Carbon Emission Characteristics of Cropland in Northeast China and Monitoring Means

Abstract

As the cereal-producing region of China’s black soil, there are many agricultural activities, mainly including cultivation, straw processing, and harvesting, in Northeast China. In the process of carrying out these agricultural activities, they inevitably lead to large carbon emissions, among which straw burning and wind erosion are two processes that directly lead to carbon emissions from farmland. In this study, we estimated the carbon emissions of these two processes based on two algorithms: the improved Fire Radiative Power and Community Multiscale Air Quality (FENGSHA) algorithms. The results showed that the carbon emissions from straw burning in Northeast China can reach up to 126,651 Gg in 2017, and those from wind erosion of agricultural land can reach up to 80.45 Gg a year. When compared with the carbon emissions in 2017, the implementation of the Action Plan for Straw Disposal in Northeast China resulted in around a 40% decrease in the carbon emissions from straw burning in 2022. However, the carbon emissions from agricultural land wind erosion increased by about 10%. The seasonal characteristics of both straw burning and farmland wind erosion were obvious, with both being concentrated in the spring. In addition, based on the potential impacts of straw burning on wind erosion, we proposed that a Y-shaped integrated monitoring network should be constructed to monitor both straw burning and wind erosion in Northeast China. Thus, the study of carbon emissions from straw burning and wind erosion in Northeast China is of great importance for energy conservation and emission reduction, and the implementation of a straw burning ban policy, straw recycling and reuse, and a black soil protection policy is recommended.

1. Introduction

Agriculture accounts for about a quarter of global carbon emissions, and, thus, quantifying carbon emissions from agriculture is important for global carbon emission reduction [1,2,3]. China is an agricultural country, with agricultural carbon emissions approaching hundreds of millions of tons [4,5,6]. The Northeast Region is China’s main agricultural production base and, consequently, produces a large amount of agricultural carbon emissions [7]. Fertilizer application, wind erosion, harvesting, grain handling, straw burning, farm machinery emissions, and land preparation all contribute to large amounts of carbon emissions. Straw burning in the Northeast has always been a hotspot of social concern, which not only causes serious air quality pollution but also contributes significantly to carbon emissions [5]. The straw in Northeast China is mainly rice and corn. However, straw burning has a potential impact on wind erosion [8,9]. Wind erosion causes large amounts of dust particles from agricultural land to enter the atmosphere, and it also leads to the loss of organic carbon (OC) from the soil. The global OC loss from farmland due to wind erosion is as high as 3149 Gg [10], and, thus, it is essential in the process of carbon cycling. To achieve China’s dual-carbon target through China’s carbon emission reduction policy, there is a need to quantify the carbon emissions from the two processes of straw burning and wind erosion in farmland. The findings could be used to propose reasonable emission reduction policies for the two processes separately and synergistically and to inform the protection of black soil.

The Northeast region produces an estimated 125 Mt of straw each year [5,11]. Some of the straw is recycled (fertilizer, feed, fuel, base material, and raw material) in an organized way, but the recycling capacity is limited, and the remaining straw is disposed of by burning [12,13]. Studies have estimated that straw burning in the Northeast Region results in CO₂ emissions of about 20–100 Tg [14,15]. Although straw burning is better managed and monitored in the Northeast Region, it is still a great challenge to accurately quantify the carbon emissions from straw burning [16]. Additionally, studies have found that some non-CO₂ gases (such as CO and CH₄) and carbonaceous aerosols (such as OC and elemental carbon [EC]) are produced during straw burning [17]. Although these are a relatively small proportion when compared with total greenhouse gas (GHG) emissions, they exacerbate the greenhouse effect [18]. Therefore, in addition to quantifying the emissions of carbon dioxide from straw burning, the emissions of other carbonaceous gases and aerosols should also be considered.

Northeast China is one of the four major black soil regions in the world and an important source of grain in China [19]. The extensive farmland and fertile soils (with a high organic content) are the defining characteristics of the Northeast Region [20]. However, these characteristics also mean that the area of farmland in the region is more wind-erodible, which increases the possibility of wind erosion. It has been found that the average annual loss of OC from wind erosion in Asian farmlands is about 541 Gg [10]. In addition, the bare farmland in the Northeast Region is an important source of dust in the region [21], which means that a large amount of OC also enters the atmosphere with dust particles [10]. Therefore, wind erosion not only causes the loss of OC from black soils in Northeast China but also contributes to the greenhouse effect [17,22]. However, previous studies have not specifically focused on the amount of OC loss caused by wind erosion. Consequently, this study estimated the loss of OC and theoretically explored the potential impact of straw burning on the loss of OC caused by wind erosion.

