Benefits and challenges of streamlined life-cycle assessment for SMEs – findings from case studies on climate change impacts

ABSTRACT

Small and medium-sized enterprises (SMEs) have a substantial role in the economy and job creation, but they are a remarkable source of environmental impacts. SMEs often lack skills and resources to compile environmental impact assessments; Streamlined Life Cycle Analysis (LCA) can provide efficient tools for this. An application of streamlined LCA relying heavily on database data, LCA clinic, was developed and tested on 23 SMEs in Finland. The climate change impacts were mainly caused by the production of raw materials, electricity and heating, whereas packaging and transportation were not influential. A significant amount of emissions were indirect, i.e. caused by production of raw materials. Thus, decreasing emissions from raw material production or selecting raw materials with a smaller environmental load could be a more efficient way to decrease emissions than reducing direct emissions such as those from electricity use. Lack of data in the LCA-databases was considered a challenge. An access to regionally customised datasets is important for the implementation of LCA clinics. Company feedback indicated that LCA clinics were useful in climate-friendly product design and increased environmental awareness, but did not lead to immediate actions to reduce emissions because of inadequate investment capabilities. Company managers had limited possibilities to use the results in marketing as comparative assessments would require a full LCA. Many company managers were willing to pay a fee sufficient to cover the costs of an LCA clinic, but some considered that the costs should be covered by external funding sources.     

中部6省生态足迹的测算与比较分析

生态足迹方法是区域可持续发展研究的一种重要方法,在中部6省大区域框架下,运用生态足迹模型对中部6省1989—2011年的生态足迹进行了测算和对比研究。研究结果表明:中部6省1989—2011年的生态承载力较为平稳,其中江西、河南、湖北和湖南4省的生态承载力略有上升,而山西、安徽两省的生态承载力有下降趋势。中部6省的社会经济活动对生态系统的消耗远大于生态系统本身的承载能力,并且这种差距正在不断增大,导致生态赤字不断增大。考察期间,山西省生态赤字的绝对值最小,平均生态赤字为0.49 hm2 cap-1,湖北省生态赤字最大,平均值为1.15 hm2 cap-1,其次为河南和湖南,生态赤字增长最快的是山西省和河南省,增长倍数分别达到了7.38和4.27倍。中部6省6种生态生产性土地的生态足迹均呈现出上升趋势,平均来看,6类生态生产性土地在中部6省总的生态足迹中所占比重由高到低依次为耕地、化石能源地、草地、建筑用地、水域、林地。耕地生态足迹是生态足迹中最重要的组成部分,在总的生态足迹中所占比重最大,中部6省耕地的生态足迹时间序列数据比较平稳,在考察时间内从1989年的0.4241上涨到2011年的0.5851,上升趋势较平稳,但由于耕地生态足迹所占比重大,尽管增长速度缓慢,但对中部6省生态足迹总的影响较大。建筑用地和林地生态足迹虽然增长幅度较大,但由于基数小,因此建筑生态足迹和林地生态足迹对中部6省生态足迹总的影响较小。草地、水域和化石能源用地生态足迹基数大,增长幅度也大,加上耕地生态足迹,共同决定了中部6省人均生态足迹的逐年上升趋势。     

Unintended consequences of price controls: An application to allowance markets

Price controls established in a cap-and-trade allowance market are intended to reduce cost uncertainty by constraining allowance prices between a ceiling and floor; however, they could provide opportunities for strategic actions by firms that would lower government revenue and increase emissions. In particular, when the ceiling price is supported by introducing new allowances into the market, firms could choose to buy allowances at the ceiling price, regardless of the prevailing market price, in order to lower the equilibrium price of all allowances. Those purchases could either be transacted by firms intending to manipulate the market price or be induced through the introduction of inaccurate information about the cost of emissions abatement. Theory and simulations using allowance elasticity estimates for U.S. firms suggest that the manipulation could be profitable under the stylized setting and assumptions evaluated in the paper, although in practice many other conditions will determine its use.     

