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As the prospect of exceeding global temperature targets set forth in the Paris Agreement becomes more likely, methods of climate intervention are increasingly being explored. With this increased interest there is a need for an assessment process to understand the range of impacts across different scenarios against a set of performance goals in order to support policy decisions. The methodology and tools developed for Performance Assessment (PA) for nuclear waste repositories shares many similarities with the needs and requirements for a framework for climate intervention. Using PA, we outline and test an evaluation framework for climate intervention, called Performance Assessment for Climate Intervention (PACI) with a focus on Stratospheric Aerosol Injection (SAI). We define a set of key technical components for the example PACI framework which include identifying performance goals, the extent of the system, and identifying which features, events, and processes are relevant and impactful to calculating model output for the system given the performance goals. Having identified a set of performance goals, the performance of the system, including uncertainty, can then be evaluated against these goals. Using the Geoengineering Large Ensemble (GLENS) scenario, we develop a set of performance goals for monthly temperature, precipitation, drought index, soil water, solar flux, and surface runoff. The assessment assumes that targets may be framed in the context of risk-risk via a risk ratio, or the ratio of the risk of exceeding the performance goal for the SAI scenario against the risk of exceeding the performance goal for the emissions scenario. From regional responses, across multiple climate variables, it is then possible to assess which pathway carries lower risk relative to the goals. The assessment is not comprehensive but rather a demonstration of the evaluation of an SAI scenario. Future work is needed to develop a more complete assessment that would provide additional simulations to cover parametric and aleatory uncertainty and enable a deeper understanding of impacts, informed scenario selection, and allow further refinements to the approach.

In a changing world, phytoplankton communities face a large variety of challenges including altered light regimes. These alterations are caused by more pronounced stratification due to rising temperatures, enhanced eutrophication, and browning of lakes. Community responses toward these effects can emerge as alterations in physiology, biomass, biochemical composition, or diversity. In this study, we addressed the combined effects of changes in light and nutrient conditions on community responses. In particular, we investigated how light intensity and variability under two nutrient conditions influence (1) fast responses such as adjustments in photosynthesis, (2) intermediate responses such as pigment adaptation and (3) slow responses such as changes in community biomass and species composition. Therefore, we exposed communities consisting of five phytoplankton species belonging to different taxonomic groups to two constant and two variable light intensity treatments combined with two levels of phosphorus supply. The tested phytoplankton communities exhibited increased fast reactions of photosynthetic processes to light variability and light intensity. The adjustment of their light harvesting mechanisms via community pigment composition was not affected by light intensity, variability, or nutrient supply. However, pigment specific effects of light intensity, light variability, and nutrient supply on the proportion of the respective pigments were detected. Biomass was positively affected by higher light intensity and nutrient concentrations while the direction of the effect of variability was modulated by light intensity. Light variability had a negative impact on biomass at low, but a positive impact at high light intensity. The effects on community composition were species specific. Generally, the proportion of green algae was higher under high light intensity, whereas the cyanobacterium performed better under low light conditions. In addition to that, the diatom and the cryptophyte performed better with high nutrient supply while the green algae as well as the cyanobacterium performed better at low nutrient conditions. This shows that light intensity, light variability, and nutrient supply interactively affect communities. Furthermore, the responses are highly species and pigment specific, thus to clarify the effects of climate change a deeper understanding of the effects of light variability and species interactions within communities is important.

In recent decades, the risk of Wildland-Urban Interface (WUI) fires has increased due to urban growth, particularly in regions with a Mediterranean climate. The identification of the WUI is crucial for formulating fire prevention and management measures. However, there is no unified methodology for defining the WUI and it is not clear if proposals that emerge from scientific research are implemented by fire management agencies. Our objectives were to identify, describe, and compare the methods and criteria used by land and fire management agencies to define the WUI in Mediterranean-climate countries. We conducted a review of laws and fire prevention and management plans and protocols on the official websites of administrative bodies and agencies of the USA, Spain, Portugal, France, Italy, Greece, South Africa, Australia, Chile, and Argentina. Each document was read and analyzed and we conducted searches for the terminology used to name the WUI, the methodology and criteria used for defining the WUI, the fire prevention and management actions implemented in the WUI, the level of territorial organization and the responsible agencies for implementing the actions, and the presence of a methodology and a map at national scale. We found no consensus on the terminology for the WUI, the most common terms used being: wildland-urban interface, urban-rural interface, and urban-forest interface. With the exception of the USA and Portugal, there is no unified methodology at the national scale. We identified three general methods for defining the WUI: considering buffer distance for urban and vegetation areas (USA, Italy, Chile, South Africa), employing networks of strips (Spain, Portugal), and delineating risk-prone zones (Australia, France). All countries undertake fire prevention actions (e.g., fuel reduction and firebreak creation) often implemented at the municipal level. There is almost no interaction between academia and fire management agencies. Our review addresses the gap in the methods to define the WUI effectively implemented by fire management agencies. We highlight the need to implement actions aimed at enhancing the interaction between fire scientists and fire managers, which is essential for formulating and implementing effective strategies for fire prevention and optimizing resources.

