Estimating changes in flood risks and benefits of non-structural adaptation strategies - a case study from Tyrol,Austria

Flood damage has increased significantly and is expected to rise further in many parts of the world. For assessing potential changes in flood risk, this paper presents an integrated model chain quantifying flood hazards and losses while considering climate and land use changes. In the case study region, risk estimates for the present and the near future illustrate that changes in flood risk by 2030 are relatively low compared to historic periods. While the impact of climate change on the flood hazard and risk by 2030 is slight or negligible, strong urbanisation associated with economic growth contributes to a remarkable increase in flood risk. Therefore, it is recommended to frequently consider land use scenarios and economic developments when assessing future flood risks. Further, an adapted and sustainable risk management is necessary to encounter rising flood losses, in which non-structural measures are becoming more and more important. The case study demonstrates that adaptation by non-structural measures such as stricter land use regulations or enhancement of private precaution is capable of reducing flood risk by around 30 %. Ignoring flood risks, in contrast, always leads to further increasing losses—with our assumptions by 17 %. These findings underline that private precaution and land use regulation could be taken into account as low cost adaptation strategies to global climate change in many flood prone areas. Since such measures reduce flood risk regardless of climate or land use changes, they can also be recommended as no-regret measures.     

Impacts of land use,restoration, and climate change on tropical peat carbon stocks in the twenty-first century: implications for climate mitigation

The climate mitigation potential of tropical peatlands has gained increased attention as Southeast Asian peatlands are being deforested, drained and burned at very high rates, causing globally significant carbon dioxide (CO₂) emissions to the atmosphere. We used a process-based dynamic tropical peatland model to explore peat carbon (C) dynamics of several management scenarios within the context of simulated twenty-first century climate change. Simulations of all scenarios with land use, including restoration, indicated net C losses over the twenty-first century ranging from 10 to 100 % of pre-disturbance values. Fire can be the dominant C-loss pathway, particularly in the drier climate scenario we tested. Simulated 100 years of oil palm (Elaeis guineensis) cultivation with an initial prescribed burn resulted in 2400–3000 Mg CO₂?ha^?1 total emissions. Simulated restoration following one 25-year oil palm rotation reduced total emissions to 440–1200 Mg CO₂?ha^?1, depending on climate. These results suggest that even under a very optimistic scenario of hydrological and forest restoration and the wettest climate regime, only about one third of the peat C lost to the atmosphere from 25 years of oil palm cultivation can be recovered in the following 75 years if the site is restored. Emissions from a simulated land degradation scenario were most sensitive to climate, with total emissions ranging from 230 to 10,600 Mg CO₂?ha^?1 over 100 years for the wettest and driest dry season scenarios, respectively. The large difference was driven by increased fire probability. Therefore, peat fire suppression is an effective management tool to maintain tropical peatland C stocks in the near term and should be a high priority for climate mitigation efforts. In total, we estimate emissions from current cleared peatlands and peatlands converted to oil palm in Southeast Asia to be 8.7 Gt CO₂ over 100 years with a moderate twenty-first century climate. These emissions could be minimized by effective fire suppression and hydrological restoration.     

Climate impact potential of utilizing forest residues for bioenergy in Norway

The utilization of forest residues for bioenergy in Norway is foreseen to increase due to the government call to double bioenergy output by 2020 to thirty Tera-Watt hours. This study focuses on the climate impacts of bioenergy utilization where four forest residue extraction scenarios at clear-cut are considered: i) 75 % above ground residues (branches, (25 %) foliage, tops); ii) 75 % above and below ground residues (branches, tops, (25 %) foliage, stumps, coarse and small roots); iii) extracting 100 % of all available forest residue; and iv) leaving all residues in the forest. The Yasso07 soil-carbon model was utilized to quantify the carbon flux to the atmosphere due to the forest residues that are left in the forest in each scenario. The climate impact potential for each scenario was then calculated for the carbon-flux neutral Norway Spruce (Picea abies) forest system in five regions of Norway. The biogenic carbon dioxide emissions associated to decomposition upon forest floor, procurement losses and bioenergy conversion are included in these calculations. Results suggest that if such bioenergy can directly replace a fossil source of energy, the utilization of this biomass was found to be climatically beneficial in most fossil energy replacement cases and time horizons when compared to leaving the residues in the forest. Integrated global temperature change displacement factors have been developed which have been used to estimate the magnitude of this climate change mitigation over a particular time horizon.     

