Environmental Research Communications最新文献

{"title":"Do private firms invest more in environmental protection under political control? Evidence from China","authors":"Chu-Yu Guo, Jiandong Wen, Hui Hu","doi":"10.1088/2515-7620/ad294b","DOIUrl":"https://doi.org/10.1088/2515-7620/ad294b","url":null,"abstract":"\u0000 For the first time, this study investigates the environmental performance outcomes of integrating local political committees into private firms. Using a nationwide survey of Chinese private firms, we find that the involvement of local party committees significantly bolsters corporate environmental investment. This finding remains consistent across various samples, alternative measures of the dependent variable, and different estimation methodologies. Notably, the influence of local party committees on pro-environmental practices is more pronounced in firms with lower family ownership, in regions with weaker environmental regulations, and where the owner is also the Party secretary. This study reveals local party committees as key mediators between government and firms, enhancing corporate engagement in environmental initiatives. It advocates for policies promoting collaboration between government and private firms, particularly emphasizing the strategic placement of party committees in firms with specific ownership and leadership characteristics to maximize environmental investment.","PeriodicalId":505267,"journal":{"name":"Environmental Research Communications","volume":"12 2","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-02-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139838492","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Modeling the Intention and Usage of Organic Pesticide Control using Value-Belief-Norm Model","authors":"Qing Yang, Abdullah Al Mamun, Mohammad Nurul Hassan Reza, Farzana Naznen, M. M. Masud","doi":"10.1088/2515-7620/ad294a","DOIUrl":"https://doi.org/10.1088/2515-7620/ad294a","url":null,"abstract":"\u0000 The degradation of farming lands caused by excessive pesticide usage is a growing concern. One of the most effective strategies for preventing this disaster from worsening is to commence organic pesticide management at a mass level. Although farmers depend highly on synthetic pesticides and fertilizers to obtain higher yields and profitable returns, the adoption of these synthetic inputs have remained surprisingly low in many agricultural contexts, spanning both developing and developed countries. The goal of this study is to utilize the Value-Belief-Norm (VBN) theory as a framework for understanding the critical sociopsychological factors influencing farmers’ decision to use organic pesticides. Specifically, this study aims to introduce and assess the impact of a new construct, i.e., the social norm withing the VBN framework. Additionally, this study empirically evaluates the core components of VBN theory and their causal relationship. The data was collected from 322 farmers from Zhoukou, Henan province, China using a survey questionnaire. The findings show that farmers' egoistic values significantly impact the ecological worldview, despite the fact that biospheric values had no discernible effect. The ecological worldview also profoundly influences the farmers' awareness of consequences and their personal norms. Although the study finds awareness of consequences to have no significant effect on personal norms, it has a substantial positive impact on ascription of responsibility. In addition, ascription of responsibility significantly influences farmers' personal norms, which substantially impacts the intention to use organic pesticides. The results also reveal that farmers' intentions significantly impact the usage of organic pesticides. The study's findings can help strengthen essential factors among farmers that can improve their perception of organic agricultural methods, create strategies for managing controlled agrochemicals, and successfully stop environmental degradation by toxic inputs.","PeriodicalId":505267,"journal":{"name":"Environmental Research Communications","volume":"41 3","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-02-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139778175","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Effect of spermidine on reproductive, seed quality and bio-physiological characteristics of chickpea (Cicer arietinum L.) genotypes under salt stress","authors":"M. Sawariya, N. Yadav, A. Kumar, H. Mehra, N Kumar, S. Devi, S. Arya","doi":"10.1088/2515-7620/ad2948","DOIUrl":"https://doi.org/10.1088/2515-7620/ad2948","url":null,"abstract":"\u0000 The experiment was conducted to study the effect of foliar application of spermidine on various aspects of chickpea genotypes under salt stress. At the seedling stage the genotypes were treated with 4 and 8 dSm-1 Cl- dominated salinity followed by the spermidine application of 0.5 and 1.0 mM at the flowering stage. Salinity changed the different parameters of chickpea genotypes. The salinity had not much significant effect on the ovule receptivity in different chickpea genotypes studied. Results showed that both concentration of spermidine increased the CSI, MSI, antioxidant activity, and phenol in chickpea under salt stress. In addition it increases the protein and reduced the starch and phosphorus content in chickpea seeds. The application of spermidine increased the pollen germination, viability and tube length in all chickpea genotypes. It reduced the Na+ ion accumulation and maintains the ionic balance in chickpea seeds. The effect of spermidine application (0.5 and 1.0mM) was more obvious but 1.0mM