Xuejuan Fang

Ground-level ozone (O₃) pollution has emerged as a significant concern impacting air quality in urban agglomerations, primarily driven by meteorological conditions and social-economic factors. However, previous studies have neglected to comprehensively reveal the spatial distribution and driving mechanism of O₃ pollution. Based on the O₃ monitoring data of 41 cities in the Yangtze River Delta (YRD) from 2014 to 2021, a comprehensive analysis framework of spatial analysis-spatial econometric regression was constructed to reveal the driving mechanism of O₃ pollution. The results revealed the following: (1) O₃ concentrations in the YRD exhibited a general increasing and then decreasing trend, indicating an improvement in pollution levels. The areas with higher O₃ concentration are mainly the cities concentrated in central and southern Jiangsu, Shanghai, and northern Zhejiang. (2) The change of O₃ concentration and distribution is the result of various factors. The effect of urbanization on O₃ concentrations followed an inverted U-shaped curve, which implies that achieving higher quality urbanization is essential for effectively controlling urban O₃ pollution. Traffic conditions and energy consumption have significant direct positive influences on O₃ concentrations and spatial spillover effects. The indirect pollution contribution, considering economic weight, accounted for about 35%. Thus, addressing overall regional energy consumption and implementing traffic source regulations are crucial paths for O₃ pollution control in the YRD. (3) Meteorological conditions play a certain role in regulating the O₃ concentration. Higher wind speed will promote the diffusion of O₃ and increase the O₃ concentration in the surrounding city. These findings provide valuable insights for designing effective policies to improve air quality and mitigate ozone pollution in urban agglomeration area.

Vegetable production in Subtropical China is distinguished by excessive nitrogen (N) fertilization, frequent irrigation, and multiple crop rotations in a single year. The aforementioned variables are closely related to soil nitrous oxide (N₂O) and methane (CH₄) emissions. Hence, we conducted a field trial to measure N₂O and CH₄ emissions using static chamber–gas chromatograph. Four treatments were used: control (CK) with no fertilizer, 100% chemical N fertilization (CN), the conventional 30% chicken manure N plus 70%CN (CMN + CN), and 30% chicken manure biochar N plus 70%CN (CMBN + CN). The annual cumulative N₂O emissions reached 12.4, 63.5, 111.8, and 44.1 kg N₂O-N ha⁻¹ for the CK, CN, CMN + CN, and CMBN + CN treatments, respectively. Compared to the CN and CMN + CN treatments, the CMBN + CN treatment reduced N₂O emissions by 35.9%–65.7%, while it simultaneously increased the total vegetable yield by 16.1% compared to the CN treatment. Seven seasons mean N₂O emission factors are 1.3% for CN, 3.8% for CMN + CN, and 0.9% for CMBN + CN. The CH₄ emission was negligible, ranging from 0.07 kg CH₄-C ha⁻¹ for the CK treatment to 0.8 kg CH₄-C ha⁻¹ for the CN treatment. N₂O emissions peaked under the conditions of an interior chamber temperature of around 31.9 °C and the water-filled pore space (WFPS) of the soil being approximately 60%. Future climate change will intensify, triggering higher N₂O emissions from subtropical vegetable fields. CMB can be one of the best substitutes for direct chicken manure application as a soil supplement because it has a beneficial effect on improving vegetable yield and reducing N₂O emissions in Subtropical China.

