Mason T. LeBlanc,a and Richard P. Vlosky,b,*
a: Drax Biomass, Monroe, LA, USA;
b: Louisiana Forest Products Development Center, Louisiana State University Agricultural Center, Baton Rouge, LA, USA.
*Corresponding author: E-mail: rvlosky@agcenter.lsu.edu
Citation: LeBlanc MT, Vlosky RP. 2023. The wood pellet industry in the United States South: an exploratory regional comparison of resident environmental, social, and economic perceptions. J.For.Bus.Res. 2(1): 94-125
Received: 11 December 2022 / Accepted: 8 April 2023 / Published: 13 April 2023
Copyright: © 2023 by the authors
This article is a companion to another article published in the same issue of the Journal of Forest Business Research.[1] As such, to preclude duplication, much of the background and literature review are not repeated in this article. While that article focuses on comparing rural and urban resident perceptions of the wood pellet industry, in this piece, we examine and compare residents by major pellet production sub-region in the US South across three dimensions: environmental, social, and economic attributes. The Southern region overall is the world's largest producer and exporter of wood pellets. The sub-regions are the Gulf Coast (Louisiana and Mississippi) and the Atlantic Coast (South Carolina, North Carolina, and Virginia). Two rounds of a web-based survey were sent to 7,500 residents in the two pellet-producing sub-regions within the US South. Within these regions, surveys were sent to randomly selected residents by zip code, 18 years or older. Overall, Gulf Coast respondents were more accepting of the pellet industry than Atlantic Coast respondents across the three attributes.
[1] LeBlanc MT, Vlosky RP. 2023. What do people think about the environmental, social, and economic impacts of the wood pellet industry? An exploratory study of residents living near pellet plants vs. urban residents in States with pellet manufacturers. J.For.Bus.Res. 2(1): 20-37.
Keywords: pellets, resident perceptions, United States, regional comparisons, Gulf South, Mid-Atlantic
Adverse environmental effects of fossil fuels accompanied by increasing world energy demand have stimulated global consciousness toward climate change issues and renewable sources of energy. Over the past 50 years, the reduction of greenhouse gas (GHG) emissions and utilization of renewable energy sources (RES) have received significant attention in global energy and environmental policy. As a result, biomass energy, in the form of wood pellets, has taken center stage in the realm of RES over the past decade, as a highly subsidized and widely utilized alternative to fossil fuels, particularly coal, for large-scale energy generation. Global consumption of wood pellets has been on an upward trajectory for the past decade, particularly in the two largest demand regions, the European Union (EU) and Asia; demand is expected to continue increasing under current policy conditions (Thrän et al. 2017).
Concurrent with increasing demand, the United States’ (US) industrial wood pellet manufacturing industry has developed into the most significant global producer and exporter of pellets, predominately from the Southern region (UN-FAO 2018). Over 95% of production in the South is exported to the EU, where wood pellets have become an integral part of strategies to mitigate carbon dioxide (CO2) and other GHG emissions (Henderson et al. 2017). The US has received considerable attention as exports have increased from negligible amounts in the early 2000s to around 6 million metric tons (MMt) in 2018 (Greene 2019).
The literature on wood pellets has focused on chemical and energy characteristics compared to fossil fuels, carbon sequestration, GHG emissions and other pollutants. Other environmental and economic issues have also been studied. Examples of issues in the environmental area include timber harvesting, life-cycle analysis of pellet production, and energy expenditures in the supply chain from the forest to end-users. In the economic area, analyses tend to examine policy instruments, economic impacts, and investment opportunities that have evolved with increasing demand. However, while these aspects of wood pellets have been studied fairly intensively, a limited amount of research has focused on social dimensions of the industry.
Public concern is evident among wood pellet manufacturers. For example, Enviva, the largest pellet manufacturer in the world, recently created a new corporate-level position of Community Outreach Manager. This manager leads engagement and communicates the company’s efforts in sustainable forest management and restoration amongst other environmental initiatives, through education programs and community outreach. As the industrial wood pellet industry grows, it is vital to understand public perceptions, as they may have implications on the formation of policy, corporate investment in manufacturing facilities, the future of wood pellet bioenergy in the US, and future environmental, social, and economic impacts of this emerging industry.
