Regional Analysis

Abstract: Agricultural decision-making by different interest groups (e.g., farmers, development agents and policymakers) usually takes place on different scales (e.g., plot, landscape and country). Currently, tools to assist decision-making
are either dedicated to small-scale management guidance or large-scale assessment, which ignore the cross-scale linkages and interactions and thus may not provide robust and consistent guidance and assessment. 

Here, we developed an advanced agricultural modeling framework by integrating the strengths of conventional crop models in representing crop growth processes and management practices into a terrestrial biosphere model
(TBM), the Dynamic Land Ecosystem Model (DLEM), to meet the cross-scale application needs (e.g., adaptation and mitigation). Specifically, dynamic crop growth processes, including crop-specific phenological development,
carbon allocation, yield formation, biological nitrogen fixation processes, and management practices such as tillage, cover cropping and genetic improvements, were explicitly represented in DLEM.

The new model was evaluated against site-scale observations, and the results showed that the model performed generally well, with an average normalized root mean square error of 19.91% for leaf area index and 17.46% for aboveground biomass
at the seasonal scale and 14.42% for annual yield. Then the model was applied to simulate corn, soybean, and winter wheat productions in the conterminous United States from 1960 to 2018. The spatial patterns of simulated crop productions were consistent with ground survey data. Our model also captured both the long-term trends and interannual variations of the total national productions of the three crops.

This study demonstrates the significance of fusing conventional crop modeling techniques into TBMs to establish a unified modeling framework, which holds the potential to address climate impacts, adaptation and mitigation across varied spatiotemporal scales.

Highlights:

• A unified agricultural modeling framework is implemented in DLEM v4.0. 

• Simulated results agree well with site-scale LAI, biomass and yield measurements.

• Regional simulations can well reproduce spatial-temporal patterns of crop production.
 
• DLEM v4.0 can be used to support agricultural climate adaptation and mitigation.

Abstract: Central banks play a critical role in the economy, with policy levers that influence and are influenced by climate change. An important part of central bank interventions is conducting climate-related stress tests and scenario analysis to increase awareness in the financial sector of the effects of climate change, improve the integration of climate-related risks into financial companies’ decisions, identify important data gaps, and start building capacity to develop more advanced and accurate climate scenarios. These exercises, however, are a challenge to central banks and financial companies because of their complexity and the new data and tools required for scenario development and analysis.

The development of scenarios for climate-related stress testing requires the integration of different model frameworks to assess the impacts of climate change, translate these impacts into macroeconomic scenarios, and evaluate the subsequent financial sector outcomes. This integration requires multidisciplinary skills such as the joint work of energy system modelers, climate scientists and macroprudential experts.

This paper provides an overview of the modelling frameworks available for assessing climate change impacts in South Africa, covering both local and global models. This should assist financial institutions and regulators with developing partnerships to build scenarios and assess the impact of climate-related risks. Gaps in current models and modelling for financial stress testing are also identified as considerations for future research.

Abstract: In their recent paper in ERL, 'Egypt's water budget deficit and suggested mitigation policies for the Grand Ethiopian Renaissance Dam (GERD) filling scenarios,' Heggy et al (2021 Environ. Res. Lett. 16 074022) paint an alarming picture of the water deficits and economic impacts for Egypt that will occur as a consequence of the filling of the GERD. Their median estimate is that filling the GERD will result in a water deficit in Egypt of ∼31 billion m3 yr−1. They estimate that under a rapid filling of the GERD over 3 yr, the Egyptian economy would lose US$51 billion and 4.74 million jobs, such that in 2024, Gross Domestic Product (GDP) per capita would be 6% lower than under a counterfactual without the GERD.

These and other numbers in Heggy et al (2021 Environ. Res. Lett. 16 074022) article are inconsistent with the best scientific and economic knowledge of the Nile Basin and are not a dependable source of information for policy-makers or the general public. In this response to Heggy et al (2021 Environ. Res. Lett. 16 074022) we draw on high quality peer-reviewed literature and appropriate modeling methods to identify and analyze many flaws in their article, which include (a) not accounting for the current storage level in the High Aswan Dam reservoir (b) inappropriately using a mass-balance approach that does not account for the Nile's hydrology or how water is managed in Egypt, Sudan and Ethiopia; (c) extreme and unfounded assumptions of reservoir seepage losses from the GERD; and (d) calculations of the economic implications for Egypt during the period of reservoir filling which are based on unfounded assumptions.

In contrast to Heggy et al (2021 Environ. Res. Lett. 16 074022), robust scientific analysis has demonstrated that, whilst there is a risk of water shortages in Egypt if a severe drought were to occur at the same time as the GERD reservoir is filling, there is minimal risk of additional water shortages in Egypt during the filling period if flows in the Blue Nile are normal or above average. Moreover, the residual risks could be mitigated by effective and collaborative water management, should a drought occur.

Authors' Summary: Perfluorocarbons (PFCs) are potent greenhouse gases with exceedingly long lifetimes. We used atmospheric measurements from a global monitoring network to track the accumulation of these gases in the atmosphere. In the case of the two most abundant PFCs, recent measurements indicate that global emissions are increasing. In Europe, we used a model to estimate regional PFC emissions. Our results show that there was no significant decline in northwest European PFC emissions between 2010 and 2019.

Abstract: We assess the contribution of India’s hard-to-abate sectors to the country’s current emissions and their likely future trajectory of development under different policy regimes. We employ an enhanced version of the MIT Economic Projection and Policy Analysis (EPPA) model to explicitly represent the following hard-to-abate sectors: iron and steel, non-ferrous metals (copper, aluminum, zinc, etc.), non-metallic minerals (cement, plaster, lime, etc.), and chemicals.

We find that, without additional policies, the Paris Agreement pledges made by India for the year 2030 still can lead to an increasing use of fossil fuels and corresponding greenhouse gas (GHG) emissions, with projected CO2 emissions from hard-to-abate sectors growing by about 2.6 times from 2020 to 2050. Scenarios with electrification, natural gas support, or increased resource efficiency lead to a decrease in emissions from these sectors by 15-20% in 2050, but without carbon pricing (or disruptive technology changes) emissions are not reduced relative to their current levels due to growth in output. Carbon pricing that makes carbon capture and storage (CCS) economically competitive is critical for achieving substantial emission reductions in hard-to-abate sectors, enabling emission reductions of 80% by 2050 relative the scenario without additional policies.

Without substantial government support, decarbonization of India’s hard-to-abate sectors will not be achievable.

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