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Forest Farm Carbon Sink (FFCS) projects are one of the effective ways to achieve carbon neutrality and mitigate global warming. Though the existing literature has widely discussed the effect of FFCS on the allocation of agricultural factors, such as land, labor employment structure and income structure, little is known about whether FFCS projects could have an effect on agricultural development. Based on the panel data of 140 counties in Sichuan province, China, from 2002 to 2018, we examined the causal effect on agricultural total factor productivity (TFP), and revealed their dynamic effect and underlying mechanisms. Propensity score matching and the difference in difference (PSM-DID) method were used to address the endogeneity problem of FFCS implementation. Results showed that FFCS projects increased agricultural TFP by 1.7%–2.4%. Health, saving and industrial structure were the important channels through which FFCS projects affect agricultural TFP. Our findings suggest that policies promoting FFCS projects can increase agricultural TFP while achieving environmental goals—a win-win situation. • The causal effect of FFCS projects on agricultural development was examined. • A theoretical framework was constructed to quantify FFCS projects and agricultural development. • FFCS projects significantly increased agricultural TFP by 1.7%–4.9%. • FFCS projects affect agricultural TFP in short term but not in the medium and long term. • Health, saving and industrial structure were the important channels underlying the effect of FFCS projects. [ABSTRACT FROM AUTHOR]

Active contour based methods are effective models for image segmentation. However, they always suffer from the limited performance due to the presence of noise and intensity inhomogeneity. To solve this problem, a kernel metric induced local image fitting (KLIF) variational model is proposed in this paper. Firstly, a kernel metric induced local fitting image (KLFI) is introduced by minimising a kernel metric based energy. The combination of the kernel metric and the local fitting image enables the model to be more robust to the noise and intensity inhomogeneity. And then, using the KLFI, a variational level set model that is a squared l2 distance between the KLFI and the original image is constructed. Two regularisation terms are employed in the model to keep the level set function to be stable during the evolution. At last, an alternating iterative algorithm combining with fixed‐point iteration and gradient descent of three‐step time‐splitting is introduced to solve the proposed model. The experimental results show the effectiveness of the proposed model for image segmentation in the presence of noise and intensity inhomogeneity, and demonstrate the competitive performance over several state‐of‐the‐art variational models in term of accuracy and robustness. [ABSTRACT FROM AUTHOR]

Increasing consumer demand has increased environmental pressure. Altering consumer behavior may be one strategy to achieve emission reduction targets. China's carbon labeling system is still in its infancy, and consumers' response to carbon labeling products is still uncertain. This study investigates consumers' willingness to pay (WTP) for carbon-labeled agricultural products (CAP) in different regions, the factors influencing them, and the strategies to implement carbon labeling. The results suggest that 77.60% of respondents are willing to pay more for CAP. The premium WTP for carbon-labeled milk, corn, bananas, tomatoes, and eggs is 25.66%, 31.96%, 24.08%, 23.62%, and 20.64%. Low-carbon awareness and the peer effect greatly and favorably impact people's reception of carbon labeling. Respondents' WTP for carbon labeling is considerably and favorably influenced by their acceptance of carbon labeling. We also put forward some suggestions on the promotion strategy of CAP from the perspective of government, enterprises, and consumers. • This study investigates consumers' WTP for carbon-labeled agricultural products (CAP). • 77.60% of respondents are willing to pay more for CAP. • People's reception of CLP is impacted by low-carbon awareness and peer effect. • Respondents' WTP for carbon labels is influenced by their acceptance of CAP. • We offer some advice on promoting CAP from multiple perspectives. [ABSTRACT FROM AUTHOR]

Atmospheric peroxides, especially hydrogen peroxide (H2O2), are essential oxidants. The peroxide concentration is closely related to the extent of OH radicals and the O3 cycle in the tropospheric atmospheric chemistry. However, only a few studies have investigated their atmospheric concentrations in China because of inadequacies in the measurement techniques or higher costs of analytical instruments. Therefore, it is essential to design a suitable analysis method of peroxides with higher sensitivity, lower detection limit, and low cost. In view of that, this study investigated the optimum analysis conditions of two H2O2 analytical techniques: the high-performance liquid chromatography (HPLC) with fluorescence detection using two-enzyme catalysis of horseradishperoxidase (HRP method) and Hemin (Hemin method). Furthermore, these two analysis methods were systematically compared in terms of detection limit, calibration curve, precision, accuracy, and applicability for the first time. The findings showed that the HRP method had a lower detection limit, higher sensitivity, and better applicability for detecting H2O2 and methyl hydroperoxide (MHP) than the Hemin method. Moreover, the HRP method is better suitable for H2O2 and MHP detection, which requires low detection limits and high sensitivity. Besides this, the Hemin method is inexpensive and is more suitable for detecting hydroxyl alkyl peroxides (C ≥ 3). The atmospheric concentrations (average) of H2O2 and MHP were 0.60 ± 0.37 ppb and 0.081 ± 0.039 ppb, respectively, as determined by the HRP method. Importantly, atmospheric peroxide concentrations were higher on sunny days than on cloudy days in Beijing in September 2016. H2O2 concentrations showed a diurnal variation with the lowest value in the morning and two peaks at 13:00–17:00. In contrast, MHP concentrations were lowest in the morning and highest after 17:00. Photochemical reactions were responsible for the production of H2O2 and MHP. The reactions of O3 and olefins emitted by motor vehicles also caused H2O2 concentration to increase during the evening rush hour. [ABSTRACT FROM AUTHOR]

An emission inventory, involving both air pollutants (APs) and greenhouse gases (GHGs), is needed so that the questions of air pollution and climate change can be co-addressed, coordinated, and collaborated upon. In this study, an emission inventory, including both APs and CO 2 (representing GHGs), was developed for China 2019 using two special measures. First, the framework of air pollution source classification was used for the integrative inventory and then the CO 2 emissions for each sector/subsector/source in the GHG inventory were precisely arranged into the framework of APs by every possible means such as drawing on the constraints from the International Industrial Classification of All Economic Activities (ISIC), which enabled the sharing of common or intrinsically connected activity data for both APs and CO 2. Second, an attempt was made to deduce the activity data of various industrial processes through proper interpretation of the information carried in Pollutant Permits. The calculated emissions of APs and CO 2 were found to be comparable to the results of other studies. Additionally, the average per capita CO 2 and pollution equivalents (PEs) were 10.29 ± 6.75 tons and 11.72 ± 7.35 tons, respectively, over the provincial regions with per capita gross domestic product (GDP) lower than ￥70000 (about $10000). Whereas the average per capita CO 2 and PEs dropped to 6.10 ± 1.83 tons and 6.70 ± 2.09 tons, respectively, over the provincial regions with per capita GDP higher than ￥70000. This somewhat supports the philosophy of the Environmental Kuznets Curve (EKC) regarding the close connection between emission and development. Moreover, the two emission intensities (for APs and CO 2) were found to vary synchronously among the provinces, reflecting the inter-linked fates of the two emissions under the control measures oriented toward either APs or GHGs. [Display omitted] • An emission inventory integrating air pollutants and CO 2 are compiled. • GHG classification framework are used for the integrative inventory with additional constraints from ISIC. • Pollutant-Permit information is employed to derive activity data of industrial processes and links. • The EKC philosophy on emission/development relation is partly supported. [ABSTRACT FROM AUTHOR]