had more positive effect in salt sensitive chickpea genotype.","PeriodicalId":505267,"journal":{"name":"Environmental Research Communications","volume":"49 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-02-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139838585","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Do perception factors affect adaptation behaviours against air pollution among vulnerable occupation groups? Evidence from Chittagong and Dehradun.","authors":"Sugat B Bajracharya, Amina Maharjan, Nidhi Singh, Nandini Sanyal, Vishal Singh, Tawhidul Sheikh Islam","doi":"10.1088/2515-7620/ad2874","DOIUrl":"https://doi.org/10.1088/2515-7620/ad2874","url":null,"abstract":"\u0000 Air pollution is a key environmental issue affecting the urban population in the urban cities of Hindu Kush Himalaya (HKH) countries. It is particularly detrimental to marginalized occupation groups like street vendors, labourers and drivers who work outdoors for their livelihood. There are mitigation strategies to reduce the brunt of air pollution that work in the long run. However, these strategies will need time to implement and operationalize. Adaptation behaviours and measures, in this context, are urgently required and become vital to cope with the impacts of air pollution exposure especially for highly exposed informal workers who have very little means of avoiding it. Adaptation behaviour is very complex and depends on socioeconomic and psychological factors. In this paper, we assess the impact of psychological factors like perception and motivation on the adaptive behaviour of the informal workers using Protection Motivation Theory (PMT). Our findings from Dehradun show that concern behaviour towards air pollution was strongly affected by motivation and perception factors. Adaptive behaviour in the form of both concern behavior and the extent of use of additional protective measures is dependent on how the risks of air pollution and related adaptation measures are perceived by the workers. In addition to this, certain adaptation behaviours like changing or adjusting the daily normal behaviour to avoid air pollution exposure are not feasible as they have direct implications on daily wage earnings.","PeriodicalId":505267,"journal":{"name":"Environmental Research Communications","volume":"60 5","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-02-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139843420","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Do perception factors affect adaptation behaviours against air pollution among vulnerable occupation groups? Evidence from Chittagong and Dehradun.","authors":"Sugat B Bajracharya, Amina Maharjan, Nidhi Singh, Nandini Sanyal, Vishal Singh, Tawhidul Sheikh Islam","doi":"10.1088/2515-7620/ad2874","DOIUrl":"https://doi.org/10.1088/2515-7620/ad2874","url":null,"abstract":"\u0000 Air pollution is a key environmental issue affecting the urban population in the urban cities of Hindu Kush Himalaya (HKH) countries. It is particularly detrimental to marginalized occupation groups like street vendors, labourers and drivers who work outdoors for their livelihood. There are mitigation strategies to reduce the brunt of air pollution that work in the long run. However, these strategies will need time to implement and operationalize. Adaptation behaviours and measures, in this context, are urgently required and become vital to cope with the impacts of air pollution exposure especially for highly exposed informal workers who have very little means of avoiding it. Adaptation behaviour is very complex and depends on socioeconomic and psychological factors. In this paper, we assess the impact of psychological factors like perception and motivation on the adaptive behaviour of the informal workers using Protection Motivation Theory (PMT). Our findings from Dehradun show that concern behaviour towards air pollution was strongly affected by motivation and perception factors. Adaptive behaviour in the form of both concern behavior and the extent of use of additional protective measures is dependent on how the risks of air pollution and related adaptation measures are perceived by the workers. In addition to this, certain adaptation behaviours like changing or adjusting the daily normal behaviour to avoid air pollution exposure are not feasible as they have direct implications on daily wage earnings.","PeriodicalId":505267,"journal":{"name":"Environmental Research Communications","volume":"83 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-02-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139783605","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Impact of Large Kernel Size on Yield Prediction: A Case Study of Corn Yield Prediction with SEDLA in the U.S. Corn Belt","authors":"A. S. Terliksiz, D. Turgay Altilar","doi":"10.1088/2515-7620/ad27fa","DOIUrl":"https://doi.org/10.1088/2515-7620/ad27fa","url":null,"abstract":"\u0000 Predicting agricultural yields is imperative for effective planning to sustain the growing global population. Traditionally, regression-based, simulation-based, and hybrid methods were employed for yield prediction. In recent times, there has been a notable shift towards the adoption of Machine Learning (ML) methods, with Deep Learning (DL), particularly Convolutional Neural Networks (CNNs) and Long-Short Term Memory (LSTM) networks, emerging as popular choices for their enhanced predictive accuracy. This research introduces a cost-effective DL architecture tailored for corn yield prediction, considering computational efficiency in processing time, data size, and NN architecture