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Due to the rapid urbanization of China, residential areas and residents in small towns exhibit dual and complex urbanization patterns and characteristics. The "one-size-fits-all" approach to programming public service facilities has led to inefficient use of idle facilities and the frequent use of facilities that are not integrated into the public service system. Therefore, an investigation of programming logic based on residents' needs within the complex urbanization patterns and characteristics of small towns is urgently required. This study distinguishes between rural and nonrural facilities, using the Kano model to evaluate residents' hypothetical satisfaction with the provision of facilities or lack thereof. Based on the "rural and nonrural" facility need coupling model, four stages of urbanization were identified. Using the Better–Worse coefficient and the chi-square test, this study analyzes residents' cognitive needs and population attributes across various stages of urbanization. Moreover, the study examines the "residential area–resident facility" matching relationship. Ultimately, a "required + optional item" public service facility guidance-control system based on the matching of human–land urbanization is proposed to improve the current programming system for public service facilities. This system provides a theoretical basis for improving the public service level in small towns and ensuring optimally relevant regulations. [ABSTRACT FROM AUTHOR]

The Jingtoushan Site (8300–7800 BP), located in Ningbo City, Zhejiang Province, is of great value for the in-depth understanding of China's prehistoric coastal culture. At this site, numerous valuable wooden relics showing past human civilization have been discovered. Multiple approaches were taken, including wood anatomy and physicochemical analyses, to assess the preservation state of waterlogged archaeological woods (WAWs), while using high-throughput sequencing (HTS) to explore their microbial diversity and composition as well as that of the surrounding soil. The secondary walls of WAWs showed to be severely degraded, whereas the compound middle layer and cell corner were well preserved. Bacteria were the main microorganisms causing the biodegradation of WAWs, and 85.6% of the phyla was also found in the surrounding soil environment. Specifically, Arcobacter, Flavobacterium, Hyphomicrobium, Pseudomonas and Sphingomonas, bacteria retrieved by HTS in high abundance, were inferred to be potentially associated with the biodegradation of WAWs at the Jingtoushan Site. Meanwhile, it is hypothesized that lignin in the wooden artefacts still buried and unexcavated at the Site might be at risk of further degradation, although it may be better preserved than the cellulose and hemicellulose. [ABSTRACT FROM AUTHOR]

Highlights: [•] OCP accumulation was measured in seafoods from four counties of Zhejiang Province. [•] OCP concentrations in 13 types of seafoods ranged from 258.3 to 3459.6ngg−1 (lw). [•] HCHs and DDTs were the most abundant OCPs in seafoods from the tested environments. [•] Total OCP content in seafoods varied regionally and was highest in Shengsi and Putuo. [•] OCPs in seafoods of Shengsi may be from dicofol products used in Yangtze Estuary. [ABSTRACT FROM AUTHOR]

Regional energy development and approaches are significant for China's overall economic and social development. The GDP in Zhejiang province surpassed 6 trillion yuan in 2019, and its energy consumption reached 200 million tons of standard coal (tce), both of which are at the forefront of China. In order to explore the main factors of the increase in energy consumption in Zhejiang and provide essential references for energy saving and other provinces, this paper analyzes the total energy consumption and industrial sectors on the basis of the logarithmic mean divisia index (LMDI) model. Study results show that the economy's scale is the most crucial factor affecting Zhejiang's energy consumption, with a significant growth effect. In 2015, the scale effect increased energy consumption to the highest value of 14 million tce and then reduced it to 13 million tce in 2019. The impact of the population on energy consumption increased by 10 million tce from 2010 to 2019. Energy intensity reduces energy consumption by between 0.05 and 0.15 billion tce per year, which is the main factor in reducing energy consumption. The energy structure generally plays a weak positive role due to the different energy types. The decomposition of the energy consumption per unit of value added in the industrial sector showed that the intensity and structural effect primarily reduce energy consumption, for example, the metal smelting and rolling, textile printing and paper, electric power, heating, and other industries. According to the results, enterprises should enhance the intelligence and efficiency of dispatch management and emergency responses. Zhejiang should also accelerate an international oil and gas trading center and resource allocation base to reach its carbon-neutrality goal. [ABSTRACT FROM AUTHOR]