mitigation potential. Insights of this study can assist policy makers in designing future EU biofuel policy in such way that landusechangeimpacts are effectively addressed.
Because ILUC occurs through global market mechanisms with many direct and indirect effects, it can only be modelled, not measured. Direct measurement will only provide partial accounting of the total effects. Previous studies have tried to quantify ILUC related emissions, to understand whether the use of biofuels really avoids greenhousegas emissions on a global scale and by how much. The current study focuses on biofuelsconsumed in the EU. Note that it does not discuss whether biofuel producers should be held accountable for effects that are indirectly induced by their actions but which take place outside their control. Nor does it answer the question regarding how it can be ensured that biofuels actually reduce greenhouse gasses emissions compared to fossil fuels, within a certain timeframe. The aim of this study is only to model biofuel induced landusechange and its greenhousegas emission consequences, as consistently as possible, using a tailored version of the GLOBIOM model. Whilst this is not the first study that quantifies landusechangeimpacts of EUbiofuels – it follows a study published by the International Food Policy Research Institute (IFPRI) in 2011 (Laborde, 2011) – the current study quantifies for the first time landusechange emissions from advanced biofuel feedstocks as well as several ‘alternative scenarios’, as further explained below. The study is relevant for the discussion on the 2030 EU policy framework for energy and climate change.
Concerns about biofuel sustainability have pushed governments and international agencies to develop sustainability criteria for biofuels that producers must respect . Special attention has been given to reporting the greenhousegas (GHG) emission savings (GES) of biofuels . Several countries have issued regulations that require reporting the GHG emission performance of biofuels. These regula- tory schemes include the Renewable Transport Fuel Obligation in the United Kingdom (UK), the Renewable Energy Directive (RED) in the European Union (EU), the Low-carbon Fuel Standard in the State of California, and the Environmental Protection Agency ’ s (EPA) Renew- able Fuel Standard (RFS) in the United States of America (USA) [3 – 5]. A major point of discussion in the assessment of biofuel GES is the impact of feedstock production on land-usechange (LUC) [6,7]. In the case of agricultural-based feedstock for biofuels, recent studies point to the signi ﬁ cance of LUC – GHG emissions for the overall GHG emission balance of biofuels [2,8 – 14]. When LUC occurs, the GES of biofuels may be offset by the direct or indirect contribution to carbon stock changes in land . Consequently, in recent years, the number of studies dealing with biofuels, LUC, and GHG emissions has grown sharply .
Henry et al. (2009) addressed the impact of soybean expansion in agricultural cropland competition. They suggest that soybean expansion accounted for the shift from dairy farms and cattle breeding, the shift from annual crops production (mainly wheat, corn, cotton, sunflower, sorghum and rice) and the decrease in pastures rotation. The displaced activity, however, varies geographically, mainly between the traditional soybean cultivation area (Santa Fe, Cordoba, Buenos Aires and Entre Rios) and the marginal area (Santiago del Estero, Salta, Chaco, and Tucuman) (Grau et al. 2005; Henry et al. 2009). OEA (2009) compared National Agricultural Census data between 1988 and 2002 to explore soybean production patterns among different regions. In the Central region, dairy farms have been replaced by soybean plantations. Moreover, Coutinho et al. (2008) indicates that rotations with pastures have been reduced and displaced to the Northern part of Santa Fe. In Cordoba the same process has occurred mainly replacing pastures in the Pampas. In Santa Fe, 70% of the agricultural area is soybean, where soybean area has almost doubled the expansion of the agricultural area, suggesting that other activities have been substituted. According to OEA (2009) 60% of the soybean area expansion was done by first occupation, suggesting that crops rotation has been reduced. They state that soybean has replaced pastures, mainly perennial and other oilseeds, particularly sunflower.
