Development of LCA-Multidimensional Map (LAMP): A Platform to Support Information Sharing and Formulate CO₂-Level-Reduction Plans toward Zero Emissions

Abstract

We propose a platform called “LCA-Multidimensional Map (LAMP)” to support companies and individuals aiming for CO₂ zero emissions (CZEs) by efficiently conducting life cycle assessments (LCAs) of their products and activities, collecting information necessary for CZEs, and developing CO₂ reduction plans. LAMP is a multidimensional platform that supports the development of CZEs targets in cyberspace without temporal or spatial constraints. Using this software, LCAs can be conducted using existing database groups constructed in two and three dimensions in various sectors as well as data groups with temporal information, such as evolving and continuous records, and spatial information in a cross-sectional manner. Furthermore, based on the LCA results, CO₂-emission-reduction plans can be formulated (extraction of alternatives), and their effectiveness can be confirmed through LCA again. As an example of how to use LAMP, we introduce the characteristics of LCA in horticulture, the second-largest source of CO₂ emissions after livestock in the agricultural sector, along with examples of alternative plans for greenhouses, collaboration plans with other sectors, and basic methods for promoting CZEs in horticulture. Although this concept needs to be tested and validated in the future, it might encourage individuals or companies to cooperate in LAMP development or inspire them to advocate for more progressive ideas.

1. Introduction

All human activities across various sectors, including manufacturing, commerce, agriculture, forestry, fisheries, food, distribution, construction, healthcare, and education, are accompanied by greenhouse gas emissions (hereafter referred to as CO₂ emissions). In recent years, countries worldwide have been required to reduce their CO₂ emissions to curb the rapid progression of global warming, compelling societies to rapidly review their corporate and individual activities [1,2]. Along with Sustainable Development Goals (SDGs) [3] and environmental, social, and governance goals, the terms carbon neutral and CO₂ zero emissions (CZE) have been coined. Although CZEs can be achieved using various methods, many individuals and organizations may require a starting point or lack the financial, material, and human resources necessary to overcome the challenges faced in achieving CZEs.

For example, upon evaluating the methods and efforts related to greenhouse horticulture toward CZEs as a model, we determined that the amount of CO₂ generated from combustion-type heating can be directly calculated based on fuel consumption and running time. However, the CO₂ generated during the production and transportation of related equipment and devices cannot be ascertained by users. Similarly, although the CO₂ emitted by cars can be estimated based on the gasoline and battery consumption, estimating the CO₂ generated during the production of the vast number of car parts and their transportation is difficult. Moreover, collecting information to conduct a life cycle assessment (LCA) for the production and distribution of a car requires an enormous amount of time and energy. In a society with complex relationships among materials, resources, energy, people, the environment, and information, achieving CZEs within a short period of time is technically impossible. Nevertheless, companies and individuals must strive to achieve CZEs in their respective positions and to the extent they are able to.

Here, we propose the concept of the “LCA-Multidimensional Map (LAMP)”, a platform to support companies and individuals aiming for CZEs by rapidly conducting LCAs for target products and activities, collecting information necessary for CZEs (see Section 3.1), and formulating CO₂ reduction plans (see Section 3.4). In addition, as an example of how to use LAMP, we introduce its potential use in horticulture (see Section 4), which is the second-largest source of CO₂ emissions after livestock in the agricultural sector.

2. Current LCA Software and Databases Used in Different Sectors

2.1. LCA Software

Over the past 20 years, several LCA calculation tools, i.e., SimaPro (Pre’s) and GaBi (sphera’s), as the worldwide main LCA tools, have been developed and have continued to evolve [4,5,6]. Recently, the databases necessary for LCA calculations have been increasingly referenced, information has been shared among multiple countries, and user-friendly software development has improved operability. In 2010, the MiLCA (Miruka) software developed by the Japan Environmental Management Association for Industry was released in Japan (https://www.milca-milca.net/english/index.php (accessed on 6 November 2023)) [7,8]. This software (MiLCA Ver. 2.3.1.4) is equipped with over 3800 entries of the world’s largest inventory database, IDEA (Ver. 3.3) (https://riss.aist.go.jp/en-idealab/ (accessed on 6 November 2023)), which were collected by the National Institute of Advanced Industrial Science and Technology and the Japan Environmental Management Association for Industry, and is designed to visually support LCA. In addition, user companies can register their collected data, general data created by industrial associations, and data created through research on public servers, which can then be used as an interface for mutual use.

