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Monitoring, Modelling and Management of Agricultural Air Pollutants and Greenhouse Gases

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A special issue of Agriculture (ISSN 2077-0472). This special issue belongs to the section "Ecosystem, Environment and Climate Change in Agriculture".

Deadline for manuscript submissions: closed (20 August 2024) | Viewed by 15009

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Special Issue Editors

Prof. Dr. Weiwei Chen

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Guest Editor

Northeast Institute of Geography and Agroecology (IGA), Chinese Academy of Sciences (CAS), Changchun 130102, China
Interests: agricultural air pollution; climate change; emission inventory; simulation modeling; remote sensing of atmospheric environment
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Prof. Dr. Qiuju Xie

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Guest Editor

College of Electrical and Information, Northeast Agricultural University, Harbin 150030, China
Interests: environmental control; environmental quality assessment; machine learning; simulation and modeling; air pollutant concentration monitoring

Prof. Dr. Li Guo

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Guest Editor

College of Biological and Agricultural Engineering, Jilin University, Changchun 130022, China
Interests: agricultural air pollution; monitoring of agricultural environment; mitigation and filtration of agricultural pollutants; remote sensing
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

The rapid development of modern agriculture has provided considerable benefits to the growing population of the world. Meanwhile, agricultural activities have also produced some undesirable environmental consequences, including air pollution and climate change, which are having increasingly deleterious effects on the health of the ecosystem and humans. In order to reduce agriculture-related atmospheric emissions, the utilization of appropriate technologies and methodologies to realistically evaluate the impact of pollution on the atmosphere and suggest options for mitigation may be of use to farmers and policy makers. These feedback mechanisms rely on observed effects, measured pollutant concentrations, and modeling to predict the transport and fate of pollutants and to estimate potential risks.

This Special Issue focuses on the monitoring, modelling and management of the air pollutants and greenhouse gases (GHG) emitted from agricultural activities, including farmland soil management, fertilization, pesticide use, agricultural machinery, residue burning, and animal feeding operations (AFOs). This Special Issue welcomes interdisciplinary studies that are relevant to a range of research fields, including agricultural environment, biology, chemistry and engineering. The published research articles will address a broad range of agricultural atmospheric pollutants and GHGs, from ground monitoring to remote sensing, and from simulation modelling to mitigation technologies. Original research articles, opinions and reviews are welcome.

Prof. Dr. Weiwei Chen
Prof. Dr. Qiuju Xie
Prof. Dr. Li Guo
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Agriculture is an international peer-reviewed open access semimonthly journal published by MDPI.

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Keywords

agricultural residues
life cycle assessment
emissions
nitrogen utilization
environmental impacts
Sustainable Development Goals (SDGs)
environmental control

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Published Papers (8 papers)

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Editorial

Jump to: Research, Review

4 pages, 142 KiB

Open AccessEditorial

Innovative Approaches in Agricultural Sustainability and Environmental Impact Management: Challenges and Opportunities

by Weiwei Chen, Qiuju Xie and Li Guo

Agriculture 2024, 14(12), 2316; https://doi.org/10.3390/agriculture14122316 - 17 Dec 2024

Viewed by 1888

Abstract

The importance of sustainable agricultural practices has gained global recognition over recent decades [...] Full article

(This article belongs to the Special Issue Monitoring, Modelling and Management of Agricultural Air Pollutants and Greenhouse Gases)

Research

Jump to: Editorial, Review

23 pages, 8130 KiB

Open AccessArticle

Prediction of Carbon Dioxide Concentrations in Strawberry Greenhouse by Using Time Series Models

by Seung Hyun Shin, Nibas Chandra Deb, Elanchezhian Arulmozhi, Niraj Tamrakar, Oluwasegun Moses Ogundele, Junghoo Kook, Dae Hyun Kim and Hyeon Tae Kim

Agriculture 2024, 14(11), 1895; https://doi.org/10.3390/agriculture14111895 - 25 Oct 2024

