Trade wars in the TRIPS Council: Intellectual property, technology transfer, and climate change

This Chapter considers the geopolitical conflicts in respect of intellectual property, trade, and climate change in the TRIPS Agreement 1994 under the World Trade Organization (WTO). In particular, it focuses upon debates in the TRIPS Council on the topic of patent law and clean energy in 2013 and 2014. The chapter highlights the development agenda of a number of developing countries who are keen for access to clean energy to combat climate change and global warming. It also considers the mixed contributions of members of the BRICS/ BASIC group – including Brazil, India, China, and South Africa. This chapter highlights the intellectual property maximalist position of a number of developed countries on intellectual property, climate change, and trade. Seeking to overcome this conflict and stalemate, this Chapter puts forward both procedural and substantial reform options in respect of intellectual property, trade, and climate change in the TRIPS Council and the WTO. It also flags that the TRIPS Agreement 1994 could well be displaced by the rise of mega-regional trade agreements – such as the Trans-Pacific Partnership (TPP), and the Trans-Atlantic Trade and Investment Partnership (TTIP).

Climate change and agriculture: theory and application of mitigation policies

Agriculture’s contribution to climate change is controversial as it is a significant source of greenhouse gases but also a sink of carbon. Hence its economic and technological potential to mitigate climate change have been argued to be noteworthy. However, social profitability of emission mitigation is a result from factors among emission reductions such as surface water quality impact or profit from production. Consequently, to value comprehensive results of agricultural climate emission mitigation practices, these co-effects to environment and economics should be taken into account. The objective of this thesis was to develop an integrated economic and ecological model to analyse the social welfare of crop cultivation in Finland on distinctive cultivation technologies, conventional tillage and conservation tillage (no-till). Further, we ask whether it would be privately or socially profitable to allocate some of barley cultivation for alternative land use, such as green set-aside or afforestation, when production costs, GHG’s and water quality impacts are taken into account. In the theoretical framework we depict the optimal input use and land allocation choices in terms of environmental impacts and profit from production and derive the optimal tax and payment policies for climate and water quality friendly land allocation. The empirical application of the model uses Finnish data about production cost and profit structure and environmental impacts. According to our results, given emission mitigation practices are not self-evidently beneficial for farmers or society. On the contrary, in some cases alternative land allocation could even reduce social welfare, profiting conventional crop cultivation. This is the case regarding mineral soils such as clay and silt soils. On organic agricultural soils, climate mitigation practices, in this case afforestation and green fallow give more promising results, decreasing climate emissions and nutrient runoff to water systems. No-till technology does not seem to profit climate mitigation although it does decrease other environmental impacts. Nevertheless, the data behind climate emission mitigation practices impact to production and climate is limited and partly contradictory. More specific experiment studies on interaction of emission mitigation practices and environment would be needed. Further study would be important. Particularly area specific production and environmental factors and also food security and safety and socio-economic impacts should be taken into account.

Mahanadi streamflow: climate change impact assessment and adaptive strategies

Impacts of climate change on hydrology are assessed by downscaling large scale general circulation model (GCM) outputs of climate variables to local scale hydrologic variables. This modelling approach is characterized by uncertainties resulting from the use of different models, different scenarios, etc. Modelling uncertainty in climate change impact assessment includes assigning weights to GCMs and scenarios, based on their performances, and providing weighted mean projection for the future. This projection is further used for water resources planning and adaptation to combat the adverse impacts of climate change. The present article summarizes the recent published work of the authors on uncertainty modelling and development of adaptation strategies to climate change for the Mahanadi river in India.

Importance of carbon dioxide physiological forcing to future climate change

An increase in atmospheric carbon dioxide (CO2) concentration influences climate both directly through its radiative effect (i.e., trapping longwave radiation) and indirectly through its physiological effect (i.e., reducing transpiration of land plants). Here we compare the climate response to radiative and physiological effects of increased CO2 using the National Center for Atmospheric Research (NCAR) coupled Community Land and Community Atmosphere Model. In response to a doubling of CO2, the radiative effect of CO2 causes mean surface air temperature over land to increase by 2.86 ± 0.02 K (± 1 standard error), whereas the physiological effects of CO2 on land plants alone causes air temperature over land to increase by 0.42 ± 0.02 K. Combined, these two effects cause a land surface warming of 3.33 ± 0.03 K. The radiative effect of doubling CO2 increases global runoff by 5.2 ± 0.6%, primarily by increasing precipitation over the continents. The physiological effect increases runoff by 8.4 ± 0.6%, primarily by diminishing evapotranspiration from the continents. Combined, these two effects cause a 14.9 ± 0.7% increase in runoff. Relative humidity remains roughly constant in response to CO2-radiative forcing, whereas relative humidity over land decreases in response to CO2-physiological forcing as a result of reduced plant transpiration. Our study points to an emerging consensus that the physiological effects of increasing atmospheric CO2 on land plants will increase global warming beyond that caused by the radiative effects of CO2.