complexity. The proposed architecture, named SEDLA (Simple and Efficient Deep Learning Architecture), leverages the spatial and temporal learning capabilities of CNNs and LSTMs, respectively, with a unique emphasis on exploring the impact of kernel size in CNNs. Simultaneously, the study aims to exclusively employ satellite and yield data, strategically minimizing input variables to enhance the model's simplicity and efficiency. Notably, the study demonstrates that employing larger kernel sizes in CNNs, especially when processing histogram-based Surface Reflectance (SR) and Land Surface Temperature (LST) data from Moderate Resolution Imaging Spectroradiometer (MODIS), allows for a reduction in the number of hidden layers. The efficacy of the architecture was evaluated through extensive testing on corn yield prediction across 13 states in the United States (U.S.) Corn Belt at county-level. The experimental results showcase the superiority of the proposed architecture, achieving a Mean Absolute Percentage Error (MAPE) of 6.71 and Root Mean Square Error (RMSE) of 14.34, utilizing a single-layer CNN with a 15x15 kernel in conjunction with LSTM. These outcomes surpass existing benchmarks in the literature, affirming the efficacy and potential of the suggested DL framework for accurate and efficient crop yield predictions.","PeriodicalId":505267,"journal":{"name":"Environmental Research Communications","volume":" 24","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-02-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139788311","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Impact of Large Kernel Size on Yield Prediction: A Case Study of Corn Yield Prediction with SEDLA in the U.S. Corn Belt","authors":"A. S. Terliksiz, D. Turgay Altilar","doi":"10.1088/2515-7620/ad27fa","DOIUrl":"https://doi.org/10.1088/2515-7620/ad27fa","url":null,"abstract":"\u0000 Predicting agricultural yields is imperative for effective planning to sustain the growing global population. Traditionally, regression-based, simulation-based, and hybrid methods were employed for yield prediction. In recent times, there has been a notable shift towards the adoption of Machine Learning (ML) methods, with Deep Learning (DL), particularly Convolutional Neural Networks (CNNs) and Long-Short Term Memory (LSTM) networks, emerging as popular choices for their enhanced predictive accuracy. This research introduces a cost-effective DL architecture tailored for corn yield prediction, considering computational efficiency in processing time, data size, and NN architecture complexity. The proposed architecture, named SEDLA (Simple and Efficient Deep Learning Architecture), leverages the spatial and temporal learning capabilities of CNNs and LSTMs, respectively, with a unique emphasis on exploring the impact of kernel size in CNNs. Simultaneously, the study aims to exclusively employ satellite and yield data, strategically minimizing input variables to enhance the model's simplicity and efficiency. Notably, the study demonstrates that employing larger kernel sizes in CNNs, especially when processing histogram-based Surface Reflectance (SR) and Land Surface Temperature (LST) data from Moderate Resolution Imaging Spectroradiometer (MODIS), allows for a reduction in the number of hidden layers. The efficacy of the architecture was evaluated through extensive testing on corn yield prediction across 13 states in the United States (U.S.) Corn Belt at county-level. The experimental results showcase the superiority of the proposed architecture, achieving a Mean Absolute Percentage Error (MAPE) of 6.71 and Root Mean Square Error (RMSE) of 14.34, utilizing a single-layer CNN with a 15x15 kernel in conjunction with LSTM. These outcomes surpass existing benchmarks in the literature, affirming the efficacy and potential of the suggested DL framework for accurate and efficient crop yield predictions.","PeriodicalId":505267,"journal":{"name":"Environmental Research Communications","volume":"399 5","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-02-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139848015","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Prediction of suitable areas and division of key monitoring zones for Solidago canadensis in Guizhou Province, China","authors":"Qingqing Zhang, Jiaguo Wang, Yan Sun, Jiawei Wu, Mengqian Long, Chong Luo, Weijie Li","doi":"10.1088/2515-7620/ad277d","DOIUrl":"https://doi.org/10.1088/2515-7620/ad277d","url":null,"abstract":"\u0000 Comprehending invasive alien species’ potential habitat area and spread trend are of great importance for effective prevention and control strategy and prevention of spread. However, previous studies have mainly been based on large regional scales (national or global level). Research on the smaller regional scale of ecologically fragile karst makes the prevention and control measures more feasible and targeted. For invasive Solidago canadensis, based on an MaxEnt model and ArcGIS, we determined its current and future potential distributions. The main drivers of S. canadensis distribution were precipitation changes and human activities. S. canadensis occurrence probability initially increased, and then decreased with increased precipitation variables, and increased rapidly initially, then gradually with increasing human footprint. Under current climate conditions, S. canadensis suitable area is 8.13×104 km2, with the highly suitable area concentrated in Guiyang, east of Bijie, Zunyi, Anshun and Duyun. Under climate conditions of the 2050s, the suitable area drops slightly to 8.00×104 km2. Under climate conditions of the 