The digital economy (DE) not only drives economic innovation and development but also has significant environmental effects by promoting lower carbon emissions. To investigate the spatial effects of DE on urban carbon emissions, this study comprehensively measures the level of DE development based on the panel data from 11 typical cities in Zhejiang Province from 2011 to 2020, by comparing analysis using different regression models. The following conclusions are obtained: (1) The total carbon emissions (TC) of Zhejiang cities in general show a fluctuating change trend of first increasing and then slowly decreasing, while carbon emission intensity and carbon emission per capita in general show a fluctuating change trend of decreasing. Cities with high TC are primarily concentrated in the Hangzhou Bay city cluster, accounted for 62 ~ 65% of the province’s carbon emissions. The development of the DE in Zhejiang cities shows steady growth, but there are large differences among cities, with Hangzhou and Ningbo standing out as particularly prominent. (2) There is a significant inverted U-shaped relationship between the DE and the level of carbon emissions in Zhejiang Province. The influence coefficient of the DE on the primary term of TC is 0.613, and the influence coefficient of the quadratic term of TC is − 1.008. (3) In terms of the spatial spillover effect of the DE on carbon emissions, the study finds that compared to the direct effect, the spatial spillover effect is not significant. However, the allocation of transport resources shows a positive spatial spillover effect (increasing carbon emissions, coefficient value is 0.138), while technological progress shows a somewhat negative spatial spillover effect (decreasing carbon emissions, coefficient value is − 0.035). (4) The study also finds that the smart city pilot policy significantly reduces urban carbon emissions. Moreover, the effect of the DE on carbon emissions is confirmed through the significance test of the quadratic term when replacing the geographical and economic distance weight matrices. This indicates that the empirical findings are robust to these tests. Finally, several countermeasures to reduce carbon emissions are proposed from the perspective of DE development.

Improving yield in potato production with minimal environmental impact is of great significance for China’s potato staple food policy. Previous research has been limited by the absence of regional-scale parameters to evaluate the environmental costs of regional potato production. To address this gap, we utilized the input–output analysis method to offer a thorough estimation of nitrogen (N), phosphorus (P), and potassium (K) inputs and outputs in the potato production stage at a regional scale, leveraging a meta-analysis dataset from plenty of the literature. On this basis, we calculated the virtual N, P, and K factors (VNFs, VPFs, and VKFs) for different potato production regions, under both conventional and optimal management practices. China’s potato production suffered from excessive N and P inputs, while K inputs remained insufficient. Significant spatial heterogeneities were observed for the VNFs, VPFs, and VKFs across different potato production regions. Northeast China and northwest China emerged as the most suitable potato cultivation regions because they demonstrated high potato yields with relatively low inputs and, consequently, lower VNFs and VPFs. Southwest China was the most vital region where targeted efforts could lead to reducing VNF and VPF, thus significantly mitigating environmental N and P losses. In addition to reducing fertilizer inputs, site-specific and whole optimization measures are proposed to lower the environmental costs and promote the sustainable development of potato production.

The digital economy (DE) not only drives economic innovation and development but also has significant environmental effects by promoting lower carbon emissions. To investigate the spatial effects of DE on urban carbon emissions, this study comprehensively measures the level of DE development based on panel data from 11 typical cities in Zhejiang Province from 2011 to 2020, by comparing analysis using different regression models. The following conclusions are obtained: (1) The total carbon emissions (TC) of Zhejiang cities in general show a fluctuating change trend of first increasing and then slowly decreasing, while carbon emissions intensity and carbon emissions per capitain general show a fluctuating change trend of decreasing. Cities with high TC are primarily concentrated in the Hangzhou Bay city cluster, including Ningbo, Hangzhou and Jiaxing. The development of the DE in Zhejiang cities shows steady growth, but there are large differences among cities, with Hangzhou and Ningbo standing out as particularly prominent. (2) There is a significant inverted U-shaped relationship between the DE and the level of carbon emissions in Zhejiang Province. Thus, the DE increases carbon emissions in the early stages of development and has a dampening effect on carbon emissions in the mature stages of development. (3) Compared to the direct effect, the spatial spillover effect of the DE on carbon emissions is not significant. However, the allocation of transport resourcesshows a positive spatial spillover effect (increasing carbon emissions), technological progress shows a somewhat negative spatial spillover effect (decreasing carbon emissions). (4) Smart city pilot policy significantly reduces urban carbon emissions, and the effect of the DE on carbon emissions is found to pass the significance test the quadratic term when replacing the geographical and economic distance weight matrices, indicating that the empirical findings are robust to these tests. Finally, several carbon emission reduction countermeasures are proposed from the perspective of DE development.

