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Currently, there is a large deviation between official road freight data and real road freight performance at a subnational level in China. In order to deal with this deviation, the new concept of local freight tonnage and ton-kilometers is presented in this paper based on the territoriality principle, where either the origin or the destination of goods transported is local. Also, the statistic procedures and estimation models of the local freight tonnage and ton-kilometers are proposed based on five accessible basic datasets. Finally, an empirical study in Sichuan province of China is conducted. The statistical results show that there is a large amount of local freight transported by local non-commercial trucks and non-local trucks, which is ignored in the existing road freight statistics. Especially, the higher the level of local economic development, the greater the deviation between the official road freight data and the real road freight performance at a subnational level. [ABSTRACT FROM AUTHOR]

Brownfields are an important part of urban land resources. Strengthening the governance and redevelopment of brownfields is significant to environmental protection, high-quality urban development and sustainable development. However, due to the complexity and harmfulness of brownfield pollution, the hasty, untimely, and blind development can cause serious consequences. It is infeasible to pay more attention to development than governance or vice versa. In this paper, aiming at brownfield redevelopment evaluation, we introduced the Wuli-Shili-Renli (WSR) system methodology, an oriental system thought combining qualitative and quantitative analyses, comprehensively analyzed the influencing factors of brownfields from three dimensions of Wuli, Shili and Renli, and constructed the evaluation index system of brownfield redevelopment. To avoid much subjectivity in the evaluation process, we established the evaluation model of brownfield redevelopment using the catastrophe progression method. Taking the renovation project of Shanghai Xintiandi in 1999–2001 as a reference, the evaluation index system and evaluation model were applied to the renovation project of Wenjia Street in Qingyang District, Chengdu, Sichuan Province, China in 2022, and the results provided a good basis for the decision-making process. [ABSTRACT FROM AUTHOR]

In this paper, three monitoring sections were set up in Heilongtan Reservoir, and water samples were collected in 2019, 2020, and 2021 for the determination of physical and chemical properties such as permanganate index, chemical oxygen demand, and biochemical oxygen demand (BOD5). The water quality was evaluated by the single factor pollution index method and the Nemerow pollution index method, and the temporal and spatial changes of water quality were analyzed.The single factor pollution index method determines the water quality category by identifying the single worst indicator of water quality, based on the classified water quality category. The Nemerow pollution index method emphasizes the most polluting factor while also taking into account the contribution of other factors in the assessment system, and determines the water quality category through the comprehensive pollution index. The results of the study indicate that the monitoring indicators of the monitoring sections have reached the Category III water quality standard and above in the "Surface Water Environmental Quality Standard" during the three years 2019 to 2021. The Heilongtan Reservoir's water quality in 2019, 2020, and 2021 is of Category I standard, according to the results of the evaluation of water quality using the single factor pollution index technique. According to the Nemerow pollution index method's results for evaluating water quality, the water quality pollution index for the three monitoring sections as a whole ranges from 0.36 to 0.51 in three years. The three monitoring sections' water quality—Dongfeng Canal, Longmiao, and Sixin Village—has not changed significantly during that time, remaining clean. In terms of temporal and spatial rates of change, the temporal rate of change (T) and spatial rate of change (S) over the three years were less than 20%, and the changes in water quality at each monitoring site were not significant. [ABSTRACT FROM AUTHOR]

