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The implementation of agroecology principles within organic farming research is a crux to redesign sustainable agri-food systems. To govern this transition, the local research demand should be addressed by direct engagement of all stakeholders in the research process. The first step is the involvement of farmers and technicians, with the aim of restoring their decision-making role, switching governance to local scale. The co-design/co-management of Long-Term Experiments (LTEs) can be crucial to govern the above-described transition through networking and participatory activities. In this study, we report the experience of co-designing a new LTE in Southern Italy by local actors and scientists. Through a participatory action research methodology, an LTE was considered as a biophysical component of an agroecological living lab, a public–private environment aimed to design a local food system. The setup of parallel field trials in satellite farms stands for the other biophysical component, whereas the stakeholder platform represents the social one. Through definition of common objectives, a step-by-step process is presented, which highlights the interest of local organic actors to share ideas and perspectives for the territory, pointing out the inclusion of end-users (the consumers) in the process to complete the transition to sustainable food systems.

Abstract Kenya has made considerable policy efforts to expand its renewable energy portfolio to meet energy demand and mitigate greenhouse gas (GHG) emissions. Development of proper policies requires a robust framework for analyzing the benefits of renewable energy investments. Towards this end, this study applied a choice experiment analysis to determine how attributes (type of energy, ownership, impact on environment, distance and visibility, community job creation, and yearly renewable energy tax) impact the public willingness to pay for renewable energy development in Kenya. A nationwide survey of 1020 households was conducted in nine counties using conditional logit (MNL) and random parameter logit (RPL) frameworks. The results reveal that the Kenyan public places a high value on environmental impact, followed by type of renewable energy and community job creation, respectively. On the other hand, respondents do not place much emphasis on ownership or distance and visibility. Policy simulation suggests that while renewable energy adoption is highly valued by households, the total willingness to pay is not enough to cover the higher capital cost for the development of various renewable energy technologies.

Integrated assessment models (IAMs) are playing an increasingly important role in long-run sustainability analysis. At their core is a set of global economic and environmental accounts which capture a complete set of inter-industry and inter-regional relationships in the global economy in a consistent manner. While much attention is focused on the raw data and parameterization required to expand or add sectoral detail to IAMs, only rarely is there discussion of how different matrix balancing methods (i.e. translating disparate raw data sources into the consistent database) affect modeling results. This article offers an in-depth look into the database–modeling nexus in IAMs, focusing on the electric power sector which is both a major source of CO2 emissions and a critical vehicle for climate change mitigation. Comparisons of the prevailing matrix balancing algorithms show how the choice of database reconciliation methodology affects modeling results using policy-relevant simulations in the context of the electric power sector. The resulting insights can be applied to the disaggregation of other, technology rich sectors in the economy. We conclude that appropriate selection of database reconciliation methodologies can reduce the deviation between bottom-up and top-down modeling.

The paper proposes a critical assessment of municipal solid waste gasification today, starting from basic aspects of the process (process types and steps, operating and performance parameters) and arriving to a comparative analysis of the reactors (fixed bed, fluidized bed, entrained bed, vertical shaft, moving grate furnace, rotary kiln, plasma reactor) as well as of the possible plant configurations (heat gasifier and power gasifier) and the environmental performances of the main commercially available gasifiers for municipal solid wastes. The analysis indicates that gasification is a technically viable option for the solid waste conversion, including residual waste from separate collection of municipal solid waste. It is able to meet existing emission limits and can have a remarkable effect on reduction of landfill disposal option.

