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The use of fossil fuels has been a major contributor to global climate change. To mitigate the negative impact of fossil fuels, renewable energy (RE) has been increasingly promoted. This study aims to investigate factors impacting the adoption of RE in the residential sector, using the U.S. as a case study. Residential RE consumption rate data in 51 states/districts of the U.S. were collected from 2010 to 2018 to examine the adoption of RE. Correspondingly, four categories of explanatory variables affecting the consumption rate were investigated, including demographics, availability, consumers' affordability, and regulatory compliance motivation. An optimal parameters-based geographical detector (OPGD) model was implemented to investigate spatio-temporal impacts of variables on the consumption rate. Results show that factors that have consistently significant impacts on residential RE adoption include percentage of RE production of the availability category and residential monthly electricity bill of the consumers' affordability category. Population was also an important factor from 2012 to 2018. The impact of RE production rate can also be further enhanced when combined with other factors, such as residential monthly bill and number of regulatory policies. Based on these results, several practical recommendations are proposed as references for government to increase RE adoption. [ABSTRACT FROM AUTHOR]

Climatic impact on re-established ecosystems at reclaimed mined lands may have changed. However, little knowledge is available about the difference in vegetation–climate relationships between reclaimed and unmined lands. In this study, ecological responses to climatic variability on reclaimed and neighbouring unmined lands were estimated using remote-sensing data at the Pingshuo Mega coal mine, one of the largest coal mines with long-term reclamation history in China. Time-series MODIS enhanced vegetation index (EVI) data and meteorological data from 1997 to 2017 were collected. Results show significantly different vegetation–climate relationships between reclaimed and unmined lands. First, the accumulation periods of all climatic variables were much longer on reclaimed mining lands. Second, vegetation on reclaimed lands responded to variabilities in temperature, rainfall, air humidity, and wind speed, while undisturbed vegetation only responded to variabilities of temperature and air humidity. Third, climatic variability made a much higher contribution to EVI variation on reclaimed land (20.0–46.5%) than on unmined land (0.7–1.7%). These differences were primarily caused by limited ecosystem resilience, and changed site hydrology and microclimate on reclaimed land. Thus, this study demonstrates that the legacy effects of surface mining can critically change on-site vegetation–climate relationships, which impacts the structure, functions, and stability of reclaimed ecosystems. Vegetation–climate relationships of reclaimed ecosystems deserve further research, and remote-sensing vegetation data are an effective source for relevant studies. [ABSTRACT FROM AUTHOR]

• The carbon and water cycles of frozen soil ecosystems on the Qinghai-Tibet Plateau were analyzed. • Water use efficiency and gross primary productivity decreased progressively with stronger freezing of the frozen soil. • Evapotranspiration increased and then decreased with increasing freezing gradient. • Vegetation dominated the change in water-carbon coupling over the largest area in each permafrost type except predominantly continuous and island permafrost. The carbon and water cycle patterns of frozen soil ecosystems in regions, such as the Qinghai-Tibet Plateau (QTP), which have fragile and sensitive ecologies, are possibly affected by climate change. However, these patterns along the gradients of varying degrees of freezing remain poorly understood. In this study, we examine the spatio-temporal patterns of water use efficiency (WUE), gross primary productivity (GPP), and evapotranspiration (ET) in six frozen soil zones of the Qinghai-Tibet Plateau (QTP) with varying degrees of frozen soil. The analysis is based on the frozen soil classification criteria and remote sensing data from 2001 to 2020. The influences of six climatic, nine edaphic, and two botanic parameters on these patterns is also investigated. The results indicate that 48.05%, 24.07%, and 20% of the regions in QTP exhibit significantly upward trends of GPP, ET, and WUE, respectively. The highest increase trends were observed in GPP in the middle-thick seasonally frozen ground zone (2.36 g C m−2 yr−1), ET in the mountain permafrost zone (2.35 mm yr−1), and WUE in the predominantly continuous permafrost zone (0.003 g C kg−1 H 2 O yr−1). Meanwhile, GPP and WUE decrease progressively with the increase of freezing degrees, from the short-time frozen ground zone (GPP: 604.99 ± 51.99 g C m−2; WUE: 2.34 ± 0.15 g C kg−1 H 2 O) to the predominantly continuous permafrost zone (GPP: 114.07 ± 11.77 g C m−2; WUE: 0.33 ± 0.04 g C kg−1 H 2 O), while ET does not show significant differences across the three permafrost zones. The enhanced vegetation index is the primary factor affecting GPP and WUE in most frozen soil zones, whereas climate variables mainly impact ET. Our findings emphasize the importance of considering the effects of different freezing degrees of frozen soil when analyzing the response of the carbon and water cycles in the QTP in the context of climate change. [ABSTRACT FROM AUTHOR]

High-quality and long time-series soil moisture (SM) data are increasingly required for the Qinghai-Tibet Plateau (QTP) to more accurately and effectively assess climate change. In this study, to evaluate the accuracy and effectiveness of SM data, five passive microwave remotely sensed SM products are collected over the QTP, including those from the soil moisture active passive (SMAP), soil moisture and ocean salinity INRA-CESBIO (SMOS-IC), Fengyun-3B microwave radiation image (FY3B), and two SM products derived from the advanced microwave scanning radiometer 2 (AMSR2). The two AMSR2 products are generated by the land parameter retrieval model (LPRM) and the Japan Aerospace Exploration Agency (JAXA) algorithm, respectively. The SM products are evaluated through a two-stage data comparison method. The first stage is direct validation at the grid scale. Five SM products are compared with corresponding in situ measurements at five in situ networks, including Heihe, Naqu, Pali, Maqu, and Ngari. Another stage is indirect validation at the regional scale, where the uncertainties of the data are quantified by using a three-cornered hat (TCH) method. The results at the regional scale indicate that soil moisture is underestimated by JAXA and overestimated by LPRM, some noise is contained in temporal variations in SMOS-IC, and FY3B has relatively low absolute accuracy. The uncertainty of SMAP is the lowest among the five products over the entire QTP. In the SM map composed by five SM products with the lowest pixel-level uncertainty, 66.64% of the area is covered by SMAP (JAXA: 19.39%, FY3B: 10.83%, LPRM: 2.11%, and SMOS-IC: 1.03%). This study reveals some of the reasons for the different performances of these five SM products, mainly from the perspective of the parameterization schemes of their corresponding retrieval algorithms. Specifically, the parameterization configurations and corresponding input datasets, including the land-surface temperature, the vegetation optical depth, and the soil dielectric mixing model are analyzed and discussed. This study provides quantitative evidence to better understand the uncertainties of SM products and explain errors that originate from the retrieval algorithms. [ABSTRACT FROM AUTHOR]