New policies to deal with climate change and other drivers impacting on resilience to flooding in urban areas: the CORFU approach

In the context of urban flood management, resilience is equal to resisting, recovering, reflecting and responding. The variety of causes of flooding and their consequences underpin the need for increased and internationally coordinated efforts to enhance technologies and policies for dealing with floods. This paper addresses this issue and presents some novel research ideas related to resilience to flooding in urban areas, which are under development within the EU FP7 project ‘Collaborative research on flood resilience in urban areas’ (CORFU). The approach adopted in this project aims to quantify the cost-effectiveness of resilience measures and integrative and adaptable flood management plans for different scenarios of relevant drivers: urban development, socio-economic trends and climate changes. It is believed that the way in which the different models are being put together, combined with the variability of conditions in case study areas in Asia and in Europe, will ultimately enable more scientifically sound policies for the management of the consequences of urban flooding.     

北京市大气污染减排潜力及居民健康效益评估

北京市能源消费正面临着污染物减排和保障居民健康的双重约束. 针对未来城市能源消费设计BAU(基准情景)和2个分别基于近期和中长期节能环保要求的受控情景(EC1、EC2),模拟预测了3个情景下主要大气污染物(SO₂、NO_x、PM₁₀、PM_2.5)在目标年(2020年)的排放水平,以确定大气污染减排潜力. 分别采用综合暴露-反应关系模型(IER)和泊松回归模型,评估北京市居民对PM_2.5暴露的健康风险,估算健康损失的经济价值. 结果表明:相较BAU情景,在EC1情景下, SO₂、NO_x、PM₁₀、PM_2.5减排率分别达到52.95%、49.77%、32.82%、41.41%,可减少PM_2.5暴露下居民死亡和发病219 783例,其中死亡1 295例、住院3 920例、门诊182 558例、患病32 011例,获得健康效益111.87×108元;在EC2情景下,SO₂、NO_x、PM₁₀、PM_2.5的减排率分别达到66.61%、63.42%、54.96%、57.44%,可减少PM_2.5暴露下居民死亡和发病519 234例,其中死亡2 930例、住院9 248例、门诊427 070例、患病79 986例,获得健康效益290.10×108元. 相较EC1情景,EC2情景可产生更大的减排潜力和居民健康效益. 从空间分布上来看,北京主城区因能源方案优化获得的健康效益较大,约占总健康经济效益的60%.      

天山北坡城市群碳储量时空变化及预测研究

为了有效评估城市群碳储量变化,以天山北坡城市群为研究对象,运用PLUS模型和InVEST模型,动态评估2000~2020年及2030年不同情景下土地利用变化及碳储量变化特征.结果表明,2000~2020年天山北坡城市群碳储量呈现持续增加趋势,且碳储量变化与土地利用变化密切相关,主要表现为2000~2010年林地面积的减少导致其碳储量减少约266×10⁶t,2010~2020年草地面积的增加使其碳储量增加约69.14×10⁶t.2030年自然发展情景、生态保护情景和经济快速发展情景下碳储量预测值分别为8875.88×10⁶t、8895.58×10⁶t和8841.58×10⁶t;经济快速发展情景下碳储量最低,生态保护情景下碳储量最高.土地利用是影响碳储量空间变化分布的第一主导因素,贡献率接近于90%,土地利用强度与碳储量协调性分析与两者双变量空间自相关分析进一步验证了这一结论.土地利用变化在一定程度上能够对碳储量产生积极影响,对于本研究区而言,生态保护发展情景可能更符合未来城市发展模式,研究结果能够为土地利用规划提供参考.     

Assessing potential future urban heat island patterns following climate scenarios,socio-economic developments and spatial planning strategies

Climate change and urban development will exacerbate current urban heat island effects. While most studies acknowledge the importance of projected temperature increases for raising urban temperatures, little attention is paid to the impacts of future changes in urbanisation patterns. Yet, steering urban development may be an effective strategy to further limit increases in the intensity and spreading of the urban heat island effect. We describe a method that allows exploring the impact of urban development scenarios on the urban heat island effect. This paper starts with a basic analysis of the strength of this effect in a temperate climate under relatively favourable conditions based on data from amateur weather stations and own observations. It explains local variation in observed temperatures and quantifies how the urban heat island effect may develop in the coming 30 years. Using the obtained relations, we assess potential future changes building on existing scenarios of climatic and socio-economic changes and a land use simulation model. Our measurements for the Amsterdam region in the Netherlands indicate that the urban heat island effect induces maximum temperature differences with the surrounding countryside of over 3 °C on moderately warm summer days. The simulations of potential future changes indicate that strong local temperature increases are likely due to urban development. Climate change will, on average, have a limited impact on these changes. Large impacts can, however, be expected from the combination of urban development and potentially more frequent occurrences of extreme climatic events such as heat waves. Spatial planning strategies that reduce the lateral spread of urban development will thus greatly help to limit a further increase in urban heat island values.     