The MiLCA software is comprehensive and contains data for all industrial sectors. In particular, it contains considerable information for the industrial and energy sectors because of the high number of users compared to other sectors. However, in sectors with limited examples of LCA and few users, collecting more information to equip the relevant databases is necessary. As a common issue with any LCA software, it is essential to provide diverse information from many sectors in conducting highly accurate LCA and formulating effective CO₂ reduction plans. In the agricultural sector, as an example, diverse information is required because the cultivation equipment, crops, cultivars, cropping seasons, facilities, and climate zones of production areas differ among individual producers.

2.2. Databases Used in Different Sectors

To help visualize the specific structure and use of LAMP, we first introduce the Kyoto Encyclopedia of Genes and Genomes (KEGG) database (https://www.kegg.jp/kegg/ (accessed on 6 November 2023)) that was developed by Kyoto University and Prof. Kanehisa’s Laboratory in 1995 [9,10]. The KEGG database integrates information on genes, proteins (genome information), and compounds (chemical information), drugs and diseases (health information) with knowledge of interactions, reactions, and relationship networks among molecules (system information). It provides information on metabolic pathways, related enzymes, and related genes of major compounds biosynthesized by organisms, such as microbes, plants, animals and human in the form of manually drawn pathway maps (Figure 1 and Figure 2). Over 200,000 secondary metabolites are biosynthesized by plants, some of which have physiological activity and functionality for humans, animals, and plants and are used in foods, pharmaceuticals, and industrial materials. However, a vast number of compounds whose functions are yet to be elucidated are not included in the database. The KEGG database is expanded monthly as analytical techniques and research progress, along with the development of software that facilitates cross-sectional data use. In addition, with the expansion of the information base, the number of research and development cases utilizing plant material production and biosynthetic capabilities [11,12] is expected to increase further.

To achieve highly accurate LCA, it is necessary to use appropriate values from highly accurate databases. Therefore, the link with many other multiple or large-scale databases such as KEGG is necessary to collect and utilize vast amounts of information. LCA requires a desirable platform that can be used across multiple databases to facilitate the search for the desired information, obtain related information as required, and visually display resources and energy flows. Thus, the development of such a platform is expected.

3. Outline of LAMP

LAMP is a multidimensional platform that implements (1) information collection (see Section 3.1), (2) LCA analysis, and (3) listing of the candidates of CO₂ reduction plans (see Section 3.4) by targeting the CZEs in cyberspace (Figure 3 and Figure 4). Therefore, LAMP is constructed with several core software (see Section 3.2). With the assistance of the software, LCA can be conducted using existing database groups constructed in two and three dimensions (3D) in various sectors as well as data groups with temporal information (evolving and continuous records) and spatial information in a cross-sectional manner. Furthermore, based on the LCA results, CO₂ reduction plans can be formulated (extraction of alternatives), and their effectiveness can be confirmed through the reanalysis of LCA with/without the simulations of the environment, products, and performances changed by alternatives. The system is called “Multidimensional Map” because it has no temporal or spatial constraints. Information on people and resources in different industries and sectors can be shared visually in the form of a map that can be expanded and viewed.

3.1. Databases Linked to LAMP

LAMP must be linked to various databases, statistics, papers, articles, images, and audio information to collect information and ensure that LCAs and CO₂ reduction proposals targeting CZEs can be accurately developed in each sector (

Table 1. Example of a database linked to LAMP.

