Application of machine learning to assess people' s perception of household energy in the developing world: A case of Nepal

Research on social aspects of energy and those applying machine learning(ML)is limited compared to the‘hard’disciplines such as science and engineering.We aim to contribute to this niche through this multidisciplinary study integrating energy,social science and ML.Specifically,we aim:(i)to compare the applicability of different ML models in household(HH)energy;and(ii)to explain people’s perception of HH energy using the most appropriate model.We carried out cross-sectional survey of 323 HHs in a developing country(Nepal)and extracted 14 predictor variables and one response variable.We tested the performance of seven ML models:K-Nearest Neighbors(KNN),Multi-Layer Perceptron(MLP),Extra Trees Classifier(ETC),Random Forest(RF),Ridge Classifier(RC),Multinomial Regression–Logit(MR-L)and Probit(MR-P)in classifying people’s responses.The models were evaluated against six metrics(confusion matrix,precision,f1 score,recall,balanced accuracy and overall accuracy).In this study,ETC outperformed all other models demonstrating a balanced accuracy of 0.79,0.95 and 0.68 respectively for the Agree,Neutral and Disagree response categories.Results showed that,compared to conventional statistical models,data driven ML models are better in classifying people’s perceptions.It was seen that the majority of the surveyed people from rural(68%)and semi-urban areas(67%)tend to resist energy changes due to economic constraints and lack of awareness.Interestingly,most(73%)of the urban residents are open to changes,but still resort to fuel-stacking because of distrust in the state.These grass-root level responses have strong policy implications.

The impact of income on household CO_2 emissions in China based on a large sample survey

Since reform and opening-up, China's energy consumption has been soaring largely due to the country's rapid economic development and urbanization [1]. As a result, C02 emissions from the household sector have been rapidly increasing [2]. China—now the second largest global economy and the largest C02 emitter [3]—has been making efforts to aggressively reduce C02 emissions and protect the environment. In line with the Paris Climate Change Agreement, China submitted its Nationally Determined Contribution (NDC) and pledged to achieve peak C02 emissions by 2030.

Poplar Plantation as an Agroforestry Approach:Economic Benefits and Its Role in Carbon Sequestration in North India

Poplar has gained popularity among farmers of Punjab,Haryana,Western Uttar Pradesh,and the foothills of Uttarakhand and Himachal Pradesh due to their fast growth rate and suitability for industrial uses such as pulp and timber production.Integrating poplar trees into agroforestry systems optimizes land resources and economic gains,as successful techniques have been developed to coordinate crop timing and arrangements effectively.Integrating poplar trees with agricultural crops provides additional income streams for farmers and contributes to soil conservation,biodiversity enhancement,and other environmental benefits.Farmers in these regions typically employ effective spacing of 5 m×4 m for block plantation and 1 m×3 m for row plantation.In the present study,a systematic literature review encompassing 137 English-language journal articles was conducted to assess the economic benefits of Poplar using discounted cash flow(DCF)analysis,considering short-rotation poplar(SRC)and very short-rotation poplar(vSRC)plantations alongside annual crops.The findings revealed that increasing canopy density led to a decline in crop yields by 37%,70%,and 99% at canopy densities of 30%,60%,and 90%,respectively,from early spring to harvest.Cost-benefit analysis in Saharanpur district,India,indicated average annual net returns of USD 346.36 for Poplar-based agrisilviculture,while monoculture yielded USD 140.73 per annum.Furthermore,economic analysis in Yamunanagar and Haridwar districts showed benefit-cost ratios ranging from 2.35 to 3.7.Additionally,Poplar block and boundary plantations were found to sequester significantly more carbon in long-lived biomass,serving as substitutes for fossil fuels(5.45 and 1.84 t ha-1 yr-1)in poplar-based systems with block and boundary plantations.The study suggested expanding spacing between tree rows may mitigate resource competition between plantations and crops.The study inferred that Poplar-based agroforestry may play a crucial role in climate mitigation programs by effectively sequestering atmospheric carbon and offering fuel,fodder,timber,and wood products,thereby alleviating pressure on existing natural forests.