粤港澳大湾区CO_(2)排放趋势、驱动因素及减排路径

粤港澳大湾区是我国为建设世界级城市群提出的国家战略,其CO_(2)排放趋势、社会经济驱动因素和减排路径对区域经济高质量发展具有重要意义。本研究编制了2000-2019年粤港澳大湾区CO_(2)排放清单,采用对数平均迪氏指数法探究CO_(2)排放的关键驱动力。结果表明,粤港澳大湾区CO_(2)排放在2017年后明显放缓,已经与国内生产总值(GDP)增长脱钩。经济增长和能源强度分别是驱动和抑制粤港澳大湾区CO_(2)排放增加的主要因素。能源生产和重工业对粤港澳大湾区CO_(2)排放增长的推动作用降低,服务业正成为主要驱动力。粤港澳大湾区通过产业结构调整和升级实现低碳发展取得了显著成效。深圳和香港地区的产业升级以及深圳、广州和佛山的技术进步抑制了粤港澳大湾区CO_(2)排放增长。粤港澳大湾区各城市异质性增加了减排指标分配难度和制定区域碳中和路线图的复杂性。本研究提出了粤港澳大湾区城市分级减排策略和碳达峰碳中和建议,为制定粤港澳大湾区城市碳达峰和碳中和行动方案以及其他城市和地区的低碳发展提供了科学依据。

Interactions of Microplastics and Methane Seepage in the Deep-Sea Environment

Microplastics(MPs)are important exempla of the Anthropocene and are exerting an increasing impact on Earth’s carbon cycle.The huge imbalance between the MPs floating on the marine surface and those that are estimated to have been introduced into the ocean necessitates a detailed assessment of marine MP sinks.Here,we demonstrate that cold seep sediments,which are characterized by methane fluid seepage and a chemosynthetic ecosystem,effectively capture and accommodate small-scale(<100μm)MPs,with 16 types of MPs being detected.The abundance of MPs in the surface of the sediment is higher in methane-seepage locations than in non-seepage areas.Methane seepage is beneficial to the accumulation,fragmentation,increased diversity,and aging of MPs.In turn,the rough surfaces of MPs contribute to the sequestration of the electron acceptor ferric oxide,which is associated with the anaerobic oxidation of methane(AOM).The efficiency of the AOM determines whether the seeping methane(which has a greenhouse effect 83 times greater than that of CO_(2)over a 20-year period)can enter the atmosphere,which is important to the global methane cycle,since the deep-sea environment is regarded as the largest methane reservoir associated with natural gas hydrates.

Can the Grain-for-Green Program Really Ensure a Low Sediment Load on the Chinese Loess Plateau?

The Chinese Loess Plateau is the most seriously eroded area in the world and contributes the vast majority of the sediment that goes into the Yellow River.Since the 1950s,progressive soil and water conservation measures have been implemented—in particular,large-scale ecological restoration has been ongoing since 1999—resulting in a significant reduction of the sediment load.However,the mechanism of the sediment transport dynamics is not fully understood due to multiple and complicated influencing factors including climate change and human activities(e.g.,ecological restoration).A challenging question,then,arises:Is the current low sediment level a“new normal”in this era and in the future?To address this question,we selected a typical loess hilly region where considerable ecological restoration has been implemented,and which is regarded as the site of the first and most representative Grainfor-Green program in the Loess Plateau.We investigated the evolution of discharge–sediment relationships in the past decades(1960–2010)and their association with the soil and water conservation measures in this area.The results showed that there was a distinct change in the regression parameters of the commonly used annual discharge–sediment regression equation—a continuously increasing trend of parameter b and a decreasing trend of parameter a,accompanying the ecological restoration.The increase in exponent b(i.e.,a steeper slope)implies a potential lower sediment load resulting from low discharge and a potential higher sediment load resulting from large discharge.This finding may question the new normal of a low sediment level and implies the potential risk of a large sediment load during extremely wet years.

Hydrological Response to Climate and Land Use Changes in the Dry–Warm Valley of the Upper Yangtze River

The hydrological process in the dry–warm valley of the mountainous area of southwest China has unique characteristics and has attracted scientific attention worldwide.Given that this is an area with fragile ecosystems and intensive water resource conflicts in the upper reaches of the Yangtze River,a systematic identification of its hydrological responses to climate and land use variations needs to be performed.In this study,MIKE SHE was employed and calibrated for the Anning River Basin in the dry–warm valley.Subsequently,a deep learning neural network model of the long short-term memory(LSTM)and a traditional multi-model ensemble mean(MMEM)method were used for an ensemble of 31 global climate models(GCMs)for climate projection.The cellular automata–Markov model was implemented to project the spatial pattern of land use considering climatic,social,and economic conditions.Four sets of climate projections and three sets of land use projections were generated and fed into the MIKE SHE to project hydrologic responses from 2021 to 2050.For the calibration and first validation periods of the daily simulation,the coefficients of determination(R)were 0.85 and 0.87 and the Nash–Sutcliffe efficiency values were 0.72 and 0.73,respectively.The advanced LSTM performed better than the traditional MMEM method for daily temperature and monthly precipitation.The average monthly temperature projection under representative concentration pathway 8.5(RCP8.5)was expected to be slightly higher than that under RCP4.5;this is contrary to the average monthly precipitation from June to October.The variations in streamflow and actual evapotranspiration(ET)were both more sensitive to climate change than to land use change.There was no significant relationship between the variations in streamflow and the ET in the study area.This work could provide general variation conditions and a range of hydrologic responses to complex and changing environments,thereby assisting with stochastic uncertainty and optimizing water resource management in critical regions.