2. Material and Methods

In this study, we estimated the total emissions of CO₂, CO, CH₄, OC, and EC from straw burning on farmland in Northeast China using the improved Fire Radiative Power (FRP) algorithm. The FRP algorithm can estimate the carbon emissions from straw burning using satellite data, with high real-time performance and high accuracy results [5,23]. Moreover, we estimated the OC emissions from farmland wind erosion in Northeast China by combining the improved Community Multiscale Air Quality (CMAQv4.7)-FENGSHA algorithm with the soil OC weight percentage data. The CMAQ-FENGSHA model can effectively simulate the wind erosion process in the Northeast, and it is more suitable for estimating the carbon loss due to wind erosion [10]. The carbon emissions of these two processes in agroecosystems were estimated using these two methods; their spatio-temporal characteristics were analyzed from 2017 to 2022; and some suggestions were provided for future policy decisions.

2.1. Study Area

The study area was in Northeast China, which included parts of Heilongjiang, Jilin, Liaoning, and Inner Mongolia. This region has a temperate monsoon climate, which is characterized by warm and short summers and long, cold, and dry winters. The Northeast Region is formed by the alluvial deposits of the Three Rivers Plain, the Songnen Plain, and the Liao River Plain, and it is a vast area with abundant water resources and fertile land. It also has a vast area of agricultural land and is an important base for food production in China and around the world (Figure 1). Farmland in the Northeast is a one-season crop. The crops are lush in summer and autumn, and the surface is exposed after the crops are harvested.

2.2. Estimation of the Carbon Emissions from Straw Burning on Agricultural Land

The carbon emissions (CO₂, CO, CH₄, OC, and EC) from straw burning on farmland in Northeast China were estimated using the following equations [23]:

$$E_{tot\_i}={\int }_{t_1}^{t_2}{FRP}^{*}dt\times \beta \times EF=FRP\times f_{FRP}\times \left(t_2-t_1\right)\times \beta \times EF\times f_{num}$$

(1)

where $E_{tot\_i}$ is the total emissions of i particular carbon-containing substance; $t_1$ and $t_2$ are the start and end times of the satellite-recorded fire points, respectively; ${FRP}^{*}$ is the corrected Fire Radiative Power (in MW); $\beta$ is the straw burning factor, set at 0.411 kg/MJ [24,25]; $EF$ is the carbon emission factor coefficient for each type of straw burning on the farmland. Then, $FRP$ is the fire radiative power value that was captured by the satellite; $f_{FRP}$ is used to address potential underestimation issues that are related to FRP, and it was set to 5 based on a previous study [23]; $f_{num}$ corrects the number of fire points that are detected by satellites, and it was set to 1.47 (1/0.68) based on a previous study [26]. The second equation for estimating carbon emissions is specified below:

$$E_{tot}=E_{tot\_{CO}_2}+E_{tot\_CO}+E_{tot\_{CH}_4}+E_{tot\_OC}+E_{tot\_EC}$$

(2)

where $E_{tot}$ is the total carbon emissions from straw burning on farmland; $E_{tot\_{CO}_2}$ is the total CO₂ emissions from straw burning; $E_{tot\_CO}$ is the total CO emissions from straw burning; $E_{tot\_{CH}_4}$ is the total CH₄ emissions from straw burning; $E_{tot\_OC}$ is the total OC emissions from straw burning; $E_{tot\_EC}$ is the total EC emissions from straw burning [5].

In addition to the above parameter improvements to the formulae, a total of 16 crop emission factors (including barley, cassava, cotton, groundnuts, corn, millet, potatoes, rapeseed, rice, sorghum, soybeans, sugar beets, sunflowers, sweet potatoes, wheat, and yams.) were considered in this study [5], which is more factors than were compared in studies on other crop types. These emission factors were partly sourced locally and partly sourced from the literature. The flame radiant power data that were used in this study were obtained from the National Oceanic and Atmospheric Administration Visible Infrared Imaging Radiation Suite (VIIRS) 375 m fire product [27]. The data include detailed information on the latitude, longitude, and time and are highly accurate and available in real-time. Sixteen types of land use data and crop acreage data were also used in this study and were derived from MAPSPAM [28]. More detailed optimization information and data information can be found in the studies by Yang et al. [23] and Liu et al. [5].

