Field Survey Data Research Articles

Characteristics, impacts and future research directions of Mongolian peatlands

Mongolia is an important peatland distribution area in the world. Over the past few decades, Mongolian peatlands have undergone significant degradation due to climate change and human activities, yet there remains substantial uncertainty about the impacts of Mongolian peatland changes on regional environment and human society. Here, compiling the data of peatland distribution, climate, human activity, as well as the permafrost, we systematically review the distribution, changes, and the ecosystem service values of the Mongolian peatlands in the face of climate warming and intensifying human activities. The current data show that the total area of peatland in the Mongolian is 15500~27000 km2, and most of the peatlands are distributed in permafrost regions, while the accuracies of these maps were not assessed. In addition to climate warming, overgrazing, mining activities, and transportation, we suggest permafrost degradation also poses significant threatens on the peatlands. Although the importance of Mongolian peatlands has been recognized, the ecosystem service values, including water provision, habitat quality, carbon fixation, soil conservation, and wind erosion prevention largely remain unknown. Currently, efforts have been made to protect the Mongolian grassland, but there are no specific measures to combat peatland degradation. To better understand the changes and roles of peatland ecosystems in regulating regional development, we propose three research directions for future studies: 1) produce a detailed map of peatland distribution based on field survey data, new remote sensing data, and new algorithms; 2) Unveil the mechanisms underlying the interaction of peat, vegetation, and permafrost; 3) Evaluate the ecosystem services of Mongolian peatlands. These knowledges are the scientific foundation to propose and implement measures to protect, maintain, and sustainably utilize peatlands in Mongolia.

Urbanization Rapidity and Its Impact on Shuklagandaki Municipality

This study examines the trends and causes of urbanization as well as how they affect Nepal's Shuklagandaki Municipality, which is urbanizing quickly. Using a mixed-methods approach, the study incorporates data from both qualitative and quantitative sources. Quantitative information was gathered from field survey and qualitative data were collected from public reports, census records, and government statistics to examine demographic and economic developments in the municipality during the previous 20 years. Through in-depth interviews with important stakeholders, such as public servants, company owners, and community leaders, qualitative data were acquired. Regression analysis and other descriptive and inferential statistics were used in the data analysis process. The results show that throughout the past 20 years, Shuklagandaki Municipality has had notable increase in both demographic and economic metrics. Urban expansion was primarily driven by population increase and economic development; infrastructural improvements, while significant, were secondary. The necessity for planning and policy initiatives that support sustainable growth while attending to the needs and well-being of present and future inhabitants is highlighted by the difficulties and possibilities brought about by the fast urbanization. The article finishes with a summary of the key results, a discussion of the research limitations, and references for future research topics to fill in the gaps in the body of knowledge and address unresolved issues with urban expansion in Shuklagandaki Municipality.

A Study on Revenue Distribution of Chinese Agricultural E-Commerce Supply Chain Based on the Modified Shapley Value Method

With the rapid development of e-commerce in China, “live broadcast + e-commerce” has become an emerging mode of the e-commerce industry. The speedy growth of the digital economy has also provided a favorable external environment for fresh agricultural products to ride on the e-commerce express train. As a result, more and more suppliers of fresh agricultural products choose to sell their products on e-commerce platforms and conduct live streaming. This paper utilizes the e-commerce supply chain field survey data, takes tomato as the specific analyzed variety, and studies the revenue distribution pattern of each subject in the supply chain. The purpose of this paper is to explore the optimization strategy of the revenue distribution of an agricultural e-commerce supply chain, and the results show that the agricultural e-commerce supply chain effectively promotes the matching of supply and demand of medium- and high-end agricultural products, realizes the quality premium of medium- and high-end agricultural products, and significantly improves the overall revenue level of the supply chain. The field survey found that under the supply chain model of “farmers + cooperatives + e-commerce platform”, farmers, cooperatives, and e-commerce platforms gained $2865, $3098, and $1111, respectively, for operating one mu of tomatoes in a year. According to the traditional Shapley value method, from the point of view of the contribution to the cooperative income, part of the income of the farmers and cooperatives should be compensated to the e-commerce platform, and the specific results are as follows: the income of the farmers should be reduced from $2865 to $2729, the income of the cooperatives should be reduced from $3099 to $2955, and the income of the e-commerce platform should be increased from $1111 to $1390. According to the Shapley value method based on the risk coefficient correction, from the perspective of risk compensation, part of the earnings of the e-commerce platform should be compensated to farmers and cooperatives, so as to establish a more equitable and reasonable pattern of earnings distribution, with the specific results: the earnings of farmers should be increased to $3205, the earnings of cooperatives should be increased to $3148, and the earnings of the e-commerce platform should be reduced to $722.

