact that the developed world contributed approximately61%–68%(61%–64%)to the change in global oceanic(terrestrial)carbon sequestration for the period from 1850 to2005,whereas the developing world contributed approximately 32%–49%(36%–39%).Under a developed world emissions scenario,the relatively larger uptake of global carbon sinks reduced the developed countries’responsibility for carbon emissions but increased their responsibility for global ocean acidification(68%).In addition,the large emissions from the developed world reduced the efficiency of the global carbon sinks,which may affect the long-term carbon sequestration and exacerbate global warming in the future.Therefore,it is necessary to further consider the interaction between carbon emissions and the carbon cycle when formulating emission reduction policy.

2060年中国实现碳中和所面临的挑战:现状与展望

China’s high ambitions to reach peak CO_(2) emissions by 2030 and carbon neutrality by 2060 make carbon mitigation an urgent issue with widespread societal consequences.To develop an achievable roadmap and an effective portfolio of climate policies,it is essential that a clear picture of the magnitude and uncertainty of China’s current carbon balance is available,at both national and regional levels.

可持续发展情景下丝绸之路沿线国家土地利用及其对陆地碳库影响

可持续发展目标(SDGs)呼吁全世界共同采取行动,促进繁荣并保护地球.本研究面向SDGs构建了环境、粮食和经济等可持续发展情景,预测2020~2030年丝绸之路沿线国家的土地利用变化,并分析其对陆地碳库的影响。研究表明:未来土地利用变化及其对陆地碳库的影响在不同情景下存在显著差异。在可持续环境情景下,林地得到了有效保护,相较于2020年中国林地碳储量增加了约0.60%;在可持续粮食情景下,耕地流失得到了缓解,尤其在南亚及东南亚地区的耕地面积呈现上升趋势:在可持续经济情景下,城市扩张速度加快,引起的碳损失量最多这项研究有助于推进丝绸之路沿线甚至全球可持续发展进程,为探寻可持续发展路径提供了科学依据。

Soil erosion affects variations of soil organic carbon and soil respiration along a slope in Northeast China

Background:Although soil erosion plays a key role in the carbon cycle,a holistic and mechanistic understanding of the soil erosion process within the cycle is still lacking.The aim of this study was therefore to improve our mechanistic understanding of soil organic carbon(SOC)and soil respiration dynamics through an experiment conducted in an eroding black soil farmland landscape in Northeast China.Results:The depositional profiles store 5.9 times more SOC than the eroding profiles and 3.3 times more SOC than the non-eroding profiles.A linear correlation between the SOC and 137Cs(Caesium-137)was observed in our study,suggesting that the SOC decreased with increased soil erosion.Furthermore,the fractions of intermediate C and the microaggregate C were lowest at the eroding position and highest at the depositional position.In the depositional topsoil,the input of labile materials plays a promotional role in soil respiration.Conversely,in the subsoil(i.e.,below 10 cm),the potential mineralization rates were lowest at the depositional position—due to effective stabilization by physical protection within soil microaggregates.The field results of soil surface respiration also suggest that the depositional topsoil SOC is prone to be mineralized and that SOC at this depositional context is stabilized at subsoil depth.In addition,the high water contents at the depositional position can limit the decomposition rates and stabilize the SOC at the same time.Conclusions:The findings from this study support that a majority of the SOC at footslope is stored within most of the soil profile(i.e.,below 10 cm)and submitted to long-term stabilization,and meanwhile support that the depositional profile emits more CO2 than the summit due to its high amount and quality of SOC.

Large-scale estimates of gross primary production on the Qinghai-Tibet plateau based on remote sensing data

Vegetation gross primary production(GPP)is an important variable for the carbon cycle on the Qinghai-Tibetan Plateau(QTP).Based on the measurements from 12 eddy covariance flux sites,we validated a light use efficiency model(i.e.EC-LUE)to evaluate the spatial-temporal patterns of GPP and the effect of environmental variables on QTP.In general,EC-LUE model performed well in predicting GPP at different time scale over QTP.Annual GPP over the entire QTP ranged from 575 to 703 Tg C,and showed a significantly increasing trend from 1982 to 2013.However,there were large spatial heterogeneities in long-term trends of GPP.Throughout the entire QTP,air temperature increase had a greater influence than solar radiation and precipitation(PREC)changes on productivity.Moreover,our results highlight the large uncertainties of previous GPP estimates due to insufficient parameterization and validations.When compared with GPP estimates of the EC-LUE model,most Coupled Model Intercomparison Project(CMIP5)GPP products overestimate the magnitude and increasing trends of regional GPP,which potentially impact the feedback of ecosystems to regional climate changes.