AbstractIn Laurentian Great Lakes coastal wetlands (GLCWs), dominant emergent invasive plants are expanding their ranges and compromising the unique habitat and ecosystem service values that these ecosystems provide. Herbiciding and burning to control invasive plants have not been effective in part because neither strategy addresses the most common root cause of invasion, nutrient enrichment. Mechanical harvesting is an alternative approach that removes tissue‐bound phosphorus and nitrogen and can increase wetland plant diversity and aquatic connectivity between wetland and lacustrine systems. In this study, we used data from three years of Great Lakes‐wide wetland plant surveys, published literature, and bioenergy analyses to quantify the overall areal extent of GLCWs, the extent and biomass of the three most dominant invasive plants, the pools of nitrogen and phosphorus contained within their biomass, and the potential for harvesting this biomass to remediate nutrient runoff and produce renewable energy. Of the approximately 212,000 ha of GLCWs, three invasive plants (invasive cattail, common reed, and reed canary grass) dominated 76,825 ha (36%). The coastal wetlands of Lake Ontario exhibited the highest proportion of invasive dominance (57%) of any of the Great Lakes, primarily from cattail. A single growing season's biomass of these invasive plants across all GLCWs was estimated at 659,545 metric tons: 163,228 metric tons of reed canary grass, 270,474 metric tons of common reed, and 225,843 metric tons of invasive cattail, and estimated to contain 10,805 and 1144 metric tons of nitrogen and phosphorus, respectively. A one‐time harvest and utilization for energy of this biomass would provide the gross equivalent of 1.8 million barrels of oil if combusted, or 0.9 million barrels of oil if converted to biogas in an anaerobic digester. We discuss the potential for mitigating non‐point source nutrient pollution with invasive wetland plant removal, and other potential uses for the harvested biomass, including compost and direct application to agricultural soils. Finally, we describe the research and adaptive management program we have built around this concept, and point to current limitations to the implementation of large‐scale invasive plant harvesting.

Abstract Real-world vehicle operating mode data (2.5 million 1 Hz records), collected by instrumenting the vehicles of 82 volunteer drivers with OBD datalogger and GPS while they drove their routine travel routes, were analyzed to quantify vehicle emissions estimate errors due to road grade and driving style in rural, hilly Vermont. Data were collected in winter and summer for MY 1996 and newer passenger cars and trucks only. EPA MOVES2010b was used to estimate running exhaust emissions associated with measured vehicle activity. Changes in vehicle specific power (VSP) and MOVES operating mode (OpMode) due to proper accounting for real-world road grade indicated emission rate errors between 10% and 48%, depending on pollutant, chiefly because grade-related changes in VSP could shift activity by as many as six OpModes, depending on road type. The correct MOVES OpMode assignment was made only 33–55% of the time when road grade was not included in the VSP calculation. Driving style of individual drivers was difficult to assess due to unknown traffic operations data, but the largest differences between individual drivers were observed on rural restricted roads, where traffic conditions and control have minimal impact. The results suggest the importance of (1) measuring and incorporating real-world road grade in order to correctly assign MOVES emission rates; and (2) developing a driving style typology to account for differences in the MOVES emissions estimates due to driver variability.

Current food systems are challenged by relying on a few input-intensive, staple crops. The prioritization of yield and the loss of diversity during the recent history of domestication has created contemporary crops and cropping systems that are ecologically unsustainable, vulnerable to climate change, nutrient poor, and socially inequitable. For decades, scientists have proposed diversity as a solution to address these challenges to global food security. Here, we outline the possibilities for a new era of crop domestication, focused on broadening the palette of crop diversity, that engages and benefits the three elements of domestication: crops, ecosystems, and humans. We explore how the suite of tools and technologies at hand can be applied to renew diversity in existing crops, improve underutilized crops, and domesticate new crops to bolster genetic, agroecosystem, and food system diversity. Implementing the new era of domestication requires that researchers, funders, and policymakers boldly invest in basic and translational research. Humans need more diverse food systems in the Anthropocene—the process of domestication can help build them.

Natural ecosystems benefit human communities by providing ecosystem services such as water purification and crop pollination. Mapping ecosystem service values has become popular, but most are static snapshots of average value. Estimating instead the economic impacts of specific ecosystem changes can better inform typical resource decisions. Here we develop an approach to mapping marginal values, those resulting from the next unit of ecosystem change, across landscapes. We demonstrate the approach with a recent model of crop pollination services in Costa Rica, simulating deforestation events to predict resulting marginal changes in pollination services to coffee farms. We find that marginal losses from deforestation vary from zero to US$700/ha across the landscape. Financial risks for farmers from these losses and marginal benefits of forest restoration show similar spatial variation. Marginal values are concentrated in relatively few forest parcels not identified using average value. These parcels lack substitutes: nearby forest parcels that can supply services in the event of loss. Indeed, the marginal value of forest parcels declines exponentially with the density of surrounding forest cover. The approach we develop is applicable to any ecosystem service. Combined with information on costs, it can help target conservation or restoration efforts to optimize benefits to people and biodiversity.