Driving forces are the factors that lead to the observed changes in the quantity and quality of ecosystem services (ESs). The relationship between driving forces and ESs involves considerable scale-related information. Place-based ecological management requires this information to support local sustainable development. Despite the importance of scale in ES research, most studies have only examined the association between ESs and their drivers at a single level, and few studies have examined this relationship at various scales or analyzed spatial heterogeneity. The purpose of this paper is to explore the significance of the scale-dependent effects of drivers on ESs for localized ecological management. The biophysical values of ESs were calculated using several ecological simulation models. The effects of driving forces on ESs were explored using the geographically weighted regression (GWR) model. Variations in the effects of driving forces on ESs were examined at three scales: provincial, ecoregional, and subecoregional scales. Finally, canonical correlation analysis was used to identify the major environmental factors associated with these variations in each ecoregion. Our results show that (1) the distribution of soil conservation and water yield is highly heterogeneous; (2) four driving forces have significant positive and negative impacts on soil conservation and water yield, and their effects on the two services vary spatially (p < 0.05); (3) the impacts of drivers on ESs vary across different spatial scales, with a corresponding shift in the related environmental factors; and (4) in the study area, at the provincial scale, physical, topographical, and biophysical factors were key factors associated with the variations in the relationship between ESs and drivers, and at the ecoregional and subecoregional scales, physical, socioeconomic, topographical, and biophysical factors all contributed to these changes. Our results suggest that significant differences in topographical conditions (e.g., altitude, slope) can be incorporated for exploring the relationship between drivers and ESs and optimizing ecological management at the provincial scale, whereas significant differences in physical and socioeconomic conditions (e.g., urbanization levels, human activity, vegetation coverage) are more meaningful for localized ecological management at the ecoregional and subecological scales. These findings provide a basis for understanding the relationship between drivers and ESs at multiple scales as well as guidelines for improving localized ecological management and achieving sustainable development. [ABSTRACT FROM AUTHOR]

In the 12th Five-Year Plan period, Sichuan province has selected strategic emerging industries such as new-generation information technology, new energy, high-end equipment manufacturing, new materials, biology, energy conservation and environmental protection. However, its strategic emerging industries are still in the stage of cultivation and development, and there are some problems such as low industrial agglomeration and obvious industrial restructuring. In essence, this is because the focus of the development of strategic emerging industries is not clear enough, and the location advantages are not fully utilized to select the most suitable strategic emerging industries for the development of the region. This paper constructs a regional strategic emerging industries selection decision model, applies ARCGIS to study the spatial distribution of strategic emerging industries in Sichuan province, and uses fuzzy comprehensive evaluation method (FCEM) and analytic hierarchy process (AHP) to solve the priority of developing strategic emerging industries. Conclusions: Firstly, Sichuan province should give priority to the development of new generation information technology industry and new energy vehicle industry, then high-end equipment manufacturing industry, energy-saving and environmental protection industry and new energy industry, and finally biological industry and new material industry. The larger the coefficient of influence is, the higher the comprehensive score is, while the larger the coefficient of sensitivity is, the lower the comprehensive score is. Secondly, the number of enterprises in the new-generation information technology industry and the new energy vehicle industry is still not dominant in Sichuan province. Finally, the study found that the current development of strategic emerging industries in Sichuan province is extremely unbalanced in various regions, and the phenomenon of competition and reconstruction is obvious. [ABSTRACT FROM AUTHOR]

Population is a major production factor in rural development in China, which makes the study of rural population distribution patterns at different times and the factors influencing the population distribution an important foundation for understanding the issues in rural China and moving forward with the implementation of rural revitalization strategies. This paper analyzed the spatial evolution of the population in rural China based on population census data for the People's Republic of China by county in 1990, 2000 and 2010. Applying the geographical detector method, this paper also delved into the contributing factors that influenced the distribution based on the natural, social and economic data, such as the potential crop productivity, the average slope, the urbanization rate and the time cost to reach the nearest cities. The results indicate that the migration of the population from the rural areas into the cities, which was a result of rapid urbanization, did not change the original population distribution in rural China significantly. The rural population was still concentrated in the eastern plains, basins and deltas, and the North China Plain and Sichuan Basin still house the bulk of rural residents, but the population density of rural residents in the North China Plain and Sichuan Basin decreased from 1990 to 2010. The rural population in China tended to be distributed around the cities. Seventy-four percent of the rural population lived in an area within a 60-minute driving distance from the surrounding cities. The areas with dense rural population were basically consistent with the locations of the current major urban agglomerations in China. The current distribution of the rural population in China was a result of natural, social and economic conditions and location factors. Among them, natural factors such as the potential crop productivity and the degree of surface fragmentation had the most significant influence. [ABSTRACT FROM AUTHOR]