We implemented a spatial application of a previously evaluated model of soil GHG emissions, ECOSSE, in the United Kingdom to examine the impacts to 2050 of land-use transitions from existing landuse, rotational crop- land, permanent grassland or woodland, to six bioenergy crops; three ‘first-generation’ energy crops: oilseed rape, wheat and sugar beet, and three ‘second-generation’ energy crops: Miscanthus, short rotation coppice wil- low (SRC) and short rotation forestry poplar (SRF). Conversion of rotational crops to Miscanthus, SRC and SRF and conversion of permanent grass to SRF show beneficial changes in soil GHG balance over a significant area. Conversion of permanent grass to Miscanthus, permanent grass to SRF and forest to SRF shows detrimental changes in soil GHG balance over a significant area. Conversion of permanent grass to wheat, oilseed rape, sugar beet and SRC and all conversions from forest show large detrimental changes in soil GHG balance over most of the United Kingdom, largely due to moving from uncultivated soil to regular cultivation. Differences in net GHG emissions between climate scenarios to 2050 were not significant. Overall, SRF offers the greatest bene- ficial impact on soil GHG balance. These results provide one criterion for selection of bioenergy crops and do not consider GHG emission increases/decreases resulting from displaced food production, bio-physical factors (e.g. the energy density of the crop) and socio-economic factors (e.g. expenditure on harvesting equipment). Given that the soil GHG balance is dominated by change in soil organic carbon (SOC) with the difference among Miscanthus, SRC and SRF largely determined by yield, a target for management of perennial energy crops is to achieve the best possible yield using the most appropriate energy crop and cultivar for the local situation.
Reliance on fossil fuels is causing unprecedented climate change and is accelerating environmental degradation and global biodiversity loss. Together, climate change and biodiversity loss, if not averted urgently, may inflict severe damage on ecosystem processes, functions and services that support the welfare of modern societies. Increasing renewable energy deployment and expanding the current protected area network represent key solu- tions to these challenges, but conflicts may arise over the use of limited land for energy production as opposed to biodiversity conservation. Here, we compare recently identified core areas for the expansion of the global pro- tected area network with the renewable energy potential available from land-based solar photovoltaic, wind energy and bioenergy (in the form of Miscanthus 9 giganteus). We show that these energy sources have very dif- ferent biodiversity impacts and net energy contributions. The extent of risks and opportunities deriving from renewable energy development is highly dependent on the type of renewable source harvested, the restrictions imposed on energy harvest and the region considered, with Central America appearing at particularly high potential risk from renewable energy expansion. Without restrictions on power generation due to factors such as production and transport costs, we show that bioenergy production is a major potential threat to biodiversity, while the potential impact of wind and solar appears smaller than that of bioenergy. However, these differences become reduced when energy potential is restricted by external factors including local energy demand. Overall, we found that areas of opportunity for developing solar and wind energy with little harm to biodiversity could exist in several regions of the world, with the magnitude of potential impact being particularly dependent on restrictions imposed by local energy demand. The evidence provided here helps guide sustainable development of renewable energy and contributes to the targeting of global efforts in climate mitigation and biodiversity con- servation.
Figure 9. Sensitivity of total cost of the GHG abatement of biofuels in 2018, 2030 and 2050 in sensitivity case 1B (corresponding to the base scenario (a)), at a constant annual 4% wheat price increase and the other variables randomly varied according to Section 2.4. The red lines show the median, the bottom and top edges of the blue box show the 25th and 75th percentiles, respectively, the whiskers extend to a maximum of 1.5 times the length of the box and outside of this interval outliers are plotted with a red cross.
management (Powlson et al., 2011). Therefore, C sequestra- tion into soils is one of the most important ecosystem ser- vices because of its role in climate regulation (IPCC, 2007). Intensification of agriculture and/or transformation of con- ventional tillage (CT) practices, may cause enormous losses of soil organic carbon (SOC), thus inducing an increase in soil erosion and a breakage of soil structure (Melero et al., 2009). Landusechange (LUC) is considered the second greatest cause of C emissions after fuel consumption (Watson et al., 2000). LUC has contributed to soil degradation and soil loss, leading to a decrease in soil C storage worldwide (Eaton et al., 2008), and even more intensely in the Mediterranean areas during the last few decades (Cerd`a et al., 2010). Long- term experimental studies have confirmed that SOC is highly sensitive to LUC (Smith, 2008). Thus, even a relatively small increase or decrease in soil carbon content due to changes in landuse or management practices may result in a significant
Climate change will have potentially significant effects on hydropower generation due to changes in the magnitude and seasonality of river runoff and increases in reservoir evaporation. These physical impacts will in turn have economic consequences through both producer revenues and consumer expenditures. We analyze the physical and economic effects of changes in hydropower generation for the contiguous U. S. in futures with and without global-scale greenhousegas (GHG) mitigation, and across patterns from 18 General Circulation Models. Using a monthly water resources systems model of 2119 river basins that routes simulated river runoff through reservoirs, and allocates water to potentially conflicting and cli- mate dependent demands, we provide a first-order estimate of the impacts of various projected emis- sions outcomes on hydropower generation, and monetize these impacts using outputs from an electric sector planning model for over 500 of the largest U.S. hydropower facilities. We find that, due to generally increasing river runoff under higher emissions scenarios in the Pacific Northwest, climate change tends to increase overall hydropower generation in the contiguous U.S. During low flow months, generation tends to fall with increasing emissions, potentially threatening the estimated low flow, firm energy from hydro- power. Although global GHG mitigation slows the growth in hydropower generation, the higher value placed on carbon-free hydropower leads to annual economic benefits ranging from $1.8 billion to $4.3 billion. The present value of these benefits to the U.S. from global greenhousegas mitigation, discounted at 3%, is $34 to $45 billion over the 2015–2050 period.
