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Since China's reform and opening up in 1978, the acceleration of industrialization and urbanization in China had led to dramatic changes in the pattern of urban-rural land use. In this paper, we focused on the rural industrialized areas in central China (Xinxiang County and Changyuan City of Henan Province). We used the average nearest neighbor index, spatial statistical analysis, and a structural equation model to analyze the spatiotemporal evolution and influencing factors of urban-rural construction land based on multi-source spatial data and survey data. The results showed that: 1) from 1975 to 2019, the spatial distribution of urban-rural construction land in rural industrialized areas had evolved from homogeneous distribution to local agglomeration. In terms of comparative analysis of cases, the spatial distribution of urban-rural construction land in Changyuan City had shown a trend from diffusion to agglomeration, and Xinxiang County had overall shown a spatial change from homogenization to agglomeration and then to regional integration development. 2) The hot spots with increased urban-rural construction land significantly expanded, and they had a high degree of spatial overlap with industrial development. Among them, Xinxiang County was concentrated in central and marginal areas, and Changyuan was mainly concentrated in central urban areas. 3) From the evolution of spatial proximity of urban-rural construction land, rural industrialized areas generally decline, showing the characteristics of internal differentiation in the rate of change. 4) Industrial development, social economy, the policy environment, and urban development played a positive role in promoting the expansion of urban-rural construction land in rural industrialized areas. To promote the optimal use of regional land and the integrated development of urban-rural areas, we should combine the advantages of regional endowment, formulate development strategies according to local conditions, and adjust the way that land is used in a timely manner. [ABSTRACT FROM AUTHOR]

• The extent of flooding in China is greater than in any other country. • Nearly 66% of China's landmass is submerged by flooding. • Financial toll of flooding accounts for approximately 1.42% of the annual GDP. • Various forms of climatic change contribute to flooding. The extent of flooding in China is more significant than in any other country. Our research reveals that approximately 66 % of China's landmass is submerged by flooding, affecting about 50 % of the population. Furthermore, the financial toll of flooding now accounts for approximately 1.42 % of the annual gross domestic product (GDP), which is almost 40 times higher than the corresponding figure for the United States. We have observed that Zhengzhou city in Henan province, which faced a devastating flood in 2021, received a significant amount of rainfall, specifically a total of 552.5 mm within a 24-hour period. The floods in Henan province in 2021 caused considerable damage, including impacting nearly 15 million people, resulting in almost 400 deaths, damaging over 10,000 square kilometers of agricultural land, causing almost $19 billion in economic losses, and leading to the collapse of over 35,000 households and damage to various properties. In a similar manner, the significant flooding that occurred in southern China in 2020 impacted approximately 7.1 million individuals across eight provinces and resulted in 54 fatalities, the collapse of 6,700 houses, and incurred a direct economic loss of US$3.33 billion. We found that rainstorms have significantly increased to 10 % in the last 60 years in China. In this paper, we delved into exploring the existing published articles, reports, and government and authoritative legal texts to analyze the causes and impacts of flooding in China's flood-prone regions and potential mitigation strategies to reduce the repercussions of distressing flood events. We believe this study will help policymakers by providing new insights while formulating policy to reduce the loss caused by high-level flooding. [ABSTRACT FROM AUTHOR]

Open biomass burning (OBB) has a high potential to trigger local and regional severe haze with elevated fine particulate matter (PM 2.5) concentrations and could thus deteriorate ambient air quality and threaten human health. Open crop straw burning (OCSB), as a critical part of OBB, emits abundant gaseous and particulate pollutants, especially in fields with intensive agriculture, such as in central and eastern China (CEC). This region includes nine provinces, i.e., Hubei, Anhui, Henan, Hunan, Jiangxi, Shandong, Jiangsu, Shanghai, and Fujian. The first four ones are located inland, while the others are on the eastern coast. However, uncertainties in current OCSB and other types of OBB emissions in chemical transport models (CTMs) lead to inaccuracies in evaluating their impacts on haze formations. Satellite retrievals provide an alternative that can be used to simultaneously quantify emissions of OCSB and other types of OBB, such as the Fire INventory from NCAR version 1.5 (FINNv1.5), which, nevertheless, generally underestimates their magnitudes due to unresolved small fires. In this study, we selected June 2014 as our study period, which exhibited a complete evolution process of OBB (from 1 to 19 June) over CEC. During this period, OBB was dominated by OCSB in terms of the number of fire hotspots and associated emissions (74 %–94 %), most of which were located at Henan and Anhui (> 60 %) with intensive enhancements from 5 to 14 June (> 80 %). OCSB generally exhibits a spatiotemporal correlation with regional haze over the central part of CEC (Henan, Anhui, Hubei, and Hunan), while other types of OBB emissions had influences on Jiangxi, Zhejiang, and Fujian. Based on these analyses, we establish a constraining method that integrates ground-level PM 2.5 measurements with a state-of-art fully coupled regional meteorological and chemical transport model (the two-way coupled WRF-CMAQ) in order to derive optimal OBB emissions based on FINNv1.5. It is demonstrated that these emissions allow the model to reproduce meteorological and chemical fields over CEC during the study period, whereas the original FINNv1.5 underestimated OBB emissions by 2–7 times, depending on specific spatiotemporal scales. The results show that OBB had substantial impacts on surface PM 2.5 concentrations over CEC. Most of the OBB contributions were dominated by OCSB, especially in Henan, Anhui, Hubei, and Hunan, while other types of OBB emissions also exerted an influence in Jiangxi, Zhejiang, and Fujian. With the concentration-weighted trajectory (CWT) method, potential OCSB sources leading to severe haze in Henan, Anhui, Hubei, and Hunan were pinpointed. The results show that the OCSB emissions in Henan and Anhui can cause haze not only locally but also regionally through regional transport. Combining with meteorological analyses, we can find that surface weather patterns played a cardinal role in reshaping spatial and temporal characteristics of PM 2.5 concentrations. Stationary high-pressure systems over CEC enhanced local PM 2.5 concentrations in Henan and Anhui. Then, with the evolution of meteorological patterns, Hubei and Hunan in the low-pressure system were impacted by areas (i.e., Henan and Anhui) enveloped in the high-pressure system. These results suggest that policymakers should strictly undertake interprovincial joint enforcement actions to prohibit irregular OBB, especially OCSB over CEC. Constrained OBB emissions can, to a large extent, supplement estimations derived from satellite retrievals as well as reduce overestimates of bottom-up methods. [ABSTRACT FROM AUTHOR]

Household labour migration experiences may have a staggering impact within developing countries, especially in dynamic societies like China, where labour migration is obvious. The present study's objective is to investigate whether household labour migration contributes to the probability of farmers' access to productive agricultural services. The study's empirical setup is comprised of household survey data of 541 farmers in Shaanxi, Henan, and Sichuan provinces. The study proposes a counterfactual model to evaluate the average processing effect of an urban migrant with the help of the endogenous transformation of the Probit model. The results show that labour migration for work directly affects farmers' access to productive agricultural services and indirectly affects farmers' access to productive agricultural services through three channels: labour input, land transfers, and planting structure adjustments. The study further confirms that labour migration for work has a significant heterogeneity in the probability of obtaining productive agricultural services for farmers with or without non-agricultural income. Simultaneously, the labour migration area for work has significant heterogeneity in the probability of farmer households' access to productive agricultural services. The government should extend support towards productive agriculture services. Agricultural demonstration services and on-hand training of migrant labour should be highlighted. [ABSTRACT FROM AUTHOR]