Higher levels of no-till agriculture associated with lower PM_2.5 in the Corn Belt

Agriculture is a major source of air pollution around the world. In some parts of the world, including parts of the U.S., emissions from agriculture are the largest anthropogenic source of particulate pollution [1]. In the United States, for instance, the primary emissions associated with all agricultural activity account for approximately 16% of PM_2.5 emissions [2]. This estimate excludes secondary particulate emissions associated with the formation of particulate matter from precursor gases emitted by agriculture. Emissions from crops grown for export from the U.S. have been estimated to generate air pollution externalities whose costs exceed $36 billion annually, primarily due to ammonia emissions [3]. More generally, based on extrapolations of the estimated marginal damages, agriculture is the largest single sector source of damages from air pollution in the United States [4].

While much of this pollution is due to fertilizer application and animal husbandry, soil management practices also contribute to localized increases in particulate pollution [1, 2, 4, 5]. Of the primary emissions associated with agricultural production, estimates suggest approximately 75% come from tillage and harvesting activities [2]. This includes emissions due to combustion of fuel in machinery operation and direct emissions of dust from soil disturbance. Another estimate suggests that roughly 25% of total (primary and secondary) air pollution damages attributable to agriculture in the United States is due to primary PM_2.5 emissions from machinery fuel combustion and 'crop related activities' [4]. Reducing this pollution is likely to have health benefits [6–8].

Improved soil management practices, in particular low or no-till approaches, have been widely promoted as a way to reduce carbon pollution and increase carbon sequestration rates by reducing soil disturbance [9, 10]. The USDA subsidizes the uptake of no-till agriculture through the Environmental Quality Incentives Program (EQIP). This program is designed to encourage farmers to take up conservation farming practices through technical and financial assistance. No-till agriculture is one practice encouraged by EQIP payments but reductions in air pollution are not mentioned as a benefit justifying the subsidies for no-till adoption [11]. Carbon sequestration is offered as reason for the subsidies. Comparisons of the costs of subsidizing no-till and the potential carbon benefits have suggested that EQIP payments may be a cost-effective way of encouraging carbon sequestration [12].

Whether no-till reduces carbon emissions is controversial. For example, a recent summary of nature-based carbon mitigation approaches [13] intentionally did not include no-till because of questions about its effectiveness in reducing carbon emissions. They argue that carbon benefits only occur when fields have been in no-till management continuously for more than a decade, which is not the case in much of the U.S. Corn Belt.

On the other hand, a global review of studies on low disturbance soil management suggests that the median rate of carbon sequestration that can be achieved is roughly 0.2 t ha⁻¹ yr⁻¹ [14]. A model-based approach specific to the United States indicates that median accumulation rates in the U.S. are close to this global median [12]. Monetizing these estimates, using the U.S. Interagency working group's interim social cost of carbon of $51 per ton and assuming the entire American Corn Belt adopted no-till, suggests that the annual benefits of carbon reductions would be roughly 5 billion (USD2020) annually [12]. But, as with many policies that have carbon benefits, no-till may also have co-benefits in the form of reduced local air pollution. For example, using the value of a statistical life used by the U.S. EPA for cost-benefit analysis (9.5 million in 2020 dollars) the reductions in air pollution from adopting no-till would need to save roughly 500 statistical lives per year for the pollution reduction benefits to equal the suggested carbon benefits.

The potential benefits of no-till that derive from reducing local air pollutants have received less attention than carbon benefits [15]. Low disturbance tillage systems may substantially reduce local particulate pollution from windblown dust, with exact results dependent on the no-till practice used, the type of cropping system, and the location of the farms [16–18]. Much of this research has focused on the air pollution impacts of no-till over a small scale and in areas that are dry relative to the corn and soy growing regions of the American Midwest. Broadly this work has focused on the benefits of no-till in reducing wind erosion from a soil management perspective rather than examining the consequences for air pollution. One examination on the Columbia Plateau in the U.S. that does look specifically at the impact of no-till on particulate matter finds that no-till leads to significant reductions in PM₁₀ emissions from treated fields [19]. Another examining no-till uptake on California fields found reductions in windblown dust particulate matter of between 55% and 97% [20]. No-till approaches also involve less use of machinery with associated reductions in the emissions due to fuel combustion [4, 21]. The benefits of no-till for local air pollution, applied over a wide geographic region and one that typically has wet soils, remain understudied.