Guidelines for the strategic management of flood risks in industrial plant oil in the Brazilian coast: adaptive measures to the impacts by relative sea level rise

This study provides guidelines for strategic management in industrial oil plants linked to uncertainties of climate change through the development of integrated planning methodology with focus on coastal flooding events caused by relative sea level rise (RSLR). The research site is in Redonda Island, located in Guanabara Bay, Rio de Janeiro City, Brazil, and since 1960, it constitutes an industrial oil plant facility. The region suffers interaction with storms and meteorological tides from extratropical cyclones over the South Atlantic Ocean, being vulnerable to risks of disasters, floods, and coastal erosion. A Program on Vulnerability and Adaptation Assessments to Relative Sea Level Rise (“Programa de Avaliação e Adaptação às Vulnerabilidades de Elevação do Nível Relativo do Mar—PAAVENRM”) was developed to avoid compromising the regional and local development in the industrial system of the island, which is an ad hoc instrument designed to anticipate and reduce risks, damages, and losses by occurrence of extreme climatic events in coastal areas prone to flooding caused by RSLR. Results from computer simulation modeling indicate 37 prospective qualitative scenarios that consolidate the conditions of future climate vulnerability of the plant, starting from United Nations Intergovernmental Panel on Climate Change (IPCC) information for RSLR up to 2100. Three quantitative forecasting scenarios were simulated, under boundary conditions preset for different altimetric ranges subject to submersion, based upon ordinary and extraordinary tides measured in the area in relation to RSLR, which allowed the evaluation of the industrial infrastructure at risk. Furthermore, three thematic maps were elaborated for the planning of specific coastal protection interventions. Percentages of physical damage and property losses were estimated. The importance of applying guidelines for medium and long-term corporate strategy management, integrating the risk of flooding, the rigging of civil defense systems, meteorology, and of the plans, programs, and existing systems and others to be developed is highlighted. From this perspective, the proposed scenarios help to identify the most relevant alternatives for mitigation and adaptation under technical criteria for decision making in the study area.     

Potential effects of climate change on birds of the Northeast

We used three approaches to assess potential effects of climate change on birds of the Northeast. First, we created distribution and abundance models for common bird species using climate, elevation, and tree species variables and modeled how bird distributions might change as habitats shift. Second, we assessed potential effects on high-elevation birds, especially Bicknell’s thrush (Catharus bicknelli), that may be particularly vulnerable to climate change, by using statistical associations between climate, spruce-fir forest vegetation and bird survey data. Last, we complemented these projections with an assessment of how habitat quality of a migratory songbird, the black-throated blue warbler (Dendroica caerulescens) might be affected by climate change. Large changes in bird communities of the Northeast are likely to result from climate change, and these changes will be most dramatic under a scenario of continued high emissions. Indeed, high-elevation bird species may currently be at the threshold of critical change with as little as 1°C warming reducing suitable habitat by more than half. Species at mid elevations are likely to experience declines in habitat quality that could affect demography. Although not all species will be affected adversely, some of the Northeast’s iconic species, such as common loon and black-capped chickadee, and some of its most abundant species, including several neotropical migrants, are projected to decline significantly in abundance under all climate change scenarios. No clear mitigation strategies are apparent, as shifts in species’ abundances and ranges will occur across all habitat types and for species with widely differing ecologies.     

A multi-criteria geographic information systems approach for the measurement of vulnerability to climate change

A flexible procedure for the development of a multi-criteria composite index to measure relative vulnerability under future climate change scenarios is presented. The composite index is developed using the Weighted Ordered Weighted Average (WOWA) aggregation technique which enables the selection of different levels of trade-off, which controls the degree to which indicators are able to average out others. We explore this approach in an illustrative case study of the United States (US), using future projections of widely available indicators quantifying flood vulnerability under two scenarios of climate change. The results are mapped for two future time intervals for each climate scenario, highlighting areas that may exhibit higher future vulnerability to flooding events. Based on a Monte Carlo robustness analysis, we find that the WOWA aggregation technique can provide a more flexible and potentially robust option for the construction of vulnerability indices than traditionally used approaches such as Weighted Linear Combinations (WLC). This information was used to develop a proof-of-concept vulnerability assessment to climate change impacts for the US Army Corps of Engineers. Lessons learned in this study informed the climate change screening analysis currently under way.     

