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Some indicators used to track the progress of the Sustainable Development Goals (SDGs) suffer from a lack of reported data, and therefore need estimates to fill the data gaps. Using crop model outputs and global cropping system datasets, we present a modeling of small-scale farmer productivity and agricultural output (conceptually similar to the formal SDG 2.3.1 and 2.3.2 indicator, respectively). We analyze the responses of the indicators for 106 low- and middle-income countries for the periods 2051–2060 and 2091–2100, relative to 2001–2010, to various scenarios of climate, socioeconomic development, cost-free adaptation, and irrigation expansion. The results show the potentials of modeling in gap-filling of reported national data, and that the agricultural output indicator indicates the positive effect of climate mitigation to small-scale farmers. The contributions of adaptation are evident when agricultural output indicator is used but are no longer visible, or even wrongly interpreted, when productivity indicator is used, underling the importance of selecting robust indicators to track SDG goals in a changing climate. Also discussed are the caveats identified in the SDG 2.3 indicators that enable the design of indicators more aligned with the other development goals, such as poverty eradication.

A unique GHG emission decline target was released by the Chinese government to facilitate the decrease in GHG emission per unit of GDP in China. In other words, an increase in GHG is permitted under a GDP reflecting a better quality environment quality. Therefore, technology promotion and policy evolution are necessary to realize this within a limited period. This research considered a GHG emission tax and subsidy policy to achieve environmental targets via environment friendly vehicle introduction and clean energy promotion. An optimization simulation model based on extended input-output model was explored to compare with four policy scenarios. The simulation result shows that hybrid vehicle and electric vehicle introduction are powerless to meet environment targets unless more attention is paid to solar power and wind power along with thermal power. This research proposed an optimal GHG emission tax rate and subsidy rate for policy makers in China to reach their environment goal.

In the early 2000s, Japan instituted the Great Heisei Consolidation, a national strategy to promote large-scale municipal mergers. This study analyzes the impact that this strategy could have on watershed management. We select the Lake Kasumigaura Basin, the second largest lake in Japan, for the case study and construct a dynamic expanded input–output model to simulate the ecological system around the Lake, the socio-environmental changes over the period, and their mutual dependency for the period 2012–2020. In the model, we regulate and control the following water pollutants: total nitrogen, total phosphorus, and chemical oxygen demand. The results show that a trade-off between economic activity and the environment can be avoided within a specific range of pollution reduction, given that the prefectural government implements optimal water environment policies, assuming that other factors constraining economic growth exist. Additionally, municipal mergers are found to significantly reduce the budget required to improve the water environment, but merger budget efficiency varies nonlinearly with the reduction rate. Furthermore, despite the increase in financial efficiency from the merger, the efficiency of installing domestic wastewater treatment systems decreases drastically beyond a certain pollution reduction level and eventually reaches a limit. Further reductions require direct regulatory instruments in addition to economic policies, along with limiting the output of each industry. Most studies on municipal mergers apply a political, administrative, or financial perspective; few evaluate the quantitative impact of municipal mergers on the environment and environmental policy implications. This study addresses these gaps.