Understanding the magnitude of the improvement in local air pollution due to adoption of no-till is important in determining the appropriate level of policy support for no-till adoption. In other settings, policies with carbon mitigation benefits have had local air pollution co-benefits whose value exceeded the cost of the policy without regard to the carbon benefits [22, 23]. Including the benefits of reductions in local air pollutants due to no-till in the determination of the proper level of policy support may be especially relevant given disagreement about the presence and size of the carbon benefit.

1.1. Our approach

We start with two descriptive facts that motivated our analysis. First, there has been a general decline in the average level of PM_2.5 across the entire United States over the period we study [28–30]. In panel (A) of figure 1 we document that general pattern also appears in our data focusing on the four weeks of the year when tillage is most likely to occur. From 2005 to 2016 average daily PM_2.5 levels in the counties we study during the four weeks that tillage is most likely to occur fell by roughly 35%, from nearly 10 $\mu\textrm{g}\,\textrm{m}^{-3}$ to 6.5 $\mu\textrm{g}\,\textrm{m}^{-3}$.

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Panel (B) of figure 1 shows the second descriptive fact that motivated our analysis—over the same time period the adoption of no-till approaches have increased substantially. From 2005 to 2016 the average share of farmland in no-till across all counties in our sample increased more than 20% from just over 40% of fields to roughly 50% of fields.

The largest changes in no-till have occurred in the upper Midwest, namely North and South Dakota, Nebraska, and Iowa (figure 2). The largest reductions in pollution have occurred in the southern part of our sample in Ohio, Indian, and Illinois. This reduction in pollution may have been driven by changes in coal-fired power generation in the Ohio River Valley.

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We find that pollution is, on average, higher during the month in which we predict tillage to occur compared to the rest of the year. On average PM_2.5 during tillage times is 0.18 $\mu\textrm{g}\,\textrm{m}^{-3}$ higher across our sample than during non-tillage. This averages across all years and counties in our sample.

Our primary result is that in years with a higher share of crop pixels managed in no-till, the increase in PM_2.5 during tillage period relative to non-tillage is smaller (table 1). Our results suggest that a percentage point increase in the share of land in no-till management in a given year is associated with a 0.01 $\mu\textrm{g}\,\textrm{m}^{-3}$ reduction in the increase in PM_2.5 during the tillage period relative to the non-tillage period. That reduction in PM_2.5 represents a 0.11% decline from the mean PM_2.5 level while a one percentage point increase in no-till is a roughly 2.22% increase from the mean level of no-till uptake.

Our result is robust to a variety of specifications, including various different sets of daily, weekly, and day of sample fixed effects (table 1). Our results are also robust to dropping temperature and precipitation controls (column 1), omitting the period immediately prior to spring planting during which some tillage may occur (column 4), including controls for the level of no-till up-take in upwind counties (column 5), and including additional meteorological controls including the boundary layer height, wind speed and wind direction (column 6). We test whether dropping Ohio, Illinois, and Indiana—the states with the largest secular changes in PM_2.5 levels and that contain the large majority of power plants that close in our sample area and period—change our results. It does not. Our results are also robust to alternative clustering of our standard errors including clustering at state × year and by state and year separately.

The large reduction in PM_2.5 levels across the entire country during our sample period raises a potential concern that our results are the consequence of the intersection of two unrelated trends: the decline in pollution nearly everywhere in our sample and the overall increase in no-till. Specifically, because pollution declined in most of the counties in our sample and most counties had an increase in the use of no-till, our results could be only detecting the correlation between these trends. An implication of this hypothesis is that the specific geographic pattern of no-till uptake does not matter as long as it is generally positive. Conversely, the causal interpretation of our results implies that changing the pattern of no-till uptake would result in a zero effect as the causal link is broken. We can test this hypothesis by conducting a placebo test, akin to a randomization inference test, where we randomly assign no-till rates across counties and re-estimate our primary specification. The hypothesis of a causal relationship between no-till up-take and changes in pollution implies that this exercise should result in a mass of estimates clustered around zero. In contrast, if we are only detecting non-causal correlation the estimates from this exercise should be clustered around our reported effects and away from zero.