Future production of rainfed wheat in Iran (Khorasan province): climate change scenario analysis

Projecting staple crop production including wheat under future climate plays a fundamental role in planning the required adaptation and mitigation strategies for climate change effects especially in developing countries. The main aim of this study was to investigate the direction and magnitude of climate change impacts on grain yield of rainfed wheat (Triticum aestivum L.) production and precipitation within growing season. This study was performed for various regions in Khorasan province which is located in northeast of Iran. Climate projections of two General Circulation Models (GCM) for four locations under three climate change scenarios were employed in this study for different future time periods. A stochastic weather generator (LARS-WG5) was used for downscaling to generate daily climate parameters from GCMs output. The Decision Support System for Agrotechnology Transfer (DSSAT) Version 4.5 was employed to evaluate rainfed wheat performance under future climate. Grain yield of rainfed wheat and precipitation during growth period considerably decreased under different scenarios in various time periods in contrast to baseline. Highest grain yield and precipitation during growth period was obtained under B1 scenario but A1B and A2 scenarios resulted in sharp decrease (by ?57 %) of grain yield. Climate change did not have marked effects on evapotranspiration during the rainfed wheat growth. A significant correlation was detected between grain yield, precipitation and evapotranspiration under climate change for both GCMs and under all study scenarios. It was concluded, that rainfed wheat production may decline during the next 80 years especially under A2 scenario. Therefore, planning the comprehensive adaptation and mitigation program is necessary for avoiding climate change negative impact on rainfed wheat production.     

Emissions associated with meeting the future global wheat demand: A case study of UK production under climate change constraints

Climate change, population growth and socio-structural changes will make meeting future food demands extremely challenging. As wheat is a globally traded food commodity central to the food security of many nations, this paper uses it as an example to explore the impact of climate change on global food supply and quantify the resulting greenhouse gas emissions. Published data on projected wheat production is used to analyse how global production can be increased to match projected demand. The results show that the largest projected wheat demand increases are in areas most likely to suffer severe climate change impacts, but that global demand could be met if northern hemisphere producers exploit climate change benefits to increase production and narrow their yield gaps. Life cycle assessment of different climate change scenarios shows that in the case of one of the most important wheat producers (the UK) it may be possible to improve yields with an increase of only 0.6% in the emission intensity per unit of wheat produced in a 2 °C scenario. However, UK production would need to rise substantially, increasing total UK wheat production emissions by 26%. This demonstrates how national emission inventories and associated targets do not incentivise minimisation of global greenhouse gas emissions while meeting increased food demands, highlighting a triad of challenges: meeting the rising demand for food, adapting to climate change and reducing emissions.     

海平面上升叠加风暴潮对2050年中国海洋经济的影响研究

本研究基于ArcGIS的淹没模型与夜光遥感的GDP空间化处理结果,同时结合对2050年中国海洋经济增长预测,评估海平面上升叠加风暴潮三种情景对中国沿海各省市海洋经济的影响效应。模拟结果表明:海平面上升叠加风暴潮与天文潮的CHmax-0.3 m情景下全国海洋经济损失最大,2050年损失达到35444.59亿元,占海洋生产总值的9.39%;从2050年各省海洋经济损失比例来看（CHmax-0.3 m情景）,辽宁省损失比例最大,其次为广东省,福建省和广西省;从各省海洋经济损失的绝对值来看,在海平面上升0.3 m的三种情景下,广东、辽宁、江苏、山东均为海洋经济损失绝对值最大的四个省份。     

Assessment of future scenarios of climate and land-use changes in the IMPRINTS test-bed areas