This paper investigates economic impacts of COVID-19 on households based on differences in the socio-economic status (SES). We determine the household-level effects of the COVID-19 shock using income sources, types of industries, communities' resilience, household susceptibility, and relevant policy measures. For this purpose, we used primary data of 555 households collected through snowball sampling technique using an online survey questionnaire from different villages mostly located in Sichuan Province, China. Using step-wise binary logistic regression analysis, we estimated and validated the model. Results suggest the use of SES as a better measure for understanding the impacts of COVID-19 on different households. We find that households with low SES tend to depend more on farmland income and transfer payments from the government. Contrarily, high SES households focus more on business and local employment as sources of income generation. Poor households were less resilient and more likely to fall back into poverty due to COVID-19, while the opposite stands true for non-poor households with high SES. Based on the estimations, policies encouraging employment and businesses complemented with loans on lower interest rates are recommended, which may increase the SES, thus minimizing vulnerability and enhancing the households' resilience towards poverty alleviation and economic shocks. [ABSTRACT FROM AUTHOR]

A mature understanding of the sandstone gas reservoir in the Xiaoheba Formation in the southeastern Sichuan Basin remains lacking. To assess the reservoir characteristics and the origin of the high-quality reservoir in the Xiaoheba Formation, this paper uses systematic field investigations, physical property analysis, thin section identification, scanning electron microscopy and electron microprobe methods. The results indicate that the Xiaoheba sandstone is an ultra-tight and ultra-low permeability reservoir, with an average porosity of 2.97% and an average permeability of 0.56×10−3 μm2. This promising reservoir is mainly distributed in the Lengshuixi and Shuangliuba regions and the latter has a relatively high-quality reservoir with an average porosity of 5.28% and average permeability of 0.53×10−3 μm2. The reservoir space comprises secondary intergranular dissolved pores, moldic pores and fractures. Microfacies, feldspar dissolution and fracture connectivity control the quality of this reservoir. The relatively weak compaction and cementation in the interbedded delta front distal bar and interdistributary bay microfacies indirectly protected the primary intergranular pores and enhanced late-stage dissolution. Late-stage potassium feldspar dissolution was controlled by the early-stage organic acid dissolution intensity and the distance from the hydrocarbon generation center. Early-stage fractures acted as pathways for organic acid migration and were therefore important factors in the formation of the reservoir. Based on these observations, the area to the west of the Shuangliuba and Lengshuixi regions has potential for gas exploration. [ABSTRACT FROM AUTHOR]

Background: In this paper, we report findings regarding the prevalence of expressed distress and depressive conditions among women living in a rural region of Sichuan Province. As well, we know of no data among women in rural China that examine whether “depression,” as categorically defined in classifications such as the DSM, adequately captures the expressed distress and symptomatic complaints of women in rural China. Methods: A multistage sampling method was employed to recruit the target population. The Center for Epidemiologic Studies Depression Scale (CES-D) was used to measure distress symptoms, and MINI International Neuropsychiatric Interview (MINI) was employed to determine the prevalence of diagnosable depression and other disorders. Results: Among 1898 rural women, 12.4% (236) scored ≥16 on the CES-D, indicative of distress, and a subset of 7.7% (146) had scores ≥21, highly suggestive of a clinically significant disorder. We found that 49.8% women with ≥16 CES-D score were identified as showing features consistent with a current major depressive episode (MDE) vs. 1.9% in a sample of randomly selected women with <16 CES-D score. Among respondents, 30 of 84 (35.7%) scoring 16–20 and 83 of 143 (58.0%) scoring ≥21 reported symptoms consistent with MDE. 25.1% of women with a positive CES-D score did not describe symptoms consistent with any DSM-IV disorder. Conclusions: We found a higher portion of women reporting significant distress than previously described. Among them, there was a clear gradient, such that 41.7% of women with moderate distress did not have a psychiatric diagnosis, and even among those with more severe symptoms, 15.4% did not manifest a DSM-specific psychiatric condition. [ABSTRACT FROM AUTHOR]