Cited by 2 | Viewed by 1112

Abstract

Carbon dioxide (CO₂) concentrations play an important role in plant production, as they have a direct impact on both plant growth and yield. Therefore, the objectives of this study were to predict CO₂ concentrations in the greenhouse by applying time series models using five datasets. To estimate the CO₂ concentrations, this study was conducted over a four-month period from 1 December 2023 to 31 March 2024, in a strawberry-cultivating greenhouse. Fifteen sensors (MCH-383SD, Lutron, Taiwan) were installed inside the greenhouse to measure CO₂ concentration at 1-min intervals. Finally, the dataset was transformed into intervals of 1, 5, 10, 30, and 60 min. The time-series data were analyzed using the autoregressive integrated moving average (ARIMA) and the Prophet Forecasting Model (PFM), with performance assessed through root mean square error (RMSE), mean absolute error (MAE), and coefficient of determination (R²). The evaluation indicated that the best model performance was achieved with data collected at 1-min intervals, while model performance declined with longer intervals, with the lowest performance observed at 60-min intervals. Specifically, the ARIMA model outperformed across all data collection intervals while comparing with the PFM. The ARIMA model, with data collected at 1-min intervals, achieved an R² of 0.928, RMSE of 7.359, and MAE of 2.832. However, both ARIMA and PFM exhibited poorer performances as the interval of data collection increased, with the lowest performance at 60-min intervals where ARIMA had an R² of 0.762, RMSE of 19.469, and MAE of 11.48. This research underscores the importance of frequent data collection for precise environmental control in greenhouse agriculture, emphasizing the critical role of short-interval data collection for accurate predictive modeling. Full article

(This article belongs to the Special Issue Monitoring, Modelling and Management of Agricultural Air Pollutants and Greenhouse Gases)

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18 pages, 1695 KiB

Open AccessArticle

Carbon Footprint of a Typical Crop–Livestock Dairy Farm in Northeast China

by Yurong Wang, Shule Liu, Qiuju Xie and Zhanyun Ma

Agriculture 2024, 14(10), 1696; https://doi.org/10.3390/agriculture14101696 - 27 Sep 2024

Cited by 3 | Viewed by 1405

Abstract

Dairy farming is one of the most important sources of greenhouse gas (GHG) emissions in the livestock sector. In order to identify the key emission links and the best emission-reduction strategies for combined dairy farms, this study selected a typical large-scale combined dairy farm in northeast China, constructed a carbon emission model based on the lifecycle assessment concept, and set up different emission reduction scenarios to explore the zero-carbon pathway for combined dairy farms. The results showed that: (1) enteric fermentation and manure management of cows are important sources of carbon emissions from the seeding-integrated dairy farms, accounting for 38.2% and 29.4% of the total, respectively; (2) the seeding-integrated system showed a 10.6% reduction in carbon footprint compared with the non-seeding-integrated system; and (3) scenarios 1–4 reduced carbon emissions by 9%, 20%, 42%, and 61% compared with the baseline scenario, respectively. Therefore, the integrated-farming model is important for the green development of animal husbandry, and as the “net-zero” goal cannot be achieved at present, integrated-farming dairy farms have the potential for further emission reduction. The results of this study provide a theoretical basis for low-carbon milk production. Full article

(This article belongs to the Special Issue Monitoring, Modelling and Management of Agricultural Air Pollutants and Greenhouse Gases)

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15 pages, 1489 KiB

Open AccessArticle

Effects of Ageing on Surface Properties of Biochar and Bioavailability of Heavy Metals in Soil

by Zhengwu Cui, Yang Wang, Nan Wang, Fangfang Ma and Yuyu Yuan

Agriculture 2024, 14(9), 1631; https://doi.org/10.3390/agriculture14091631 - 18 Sep 2024

