Time series of the average annual Palmer drought severity index (PDSI) and standardized precipitation index (SPI) were calculated for 483 meteorological stations in China using monthly data from 1961 to 2005. The time series were analyzed for 10 large regions covering the territory of China and represented by seven river basins and three areas in the southeast, southwest, and northwest. Results show that the frequencies of both dry and wet years for the whole period are lower for southern basins than for the northern ones when estimated by PDSI but very similar for all basins when calculated by SPI. The frequencies of dry and wet years calculated for 5- and 15-yr subperiods by both indices show the upward dry trends for three northeastern basins, Songhuajiang, Liaohe, and Haihe; a downward dry trend for the northwest region; a downward wet trend for the Yellow River basin; and an upward wet trend for the northwest region. Trend detection using PDSI indicates statistically significant negative trends for many stations in the northeastern basins (Songhuajiang, Liaohe, Haihe, and Yellow) and in the middle part of the Yangtze, whereas statistically significant positive trends were found in the mountainous part of the northwest region and for some stations in the upper and lower Yangtze. A moderately high and statistically significant correlation between the percentage of runoff anomaly (PRA) and the annual average PDSI and SPI was found for six large rivers. The results confirm that PDSI and SPI indices can be used to describe the tendency of dryness and wetness severity and for comparison in climate impact assessment.

Beginning in 2016, all couples in China were allowed to have two children without any restrictions. This paper provides population and economic projections under five shared socioeconomic pathways (SSPs) and three fertility policies. By replacing the one‐child policy with a two‐child policy, the population is predicted to continue growing until 2025‐2035, with a peak of approximately 1.39‐1.42 billion, and then to decline under four SSPs, with the exception of the fragmented world SSP3. As a result, the two‐child policy will lead to mitigation of the pressure from labour shortages and ageing problems to a certain extent. In addition, an increase in working‐age people with higher education level relative to projections based on the one‐child policy will lead to an increase in gross domestic product by approximately 38.1%‐43.9% in the late 21^st century. However, labour shortages and ageing problems are inevitable, and the proportion of elderly in China will be greater than 14% and 21% by approximately 2025 and 2035, respectively. Full liberalization of fertility is expected to reduce the share of elderly people by 0.7%‐1.0% and to lead to an increase in gross domestic product by 5.3%‐6.7% relative to the two‐child policy in the late 21^st century. The full liberalization of fertility policies is recommended, supplemented by increases in pension and child‐rearing funds, improvement in the quality of health services for females and children, and extension of compulsory education to meet the needs of an aged society.

The increase in surface air temperature in China has been faster than the global rate, and more high temperature spells are expected to occur in future. Here we assess the annual heat-related mortality in densely populated cities of China at 1.5 °C and 2.0 °C global warming. For this, the urban population is projected under five SSPs, and 31 GCM runs as well as temperature-mortality relation curves are applied. The annual heat-related mortality is projected to increase from 32.1 per million inhabitants annually in 1986–2005 to 48.8–67.1 per million for the 1.5 °C warming and to 59.2–81.3 per million for the 2.0 °C warming, taking improved adaptation capacity into account. Without improved adaptation capacity, heat-related mortality will increase even stronger. If all 831 million urban inhabitants in China are considered, the additional warming from 1.5 °C to 2 °C will lead to more than 27.9 thousand additional heat-related deaths, annually.

Devastating health effects from recent heat waves in China have highlighted the importance of understanding health consequences from extreme heat stress. Despite the increasing mortality from extreme heat, very limited studies have quantified the effects of summer extreme temperature on heat-related illnesses in China. The associations between extreme heat and daily heat-related illnesses that occurred in the summers of 2011-2013 in Ningbo, China, have been examined, using a distributed lag non-linear model (DLNM) based on 3862 cases. The excess morbidities of heat-related illness during each heat wave have been calculated separately and the cumulative heat wave effects on age-, sex-, and cause-specific illnesses in each year along lags have been estimated as well. After controlling the effect of relative humidity, it is found that maximum temperature, rather than heat index, was a better predictor of heat-related illnesses in summers. A positive association between maximum temperatures and occurrence of heat-related diseases was apparent, especially at short lag effects. Six heat waves during the period of 2011-2013 were identified and all associated with excess heat-related illnesses. Relative to the average values for the corresponding periods in 2011 and 2012, a total estimated 679 extra heat-related illnesses occurred during three heat waves in 2013. The significant prolonged heat wave effects on total heat-related illnesses during heat waves in three study years have also been identified. The strongest cumulative effect of heat waves was on severe heat diseases in 2013, with a 10-fold increased risk. More males than females, individuals with more severe forms of illness, were more affected by the heat. However, all age groups were vulnerable. Recent heat waves had a substantial and delayed effect on heat illnesses in Ningbo. Relevant active well-organized public health initiatives should be implemented to reduce the adverse effects of heat extremes on the illnesses.