Optimizing photosynthetic and respiratory parameters based on the seasonal variation pattern in regional net ecosystem productivity obtained from atmospheric inversion

In this study, we explore the feasibility of optimizing ecosystem photosynthetic and respiratory parameters from the seasonal variation of the net carbon flux. An optimization scheme is proposed to estimate two key parameters （V2max and Q10） by exploiting the seasonal variation in the net ecosystem carbon flux retrieved by an atmospheric inversion system. This scheme is implemented to estimate V25max and Q10 of the boreal ecosystem productivity simulator （BEPS） to improve its NEP simulation in the boreal North American region. Then, in situ NEE observations at six eddy covariance sites are used to evaluate the NEE simulations from BEPS with initial and optimized parameters. The results show that the performance of the optimized BEPS is superior to that of the BEPS with the default parameter values. These results implicate that it is possible to optimize ecosystem model parameters by different sensitivities of V25max and Q10 during growing and non-growing seasons through atmospheric inversion or data assimilation techniques.

Improving a PenmanMonteith evapotranspiration model by incorporating soil moisture control on soil evaporation in semiarid areas

PenmanMonteith(PM)theory has been successfully applied to calculate land surface evapotranspiration(ET)for regional and global scales.However,soil surface resistance,related to soil moisture,is always difficult to determine over a large region,especially in arid or semiarid areas.In this study,we developed an ET estimation algorithm by incorporating soil moisture control,a soil moisture index(SMI)derived from the surface temperature and vegetation index space.We denoted this ET algorithm as the PM-SMI.The PM-SMI algorithm was compared with several other algorithms that calculated soil evaporation using relative humidity,and validated with Bowen ratio measurements at seven sites in the Southern Great Plain(SGP)that were covered by grassland and cropland with low vegetation cover,as well as at three eddy covariance sites from AmeriFlux covered by forest with high vegetation cover.The results show that in comparison with the other methods examined,the PM-SMI algorithm significantly improved the daily ET estimates at SGP sites with a root mean square error(RMSE)of 0.91 mm/d,bias of 0.33 mm/d,and R^(2) of 0.77.For three forest sites,the PM-SMI ET estimates are closer to the ET measurements during the non-growing season when compared with the other three algorithms.At all the 10 validation sites,the PMSMI algorithm performed the best.PM-SMI 8-day ET estimates were also compared with MODIS 8-day ET products(MOD16A2),and the latter showed negligible bias at SGP sites.In contrast,most of the PM-SMI 8-day ET estimates are around the 1:1 line.

A 30m Resolution Distribution Map of Maize for China Based on Landsat and Sentinel Images

As the second largest producer of maize,China contributes 23%of global maize production and plays an important role in guaranteeing maize markets stability.In spite of its importance,there is no 30m spatial resolution distribution map of maize for all of China.This study used a time-weighted dynamic time warping method to identify planting areas of maize by comparing the similarity of time series of a satellite-based vegetation index at each pixel with a standard time series derived from known maize fields and mapped maize distribution from 2016 to 2020 over 22 provinces accounting for more than 99%of the maize planting area in China.Based on 18800 field-surveyed pixels at 30-meter spatial resolution,the distribution map yields 76.15%and 81.59%of producer’s and user’s accuracies averaged over the entire investigated provinces,respectively.Municipality-and county-level census data also show a good performance in reproducing the spatial distribution of maize.This study provides an approach to mapping maize over large areas based on a small volume of field survey data.