We conduct our test in two stages. We first randomly assign no-till uptake levels to all counties in our sample in each year, maintaining the observed distribution of no-till uptake within each year. This maintains the general positive trend in no-till uptake across the whole sample. We then re-estimate our primary specification. We do this 10 000 times. In results reported in figure 3 we show that this simulation results in a mass of estimates clustered around zero and substantially different from our main results.

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Using the estimates in table 1 we can estimate the share of the reduction in PM_2.5 levels that is due to increased use of no-till. Collectively the average share of crop pixels in no-till has increased by 9.67 percentage points from the first 2 years of our sample to the last (table 2). Average PM_2.5 levels during the tillage period have fallen 3.29 $\mu\textrm{g}\,\textrm{m}^{-3}$ over that same period. Combining our estimates of the impact of increasing no-till with the change in share of cropland in no-till suggests that the increase in no-till management can account for 3.8% of the 3.29 $\mu\textrm{g}\,\textrm{m}^{-3}$ decrease in PM_2.5.

2.1. Local air pollutant benefits compared to carbon benefits of no-till

2.2. Cost benefit analysis

Adoption of no-till agricultural practices has benefits for erosion, soil health, and may have carbon benefits as well. Less well understood are the potential benefits from reducing local air pollutants. We show here that adoption of no-till throughout the American Corn Belt is associated with declines in local PM_2.5 levels. The implied reductions in mortality due to these reductions in pollution suggest that the monetary benefits of adopting no-till may be substantially higher than previously estimated, which have focused primarily on the environmental and carbon reduction benefits. Including benefits from reduced mortality due to lower air pollution could raise these benefits substantially.

Our analysis is subject to several limitations. The adoption of no-till agricultural approaches that we study is not randomly assigned. Although there are clear theoretical and practical reasons why no-till would reduce pollution levels (e.g. reductions in wind erosion, soil disturbance, and emissions from machine operation), it remains possible that the reductions in pollution we observe are due to other changes in these counties. Notably, to affect our estimates these changes would have to both be not fully captured by the county and year fixed effects, and correlated with the residual variation in tillage and PM_2.5.

One possibility is that our results are attributing reductions in local pollutants due to broad shifts in power generation to the adoption of no-till agriculture. We have attempted to address this by examining how our estimates change under random assignment of no-till shares. If our estimates were due simply to general declines in pollution the results from this random assignment should be similar to our estimated effects. They are not and so we believe our estimates are capturing the impact of adoption of no-till approaches. But more examination of this question that can more clearly identify causal effects is warranted.

Another potential concern is that our calculation of the benefits of reduced air pollution assumes the mortality benefits are uniform across our study area. The impact that air pollution has on mortality can be highly variable across space [45]. Because we study reductions in pollution due to changes in agricultural practices the largest reductions in emissions will be in rural areas that have lower populations and so may have lower benefits from reductions in mortality. If the pollution reductions from adoption of no-till only accrue to rural areas our estimates of the health impacts may be biased upwards. However, emitted PM_2.5 can travel long distances and there are several large population centers in our study area. If rural reductions in emissions reduce pollutant levels in these population centers, our mortality estimates are more likely to be accurate. Rural areas also tend to have more vegetation that may help reduce pollutant concentrations. To the extent that vegetation is relatively constant across years our estimation strategy accounts for this difference between rural and urban locations with our fixed effects. We do not account for the impact that vegetation may have on long-range transport of particulates explicitly but existing work suggests that ground level emissions from rural counties can travel long distances even in the presence of vegetation [46].

Much of the existing research on no-till has focused either on highly local benefits to soil health or water quality or global benefits of higher carbon sequestration. Our estimates here offer evidence that there may also be regional benefits in the form of reductions in local air pollutants. Like in other settings the benefits of these reductions in air pollutants may be substantial.

More research is needed to provide additional insight into the size of these potential benefits and identify a clear causal link between adoption of no-till approaches and changes in air pollution. Our estimates also point to another channel through which agriculture influences local air pollution and highlight the importance of research on the links between air pollution and agricultural practices.

This work was supported by the NASA Harvest Consortium (NASA Applied 787 Sciences Grant No. 80NSSC17K0652, sub-award 54308-Z6059203 to DBL).

The data that support the findings of this study are available upon reasonable request from the authors.