基于生态足迹的中国生态承载力供需平衡分析

以生态承载力供需关系为切入点,应用生态足迹模型,构建生态承载力供需平衡指数(ECCI),以分县为基本单元,系统评价了我国县域尺度生态承载力供需平衡状况。结果表明:①中国生态承载力供需平衡以生态赤字区为主,生态盈余区和生态平衡区为辅。不足1/5的人口分布在约2/3表现为生态平衡或盈余的国土面积上,而4/5的人口集中分布在不足1/3表现为生态赤字的国土面积上;②中国分县生态承载力空间分布呈较明显的不平衡性,大体由东南到西北呈现从严重超载到富富有余的分布态势。中国生态承载力供需已严重失衡,且人口密度大、 流动人口迁入较为集中的沿海城市地区表现尤为突出。随着城市化进程的不断加快,这些地区空间生态不平衡性将更加严重,生态环境问题需引起足够关注。从流域关系来看,应妥善处理上中下游间的关系,把对生态环境的影响以及生态环境的保护摆在重要位置。研究结果可为国家主体功能区规划、 人口发展功能区划提供科学依据和决策支持。     

安徽省近10年能源足迹测度及驱动因子分析

安徽省为生态建设省,随着中部崛起战略与皖江城市带承接产业转移示范区建设的实施,能源消费给当地生态环境形成了较大压力. 依据生态足迹模型对安徽省2000—2009年能源足迹进行了时间序列测度,基于STIRPAT模型揭示了能源足迹驱动因子的边际贡献,运用灰色GM(1,1)模型预测了2015年与2020年能源足迹. 结果表明:安徽省人均能源足迹由2000年的0500 8 hm2增至2009年的1043 5 hm2,人均能源足迹赤字由2000年的0432 9 hm2扩至2009年的0975 5 hm2;煤炭足迹对能源足迹平均贡献率为7629%,占主导地位;能源足迹强度由2000年的1083 3 hm2104元降至2009年的0704 7 hm2104元;研究时段内,能源足迹生态压力指数均大于5 人均GDP和第二产业在经济中所比例均与能源足迹呈正相关,二者边际弹性系数分别为0000 073 57和0006;而单位工业增加值能耗与能源足迹呈负相关,其边际弹性系数为-0186.      

Changes in CO2 flux for different recovery processes of desertification in the alpine meadows of Northwest Sichuan北大核心CSCD

Desertification has emerged as a serious threat to the alpine meadows of Northwest Sichuan in recent decades. Artificial vegetation had certain effects on desertification recovery, while how the CO2 flux changed and its reasons are still unclear. During the growing season in 2016 (i.e., from July to September), we selected the desertified alpine meadows with different recovery degrees, including the early stage of restoration, the middle stage of restoration, the late stage of restoration, and control (the unrecovered desertification meadow) as four transects. CO2 flux was measured by the instrument LI-8100, and the microenvironment factors that affected CO2 flux changes were analyzed. The results showed that the carbon sequestration function of desertified alpine meadows gradually increased with the degree of recovery. Net ecosystem exchange (NEE) were -1.61, -3.55, and -4.38 μmol m-2 s-1 in the early, mid-term, and late transects, respectively, and the most dramatic changes occurred from the early stage to mid-term stage, increasing by 120.50%. Both ecosystem respiration (ER) and soil respiration (SR) were enhanced significantly with restoration (P < 0.05). In mid or late July, NEE, ER, and SR reached their maximum values, and thereafter, the indicators varied to near zero (P < 0.05). During the whole growing season, the daily dynamic in CO2 flux for the control alpine meadow was mild and retained the trend of continuous release all day, but that in the desertified alpine meadow was a single peak pattern. Moreover, with restoration process, the peak of CO2 flux increased and reached a peak in the late stage of the recovery process. The regression analysis showed that there was a significant positive correlation between CO2 flux and vegetation coverage, aboveground biomass, and soil moisture (0-5 cm) (P < 0.01), and a weak correlation with 0-5-cm soil temperature (P < 0.01). This indicates that topsoil moisture (5 cm) is a more significant factor for CO2 flux than topsoil temperature during the growing season in the restoration of desertified alpine meadows in Northwest Sichuan. In general, the vegetation recovery significantly improved the carbon-sequestration ability of the desertified alpine meadows during the growing season in Northwest Sichuan, and at the middle stage of restoration, the carbon-sequestration ability improved significantly due to vegetation restoration and increase in topsoil (0-5 cm) moisture. © 2018 Science Press. All rights reserved.     