Estimating Aboveground Carbon Dynamic of China Using Optical and Microwave Remote-Sensing Datasets from 2013 to 2019

Over the past 2 to 3 decades,Chinese forests are estimated to act as a large carbon sink,yet the magnitude and spatial patterns of this sink differ considerably among studies.Using 3 microwave(L-and X-band vegetation optical depth[VOD])and 3 optical(normalized difference vegetation index,leaf area index,and tree cover)remote-sensing vegetation products,this study compared the estimated live woody aboveground biomass carbon(AGC)dynamics over China between 2013 and 2019.Our results showed that tree cover has the highest spatial consistency with 3 published AGC maps(mean correlation value R=0.84),followed by L-VOD(R=0.83),which outperform the other VODs.An AGC estimation model was proposed to combine all indices to estimate the annual AGC dynamics in China during 2013 to 2019.The performance of the AGC estimation model was good(root mean square error=0.05 Pg C and R^(2)=0.90 with a mean relative uncertainty of 9.8% at pixel scale[0.25°]).Results of the AGC estimation model showed that carbon uptake by the forests in China was about+0.17 Pg C year^(-1) from 2013 to 2019.At the regional level,provinces in southwest China including Guizhou(+22.35 Tg C year^(-1)),Sichuan(+14.49 Tg C year^(-1)),and Hunan(+11.42 Tg C year^(-1))provinces had the highest carbon sink rates during 2013 to 2019.Most of the carbon-sink regions have been afforested recently,implying that afforestation and ecological engineering projects have been effective means for carbon sequestration in these regions.

A comprehensive framework for seasonal controls of leaf abscission and productivity in evergreen broadleaved tropical and subtropical forests

Relationships among productivity,leaf phenology,and seasonal variation in moisture and light availability are poorly understood for evergreen broadleaved tropical/subtropical forests,which contribute 25% of terrestrial productivity.On the one hand,as moisture availability declines,trees shed leaves to reduce transpiration and the risk of hydraulic failure.On the other hand,increases in light availability promote the replacement of senescent leaves to increase productivity.Here,we provide a comprehensive framework that relates the seasonality of climate,leaf abscission,and leaf productivity across the evergreen broadleaved tropical/subtropical forest biome.The seasonal correlation between rainfall and light availability varies from strongly negative to strongly positive across the tropics and maps onto the seasonal correlation between litterfall mass and productivity for 68 forests.Where rainfall and light covary positively,litterfall and productivity also covary positively and are always greater in the wetter sunnier season.Where rainfall and light covary negatively,litterfall and productivity are always greater in the drier and sunnier season if moisture supplies remain adequate;otherwise productivity is smaller in the drier sunnier season.This framework will improve the representation of tropical/subtropical forests in Earth system models and suggests how phenology and productivity will change as climate change alters the seasonality of cloud cover and rainfall across tropical/subtropical forests.

Higher plant photosynthetic capability in autumn responding to low atmospheric vapor pressure deficit

It has been long established that the terrestrial vegetation in spring has stronger photosynthetic capability than in autumn.However,this study challenges this consensus by comparing photosynthetic capability of terrestrial vegetation between the spring and autumn seasons based on measurements of 100 in situ eddy covariance towers over global extratropical ecosystems.At the majority of these sites,photosynthetic capability,indicated by light use efficiency(LUE)and apparent quantum efficiency,is significantly higher in autumn than in spring,due to lower atmosphere vapor pressure deficit(VPD)at the same air temperature.Seasonal VPD differences also substantially explain the interannual variability of the differences in photosynthetic capability between spring and autumn.We further reveal that VPD in autumn is significantly lower than in spring over 74.14% of extratropical areas,based on a global climate dataset.In contrast,LUE derived from a data-driven vegetation production dataset is significantly higher in autumn in over 61.02% of extratropical vegetated areas.Six Earth system models consistently projected continuous larger VPD values in spring compared with autumn,which implies that the impacts on vegetation growth will long exist and should be adequately considered when assessing the seasonal responses of terrestrial ecosystems to future climate conditions.