Agricultural expansion and climate change in the Taita Hills, Kenya: an assessment of potential environmental impacts

The indigenous cloud forests in the Taita Hills have suffered substantial degradation for several centuries due to agricultural expansion. Currently, only 1% of the original forested area remains preserved in this region. Furthermore, climate change imposes an imminent threat for local economy and environmental sustainability. In such circumstances, elaborating tools to conciliate socioeconomic growth and natural resources conservation is an enormous challenge. This dissertation tackles essential aspects for understanding the ongoing agricultural activities in the Taita Hills and their potential environmental consequences in the future. Initially, alternative methods were designed to improve our understanding of the ongoing agricultural activities. Namely, methods for agricultural survey planning and to estimate evapotranspiration were evaluated, taking into account a number of limitations regarding data and resources availability. Next, this dissertation evaluates how upcoming agricultural expansion, together with climate change, will affect the natural resources in the Taita Hills up to the year 2030. The driving forces of agricultural expansion in the region were identified as aiming to delineate future landscape scenarios and evaluate potential impacts from the soil and water conservation point of view. In order to investigate these issues and answer the research questions, this dissertation combined state of the art modelling tools with renowned statistical methods. The results indicate that, if current trends persist, agricultural areas will occupy roughly 60% of the study area by 2030. Although the simulated land use changes will certainly increase soil erosion figures, new croplands are likely to come up predominantly in the lowlands, which comprise areas with lower soil erosion potential. By 2030, rainfall erosivity is likely to increase during April and November due to climate change. Finally, this thesis addressed the potential impacts of agricultural expansion and climate changes on Irrigation Water Requirements (IWR), which is considered another major issue in the context of the relations between land use and climate. Although the simulations indicate that climate change will likely increase annual volumes of rainfall during the following decades, IWR will continue to increase due to agricultural expansion. By 2030, new cropland areas may cause an increase of approximately 40% in the annual volume of water necessary for irrigation.

Religion´s role in Development, Ecology & Climate Change

Islam, Development, Ecology,

What do hydrological time series tell about climate change?

Yhteenveto: Mitä hydrologiset mallit kertovat ilmaston muutoksesta?

Fast versus slow response in climate change: implications for the global hydrological cycle

Recent studies have shown that changes in global mean precipitation are larger for solar forcing than for CO2 forcing of similar magnitude.In this paper, we use an atmospheric general circulation model to show that the differences originate from differing fast responses of the climate system. We estimate the adjusted radiative forcing and fast response using Hansen's ``fixed-SST forcing'' method.Total climate system response is calculated using mixed layer simulations using the same model. Our analysis shows that the fast response is almost 40% of the total response for few key variables like precipitation and evaporation. We further demonstrate that the hydrologic sensitivity, defined as the change in global mean precipitation per unit warming, is the same for the two forcings when the fast responses are excluded from the definition of hydrologic sensitivity, suggesting that the slow response (feedback) of the hydrological cycle is independent of the forcing mechanism. Based on our results, we recommend that the fast and slow response be compared separately in multi-model intercomparisons to discover and understand robust responses in hydrologic cycle. The significance of this study to geoengineering is discussed.