2.3. Estimation of the Carbon Emissions from Agricultural Land Wind Erosion

The carbon emissions (mainly the loss of OC from agricultural land due to wind erosion) from agricultural land wind erosion were estimated using the following equation [10]:

$$E_{toc}=\mathrm{k}\times \mathrm{A}\times \frac{\rho }{g}\times u^{*}\left(u^{*2}-u_t^{*2}\right)\times SEP\times S\times P$$

(3)

where $E_{toc}$ is the amount of OC lost due to farmland wind erosion; $\mathrm{k}$ is the ratio of the vertical and horizontal fluxes; $\mathrm{A}$ is the scaling factor; $\mathsf{\rho }$ is the air density; $g$ is the gravitational acceleration; $u^{*}$ is the friction velocity; $u_t^{*}$ is the critical friction velocity; $SEP$ is the soil erosion coefficient; $S$ is the wind-erodible area of the farmland; and $P$ is the weight percentage of the OC of the farmland soil.

For the optimization of the algorithm of the wind erosion carbon emissions from agricultural soils, the soil weight percentage data of the farmland in Northeast China was added, which was obtained from a gridded soil dataset that was developed for the Earth System Model [29]. The OC weight percentage data from the topsoil layer at depths of 0–4.5 cm were selected at a resolution of 1 km [29]. The CMAQ-FENGSHA algorithm requires input data of 0.1 × 0.1°, and the dataset was resampled to a resolution of 0.1° × 0.1°. The main optimization for the CMAQ-FENGSHA algorithm was the determination of the wind erosion area of farmland, as this is the most important parameter for estimating dust emissions. The wind erodible area was estimated based on two sources of information. Firstly, the area of farmland soil in Northeast China that may be wind eroded by the end date of tillage and harvest was determined. Secondly, the area of farmland soil in Northeast China that may be wind eroded by the end date of sowing, one week after the end date of sowing, and the end date of harvest were determined. The effect of snow cover on wind erosion is taken into account in the CMAQ-FENGSHA estimation to make the model more accurate. Considering the ease of use of the model, we used MODIS/Terra Snow Cover Daily L3 Global 0.05° CMG (MOD10C1) data that were processed by the Integrated Climate Data Center of the University of Hamburg with a resolution of 0.05 × 0.05° [30]. The wind speeds in the direction of longitude at 10 m and those in the direction of latitude at 10 m were converted to mean wind speeds, and the mean wind speeds were converted to surface wind speeds with the same resolution of 0.1 × 0.1°. In addition, the wind erosion parameters of the agricultural fields were adjusted in CMAQ-FENGSHA to improve its estimation accuracy, which was described in detail in the studies of Liu et al. [10].

3. Results

3.1. Spatial and Temporal Characteristics of the Carbon Emissions from Straw Burning on Farmland in Northeast China

The total carbon emissions from straw burning in Northeast China from 2017 to 2022 were 126,651 Gg, 42,768 Gg, 80,416 Gg, 75,712 Gg, 65,478 Gg, and 73,631 Gg, respectively. The carbon emissions from straw burning showed a trend of first decreasing and then increasing, dropping to a minimum in 2018, and then gradually starting to rebound after 2019 (Figure 2a). In terms of monthly carbon emissions from straw burning, firstly, the seasonality was obvious and was basically concentrated in spring and autumn. Secondly, the peak emissions in spring (April) were about 1–7 times higher than those in autumn (October). Thirdly, the carbon emissions gradually increased from autumn to spring. Among the carbon emissions from agricultural straw in the whole Northeast region, Heilongjiang Province contributed about 37–66%, almost half of the total (Figure 2b); Jilin Province contributed about 16–36%, with more than 30% in both 2020 and 2021; Inner Mongolia contributed about 9–18%; and Liaoning Province contributed the least, at about 6–15%, with a relatively stable contribution.