The main objective of this work is to identify and evaluate the potential impacts produced by climate and land-use changes in six European test-bed basins (Llobregat, Guadalhorce, Gardon d’Anduze, Linth, Verzasca and Sambuco). Data to build future scenarios that can modify the different basins’ flash flood and debris flow risk level has been analyzed in this paper. High resolution climate scenarios have been obtained from several European projects and/or National initiatives, depending on each case. Climatic variables have been widely analyzed, with a special focus on extreme precipitation. Typical generalized extreme value (GEV) distributions have been fitted to observed and projected rainfall data to assess impacts in the frequency distributions of extreme rainfall up to 2100. Regarding climate, the main conclusion is the importance of using data at the maximum spatial and temporal resolution applying downscaling methodologies adapted to basin scale (test-bed areas ranging from approx 200 to 5000 km²) and oriented to obtain extreme rainfall values.In general, high variability has been detected, obtaining very different results for the different models and scenarios. Data corrections may lead to better representations of present situations and, therefore, more reliable future projections, but currently some of them are not suitable for extreme precipitation assessment.Regarding land-use changes, a cellular automata-based model has been used (MOLAND) to simulate the 2000–2040 period taking the CORINE land-use dataset as input data. Llobregat, Guadalhorce and Gardon d’Anduze basins have been identified as potentially interesting for simulating urban land-use dynamics due to the existence of important urban areas within their limits. The assessment of the rural land-use changes has been carried out using the results from the EURURALIS project (2000–2030 period), available for all the basins.The results of this paper are framed in the FP7 project IMPRINTS that has the aim of analyzing impacts of future changes to provide guidelines for mitigation and adaptation measures and, in general, to improve the application of the EC Flood Risk Management Directive.     

基于Z指数的昆明市洪涝研究

本文基于昆明市12个气象站点1963～2013年逐月降水量数据,采用Z指数的方法,得到旱涝等级评定结果,对昆明市洪涝的时空分布特征及成因进行了深入分析与研究,在此基础上提出防洪减灾对策.研究结果表明:时间分布上,昆明市在1963～2013年间,降水量经历了上升-下降-上升下降的波动状态,51年内共出现了8次重涝,3次大涝,10次偏涝,洪涝类型以重涝和偏涝为主,洪涝主要集中出分布在60年代中期至70年代中期、80年代末至21世纪初.空间分布上,昆明市的主城区昆明及其下风方向的嵩明地区降水较多,洪涝程度最为严重,呈贡、东川地区的降水较少,洪涝程度最轻.影响因素上,影响降水量最大的自然因素是相对湿度,其次是蒸发量及总云量;最大的人为因素是城市人口,其次是SO2排放量、建成区面积及道路面积.     

Economic analysis of adaptive strategies for flood risk management under climate change

Climate change requires reconsideration of flood risk management strategies. Cost-benefit analysis (CBA), an economic decision-support tool, has been widely applied to assess these strategies. This paper aims to describe and discuss probabilistic extensions of CBA to identify welfare-maximising flood risk management strategies under climate change. First, uncertainty about the changes in return periods of hydro-meteorological extremes is introduced by probability-weighted climate scenarios. Second, the analysis is extended by learning about climate change impacts. Learning occurs upon the probabilistic arrival of information. We distinguish between learning from scientific progress, from statistical evidence and from flood disasters. These probabilistic extensions can be used to analyse and compare the economic efficiency and flexibility of flood risk management strategies under climate change. We offer a critical discussion of the scope of such extensions and options for increasing flexibility. We find that uncertainty reduction from scientific progress may reduce initial investments, while other types of learning may increase initial investments. This requires analysing effects of different types of learning. We also find that probabilistic information about climate change impacts and learning is imprecise. We conclude that risk-based CBA with learning improves the flexibility of flood risk management strategies under climate change. However, CBA provides subjective estimates of expected outcomes and reflects different decision-maker preferences than those captured in robustness analyses. We therefore advocate robustness analysis in addition to, or combined with, cost-benefit analysis to support local investment decisions on flood risk reduction and global strategies on allocation of adaptation funds for flood risk management.     

Accounting for risk and uncertainty in determining preferred strategies for adapting to future climate change

Individuals, businesses, and policymakers face the problem of selecting a preferred strategy for adapting a managed ecosystem to future climate change when there is risk and/or uncertainty about future climate change and its ecosystem impacts, and the conditional outcomes of adaptive strategies (i.e., performance of an adaptive strategy given a particular future climate change scenario occurs). Evaluation methods for this purpose are described for two cases; one in which the decision-maker can (climate risk case) and cannot (climate uncertainty case) assign probabilities to future climate change scenarios. Fuzzy sets are used to characterize uncertainty regarding both future climate change, and the conditional outcomes of adaptive strategies. The preferred conditional adaptive strategy for a future climate change scenario is determined by ordering the adaptive strategies for that scenario using a fuzzy set operation. Two methods are described for determining the adaptive strategy that is preferred across all climate change scenarios. The preferred overall adaptive strategy for the climate risk case is determined by maximizing a performance index for strategies. The preferred overall adaptive strategy for the climate uncertainty case is determined using the minimax regret criterion, which selects the strategy that minimizes the maximum loss in performance that can occur across all strategies and climate change scenarios. Ways for making the evaluation methods dynamic are considered.     