Constraining uncertainty in regional hydrologic impacts of climate change: Nonstationarity in downscaling

Regional impacts of climate change remain subject to large uncertainties accumulating from various sources, including those due to choice of general circulation models (GCMs), scenarios, and downscaling methods. Objective constraints to reduce the uncertainty in regional predictions have proven elusive. In most studies to date the nature of the downscaling relationship (DSR) used for such regional predictions has been assumed to remain unchanged in a future climate. However,studies have shown that climate change may manifest in terms of changes in frequencies of occurrence of the leading modes of variability, and hence, stationarity of DSRs is not really a valid assumption in regional climate impact assessment. This work presents an uncertainty modeling framework where, in addition to GCM and scenario uncertainty, uncertainty in the nature of the DSR is explored by linking downscaling with changes in frequencies of such modes of natural variability. Future projections of the regional hydrologic variable obtained by training a conditional random field (CRF) model on each natural cluster are combined using the weighted Dempster-Shafer (D-S) theory of evidence combination. Each projection is weighted with the future projected frequency of occurrence of that cluster (''cluster linking'') and scaled by the GCM performance with respect to the associated cluster for the present period (''frequency scaling''). The D-S theory was chosen for its ability to express beliefs in some hypotheses, describe uncertainty and ignorance in the system, and give a quantitative measurement of belief and plausibility in results. The methodology is tested for predicting monsoon streamflow of the Mahanadi River at Hirakud Reservoir in Orissa, India. The results show an increasing probability of extreme, severe, and moderate droughts due to limate change. Significantly improved agreement between GCM predictions owing to cluster linking and frequency scaling is seen, suggesting that by linking regional impacts to natural regime frequencies, uncertainty in regional predictions can be realistically quantified. Additionally, by using a measure of GCM performance in simulating natural regimes, this uncertainty can be effectively constrained.

Climate change, sustainable development and India: Global and national concerns

Climate change is one of the most important global environmental challenges, with implications for food production, water supply, health, energy, etc. Addressing climate change requires a good scientific understanding as well as coordinated action at national and global level. This paper addresses these challenges. Historically, the responsibility for greenhouse gas emissions' increase lies largely with the industrialized world, though the developing countries are likely to be the source of an increasing proportion of future emissions. The projected climate change under various scenarios is likely to have implications on food production, water supply, coastal settlements, forest ecosystems, health, energy security, etc. The adaptive capacity of communities likely to be impacted by climate change is low in developing countries. The efforts made by the UNFCCC and the Kyoto Protocol provisions are clearly inadequate to address the climate change challenge. The most effective way to address climate change is to adopt a sustainable development pathway by shifting to environmentally sustainable technologies and promotion of energy efficiency, renewable energy, forest conservation, reforestation, water conservation, etc. The issue of highest importance to developing countries is reducing the vulnerability of their natural and socio-economic systems to the projected climate change. India and other developing countries will face the challenge of promoting mitigation and adaptation strategies, bearing the cost of such an effort, and its implications for economic development.

Forest governance and climate change adaptation : Case studies of four African countries

Africa is threatened by climate change. The adaptive capacity of local communities continues to be weakened by ineffective and inefficient livelihood strategies and inappropriate development interventions. One of the greatest challenges for climate change adaptation in Africa is related to the governance of natural resources used by vulnerable poor groups as assets for adaptation. Practical and good governance activities for adaptation in Africa is urgently and much needed to support adaptation actions, interventions and planning. The adaptation role of forests has not been as prominent in the international discourse and actions as their mitigation role. This study therefore focused on the forest as one of the natural resources used for adaptation. The general objective of this research was to assess the extent to which cases of current forest governance practices in four African countries Burkina Faso, The Democratic Republic of Congo (DRC), Ghana and Sudan are supportive to the adaptation of vulnerable societies and ecosystems to impacts of climate change. Qualitative and quantitative analyses from surveys, expert consultations and group discussions were used in analysing the case studies. The entire research was guided by three conceptual sets of thinking forest governance, climate change vulnerability and ecosystem services. Data for the research were collected from selected ongoing forestry activities and programmes. The study mainly dealt with forest management policies and practices that can improve the adaptation of forest ecosystems (Study I) and the adaptive capacity through the management of forest resources by vulnerable farmers (Studies II, III, IV and V). It was found that adaptation is not part of current forest policies, but, instead, policies contain elements of risk management practices, which are also relevant to the adaptation of forest ecosystems. These practices include, among others, the management of forest fires, forest genetic resources, non-timber resources and silvicultural practices. Better livelihood opportunities emerged as the priority for the farmers. These vulnerable farmers had different forms of forest management. They have a wide range of experience and practical knowledge relevant to ensure and achieve livelihood improvement alongside sustainable management and good governance of natural resources. The contributions of traded non-timber forest products to climate change adaptation appear limited for local communities, based on their distribution among the stakeholders in the market chain. Plantation (agro)forestry, if well implemented and managed by communities, has a high potential in reducing socio-ecological vulnerability by increasing the food production and restocking degraded forest lands. Integration of legal arrangements with continuous monitoring, evaluation and improvement may drive this activity to support short, medium and long term expectations related to adaptation processes. The study concludes that effective forest governance initiatives led by vulnerable poor groups represent one practical way to improve the adaptive capacities of socio-ecological systems against the impacts of climate change in Africa.