2070s, the suitable area expands to 8.31×104 km2. And move toward the south within the study area. Based on the modelling and space optimization software ZONATION key monitoring area covers 79,857 km2, including a primary monitoring area mainly distributed in Guiyang, east of Bijie, northeast of Anshun and northwest of Duyun, a secondary monitoring area mainly outside the primary monitoring area, and a third-level monitoring area widely distributed in Zunyi, Tongren, Duyun, west of Kaili and Anshun and east of Bijie. Linking our results with this specie’s invasive power, we thus recommended to increase the prevention and control sites in the first-level monitoring area, and continue to pay attention to the risk of the southward spread of this species.","PeriodicalId":505267,"journal":{"name":"Environmental Research Communications","volume":"7 2","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-02-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139854452","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Prediction of suitable areas and division of key monitoring zones for Solidago canadensis in Guizhou Province, China","authors":"Qingqing Zhang, Jiaguo Wang, Yan Sun, Jiawei Wu, Mengqian Long, Chong Luo, Weijie Li","doi":"10.1088/2515-7620/ad277d","DOIUrl":"https://doi.org/10.1088/2515-7620/ad277d","url":null,"abstract":"\u0000 Comprehending invasive alien species’ potential habitat area and spread trend are of great importance for effective prevention and control strategy and prevention of spread. However, previous studies have mainly been based on large regional scales (national or global level). Research on the smaller regional scale of ecologically fragile karst makes the prevention and control measures more feasible and targeted. For invasive Solidago canadensis, based on an MaxEnt model and ArcGIS, we determined its current and future potential distributions. The main drivers of S. canadensis distribution were precipitation changes and human activities. S. canadensis occurrence probability initially increased, and then decreased with increased precipitation variables, and increased rapidly initially, then gradually with increasing human footprint. Under current climate conditions, S. canadensis suitable area is 8.13×104 km2, with the highly suitable area concentrated in Guiyang, east of Bijie, Zunyi, Anshun and Duyun. Under climate conditions of the 2050s, the suitable area drops slightly to 8.00×104 km2. Under climate conditions of the 2070s, the suitable area expands to 8.31×104 km2. And move toward the south within the study area. Based on the modelling and space optimization software ZONATION key monitoring area covers 79,857 km2, including a primary monitoring area mainly distributed in Guiyang, east of Bijie, northeast of Anshun and northwest of Duyun, a secondary monitoring area mainly outside the primary monitoring area, and a third-level monitoring area widely distributed in Zunyi, Tongren, Duyun, west of Kaili and Anshun and east of Bijie. Linking our results with this specie’s invasive power, we thus recommended to increase the prevention and control sites in the first-level monitoring area, and continue to pay attention to the risk of the southward spread of this species.","PeriodicalId":505267,"journal":{"name":"Environmental Research Communications","volume":"46 S220","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-02-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139794580","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Assessing Light Performance of Vertical Greenery Shading in Tropical Climate","authors":"Luciana Kristanto, S. Ekasiwi, Asri Dinapradipta","doi":"10.1088/2515-7620/ad277b","DOIUrl":"https://doi.org/10.1088/2515-7620/ad277b","url":null,"abstract":"\u0000 In tropical climate, natural light is abundant and advantageous for incorporating daylighting into building designs. However, this daylight intensity often leads to excessive brightness indoors, specifically in high-rise buildings with glass façades. In addressing sustainability concerns, incorporating greenery outside glass façades can serve as effective sun-shading, and alleviate eyestrain for building occupants. Therefore, this study aimed to investigate the effectiveness of plant leaves in reducing the high light intensity on glass facades. To achieve this, an experiment was conducted using the Vernonia elliptica plant, a plant known to thrive in medium to high sunlight in tropical climates. Three different leaf area indexes (LAI) were examined in this study as the independent variables, while light illuminance and luminance served as the dependent variables. To experiment, two identical box models measuring 1m x 1m x 1m were utilized. The two models were orientated towards the West and North, representing intense and longer light exposure. The first, which is the base case, featured a glass façade without any other additional element, whereas the other incorporated greenery on its glass façade. The obtained results indicated that the impact of leaf density on illuminance and luminance is significant, specifically when the LAI was doubled. It was also found that denser foliage with longer strands of leaves produced better results, specifically at low altitudes. These results can be used for the implementation of vertical greenery shading in real high-rise office buildings.","PeriodicalId":505267,"journal":{"name":"Environmental Research Communications","volume":"32 6","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-02-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139853278","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}