The interest in developing biofuels has rapidly increased during the last decades followed by a strong controversy about their sustainability. Diverting a large amount of land from agriculture to fuels, impacting forests and grasslands, loss of biodiversity due to large monocropped fields are some threats that inhibit the momentum towards a significant substitution of fossil fuels by biofuels. From a methodological point of view, several estimations of the reduction of greenhousegas (GHG) emissions from biofuels lead to a large variability of results even if they address the same biofuel pathway. It has been shown that the methods used and the assumptions on data inventories, system boundaries, allocation of resources and emissions may significantly impact the results. In different countries and regions in the world, sustainability standards are being developed in order to limit the promotion of biofuels to those that are environmentally sound, socially responsible and economically effective. Global warming is of a particular interest when assessing the sustainability of biofuels as one of the main drivers of their development is their potential to mitigate GHG emissions. Therefore global sustainability standards include GHG balances as a main point. In many cases, Carbon reporting is separate from the reporting on other sustainability criteria (e.g. UK and California initiatives), reflecting the importance given to that item. Furthermore, the general impression is that at policy level it is easier to quantify Carbon balances than local environmental and social impacts. However evaluating GHG balances of biofuels is not straightforward. This paper aims at investigating the main assumptions made in the literature when estimating the reduction of GHG emissions of biofuels in comparison with their fossil competitors. In section 2 the main items that structure the Life Cycle Analysis (LCA) of biofuels are commented and methodological choices are addressed from a constructive criticism point of view. Section 3 analyses selected papers and works on biofuels. Finally, the conclusion highlights the necessity of transparency and gives some recommendations for estimating the reduction of GHG emissions.
The peatland maps used by the US EPA were the one by Wahyunto et al. (2003, 2004, 2006) which were relied heavily on landsat TM imageries with a relatively limited ground truthing. Ritung et al. (2011) updated the maps of Wahyunto et al. (2003, 2004, 2006) using soil survey data conducted between 2001 2010. These new maps showed a 14% reduction in the estimate of peatland area in Sumatra and Kalimantan. Comparing between the two maps, there are cases where shallow peat (< 100 cm) has undergone subsidence until its thickness was less than 50 cm for which the area can no longer be classified as peatland. On the other hand, there are cases of areas depicted as peatland in the older map, but turned to be mineral soils based on the ground truth data. Furthermore, there are also cases in which the land was interpreted as mineral soil whereas it actually was peat. Comparison of peat area estimate in the three main islands of Indonesia is presented in Table 3. This new maps show a 14% reduction of peatland in Sumatra and Kalimantan. We estimate the future oil palm expansion on peatland of 10%
Several states and cities in the U.S. have taken the initiative to cap their emissions of greenhouse gases. The U.S. Mayors Climate Protection Agreement, initiated by Mayor Greg Nickles of Seattle, has been responded to by at least 227 mayors across the nation. These cities, home to approximately forty-four million Americans, have agreed to reduce greenhousegas emissions to seven percent below 1990 levels in the near future by improving their mass transit systems, encouraging ride sharing, building bike lanes and trails, curbing urban sprawl, and improving sidewalks . Portland Oregon, the first U.S. city to develop a global warming action plan, has succeeded in increasing public transit use by 75 percent since 1990. A new major light rail line was built and the central city streetcar was reinstated. City workers receive free parking if they car pool and free monthly bus passes, and businesses are encouraged to subsidize public transit commutes just as they do employee parking. Portland also has 430 kilometers of bikeways which it plans to increase two-fold in the next decade. Traffic signals were converted to LED bulbs that have decreased energy use by 80 percent saving the city $500,000 each year, and Portland is currently researching the feasibility of powering all its city facilities with wind energy. There is no shortage of innovative ideas or technical solutions. However, neither is there a shortage of those who have vested interests in maintaining the status quo. Rajan  writes that to reduce emissions to the extent necessary over the next decades, technological, economical and political solutions must be supplemented by landuse and life style changes that reduce car dependence.