The carbon emissions due to the burning of agricultural straw in Northeast China were basically spatially concentrated in the Heilongjiang and Jilin provinces, and they were lower in Liaoning and Inner Mongolia, which is consistent with the results of the carbon emission contributions in the previous section (Figure 3). The emissions in Heilongjiang Province were mainly concentrated in Jiamusi City, Shuangyashan City, Qitaihe City, Jixi City, Suihua City, Qiqihar City, Heihe City, and Western Harbin City. The emissions in Jilin Province were mainly concentrated in the cities of Baicheng, Siping, and Northeastern Changchun, and those in Inner Mongolia were mainly concentrated in Hulunbuir and Tongliao. Moreover, the emissions in Liaoning Province were mainly concentrated in Tieling City, Shenyang City, Panjin City, and Anshan City. There were two main emission regions in the whole Northeast region: a curved-shaped emission region with Heihe City, Hulunbuir City, Harbin City, Changchun City, and Panjin City in the west, and a triangular-shaped emission region with Jiamusi, Shuangyashan, Qitaihe City, Jixi City, and Mudanjiang City in the east. By 2022, the carbon emissions from straw combustion in Northeast China began to shrink in a large area, with obvious changes in the emission areas; the emission intensity of the triangular-shaped emission area on the east side decreased very significantly, the curved-shaped emission area on the west side gradually decreased, and the emission intensity also gradually decreased.

3.2. Spatial and Temporal Characteristics of the Organic Carbon Loss Due to Farmland Wind Erosion in Northeast China

The OC losses from farmland in Northeast China from 2017 to 2022 were 57.85 Gg, 64.34 Gg, 78.65 Gg, 69.30 Gg, and 80.36 Gg, respectively. The overall trend of OC loss due to farmland wind erosion in Northeast China was increasing, and it slightly decreased in 2020. In terms of the monthly OC losses from farmland wind erosion, firstly, like the straw burning carbon emissions, the seasonality was obvious, but the peak of OC loss was concentrated in spring and winter (Figure 4a). Secondly, the peak in spring was 1–3 times higher than that in winter. Finally, the frequency of the peak in spring was higher than that in winter. In terms of the loss of OC due to farmland wind erosion in the whole Northeast region, Heilongjiang Province accounted for about 70% of the loss, and the contribution rate remained relatively stable (Figure 4b). The loss in Jilin Province accounted for about 12–15%; that in Inner Mongolia accounted for about 11–13%, and that in Liaoning Province accounted for about 4–5%.

The OC loss from farmland wind erosion in Northeast China was basically spatially concentrated in Heilongjiang Province, with a small proportion in Jilin Province, Liaoning Province, and Inner Mongolia (Figure 5). The loss of OC in Heilongjiang Province formed a “V” shaped area, i.e., the Heihe-Qiqihaer-Suihua-Harbin-Qitaihe-Shuangbashan-Jiamusi loss area. The loss of OC in Inner Mongolia was basically concentrated in Hulunbuir City and the border of Heilongjiang Province. In Jilin Province, it was basically concentrated in the northeast of Changchun City. Additionally, the OC loss in Liaoning Province was basically concentrated in Tieling City. The intensity of the OC loss in the whole northeast region was gradually increasing, but the OC loss area was almost unchanged.

3.3. Characteristics of the Total Carbon Emissions from the Two Carbon Emission Processes in Farmland in Northeast China

The total carbon emissions of the two processes showed a trend of first decreasing and then gradually increasing (Figure 6b). The change trend of the total carbon emissions was consistent with the change trend of the straw burning process, with the straw burning carbon emissions accounting for about 99% and the wind erosion carbon emissions accounting for less than 1% (Figure 6a). The total carbon emissions in the Heilongjiang and Liaoning provinces basically showed a decreasing trend, which decreased by almost half (Figure 6d,e). Then, Jilin Province’s total carbon emissions fluctuated, falling to a minimum in 2018 and rising to a maximum in 2020 before gradually declining (Figure 6d). Similarly, Inner Mongolia’s carbon emissions were also volatile, plummeting in 2018, increasing sharply in 2020, dropping to a minimum in 2021, and then rising to a maximum in 2022 (Figure 6f).