碳中和——中国发展转型的机遇与挑战

碳中和是《巴黎协定》提出的到21世纪末在全球范围内实现人为活动排放的温室气体排放总量与大自然吸收总量相平衡,这是《联合国气候变化框架公约》应对气候变化问题的终极目标。本文从碳中和的目的、本质和进展分析入手,提出了在实现碳中和问题上中国的机遇与挑战。     

基于水足迹理论的区域水资源利用评价

水资源是一个地区经济发展、社会稳定的基础。水资源利用评价研究对分析区域水资源问题、制定合理的水资源战略具有重要意义。论文引入水足迹理论,构建区域水足迹结构、效益、生态安全以及可持续性指标体系,对区域水资源的利用现状和可持续性进行评价分析,并以大连市为案例对其水资源利用情况进行评价,结果表明该评价方法简便直观、合理可行。     

Development and optimization of an Agro-BGC ecosystem model for C4 perennial grasses

Extrapolating simulations of bioenergy crop agro-ecosystems beyond data-rich sites requires biophysically accurate ecosystem models and careful estimation of model parameters not available in the literature. To increase biophysical accuracy we added C₄ perennial grass functionality and agricultural practices to the Biome-BGC (BioGeochemical Cycles) ecosystem model. This new model, Agro-BGC, includes enzyme-driven C₄ photosynthesis, individual live and dead leaf, stem, and root carbon and nitrogen pools, separate senescence and litter fall processes, fruit growth, optional annual seeding, flood irrigation, a growing degree day phenology with a killing frost option, and a disturbance handler that simulates nitrogen fertilization, harvest, fire, and incremental irrigation. To obtain spatially generalizable vegetation parameters we used a numerical method to optimize five unavailable parameters for Panicum virgatum (switchgrass) using biomass yield data from three sites: Mead, Nebraska, Rockspring, Pennsylvania, and Mandan, North Dakota. We then verified simulated switchgrass yields at three independent sites in Illinois (IL). Agro-BGC is more accurate than Biome-BGC in representing the physiology and dynamics of C₄ grass and management practices associated with agro-ecosystems. The simulated two-year average mature yields with single-site Rockspring optimization have Root Mean Square Errors (RMSE) of 70, 152, and 162 and biases of 43, −87, 156 g carbon m⁻² for Shabbona, Urbana, and Simpson IL, respectively. The simulated annual yields in June, August, October, December, and February have RMSEs of 114, 390, and 185 and biases of −19, −258, and 147 g carbon m⁻² for Shabbona, Urbana, and Simpson IL, respectively. These RMSE and bias values are all within the largest 90% confidence interval around respective IL site measurements. Twenty-four of twenty-six simulated annual yields with Rockspring optimization are within 95% confidence intervals of Illinois site measurements during the mature fourth and fifth years of growth. Ten of eleven simulated two-year average mature yields with Rockspring optimization are within 65% confidence intervals of Illinois site measurements and the eleventh is within the 95% confidence interval. Rockspring optimized Agro-BGC achieves accuracies comparable to those of two previously published models: Agricultural Land Management Alternatives with Numerical Assessment Criteria (ALMANAC) and Integrated Farm System Model (IFSM). Agro-BGC suffers from static vegetation parameters that can change seasonally and as plants age. Using mature plant data for optimization mitigates this deficiency. Our results suggest that a multi-site optimization scheme using mature plant data from more sites would be adequate for generating spatially generalizable vegetation parameters for simulating mature bioenergy crop agro-ecosystems with Agro-BGC.     

Modelling forest management within a global vegetation model—Part 1: Model structure and general behaviour

This article describes a new forest management module (FMM) that explicitly simulates forest stand growth and management within a process-based global vegetation model (GVM) called ORCHIDEE. The net primary productivity simulated by ORCHIDEE is used as an input to the FMM. The FMM then calculates stand and management characteristics such as stand density, tree size distribution, tree growth, the timing and intensity of thinnings and clear-cuts, wood extraction and litter generated after thinning. Some of these variables are then fed back to ORCHIDEE. These computations are made possible with a distribution-based modelling of individual tree size. The model derives natural mortality from the relative density index (rdi), a competition index based on tree size and stand density. Based on the common forestry management principle of avoiding natural mortality, a set of rules is defined to calculate the recurrent intensity and frequency of forestry operations during the stand lifetime. The new-coupled model is called ORCHIDEE-FM (forest management).The general behaviour of ORCHIDEE-FM is analysed for a broadleaf forest in north-eastern France. Flux simulation throughout a forest rotation compare well with the literature values, both in absolute values and dynamics.Results from ORCHIDEE-FM highlight the impact of forest management on ecosystem C-cycling, both in terms of carbon fluxes and stocks. In particular, the average net ecosystem productivity (NEP) of 225 gC m⁻² year⁻¹ is close to the biome average of 311 gC m⁻² year⁻¹. The NEP of the “unmanaged” case is 40% lower, leading us to conclude that management explains 40% of the cumulated carbon sink over 150 years. A sensitivity analysis reveals 4 major avenues for improvement: a better determination of initial conditions, an improved allocation scheme to explain age-related decline in productivity, and an increased specificity of both the self-thinning curve and the biomass-diameter allometry.