The effects of multiple environmental factors on global carbon allocation

Background The allocation of photosynthate among the parts of plants(e.g.,leaves,wood tissues and roots)strongly regulates their growth,and this conditions the terrestrial carbon cycle.Recent studies have shown that atmospheric CO_(2)and climate change dominate the changes in carbon allocation in plants,but the magnitude and mechanism of its effects remain unclear.Methods The Community Atmosphere Biosphere Land Exchange(CABLE)model can accurately simulate the responses of carbon allocation to environmental changes.This study quantifies the contributions of four environmental factors-atmospheric CO_(2),temperature,precipitation,and radiation-on resource availability and carbon allocation from 1979 to 2014 by using the CABLE model.Results The results of the CABLE model showed that rising CO_(2)significantly reduced carbon allocation to the leaves of plants at a global scale,but the other three environmental factors exhibited contrasting effects that dominated the rise in carbon allocation to the leaves.The increased precipitation and CO_(2)significantly reduced the light availability and increased carbon allocation to the wooden parts of plants.By contrast,the rising temperature reduced the water availability,resulting in a decrease in carbon allocation to the wooden parts.All four environmental factors consistently exhibited negative effects on carbon allocation to the roots,with rising precipitation causing the largest reduction in carbon allocation to them.Moreover,except for CO_(2),the effects of the other three environmental factors were heterogeneous owing to their variable interactions in different regions.Conclusions The CABLE model can accurately represent the mechanisms of response of resource availability and carbon allocation to environmental changes.Our study highlights the substantial environmental regulation of global carbon allocation.The responses of carbon allocation to global environmental changes need to be extensively studied through ecosystem models based on different hypotheses.

Are regional precipitation-productivity relationships robust to decadal-scale dry period?

Precipitation(PPT)is the primary climatic determinant of plant growth and aboveground net primary productivity(ANPP)for many of the world’s major terrestrial ecosystems.Thus,relationships between PPT and productivity can provide insight into how changes in climate may alter ecosystem functions globally.Spatial PPT–ANPP relationships for grasslands are found remarkably similar around the world,but whether and how they change during periods of extended climatic anomalies remain unknown.Here,we quantifed how regional-scale PPTANPP relationships vary between an extended wet and a dry period by taking advantage of a 35-year record of PPT and NDVI(as a surrogate for ANPP)at 1700 sites in the temperate grasslands of northern China.We found a sharp decrease in the strength of the spatial PPT–ANPP relationship during an 11-year period of below average PPT.We attributed the collapse of this relationship to asynchrony in the responses of different grassland types to this decadal period of increased aridity.Our results challenge the robustness of regional PPT–productivity if aridity in grasslands is increased globally by climate change.

Improvement of predicting ecosystem productivity by modifying carbon-water-nitrogen coupling processes in a temperate grassland

Aims Prediction of changes in ecosystem gross primary productivity(GPP)in response to climatic variability is a core mission in the field of global change ecology.However,it remains a big challenge for the model community to reproduce the interannual variation(IAV)of GPP in arid ecosystems.Accurate estimates of soil water content(SWC)and GPP sensitivity to SWC are the two most critical aspects for predicting the IAV of GPP in arid ecosystems.Methods We took a widely used model Biome-BGC as an example,to improve the model performances in a temperate grassland ecosystem.Firstly,we updated the estimation of SWC by modifying modules of evapotrainspiration,SWC vertical profile and field capacity.Secondly,we modified the function of controlling water-nitrogen relation,which regulates the GPP-SWC sensitivity.Important Findings The original Biome-BGC overestimated the SWC and underestimated the IAV of GPP sensitivity,resulting in lower IAV of GPP than the observations,e.g.it largely underestimated the reduction of GPP in drought years.In comparison,the modified model accurately reproduced the observed seasonal and IAVs in SWC,especially in the surface layer.Simulated GPP-SWC sensitivity was also enhanced and became closer to the observations by optimizing parameter controlling nitrogen mineralization.Consequently,the model's capability of reproducing IAV of GPP has been largely improved by the modifications.Our results demonstrate that SWC in the surface layer and the consequent effects on nitrogen availability should be among the first considerations for accurate modeling IAV of GPP in arid ecosystems.

What can the Glasgow Declaration on Forests bring to global emission reduction?

The Glasgow Declaration on Forests signed at the recent UN Climate Change Conference(COP 26)committed to halting forest loss by 2030.141 countries and regions,collectively covering over 90%of global forest,endorsed this declaration.Avoiding forest loss can generally contribute to climate change mitigation;however,the impacts of the declaration on global carbon dioxide(CO_(2))emission reduction are still unclear.Here we show that the Glasgow Declaration,if implemented fully and in a timely fashion,could reduce 123 Gt CO_(2) of emission from 2021 to 2050.This study also highlights that any delays in implementing the declaration would decrease the avoided emission.Although the Glasgow Declaration is a milestone for mitigating climate change,the more ambitious afforestation plan is urgently needed to keep the global temperature rise to below 1.5
C relative to pre-industrial levels.