Database	Examples
LCA	Software and data (MiLCA based on IDEA, SimaPro).
Statistical data published for each country	Import/export, resources, production/consumption, population, and economic balance.
Compound information	Contained organisms, manufacturing methods, new or alternative compounds, and expansion of use.
Genetics and its related information	Morphology, traits, metabolism, genetic background, conditions for recombination and editing, and external and internal responses to the environment.
Natural and artificial material	Manufacturing methods, identification of new or alternative materials, and expansion of use.
Energy and resource	Natural/renewable energy, fuel oil, electricity, water, and minerals (e.g., new or alternative materials and impact assessment).
Production/utilization of resources for agriculture/simulation	Climate zones, production methods, crop-specific LCA, and environmental assessment.
Environmental information	Energy balance in the agriculture/building sector, production volume, and extreme weather damage forecast.
Processing and distribution of crops and other manufacturing	Labor of harvest, packaging, distribution, and consumption.
Consumption	Food loss from each process, sector, market, sales, and preservation methods and techniques.
Research organization or researcher	Human links, expanded professional knowledge, research proposals, and avoidance of duplication.
AI/Machine learning software	Determine optimal LCA conditions and accelerate data acquisition/analysis.
Medical information	Begin new or alternative technologies, drug information, medical waste, sanitation, and staffing.
Educational information	LCA/IT education, learning material development, distance and international and recurrent education, and cooperation.
Administration/services	Staffing, budget planning, LCA-related projects, support, and urban planning.

), for example, databases in the LCA software (SimaPro, GaBi, MiLCA, etc.) or actual measurement data owned by the user that can be used to effectively conduct a current LCA on the production process and logistics of a product or production. However, when examining alternative materials, genetic resources, and production methods that lead to CO₂ reduction for production processes and logistics based on LCA results, numerous databases that have not been previously used for LCA, such as material databases from other sectors, genetic and phenotypic information, and technical reports, are necessary.

3.2. Core Software to Be Developed and Installed in LAMP

In addition to the core software of LCA, LAMP collects information on alternative materials and methods, uses databases from other sectors, and performs LCA simulations using alternative proposals. This allows, for the first time, the determination of effective CO₂ reduction methods and the prioritization of feasible alternatives. Therefore, software that can reference and share information from numerous databases in various formats and languages must be developed. Specifically, the following conventional software and new developments are required. When new software is needed, it is expected that users may outsource development to a vendor or may cooperate with each other. Regardless of the method of development of the software, it is expected that it will be included as part of LAMP and shared by many more users.

Developing software that can obtain, integrate, and use the information required for LCA across multiple existing databases and statistical data from various sectors such as industry, agriculture, commerce, medicine, and education is necessary. In the absence of appropriate databases and information, the speed and accuracy of LCA for other users can be increased by adding and releasing information obtained from trial calculations and actual measurements by one user as needed.

In horticulture, core software is required to perform LCA on the greenhouse gases (CO₂ equivalent) emitted by hardware and software for cultivation, labor, transportation processes, and services. Although specialized LCA software such as MiLCA is effective for this purpose, LCA accuracy can be improved by incorporating simulation models used in various sectors such as “heat and light environment simulation models” used in the construction sector, “plant growth models” used in the horticulture or crop science sector, and “impact and damage models” used in the transportation process of products. Following LCA analysis, energy and resources emitted or absorbed from the target are converted to CO₂, and items in the cultivation and transportation process with significant contributions to CZEs are extracted.

In addition, LCA analysis can be conducted using alternative products and technological proposals to substitute existing or new materials and methods, making full use of database groups and diverse information. Based on the costs and revenues, the candidate alternatives are specified under feasible conditions and ranked using optimization methods, as described in Section 4.2.

3.3. LAMP Development and Updates

Although a platform for CZEs has been unprecedented in the past, once the essential software is developed, subsequent software improvements and individual software development for each sector can be simultaneously accomplished by multiple users based on their own ideas. Users can freely add information and software such as simulation models, image analysis, and 3D image construction necessary for CZEs conversion in their sectors of expertise or develop LAMP as needed (beyond time and distance) through collaborative sharing among multiple people. As LCA is a cross-disciplinary task, individuals and organizations specializing in it should provide and update such information to acquire data with a high degree of expertise and accuracy. In addition, although basic rules of use are necessary, knowing that information can be used and applied to research and businesses will help expand the number of users. Furthermore, even if the initial information is limited, as the number of users increases, the information pool will also increase, thereby increasing LCA accuracy and connections with related sectors. This will accelerate the development process and enable the simultaneous promotion of CZEs in diverse sectors worldwide.