Spatiotemporal Prediction of Greenhouse Gas Emissions from Rubber Wood Furniture Industry, Taking Hainan as the Case

The rubber wood furniture industry chain, including planting and manufacturing subsystems, emits significant greenhouse gases (GHGs), meanwhile, has huge carbon emission reduction potential. However, quite few studies have taken the whole industry chain GHGs into consideration, especially assessing and modelling those from rubber tree planting to furniture manufacturing. We took the rubber wood furniture of Hainan province as the case, explored its whole life cycle GHGs from cradle-to-gate and predicted the potential GHGs from 2031 to 2062. This study is fully based on field survey and sampling data, including that of the rubber tree planting (40-year cycle) and furniture manufacturing. The results reveal: (1) Whole industry chain of rubber wood furniture emits 3.27×106 kgCO2-eq GHGs per 20,000t rubber logs consuming, where the planting accounts the most (88.20%). Transport and electricity consumption are the main GHGs sources of planting and manufacturing subsystems respectively; (2) The whole life-cycle GHGs of rubber wood furniture in 2023 of Hainan is 2.07×107 kgCO2-eq, which mainly come from Danzhou (24.74%), Haikou (19.55%), and Qiongzhong (15.79%); (3) The total GHGs from the rubber wood furniture industry in Hainan from 2031 to 2062 are 210 MtCO2-eq and 129 MtCO2-eq respectively, without or with felling restriction. The changes of GHGs from 2051 to 2062 are caused by the regional center shift of planting gravity; (4) Improving energy use efficiency and optimizing the location of furniture factories would reduce GHGs. This study can provide empirical support for the low carbon sustainable transformation of the rubber wood furniture industry worldwide.

A Typical of Tsunami Generation Caused by Volcano Flank Collapse in Banda Neira, Maluku, Indonesia

Abstract The history eruption of the Banda volcanoes was recorded in 1632, 1816, and 1988 and was preceded by significant earthquakes. In the eruption in 2017, there were 28 volcanic earthquakes, indicating a rock cracking process due to the movement of magma in the form of gas, liquid, and rock solids. We suspect that when the earthquake occurs, the rock-cracking process upon the eruption will potentially trigger the volcano flank to collapse into the sea and generate a tsunami in the Banda Naira and surrounding area. We contribute to modeling the travel time and tsunami inundation resulting from the flank collapse of Banda Volcano. BATNAS bathymetry data is used to run tsunami simulations. We use aerial photography from field survey data to interpret Banda Volcano failure parameters, including diameter, direction of sliding of the collapse, and slope of the collapse of the side of the Banda Volcano. Based on the tsunami simulation, the volcano flank collapse source on Banda Volcano produced a maximum tsunami in Banda Naira as high as 6.2 meters, and the tsunami will arrive around 6 – 8 minutes. While in AI Island, tsunami inundation reached 55.87 m and arrived in 4 minutes. Meanwhile, the maximum elevation of Banda Naira Island is 3.5 meters, with a population of 21,000 people in March 2024. Tsunami inundation has the potential to submerge entire residential areas in Banda Neira.