Improving the digital economy and environmental governance efficiency are important methods for current high-quality economic development. Based on the panel data of 11 cities in Zhejiang, on the eastern coast of China, fine particulate matter smaller than a 2.5 μm (PM_2.5) environmental efficiency (PMEE) was measured by the undesirable output Slack-Based Measure-Data Envelopment Analysis (SBM-DEA) model. The fixed effect regression model, the divergences in the difference model and other empirical methods were obtained to test the driving mechanism of social-economic factors on the PMEE. The results showed that: (1) the concentration of PM_2.5 was continually decreasing, and environmental quality experienced a continuous improvement in Zhejiang province in the observation period, although cities such as Hangzhou, Jiaxing and Shaoxing have relatively severe PM_2.5 pollution. (2) The total average value of PMEE in Zhejiang was 0.6430 over the observation period, while there was still a lot of room for improvement when compared to the production frontier. Additionally, PMEE in each city showed a fluctuating growth trend. Cities with a higher PMEE were mainly Zhoushan, Hangzhou and Ningbo. (3) The level of the digital economy had a positive role in promoting the PMEE, which was statistically significant. The level of pollution control and technological innovation also had a significantly positive effect. However, the ratio of the industrial output value to the gross domestic product (GDP) presented a negative effect on the PMEE. In the future, it is suggested that the development of the urban digital economy should be accelerated in an all-around way to improve the efficiency of government pollution control and to improve the technical efficiency of PM_2.5 via innovative technological progress.

Based on China’s potato staple food policy, we chose potatoes as a study case to analyze the following indicators—the virtual new nitrogen factor (VNNF), the virtual new phosphorus factor (VNPF), the virtual irrigation-water (IW) factor (VIWF), the virtual total water (IW + precipitation) factor (VTWF), and the virtual greenhouse gas (GHG) emission factor (VCF) of the potatoes consumed by households in the six potato cultivation regions—by reviewing 220 publications from 2000 to 2020. The results showed that the VNNF ranged between 17.8 ± 7.8 and 30.1 ± 17.0 kg N kg⁻¹ N in the consumed potato, the VNPF ranged between 8.4 ± 5.0 and 18.8 ± 11.3 kg P kg⁻¹ P in the consumed potato, the VIWF ranged between 0.3 ± 1.0 and 1.8 ± 1.4 m³ IW kg⁻¹ for the consumed standard yield (except in the three mainly rainfed potato regions), the VTWF ranged between 4.8 ± 2.2 and 9.3 ± 3.7 m³ total water kg⁻¹ for the consumed standard yield, and the VCF ranged between 3.4 ± 1.5 and 5.9 ± 2.4 kg CO₂ equivalent kg⁻¹ for the consumed standard yield, under the conventional practice in the six potato cultivation regions. The normalization score results indicate that the northeast, northwest, southwest, and south of China are relatively more suitable regions in which to plant potatoes, based on the VNNF, VNPF, VIWF or VTWF, and VCF indicators.

College students are one of the most important groups of participants and promoters of household waste separation. Taking Ningbo as a case study, an online + offline questionnaire survey among more than 1700 students in 10 colleges is conducted to identify the main factors and pathways influencing waste separation behavior in the post COVID-19 pandemic period. The results show that the KMO statistic is 0.926, Bartlet test is p < 0.001, indicating that questionnaire sample data is suitable for factor analysis. The modified Structural Equation Model test indicates that waste separation behavior of college students mainly results from the combined effect of eight subjective intrinsic factors and seven external situational factors. Among them, the convenience of recycling facilities, the convenience of sorting facilities and the publicity and education of sorting knowledge are the top three factors with the most significant influence. The mean value of epidemic impact factors is 0.277, which is slightly lower than conventional influence factors (0.289). Environmental Norms and Constraints are an essential component in the analysis framework of college students’ waste separation behavior. In the future, society and colleges should give full play to the positive influence of the epidemic factor on college students’ waste separation behavior.