The update method is concurrent with the development; LAMP will automatically evolve as users update their information and software. This could result in a large-scale map, unlike any other, that is free but provides a specialized space for sharing information (similar to Linux Development and GitHub) and involves information from all sectors related to CZEs. Anybody from individual to national level bodies, including people belonging to any age group, can become developers and users. In the future, when voice input/output and translation functions are enhanced, anyone can easily become an effective information provider for CZEs, regardless of language or IT skills. In addition, some areas may be integrated in a metaverse, and human-like interactions may occur. In such spaces, collaborations among sectors that would otherwise be unthinkable can be expected. Therefore, an idea in one part of LAMP can lead to a significant evolution of the entire map.

3.4. Formulation of CO₂ Reduction Plan

When formulating CZEs initiatives, even if the LCA reveals an event with high CO₂ emissions, the combination of materials and conditions that can be substituted is vast. For example, the replacement of fuel-oil-fired heaters in typical greenhouses with electric heat pumps for agriculture has been widely proposed. However, how operational electrical energy is procured depends on the weather conditions and local resources.

As another example, if the goal is to reduce the amount of CO₂ associated with greenhouse structural materials, various alternatives can be proposed, such as reducing the number of steel frames in the greenhouse, replacing them with new reinforced wood, and replacing covering materials with biodegradable films or films with a service life several times longer than that of conventional materials. However, in practical terms, determining whether the carbon equivalents and costs required to install and operate the system are within acceptable user ranges is essential.

When multiple alternatives (materials and methods) and objectives (carbon input, cost, and revenue) have various combinations, the optimal order of combinations is calculated according to the priority of the goals, such as multiobjective optimization [13,14,15]. This method simultaneously optimizes multiple objective functions with two or more tradeoff relationships and creates a set of superior solutions (Pareto optimal solutions) from the combinations, among which the one that meets the conditions (feasible) can be selected. If the requirements for the optimal solution (Pareto front) are known, a different solution can be determined even when the initial solution becomes unfeasible. Having these software programs makes it easier to solve problems early and save time.

4. Examples for the Use of LAMP in Horticulture

Greenhouse gas emissions from agriculture, forestry, and other land use amount to 18.4% of global CO₂ emissions, and these emissions mostly originate from agriculture (cultivation of crops and livestock) and deforestation [16]. In horticulture sectors, large amounts of fossil fuels are used to heat greenhouses [17,18,19,20,21,22].

Recently, CZEs and LCA have been incorporated into the horticulture sector [23,24], with an increasing number of reports comparing LCA in open fields [25,26], greenhouses, and plant factories or vertical farming [27,28,29,30,31]. In particular, many reports compare LCA of greenhouses and plant factories for leafy vegetables such as lettuce. According to these reports, plant factories might be advantageous for CZEs and may have lower environmental impact if electricity is supplied by natural/renewable energy [32,33,34,35]. Examples of the use of LAMP in horticulture, including plant factories, are as follows (

Table 2. Items and conditions for conducting LCA in horticulture.

Items and Conditions	Examples
Location	Climate, resource availability, and distance from consumption areas.
Structural & cultivation materials	Aggregates, covering materials, and cultivation system.
Operation	Environmental control system, plant monitoring, human resources, degree of automation and resource recovery ratio.
Germplasm, cultivar	Morphology, disease resistance, parthenocarpy, quality, uniformity, storage, and propagation.
Cultivation management	Soil/substrate, fertilizers/nutrient solution, pesticides, thinning leaves and lateral buds, harvest, and cleaning.
Processing and distribution	Grading, processing, packaging, distribution, shipping, and consumption.

).

4.1. Characteristics of LCA in Horticulture

In addition to the cultivation process from sowing to harvesting, as in other agricultural production, horticulture involves production facilities such as greenhouses and plant factories, which mainly require hardware such as structural and covering materials, and environmental control equipment for shading, heating, and cooling, as well as energy and resources for their operation. However, using production facilities means that the consumption of water, fertilizers, and pesticides for cultivation is much lower than in open-field production. Table 2 presents a list of items and specific conditions to consider when conducting an LCA of greenhouse production.