Has Cross-City Commuting Promoted Housing Purchases among the Workforce within Metropolitan Areas?—An Empirical Analysis from Micro Survey Data from China’s Three Major Metropolitan Areas

The ability of the cross-city commuting labor force to obtain housing has a profound impact on the development of the housing market and the enhancement of social welfare, but whether cross-city commuting has facilitated housing purchases remains to be verified However, the research on whether cross-city commuting behavior promotes labor force housing purchase in metropolitan areas is still lacking, especially in China, where the culture of buying houses is relatively special. This article used field survey data from the 2023 China Metropolitan Area Occupation and Housing Status Sampling Survey to empirically analyze whether cross-city commuting has facilitated housing purchases within metropolitan areas. The analysis was conducted by constructing a baseline model, a mediation effect model, and a subsample regression model. The results show that the cross-city commuting facilitated housing purchase within metropolitan areas, and the location preference is to purchase a house with a distance of 20–40 km from the workplace, but the contribution of the cross-city commuting to multi-suite purchases is relatively low. Mechanism analysis shows that compared to the workers who work and live in peripheral areas or the workers who work and live in cores, intercity commuters are promoted to purchase housing by relatively higher income and inducement of the housing price gap. The above conclusions still hold after controlling potential endogeneity issues and in robustness tests. The research of this paper can provide a new perspective for alleviating the housing inequality in the metropolitan area.

Analysis of organic matter stock dynamics in arable soils of Yamal: simulation experiments with the ROMUL model

The goal of this work is to analyze the dynamics of soil organic matter (SOM) in arable soils of Yamal using computational experiments with the ROMUL model. Soil temperature and moisture dynamics were simulated using the SCLISS model. The Yamal experimental station was organized in 1932. The soil is Plaggic Podzol. The thickness of humus horizon (PY) is 30 cm. Pools, kg/m2: SOM – 9.32 and 13.75; N – 0.46 and 0.66 for 0–20 and 0–30 cm respectively. Background: soddy-green-moss tundra near Salekhard. Soil: Folic Podzol: litter (O, 2 cm) and humus-accumulative (AY, 4 cm) and illuvial ferruginous (BF, 6 cm) horizons. Pools, kg/m2: SOM – 1.38 and 2.69, N – 0.03 and 0.18 for 0–2 and 2–6 cm respectively. The quantity and quality of background fall was estimated according to literature data. Clarification of the amount of fall was carried out by the method of inverse problem solving (spin-up). Peat application was simulated: starting application in the dose of 12 kg/m2 and maintenance (every 6 years) in doses 4, 8 and 12 kg/m2, N 1%. Application of mineral fertilizers, 2 variants: a) N 4 g/m2 (40 kg/ha) in peatting years and b) application of the same dose of nitrogen every year. The duration of computational experiments is 30 and 90 years. Computational experiments showed that after the starting peatting of Folic Podzol at the rate of 12 kg/m2 after 30 years, only 15% of the applied detritus remained. Maintenance peatting of 8–12 kg/m2 leads to an increase in SOM pool to 20–30 kg/m2 and excessive accumulation of detritus. Application of 4 kg/m2 of peat once every 6 years for 90 years shows the dynamics of SOM pools from Folic Podzol to Plaggic Podzol which is confirmed by field survey data. Application of mineral nitrogen (4 g/m2) once every 6 years does not affect SOM pools. Annual application of mineral N (4 g/m2) increases SOM pools due to intensified humification. This fact requires experimental verification.

Exploring the influence of workplace environment on job performance: a socio-cognitive perspective

This study investigates the evolution of job performance from socio-cognitive and knowledge-based perspectives, focusing on key perceived environmental factors. The research model proposed posits that perceived diversity and procedural justice positively affect job performance through the mediation of job self-efficacy and work engagement. Additionally, knowledge-oriented leadership is examined as a moderator influencing the formation of job self-efficacy and work engagement. Empirical testing of these hypotheses was conducted using field survey data collected from working professionals in a prominent computer and communication firm within the high-tech industry. The findings not only have theoretical and practical implications but also acknowledge certain limitations inherent in the research. Specifically, a limitation of this study is that it surveyed professionals in technology companies, so caution is advised when extending its implications to employees in non-tech sectors.