This study analyzes the impact of electricity prices on the development of the agriculture sector in Qatar, using annual data from 2003 to 2019. Its findings contribute to addressing a gap in current literature and offer valuable perspectives on the sector’s obstacles and potential prospects. An extended Cobb-Douglas production function was employed as a theoretical framework, in conjunction with several econometric techniques, including Fully Modified Least Squares, Dynamic Ordinary Least Square, Canonical Cointegration Regression, and Gets, to analyze the persistent relationship between electricity prices, and the gross value added of the agriculture sector. Our research found that electricity prices exert a positive effect on agricultural development. Although the magnitude of the impact was small over the long term, it remained statistically significant. Specifically, the elasticity of the electricity prices ranged between 0.097–0.11, whereas the elasticity of another examined variable, labor productivity, was also positive and ranged between 0.67–0.74. These empirical findings support the ongoing government policy to reform energy prices, increase vegetable production using modernized hydroponic systems, and reduce groundwater use for irrigation, among other policies to sustain food production. Clearly, if these policy options are managed properly, the agriculture sector can play a significant role in diversifying the economy, maintaining environmental conditions and improving food sustainability.

Solar photovoltaic (PV) technology is being deployed at an unprecedented rate. However, utility-scale solar energy development is land intensive and its large-scale installation can have negative impacts on the environment. In particular, solar energy infrastructure can require extensive landscape modification that transforms soil ecological functions, thereby impacting hydrologic, vegetative, and carbon dynamics. However, reintroducing native vegetation to solar PV sites may be a means of restoring their soils. To this end, we investigated critical soil physical and chemical parameters at a revegetated photovoltaic array and an adjacent reference grassland in Colorado, United States. Seven years after revegetation, we found that carbon and nitrogen remained lower in the PV soil than in the reference soil and contained a greater fraction of coarse particles. We also found that the PV modules introduced heterogeneity in the soil moisture distribution, with precipitation accumulating along the lower edges of panels. The redistribution of soil moisture by panel arrays could potentially be used in concert with planting strategies to maximize plant growth or minimize soil erosion, and should be considered when evaluating the potential to co-locate vegetation with solar infrastructure.

Methane (CH4) is a potent greenhouse gas with an important contribution to global warming. While national and international efforts have been put in place to reduce methane emissions, little is known about its variability, especially in hotspot regions where natural and anthropogenic emissions are compounded. In this study, the current state of CH4 concentrations and their trends over the United Arab Emirates (UAE) and surrounding region are investigated with satellite and reanalysis data. CH4 concentrations have increased over the last 5 years, with a trend in the satellite-derived column values (XCH4) of about 9 ppb/year. A clear annual cycle is detected in XCH4, with an amplitude of up to 75 ppb and peak values in the warmer months. The largest concentrations are found in coastal sites, where sabkhas and landfills are present, and along the Al Hajar mountains, where agricultural activities and microhabitats that may host CH4-producing microbes occur and where advection by the background flow is likely an important contributor. The reanalysis data shows a good agreement with the satellite-derived estimates in terms of the spatial pattern, but the magnitudes are smaller by up to 50 ppb, due to deficiencies in the data assimilated. Surface CH4 concentrations in the reanalysis data account for more than 50% of the corresponding XCH4 values, and exhibit a seasonal cycle with the opposite phase due to uncertainties in the emissions inventory. Our findings provide an overview of the state of CH4 concentration in the UAE and surrounding region, and may aid local authorities to propose the appropriate emission reduction strategies in order to meet the proposed net-zero greenhouse gas emission target by 2050. This study highlights the need for the establishment in the Arabian Peninsula region of a ground-based observational network for greenhouse gas concentrations which is still lacking to date.