Cognitive performance is essential to foster learning. High CO2 concentrations are common in classrooms and can lead to reduced cognitive performance. Negative air ions (NAIs) can improve cognitive performance. This study explored the effects of indoor NAIs on the cognitive performance and health of college students exposed to a high pure CO2 environment. Forty college students were exposed to four sets of conditions (NAIs+500 ppm CO2, 500 ppm CO2, NAIs+2500 ppm CO2, and 2500 ppm CO2). Participants’ cognitive performance, including reasoning, short-term memory, concentration, and verbal ability, was assessed under each condition using the Cambridge Brain Sciences tool. Acute health symptoms were investigated using a subjective questionnaire, and simultaneously, participants’ blood pressure, heart rate, and lung function were tested. Analysis of variance (ANOVA) in a repeated-measures design was used to analyze the effects of different conditions on cognitive performance and health symptoms. The results revealed that the different levels of CO2 and NAIs had a significant effect on cognitive performance after one hour of exposure and had no significant effect after three hours of exposure. Compared with 500 ppm CO2, 500 ppm CO2+NAIs resulted in better reasoning skills, short-term memory, and verbal skills, and 2500 ppm CO2 led to poorer reasoning skills. The addition of NAIs to 2500 ppm CO2 improved reasoning skills, short-term memory, and verbal skills. The benefits of adding NAIs to high pure CO2 condition on cognitive performance are more noticeable than those to low CO2 condition. Moreover, adding NAIs can reduce nasal irritation or dryness, skin irritation or dryness, sleepiness symptoms, and heart rate elevation caused by pure CO2. However, the benefits of NAIs on health symptoms and physiology were not observed under the 500 ppm CO2 condition. Adding NAIs to a high pure CO2 level is an effective means to improve the cognitive performance and health of college students.
In response to China’s “double carbon” policy, cold, rural areas of the nation are currently upgrading their heating methods. Since rural areas are more dispersed than urban areas, centralized heating is not easy to use. Therefore, electric heating has become one of the major solutions. However, few studies have investigated the performance, suitability, and user impressions of electric heating in rural areas in China. Here, therefore, we used a literature review, questionnaires, and expert consultations to determine the relevant indicators that best reflect the suitability of electric heating usage in cold rural areas in northern China. Then, by using both expert questionnaires and the analytic hierarchy process (AHP) to determine the weights of these indicators, we developed a hybrid model established based on the gray whitening weight clustering method. We then applied this model to two case studies in different provinces, namely 20 households from a village in northern China where electric heating was being uses. Our major findings were 1) the primary indicators were technology, economy, comfort, safety, aesthetic portability, and environmental protection; 2) the weights of these indicators were 16.17%, 31.58%, 23.37%, 18.46%, 5.16%, and 5.25%, respectively, with all indicators passing the consistency test; 3) results of two case studies were consistent with the villagers' actual subjective evaluation results; 4) evaluation software has been developed. Our evaluation method developed can effectively reflect the actual needs of people living in rural areas of China. The government can use evaluation software to get the feasibility of adopting electric heating in villages to achieve reasonable low-carbon promotion in rural areas.
Responding to the national “double carbon” policy, rural areas in China are upgrading their heating methods. Since rural areas are more dispersed than urban areas, centralized heating is not easy to use. Therefore, electric heating has become one of the major solutions. However, relevant studies on electric heating usage in rural areas are limited. In this study, therefore, research methods including literature review, questionnaire, and expert consultation have been adopted, to decide relevant indicators reflecting the suitability of using electric heating in cold rural areas in China. Then, both expert questionnaire and analytic hierarchy process were used to decide the weight of these indicators, with a hybrid model established based on the gray whitening weight clustering method. Finally, a case village was selected to validate the performance of the model, with 20 households involved. The main results from this study include: 1) the primary indicators were technology, economy, comfort, safety, aesthetic portability, and environmental protection; 2) the weights of these indicators were 0.1617, 0.3158, 0.2337, 0.1846, 0.0516, and 0.0525; 3) the evaluation result for the case village was ‘suitable’, which was consistent with the villagers' actual subjective evaluation results. The evaluation method developed in this study can effectively reflect the actual needs of people living in cold rural areas of China and can help to achieve low-carbon heating in rural areas.
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