As can be seen from the figure 6, initially the number of years is quite large. However, it quickly drops and stabilizes overtime. For example, it would take about 50 years to generate enough GHG mitigation that compensates for the GHG increases due to deforestation activities in 2010. However, as we move ahead in time, less conversion of forest lands to agricultural lands would be needed to meet increasing biofuel demand. By 2020, only 9 more years would be needed to counterbalance the emissions from land-usechange with GHG mitigation resulting from fossil fuel substitution if penetration of biofuels is not increased from the level of 2020. In reality, however, penetration of biofuels would be continuously increasing. We assumed that, after year 2020, the level of incentives (i.e., subsidy) for biofuels will remain the same at the level in year 2020 (or no additional incentive was provided, whereas incentives were increasing yearly between 2009 and 2020).
In the absence of a national policy to lower net GHG emissions, deliberate policies in the US have instead been enacted at the state level. State energy policy makers and their constituents can better understand the range and scope of local emissions sources which feed climate warming trends through periodic greenhousegas (GHG) accounting. Measuring emissions levels also establishes the baseline by which states can benchmark mandatory reduction targets. Eighteen US states have passed global warming reporting requirements to track state-based contributions to climate change, with three more state reporting mandates in progress . As example, the Con- necticut General Assembly’s 2008 passage of Public Act 08-98, an Act Concerning Connecticut Global Warm- ing Solutions (GWSA), introduced a triennial GHG inventory reporting requirement for that state . The com- plexity of information behind emissions data collection, as well as the need for standardization of collection protocols among states for comparison at the federal level, has given rise to default data aggregators such as the US Environmental Protection Agency’s (EPA) State Inventory Tool (SIT) . The EPA SIT is the principal data collection tool for assembling state-level GHG inventories using data collected by US federal agencies and de- fault estimates of C content and combustion efficiencies. EPA bases the landuse, change and forest (LUCF) module of the SIT on GHG guidelines developed for country-wide assessment of land-based C sinks . This approach requires a consistent, comprehensive division of land-based biomass according to the six main IPCC landuse categories—forest land, cropland, grassland, settlements, wetlands and other lands—but does not pro- vide single states the measurement tool to assess ground-level changes in biomass that alter C accounting results over time.
Direct, Indirect Indirect and and Induced Induced ImpactsImpacts of of Agricultural Agricultural Intensification Intensification and and Bio
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Brazil and USA representing 84% of the total net imports of EU27 (see ﬁgure 2 ; for a comparison of EU27 and global agricultural structure and emissions see supplementary information S5) that entails sig- niﬁcant trade of embodied cropland surface (MacDo- nald et al 2015 ). According to calculations based on FAOSTAT ( 2014 ) data, in 2004 about 70% of the Eur- opean livestock production was used for intra- national consumption and 18% –27% (respectively for chicken and cattle meat, expressed in N ) was traded between EU27 countries with signi ﬁcant associated embodied GHG emissions (Caro et al 2014 ). The EU was thus close to self-sufﬁciency for meat and dairy products, but the share of pig meat production was much higher than in the rest of the world, while the share of ruminant meat was signiﬁcantly lower (22% versus 29% globally).
