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AbstractEnergy poverty, especially in rural areas, has become a central focus of scholarly and policy discussions. However, there is a significant gap in understanding the impact of religious beliefs on this phenomenon. This paper aims to fill this gap by utilizing household survey data from the China Labor-force Dynamics Survey (CLDS) spanning three waves (2012, 2014, and 2016) to examine the causal link between religious beliefs and energy poverty, covering clean energy accessibility and affordability among rural residents. Our analysis unveils a substantial positive influence of religious beliefs on the likelihood of experiencing energy poverty, especially concerning accessibility and affordability. This effect is notably pronounced among males, ethnic minorities, and low-income groups. Low income and education are recognized as pivotal mediating factors through which religious beliefs contribute to energy poverty. The findings of this study offer valuable insights for formulating strategies to mitigate energy poverty in rural China, with a particular emphasis on the role of religious beliefs.

The number of recent publications on food loss and waste, and policy initiatives of governments and international organizations indicate the high priority of this topic. With this in mind, the methodology to measure food loss and waste has important implications for policy recommendations. The authors of this IAMO Policy Brief state that the many individual studies use different methodologies to quantify the size of waste with respect to metric measures and value for individual products and for the aggregate of food loss and waste. Most studies do not consider the costs incurred by reducing or redirecting food loss and waste. A recent publication has taken up the methodological problem (Bellamare et al.,2017). The authors of this IAMO Policy Brief investigate whether the proposed methodology solves the problem and can contribute to designing a rational policy to manage food loss and waste.

The number of recent publications on food loss and waste, and policy initiatives of governments and international organizations indicate the high priority of this topic. With this in mind, the methodology to measure food loss and waste has important implications for policy recommendations. The authors of this IAMO Policy Brief state that the many individual studies use different methodologies to quantify the size of waste with respect to metric measures and value for individual products and for the aggregate of food loss and waste. Most studies do not consider the costs incurred by reducing or redirecting food loss and waste. A recent publication has taken up the methodological problem (Bellamare et al.,2017). The authors of this IAMO Policy Brief investigate whether the proposed methodology solves the problem and can contribute to designing a rational policy to manage food loss and waste.

Changes in land management and climate alter vegetation dynamics, but the determinants of vegetation changes often remain elusive, especially in global drylands. Here we assess the determinants of grassland greenness on the Mongolian Plateau, one of the world's largest grassland biomes, which covers Mongolia and the province of Inner Mongolia in China. We use spatial panel regressions to quantify the impact of precipitation, temperature, radiation, and the intensity of livestock grazing on the normalized difference vegetation indices (NDVI) during the growing seasons from 1982 to 2015 at the county level. The results suggest that the Mongolian Plateau experienced vegetation greening from 1982 to 2015. Precipitation and animal density were the most influential factors contributing to higher NDVI on the grasslands of Inner Mongolia and Mongolia. Our results highlight the dominant effect of climate variability, and especially of the precipitation variability, on the grassland greenness in Mongolian drylands. The findings challenge the common belief that higher grazing pressure is the key driver for land degradation. The analysis exemplifies how representative wall‐to‐wall results for large areas can be attained from exploring space–time data and adds empirical insights to the puzzling relationship between grazing intensity and vegetation growth in dryland areas. ; European Union's Framework Programme for Research and Innovation ‐ Horizon 2020 (2014‐2020) ; Alexander von Humboldt Foundation of Germany ; Peer Reviewed