Principle, structure and application progress of the forest landscape model FireBGCv2.

Forest landscape model can quantitatively simulate the spatiotemporal variations in forest structure and function at the landscape scale based on traditional field survey data and mathematical models, providing a reference for the formulation of scientific forest management strategies. FireBGCv2 is one of the representative models currently used in the research area of forest landscape changes. It can simulate ecological processes at various scales, including trees scale (tree growth, establishment, and mortality), stand scale (carbon and nitrogen pools, fuel treatment, decomposition), site scale (resource competition and species phenology), and landscape scale (seed dispersal and wildfire disturbances), and the effects of those processes on forest landscape structure and function. The advantage of this model lies in its ability to simulate multiple ecological processes while considering the diversity and complexity of ecosystems. However, it also has drawbacks, such as high computational demands and complexity of use. We summarized the basic principles and structure of FireBGCv2 and introduced its application progress in forest landscape research and management. Currently, the application of the FireBGCv2 model, both domestically and internationally, mainly focused on exploring the interactions between fire, climate, and vegetation, quantifying the spatial and temporal dynamics of fires, and describing potential fire dynamics under future climate scenarios and land management strategies. With the in-depth development of forest landscape model theories and applications, the future prospects of FireBGCv2 include improving and updating the model's algorithms, adding new functional modules to explore fire management issues, and meeting the needs of different users.

Impact of Ecological Cognitive Bias on Pesticide Reduction by Natural Rubber Farmers in China: Insight from Price Insurance Satisfaction

Some natural rubber farmers mistakenly equate the ecological functions of rubber plantations with those of primary forests. This cognitive bias can hinder pesticide reduction efforts. Meanwhile, natural rubber farmers gain security through price insurance, which helps them adopt a long-term perspective on environmental protection, mitigating the negative impact of cognitive biases on pesticide use decisions. However, existing research often overlooks the influence of ecological cognitive bias on pesticide reduction and the moderating role of price insurance satisfaction. This study utilizes field survey data from Hainan and employs logit models and double machine learning models to empirically analyze the impact of ecological cognitive bias on pesticide reduction among natural rubber farmers. It further tests the underlying mechanisms using moderation models. The results indicate that (1) ecological cognitive bias negatively affects pesticide reduction among natural rubber farmers, and (2) price insurance satisfaction mitigates the impact of ecological cognitive bias on pesticide reduction. Based on these findings, the government should enhance education and training to raise ecological awareness among natural rubber farmers and reduce ecological cognitive biases. Disseminating knowledge about price insurance and establishing a comprehensive insurance system can secure farmers’ income and promote the rational use of pesticides.

Occurrence of biennial sporophytes of the kelp Saccharina japonica in Hokkaido, Japan

Recent studies suggest that relict communities of Saccharina japonica var. ochotensis are rarely observed in southwestern Hokkaido, where S. japonica. var. religiosa is generally distributed. Previous research has mainly focused on the morphology of these species, and field survey data is very limited. In the present study, relict S. japonica var. ochotensis communities were observed only near the estuaries of larger rivers, specifically in estuarine areas where bedrock is present and the seashore has a gentle gradient slope. The biomass and size (length, width, and weight) of annual and biennial relict S. japonica. var. ochotensis were recorded. The carbon/nitrogen ratio of the kelp sporophytes was analyzed, and relatively lower values were observed in the relict community of this species. This information may help in the maintenance of kelp beds in southwestern Hokkaido and the wise utilization of relict S. japonica var. ochotensis in the estuarine areas of southwestern Hokkaido, Sea of Japan.

