Despite achieving remarkable development, China’s agricultural economy has been under severe environmental pressure. Based on previous studies, the present study further considers the sources of agricultural carbon emissions in depth, estimates China’s agricultural carbon emissions from 1997 to 2016, and analyzes the agricultural pollution faced by China and its provinces. The study estimates the amount and intensity of agricultural carbon emissions in China from five carbon sources—agricultural materials, rice planting, soil N₂O, livestock and poultry farming, and straw burning—and analyzes their spatial and temporal characteristics. The following results were obtained: (1) between 1997 and 2016, the amount of agricultural carbon emissions in China generally increased, while the intensity of agricultural carbon emissions decreased; (2) in the same period, the amount of carbon emissions from each category of carbon source generally increased, with the exception of rice planting; however, the amount of emissions fluctuated; (3) the amount and intensity of carbon emissions varied greatly among provinces; (4) the emissions from different categories of carbon source showed different concentration trends and agglomeration forms; (5) China’s agricultural carbon emissions showed obvious spatial correlation, which overall was high–high agglomeration; however, its carbon emissions gradually weakened, and the spatial agglomeration of agricultural carbon emissions in each province changed between 1997 and 2016.

Environmental costs should be taken into account when measuring the achievements of China’s agricultural development, since the long-term extensive development of agriculture has caused huge environmental pollution. This study took agricultural carbon emissions as an undesired output to estimate the agricultural development efficiency in 31 provinces of China from 1998 to 2016, based on the green total factor productivity, as assessed by the slacks-based measure directional distance function and constructing the global Malmquist–Luenberger index. We measured agricultural carbon emissions in terms of five aspects: agricultural materials, rice planting, soil, livestock and poultry farming, and straw burning, and then compared the green total factor productivity index and the total factor productivity index. The study came to the following conclusions: (1) the green technology efficiency change was smaller than the technology efficiency change at first, but the gap between them is narrowing with time, such that the former is now larger than the latter; (2) the green technology efficiency was in a declining state and the green technology progress was increasing, promoting the green total factor productivity growth, from 1998 to 2016; and (3) China’s agricultural green total factor productivity increased by 4.2% annually in the east, 3.4% annually in the central region, and 2.5% annually in the west.

Background: The growing demand for LTC (Long-term care) services for disabled elderly has become a daunting task for countries worldwide, especially China, where population aging is particularly severe. According to CSY (China Statistical Yearbook,2019), the elderly aged 65 or above has reached 167 million in 2018, and the number of disabled elderly is as high as 54%. Germany and other countries have alleviated the crisis by promoting the public LTCI (Long-Term Care Insurance) system since the 1990s, while China’s public LTCI system formal pilot only started in 2016. Therefore, the development of the public LTCI system has gradually become a hot topic for scholars in various countries, including China. Methods: This review has been systematically sorted the existing related literature to discuss the development of public LTCI (Long-Term Care Insurance)system form four aspects, namely, the comparison of public LTCI systems in different countries, the influence of public LTCI, challenge of public LTCI, and the relationship between public LTCI and private LTCI. We searched some databases including Web of Science Core Collection, Medline, SCOPUS, EBSCO, EMBASE, ProQuest and PubMed from January 2008 to September 2020. The quality of 38 quantitative and 21 qualitative articles was evaluated using the CASP(Critical Appraisal Skills Programme) critical evaluation checklist. Results: The review systematically examines the development of public LTCI system from four aspects, namely, the comparison of public LTCI systems in different countries, the influence of public LTCI, the challenge of public LTCI, and the relationship between public LTCI and private LTCI. For example, LTCI has a positive effect on the health and life quality of the disabled elderly. However, the role of LTCI in alleviating the financial burden on families with the disabled elderly may be limited. Conclusion: Some policy implications on the future development of China’s LTCI system can be obtained. For example, the government should fully consider the constraints such as price rise, the elderly disability rate, and the substantial economic burden. It also can strengthen the effective combination of public LTCI and private LTCI. It does not only help to expand the space for its theoretical research but also to learn the experiences in the practice of the LTCI system in various countries around the world. It will significantly help the smooth development and further promote the in-depth reform of the LTCI system in China.

The aging population in China highlights the significance of elderly long-term care (LTC) services. The number of people aged 65 and above increased from 96 million in 2003 to 150 million in 2016, some of whom were disabled due to chronic diseases or the natural effects of aging on bodily functions. Therefore, the measurement of future LTC costs is of crucial value. Following the basic framework but using different empirical methods from those presented in previous literature, this paper attempts to use the Bayesian quantile regression (BQR) method, which has many advantages over traditional linear regression. Another innovation consists of setting and measuring the high, middle, and low levels of LTC cost prediction for each disability state among the elderly in 2020–2050. Our projections suggest that by 2020, LTC costs will increase to median values of 39.46, 8.98, and 20.25 billion dollars for mild, moderate, and severe disabilities, respectively; these numbers will reach 141.7, 32.28, and 72.78 billion dollars by 2050. The median level of daily life care for mild, moderate, and severe disabilities will increase to 26.23, 6.36, and 27 billion dollars. Our results showed that future LTC cost increases will be enormous, and therefore, the establishment of a reasonable individual-social-government payment mechanism is necessary for the LTC system. The future design of an LTCI system must take into account a variety of factors, including the future elderly population, different care conditions, the financial burden of the government, etc., in order to maintain the sustainable development of the LTC system.

Industrial development has brought about not only rapid economic growth, but also serious environmental pollution in China, which has led to serious health problems and heavy economic burdens on healthcare. Therefore, the relationship between the industrial air pollution and health care expenditure (HCE) has attracted the attention of researchers, most of which used the traditional empirical methods, such as ordinary least squares (OLS), logistic and so on. By collecting the panel data of 30 provinces of China during 2005–2016, this paper attempts to use the Bayesian quantile regression (BQR) to reveal the impact of industrial air pollution represented by industrial waste gas emission (IWGE) on HCE in high-, middle-, low-income regions. It was found that double heterogeneity in the influence of IWGE on HCE was obvious, which revealed that people in high-, middle-, low-income regions have significantly different understandings of environmental pollution and health problems. In addition, the BQR method provided more information than the traditional empirical methods, which verified that the BQR method, as a new empirical method for previous studies, was applicable in this topic and expanded the discussion space of this research field.

The decision in 2006 to abolish the agricultural tax, which had lasted for thousands of years, contributed to the prosperity of agriculture, and with it the growing importance of soil N₂O emissions in China. However, most of the previous literature ignored soil N₂O emissions due to their too small share in total agricultural greenhouse gas (GHG) emissions. This paper attempts to take soil N₂O emissions as an important variable in the measurement of agricultural green total factor productivity (AGTFP), which incorporates environmental pollution into the analytical framework of agricultural production efficiency. Three impressive results were found. Firstly, soil N₂O emissions play an increasingly important role in agricultural GHG emissions. The proportion of soil N₂O emissions in agricultural GHG emissions increased from 4.52% in 1998 to 4.83% in 2006, and then to 5.36% in 2016. Secondly, the regional difference of soil N₂O emissions in AGTFP is visible. In 2016, although soil N₂O emissions accounted for a small proportion (about 5%) of the total agricultural GHG emissions in China, the AGTFP including soil N₂O emissions was much lower than that excluding soil N₂O emissions, especially in areas with high agricultural and population density. Finally, over time, soil N₂O emissions have had an increasing effect on AGTFP. Compared with 1998–2006, the impact of excluding soil N₂O emissions on AGTFP in 2007–2016 was more evident than that including soil N₂O emissions.