However, compared with open-field production, where cultivation systems and mechanization are more advanced, horticulture facilities are characterized by considerable differences in operational energy use depending on the crops, growing season, and production method. Therefore, the accuracy of LCA can be improved by adding information on the environmental conditions inside or outside the greenhouse during the growing season (even in a typical year) to the input values. In addition, by incorporating the “environment, growth, and labor simulation model” [36], which has been implemented in the horticultural sector, the amount of work and time required for harvesting and cultivation management can be estimated, and LCA can be performed with high accuracy.

4.2. Examples of Alternatives for Greenhouse Cultivation

When conducting LCA for greenhouse hardware (structural and covering materials) as an example in the LAMP, the significant main sectors, such as “industry”, “medical care”, “agriculture”, and “education”, are the first selection. Then, the subdivision “horticulture” is selected from “agriculture”, and the system proceeds to further selection of details in the order, such as by specifying “production location” to “greenhouse” (Figure 3). Once the requirements are selected, the coefficients specific to the covering material (e.g., thermal transmittance) are determined. The heat and water resource energy required to control the set environmental conditions are then calculated as is or as a CO₂ amount.

Figure 5 depicts a candidate searching for alternatives, showing a situation in which (although skipping a few steps) the heating and cooling equipment used to control the air temperature of the greenhouse is an electric heat pump; a proposal to replace this electricity with “natural energy” in the “energy” sector is a candidate. To conduct an LCA on such alternative proposals, reference to research results and methods from other sectors is necessary.

To date, there have been many studies in which greenhouses in specific regions were evaluated by LCA using different types of covering materials and energy sources for greenhouse heating [17,18,19,20,21,22]. Furthermore, by introducing LAMP, it is possible to find many options more easily and in a shorter time, and it is thought that more diverse LCAs can be realized. In addition, the LCA history and additional information might be shared with artificial intelligence (AI) learning to ensure that the AI can determine and propose alternative candidates in other sectors.

If the subject of LCA in a greenhouse is software (cultivation and operation), the climate zone, internal environmental settings, crop, variety, cropping type, cultivation method, harvesting, processing, and transportation methods should be set. Depending on these parameters, the amounts of water, fertilizer, pesticide, and transportation used by cultivation could be calculated as the CO₂ amount.

For the next step, an LCA with alternative plans is subsequently conducted. If an evaluation is desirable from a management perspective, resource costs and sales values could be estimated using growth, yield, and labor management simulations. In particular, switching from fuel oil to electric heat pumps is essential for CZEs conversion. However, the initial and operating costs are expected to vary significantly depending on the capacity and number of heat pumps. In the future, as mechanization, labor savings, and unmanned farm operations are actively promoted and integrated with natural/renewable energy, the options applicable to CZEs conversion will also increase.

4.3. Examples of Collaboration with Other Sectors

As an example of how LCA in horticulture can be linked to multiple sectors, consider the case of urban planning with a CZEs target for an entire town (Figure 6). One manufacturing plant serves the town’s core industries and emits heat and CO₂ daily. Using this in a greenhouse or plant factory built nearby, and locally producing and consuming the vegetables harvested there instead of transporting them over long distances, would reduce CO₂ emissions and food loss during transportation. Food loss and waste from plant factories and ordinary households may be converted into fuel and reused in the companies or plant factories. Plant factories produce not only food but also seedlings of trees, ornamental flowers, and other functional or medicinal plants, which can be utilized in gardening, fuels, medicines, and raw materials for building and biodegradable plastics. These wood seedlings can be grown in the town’s perimeter green areas, and periodically cut and harvested as buildings or plastic materials. In this way, energy and resources can be circulated in the city in a manner that does not use petroleum resources, thus bringing them closer to the CZEs.

As an example in the sector of education, CZEs and environmental education, including CO₂ absorption and emission, on these series of LCAs and CO₂ reduction can develop into problem-solving by collaboration with worldwide students and schools as educational materials. The more diverse the connections in various sectors, the more rapid the social recognition of the CZEs, and the more companies and individuals will accelerate their efforts to achieve it. By collaborating with other sectors, multiple goals can be achieved more smoothly.