How does digital technology application empower specialty agricultural farmers? Evidence from Chinese litchi farmers

IntroductionSpecialty agricultural farmers have widely adopted digital technologies in all aspects of their specialty agricultural operations. However, the effect of digital technology application (DTA) on specialty agricultural farmers’ income has not been fully evaluated. Moreover, it remains unclear whether DTA enhances farmers’ income (FI) by improving their varied capabilities. To fill this gap, we analyzed the intrinsic relationship and mechanism between DTA, farmers’ capability (FC), and specialty agricultural farmers’ income.MethodsUsing field survey data from 635 litchi farmers in China, we employed OLS regression models and mediation effect models to empirically investigate DTA’s direct and indirect impacts on litchi farmers’ income. Additionally, we examined the group heterogeneity and regional heterogeneity.Results and discussionThe empirical results show that DTA can promote specialty agricultural farmers’ income by enhancing their production capacity (PC) and transaction capacity (TC). Heterogeneity analysis showed that the empowering effect of DTA is especially significant for disadvantaged farmers, and farmers who are in specialty agricultural resources-rich regions.ConclusionThis study contributes to the body of research on the empowerment of specialty agricultural farmers by examining the effect of DTA from a capability perspective. Consequently, to better play the empowering effect of DTA for specialty agricultural farmers, policymakers should account for regional disparities in promoting digital agriculture, and enhance heterogeneous farmers’ DTA capability.

Development of a detailed bathymetry map of the Nhat Le estuary, Quang Binh province by remote sensing image treatment

Multispectral remote sensing images with the advantages of low cost, wide area coverage, and increased resolution have been widely used recently for determining the bathymetry of coastal waters. In this study, the correlation equation is developed based on the Landsat 8 OLI satellite images captured on September 22, 2022, and the survey data measured during the time period of September 12–22, 2022, was used for mapping bathymetry in the Nhat Le Estuary area, Quang Binh Province, a relatively clear area from sediment. The correlation between the image and the field survey data is quite good, with R2 = 0.88. This shows that Landsat 8 OLI data is suitable for mapping sea areas with depths up to 20 m.

Are farmers willing to pay for low-carbon agriculture? Evidence from China

PurposeReducing carbon emissions in agriculture is vital for fostering sustainable agricultural growth and promoting ecological well-being in rural areas. The adoption of Low-Carbon Agriculture (LCA) by farmers holds great potential to accomplish substantial reductions in carbon emissions. The purpose of this study is to explore the farmers' preference and willingness to engage in LCA.Design/methodology/approachThis study employs the Choice Experiment (CE) method to examine farmers' preferences and willingness to adopt LCA, using field survey data of 544 rural farmers in the Weihe River Basin between June and July 2023. We further investigate differences in willingness to pay (WTP) and personal characteristics among different farmer categories.FindingsThe empirical results reveal that farmers prioritize government-led initiatives providing pertinent technical training as a key aspect of the LCA program. Farmers' decisions to participate in LCA are influenced by factors including age, gender, education and the proportion of farm income in household income, with their evaluations further shaped by subjective attitudes and habits. Notably, we discovered that nearly half of the farmers exhibit indifference towards LCA attributes.Originality/valueTo the best of the authors' knowledge, this study is the first to investigate farmers' attitudes toward LCA from their own perspectives and to analyze the factors influencing them from both subjective and objective standpoints. This study presents a fresh perspective for advocating LCA, bolstering rural ecology and nurturing sustainable development in developing nations.