Cited by 3 | Viewed by 1952

Abstract

This study aims to explore the effects of biochar ageing on its surface properties and the bioavailability of heavy metals in soil. The biochar was subjected to chemical oxidation/dry–wet cycles (CDWs), chemical oxidation/freeze–thaw cycles (CFTs), and natural ageing (NT) to analyze changes in the elemental composition, pH, specific surface area, pore volume, and surface functional groups. Fourier transform infrared spectroscopy (FTIR) and scanning electron microscopy (SEM) were applied to characterize the functional groups and microstructure, and the BCR sequential extraction method was employed to demonstrate the fractionation distribution of Cu, Cd, and Pb. The results showed that the CDWs and CFTs treatments significantly reduced the carbon content of the biochar (with a maximum reduction to 47.70%), increased the oxygen content (up to 49.17%), and notably increased the specific surface area and pore volume. The pH decreased significantly from 9.91 to 4.92 and 4.99 for the CDWs and the CFTs, respectively. The FTIR analysis indicated notable changes in hydroxyl and carboxyl functional groups, and the SEM revealed severe microstructural damage in biochar after the CDWs and CFTs treatments. The heavy metal fractionation analysis indicated that exchangeable Cu, Cd, and Pb significantly increased after the CDWs treatment, reaching 31.40%, 5.25%, and 6.79%, respectively. In conclusion, biochar ageing significantly affects its physicochemical properties and increases the bioavailability of heavy metals, raising concerns about its long-term remediation effectiveness. Full article

(This article belongs to the Special Issue Monitoring, Modelling and Management of Agricultural Air Pollutants and Greenhouse Gases)

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16 pages, 2620 KiB

Open AccessArticle

Effect of Climate Change on Identification of Delayed Chilling Damage of Rice in China’s Cold Region

by Lixia Jiang, Junjie Han, Hongtao Cui, Zheng Chu, Shuling Li, Yining Zhang, Yanghui Ji, Qiujing Wang, Xiufen Li and Ping Wang

Agriculture 2024, 14(9), 1456; https://doi.org/10.3390/agriculture14091456 - 25 Aug 2024

Cited by 1 | Viewed by 1251

Abstract

This study analyzed temperature and yield data from 34 meteorological stations in Heilongjiang Province during 1961–2020. Four climate averages (P₁, P₂, P₃, and P₄) were determined based on their respective time distributions (1961–1990, 1971–2000, 1981–2010, and 1991–2020). The national standard temperature anomaly index was used to identify delayed chilling damage in rice cultivation compared to these climate averages. Climate tendency rate analysis, Mann–Kendall detection, and linear regression methods were employed to examine the relationship between temperature anomaly and rice yield from May to September. The results showed that there were noticeable differences in recognizing delayed chilling damage across different climate averages from 1961 to 2020. The average duration of chilling damage under P₁, P₂, P₃, and P₄ was, respectively, estimated as 8.5 years, 13.3 years, 21.4 years, and 30.9 years, with severe cold damage accounting for a significant portion (68.2–76.0%) of the total chilling damage period. The occurrence of severe cold damage increased significantly over time while light and moderate cold damage did not show a clear increasing or decreasing trend. Based on the test results, P₃ was found to be the most suitable climate average for identifying delayed chilling damage in rice cultivation from 1961 to 2020. Moreover, the incidence of chilling damage revealed declining trend over time. There was a high incidence of chilling damage in the 1960s and 1970s, followed by a decrease from the 1980s to the mid 1990s, and finally a low-incidence period after the mid-1990s. Spatially, the western regions experienced greater occurrence of chilling damage than the eastern regions. Additionally, there was a highly significant positive correlation (p < 0.01) between temperature anomalies from May to September and relative meteorological yield of rice. As temperature anomalies decreased during this period, there was an observed downward trend in relative meteorological yield of rice, indicating that delayed cold injury had a negative impact on rice production. Full article

(This article belongs to the Special Issue Monitoring, Modelling and Management of Agricultural Air Pollutants and Greenhouse Gases)