This article examines and compares perceptions of residents in the two primary wood pellet-producing regions in the US South; the Gulf Coast, including Louisiana and Mississippi, which utilizes softwood pine as primary feedstock and the South Atlantic Coast, including North Carolina, South Carolina and Virginia, which utilizes hardwood as primary feedstock. We investigate the attitudes, awareness, behaviors, perceptions, and underlying issues of the wood pellet manufacturing industry from perceptions of the general public, combining responses from residents living near or in communities where pellet mills are located and urban residents. This study examines perceptions of the wood pellet sector in the context of environmental, social, and economic constructs.
This study was conducted by administering a web-based survey to residents within a 50-mile radius of selected pellet mills and residents living within the two largest metropolitan statistical areas (MSA) in each state where these mills are located. Although it would be valuable to understand the pellet industry’s perceptual dynamics from the perspective of many stakeholders, due to time and funding constraints, as well as the pressing need to study resident opinions, residents were the focal group.
In the study, “pellet manufacturing facility” or “pellet mill” refers to a facility where industrial pellets are produced and “power station” refers to an industrial facility that produces energy in the form of heat, electricity, or both. The US Census Bureau defines urban areas as areas with a population of 50,000 or more people, and rural areas are defined as areas not included within an urban area. However, since zip code boundaries, rather than cities, were used to identify residents within 50-mile radius of pellet mills, residents within the 50-mile radius were the rural sample and residents within MSAs were the urban sample. The Census Bureau defines MSAs as core areas containing a substantial population nucleus, together with adjacent communities having a high degree of economic and social integration.
An email list of 7,500 residents, including demographic data, was purchased from the direct marketing services company, Exact Data. The list was randomly but proportionately selected by ZIP code and limited to residents 18 years or older that owned or rented homes within the collected ZIP code lists.
List parameters, spanning 171 counties and 1,139 ZIP codes for inclusion in the sample frame were: 1) Counties with a land mass of 50% or more contained within the 50-mile radius from selected pellet mills; 2) Counties within MSAs defined by the US Office of Management and Budget and; 3) Residents older than 18 years of age. As shown in Figure 1, the radii around mills 1 and 2 overlapped, as well as the radii around mills 2 and 3, causing duplicates amongst individual ZIP code lists. To resolve this issue, duplicates were kept in the list for mill one and deleted from mill two list. The same procedure was followed for mills two and three. Mill 2 maintained the duplicate codes, which were removed from mill 3. Duplicate ZIP codes also occurred between mill three and Baton Rouge and Memphis MSAs, mill four and Virginia Beach- Norfolk- Newport News MSA, mill five and Raleigh- Cary MSA, and mill six and Greenville- Mauldin- Easley and Columbia MSAs. To resolve this, every other duplicate was deleted from one list and maintained by the other. In the case that a mill’s ZIP code list coincided with two MSAs, the procedure was repeated for the second MSA once the first was completed. In addition, ZIP codes with a population of zero were removed (Table 1).
As mentioned earlier in this section, mills in the Gulf Coast and Atlantic Coast vary by types of feedstock utilized for pellet production. The 50-mile radius around mills was chosen to gather data from residents who potentially experience direct impacts from the industry, supply forest feedstock to mills, or live in rural communities. MSAs were elected as an urban comparison, contrasting the potentially more intimate mill radii (Table 2). The quasi-control sample base of this study allowed us to draw comparisons between residential perceptions in Gulf Coast and the Atlantic Coast sub-regions.
Figure 1. Study areas including six selected wood pellet mills and ten metropolitan statistical areas (created using eSpatial).
Table 1. Characteristics of selected wood pellet mills included in the study.
Mill |
Morehouse |
Lasalle |
Amite |
Southampton |
Sampson |
Greenwood |
Mill Study Number |
1 |
2 |
3 |
4 |
5 |
6 |
Sub-region |
Gulf-Coast |
Gulf-Coast |
Gulf-Coast |
Atlantic-Coast |
Atlantic-Coast |
Atlantic-Coast |
Company |
Drax Biomass |
Drax Biomass |
Drax Biomass |
Enviva LP |
Enviva LP |
Enviva LP |
State |
LA |
LA |
MS |
VA |
NC |
SC |
City/ Town |
Bastrop |
Urania |
Gloster |
Franklin |
Faison |
Greenwood |
Acquisition or Commission |
2015 |
2017 |
2015 |
2013 |
2016 |
2018 |
Direct Employees |
>60 |
>70 |
>60 |
70 |
90 |
80 |
2019 Capacity (Metric Tons) |
525,000 |
525,000 |
525,000 |
550,000 |
500,000 |
600,000 |
Feedstock |
SW |
SW |
SW |
HW/SW |
HW/SW |
HW/SW |
Transport from Mill to Port |
Train |
Train/ Truck |
Truck |
Truck |
Truck |
Truck |
Exporting Facility Location |
Baton Rouge |
Baton Rouge |
Baton Rouge |
Chesapeake |
Wilming-ton |
Wilmington |
Note: SW - softwood, HW – hardwood.