Hydrologic drought prediction under climate change: Uncertainty modeling with Dempster-Shafer and Bayesian approaches

Representation and quantification of uncertainty in climate change impact studies are a difficult task. Several sources of uncertainty arise in studies of hydrologic impacts of climate change, such as those due to choice of general circulation models (GCMs), scenarios and downscaling methods. Recently, much work has focused on uncertainty quantification and modeling in regional climate change impacts. In this paper, an uncertainty modeling framework is evaluated, which uses a generalized uncertainty measure to combine GCM, scenario and downscaling uncertainties. The Dempster-Shafer (D-S) evidence theory is used for representing and combining uncertainty from various sources. A significant advantage of the D-S framework over the traditional probabilistic approach is that it allows for the allocation of a probability mass to sets or intervals, and can hence handle both aleatory or stochastic uncertainty, and epistemic or subjective uncertainty. This paper shows how the D-S theory can be used to represent beliefs in some hypotheses such as hydrologic drought or wet conditions, describe uncertainty and ignorance in the system, and give a quantitative measurement of belief and plausibility in results. The D-S approach has been used in this work for information synthesis using various evidence combination rules having different conflict modeling approaches. A case study is presented for hydrologic drought prediction using downscaled streamflow in the Mahanadi River at Hirakud in Orissa, India. Projections of n most likely monsoon streamflow sequences are obtained from a conditional random field (CRF) downscaling model, using an ensemble of three GCMs for three scenarios, which are converted to monsoon standardized streamflow index (SSFI-4) series. This range is used to specify the basic probability assignment (bpa) for a Dempster-Shafer structure, which represents uncertainty associated with each of the SSFI-4 classifications. These uncertainties are then combined across GCMs and scenarios using various evidence combination rules given by the D-S theory. A Bayesian approach is also presented for this case study, which models the uncertainty in projected frequencies of SSFI-4 classifications by deriving a posterior distribution for the frequency of each classification, using an ensemble of GCMs and scenarios. Results from the D-S and Bayesian approaches are compared, and relative merits of each approach are discussed. Both approaches show an increasing probability of extreme, severe and moderate droughts and decreasing probability of normal and wet conditions in Orissa as a result of climate change. (C) 2010 Elsevier Ltd. All rights reserved.

From ‘Afflicted’ to Activists: Structural Violence and Climate Change Discourse in the States of Pernambuco and Paraíba in Northeast Brazil

This study approaches the problem of poverty in the hinterlands of Northeast Brazil through the concept of structural violence, linking the environmental threats posed by climate change, especially those related to droughts, to the broader social struggles in the region. When discussions about potentials and rights are incorporated into the problematic of poverty, a deeper insight is obtained regarding the various factors behind the phenomenon. It is generally believed that climate change is affecting the already marginalized and poor more than those of higher social standing, and will increasingly do so in the future. The data for this study was collected during a three month field work in the states of Pernambuco and Paraíba in Northeast Brazil. The main methods used were semi-structured interviews and participant observation, including attending seminars concerning climate change on the field. The focus of the work is to compare both layman and expert perceptions on what climate change is about, and question the assumptions about its effects in the future, mainly that of increased numbers of ‘climate refugees’ or people forced to migrate due to changes in climate. The focus on droughts, as opposed to other manifestations of climate change, arises from the fact that droughts are not only phenomena that develop over a longer time span than floods or hurricanes, but is also due to the historical persistence of droughts in the region, and both the institutional and cultural linkages that have evolved around it. The instances of structural violence that are highlighted in this study; the drought industry, land use, and the social and power relations present in the region, including those between the civil society, the state and the private agribusiness sector, all work against a backdrop of symbolic and moral realms of value production, where relations between the different actors are being negotiated anew with the rise of the climate change discourse. The main theoretical framework of the study consists of Johan Galtung’s and Paul Farmer’s theory of structural violence, Ulrich Beck’s theory of the risk society, and James Scott’s theory of everyday peasant resistance.