fluvial ecosystems by Cole et al. (2007) was an admittedly conservative 0.8 Pg C per year. Over the following decade, this estimate was revised upward to 1.8 Pg C per year (Raymond et al., 2013) and then again to 3.9 Pg C per year (Drake et al., 2018). Estimates of the global extent of rivers and streams (i.e. total surface area) were also recently revised upward (Allen & Pavelsky, 2018). Collectively, these revised estimates suggest that fluvial ecosystems play a larger role in fluxes of GHGs than is represented by current global carbon budgets. Although the magnitude of CH 4 and N 2 O emissions is generally lower than that of CO 2 , they are more effective at trapping
Table 4 shows the difference in landusechange with higher price sensitivity. The results on the “A” columns are the baseline results, the “B” columns are the price sensitive results, and the “C” columns list the difference between two scenarios (C = B − A). With the increased price sensitivity, about 3.8 million hectares of forest are spared, while both cropland and pasture area decline by just over 3 million hectares and 767 thousand hectares, respectively. Even with the reduction in crop and pasture land, livestock output is higher at the global level for the price sensitive scenario compared to the baseline (Figure 6). While most regions had a decline in deforesta- tion under the price sensitive scenario, four regions had an increase, which includes BRAZIL, C_C_Amer, MEAS_NAfr, and S_S_AFR. The regions having the most reduction in deforestation are CHIHKG, INDIA, Mal_Indo, R_SE_Asia, and Rest of South Asia (R_S_Asia). Most of these regions are also the regions with the largest decrease in the cropland area (Table 4).
This research was conducted in Tirtomoyo District of Wonogiri Regency, Central Java. The study was conducted from October 2016 to January 2017. The analysis of landusechange was performed through visual interpretation (manually) on any past 12 years landusechange on Google Earth Pro imaging with image retrieval times in 2004 and 2016. The use of Google Earth Pro software facilitates more precise results of vegetation interpretation when compared to Landsat imaging interpretation. According to Thoha (2008), standard multispectral classification based on 20-30 meters spatial resolution such as Landsat and SPOT are often considered less subtle for the study of agricultural and urban areas in Java. Soil sampling at each location was divided based on the result of satellite imaging visual interpretation, namely the lands undergoing landuse changes in 2004 to 2016 and lands that had not experienced any landusechange (control point/baseline). The physical properties and soil morphology observed were slope, erosion sensitivity, erosion level, soil depth, upper and lower soil texture, permeability, drainage, gravel, flood threat, and salinity.
Abstract— The changes in Landuse have mostly occurred locally, regionally and globally over the last few decades and will carry on in the future as well. The increase in impervious surfaces has a major impact on rainfall and groundwater. The increase in urbanization results in changes in regular behavior of rainfall and also reduction in infiltration, which affects the groundwater recharge and storage. In the present study landuse detection in Chennai city and its impact on rainfall changes and groundwater level have been carried out using the latest techniques of Remote Sensing and Geographical Information System.
Methods used to assess the impacts of LU and climate on streamflow can be broadly classified into four categories: (i) experimental paired catchment approach, (ii) statistical techniques such as Mann–Kendall test, (iii) empirical or con- ceptual models and (iv) distributed physically based hydro- logic models. Among these techniques, the paired catchment approach is most difficult but often considered as the best ap- proach for smaller catchments. However, applicability of the paired catchment approach over large catchments may not be possible (Lørup et al., 1998) since it requires years of con- tinuous monitoring to gather sufficient data for the analysis. Statistical trend detection tests have been proved to be very useful in qualitatively determining the presence of a signif- icant trend in the time series along with direction and rate of change (Zhang et al., 2008; Li et al., 2009). But these techniques cannot be used for quantifying the change and attributing it to a particular cause due to a lack of a physical mechanism (Li et al., 2009). Empirical or conceptual mod- els are simple hydrologic models that require only a few pa- rameters to simulate a catchment. However, a major draw- back with these models is that the parameters may not be di- rectly related to the physical conditions of the catchment, and thus may lack the ability to correctly represent a catchment. Therefore, one is left with the option of using distributed physically based hydrologic models, which are by far the most appealing tools to carry out impact assessment stud- ies (Ott and Uhlenbrook, 2004; Mango et al., 2011; Wang et al., 2012). These models operate within a distributed frame- work to take physical and meteorological conditions of the basin into account (Refsgaard and Knudsen, 1996). Physi- cally distributed models include both fully distributed and semi-distributed models. Owing to their extensive parame- terization, fully distributed models are difficult to employ at a large catchment scale which make comparatively less data- intensive semi-distributed models a practical alternative. This paper presents a simple hydrologic modeling-based approach to isolate the impacts of landuse and climate on stream- flow. For this purpose, a physically based macroscale vari- able infiltration capacity (VIC) hydrologic model (Liang et al., 1994) has been employed for the analysis.