5. Basic Methods to Promote CZEs

CZEs are an urgent issue, and specific solutions in each sector must be proposed rapidly by using and developing LAMP simultaneously. All proposals and efforts in each sector will provide essential data for LAMP development and accelerate the subsequent actions of its users.

As mentioned in previous sections, CO₂ emissions from the horticultural sector differ depending on the type and size of the facility, i.e., small plastic houses, large-scale greenhouses, or plant factories. In addition, the amount of energy input and resources also varies considerably depending on the cultivation method, environmental control system, variety of crop, cultivation season, and the grower’s cultivation management method. The more complex and diverse such cases are, the better the proposed LAMP can demonstrate its capabilities and formulate an individual and optimal CO₂ reduction plan. However, in the case of subdivided cultivation conditions, a huge number of slightly different proposals for CO₂ reduction might be formulated, and the extent to which such proposals can be implemented by individual growers is limited. Therefore, impactful CO₂ reduction proposals should first consider CZEs in common areas, such as in an entire horticulture facility, rather than at small or individual scales.

CZEs can be promoted via four methods:

• Savings (reduction in duplications and excesses).
• Standardization (lower costs through mass production).
• Individualization and downsizing (cost reduction by producing the minimum necessary quantity).
• Knowledge sharing and dissemination (sharing results and fostering the next generation with consideration for CZEs and environmental impact).

Figure 7 shows specific examples for CZEs in horticulture. The basic concept for CZEs is the same regardless of the sector.

5.1. Savings

5.1.1. Reduction of Water and Fertilizer

In plant factory production, the ideal maximum utilization efficiency of water, applied CO₂, and mineral fertilizer is 1.0 (100% of resources can be used). However, in practice, the utilization efficiencies are considerably lower than the theoretical values [37,38]. There is considerable room for technological improvement in the future, such as precise quantitative control of water and mineral fertilizer to reduce the amount of wastewater and promote the recovery and reuse of evapotranspiration water. In addition to lowering these input resources, the production and shipping costs of mineral fertilizer and CO₂ application can also significantly reduce the environmental load, such as the amount of plant residue and groundwater contamination [39]. In vegetable and fruit production, irrigation control can optimize the leaf area and maximize the total weight percentage of harvested (edible) parts. LAMP, which can integrate multiple information, can propose several ideas, such as the combination of irrigation control, genome-edited crops, and growth models, to maximize the edible portion of the target plant.

5.1.2. Reduction of Duplicated Research Plans

Currently, in the sector of horticultural research, the government, universities, prefectures, and municipalities have their own research plans and cultivation experiments to respond to their own differentiated cultivation system in each production area. Therefore, overlapping issues can often be found among production areas and researchers. If these are integrated, the results can be organized into content that can easily be shared and recommissioned to research institutes and cooperating growers in each region. In addition, by consolidating some cultivation experiments and analyses that require a lot of materials and labor, it is possible to save resources and achieve a significant reduction in CO₂ emissions related to resources, energy, and labor. To promote CZEs in future research activities, conventional administrative units must be reviewed and inspected, and the researches should be conducted depending on the research characteristics by institutions such as municipalities, governments, and universities. LAMP is also expected to support the development of these research plans and forums utilized for exchanging opinions and sharing information among the research institutions.

5.2. Standardization of Production Facilities, Cultivation Methods, and Materials

CZEs are a vital mission on a global scale, but this does not indicate that individuals and companies tolerate voluntary work and losses to implement it. Activities that lead to CZEs do not necessarily consist of conventional “returns on input costs” alone, and in some cases, “new capital investment that does not increase yields” may be required. For instance, if a fuel-oil-combustion type heating in a greenhouse is replaced by an electric heat pump (EHP), the yield will be the same if the greenhouse air temperature setting is the same. Although using the EHP for both heating and cooling/dehumidification year-round may contribute to quality improvement, unless the electricity bill for the EHP is close to zero when using natural/renewable energy, the annual fuel oil and heat pump bills will be the same. However, recovering the capital investment for EHP in the short term from the difference between the annual cost of fuel oil and electricity is not easy unless the running cost of the EHP is close to zero due to the use of natural/renewable energy.