4. Discussion

4.1. Analysis of the Factors Influencing the Carbon Emissions from Straw Burning in Northeast China

The total carbon emissions from straw burning in the Northeast Region fell to a minimum in 2018, mainly due to the strong control of straw burning [16]. It was also caused by several snowfalls in 2018 that made straw unsuitable for burning, and the recycling of straw (for feed, power generation, and new materials), which began to rapidly develop in the Northeast in 2018 [5]. After 2019, the trend gradually began to increase, and the main reason was a lack of control, but control is not the fundamental solution to the problem of carbon emissions from straw burning [13]. The Northeast region is one of the main agricultural production areas and produces a considerable amount of straw every year; thus, if recycling technology or other treatments for straw are not developed, delaying the farming burning time would be the most effective and fast method. Based on the monthly carbon emissions from 2017 to 2022, the peak carbon emissions were significantly higher, and the frequency of the carbon emissions significantly increased from straw burning in spring when compared with those in autumn. This was mainly due to stricter control in autumn in the northeast and because the autumn harvest in the northeast was affected by snowfall. In Heilongjiang Province, the extensive arable lands predominantly dedicated to cereal crops significantly contribute to the large volume of straw residue. This, coupled with the challenges of managing such vast amounts of agricultural waste, results in straw burning accounting for 50% of the total carbon emissions in the region. Notably, compared to vegetable cultivation, cereal production occupies larger tracts of land, which not only increases the total volume of straw generated but also exacerbates the difficulties in its disposal, thereby influencing both the proportion and spatial distribution of carbon emissions.

4.2. Analysis of the Factors Influencing the Carbon Emissions from Farmland Wind Erosion in Northeast China

The carbon emissions from wind erosion in the Northeast region generally showed an increasing trend from 2017 to 2022, decreasing to a minimum in 2020. The area of farmland in the Northeast region has been recently increasing [31], leading to an increase in agricultural activities. As agricultural technology continues to advance, the use of various large agricultural machines also affects the structure of the soil and soil moisture [32,33]. These changes have led to an increase in the wind erosion area of the fields and the activation of the wind erosion mechanism, resulting in the emission of a large amount of dust and further leading to carbon emissions. In addition, the outbreak of COVID-19 in 2020 resulted in the immobility of domestic laborers and a reduction in the intensity of agricultural activities when compared with previous years, making many agricultural tillage activities impossible [34]. The agricultural activities did not take place on time, which resulted in the straw not being burned during peak wind erosion, and large areas of straw mulch weakened the wind erosion to some extent.

In terms of the monthly emissions from farmland wind erosion, the carbon emissions were mainly concentrated in spring and winter. In Northeast China, the crops are planted once a year, and wind erosion is more likely to occur in spring and winter because no crops are covering the surface. Also, the dry climate and high wind speed in spring and winter in Northeast China are important causes of carbon emissions [35]. The peak and frequency of the carbon emissions caused by wind erosion were two to three times higher in spring than those in winter, which was mainly related to the sudden decrease in the farmland wind erosion area due to cold and snowy winters in Northeast China [10]. In addition, the wind speed was greater, the temperature was higher, and the humidity was lower in the spring than in the winter in Northeast China. In terms of the share and spatial distribution of the carbon emissions in each province in Northeast China, the carbon emissions due to wind erosion in Heilongjiang Province contributed about 70%. The vast and gentle plain topography of the agricultural land in this province, when compared to that in other provinces, is one of the main causes. Moreover, Heilongjiang Province is also one of the areas with more serious wind damage, and there are two wind-prone areas in Heilongjiang Province, which lead to better conditions for wind erosion [36].

4.3. Uncertainty of the Two Algorithms Fire Radiative Power and Community Multiscale Air Quality-FENGSHA

This study estimated agricultural straw burning using an improved FRP algorithm, which is a top-down approach. When compared with other traditional algorithms, this algorithm has the characteristics of being real-time and having higher accuracy, but there are still some uncertainties. Although most of the localized emission factors have been used in the process of estimating carbon emissions, there are still some straw emission factors from the literature that can cause uncertainty in the estimation. Moreover, the FRP data that was used in this study was obtained from the VIIRS at 375 m, which has a high resolution. However, this satellite only captures fires between 12:00 and 14:00, and although we have made several corrections to accurately estimate the number and duration of the fires, there still may be some uncertainty.

The estimation of the carbon emissions caused by farmland wind erosion was mainly obtained by estimating the amount of sand in the farmland using the CMAQ-FENGSHA algorithm and then combining it with the farmland soil percentage data in Northeast China. The accuracy of the CMAQ-FENGSHA algorithm has been verified by Zhang et al. [21], and both models outperformed the other models in estimating dust emissions in Northeast China. However, under global climate change, extreme weather events occur. Extreme weather can have drastic effects on wind speed, soil moisture, and vegetation cover over a short period of time, which will introduce some uncertainty into the model estimates.