Investigation of the Relationship between Topographic and Forest Stand Characteristics Using Aerial Laser Scanning and Field Survey Data

The article thoroughly investigates the relationships between terrain features and tree measurements derived from aerial laser scanning (ALS) data and field surveys in a 1067-hectare forested area. A digital elevation model (DEM) was generated from ALS data, which was then used to derive additional layers such as slope, aspect, topographic position index (TPI), and landforms. The authors developed a mathematical procedure to determine the radii for the topographic position index. The canopy height model was created, and individual trees were segmented using a novel voxel aggregation method, allowing for the calculation of tree height and crown size. Accuracy assessments were conducted between ALS-derived data and field-collected data. Terrain variability within each forest unit was evaluated using characteristics such as standard deviation, entropy, and frequency. The relationships between tree height and the derived topographic features within forest subcompartments, as well as the correlation between the height yield map for the entire area and the TPI layer, were analysed. The authors found strong correlation between the topographic position index and tree heights in both cases. The presented remote-sensing-based methodology and the results can be effectively used in digital forest site mapping, complemented by field sampling and laboratory soil analyses, and, as final goal, in carbon stock assessment.

Seismic risk assessment based on residential building stock and field survey results: a case study of 3 cities in Shanxi Province

IntroductionBuildings that collapse or are damaged by earthquakes are responsible for the majority of earthquake-related casualties. High-precision building data are the key to improving the accuracy of risk assessments of earthquake disaster loss. Many countries and regions have also proposed varying regional building exposure models, but most of these models are still based on administrative-level (city or county) statistical data; furthermore, they cannot accurately reflect the differences among buildings in different towns or villages.MethodsAlthough field investigation-based “township to township” methods can obtain more accurate building inventory data, considering costs and timeliness, remote sensing and other diverse data should be combined to acquire building data. Based on the field survey data of three cities in shanxi Province, combined with Global Human Settlement Layer (GHSL) data, this study is conducted on building inventory data. Data regarding the proportion of each building type and corresponding lethality level in each township are obtained based on the classification of building height, and the overall lethality level at the building level and township level is calculated on this basis.ResultsThe fitting results between the calculated results and the field survey results are good, the error is within 0.15, and the fitting R2 values of Xian, Baoji and Ankang are 0.6552, 0.5788 and 0.5937, respectively. Therefore, an earthquake disaster loss risk assessment is conducted based on the building level.DiscussionThe findings indicate that the risk of casualties caused by the same building type can vary by city. Generally, the areas with high disaster loss risk in the three cities are distributed mainly in urban areas; the disaster loss risk in the newly built areas of each city is relatively low. According to the quantitative assessment results for each city, Xi’an has the highest loss risk, while Baoji and Ankang have the same loss risk. Based on the method constructed in this paper, we can realize the quantitative assessment of earthquake disaster loss risk at the building level to better target pre-earthquake emergency preparation and post-earthquake auxiliary decision-making.

Evaluating the influence of ambient conditions in the cooking space of railway pantry car using selected thermal indices and physiological parameter.

Hot and humid indoor environment of the kitchen affects worker performance. The Indian Railway's pantry car culinary is one of them that cooks food for the on-board passengers, which could be bothered by the hot indoor climate. The current study aimed to identify the indoor working environment of the railway "pantry car" using heat stress indices such as "Universal Thermal Climate Index-UTCI," "Wet-Bulb Globe Temperature-WBGT," "Discomfort Index-DI," "Tropical Summer Index-TSI," "Heat Index-HI," and Heart Rate-HR with clothing insulation. METHODS: The study was performed in 2018 (August-summer season) to collect field survey data on 6 railway pantry cars. Measurements were carried out during peak cooking times such as morning "7 : 00 am", day "11 : 30 am", evening "4 : 00 pm," and night "6 : 30 pm". This study's descriptive and Pearson's correlation analysis was accomplished using SPSS version 2016 software. The analysis results revealed that the average values were for UTCI (37.77±5.26°C), WBGT (30.42±2.28°C), DI (30.05±2.70°C), TSI (33.21±2.90°C), HI (48.53±4.86°C), correspondingly. During analysis, the strongest correlation association was observed between "TSI and DI" (r = 0.985, p < 0.000) and WBGT and TSI (r = 0.958, p < 0.000). A "significant correlation" was found between UTCI and HI (r = 0.637, p < 0.05). While no signification correlation was found between "heat stress indices and physiological parameters (p > 0.05)". In this study, all the heat stress index limit values showed highly harsh working conditions inside the pantry car, which created unfavorable circumstances for the culinarians. Inappropriate "ventilation design" could be a reason for discomfort in the railway pantry car.