Urban energy consumption and related carbon emission estimation： a study at the sector scale

With rapid economic development and energy consumption growth, China has become the largest energy consumer in the world. Impelled by extensive international concern, there is an urgent need to analyze the character- istics of energy consumption and related carbon emission, with the objective of saving energy, reducing carbon emission, and lessening environmental impact. Focusing on urban ecosystems, the biggest energy consumer, a method for estimating energy consumption and related carbon emission was established at the urban sector scale in this paper. Based on data for 1996-2010, the proposed method was applied to Beijing in a case study to analyze the consumption of different energy resources （i.e., coal, oil, gas, and electricity） and related carbon emission in different sectors （i.e., agriculture, industry, construction, transportation, household, and service sectors）. The results showed that coal and oil contributed most to energy consumption and carbon emission among different energy resources during the study period, while the industrial sector consumed the most energy and emitted the most carbon among different sectors. Suggestions were put forward for energy conservation and emission reduction in Beijing. The analysis of energy consumption and related carbon emission at the sector scale is helpful for practical energy saving and emission reduction in urban ecosystems.

Coupled planning of water resources and agricultural land-use based on an inexact-stochastic programming model

Water resources are fundamental for support of regional development. Effective planning can facilitate sustainable management of water resources to balance socioeconomic development and water conservation. In this research, coupled planning of water resources and agricultural land use was undertaken through the develop- ment of an inexact-stochastic programming approach. Such an inexact modeling approach was the integration of interval linear programming and chance-constraint pro- gramming methods. It was employed to successfully tackle uncertainty in the form of interval numbers and probabil- istic distributions existing in water resource systems. Then it was applied to a typical regional water resource system for demonstrating its applicability and validity through generating efficient system solutions. Based on the process of modeling formulation and result analysis, the developed model could be used for helping identify optimal water resource utilization patterns and the corresponding agri- cultural land-use schemes in more, a number of decision three sub-regions. Further- alternatives were generated under multiple water-supply conditions, which could help decision makers identify desired management policies.

利器善事:深海装备引领深海生物科学发展

深海环境高压、高/低温、强腐蚀、黑暗和营养缺乏等特点孕育了生机蓬勃的特殊生态系统.本文回顾了过去50年深海生物学的研究进展.首先,分析阐明了深海装备技术如何促进深海生物研究的深入发展.然后,概述了深海环境中的生物研究的发展历程;从生物多样性、环境适应机制、生物进化过程和生态系统连通性四个方面解析了深海技术对热液、冷泉、海山、海沟及鲸落等生态系统研究的促进作用.最后,为提升深海生态系统的服务功能研究,以及更好地保护受人类活动和气候变化影响的深海特殊生态系统,本文阐述了深海装备技术创新对促进深海生物及生态系统前沿研究的重要性,并提出了以深海生物研究为导向的深海装备技术未来的潜在发展方向.

The frontier evolution and emerging trends of hydrological connectivity in river systems:a scientometric review

With the intensification of climate change and human activities,the watershed ecosystem is seriously fragmented,which leads to the obstruction of hydrological connectivity,and further causes the degradation of the ecosystem.As the value of wetlands continues to be exploited,hydrological connectivity becomes increasingly significant.In this paper,the characteristics and development of hydrological connectivity research from 1998 to 2018 were analyzed through the scientometric analysis based on Web of Science database.CiteSpace,an analytical software for scientific measurement,is used to visualize the results of the retrieval.The analysis results of co-occurrence,co-operative and co-cited network indicate that the hydrological connectivity is a multidisciplinary field which involves the Environment Science and Ecology,Water Resources,Environmental Sciences,Geology and Geosciences.According to Keyword cooccurrence analysis,ecosystem,floodplain,dynamics,climate change and management are the main research hotspots in each period.In addition,the co-cited analysis of references shows that“amphibians”is the largest cluster of hydrological connectivity,and the“channel network”is the most important research topic.It is worth noting that the“GIWS”(Geographically Isolated Wetlands)is the latest research topic and may be a major research direction in the future.

Development of a model-based flood emergency management system in Yujiang River Basin, South China

Flooding is the most frequent disaster in China. It affects people＇s lives and properties, causing considerable economic loss. Flood forecast and operation of reservoirs are important in flood emergency management. Although great progress has been achieved in flood forecast and reservoir operation through using computer, network technology, and geographic information system technology in China, the prediction accuracy of models are not satisfactory due to the unavailability of real-time monitoring data. Also, real-time flood control scenario analysis is not effective in many regions and can seldom provide online decision support function. In this research, a decision support system for real-time flood forecasting in Yujiang River Basin, South China （DSS-YRB） is introduced in this paper. This system is based on hydrological and hydraulic mathematical models. The conceptual framework and detailed components of the proposed DSS-YRB is illustrated, which employs real-time rainfall data conversion, model-driven hydrologic forecasting, model calibration, data assimilation methods, and reservoir operational scenario analysis. Multi-tiered architecture offers great flexibility, portability, reusability, and relia- bility. The applied case study results show the development and application of a decision support system for realtime flood forecasting and operation is beneficial for flood control.