黄淮海平原冬小麦种植的气候变化适应评估

水资源短缺影响黄淮海平原农业稳定和可持续发展。气候变化情景下,农业用水紧张的问题可能进一步加剧,种植制度和作物品种区域布局将面临调整。论文利用IPCC 5三种代表性温室气体浓度排放路径（RCP 2.6、RCP 4.5和RCP 8.5）的多模式集成数据,基于VIP（soil-Vegetation-atmosphere Interface Processes）生态水文模型,模拟了2011—2059年黄淮海平原二级子流域的水资源盈亏变化。在此基础上,针对水分亏缺最严重的子流域,设计无外来调水和维持2000—2010年调水总量水平的两种流域地下水采补均衡情景,对冬小麦种植区域的合理布局及其对产量的影响进行评估。结果表明,2050年代黄淮海平原农作物蒸散量增幅大于降雨量增幅,北部地区水分亏缺量将增加,南部地区水分盈余量则减少。在低到高的排放情景下,全区域水分盈余量下降0.1%~14.1%。两种地下水采补均衡情景下,2050年代黄淮海平原冬小麦种植面积应分别减少9.8%~11.3%和7.0%~8.8%,相应产量分别增加0~11.9%和3.0%~15.9%。适当减少冬小麦种植面积,可有效减缓黄淮海地区农业水资源的不足,保护生态环境,促进农业可持续发展。     

差异化碳减排目标对区域产业部门经济与碳减排的影响

碳减排目标是实现减排任务的重要保障.为探讨差异化减排目标对区域产业部门经济与碳减排的影响,以在我国具有特定区位条件（“21世纪海上丝绸之路”的重要节点）和经济发展现状（相对较为落后）的广西壮族自治区为主要研究区域,构建包括广西壮族自治区和我国其他地区〔除广西壮族自治区以外的其他省（自治区、直辖市）,但不含港澳台地区,下同〕在内的可计算的一般均衡模型,设定P55C65、P75C65、P65C55、P65C65、P65C75（“P”表示广西壮族自治区,“C”表示我国其他地区,“55”“65”“75”分别表示碳减排目标依次为55%、65%、75%）和基准情景（无减排目标）,研究区域间宏观经济和微观产业部门指标之间的相互影响.结果表明:①无差异情景（P65C65）下,广西壮族自治区农林牧渔业2030年的产值为741.17×108元,比基准情景下降0.19%;我国其他地区电子设备制造业的产值为33 457.49×108元,比基准情景下降2.00%.对广西壮族自治区碳排放贡献较大的产业部门主要为食品制造业、金属冶炼及压延业和服务业,而我国其他地区碳排放主要受电力热力生产的影响.②差异化情景下,这两个区域的金属冶炼及压延部门受减排约束影响均较明显.相比无差异情景,P75C65情景下,广西壮族自治区2030年金属冶炼及压延部门的出口总值和省际输出分别降至17.55×108和186.32×108元,分别下降了6.80%和1.65%;本地供应和产出分别降至358.72×108和562.59×108元,分别下降了1.85%和1.95%;金属冶炼及压延部门碳排放降至4 997×104 t,下降了12.79%.而我国其他地区2030年P75C65情景下,金属冶炼及压延部门的出口总值、省际输出、本地供应和产出则分别上升了0.05%、2.06%、0.06%和0.06%,分别增至1 283.24×108、28.25×108、26 598.95×108和27 910.43×108元,该部门的碳排放上升了0.05%,增至82 927×104 t.尽管碳减排目标能有效降低广西壮族自治区的碳排放,但也会给其产业部门带来一定的经济损失,该区域的出口、省际输出、本地供应和产出不仅受自身减排目标的影响,也受到我国其他地区减排目标的约束.建议在落实各省（自治区、直辖市）减排任务时,也要实施差异化减排目标,发展当地的优势产业.