4.4. Implications for Policy

Straw is abundant in Northeast China. When faced with such a large amount of straw production, strict control cannot completely solve the problem of straw burning [13]. Based on the results of our study, Heilongjiang Province had the highest straw burning percentage. It is recommended that the period and strength of the straw burning control be standardized. It should also be jointly handled by other provinces to form a joint management policy, and the province should increase the technical input for straw recycling and reuse to alleviate the problem of farmers’ inability to process the straw timeously.

The agricultural land in the Northeast region is vast and has undergone land changes for more than 20 years [21]. Land clearing for farming and overplanting of crops have reduced the nutrient content of the farmland soils, which have gradually sanded. Sandy loam soils are more susceptible to erosion and are now an important source of dust in the region [21]. A large amount of dust emissions directly carry the OC in the soil into the atmosphere, further aggravating the greenhouse effect [37]. To address this issue, firstly, in terms of the intensity of the wind erosion, the farmland in Heilongjiang Province should be protected, and the straw burning time and the most serious period of farmland wind erosion should be considered to reduce the area of soil that is subject to wind erosion. Secondly, the provinces should set up wind erosion monitoring stations in several regions to form a monitoring network and conduct real-time observation to provide a basis for developing wind erosion prevention techniques. Thirdly, the provinces should give priority to areas with serious wind erosion to carry out timely protection to gradually alleviate the continuous impact of wind erosion.

Although there is still no definitive research on the mechanisms of the effect of straw burning on wind erosion, it is important to determine whether there are synergies between the two processes in terms of carbon reduction policies. Some studies have found that large wildfires reduce vegetation cover, thereby greatly increasing the severity of wind erosion [8]. Large areas of straw in the Northeast would undoubtedly reduce the amount of exposed agricultural land surface, which would theoretically reduce the potential for wind erosion. In addition, agricultural fires can significantly modulate near-surface wind patterns and friction velocities, thus, producing conditions that are suitable for wind erosion [9]. Therefore, straw burning could have an impact on wind erosion and increase carbon emissions due to wind erosion. Due to this potential impact, agricultural straw burning and wind erosion can be coordinated in space and time to reduce emissions.

The Northeast Plain, the largest plain in China, is mostly located in Heilongjiang Province and has an extremely vast farmland area. Spatially, carbon emissions from straw burning have a wide spatial distribution, while OC emissions from wind erosion are concentrated in Heilongjiang Province. The spatial distribution of the two types of carbon emissions is almost the same in Heilongjiang Province, thus, a Y-shaped integrated monitoring network of straw burning and wind erosion should be established in the Northeast Region (Figure 7). This would allow for straw burning and wind erosion activities to be monitored at the same time, and multi-provincial collaborative emission reduction and joint prevention and control could be conducted in the Northeast Region. Temporally, April is the most active period for straw burning and wind erosion activities, and the application of new technologies, such as delaying straw treatment or waiting until spring to directly return the straw to the field during the period of strong wind erosion, could reduce the emissions of straw burning and wind erosion.

5. Conclusions

This study estimated two processes that directly contribute to carbon emissions in farmland in Northeast China, namely straw burning and wind erosion. It was found that straw burning caused about 99% of carbon emissions and was the main carbon emission source for both processes. Although wind erosion of agricultural land only accounted for about 1% of carbon emissions, OC emissions were directly lost from the soil, and the long-term damage is incalculable. Both the carbon emission processes were found to be seasonally distinct. The carbon emissions from the straw-burning process were influenced by the season of the crop, snowfall, and seasonal controls. In contrast, the carbon emissions from farmland wind erosion were influenced by seasonal weather characteristics and the seasonal exposure of the ground surface. In Northeast China, both straw burning and farmland wind erosion in Heilongjiang Province accounted for about 50–70% of the carbon emissions, while the other three provinces accounted for about 30%, which was attributed to the larger farmland area and more pronounced weather characteristics (two windy areas) in Heilongjiang Province.

Regarding policy measures that go beyond traditional approaches, a Y-shaped integrated monitoring system for both straw burning and wind erosion should be established in the Northeast. This would facilitate real-time tracking and synergistic emission reductions, promoting cooperative prevention across the provinces. Additionally, delaying straw disposal or reincorporating straw into fields during planting could further reduce emissions from both sources. This study quantified carbon emissions from crop residue burning and wind erosion and highlighted their potential interactions. However, the carbon balance resulting from these interactions was not assessed, and this should be conducted in future research.