Table 2. Metropolitan statistical areas included in the study.
State |
MSA 1 |
MSA 2 |
LA |
New Orleans-Metairie |
Baton Rouge |
MS |
Memphis |
Jackson |
NC |
Charlotte-Gastonia-Rockhill |
Raleigh-Cary |
SC |
Greenville-Mauldin-Easley |
Columbia |
VA |
Washington-Arlington-Alexandria |
Virginia Beach-Norfolk-Newport News |
Note: LA - Louisiana, MS - Mississippi, NC - North Carolina, SC - South Carolina, VA – Virginia.
Environmental, social, and economic constructs were included in four sections within a web-based questionnaire. Each of the four sections contained questions regarding perceived impacts relevant to issues of the industry, such as pollution, effects on municipal infrastructure, and employment opportunities. An awareness section was included to measure the general awareness and knowledge of residents concerning the wood pellet manufacturing industry. The final section was comprised of socio-demographic inquiries to compare sample data to the population data gathered from data provided by the list company, ExactData.
The survey instrument contained fixed response, open-ended, and scale questions to measure the environmental, social, and economic constructs, which were independent variables influencing the dependent variable, company profiles. Scale questions were adapted from Likert-type scale found in Bruner et al. (2001) Marketing Scales Handbook, volume III, and Bearden et al. (2011) Handbook of Marketing Scales, 3rd edition. Open-ended questions were designed to give respondents the opportunity to present answers that were not included in the survey instrument.
Procedures, follow-up efforts, and data analysis were implemented using a modified version of the Tailored Design Method (Dillman et al. 2014). The survey instrument was developed and administered using Survey-Monkey®. The initial mailing was sent to 7,500 recipient emails. A second mailing was sent ten days after the initial mailing to non-respondents and partial respondents to remind them to complete the questionnaire. At the time of the second mailing, Hurricane Dorian was threatening the Gulf and Atlantic Coasts, which may have impacted the ability of potential respondents in its path to complete the questionnaire, affecting the response rate of the survey.
The survey variables were exported from Survey-Monkey® into a database in Microsoft Excel® to ease the process of further analysis. The Excel database stored records of returned responses from each mailing, demographic variables from the list provider ExactData, and data obtained by the survey instrument. Statistical data analysis was performed using SPSS version 25; a statistical program widely used in social science research. Descriptive statistics, including frequencies and mean responses, independent sample two-tailed t-tests, χ2 test, and Analysis of Variance (ANOVA) tests, were utilized for the analysis.
Of the 7,500 surveys administered, 1,112 were either undeliverable or inappropriate due to respondents’ previous unwillingness to participate in Survey-Monkey® based surveys, or their unwillingness to participate in this survey. The total number of useable surveys received was 122, for an overall adjusted response rate of 2%. Due to such a low response rate, the study can only be positioned as exploratory.
An adjusted response rate was calculated using the following formula:
Adjusted Response Rate = Useable Surveys / [Total Sample – (Undeliverables + Unusable)] %
Nonresponse bias was measured using an independent sample two-tailed t-test conducted on age, zip code, and income, comparing respondents and non-respondents that did not fall into the undeliverable or unusable categories. No statistically significant difference was detected at α = 0.05 significance level. In addition, research has shown that late respondents typically respond similarly to non-respondents (Armstrong and Overton 1977). Accordingly, respondents to the second mailing were used as a proxy for non-respondents and compared to first mailing respondents using 84 continuous variables. Less than 5% of all continuous variables comparing first and second-mailing respondents were found to be statistically significantly different at α = 0.05 significance level; therefore, nonresponse bias was not a problem.
Approximately 53.8% (n=65) of respondents were female. Annual 2018 household income was more than $100,000 for 52.3% (n=63) of respondents, and 58.5% (n=65) were 55 or older. In terms of ethnicity, 84.4% (n=64) of respondents were white or Caucasian, and 66.2% (n=65) have a college (B.S. or B.A.) or advanced degree (M.S., Ph.D., MBA, JD). As for political affiliation, 38.5% identified as Republican, while 33.8% identified as Democrat and 16.9% identified as independent (n=65). Of the 122 respondents, 72.1% were urban, and 27.9% were rural. The density of responses received is geographically represented by Figure 2, which was based on respondent ZIP codes.