Evaluasi Kinerja APILL di Simpang Empat Bundaran Burung Kota Palangka Raya

Burung Roundabout is an important roundabout for mobilizing the activities of people entering and leaving the city of Palangka Raya, with the increase in population and the rise in community activities the density of vehicles also increases significantly every year. Traffic problems can occur if there is a lack of coordination in each arm of the roundabout. The research objective is to know the performance of Weaving Area and the performance of APILL at Burung Roundabout. The obtained data consists of quantitative data from field survey data. The data is analyzed using Indonesian Road Capacity Manual (MKJI, 1997). The research result using the calculations from (MKJI, 1997) for the Weaving Area section show that the maximum Capacity (C) obtained is 11,125 smp/h at the DA section. The average traffic delay at the roundabout is 0,77 second/smp with the highest delay index (DS) is 0,22 at the CD section. Consequently the service level during peak hours is classified as grade A. The analysis of APILL at Burung roundabout has good traffic flow result. The highest capacity on the southern arm is 1566 smp/hour and the highest delay is 21 second/smp. The highest queue length is 22 meters on the Southern with a highest saturation degree of 0,44 on the Southern with indicates level of service index C.

Kajian Ruang Terbuka Biru Guna Menunjang Optimasi Ecosytem Services (Lokasi Kota Bandar Lampung)

One of the methods to maintain the balance of the perkotaan environment is to maintain its blue open space. There have been a lot of research on Green Open Space, but not on Blue Open Space (BOS). However, BOS also has a very important function and moreover, the ecosystem services provided by BOS can give positive implications. This research is aims to identify the existing BOS area in Bandar Lampung City. The data used in this research are Sentinel-2 satellite images for the extraction of BOS using AWEI on the Google Earth Engine platform, administrative data for the study area, field survey data for validation of the extraction results, Google Earth images for the delineation of existing BOS objects, and river stream data for the river objects of BOS. The methods used for obtaining BOS objects are machine learning-based supervised classification on Google Earth Engine, delineation, buffering, and overlay. The results of the identification of existing RTB in Bandar Lampung city are 206,01 ha consisting of embung/reservoirs, lakes, and rivers.

Does Scaling Up Pig Farming Promote Carbon Neutrality Among Pig Farmers?

Pig farming is a major source of carbon emissions in China's livestock industry, and the promotion and application of carbon neutral technologies dedicated to carbon reduction and sequestration is a key measure to promote the realization of carbon neutrality in pig farming industry. In the absence of a system for carbon emission reduction in agriculture, it is important to explore whether large-scale pig farming can spontaneously promote the application of carbon neutral technologies by pig farmers. Combined with the technical background of carbon neutrality in pig farming industry and using the field survey data of 468 pig farmers in Shandong Province, this paper empirically analyzed the effect of large-scale pig farming on the carbon neutral behavior of pig farmers. The findings are threefold. Firstly, because of the effect of economies of scale in the application of carbon neutral technologies, large-scale pig farming can promote the carbon neutral behavior of pig farmers. However, the effect of economies of scale in the application of carbon neutral technologies has a boundary, and the annual output of pigs should be maintained at 3000 to 4999. Secondly, among the effects of pig breeding scale on the application and its degree of composting project, state of planting and breeding cycle has no regulating effect. Thirdly, among the effects of pig breeding scale on the application and its degree of biogas engineering, both state of planting and breeding cycle and subsidy for construction of biogas digester have negative regulating effects. In this paper, the pig farming industry is taken as a typical example to reveal the endogenous incentive mechanism of promoting agricultural carbon emission reduction, which provides theoretical reference and experience enlightenment for the formulation of effective policies to promote agricultural carbon neutrality, which are different from industrial industries.