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18 pages, 2711 KiB

Open AccessArticle

Volatile Organic Compound Emission Inventory for Pesticide Spraying in an Agricultural City of Northeast China: Real-Time Monitoring and Method Optimization

by Ruimin Li, Zixuan Xia, Bo You, Bowen Shi and Jing Fu

Agriculture 2024, 14(8), 1223; https://doi.org/10.3390/agriculture14081223 - 25 Jul 2024

Cited by 1 | Viewed by 1473

Abstract

Atmospheric volatile organic compounds (VOCs), such as olefins and aromatics, released from synthetic chemical pesticide sprays can increase regional air pollution, public health risks, and food security risks. However, significant uncertainties remain regarding the measurement methods and chemical profiles of VOC emissions. Using an agricultural city, Changchun City in Northeast China, as a case study, we quantified real-time concentration and composition data based on online monitoring instruments for the year 2023. This study optimized data collection methods for emission factors and activity levels and developed a high-precision emission inventory of VOCs in pesticides at the city scale. The emission factors for VOCs from the seven categories of pesticides were estimated as follows: 78 g/kg (nicosulfuron and atrazine, oil-dispersible [OD] and suspension emulsion [SE], respectively), 4 g/kg (chlorpyrifos and indoxair conditioningarb, suspension concentrate [SC]), 5 g/kg (fluopicolide and propamocarb hydrochloride, SC), 217 g/kg (MCPA-dimethylammonium, aqueous solution [AS]), 34 g/kg (glyphosate, AS), 575 g/kg (beta-cypermethrin and malathion, emulsifiable concentrate [EC]), and 122 g/kg (copper abietate, emulsion in water [EW]), depending on the pesticide formulation components and formulation types. The orchard insecticide exhibited the highest emission factors among all pesticides owing to its emulsifiable concentrate formulation and 80% content of inactive ingredients (both factors contribute to the high content of organic solvents in the pesticide). The major components of VOC emissions from pesticide spraying were halocarbons (27–44%), oxygenated VOCs (OVOCs) (25–38%), and aromatic hydrocarbons (15–28%). The total VOC emissions from pesticide spraying in the Changchun region accounted for 10.6 t, with Yushu City contributing 28% of the VOC emissions and Gongzhuling City and Dehui City contributing 18.7% and 16.0%, respectively. Herbicides were the main contributors to VOC emissions because of their high emission factors and extensive use in fields (used for spraying maize and rice, the main crops in Changchun City). May and June exhibited the highest VOC emissions from pesticide application, with May accounting for 57.0% of annual pesticide emissions, predominantly from herbicides (95.1%), followed by insecticides (4.9%). June accounted for 30.1% of the annual pesticide emissions, with herbicides being the largest contributor of VOC emissions. An emission inventory of VOC with a monthly scale and spatial grid resolutions of 0.083° and 0.5° in 2023 was developed. These emission factors and inventories of pesticide applications provide valuable information for air quality modeling. This study also provides an important scientific basis for enhancing regional air quality and mitigating the environmental impact of pesticide use in major grain-producing areas. Full article

(This article belongs to the Special Issue Monitoring, Modelling and Management of Agricultural Air Pollutants and Greenhouse Gases)

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21 pages, 1309 KiB

Open AccessArticle

The Residue Chemistry Transformation Linked to the Fungi Keystone Taxa during Different Residue Tissues Incorporation into Mollisols in Northeast China

by Qilin Zhang, Xiujun Li, Guoshuang Chen, Nana Luo, Jing Sun, Ezemaduka Anastasia Ngozi and Xinrui Lu

Agriculture 2024, 14(6), 792; https://doi.org/10.3390/agriculture14060792 - 21 May 2024

