Land surface evapotranspiration (ET) is an important component of the surface energy budget and water cycle. To solve the problem of the spatial-scale mismatch between in situ observations and remotely sensed ET, it is necessary to find the most appropriate upscaling approach for acquiring ground truth ET data at the satellite pixel scale. Based on a data set from two flux observation matrices in the middle stream and downstream of the Heihe River Basin, six upscaling methods were intercompared via direct validation and cross validation. The results showed that the area-weighted method performed better than the other five upscaling methods introducing auxiliary variables (the integrated Priestley-Taylor equation, weighted area-to-area regression kriging [WATARK], artificial neural network, random forest [RF], and deep belief network methods) over homogeneous underlying surfaces. Over moderately heterogeneous underlying surfaces, the WATARK method performed better. However, the RF method performed better over highly heterogeneous underlying surfaces. A combined method (using the area-weighted and WATARK methods for homogeneous and moderately heterogeneous underlying surfaces, respectively, and using the RF method for highly heterogeneous underlying surfaces) was proposed to acquire the daily ground truth ET data at the satellite pixel scale, and the errors in the ground truth ET data were evaluated. The Dual Temperature Difference (DTD) and ETMonitor were validated using ground truth ET data, which solve the problem of the spatial-scale mismatch and quantify uncertainties in the validation process.

In this study, we investigate how dyadic air and rail transport connectivity affects domestic tourist flows among 343 Chinese cities. Using geo-tagged Sina Weibo data to track tourists during China’s National Day Golden Week in 2014, we estimate several gravity models with a negative binomial distribution. The estimation results suggest that air transport connectivity generally has a greater influence than rail transport on dyadic tourist flows, while connectivity provided by ordinary trains (compared to other rail types) is most important in the context of rail transport. Also, we find the effects of transport connectivity and intermodal transport competition to depend on the origin-to-destination distance. Different types of railway trains appear to have distinct effective distance ranges: the effect of high-speed rail trains is strongest at travel distances between 1,800 and 2,000 km, whereas bullet trains’ effect is strongest at distances between 400 and 600 km.

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Well water for drinking with increased levels of iron in arsenic-polluted areas has been reported worldwide. Oral exposure to arsenic has been shown to be associated with hearing loss, while there is no evidence for an association between excessive exposure to iron and hearing loss in humans. In this study, we determined iron and arsenic levels in biological samples and hearing levels by pure tone audiometry (PTA) in subjects in a control area and an arsenic-polluted area in Bangladesh. The iron level in well water in the arsenic-polluted area was significantly higher than that in piped supply water in the control area. Subjects in the polluted area (n = 109), who had higher iron and arsenic levels in hair and toenails than those in subjects in the control area (n = 36), had an increased risk of hearing loss at 8 kHz and 12 kHz after adjustments for age, gender, smoking and BMI. Significant associations of the exposure group with hearing loss at 8 kHz and 12 kHz remained after further adjustment for arsenic levels in toenails and hair. Thus, this pilot study showed that excessive exposure to iron via drinking water is a potential risk for hearing loss in humans.

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