To significantly reduce CO₂ and costs in horticultural facilities, standardization must be promoted, as in the industrial sector, and the cost of structural materials, cultivation materials [40], and inorganic fertilizers must be reduced through mass production. In the past, popular light sources in plant factories were white fluorescent lamps, which were mass-produced and commonly used at the time, leading to lower costs. Currently, white LEDs, which are mass-produced and used in public facilities, are the least expensive light sources that reduce facility costs.

Numerous companies have developed and marketed globally various greenhouse shapes, growing materials, and cultivation methods to suit their diverse climatic zones and regional characteristics. However, many parts can be standardized, and by replacing them with mass-produced products, significant CO₂ emissions and cost reductions can be achieved. In practice, collecting information and evaluating the features for standardization is necessary. LAMP is expected to be utilized in collaboration with industrial sectors and in the search for new common materials and diffusion technologies.

5.3. Individualization and Downsizing of Manufacturing Facilities, Materials, and Products

Although it seems contradictory, in horticulture, standardization and large-scale production for facilities and cultivation methods may not necessarily lead to greater efficiency toward CZEs. When considering options for CZEs, individualization and small-scale output should also be accounted for, although this is the opposite of mass production mentioned in Section 5.2. For example, the mass production of tomatoes and lettuce, which are consumed in large quantities, can reduce costs and contribute to CZEs through mass production in greenhouses and plant factories. However, this mass-production method may not be cost-effective for producing a wide variety of herbs, medicinal plants, and fruit vegetables that require a small-lot, multi-item production, and a longer cultivation period.

Three-dimensional printers have been proposed for producing individualized or small-volume products, wherein CO₂ and cost reductions are problematic for large-scale production [41]. As manufacturing machinery and production become more personalized and regionalized, the shift to CZEs through local production for local consumption will also be promoted. As for food and medicine, in the future, doctors and hospitals may prescribe processed foods such as alternative and artificial meat and medications that correspond to an individual’s constitution and medical history and download blueprints for these products to be produced by a 3D printer in the home kitchen. The LAMP network is a platform that should be utilized across sectors, not just in agriculture, health, and medicine.

5.4. Knowledge Sharing and Dissemination of Research, Development, and Use of Results as Educational Materials or Hobbies

As mentioned in Section 5.1.2, sharing results is essential for reducing the duplication of research and increasing the speed of CZEs promotion. In addition, the knowledge gained through this series of efforts can be used as educational material, contributing to the development of next-generation research. Compared with conventional horticulture, indicators such as “yield/profit per unit area” and “quality per input time” are difficult to understand except for producers and specialists; however, in terms of CZEs, all sectors can be converted and compared to a common unit, “CO₂”, making it easy for researchers, companies of educational materials, and consumers to “visualize”.

Another idea for using LAMP is a “CO₂ balance meter” (not a CO₂ concentration meter) that displays the balance between the amount of CO₂ reduced per day (carbon negative), e.g., through solar power generation, and the amount of CO₂ generated (carbon positive), e.g., through the disposal of food and plastic bottles in homes and schools. With this, we can develop a simulation-type online game to learn about the current situation, including prompts such as “What I can do today and tomorrow” and “How much CO₂ can I reduce by doing it?”. New product development may also be promoted by connecting companies that specialize in developing playful environmental educational materials with LAMP.

6. Conclusions

This paper presents the concept of LAMP to achieve CZEs. This concept needs to be tested and validated in the future. By implementing this concept, we hope to reduce the rate of global warming and disasters caused by the climate changes, if only slightly. The global COVID-19 pandemic has led to the rapid development of remote technology and a significant change in working methods in just a few years. Therefore, horticulture, which has remained unchanged for decades, could be at an opportune moment for substantial cost reductions and efficiency improvements under the global-scale external pressure of CZEs. This is also an opportunity to revolutionize horticulture around the world. With this paper, we hope to encourage individuals or companies to cooperate in LAMP development or inspire them to advocate for more progressive ideas.