Cited by 2 | Viewed by 962

Abstract

Managing carbon input from crop straw in cropland ecosystems could increase soil organic carbon (SOC) sequestration to achieve C neutrality and mitigate climate change. The complexity of the chemical structures of crop residue largely affects SOC sequestration. Fungi communities play an important role in the degradation of crop residues. However, the relationship between the fungal community composition and the chemical structures of crop residues remains unclear and requires further investigation. Therefore, a 120-day incubation experiment was conducted in Mollisols in Northeast China to investigate the decomposition processes and dynamics of maize straw stem (ST), leaf (LE) and sheath (SH) residues using ¹³C-NMR spectroscopy. Additionally, the microbiomes associated with these residues were analyzed through high-throughput sequencing to explore their relationship. Our results showed that the alkyl C contents in all treatments exhibited increases ranging from 15.1% to 49.1%, while the O-alkyl C contents decreased, ranging from 0.02% to 11.2%, with the incubation time. The A/OA ratios of ST, LE and SH treatments were increased by 23.7%, 43.4% and 49.3% with incubation time, respectively. During the early stages of straw decomposition, Ascomycota dominated, and in the later stage, Basidiomycota were predominant. The class of Sordariomycetes played a key role in the chemistry transformation of straw tissues during decomposition. The keystone taxa abundances, Fusarium_kyushuense, and Striatibotrys_eucylindrospora, showed strong negative correlations with di-O-alkyl C and carbonyl-C content and positive correlations with the β-glucosidase and peroxidase enzyme activity, respectively. In conclusion, our study demonstrated that the keystone taxa play a significant role in regulating the chemical structures of straw tissues, providing a better understanding of the influence of residue quality on SOC sequestration. Full article

(This article belongs to the Special Issue Monitoring, Modelling and Management of Agricultural Air Pollutants and Greenhouse Gases)

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Review

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25 pages, 1406 KiB

Open AccessReview

An Overview on Bioeconomy in Agricultural Sector, Biomass Production, Recycling Methods, and Circular Economy Considerations

by Ioana-Maria Toplicean and Adina-Daniela Datcu

Agriculture 2024, 14(7), 1143; https://doi.org/10.3390/agriculture14071143 - 15 Jul 2024

Cited by 8 | Viewed by 3688

Abstract

This review examines the essential components of a circular economy (CE) in relation to the agricultural sector. The bioeconomy and circular economy are crucial for sustainable global industrial growth, focusing on closed-loop systems. The sustainability debate centers on intergenerational equity and natural capital. The CE requires new environmental technologies and global coordination in order to combat climate change and biodiversity loss. In addition, efficient food production and waste reduction are essential due to population growth. However, biomass is vital for a bio-based economy, impacting food waste and climate change. Grasslands support sustainable dairy production and carbon sequestration. Thus, effective waste and wastewater management are critical, with biomass energy providing renewable alternatives. Nonetheless, biofuels remain key for sustainability, focusing on pollution control and Green Chemistry. It is well known that sustainable transportation relies on bioenergy, with ongoing research improving processes and discovering new fuels. One notable challenge is managing heavy metals in biofuel production, and this underscores the need for eco-friendly energy solutions. The main purpose for this review paper is to create a connection between circular economy aspects and the agricultural system, with focus on the following: bioeconomy research, biomass utilities, and biofuel production. Extensive research was performed on the specialized literature by putting in common the main problems. Key subjects in this paper include the use of biomass in agriculture, the problems of plastic recycling, and the function of the CE in mitigating climate change and biodiversity loss. Efficient food production and waste minimization are highlighted due to their relevance in a growing population. The study’s detailed research and discussion aim to give important insights into how these practices might promote economic development and sustainability. Furthermore, the study covers important waste management issues such as food waste, plant composting, and chemical waste neutralization. These topics are critical to understanding the circular economy’s broader implications for minimizing environmental damage and implementing sustainable waste management strategies. Full article

(This article belongs to the Special Issue Monitoring, Modelling and Management of Agricultural Air Pollutants and Greenhouse Gases)

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