A dynamic irrigation scheme that considers groundwater processes and dynamic vegetation was constructed and incorporated into Noah land surface model with multiparameterization options coupled with the weather research and forecasting model. Multiple experiments (with and without irrigation) were designed to simulate the impacts of irrigation over the North China Plain (NCP) on regional climate. The simulated irrigation rate of the NCP was close to observations, and its interannual variations were clearly associated with dry or wet years. The groundwater table affected by irrigation varied in the NCP irrigated areas during simulation period but declined overall. The irrigation‐induced increases in green vegetation fraction led to increases in transpiration, indicating that the influences of irrigation on latent heat flux should contain the changes of transpiration besides changes of soil evaporation. The modified surface energy budget caused by irrigation affected surface air temperature (SAT), and the spring and summer SAT in the areas with larger irrigation rate decreased significantly by 0.8–1.6 and 1.2–2.6 °C, respectively. The experiment that considered irrigation showed obvious improvement in simulating several key variables (gross primary productivity, green vegetation fraction, sensible heat flux, and summer SAT). In the NCP, irrigation increased water vapor and caused cooling in boundary layer, which had opposing influences on precipitation, resulting in heterogeneous changes in summer precipitation. The changes of precipitation in nonirrigated areas were related to the influences of irrigation on wind fields. The contribution of direct effects of irrigation to blended influences of irrigation and dynamic vegetation on spring (summer) SAT was 70.9% (63.8%).

The mitigation of the urban heat island effect is increasingly imperative in light of climate change. Blue–green space, integrating water bodies and green spaces, has been demonstrated to be an effective strategy for reducing the urban heat island effect and enhancing the urban environment. However, there is a lack of coupled analysis on the cooling island effect of blue–green space at the meso-micro scale, with previous studies predominantly focusing on the heat island effect. This study coupled the single urban canopy model (UCM) with the mesoscale Weather Research and Forecasting (WRF) numerical model to simulate the cooling island effect of blue–green space in the Eastern Sea-River-Stream-Lake Linkage Zone (ESLZ) within the northern subtropical zone. In particular, we comparatively investigated the cooling island effect of micro-scale blue–green space via three mitigation strategies of increasing vegetation, water bodies, and coupling blue–green space, using the temperature data at the block scale within 100 m square of the urban center on the hottest day in summer. Results showed that the longitudinally distributed lakes and rivers in the city had a significant cooling effect on the ambient air temperature (Ta) at the mesoscale, with the largest cooling range occurring during the daytime and ranging from 1.01 to 2.15 °C. In contrast, a 5~20% increase in vegetation coverage or 5~15% increase in water coverage at the micro-scale was observed to reduce day and night Ta by 0.71 °C. Additionally, the most significant decrease in physiologically equivalent temperature (PET) was found in the mid-rise building environment, with a reduction of 2.65–3.26 °C between 11:00 and 13:00 h, and an average decrease of 1.25°C during the day. This study aims to guide the optimization of blue–green space planning at the meso-micro scale for the fast-development and expansion of new urban agglomerations.

Plastic film mulch, which effectively maintains soil moisture by suppressing soil evaporation, has been widely used in cropland in Northwest China, where water scarcity severely restricts agricultural development. Plastic mulch affects surface albedo and blocks water vapor exchange between soil and atmosphere. Therefore, the large area of cropland covered by plastic film will have serious impacts on regional climate by modifying the surface-atmosphere partitioning of vapor and energy. In this study, a dynamic irrigation scheme was incorporated into the Weather Research and Forecasting model with Noah land surface scheme; two experiments (with and without plastic mulch) were designed to simulate the impacts of plastic mulch over cropland in Northwest China on regional climate. In irrigated cropland, the irrigation amount decreased substantially during the early stage of crop growth (ESCG; from 22 April to 1 July) with plastic mulch, especially in May, indicating that plastic mulch conserved agricultural water. In nonirrigated cropland, soil moisture in cropland with plastic mulch was clearly greater than that without plastic mulch. The influences of plastic mulch on land surface processes were mainly reflected in the ESCG, such that upward shortwave radiation increased and latent heat flux decreased. In cropland during the ESCG, after plastic mulch, the latent heat flux decreased significantly by 12–30 W m⁻², the sensible heat flux increased significantly by 8–16 W m⁻², and the surface air temperature increased significantly by 0.2–0.8 °C. The plastic mulch reduced water vapor in the lower atmosphere, which might lead to decrease precipitation in Northwest China.

As urbanization advances, the issue of urban heat islands (UHIs) grows increasingly serious, with UHIs gradually transitioning into regional urban heat islands. There is still a lack of research on the evolution and drivers of the thermal environment in urban agglomerations; therefore, in this study, we used trend analysis methods and spatial statistical analysis tools to investigate these issues in the Beijing–Tianjin–Hebei (BTH) urban agglomeration. The results demonstrated the following: (1) The land surface temperature (LST) exhibited low fluctuation, while the relative land surface temperature (RLST) fluctuated significantly. In Zhangjiakou and Chengde, the LST and RLST evolution trends were complex, and the results differed between daytime and nighttime, as well as between the annual and seasonal scales. In other regions, the trends of LST and RLST evolution were more obvious. (2) During the daytime, the high UHI clusters centered on “BJ–TJ–LF” and “SJZ–XT–HD” formed gradually; during the nighttime, the high UHI clusters were mainly observed in built-up areas. The distribution range and direction of UHIs showed greater degrees of evolution during the daytime in summer. (3) The total UHI area showed an increasing trend, and the intensity of heat stress suffered by the BTH agglomeration was increasing. (4) In BTH and Hebei, aerosol optical depth, surface solar radiation, population density, and gross domestic product were the dominant factors influencing UHIs; moreover, in Beijing and Tianjin, all factors showed an basically equal impact. The methodology and findings of this study hold significant implications for guiding urban construction, optimizing urban structure, and improving urban thermal comfort in the BTH urban agglomeration.

Surface fine particulate matter (PM) with a diameter of less than 2.5 microns (PM2.5) negatively impacts human health and the economy. However, due to data and model limitations, obtaining high-quality, high-spatial-resolution surface PM2.5 concentration data is a challenging task, and it is difficult to accurately assess the temporal and spatial changes in PM2.5 levels at a small regional scale. Here, we combined multi-angle implementation of atmospheric correction (MAIAC) aerosol products, ERA5 reanalysis data, etc., to construct an STW-LightGBM model that considers the spatiotemporal characteristics of air pollution and estimate the PM2.5 concentration of China’s surface at 1 km resolution from 2015 to 2020. Our model performed well, and the fitting accuracy of the 10-fold cross-validation between years was 0.877–0.917. The fitting accuracy of the model was >0.85 at different time scales (month, season, and year). The average slope of the regression prediction was 0.9 annually. The results showed that PM2.5 pollution improved from 2015 to 2020. The average PM2.5 concentration decreased by 4.55 μg/m³, and the maximum decrease reached 90.51 μg/m³. The areas with high PM2.5 concentrations were predominantly in the North China Plain, Sichuan Basin, and Xinjiang in the west, and the levels in areas with elevated PM2.5 levels were consistent across most study years. The standard deviation ellipse for PM2.5 in China showed a ‘northeast–southwest’ spatial distribution. From an interannual perspective, the average values of the four seasonal stations in the country showed a downward trend from 2015 to 2020, with the most obvious decline in winter, from 70.67 μg/m³ in 2015 to 46.75 μg/m³ in 2020. Compared to earlier inversion studies, this work provides a more stable and accurate method for obtaining high-resolution PM2.5 data, which is necessary for local air governance and environmental ecological construction at a fine scale.